Clinical OMICS

JAN-FEB 2018

Healthcare magazine for research scientists, labs, pathologists, hospitals, cancer centers, physicians and biopharma companies providing news articles, expert interviews and videos about molecular diagnostics in precision medicine

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Page 14 of 51 January/February 2018 Clinical OMICs 13 In 2010, Denny and Ritchie introduced a new method, published in Bioinformatics, to answer the complex riddles genetics poses. Referred to as a "reverse GWAS," phe- nome-wide association studies (PheWAS) created a new paradigm for studying associations between genetics and disease. In contrast to GWAS, which selects a disease phe- notype and then compares genetic variants in affected and unaffected individuals, PheWAS selects a genetic variant and then searches for phenotypes common among individ- uals with that mutation. While GWAS laid the foundation by building the statisti- cal methods required to test for multiple gene–disease asso- ciations, "the electronic health record was the modality that made it all possible," said Denny. Electronic health records have assembled comprehensive, unbiased repositories of information on disease phenotypes, and, when linked to genotypes, researchers can use PheWAS to mine these store- houses for causal variants, pleiotropic effects, and other relationships between phenotypes. According to David Carey, Ph.D., associate chief research officer at Geisinger Health System, the approach could also shed light on dark portions of the "druggable genome." Approximately 3,000 genes constitute the druggable genome, which encodes proteins with pockets capable of binding small –molecule drugs. However, the biological function of many of these proteins remains a mystery, and less than 10% of them are targeted by FDA-approved drugs. "If you interfere with the function of those genes, what are the clinical consequences?" Carey posed. "That's an area where PheWAS has an advantage over GWAS approaches." Geisinger, which now has a biorepository linked to elec- tronic healthcare data for more than 100,000 individuals as part of their MyCode program, is using PheWAS to inves- tigate one of four protein families known to harbor most of the proteins in the druggable genome. By looking for indi- viduals with mutations in orphan G-protein coupled recep- tor genes and then asking what clinical traits are associated with those mutations, Geisinger hopes to bring to light their function and potential as a therapeutic target. The Secret Sauce Phenome-wide association studies have a distinct advantage over GWAS for investigating potential drug target genes with an unknown function. However, researchers need to first identify genes of interest, and many have turned to GWAS. In a preprint posted on bioRxiv, 23andMe collabo- rated with multiple institutions to validate potential drug targets for common immune-mediated, cardiometabolic, or neurodegenerative diseases. The study's authors, Diogo et al., used PheWAS with a cohort of 800,000 individuals to successfully replicate 70% of known disease-gene associa- tions among 25 single nucleotide polymorphisms (SNPs) previously identified by GWAS. The study also identified 10 novel associations that suggest potential adverse effects for therapies targeting pathways controlled by those genes. For example, while the study confirmed a gain-of-function mutation in the PNPLA3 gene that increases the risk for liver disease, it also identified previously unknown associations that suggested (continued on next page) Jxfzsy / Getty Images

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