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The genetics of obesity: from discovery to biology

Nature Reviews Genetics volume 23, pages 120–133 (2022)Cite this article

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Abstract

The prevalence of obesity has tripled over the past four decades, imposing an enormous burden on people’s health. Polygenic (or common) obesity and rare, severe, early-onset monogenic obesity are often polarized as distinct diseases. However, gene discovery studies for both forms of obesity show that they have shared genetic and biological underpinnings, pointing to a key role for the brain in the control of body weight. Genome-wide association studies (GWAS) with increasing sample sizes and advances in sequencing technology are the main drivers behind a recent flurry of new discoveries. However, it is the post-GWAS, cross-disciplinary collaborations, which combine new omics technologies and analytical approaches, that have started to facilitate translation of genetic loci into meaningful biology and new avenues for treatment.

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Fig. 1: Prevalence of obesity in males and females according to age and geographical region.
Fig. 2
Fig. 3: Timeline of key discoveries in obesity genetics.
Fig. 4: The leptin–melanocortin pathway.
Fig. 5: Schematic representation of the FTO locus and its neighbouring genes on human chromosome 16q22.
Fig. 6: Predicting obesity using a polygenic score.

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References

  1. GBD 2015 Obesity Collaborators. Health effects of overweight and obesity in 195 countries over 25 years. N. Engl. J. Med. 377, 13–27 (2017).

    Article  Google Scholar 

  2. Must, A. et al. The disease burden associated with overweight and obesity. JAMA 282, 1523–1529 (1999).

    Article  CAS  PubMed  Google Scholar 

  3. Fontaine, K. R. & Barofsky, I. Obesity and health-related quality of life. Obes. Rev. 2, 173–182 (2001).

    Article  CAS  PubMed  Google Scholar 

  4. Bhattacharya, I., Ghayor, C., Perez Dominguez, A. & Weber, F. E. From influenza virus to novel corona virus (SARS-CoV-2)—the contribution of obesity. Front. Endocrinol. 11, 556962 (2020).

    Article  Google Scholar 

  5. Petrilli, C. M. et al. Factors associated with hospital admission and critical illness among 5279 people with coronavirus disease 2019 in New York City: prospective cohort study. BMJ 369, m1966 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  6. Cummings, M. J. et al. Epidemiology, clinical course, and outcomes of critically ill adults with COVID-19 in New York City: a prospective cohort study. Lancet 395, 1763–1770 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Zhao, X. et al. Obesity increases the severity and mortality of influenza and COVID-19: a systematic review and meta-analysis. Front. Endocrinol. 11, 595109 (2020).

    Article  Google Scholar 

  8. Abarca-Gómez, L. et al. Worldwide trends in body-mass index, underweight, overweight, and obesity from 1975 to 2016: a pooled analysis of 2416 population-based measurement studies in 128.9 million children, adolescents, and adults. Lancet 390, 2627–2642 (2017).

    Article  Google Scholar 

  9. Maes, H. H., Neale, M. C. & Eaves, L. J. Genetic and environmental factors in relative body weight and human obesity. Behav. Genet. 27, 325–351 (1997).

    Article  CAS  PubMed  Google Scholar 

  10. Elks, C. E. et al. Variability in the heritability of body mass index: a systematic review and meta-regression. Front. Endocrinol. 3, 29 (2012). This paper reports a large-scale meta-analysis of heritability data of twin and family studies.

    Article  Google Scholar 

  11. Chami, N., Preuss, M., Walker, R. W., Moscati, A. & Loos, R. J. F. The role of polygenic susceptibility to obesity among carriers of pathogenic mutations in MC4R in the UK Biobank population. PLoS Med. 17, e1003196 (2020). This study shows that the effect of MC4R mutations on BMI and obesity risk is attenuated by the polygenic background.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Kaur, Y., de Souza, R. J., Gibson, W. T. & Meyre, D. A systematic review of genetic syndromes with obesity. Obes. Rev. 18, 603–634 (2017).

    Article  CAS  PubMed  Google Scholar 

  13. Ingalls, A. M., Dickie, M. M. & Snell, G. D. Obese, a new mutation in the house mouse. J. Hered. 41, 317–318 (1950).

    Article  CAS  PubMed  Google Scholar 

  14. Hummel, K. P., Dickie, M. M. & Coleman, D. L. Diabetes, a new mutation in the mouse. Science 153, 1127–1128 (1966).

    Article  CAS  PubMed  Google Scholar 

  15. Zhang, Y. et al. Positional cloning of the mouse obese gene and its human homologue. Nature 372, 425–432 (1994). This paper reports the cloning of leptin, which provided the first molecular evidence that feeding and regulation of body weight had a hormonal basis.

    Article  CAS  Google Scholar 

  16. Chen, H. et al. Evidence that the diabetes gene encodes the leptin receptor: identification of a mutation in the leptin receptor gene in db/db mice. Cell 84, 491–495 (1996). This paper reports the cloning of the LEPR and the localization of its signalling version, which highlights the role of the brain in the control of appetitive behaviour.

    Article  CAS  PubMed  Google Scholar 

  17. Bultman, S. J., Michaud, E. J. & Woychik, R. P. Molecular characterization of the mouse agouti locus. Cell 71, 1195–1204 (1992).

