The sleep diet: Could this work?

Gastric band Surgery In France

The sleep diet: Could this work?

Sign in

Log in with your Medical News Today account to create or edit your custom homepage, catch-up on your opinions notifications and set your newsletter preferences.

Four pivotal NIH-funded artificial pancreas research efforts begin

News Release

Tuesday, February 7, 2017

Devices would replace traditional, manual methods for management of type 1 diabetes.

The first of several major research efforts to test and refine artificial pancreas systems is now underway. Four separate projects, funded by the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), are designed to be the potential last steps between testing the fully automated devices and requesting regulatory approval for permanent use. A successful artificial pancreas would be a life-changing advance for many people with type 1 diabetes. NIDDK is part of the National Institutes of Health.

The artificial pancreas is an integrated system that monitors blood glucose levels automatically and provides insulin or a combination of insulin and a second hormone. The closed-loop system would replace reliance on testing by fingerstick or continuous glucose monitoring systems and separate, non-integrated delivery of insulin by shots or a pump.

“These studies aim to collect the data necessary to bring artificial pancreas technology to the people who need it,” said Dr. Guillermo Arreaza-Rubín, director of NIDDK’s Diabetes Technology Program. “Results from these studies could change and save lives.”

Previously, researchers and participants worked together to test artificial pancreas devices in short-term trials, with varying levels of patient supervision, including at summer camps for youth with type 1 diabetes and in hotels near study sites. In 2016, the U.S. Food and Drug Administration approved a hybrid model of an artificial pancreas, an automated system that requires users to adjust insulin intake at mealtimes. A fully automated system will sense rising glucose levels, including at mealtimes, and adjust insulin automatically.

In addition to easing the burden of management for people with type 1 diabetes or their caregivers, in shorter studies, the devices brought glucose levels closer to normal than traditional management. NIH research has found that early, tight control of blood glucose helps reduce diabetes complications including nerve, eye and kidney diseases.

The four research projects beginning in 2017-2018 will be conducted in larger groups over longer periods of time and in largely unrestricted conditions. The participants will live at home and monitor themselves, going about their normal lives, with remote monitoring by study staff.

“Managing type 1 diabetes currently requires a constant juggling act between checking blood glucose levels frequently and delivering just the right amount of insulin while taking into account meals, physical activity, and other aspects of daily life, where a missed or wrong delivery could lead to potential complications,” said Dr. Andrew Bremer, the NIDDK program official overseeing the studies. “Unifying the management of type 1 diabetes into a single, integrated system could lift so much of that burden.”

Studies will look at factors including safety, efficacy, user-friendliness, physical and emotional health of participants, and cost. The Jaeb Center for Health Research in Tampa, Florida, will serve as coordinating center. The trials are:

  • Now recruiting, the International Diabetes Closed-Loop trial, led by Drs. Boris Kovatchev and Stacey Anderson of the University of Virginia in Charlottesville, will test an automated insulin delivery system called inControl. The trial, which uses smartphones, will follow 240 people age 14 and up with type 1 diabetes for six months. The study has sites in California, Colorado, Florida, Massachusetts, Minnesota, New York and Virginia, and abroad in France, Holland and Italy. A second, six-month study will recruit from the 180 U.S. participants of the first trial to test an alternative algorithm. (NIH grant DK108483) Learn more at Clinicaltrials.gov: NCT02985866 and NCT02844517.
  • Early this year, recruitment will begin for youth aged 6-18 for a full-year trial of an artificial pancreas. Led by Dr. Roman Hovorka of the University of Cambridge in England, the study seeks to enroll 130 youth for a full year of use of an artificial pancreas system that uses a smartphone as one component. The study will be conducted at sites in California, Colorado, Connecticut, Minnesota, and two sites in the United Kingdom. (NIH grant DK108520) Learn more: NCT02925299.
  • Starting in late 2017, research led by Drs. Richard Bergenstal of International Diabetes Center, Minneapolis, and Moshe Phillip of Schneider Children’s Medical Center, Petah Tikva, Israel, will compare the FDA-approved hybrid artificial pancreas to a next-generation system, programmed to further improve glucose control, particularly around mealtime. One hundred youth will test each system for three months at sites in California, Connecticut, Florida, Massachusetts and Minnesota and abroad in Germany, Israel and Slovenia. (NIH grant DK108611) Learn more: NCT03040414.
  • In mid-2018, a study led by Drs. Steven Russell of the Massachusetts General Hospital in Boston, and Ed Damiano of Boston University will enroll 312 people ages 18 and older. The six-month study uses a bihormonal “bionic pancreas” system, with a dual-chamber pump to deliver both insulin and its counteracting hormone, glucagon, using tested algorithms for automated dual-hormone delivery. The study will take place at two sites in California and one each in Massachusetts, Michigan, Missouri, North Carolina, Ohio and Washington. (NIH grant DK108612) Learn more at www.bionicpancreas.org.

“For many people with type 1 diabetes, the realization of a successful, fully automated artificial pancreas is a dearly held dream. It signifies a life freer from nightly wake-up calls to check blood glucose or deliver insulin, a life freer from dangerous swings of blood glucose,” said NIDDK Director Dr. Griffin P. Rodgers. “Nearly 100 years since the discovery of insulin, a successful artificial pancreas would mark another huge step toward better health for people with type 1 diabetes.”

The trials are made possible through the Special Statutory Funding Program for Type 1 Diabetes, a Congressional appropriation administered by NIDDK to support research to prevent and cure type 1 diabetes and its complications. Cumulatively, the grants total about $41 million.

The NIDDK, part of the NIH, conducts and supports basic and clinical research and research training on some of the most common, severe, and disabling conditions affecting Americans. The Institute’s research interests include: diabetes and other endocrine and metabolic diseases; digestive diseases, nutrition, and obesity; and kidney, urologic, and hematologic diseases. For more information, visit www.niddk.nih.gov.

Read more……>click Here<

Couples with obesity may take longer to achieve pregnancy, NIH study suggests

News Release

Friday, February 3, 2017

“Our results also indicate that fertility specialists may want to consider couples’ body compositions when counseling patients.”

Rajeshwari Sundaram, Ph.D., Senior Investigator, Division of Intramural Population Health Research, NICHD

Couples in which both partners are obese may take from 55 to 59 percent longer to achieve pregnancy, compared to their normal weight counterparts, according to a study by researchers at the National Institutes of Health. The findings appear online in Human Reproduction.

“A lot of studies on fertility and body composition have focused on the female partner, but our findings underscore the importance of including both partners,” said Rajeshwari Sundaram, Ph.D., a senior investigator in the Division of Intramural Population Health Research at NIH’s Eunice Kennedy Shriver National Institute of Child Health and Human Development. “Our results also indicate that fertility specialists may want to consider couples’ body compositions when counseling patients.”

The couples in the study were part of the Longitudinal Investigation of Fertility and the Environment (LIFE) Study, which examined the relationship between fertility and exposure to environmental chemicals. The study enrolled 501 couples from Michigan and Texas from 2005 to 2009. The women ranged from 18 to 44 years of age, and the men were over 18 years old. Women kept journals to record their monthly menstrual cycles, intercourse and the results of home pregnancy tests. The couples were followed until pregnancy or for up to one year of trying to conceive.

Researchers also calculated body mass index (BMI) for each participant, categorizing couples with obesity into two subgroups:  obese class I (with a BMI from 30 to 34.9) and the most obese group, obese class II (a BMI of 35 or greater).

The researchers compared the average time to achieve a pregnancy among couples in the non- obese group (84 men and 228 women) to that of the couples in the obese class II group (75 men and 69 women).

The researchers then calculated the probability that a couple would achieve pregnancy by using a statistical measure called the fecundability odds ratio (FOR). The measure estimates couples’ probability of pregnancy each menstrual cycle while trying for pregnancy, relative to their BMIs.

The researchers found that the class II couples took much longer to achieve pregnancy than couples not struggling with obesity. Couples in the non-obese group had a FOR of 1. , Obese class II couples had a FOR of .45— indicating that they took 55 percent longer to achieve pregnancy than their normal weight counterparts. When the researchers took into account other factors known to influence fertility — such as age, smoking status, physical activity level and cholesterol level &mdash ;the ratio for obese class II couples dropped to .41, or a 59 percent longer time to achieve pregnancy.

The study authors noted that previous studies have focused largely on just the female partner’s BMI or self-reported height and weight. However, findings similar to the current study have been reported among couples undergoing assisted reproductive technologies. The current study focused on couples in the general population, not those undergoing treatment for infertility. 

The authors concluded that couples’ obesity may reduce fertility chances and that fertility specialists may want to take couples’ weight status into account when counseling them about achieving pregnancy. In addition to the health benefits of a healthy weight for reducing risk of other diseases such as Type 2 diabetes, heart disease and cancer, taking steps to lose weight may help reduce the time needed to conceive.

About the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD): NICHD conducts and supports research in the United States and throughout the world on fetal, infant and child development; maternal, child and family health; reproductive biology and population issues; and medical rehabilitation. For more information, visit NICHD’s website.

About the National Institutes of Health (NIH): NIH, the nation’s medical research agency, includes 27 Institutes and Centers and is a component of the U.S. Department of Health and Human Services. NIH is the primary federal agency conducting and supporting basic, clinical, and translational medical research, and is investigating the causes, treatments, and cures for both common and rare diseases. For more information about NIH and its programs, visit www.nih.gov.

NIH…Turning Discovery Into Health®

Read more……>click Here<

Selective Antagonism of Muscarinic Receptors Is Neuroprotective in Peripheral Neuropathy.

Research ArticleNeuroscience Free access | 10.1172/JCI88321

Nigel A. Calcutt,1 Darrell R. Smith,2 Katie Frizzi,1 Mohammad Golam Sabbir,2 Subir K. Roy Chowdhury,2 Teresa Mixcoatl-Zecuatl,1 Ali Saleh,2 Nabeel Muttalib,1 Randy Van der Ploeg,2 Joseline Ochoa,1 Allison Gopaul,1 Lori Tessler,2 Jürgen Wess,3 Corinne G. Jolivalt,1 and Paul Fernyhough2,4

1Department of Pathology, UCSD, La Jolla, California, USA.

2Division of Neurodegenerative Disorders, St. Boniface Hospital Research Centre, Winnipeg, Manitoba, Canada.

3Molecular Signaling Section, Laboratory of Bioorganic Chemistry, National Institute of Diabetes and Digestive and Kidney Diseases, NIH, Bethesda, Maryland, USA.

4Department of Pharmacology and Therapeutics, University of Manitoba, Winnipeg, Manitoba, Canada.

Address correspondence to: Paul Fernyhough, R4046 – 351 Taché Avenue, St. Boniface Hospital Research Centre, Winnipeg, Manitoba, R2H 2A6, Canada. Phone: 204.235.3692; E-mail: pfernyhough@sbrc.ca.

Find articles by Calcutt, N. in: JCI | PubMed | Google Scholar

1Department of Pathology, UCSD, La Jolla, California, USA.

2Division of Neurodegenerative Disorders, St. Boniface Hospital Research Centre, Winnipeg, Manitoba, Canada.

3Molecular Signaling Section, Laboratory of Bioorganic Chemistry, National Institute of Diabetes and Digestive and Kidney Diseases, NIH, Bethesda, Maryland, USA.

4Department of Pharmacology and Therapeutics, University of Manitoba, Winnipeg, Manitoba, Canada.

Address correspondence to: Paul Fernyhough, R4046 – 351 Taché Avenue, St. Boniface Hospital Research Centre, Winnipeg, Manitoba, R2H 2A6, Canada. Phone: 204.235.3692; E-mail: pfernyhough@sbrc.ca.

Find articles by Smith, D. in: JCI | PubMed | Google Scholar

1Department of Pathology, UCSD, La Jolla, California, USA.

2Division of Neurodegenerative Disorders, St. Boniface Hospital Research Centre, Winnipeg, Manitoba, Canada.

3Molecular Signaling Section, Laboratory of Bioorganic Chemistry, National Institute of Diabetes and Digestive and Kidney Diseases, NIH, Bethesda, Maryland, USA.

4Department of Pharmacology and Therapeutics, University of Manitoba, Winnipeg, Manitoba, Canada.

Address correspondence to: Paul Fernyhough, R4046 – 351 Taché Avenue, St. Boniface Hospital Research Centre, Winnipeg, Manitoba, R2H 2A6, Canada. Phone: 204.235.3692; E-mail: pfernyhough@sbrc.ca.

Find articles by Frizzi, K. in: JCI | PubMed | Google Scholar

1Department of Pathology, UCSD, La Jolla, California, USA.

2Division of Neurodegenerative Disorders, St. Boniface Hospital Research Centre, Winnipeg, Manitoba, Canada.

3Molecular Signaling Section, Laboratory of Bioorganic Chemistry, National Institute of Diabetes and Digestive and Kidney Diseases, NIH, Bethesda, Maryland, USA.

4Department of Pharmacology and Therapeutics, University of Manitoba, Winnipeg, Manitoba, Canada.

Address correspondence to: Paul Fernyhough, R4046 – 351 Taché Avenue, St. Boniface Hospital Research Centre, Winnipeg, Manitoba, R2H 2A6, Canada. Phone: 204.235.3692; E-mail: pfernyhough@sbrc.ca.

Find articles by Sabbir, M. in: JCI | PubMed | Google Scholar

1Department of Pathology, UCSD, La Jolla, California, USA.

2Division of Neurodegenerative Disorders, St. Boniface Hospital Research Centre, Winnipeg, Manitoba, Canada.

3Molecular Signaling Section, Laboratory of Bioorganic Chemistry, National Institute of Diabetes and Digestive and Kidney Diseases, NIH, Bethesda, Maryland, USA.

4Department of Pharmacology and Therapeutics, University of Manitoba, Winnipeg, Manitoba, Canada.

Address correspondence to: Paul Fernyhough, R4046 – 351 Taché Avenue, St. Boniface Hospital Research Centre, Winnipeg, Manitoba, R2H 2A6, Canada. Phone: 204.235.3692; E-mail: pfernyhough@sbrc.ca.

Find articles by Chowdhury, S. in: JCI | PubMed | Google Scholar

1Department of Pathology, UCSD, La Jolla, California, USA.

2Division of Neurodegenerative Disorders, St. Boniface Hospital Research Centre, Winnipeg, Manitoba, Canada.

3Molecular Signaling Section, Laboratory of Bioorganic Chemistry, National Institute of Diabetes and Digestive and Kidney Diseases, NIH, Bethesda, Maryland, USA.

4Department of Pharmacology and Therapeutics, University of Manitoba, Winnipeg, Manitoba, Canada.

Address correspondence to: Paul Fernyhough, R4046 – 351 Taché Avenue, St. Boniface Hospital Research Centre, Winnipeg, Manitoba, R2H 2A6, Canada. Phone: 204.235.3692; E-mail: pfernyhough@sbrc.ca.

Find articles by Mixcoatl-Zecuatl, T. in: JCI | PubMed | Google Scholar

1Department of Pathology, UCSD, La Jolla, California, USA.

2Division of Neurodegenerative Disorders, St. Boniface Hospital Research Centre, Winnipeg, Manitoba, Canada.

3Molecular Signaling Section, Laboratory of Bioorganic Chemistry, National Institute of Diabetes and Digestive and Kidney Diseases, NIH, Bethesda, Maryland, USA.

4Department of Pharmacology and Therapeutics, University of Manitoba, Winnipeg, Manitoba, Canada.

Address correspondence to: Paul Fernyhough, R4046 – 351 Taché Avenue, St. Boniface Hospital Research Centre, Winnipeg, Manitoba, R2H 2A6, Canada. Phone: 204.235.3692; E-mail: pfernyhough@sbrc.ca.

Find articles by Saleh, A. in: JCI | PubMed | Google Scholar

1Department of Pathology, UCSD, La Jolla, California, USA.

2Division of Neurodegenerative Disorders, St. Boniface Hospital Research Centre, Winnipeg, Manitoba, Canada.

3Molecular Signaling Section, Laboratory of Bioorganic Chemistry, National Institute of Diabetes and Digestive and Kidney Diseases, NIH, Bethesda, Maryland, USA.

4Department of Pharmacology and Therapeutics, University of Manitoba, Winnipeg, Manitoba, Canada.

Address correspondence to: Paul Fernyhough, R4046 – 351 Taché Avenue, St. Boniface Hospital Research Centre, Winnipeg, Manitoba, R2H 2A6, Canada. Phone: 204.235.3692; E-mail: pfernyhough@sbrc.ca.

Find articles by Muttalib, N. in: JCI | PubMed | Google Scholar

1Department of Pathology, UCSD, La Jolla, California, USA.

2Division of Neurodegenerative Disorders, St. Boniface Hospital Research Centre, Winnipeg, Manitoba, Canada.

3Molecular Signaling Section, Laboratory of Bioorganic Chemistry, National Institute of Diabetes and Digestive and Kidney Diseases, NIH, Bethesda, Maryland, USA.

4Department of Pharmacology and Therapeutics, University of Manitoba, Winnipeg, Manitoba, Canada.

Address correspondence to: Paul Fernyhough, R4046 – 351 Taché Avenue, St. Boniface Hospital Research Centre, Winnipeg, Manitoba, R2H 2A6, Canada. Phone: 204.235.3692; E-mail: pfernyhough@sbrc.ca.

Find articles by Van der Ploeg, R. in: JCI | PubMed | Google Scholar

1Department of Pathology, UCSD, La Jolla, California, USA.

2Division of Neurodegenerative Disorders, St. Boniface Hospital Research Centre, Winnipeg, Manitoba, Canada.

3Molecular Signaling Section, Laboratory of Bioorganic Chemistry, National Institute of Diabetes and Digestive and Kidney Diseases, NIH, Bethesda, Maryland, USA.

4Department of Pharmacology and Therapeutics, University of Manitoba, Winnipeg, Manitoba, Canada.

Address correspondence to: Paul Fernyhough, R4046 – 351 Taché Avenue, St. Boniface Hospital Research Centre, Winnipeg, Manitoba, R2H 2A6, Canada. Phone: 204.235.3692; E-mail: pfernyhough@sbrc.ca.

Find articles by Ochoa, J. in: JCI | PubMed | Google Scholar

1Department of Pathology, UCSD, La Jolla, California, USA.

2Division of Neurodegenerative Disorders, St. Boniface Hospital Research Centre, Winnipeg, Manitoba, Canada.

3Molecular Signaling Section, Laboratory of Bioorganic Chemistry, National Institute of Diabetes and Digestive and Kidney Diseases, NIH, Bethesda, Maryland, USA.

4Department of Pharmacology and Therapeutics, University of Manitoba, Winnipeg, Manitoba, Canada.

Address correspondence to: Paul Fernyhough, R4046 – 351 Taché Avenue, St. Boniface Hospital Research Centre, Winnipeg, Manitoba, R2H 2A6, Canada. Phone: 204.235.3692; E-mail: pfernyhough@sbrc.ca.

Find articles by Gopaul, A. in: JCI | PubMed | Google Scholar

1Department of Pathology, UCSD, La Jolla, California, USA.

2Division of Neurodegenerative Disorders, St. Boniface Hospital Research Centre, Winnipeg, Manitoba, Canada.

3Molecular Signaling Section, Laboratory of Bioorganic Chemistry, National Institute of Diabetes and Digestive and Kidney Diseases, NIH, Bethesda, Maryland, USA.

4Department of Pharmacology and Therapeutics, University of Manitoba, Winnipeg, Manitoba, Canada.

Address correspondence to: Paul Fernyhough, R4046 – 351 Taché Avenue, St. Boniface Hospital Research Centre, Winnipeg, Manitoba, R2H 2A6, Canada. Phone: 204.235.3692; E-mail: pfernyhough@sbrc.ca.

Find articles by Tessler, L. in: JCI | PubMed | Google Scholar

1Department of Pathology, UCSD, La Jolla, California, USA.

2Division of Neurodegenerative Disorders, St. Boniface Hospital Research Centre, Winnipeg, Manitoba, Canada.

3Molecular Signaling Section, Laboratory of Bioorganic Chemistry, National Institute of Diabetes and Digestive and Kidney Diseases, NIH, Bethesda, Maryland, USA.

4Department of Pharmacology and Therapeutics, University of Manitoba, Winnipeg, Manitoba, Canada.

Address correspondence to: Paul Fernyhough, R4046 – 351 Taché Avenue, St. Boniface Hospital Research Centre, Winnipeg, Manitoba, R2H 2A6, Canada. Phone: 204.235.3692; E-mail: pfernyhough@sbrc.ca.

Find articles by Wess, J. in: JCI | PubMed | Google Scholar

1Department of Pathology, UCSD, La Jolla, California, USA.

2Division of Neurodegenerative Disorders, St. Boniface Hospital Research Centre, Winnipeg, Manitoba, Canada.

3Molecular Signaling Section, Laboratory of Bioorganic Chemistry, National Institute of Diabetes and Digestive and Kidney Diseases, NIH, Bethesda, Maryland, USA.

4Department of Pharmacology and Therapeutics, University of Manitoba, Winnipeg, Manitoba, Canada.

Address correspondence to: Paul Fernyhough, R4046 – 351 Taché Avenue, St. Boniface Hospital Research Centre, Winnipeg, Manitoba, R2H 2A6, Canada. Phone: 204.235.3692; E-mail: pfernyhough@sbrc.ca.

Find articles by Jolivalt, C. in: JCI | PubMed | Google Scholar

1Department of Pathology, UCSD, La Jolla, California, USA.

2Division of Neurodegenerative Disorders, St. Boniface Hospital Research Centre, Winnipeg, Manitoba, Canada.

3Molecular Signaling Section, Laboratory of Bioorganic Chemistry, National Institute of Diabetes and Digestive and Kidney Diseases, NIH, Bethesda, Maryland, USA.

4Department of Pharmacology and Therapeutics, University of Manitoba, Winnipeg, Manitoba, Canada.

Address correspondence to: Paul Fernyhough, R4046 – 351 Taché Avenue, St. Boniface Hospital Research Centre, Winnipeg, Manitoba, R2H 2A6, Canada. Phone: 204.235.3692; E-mail: pfernyhough@sbrc.ca.

Find articles by Fernyhough, P. in: JCI | PubMed | Google Scholar

First published January 17, 2017 – More info

First published January 17, 2017
Received: May 11, 2016; Accepted: November 22, 2016

Abstract

Sensory neurons have the capacity to produce, release, and respond to acetylcholine (ACh), but the functional role of cholinergic systems in adult mammalian peripheral sensory nerves has not been established. Here, we have reported that neurite outgrowth from adult sensory neurons that were maintained under subsaturating neurotrophic factor conditions operates under cholinergic constraint that is mediated by muscarinic receptor–dependent regulation of mitochondrial function via AMPK. Sensory neurons from mice lacking the muscarinic ACh type 1 receptor (M1R) exhibited enhanced neurite outgrowth, confirming the role of M1R in tonic suppression of axonal plasticity. M1R-deficient mice made diabetic with streptozotocin were protected from physiological and structural indices of sensory neuropathy. Pharmacological blockade of M1R using specific or selective antagonists, pirenzepine, VU0255035, or muscarinic toxin 7 (MT7) activated AMPK and overcame diabetes-induced mitochondrial dysfunction in vitro and in vivo. These antimuscarinic drugs prevented or reversed indices of peripheral neuropathy, such as depletion of sensory nerve terminals, thermal hypoalgesia, and nerve conduction slowing in diverse rodent models of diabetes. Pirenzepine and MT7 also prevented peripheral neuropathy induced by the chemotherapeutic agents dichloroacetate and paclitaxel or HIV envelope protein gp120. As a variety of antimuscarinic drugs are approved for clinical use against other conditions, prompt translation of this therapeutic approach to clinical trials is feasible.

Introduction

The innervation territory of intraepidermal nerve fibers (IENF) within the skin is plastic and maintained through a combination of collateral sprouting and regeneration that is regulated partly by neurotrophic factors (1). Distal dying-back or degeneration of nerve fibers is observed in many axonopathic diseases, including diabetic neuropathy, chemotherapy-induced peripheral neuropathy (CIPN), Friedreich ataxia, Charcot-Marie-Tooth disease type 2, and HIV-associated distal-symmetric neuropathy. There are no therapies for any of these diseases, all of which display some degree of mitochondrial dysfunction (24). This is pertinent, as the growth-cone motility required to maintain fields of innervation consumes 50% of ATP supplies in neurons due to high rates of actin treadmilling (5). Maintenance of plastic innervation therefore requires high consumption of ATP for growth-cone motility and maintenance of terminals and synapses (6, 7). Unmyelinated axons are also more energetically demanding than myelinated axons, consuming 2.5- to 10-fold more energy per action potential (8). Mitochondria are known to concentrate in regions of high metabolic demand (9), and sensory terminal boutons are packed with mitochondria (10).

Our work in rodent models of type 1 and 2 diabetes exhibiting neuropathy demonstrates that hyperglycemia triggers nutrient excess in neurons that, in turn, mediates a phenotypic change in mitochondria through alteration of the AMPK/peroxisome proliferator–activated receptor γ coactivator-1α (PGC-1α) signaling axis (4, 11). This vital energy-sensing metabolic pathway modulates mitochondrial function, biogenesis, and regeneration (12). There is accumulating evidence that stimulation of the AMPK/PGC-1α axis in neurons promotes improved mitochondrial function and regeneration (4, 13). For example, the AMPK activator resveratrol enhances neurite outgrowth (14), while augmented AMPK signaling maintains outer retina synapses (15) and directs mitochondria to axons to drive branching in cerebellar granule neurons (16). Upregulation of PGC-1α is protective against oxidative stress in hippocampal neurons (17) and prevents mutant Parkin-related degeneration in dopaminergic neurons (18). In the context of diabetes, the bioenergetic phenotype of mitochondria in dorsal root ganglia–derived (DRG-derived) sensory neurons is characterized by inner membrane depolarization, reduced expression of respiratory chain components, and suboptimal spare respiratory capacity (4, 11) without remarkable ultrastructural alterations (19). Activation of AMPK by resveratrol protected mitochondrial function and peripheral nerve structure and function in rodent models of both type 1 and type 2 diabetes (11).

