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.

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.

Citation

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. https://doi.org/10.1093/aje/kwaa246

• 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