    Article  CAS  PubMed  Google Scholar 

  18. Miller, M. W. et al. Cloning of the mouse agouti gene predicts a secreted protein ubiquitously expressed in mice carrying the lethal yellow mutation. Genes Dev. 7, 454–467 (1993).

    Article  CAS  PubMed  Google Scholar 

  19. Lu, D. et al. Agouti protein is an antagonist of the melanocyte-stimulating-hormone receptor. Nature 371, 799–802 (1994).

    Article  CAS  PubMed  Google Scholar 

  20. Fan, W., Boston, B. A., Kesterson, R. A., Hruby, V. J. & Cone, R. D. Role of melanocortinergic neurons in feeding and the agouti obesity syndrome. Nature 385, 165–168 (1997).

    Article  CAS  PubMed  Google Scholar 

  21. Montague, C. T. et al. Congenital leptin deficiency is associated with severe early-onset obesity in humans. Nature 387, 903–908 (1997). This work demonstrates that leptin signalling is also relevant in the human context, and provides early evidence, together with mutations in PCSK1, of a monogenic cause of severe human obesity.

    Article  CAS  PubMed  Google Scholar 

  22. Clement, K. et al. A mutation in the human leptin receptor gene causes obesity and pituitary dysfunction. Nature 392, 398–401 (1998). This work confirms the observations from mice about leptin signalling to the brain.

    Article  CAS  PubMed  Google Scholar 

  23. Jackson, R. S. et al. Obesity and impaired prohormone processing associated with mutations in the human prohormone convertase 1 gene. Nat. Genet. 16, 303–306 (1997). This study, together with mutations in the leptin gene, provides early evidence of a monogenic cause of severe human obesity, and also highlights the role of the nascent melanocortin pathway in body-weight regulation.

    Article  CAS  PubMed  Google Scholar 

  24. Huszar, D. et al. Targeted disruption of the melanocortin-4 receptor results in obesity in mice. Cell 88, 131–141 (1997).

    Article  CAS  PubMed  Google Scholar 

  25. Yeo, G. S. et al. A frameshift mutation in MC4R associated with dominantly inherited human obesity. Nat. Genet. 20, 111–112 (1998).

    Article  CAS  PubMed  Google Scholar 

  26. Vaisse, C., Clement, K., Guy-Grand, B. & Froguel, P. A frameshift mutation in MC4R is associated with a dominant form of obesity. Nat. Genet. 20, 113–114 (1998). This paper, together with Yeo et al. (1998), shows that heterozygous mutations in MC4R result in severe human obesity, establishing the role of the central melanocortin pathway in regulating human appetitive behaviour.

    Article  CAS  PubMed  Google Scholar 

  27. Krude, H. et al. Severe early-onset obesity, adrenal insufficiency and red hair pigmentation caused by POMC mutations in humans. Nat. Genet. 19, 155–157 (1998). This paper provides direct evidence that melanocortin peptides play a key role in the regulation of energy homeostasis.

    Article  CAS  PubMed  Google Scholar 

  28. Yaswen, L., Diehl, N., Brennan, M. B. & Hochgeschwender, U. Obesity in the mouse model of pro-opiomelanocortin deficiency responds to peripheral melanocortin. Nat. Med. 5, 1066–1070 (1999).

    Article  CAS  PubMed  Google Scholar 

  29. Challis, B. G. et al. Mice lacking pro-opiomelanocortin are sensitive to high-fat feeding but respond normally to the acute anorectic effects of peptide-YY(3-36). Proc. Natl Acad. Sci. USA 101, 4695–4700 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. van der Klaauw, A. A. et al. Human semaphorin 3 variants link melanocortin circuit development and energy balance. Cell 176, 729–742.e18 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  31. Farooqi, S. & O’Rahilly, S. Genetics of obesity in humans. Endocr. Rev. 27, 710–718 (2006).

    Article  CAS  PubMed  Google Scholar 

  32. Saeed, S., Arslan, M. & Froguel, P. Genetics of obesity in consanguineous populations: toward precision medicine and the discovery of novel obesity genes. Obesity 26, 474–484 (2018).

    Article  PubMed  Google Scholar 

  33. Saeed, S. et al. Genetic variants in LEP, LEPR, and MC4R explain 30% of severe obesity in children from a consanguineous population. Obesity 23, 1687–1695 (2015).

    Article  CAS  PubMed  Google Scholar 

  34. Saeed, S. et al. Genetic causes of severe childhood obesity: a remarkably high prevalence in an inbred population of Pakistan. Diabetes 69, 1424–1438 (2020).

    Article  PubMed  Google Scholar 

  35. Kurokawa, N. et al. The ADRB3 Trp64Arg variant and BMI: a meta-analysis of 44 833 individuals. Int. J. Obes. 32, 1240–1249 (2008).

    Article  CAS  Google Scholar 

  36. Shugart, Y. Y. et al. Two British women studies replicated the association between the Val66Met polymorphism in the brain-derived neurotrophic factor (BDNF) and BMI. Eur. J. Hum. Genet. 17, 1050–1055 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Benzinou, M. et al. Endocannabinoid receptor 1 gene variations increase risk for obesity and modulate body mass index in European populations. Hum. Mol. Genet. 17, 1916–1921 (2008).