In an effort to identify molecules capable of enhancing peripheral nerve repair, we screened compounds for their ability to enhance neurite outgrowth in adult sensory neurons using the NIH/Juvenile Diabetes Research Foundation (JDRF) Custom Collection (maintained by Micro Source Discovery Systems Inc.). The primary screen utilized sensory neurons derived from DRG of adult rats, with subsequent hits advanced to neurons derived from rat models of type 1 (streptozotocin [STZ]) and type 2 (Zucker diabetic fatty [ZDF]) diabetes. A number of molecules with antimuscarinic properties were identified as promoting neurite outgrowth in this system. Prior work in neurons from Aplysia and Xenopus showed both spontaneous and evoked release of quantal packets of acetylcholine (ACh) from growth cones. ACh modulated Ca2+-dependent motility via nicotinic and muscarinic receptors, with nicotinic signaling being positive for growth and muscarinic signaling negative (20, 21). Studies in embryonic sensory neurons have also demonstrated that ACh signaling through muscarinic receptors, and associated mobilization of Ca2+ from internal stores, acts as a regulator of growth-cone motility during development (22, 23). In mammals, cell bodies of sensory neurons synthesize and secrete ACh (24), express a peripheral form of choline acetyltransferase (pChAT), exhibit ChAT activity, have low acetylcholinesterase (AChE) activity, and express multiple muscarinic receptors including muscarinic Ach type 1 receptor (M1R) (2527). Together, these findings support the credibility of an endogenous cholinergic system that tonically suppresses neurite outgrowth in adult mammalian neuronal cells.

The aim of the current study was to determine the mechanism by which antimuscarinic compounds enhance neurite outgrowth and to translate findings into a therapeutic approach that could prevent or reverse peripheral neuropathy in a range of in vitro and in vivo models. Our data introduce selective or specific antimuscarinic drugs as a therapeutic approach for preventing and reversing sensory neuropathy in a variety of disease states of the PNS.

Results

Muscarinic antagonists selective or specific for M1R enhance neurite outgrowth. A preliminary screen (summarized in Supplemental Figures 1 and 2; supplemental material available online with this article; doi:10.1172/JCI88321DS1; and previously described in ref. 28) identified pirenzepine, a selective M1R antagonist (29), as able to induce a dose-dependent (3 to 100 nM) increase of total neurite outgrowth from neurons derived from normal rats (Figure 1, A and B). This effect was mimicked by 30 nM VU0255035, a structurally dissimilar but also selective M1R antagonist (30) (Figure 1C). Selective antagonists of the M2R (gallamine, 1 μM), M3R (darafenacin, 1 μM) (31), or M4R (tropicamide, 1 μM) (32) had no effect on neurite outgrowth (Figure 1C). The muscarinic receptor agonist muscarine (10 μM) significantly inhibited neurite outgrowth, by approximately 50% (Figure 1D). As ACh also activates a variety of nicotinic receptor subtypes in neurons, we determined whether blockade of this signaling pathway also modulated neurite outgrowth. The broad-spectrum nicotinic antagonists hexamethonium (20 μM) and mecamylamine (50 μM) had no effect on neurite outgrowth (Figure 1D). Pirenzepine and VU0255035 are selective M1R antagonists, whereas the only specific antagonist of the M1R is muscarinic toxin 7 (MT7)(33). Concentrations of MT7 as low as 10 nM significantly augmented neurite outgrowth (Figure 1E). The capacity of adult sensory neurons to support cholinergic signaling was confirmed using fluo-4 loading and fluorescence video microscopy. Application of 50 μM muscarine caused an acute and transient increase of intracellular Ca2+ levels that was inhibited by prior exposure (2 minutes) to 1.0 μM pirenzepine or 0.1 μM atropine, a nonspecific antimuscarinic (Figure 1, F–H).

The M1R regulates neurite outgrowth from adult sensory neurons.Figure 1

The M1R regulates neurite outgrowth from adult sensory neurons. (A) Neurons derived from normal rats were cultured for 24 hours and total neurite outgrowth presented as mean ± SEM of n = 7 replicate cultures. *P < 0.05; **P < 0.01; ****P < 0.0001 vs. 0 by 1-way ANOVA with Dunnett’s post-hoc test. PZ, pirenzepine. (B) β-tubulin III–immunostained sensory neurons that were untreated (control) or treated with 1 μM pirenzepine for 24 hours. Scale bar: 100 μm. (C) Total neurite outgrowth when exposed to 1 μM pirenzepine, 30 nM VU0255035 (VU), 1 μM darafenacin (DA), 1 μM gallamine (GA), and 1 μM tropicamide (TR) or (D) 1 μM pirenzepine, 10 μM muscarine (MU), 20 μM hexamethonium (HX), and 50 μM mecamylamine (ME). Open circles indicate individual data points. C, control. (E) Dose-response curve for effect of MT7 on total neurite outgrowth. Data points represent mean ± SEM of n = 6–12 replicate cultures. Within an experiment, *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001 by 1-way ANOVA with Dunnett’s (in E vs. untreated) or Tukey’s (in C and D) post-hoc test. Sensory neurons were loaded with fluo-4 and transient changes in intracellular calcium concentration were measured in response to (F) 50 μM muscarine (n = 54 neurons), (G) pretreated with 1 μM pirenzepine, then treated with muscarine (n = 69 neurons), and (H) pretreated with 0.1 μM atropine, then treated with muscarine (n = 78 neurons). Group mean ± SEM are shown.

Overexpression of M1R inhibits neurite outgrowth. We constructed a plasmid that overexpressed a full-length rat GFP-M1R fusion protein (Figure 2A). Adult sensory neurons transfected with this plasmid exhibited low levels of neurite outgrowth compared with neurons transfected with GFP alone (Figure 2, B–D). The bright-field images in Figure 2B show that GFP-expressing neurons exhibited extensive neurite outgrowth and that this was stunted by overexpression of GFP-M1R. Immunocytochemistry confirmed that neurite outgrowth was significantly suppressed in neurons overexpressing GFP-M1R (Figure 2, C and D). Diminished neurite outgrowth by neurons that overexpressed GFP-M1R was partially rescued by treatment with MT7 (100 nM) or pirenzepine (1 μM; Figure 2E). To further establish the specific role of the M1R, we next cultured sensory neurons from adult M1R-deficient mice (M1R-KO mice), having confirmed neuronal M1R expression in WT mice and lack thereof in M1R-KO mice (Supplemental Figure 3A). Neurons from adult M1R-KO mice showed enhanced neurite outgrowth when maintained under a low- or medium-dose concentration of a cocktail of neurotrophic growth factors in the culture medium, compared with those from WT mice (Figure 2F). In the presence of high-dose concentrations of growth factors, the inhibitory effect of the M1R pathway was not observed.

Overexpression of GFP-M1R fusion protein inhibits neurite outgrowth.Figure 2

Overexpression of GFP-M1R fusion protein inhibits neurite outgrowth. (A) Immunoblot showing expression of GFP-tagged M1R protein in DRG neurons. M1R cDNA was cloned in PEGFP-C1 vector and used for transient transfection of DRG neurons using Amaxa Nucleofection reagent. Cells were harvested 24 hours after transfection, and proteins were separated by SDS-PAGE, followed by immunoblotting using anti-GFP and anti-M1R antibodies. (B) Bright-field (BF) and fluorescence images showing expression of GFP and GFP-M1R in neurons. Note extensive growth in GFP- vs. GFP-M1R–overexpressing neuron. (C) Fluorescent and immunostained images showing expression of GFP-tagged M1R in DRG neurons. Neurons were immunostained for β-tubulin III. Neurons with coexpression of GFP-M1R and β-tubulin III exhibited reduced neurite outgrowth compared with neurons expressing GFP alone. Scale bars: 100 μm. Colocalization of GFP (green) and β-tubulin III (red) indicated by yellow. (D) Neurons were transfected with GFP or GFP-M1R plasmids and maintained in vitro for 48 hours and immunostained for β-tubulin III. Total neurite outgrowth is shown as mean + SEM of n = 51 neurons; open circles indicate individual data points. ****P < 0.0001, Student’s unpaired t test. (E) Cultures overexpressing GFP-M1R were treated with 100 nM MT7 or 1 μM pirenzepine for 48 hours. Total neurite outgrowth is shown as group median with n = 100 neurons. ***P < 0.001; ****P < 0.0001 vs. control by 1-way ANOVA with Dunnett’s post-hoc test. Box and whisker plot where upper and lower limits of box indicate 75th and 25th percentiles, respectively. The middle lines show median, and error bars show maximum and minimum values. (F) WT (+/+) or M1R knockout (M1R-KO) mouse cultures were maintained for 48 hours in the presence of a low- (LD), medium- (MD), or high-dose (HD) neurotrophic factor cocktail. Total neurite outgrowth is shown as mean + SEM of n = 8 replicate cultures. *P < 0.05; **P < 0.01, Student’s t test.

As ACh was not a component of the culture media, we hypothesized that, under cell culture conditions, the M1R-mediated modulation of neurite outgrowth involved neuron-derived ACh. We confirmed that sensory neurons expressed the peripheral form of ChAT (25) (Supplemental Figure 3B) and ACh was detected in the culture medium from neurons grown at the same density as in all other experiments (16.52 ± 1.42 nmol/ml). Cultured neurons exhibited immunostaining for ChAT in perikarya, axons, and growth cones when using an antibody with selectivity for peripheral ChAT (Supplemental Figure 3, C–E). We therefore propose that the cholinergic phenotype of isolated adult sensory neurons places a tonic constraint on neurite outgrowth via a mechanism involving sensory neuron-derived ACh and the M1R.

Muscarinic receptor blockade enhances mitochondrial function. Neuronal growth cones require optimal mitochondrial function to produce ATP for axon growth/plasticity, and sensory axons exhibit a high density of condensed organelles reflective of high ATP demand (5, 8, 34). Given the constraint on neurite outgrowth imposed by ACh, we investigated whether manipulation of cholinergic systems operating in peripheral sensory neurons altered mitochondrial regulatory pathways. We first measured the oxygen consumption rate (OCR) of isolated adult sensory neurons to determine whether M1R inhibition directly affects neuronal respiration. Neurons derived from M1R-KO mice exhibited enhanced spare respiratory capacity compared with those from WT mice without any concurrent change in basal respiration, coupling efficiency, or respiratory control ratio (Figure 3A and Supplemental Figure 4A). This suggests that ongoing cholinergic signaling via the M1R constrains mitochondrial maximal respiratory capacity, which will restrict mitochondrial ATP generation under conditions of high demand.

M1R blockade augmented mitochondrial function and elevated neurite outgrowtFigure 3

M1R blockade augmented mitochondrial function and elevated neurite outgrowth via AMPK/PGC-1α. (A) DRG cultures from adult M1R-KO mice and WT mice. OCR per 1,000 neurons. Oligo, oligomycin; rot/AA, rotenone plus antimycin A. Arrows indicate time added. (B) Neurons from STZ-induced diabetic mice were maintained overnight and exposed to 100 nM MT7 or vehicle for 1 hour. (A and B) Data are shown as mean ± SEM of n = 4–5 replicate cultures. *P < 0.05 vs. WT or untreated diabetic mice by unpaired Student’s t test. Neurons from diabetic rats were exposed to 100 nM MT7 for various times. Blots for p-AMPK and p-ACC in C and D data normalized to total ERK (T-ERK). Data are shown as mean + SEM of n = 3 replicate cultures. *P < 0.05; **P < 0.01; ***P < 0.001 vs. time 0 by 1-way ANOVA with Dunnett’s post-hoc test. (E) Reporter assay for PGC-1α in neurons from STZ-diabetic rats exposed to 10 μM VU0255035 or 100 nM MT7 for 1 hour. Data are shown as mean + SEM of n = 3 replicate cultures. *P < 0.05 vs. untreated cells (red bar) by 1-way ANOVA with Dunnett’s post-hoc test. Normalized to control plasmid, pGL3 (black bar). (F) Reporter activity for PGC-1α in neurons from STZ-diabetic rats exposed to 100 nM MT7 or 0.3 μM CC or in combination for 30 minutes. Untreated is shown as red bar. Data are shown as mean + SEM of n = 3 replicate cultures. **P < 0.01; ***P < 0.001, 1-way ANOVA with Tukey’s post-hoc test. (GH) Total neurite outgrowth of neurons from diabetic rats transduced with adenovirus carrying dominant negative mutants of α1 (DN1) or α2 (DN2) subunits of AMPK. (H) Constitutively active α1 subunit of AMPK (Ad-CA-AMPK) expressed. Data are shown as mean + SEM of n = 3 replicate cultures. (G) **P < 0.01; ***P < 0.001; ****P < 0.0001 by 1 -way ANOVA with Tukey’s post-hoc test. (H) ***P < 0.05 by Student’s unpaired t test.

Neurons derived from STZ-induced diabetic rodents exhibited oxidative stress, reduced spare respiratory capacity, and when dissociated and placed in culture, impaired neurite outgrowth (4, 11, 35). Spare respiratory capacity was increased in these neurons by the M1R antagonists MT7 (100 nM, in STZ-mouse DRG culture) (Figure 3B and Supplemental Figure 4B), VU0255035 (10 μM, in STZ-rat DRG culture), or pirenzepine (1 μM, in STZ-mouse DRG culture) (Supplemental Figure 4D). Note that in all studies of neurons derived from STZ-induced diabetic rodents, the basal rate of respiration was not significantly different from that of age-matched controls. This confirms previous work from our laboratory and others (11, 3638). Neurons derived from STZ-diabetic mice also exhibited enhanced neurite outgrowth when exposed to pirenzepine (1 μM) or MT7 (100 nM) (Supplemental Figure 4C), further illustrating the potential of antagonizing endogenous muscarinic receptor activity to overcome a disease phenotype.

M1R-selective antagonists activate the AMPK pathway to drive neurite outgrowth. A key pathway that senses cellular energy demands and modulates mitochondrial function is the AMPK and PGC-1α signaling axis (39). Exposure of sensory neurons derived from STZ-induced diabetic rats to 100 nM MT7 or 10 μM VU0255035 enhanced activation (phosphorylation) of AMPK and its endogenous substrate, acetyl-CoA carboxylase (ACC) (Figure 3, C and D, and Supplemental Figure 4E). MT7, VU0255035, and pirenzepine also augmented luciferase reporter activity for PGC-1α, a downstream target of AMPK, when added to neurons derived from STZ-diabetic rats (Figure 3E and Supplemental Figure 4F). MT7 enhancement of PGC-1α was blocked by compound C (0.3 μM), a well-characterized pharmacological inhibitor of AMPK (Figure 3F). The mechanistic association between M1R regulation of AMPK activation and neurite outgrowth was confirmed using sensory neurons derived from STZ-induced diabetic rats transduced with adenovirus carrying dominant negative mutants of AMPKα1 and AMPKα2 subunits. Neurons overexpressing mutant AMPK did not show enhanced neurite outgrowth in response to 1 μM pirenzepine (Figure 3G and Supplemental Figure 4G), whereas overexpression of a constitutively active mutant of AMPK augmented neurite outgrowth (Figure 3H). Thus, ongoing activity of M1R and subsequent dampening of the AMPK/PGC-1α signaling axis restricted the capacity of sensory neurons to respond to increased energy demands such as those required to sustain neurite outgrowth.

M1R antagonism prevents and reverses indices of diabetic neuropathy in mice. Mitochondrial dysfunction is linked to the onset of diabetic peripheral neuropathy (24). We therefore tested the therapeutic potential of antagonizing muscarinic receptor–mediated suppression of mitochondrial function in diabetic mice, a model that reflects human diabetic neuropathy by developing loss of terminal regions of small sensory fibers and loss of sensorimotor function (40). We focused on pirenzepine as the test agent due to its well-characterized pharmacokinetics/dynamics, limited penetration of the blood-brain barrier, and history of safe clinical use for other indications (41). Pirenzepine did not alter disease severity, as body weight, plasma glucose, and HbA1c were unchanged (Supplemental Table 1). Analysis of expression of the M1R in the DRG of C57BL/6 mice with STZ-induced diabetes revealed no significant change in mRNA expression (Supplemental Figure 5). Adult C57BL/6 mice with STZ-induced type 1 diabetes developed loss of paw IENF (illustrated in Supplemental Figure 6A) with concurrent thermal hypoalgesia, and both disorders were prevented by pirenzepine in a dose-dependent fashion (Figure 4A). Mice lacking the M1R had normal response times to paw heat stimulation and normal paw-skin IENF density when compared with WT mice (Figure 4B). Induction of diabetes in WT mice caused paw thermal hypoalgesia and depletion of IENF, whereas induction of diabetes in mice lacking the M1R was without effect on these parameters (Figure 4B). Importantly for potential clinical translation, the therapeutic capacity of pirenzepine extended to reversal of established neuropathy in mouse models of type 1 (STZ) and type 2 (db/db) diabetes (Figure 4, C, E, and F). Moreover, efficacy persisted for 5 to 9 weeks after cessation of treatment (Figure 4, D and E). The efficacy of pirenzepine was replicated by VU0255035, which also corrected loss of thermal sensation and IENF depletion without affecting disease severity in a mouse model of type 1 diabetes (Supplemental Figure 6B).

M1R antagonism prevents and reverses diabetic sensory neuropathy.Figure 4

M1R antagonism prevents and reverses diabetic sensory neuropathy. (A) Thermal response latency and paw skin IENF density in female C57BL/6 (Ctrl, control) and STZ-diabetic mice ± pirenzepine (0.1–10 mg/kg/d s.c.) after 4 weeks of diabetes. Data are shown as mean ± SEM of n = 11–12. *P < 0.05; ****P < 0.0001 vs. control by 1-way ANOVA with Dunnett’s post-hoc test. (B) Thermal response latency and paw skin IENF density in WT and M1R-KO mice after 6 weeks (thermal response) or 12 weeks (IENF) of STZ-induced diabetes. Data are shown as mean ± SEM of n = 3–7. **P < 0.01; ***P < 0.001 vs. WT by 1-way ANOVA with Dunnett’s post-hoc test. (C) Thermal response latency in Swiss Webster, STZ-diabetic, and STZ-diabetic mice with pirenzepine (10 mg/kg/day s.c.) from 14 weeks. Data are shown as mean ± SEM of n = 8–10. ***P < 0.001 vs. control by repeated-measures 2-way ANOVA and Dunnett’s post-hoc test. (D) Thermal response latency in female C57BL/6 mice, STZ-diabetic mice, and STZ-diabetic mice with pirenzepine (10 mg/kg/d s.c.) up to 8 weeks, when treatment was withdrawn. Data are shown as mean ± SEM of n = 8–10. ***P < 0.001 vs. control by repeated-measures 2-way ANOVA and Dunnett’s post-hoc test. Groups as indicated by key in C. (E) Paw IENF density in mice where thermal response latency shown in C (14 weeks and 21 weeks of diabetes) and D (8 weeks and 17 weeks of diabetes), normalized to IENF of control mice at same time. The mean − SEM of control mice at each time point defined lower limit of control group range, and mean + SEM of STZ-diabetic mice at each time point defined upper limit of diabetic group range. Data are shown as mean ± SEM of n = 8–10. **P < 0.01 vs. start or cessation of treatment in same cohort by unpaired t test. (F) Paw thermal response latency in male C57BL/6 mice, db/db mice, and C57BL/6 or db/db mice with pirenzepine (10 mg/kg/d s.c.) from 12 weeks onwards. Data are shown as mean ± SEM of n = 9–10. ***P < 0.001 vs. db/db by repeated-measures 2-way ANOVA and Dunnett’s post-hoc test.

Pirenzepine-dependent recovery from diabetic neuropathy was associated with correction of mitochondrial dysfunction. Concurrent protection of mitochondria was confirmed by assays performed on sensory ganglia derived from diabetic rodents. Diabetes-induced defects in AMPK/PGC-1α, mitochondrial complex protein expression, and OCR were absent in pirenzepine-treated models of type 1 and type 2 diabetes (Figure 5, A and B, and Supplemental Figure 6, C–E). Furthermore, pirenzepine corrected the depression of respiratory chain complex I and IV activities in DRG obtained from the same diabetic animals (Figure 5C). These data establish the therapeutic potential of M1R antagonism against functional and structural indices of small fiber sensory neuropathy in diverse models of type 1 and type 2 diabetes in conjunction with protection of AMPK and mitochondrial activity in the sensory ganglia of such animals.

Pirenzepine augments AMPK/PGC-1α pathway gene expression and mitochondrialFigure 5

Pirenzepine augments AMPK/PGC-1α pathway gene expression and mitochondrial activity in STZ-diabetic mice. (A and B) DRG homogenates from animals reported in Figure 4, C and E (21-week time point), underwent Western blotting and were probed for p-AMPK (on Thr-172), T-AMPK, PGC-1α, NDUFS3 (complex I), and COX IV (complex IV). ERK was probed as a loading control. Data are calculated relative to T-ERK and expressed as mean ± SEM of n = 5–6/group. *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001, 1-way ANOVA with Tukey’s post-hoc test. (C) DRG homogenates from the same study were analyzed for respiratory chain complex activities. Data are shown as mean ± SEM of n = 8/group. *P < 0.05; **P < 0.01; ***P < 0.001, 1-way ANOVA with Tukey’s post-hoc test.

M1R antagonism prevents diabetic neuropathy in other models. The ability of M1R antagonism to prevent loss of thermal sensation and IENF in mice extended to other indices of neuropathy measured in other species. Reduced large-fiber sensory nerve-conduction velocity (NCV) and increased sensitivity to light touch (Figure 6A) in female STZ-diabetic rats and progressive large-fiber motor nerve-conduction velocity (MNCV) slowing in male STZ-diabetic rats (Figure 6B) were prevented by pirenzepine without affecting disease severity (Supplemental Table 2). These findings demonstrate that efficacy of treatment with this M1R antagonist was not species, fiber type, or sex specific. Pirenzepine did not act as an acute antinociceptive agent or general sedative, as a single dose to otherwise untreated STZ-diabetic rats did not affect paw tactile responses (Supplemental Figure 7A) or motor function (Supplemental Figure 7B). However, pirenzepine treatment suppressed primary afferent-driven phase 1 activity during the paw formalin test in STZ-diabetic rats without altering the increased paw flinching during phase 2 (Figure 6C). As pirenzepine has poor CNS penetration (42), a peripheral mode of action against phase 1 activity in the formalin test may be suspected.

M1R antagonism prevents nerve-conduction deficits and tactile allodynia inFigure 6

M1R antagonism prevents nerve-conduction deficits and tactile allodynia in diabetic neuropathy. (A) SNCV (left panel) and 50% paw withdrawal threshold (PWT, right panel) to von Frey filaments (right panel) in control female Sprague-Dawley rats (C), STZ-diabetic rats (STZ), and diabetic rats treated with pirenzepine at 10 mg/kg/d s.c. for the last given 24 hours before assay (STZ+PZ) after 8 weeks of diabetes. Data are shown as mean ± SEM of n = 8–12/group. ***P < 0.001; ****P < 0.0001 vs. control by 1-way ANOVA with Dunnett’s post-hoc test. (B) Time course of sciatic MNCV in male Wistar rats (open circles), STZ-diabetic rats (black circles), and STZ-diabetic rats treated with pirenzepine (5 mg/kg/d s.c.) for 8 weeks of diabetes (red squares). Data are shown as mean ± SEM of n = 5–8/group. ****P < 0.0001 vs. control by repeated-measures 2-way ANOVA with Dunnett’s post-hoc test. (C) Paw flinching in response to subdermal injection of 50 μl 0.5% formalin to the dorsal hind paw of female Sprague-Dawley rats (C), diabetic rats (STZ), and diabetic rats treated with pirenzepine (10 mg/kg/day s.c.) daily from onset of diabetes for 8 weeks and last given 24 hours before assay (STZ+PZ). Phase 1 represents the sum of flinches during minutes 1–2, 6–7, and 11–12, and phase 2 represents the sum of flinches during minutes 16–17, 21–22, 26–27, 31–32, 36–37, 41–42, 46–47, 51–52, 56–57, and 61–62 after paw formalin injection. Data are shown as mean + SEM of n = 8–11/group. *P < 0.05; **P < 0.01 vs. STZ by 1-way ANOVA with Dunnett’s post-hoc test.

M1R antagonists are neuroprotective in models of chemotherapy- and HIV-induced peripheral neuropathy. The neuroprotective effects of pirenzepine were not restricted to diabetic neuropathy. Dichloracetic acid (DCA) is a compound under investigation as a cancer treatment that causes dose-dependent peripheral neuropathy (43). The paw thermal hypoalgesia and loss of IENF that are indicative of degenerative neuropathy in mice following chronic exposure to DCA were prevented by pirenzepine (Figure 7A). Paw tactile allodynia and thermal hyperalgesia, indicative of painful neuropathy in mice exposed to the chemotherapeutic agent paclitaxel, were also prevented by treatment with pirenzepine (Figure 7B). To confirm that pirenzepine can have direct protective effects on peripheral neurons undergoing stress from exposure to chemotherapeutic agents, we isolated neurons from the DRG of normal rats and measured subsequent neurite outgrowth during exposure to the chemotherapeutic agent paclitaxel (0.3 μM) or oxaliplatin (3.0 μM). Reduced total neurite outgrowth induced by these agents was prevented by exposure to 1 to 10 μM pirenzepine (Figure 7, C and D). To extend our investigations to a model of HIV-associated neuropathy, we exposed adult DRG neurons in culture to the HIV envelope protein gp120, which causes direct axonal damage (44). The reduced neurite outgrowth from gp120-exposed DRG neurons was prevented by 1 μM pirenzepine (Figure 8A). Delivery of gp120 to the eye of normal mice daily for 5 weeks induced reduced nerve density in the corneal subbasal nerve plexus, as detected using noninvasive corneal confocal microscopy (Figure 8, B–E). Loss of corneal nerves was both prevented and reversed by concurrent topical application of the specific M1R antagonist MT7 (Figure 8F).

