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Genomics and personalized strategies in nutrition

Association of common genetic variants with body mass index in Russian population



Overweight is the scourge of modern society and a major risk factor for many diseases. For this reason, understanding the genetic component predisposing to high body mass index (BMI) seems to be an important task along with preventive measures aimed at improving eating behavior and increasing physical activity.


We analyzed genetic data of a European cohort (n = 21,080, 47.25% women, East Slavs ancestry >80%) for 5 frequently found genes in the context of association with obesity: IPX3 (rs3751723), MC4R (rs17782313), TMEM18 (rs6548238), PPARG (rs1801282) and FTO (rs9939609).


Our study revealed significant associations of FTO (rs9939609) (β = 0.37 (kg/m2)/allele, p = <2 × 10−16), MC4R (rs17782313) (β = 0.28 (kg/m2)/allele, p = 5.79 × 10−9), TMEM18 (rs6548238) (β = 0.29 (kg/m2)/allele, p = 2.43 × 10−8) with BMI and risk of obesity.


The results confirm the contribution of FTO, M4CR, and TMEM18 genes to the mechanism of body weight regulation and control.

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Fig. 1: Forest-plot of effect sizes of the studied SNPs of BMI in East Slavs.

Data availability

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  1. World Health Organization (WHO). Obesity. 2021.

  2. World Health Organization (WHO). Obesity and overweight. 2021. (accessed 18 Nov 2021).

  3. Chooi YC, Ding C, Magkos F. The epidemiology of obesity. Metabolism. 2019;92:6–10.

    CAS  PubMed  Google Scholar 

  4. Upadhyay J, Farr O, Perakakis N, Ghaly W, Mantzoros C. Obesity as a disease. Med Clin North Am. 2018;102:13–33.

    PubMed  Google Scholar 

  5. Blüher M. Obesity: global epidemiology and pathogenesis. Nat Rev Endocrinol. 2019;15:288–98.

    PubMed  Google Scholar 

  6. Popkin BM, Hawkes C. Sweetening of the global diet, particularly beverages: patterns, trends, and policy responses. Lancet Diabetes Endocrinol. 2016;4:174–86.

    PubMed  Google Scholar 

  7. Heymsfield SB, Wadden TA. Mechanisms, pathophysiology, and management of obesity. N. Engl J Med. 2017;376:254–66.

    CAS  PubMed  Google Scholar 

  8. Fewtrell MS, Haschke F, Prescott SL (eds): Preventive Aspects of Early Nutrition. Nestlé Nutr Inst Workshop Ser. Nestec Ltd. Vevey/S. Karger AG Basel, 2016, vol 85, pp 155–165.

  9. Bray MS, Loos RJ, McCaffery J. Erratum: NIH working group report-using genomic information to guide weight management: from universal to precision treatment. Obesity. 2016;24:757–757.

    Google Scholar 

  10. Rohde K, Keller M, la Cour Poulsen L, Blüher M, Kovacs P, Böttcher Y. Genetics and epigenetics in obesity. Metabolism. 2019;92:37–50.

    CAS  PubMed  Google Scholar 

  11. Goodarzi MO. Genetics of obesity: what genetic association studies have taught us about the biology of obesity and its complications. Lancet Diabetes Endocrinol. 2018;6:223–36.

    CAS  PubMed  Google Scholar 

  12. Müller MJ, Geisler C, Blundell J, Dulloo A, Schutz Y, Krawczak M, et al. The case of GWAS of obesity: does body weight control play by the rules? Int J Obes. 2018;42:1395–405.

    Google Scholar 

  13. Herbert A, Gerry NP, McQueen MB, Heid IM, Pfeufer A, Illig T, et al. A common genetic variant is associated with adult and childhood obesity. Science. 2006;312:279–83.

    CAS  PubMed  Google Scholar 

  14. Boes E, Kollerits B, Heid IM, Hunt SC, Pichler M, Paulweber B, et al. INSIG2 Polymorphism is neither associated with BMI nor with phenotypes of lipoprotein metabolism. Obesity. 2008;16:827–33.

