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Relationship between case‐control studies and the transmission/disequilibrium test
Author(s) -
Mitchell Laura E.
Publication year - 2000
Publication title -
genetic epidemiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.301
H-Index - 98
eISSN - 1098-2272
pISSN - 0741-0395
DOI - 10.1002/1098-2272(200010)19:3<193::aid-gepi1>3.0.co;2-2
Subject(s) - transmission disequilibrium test , linkage disequilibrium , genetics , confounding , disequilibrium , sample size determination , genetic association , case control study , biology , multiple comparisons problem , disease , allele , statistics , medicine , haplotype , single nucleotide polymorphism , genotype , mathematics , gene , ophthalmology
Case‐control studies provide a powerful approach for detecting disease susceptibility loci that have only a weak to moderate impact on the risk of disease, or markers that are in linkage disequilibrium with such loci. However, since any association detected in a case‐control study may result from uncontrolled confounding, evidence for disease‐marker associations obtained from such studies must be confirmed by alternative methods. Since studies that use the transmission/disequilibrium test or TDT are frequently employed to confirm disease‐marker associations detected in case‐control studies, data are increasingly available from both case‐control studies and “TDT studies” of the same disease‐marker association. It would, therefore, be useful to have a single measure of the magnitude of the disease‐marker association that would allow for comparison of results from these two study designs. Such a measure could also be used to estimate minimum sample size requirements for TDT studies of previously reported disease‐marker associations. An obvious measure of the disease‐marker association in TDT studies is the frequency (T) with which heterozygous parents transmit the putative, high‐risk marker allele to affected offspring. In this paper, it is shown that T can also be estimated from case‐control data with a minimum of assumptions, and that T is the critical parameter for determining power and estimating sample sizes for the TDT. Genet. Epidemiol. 19:193–201, 2000. © 2000 Wiley‐Liss, Inc.