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Genetics and Epigenetics

The heritability of BMI varies across the range of BMI—a heritability curve analysis in a twin cohort



The heritability of traits such as body mass index (BMI), a measure of obesity, is generally estimated using family and twin studies, and increasingly by molecular genetic approaches. These studies generally assume that genetic effects are uniform across all trait values, yet there is emerging evidence that this may not always be the case.


This paper analyzes twin data using a recently developed measure of heritability called the heritability curve. Under the assumption that trait values in twin pairs are governed by a flexible Gaussian mixture distribution, heritability curves may vary across trait values. The data consist of repeated measures of BMI on 1506 monozygotic (MZ) and 2843 like-sexed dizygotic (DZ) adult twin pairs, gathered from multiple surveys in older Finnish Twin Cohorts.


The heritability curve and BMI value-specific MZ and DZ pairwise correlations were estimated, and these varied across the range of BMI. MZ correlations were highest at BMI values from 21 to 24, with a stronger decrease for women than for men at higher values. Models with additive and dominance effects fit best at low and high BMI values, while models with additive genetic and common environmental effects fit best in the normal range of BMI.


We demonstrate that twin and molecular genetic studies need to consider how genetic effects vary across trait values. Such variation may reconcile findings of traits with high heritability and major differences in mean values between countries or over time.

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Fig. 1: Regression analysis used to estimate \({{{\boldsymbol{BMI}}}}_{35}\) (BMI at age 35) for each of 8598 individuals in the study.
Fig. 2: \({{{\boldsymbol{BMI}}}}_{35}\) for pairs of female dizygotic twins, obtained by regression analysis.
Fig. 3: Correlation curves for male and female data for monozygotic (top) and dizygotic (bottom) twins, with pointwise 95% confidence bands (shaded regions).
Fig. 4: Decomposition of total variance into genetic and environmental effects by BMI, sex, and genetic model (ACE in red; ADE in blue).

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Data availability

The FTC data is not publicly available due to the restrictions of informed consent. However, the FTC data is available through the Institute for Molecular Medicine Finland (FIMM) Data Access Committee (DAC) ( for authorized researchers who have IRB/ethics approval and an institutionally approved study plan. To ensure the protection of privacy and compliance with national data protection legislation, a data use/transfer agreement is needed, the content and specific clauses of which will depend on the nature of the requested data.


  1. Benn R. Some mathematical properties of weight-for-height indices used as measures of adiposity. Br J of Prev & Soc Med. 1971;25:42.

    CAS  Google Scholar 

  2. Must A, Spadano J, Coakley EH, Field AE, Colditz G, Dietz WH. The disease burden associated with overweight and obesity. JAMA. 1999;282:1523–9.

    Article  CAS  Google Scholar 

  3. Elks CE, Den Hoed M, Zhao JH, Sharp SJ, Wareham NJ, Loos RJ, et al. Variability in the heritability of body mass index: a systematic review and meta-regression. Front in endocrinol. 2012;3:29.

    Article  Google Scholar 

  4. Maes HH, Neale MC, Eaves LJ. Genetic and environmental factors in relative body weight and human adiposity. Behav genet. 1997;27:325–51.

    Article  CAS  Google Scholar 

  5. Riveros-McKay F, Mistry V, Bounds R, Hendricks A, Keogh JM, Thomas H, et al. Genetic architecture of human thinness compared to severe obesity. PLoS genet. 2019;15:e1007603.

    Article  Google Scholar 

  6. Price A, Stunkard AJ. Commingling analysis of obesity in twins. Hum Heredity. 1989;39:121–35.

    Article  CAS  Google Scholar 

  7. Williams PT. Quantile-dependent heritability of computed tomography, dual-energy x-ray absorptiometry, anthropometric, and bioelectrical measures of adiposity. International Journal of Obesity. 2020;44:2101–12.

    Article  CAS  Google Scholar 

  8. Berentsen GD, Azzolini F, Skaug HJ, Lie RT, Gjessing HK. Heritability curves: a local measure of heritability in family models. Stat in Med. 2021;40:1357–82.

    Article  Google Scholar 

  9. Hjelmborg JV, Fagnani C, Silventoinen K, McGue M, Korkeila M, Christensen K, et al. Genetic influences on growth traits of BMI: a longitudinal study of adult twins. Obesity. 2008;16:847–52.

    Article  Google Scholar 

  10. Kaprio J, Bollepalli S, Buchwald J, Iso-Markku P, Korhonen T, Kovanen V, et al. The older Finnish Twin Cohort—45 years of follow-up. Twin Res and Hum Genet. 2019;22:240–54.

    Article  Google Scholar 

  11. Khoury MJ, Beaty TH, Beaty TH, Cohen BH. Fundamentals of genetic epidemiology, vol. 22. Monographs in Epidemiology and, 1993.

  12. Falconer DS. Introduction to quantitative genetics, Oliver & Boyd:Edinburgh/London, 1960.

  13. Bjerve S, Doksum K. Correlation curves: measures of association as functions of covariate values. The Annals of Statistics. 1993;21:890–902.

    Article  Google Scholar 

  14. Kristensen K, Nielsen A, Berg CW, Skaug H, Bell B. TMB: automatic differentiation and Laplace approximation. 2015:arXiv preprint arXiv:1509.00660.

  15. Silventoinen K, Jelenkovic A, Sund R, Yokoyama Y, Hur Y-M, Cozen W, et al. Differences in genetic and environmental variation in adult BMI by sex, age, time period, and region: an individual-based pooled analysis of 40 twin cohorts. The Am J of clin nutr. 2017;106:457–66.