    Article  CAS  PubMed  Google Scholar 

  38. Wang, D. et al. Association of the MC4R V103I polymorphism with obesity: a Chinese case–control study and meta-analysis in 55,195 individuals. Obesity 18, 573–579 (2010).

    Article  PubMed  Google Scholar 

  39. Nead, K. T. et al. Contribution of common non-synonymous variants in PCSK1 to body mass index variation and risk of obesity: a systematic review and meta-analysis with evidence from up to 331 175 individuals. Hum. Mol. Genet. 24, 3582–3594 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Tonjes, A., Scholz, M., Loeffler, M. & Stumvoll, M. Association of Pro12Ala polymorphism in peroxisome proliferator-activated receptor gamma with pre-diabetic phenotypes: meta-analysis of 57 studies on nondiabetic individuals. Diabetes Care 29, 2489–2497 (2006).

    Article  PubMed  Google Scholar 

  41. Rankinen, T. et al. The human obesity gene map: the 2005 update. Obesity 14, 529–644 (2006).

    Article  PubMed  Google Scholar 

  42. Frayling, T. M. et al. A common variant in the FTO gene is associated with body mass index and predisposes to childhood and adult obesity. Science 316, 889–894 (2007). This paper describes the first GWAS (for type 2 diabetes) to identify a locus (FTO) robustly associated with BMI.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Scuteri, A. et al. Genome-wide association scan shows genetic variants in the FTO gene are associated with obesity-related traits. PLoS Genet. 3, e115 (2007).

    Article  PubMed  PubMed Central  Google Scholar 

  44. Buniello, A. et al. The NHGRI-EBI GWAS Catalog of published genome-wide association studies, targeted arrays and summary statistics 2019. Nucleic Acids Res. 47, D1005–D1012 (2019).

    Article  CAS  PubMed  Google Scholar 

  45. Yengo, L. et al. Meta-analysis of genome-wide association studies for height and body mass index in approximately 700 000 individuals of European ancestry. Hum. Mol. Genet. 27, 3641–3649 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Javed, A. et al. Diagnostic performance of body mass index to identify obesity as defined by body adiposity in children and adolescents: a systematic review and meta-analysis. Pediatr. Obes. 10, 234–244 (2015).

    Article  CAS  PubMed  Google Scholar 

  47. Kilpelainen, T. O. et al. Genetic variation near IRS1 associates with reduced adiposity and an impaired metabolic profile. Nat. Genet. 43, 753–760 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Lu, Y. et al. New loci for body fat percentage reveal link between adiposity and cardiometabolic disease risk. Nat. Commun. 7, 10495 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Zillikens, M. C. et al. Large meta-analysis of genome-wide association studies identifies five loci for lean body mass. Nat. Commun. 8, 80 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  50. Chu, A. Y. et al. Multiethnic genome-wide meta-analysis of ectopic fat depots identifies loci associated with adipocyte development and differentiation. Nat. Genet. 49, 125–130 (2017).

    Article  CAS  PubMed  Google Scholar 

  51. Kilpelainen, T. O. et al. Genome-wide meta-analysis uncovers novel loci influencing circulating leptin levels. Nat. Commun. 7, 10494 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Sun, Q. et al. Genome-wide association study identifies polymorphisms in LEPR as determinants of plasma soluble leptin receptor levels. Hum. Mol. Genet. 19, 1846–1855 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Riveros-McKay, F. et al. Genetic architecture of human thinness compared to severe obesity. PLoS Genet. 15, e1007603 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  54. Orthofer, M. et al. Identification of ALK in thinness. Cell 181, 1246–1262.e22 (2020).

    Article  CAS  PubMed  Google Scholar 

  55. Bradfield, J. P. et al. A trans-ancestral meta-analysis of genome-wide association studies reveals loci associated with childhood obesity. Hum. Mol. Genet. 28, 3327–3338 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Felix, J. F. et al. Genome-wide association analysis identifies three new susceptibility loci for childhood body mass index. Hum. Mol. Genet. 25, 389–403 (2016).

    Article  CAS  PubMed  Google Scholar 

  57. Vogelezang, S. et al. Novel loci for childhood body mass index and shared heritability with adult cardiometabolic traits. PLoS Genet. 16, e1008718 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Akiyama, M. et al. Genome-wide association study identifies 112 new loci for body mass index in the Japanese population. Nat. Genet. 49, 1458–1467 (2017).

    Article  CAS  PubMed  Google Scholar 

  59. Ng, M. C. Y. et al. Discovery and fine-mapping of adiposity loci using high density imputation of genome-wide association studies in individuals of African ancestry: African Ancestry Anthropometry Genetics Consortium. PLoS Genet. 13, e1006719 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  60. Gurdasani, D. et al. Uganda genome resource enables insights into population history and genomic discovery in Africa. Cell 179, 984–1002.e36 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Wojcik, G. L. et al. Genetic analyses of diverse populations improves discovery for complex traits. Nature 570, 514–518 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Martin, A. R. et al. Clinical use of current polygenic risk scores may exacerbate health disparities. Nat. Genet. 51, 584–591 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Grarup, N. et al. Loss-of-function variants in ADCY3 increase risk of obesity and type 2 diabetes. Nat. Genet. 50, 172–174 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Saeed, S. et al. Loss-of-function mutations in ADCY3 cause monogenic severe obesity. Nat. Genet. 50, 175–179 (2018).

