DNA methylation predicts the outcome of COVID-19 patients with acute respiratory distress syndrome

Evaluation of methylation changes in blood cells of COVID-19 patients as a biomarker of severity of the infection

BACKGROUND

A number of studies have shown that methylomes of blood cells of COVID-19 patients display infection-related methylation changes. Those methylation abnormalities were associated with clinical outcomes of the infection and, thus, can potentially be utilized as biomarkers in clinical COVID-19 management. However, a number of parameters need to be assessed, before a clinical use of a biomarker candidate is proposed, with the most important one being reproducible detection in independent target populations.

METHODS

We benchmarked data reported in publications investigating genome-wide methylation changes occurring in blood cells during SARS-CoV-2 virus infection to assess potential applicability of these changes as biomarkers in clinical management of COVID-19 patients.

RESULTS

We identified nine studies, in which infection-related genome-wide methylation changes in blood cells of COVID-19 patients were reported and associations of those changes with outcomes of the infection was assessed. Our benchmarking analysis showed that each of those studies included patients with different clinical characteristics and each study utilized different symptoms assessment criteria. Most importantly, no uniform data analysis methodologies to identify virus-related methylation changes were used in the analyzed studies. Consequently, analyzed studies, except for one, which was based on uniform data analysis workflow applied across independent patient cohorts, reported sufficiently uniform results that would allow to propose the use of the identified infection-related methylation changes as biomarkers for clinical management of COVID-19 patients.

CONCLUSIONS

Due to lack of coherence between studies reporting SARS-CoV-2 associated methylation changes in blood, the potential use of already reported methylation changes as biomarkers for clinical management of COVID-19 patients needs to be further assessed in rigorously controlled studies. At the same time unified data analysis framework appears to be the most critical in development of biomarkers associated with the severity of SARS-CoV-2 infection.

The micro-RNA expression profile predicts the severity of SARS-CoV-2 infection

Although much is known about the pathophysiology of severe COVID-19, there are still areas that remain to be determined. It is well established that the pivotal molecular event is a hyperinflammatory response also referred to as a cytokine storm. The aim of this retrospective cohort study was to determine miRNAs which might be predictive for the admission to the intensive care unit (ICU). We analyzed blood samples from 210 COVID-19 patients and the control group consisted of 80 healthy individuals. Results revealed the miRNA expression pattern has the potential to predict the severity of COVID-19, reflecting the clinical symptoms of the infection, such as the need for oxygen therapy and concomitant pneumonia. In particular, low expression of miRNAs miR106a-5p, miR17-5p, miR181a-5p, miR191-5p, miR20a-5p and miR451a, especially in the initial phase of the disease, is associated with an unfavorable clinical course of SARS-CoV-2 infection (admission to the ICU).

Advancements in omics technologies: Molecular mechanisms of acute lung injury and acute respiratory distress syndrome (Review)

Acute lung injury (ALI)/acute respiratory distress syndrome (ARDS) is an inflammatory response arising from lung and systemic injury with diverse causes and associated with high rates of morbidity and mortality. To date, no fully effective pharmacological therapies have been established and the relevant underlying mechanisms warrant elucidation, which may be facilitated by multi‑omics technology. The present review summarizes the application of multi‑omics technology in identifying novel diagnostic markers and therapeutic strategies of ALI/ARDS as well as its pathogenesis.

The COVID-19 legacy: consequences for the human DNA methylome and therapeutic perspectives

The COVID-19 pandemic has left a lasting legacy on human health, extending beyond the acute phase of infection. This article explores the evidence suggesting that SARS-CoV-2 infection can induce persistent epigenetic modifications, particularly in DNA methylation patterns, with potential long-term consequences for individuals' health and aging trajectories. The review discusses the potential of DNA methylation-based biomarkers, such as epigenetic clocks, to identify individuals at risk for accelerated aging and tailor personalized interventions. Integrating epigenetic clock analysis into clinical management could mark a new era of personalized treatment for COVID-19, possibly helping clinicians to understand patient susceptibility to severe outcomes and establish preventive strategies. Several valuable reviews address the role of epigenetics in infectious diseases, including the Sars-CoV-2 infection. However, this article provides an original overview of the current understanding of the epigenetic dimensions of COVID-19, offering insights into the long-term health implications of the pandemic. While acknowledging the limitations of current data, we emphasize the need for future research to unravel the precise mechanisms underlying COVID-19-induced epigenetic changes and to explore potential approaches to target these modifications.

