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Epigenetic Clocks Are Not Accelerated in COVID-19 Patients.

ABSTRACT: Age is a major risk factor for severe outcome of the 2019 coronavirus disease (COVID-19). In this study, we followed the hypothesis that particularly patients with accelerated epigenetic age are affected by severe outcomes of COVID-19. We investigated various DNA methylation datasets of blood samples with epigenetic aging signatures and performed targeted bisulfite amplicon sequencing. Overall, epigenetic clocks closely correlated with the chronological age of patients, either with or without acute respiratory distress syndrome. Furthermore, lymphocytes did not reveal significantly accelerated telomere attrition. Thus, these biomarkers cannot reliably predict higher risk for severe COVID-19 infection in elderly patients.

SUBMITTER: Franzen J

PROVIDER: S-EPMC8431654 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:The host epigenetic landscape rapidly changes during SARS-CoV-2 infection, and evidence suggest that severe COVID-19 is associated with durable scars to the epigenome. Specifically, aberrant DNA methylation changes in immune cells and alterations to epigenetic clocks in blood relate to severe COVID-19. However, a longitudinal assessment of DNA methylation states and epigenetic clocks in blood from healthy individuals prior to and following test-confirmed non-hospitalized COVID-19 has not been performed. Moreover, the impact of mRNA COVID-19 vaccines upon the host epigenome remains understudied. Here, we first examined DNA methylation states in the blood of 21 participants prior to and following test-confirmed COVID-19 diagnosis at a median time frame of 8.35 weeks; 756 CpGs were identified as differentially methylated following COVID-19 diagnosis in blood at an FDR adjusted p-value < 0.05. These CpGs were enriched in the gene body, and the northern and southern shelf regions of genes involved in metabolic pathways. Integrative analysis revealed overlap among genes identified in transcriptional SARS-CoV-2 infection datasets. Principal component-based epigenetic clock estimates of PhenoAge and GrimAge significantly increased in people over 50 following infection by an average of 2.1 and 0.84 years. In contrast, PCPhenoAge significantly decreased in people fewer than 50 following infection by an average of 2.06 years. This observed divergence in epigenetic clocks following COVID-19 was related to age and immune cell-type compositional changes in CD4+ T cells, B cells, granulocytes, plasmablasts, exhausted T cells, and naïve T cells. Complementary longitudinal epigenetic clock analyses of 36 participants prior to and following Pfizer and Moderna mRNA-based COVID-19 vaccination revealed that vaccination significantly reduced principal component-based Horvath epigenetic clock estimates in people over 50 by an average of 3.91 years for those who received Moderna. This reduction in epigenetic clock estimates was significantly related to chronological age and immune cell-type compositional changes in B cells and plasmablasts pre- and post-vaccination. These findings suggest the potential utility of epigenetic clocks as a biomarker of COVID-19 vaccine responses. Future research will need to unravel the significance and durability of short-term changes in epigenetic age related to COVID-19 exposure and mRNA vaccination.

Project description:BackgroundCardiovascular health (CVH) was defined by the American Heart Association as an integrative idealness of seven clinical or lifestyle factors. Based on populations of European ancestry, recent studies have shown that ideal CVH is associated with a slower aging rate. The aging rate is measured by levels of epigenetic age acceleration (EAA), usually obtained from the residuals of regressing DNA methylation (DNAm) age on chronological age. However, little has been known about the association of CVH with biological aging in Asian populations.Methods and resultsWe here analyzed blood DNAm data and clinical/lifestyle factors of 2474 Taiwan Biobank (TWB) participants, to investigate the association of CVH with EAA. CVH was assessed by seven components: smoking status, physical activity, dietary habits, body mass index, total cholesterol, fasting glucose, and blood pressure levels. Four measures of EAA were applied, among which two were based on the first-generation DNAm clocks (HannumEAA and IEAA) and two were based on the second-generation clocks (PhenoEAA and GrimEAA). After excluding 276 individuals with cardiovascular diseases, we regressed EAA on the CVH score (ranging from 0 to 7, integrating the abovementioned seven components) while adjusting for sex, drinking status, and educational attainment. Our results showed that a decrease in one point in the CVH score was associated with a 0.350-year PhenoEAA (p = 4.5E-4) and a 0.499-year GrimEAA (p = 4.2E-15). By contrast, HannumEAA and IEAA were not significantly associated with the CVH score. We have obtained consistent results within each generation of epigenetic clocks.ConclusionsThis is one of the first studies to comprehensively investigate the associations of CVH with four epigenetic clocks. Our TWB data showed that ideal CVH is associated with lower levels of EAA calculated according to the second-generation epigenetic clocks (PhenoEAA and GrimEAA). Having an ideal CVH status can lower EAA and reduce the risk of aging-related disorders.

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Epigenetic Clocks Are Not Accelerated in COVID-19 Patients.

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