M1R antagonists are neuroprotective in models of CIPN.Figure 7

M1R antagonists are neuroprotective in models of CIPN. (A) Paw thermal response latency (left panel) and IENF profiles (right panel) in female Swiss Webster mice (C), DCA-exposed mice (DCA), and DCA-exposed mice treated with pirenzepine (10 mg/kg/d s.c. last given 24 hours before assay) for 8 weeks during DCA exposure (DCA+PZ). (B) Paw withdrawal threshold (left panel) and thermal response latency (right panel) in female Swiss Webster mice (C), paclitaxel-exposed mice (PX), and paclitaxel-exposed mice treated with pirenzepine (10 mg/kg/d s.c. for 4 weeks following the last paclitaxel exposure and last given 24 hours before assay; PX+PZ). Data in AB are shown as group mean + SEM of n = 9–12/group. *P < 0.05; **P < 0.01; ****P < 0.0001 vs. control by 1-way ANOVA with Dunnett’s post-hoc test. Neurite outgrowth in adult sensory neuron cultures exposed to (C) paclitaxel (0.3 μM) or (D) oxaliplatin (3 μM) for 1 day in the absence/presence of 1 μM (C) or 0.1–10 μM (D) pirenzepine. Data are shown as mean ± SEM of n = 5–8 replicates/group. (C) **P < 0.01, 1-way ANOVA with Tukey’s post-hoc test. (D) *P < 0.05 vs. oxaliplatin alone by 1-way ANOVA with Dunnett’s post-hoc test.

M1R antagonists are neuroprotective in models of peripheral neuropathy induFigure 8

M1R antagonists are neuroprotective in models of peripheral neuropathy induced by the HIV envelope protein gp120. (A) Neurite outgrowth in adult sensory neuron cultures exposed to gp120 (1–3 ng/ml) ± 1 μM pirenzepine for 24 hours. Data are shown as mean + SEM of n = 5–8 replicate cultures. *P < 0.05; **P < 0.01, 1-way ANOVA with Tukey’s post-hoc test. (BC) Unprocessed and (DE) processed images corneal nerves of the subbasal plexus. Dimensions = 400 × 400 μm, resolution = 384 × 384 pixels. (B) Corneal nerves from a control Swiss Webster mouse. (C) Corneal nerves from a Swiss Webster mouse that received daily eye drops of gp120 for 10 weeks. (D and E) Same images overlaid with tracings of the corneal nerve and an 8 × 8 counting grid. Grid squares bounded by red lines represent those that contain 1 or more corneal nerves. Panel D shows 56/64 sectors that contain nerve (occupancy = 87.5%), and panel E shows 36/64 sectors containing nerve (occupancy = 56.3%). (F) Time course of subbasal plexus nerve density (as percentage of occupancy) in adult female Swiss Webster mice that received daily eye drops of vehicle (solid black line), gp120 (dashed black line), or both gp120 and MT7, where MT7 treatment was initiated either on the same day as gp120 (MT7 prevention, dot/dash green line) or 5 weeks after onset of gp120 treatment (MT7 reversal, dotted red line). Values are shown as mean ± SEM of n = 10. *P < 0.05 for gp120 untreated vs. other groups; **P < 0.01 for gp120 untreated vs. MT7 prevention and vehicle by repeated-measures 2-way ANOVA and Dunnett’s post-hoc test.

Discussion

We have discovered that adult peripheral sensory neurons maintained in vitro exhibit ongoing cholinergic constraint of mitochondrial function and neurite outgrowth. The signal transduction pathway linking M1R receptor activity to modulation of the AMPK/PGC-1α axis and mitochondrial function in neurons can be antagonized, and blocking this pathway may contribute to our observations of neuroprotection and recovery from injury promoted by M1R antagonists in models of metabolic-, chemical-, and HIV-related peripheral neuropathy.

There are 5 distinct subtypes of muscarinic receptor (M1–5R) that are divided into 2 classes according to their G protein–coupling preference (45). The M1, M3, and M5 subtypes couple to the Gq/G11 G proteins, whereas the M2 and M4 subtypes link to Gi/Go G proteins (45). While we cannot entirely exclude a contribution by other subtypes of this class when interpreting data using selective M1R antagonists, our data using M1R-deficient mice, overexpression of GFP-M1R, and the M1R-specific antagonist MT7 indicate that this receptor subtype mediates cholinergic constraint of the AMPK/PGC-1α axis, mitochondrial function, and neurite outgrowth. A role for endogenous ACh in regulating this pathway is supported by our measurement of secreted ACh detected in the culture medium, approximately 16 nmoles/ml (16 μM), which far exceeds estimations of the ACh KD of 0.2-0.4 nM for the M1R taken from studies with rat brain neurons (46, 47). These data also correspond well with extracellular levels of ACh in the range of 0.1 to 0.6 nM detected using microdialysis in human and rat skin (48, 49). Thus, it is feasible that endogenously released ACh could act on M1R at nerve endings in the skin. In vitro work in the current study (Supplemental Figure 3, C–E) and in vivo studies in adult rat utilizing immunohistochemistry for the peripheral form of ChAT reveal that the protein is present in the cell body, axon, and nerve endings in the skin (25, 48). Furthermore, compartmented cultures using Campenot chambers of embryonic chick sensory neurons demonstrated secretion of ACh within the cell body compartment and also within the distal axonal compartment (49), emphasizing that ACh could be derived from sites along the whole sensory neuron axis.

The best-characterized role of M1R in the PNS is in sympathetic neurons, where it mediates the M current (50). Acute ACh activation of M1R stimulates phospholipase C β (PLCβ) and triggers generation of inositol triphosphate, which induces endoplasmic reticulum Ca2+ release. Downstream Ca2+-dependent pathways drive closing of Kv7 channels, and the outcome is an enhanced propensity for depolarization of the plasma membrane. Sensory neurons also express Kv7 channels and exhibit the M current, but an initiating role of M1R in this pathway has not been confirmed (51). Upon axotomy, sensory neurons exhibit spontaneous electrical activity that consumes extensive ATP. Given our findings that M1R antagonism of axotomized adult sensory neurons in culture enhances neurite outgrowth, we speculate that blockade of the M current would reduce likelihood of depolarization, thus preserving ATP to support actin-treadmilling in the growth cone and enhancing axon outgrowth (5).

Sensory neuron culture data presented in Supplemental Figure 8 indicate that the antimuscarinic drug-driven activation of AMPK is mediated by Ca2+/calmodulin-dependent protein kinase kinase β (CaMKKβ), a well-characterized upstream kinase that phosphorylates AMPK in an AMP-independent manner (52). In cultured sensory neurons, lipid nanoparticle-mediated siRNA knockdown of CaMKKβ caused reduced phosphorylation of AMPK (Supplemental Figure 8C) and a shift in isoelectric focusing to more positively charged, presumably less phosphorylated, AMPK isoforms (Supplemental Figure 8D). In nonneuronal transformed cells coexpressing Halo-CaMKKβ and M1R or Halo-AMPKα2 and M1R, subsequent treatment with pirenzepine altered the charged state of CaMKKβ isoforms (Supplemental Figure 8E) and phosphorylation state of AMPK α2 isoforms (Supplemental Figure 8F), indicative of direct modulation via M1R (no effect was seen in the absence of M1R coexpression). Finally, in cultured sensory neurons, the MT7-induced phosphorylation of AMPK was blocked by the CaMKK inhibitor STO-609 (Supplemental Figure 8, G and H). The in vitro activation of AMPK in response to MT7 or VU0255035 developed slowly over 60 minutes (Figure 3, C and D, and Supplemental Figure 4E). Fluo-4 live imaging indicated that this activation of AMPK was associated with a rise of intracellular Ca2+ concentration in neurites over a 37.5-minute time period (Supplemental Figure 9). This observation seems counterintuitive, since, as shown in Figure 1, F–H, pirenzepine blocks the acute Ca2+ transient following muscarine treatment. However, this longer-term effect of M1R blockade, of as-yet-unknown genesis, that is driving elevation of intracellular Ca2+ concentration in axons could mediate activation of CaMKKβ and subsequently AMPK. AMPK activity maintains optimal mitochondrial function under high ATP demand, and this pathway is critical for axonal plasticity and growth-cone motility (5, 1416). For example, the specific complex I inhibitor rotenone lowered intraneuritic ATP concentration and diminished neurite outgrowth in mouse adult sensory neurons (53) and embryonic rat neurons (54). Rotenone similarly blocked neurite outgrowth in adult sensory neurons, without concomitant cell death (P. Fernyhough, unpublished observations). In vivo, axotomy of adult sensory neurons causes mitochondrial depolarization and ATP depletion, and subsequent genetically mediated enhancement of mitochondrial trafficking elevates rates of nerve regeneration in response to a sciatic nerve crush (55). The pathogenic mechanisms that depress AMPK activity in peripheral neuropathies caused by diabetes (4) and paclitaxel (P. Fernyhough, unpublished observations) remain unclear. In nonneuronal cells from animal and human tissues, high extracellular glucose concentration drives down AMPK activity via nutrient stress (13). This inhibition of AMPK activity, and subsequently mitochondrial respiration, is mediated by a fall in the AMP/ATP ratio, so that high intracellular glucose concentration funnels through glycolysis to generate ATP and obviates a requirement for extensive mitochondrial-dependent ATP production (56). An attractive feature of the M1R-mediated activation of AMPK is that it likely occurs through an AMP-independent pathway, such as CaMKKβ. Alternatively, it is possible that AMPK activation in response to M1R blockade is a consequence of neurite outgrowth–driven diminishment of local ATP supplies and a subsequent rise in the AMP/ATP ratio. Nevertheless, we have identified a therapeutic approach that may release mitochondrial respiration and neuronal plasticity from tonic cholinergic constraint and offers an alternative approach to neuroprotection and regeneration following acute stress or ongoing metabolic injury.

Antimuscarinic drugs were effective in several aspects of peripheral neuropathy. The ability of pirenzepine to reverse loss of IENF profiles in type 1 diabetes is the first experimental evidence, to our knowledge, showing reversal of this clinically significant end point. Previous studies have focused on prevention of IENF loss, for example, when studying protective effects of neurotrophin treatment in STZ-induced diabetic mice (57, 58). M1R-KO mice were also protected from diabetic neuropathy, revealing a primary role for M1R in driving neuroprotection (Figure 4B). However, these findings require cautious interpretation. We found no evidence for diabetes altering the endogenous muscarinic receptor signaling pathway. Previous work revealed no change in ChAT activity in the sciatic nerve of db/db mice (59), and in the current study, mRNA levels for the M1R in the DRG were not affected by STZ-induced diabetes (Supplemental Figure 5). Further studies are required to determine whether endogenous GPCR activity was altered by diabetes. Nonneuronal cells such as keratinocytes also express M1R, so that systemic delivery of M1R antagonists or loss of M1R in the M1R-KO mice may impart neuroprotective and regenerative effects via alternative and/or additional pathways. Keratinocytes exhibit a rich cholinergic phenotype with expression of a range of muscarinic and nicotinic components, including M1R, ChAT, and AChE (60). It has been reported that, during development, keratinocytes produce a cholinergic barrier to penetration of the superficial layers of the epidermis by the plastic peripheral terminals of epidermal sensory neurons (60). Thus, in our studies using systemically delivered M1R antagonists in animals, these agents could also operate via blockade of M1R activity in keratinocytes or by disruption of the keratinocyte cholinergic barrier. Blockade of M1R signaling in satellite cells within the DRG, which then affects neighboring neurons, also cannot be excluded. However, M1R expression has not yet been demonstrated in satellite cells, and a study utilizing electron microscopy combined with autoradiography in rat superior cervical ganglia found specific binding of a muscarinic agonist to the M1R in neuronal somata and dendrites and not satellite cells (61). Given the possible range of off-target effects of the antimuscarinic drugs, it was promising that, from a therapeutic standpoint, no side effects were observed. Moreover, none of the drugs in the long term (3- to 4-month treatment protocols) affected the diabetic state, thereby excluding acute or long-term modulation of pancreatic function (Supplemental Tables 1 and 2). Noninvasive and iterative echocardiogram studies in STZ-induced diabetic mice have also been unable to demonstrate alterations in cardiac structure or function (data not shown).

Although the manifestations of peripheral neuropathy can vary between patients with any of the diseases modeled in our studies, there is a growing appreciation that mitochondrial dysfunction contributes to many types of neuropathy by promoting retraction or loss of peripheral sensory terminals and sensory loss (24). Sensory neurons exhibit a condensed mitochondrial network, and this is particularly apparent in unmyelinated neurons that require very high rates of ATP production to maintain electrical activity along the whole length of the axon due to the absence of nodes of Ranvier to mediate saltatory conduction (8, 34). In human skin biopsies, loss of mitochondrial content in IENF of patients with early signs of neuropathy has been documented (62). Our in vivo studies with pirenzepine-treated type 1 and type 2 diabetic rodents indicate that nerve protection and/or repair occurred in association with correction of deactivation of AMPK and of multiple indices of mitochondrial dysfunction in the DRG (Figure 5, A–C, and Supplemental Figure 6, C–E). Other factors that augment mitochondrial function, such as ciliary neurotrophic factor and C-terminal inhibitors of heat shock protein 90, also correct neuropathy in diabetic rodents (37, 38). The blockade of muscarinic receptor–mediated inhibition of mitochondrial activity using antimuscarinic drugs may not represent a specific intervention against any one primary pathogenic mechanism and potentially allows broad therapeutic application to all conditions that show diminished energy capacity under stress. Moreover, diminished AMPK activity and mitochondrial complex expression and activity are not unique to the nervous system in diabetes, and similar deficits have been reported in mesangial cells of the kidney in diabetic nephropathy (63). Interestingly, a recent drug screen for factors enhancing myelination in models of multiple sclerosis also identified broad spectrum antimuscarinics as potential therapeutics (64). While the animal models of peripheral neuropathy that we studied do not exhibit overt demyelination, it is a feature of the equivalent human diseases that may also be amenable to antimuscarinic therapy.

Peripheral neuropathy is a major, and largely untreated, cause of human morbidity, with huge associated health care costs (65). One particularly encouraging implication of our identification of the endogenous M1R-mediated suppression of sensory neuron metabolism is that drugs that modulate this process are already in widespread clinical use for other indications. Moreover, the safety profile of antimuscarinic drugs is well characterized, with over 20 years of clinical application for a variety of indications in Europe and the safe use of topical pirenzepine applied to the eye to treat myopia in children (41). The therapeutic application of M1R antagonists suggested by our studies could potentially translate relatively rapidly to clinical use. Nerve conduction slowing is commonly used as an efficacy end point in clinical trials, and this disorder was prevented in diabetic rodents by pirenzepine therapy. Most notably, structural (IENF loss) and functional (thermal hypoalgesia) indices of small fiber neuropathy present in diabetic rodents were both prevented and reversed by antimuscarinic drugs. Since small fiber degeneration develops early in the human disease and can be reliably quantified using a variety of minimal or noninvasive techniques that can be applied iteratively (6668), future clinical trials of antimuscarinic drugs might feasibly focus on reversal of these early indices of neuropathy. Further, as antimuscarinic drugs were effective in augmenting collateral sprouting in our in vitro assay, this new therapeutic approach may be most effective during the early stages of a dying-back neuropathy prior to overt and/or complete fiber loss.

Methods

Culture of adult sensory neurons from rats and mice. DRGs from adult male rats or mice (from Central Animal Care, University of Manitoba) were dissociated using previously described methods (37, 69, 70). Centrifugation through a 15% BSA column was used to enrich for neurons, as described (71). This procedure removed the vast majority of fibroblasts and Schwann cells; however, a small number of satellite cells approximating 5% to 10% of the final culture remained (mostly directly associated with large sensory neurons). Neurons were cultured in defined Hams F12 media in the presence of modified Bottenstein’s N2 supplement without insulin (0.1 mg/ml transferrin, 20 nM progesterone, 100 μM putrescine, 30 nM sodium selenite, 0.1 mg/ml BSA; all additives were from Sigma-Aldrich; culture medium was from Life Technologies). In all experiments, the media was also supplemented with a low-dose cocktail of neurotrophic factors (0.1 ng/ml NGF, 1.0 ng/ml GDNF, and 0.1 ng/ml NT-3; all from Promega). The growth factor treatment attempted to mimic the levels of neurotrophic support experienced in vivo by sensory neurons (see Supplemental Figure 1 for rationale). As shown in Figure 2F and Supplemental Figure 1, we also used a medium-dose cocktail (0.3 ng/ml NGF, 5 ng/ml GDNF, 1 ng/ml NT-3, and 0.1 nM insulin) or a high-dose cocktail (1 ng/ml NGF, 10 ng/ml GDNF, 10 ng/ml NT-3, and 1 nM insulin). Age-matched control neurons were cultured in the presence of 10 mM d-glucose and 0.1 nM insulin and diabetic neurons with 25 mM d-glucose and zero insulin. MT7 was purchased from Alomone Labs.

Assessment of total neurite outgrowth. Rat or mouse neurons grown on glass coverslips were fixed with 2% paraformaldehyde in PBS (pH 7.4) for 15 minutes at room temperature and permeabilized with 0.3% Triton X-100 in PBS for 5 minutes. Cells were then incubated in blocking buffer (Roche) diluted with FBS and 1.0 mM PBS (1:1:3) for 1 hour, then rinsed 3 times with PBS. The primary antibody used was against β-tubulin isotype III (cat. T8578; 1:1000), which is neuron specific (Sigma Aldrich). Plates were incubated at 4°C overnight. The following day, the coverslips were incubated with CY3-conjugated secondary antibodies (Jackson ImmunoResearch Laboratories) for 1 hour at room temperature and then mounted and imaged using a Carl Zeiss Axioscope-2 fluorescence microscope equipped with an AxioCam camera. Random images were captured using Axio-Vision4.8 software. Alternatively, in neurons transfected with GFP-expressing vectors, random images of the GFP signal were captured. Quantification of total neurite outgrowth was performed by measuring the mean pixel area of captured images using ImageJ software (NIH) adjusted for the cell body signal. All values were adjusted for neuronal number (38, 72). In this culture system, the level of total neurite outgrowth has been validated to be directly related to an arborizing form of axonal plasticity and homologous to collateral sprouting in vivo (73).

Real-time intracellular calcium imaging. For acute measurements, as shown in Figure 1, F–H, neurons were cultured in 96-well glass-bottom dishes overnight and then loaded with calcium-sensitive dye using the Fluo-4 NW (no wash) Kit from Thermo Fisher Scientific. The dish was placed in a Cellomics Arrayscan–VTI HCS Reader (Thermo Fisher Scientific) with liquid delivery attachment. Baseline signals were collected over 1 to 2 minutes; then drugs were added, after which images were collected over 80 seconds. At least 54–78 neurons were imaged in each well over this period. The data are presented as averaged intensity of fluo-4 fluorescence.Cloning and expression of M1R. The full-length cDNA of M1R was amplified using the forward and reverse primers (ATGAACACCTCAGTGCCCCCTGC and TTAGCATTGGCGGGAGGGGGTG, respectively) from total RNA extracted from C57BL/J mouse brain tissue. The M1R-cDNA was subsequently cloned in pEGFP-C1 vector (Promega) at the Xho1 and SacII restriction sites. The pEGFP-M1R plasmid was transfected into adult primary rat DRG neurons using Amaxa Rat Neuron Nucleofection Reagent (VPG-01003) and cultured as described above. The neurons were harvested 48 hours after transfection, and cell lysates were prepared for Western blot, or neurons were fixed in 2% paraformaldehyde. Western blot was immunoblotted using antibodies to GFP (ab-290, Abcam) and M1R (AMR-001, Alomone Labs) to detect M1R-GFP fusion protein.

Measurement of mitochondrial respiration in DRG neurons from mice and rats. An XF24 Analyzer (Seahorse Biosciences) was used to measure neuronal bioenergetic function. The XF24 creates a transient 7-μl chamber in specialized 24-well microplates that allows for OCR to be monitored in real time. Culture medium was changed 1 hour before the assay to unbuffered DMEM (pH 7.4) supplemented with 1 mM pyruvate and 10 mM d-glucose. Neuron density in the range of 2,500-5,000 cells per well gave linear OCR. Oligomycin (1 μM), carbonyl cyanidep-trifluorocarbonyl-cyanide methoxyphenyl hydrazone (FCCP) (range of 0.1 to 1.0 μM), and rotenone (1 μM) plus antimycin A (1 μM) was injected sequentially through ports in the Seahorse Flux Pak cartridges. Each loop was started with mixing for 3 minutes, then delayed for 2 minutes and OCR measured for 3 minutes. This allowed determination of the basal level of oxygen consumption, the amount of oxygen consumption linked to ATP production, the level of non–ATP-linked oxygen consumption (proton leak), the maximal respiration capacity, and the nonmitochondrial oxygen consumption (74, 75). Oligomycin inhibits the ATP synthase, leading to a build-up of the proton gradient that inhibits electron flux and reveals the state of coupling efficiency. Uncoupling of the respiratory chain by FCCP injection reveals the maximal capacity to reduce oxygen. Finally, rotenone plus antimycin A was injected to inhibit the flux of electrons through complexes I and III, and thus no oxygen was further consumed at cytochrome c oxidase. The remaining OCR determined after this intervention is primarily nonmitochondrial. Following OCR measurement, the cells were immediately fixed and double-stained for β-tubulin III and activating transcription factor 3 (ATF3), which specifically labels nuclei of axotomized sensory neurons. The plates were then inserted into a Cellomics Arrayscan–VTI HCS Reader (Thermo Scientific) equipped with Cellomics Arrayscan–VTI software to determine total neuronal number in each well. Data are expressed as OCR in pmoles/min for 1,000 cells. For mitochondria isolated from rat DRG, oxygen consumption was determined at 37°C using the OROBOROS Oxygraph-2K (OROBOROS Instruments GmbH) (76). Isolated mitochondria from lumbar DRG were resuspended in KCl medium (80 mM KCl, 10 mM Tris-HCl, 3 mM MgCl2, 1 mM EDTA, 5 mM potassium phosphate, pH 7.4). Various substrates and inhibitors for mitochondrial respiratory chain complexes were used as described in Supplemental Figure 6, D and E. OROBOROS DatLab software was used to calculate the OCRs and for the graphic presentation of experimental data.

Protein expression in DRG. DRG homogenate or lysate from DRG cell culture (7.5–10.0 μg) was resolved on a 10% SDS-PAGE gel (8% for phosphorylated acetyl coenzyme A carboxylase [P-ACC]) and electroblotted onto nitrocellulose membrane. Blots were then blocked in 5% nonfat milk containing 0.05% Tween-20, rinsed in TBS then PBS (pH 7.4), and incubated with antibodies to the following proteins: phosphorylated AMPK (Thr172, p-AMPK; cat. SC3352; 1:500, Santa Cruz Biotechnology Inc.; Cell Signaling Technology), total AMPK (T-AMPK; cat. SC25792; 1:500, Santa Cruz Biotechnology Inc.), PGC-1α (cat SC13067; 1:500, Santa Cruz Biotechnology Inc.), p-ACC (cat. ab31931; 1:2000, Abcam), CaMKKβ (cat. SC100364; 1:1000, Santa Cruz Biotechnology Inc.), CaMKKα (cat. SC17827 [F-2]; 1:1000, Santa Cruz Biotechnology Inc.), cytochrome c oxidase subunit 4 (COX IV; cat. MS407; 1:1000, Mitoscience), and NADH dehydrogenase (ubiquinone) iron-sulfur protein 3 (NDUFS3; cat. MS110; 1:1000, Mitoscience). Total extracellular regulated protein kinase (T-ERK; cat. SC93 [C-16]; 1:2000, Santa Cruz Biotechnology Inc.) was probed as a loading control (previous studies have shown that the expression of this protein does not change in intact DRG or cultures from diabetic rats). The blots were rinsed, incubated in Western blotting Luminol Reagent (Santa Cruz Biotechnology Inc.), Bio-Rad Clarity Western ECL substrate, or ECL Advanced (GE Healthcare) and imaged using a Bio-Rad or Fluor-S analyzer or ChemiDoc MP (Bio-Rad).

Luciferase reporter constructs for PGC-1α and cell transfection. Reporter plasmids with the PGC-1α promoter upstream from luciferase were donated by Michael Czubryt (University of Manitoba). Rat DRG cells (30 × 103) were transfected in triplicate with 1.8 μg of PGC-1α Luc-promoter plasmid DNA and 0.2 μg of pCMV-Renilla (Promega) using the Amaxa Nucleofector Electroporation Kit for low numbers of cells according to the manufacturer’s instructions (ESBE Scientific). Cells were lysed using passive lysis buffer provided with the Dual-Luciferase Reporter Assay System (Promega). Luciferase activity was measured using a luminometer (model LMAXII; Molecular Devices). 20 μl of each sample was loaded in a 96-well plate and was mixed with 100 μl of Luciferase Assay Reagent II, and firefly luciferase activity was first recorded. Then, 100 μl of Stop-and-Glo Reagent (Promega) was added, and Renilla luciferase activity was measured. All values were adjusted to Renilla luciferase activity and normalized to control plasmid pGL3 levels. CC, a specific inhibitor of AMPK (77), was obtained from Abcam.

Viral transduction of AMPK mutants in cultured sensory neurons. Adult sensory neurons from control or diabetic rats maintained in the presence of a low-dose cocktail of neurotrophic factors were infected with adenovirus carrying dominant negative mutants of AMPKα1 or AMPKα2 subunits (DN1 or DN2) or constitutively active AMPK (ad-AMPK-CA), respectively. The ad-AMPK-CA and dominant negative adenoviral constructs were delivered at 20 PFU/cell, and the control adenoviral construct was delivered at 10 PFU/cell. Cultures were allowed to attach/grow for 1 day and were incubated with adenovirus for 3 hours, and the media was changed. Neurite outgrowth was determined in GFP-positive neurons 48 hours after infection. The constructs were gifts from Jason Dyck (University of Alberta, Edmonton, Alberta, Canada) (78).

