{
  "abstract": "Understanding how genetic influences on complex traits change with age is a fundamental question in genetic epidemiology. 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's r= 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.",
  "abstract_shown": true,
  "affiliations": [
    "Department of Computational Biology, University of Lausanne, Lausanne, Switzerland. tabea.schoeler@unil.ch.",
    "Department of Clinical, Educational and Health Psychology, University College London, London, UK. tabea.schoeler@unil.ch.",
    "Swiss Institute of Bioinformatics, Lausanne, Switzerland. tabea.schoeler@unil.ch.",
    "University Center for Primary Care and Public Health, Lausanne, Switzerland. tabea.schoeler@unil.ch.",
    "Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany.",
    "Statistical Consulting Unit StaBLab, Department of Statistics, LMU Munich, Munich, Germany.",
    "Department of Computational Biology, University of Lausanne, Lausanne, Switzerland. zoltan.kutalik@unil.ch.",
    "Swiss Institute of Bioinformatics, Lausanne, Switzerland. zoltan.kutalik@unil.ch.",
    "University Center for Primary Care and Public Health, Lausanne, Switzerland. zoltan.kutalik@unil.ch."
  ],
  "article_type": "research article",
  "arxiv": null,
  "author_total": 4,
  "authors": [
    {
      "affs": [
        0,
        1,
        2,
        3
      ],
      "name": "Tabea Schoeler",
      "orcid": "0000-0003-4846-2741"
    },
    {
      "affs": [
        4,
        5
      ],
      "name": "Simon Wiegrebe"
    },
    {
      "affs": [
        4
      ],
      "name": "Thomas W Winkler"
    },
    {
      "affs": [
        6,
        7,
        8
      ],
      "name": "Zoltán Kutalik",
      "orcid": "0000-0001-8285-7523"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/7xj8wneny6wyw.bib",
  "cited_by": 1,
  "doi": "10.1038/s43587-026-01232-w",
  "fulltext_url": "https://europepmc.org/articles/PMC13661259",
  "id": "7xj8wneny6wyw",
  "issns": [
    "2662-8465"
  ],
  "landing_url": "https://europepmc.org/article/MED/42839093",
  "language": "eng",
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "1311|Genetic Associations and Epidemiology"
    ]
  ],
  "openalex": "W7220690052",
  "pdf_url": "https://europepmc.org/articles/PMC13661259?pdf=render",
  "pmcid": "PMC13661259",
  "pmid": "42839093",
  "published": "2026-10-06",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/7xj8wneny6wyw.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:18:02Z",
      "native_id": "MED:42839093",
      "source": "europepmc",
      "url": "https://europepmc.org/article/MED/42839093"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "openalex:1311|Genetic Associations and Epidemiology",
      "subfield": "genetics-genomics"
    }
  ],
  "title": "Design and model choices shape inference of age-varying genetic effects on complex traits.",
  "title_text": "Design and model choices shape inference of age-varying genetic effects on complex traits.",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:18:02Z",
  "url": "https://research.draconitic.com/paper/7xj8wneny6wyw",
  "venue": "Nature aging",
  "versions": []
}