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Candidate-gene association analysis for a continuous phenotype with a spike at zero using parent-offspring trios

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posted on 2019-12-20, 04:09 authored by Nadja Klein, Andrew Entwistle, Albert Rosenberger, Thomas Kneib, Heike Bickeböller

In this paper, we propose the class of generalized additive models for location, scale and shape in a test for the association of genetic markers with non-normally distributed phenotypes comprising a spike at zero. The resulting statistical test is a generalization of the quantitative transmission disequilibrium test with mating type indicator, which was originally designed for normally distributed quantitative traits and parent-offspring data. As a motivational example, we consider coronary artery calcification (CAC), which can accurately be identified by electron beam tomography. In the investigated regions, individuals will have a continuous measure of the extent of calcium found or they will be calcium-free. Hence, the resulting distribution is a mixed discrete-continuous distribution with spike at zero. We carry out parent-offspring simulations motivated by such CAC measurement values in a screening population to study statistical properties of the proposed test for genetic association. Furthermore, we apply the approach to data of the Genetic Analysis Workshop 16 that are based on real genotype and family data of the Framingham Heart Study, and test the association of selected genetic markers with simulated coronary artery calcification.

Funding

Heike Bickeböller was supported by the Deutsche Forschungsgemeinschaft (grant Klinische Forschergruppe (KFO) 241: TP5, BI 576/5-1) and by the German Federal Ministry of Education and Research Bundesministerium für Bildung und Forschung (BMBF) (German National Genome Research Net NGFN grant 01GS0837). The work of Nadja Klein and Thomas Kneib was supported by the German Research Foundation (DFG) via the research projects KN 922/4-1/2 and together with the work of Heike Bickeböller also via the research training group 1644 on ‘Scaling Problems in Statistics’.

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