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Both cross-sectional (between-subject) and longitudinal (within-subject) approaches can contribute to answering this question but come with distinct strengths and limitations. Here we show that age-varying genetic effects obtained from the two designs were highly concordant in direction (84.21% of the 57 identified variants) but showed only moderate agreement in effect-size magnitude (Pearson\u02bcs\n                    <jats:inline-formula>\n                      <jats:alternatives>\n                        <jats:tex-math>$$r=$$<\/jats:tex-math>\n                        <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\">\n                          <mml:mrow>\n                            <mml:mi>r<\/mml:mi>\n                            <mml:mo>=<\/mml:mo>\n                          <\/mml:mrow>\n                        <\/mml:math>\n                      <\/jats:alternatives>\n                    <\/jats:inline-formula>\n                    0.51). Confounding by gene-by-birth year effects accounted for the largest proportion of variance in effect-size differences across single-nucleotide polymorphisms (SNPs) with age-varying effects between designs (70.8%). Participation bias accounted for an additional 11.6%, whereas unmodeled nonlinear age trajectories contributed minimally to these differences (4.2%). Overall, our results demonstrate that both cross-sectional and longitudinal designs can yield different estimates of age-varying genetic effects, principally due to cohort confounding and participation bias. As neither approach is immune to design-specific limitations, we recommend integrating both designs for robust inference, to help improve interpretability and more accurately characterize how genetic effects on complex traits change over the lifespan.\n                  <\/jats:p>","DOI":"10.1038\/s43587-026-01232-w","type":"journal-article","created":{"date-parts":[[2026,10,6]],"date-time":"2026-10-06T09:02:02Z","timestamp":1791277322000},"page":"2253-2264","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Design and model choices shape inference of age-varying genetic effects on complex traits"],"prefix":"10.1038","volume":"6","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4846-2741","authenticated-orcid":false,"given":"Tabea","family":"Schoeler","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Simon","family":"Wiegrebe","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Thomas W.","family":"Winkler","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8285-7523","authenticated-orcid":false,"given":"Zolt\u00e1n","family":"Kutalik","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,10,6]]},"reference":[{"key":"1232_CR1","doi-asserted-by":"publisher","first-page":"324","DOI":"10.1038\/s42003-023-04679-4","volume":"6","author":"H-U Jung","year":"2023","unstructured":"Jung, H.-U. et al. 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