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    Disease Model Distortion in Association Studies

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    Author
    Vukcevic, D; Hechter, E; Spencer, C; Donnelly, P
    Date
    2011-05-01
    Source Title
    Genetic Epidemiology
    Publisher
    WILEY
    University of Melbourne Author/s
    Vukcevic, Damjan
    Affiliation
    School of Mathematics and Statistics
    Metadata
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    Document Type
    Journal Article
    Citations
    Vukcevic, D., Hechter, E., Spencer, C. & Donnelly, P. (2011). Disease Model Distortion in Association Studies. GENETIC EPIDEMIOLOGY, 35 (4), pp.278-290. https://doi.org/10.1002/gepi.20576.
    Access Status
    Open Access
    URI
    http://hdl.handle.net/11343/257135
    DOI
    10.1002/gepi.20576
    Abstract
    Most findings from genome-wide association studies (GWAS) are consistent with a simple disease model at a single nucleotide polymorphism, in which each additional copy of the risk allele increases risk by the same multiplicative factor, in contrast to dominance or interaction effects. As others have noted, departures from this multiplicative model are difficult to detect. Here, we seek to quantify this both analytically and empirically. We show that imperfect linkage disequilibrium (LD) between causal and marker loci distorts disease models, with the power to detect such departures dropping off very quickly: decaying as a function of r4, where r2 is the usual correlation between the causal and marker loci, in contrast to the well-known result that power to detect a multiplicative effect decays as a function of r2. We perform a simulation study with empirical patterns of LD to assess how this disease model distortion is likely to impact GWAS results. Among loci where association is detected, we observe that there is reasonable power to detect substantial deviations from the multiplicative model, such as for dominant and recessive models. Thus, it is worth explicitly testing for such deviations routinely.

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