Table 2.

Post-genome-wide association study (GWAS) analyses of AD GWAS datasets.

Post-GWAS method	Reference	Methods and findings
SNP heritability	Vrieze et al., 2013	Using Genome-wide Complex Trait Analysis (GCTA), estimated a SNP heritability of 16% for AD and 18% for alcohol consumption in the MCTFR family-based sample (unrelated parents only); the estimate for AD was not significant. Estimates in the full family-based sample were high and likely reflect shared environmental effects.
	Yang et al., 2014	Using GCTA, estimated a SNP heritability of 22.1% for AD in the unrelated AA subset of the Yale-UPenn sample (n=1,838).
Risk profile scoring	Frank et al., 2012	Split the German GWAS sample into a discovery sample and a target sample; constructed a polygenic risk score in the discovery sample that significantly predicted AD case-control status in the target sample; used the full German GWAS sample as a discovery sample and significantly predicted AD case-control status in SAGE and COGA samples.
	Kos et al., 2013	Significantly predicted AD case-control status using EA and AA discovery samples from COGA and EA and AA target samples from SAGE. Although significant, the variance explained was small (0.73% in EAs and 2.14% in AAs).
	Vrieze et al., 2013	Used k-fold cross-validation within the Minnesota Center for Twin and Family Research (MCTFR) sample and observed polygenicity; as the P-value threshold increased, the percent of variation increased.
	Yan et al., 2014	Used the COGA and SAGE samples to conduct risk profile scoring for candidate gene SNPs as well as with SNPs from GWAS. Did not observe significant risk prediction from a set of 21 candidate gene SNPs. When combined COGA and SAGE datasets and split this sample in half, able to significantly predict AD case-control status in the target sample using results from the discovery sample.
	Levey et al., 2014	Used a Convergent Functional Genomic approach to integrate multiple sources of information and generated a list of 713 nominally significant SNPs in 135 candidate genes. Were unable to predict case-control status in the German GWAS target sample, but when this list was prioritized to a set of 11 genes using data from a DBP stress-reactive knockout mouse model for alcoholism, significantly predicted risk in German sample and two additional samples.
Gene set analysis	McGue et al., 2013	Used the versatile gene-based association study gene set method in the MCTFR sample but did not identify any significant genes after Bonferroni correction. Did not identify enrichment of candidate genes for substance abuse or related phenotypes.
	Han et al., 2013	Used a network-based gene set analysis approach to identify human protein interaction networks (HPIN) enriched for AD-associated genes in the SAGE and COGA EA and AA datasets. Identified seven HPIN that were enriched for AD-associated genes within EAs and AAs. Found that this subnetwork was associated AD case-control status in EAs and AAs, and replicated this finding in two additional samples.
Pathway analysis	Kendler et al., 2011	Conducted pathway analysis in MGS2 controls GWAS sample using ALIGATOR and found significant enrichment of Gene Ontology (GO) categories and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways in EAs and AAs, including those related to lipid and cholesterol metabolism and cell adhesion.
	Biernacka et al., 2013	Used the EA SAGE dataset and grouped genes into sets based on KEGG pathway annotations, but did not observe significant association with AD case-control status. Several gene sets showed suggestive association including “synthesis and degradation of ketone bodies” and “neuroactivated ligand-receptor interaction”.
	Kos et al., 2013	Evaluated enrichment of pathways/ontologies enriched among SNPs identified in risk profile scoring analysis using the COGA discovery sample and SAGE target sample. Identified four ontologies relevant to brain development and inhibitory neurotransmission with significant enrichment among the gene sets from EAs and AAs.
	Juraeva et al., 2015	Conducted pathway analysis in AD cases and controls from the German GWAS sample using annotations from KEGG, Reactome, Gene Ontology, Biocarta, microRNA targets, transcription factor targets, and positional information. Found that 19 gene sets contained the gene XRCC5, and followed up on this gene with functional studies. Found that Drosophila knockdown model of the XRCC5 ortholog Ku80 had lower sensitivity to alcohol than controls. In a human laboratory-based self-admnistration study, found significant association between maximum blood alcohol concentration and the top XRCC5 SNP from the GWAS, rs828701.

Abbreviations: GWAS, genome-wide association study; AD, alcohol dependence