    Article  CAS  PubMed  Google Scholar 

  65. Minster, R. L. et al. A thrifty variant in CREBRF strongly influences body mass index in Samoans. Nat. Genet. 48, 1049–1054 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Andersen, M. K. et al. The derived allele of a novel intergenic variant at chromosome 11 associates with lower body mass index and a favorable metabolic phenotype in Greenlanders. PLoS Genet. 16, e1008544 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  67. Siljee, J. E. et al. Subcellular localization of MC4R with ADCY3 at neuronal primary cilia underlies a common pathway for genetic predisposition to obesity. Nat. Genet. 50, 180–185 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Willer, C. J. et al. Six new loci associated with body mass index highlight a neuronal influence on body weight regulation. Nat. Genet. 41, 25–34 (2009).

    Article  CAS  PubMed  Google Scholar 

  69. Singh, K. et al. Neural cell adhesion molecule Negr1 deficiency in mouse results in structural brain endophenotypes and behavioral deviations related to psychiatric disorders. Sci. Rep. 9, 5457 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  70. Speliotes, E. K. et al. Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index. Nat. Genet. 42, 937–948 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Soni, A., Amisten, S., Rorsman, P. & Salehi, A. GPRC5B a putative glutamate-receptor candidate is negative modulator of insulin secretion. Biochem. Biophys. Res. Commun. 441, 643–648 (2013).

    Article  CAS  PubMed  Google Scholar 

  72. Jarick, I. et al. Novel common copy number variation for early onset extreme obesity on chromosome 11q11 identified by a genome-wide analysis. Hum. Mol. Genet. 20, 840–852 (2011).

    Article  CAS  PubMed  Google Scholar 

  73. Sainsbury, A. et al. Synergistic effects of Y2 and Y4 receptors on adiposity and bone mass revealed in double knockout mice. Mol. Cell Biol. 23, 5225–5233 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  74. Falchi, M. et al. Low copy number of the salivary amylase gene predisposes to obesity. Nat. Genet. 46, 492–497 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  75. Meisler, M. H. & Ting, C. N. The remarkable evolutionary history of the human amylase genes. Crit. Rev. Oral Biol. Med. 4, 503–509 (1993).

    Article  CAS  PubMed  Google Scholar 

  76. Hendricks, A. E. et al. Rare variant analysis of human and rodent obesity genes in individuals with severe childhood obesity. Sci. Rep. 7, 4394 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  77. Turcot, V. et al. Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity. Nat. Genet. 50, 26–41 (2018). This large-scale exome-wide discovery study reports the use of array data to identify rare coding variations associated with BMI.

    Article  CAS  PubMed  Google Scholar 

  78. Emdin, C. A. et al. Analysis of predicted loss-of-function variants in UK Biobank identifies variants protective for disease. Nat. Commun. 9, 1613 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  79. Akbari, P. et al. Sequencing of 640,000 exomes identifies GPR75 variants associated with protection from obesity. Science 373, eabf8683 (2021). This large-scale exome-wide discovery study reports the use of WES data to identify mutations associated with BMI.

    Article  CAS  PubMed  Google Scholar 

  80. Baggio, L. L. & Drucker, D. J. Biology of incretins: GLP-1 and GIP. Gastroenterology 132, 2131–2157 (2007).

    Article  CAS  PubMed  Google Scholar 

  81. Antolin-Fontes, B. et al. The habenular G-protein-coupled receptor 151 regulates synaptic plasticity and nicotine intake. Proc. Natl Acad. Sci. USA 117, 5502–5509 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  82. Winkler, T. W. et al. The influence of age and sex on genetic associations with adult body size and shape: a large-scale genome-wide interaction study. PLoS Genet. 11, e1005378 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  83. Graff, M. et al. Genome-wide physical activity interactions in adiposity — a meta-analysis of 200,452 adults. PLoS Genet. 13, e1006528 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  84. Smith, C. E. et al. Genome-wide interactions with dairy intake for body mass index in adults of European descent. Mol. Nutr. Food Res. 62, 1700347 (2018).

    Article  Google Scholar 

  85. Justice, A. E. et al. Genome-wide meta-analysis of 241,258 adults accounting for smoking behaviour identifies novel loci for obesity traits. Nat. Commun. 8, 14977 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  86. Qi, Q. et al. Fried food consumption, genetic risk, and body mass index: gene–diet interaction analysis in three US cohort studies. BMJ 348, g1610 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  87. Kilpelainen, T. O. et al. Physical activity attenuates the influence of FTO variants on obesity risk: a meta-analysis of 218,166 adults and 19,268 children. PLoS Med. 8, e1001116 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  88. Yeo, G. S. H. Genetics of obesity: can an old dog teach us new tricks? Diabetologia 60, 778–783 (2017).

