Genome-wide association analysis and Mendelian randomization proteomics identify drug targets for heart failure.

We conduct a large-scale meta-analysis of heart failure genome-wide association studies (GWAS) consisting of over 90,000 heart failure cases and more than 1 million control individuals of European ancestry to uncover novel genetic determinants for heart failure. Using the GWAS results and blood protein quantitative loci, we perform Mendelian randomization and colocalization analyses on human proteins to provide putative causal evidence for the role of druggable proteins in the genesis of heart failure. We identify 39 genome-wide significant heart failure risk variants, of which 18 are previously unreported.

Comparative effectiveness of third doses of mRNA-based COVID-19 vaccines in US veterans.

Vaccination against SARS-CoV-2 has been effective in reducing the burden of severe disease and death from COVID-19. Third doses of mRNA-based vaccines have provided a way to address waning immunity and broaden protection against emerging SARS-CoV-2 variants. However, their comparative effectiveness for a range of COVID-19 outcomes across diverse populations is unknown.

Visualizing novel connections and genetic similarities across diseases using a network-medicine based approach.

Understanding the genetic relationships between human disorders could lead to better treatment and prevention strategies, especially for individuals with multiple comorbidities. A common resource for studying genetic-disease relationships is the GWAS Catalog, a large and well curated repository of SNP-trait associations from various studies and populations. Some of these populations are contained within mega-biobanks such as the Million Veteran Program (MVP), which has enabled the genetic classification of several diseases in a large well-characterized and heterogeneous population.

Network-medicine framework for studying disease trajectories in U.S. veterans.

A better understanding of the sequential and temporal aspects in which diseases occur in patient's lives is essential for developing improved intervention strategies that reduce burden and increase the quality of health services. Here we present a network-based framework to study disease relationships using Electronic Health Records from > 9 million patients in the United States Veterans Health Administration (VHA) system. We create the Temporal Disease Network, which maps the sequential aspects of disease co-occurrence among patients and demonstrate that network properties reflect clinical aspects of the respective diseases.

Comparative Safety of BNT162b2 and mRNA-1273 Vaccines in a Nationwide Cohort of US Veterans.

Importance: The risk of adverse events has been found to be low for participants receiving the BNT162b2 (Pfizer-BioNTech) and mRNA-1273 (Moderna Inc) vaccines in randomized trials. However, a head-to-head comparison of their safety for a broader range of potential adverse events over longer follow-up and in larger and more diverse populations is lacking, to our knowledge.

Objective: To compare the head-to-head safety in terms of risk of adverse events of the BNT162b2 and mRNA-1273 vaccines in the national health care databases of the US Department of Veterans Affairs, the largest integrated health care system in the US.

Comparative Effectiveness of BNT162b2 and mRNA-1273 Vaccines in U.S. Veterans.

Background: The messenger RNA (mRNA)-based vaccines BNT162b2 and mRNA-1273 are more than 90% effective against coronavirus disease 2019 (Covid-19). However, their comparative effectiveness for a range of outcomes across diverse populations is unknown.

Methods: We emulated a target trial using the electronic health records of U.