Dataset Information

Genetic and phenotypic analysis of the causal relationship between aging and COVID-19.

ABSTRACT:

Background

Epidemiological studies revealed that the elderly and those with comorbidities are most affected by COVID-19, but it is important to investigate shared genetic mechanisms between COVID-19 risk and aging.

Methods

We conducted a multi-instrument Mendelian Randomization analysis of multiple lifespan-related traits and COVID-19. Aging clock models were applied to the subjects with different COVID-19 conditions in the UK-Biobank cohort. We performed a bivariate genomic scan for age-related COVID-19 and Mendelian Randomization analysis of 389 immune cell traits to investigate their effect on lifespan and COVID-19 risk.

Results

We show that the genetic variation that supports longer life is significantly associated with the lower risk of COVID-19 infection and hospitalization. The odds ratio is 0.31 (P = 9.7 × 10^-6) and 0.46 (P = 3.3 × 10^-4), respectively, per additional 10 years of life. We detect an association between biological age acceleration and future incidence and severity of COVID-19 infection. Genetic profiling of age-related COVID-19 infection indicates key contributions of Notch signaling and immune system development. We reveal a negative correlation between the effects of immune cell traits on lifespan and COVID-19 risk. We find that lower B-cell CD19 levels are indicative of an increased risk of COVID-19 and decreased life expectancy, which is further validated by COVID-19 clinical data.

Conclusions

Our analysis suggests that the factors that accelerate aging lead to an increased COVID-19 risk and point to the importance of Notch signaling and B cells in both. Interventions that target these factors to reduce biological age may reduce the risk of COVID-19.

SUBMITTER: Ying K

PROVIDER: S-EPMC9053191 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Publications

Genetic and phenotypic analysis of the causal relationship between aging and COVID-19.

Ying Kejun K Zhai Ranran R Pyrkov Timothy V TV Shindyapina Anastasia V AV Mariotti Marco M Fedichev Peter O PO Shen Xia X Gladyshev Vadim N VN

Communications medicine 20211005

<h4>Background</h4>Epidemiological studies revealed that the elderly and those with comorbidities are most affected by COVID-19, but it is important to investigate shared genetic mechanisms between COVID-19 risk and aging.<h4>Methods</h4>We conducted a multi-instrument Mendelian Randomization analysis of multiple lifespan-related traits and COVID-19. Aging clock models were applied to the subjects with different COVID-19 conditions in the UK-Biobank cohort. We performed a bivariate genomic scan ...[more]

PMID: 35602207

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Project description:ObjectiveObservational evidence reported that air pollution is a significant risk element for numerous health problems, such as obesity and coronavirus disease 2019 (COVID-19), but their causal relationship is currently unknown. Our objective was to probe the causal relationship between air pollution, obesity, and COVID-19 and to explore whether obesity mediates this association.MethodsWe obtained instrumental variables strongly correlated to air pollutants [PM2.5, nitrogen dioxide (NO2) and nitrogen oxides (NOx)], 9 obesity-related traits (abdominal subcutaneous adipose tissue volume, waist-to-hip ratio, body mass index, hip circumference, waist circumference, obesity class 1-3, visceral adipose tissue volume), and COVID-19 phenotypes (susceptibility, hospitalization, severity) from public genome-wide association studies. We used clinical and genetic data from different public biological databases and performed analysis by two-sample and two-step Mendelian randomization.ResultsPM2.5 genetically correlated with 5 obesity-related traits, which obesity class 1 was most affected (beta = 0.38, 95% CI = 0.11 - 0.65, p = 6.31E-3). NO2 genetically correlated with 3 obesity-related traits, which obesity class 1 was also most affected (beta = 0.33, 95% CI = 0.055 - 0.61, p = 1.90E-2). NOx genetically correlated with 7 obesity-related traits, which obesity class 3 was most affected (beta = 1.16, 95% CI = 0.42-1.90, p = 2.10E-3). Almost all the obesity-related traits genetically increased the risks for COVID-19 phenotypes. Among them, body mass index, waist circumference, hip circumference, waist-to-hip ratio, and obesity class 1 and 2 mediated the effects of air pollutants on COVID-19 risks (p < 0.05). However, no direct causal relationship was observed between air pollution and COVID-19.ConclusionOur study suggested that exposure to heavy air pollutants causally increased risks for obesity. Besides, obesity causally increased the risks for COVID-19 phenotypes. Attention needs to be paid to weight status for the population who suffer from heavy air pollution, as they are more likely to be susceptible and vulnerable to COVID-19.

Project description:BackgroundIn the aftermath of the coronavirus disease 2019 (COVID-19) pandemic, we sought to explore the causal association between COVID-19 and 17 prevalent post-COVID-19 syndrome (PCS) symptoms using Mendelian randomisation (MR) methodology.MethodsWe used 22 extensive genome-wide association study (GWAS) data sets, incorporating genetic variants as instrumental variables. Univariate Mendelian randomisation (UVMR) analyses involved 15 single nucleotide polymorphisms (SNPs) for COVID-19 patients, 33 for hospitalised COVID-19 patients, and 29 for patients with severe respiratory symptoms due to COVID-19. Furthermore, we further used multivariable Mendelian randomisation (MVMR) analyses based on 93 SNPs for COVID-19 patients, 105 for hospitalised COVID-19 patients, and 99 for patients with severe respiratory symptoms due to COVID-19. With these analyses, we aimed to assess the causal associations between varying levels of COVID-19 infection and 17 prevalent PCS symptoms while accounting for the influence of educational and income levels.ResultsUVMR analysis identified potential causal effects of COVID-19 genetic susceptibility on myalgia and pain in various regions. Hospitalised COVID-19 was potentially linked to erectile dysfunction and alopecia areata. Very severe respiratory confirmed patients exhibited increased pain and tobacco use. Meanwhile, the MVMR analysis demonstrated a potential causal link between hospitalised COVID-19 and heart arrhythmia, and a protective effect of COVID-19 on tobacco use after adjusting for educational and income levels.ConclusionsOur MR analysis provides compelling evidence of causal associations between genetic susceptibility to COVID-19 and specific PCS symptoms, in which educational and income levels play a mediating role. These findings shed light on PCS pathogenesis and underscore the importance of considering social factors in its management. Tailored interventions and policies are crucial for PCS-affected individuals' well-being. Further research is needed to explore the impact of social determinants on COVID-19 patients and the wider population.

Dataset Information

Genetic and phenotypic analysis of the causal relationship between aging and COVID-19.

Background

Methods

Results

Conclusions

Publications

Genetic and phenotypic analysis of the causal relationship between aging and COVID-19.

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