Respiratory complex activities in mouse DRG. Measurements of enzymatic activities of respiratory complexes from mouse DRG homogenates were performed using a temperature-controlled Ultrospec 2100 UV-visible spectrophotometer equipped with Biochrom Swift II software (Biopharmacia Biotech) as previously described (11).

Animals. Studies were performed in Sprague-Dawley rats (Harlan) and Swiss Webster, C57BL/6 (stock 000664), C57BLKS (stock 000662), and BKS.Cg-Dock7m+/+Leprdb/J (stock 000642: commonly called db/db) mice (all Jackson Laboratories) or M1R knockout mice on a C57BL/6 background (line 1784; Taconic Biosciences Inc.) (79). In all but the spontaneously diabetic db/db mice, type 1 diabetes was induced by injection of STZ (from Sigma-Aldrich) in 0.9% saline after overnight fast at a single dose of 50–60 mg/kg for female rats, 75 mg/kg for male rats, or 90–100 mg/kg on 2 consecutive days for mice. Blood glucose levels were confirmed 4 to 7 days later in samples obtained by tail prick and measured using a strip-operated reflectance meter (One Touch Ultra, LifeScan Inc.). Persistence of diabetic status was confirmed at the end of each study (see Supplemental Tables 1 and 2) by recording body weight, blood glucose, and in select studies, plasma insulin concentration (Ultra Mouse Insulin ELISA kit, Crystal Chem Inc.) and HbA1c (A1CNow Test Kit, Bayer Healthcare). Paclitaxel neuropathy was induced by injection (5.0 mg/kg i.p.) on days 1, 3, 5, and 7 of the study (80). DCA neuropathy was induced by daily injection (1.0 g/kg i.p.) throughout the study (43, 81). Local exposure to gp120 (product 1021, ImmunoDX) was used to model HIV neuropathy (44). Adult female Swiss Webster mice received 1 daily eye drop containing vehicle alone (20 μl of 0.1M sodium phosphate buffer) or gp120 (2.5 ng/ml in vehicle) for 10 weeks. In all studies, animals were randomly assigned to groups, and all animals and their derived tissues were coded to ensure blinding of investigators during behavioral, physiological, and histological assays. Pirenzepine (Sigma-Aldrich) was given at 0.1–10 mg/kg s.c. 5 times weekly, and VU0255035 (a gift from Vanderbilt Center for Neuroscience Drug Discovery, Franklin, Tennessee) was given at 10 mg/kg i.p. 5 times weekly. MT7 (product M-200, Alomone Labs) was given as eye drops (20 μl of 25 ng/ml solution in 0.1 M sodium phosphate buffer) either once daily from the onset of gp120 exposure or 3 times daily starting after 5 weeks of gp120 exposure.

Behavioral tests. Hind-paw withdrawal responses to von Frey filaments (50% paw withdrawal threshold in gram of force applied) and radiant heat (latency to withdrawal in seconds) and also paw flinching following injection of 50 μl 0.5% formalin were measured in conscious unrestrained animals (82, 83).

Electrophysiology. Electrophysiological parameters were determined as previously described in multiple papers (84, 85). Animals were anesthetized with isoflurane and stimulating electrodes placed at the sciatic notch and Achilles tendon of the left hind limb, with recording electrodes placed in the interosseus muscles of the ipsilateral foot. Nerve temperature was maintained at 37°C and the nerve stimulated by single-square wave pulses applied first to the notch and then the tendon. Peak-peak latency of the resulting M or H waves was used to derive MNCV and sciatic sensory nerve-conduction velocity (SNCV), respectively, using the distance between stimulating electrodes. NCV was measured in triplicate and the median used to represent NCV of the animal.

IENF quantification. The plantar dermis and epidermis of the hind paw was removed and added to 4% paraformaldehyde. Tissue was processed to paraffin blocks, cut as 6-μm sections, and immunostained using an antibody to PGP 9.5 (cat. 7863-0504; 1:1000, AbD Serotec); the number of immunoreactive IENF profiles was quantified under blinded conditions by light microscopy and normalized to length of the dermal/epidermal junction (86).

Corneal confocal microscopy. Corneal nerves of the subbasal nerve plexus were imaged in anesthetized mice using a Heidelberg Retina Tomograph 3 with Rostock Cornea Module (Heidelberg Engineering), and occupancy of 5 consecutive images (2 μm intervals) per animal was calculated using an 8 × 8 grid (Figure 8) as described elsewhere (87).

Statistics. Data are expressed as mean ± SEM and individual data points shown in scatter dot plots when n is greater than 3. Where appropriate, data were subjected to unpaired 2-tailed Student’s t test, 1-way ANOVA with post-hoc comparisons using Tukey’s or Dunnett’s post-hoc tests, or 2-way ANOVA with repeat measures followed by Dunnett’s post-hoc test. GraphPad Prism software was used to perform statistical analysis.

Study approval. All animal procedures were approved by the University of Manitoba Animal Care Committee (overseen by the Committee on Animal Care) using Canadian Council of Animal Care rules or the Institutional Animal Care and Use Committee at UCSD.

Author contributions

KF, AG, TMZ, and DRS established, maintained, treated, and performed behavioral assays on groups of rats and mice. LT, RVDP, MGS, and DRS performed primary neuron cell culture, Western blotting, and immunocytochemistry. RVDP carried out the initial drug screen and analyzed calcium signals in cultured neurons. SKR performed mitochondrial enzymatic activities and Seahorse and Oroboros analysis of mitochondrial function. AS carried out gene reporter and adenoviral infection studies. MGS generated the GFP-M1R and Halo constructs, reverse-transcriptase PCR (RT-PCR), siRNA knockdown, 2D gel and isoelectric focusing, and time-lapse calcium imaging. KF, JO, AG, NM, and CGJ performed morphometric, electrophysiological, and biochemical assays. LT, RVP, DRS, MGS, AS, SKRC, KF, and CGJ analyzed data. JW provided M1R knockout mice and edited the paper. DRS, MGS, and CGJ designed experiments. PF and NAC designed experiments, analyzed data, and wrote and edited the paper.

Supplemental material

View Supplemental data

Acknowledgments

Severe obesity may be caused by this genetic mutation

Gastric band Surgery In France

Severe obesity may be caused by this genetic mutation

Sign in

Log in with your Medical News Today account to create or edit your custom homepage, catch-up on your opinions notifications and set your newsletter preferences.

Early-life exposures affect infant health

Research Update Jan. 9, 2017

Three recent studies have shown how dietary and other environmental exposures, including those that shape the internal environment created by gut microbes, are critically important during the first few years of life, with implications for a lifetime of good health. These exposures include not only the diet of the mother and child, but also other experiences that have a large impact on the bacterial populations of a child’s gut, such as antibiotic treatment and delivery by vaginal or cesarean modes. More and more, the gut microbial community is being appreciated for its effects on human health, and the first 3 years of life is an important period for maturation of this gut microbial community. For example, by training the developing immune system, gut microbes are thought to play a possible role in guarding against autoimmune diseases such as type 1 diabetes and inflammatory bowel disease, as well as other immune-related diseases, including asthma and allergies. Early disturbances in the gut microbial community from such factors as antibiotics or cesarean delivery have also been linked to an increased risk for metabolic disorders, such as obesity. Studies by three research groups have delved into how great an impact these early exposures can have on infants, potentially affecting their future health.

As part of the Healthy Start Study, researchers studied over 1,000 pairs of mothers and infants from multiple ethnic backgrounds to see how different types of foods eaten during pregnancy might affect infant body fat. The mothers were recruited during pregnancy. The researchers collected blood samples and information from the mothers on such subjects as physical activity and diet. Throughout pregnancy, participating mothers also completed several 24-hour dietary recalls online to provide a more complete picture of their diets. After delivery, information was collected in the hospital on the mothers and babies, including measurements of the infants’ length, weight, and skin-fold thickness. The researchers also estimated the infants’ body composition, including fat mass and fat-free mass. The mothers’ diet quality was measured using a scoring system based on the 2010 Dietary Guidelines for Americans. The researchers found that consuming a lower-quality diet (e.g., more fat and sodium, and fewer fruits and vegetables) during pregnancy was associated with a higher percent of fat mass in the newborns, regardless of how much the women had weighed before pregnancy. The researchers plan to continue studying these infants to figure out what effect a larger fat mass at birth has on the risk of developing obesity in childhood and later in life. This study highlights a potential way to improve the health of newborns—eating more healthfully during pregnancy.

Another research group followed the gut microbial development of 43 U.S. children during their first 2 years using genetic techniques to characterize the evolving community of bacterial species present in their stool samples during this dynamic period of development. They collected vaginal swabs, rectal swabs, and stool samples from mothers, both before and after delivery, and stool samples from the infants. Typically, infants’ gut microbes follow a developmental program of maturation with some species dominating the mix at certain stages, which continues from birth until around age 3, after which point the microbial mix resembles that of adults. The researchers identified three major phases in the development of the gut microbiome in early life, with a type of bacteria called Enterobacteriaceae dominating in the first month, a more dynamic period from 1 to 24 months of life, then a more adult-like gut bacterial community resembling their mothers’ around age 2 years. However, they observed that the predominant species in the mix were affected in early life by delivery mode (vaginal versus cesarean section), infant diet (breastfeeding versus formula feeding), and antibiotic treatment, particularly during the dynamic middle phase. After the first few months of life, infants delivered by cesarean section had less diverse and less mature gut microbial communities than those in vaginally delivered infants. With antibiotic treatment, the diversity of species in the gut also diminished, and the developmental maturation of the gut microbial community as a whole was delayed; however, the effect was less than that of delivery mode. Gut microbiota diversity and maturity was also reduced between ages 1 to 2 years in infants fed with formula compared to breastmilk.

A similar study focused on the gut microbial changes in 39 children living in Finland during their first 3 years of life, using some more in-depth DNA sequencing of the children’s stool samples. In these children, all of whom were breastfed for some amount of time, the gut microbial community development was most rapid during the first 6 months of life. As with the study of the gut microbiota in American children, the researchers found the Finnish children who were born by cesarean section or who received antibiotic treatment had a less diverse set of bacterial species in their gut. However, unlike the American study, they found that a proportion (20 percent) of vaginally born children also showed reduced numbers of some key bacterial species, called Bacteroides, that were lacking in all of those born by cesarean. Also unique to this analysis was their ability to probe deeper into the specific strains of bacteria present within the species. Through this analysis, they could see that antibiotic treatment had an even greater impact on reducing gut microbial community diversity at the level of specific bacterial strains than it did at the species level. Antibiotic treatment was also associated with a less stable gut microbial community and an increase in antibiotic resistance genes.

More research will be needed to understand fully the long-term effects of these early exposures—from the quality of the mothers’ diet during pregnancy to disruptions within the infant gut microbiome due to delivery mode, antibiotic treatment, or feeding method—on the health and disease risk of children as they grow. For example, future studies could determine, at the level of bacterial genes and their gene products, the implications of these disruptions for gut microbial community function and, by extension, human health.

References

Shapiro ALB, Kaar JL, Crume TL, Starling AP, Siega-Riz AM, Ringham BM, Glueck DH, Norris JM, Barbour LA, Friedman JE, and Dabelea D. Maternal diet quality in pregnancy and neonatal adiposity: the Healthy Start Study. Int J Obes (Lond). 2016;40:1056-1062.

Bokulich NA, Chung J, Battaglia T, Henderson N, Jay M, Li H, Lieber AD, Wu F, Perez-Perez GI, Chen Y, Schweizer W, Zheng X, Contreras M, Dominguez-Bello MG, and Blaser MJ. Antibiotics, birth mode, and diet shape microbiome maturation during early life. Sci Transl Med. 2016;8:343ra82.

Read more……>click Here<

Heart failure risk could be reversed with exercise program

Gastric band Surgery In France

Heart failure risk could be reversed with exercise program

Sign in

Log in with your Medical News Today account to create or edit your custom homepage, catch-up on your opinions notifications and set your newsletter preferences.

NIH-sponsored expert panel issues clinical guidelines to prevent peanut allergy

News Release

Thursday, January 5, 2017

Recommendations focus on introducing peanut-containing foods to infants.

An expert panel sponsored by the National Institute of Allergy and Infectious Diseases (NIAID), part of the National Institutes of Health, issued clinical guidelines today to aid health care providers in early introduction of peanut-containing foods to infants to prevent the development of peanut allergy.

Peanut allergy is a growing health problem for which no treatment or cure exists. People living with peanut allergy, and their caregivers, must be vigilant about the foods they eat and the environments they enter to avoid allergic reactions, which can be severe and even life-threatening. The allergy tends to develop in childhood and persist through adulthood. However, recent scientific research has demonstrated that introducing peanut-containing foods into the diet during infancy can prevent the development of peanut allergy.

The new Addendum Guidelines for the Prevention of Peanut Allergy in the United States supplement the 2010 Guidelines for the Diagnosis and Management of Food Allergy in the United States. The addendum provides three separate guidelines for infants at various levels of risk for developing peanut allergy and is targeted to a wide variety of health care providers, including pediatricians and family practice physicians.

“Living with peanut allergy requires constant vigilance. Preventing the development of peanut allergy will improve and save lives and lower health care costs,” said NIAID Director Anthony S. Fauci, M.D. “We expect that widespread implementation of these guidelines by health care providers will prevent the development of peanut allergy in many susceptible children and ultimately reduce the prevalence of peanut allergy in the United States.”

Addendum Guideline 1 focuses on infants deemed at high risk of developing peanut allergy because they already have severe eczema, egg allergy or both. The expert panel recommends that these infants have peanut-containing foods introduced into their diets as early as 4 to 6 months of age to reduce the risk of developing peanut allergy. Parents and caregivers should check with their infant’s health care provider before feeding the infant peanut-containing foods. The health care provider may choose to perform an allergy blood test or send the infant to a specialist for other tests, such as a skin prick test or an oral food challenge. The results of these tests will help decide if and how peanut should be safely introduced into the infant’s diet.

Guideline 2 suggests that infants with mild or moderate eczema should have peanut-containing foods introduced into their diets around 6 months of age to reduce the risk of peanut allergy. Guideline 3 suggests that infants without eczema or any food allergy have peanut-containing foods freely introduced into their diets.

In all cases, infants should start other solid foods before they are introduced to peanut-containing foods.

Development of the Addendum Guidelines was prompted by emerging data suggesting that peanut allergy can be prevented by the early introduction of peanut-containing foods. Clinical trial results reported in February 2015 showed that regular peanut consumption begun in infancy and continued until 5 years of age led to an 81 percent reduction in development of peanut allergy in infants deemed at high risk because they already had severe eczema, egg allergy or both. This finding came from the landmark, NIAID-funded Learning Early About Peanut Allergy (LEAP) study, a randomized clinical trial involving more than 600 infants.

“The LEAP study clearly showed that introduction of peanut early in life significantly lowered the risk of developing peanut allergy by age 5. The magnitude of the benefit and the scientific strength of the study raised the need to operationalize these findings by developing clinical recommendations focused on peanut allergy prevention,” said Daniel Rotrosen, M.D., director of NIAID’s Division of Allergy, Immunology and Transplantation. 

In 2015, NIAID established a coordinating committee representing 26 professional organizations, advocacy groups and federal agencies to oversee development of the Addendum Guidelines to specifically address the prevention of peanut allergy. The coordinating committee convened a 26-member expert panel comprising specialists from a variety of relevant clinical, scientific and public health areas. The panel, chaired by Joshua Boyce, M.D., professor of medicine and pediatrics at Harvard Medical School, used a literature review of food allergy prevention research and their own expert opinions to prepare draft guidelines. The draft guidelines were available on the NIAID website for public comment from March 4 to April 18, 2016. The expert panel and coordinating committee reviewed the 104 comments received to develop the final Addendum Guidelines.

The Addendum Guidelines appear January 5 in the Journal of Allergy and Clinical Immunology and will be co-published in the Annals of Allergy, Asthma, and Immunology; Journal of Pediatric Nursing; Pediatric Dermatology; World Allergy Organization Journal; and Allergy, Asthma, and Clinical Immunology. Related resources, including a Summary for Clinicians and Summary for Parents and Caregivers, are freely accessible on the NIAID food allergy guidelines webpage. A PDF copy of the Addendum Guidelines also will be made available there soon.

NIAID conducts and supports research — at NIH, throughout the United States, and worldwide — to study the causes of infectious and immune-mediated diseases, and to develop better means of preventing, diagnosing and treating these illnesses. News releases, fact sheets and other NIAID-related materials are available on the NIAID website.

About the National Institutes of Health (NIH): NIH, the nation’s medical research agency, includes 27 Institutes and Centers and is a component of the U.S. Department of Health and Human Services. NIH is the primary federal agency conducting and supporting basic, clinical, and translational medical research, and is investigating the causes, treatments, and cures for both common and rare diseases. For more information about NIH and its programs, visit www.nih.gov.

NIH…Turning Discovery Into Health®

Read more……>click Here<

Does green tea help weight loss?

Gastric band Surgery In France

Does green tea help weight loss?

Sign in

Log in with your Medical News Today account to create or edit your custom homepage, catch-up on your opinions notifications and set your newsletter preferences.

Deficiency in Prohormone Convertase PC1 Impairs Prohormone Processing in Prader-Willi Syndrome.

Research ArticleEndocrinologyGenetics Free access | 10.1172/JCI88648

Lisa C. Burnett,1,2,3 Charles A. LeDuc,2,3,4 Carlos R. Sulsona,5 Daniel Paull,6 Richard Rausch,2,3 Sanaa Eddiry,7 Jayne F. Martin Carli,2,3,8 Michael V. Morabito,2,3 Alicja A. Skowronski,1,2,3 Gabriela Hubner,9 Matthew Zimmer,6 Liheng Wang,2,3 Robert Day,10 Brynn Levy,11 Ilene Fennoy,12 Beatrice Dubern,13 Christine Poitou,13 Karine Clement,13 Merlin G. Butler,14 Michael Rosenbaum,2,3 Jean Pierre Salles,7,15 Maithe Tauber,7,15,16 Daniel J. Driscoll,5,17 Dieter Egli,2,3,6 and Rudolph L. Leibel2,3,4

1Institute of Human Nutrition,

2Department of Pediatrics, Division of Molecular Genetics, and

3Naomi Berrie Diabetes Center, Columbia University, New York, New York, USA.

4New York Obesity Research Center, New York, New York, USA.

5Department of Pediatrics, Division of Genetics and Metabolism, University of Florida College of Medicine Gainesville, Florida, USA.

6The New York Stem Cell Foundation Research Institute, New York, New York, USA.

7Centre de Physiopathologie de Toulouse-Purpan, Université de Toulouse, CNRS UMR 5282, INSERM UMR 1043, Université Paul Sabatier, Toulouse, France.

8Department of Biochemistry and Molecular Biophysics, Columbia University, New York, New York, USA.

9Packer Collegiate Institute, New York, New York, USA.

10Institut de pharmacologie de Sherbrooke, Department of Surgery, Division of Urology, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, Quebec, Canada.

11Department of Pathology and Cell Biology, Columbia University, New York, New York, USA.

12Department of Pediatrics, Division of Pediatric Diabetes, Endocrinology and Metabolism, Columbia University, New York, New York, USA.

13Institute of Cardiometabolism and Nutrition, Assistance Publique Hôpitaux de Paris, Sorbonne University, University Pierre et Marie-Curie, INSERM UMRS 1166, Paris, France.

14Department of Psychiatry and Behavioral Sciences, Division of Research and Genetics, Kansas University Medical Center, Kansas City, Kansas, USA.

15Unité d’Endocrinologie, Hôpital des Enfants, and

16Centre de Référence du Syndrome de Prader-Willi, CHU Toulouse, Toulouse, France.

17Center for Epigenetics, University of Florida College of Medicine, Gainesville, Florida, USA.

Address correspondence to: Lisa C. Burnett or Rudolph L. Leibel, 1150 St. Nicholas Avenue Russ Berrie Pavilion Room 620 New York, NY 10033; Phone: 212 851 5315; E-mail: lmc2200@cumc.columbia.edu (L.C. Burnett); rl2332@cumc.columbia.edu (R.L. Leibel).

Find articles by Burnett, L. in: JCI | PubMed | Google Scholar

1Institute of Human Nutrition,

2Department of Pediatrics, Division of Molecular Genetics, and

3Naomi Berrie Diabetes Center, Columbia University, New York, New York, USA.

4New York Obesity Research Center, New York, New York, USA.

5Department of Pediatrics, Division of Genetics and Metabolism, University of Florida College of Medicine Gainesville, Florida, USA.

6The New York Stem Cell Foundation Research Institute, New York, New York, USA.

7Centre de Physiopathologie de Toulouse-Purpan, Université de Toulouse, CNRS UMR 5282, INSERM UMR 1043, Université Paul Sabatier, Toulouse, France.

8Department of Biochemistry and Molecular Biophysics, Columbia University, New York, New York, USA.

9Packer Collegiate Institute, New York, New York, USA.

10Institut de pharmacologie de Sherbrooke, Department of Surgery, Division of Urology, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, Quebec, Canada.

11Department of Pathology and Cell Biology, Columbia University, New York, New York, USA.

12Department of Pediatrics, Division of Pediatric Diabetes, Endocrinology and Metabolism, Columbia University, New York, New York, USA.

13Institute of Cardiometabolism and Nutrition, Assistance Publique Hôpitaux de Paris, Sorbonne University, University Pierre et Marie-Curie, INSERM UMRS 1166, Paris, France.

14Department of Psychiatry and Behavioral Sciences, Division of Research and Genetics, Kansas University Medical Center, Kansas City, Kansas, USA.

15Unité d’Endocrinologie, Hôpital des Enfants, and

16Centre de Référence du Syndrome de Prader-Willi, CHU Toulouse, Toulouse, France.

17Center for Epigenetics, University of Florida College of Medicine, Gainesville, Florida, USA.

Address correspondence to: Lisa C. Burnett or Rudolph L. Leibel, 1150 St. Nicholas Avenue Russ Berrie Pavilion Room 620 New York, NY 10033; Phone: 212 851 5315; E-mail: lmc2200@cumc.columbia.edu (L.C. Burnett); rl2332@cumc.columbia.edu (R.L. Leibel).

Find articles by LeDuc, C. in: JCI | PubMed | Google Scholar

1Institute of Human Nutrition,

2Department of Pediatrics, Division of Molecular Genetics, and

3Naomi Berrie Diabetes Center, Columbia University, New York, New York, USA.

4New York Obesity Research Center, New York, New York, USA.

5Department of Pediatrics, Division of Genetics and Metabolism, University of Florida College of Medicine Gainesville, Florida, USA.

6The New York Stem Cell Foundation Research Institute, New York, New York, USA.

7Centre de Physiopathologie de Toulouse-Purpan, Université de Toulouse, CNRS UMR 5282, INSERM UMR 1043, Université Paul Sabatier, Toulouse, France.

8Department of Biochemistry and Molecular Biophysics, Columbia University, New York, New York, USA.

9Packer Collegiate Institute, New York, New York, USA.

10Institut de pharmacologie de Sherbrooke, Department of Surgery, Division of Urology, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, Quebec, Canada.

11Department of Pathology and Cell Biology, Columbia University, New York, New York, USA.

12Department of Pediatrics, Division of Pediatric Diabetes, Endocrinology and Metabolism, Columbia University, New York, New York, USA.

13Institute of Cardiometabolism and Nutrition, Assistance Publique Hôpitaux de Paris, Sorbonne University, University Pierre et Marie-Curie, INSERM UMRS 1166, Paris, France.

14Department of Psychiatry and Behavioral Sciences, Division of Research and Genetics, Kansas University Medical Center, Kansas City, Kansas, USA.

15Unité d’Endocrinologie, Hôpital des Enfants, and

16Centre de Référence du Syndrome de Prader-Willi, CHU Toulouse, Toulouse, France.

17Center for Epigenetics, University of Florida College of Medicine, Gainesville, Florida, USA.

Address correspondence to: Lisa C. Burnett or Rudolph L. Leibel, 1150 St. Nicholas Avenue Russ Berrie Pavilion Room 620 New York, NY 10033; Phone: 212 851 5315; E-mail: lmc2200@cumc.columbia.edu (L.C. Burnett); rl2332@cumc.columbia.edu (R.L. Leibel).

Find articles by Sulsona, C. in: JCI | PubMed | Google Scholar

1Institute of Human Nutrition,

2Department of Pediatrics, Division of Molecular Genetics, and

3Naomi Berrie Diabetes Center, Columbia University, New York, New York, USA.

4New York Obesity Research Center, New York, New York, USA.

5Department of Pediatrics, Division of Genetics and Metabolism, University of Florida College of Medicine Gainesville, Florida, USA.

6The New York Stem Cell Foundation Research Institute, New York, New York, USA.

7Centre de Physiopathologie de Toulouse-Purpan, Université de Toulouse, CNRS UMR 5282, INSERM UMR 1043, Université Paul Sabatier, Toulouse, France.

8Department of Biochemistry and Molecular Biophysics, Columbia University, New York, New York, USA.

9Packer Collegiate Institute, New York, New York, USA.

10Institut de pharmacologie de Sherbrooke, Department of Surgery, Division of Urology, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, Quebec, Canada.

11Department of Pathology and Cell Biology, Columbia University, New York, New York, USA.

12Department of Pediatrics, Division of Pediatric Diabetes, Endocrinology and Metabolism, Columbia University, New York, New York, USA.

13Institute of Cardiometabolism and Nutrition, Assistance Publique Hôpitaux de Paris, Sorbonne University, University Pierre et Marie-Curie, INSERM UMRS 1166, Paris, France.

14Department of Psychiatry and Behavioral Sciences, Division of Research and Genetics, Kansas University Medical Center, Kansas City, Kansas, USA.

