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. 2000 Nov;67(5):1208-18.
doi: 10.1086/321201. Epub 2000 Oct 13.

Linkage disequilibrium analysis of biallelic DNA markers, human quantitative trait loci, and threshold-defined case and control subjects

N J Schork  1 , S K Nath, D Fallin, A Chakravarti
Affiliations

Linkage disequilibrium analysis of biallelic DNA markers, human quantitative trait loci, and threshold-defined case and control subjects

N J Schork et al. Am J Hum Genet. 2000 Nov.

Abstract

Linkage disequilibrium (LD) mapping has been applied to many simple, monogenic, overtly Mendelian human traits, with great success. However, extensions and applications of LD mapping approaches to more complex human quantitative traits have not been straightforward. In this article, we consider the analysis of biallelic DNA marker loci and human quantitative trait loci in settings that involve sampling individuals from opposite ends of the trait distribution. The purpose of this sampling strategy is to enrich samples for individuals likely to possess (and not possess) trait-influencing alleles. Simple statistical models for detecting LD between a trait-influencing allele and neighboring marker alleles are derived that make use of this sampling scheme. The power of the proposed method is investigated analytically for some hypothetical gene-effect scenarios. Our studies indicate that LD mapping of loci influencing human quantitative trait variation should be possible in certain settings. Finally, we consider possible extensions of the proposed methods, as well as areas for further consideration and improvement.

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Figures

Figure 1
Figure 1
Effect of sampling thresholds on the power to identify a QTL via association mapping. Simulating conditions were: D′ between trait/marker loci = 0.75, pM = 0.25, and p+ =.025, when the dominant model is assumed. Type I–error rate was set to .05.
Figure 2
Figure 2
Effect of the heritability of a QTL on the power to identify that locus via association mapping
Figure 3
Figure 3
Effect of LD strength between marker and trait loci on the power to identify a QTL via association mapping
Figure 4
Figure 4
Effect of quantitative trait and marker-locus allele frequencies on the power to identify the QTL via association mapping.
Figure 5
Figure 5
Effect of the definition of a “control subject” on the power to identify a QTL via association mapping. A, Power as a function of the number of control subjects sampled while keeping case-subject sample size and sampling percentiles constant (control subjects sampled from the bottom 25th percentile). B, Power as a function of control subject–sampling threshold while keeping case- and control-subject sampling sizes constant (100 each).
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