Scientific Publications

Genetic association studies of complex traits: design and analysis issues.

Publication TypeJournal Article
AuthorsNewton-Cheh, C., and Hirschhorn JN
AbstractMost common diseases and many important quantitative traits are complex genetic traits, with multiple genetic and environmental variables contributing to the observed phenotype. Because of the multi-factorial nature of complex traits, each individual genetic variant generally has only a modest effect, and the interaction of genetic variants with each other or with environmental factors can potentially be quite important in determining the observed phenotype. It remains largely unknown what sort of genetic variants explain inherited variation in complex traits, but recent evidence suggests that common genetic variants will explain at least some of the inherited variation in susceptibility to common disease. Genetic association studies, in which the allele or genotype frequencies at markers are determined in affected individuals and compared with those of controls (either population- or family-based), may be an effective approach to detecting the effects of common variants with modest effects. With the explosion in single nucleotide polymorphism (SNP) discovery and genotyping technologies, large-scale association studies have become feasible, and small-scale association studies have become plentiful. We review the different types of association studies and discuss issues that are important to consider when performing and interpreting association studies of complex genetic traits. Heritable and accurately measured phenotypes, carefully matched large samples, well-chosen genetic markers, and adequate standards in genotyping, analysis, and interpretation are all integral parts of a high-quality association study.
Year of Publication2005
JournalMutation research
Volume573
Issue1-2
Pages54-69
Date Published (YYYY/MM/DD)2005/06/03
ISSN Number0027-5107
DOI10.1016/j.mrfmmm.2005.01.006
PubMedhttp://www.ncbi.nlm.nih.gov/pubmed/15829237?dopt=Abstract