    Article  CAS  PubMed  Google Scholar 

  89. Locke, A. E. et al. Genetic studies of body mass index yield new insights for obesity biology. Nature 518, 197–206 (2015). This large-scale GWAS for BMI shows that BMI-associated loci frequently localize in or near genes that act in the brain.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  90. Friedman, J. M. & Halaas, J. L. Leptin and the regulation of body weight in mammals. Nature 395, 763–770 (1998).

    Article  CAS  PubMed  Google Scholar 

  91. Ahima, R. S. et al. Role of leptin in the neuroendocrine response to fasting. Nature 382, 250–252 (1996).

    Article  CAS  PubMed  Google Scholar 

  92. Cowley, M. A. et al. Integration of NPY, AGRP, and melanocortin signals in the hypothalamic paraventricular nucleus: evidence of a cellular basis for the adipostat. Neuron 24, 155–163 (1999).

    Article  CAS  PubMed  Google Scholar 

  93. Bertagna, X. Proopiomelanocortin-derived peptides. Endocrinol. Metab. Clin. North Am. 23, 467–485 (1994).

    Article  CAS  PubMed  Google Scholar 

  94. Ollmann, M. M. et al. Antagonism of central melanocortin receptors in vitro and in vivo by agouti-related protein. Science 278, 135–138 (1997).

    Article  CAS  PubMed  Google Scholar 

  95. Butler, A. A. et al. A unique metabolic syndrome causes obesity in the melanocortin-3 receptor-deficient mouse. Endocrinology 141, 3518–3521 (2000).

    Article  CAS  PubMed  Google Scholar 

  96. Chen, A. S. et al. Inactivation of the mouse melanocortin-3 receptor results in increased fat mass and reduced lean body mass. Nat. Genet. 26, 97–102 (2000).

    Article  CAS  PubMed  Google Scholar 

  97. Doche, M. E. et al. Human SH2B1 mutations are associated with maladaptive behaviors and obesity. J. Clin. Invest. 122, 4732–4736 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  98. Marenne, G. et al. Exome sequencing identifies genes and gene sets contributing to severe childhood obesity, linking PHIP variants to repressed POMC transcription. Cell Metab. 31, 1107–1119.e12 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  99. Asai, M. et al. Loss of function of the melanocortin 2 receptor accessory protein 2 is associated with mammalian obesity. Science 341, 275–278 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  100. Michaud, J. L. et al. Sim1 haploinsufficiency causes hyperphagia, obesity and reduction of the paraventricular nucleus of the hypothalamus. Hum. Mol. Genet. 10, 1465–1473 (2001).

    Article  CAS  PubMed  Google Scholar 

  101. Farooqi, I. S. et al. Clinical spectrum of obesity and mutations in the melanocortin 4 receptor gene. N. Engl. J. Med. 348, 1085–1095 (2003).

    Article  CAS  PubMed  Google Scholar 

  102. Wade, K. H. et al. Loss-of-function mutations in the melanocortin 4 receptor in a UK birth cohort. Nat. Med. 27, 1088–1096 (2021). This paper establishes the frequency of loss-of-function mutations in MC4R to be 0.3%, much more common than previously appreciated.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  103. van der Klaauw, A. et al. Role of melanocortin signalling in the preference for dietary macronutrients in human beings. Lancet 385, S12 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  104. Raffan, E. et al. A deletion in the canine POMC gene is associated with weight and appetite in obesity-prone Labrador retriever dogs. Cell Metab. 23, 893–900 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  105. Kim, K. S., Larsen, N., Short, T., Plastow, G. & Rothschild, M. F. A missense variant of the porcine melanocortin-4 receptor (MC4R) gene is associated with fatness, growth, and feed intake traits. Mamm. Genome 11, 131–135 (2000).

    Article  CAS  PubMed  Google Scholar 

  106. Aspiras, A. C., Rohner, N., Martineau, B., Borowsky, R. L. & Tabin, C. J. Melanocortin 4 receptor mutations contribute to the adaptation of cavefish to nutrient-poor conditions. Proc. Natl Acad. Sci. USA 112, 9668–9673 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  107. Pinto, S. et al. Rapid rewiring of arcuate nucleus feeding circuits by leptin. Science 304, 110–115 (2004).

    Article  CAS  PubMed  Google Scholar 

  108. Davies, A. M. The role of neurotrophins in the developing nervous system. J. Neurobiol. 25, 1334–1348 (1994).

    Article  CAS  PubMed  Google Scholar 

  109. McAllister, A. K., Katz, L. C. & Lo, D. C. Opposing roles for endogenous BDNF and NT-3 in regulating cortical dendritic growth. Neuron 18, 767–778 (1997).

    Article  CAS  PubMed  Google Scholar 

  110. Korte, M. et al. Hippocampal long-term potentiation is impaired in mice lacking brain-derived neurotrophic factor. Proc. Natl Acad. Sci. USA 92, 8856–8860 (1995).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  111. Kernie, S. G., Liebl, D. J. & Parada, L. F. BDNF regulates eating behavior and locomotor activity in mice. EMBO J. 19, 1290–1300 (2000).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  112. Xu, B. et al. Brain-derived neurotrophic factor regulates energy balance downstream of melanocortin-4 receptor. Nat. Neurosci. 6, 736–742 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  113. Xu, B. & Xie, X. Neurotrophic factor control of satiety and body weight. Nat. Rev. Neurosci. 17, 282–292 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  114. Rios, M. et al. Conditional deletion of brain-derived neurotrophic factor in the postnatal brain leads to obesity and hyperactivity. Mol. Endocrinol. 15, 1748–1757 (2001).

