Genetically predicted effects of COVID-19 on 2272 traits: exploring through a phenome-wide Mendelian randomization...

The COVID-19 pandemic has significantly impacted global health, making it essential to understand its genetic effects on various traits.

Leveraging the extensive FinnGen dataset comprising 500 000 individuals, we performed a Mendelian randomization (MR) phenome-wide association study. COVID-19-related phenotypes obtained from the COVID-19 Host Genetics Initiative GWAS (release 7). We employed four distinct approaches, including MR-Egger, weighted median, random-effect inverse variance weighted (IVW), and weighted mode, to conduct the MR analysis.

Two hundred fifty-five potential causal effects of COVID-19 were observed for a diverse range of outcomes using the IVW method, including cardiovascular disorders, respiratory conditions, autoimmune diseases, and metabolic disorders. Apart from a few that can be classified as "other traits," the majority of the traits are disease-related traits. We have also identified 31 traits, wherein all four distinct MR analyses yielded a P-value of less than 0.05. Only one trait remained statistically significant after multiple testing correction using the conservative Bonferroni threshold (P < 2.2E-5).

This phenome-wide MR study provides valuable insights into the genetically predicted effects of COVID-19 on a comprehensive range of traits. The identified associations contribute to our understanding of the complex interplay between the impact of the post-COVID-19 era on healthcare and may have implications for the development of targeted therapeutic strategies and public health interventions. Key messages What is already known on this topic - COVID-19 has a high mortality rate, and patients often have many sequelae, including myocarditis, acute respiratory distress syndrome, and neurological and hematologic complications. What this study adds Most of the current relevant studies lack large-scale phenotype-group ranging Mendelian randomization (MR) studies on the outcome of COVID-19 due to their small sample sizes. Therefore, this study performed a full phenotypic group MR analysis in the FinnGen dataset to investigate the relationship between COVID-19 and thousands of outcome variables. How this study might affect research, practice or policy- The study identified a set of traits that are strongly associated with genetic susceptibility to the long-term effects of COVID-19.