These sequential integration examples highlight a challenge for the field of addiction, and psychiatric disease more broadly, because functional and regulatory effects can be highly tissue-specific [135] and brain is the most relevant tissue for studying the neurobiology of addiction. GWAS genotypes, other ‘omics data in brain, and addiction phenotypes are seldom available in the same dataset. Other ‘omics data derived in blood or other peripheral tissues that are easily accessible in living participants may offer informative biomarkers of addiction but overall provide poor indicators of neurobiology. Poor correlations in RNA expression levels between blood and brain has been repeatedly shown [136, 137, 135]. Most recently, pilot GTEx analyses with RNA expression measured in 43 tissues showed that blood vs. brain had the most distinct expression profiles among the tissue comparisons [135]. There is also limited overlap of meQTL and eQTL [136, 137, 135] variants mapped in blood vs. brain. Thus, when analyzing gene regulatory potential to study the neurobiology of addiction, it is critical to use disease-relevant brain tissue. Reliance on blood-specific regulatory effects could even lead to erroneous
