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pmid:34895312
Risk-focused differences in molecular processes implicated in SARS-CoV-2 infection: corollaries in DNA methylation and gene expression.
Chaini Konwar · Rebecca Asiimwe · Amy M Inkster · Sarah M Merrill · Gian L Negri · Maria J Aristizabal · Christopher F Rider · Julie L MacIsaac · Christopher Carlsten · Michael S Kobor
Epigenetics & chromatin · 2021 doi:10.1186/s13072-021-00428-1
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Complete file
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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).\nMETHODS: 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.\nRESULTS: 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 Δβ > 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, Δβ > 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, Δβ > 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, Δβ > 0.05).\nCONCLUSION: 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 (NO2) 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.", "claims": [{"id": "claim-method", "statement": "To investigate sex associated DNA methylation differences in our candidate genes, we first focused on the infection-relevant respiratory tissues (lung, nasal epithelia, and airway epithelia) and applied a linear model on M values for each CpG site using the R limma package. Sex was included as the main effect and age and disease status as the covariates. To account for multiple tests, p values were adjusted using the FDR method.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34895312", "locator": "sections[7] \"DNA methylation analysis: autosomal loci\" paragraph 2", "quote": "To investigate sex associated DNA methylation differences in our candidate genes, we first focused on the infection-relevant respiratory tissues (lung, nasal epithelia, and airway epithelia) and applied a linear model on M values for each CpG site using the R limma package. Sex was included as the main effect and age and disease status as the covariates. To account for multiple tests, p values were adjusted using the FDR method."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Accession numbers for the publicly available data sets utilized in the study are mentioned in the methods section. Data needed to evaluate the paper are either presented in the manuscript and/or the Supplementary Materials. The controlled human exposure data set utilized in the current study is available on the KoborLab Github repository (https://github.com/kobor-lab/Data). Additional relevant data, if required is available on request. Data preprocessing R scripts are available on the KoborLab Github repository (https://github.com/kobor-lab/Public-Scripts/tree/master/COVID-19).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34895312", "locator": "sections[28] \"notes\" paragraph 1", "quote": "Accession numbers for the publicly available data sets utilized in the study are mentioned in the methods section. Data needed to evaluate the paper are either presented in the manuscript and/or the Supplementary Materials. The controlled human exposure data set utilized in the current study is available on the KoborLab Github repository (https://github.com/kobor-lab/Data). Additional relevant data, if required is available on request. Data preprocessing R scripts are available on the KoborLab Github repository (https://github.com/kobor-lab/Public-Scripts/tree/master/COVID-19)."}], "state": "complete"}, {"id": "claim-target-result", "statement": "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.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:34895312", "locator": "sections[0] \"Abstract\" paragraph 4", "quote": "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."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "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.", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:34895312"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. 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[], "expressible": null, "parameters": {}, "data_shapes": [], "evidence": {"score": 1.0, "band": "verbatim", "quote": "To investigate sex associated DNA methylation differences in our candidate genes, we first focused on the infection-relevant respiratory tissues (lung, nasal epithelia, and airway epithelia) and applied a linear model on M values for each CpG site using the R limma package. 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The physical bench the paper used is not, so a physical validation cannot be run here."}, "data": {"tier": "R1", "reachable": true, "accessions": ["GSE101641", "GSE104471", "GSE65163", "GSE85568", "GSE137716", "GSE111629", "GSE174818", "GSE111396", "GSE52401", "GSE65205"], "resolved_accessions": ["GSE101641", "GSE104471", "GSE65163", "GSE85568", "GSE137716", "GSE111629", "GSE174818", "GSE111396", "GSE52401", "GSE65205"], "statements": ["Accession numbers for the publicly available data sets utilized in the study are mentioned in the methods section. Data needed to evaluate the paper are either presented in the manuscript and/or the Supplementary Materials. The controlled human exposure data set utilized in the current study is available on the KoborLab Github repository (https://github.com/kobor-lab/Data). Additional relevant data, if required is available on request. Data preprocessing R scripts are available on the KoborLab Github repository (https://github.com/kobor-lab/Public-Scripts/tree/master/COVID-19)."], "basis": "The paper names GSE101641, GSE104471, GSE65163, GSE85568, GSE137716, GSE111629, GSE174818, GSE111396, GSE52401, GSE65205 in GEO and the accession resolves in the repository. 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