    Article  CAS  PubMed  Google Scholar 

  115. Gray, J. et al. Hyperphagia, severe obesity, impaired cognitive function, and hyperactivity associated with functional loss of one copy of the brain-derived neurotrophic factor (BDNF) gene. Diabetes 55, 3366–3371 (2006).

    Article  CAS  PubMed  Google Scholar 

  116. Yeo, G. S. et al. A de novo mutation affecting human TrkB associated with severe obesity and developmental delay. Nat. Neurosci. 7, 1187–1189 (2004).

    Article  CAS  PubMed  Google Scholar 

  117. Thorleifsson, G. et al. Genome-wide association yields new sequence variants at seven loci that associate with measures of obesity. Nat. Genet. 41, 18–24 (2009).

    Article  CAS  PubMed  Google Scholar 

  118. Finucane, H. K. et al. Heritability enrichment of specifically expressed genes identifies disease-relevant tissues and cell types. Nat. Genet. 50, 621–629 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  119. Ndiaye, F. K. et al. The expression of genes in top obesity-associated loci is enriched in insula and substantia nigra brain regions involved in addiction and reward. Int. J. Obes. 44, 539–543 (2020).

    Article  CAS  Google Scholar 

  120. Loos, R. J. & Yeo, G. S. The bigger picture of FTO: the first GWAS-identified obesity gene. Nat. Rev. Endocrinol. 10, 51–61 (2014).

    Article  CAS  PubMed  Google Scholar 

  121. Church, C. et al. Overexpression of Fto leads to increased food intake and results in obesity. Nat. Genet. 42, 1086–1092 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  122. Fischer, J. et al. Inactivation of the Fto gene protects from obesity. Nature 458, 894–898 (2009).

    Article  CAS  PubMed  Google Scholar 

  123. Cheung, M. K., Gulati, P., O’Rahilly, S. & Yeo, G. S. FTO expression is regulated by availability of essential amino acids. Int. J. Obes. 37, 744–747 (2013).

    Article  CAS  Google Scholar 

  124. Gulati, P. et al. Role for the obesity-related FTO gene in the cellular sensing of amino acids. Proc. Natl Acad. Sci. USA 110, 2557–2562 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  125. Karra, E. et al. A link between FTO, ghrelin, and impaired brain food-cue responsivity. J. Clin. Invest. 123, 3539–3551 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  126. Hess, M. E. et al. The fat mass and obesity associated gene (Fto) regulates activity of the dopaminergic midbrain circuitry. Nat. Neurosci. 16, 1042–1048 (2013).

    Article  CAS  PubMed  Google Scholar 

  127. Ruud, J. et al. The fat mass and obesity-associated protein (FTO) regulates locomotor responses to novelty via D2R medium spiny neurons. Cell Rep. 27, 3182–3198.e9 (2019).

    Article  CAS  PubMed  Google Scholar 

  128. Stratigopoulos, G., LeDuc, C. A., Cremona, M. L., Chung, W. K. & Leibel, R. L. Cut-like homeobox 1 (CUX1) regulates expression of the fat mass and obesity-associated and retinitis pigmentosa GTPase regulator-interacting protein-1-like (RPGRIP1L) genes and coordinates leptin receptor signaling. J. Biol. Chem. 286, 2155–2170 (2011).

    Article  CAS  PubMed  Google Scholar 

  129. Stratigopoulos, G. et al. Hypomorphism for RPGRIP1L, a ciliary gene vicinal to the FTO locus, causes increased adiposity in mice. Cell Metab. 19, 767–779 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  130. Stratigopoulos, G. et al. Hypomorphism of Fto and Rpgrip1l causes obesity in mice. J. Clin. Invest. 126, 1897–1910 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  131. Smemo, S. et al. Obesity-associated variants within FTO form long-range functional connections with IRX3. Nature 507, 371–375 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  132. Claussnitzer, M. et al. FTO obesity variant circuitry and adipocyte browning in humans. N. Engl. J. Med. 373, 895–907 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  133. O’Rahilly, S., Coll, A. P. & Yeo, G. S. FTO obesity variant and adipocyte browning in humans. N. Engl. J. Med. 374, 191 (2016).

    PubMed  Google Scholar 

  134. Sobreira, D. R. et al. Extensive pleiotropism and allelic heterogeneity mediate metabolic effects of IRX3 and IRX5. Science 372, 1085–1091 (2021).

