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Chunk #63 — Conclusions and perspectives

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Genetics of substance use disorders in the era of big data.
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Until quite recently the only risk genes that were well established for SUDs acted pharmacogenomically — metabolizing enzymes and receptor variants. Now, for some traits, we have many more significant risk variants, and have moved into brain biology. The single greatest advance to emerge from more powerful GWAS, in our view, has been the characterization of the genetic differences between quantity/frequency traits and dependence traits across multiple substances. Despite these remarkable advances, we can still account for only a small proportion of genetic risk based on currently identified variants. Accordingly, we are very far from widespread clinical application of these data. Recent studies based on whole-genome sequencing (WGS) data showed that the ‘missing heritability’182 of complex traits (i.e., the difference between twin-based heritability and GWAS-based heritability; Figure 3) appears to be due, at elast for some traits, to uncommon variants located in regions with low linkage disequilibrium183, 184 that cannot be ascertained by genotyping array. Accordingly, the WGS being generted by large-scale efforts (e.g., AllOfUs, the Million Veteran Program (MVP), and the Trans-Omics for Precision Medicine (TOPMed) program) are likely