ArticleAmerican journal of epidemiology2021
A Structured Approach to Evaluating Life-Course Hypotheses: Moving Beyond Analyses of Exposed Versus Unexposed in the -Omics Context.
Article in American journal of epidemiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
16 citing papers in PubMed.
- Social Connection and Epigenetic Aging: Insights from DNA Methylation Clocks.Annals of the New York Academy of Sciences · 2026Article
- Timing effects in the association between childhood and adolescent bullying victimisation with late adolescence and emerging adulthood depressive symptoms.European child & adolescent psychiatry · 2026Article
- Timing of adverse childhood experiences shapes epigenetic ageing and life-history outcomes.Scientific reports · 2026Article
- Accumulation and sensitive period effects for childhood abuse and financial hardship on depressive symptoms in late adolescence.Journal of mood and anxiety disorders · 2026Article
- Prenatal Alcohol Exposure and Mental Health Outcomes: A Two-Sample Mendelian Randomization Study of DNA Methylation Signatures.medRxiv : the preprint server for health sciences · 2026Article
- Development of Life Course Exposure Estimates Using Geospatial Data and Residence History.International journal of environmental research and public health · 2025Article
- Childhood adversity and adolescent mental health: Examining cumulative and specificity effects across contexts and developmental timing.Development and psychopathology · 2025Article
- Maximizing insights from longitudinal epigenetic age data: simulations, applications, and practical guidance.Clinical epigenetics · 2024Article
- A Bayesian functional approach to test models of life course epidemiology over continuous time.International journal of epidemiology · 2024Article
- Association between the timing of childhood adversity and epigenetic patterns across childhood and adolescence: findings from the Avon Longitudinal Study of Parents and Children (ALSPAC) prospective cohort.The Lancet. Child & adolescent health · 2023Article
- Testing lifecourse theories characterising associations between maternal depression and offspring depression in emerging adulthood: the Avon Longitudinal Study of Parents and Children.Journal of child psychology and psychiatry, and allied disciplines · 2023Article
- Sensitive Periods for the Effect of Childhood Adversity on DNA Methylation: Updated Results From a Prospective, Longitudinal Study.Biological psychiatry global open science · 2023Article
- Socioeconomic changes predict genome-wide DNA methylation in childhood.Human molecular genetics · 2023Article
- Incorporating interactions into structured life course modelling approaches: A simulation study and applied example of the role of access to green space and socioeconomic position on cardiometabolic health.medRxiv : the preprint server for health sciences · 2023Article
- Updates to data versions and analytic methods influence the reproducibility of results from epigenome-wide association studies.Epigenetics · 2022Article
- Associations between indicators of socioeconomic position and DNA methylation: a scoping review.Clinical epigenetics · 2021Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
The structured life-course modeling approach (SLCMA) is a theory-driven analytical 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 genomewide DNA methylation (DNAm). Using simulations (n = 700), we compared 5 statistical inference tests used with SLCMA, 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-2 hallmark challenges of inference from -omics data. In the empirical analyses (n = 703), we evaluated the time-dependent relationship between childhood abuse and genomewide DNAm. In simulations, selective inference and the max-|t|-test performed best: Both controlled the familywise 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 individuals.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.