    Article  CAS  PubMed  Google Scholar 

  135. Almen, M. S. et al. The obesity gene, TMEM18, is of ancient origin, found in majority of neuronal cells in all major brain regions and associated with obesity in severely obese children. BMC Med. Genet. 11, 58 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  136. Larder, R. et al. Obesity-associated gene TMEM18 has a role in the central control of appetite and body weight regulation. Proc. Natl Acad. Sci. USA 114, 9421–9426 (2017). Aside from the efforts at characterizing the FTO locus, this paper establishes a plausible role for yet another GWAS-identified candidate gene, TMEM18, in energy homeostasis.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  137. Wiemerslage, L. et al. The Drosophila ortholog of TMEM18 regulates insulin and glucagon-like signaling. J. Endocrinol. 229, 233–243 (2016).

    Article  CAS  PubMed  Google Scholar 

  138. Biederer, T. et al. SynCAM, a synaptic adhesion molecule that drives synapse assembly. Science 297, 1525–1531 (2002).

    Article  CAS  PubMed  Google Scholar 

  139. Yan, X. et al. Cadm2 regulates body weight and energy homeostasis in mice. Mol. Metab. 8, 180–188 (2018).

    Article  CAS  PubMed  Google Scholar 

  140. Rathjen, T. et al. Regulation of body weight and energy homeostasis by neuronal cell adhesion molecule 1. Nat. Neurosci. 20, 1096–1103 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  141. Wheeler, E. et al. Genome-wide SNP and CNV analysis identifies common and low-frequency variants associated with severe early-onset obesity. Nat. Genet. 45, 513–517 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  142. Schafer, M., Brauer, A. U., Savaskan, N. E., Rathjen, F. G. & Brummendorf, T. Neurotractin/kilon promotes neurite outgrowth and is expressed on reactive astrocytes after entorhinal cortex lesion. Mol. Cell. Neurosci. 29, 580–590 (2005).

    Article  PubMed  Google Scholar 

  143. Matikainen-Ankney, B. A. & Kravitz, A. V. Persistent effects of obesity: a neuroplasticity hypothesis. Ann. N. Y. Acad. Sci. 1428, 221–239 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  144. Lee, A. W. et al. Functional inactivation of the genome-wide association study obesity gene neuronal growth regulator 1 in mice causes a body mass phenotype. PLoS ONE 7, e41537 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  145. Joo, Y., Kim, H., Lee, S. & Lee, S. Neuronal growth regulator 1-deficient mice show increased adiposity and decreased muscle mass. Int. J. Obes. 43, 1769–1782 (2019).

    Article  CAS  Google Scholar 

  146. Boender, A. J., van Gestel, M. A., Garner, K. M., Luijendijk, M. C. & Adan, R. A. The obesity-associated gene Negr1 regulates aspects of energy balance in rat hypothalamic areas. Physiol. Rep. 2, e12083 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  147. Singh, K. et al. Neuronal growth and behavioral alterations in mice deficient for the psychiatric disease-associated negr1 gene. Front. Mol. Neurosci. 11, 30 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  148. Szczurkowska, J. et al. NEGR1 and FGFR2 cooperatively regulate cortical development and core behaviours related to autism disorders in mice. Brain 141, 2772–2794 (2018).

    PubMed  PubMed Central  Google Scholar 

  149. Noh, K. et al. Negr1 controls adult hippocampal neurogenesis and affective behaviors. Mol. Psychiatry 24, 1189–1205 (2019).

    Article  CAS  PubMed  Google Scholar 

  150. Cano-Gamez, E. & Trynka, G. From GWAS to function: using functional genomics to identify the mechanisms underlying complex diseases. Front. Genet. 11, 424 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  151. Loos, R. J. et al. Common variants near MC4R are associated with fat mass, weight and risk of obesity. Nat. Genet. 40, 768–775 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  152. Chambers, J. C. et al. Common genetic variation near MC4R is associated with waist circumference and insulin resistance. Nat. Genet. 40, 716–718 (2008).

    Article  CAS  PubMed  Google Scholar 

  153. Yaghootkar, H. et al. Genetic studies of leptin concentrations implicate leptin in the regulation of early adiposity. Diabetes 69, 2806–2818 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  154. Kichaev, G. et al. Leveraging polygenic functional enrichment to improve GWAS power. Am. J. Hum. Genet. 104, 65–75 (2019).

    Article  CAS  PubMed  Google Scholar 

  155. Pulit, S. L. et al. Meta-analysis of genome-wide association studies for body fat distribution in 694 649 individuals of European ancestry. Hum. Mol. Genet. 28, 166–174 (2019).

    Article  CAS  PubMed  Google Scholar 

  156. Wang, Y. et al. Melanocortin 4 receptor signals at the neuronal primary cilium to control food intake and body weight. J. Clin. Invest. 131, e142064 (2021).

    Article  CAS  PubMed Central  Google Scholar 

  157. Farooqi, I. S. et al. Effects of recombinant leptin therapy in a child with congenital leptin deficiency. N. Engl. J. Med. 341, 879–884 (1999). This paper is the first description of the treatment of leptin deficiency using leptin replacement therapy.

    Article  CAS  PubMed  Google Scholar 

  158. Farooqi, I. S. & O’Rahilly, S. 20 years of leptin: human disorders of leptin action. J. Endocrinol. 223, T63–T70 (2014).