    CAS  PubMed  Google Scholar 

  15. Hubáček J, Suchánek P, Lánská V, Piťha J, Adámková V. INSIG2 G-102A promoter variant exhibits context-dependent effect on HDL-cholesterol levels but not on BMI in Caucasians. Folia Biol. 2011;57:170–2.

    Google Scholar 

  16. Bressler J, Fornage M, Hanis CL, Kao WHL, Lewis CE, McPherson R, et al. The INSIG2 rs7566605 genetic variant does not play a major role in obesity in a sample of 24,722 individuals from four cohorts. BMC Med Genet. 2009;10.

  17. Campa D, Hüsing A, McKay JD, Sinilnikova O, Vogel U, Tjønneland A, et al. The INSIG2 rs7566605 polymorphism is not associated with body mass index and breast cancer risk. BMC Cancer. 2010;10.

  18. Frayling TM, Timpson NJ, Weedon MN, Zeggini E, Freathy RM, Lindgren CM, et al. A common variant in the FTO gene is associated with body mass index and predisposes to childhood and adult obesity. Science. 2007;316:889–94.

    CAS  PubMed  PubMed Central  Google Scholar 

  19. Thorleifsson G, Walters GB, Gudbjartsson DF, Steinthorsdottir V, Sulem P, Helgadottir A, et al. Genome-wide association yields new sequence variants at seven loci that associate with measures of obesity. Nat Genet. 2008;41:18–24.

    PubMed  Google Scholar 

  20. the GIANT Consortium. Six new loci associated with body mass index highlight a neuronal influence on body weight regulation. Nat Genet. 2009;41:25–34.

    Google Scholar 

  21. Speliotes E, Willer C, Berndt S, Monda K, Thorleifsson G, Jackson A, et al. Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index. Nat Genet. 2010;42:937–48.

    CAS  PubMed  PubMed Central  Google Scholar 

  22. Locke A, Kahali B, Berndt S, Justice A, Pers T, Day F, et al. Genetic studies of body mass index yield new insights for obesity biology. Nature. 2015;518:197–206.

    CAS  PubMed  PubMed Central  Google Scholar 

  23. Pigeyre M, Yazdi FT, Kaur Y, Meyre D. Recent progress in genetics, epigenetics and metagenomics unveils the pathophysiology of human obesity. Clin Sci. 2016;130:943–86.

    CAS  Google Scholar 

  24. Fall T, Ingelsson E. Genome-wide association studies of obesity and metabolic syndrome. Mol Cell Endocrinol. 2014;382:740–57.

    CAS  PubMed  Google Scholar 

  25. Akiyama M, Okada Y, Kanai M, Takahashi A, Momozawa Y, Ikeda M, et al. Genome-wide association study identifies 112 new loci for body mass index in the Japanese population. Nat Genet. 2017;49:1458–67.

    CAS  PubMed  Google Scholar 

  26. 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  PubMed  PubMed Central  Google Scholar 

  27. Schlauch KA, Read RW, Lombardi VC, Elhanan G, Metcalf WJ, Slonim AD, et al. A comprehensive genome-wide and phenome-wide examination of BMI and obesity in a Northern Nevadan cohort. G3 Genes|Genomes|Genet. 2020;10:645–64.

    CAS  PubMed  Google Scholar 

  28. Chauhdary Z, Rehman K, Akash MSH. The composite alliance of FTO locus with obesity‐related genetic variants. Clin Exp Pharmacol Physiol. 2021;48:954–65.

    CAS  PubMed  Google Scholar 

  29. Todendi PF, de Moura Valim AR, Klinger E, Reuter CP, Molina S, Martínez JA, et al. The role of the genetic variants IRX3 rs3751723 and FTO rs9939609 in the obesity phenotypes of children and adolescents. Obes Res Clin Pract. 2019;13:137–42.

    Google Scholar 

  30. Bañales-Luna M, Figueroa-Vega N, Marín-Aragón CI, Perez-Luque E, Ibarra-Reynoso L, Gallardo-Blanco HL, et al. Associations of nicotidamide-N-methyltransferase, FTO, and IRX3 genetic variants with body mass index and resting energy expenditure in Mexican subjects. Sci Rep. 2020;10.

