Journal
AMERICAN JOURNAL OF MEDICAL GENETICS PART B-NEUROPSYCHIATRIC GENETICS
Volume 118B, Issue 1, Pages 66-71Publisher
WILEY
DOI: 10.1002/ajmg.b.10057
Keywords
quantitative trait; alcoholism; epistatic interaction
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Funding
- FIC NIH HHS [1D43 TW 05811] Funding Source: Medline
- NIAAA NIH HHS [U10 AA 08403, U10 AA 08401, K02 AA 00285] Funding Source: Medline
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Parametric linkage methods for analyzing quantitative trait loci are sensitive to violations in trait distributional assumptions. Non-parametric methods are relatively more robust. In this article, we modify the non-parametric regression procedure proposed by Ghosh and Majumder [2000: Am J Hum Genet 66:1046-1061] to map Beta 2 EEG waves using genome-wide data generated in the COGA project. Significant linkage findings are obtained on chromosomes 1, 4, 5, and 15 with findings at multiple regions on chromosomes 4 and 15. We analyze the data both with and without incorporating alcoholism as a covariate. We also test for epistatic interactions between regions of the genome exhibiting significant linkage with the EEG phenotypes and find evidence of epistatic interactions between a region each on chromosome 1 and chromosome 4 with one region on chromosome 15. While regressing out the effect of alcoholism does not affect the linkage findings, the epistatic interactions become statistically insignificant. (C) 2003 Wiley-Liss, Inc.
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