Blood DNA methylation and COVID-19 outcomes

Abstract

Background There are no prior reports that compare differentially methylated regions of DNA in blood samples from COVID-19 patients to samples collected before the SARS-CoV-2 pandemic using a shared epigenotyping platform. We performed a genome-wide analysis of circulating blood DNA CpG methylation using the Infinium Human MethylationEPIC BeadChip on 124 blood samples from hospitalized COVID-19-positive and COVID-19-negative patients and compared these data with previously reported data from 39 healthy individuals collected before the pandemic. Prospective outcome measures such as COVID-19-GRAM risk-score and mortality were combined with methylation data. Results Global mean methylation levels did not differ between COVID-19 patients and healthy pre-pandemic controls. About 75% of acute illness-associated differentially methylated regions were located near gene promoter regions and were hypo-methylated in comparison with healthy pre-pandemic controls. Gene ontology analyses revealed terms associated with the immune response to viral infections and leukocyte activation; and disease ontology analyses revealed a predominance of autoimmune disorders. Among COVID-19-positive patients, worse outcomes were associated with a prevailing hyper-methylated status. Recursive feature elimination identified 77 differentially methylated positions predictive of COVID-19 severity measured by the GRAM-risk score. Conclusion Our data contribute to the awareness that DNA methylation may influence the expression of genes that regulate COVID-19 progression and represent a targetable process in that setting.

Epigenetic Clocks Are Not Accelerated in COVID-19 Patients

“…The discrepancy might be attributed to the even smaller sample number of COVID-19 samples in the other study (n = 9) and to the application of epigenetic clocks that were specifically trained to capture changes in the leukocyte composition [8], which is clearly affected by the disease. On the other hand, there have been epigenome-wide association studies with COVID-19 severity that clearly demonstrate specific DNA methylation changes that are directly linked to the disease [9,10]. Despite such changes in the DNA methylation landscape of COVID-19 patients, our analysis with four aging-signatures and different available datasets demonstrate that epigenetic clocks are not generally affected in patients with severe outcome.…”

“…In this study, we used blood samples of 50 hospitalized patients with severe SARS-CoV-2 infection, with or without acute respiratory distress syndrome (ARDS) (Supplementary Table S1). In addition, we used available DNA methylation profiles generated with the Illumina EPIC BeadChips of 102 hospitalized COVID-19 patients (GSE174818) [9], of 407 COVID-19 patients with both mild or severe symptoms (GSE168739) [10], and of 9 COVID-19 patients from our hospital (GSE161988). For comparison, we utilized datasets of healthy donors, which were generated before the pandemic (GSE123914, GSE42861, and GSE61496).…”

Increased risk of severe clinical course of COVID-19 in carriers of HLA-C*04:01

“…Importantly these findings were reproduced in an independent public data set obtained from patients with COVID-19 at Albany Medical Center, in the United States using RNA sequencing [ 17 , 18 ] and a data set from the University of California, San Francisco, United States. Using this approach, we demonstrated broad applicability of our findings and confirmed reproducibility in data gathered through a distinct method – the analysis of the transcriptome [34] .…”

“…All patients of the Charité Universitätsmedizin Berlin are included in data set 1 (DS1) and patients from Switzerland and Spain in data set 2 (DS2) according to the sequence of their enrollment into the study. In addition to the 288 patients recruited for this study (DS1 and DS2), we used data from a public data set containing RNA sequencing data for a total of 99 patients with COVID-19 containing phenotypic information on requirement for intensive care or intubation (https://www.ncbi.nlm.nih.gov/geo; GSE157103 [17] , GSE174818 [18] ) and for 48 patients with COVID-19 enrolled in the UCSF COVID-19 Multiphenotyping for Effective Therapies (COMET) Cohort with available RNA sequencing data (data set 3, DS3; Supplemental Table 1). Through inclusion of multiple international data sets we tested for broad applicability of our results.…”

Epigenetic Mechanisms Underlying COVID-19 Pathogenesis

“…The DNA methylation status in the host is reported to change with bacterial and viral infections [82], and analysis of the DNA methylation state is expected to aid in estimating the infection history and future disease severity [83]. Balnis et al performed a comprehensive DNA methylation analysis using blood from hospitalized patients (COVID-19 and non-COVID-19) and healthy individuals [84] (Figure 2c) and found that although global DNA methylation levels did not differ between healthy and hospitalized individuals, 1089 hypo-differentially methylated regions (DMRs) and 416 hyper DMRs were found [84]. In addition, a comparison between patients with and without COVID-19 revealed 47 COVID-19 patient-specific DMRs, 36 of which were inversely correlated with the expression of neighboring genes.…”