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Updated: Jun 20, 2025

Sample Preparation to Bioinformatics Analysis of DNA Methylation: Association Strategy for Obesity and Related Trait Studies
Published on: May 6, 2022
Blood DNA methylation in post-acute sequelae of COVID-19 (PASC): a prospective cohort study
Joseph Balnis1, Andy Madrid2, Lisa A Drake1
1Division of Pulmonary and Critical Care Medicine, Albany Medical Center, Albany, NY, USA; Department of Molecular and Cellular Physiology, Albany Medical College, Albany, NY, USA.
Background:
DNA methylation integrates environmental signals with transcriptional programs. COVID-19 infection induces changes in the host methylome. While post-acute sequelae of COVID-19 (PASC) is a long-term complication of acute illness, its association with DNA methylation is unknown. No universal blood marker of PASC, superseding single organ dysfunctions, has yet been identified.
Methods:
In this single centre prospective cohort study, PASC, post-COVID without PASC, and healthy participants were enrolled to investigate their symptoms association with peripheral blood DNA methylation data generated with state-of-the-art whole genome sequencing. PASC-induced quality-of-life deterioration was scored with a validated instrument, SF-36. Analyses were conducted to identify potential functional roles of differentially methylated loci, and machine learning algorithms were used to resolve PASC severity.
Findings:
103 patients with PASC (22.3% male, 77.7% female), 15 patients with previous COVID-19 infection but no PASC (40.0% male, 60.0% female), and 27 healthy volunteers (48.1% male, 51.9% female) were enrolled. Whole genome methylation sequencing revealed 39 differentially methylated regions (DMRs) specific to PASC, each harbouring an average of 15 consecutive positions, that differentiate patients with PASC from the two control groups. Motif analyses of PASC-regulated DMRs identify binding domains for transcription factors regulating circadian rhythm and others. Some DMRs annotated to protein coding genes were associated with changes of RNA expression. Machine learning support vector algorithm and random forest hierarchical clustering reveal 28 unique differentially methylated positions (DMPs) in the genome discriminating patients with better and worse quality of life.
Interpretation:
Blood DNA methylation levels identify PASC, stratify PASC severity, and suggest that DNA motifs are targeted by circadian rhythm-regulating pathways in PASC.
Funding:
This project has been funded by the following agencies: NIH-AI173035 (A. Jaitovich and R. Alisch); and NIH-AG066179 (R. Alisch).

