Skip to main content

Thank you for visiting You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Genetics and Epigenetics

The expression of genes in top obesity-associated loci is enriched in insula and substantia nigra brain regions involved in addiction and reward




Genome-wide association studies (GWAS) have identified more than 250 loci associated with body mass index (BMI) and obesity. However, post-GWAS functional genomic investigations have been inadequate for understanding how these genetic loci physiologically impact disease development.


We performed a PCR-free expression assay targeting genes located nearby the GWAS-identified SNPs associated with BMI/obesity in a large panel of human tissues. Furthermore, we analyzed several genetic risk scores (GRS) summing GWAS-identified alleles associated with increased BMI in 4236 individuals.


We found that the expression of BMI/obesity susceptibility genes was strongly enriched in the brain, especially in the insula (p = 4.7 × 10–9) and substantia nigra (p = 6.8 × 10–7), which are two brain regions involved in addiction and reward. Inversely, we found that top obesity/BMI-associated loci, including FTO, showed the strongest gene expression enrichment in the two brain regions.


Our data suggest for the first time that the susceptibility genes for common obesity may have an effect on eating addiction and reward behaviors through their high expression in substantia nigra and insula, i.e., a different pattern from monogenic obesity genes that act in the hypothalamus and cause hyperphagia. Further epidemiological studies with relevant food behavior phenotypes are necessary to confirm these findings.

This is a preview of subscription content, access via your institution

Relevant articles

Open Access articles citing this article.

Access options

Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

Fig. 1


  1. Turcot V, Lu Y, Highland HM, Schurmann C, Justice AE, Fine RS, et al. Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity. Nat Genet. 2018;50:26–41.

    CAS  Article  Google Scholar 

  2. Ndiaye FK, Ortalli A, Canouil M, Huyvaert M, Salazar-Cardozo C, Lecoeur C, et al. Expression and functional assessment of candidate type 2 diabetes susceptibility genes identify four new genes contributing to human insulin secretion. Mol Metab. 2017;6:459–70.

    CAS  Article  Google Scholar 

  3. Locke AE, Kahali B, Berndt SI, Justice AE, Pers TH, Day FR, et al. Genetic studies of body mass index yield new insights for obesity biology. Nature. 2015;518:197–206.

    CAS  Article  Google Scholar 

  4. Speliotes EK, Willer CJ, Berndt SI, Monda KL, Thorleifsson G, Jackson AU, et al. Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index. Nat Genet. 2010;42:937–48.

    CAS  Article  Google Scholar 

  5. Berndt SI, Gustafsson S, Mägi R, Ganna A, Wheeler E, Feitosa MF, et al. Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture. Nat Genet. 2013;45:501–12.

    CAS  Article  Google Scholar 

  6. Wen W, Cho Y-S, Zheng W, Dorajoo R, Kato N, Qi L, et al. Meta-analysis identifies common variants associated with body mass index in east Asians. Nat Genet. 2012;44:307–11.

    CAS  Article  Google Scholar 

  7. Bradfield JP, Taal HR, Timpson NJ, Scherag A, Lecoeur C, Warrington NM, et al. A genome-wide association meta-analysis identifies new childhood obesity loci. Nat Genet. 2012;44:526–31.

    CAS  Article  Google Scholar 

  8. Wheeler E, Huang N, Bochukova EG, Keogh JM, Lindsay S, Garg S, et al. Genome-wide SNP and CNV analysis identifies common and low-frequency variants associated with severe early-onset obesity. Nat Genet. 2013;45:513–17.

    CAS  Article  Google Scholar 

  9. Monda KL, Chen GK, Taylor KC, Palmer C, Edwards TL, Lange LA, et al. A meta-analysis identifies new loci associated with body mass index in individuals of African ancestry. Nat Genet. 2013;45:690–96.

    CAS  Article  Google Scholar 

  10. Jiao H, Arner P, Hoffstedt J, Brodin D, Dubern B, Czernichow S, et al. Genome wide association study identifies KCNMA1 contributing to human obesity. BMC Med Genom. 2011;4:51.

    CAS  Article  Google Scholar 

  11. Anderson D, Cordell HJ, Fakiola M, Francis RW, Syn G, Scaman ESH, et al. First genome-wide association study in an Australian aboriginal population provides insights into genetic risk factors for body mass index and type 2 diabetes. PLoS ONE. 2015;10:e0119333.

    Article  Google Scholar 

  12. Yengo L, Sidorenko J, Kemper KE, Zheng Z, Wood AR, Weedon MN, et al. Meta-analysis of genome-wide association studies for height and body mass index in 700000 individuals of European ancestry. Hum Mol Genet. 2018;27:3641–49.

    CAS  Article  Google Scholar 

  13. Vaxillaire M, Yengo L, Lobbens S, Rocheleau G, Eury E, Lantieri O, et al. Type 2 diabetes-related genetic risk scores associated with variations in fasting plasma glucose and development of impaired glucose homeostasis in the prospective DESIR study. Diabetologia. 2014;57:1601–10.