  31. Yılmaz B, Gezmen, Karadağ M. The current review of adolescent obesity: the role of genetic factors. J Pediatr Endocrinol Metab. 2020;34:151–62.

    PubMed  Google Scholar 

  32. Castro GV, Latorre AFS, Korndorfer FP, de Carlos Back LK, Lofgren SE. The impact of variants in four genes: MC4R, FTO, PPARG and PPARGC1A in overweight and obesity in a large sample of the Brazilian population. Biochem Genet. 2021;59:1666–79.

    PubMed  Google Scholar 

  33. Yu K, Li L, Zhang L, Guo L, Wang C. Association between MC4R rs17782313 genotype and obesity: a meta-analysis. Gene. 2020;733:144372.

    CAS  PubMed  Google Scholar 

  34. Todendi PF, Klinger EI, Geraldo ACR, Brixner L, Reuter CP, Lindenau JDR, et al. Genetic risk score based on fat mass and obesity-associated, transmembrane protein 18 and fibronectin type III domain containing 5 polymorphisms is associated with anthropometric characteristics in South Brazilian children and adolescents. Br J Nutr. 2018;121:93–9.

    PubMed  Google Scholar 

  35. Velazquez-Roman J, Angulo-Zamudio UA, León-Sicairos N, Medina-Serrano J, DeLira-Bustillos N, Villamil-Ramírez H, et al. Association of FTO, ABCA1, ADRB3, and PPARG variants with obesity, type 2 diabetes, and metabolic syndrome in a Northwest Mexican adult population. J Diabetes Complicat. 2021;35:108025.

    CAS  Google Scholar 

  36. Gholamalizadeh M, Mirzaei Dahka S, Vahid F, Bourbour F, Badeli M, Javadi Kooshesh S et al. Does the rs9939609 FTO gene polymorphism affect fat percentage? A meta-analysis. Arch Physiol Biochem. 2020; 128:1421–1425.

  37. Yasri S, Wiwanitkit V. Association of FTO rs9939609 with obesity. Med Princ Pract. 2018;27:496–6.

    PubMed  PubMed Central  Google Scholar 

  38. Gerken T, Girard CA, Tung Y-CL, Webby CJ, Saudek V, Hewitson KS, et al. The obesity-associated FTO gene encodes a 2-oxoglutarate-dependent nucleic acid demethylase. Science. 2007;318:1469–72.

    CAS  PubMed  PubMed Central  Google Scholar 

  39. Gulati P, Yeo GSH. The biology of FTO: from nucleic acid demethylase to amino acid sensor. Diabetologia. 2013;56:2113–21.

    CAS  PubMed  PubMed Central  Google Scholar 

  40. Koj N, Grochowalski Ł, Jarczak J, Wójtowicz W, Sobalska-Kwapis M, Słomka M et al. The association between polymorphisms near TMEM18 and the risk of obesity: a meta-analysis. BMC Med Genom. 2021;14.

  41. Delhanty PJD, Bouw E, Huisman M, Vervenne RML, Themmen APN, van der Lely AJ, et al. Functional characterization of a new human melanocortin-4 receptor homozygous mutation (N72K) that is associated with early-onset obesity. Mol Biol Rep. 2014;41:7967–72.

    CAS  PubMed  Google Scholar 

  42. Dina C, Meyre D, Gallina S, Durand E, Körner A, Jacobson P, et al. Variation in FTO contributes to childhood obesity and severe adult obesity. Nat Genet. 2007;39:724–6.

    CAS  PubMed  Google Scholar 

  43. Scuteri A, Sanna S, Chen W-M, Uda M, Albai G, Strait J, et al. Genome-wide association scan shows genetic variants in the FTO gene are associated with obesity-related traits. PLoS Genet. 2007;3:e115.