Epigenetic patterns, accelerated biological aging, and enhanced epigenetic drift detected 6 months following COVID-19 infection: insights from a genome-wide DNA methylation study

BACKGROUND

The epigenetic status of patients 6-month post-COVID-19 infection remains largely unexplored. The existence of long-COVID, or post-acute sequelae of SARS-CoV-2 infection (PASC), suggests potential long-term changes. Long-COVID includes symptoms like fatigue, neurological issues, and organ-related problems, regardless of initial infection severity. The mechanisms behind long-COVID are unclear, but virus-induced epigenetic changes could play a role.

METHODS AND RESULTS

Our study explores the lasting epigenetic impacts of SARS-CoV-2 infection. We analyzed genome-wide DNA methylation patterns in an Italian cohort of 96 patients 6 months after COVID-19 exposure, comparing them to 191 healthy controls. We identified 42 CpG sites with significant methylation differences (FDR < 0.05), primarily within CpG islands and gene promoters. Dysregulated genes highlighted potential links to glutamate/glutamine metabolism, which may be relevant to PASC symptoms. Key genes with potential significance to COVID-19 infection and long-term effects include GLUD1, ATP1A3, and ARRB2. Furthermore, Horvath's epigenetic clock showed a slight but significant age acceleration in post-COVID-19 patients. We also observed a substantial increase in stochastic epigenetic mutations (SEMs) in the post-COVID-19 group, implying potential epigenetic drift. SEM analysis identified 790 affected genes, indicating dysregulation in pathways related to insulin resistance, VEGF signaling, apoptosis, hypoxia response, T-cell activation, and endothelin signaling.

CONCLUSIONS

Our study provides valuable insights into the epigenetic consequences of COVID-19. Results suggest possible associations with accelerated aging, epigenetic drift, and the disruption of critical biological pathways linked to insulin resistance, immune response, and vascular health. Understanding these epigenetic changes could be crucial for elucidating the complex mechanisms behind long-COVID and developing targeted therapeutic interventions.

The Initial COVID-19 Reliable Interactive DNA Methylation Markers and Biological Implications

Earlier research has established the existence of reliable interactive genomic biomarkers. However, reliable DNA methylation biomarkers, not to mention interactivity, have yet to be identified at the epigenetic level. This study, drawing from 865,859 methylation sites, discovered two miniature sets of Infinium MethylationEPIC sites, each having eight CpG sites (genes) to interact with each other and disease subtypes. They led to the nearly perfect (96.87-100% accuracy) prediction of COVID-19 patients from patients with other diseases or healthy controls. These CpG sites can jointly explain some post-COVID-19-related conditions. These CpG sites and the optimally performing genomic biomarkers reported in the literature become potential druggable targets. Among these CpG sites, cg16785077 (gene MX1), cg25932713 (gene PARP9), and cg22930808 (gene PARP9) at DNA methylation levels indicate that the initial SARS-CoV-2 virus may be better treated as a transcribed viral DNA into RNA virus, i.e., not as an RNA virus that has concerned scientists in the field. Such a discovery can significantly change the scientific thinking and knowledge of viruses.

Restoring the epigenetic landscape of lung microbiome: potential therapeutic approach for chronic respiratory diseases

BACKGROUND

Chronic respiratory diseases, such as chronic obstructive pulmonary disease (COPD) and bronchiectasis, present significant threats to global health. Recent studies have revealed the crucial role of the lung microbiome in the development of these diseases. Pathogens have evolved complex strategies to evade the immune response, with the manipulation of host cellular epigenetic mechanisms playing a pivotal role. There is existing evidence regarding the effects of Pseudomonas on epigenetic modifications and their association with pulmonary diseases. Therefore, this study aims to directly assess the connection between Pseudomonas abundance and chronic respiratory diseases. We hope that our findings will shed light on the molecular mechanisms behind lung pathogen infections.

METHODS

We analyzed data from 366 participants, including individuals with COPD, acute exacerbations of COPD (AECOPD), bronchiectasis, and healthy individuals. Previous studies have given limited attention to the impact of Pseudomonas on these groups and their comparison with healthy individuals. Two independent datasets from different ethnic backgrounds were used for external validation. Each dataset separately analyzed bacteria at the genus level.

