M. Asai, Loss of function of the melanocortin 2 receptor accessory protein 2 is associated with mammalian obesity, Science, vol.341, pp.275-278, 2013.

E. Geets, Copy number variation (CNV) analysis and mutation analysis of the 6q14.1-6q16.3 genes SIM1 and MRAP2 in Prader Willi like patients, Mol. Genet. Metab, vol.117, pp.383-388, 2016.

L. Schonnop, Decreased melanocortin-4 receptor function conferred by an infrequent variant at the human melanocortin receptor accessory protein 2 gene, Obesity (Silver Spring), vol.24, pp.1976-1982, 2016.

J. R. Greenfield, Modulation of blood pressure by central melanocortinergic pathways, N. Engl. J. Med, vol.360, pp.44-52, 2009.

J. S. El-sayed-moustafa and P. Froguel, From obesity genetics to the future of personalized obesity therapy, Nat Rev Endocrinol, vol.9, pp.402-413, 2013.

P. Kühnen, Proopiomelanocortin Deficiency Treated with a Melanocortin-4

, Receptor Agonist. New England Journal of Medicine, vol.375, pp.240-246, 2016.

K. Clément, MC4R agonism promotes durable weight loss in patients with leptin receptor deficiency, Nature Medicine, vol.24, pp.551-555, 2018.

L. Soletto, Melanocortin Receptor Accessory Protein 2-Induced Adrenocorticotropic Hormone Response of Human Melanocortin 4 Receptor, J Endocr Soc, vol.3, pp.314-323, 2019.

J. Agulleiro and M. , Melanocortin 4 receptor becomes an ACTH receptor by coexpression of melanocortin receptor accessory protein 2, Mol. Endocrinol, vol.27, pp.1934-1945, 2013.

J. Zhang, The interaction of MC3R and MC4R with MRAP2, ACTH, ?-MSH and AgRP in chickens, J. Endocrinol, vol.234, pp.155-174, 2017.

P. T. Bradshaw, K. L. Monda, and J. Stevens, Metabolic syndrome in healthy obese, overweight, and normal weight individuals: the Atherosclerosis Risk in Communities Study, Obesity (Silver Spring), vol.21, pp.203-209, 2013.

C. A. Stanley, Perspective on the Genetics and Diagnosis of Congenital Hyperinsulinism Disorders, J. Clin. Endocrinol. Metab, vol.101, pp.815-826, 2016.

A. Bonnefond and P. Froguel, Rare and common genetic events in type 2 diabetes: what should biologists know?, Cell Metab, vol.21, pp.357-368, 2015.

F. K. Ndiaye, Expression and functional assessment of candidate type 2 diabetes susceptibility genes identify four new genes contributing to human insulin secretion, Mol Metab, vol.6, pp.459-470, 2017.

P. Ravassard, A genetically engineered human pancreatic ? cell line exhibiting glucose-inducible insulin secretion, J. Clin. Invest, vol.121, pp.3589-3597, 2011.

A. A. Rouault, D. K. Srinivasan, T. C. Yin, A. A. Lee, and J. A. Sebag, Melanocortin Receptor Accessory Proteins (MRAPs): Functions in the melanocortin system and beyond, Biochim Biophys Acta Mol Basis Dis, vol.1863, pp.2462-2467, 2017.

T. V. Novoselova, Loss of Mrap2 is associated with Sim1 deficiency and increased circulating cholesterol, J. Endocrinol, vol.230, pp.13-26, 2016.

A. L. Chaly, D. Srisai, E. E. Gardner, and J. A. Sebag, The Melanocortin Receptor Accessory Protein 2 promotes food intake through inhibition of the Prokineticin Receptor

, Elife, vol.5, 2016.

D. Srisai, MRAP2 regulates ghrelin receptor signaling and hunger sensing, Nat Commun, vol.8, p.713, 2017.

Y. Mao, T. Tokudome, and I. Kishimoto, Ghrelin and Blood Pressure Regulation, Curr. Hypertens. Rep, vol.18, p.15, 2016.

L. F. Chan, MRAP and MRAP2 are bidirectional regulators of the melanocortin receptor family, PNAS, vol.106, pp.6146-6151, 2009.

, After 1 hour, supernatants were collected and cells were lysed using TETG buffer (20 mM Tris-HCl pH 8.0, 137 mM NaCl, buffer containing 0.5 mM glucose was added to each well

. Roche,

, To ensure a reduced technical bias from the absorbance data, the technical duplicates' average absorbance was kept when the relative error was lower than 20% among the technical duplicates (this threshold being based on the observed distribution of the technical relative errors over 100 experiments). Fold changes of insulin secretion (i.e. secretion at stimulatory glucose levels divided by secretion at basal glucose levels) were then computed. Fold change of insulin secretion, Supernatants and lysates were centrifuged at 700 g, 4 °C for 5 minutes and insulin was assessed after proper dilution of the samples in water (1:16 for supernatants; 1:200 for lysates), using ELISA Human Insulin Kit (Mercodia

, Among children and adolescents, we performed a case-control study for 'obesity', adjusted for age and sex (controls were children/adolescents with normal weight), Statistical analyses for association studies: Among adults

R. Sladek, A genome-wide association study identifies novel risk loci for type 2 diabetes, Nature, vol.445, pp.881-885, 2007.
URL : https://hal.archives-ouvertes.fr/hal-00173692

D. Meyre, Genome-wide association study for early-onset and morbid adult obesity identifies three new risk loci in European populations, Nat. Genet, vol.41, pp.157-159, 2009.
URL : https://hal.archives-ouvertes.fr/hal-01655335

J. Leger, Reduced final height and indications for insulin resistance in 20 year olds born small for gestational age: regional cohort study, BMJ, vol.315, pp.341-347, 1997.

M. Romon, Relationships between physical activity and plasma leptin levels in healthy children: the Fleurbaix-Laventie Ville Santé II Study, Int. J. Obes. Relat. Metab. Disord, vol.28, pp.1227-1232, 2004.

, American Diabetes Association. 2. Classification and Diagnosis of Diabetes: Standards of Medical Care in Diabetes-2019, Diabetes Care, vol.42, pp.13-28, 2019.

, Executive Summary of the Third Report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III), JAMA: The Journal of the American Medical Association, vol.285, pp.2486-2497, 2001.

H. Li and R. Durbin, Fast and accurate short read alignment with Burrows-Wheeler transform, Bioinformatics, vol.25, pp.1754-1760, 2009.

A. Mckenna, The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data, Genome Res, vol.20, pp.1297-1303, 2010.

S. T. Sherry, dbSNP: the NCBI database of genetic variation, Nucleic Acids Res, vol.29, pp.308-311, 2001.

X. Liu, C. Wu, C. Li, and E. Boerwinkle, 0: A One-Stop Database of Functional Predictions and Annotations for Human Nonsynonymous and Splice-Site SNVs, Hum. Mutat, vol.37, pp.235-241, 2016.

S. Richards, Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology, Genet. Med, vol.17, pp.405-424, 2015.

P. Ravassard, A genetically engineered human pancreatic ? cell line exhibiting glucose-inducible insulin secretion, J. Clin. Invest, vol.121, pp.3589-3597, 2011.

J. Sun, Y. Zheng, and L. Hsu, A unified mixed-effects model for rare-variant association in sequencing studies, Genet. Epidemiol, vol.37, pp.334-344, 2013.