    PubMed  PubMed Central  Google Scholar 

  44. Egorenkova NP, Sorokina EY, Pogozheva AV, Peskova EV, Makurina ON, Levin LG, et al. The study of the peculiarities of metabolism in individuals with rs9939609 polymorphism of FTO gene. Vopr Pitan. 2015;84:97–104.

    CAS  PubMed  Google Scholar 

  45. Willer CJ, Speliotes EK, Loos RJF. Six new loci associated with body mass index highlight a neuronal influence on body weight regulation. Nat Genet. 2008;41:25–34.

    PubMed  PubMed Central  Google Scholar 

  46. Qi L, Kraft P, Hunter DJ, Hu FB. The common obesity variant near MC4R gene is associated with higher intakes of total energy and dietary fat, weight change and diabetes risk in women. Hum Mol Genet. 2008;17:3502–8.

    CAS  PubMed  PubMed Central  Google Scholar 

  47. Magno FCCM, Guaraná HC, da Fonseca ACP, Pedrosa AP, Zembrzuski VM, Cabello PH, et al. Association of the MC4R rs17782313 polymorphism with plasma ghrelin, leptin, IL6 and TNFα concentrations, food intake and eating behaviors in morbidly obese women. Eat Weight Disord - Stud Anorex, Bulim Obes. 2020;26:1079–87.

    Google Scholar 

  48. El Hajj Chehadeh S, Osman W, Nazar S, Jerman L, Alghafri A, Sajwani A, et al. Implication of genetic variants in overweight and obesity susceptibility among the young Arab population of the United Arab Emirates. Gene. 2020;739:144509.

    CAS  PubMed  Google Scholar 

  49. Kang J, Guan R-C, Zhao Y, Chen Y. Obesity-related loci in TMEM18, CDKAL1 and FAIM2 are associated with obesity and type 2 diabetes in Chinese Han patients. BMC Med. Genet. 2020;21.

  50. Smemo S, Tena JJ, Kim K-H, Gamazon ER, Sakabe NJ, Gómez-Marín C, et al. Obesity-associated variants within FTO form long-range functional connections with IRX3. Nature. 2014;507:371–75.

    CAS  PubMed  PubMed Central  Google Scholar 

  51. Liu C, Chu C, Zhang J, Wu D, Xu D, Li P, et al. IRX3is a genetic modifier for birth weight, adolescent obesity and transaminase metabolism. Pediatr Obes. 2017;13:141–8.

    PubMed  Google Scholar 

  52. Srivastava A, Mittal B, Prakash J, Srivastava P, Srivastava N, Srivastava N. A multianalytical approach to evaluate the association of 55 SNPs in 28 genes with obesity risk in North Indian adults. Am J Hum Biol. 2016;29:e22923.

    Google Scholar 

  53. Bakhashab S, Filimban N, Altall RM, Nassir R, Qusti SY, Alqahtani MH, et al. The effect sizes of PPARγ rs1801282, FTO rs9939609, and MC4R rs2229616 variants on type 2 diabetes mellitus risk among the Western Saudi population: a cross-sectional prospective study. Genes. 2020;11:98.

    CAS  PubMed  PubMed Central  Google Scholar 

  54. Bordoni L, Marchegiani F, Piangerelli M, Napolioni V, Gabbianelli R. Obesity-related genetic polymorphisms and adiposity indices in a young Italian population. IUBMB Life. 2017;69:98–105.

    CAS  PubMed  Google Scholar 

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Authors and Affiliations



AB, EK and AR conceived and planned the study. AB, EK, EV, AP and AR processed the experimental data. AB, EK and EV implemented visualizations for analysis. AR, IP and EV developed software. AB, EK and EV conducted the statistical analysis. EK, EV, IP, AR, AK, NP, AI and VI curated research data. AR, AE and VI administered the project. AR supervised the whole study. AB, EK, AP and AR drafted the manuscript. All authors reviewed and edited the final manuscript.

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Correspondence to Alexander Rakitko.

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Berseneva, A., Kovalenko, E., Vergasova, E. et al. Association of common genetic variants with body mass index in Russian population. Eur J Clin Nutr 77, 574–578 (2023).

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