ArticleHuman heredity2011
Causal models for investigating complex disease: I. A primer.
Article in Human heredity, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- AGAP1-associated endolysosomal trafficking abnormalities link gene-environment interactions in neurodevelopmental disorders.Disease models & mechanisms · 2023Article
- AGAP1-associated endolysosomal trafficking abnormalities link gene-environment interactions in a neurodevelopmental disorder.bioRxiv : the preprint server for biology · 2023Article
- Symptoms of mania and anxiety do not contribute to suicidal ideation or behavior in the presence of bipolar depression.Psychiatry research · 2022Article
- Sub-multiplicative interaction between polygenic risk score and household coal use in relation to lung adenocarcinoma among never-smoking women in Asia.Environment international · 2021Article
- Segregation Analysis of Genotyped and Family-Phased, Long Range MHC Classical Class I and Class II Haplotypes in 5 Families With Type 1 Diabetes Proband in the United Arab Emirates.Frontiers in genetics · 2021Article
- A stochastic epigenetic Mendelian oligogenic disease model for type 1 diabetes.Journal of autoimmunity · 2019Article
- Source Attribution and Risk Assessment of Antimicrobial Resistance.Microbiology spectrum · 2018Review
- Update on the State of the Science for Analytical Methods for Gene-Environment Interactions.American journal of epidemiology · 2017Article
- Rare high-impact disease variants: properties and identifications.Genetics research · 2016Article
- Reflections on the Field of Human Genetics: A Call for Increased Disease Genetics Theory.Frontiers in genetics · 2016Article
- Article
- Causal models for investigating complex genetic disease: II. what causal models can tell us about penetrance for additive, heterogeneity, and multiplicative two-locus models.Human heredity · 2011Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
BACKGROUND/
aimsTo illustrate the utility of causal models for research in genetic epidemiology and statistical genetics. Causal models are increasingly applied in risk factor epidemiology, economics, and health policy, but seldom used in statistical genetics or genetic epidemiology. Unlike the statistical models usually used in genetic epidemiology, causal models are explicitly formulated in terms of cause and effect relationships occurring at the individual level.
methodsWe describe two causal models, the sufficient component cause model and the potential outcomes model, and show how key concepts in genetic epidemiology, including penetrance, phenocopies, genetic heterogeneity, etiologic heterogeneity, gene-gene interaction, and gene-environment interaction, can be framed in terms of these causal models. We also illustrate how potential outcomes models can provide insight into the potential for confounding and bias in the measurement of causal effects in genetic studies.
resultsOur analysis illustrates how causal models can elucidate the relationships among underlying causal mechanisms and measures obtained from statistical analysis of observed data.
conclusionCausal models can enhance research aimed at identifying causal genes.
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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.