Changing genetic architecture of body mass index from infancy to early adulthood: an individual based pooled analysis of 25 twin cohorts.
Journal
International journal of obesity (2005)
ISSN: 1476-5497
Titre abrégé: Int J Obes (Lond)
Pays: England
ID NLM: 101256108
Informations de publication
Date de publication:
10 2022
10 2022
Historique:
received:
31
03
2022
accepted:
25
07
2022
revised:
22
07
2022
pubmed:
10
8
2022
medline:
24
9
2022
entrez:
9
8
2022
Statut:
ppublish
Résumé
Body mass index (BMI) shows strong continuity over childhood and adolescence and high childhood BMI is the strongest predictor of adult obesity. Genetic factors strongly contribute to this continuity, but it is still poorly known how their contribution changes over childhood and adolescence. Thus, we used the genetic twin design to estimate the genetic correlations of BMI from infancy to adulthood and compared them to the genetic correlations of height. We pooled individual level data from 25 longitudinal twin cohorts including 38,530 complete twin pairs and having 283,766 longitudinal height and weight measures. The data were analyzed using Cholesky decomposition offering genetic and environmental correlations of BMI and height between all age combinations from 1 to 19 years of age. The genetic correlations of BMI and height were stronger than the trait correlations. For BMI, we found that genetic correlations decreased as the age between the assessments increased, a trend that was especially visible from early to middle childhood. In contrast, for height, the genetic correlations were strong between all ages. Age-to-age correlations between environmental factors shared by co-twins were found for BMI in early childhood but disappeared altogether by middle childhood. For height, shared environmental correlations persisted from infancy to adulthood. Our results suggest that the genes affecting BMI change over childhood and adolescence leading to decreasing age-to-age genetic correlations. This change is especially visible from early to middle childhood indicating that new genetic factors start to affect BMI in middle childhood. Identifying mediating pathways of these genetic factors can open possibilities for interventions, especially for those children with high genetic predisposition to adult obesity.
Sections du résumé
BACKGROUND
Body mass index (BMI) shows strong continuity over childhood and adolescence and high childhood BMI is the strongest predictor of adult obesity. Genetic factors strongly contribute to this continuity, but it is still poorly known how their contribution changes over childhood and adolescence. Thus, we used the genetic twin design to estimate the genetic correlations of BMI from infancy to adulthood and compared them to the genetic correlations of height.
METHODS
We pooled individual level data from 25 longitudinal twin cohorts including 38,530 complete twin pairs and having 283,766 longitudinal height and weight measures. The data were analyzed using Cholesky decomposition offering genetic and environmental correlations of BMI and height between all age combinations from 1 to 19 years of age.
RESULTS
The genetic correlations of BMI and height were stronger than the trait correlations. For BMI, we found that genetic correlations decreased as the age between the assessments increased, a trend that was especially visible from early to middle childhood. In contrast, for height, the genetic correlations were strong between all ages. Age-to-age correlations between environmental factors shared by co-twins were found for BMI in early childhood but disappeared altogether by middle childhood. For height, shared environmental correlations persisted from infancy to adulthood.
CONCLUSIONS
Our results suggest that the genes affecting BMI change over childhood and adolescence leading to decreasing age-to-age genetic correlations. This change is especially visible from early to middle childhood indicating that new genetic factors start to affect BMI in middle childhood. Identifying mediating pathways of these genetic factors can open possibilities for interventions, especially for those children with high genetic predisposition to adult obesity.
Identifiants
pubmed: 35945263
doi: 10.1038/s41366-022-01202-3
pii: 10.1038/s41366-022-01202-3
pmc: PMC9492534
doi:
Types de publication
Journal Article
Twin Study
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
1901-1909Subventions
Organisme : NIMH NIH HHS
ID : R01 MH081813
Pays : United States
Organisme : NICHD NIH HHS
ID : R01 HD066040
Pays : United States
Organisme : NIMH NIH HHS
ID : R01 MH092377
Pays : United States
Organisme : NIA NIH HHS
ID : T32 AG052371
Pays : United States
Organisme : NIDA NIH HHS
ID : T32 DA017637
Pays : United States
Organisme : Medical Research Council
ID : MR/M021475/1
Pays : United Kingdom
Organisme : Medical Research Council
ID : G0901245
Pays : United Kingdom
Informations de copyright
© 2022. The Author(s).