RESULTS

The study reveals that Pseudomonas, a bacterium, was consistently found in high concentrations in all chronic lung disease datasets but it was present in very low abundance in the healthy datasets. This suggests that Pseudomonas may influence cellular mechanisms through epigenetics, contributing to the development and progression of chronic respiratory diseases.

CONCLUSIONS

This study emphasizes the importance of understanding the relationship between the lung microbiome, epigenetics, and the onset of chronic pulmonary disease. Enhanced recognition of molecular mechanisms and the impact of the microbiome on cellular functions, along with a better understanding of these concepts, can lead to improved diagnosis and treatment.

Epigenetic age acceleration in surviving versus deceased COVID-19 patients with acute respiratory distress syndrome following hospitalization

BACKGROUND

Aging has been reported as a major risk factor for severe symptoms and higher mortality rates in COVID-19 patients. Molecular hallmarks such as epigenetic alterations and telomere attenuation reflect the biological process of aging. Epigenetic clocks have been shown to be valuable tools for measuring biological age in various tissues and samples. As such, these epigenetic clocks can determine accelerated biological aging and time-to-mortality across various tissues. Previous reports have shown accelerated biological aging and telomere attrition acceleration following SARS-CoV-2 infection. However, the effect of accelerated epigenetic aging on outcome (death/recovery) in COVID-19 patients with acute respiratory distress syndrome (ARDS) has not been well investigated.

RESULTS

In this study, we measured DNA methylation age and telomere attrition in 87 severe COVID-19 cases with ARDS under mechanical ventilation. Furthermore, we compared dynamic changes in epigenetic aging across multiple time points until recovery or death. Epigenetic age was measured using the Horvath, Hannum, DNAm skin and blood, GrimAge, and PhenoAge clocks, whereas telomere length was calculated using the surrogate marker DNAmTL. Our analysis revealed significant accelerated epigenetic aging but no telomere attrition acceleration in severe COVID-19 cases. In addition, we observed epigenetic age deceleration at inclusion versus end of follow-up in recovered but not in deceased COVID-19 cases using certain clocks. When comparing dynamic changes in epigenetic age acceleration (EAA), we detected higher EAA using both the Horvath and PhenoAge clocks in deceased versus recovered patients. The DNAmTL measurements revealed telomere attrition acceleration in deceased COVID-19 patients between inclusion and end of follow-up and a significant change in dynamic telomere attrition acceleration when comparing patients who recovered versus those who died.

CONCLUSIONS

EAA and telomere attrition acceleration were associated with treatment outcomes in hospitalized COVID-19 patients with ARDS. A better understanding of the long-term effects of EAA in COVID-19 patients and how they might contribute to long COVID symptoms in recovered individuals is urgently needed.

Epigenome-wide association study of peripheral immune cell populations in Parkinson's disease

Understanding the contribution of immune mechanisms to Parkinson's disease pathogenesis is an important challenge, potentially of major therapeutic implications. To further elucidate the involvement of peripheral immune cells, we studied epigenome-wide DNA methylation in isolated populations of CD14+ monocytes, CD19+ B cells, CD4+ T cells, and CD8+ T cells from Parkinson's disease patients and healthy control participants. We included 25 patients with a maximum five years of disease duration and 25 controls, and isolated four immune cell populations from each fresh blood sample. Epigenome-wide DNA methylation profiles were generated from 186 samples using the Illumina MethylationEpic array and association with disease status was tested using linear regression models. We identified six differentially methylated CpGs in CD14+ monocytes and one in CD8 + T cells. Four differentially methylated regions were identified in monocytes, including a region upstream of RAB32, a gene that has been linked to LRRK2. Methylation upstream of RAB32 correlated negatively with mRNA expression, and RAB32 expression was upregulated in Parkinson's disease both in our samples and in summary statistics from a previous study. Our epigenome-wide association study of early Parkinson's disease provides evidence for methylation changes across different peripheral immune cell types, highlighting monocytes and the RAB32 locus. The findings were predominantly cell-type-specific, demonstrating the value of isolating purified cell populations for genomic studies.