Causal association of epigenetic aging and COVID-19 severity and susceptibility: A bidirectional Mendelian randomization study

Abstract

Observational data from China, the United States, France, and Italy suggest that chronological age is an adverse COVID-19 outcome risk factor, with older patients having a higher severity and mortality rate than younger patients. Most studies have gotten the same view. However, the role of aging in COVID-19 adverse effects is unclear. To more accurately assess the effect of aging on adverse COVID-19, we conducted this bidirectional Mendelian randomization (MR) study. Epigenetic clocks and telomere length were used as biological indicators of aging. Data on epigenetic age (PhenoAge, GrimAge, Intrinsic HorvathAge, and HannumAge) were derived from an analysis of biological aging based on genome-wide association studies (GWAS) data. The telomere length data are derived from GWAS and the susceptibility and severity data are derived from the COVID-19 Host Genetics Initiative (HGI). Firstly, epigenetic age and telomere length were used as exposures, and following a screen for appropriate instrumental variables, we used random-effects inverse variance weighting (IVW) for the main analysis, and combined it with other analysis methods (e.g., MR Egger, Weighted median, simple mode, Weighted mode) and multiple sensitivity analysis (heterogeneity analysis, horizontal multiplicity analysis, "leave-one-out" analysis). For reducing false-positive rates, Bonferroni corrected significance thresholds were used. A reverse Mendelian randomization analysis was subsequently performed with COVID-19 susceptibility and severity as the exposure. The results of the MR analysis showed no significant differences in susceptibility to aging and COVID-19. It might suggest that aging is not a risk factor for COVID-19 infection (P-values are in the range of 0.05-0.94). According to the results of our analysis, we found that aging was not a risk factor for the increased severity of COVID-19 (P > 0.05). However, severe COVID-19 can cause telomere lengths to become shorter (beta = -0.01; se = 0.01; P = 0.02779). In addition to this, severe COVID-19 infection can slow the acceleration of the epigenetic clock "GrimAge" (beta = -0.24, se = 0.07, P = 0.00122), which may be related to the closely correlation of rs35081325 and COVID-19 severity. Our study provides partial evidence for the causal effects of aging on the susceptibility and severity of COVID-19.

Keywords: COVID-19; Mendelian randomization; SARS-CoV-2; aging; epigenetic age; genome-wide association study (GWAS); telomere length.

FIGURE 1

BidirectionalMendelian randomization paradigm and assumptions of aging and COVID-19. Mendelian randomization assumptions: (1)the instrument variants must be closely related to the exposure, (2) the instrument variants must be independent of any confounder of the exposure-outcome association, (3) the instrument variants must be associated with the outcome only viathe exposure.

FIGURE 2

Inverse variance weighted (IVW) method was used as the main method to analyze the causal association between aging and susceptibility and severity of COVID-19. Aging is based on epigenetic age (PhenoAge, GrimAge, Hannum, HorvathAge) and telomere length as biological indicators. Beta: risk index; Se: standard error; OR (95% CI): odds ratio (95% confidence interval); Forest plot: Visualize the causal effect of exposure on the risk of outcome by IVW method [The standard line is the line of “X = 1” (red dashed line)], The blue marker dot is a positive result of P < 0.05).

FIGURE 3

MR “leave-one-out” sensitivity analysis “COVID-19 severity” on “GrimAge.” “Leave-one-out” plot to visualize the causal effect of COVID-19 severity on the risk of GrimAge when leaving one SNP out.

FIGURE 4

Scatter plots of aging and COVID-19 susceptibility and severity. Horizontal ordinate: SNP effect on “exposure”; Vertical coordinates: SNP effect on “outcome.” (A) Exposure: PhenoAge, outcome: severity; (B) exposure: PhenoAge, outcome: susceptibility; (C) exposure: GrimAge, outcome: severity; (D) exposure: GrimAge, outcome: susceptibility; (E) exposure: HorvathAge, outcome: severity; (F) exposure: HannumAge, outcome: susceptibility; (G) exposure: telomere length, outcome: severity; (H) exposure: HorvathAge, outcome: susceptibility; (I) exposure: telomere length, outcome: susceptibility.

FIGURE 5

Scatter plots of COVID-19 susceptibility and severity and aging. Horizontal ordinate: SNP effect on “exposure”; Vertical coordinates: SNP effect on “outcome.” (J) Exposure: severity, outcome: PhenoAge; (K) exposure: susceptibility, outcome: PhenoAge; (L) exposure: severity, outcome: GrimAge; (M) exposure: susceptibility, outcome: GrimAge; (N) exposure: severity, outcome: HannumAge; (O) exposure: susceptibility, outcome: HannumAge; (P) exposure: severity, outcome: HorvathAge; (Q) exposure: susceptibility, outcome: HorvathAge; (R) exposure: severity, outcome: telomere length; (S) exposure: susceptibility, outcome: telomere length.