15Unité d’Endocrinologie, Hôpital des Enfants, and

16Centre de Référence du Syndrome de Prader-Willi, CHU Toulouse, Toulouse, France.

17Center for Epigenetics, University of Florida College of Medicine, Gainesville, Florida, USA.

Address correspondence to: Lisa C. Burnett or Rudolph L. Leibel, 1150 St. Nicholas Avenue Russ Berrie Pavilion Room 620 New York, NY 10033; Phone: 212 851 5315; E-mail: lmc2200@cumc.columbia.edu (L.C. Burnett); rl2332@cumc.columbia.edu (R.L. Leibel).

Find articles by Paull, D. in: JCI | PubMed | Google Scholar

1Institute of Human Nutrition,

2Department of Pediatrics, Division of Molecular Genetics, and

3Naomi Berrie Diabetes Center, Columbia University, New York, New York, USA.

4New York Obesity Research Center, New York, New York, USA.

5Department of Pediatrics, Division of Genetics and Metabolism, University of Florida College of Medicine Gainesville, Florida, USA.

6The New York Stem Cell Foundation Research Institute, New York, New York, USA.

7Centre de Physiopathologie de Toulouse-Purpan, Université de Toulouse, CNRS UMR 5282, INSERM UMR 1043, Université Paul Sabatier, Toulouse, France.

8Department of Biochemistry and Molecular Biophysics, Columbia University, New York, New York, USA.

9Packer Collegiate Institute, New York, New York, USA.

10Institut de pharmacologie de Sherbrooke, Department of Surgery, Division of Urology, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, Quebec, Canada.

11Department of Pathology and Cell Biology, Columbia University, New York, New York, USA.

12Department of Pediatrics, Division of Pediatric Diabetes, Endocrinology and Metabolism, Columbia University, New York, New York, USA.

13Institute of Cardiometabolism and Nutrition, Assistance Publique Hôpitaux de Paris, Sorbonne University, University Pierre et Marie-Curie, INSERM UMRS 1166, Paris, France.

14Department of Psychiatry and Behavioral Sciences, Division of Research and Genetics, Kansas University Medical Center, Kansas City, Kansas, USA.

15Unité d’Endocrinologie, Hôpital des Enfants, and

16Centre de Référence du Syndrome de Prader-Willi, CHU Toulouse, Toulouse, France.

17Center for Epigenetics, University of Florida College of Medicine, Gainesville, Florida, USA.

Address correspondence to: Lisa C. Burnett or Rudolph L. Leibel, 1150 St. Nicholas Avenue Russ Berrie Pavilion Room 620 New York, NY 10033; Phone: 212 851 5315; E-mail: lmc2200@cumc.columbia.edu (L.C. Burnett); rl2332@cumc.columbia.edu (R.L. Leibel).

Find articles by Rausch, R. in: JCI | PubMed | Google Scholar

1Institute of Human Nutrition,

2Department of Pediatrics, Division of Molecular Genetics, and

3Naomi Berrie Diabetes Center, Columbia University, New York, New York, USA.

4New York Obesity Research Center, New York, New York, USA.

5Department of Pediatrics, Division of Genetics and Metabolism, University of Florida College of Medicine Gainesville, Florida, USA.

6The New York Stem Cell Foundation Research Institute, New York, New York, USA.

7Centre de Physiopathologie de Toulouse-Purpan, Université de Toulouse, CNRS UMR 5282, INSERM UMR 1043, Université Paul Sabatier, Toulouse, France.

8Department of Biochemistry and Molecular Biophysics, Columbia University, New York, New York, USA.

9Packer Collegiate Institute, New York, New York, USA.

10Institut de pharmacologie de Sherbrooke, Department of Surgery, Division of Urology, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, Quebec, Canada.

11Department of Pathology and Cell Biology, Columbia University, New York, New York, USA.

12Department of Pediatrics, Division of Pediatric Diabetes, Endocrinology and Metabolism, Columbia University, New York, New York, USA.

13Institute of Cardiometabolism and Nutrition, Assistance Publique Hôpitaux de Paris, Sorbonne University, University Pierre et Marie-Curie, INSERM UMRS 1166, Paris, France.

14Department of Psychiatry and Behavioral Sciences, Division of Research and Genetics, Kansas University Medical Center, Kansas City, Kansas, USA.

15Unité d’Endocrinologie, Hôpital des Enfants, and

16Centre de Référence du Syndrome de Prader-Willi, CHU Toulouse, Toulouse, France.

17Center for Epigenetics, University of Florida College of Medicine, Gainesville, Florida, USA.

Address correspondence to: Lisa C. Burnett or Rudolph L. Leibel, 1150 St. Nicholas Avenue Russ Berrie Pavilion Room 620 New York, NY 10033; Phone: 212 851 5315; E-mail: lmc2200@cumc.columbia.edu (L.C. Burnett); rl2332@cumc.columbia.edu (R.L. Leibel).

Find articles by Eddiry, S. in: JCI | PubMed | Google Scholar

1Institute of Human Nutrition,

2Department of Pediatrics, Division of Molecular Genetics, and

3Naomi Berrie Diabetes Center, Columbia University, New York, New York, USA.

4New York Obesity Research Center, New York, New York, USA.

5Department of Pediatrics, Division of Genetics and Metabolism, University of Florida College of Medicine Gainesville, Florida, USA.

6The New York Stem Cell Foundation Research Institute, New York, New York, USA.

7Centre de Physiopathologie de Toulouse-Purpan, Université de Toulouse, CNRS UMR 5282, INSERM UMR 1043, Université Paul Sabatier, Toulouse, France.

8Department of Biochemistry and Molecular Biophysics, Columbia University, New York, New York, USA.

9Packer Collegiate Institute, New York, New York, USA.

10Institut de pharmacologie de Sherbrooke, Department of Surgery, Division of Urology, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, Quebec, Canada.

11Department of Pathology and Cell Biology, Columbia University, New York, New York, USA.

12Department of Pediatrics, Division of Pediatric Diabetes, Endocrinology and Metabolism, Columbia University, New York, New York, USA.

13Institute of Cardiometabolism and Nutrition, Assistance Publique Hôpitaux de Paris, Sorbonne University, University Pierre et Marie-Curie, INSERM UMRS 1166, Paris, France.

14Department of Psychiatry and Behavioral Sciences, Division of Research and Genetics, Kansas University Medical Center, Kansas City, Kansas, USA.

15Unité d’Endocrinologie, Hôpital des Enfants, and

16Centre de Référence du Syndrome de Prader-Willi, CHU Toulouse, Toulouse, France.

17Center for Epigenetics, University of Florida College of Medicine, Gainesville, Florida, USA.

Address correspondence to: Lisa C. Burnett or Rudolph L. Leibel, 1150 St. Nicholas Avenue Russ Berrie Pavilion Room 620 New York, NY 10033; Phone: 212 851 5315; E-mail: lmc2200@cumc.columbia.edu (L.C. Burnett); rl2332@cumc.columbia.edu (R.L. Leibel).

Find articles by Carli, J. in: JCI | PubMed | Google Scholar

1Institute of Human Nutrition,

2Department of Pediatrics, Division of Molecular Genetics, and

3Naomi Berrie Diabetes Center, Columbia University, New York, New York, USA.

4New York Obesity Research Center, New York, New York, USA.

5Department of Pediatrics, Division of Genetics and Metabolism, University of Florida College of Medicine Gainesville, Florida, USA.

6The New York Stem Cell Foundation Research Institute, New York, New York, USA.

7Centre de Physiopathologie de Toulouse-Purpan, Université de Toulouse, CNRS UMR 5282, INSERM UMR 1043, Université Paul Sabatier, Toulouse, France.

8Department of Biochemistry and Molecular Biophysics, Columbia University, New York, New York, USA.

9Packer Collegiate Institute, New York, New York, USA.

10Institut de pharmacologie de Sherbrooke, Department of Surgery, Division of Urology, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, Quebec, Canada.

11Department of Pathology and Cell Biology, Columbia University, New York, New York, USA.

12Department of Pediatrics, Division of Pediatric Diabetes, Endocrinology and Metabolism, Columbia University, New York, New York, USA.

13Institute of Cardiometabolism and Nutrition, Assistance Publique Hôpitaux de Paris, Sorbonne University, University Pierre et Marie-Curie, INSERM UMRS 1166, Paris, France.

14Department of Psychiatry and Behavioral Sciences, Division of Research and Genetics, Kansas University Medical Center, Kansas City, Kansas, USA.

15Unité d’Endocrinologie, Hôpital des Enfants, and

16Centre de Référence du Syndrome de Prader-Willi, CHU Toulouse, Toulouse, France.

17Center for Epigenetics, University of Florida College of Medicine, Gainesville, Florida, USA.

Address correspondence to: Lisa C. Burnett or Rudolph L. Leibel, 1150 St. Nicholas Avenue Russ Berrie Pavilion Room 620 New York, NY 10033; Phone: 212 851 5315; E-mail: lmc2200@cumc.columbia.edu (L.C. Burnett); rl2332@cumc.columbia.edu (R.L. Leibel).

Find articles by Morabito, M. in: JCI | PubMed | Google Scholar

1Institute of Human Nutrition,

2Department of Pediatrics, Division of Molecular Genetics, and

3Naomi Berrie Diabetes Center, Columbia University, New York, New York, USA.

4New York Obesity Research Center, New York, New York, USA.

5Department of Pediatrics, Division of Genetics and Metabolism, University of Florida College of Medicine Gainesville, Florida, USA.

6The New York Stem Cell Foundation Research Institute, New York, New York, USA.

7Centre de Physiopathologie de Toulouse-Purpan, Université de Toulouse, CNRS UMR 5282, INSERM UMR 1043, Université Paul Sabatier, Toulouse, France.

8Department of Biochemistry and Molecular Biophysics, Columbia University, New York, New York, USA.

9Packer Collegiate Institute, New York, New York, USA.

10Institut de pharmacologie de Sherbrooke, Department of Surgery, Division of Urology, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, Quebec, Canada.

11Department of Pathology and Cell Biology, Columbia University, New York, New York, USA.

12Department of Pediatrics, Division of Pediatric Diabetes, Endocrinology and Metabolism, Columbia University, New York, New York, USA.

13Institute of Cardiometabolism and Nutrition, Assistance Publique Hôpitaux de Paris, Sorbonne University, University Pierre et Marie-Curie, INSERM UMRS 1166, Paris, France.

14Department of Psychiatry and Behavioral Sciences, Division of Research and Genetics, Kansas University Medical Center, Kansas City, Kansas, USA.

15Unité d’Endocrinologie, Hôpital des Enfants, and

16Centre de Référence du Syndrome de Prader-Willi, CHU Toulouse, Toulouse, France.

17Center for Epigenetics, University of Florida College of Medicine, Gainesville, Florida, USA.

Address correspondence to: Lisa C. Burnett or Rudolph L. Leibel, 1150 St. Nicholas Avenue Russ Berrie Pavilion Room 620 New York, NY 10033; Phone: 212 851 5315; E-mail: lmc2200@cumc.columbia.edu (L.C. Burnett); rl2332@cumc.columbia.edu (R.L. Leibel).

Find articles by Skowronski, A. in: JCI | PubMed | Google Scholar

1Institute of Human Nutrition,

2Department of Pediatrics, Division of Molecular Genetics, and

3Naomi Berrie Diabetes Center, Columbia University, New York, New York, USA.

4New York Obesity Research Center, New York, New York, USA.

5Department of Pediatrics, Division of Genetics and Metabolism, University of Florida College of Medicine Gainesville, Florida, USA.

6The New York Stem Cell Foundation Research Institute, New York, New York, USA.

7Centre de Physiopathologie de Toulouse-Purpan, Université de Toulouse, CNRS UMR 5282, INSERM UMR 1043, Université Paul Sabatier, Toulouse, France.

8Department of Biochemistry and Molecular Biophysics, Columbia University, New York, New York, USA.

9Packer Collegiate Institute, New York, New York, USA.

10Institut de pharmacologie de Sherbrooke, Department of Surgery, Division of Urology, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, Quebec, Canada.

11Department of Pathology and Cell Biology, Columbia University, New York, New York, USA.

12Department of Pediatrics, Division of Pediatric Diabetes, Endocrinology and Metabolism, Columbia University, New York, New York, USA.

13Institute of Cardiometabolism and Nutrition, Assistance Publique Hôpitaux de Paris, Sorbonne University, University Pierre et Marie-Curie, INSERM UMRS 1166, Paris, France.

14Department of Psychiatry and Behavioral Sciences, Division of Research and Genetics, Kansas University Medical Center, Kansas City, Kansas, USA.

15Unité d’Endocrinologie, Hôpital des Enfants, and

16Centre de Référence du Syndrome de Prader-Willi, CHU Toulouse, Toulouse, France.

17Center for Epigenetics, University of Florida College of Medicine, Gainesville, Florida, USA.

Address correspondence to: Lisa C. Burnett or Rudolph L. Leibel, 1150 St. Nicholas Avenue Russ Berrie Pavilion Room 620 New York, NY 10033; Phone: 212 851 5315; E-mail: lmc2200@cumc.columbia.edu (L.C. Burnett); rl2332@cumc.columbia.edu (R.L. Leibel).

Find articles by Hubner, G. in: JCI | PubMed | Google Scholar

1Institute of Human Nutrition,

2Department of Pediatrics, Division of Molecular Genetics, and

3Naomi Berrie Diabetes Center, Columbia University, New York, New York, USA.

4New York Obesity Research Center, New York, New York, USA.

5Department of Pediatrics, Division of Genetics and Metabolism, University of Florida College of Medicine Gainesville, Florida, USA.

6The New York Stem Cell Foundation Research Institute, New York, New York, USA.

7Centre de Physiopathologie de Toulouse-Purpan, Université de Toulouse, CNRS UMR 5282, INSERM UMR 1043, Université Paul Sabatier, Toulouse, France.

8Department of Biochemistry and Molecular Biophysics, Columbia University, New York, New York, USA.

9Packer Collegiate Institute, New York, New York, USA.

10Institut de pharmacologie de Sherbrooke, Department of Surgery, Division of Urology, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, Quebec, Canada.

11Department of Pathology and Cell Biology, Columbia University, New York, New York, USA.

12Department of Pediatrics, Division of Pediatric Diabetes, Endocrinology and Metabolism, Columbia University, New York, New York, USA.

13Institute of Cardiometabolism and Nutrition, Assistance Publique Hôpitaux de Paris, Sorbonne University, University Pierre et Marie-Curie, INSERM UMRS 1166, Paris, France.

14Department of Psychiatry and Behavioral Sciences, Division of Research and Genetics, Kansas University Medical Center, Kansas City, Kansas, USA.

15Unité d’Endocrinologie, Hôpital des Enfants, and

16Centre de Référence du Syndrome de Prader-Willi, CHU Toulouse, Toulouse, France.

17Center for Epigenetics, University of Florida College of Medicine, Gainesville, Florida, USA.

Address correspondence to: Lisa C. Burnett or Rudolph L. Leibel, 1150 St. Nicholas Avenue Russ Berrie Pavilion Room 620 New York, NY 10033; Phone: 212 851 5315; E-mail: lmc2200@cumc.columbia.edu (L.C. Burnett); rl2332@cumc.columbia.edu (R.L. Leibel).

Find articles by Zimmer, M. in: JCI | PubMed | Google Scholar

1Institute of Human Nutrition,

2Department of Pediatrics, Division of Molecular Genetics, and

3Naomi Berrie Diabetes Center, Columbia University, New York, New York, USA.

4New York Obesity Research Center, New York, New York, USA.

5Department of Pediatrics, Division of Genetics and Metabolism, University of Florida College of Medicine Gainesville, Florida, USA.

6The New York Stem Cell Foundation Research Institute, New York, New York, USA.

7Centre de Physiopathologie de Toulouse-Purpan, Université de Toulouse, CNRS UMR 5282, INSERM UMR 1043, Université Paul Sabatier, Toulouse, France.

8Department of Biochemistry and Molecular Biophysics, Columbia University, New York, New York, USA.

9Packer Collegiate Institute, New York, New York, USA.

10Institut de pharmacologie de Sherbrooke, Department of Surgery, Division of Urology, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, Quebec, Canada.

11Department of Pathology and Cell Biology, Columbia University, New York, New York, USA.

12Department of Pediatrics, Division of Pediatric Diabetes, Endocrinology and Metabolism, Columbia University, New York, New York, USA.

13Institute of Cardiometabolism and Nutrition, Assistance Publique Hôpitaux de Paris, Sorbonne University, University Pierre et Marie-Curie, INSERM UMRS 1166, Paris, France.

14Department of Psychiatry and Behavioral Sciences, Division of Research and Genetics, Kansas University Medical Center, Kansas City, Kansas, USA.

15Unité d’Endocrinologie, Hôpital des Enfants, and

16Centre de Référence du Syndrome de Prader-Willi, CHU Toulouse, Toulouse, France.

17Center for Epigenetics, University of Florida College of Medicine, Gainesville, Florida, USA.

Address correspondence to: Lisa C. Burnett or Rudolph L. Leibel, 1150 St. Nicholas Avenue Russ Berrie Pavilion Room 620 New York, NY 10033; Phone: 212 851 5315; E-mail: lmc2200@cumc.columbia.edu (L.C. Burnett); rl2332@cumc.columbia.edu (R.L. Leibel).

Find articles by Wang, L. in: JCI | PubMed | Google Scholar

1Institute of Human Nutrition,

2Department of Pediatrics, Division of Molecular Genetics, and

3Naomi Berrie Diabetes Center, Columbia University, New York, New York, USA.

4New York Obesity Research Center, New York, New York, USA.

5Department of Pediatrics, Division of Genetics and Metabolism, University of Florida College of Medicine Gainesville, Florida, USA.

6The New York Stem Cell Foundation Research Institute, New York, New York, USA.

7Centre de Physiopathologie de Toulouse-Purpan, Université de Toulouse, CNRS UMR 5282, INSERM UMR 1043, Université Paul Sabatier, Toulouse, France.

8Department of Biochemistry and Molecular Biophysics, Columbia University, New York, New York, USA.

9Packer Collegiate Institute, New York, New York, USA.

10Institut de pharmacologie de Sherbrooke, Department of Surgery, Division of Urology, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, Quebec, Canada.

11Department of Pathology and Cell Biology, Columbia University, New York, New York, USA.

12Department of Pediatrics, Division of Pediatric Diabetes, Endocrinology and Metabolism, Columbia University, New York, New York, USA.

13Institute of Cardiometabolism and Nutrition, Assistance Publique Hôpitaux de Paris, Sorbonne University, University Pierre et Marie-Curie, INSERM UMRS 1166, Paris, France.

14Department of Psychiatry and Behavioral Sciences, Division of Research and Genetics, Kansas University Medical Center, Kansas City, Kansas, USA.

15Unité d’Endocrinologie, Hôpital des Enfants, and

16Centre de Référence du Syndrome de Prader-Willi, CHU Toulouse, Toulouse, France.

17Center for Epigenetics, University of Florida College of Medicine, Gainesville, Florida, USA.

Address correspondence to: Lisa C. Burnett or Rudolph L. Leibel, 1150 St. Nicholas Avenue Russ Berrie Pavilion Room 620 New York, NY 10033; Phone: 212 851 5315; E-mail: lmc2200@cumc.columbia.edu (L.C. Burnett); rl2332@cumc.columbia.edu (R.L. Leibel).

Find articles by Day, R. in: JCI | PubMed | Google Scholar

1Institute of Human Nutrition,

2Department of Pediatrics, Division of Molecular Genetics, and

3Naomi Berrie Diabetes Center, Columbia University, New York, New York, USA.

4New York Obesity Research Center, New York, New York, USA.

5Department of Pediatrics, Division of Genetics and Metabolism, University of Florida College of Medicine Gainesville, Florida, USA.

6The New York Stem Cell Foundation Research Institute, New York, New York, USA.

7Centre de Physiopathologie de Toulouse-Purpan, Université de Toulouse, CNRS UMR 5282, INSERM UMR 1043, Université Paul Sabatier, Toulouse, France.

8Department of Biochemistry and Molecular Biophysics, Columbia University, New York, New York, USA.

9Packer Collegiate Institute, New York, New York, USA.

10Institut de pharmacologie de Sherbrooke, Department of Surgery, Division of Urology, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, Quebec, Canada.

11Department of Pathology and Cell Biology, Columbia University, New York, New York, USA.

12Department of Pediatrics, Division of Pediatric Diabetes, Endocrinology and Metabolism, Columbia University, New York, New York, USA.

13Institute of Cardiometabolism and Nutrition, Assistance Publique Hôpitaux de Paris, Sorbonne University, University Pierre et Marie-Curie, INSERM UMRS 1166, Paris, France.

14Department of Psychiatry and Behavioral Sciences, Division of Research and Genetics, Kansas University Medical Center, Kansas City, Kansas, USA.

15Unité d’Endocrinologie, Hôpital des Enfants, and

16Centre de Référence du Syndrome de Prader-Willi, CHU Toulouse, Toulouse, France.

17Center for Epigenetics, University of Florida College of Medicine, Gainesville, Florida, USA.

Address correspondence to: Lisa C. Burnett or Rudolph L. Leibel, 1150 St. Nicholas Avenue Russ Berrie Pavilion Room 620 New York, NY 10033; Phone: 212 851 5315; E-mail: lmc2200@cumc.columbia.edu (L.C. Burnett); rl2332@cumc.columbia.edu (R.L. Leibel).

Find articles by Levy, B. in: JCI | PubMed | Google Scholar

1Institute of Human Nutrition,

2Department of Pediatrics, Division of Molecular Genetics, and

3Naomi Berrie Diabetes Center, Columbia University, New York, New York, USA.

4New York Obesity Research Center, New York, New York, USA.

5Department of Pediatrics, Division of Genetics and Metabolism, University of Florida College of Medicine Gainesville, Florida, USA.

6The New York Stem Cell Foundation Research Institute, New York, New York, USA.

7Centre de Physiopathologie de Toulouse-Purpan, Université de Toulouse, CNRS UMR 5282, INSERM UMR 1043, Université Paul Sabatier, Toulouse, France.

8Department of Biochemistry and Molecular Biophysics, Columbia University, New York, New York, USA.

9Packer Collegiate Institute, New York, New York, USA.

10Institut de pharmacologie de Sherbrooke, Department of Surgery, Division of Urology, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, Quebec, Canada.

11Department of Pathology and Cell Biology, Columbia University, New York, New York, USA.

12Department of Pediatrics, Division of Pediatric Diabetes, Endocrinology and Metabolism, Columbia University, New York, New York, USA.

13Institute of Cardiometabolism and Nutrition, Assistance Publique Hôpitaux de Paris, Sorbonne University, University Pierre et Marie-Curie, INSERM UMRS 1166, Paris, France.

14Department of Psychiatry and Behavioral Sciences, Division of Research and Genetics, Kansas University Medical Center, Kansas City, Kansas, USA.

15Unité d’Endocrinologie, Hôpital des Enfants, and

16Centre de Référence du Syndrome de Prader-Willi, CHU Toulouse, Toulouse, France.

17Center for Epigenetics, University of Florida College of Medicine, Gainesville, Florida, USA.

Address correspondence to: Lisa C. Burnett or Rudolph L. Leibel, 1150 St. Nicholas Avenue Russ Berrie Pavilion Room 620 New York, NY 10033; Phone: 212 851 5315; E-mail: lmc2200@cumc.columbia.edu (L.C. Burnett); rl2332@cumc.columbia.edu (R.L. Leibel).

Find articles by Fennoy, I. in: JCI | PubMed | Google Scholar

1Institute of Human Nutrition,

2Department of Pediatrics, Division of Molecular Genetics, and

3Naomi Berrie Diabetes Center, Columbia University, New York, New York, USA.

4New York Obesity Research Center, New York, New York, USA.

5Department of Pediatrics, Division of Genetics and Metabolism, University of Florida College of Medicine Gainesville, Florida, USA.

6The New York Stem Cell Foundation Research Institute, New York, New York, USA.

7Centre de Physiopathologie de Toulouse-Purpan, Université de Toulouse, CNRS UMR 5282, INSERM UMR 1043, Université Paul Sabatier, Toulouse, France.

8Department of Biochemistry and Molecular Biophysics, Columbia University, New York, New York, USA.

9Packer Collegiate Institute, New York, New York, USA.

10Institut de pharmacologie de Sherbrooke, Department of Surgery, Division of Urology, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, Quebec, Canada.

11Department of Pathology and Cell Biology, Columbia University, New York, New York, USA.

12Department of Pediatrics, Division of Pediatric Diabetes, Endocrinology and Metabolism, Columbia University, New York, New York, USA.

13Institute of Cardiometabolism and Nutrition, Assistance Publique Hôpitaux de Paris, Sorbonne University, University Pierre et Marie-Curie, INSERM UMRS 1166, Paris, France.

14Department of Psychiatry and Behavioral Sciences, Division of Research and Genetics, Kansas University Medical Center, Kansas City, Kansas, USA.

15Unité d’Endocrinologie, Hôpital des Enfants, and

16Centre de Référence du Syndrome de Prader-Willi, CHU Toulouse, Toulouse, France.

17Center for Epigenetics, University of Florida College of Medicine, Gainesville, Florida, USA.

Address correspondence to: Lisa C. Burnett or Rudolph L. Leibel, 1150 St. Nicholas Avenue Russ Berrie Pavilion Room 620 New York, NY 10033; Phone: 212 851 5315; E-mail: lmc2200@cumc.columbia.edu (L.C. Burnett); rl2332@cumc.columbia.edu (R.L. Leibel).

Find articles by Dubern, B. in: JCI | PubMed | Google Scholar

1Institute of Human Nutrition,

2Department of Pediatrics, Division of Molecular Genetics, and

3Naomi Berrie Diabetes Center, Columbia University, New York, New York, USA.

4New York Obesity Research Center, New York, New York, USA.

5Department of Pediatrics, Division of Genetics and Metabolism, University of Florida College of Medicine Gainesville, Florida, USA.

6The New York Stem Cell Foundation Research Institute, New York, New York, USA.

