In addition to GWAS data network-based models can be made to incorporate micro-array/RNA-Seq (i.e., whole genome sequencing of mRNA transcripts) and Chip-Seq (i.e., whole genome sequencing of immune-precipitation-enriched genomic DNA) data. For instance, although microarray studies have suffered from multiple testing issues resulting from the agnostic interrogation of the expression of thousands of genes, they have demonstrated that alcohol induces changes in the expression level of DNA binding and cell signaling genes within the prefrontal cortex (Flatscher-Bader et al., 2006). Alcohol has also been shown to influence the expression of genes involved in matrix remodeling, proliferation, and cell morphogenesis in the nucleus accumbens and ventral tegmental area (Flatscher-Bader et al., 2010). The combination of DNA whole genome genetic variation with epigenetic, transcriptomic, and proteomic profiles taken from select neural tissues involved in different stages of addiction (e.g., hippocampus) would be the ideal approach to achieving Systems-based models of AD. By accounting for the relationship between the genome as a whole and the transcriptome of select tissue as a whole, we would obtain effects that are more robust. For instance, recent studies that have examined the covariation between variation in the genome and the transcriptome, and the proteome suggest modest correlations
