Genome-wide association studies (GWAS) have identified thousands of variants robustly associated with complex traits. However, the biological mechanisms underlying these associations are, in general, not well understood. We propose a gene-based association method called PrediXcan that directly tests the molecular mechanisms through which genetic variation affects phenotype. The approach estimates the component of gene expression determined by an individual’s genetic profile and correlates the “imputed” gene expression with the phenotype under investigation to identify genes involved in the etiology of the phenotype. The genetically regulated gene expression is estimated using whole-genome tissue-dependent prediction models trained with reference transcriptome datasets. PrediXcan enjoys the benefits of gene-based approaches such as reduced multiple testing burden and a principled approach to the design of follow-up experiments. Our results demonstrate that PrediXcan can detect known and novel genes associated with disease traits and provide insights into the mechanism of these associations.

A major challenge in human genetics is to devise a systematic strategy to integrate disease-associated variants with diverse genomic and biological datasets to provide insight into disease pathogenesis and guide drug discovery for complex traits such as rheumatoid arthritis (RA)1. Here, we performed a genome-wide association study (GWAS) meta-analysis in a total of >100,000 subjects of European and Asian ancestries (29,880 RA cases and 73,758 controls), by evaluating ~10 million single nucleotide polymorphisms (SNPs). We discovered 42 novel RA risk loci at a genome-wide level of significance, bringing the total to 1012–4. We devised an in-silico pipeline using established bioinformatics methods based on functional annotation5, cis-acting expression quantitative trait loci (cis-eQTL)6, and pathway analyses7–9 – as well as novel methods based on genetic overlap with human primary immunodeficiency (PID), hematological cancer somatic mutations and knock-out mouse phenotypes – to identify 98 biological candidate genes at these 101 risk loci. We demonstrate that these genes are the targets of approved therapies for RA, and further suggest that drugs approved for other indications may be repurposed for the treatment of RA. Together, this comprehensive genetic study sheds light on fundamental genes, pathways and cell types that contribute to RA pathogenesis, and provides empirical evidence that the genetics of RA can provide important information for drug discovery.

Electronic phenotype algorithms allow rapid identification of case populations in multiple sites with little retraining.

This study demonstrated that AL can be useful in ML-based phenotyping methods. Moreover, AL and feature engineering based on domain knowledge could be combined to develop efficient and generalizable phenotyping methods.

Background Immunosuppressants decrease circulating dipeptidyl peptidase IV (DPPIV) activity in transplant patients, and decreased DPPIV activity has been associated with angiotensin-converting enzyme (ACE) inhibitor-associated angioedema. One study has reported an increased incidence of ACE inhibitor-associated angioedema among transplant patients compared to published rates, while several case series report angioedema in patients taking specific immunosuppressant agents. Objective To test the hypothesis that transplant patients are at increased risk of ACE inhibitor-associated angioedema. Methods We assessed the proportion of transplant patients in 145 cases with ACE inhibitor-associated angioedema and 280 ACE inhibitor-exposed controls. We measured the relationship between case–control status, transplant status, and immunosuppressant use and circulating DPPIV activity. We also assessed the incidence of angioedema among consecutive patients who underwent renal or cardiac transplant and were treated with an ACE inhibitor. Results Transplant patients were significantly overrepresented among ACE inhibitor-associated angioedema cases compared to controls (odds ratio 18.5, 95% CI 2.3–147.2, P = 0.0004). Immunosuppressant use, chronic renal failure, seasonal allergies and smoking were also associated with ACE inhibitor-associated angioedema in univariate analysis. The association of transplant status with ACE inhibitor-associated angioedema was no longer significant after inclusion of immunosuppressant therapy in a multivariate analysis. Dipeptidyl peptidase IV activity was significantly decreased in sera from cases compared to ACE inhibitor-exposed controls, as well as in individuals taking immunosuppressants. Two of 47 ACE inhibitor-treated renal transplant patients and one of 36 ACE inhibitor-treated cardiac transplant patients developed angioedema. Conclusion Transplant patients are at increased risk of ACE inhibitor-associated angioedema possibly because of the effects of immunosuppressants on the activity of DPPIV.