The effectiveness of a pharmacist-led telephone intervention directed at providers or members was examined in this randomized study. Pharmacist calls to members did not improve osteoporosis management over member and provider mail and fax notifications. Greater impact was demonstrated by performing a pharmacist call intervention with providers rather than with members.

Although vaccines for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been successful, there are no good treatments for those who are actively infected and potentially suffer from diverse neurological symptoms. While SARS-CoV-2 primarily infects the respiratory tract, clinical evidence indicates that cells from sensory organs, brain, and heart are also susceptible to infection. An understanding of factors critical for viral infection in these tissues may help identify novel therapeutics. To discover host factors involved in SARS-CoV-2 viral entry, we performed CRISPR activation (CRISPRa) screens targeting all 6000+ human membrane proteins in cells with and without overexpression of ACE2 using Spike-pseudotyped lentiviruses. We identified both novel as well as previously validated host factors. Notably, we used replication-competent SARS-CoV-2 to validate new viral-entry promoting genes, including potassium channel KCNA6, protease LGMN, and MHC-II component HLA-DPB1. We found that the overexpression of KCNA6 led to a marked increase in infection even in cells with undetectable levels of ACE2 expression. Our analysis of human olfactory neuroepithelium scRNA-seq data revealed that OLIG2+ cells--previously identified as sites of infection in COVID-19 autopsy studies--have high KCNA6 expression and minimal levels of ACE2, suggesting that the presence of KCNA6 may explain sensory/neuronal aspects of COVID-19 symptoms. Further, we demonstrate that FDA-approved compound dalfampridine, an inhibitor of KCNA-family potassium channels, suppresses viral entry in a dosage-dependent manner. Finally, we identified common prescription drugs likely to modulate the top screen hits. We then performed a retrospective analysis of insurance claims of ~8 million patients and found a clinical association between screen-identified drug classes, particularly those targeting potassium channels, and COVID-19 severity. We have thus identified the potassium channel KCNA6 as a SARS-CoV-2 host factor, expanded our understanding of potential viral tropism, and identified promising targets for drug repurposing and development.

Motivation Gene set analysis methods rely on knowledge-based representations of genetic interactions in the form of both gene set collections and protein-protein interaction (PPI) networks. However, explicit representations of genetic interactions often fail to capture complex interdependencies among genes, limiting the analytic power of such methods. Results We propose an extension of gene set enrichment analysis to a latent embedding space reflecting PPI network topology, called gene set proximity analysis (GSPA). Compared with existing methods, GSPA provides improved ability to identify disease-associated pathways in disease-matched gene expression datasets, while improving reproducibility of enrichment statistics for similar gene sets. GSPA is statistically straightforward, reducing to a version of traditional gene set enrichment analysis through a single user-defined parameter. We apply our method to identify novel drug associations with SARS-CoV-2 viral entry. Finally, we validate our drug association predictions through retrospective clinical analysis of claims data from 8 million patients, supporting a role for gabapentin as a risk factor and metformin as a protective factor for severe COVID-19. Availability GSPA is available for download as a command-line Python package at https://github.com/henrycousins/gspa. Supplementary information Supplementary data are available at Bioinformatics online.

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