    Article  CAS  PubMed  Google Scholar 

  159. Yeo, G. S. H. et al. The melanocortin pathway and energy homeostasis: from discovery to obesity therapy. Mol. Metab. 48, 101206 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  160. Kuhnen, P. et al. Proopiomelanocortin deficiency treated with a melanocortin-4 receptor agonist. N. Engl. J. Med. 375, 240–246 (2016). This paper is the first to demonstrate that the melanocortin pathway is a relevant and, so far, safe therapeutic target for the treatment of at least rare genetic causes of obesity.

    Article  PubMed  Google Scholar 

  161. Clement, K. et al. MC4R agonism promotes durable weight loss in patients with leptin receptor deficiency. Nat. Med. 24, 551–555 (2018).

    Article  CAS  PubMed  Google Scholar 

  162. Clement, K. et al. Efficacy and safety of setmelanotide, an MC4R agonist, in individuals with severe obesity due to LEPR or POMC deficiency: single-arm, open-label, multicentre, phase 3 trials. Lancet Diabetes Endocrinol. 8, 960–970 (2020).

    Article  CAS  PubMed  Google Scholar 

  163. Ayers, K. L. et al. Melanocortin 4 receptor pathway dysfunction in obesity: patient stratification aimed at MC4R agonist treatment. J. Clin. Endocrinol. Metab. 103, 2601–2612 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  164. Heymsfield, S. B. et al. Recombinant leptin for weight loss in obese and lean adults: a randomized, controlled, dose-escalation trial. JAMA 282, 1568–1575 (1999).

    Article  CAS  PubMed  Google Scholar 

  165. Collet, T. H. et al. Evaluation of a melanocortin-4 receptor (MC4R) agonist (setmelanotide) in MC4R deficiency. Mol. Metab. 6, 1321–1329 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  166. Khera, A. V. et al. Polygenic prediction of weight and obesity trajectories from birth to adulthood. Cell 177, 587–596.e9 (2019). This study describes a comprehensive PGS and its association with BMI throughout the life course.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  167. Loos, R. J. F. 15 years of genome-wide association studies and no signs of slowing down. Nat. Commun. 11, 5900 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  168. Pearce, L. R. et al. KSR2 mutations are associated with obesity, insulin resistance, and impaired cellular fuel oxidation. Cell 155, 765–777 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  169. Greenfield, J. R. et al. Modulation of blood pressure by central melanocortinergic pathways. N. Engl. J. Med. 360, 44–52 (2009).

    Article  CAS  PubMed  Google Scholar 

  170. Torkamani, A. & Topol, E. Polygenic risk scores expand to obesity. Cell 177, 518–520 (2019).

    Article  CAS  PubMed  Google Scholar 

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Acknowledgements

R.J.F.L. is supported by funding from Novo Nordisk Foundation (NNF Laureate Award) and the US National Institutes of Health (R01DK110113; R01DK107786; R01HL142302; R01 DK124097). G.S.H.Y. is supported by the Medical Research Council (MRC Metabolic Diseases Unit (MC_UU_00014/1)). The authors thank M. Guindo Martinez for her help with creating data for Fig. 3 and Supplementary Tables 1 and 2.

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Authors and Affiliations

  1. Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark

    Ruth J. F. Loos

  2. Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA

    Ruth J. F. Loos

  3. Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA

    Ruth J. F. Loos

  4. Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA

    Ruth J. F. Loos

  5. MRC Metabolic Diseases Unit, University of Cambridge Metabolic Research Laboratories, Wellcome-MRC Institute of Metabolic Science, Addenbrooke’s Hospital, Cambridge, UK

    Giles S. H. Yeo

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Supplementary information

Glossary

Obesogenic environment

An environment that promotes weight gain.

Monogenic obesity

A severe, early-onset form of obesity, caused by a single-gene mutation, with little or no influence of the environment.

Polygenic obesity

A common multifactorial form of obesity, resulting from an interaction between the obesogenic environment and hundreds of genetic variants.

Reverse genetics

An approach used to understand the function of a gene by analysing the consequences of genetically manipulating specific sequences within the gene.

Candidate gene studies

A hypothesis-driven approach to study the effect of a given gene (chosen based on the current understanding of its biology and pathophysiology) on susceptibility to the phenotype under study.

Genome-wide linkage studies

A method that relies on the relatedness of study participants to test whether certain chromosomal regions co-segregate with a disease or trait across generations.

Genome-wide association studies

(GWAS). A hypothesis-generating approach that screens whole genomes for associations between genetic variants and a phenotype of interest at much higher resolution than is possible for genome-wide linkage studies, and is thus better able to narrow down the associated locus.

Polygenic score

(PGS). A measure used to assess an individual’s genetic susceptibility to disease, calculated by summing the number of disease-increasing alleles, weighted by each variant’s effect size observed in a genome-wide association study.

Area under the receiver operating characteristic curve

(AUCROC). A metric used to assess the ability of a predictor to discriminate between individuals with and without a disease. The AUC ranges from 0.50 (equal to tossing a coin) to 1.0 (perfect prediction).

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Loos, R.J.F., Yeo, G.S.H. The genetics of obesity: from discovery to biology. Nat Rev Genet 23, 120–133 (2022). https://doi.org/10.1038/s41576-021-00414-z

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