Références
GBD 2015 Risk Factors Collaborators. Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990–2015: a systematic analysis for the Global Burden of Disease Study 2015. Lancet. 2016;388:1659–724.
doi: 10.1016/S0140-6736(16)31679-8
NCD Risk Factor Collaboration (NCD-RisC). 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. 2017;390:2627–42.
Rokholm B, Baker JL, Sørensen TIA. The levelling off of the obesity epidemic since the year 1999-a review of evidence and perspectives. Obes Rev. 2010;11:835–46.
pubmed: 20973911
doi: 10.1111/j.1467-789X.2010.00810.x
Baker JL, Olsen LW, Sørensen TIA. Childhood body-mass index and the risk of coronary heart disease in adulthood. N Engl J Med. 2007;357:2329–37.
pubmed: 18057335
pmcid: 3062903
doi: 10.1056/NEJMoa072515
Bjerregaard LG, Jensen BW, Ängquist L, Osler M, Sørensen TIA, Baker JL. Change in overweight from childhood to early adulthood and risk of type 2 diabetes. N Engl J Med. 2018;378:1302–12.
pubmed: 29617589
doi: 10.1056/NEJMoa1713231
Lloyd LJ, Langley-Evans SC, McMullen S. Childhood obesity and risk of the adult metabolic syndrome: a systematic review. Int J Obes. 2012;36:1–11.
doi: 10.1038/ijo.2011.186
Bayer O, Krüger H, von Kries R, Toschke AM. Factors associated with tracking of BMI: a meta-regression analysis on BMI tracking. Obesity. 2011;19:1069–76.
pubmed: 20948517
doi: 10.1038/oby.2010.250
Singh AS, Mulder C, Twisk JWR, van Mechelen W, Chinapaw MJM. Tracking of childhood overweight into adulthood: a systematic review of the literature. Obes Rev. 2008;9:474–88.
pubmed: 18331423
doi: 10.1111/j.1467-789X.2008.00475.x
Langeveld M, DeVries JH. The long-term effect of energy restricted diets for treating obesity. Obesity. 2015;23:1529–38.
pubmed: 26179364
doi: 10.1002/oby.21146
Silventoinen K, Jelenkovic A, Sund R, Hur YM, 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. Am J Clin Nutr. 2016;104:371–9.
pubmed: 27413137
pmcid: 4962159
doi: 10.3945/ajcn.116.130252
Silventoinen K, Jelenkovic A, Sund R, Yokoyama Y, Hur YM, 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. Am J Clin Nutr. 2017;106:457–66.
pubmed: 28679550
pmcid: 5525120
doi: 10.3945/ajcn.117.153643
Vogelezang S, Bradfield JP, Ahluwalia TS, Curtin JA, Lakka TA, Grarup N, et al. Novel loci for childhood body mass index and shared heritability with adult cardiometabolic traits. PLoS Genet. 2020;16:e1008718.
pubmed: 33045005
pmcid: 7581004
doi: 10.1371/journal.pgen.1008718
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;27:3641–9.
pubmed: 30124842
pmcid: 6488973
doi: 10.1093/hmg/ddy271
Silventoinen K, Pietiläinen KH, Tynelius P, Sørensen TIA, Kaprio J, Rasmussen F. Genetic and environmental factors in relative weight from birth to age 18: the Swedish Young Male Twins Study. Int J Obes. 2007;31:615–21.
doi: 10.1038/sj.ijo.0803577
Silventoinen K, Bartels M, Posthuma D, Estourgie-van Burk GF, Willemsen G, van Beijsterveldt TCEM, et al. Genetic regulation of growth in height and weight from 3 to 12 years of age: a longitudinal study of Dutch twin children. Twin Res Hum Genet. 2007;10:354–63.
pubmed: 17564525
doi: 10.1375/twin.10.2.354
Cornes BK, Zhu G, Martin NG. Sex differences in genetic variation in weight: a longitudinal study of body mass index in adolescent twins. Behav Genet. 2007;37:648–60.
pubmed: 17896175
doi: 10.1007/s10519-007-9165-0
Haworth CMA, Carnell S, Meaburn EL, Davis OSP, Plomin R, Wardle J. Increasing heritability of BMI and stronger associations with the FTO gene over childhood. Obesity. 2008;16:2663–8.