7Centre de Physiopathologie de Toulouse-Purpan, Université de Toulouse, CNRS UMR 5282, INSERM UMR 1043, Université Paul Sabatier, Toulouse, France.

8Department of Biochemistry and Molecular Biophysics, Columbia University, New York, New York, USA.

9Packer Collegiate Institute, New York, New York, USA.

10Institut de pharmacologie de Sherbrooke, Department of Surgery, Division of Urology, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, Quebec, Canada.

11Department of Pathology and Cell Biology, Columbia University, New York, New York, USA.

12Department of Pediatrics, Division of Pediatric Diabetes, Endocrinology and Metabolism, Columbia University, New York, New York, USA.

13Institute of Cardiometabolism and Nutrition, Assistance Publique Hôpitaux de Paris, Sorbonne University, University Pierre et Marie-Curie, INSERM UMRS 1166, Paris, France.

14Department of Psychiatry and Behavioral Sciences, Division of Research and Genetics, Kansas University Medical Center, Kansas City, Kansas, USA.

15Unité d’Endocrinologie, Hôpital des Enfants, and

16Centre de Référence du Syndrome de Prader-Willi, CHU Toulouse, Toulouse, France.

17Center for Epigenetics, University of Florida College of Medicine, Gainesville, Florida, USA.

Address correspondence to: Lisa C. Burnett or Rudolph L. Leibel, 1150 St. Nicholas Avenue Russ Berrie Pavilion Room 620 New York, NY 10033; Phone: 212 851 5315; E-mail: lmc2200@cumc.columbia.edu (L.C. Burnett); rl2332@cumc.columbia.edu (R.L. Leibel).

Find articles by Poitou, C. in: JCI | PubMed | Google Scholar

1Institute of Human Nutrition,

2Department of Pediatrics, Division of Molecular Genetics, and

3Naomi Berrie Diabetes Center, Columbia University, New York, New York, USA.

4New York Obesity Research Center, New York, New York, USA.

5Department of Pediatrics, Division of Genetics and Metabolism, University of Florida College of Medicine Gainesville, Florida, USA.

6The New York Stem Cell Foundation Research Institute, New York, New York, USA.

7Centre de Physiopathologie de Toulouse-Purpan, Université de Toulouse, CNRS UMR 5282, INSERM UMR 1043, Université Paul Sabatier, Toulouse, France.

8Department of Biochemistry and Molecular Biophysics, Columbia University, New York, New York, USA.

9Packer Collegiate Institute, New York, New York, USA.

10Institut de pharmacologie de Sherbrooke, Department of Surgery, Division of Urology, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, Quebec, Canada.

11Department of Pathology and Cell Biology, Columbia University, New York, New York, USA.

12Department of Pediatrics, Division of Pediatric Diabetes, Endocrinology and Metabolism, Columbia University, New York, New York, USA.

13Institute of Cardiometabolism and Nutrition, Assistance Publique Hôpitaux de Paris, Sorbonne University, University Pierre et Marie-Curie, INSERM UMRS 1166, Paris, France.

14Department of Psychiatry and Behavioral Sciences, Division of Research and Genetics, Kansas University Medical Center, Kansas City, Kansas, USA.

15Unité d’Endocrinologie, Hôpital des Enfants, and

16Centre de Référence du Syndrome de Prader-Willi, CHU Toulouse, Toulouse, France.

17Center for Epigenetics, University of Florida College of Medicine, Gainesville, Florida, USA.

Address correspondence to: Lisa C. Burnett or Rudolph L. Leibel, 1150 St. Nicholas Avenue Russ Berrie Pavilion Room 620 New York, NY 10033; Phone: 212 851 5315; E-mail: lmc2200@cumc.columbia.edu (L.C. Burnett); rl2332@cumc.columbia.edu (R.L. Leibel).

Find articles by Clement, K. in: JCI | PubMed | Google Scholar

1Institute of Human Nutrition,

2Department of Pediatrics, Division of Molecular Genetics, and

3Naomi Berrie Diabetes Center, Columbia University, New York, New York, USA.

4New York Obesity Research Center, New York, New York, USA.

5Department of Pediatrics, Division of Genetics and Metabolism, University of Florida College of Medicine Gainesville, Florida, USA.

6The New York Stem Cell Foundation Research Institute, New York, New York, USA.

7Centre de Physiopathologie de Toulouse-Purpan, Université de Toulouse, CNRS UMR 5282, INSERM UMR 1043, Université Paul Sabatier, Toulouse, France.

8Department of Biochemistry and Molecular Biophysics, Columbia University, New York, New York, USA.

9Packer Collegiate Institute, New York, New York, USA.

10Institut de pharmacologie de Sherbrooke, Department of Surgery, Division of Urology, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, Quebec, Canada.

11Department of Pathology and Cell Biology, Columbia University, New York, New York, USA.

12Department of Pediatrics, Division of Pediatric Diabetes, Endocrinology and Metabolism, Columbia University, New York, New York, USA.

13Institute of Cardiometabolism and Nutrition, Assistance Publique Hôpitaux de Paris, Sorbonne University, University Pierre et Marie-Curie, INSERM UMRS 1166, Paris, France.

14Department of Psychiatry and Behavioral Sciences, Division of Research and Genetics, Kansas University Medical Center, Kansas City, Kansas, USA.

15Unité d’Endocrinologie, Hôpital des Enfants, and

16Centre de Référence du Syndrome de Prader-Willi, CHU Toulouse, Toulouse, France.

17Center for Epigenetics, University of Florida College of Medicine, Gainesville, Florida, USA.

Address correspondence to: Lisa C. Burnett or Rudolph L. Leibel, 1150 St. Nicholas Avenue Russ Berrie Pavilion Room 620 New York, NY 10033; Phone: 212 851 5315; E-mail: lmc2200@cumc.columbia.edu (L.C. Burnett); rl2332@cumc.columbia.edu (R.L. Leibel).

Find articles by Butler, M. in: JCI | PubMed | Google Scholar

1Institute of Human Nutrition,

2Department of Pediatrics, Division of Molecular Genetics, and

3Naomi Berrie Diabetes Center, Columbia University, New York, New York, USA.

4New York Obesity Research Center, New York, New York, USA.

5Department of Pediatrics, Division of Genetics and Metabolism, University of Florida College of Medicine Gainesville, Florida, USA.

6The New York Stem Cell Foundation Research Institute, New York, New York, USA.

7Centre de Physiopathologie de Toulouse-Purpan, Université de Toulouse, CNRS UMR 5282, INSERM UMR 1043, Université Paul Sabatier, Toulouse, France.

8Department of Biochemistry and Molecular Biophysics, Columbia University, New York, New York, USA.

9Packer Collegiate Institute, New York, New York, USA.

10Institut de pharmacologie de Sherbrooke, Department of Surgery, Division of Urology, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, Quebec, Canada.

11Department of Pathology and Cell Biology, Columbia University, New York, New York, USA.

12Department of Pediatrics, Division of Pediatric Diabetes, Endocrinology and Metabolism, Columbia University, New York, New York, USA.

13Institute of Cardiometabolism and Nutrition, Assistance Publique Hôpitaux de Paris, Sorbonne University, University Pierre et Marie-Curie, INSERM UMRS 1166, Paris, France.

14Department of Psychiatry and Behavioral Sciences, Division of Research and Genetics, Kansas University Medical Center, Kansas City, Kansas, USA.

15Unité d’Endocrinologie, Hôpital des Enfants, and

16Centre de Référence du Syndrome de Prader-Willi, CHU Toulouse, Toulouse, France.

17Center for Epigenetics, University of Florida College of Medicine, Gainesville, Florida, USA.

Address correspondence to: Lisa C. Burnett or Rudolph L. Leibel, 1150 St. Nicholas Avenue Russ Berrie Pavilion Room 620 New York, NY 10033; Phone: 212 851 5315; E-mail: lmc2200@cumc.columbia.edu (L.C. Burnett); rl2332@cumc.columbia.edu (R.L. Leibel).

Find articles by Rosenbaum, M. in: JCI | PubMed | Google Scholar

1Institute of Human Nutrition,

2Department of Pediatrics, Division of Molecular Genetics, and

3Naomi Berrie Diabetes Center, Columbia University, New York, New York, USA.

4New York Obesity Research Center, New York, New York, USA.

5Department of Pediatrics, Division of Genetics and Metabolism, University of Florida College of Medicine Gainesville, Florida, USA.

6The New York Stem Cell Foundation Research Institute, New York, New York, USA.

7Centre de Physiopathologie de Toulouse-Purpan, Université de Toulouse, CNRS UMR 5282, INSERM UMR 1043, Université Paul Sabatier, Toulouse, France.

8Department of Biochemistry and Molecular Biophysics, Columbia University, New York, New York, USA.

9Packer Collegiate Institute, New York, New York, USA.

10Institut de pharmacologie de Sherbrooke, Department of Surgery, Division of Urology, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, Quebec, Canada.

11Department of Pathology and Cell Biology, Columbia University, New York, New York, USA.

12Department of Pediatrics, Division of Pediatric Diabetes, Endocrinology and Metabolism, Columbia University, New York, New York, USA.

13Institute of Cardiometabolism and Nutrition, Assistance Publique Hôpitaux de Paris, Sorbonne University, University Pierre et Marie-Curie, INSERM UMRS 1166, Paris, France.

14Department of Psychiatry and Behavioral Sciences, Division of Research and Genetics, Kansas University Medical Center, Kansas City, Kansas, USA.

15Unité d’Endocrinologie, Hôpital des Enfants, and

16Centre de Référence du Syndrome de Prader-Willi, CHU Toulouse, Toulouse, France.

17Center for Epigenetics, University of Florida College of Medicine, Gainesville, Florida, USA.

Address correspondence to: Lisa C. Burnett or Rudolph L. Leibel, 1150 St. Nicholas Avenue Russ Berrie Pavilion Room 620 New York, NY 10033; Phone: 212 851 5315; E-mail: lmc2200@cumc.columbia.edu (L.C. Burnett); rl2332@cumc.columbia.edu (R.L. Leibel).

Find articles by Salles, J. in: JCI | PubMed | Google Scholar

1Institute of Human Nutrition,

2Department of Pediatrics, Division of Molecular Genetics, and

3Naomi Berrie Diabetes Center, Columbia University, New York, New York, USA.

4New York Obesity Research Center, New York, New York, USA.

5Department of Pediatrics, Division of Genetics and Metabolism, University of Florida College of Medicine Gainesville, Florida, USA.

6The New York Stem Cell Foundation Research Institute, New York, New York, USA.

7Centre de Physiopathologie de Toulouse-Purpan, Université de Toulouse, CNRS UMR 5282, INSERM UMR 1043, Université Paul Sabatier, Toulouse, France.

8Department of Biochemistry and Molecular Biophysics, Columbia University, New York, New York, USA.

9Packer Collegiate Institute, New York, New York, USA.

10Institut de pharmacologie de Sherbrooke, Department of Surgery, Division of Urology, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, Quebec, Canada.

11Department of Pathology and Cell Biology, Columbia University, New York, New York, USA.

12Department of Pediatrics, Division of Pediatric Diabetes, Endocrinology and Metabolism, Columbia University, New York, New York, USA.

13Institute of Cardiometabolism and Nutrition, Assistance Publique Hôpitaux de Paris, Sorbonne University, University Pierre et Marie-Curie, INSERM UMRS 1166, Paris, France.

14Department of Psychiatry and Behavioral Sciences, Division of Research and Genetics, Kansas University Medical Center, Kansas City, Kansas, USA.

15Unité d’Endocrinologie, Hôpital des Enfants, and

16Centre de Référence du Syndrome de Prader-Willi, CHU Toulouse, Toulouse, France.

17Center for Epigenetics, University of Florida College of Medicine, Gainesville, Florida, USA.

Address correspondence to: Lisa C. Burnett or Rudolph L. Leibel, 1150 St. Nicholas Avenue Russ Berrie Pavilion Room 620 New York, NY 10033; Phone: 212 851 5315; E-mail: lmc2200@cumc.columbia.edu (L.C. Burnett); rl2332@cumc.columbia.edu (R.L. Leibel).

Find articles by Tauber, M. in: JCI | PubMed | Google Scholar

1Institute of Human Nutrition,

2Department of Pediatrics, Division of Molecular Genetics, and

3Naomi Berrie Diabetes Center, Columbia University, New York, New York, USA.

4New York Obesity Research Center, New York, New York, USA.

5Department of Pediatrics, Division of Genetics and Metabolism, University of Florida College of Medicine Gainesville, Florida, USA.

6The New York Stem Cell Foundation Research Institute, New York, New York, USA.

7Centre de Physiopathologie de Toulouse-Purpan, Université de Toulouse, CNRS UMR 5282, INSERM UMR 1043, Université Paul Sabatier, Toulouse, France.

8Department of Biochemistry and Molecular Biophysics, Columbia University, New York, New York, USA.

9Packer Collegiate Institute, New York, New York, USA.

10Institut de pharmacologie de Sherbrooke, Department of Surgery, Division of Urology, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, Quebec, Canada.

11Department of Pathology and Cell Biology, Columbia University, New York, New York, USA.

12Department of Pediatrics, Division of Pediatric Diabetes, Endocrinology and Metabolism, Columbia University, New York, New York, USA.

13Institute of Cardiometabolism and Nutrition, Assistance Publique Hôpitaux de Paris, Sorbonne University, University Pierre et Marie-Curie, INSERM UMRS 1166, Paris, France.

14Department of Psychiatry and Behavioral Sciences, Division of Research and Genetics, Kansas University Medical Center, Kansas City, Kansas, USA.

15Unité d’Endocrinologie, Hôpital des Enfants, and

16Centre de Référence du Syndrome de Prader-Willi, CHU Toulouse, Toulouse, France.

17Center for Epigenetics, University of Florida College of Medicine, Gainesville, Florida, USA.

Address correspondence to: Lisa C. Burnett or Rudolph L. Leibel, 1150 St. Nicholas Avenue Russ Berrie Pavilion Room 620 New York, NY 10033; Phone: 212 851 5315; E-mail: lmc2200@cumc.columbia.edu (L.C. Burnett); rl2332@cumc.columbia.edu (R.L. Leibel).

Find articles by Driscoll, D. in: JCI | PubMed | Google Scholar

1Institute of Human Nutrition,

2Department of Pediatrics, Division of Molecular Genetics, and

3Naomi Berrie Diabetes Center, Columbia University, New York, New York, USA.

4New York Obesity Research Center, New York, New York, USA.

5Department of Pediatrics, Division of Genetics and Metabolism, University of Florida College of Medicine Gainesville, Florida, USA.

6The New York Stem Cell Foundation Research Institute, New York, New York, USA.

7Centre de Physiopathologie de Toulouse-Purpan, Université de Toulouse, CNRS UMR 5282, INSERM UMR 1043, Université Paul Sabatier, Toulouse, France.

8Department of Biochemistry and Molecular Biophysics, Columbia University, New York, New York, USA.

9Packer Collegiate Institute, New York, New York, USA.

10Institut de pharmacologie de Sherbrooke, Department of Surgery, Division of Urology, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, Quebec, Canada.

11Department of Pathology and Cell Biology, Columbia University, New York, New York, USA.

12Department of Pediatrics, Division of Pediatric Diabetes, Endocrinology and Metabolism, Columbia University, New York, New York, USA.

13Institute of Cardiometabolism and Nutrition, Assistance Publique Hôpitaux de Paris, Sorbonne University, University Pierre et Marie-Curie, INSERM UMRS 1166, Paris, France.

14Department of Psychiatry and Behavioral Sciences, Division of Research and Genetics, Kansas University Medical Center, Kansas City, Kansas, USA.

15Unité d’Endocrinologie, Hôpital des Enfants, and

16Centre de Référence du Syndrome de Prader-Willi, CHU Toulouse, Toulouse, France.

17Center for Epigenetics, University of Florida College of Medicine, Gainesville, Florida, USA.

Address correspondence to: Lisa C. Burnett or Rudolph L. Leibel, 1150 St. Nicholas Avenue Russ Berrie Pavilion Room 620 New York, NY 10033; Phone: 212 851 5315; E-mail: lmc2200@cumc.columbia.edu (L.C. Burnett); rl2332@cumc.columbia.edu (R.L. Leibel).

Find articles by Egli, D. in: JCI | PubMed | Google Scholar

1Institute of Human Nutrition,

2Department of Pediatrics, Division of Molecular Genetics, and

3Naomi Berrie Diabetes Center, Columbia University, New York, New York, USA.

4New York Obesity Research Center, New York, New York, USA.

5Department of Pediatrics, Division of Genetics and Metabolism, University of Florida College of Medicine Gainesville, Florida, USA.

6The New York Stem Cell Foundation Research Institute, New York, New York, USA.

7Centre de Physiopathologie de Toulouse-Purpan, Université de Toulouse, CNRS UMR 5282, INSERM UMR 1043, Université Paul Sabatier, Toulouse, France.

8Department of Biochemistry and Molecular Biophysics, Columbia University, New York, New York, USA.

9Packer Collegiate Institute, New York, New York, USA.

10Institut de pharmacologie de Sherbrooke, Department of Surgery, Division of Urology, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, Quebec, Canada.

11Department of Pathology and Cell Biology, Columbia University, New York, New York, USA.

12Department of Pediatrics, Division of Pediatric Diabetes, Endocrinology and Metabolism, Columbia University, New York, New York, USA.

13Institute of Cardiometabolism and Nutrition, Assistance Publique Hôpitaux de Paris, Sorbonne University, University Pierre et Marie-Curie, INSERM UMRS 1166, Paris, France.

14Department of Psychiatry and Behavioral Sciences, Division of Research and Genetics, Kansas University Medical Center, Kansas City, Kansas, USA.

15Unité d’Endocrinologie, Hôpital des Enfants, and

16Centre de Référence du Syndrome de Prader-Willi, CHU Toulouse, Toulouse, France.

17Center for Epigenetics, University of Florida College of Medicine, Gainesville, Florida, USA.

Address correspondence to: Lisa C. Burnett or Rudolph L. Leibel, 1150 St. Nicholas Avenue Russ Berrie Pavilion Room 620 New York, NY 10033; Phone: 212 851 5315; E-mail: lmc2200@cumc.columbia.edu (L.C. Burnett); rl2332@cumc.columbia.edu (R.L. Leibel).

Find articles by Leibel, R. in: JCI | PubMed | Google Scholar

First published December 12, 2016 – More info

First published December 12, 2016
Received: May 19, 2016; Accepted: October 20, 2016

See the related Commentary at Impaired prohormone processing: a grand unified theory for features of Prader-Willi syndrome?.

Abstract

Prader-Willi syndrome (PWS) is caused by a loss of paternally expressed genes in an imprinted region of chromosome 15q. Among the canonical PWS phenotypes are hyperphagic obesity, central hypogonadism, and low growth hormone (GH). Rare microdeletions in PWS patients define a 91-kb minimum critical deletion region encompassing 3 genes, including the noncoding RNA gene SNORD116. Here, we found that protein and transcript levels of nescient helix loop helix 2 (NHLH2) and the prohormone convertase PC1 (encoded by PCSK1) were reduced in PWS patient induced pluripotent stem cell–derived (iPSC-derived) neurons. Moreover, Nhlh2 and Pcsk1 expression were reduced in hypothalami of fasted Snord116 paternal knockout (Snord116p–/m+) mice. Hypothalamic Agrp and Npy remained elevated following refeeding in association with relative hyperphagia in Snord116p–/m+ mice. Nhlh2-deficient mice display growth deficiencies as adolescents and hypogonadism, hyperphagia, and obesity as adults. Nhlh2 has also been shown to promote Pcsk1 expression. Humans and mice deficient in PC1 display hyperphagic obesity, hypogonadism, decreased GH, and hypoinsulinemic diabetes due to impaired prohormone processing. Here, we found that Snord116p–/m+ mice displayed in vivo functional defects in prohormone processing of proinsulin, pro-GH–releasing hormone, and proghrelin in association with reductions in islet, hypothalamic, and stomach PC1 content. Our findings suggest that the major neuroendocrine features of PWS are due to PC1 deficiency.

Introduction

Prader-Willi syndrome (PWS) is the most common syndromic obesity, affecting 1 in 25,000 live births (1, 2). PWS results from a loss of paternally expressed genes at 15q11.2–q13 (Figure 1A) (3). Seventy percent of instances of PWS are due to a 5- to 6-Mb deletion in 15q11.2–q13 (Figure 1A). The major phenotypes of PWS include: hyperphagic obesity, hypogonadism, growth hormone (GH) deficiency, hyperghrelinemia, and relative hypoinsulinemia (2, 4). Five paternal microdeletion (118–237 kbp) PWS patients have been identified (59). The overlap among these patients’ paternal deletion regions identifies a 91-kb critical deletion region sufficient to cause the major physical and neuroendocrine phenotypes of PWS (Figure 1A). This region contains 3 noncoding RNA genes, including SNORD109A, SNORD116, and IPW. None of the extant PWS mouse models (more than a dozen have been generated) develop obesity (10). However, mice in which the paternal copy of Snord116 is deleted (Snord116p–/m+) display many of the neuroendocrine phenotypes of PWS, including hyperphagia, low GH, decreased body length, impaired motor learning, hypoinsulinemia, and hyperghrelinemia (11, 12).

NHLH2 and PCSK1 are reduced in PWS iPSC-derived neurons and Snord116p–/m+ (Figure 1

NHLH2 and PCSK1 are reduced in PWS iPSC-derived neurons and Snord116p–/m+ (DEL) hypothalami. (A) Diagram of the PWS locus. Maternally expressed genes are shown in pink, paternally expressed genes in blue, non-imprinted genes in green. Protein-coding genes are shown as ovals, snoRNAs as rectangles, long noncoding RNAs as triangles, imprinting center as a diamond. Not drawn to scale. cen, centromere; tel, telomere. (BF) Gene expression in the PWS locus following neuron differentiation (n = 7 control [CON], n = 1 PWS MD [2 clones used], n = 3 PWS LD). (G) RNA sequencing identified a downregulation in PCSK1 in PWS neurons (n = 7 CON, n = 1 PWS MD [2 clones used], n = 2 PWS LD). This heatmap is also shown in Supplemental Figure 4A and includes the full list of all genes differentially expressed. (H and J) PCSK1 and NHLH2 gene expression levels from an independent differentiation experiment, as measured by qRT-PCR (n = 7 CON, n = 1 PWS MD [2 clones used], n = 3 PWS LD). (I and K) Quantification of PC1 and NHLH2 protein levels in iPSC-derived neurons (n = 5 CON [3 lines], n = 2 PWS LD, n = 1 PWS MD). (L and M) Food intake after 5 hours of refeeding (n = 6 WT, n = 5 DEL). (NR) Transcript levels in hypothalami at fasting and refeeding (n = 11 WT, n = 13 DEL, overnight fasted; n = 15 WT, n = 14 DEL, 5-hour refed). All data are expressed as mean ± SEM. BF were analyzed with Kruskal-Wallis with post hoc Dunn’s multiple comparison test; comparisons are against unaffected controls. L and M were analyzed with a 2-tailed, type 3 (assumes unequal variance) Student’s t test. N, P, and Q were analyzed with 1-way ANOVA with Tukey’s post hoc test. (O) WT fast and DEL fast were compared with a 2-tailed, type 3 Student’s t test. (R) WT refed and DEL refed were compared with a 2-tailed, type 3 Student’s t test. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001.

C/D box small nucleolar RNAs (snoRNAs) are noncoding small nucleolar RNAs that methylate ribosomal RNAs. However, there are no known ribosomal RNA targets for SNORD116-encoded snoRNAs (13). Thus, SNORD116 is thought to be a noncanonical snoRNA; and the mechanisms by which SNORD116 influences biological processes are unknown. Although the endocrine features and natural history of PWS have been well described, a molecular mechanism linking these features to the genes deleted in the PWS minimum critical deletion region has not been identified. Using mice in which the paternal copy of only Snord116 has been deleted (Snord116p–/m+), induced pluripotent stem cell–derived (iPSC-derived) neurons from PWS patients, and plasma from PWS patients, we find that the major PWS clinical phenotypes can be accounted for by reduced expression of the prohormone processing enzyme prohormone convertase 1 (PC1, encoded by PCSK1).

Results

The major PWS phenotypes are likely of central nervous system origin (hyperphagia, central hypogonadism, GH deficiency, intellectual disability, developmental delay). We generated iPSC-derived neurons from 3 large deletion (LD) PWS patients and one microdeletion (MD) PWS patient with the smallest deletion (118-kb deletion, chromosome 15q: 15:25,257,217–15:25,375,376) identified to date; iPSC-derived neurons were also differentiated from 6 unaffected individuals (Figure 1A and Supplemental Table 1; supplemental material available online with this article; doi:10.1172/JCI88648DS1) (14). PWS iPSCs were differentiated to neurons using a modified dual SMAD signaling pathway inhibition protocol (15). PWS region genes were expressed in proportion to gene dosage in iPSC-derived neurons from unaffected controls, PWS LD patients, and a PWS microdeletion patient (Figure 1, B–F). PWS iPSC-derived neurons express canonical neural markers, including β-III-tubulin (TUJ1), NeuN, MAP2, and neural cell adhesion molecule (NCAM) (Supplemental Figure 1). PWS genotype status did not affect neuronal proliferation rates (percentage of Ki-67+ neurons) (Supplemental Figure 2) or the percentage of NCAM+ neuron progenitors (measured by FACS) at day 12 or day 34 of differentiation (Supplemental Figure 3). These data suggest that general neuron differentiation efficiency using the modified dual SMAD inhibition protocol is similar between unaffected control and PWS large and microdeletion iPSC lines. These data further suggest that transcriptional differences between genotypes are not due solely to gross defects in neuronal differentiation in PWS lines.

