title: Is replication the gold standard for validating genome-wide association findings?
abstract: With the advent of genome-wide association (GWA) studies, researchers are hoping that reliable genetic association of common human complex diseases/traits can be detected. Currently, there is an increasing enthusiasm about GWA and a number of GWA studies have been published. In the field a common practice is that replication should be used as the gold standard to validate an association finding. In this article, based on empirical and theoretical data, we emphasize that replication of GWA findings can be quite difficult, and should not always be expected, even when true variants are identified. The probability of replication becomes smaller with the increasing number of independent GWA studies if the power of individual replication studies is less than 100% (which is usually the case), and even a finding that is replicated may not necessarily be true. We argue that the field may have unreasonably high expectations on success of replication. We also wish to raise the question whether it is sufficient or necessary to treat replication as the ultimate and gold standard for defining true variants. We finally discuss the usefulness of integrating evidence from multiple levels/sources such as genetic epidemiological studies (at the DNA level), gene expression studies (at the RNA level), proteomics (at the protein level), and follow-up molecular and cellular studies for eventual validation and illumination of the functional relevance of the genes uncovered.
authors.affiliation: School of Medicine, University of Missouri - Kansas City, Kansas City, Missouri, USA.
authors.forename: Yong-Jun
authors.initials: YJ
authors.lastname: Liu
authors.forename: Christopher J
authors.initials: CJ
authors.lastname: Papasian
authors.forename: Jian-Feng
authors.initials: JF
authors.lastname: Liu
authors.forename: James
authors.initials: J
authors.lastname: Hamilton
authors.forename: Hong-Wen
authors.initials: HW
authors.lastname: Deng
mesh_terms: D000465:Algorithms; D000483:Alleles; D000818:Animals; D020869:Gene Expression Profiling; D005787:Gene Frequency; D005821:Genetic Techniques; D016678:Genome; D055106:Genome-Wide Association Study; D023281:Genomics; D006801:Humans; D015810:Linkage Disequilibrium; D008957:Models, Genetic; D011336:Probability; D040641:Quantitative Trait Loci; D015203:Reproducibility of Results