Powerful designs for genetic association studies that consider twins and sibling pairs with discordant genotypes
Abstract
Genetic association studies are becoming commonplace due to the availability of cost‐effective yet sophisticated DNA sequencing and genotyping resources and technologies. In addition, technologies designed to identify molecular and subclinical phenotypes that reflect disease pathogenesis are continually being developed and refined (consider, e.g., imaging technologies, microarray‐based gene expression and proteomic platforms, histological analyses of excised tissues, etc.). Unfortunately, the large‐scale use of many of these molecular and subclinical phenotyping technologies in genetic association studies is difficult logistically and is currently cost‐prohibitive. In this paper, we consider efficient designs for testing the association between particular genetic variations and expensive, yet appropriate, subclinical phenotypes of relevance to a disease that take advantage of twins or sibling pairs discordant for genotypes at the locus (or loci) being tested. We demonstrate that including genotypically discordant twins or siblings in an association study can result in a substantial increase in power over designs that use monozygotic twins or only unrelated individuals. We ultimately argue that, from a practical standpoint, sampling from existing family or twin‐based cohorts in which: (1) follow‐up studies of a genetic association are warranted in order to assess the in vivo significance of an association with respect to more refined pathological phenotypes; and/or (2) large‐scale, genome‐wide linkage and association studies have been pursued that have focused on clinical endpoints for which the study subjects have consented to more elaborate follow‐up studies, is a powerful way to test associations. Genet. Epidemiol. 2007. © 2007 Wiley‐Liss, Inc.
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Approaches that capture subtle synergistic effects among many loci in a region, or among different variant types affecting gene function, such as sequence- or functional-similarity-based methods, are probably also suitable.
“However, methods which can account for subtle synergistic effects of many loci within a defined region and/or different forms of variation that might contribute to gene function, such as those rooted in sequence or functional similarity56, 57, 87, 88 are also likely to be appropriate.”
From Statistical analysis strategies for association studies involving rare variants (2010) · cites this paper as [87]
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References 33 · Cited by 12
- Authors
- Wessel, J., Schork, A. J., Tiwari, H. K., & Schork, N. J.
- Affiliations
- Scripps Research Institute (US)
- University of California San Diego (US)
- University of Alabama at Birmingham (US)
- Corresponding author
- Schork, Nicholas J.
- Venue
- Genetic Epidemiology
- Publisher
- Wiley
- Published
- 2007-06-04
- Volume
- 31
- Issue
- 7
- Pages
- 789-796
- ISSN
- 0741-0395 (ISSN-L)
- 1098-2272
- OpenAlex
- W2029921560
- Cited by
- 12
- References
- 33
- Citations by year
- 2026: 1 · 2020: 3 · 2016: 1 · 2014: 1
- FWCI
- 0.89
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Genetic Epidemiology (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health (5r01gm074913-05)
- National Institute on Aging (U19AG023122)
- National Heart, Lung, and Blood Institute (5R01 HL/MH 065571-02, U01HL064777, R01HL070137, R01 HL074730-02S, R01HL074730, R01HL055673)
- National Institute of Mental Health (R01MH065571)
- National Institute of General Medical Sciences (R01 GM74913)
- National Institute of Diabetes and Digestive and Kidney Diseases (R01 DK 52431, R01DK052431)
- National Center for Research Resources (P20RR016430)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Keywords
- statistical power, discordant twins, monozygotic twins, family-based cohort, follow-up study
- MeSH terms
- Follow-Up Studies, Gene Expression Regulation, Genotype, Humans, Models, Genetic, Twins, Monozygotic, Linkage Disequilibrium, Genome, Human, Sequence Analysis, DNA, Genetic Predisposition to Disease, Proteome, Siblings, Quantitative Trait Loci
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