Unidirectional RNA sequencing of iPSC/hESC-derived neurons FACS-sorted for NCAM (Supplemental Figure 4) identified PCSK1 among the top downregulated genes (Figure 1G). Pathway analysis using DAVID (https://david.ncifcrf.gov/) found that most dysregulated pathways included PCSK1: for example, “signal peptide,” “response to steroid hormone stimulus,” “pituitary gland development,” “pancreas development,” and “diencephalon development” (Supplemental Table 5). Quantitative RT-PCR (qRT-PCR) from an independent differentiation experiment confirmed the downregulation of PC1 in PWS iPSC-derived neurons (Figure 1H). By Western blotting, PC1 protein is reduced >80% in both microdeletion and LD PWS iPSC-derived neurons (Figure 1I and Supplemental Figure 5). While both PCSK1 and nescient helix loop helix 2 (NHLH2) were among the top downregulated genes in PWS iPSC-derived neurons in a pilot RNA sequencing study, downregulation of NHLH2 was not statistically significant (P = 0.52) in the follow-up RNA sequencing study. However, qRT-PCR and Western blotting showed downregulation of NHLH2 at both the transcript and protein levels in PWS microdeletion and LD iPSC-derived neurons compared with unaffected controls (Figure 1, J and K, and Supplemental Figure 6). Because of the known relationship between Nhlh2 and Pcsk1, we thought it important to report the Nhlh2 data.

Nhlh2-null mice are obese, hypogonadal, and display reduced linear growth (16). Hypothalamic levels of Pcsk1 transcript and PC1 protein are reduced by more than 50% in these animals (17). NHLH2 transcript levels were reduced 1.5-fold in lymphoblast RNA from individuals with PWS compared with controls (18). NHLH2 is a basic helix-loop-helix transcription factor that positively regulates PCSK1 transcription as a heterodimer with STAT3 (19). Nhlh2 binds to E-box motifs within the PCSK1 promoter that are adjacent to STAT3 binding sites (19).

PC1 is the protein product of the PCSK1 gene. PC1 is an enzyme involved in the posttranslational modification of propeptides. PC1 is most active in the acidic environment of secretory vesicles, cleaving proproteins at dibasic residues (20). In conjunction with other prohormone convertases, including PC2, carboxypeptidase E (CPE), and furin, PC1 participates in the excision the hormone’s pro-domain, generally increasing the hormone’s bioactivity (21). Known substrates of PC1 include pro-opiomelanocortin (POMC), pro-gonadotropin-releasing hormone (proGnRH), pro-GH-releasing hormone (proGHRH), proinsulin, and proghrelin. Individuals hypomorphic for PCSK1 are hyperphagic, obese, hypogonadal, have low circulating GH levels, and have hyperproinsulinemia associated with hypoinsulinemia (22). Nhlh2-null and Pcsk1N222D mice develop obesity that is associated with impaired hypothalamic processing of POMC to α-MSH as well as impaired proprotein processing of other hormones (17, 23). In humans and mice, hypomorphic mutations of POMC or the α-MSH receptor cause obesity (24, 25). Nhlh2– and Pcsk1-null mice show reduced hypothalamic processing of pro-thyrotropin-releasing hormone (proTRH) to TRH (17, 26).

SNORD116 may act upstream of NHLH2 and/or PCSK1. We sought to determine whether we could detect downregulation of Nhlh2 and Pcsk1 in vivo in mice in which only the paternal allele of Snord116 (Snord116p–/m+) is deleted (11). Snord116 is not expressed in hypothalami of Snord116p–/m+ mice (Figure 1N). In WT animals, Snord116 transcript levels increase 171% following 5-hour refeeding, suggesting that Snord116 may have anorexigenic properties (Figure 1N). In agreement with a putative anorexigenic function for Snord116, the food intake during 5-hour refeeding of Snord116p–/m+ mice is 67% greater than that of WT littermates (Figure 1, L and M). Levels of Pcsk1 transcripts are reduced 41% after fasting but are unchanged after refeeding (Figure 1O). Compared with WT, in Snord116p-/m+ mice hypothalamic Nhlh2 transcript levels are decreased at fasting (–23%) and refeeding (–19%) (Figure 1P).

Snord116p–/m+ mice ingest more calories than WT littermates relative to lean mass during 5-hour refeeding (Figure 1L). Furthermore, despite their reduced total body weights, accounted for by reductions in both lean and fat mass, Snord116p–/m+ mice consumed the same number of calories as WT littermates over the course of 6 days in calorimetry (Supplemental Figure 7, A, G, and H, and see below). When daily food intake was normalized to body weight, the results indicated that Snord116p–/m+ mice are actually hyperphagic relative to body weight (Supplemental Figure 7B). With energy expenditure plotted against BW2/3, we were able to use a single linear regression equation to describe both Snord116p–/m+ and WT data sets; this suggests that the increased energy expenditure of Snord116p–/m+ mice may be accounted for by increased heat loss due to higher surface area to body mass ratio of Snord116p–/m+ animals (Supplemental Figure 7C). No effects on 24-hour respiratory exchange ratio or mean daily movement were detected (Supplemental Figure 7, D and E).

Consistent with the relative hyperphagia of Snord116p–/m+ mice, hypothalamic transcript levels of the orexigenic neuropeptides neuropeptide Y (Npy) and agouti-related peptide (Agrp) were elevated in Snord116p–/m+ animals (Figure 1, L, Q, and R, and Supplemental Figure 7). AgRP is also processed by PC1, and Pcsk1–/– mice have 3.3-fold more full-length AgRP in the hypothalamus; however, unlike POMC, processing is not necessary for antagonist activity of AgRP at the melanocortin receptor MC4R (27, 28). Pcsk1–/– and Snord116p–/m+ mice are runted, confounding effects of genotype on obesity-related phenotypes. Nonetheless, Snord116p–/m+ mice also display long- and short-term increased energy intake relative to their diminished lean mass, associated with decreased hypothalamic Nhlh2 and Pcsk1 at fasting and persistence of increased hypothalamic Npy and Agrp following feeding (Figure 1, L–R, and Supplemental Figure 7).

Based on the data in Figure 1, we hypothesized that specific endocrine phenotypes of PWS might be a consequence of defective prohormone processing owing to a functional deficiency of PC1 activity. We tested this hypothesis by measuring the processing of proinsulin to insulin, proGHRH to GHRH, and proghrelin to ghrelin in vivo in Snord116p–/m+ mice and WT littermates, as well as in human PWS patients and controls matched for age and BMI (Figures 2, 3, and 4).

Proinsulin processing is impaired in Snord116p–/m+ (DEL) mice, and human PWFigure 2

Proinsulin processing is impaired in Snord116p–/m+ (DEL) mice, and human PWS patients have impaired proinsulin processing compared with age- and BMI-matched controls. (A) There is no difference in blood glucose levels by genotype (n = 9 WT, n = 7 DEL). (B) An increase in the ratio of proinsulin to insulin is detected 30 minutes after glucose stimulation (n = 9 WT, n = 7 DEL). (C) The ratio of proinsulin to C-peptide in culture media is also increased in Snord116p–/m+ isolated islets (n = 9 WT, n = 10 DEL). (D) Snord116 is not expressed in Snord116p–/m+ islets (n = 6 WT, n = 5 DEL). (E and G) Pcsk1 and Pcsk2 are downregulated in Snord116p–/m+ islets (n = 6 WT, n = 5 DEL). (F and H) Both PC1 and PC2 protein levels are decreased in Snord116p–/m+ islets (n = 15 WT, n = 15 DEL). (I) Fasting plasma glucose levels of PWS patients, a patient with an inactivating mutation in PCSK1, and age- and BMI-matched controls were measured (n = 25 unaffected controls, n = 16 PWS patients, n = 1 PCSK1 mutation patient). (J and K) Fasting proinsulin and insulin levels were measured (n = 25 unaffected controls, n = 16 PWS patients, n = 1 PCSK1 mutation patient). (L) The plasma proinsulin to insulin ratio is increased by 60% in individuals with PWS at fasting compared with control (P = 0.086) (n = 25 age/BMI-matched controls, n = 16 PWS patients, n = 1 PCSK1 mutation patient). This effect is intermediate to that observed in the patients segregating for hypomorphic alleles of PCSK1 and manifesting a 170% increase in plasma proinsulin to insulin ratio. All data are expressed as mean ± SEM. A and B were analyzed with 1-way ANOVA with post hoc Tukey test; comparisons between all groups. CH were analyzed with a 2-tailed, type 3 Student’s t test. Comparison between CON and PWS in IL was done with a 2-tailed, type 3 Student’s t test; there is no statistical analysis included the PC1 mutation patient, as there was only data from 1 patient. *P < 0.05, **P < 0.01 vs. WT.

Proghrelin and ProGHRH processing are impaired in Snord116p–/m+ mice.Figure 3

Proghrelin and ProGHRH processing are impaired in Snord116p–/m+ mice. (A) Levels of total circulating ghrelin are increased in Snord116p–/m+ mice (n = 21 WT, n = 17 DEL). (B) Snord116 is expressed in stomachs of WT mice but not of Snord116p–/m+ mice (n = 6 WT, n = 6 DEL). (C) Pcsk1 transcript and levels are decreased in stomachs of Snord116p–/m+ mice compared with WT littermates (n = 6 WT, n = 6 DEL). (D) PC1 protein is decreased in the stomach of Snord116p–/m+ mice, p=0.052 (n = 6 WT, n = 6 DEL). (E) Preproghrelin transcript (Ghrl) is increased in Snord116p–/m+ mice (n = 6 WT, n = 6 DEL). (F) The ratio of proghrelin to ghrelin is increased in the stomachs of Snord116p–/m+ and Psck1–/– (PC1-KO) animals (n = 9 WT; n = 7 DEL; n = 2 PC1 KO). (G and H) From weaning throughout adulthood, Snord116p–/m+ mice weigh less and are shorter than WT littermates (G: n = 4–20 mice/time point; H: n = 6 WT, n = 7 DEL). (I) Circulating IGF1 is reduced by 45% in P30 Snord116p–/m+ mice compared with WT littermates (n = 6 WT, n = 7 DEL). (J) Transcript levels of liver Igf1 are reduced by 64% in Snord116p–/m+ P30 livers compared with WT littermates (n = 6 WT, n = 7 DEL). (K) There is no change in pituitary GH content between Snord116p–/m+ mice and WT (n = 5 WT, n = 4 DEL). (L) An increased ratio of hypothalamic proGHRH to GHRH content suggests that proGHRH to GHRH processing is impaired in Snord116p–/m+ animals compared with WT littermates (n = 14 WT, n = 11 DEL). All data are expressed as mean ± SEM. AE and GL were analyzed with a 2-tailed, type 3 Student’s t test. F was analyzed with 1-way ANOVA with post hoc Tukey test; comparisons between all groups. *P < 0.05, **P < 0.01, ****P < 0.0001 vs. WT.

Deficiencies in PC1 drive the major neuroendocrine phenotypes of PWS.Figure 4

Deficiencies in PC1 drive the major neuroendocrine phenotypes of PWS. This schematic illustrates our hypothesis that paternal loss of SNORD116 is sufficient to cause deficiencies in the expression of NHLH2 and PCSK1 (PC1), resulting in impaired prohormone processing. We propose that deficiencies in prohormone processing (owing to deficits in PC1 production) explain the major neuroendocrine phenotypes of PWS.

Proinsulin is processed to insulin and C-peptide in β cells by the combined actions of PC1 and PC2 (29). Patients with PCSK1-inactivating mutations display hyperproinsulinemia and low circulating concentrations of insulin (30, 31). Snord116p–/m+ and WT mice were fasted overnight and injected intraperitoneally with 3 mg glucose per kg body weight. Fasting and post-injection blood glucose levels did not differ by genotype (Figure 2A). At 30 minutes, Snord116p–/m+ mice displayed elevated plasma proinsulin/insulin ratios (Figure 2B and Supplemental Figure 8). Isolated islets of Snord116p–/m+ mice secreted higher ratios of proinsulin:c-peptide in response to 20 mM glucose (Figure 2C). While Snord116 expression is highest in the brain, qRT-PCR in WT mice detects Snord116 expression in most tissues, including isolated islets, the pituitary, adrenal gland, stomach, small intestine, and testes (Supplemental Figure 9). Snord116 is expressed in WT isolated islets but not those from Snord116p–/m+ mice (Figure 2D). Pcsk1 and Pcsk2 transcripts and PC1 and PC2 protein levels were decreased in islets from Snord116p–/m+ mice (Figure 2, E–H, and Supplemental Figures 10 and 11). These results suggest that loss of Snord116 alone is sufficient to cause a downregulation in PC1 and PC2, with a resulting functional impairment in proinsulin processing in vivo.

We identified a 60% increase in the ratio of proinsulin to insulin in fasting plasma of individuals with PWS as compared with age- and BMI-matched controls (P = 0.08) (Figure 2L and Supplemental Table 2). There was no difference in blood glucose or proinsulin concentrations between the subjects. The increase in the proinsulin/insulin ratio was driven by reductions in mature insulin (Figure 2, I–L). Plasma from a fasted patient compound heterozygous for inactivating mutations (heterozygous deletion c.71del/p.Ser24Met*73/stop codon position 72) in PCSK1 was included as a control. The ratio of proinsulin to insulin was increased 267% compared with that in unaffected controls (Figure 2K). As we hypothesize that individuals with PWS have a downregulation of PC1, not a complete loss of function, an intermediate impairment in proinsulin processing as compared with PCSK1 mutation patients is expected.

Ghrelin (encoded by Ghrl) is an orexigenic peptide produced in the stomach that is an endogenous ligand for the GH secretagogue receptor (GHSR) (32). Hyperghrelinemia preceding the onset of obesity is a clinical feature of PWS that is not seen in common obesity or other syndromic or monogenetic obesities (3339). Fasted Snord116p–/m+ mice displayed increased levels of circulating total ghrelin (Figure 3, A and B). Pcsk1 transcript levels were 20% lower in the stomachs of Snord116p–/m+ animals (Figure 3C). A trend toward decreased PC1 protein was identified in stomach lysates from Snord116p–/m+ mice compared with WT littermates (P = 0.052) (Figure 3D and Supplemental Figure 12). Transcript levels of Ghrl, which encodes the full-length preproghrelin protein, are reported to be elevated by 40% in the stomachs of PC1-null mice (40). This is the only other rodent obesity model in which hyperghrelinemia has been identified. Ghrl transcript was also increased in the stomachs of the Snord116p–/m+ mice (Figure 3E). Snord116 transcripts are increased >10-fold in stomachs of Pcsk1+/– mice, suggesting a possible negative feedback loop (Supplemental Figure 13). Ratios of proghrelin to mature ghrelin protein are elevated in Snord116p–/m+ stomach lysates (Figure 3F and Supplemental Figure 14). Stomach lysates from PC1-null mice were included as a positive control for impaired proghrelin processing. The processing defect in Snord116p–/m+ mice appears to be less severe than that of Pc1-null mice, consistent with the ~50% decrease in PC1 protein in their stomachs. The antibodies used in conventional ghrelin assays to detect circulating total ghrelin in mouse and human also detect proghrelin (Supplemental Figure 15). Specifically, multiple groups have identified elevated circulating total ghrelin in individuals with PWS using the Phoenix Peptide RK-031-30 RIA kit; Supplemental Figure 15 shows that this antibody detects 14-kDa and 17-kDa proghrelin species in addition to 3.4-kDa mature ghrelin (33, 4144). Thus, the reported hyperghrelinemia in PWS patients as well as the Snord116p–/m+ mice likely reflects elevated circulating proghrelin, consistent with our results in Snord116p–/m+ stomach lysates (Figure 3, A–F, and Supplemental Figures 14 and 15).

ProGHRH is processed to its active form by PC1 in the arcuate nucleus of the hypothalamus (45, 46). Similar to PWS patients, PC1-null mice, and PC1-deficient patients, Snord116p–/m+ mice exhibit growth retardation and decreased circulating GH/IGF1 levels (3, 4648). At weaning and throughout adulthood, Snord116p–/m+ animals display decreased body length and weight (Figure 3, G and H). GH stimulates IGF1 production in the liver, generating the major endocrine mediator of GH effects on somatic growth. Both circulating IGF1 and liver transcript levels of Igf1 were decreased in Snord116p–/m+ mice (Figure 3, I and J).

Although circulating levels of IGF1 and liver transcript levels of Igf1 were decreased, GH levels in the pituitaries of four-week old, overnight fasted male Snord116p–/m+ mice were the same as WT littermates, suggesting impaired release of GH rather than impaired pituitary production of GH (Figure 3K and Supplemental Figure 16). Mice null for Nhlh2 have reduced growth from 4 to 7 weeks of age and a >50% reduction in hypothalamic PC1 (16, 17). In PC1-null animals, impaired release of GH is associated with a defect in the processing of proGHRH to GHRH (46). We detected a trend toward an elevated ratio of proGHRH to GHRH in hypothalamic lysates of 6-week-old overnight-fasted Snord116p–/m+ mice as compared with their WT littermates (Figure 3L). Nhlh2 and Pcsk1 transcripts are reduced in the hypothalami of fasted Snord116p–/m+ mice (Figure 1, O and P). Individuals with PWS do respond to GHRH administration by release of GH into the plasma (49). This finding is consistent with the inference that the short stature and decreased GH levels of individuals with PWS results from a hypothalamic deficiency of PC1.

Discussion

Our finding of reductions in NHLH2 and PC1 at both the transcript and protein levels in PWS iPSC-derived neurons is consistent with the possibility that the major neuroendocrine phenotypes of PWS are due to defects in prohormone processing. The deleted region of the PWS microdeletion patient studied here includes only 3 noncoding RNA genes: SNORD109A, SNORD116, and IPW. Mice lacking just the paternal copy of Snord116 have reduced levels of hypothalamic Nhlh2 and Pcsk1 during fasting. Snord116p–/m+ mice display functional defects in prohormone processing in vivo: the processing of proinsulin, proGHRH, and proghrelin was impaired in these animals associated with tissue-specific reductions in PC1. The impaired processing of proGHRH was associated with the physiological readout of decreased circulating IGF1 and the anatomical phenotype of runted Snord116p–/m+ mice that have reduced body weight and body length. Furthermore, impaired processing of proghrelin to ghrelin was associated with increased circulating total ghrelin during fasting in Snord116p–/m+ mice. Finally, an elevated ratio of proinsulin to insulin during fasting was detected in the plasma of PWS patients compared with age- and BMI-matched controls, suggesting that proinsulin processing is impaired in human PWS patients as well.

These data led to the formulation of the hypothesis, presented graphically in Figure 4, that PC1 deficiency due to paternal deletion of SNORD116 is the major driver of the salient clinical phenotypes of the PWS. The major phenotypes of PWS that could be accounted for by PC1 deficiency include hyperphagic obesity (multiple candidate prohormones), low GH and short stature (impaired proGHRH processing), hypogonadism (impaired proGnRH processing), hyperghrelinemia (impaired proghrelin processing), relative hypoinsulinemia and type 2 diabetes mellitus (impaired proinsulin processing), adrenal insufficiency (impaired processing of proCRH), hyperghrelinemia (impaired proghrelin processing), and hypothyroidism (impaired proTRH processing). Individuals with inactivating mutations in PCSK1 phenocopy PWS patients in many aspects of the disease phenotype (Supplemental Table 3). PCSK1 hypomorphic patients also present with severe, early-onset hyperphagic obesity (multiple prohormone candidates), hypogonadotropic hypogonadism (impaired proGnRH processing), growth deficiency associated with low levels of circulating GH (impaired proGHRH processing), hypoadrenalism (impaired processing of CRH), and hyperproinsulinemia associated with hypoglycemia which can progress to type 2 diabetes later in life (impaired proinsulin processing) (22). Circulating ghrelin levels have not been measured in individuals hypomorphic for PCSK1; however, mice null for Pcsk1 display increased transcript levels of preproghrelin in the stomach associated with impaired stomach proghrelin processing. We identified that Snord116p–/m+ mice also display increased transcript levels of preproghrelin in the stomach associated with impaired stomach proghrelin processing. These data suggest that circulating total ghrelin levels are also likely increased in Pcsk1-null mice and humans hypomorphic for PCSK1.

Based on the data presented in Figures 1–3 and the known consequences of PC1 deficiency, we hypothesize that PC1 deficiency in the central nervous system — due to paternal deletion of SNORD116 — is a major cause of hyperphagic obesity in PWS. However, the precise molecular physiology by which deficiency of PCSK1 drives hyperphagic obesity has not been definitively determined at present. While impaired processing of POMC to α-MSH is an obvious candidate for the hyperphagia, POMC transcript and protein levels can be upregulated in the setting of PC1 deficiency and could compensate for impaired POMC processing (likely due to impairment of a negative feedback regulatory mechanism) (23, 46). There are conflicting reports in the literature regarding α-MSH levels in mouse models of PC1 deficiency. Initial studies of PC1-deficient mice reported reductions in hypothalamic and pituitary α-MSH by gel filtration and RIA; however, follow-up studies using liquid chromatography–mass spectrometry (LC-MS) did not detect reductions in pituitary α-MSH (23, 46, 50). The quantitative LC-MS data suggest that other prohormones in the central nervous system that are processed by PC1 may account for the hyperphagia in PC1-deficient models.

In addition to POMC, many other hormones involved in food intake and energy expenditure are processed by PC1, including prohormones for AgRP, NPY, CART, oxytocin, and brain-derived neurotrophic factor (BDNF) (22). Hypothalamic levels of the orexigenic ProAgRP are increased in Pcsk1 hypomorphs (28). We found that hypothalami of Snord116p–/m+ mice have increased transcript levels of Npy and Agrp and decreased transcript levels of Pcsk1. Processing of AgRP is not necessary for its biological activity, and ProAgRP has considerable antagonistic activity toward α-MSH at melanocortin 4 receptor (MC4R) (27, 28). Thus, increased hypothalamic levels of ProAgRP could drive hyperphagia.

Oxytocin is an anorexigenic hormone important for the regulation of body weight; the pro-form of oxytocin is cleaved by PC1 (50). It is unclear whether pro-oxytocin is bioactive. Pituitary processed oxytocin levels are severely reduced in pituitaries of PC1-null mice (hypothalami were not assessed) (50). Oxytocin-producing neurons in the paraventricular nucleus (PVN) and supraoptic nucleus (SON) express MC4R, the receptor for α-MSH (endogenous ligand) and AgRP (endogenous antagonist) (51). Central and peripheral administration of oxytocin reduces food intake in humans, rhesus macaques, rats, and mice (5153). Oxytocin receptor –knockout mice weigh more (~16%) than WT littermates; however, the mechanism of increased body weight remains unclear (54). Oxytocin is produced in Sim1-expressing neurons in the PVN (55). Patients with inactivating mutations in SIM1 have severe, early-onset hyperphagic obesity (56). Mice that are haploinsufficient for Sim1 are hyperphagic and obese and have reductions in PVN oxytocin levels; administration of exogenous oxytocin reverses hyperphagia in Sim1+/– mice (55). These data indicate that hypothalamic oxytocin likely contributes to the regulation of body weight directly downstream of melanocortin signaling. Thus, improper pro-oxytocin processing resulting in reduced levels of oxytocin in the setting of PC1 deficiency is a plausible candidate mechanism for the associated hyperphagia.

Swaab et al. identified a reduction in the number of oxytocin-positive neurons in the PVH of post mortem brains of PWS patients (57). Adult PWS patients have been reported to have decreased plasma oxytocin levels, while pediatric PWS patients (aged 5–11 years) have increased plasma oxytocin levels (58, 59). Phenotypes of PWS — including impaired suckling in infants and behavioral symptoms consistent with autism spectrum disorder — could be due to impaired oxytocin function (60, 61).

BDNF is highly expressed in the hypothalamic paraventricular and ventromedial nuclei; while NTRK2 (nominal mature BDNF receptor) is highly expressed in the paraventricular and ventromedial hypothalamic nuclei, as well as the lateral hypothalamic area. BDNF has been implicated in regulation of human body weight as a molecule able to increase energy expenditure and decrease food intake. In common obesity, as well as in PWS, serum BDNF levels are reduced (62). BDNF is also synthesized as a prohormone. ProBDNF can be cleaved by PC7 and furin to mature BDNF, which is released by both the regulated and constitutive secretory pathways (63). Hypothalamic BDNF involved in the control of body weight is most likely secreted by the regulated secretory pathway. Pcsk7–/– mice are not obese, whereas Bdnf+/– mice are obese (64). Pcsk1 expression is upregulated in injured nerve cells in association with an increased demand for proBDNF and proNGF cleavage. It been suggested that PC1 is capable of processing proBDNF (65). Although speculative, Stijnen and others have postulated that PC1 may process proBDNF in the regulated secretory pathway in neurons, such as in the PVH, involved in the regulation of food intake and energy expenditure (66). Hypothalamic or circulating levels of BDNF have not been assessed in models of PC1 deficiency. Further studies are needed to determine whether hypothalamic processing of pro-BDNF is impaired in Pcsk1-null mice or iPSC-derived neurons hypomorphic for PC1. ProBDNF processing should also be assessed in mouse and iPSC-derived neuron models of PWS.

Thus, the impaired processing of 3 candidate hormones besides POMC —pro-oxytocin, proBDNF, or proAgRP — may contribute to hyperphagia in the setting of PC1 deficiency, and thus potentially PWS. These possibilities are not mutually exclusive. Further studies are necessary to determine whether these hormones are misprocessed in the hypothalamic neurons of mice and humans (iPSC-derived neurons) hypomorphic for PCSK1 or SNORD116.

Nhlh2 colocalizes with 33% of Pomc-expressing neurons in the rostral arcuate nucleus and 41% of Trh-expressing neurons in the PVN (17). In Nhlh2–/– mice, the prohormone processing of POMC to α-MSH and adrenocorticotropic hormone (ACTH) is impaired, as well as prohormone processing of proTRH to TRH (17). Nhlh2, PC1, and PC2 are physiologically regulated by nutritional status and leptin (20). Leptin can increase NHLH2, PCSK1, and PCSK2 promoter activity through STAT3-dependent mechanisms in mouse hypothalamus and 293T cells, respectively (20). For TRH, leptin can couple the upregulation of TRH transcription to increased proTRH processing (20). Individuals with PWS, and Snord116p–/m+ mice, produce appropriate quantities of leptin relative to fat mass; however, it is unclear whether the regulation of NHLH2, PCSK1, and PCSK2 by leptin is affected in PWS individuals or mouse models (Supplemental Figure 17).