    CAS  Article  Google Scholar 

  14. Blundell JE, Gillett A. Control of food intake in the obese. Obes Res. 2001;9 Suppl 4:263S–270S.

    CAS  Article  Google Scholar 

  15. Flint AJ, Gearhardt AN, Corbin WR, Brownell KD, Field AE, Rimm EB. Food-addiction scale measurement in 2 cohorts of middle-aged and older women. Am J Clin Nutr. 2014;99:578–86.

    CAS  Article  Google Scholar 

  16. Hebebrand J, Albayrak Ö, Adan R, Antel J, Dieguez C, de Jong J, et al. ‘Eating addiction’, rather than ‘food addiction’, better captures addictive-like eating behavior. Neurosci Biobehav Rev. 2014;47:295–306.

    Article  Google Scholar 

  17. Naqvi NH, Bechara A. The hidden island of addiction: the insula. Trends Neurosci. 2009;32:56–67.

    CAS  Article  Google Scholar 

  18. Zaghloul KA, Blanco JA, Weidemann CT, McGill K, Jaggi JL, Baltuch GH, et al. Human substantia nigra neurons encode unexpected financial rewards. Science. 2009;323:1496–99.

    CAS  Article  Google Scholar 

  19. Luo SX, Huang EJ. Dopaminergic neurons and brain reward pathways: from neurogenesis to circuit assembly. Am J Pathol. 2016;186:478–88.

    CAS  Article  Google Scholar 

  20. Micali N, Field AE, Treasure JL, Evans DM. Are obesity risk genes associated with binge eating in adolescence? Obesity. 2015;23:1729–36.

    Article  Google Scholar 

  21. Castellini G, Franzago M, Bagnoli S, Lelli L, Balsamo M, Mancini M, et al. Fat mass and obesity-associated gene (FTO) is associated to eating disorders susceptibility and moderates the expression of psychopathological traits. PLoS ONE. 2017;12:e0173560.

    Article  Google Scholar 

  22. Corwin RLW, Wojnicki FHE, Zimmer DJ, Babbs RK, McGrath LE, Olivos DR, et al. Binge-type eating disrupts dopaminergic and GABAergic signaling in the prefrontal cortex and ventral tegmental area. Obesity. 2016;24:2118–25.

    CAS  Article  Google Scholar 

  23. Claussnitzer M, Dankel SN, Kim K-H, Quon G, Meuleman W, Haugen C, et al. FTO obesity variant circuitry and adipocyte browning in humans. N Engl J Med. 2015;373:895–907.

    CAS  Article  Google Scholar 

Download references


We thank Endocells for providing the pancreatic beta-cell line, EndoC-βH1. The GTEx Project was supported by the Common Fund of the Office of the Director of the National Institutes of Health, and by NCI, NHGRI, NHLBI, NIDA, NIMH, and NINDS. The data used for the analyses described in this manuscript were obtained from the GTEx Portal on 23 Novermber 2018. This work was supported by grants from the French National Research Agency (ANR-10-LABX-46 [European Genomics Institute for Diabetes] and ANR-10-EQPX-07-01 [LIGAN-PM], to PF), from the European Research Council (ERC GEPIDIAB—294785, to PF; ERC Reg-Seq—715575, to AB), from FEDER (to PF), and from the ‘Région Nord Pas-de-Calais’ (to PF and to FKN). AB was supported by Inserm. The D.E.S.I.R. study has been funded by Inserm contracts with Caisse nationale de l’assurance maladie des travailleurs salariés, Lilly, Novartis Pharma, and Sanofi-Aventis; Inserm (Réseaux en Santé Publique, Interactions entre les déterminants de la santé, Cohortes Santé TGIR 2008); the Association Diabète Risque Vasculaire; the Fédération Française de Cardiologie; La Fondation de France; the Association de Langue Française pour l’Etude du Diabète et des Maladies Métaboliques/Société Francophone de Diabétologie; the Office national interprofessionnel des vins; Ardix Medical; Bayer Diagnostics; Becton Dickinson; Cardionics; Merck Santé; Novo Nordisk; Pierre Fabre; Roche; and Topcon. The D.E.S.I.R. study group includes: Inserm U1018: B. Balkau, P. Ducimetière, and E. Eschwège; Inserm U367: F. Alhenc-Gelas; CHU D’Angers: Y Gallois and A. Girault; Center de Recherche des Cordeliers, Inserm U1138, Bichat Hospital: F. Fumeron, M. Marre, and R. Roussel; CHU de Rennes: F. Bonnet; CNRS UMR8199, Lille: A. Bonnefond and P. Froguel; Centers d’Examens de Santé: Alençon, Angers, Blois, Caen, Chateauroux, Chartres, Cholet, Le Mans, Orléans, and Tours; Institute de Recherche Médecine Générale: J. Cogneau; General practitioners of the region; Institute Inter-Regional pour la Santé: C. Born, E. Caces, M. Cailleau, O Lantieri, J.G. Moreau, F. Rakotozafy, J. Tichet, and S. Vol.

Author information

Authors and Affiliations


Corresponding authors

Correspondence to Philippe Froguel or Amélie Bonnefond.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Additional information

Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Ndiaye, F.K., Huyvaert, M., Ortalli, A. 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).

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI:

Further reading


Quick links