Acute and Chronic Post-COVID-19 Conditions: A Study of Genetic Integrity and Clinical Markers, 2025, Martins et al

Acute and Chronic Post-COVID-19 Conditions: A Study of Genetic Integrity and Clinical Markers

Bruna Alves Alonso Martins, Ana Leticia Hilario Garcia, Malu Siqueira Borges, Daiane Dias Ribeiro Nobles, Alana Witt Hansen, Fernando Rosado Spilki, Lavínia Schuler-Faccini, Pabulo Henrique Rampelotto, Juliana da Silva

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Highlights
• Oxidative lesions were detected across all study groups.
• Hematological changes were observed in women with long COVID.
• Men with acute long COVID exhibited significantly higher levels of CRP and ferritin.
• Age-related factors influence the severity of long COVID's systemic effects.

Abstract
The long-term effects of COVID-19 infection on genomic integrity, along with hematological, biochemical, and inflammatory, remain poorly understood. Viral infections, including SARS-CoV-2, are known to induce genomic instability, potentially contributing to the persistence of post-COVID-19 symptoms.

This study aimed to assess genomic instability in individuals with acute and chronic post-COVID-19 conditions, alongside hematological profiles, metabolic parameters, and inflammatory markers, compared to a SARS-CoV-2-negative control group. Participants (n=231) from southern Brazil were stratified into acute post-COVID (n=78), chronic post-COVID (n=79), and control groups (n=74). DNA damage was assessed using alkaline and enzyme-modified comet assays.

Oxidative lesions were detected across all groups, but no significant differences were observed among them.

Correlations with biochemical markers suggest inflammation and oxidative stress as central mechanisms in post-COVID-19 pathophysiology. Hematological and biochemical analyses revealed persistent inflammation, lipid metabolism disruptions, and gender-specific alterations, such as higher levels of inflammatory markers (C-reactive protein and ferritin) and lipid abnormalities in men, whereas women exhibited distinct hematological patterns.

Age-related influences on metabolic and inflammatory markers further illustrate the systemic complexity of post-COVID-19 effects. The chronic group exhibited ongoing but attenuated markers of inflammation and oxidative stress compared to the acute group.

These findings suggest that genetic instability alone may not fully explain the observed clinical manifestations, emphasizing the role of persistent inflammation and metabolic dysregulation. This study provides a comprehensive view of the interplay between genomic instability, inflammation, oxidative damage, and systemic alterations in post-COVID-19 condition. It underscores the importance of a multifaceted approach to understanding disease mechanisms and the need for longitudinal studies to explore the dynamic nature of these alterations and their long-term health implications.

Link (Mutation Research - Genetic Toxicology and Environmental Mutagenesis) [Paywall, Journal Pre-proof]

 

I wish people would tell us what they found rather than what they thought they ought to be looking for.

 

I didn't think viruses could affect your genes. Is that because I've only read the Ladybird Book of Genetics?

 

I think that they’re specifically looking for virus-induced DNA damage in cells, like what UV rays do that eventually leads to skin cancer. Individual cells could end up with some issues in their own copy of the genome

 

So it seems like they were investigating the hypothesis that post-COVID effects were due to viral damage to the genome because evidence of that damage has been found with other viruses. And they found that everyone had evidence of oxidative damage in their DNA regardless of whether they had COVID or not, so that theory can be scratched off the board.

 

Fig 3: Similarly no change in hemotological parameters between groups

In the next section, examining biochemical parameters (Fig 4):

Fig 4: However overall, their panel is not able to differentiate the groups so they are not strong differences.

I don't really see the point in their later correlation analyses if those parameters were not significantly different between control and COVID groups to begin with.