Abstract
Introduction
Genetic and environmental factors contribute to weight gain, but how these effects change over adulthood is largely unknown. We examined how genetic factors influence BMI changes from young adulthood to old age and how this change relates to BMI in early adulthood.
Data and methods
Data from 16 longitudinal twin cohorts, including 111,370 adults (56% women) and 55,657 complete twin pairs (42% monozygotic), were pooled. The data were divided into three stages (young adulthood-early middle age, late middle age, and old age). BMI changes were calculated via linear mixed effects and delta slope methods. Genetic and environmental contributions to these changes and their correlations with BMI in early young adulthood were estimated through structural equation modeling.
Results
The average BMI increase per year was 0.18 kg/m² in men and 0.15 kg/m² in women during young adulthood-early middle age (18–50 years), decreasing to ≤0.07 kg/m² at older ages. Genetic effects contributed to variance of BMI changes during young adulthood-early middle age (men a² = 0.29; women a² = 0.26) and less so in late middle age (51–64 years) (men a² = 0.05; women a² = 0.16) and old age ( > 65 years) (men a² = 0.13; women a² = 0.18). Most variation was explained by non-shared environmental effects (e² = 0.71–0.95 in men and e²= 0.74–0.84 in women). In men, greater BMI during early young adulthood (18–30 years) was associated with lower BMI changes later in life (r = −0.22 to −0.13), and the association was driven by genetic (rA = −0.27) and non-shared environmental (rE = −0.22 to −0.14) factors. In contrast, the association was positive in women (r = 0.05–0.28) and was explained by genetic factors (rA=0.27–0.51).
Conclusion
Genotype influences BMI changes across adulthood, with its effect varying by age and sex. Environmental effects are the main drivers of adult BMI changes, highlighting the role of modifiable factors in long-term weight regulation.
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Data availability
The data used in this study is owned by the third parties (the individual twin cohorts) and made available to this study in condition that they will be used only in this meta-analysis. The data can be used based on the same principles as used in this study (more information from Karri Silventoinen karri.silventoinen@helsinki.fi).
Code availability
All R scripts are available from the corresponding author.
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Funding
This study has been conducted within the CODATwins project. AO, KS, JK, AE, DIB, SB and RP have been supported by the BETTER4U project which has received funding from the European Union’s Horizon Europe Research and Innovation program under Grant Agreement n° 101080117, by UK Research and Innovation (UKRI) under the UK government’s Horizon Europe funding guarantee (grant number 10093560 for QMUL and 10106435 for BiB) and from the Swiss State Secretariat for Education, Research and Innovation (SERI). Views and opinions expressed are, however, those of the author(s) only and do not necessarily reflect those of the European Union. Data collection of the Finnish twin cohorts has been supported by the National Institute of Alcohol Abuse and Alcoholism (grants AA-12502, AA-00145, AA-09203, AA15416, and AA015416) and the Academy of Finland (grants 100499, 205585, 118555, 141054, 264146 and 308248). JK acknowledges support by the Academy of Finland Center of Excellence in Complex Disease Genetics (grant 352792). The Italian Twin Registry acknowledges the financial support from the Center for Behavioral Sciences and Mental Health, Istituto Superiore di Sanità, Rome, Italy. TwinsUK is funded by the Wellcome Trust, Medical Research Council, Versus Arthritis, European Union Horizon 2020, Chronic Disease Research Foundation (CDRF), Wellcome Leap Dynamic Resilience Program (co-funded by Temasek Trust), Zoe Ltd, the National Institute for Health and Care Research (NIHR) Clinical Research Network (CRN) and Biomedical Research Center based at Guy’s and St Thomas’ NHS Foundation Trust in partnership with King’s College London. The authors acknowledge the Swedish Twin Registry for access to data. The Swedish Twin Registry is managed by Karolinska Institutet and receives funding through the Swedish Research Council under the grant no 2017-00641. The Murcia Twin Registry is supported by Fundación Seneca-Regional Agency for Science and Technology, Murcia, Spain (22649/PI/24) and the Spanish Ministry of Science and Innovation (RTI2018-095185-B-I00, Ref.2098/2018), co-funded by European Regional Development Fund (FEDER). Colorado Twin Registry is funded by NIDA funded center grant DA011015, & Longitudinal Twin Study HD10333. Danish Twin Registry is supported by the National Program for Research Infrastructure 2007 from the Danish Agency for Science, Technology and Innovation, The Research Council for Health and Disease, the Velux Foundation and the US National Institute of Health (P01 AG08761). Korean Twin-Family Register was supported by the Global Research Network Program of the National Research Foundation (NRF 2011-220-E00006). The NAS-NRC Twin Registry acknowledges financial support from the National Institutes of Health grant number R21 AG039572. Netherlands Twin Register acknowledges the Netherlands Organization for Scientific Research (NWO) and MagW/ZonMW grants 904-61-090, 985-10-002, 912-10-020, 904-61-193,480-04-004, 463-06-001, 451-04-034, 400-05-717, Addiction-31160008, Middelgroot-911-09-032, Spinozapremie 56-464-14192; VU University’s Institute for Health and Care Research (EMGO + ); the European Research Council (ERC - 230374), the Avera Institute, Sioux Falls, South Dakota (USA). Washington State Twin Registry (formerly the University of Washington Twin Registry) was supported in part by grant NIH RC2 HL103416 (D. Buchwald, PI). Vietnam Era Twin Study of Aging was supported by National Institute of Health grants NIA R01 AG018384, R01 AG018386, R01 AG022381, and R01 AG022982, R01 AG050595, R01 AG076838. The Cooperative Studies Program of the Office of Research & Development of the United States Department of Veterans Affairs has provided financial support for the development and maintenance of the Vietnam Era Twin (VET) Registry. Queensland Twin registry is part of Twins Research Australia, a national resource supported by a Center of Research Excellence Grant (ID: 1079102), from the National Health and Medical Research Council.
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Contributions
AO, GD, JK, and KS designed the study. JO, JSR, LCC, MO, SA, RC, BH, EM, CF, VT, MG, DB, MB, LL, EG, KC, AS, KK, SM, SG, FR, PT, CF, WK, ML, TS, MM, GL, PM, NP, ADA, GED, DB, HP, JL, SJL, JS, SB, RP, AE, NM, DIB, JK collected the original data files. KS, JK, AJ and AO pooled the data together. AO conducted the analyses and drafted the manuscript. GD, AJ, JO, JSR, LCC, MO, SA, RC, BH, EM, CF, VT, MG, DB, MB, LL, EG, KC, AS, KK, SM, SG, FR, PT, CF, WK, ML, TS, MM, GL, PM, NP, ADA, GED, DB, HP, JL, SJL, JS, SB, RP, AE, NM, DIB, JK and KS revised the manuscript. All authors approved the final version and agreed to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.
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The pooled analysis was approved by the ethical board of the Department of Public Health, University of Helsinki. The data collections procedures of participating twin cohorts were approved by local ethical boards following the regulation in each country. Only anonymized data were delivered to the data management center at University of Helsinki. All participants were volunteers and they or their parents gave informed consent when participating in their original studies.
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Obeso, A., Drouard, G., Jelenkovic, A. et al. Genetic and environmental effects on weight gain from young adulthood to old age and its association with body mass index in early young adulthood: an individual-based pooled analysis of 16 twin cohorts. Int J Obes (2025). https://doi.org/10.1038/s41366-025-01998-w
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DOI: https://doi.org/10.1038/s41366-025-01998-w
