The power to detect linkage disequilibrium with quantitative traits in selected samples.
Results from power studies for linkage detection have led to many ongoing and planned collections of phenotypically extreme nuclear families. Given the great expense of collecting these families and the imminent availability of a dense diallelic marker map, the families are likely to be used in allelic-association as well as linkage studies. However, optimal selection strategies for linkage may not be equally powerful for association. We examine the power to detect linkage disequilibrium for quantitative traits after phenotypic selection. The results encompass six selection strategies that are in widespread use, including single selection (two designs), affected sib pairs, concordant and discordant pairs, and the extreme-concordant and -discordant design. Selection of sibships on the basis of one extreme proband with high or low trait scores provides as much power as discordant sib pairs but requires the screening and phenotyping of substantially fewer initial families from which to select. Analysis of the role of allele frequencies within each selection design indicates that common trait alleles generally offer the most power, but similarities between the marker- and trait-allele frequencies are much more important than the trait-locus frequency alone. Some of the most widespread selection designs, such as single selection, yield power gains only when both the marker and quantitative trait loci (QTL) are relatively rare in the population. In contrast, discordant pairs and the extreme-proband design provide power for the broadest range of QTL-marker-allele frequency differences. Overall, proband selection from either tail provides the best balance of power, robustness, and simplicity of ascertainment for family-based association analysis.
Abecasis
G R
GR
University of Oxford, Oxford, OX3 7BN, United Kingdom.
Cookson
W O
WO
Cardon
L R
LR
D000483:Alleles; D002874:Chromosome Mapping / Q000379:methods* / Q000706:statistics & numerical data*; D003198:Computer Simulation; D005787:Gene Frequency / Q000235:genetics; D006801:Humans; D015810:Linkage Disequilibrium / Q000235:genetics*; D016555:Matched-Pair Analysis; D008957:Models, Genetic; D009679:Nuclear Family; D018579:Patient Selection; D019655:Quantitative Trait, Heritable; D018401:Sample Size; D012494:Sampling Studies