A catalog of associations between rare coding variants and COVID-19 outcomes.

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) causes coronavirus disease-19 (COVID-19), a respiratory illness that can result in hospitalization or death. We investigated associations between rare genetic variants and seven COVID-19 outcomes in 543,213 individuals, including 8,248 with COVID-19. After accounting for multiple testing, we did not identify any clear associations with rare variants either exome-wide or when specifically focusing on (i) 14 interferon pathway genes in which rare deleterious variants have been reported in severe COVID-19 patients; (ii) 167 genes located in COVID-19 GWAS risk loci; or (iii) 32 additional genes of immunologic relevance and/or therapeutic potential. Our analyses indicate there are no significant associations with rare protein-coding variants with detectable effect sizes at our current sample sizes. Analyses will be updated as additional data become available, with results publicly browsable at https://rgc-covid19.regeneron.com.

Genome-wide analysis in 756,646 individuals provides first genetic evidence that ACE2 expression influences COVID-19 risk and yields genetic risk scores predictive of severe disease.

SARS-CoV-2 enters host cells by binding angiotensin-converting enzyme 2 (ACE2). Through a genome-wide association study, we show that a rare variant (MAF = 0.3%, odds ratio 0.60, P=4.5×10-13) that down-regulates ACE2 expression reduces risk of COVID-19 disease, providing human genetics support for the hypothesis that ACE2 levels influence COVID-19 risk. Further, we show that common genetic variants define a risk score that predicts severe disease among COVID-19 cases.

Getting to precision psychopharmacology: Combining clinical and genetic information to predict fat gain from aripiprazole.

INTRODUCTION: All atypical antipsychotics are associated with some degree of weight gain. We applied a novel statistical approach to identify moderators of aripiprazole-induced fat gain using clinical and genetic data from a randomized clinical trial (RCT) of treatment resistant depression in older adults. MATERIALS AND METHODS: Adults aged ≥60 years with non-response to a prospective trial of venlafaxine were randomized to 12 weeks of aripiprazole augmentation (n = 91) or placebo (n = 90). Dual energy x-ray absorptiometry (DEXA) measured adiposity at baseline and 12 weeks. Independent moderators of total body fat gain were used to generate two combined multiple moderators, one including clinical data alone and one including both clinical and genetic data to characterize individuals who gained fat during aripiprazole augmentation. RESULTS: The value of the combined genetic + clinical multiple moderator (Mcg) was 0.57 [95% CI 0.46, 0.68] (effect size: 0.57), compared to the combined clinical moderator (Mc) value of 0.49 [0.34, 0.63] (effect size: 0.49). Individuals who gained adiposity in this study were more likely to be female and younger in age, have lower weight, fasting glucose and lipids at baseline and positive for the HTR2C polymorphism. DISCUSSION: These results demonstrate a combined multiple moderator approach, including both clinical and genetic moderators, can be applied to existing clinical trial data to understand adverse treatment effects. This method allowed for more specific characterization of individuals at risk for the outcome of interest. Further work is needed to identify additional genetic moderators and to validate the approach.