{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,18]],"date-time":"2026-06-18T17:54:47Z","timestamp":1781805287906,"version":"3.54.5"},"reference-count":77,"publisher":"Public Library of Science (PLoS)","issue":"6","license":[{"start":{"date-parts":[[2026,6,18]],"date-time":"2026-06-18T00:00:00Z","timestamp":1781740800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000265","name":"Medical Research Council","doi-asserted-by":"publisher","award":["MR\/V002147\/1"],"award-info":[{"award-number":["MR\/V002147\/1"]}],"id":[{"id":"10.13039\/501100000265","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000269","name":"Economic and Social Research Council","doi-asserted-by":"publisher","award":["ES\/M001660\/1"],"award-info":[{"award-number":["ES\/M001660\/1"]}],"id":[{"id":"10.13039\/501100000269","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100005416","name":"Norwegian Research Council","doi-asserted-by":"crossref","award":["295989"],"award-info":[{"award-number":["295989"]}],"id":[{"id":"10.13039\/501100005416","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["www.plosgenetics.org"],"crossmark-restriction":false},"short-container-title":["PLoS Genet"],"abstract":"<jats:p>\n                    Obesity is a highly heritable trait, but rising obesity rates suggest environmental change is also of profound importance. We conducted a cross-cohort analysis to examine how associations between genetic risk for high BMI and observed BMI differed in four British birth cohorts born before and amidst the obesity epidemic (1946, 1958, 1970 and ~2001; N\u2009=\u200919,379). BMI (kg\/m\n                    <jats:sup>2<\/jats:sup>\n                    ) was measured at multiple time points between ages 3 and 69 years. We used polygenic indices (PGI) derived from GWAS of adulthood and childhood BMI, respectively, with mixed effects models used to estimate associations with mean BMI and quantile regression used to assess associations across the distribution of BMI. We further used linear regression to estimate PGI-heritability (PGI-h\n                    <jats:sup>2<\/jats:sup>\n                    ; incremental variance explained by the PGI) and Genomic Relatedness Restricted Maximum Likelihood (GREML) to calculate SNP-heritability (SNP-h\n                    <jats:sup>2<\/jats:sup>\n                    ) by cohort and age. Adulthood BMI PGI was associated with BMI in all cohorts and ages but was more strongly associated with BMI in more recently born generations, e.g., at age 16y, a 1 SD increase in the adulthood PGI was associated with 0.46 kg\/m\n                    <jats:sup>2<\/jats:sup>\n                    (0.37, 0.55) higher BMI in the 1946c and 0.90 kg\/m\n                    <jats:sup>2<\/jats:sup>\n                    (0.83, 0.97) higher BMI in the 2001c. Cross-cohort differences widened with age and were larger at the upper end of the BMI distribution, indicating disproportionate increases in obesity in more recent generations for those with higher PGIs. Differences were also observed when using the childhood PGI. There were no clear, consistent differences in PGI-h\n                    <jats:sup>2<\/jats:sup>\n                    or SNP-h\n                    <jats:sup>2<\/jats:sup>\n                    , possibly due to limited statistical power, except that PGI-h\n                    <jats:sup>2<\/jats:sup>\n                    was highest in the most recently born cohort (2001c) when using the most predictive PGI for adulthood BMI. Findings highlight how the environment can modify genetic associations; genetic associations with BMI differed by birth cohort, age, and outcome centile.\n                  <\/jats:p>","DOI":"10.1371\/journal.pgen.1012138","type":"journal-article","created":{"date-parts":[[2026,6,18]],"date-time":"2026-06-18T17:21:55Z","timestamp":1781803315000},"page":"e1012138","update-policy":"https:\/\/doi.org\/10.1371\/journal.pgen.corrections_policy","source":"Crossref","is-referenced-by-count":0,"title":["Genetic risk for high body mass index before and amidst the obesity epidemic: Cross-cohort analysis of four british birth cohort studies"],"prefix":"10.1371","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6347-5121","authenticated-orcid":true,"given":"Liam","family":"Wright","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2460-0508","authenticated-orcid":true,"given":"Neil M.","family":"Davies","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gemma","family":"Shireby","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3825-2487","authenticated-orcid":true,"given":"Dylan M.","family":"Williams","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tim T.","family":"Morris","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"David","family":"Bann","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2026,6,18]]},"reference":[{"issue":"3","key":"pgen.1012138.ref001","doi-asserted-by":"crossref","first-page":"221","DOI":"10.1016\/S2213-8587(24)00316-4","article-title":"Definition and diagnostic criteria of clinical obesity","volume":"13","author":"F Rubino","year":"2025","journal-title":"Lancet Diabetes Endocrinol"},{"key":"pgen.1012138.ref002","article-title":"The global burden of disease attributable to high body mass index in 195 countries and territories, 1990\u20132017: An analysis of the Global Burden of Disease Study","volume":"17","author":"H Dai","year":"2020","journal-title":"PLoS Med"},{"key":"pgen.1012138.ref003","unstructured":"World Obesity Federation. 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