Most prohormones, including proinsulin and POMC, are much less biologically active than their processed forms. Sertoli cells exposed to prepro-GHRH-(75–92)-NH2 increase cellular cAMP levels, while Sertoli cell exposed to prepro-GHRH-(75–83) do not change cellular cAMP levels (67). However, mice null for PC1 produce increased levels of proGHRH and decreased levels of GHRH compared with WT littermates and are very clearly runted (46). Thus, it seems unlikely that proGHRH retains physiologically significant agonist activity at GHRH receptor (GHRHR). Short-term exogenous administration of recombinant rat proghrelin to mice increases food intake and energy expenditure, resulting in a net body weight loss (68). Treatment of HEK-293 cells transfected with Ghsr-1a increases intracellular calcium signaling in response to synthetic ghrelin but not in response to synthetic proghrelin (68). The biological effects and mechanism of action of synthetic proghrelin appear to be distinct from those of mature ghrelin (68).

Snord116p–/m+ mice are runted and do not develop obesity. Pwscrp–/m+ mice, which carry a paternal deletion in a critical region of the PWS locus, segregate for a slightly different deletion of the Snord116 gene cluster. These mice are also runted and do not develop obesity. Knockin of a 5′HPRT-LoxP-NeoR cassette 27 kb upstream of Snord116 on the maternal allele induces maternal expression of Snord116. PWScrp−/m5′LoxP mice, which have a 5′HPRT-LoxP-NeoR cassette (5′LoxP) inserted upstream of the maternal PWScr allele, are not runted and have body weights indistinguishable from those of WT mice. Pcsk1-null mice are also runted and do not become obese. The growth curves for the Pcsk1-null and Snord116p–/m+ mice are very similar. However, the Pcsk1N222D mouse (hypomorphic for PC1), is obese and not runted. Furthermore, Pcsk1+/– mice have increased body weights compared with WT littermates and likewise are not runted. These data suggest that there may be a critical threshold for PC1 levels important to growth and adiposity.

The human PWS microdeletion patient cells utilized in this study harbor a paternal deletion of SNORD116, IPW, and SNORD109A. Without isogenic models of SNORD116, IPW, and SNORD109A deficiency, we cannot definitively conclude whether SNORD116, SNORD109, and IPW are, individually or in combination, the main drivers of downregulation of NHLH2 and PCSK1. Although the downregulation of Nhlh2 and Pcsk1 in Snord116p–/m+ mice suggests that paternal deletion of just Snord116 is at least sufficient for downregulation of Nhlh2 and Pcsk1 in vivo.

SNORD116 is an imprinted, paternally expressed, noncoding RNA cluster that contains thirty snoRNAs that are 85% homologous to one another, 5 sno-lnc RNAs, and one long noncoding RNA, 116HG. We have implicated NHLH2 and PCSK1 as major molecular targets of SNORD116, although it is unclear whether there are direct interactions between SNORD116 and PCSK1 and/or SNORD116 and NHLH2. It is also unclear whether such interaction(s) were to occur, exactly which noncoding RNA sequences encoded from the SNORD116 snoRNA cluster would interact with PCSK1 and/or NHLH2. Furthermore, it is not known whether such interactions would occur at the RNA-DNA, RNA-RNA, or RNA-protein levels. It is also likely that there are targets of SNORD116 other than PCSK1 and NHLH2 that may be clinically relevant in PWS. It is possible that other targets of SNORD116 may account for aspects of the PWS phenotype that are not present in PC1-deficient patients, such as delayed gastric emptying, characteristic PWS facial features, and behavioral phenotypes such as skin picking.

Methods

Human subjects. All studies and consenting procedures were approved by the Institutional Review Boards of the participating institutions including Columbia University Medical Center, University of Florida, and University of Kansas.

iPSC and PSC culture methods. Human iPSC cultures were generated and maintained as previously described (14).

Neuronal differentiation. Neuronal differentiation was performed as previously described (14).

FACS for CD56. Cells were enzymatically dissociated with Accutase and filtered through a 35-mm cell strainer (BD Biosciences) to obtain a single-cell suspension prior to resuspension in 100 μl of a sterile iPSC staining buffer (DPBS containing 0.5% BSA fraction V [Invitrogen], 100 U/ml penicillin/streptomycin [Invitrogen], 2 mM EDTA [Invitrogen], and 20 mM glucose [Sigma-Aldrich]). CD56-V450 (1 μl; BD Biosciences, 560360) or Stem Cell Technologies Anti-Human CD56 (NCAM) antibody (60021AZ) was added to the cells and incubated at room temperature for 15 minutes shielded from light. The stained cells were washed once with iPSC staining buffer and sorted immediately on a 5 laser BD Biosciences ARIA-IIu SOU Cell Sorter configured with a 100-μm ceramic nozzle and operating at 20-psi sheath fluid pressure. Cells were sorted into a 15-ml tube containing growth media as described above.

RNA sequencing. CD56+ iPSC-derived neurons were immediately pelleted following FACS. Total RNA was isolated from CD56+ iPSC–derived neurons using the Norgen Biotek Total RNA Purification Micro Kit with DNAse treatment. RNA sequencing was performed at the Columbia Genome Center, 1 × 100–bp read length, 30-M read count. RNA sequencing was performed on CD56+ iPSC–derived neurons from 7 unaffected control iPSC/ESC lines, 2 PWS LD iPSC lines, and 1 (2 clones were used) PWS microdeletion iPSC line. Reads were mapped to a reference genome (human: NCBI/build37.2; mouse: University of California Santa Cruz [UCSC]/mm9) using Tophat software with 4 mismatches (–read-mismatches = 4) and 10 maximum multiple hits (–max-multihits = 10). The relative abundance (FPKM value) of transcripts was estimated using default settings in Cufflinks software (version 2.0.2; http://cole-trapnell-lab.github.io/cufflinks/). Transcripts were then sorted in Microsoft Excel by FPKM status; genes with “low data” or “fail” FPKM status (189 genes) were not considered for analysis. Only FPKM values of “OK” were kept. FPKM OK status was determined by Cufflinks software to have adequate coverage. The average FPKM values were then calculated for each genotype: unaffected control (CON), PWS microdeletion (MD), and PWS LD (LD). The ratios of differential gene expression (DE) between PWS LD and unaffected control and PWS microdeletion and unaffected control were then calculated. DE ratios >2 and <0.5 were considered as upregulated or downregulated, respectively. A 2-tailed, type 3 t test was performed for all genes; P values less than 0.05 were considered significant.

qRT-PCR on iPSC-derived neurons. RNA was isolated from PSCs using the QIAGEN RNeasy kit with DNAse treatment. RNA was isolated from iPSC-derived neurons using the Norgen Biotek Total RNA Purification Micro Kit with DNAse treatment. Total RNA was converted to cDNA using the Roche Transcriptor First Strand cDNA Synthesis Kit. qRT-PCR was performed using Roche LightCycler 480 SYBR Green I Master mix. Primers are listed in Supplemental Table 4. All primers used for a qRT-PCR assays were validated using a 5-point standard curve. TBP was used as a housekeeping gene, and fold change was calculated using the 2–ΔΔCt method (Figure 1, B–F, H, and K; n = 7 unaffected control PSCs, n = 1 PWS microdeletion [2 clones used], n = 3 PWS LD lines used).

Western blot in iPSC-derived neurons for NHLH2 and PC1. Protein levels of NHLH2 (WH0004808M1, Sigma-Aldrich), PC1 (11914 Cell Signaling Technology), and α-tubulin (2144 or 3873 [clone DM1A], Cell Signaling Technology) were examined by Western blot analysis. Whole cell lysates from D34 PSC-derived neurons were obtained by reconstituting and lysing frozen cell pellets (–80°C) in RIPA buffer (Thermo Fisher, 89900) with protease inhibitors (Halt protease and phosphatase inhibitor cocktail, Thermo Scientific, 78442). Samples were sonicated for 15 seconds. Total protein content was quantified using the Pierce BCA Protein assay kit (Thermo Fisher, 23227). Total protein (15 μg) was mixed with sample reducing agent (NuPAGE, NP0009) and LDS sample buffer (NuPAGE, NP0008); samples were incubated at 90°C for 5 minutes. Total protein (15 μg) was run on 4%–12% Bis-Tris mini gels (NuPAGE, NP0321) with MOPS SDS running buffer (Novex Life Technologies, B0001); 1× antioxidant (NuPAGE, NP0005) was added to the inner chamber. Electrophoresis was run at 70 V for 15 minutes and then 200 V until desired molecular weight separation was achieved. Protein was transferred to nitrocellulose blots using the Invitrogen iBlot system run at P1. Primary antibody was incubated overnight at 4°C with gentle rocking. Blots were washed 3 times for 5 minutes in TBST. LI-COR secondary antibodies (IRDye 800 CW goat anti-rabbit, 926-32211; IRDye 680 LT donkey anti-mouse, 926-68022; IRDye 800 CW goat anti-mouse, 926-32210; IRDye 680LT donkey anti-rabbit, 926-68023) were used at 1:5,000 dilution and incubated at room temperature with gentle rocking for 1 hour. Blots were washed twice in TBST for 5 minutes, then twice in TBS for 5 minutes. Blots were then imaged using the Odyssey Classic imaging system (LI-COR Biotechnology). Data were analyzed using Image Studio Lite version 5.0 and GraphPad Prism 6.

Mouse breeding, genotyping, and anthropometric measurements. All animal work was carried out with approval of the IACUC of Columbia University Medical Center under protocol AC-AAAH1203. Snord116p–/m+ mice on a C57BL/6J background were ordered from the Jackson Laboratory (stock number 008149). A male Snord116p–/m+ mouse was mated to WT C57BL/6J females. Ovulation cycles of WT C57BL/6J females were synced by exposure to male mouse urine. Offspring were genotyped using methods published by Ding et al. (11). Only male mice were kept for study. Mice were weighed weekly (Figure 3G, n = 4–20 mice/time point) and body composition was measured by NMR monthly using a Bruker Minispec TD NMR. Mice were fed 21.56% fat breeder chow for the entirety of the study (Purina Irradiated 5058 Picomouse Diet 20). Mouse nasal to anal length was measured at 1 and 6 months of age immediately following sacrifice (Figure 3H, n = 6 WT, n = 7 Snord116p–/m+ mice/time point).

Intraperitoneal glucose tolerance test in Snord116 deletion mice; ELISA for proinsulin, insulin, and C-peptide; islet isolation procedures; expression levels of PC1 and PC2. Mice were fasted overnight (16 hours). In the morning, mice were intraperitoneally injected with 50% dextrose at a dose of 3 mg glucose per kg body weight (Hospira Inc., NDC 0409-6648702). Blood glucose was assayed at time 0 (fasting, prior to injection) and 30 minutes following injection using a FreeStyle Lite blood glucose meter and strips (accurate range 30–372 mg/dl) (n = 9 WT, n = 7 Snord116p–/m+ mice). Whole blood was also collected into heparin tubes on ice at time 0 and 30 minutes after injection. Heparin-treated blood was centrifuged at 2,000 RCF for 15 minutes at 4°C; plasma was collected and frozen at –80°C for analysis of insulin and proinsulin content. Proinsulin, insulin, and C-peptide content was measured by ELISA (Crystal Chem Ultra Sensitive Mouse Insulin ELISA Kit, 90080; Mercodia Rat/Mouse Proinsulin ELISA, 10-1232-01; ALPCO Mouse C-peptide ELISA, 80-CPTMS-E01). Prior to islet isolation, mice were fasted overnight (16 hours). Mice were sacrificed by cervical dislocation. A 30-gauge needed connected to a 5-ml syringe filled with 50% wt/vol collagenase P (dissolved in M199 media with 1% penicillin-streptomycin (Pen Strep) (Roche, 11249002001; Gibco, 31150022) was inserted into the common bile duct, and the pancreas was perfused with collagenase P. Islet isolation was carried out as described previously (69). After picking, islets recovered overnight (~16 hours) in RMPI media (Thermo Fisher, 11875) with 15% FBS, 1% Pen Strep, 1% GlutaMAX at 37°C, 5% CO2. The following day, islets were placed into 1.7-ml microcentrifuge tubes (40 islets/tube for RNA analysis; n = 6 WT, n = 5 Snord116p–/m+ mice; islets were pooled according to genotype, 20 islets/tube for protein analysis; n = 15 WT mice, n = 15 Snord116p–/m+ mice ranged in age from 6 to 8 months) containing 200 μl of basal media, RMPI media (Thermo Fisher, 11879) with 1% Pen Strep, 1% GlutaMAX, 2 mM glucose. Islets were allowed to recover for 1 hour. Islets were then incubated in basal media for 1 hour, high glucose (20 mM glucose) for 30 minutes (for RNA collection) or 90 minutes (for protein analysis). Total RNA was isolated as described for PSC-derived neurons. Primer sequences are listed in Supplemental Table 4. Protein levels of PC1 (Cell Signaling Technology, 11914 or Sigma-Aldrich, WH0005122M2 clone 3D2), PC2 (Cell Signaling Technology, 14013, clone D1E1S), and β-actin (Cell Signaling Technology, 3700) were probed as described for PSC-derived neurons.

qRT-PCR of liver Igf1. Livers from p30 ad libitum fed animals were homogenized in QIAzol, followed by phenol chloroform separation and precipitation with 70% ethanol of the aqueous fraction, which was subsequently applied to QIAGEN RNeasy columns. DNase treatment was performed. qRT-PCR was performed as described for PSC-derived neurons (n = 6 WT, n = 7 Snord116p–/m+ P30 male mice). Bact was used as a housekeeping gene control for all mouse qRT-PCR assays, and fold change was calculated using the 2–ΔΔCt method.

qRT-PCR in hypothalamus of 5-hour-fasted/refed mice. Mice were fasted overnight (16 hours) and refed for 5 hours. Mice were individually housed in order to obtain food intake measurements on a per-mouse basis. One cohort of animals was sacrificed following an overnight (16 hours) fast. Another cohort was sacrificed following an overnight (16 hours) fast with 5-hour refeeding. Mice were sacrificed by cervical dislocation. The hypothalamus was dissected out of the brain using a brain block and clean razor blades. Hypothalami were immediately homogenized in QIAzol, and subsequent isolation of RNA was carried out as described for liver. RT and qPCR were performed as described for PSC-derived neurons; primers are listed in Supplemental Table 4 (n = 11 WT, n = 13 DEL [Snord116p–/m+] adult males, overnight fasted; n = 15 WT, n = 14 DEL adult males, 5-hour refeed).

IGF1 ELISA. Circulating IGF1 levels were measured from ad libitum fed 1-month-old mice; the Mouse/Rat IGF-I Quantikine ELISA Kit MG100 from R&D Systems was used (n = 6 WT, n = 7 Snord116p–/m+ P30 male mice).

ProGHRH/GHRH measurements. Hypothalami were dissected out of 6-week-old overnight-fasted (16 hours) male mice using a brain block and clean razor blades (changed between each mouse). Preparation of hypothalamic extract was done according to Miki et al.; hypothalamus was immediately placed into 500 μl of 1N acetic acid, 0.02 N HCl, 10 mM EDTA, 1 μg/ml pepstatin (70). These extracts were then lyophilized and resuspended in 100 μl of 3N acetic acid. Further sample preparation and protein gel electrophoresis conditions were the same as for the stomach lysate Western blot probing for ghrelin. Electrophoresis was stopped once the desired molecular weight separation between mature GHRH, 5.2 kDa, and proGHRH, 12.3 kDa, was achieved, as visualized by the SeeBlue Plus2 Pre-Stained molecular weight standard (Life Technologies, LC5925). Clean razor blades were then used to excise gel slices from the proGHRH and mature GHRH fractions for each sample lane at 12.3 kDa and 5.2 kDa, respectively. Gel slices were placed into 1.0 ml of elution buffer (50 mM Tris-Hcl, 150 mM NaCl, 0.1 mM EDTA; pH 7.5) in clean 1.7-ml microcentrifuge tubes. Gel pieces were then chopped into much smaller pieces approximately of uniform size, to increase the surface area from which protein could passively diffuse into elution buffer with clean surgical scissors. The chopped gel slice and elution buffer mixture was then incubated on a shaking heat block overnight at 50°C. The following day, samples were centrifuged at 10,000 g for 15 minutes, and supernatant was collected. Immunoreactive GHRH content was then measured using a GHRH ELISA kit (Clone-Cloud Corp. ELISA Kit for Growth Hormone Releasing Hormone, CEA438Mu). Six-week-old male mice were used (n = 14 WT, n = 11 DEL, error bars are SEM in Figure 3L).

Pituitary GH Western blotting. Pituitaries were removed from overnight-fasted (16 hours) 4-week-old male mice. De-brained skulls were placed in Petri dishes with PBS. While viewing pituitary in de-brained skull via dissecting microscope, fine-tip tweezers were used to excise pituitary out of skull. Use of the PBS-filled Petri dish prevented pituitaries from folding in on itself. Excised pituitaries were then flash frozen in LN2. Pituitaries were homogenized in RIPA buffer (Thermo Fisher, 89900) supplemented with protease inhibitors (Halt protease & phosphatase inhibitor cocktail, Thermo Scientific, 78442). Five micrograms of total protein was loaded onto 4%–12% bis-tris gels, transferred to nitrocellulose membranes using iBlot program 0. Primary GH antibody (National Hormone and Peptide Program) in LI-COR blocking buffer and 1% Tween 20 was incubated for 2 hours at room temperature; blots were then washed 3 times for 5 minutes each in PBST. Blots were incubated with secondary antibodies at room temperature for 1 hour with gentle shaking. Blots were again washed 3 times for 5 minutes each in PBST. Two final washes were performed in PBS. Blots were imaged using the Odyssey Classic imaging system (LI-COR Biotechnology). Data were analyzed using Image Studio Lite version 5.0 and GraphPad Prism 6 (n = 5 WT, n = 4 Snord116p–/m+ P30 male mice).

Total ghrelin ELISA. Total circulating ghrelin was measured from adult male mice that were fasted overnight (16 hours). Whole blood was collected in the morning into heparinized tubes on ice, which was spun at 2,000 RCF at 4°C for 15 minutes. Total ghrelin content of plasma was measured using the Millipore Rat/Mouse Total Ghrelin ELISA kit EZRGRT-91K (n = 21 WT, n = 17 DEL adult males, fasted).

qRT-PCR for Snord116 and Ghrl, and Western blot for PC1 in P30 stomachs. Whole stomachs were excised from overnight (16 hours) fasted 1-month-old (P30) male mice. Stomachs were cut open sagitally, and residual food content was removed from stomachs. Stomach tissue was rinsed twice in room-temperature PBS before flash freezing in liquid nitrogen. Frozen stomachs were then cryohomogenized (Cryo-Cup Grinders, Research Products International, catalog 206), and 25% of the homogenate was used for RNA analysis, while 75% was used for protein analysis. RNA was isolated as described for liver. For protein analysis the homogenate was further homogenized briefly in RIPA buffer (Thermo Fisher, 89900) supplemented with protease inhibitors (Halt protease & phosphatase inhibitor cocktail, Thermo Scientific, 78442) using a handheld homogenizer. Lysates were centrifuged at for 20 minutes at 20,000 RCF at 4°C; clear supernatant was collected for analysis. Western blot for PC1 was performed as described for iPSC-derived neurons (n = 6 WT, n = 6 DEL P30 male mice).

Western blot for proghrelin/ghrelin in stomachs. Stomach lysates from adult mice fasted overnight (16 hours) were probed for ghrelin content by Western blot following the methods based on that of Zhu et al. and Yang et al. (40, 71). Stomachs were dissected out from the mouse and rinsed twice in deionized (DI) H2O. Stomachs were placed into 200 μl DI H2O and boiled for 10 minutes using a water bath. Boiled stomachs were then cooled on ice. Next, stomachs were minced, and 200 μl 2 M acetic acid, 0.04N HCl were added such that the final concentration was 1 M acetic acid and 0.02N HCl. This mixture was then homogenized. Stomach homogenate was centrifuged at 20,000 g for 1.5 hours at 4°C in order to obtain a clear supernatant. Supernatant was collected and reduced to 300 μl in a vacuum centrifuge. Acetone precipitation was then performed. Acetone was cooled to –20°C. 600 μl (2× volume of sample) acetone was added to the protein sample. Samples were incubated overnight at –20 °C. Samples were then centrifuged for 10 minutes at 15,000 RCF at 4°C. Supernatant was collected because ghrelin is dissolved in the hydrophobic fraction. The supernatant was then dried in vacuo overnight. Dried protein was then resuspended in 30 μl DI H2O. Total protein content for each sample was determined by BCA assay. Ten micrograms total protein was mixed with loading buffer such that final concentrations were 0.1 M Tris-chloride at pH 6.8, 5% wt/vol SDS, 0.1 M DTT, 5% glycerol. Sample loading buffer mixture was then incubated at 100°C for 5 minutes. Ten micrograms total protein was loaded onto a 16% tricine gel which was run in Tricine-SDS running buffer. 500 μl antioxidant was added to the center chamber. The gel was run at 70 V for 15 minutes, then 126 V until optimal migration was achieved. Proteins were transferred from the electrophoresis gel to a PVDF membrane using the iBlot system. Transfer conditions were 20 V for 5 minutes (program 3 run for 5 minutes). PVDF blots were immediately placed in PBST. To prevent diffusion of the 3.4-kDa mature ghrelin, blots were fixed at room temperature for 15 minutes (on a shaker) in 50 mM HEPES-NaOH, pH 7.4, and containing 2.5% wt/vol glutaraldehyde. The membrane was then washed 3 times, 5 minutes each, in PBST. The membrane was blocked for 30 minutes at room temperature in LI-COR blocking buffer with 1% Tween 20. The blot was exposed to anti-ghrelin (Santa Cruz Biotechnology Inc., sc-10368) and anti-preproghrelin (Pheonix Pharmaceuticals, H-031-34) primary antibodies during an overnight incubation at 4°C and gentle shaking. Blots were then washed 3 times for 5 minutes each in PBST. Blots were incubated with secondary antibodies at room temperature for 1 hour with gentle shaking. Blots were again washed 3 times for 5 minutes each in PBST. Two final washes were performed in PBS. Blots were imaged using the Odyssey Classic imaging system (LI-COR Biotechnology). Data were analyzed using Image Studio Lite Version 5.0 and GraphPad Prism 6 (n = 9 WT; n = 7 Snord116 deletion; n = 2 PC1-null adult mice fasted overnight).

Measurement of proinsulin, insulin, and glucose in human plasma. Plasma glucose levels were measured using the Wako Diagnostics AUTOKIT GLUCOSE C2. Proinsulin was measured using a Human Total Proinsulin ELISA kit (Millipore, EZHPI-15K). Insulin was measured using an Ultrasensitive Human Insulin ELISA kit (Mercodia, 10-1132-01) (n = 25 age/BMI-matched controls, n = 16 PWS patients, n = 1 PCSK1 mutation patient). All patient plasma collected at fasting. Unaffected control/patient genotype, sex, age, BMI Z score, and weight are listed in Supplemental Table 2.

Neuron IHC. iPSC-derived neurons were stained with the neural makers: TUJ1 (Sigma-Aldrich, T2200), NCAM (Santa Cruz Biotechnology Inc., sc-106) and Ki-67 (Abcam, ab15580). The staining procedure was the same as for iPSCs.

Calorimetry of Snord116 deletion mice and WT littermates. Food intake and energy expenditure were monitored using a LabMaster CaloSys calorimetry system (TSE Systems). The first 24 hours was an acclimation period; data from this period were not used in analyses. Mice were weighed, and body composition was measured using the Bruker Minispec TD NMR prior to and following housing in the calorimetry system. Mice were maintained on breeder chow while in the calorimetry system (n = 10 WT, n = 9 deletion, 6-month-old males).

Leptin ELISA. The R&D Systems Mouse/Rat Leptin Quantikine ELISA Kit (SMOB00) was used to measure leptin from ad libitum fed male mice at 1 month of age and 6 months of age (n = 13 WT, n = 13 deletion).

Accession numbers. The genomic data reported here were deposited in the NCBI’s Gene Expression Omnibus (GEO) database (GEO GSE89991).

Statistics. Data are presented as mean ± SEM. Comparisons between 2 groups were analyzed using 2-tailed Student’s t tests. Comparisons among more than 2 groups were analyzed with 1-way ANOVA with the post hoc Tukey test, except for data in Figure 1, B–F, which were analyzed with Kruskal-Wallis and the post hoc Dunn’s test. P α values less than 0.05 were considered significant. Asterisks throughout indicate *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001.

Study approval. The studies using human plasma or human iPSC-derived neurons in this work were approved by the Columbia University Medical Center Institutional Review Board, Human Research Protection Office, New York, New York, USA. All subjects provided written informed consent prior to their participation in the study. The studies using mice in this work were approved by the IACUC of Columbia University Animal Care Facility.

Author contributions

LCB, CAL, DE, and RLL designed experiments. LCB, CAL, CRS, DP, RR, MZ, JFMC, MVM, AAS, GH, BL, and DE performed experiments. SE, JPS, and MT provided PWS microdeletion fibroblast line 066, PWS LD fibroblast line 031, and one unaffected control fibroblast line, 056. CRS and DJD provided PWS LD fibroblast lines 129 and 139, as well as plasma from individuals with PWS and unaffected controls. MGB, KC, BD, CP, MR, and IF provided human plasma samples. RD provided tissues from PC1-null mice. LW provided technical expertise. LCB, CAL, DJD, BL, DE, and RLL analyzed and interpreted data. LCB and RLL wrote the manuscript.

Supplemental material

View Supplemental data

Acknowledgments