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.

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.

Injury and fitness outcomes during implementation of physical readiness training

This study examined injury and physical fitness outcomes in Basic Combat Training (BCT) during implementation of Physical Readiness Training (PRT). PRT is the U.S. Army's emerging physical fitness training program. An experimental group (EG, n = 1284), which implemented the PRT program, was compared to a control group (CG, n = 1296), which used a traditional BCT physical training program during the 9-week BCT cycle. Injury cases were obtained from recruit medical records and physical fitness was measured using the U.S. Army Physical Fitness Test (APFT, consisting of push-ups, sit-ups and a two-mile run). Injury rates were examined using Cox regression after controlled for initial group differences in demographics, fitness and other variables. Compared to the EG, the adjusted relative risk of a time-loss overuse injury in the CG was 1.5 (95 % confidence interval [CI] = 1.0 - 2.1, p < 0.01) for men and 1.4 (95 %CI = 1.1 - 1.8, p < 0.01) for women. There were no differences between groups for traumatic injuries. On the first administration of the final APFT, the EG had a greater proportion of recruits passing the test than the CG (men: 85 % vs. 81 %, p = 0.04; women: 80 % vs. 70 %, p < 0.01). After all APFT retakes, the EG had significantly fewer APFT failures than the CG among the women (1.6 % vs. 4.6 %, p < 0.01) but not the men (1.6 % vs. 2.8 %, p = 0.18); the gender-combined EG had a higher pass rate (1.6 % vs. 3.7 %, p < 0.01). Overall, the PRT program reduced overuse injuries and allowed a higher success rate on the APFT.

A latent variable model of evidence-based quality improvement for substance abuse treatment

Attempts to improve the quality of substance abuse treatment are hampered by an inability to define specifically the elements of high quality of care and, more important, the lack of a research paradigm within which to study the necessary and sufficient elements of appropriate care. This study proposes that the quality-of-care (QOC) construct for substance abuse treatment might be best considered as a latent construct that does not necessarily exist as a single set of criteria but instead is indicated by a set of empirically derived indicators manifested as a latent factor. Results support defining latent QOC variables across levels of care for alcoholism treatment and empirically defining latent QOC measures from administrative records.