    Article  CAS  Google Scholar 

  16. Khera AV, Chaffin M, Wade KH, Zahid S, Brancale J, Xia R, et al. Polygenic prediction of weight and obesity trajectories from birth to adulthood. Cell. 2019;177:587–96. e9.

    Article  CAS  Google Scholar 

  17. Naukkarinen J, Rissanen A, Kaprio J, Pietiläinen KH. Causes and consequences of obesity: the contribution of recent twin studies. Int J of Obes. 2012;36:1017–24.

    Article  CAS  Google Scholar 

  18. van der Kolk BW, Saari S, Lovric A, Arif M, Alvarez M, Ko A, et al. Molecular pathways behind acquired obesity: Adipose tissue and skeletal muscle multiomics in monozygotic twin pairs discordant for BMI. Cell Rep Med. 2021;2:100226.

    Article  Google Scholar 

  19. Kaur Y, De Souza R, Gibson W, Meyre D. A systematic review of genetic syndromes with obesity. Obes Rev. 2017;18:603–34.

    Article  CAS  Google Scholar 

  20. Seidell JC, Flegal KM. Assessing obesity: classification and epidemiology. Br med bull. 1997;53:238–52.

    Article  CAS  Google Scholar 

  21. Collaborators GO. Health effects of overweight and obesity in 195 countries over 25 years. New Engl J of Med. 2017;377:13–27.

    Article  Google Scholar 

  22. Mitchell JA, Hakonarson H, Rebbeck TR, Grant SF. Obesity‐susceptibility loci and the tails of the pediatric BMI distribution. Obesity. 2013;21:1256–60.

    Article  CAS  Google Scholar 

  23. Beyerlein A, von Kries R, Ness AR, Ong KK. Genetic markers of obesity risk: stronger associations with body composition in overweight compared to normal-weight children. Plos one. 2011;6:e19057.

    Article  CAS  Google Scholar 

  24. Abadi A, Alyass A, du Pont SR, Bolker B, Singh P, Mohan V, et al. Penetrance of polygenic obesity susceptibility loci across the body mass index distribution. The Am J of Hum Genet. 2017;101:925–38.

    Article  CAS  Google Scholar 

  25. Rokholm B, Silventoinen K, Ängquist L, Skytthe A, Kyvik KO, Sørensen TI. Increased genetic variance of BMI with a higher prevalence of obesity. PloS one. 2011;6:e20816.

    Article  CAS  Google Scholar 

  26. Nan C, Guo B, Warner C, Fowler T, Barrett T, Boomsma D, et al. Heritability of body mass index in pre-adolescence, young adulthood and late adulthood. Eur J of epidemiol. 2012;27:247–53.

    Article  Google Scholar 

  27. Silventoinen K, Rokholm B, Kaprio J, Sørensen TI. The genetic and environmental influences on childhood obesity: a systematic review of twin and adoption studies. Int J of obes. 2010;34:29–40.

    Article  CAS  Google Scholar 

  28. He L, Sillanpää MJ, Silventoinen K, Kaprio J, Pitkäniemi J. Estimating modifying effect of age on genetic and environmental variance components in twin models. Genetics. 2016;202:1313–28.

    Article  CAS  Google Scholar 

  29. Silventoinen K, Jelenkovic A, Sund R, Hur Y-M, Yokoyama Y, Honda C, et al. Genetic and environmental effects on body mass index from infancy to the onset of adulthood: an individual-based pooled analysis of 45 twin cohorts participating in the COllaborative project of Development of Anthropometrical measures in Twins (CODATwins) study. The Am J of Clin Nutr. 2016;104:371–9.

    Article  CAS  Google Scholar 

  30. Choh AC, Lee M, Kent JW, Diego VP, Johnson W, Curran JE, et al. Gene‐by‐age effects on BMI from birth to adulthood: the Fels longitudinal study. Obesity. 2014;22:875–81.

    Article  Google Scholar 

  31. Silventoinen K, Kaprio J, Yokoyama Y. Genetic regulation of pre-pubertal development of body mass index: a longitudinal study of Japanese twin boys and girls. Behav genet. 2011;41:234–41.

    Article  Google Scholar 

  32. Silventoinen K, Pietiläinen KH, Tynelius P, Sørensen TI, Kaprio J, Rasmussen F. Genetic regulation of growth from birth to 18 years of age: the Swedish young male twins study. Am J of Hum Biol. 2008;20:292–8.

    Article  Google Scholar 

  33. Ortega-Alonso A, Pietiläinen KH, Silventoinen K, Saarni SE, Kaprio J. Genetic and environmental factors influencing BMI development from adolescence to young adulthood. Behav genet. 2012;42:73–85.

    Article  Google Scholar 

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Parts of this work have been done in the context of CEDAS (Center for Data Science, University of Bergen, Norway).

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FA, GDB, HJS and JBH contributed to the conception and design of the work. JBH and JAK provided the data material. FA carried out all statistical analyses. FA drafted the manuscript, except for sections Introduction and Discussion which were drafted by JAK. All authors participated in finalizing the manuscript and gave final approval and agreed to be accountable for all aspects of work ensuring integrity and accuracy.

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Correspondence to Francesca Azzolini.

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Azzolini, F., Berentsen, G.D., Skaug, H.J. et al. The heritability of BMI varies across the range of BMI—a heritability curve analysis in a twin cohort. Int J Obes 46, 1786–1791 (2022).

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