On the Replication of Genetic Associations: Timing Can Be Everything

The failure of researchers to replicate genetic-association findings is most commonly attributed to insufficient statistical power, population stratification, or various forms of between-study heterogeneity or environmental influences.1 Here, we illustrate another potential cause for nonreplications...

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Veröffentlicht in:American journal of human genetics 2008-04, Vol.82 (4), p.849-858
Hauptverfasser: Lasky-Su, Jessica, Lyon, Helen N., Emilsson, Valur, Heid, Iris M., Molony, Cliona, Raby, Benjamin A., Lazarus, Ross, Klanderman, Barbara, Soto-Quiros, Manuel E., Avila, Lydiana, Silverman, Edwin K., Thorleifsson, Gudmar, Thorsteinsdottir, Unnur, Kronenberg, Florian, Vollmert, Caren, Illig, Thomas, Fox, Caroline S., Levy, Daniel, Laird, Nan, Ding, Xiao, McQueen, Matt B., Butler, Johannah, Ardlie, Kristin, Papoutsakis, Constantina, Dedoussis, George, O'Donnell, Christopher J., Wichmann, H.-Erich, Celedón, Juan C., Schadt, Eric, Hirschhorn, Joel, Weiss, Scott T., Stefansson, Kari, Lange, Christoph
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Sprache:eng
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Zusammenfassung:The failure of researchers to replicate genetic-association findings is most commonly attributed to insufficient statistical power, population stratification, or various forms of between-study heterogeneity or environmental influences.1 Here, we illustrate another potential cause for nonreplications that has so far not received much attention in the literature. We illustrate that the strength of a genetic effect can vary by age, causing “age-varying associations.” If not taken into account during the design and the analysis of a study, age-varying genetic associations can cause nonreplication. By using the 100K SNP scan of the Framingham Heart Study, we identified an age-varying association between a SNP in ROBO1 and obesity and hypothesized an age-gene interaction. This finding was followed up in eight independent samples comprising 13,584 individuals. The association was replicated in five of the eight studies, showing an age-dependent relationship (one-sided combined p = 3.92 × 10−9, combined p value from pediatric cohorts = 2.21 × 10−8, combined p value from adult cohorts = 0.00422). Furthermore, this study illustrates that it is difficult for cross-sectional study designs to detect age-varying associations. If the specifics of age- or time-varying genetic effects are not considered in the selection of both the follow-up samples and in the statistical analysis, important genetic associations may be missed.
ISSN:0002-9297
1537-6605
1537-6605
DOI:10.1016/j.ajhg.2008.01.018