Following the identification of gene networks of relevance to GWAS findings (as described above via GeneMANIA), gene-based tests of association with fast beta EEG were conducted in PLINK (Purcell et al., 2007), using set-based analyses (“--set-test”). Gene-based tests included all available SNPs in a given gene, corrected for the number of independent signals (i.e., linkage disequilibrium blocks) within that gene set. In addition, association models were adjusted for the relatedness in the family sample, sex, log-transformed age, and ancestry. Tests of association were accepted as significant if the 100,000 permutations of the set-based regression analysis (Bonferroni corrected for the number of independent signals within the set) produced an empirical p-value <0.05. Subsequently, these procedures were repeated for tests of gene-based association with DSM-V AUD severity only among genes that were associated with beta EEG. In addition, GABRA2 variants previously shown to be associated with aspects of beta EEG (Edenberg et al., 2004; Lydall et al., 2011; Malone et al., 2014) were tested for association with fast beta EEG (20–28 Hz) at fronto-central pairs: Fz-Cz, F3-C3, and F4-C4.
