COVID-19 infection and longevity: an observational and mendelian randomization study

Studies have indicated that COVID-19 infection may accelerate the aging process in organisms. However, it remains unknown whether contracting COVID-19 affects life expectancy. Furthermore, the underlying biological mechanisms behind these findings are still unclear.

We conducted a prospective cohort study on 56,504 participants of European ancestry from the UK Biobank who reported the time and number of COVID-19 infection between January 2020 and September 2023. The parental average longevity was used as a proxy for their own longevity. Linear regression was used to assess the relationship between COVID-19 infection and longevity. Furthermore, we investigated the shared genetic basis between COVID-19 and longevity using large-scale genome-wide association studies (GWAS) for COVID-19 (122,616 cases and 2,475,240 controls) and longevity (3,484 cases and 25,483 controls). Mendelian randomization (MR) and mediation analysis were utilized to assess causal relationships and potential mediators between COVID-19 susceptibility and longevity. Shared genetic loci between the two phenotypes were identified using conjunctional false discovery rate (conjFDR) statistical frameworks.

After controlling for relevant covariates, COVID-19 infection might not be significantly correlated with longevity. In all MR methods, generalized summary-data-based Mendelian randomization (GSMR) analysis revealed a significant decrease in longevity due to severe COVID-19 infection (OR = 0.91, 95%CI: 0.84-0.98, P = 0.015). Mediation analysis identified stroke and myocardial infarction as potential mediators between COVID-19 susceptibility and reduced longevity. At conjFDR < 0.05, we identified rs62062323 (KANSL1) and rs9530111 (PIBF1) as shared loci between COVID-19 and longevity.

Together, our findings provided preliminary evidence for the shared genetic basics between COVID-19 and aging. This discovery may have implications for personalized medicine and preventive strategies, helping identify individuals who may be more vulnerable to severe outcomes from COVID-19 due to their genetic makeup.