pubmed: 18846049
doi: 10.1038/oby.2008.434
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.
pubmed: 20607380
doi: 10.1007/s10519-010-9380-y
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–.e9.
pubmed: 31002795
pmcid: 6661115
doi: 10.1016/j.cell.2019.03.028
Silventoinen K, Jelenkovic A, Sund R, Honda C, Aaltonen S, Yokoyama Y, et al. The CODATwins Project: The cohort description of COllaborative Project of Development of Anthropometrical Measures in Twins to study macro-environmental variation in genetic and environmental effects on anthropometric traits. Twin Res Hum Genet. 2015;18:348–60.
pubmed: 26014041
pmcid: 4696543
doi: 10.1017/thg.2015.29
Silventoinen K, Jelenkovic A, Yokoyama Y, Sund R, Sugawara M, Tanaka M, et al. The CODATwins Project: The current status and recent findings of COllaborative Project of Development of Anthropometrical Measures in Twins. Twin Res Hum Genet. 2019;22:800–8.
pubmed: 31364586
pmcid: 7775258
doi: 10.1017/thg.2019.35
Posthuma D, Beem AL, de Geus EJC, van Baal GCM, von Hjelmborg JB, Iachine I, et al. Theory and practice in quantitative genetics. Twin Res. 2003;6:361–76.
pubmed: 14624720
doi: 10.1375/136905203770326367
Neale MC, Hunter MD, Pritikin JN, Zahery M, Brick TR, Kirkpatrick RM, et al. OpenMx 2.0: Extended structural equation and statistical modeling. Psychometrika. 2016;81:535–49.
pubmed: 25622929
doi: 10.1007/s11336-014-9435-8
Jelenkovic A, Yokoyama Y, Sund R, Honda C, Bogl LH, Aaltonen S, et al. Zygosity differences in height and body mass index of twins from infancy to old age: A study of the CODATwins project. Twin Res Hum Genet. 2015;18:557–70.
pubmed: 26337138
pmcid: 4605819
doi: 10.1017/thg.2015.57
Jelenkovic A, Sund R, Hur YM, Yokoyama Y, Hjelmborg JVB, Möller S, et al. Genetic and environmental influences on height from infancy to early adulthood: An individual-based pooled analysis of 45 twin cohorts. Sci Rep. 2016;6:28496.
pubmed: 27333805
pmcid: 4917845
doi: 10.1038/srep28496
Kaprio J, Silventoinen K. Advanced methods in twin studies. Methods Mol Biol. 2011;713:143–52.
pubmed: 21153617
doi: 10.1007/978-1-60327-416-6_11
Malina M, Bouchard C, Bar-Or O. Growth, Maturation and Physical Growth. 2. Champaign, IL, USA: Human Kinetics; 2004.
Hasselbalch AL, Benyamin B, Visscher PM, Heitmann BL, Kyvik KO, Sørensen TIA. Common genetic components of obesity traits and serum leptin. Obesity. 2008;16:2723–9.
pubmed: 18927547
doi: 10.1038/oby.2008.440
Purcell S. Variance components models for gene-environment interaction in twin analysis. Twin Res. 2002;5:554–71.
pubmed: 12573187
doi: 10.1375/136905202762342026
Sovio U, Mook-Kanamori DO, Warrington NM, Lawrence R, Briollais L, Palmer CNA, et al. Association between common variation at the FTO locus and changes in body mass index from infancy to late childhood: the complex nature of genetic association through growth and development. PLoS Genet. 2011;7:e1001307.
pubmed: 21379325
pmcid: 3040655
doi: 10.1371/journal.pgen.1001307
Warrington NM, Howe LD, Paternoster L, Kaakinen M, Herrala S, Huikari V, et al. A genome-wide association study of body mass index across early life and childhood. Int J Epidemiol. 2015;44:700–12.
pubmed: 25953783
pmcid: 4469798
doi: 10.1093/ije/dyv077
Helgeland Ø, Vaudel M, Juliusson PB, Lingaas Holmen O, Juodakis J, Bacelis J, et al. Genome-wide association study reveals dynamic role of genetic variation in infant and early childhood growth. Nat Commun. 2019;10:4448.
pubmed: 31575865
pmcid: 6773698
doi: 10.1038/s41467-019-12308-0
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.
pubmed: 25673413
pmcid: 4382211
doi: 10.1038/nature14177
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.
