The Genome-Wide Association Analysis with Family Data package was utilized to analyze ANYDEP, implemented as a logistic regression model. Relatedness between family members was accounted for via generalized estimating equations. QUANTDEP was analyzed using a linear mixed effects model as implemented in the kinship library (lmekin) in R (http://www.inside-r.org/packages/cran/kinship/docs/print.lmekin). This model in the kinship function allows for the covariance matrix to be completely specified for the random effects. The result is that each family has a different covariance pattern based on the kinship coefficients, to model the familial genetic random effects. Gender and birth cohort defined by year of birth (<1930, 1930-1949, 1950-1969, and ≥1970), were included as covariates in all analyses described above, including statistical models of association, to account for secular trends (Grucza et al., 2008). As needed, genomic control was applied to correct for inflation. To reduce the scope of multiple testing, only genotyped SNPs were included in the initial analyses. After correcting for the final number of autosomal SNPs (n=591,785), the genome-wide significance threshold was p=8.45×10−8.
