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A structured approach to evaluating life course hypotheses: Moving beyond analyses of exposed versus unexposed in the omics context

Zhu, Yiwen; Simpkin, Andrew J.; Suderman, Matthew J.; Lussier, Alexandre A.; Walton, Esther; Dunn, Erin C.; Smith, Andrew D. A. C.

A structured approach to evaluating life course hypotheses: Moving beyond analyses of exposed versus unexposed in the omics context Thumbnail


Authors

Yiwen Zhu

Andrew J. Simpkin

Matthew J. Suderman

Alexandre A. Lussier

Esther Walton

Erin C. Dunn



Abstract

The structured life course modeling approach (SLCMA) is a theory-driven analytic method that empirically compares multiple prespecified life course hypotheses characterizing time-dependent exposure-outcome relationships to determine which theory best fits the observed data. In this study, we performed simulations and empirical analyses to evaluate the performance of the SLCMA when applied to genome-wide DNA methylation (DNAm). Using simulations, we compared five statistical inference tests used with SLCMA (n=700), assessing the familywise error rate, statistical power, and confidence interval coverage to determine whether inference based on these tests was valid in the presence of substantial multiple testing and small effects, two hallmark challenges of inference from omics data. In the empirical analyses, we evaluated the time-dependent relationship of childhood abuse with genome-wide DNAm (n=703). In simulations, selective inference and max-|t|-test performed best: both controlled family-wise error rate and yielded moderate statistical power. Empirical analyses using SLCMA revealed time-dependent effects of childhood abuse on DNAm. Our findings show that SLCMA, applied and interpreted appropriately, can be used in high-throughput settings to examine time-dependent effects underlying exposure-outcome relationships over the life course. We provide recommendations for applying the SLCMA in omics settings and encourage researchers to move beyond analyses of exposed versus unexposed.

Journal Article Type Article
Acceptance Date Oct 28, 2020
Online Publication Date Oct 30, 2020
Publication Date Jun 1, 2021
Deposit Date Dec 18, 2020
Publicly Available Date Oct 31, 2021
Print ISSN 0002-9262
Electronic ISSN 1476-6256
Publisher Oxford University Press (OUP)
Peer Reviewed Peer Reviewed
Volume 190
Issue 6
Pages 1101-1112
DOI https://doi.org/10.1093/aje/kwaa246
Keywords life course, structured approach, ALSPAC, omics, DNA methylation, post-selection inference
Public URL https://uwe-repository.worktribe.com/output/6959612
Publisher URL https://academic.oup.com/aje/advance-article-abstract/doi/10.1093/aje/kwaa246/5943467

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Copyright Statement
Zhu, Y., Simpkin, A. J., Suderman, M. J., Lussier, A. A., Walton, E., Dunn, E. C., & Smith, A. D. A. C. (2021). A structured approach to evaluating life course hypotheses: Moving beyond analyses of exposed versus unexposed in the omics context. American Journal of Epidemiology, 190(6), 1101-1112. Reproduced by permission of Oxford University Press. The published article is available here: https://doi.org/10.1093/aje/kwaa246






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