Risk-focused differences in molecular processes implicated in SARS-CoV-2 infection: corollaries in DNA methylation and gene expression
Bibliographic record
Abstract
Abstract Background Understanding the molecular basis of susceptibility factors to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is a global health imperative. It is well-established that males are more likely to acquire SARS-CoV-2 infection and exhibit more severe outcomes. Similarly, exposure to air pollutants and pre-existing respiratory chronic conditions, such as asthma and chronic obstructive respiratory disease (COPD) confer an increased risk to coronavirus disease 2019 (COVID-19). Methods We investigated molecular patterns associated with risk factors in 398 candidate genes relevant to COVID-19 biology. To accomplish this, we downloaded DNA methylation and gene expression data sets from publicly available repositories (GEO and GTEx Portal) and utilized data from an empirical controlled human exposure study conducted by our team. Results First, we observed sex-biased DNA methylation patterns in autosomal immune genes, such as NLRP2 , TLE1 , GPX1 , and ARRB2 (FDR < 0.05, magnitude of DNA methylation difference Δ β > 0.05). Second, our analysis on the X-linked genes identified sex associated DNA methylation profiles in genes, such as ACE2 , CA5B , and HS6ST2 (FDR < 0.05, Δ β > 0.05). These associations were observed across multiple respiratory tissues (lung, nasal epithelia, airway epithelia, and bronchoalveolar lavage) and in whole blood. Some of these genes, such as NLRP2 and CA5B , also exhibited sex-biased gene expression patterns. In addition, we found differential DNA methylation patterns by COVID-19 status for genes, such as NLRP2 and ACE2 in an exploratory analysis of an empirical data set reporting on human COVID-9 infections. Third, we identified modest DNA methylation changes in CpGs associated with PRIM2 and TATDN1 (FDR < 0.1, Δ β > 0.05) in response to particle-depleted diesel exhaust in bronchoalveolar lavage. Finally, we captured a DNA methylation signature associated with COPD diagnosis in a gene involved in nicotine dependence ( COMT ) (FDR < 0.1, Δ β > 0.05). Conclusion Our findings on sex differences might be of clinical relevance given that they revealed molecular associations of sex-biased differences in COVID-19. Specifically, our results hinted at a potentially exaggerated immune response in males linked to autosomal genes, such as NLRP2. In contrast, our findings at X-linked loci such as ACE2 suggested a potentially distinct DNA methylation pattern in females that may interact with its mRNA expression and inactivation status. We also found tissue-specific DNA methylation differences in response to particulate exposure potentially capturing a nitrogen dioxide (NO 2 ) effect—a contributor to COVID-19 susceptibility. While we identified a molecular signature associated with COPD, all COPD-affected individuals were smokers, which may either reflect an association with the disease, smoking, or may highlight a compounded effect of these two risk factors in COVID-19. Overall, our findings point towards a molecular basis of variation in susceptibility factors that may partly explain disparities in the risk for SARS-CoV-2 infection.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".