pubmed: 29273807
doi: 10.1038/s41588-017-0011-x
Lenard NR, Berthoud HR. Central and peripheral regulation of food intake and physical activity: pathways and genes. Obesity. 2008;16:S11–22.
pubmed: 19190620
doi: 10.1038/oby.2008.511
Mehlig K, Holmberg C, Bogl LH, Erhardt E, Hadjigeorgiou C, Hebestreit A, et al. Weight status and BMI-related traits in adolescent friendship groups and role of sociodemographic factors: The European IDEFICS/I.Family Cohort. Obes Facts. 2021;14:121–30.
pubmed: 33352571
doi: 10.1159/000512356
Herle M, Abdulkadir M, Hübel C, Ferreira DS, Bryant-Waugh R, Loos RJF, et al. The genomics of childhood eating behaviours. Nat Hum Behav. 2021;5:625–30.
pubmed: 33432183
pmcid: 7610819
doi: 10.1038/s41562-020-01019-y
Aaltonen S, Kujala UM, Kaprio J. Factors behind leisure-time physical activity behavior based on Finnish twin studies: the role of genetic and environmental influences and the role of motives. Biomed Res Int. 2014;2014:931820.
pubmed: 24809061
pmcid: 3997869
doi: 10.1155/2014/931820
Schnurr TM, Stallknecht BM, Sørensen TIA, Kilpeläinen TO, Hansen T. Evidence for shared genetics between physical activity, sedentary behaviour and adiposity-related traits. Obes Rev. 2021;22:e13182.
pubmed: 33354910
doi: 10.1111/obr.13182
Péneau S, González-Carrascosa R, Gusto G, Goxe D, Lantieri O, Fezeu L, et al. Age at adiposity rebound: determinants and association with nutritional status and the metabolic syndrome at adulthood. Int J Obes. 2016;40:1150–6.
doi: 10.1038/ijo.2016.39
Couto Alves A, De Silva NMG, Karhunen V, Sovio U, Das S, Taal HR, et al. GWAS on longitudinal growth traits reveals different genetic factors influencing infant, child, and adult BMI. Sci Adv. 2019;5:eaaw3095.
pubmed: 31840077
pmcid: 6904961
doi: 10.1126/sciadv.aaw3095
Switkowski KM, Jacques PF, Must A, Fleisch A, Oken E. Associations of protein intake in early childhood with body composition, height, and insulin-like growth factor I in mid-childhood and early adolescence. Am J Clin Nutr. 2019;109:1154–63.
pubmed: 30869114
pmcid: 6462426
doi: 10.1093/ajcn/nqy354
Shrewsbury V, Wardle J. Socioeconomic status and adiposity in childhood: a systematic review of cross-sectional studies 1990–2005. Obesity. 2008;16:275–84.
pubmed: 18239633
doi: 10.1038/oby.2007.35
Silventoinen K, Jelenkovic A, Latvala A, Yokoyama Y, Sund R, Sugawara M, et al. Parental education and genetics of BMI from infancy to old age: A pooled analysis of 29 twin cohorts. Obesity. 2019;27:855–65.
pubmed: 30950584
Hüls A, Wright MN, Bogl LH, Kaprio J, Lissner L, Molnár D, et al. Polygenic risk for obesity and its interaction with lifestyle and sociodemographic factors in European children and adolescents. Int J Obes. 2021;45:1321–30.
doi: 10.1038/s41366-021-00795-5
Bell JA, Carslake D, O’Keeffe LM, Frysz M, Howe LD, Hamer M, et al. Associations of body mass and fat indexes with cardiometabolic traits. J Am Coll Cardiol. 2018;72:3142–54.
pubmed: 30545453
pmcid: 6290112
doi: 10.1016/j.jacc.2018.09.066
Nelson TL, Brandon DT, Wiggins SA, Whitfield KE. Genetic and environmental influences on body-fat measures among African-American twins. Obes Res. 2002;10:733–9.
pubmed: 12181381
doi: 10.1038/oby.2002.100
Silventoinen K, Kaprio J, Lahelma E, Viken RJ, Rose RJ. Assortative mating by body height and BMI: Finnish twins and their spouses. Am J Hum Biol. 2003;15:620–7.
pubmed: 12953173
doi: 10.1002/ajhb.10183