scholarly journals Association of Asthma and Rhinitis with Epigenetics of Coronavirus Related Genes

2021 ◽  
Vol 14 ◽  
pp. 251686572110392
Author(s):  
Aniruddha Rathod ◽  
Rutu Rathod ◽  
Hongmei Zhang ◽  
Parnian Kheirkhah Rahimabad ◽  
Wilfried Karmaus ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Significant Interaction ◽  
Total N ◽  
Isle Of Wight ◽  
Susceptibility Factors ◽  
Sex Assessment ◽  
Sex Specificity ◽  
Functional Relevance ◽  
Linear Regressions

Introduction: Susceptibility factors for coronavirus disease 2019 (COVID-19) include sex and medical conditions such as asthma and rhinitis. DNA methylation (DNAm) is associated with asthma, rhinitis, and several viruses. We examined associations of asthma/rhinitis with DNAm at CpGs located on coronavirus related genes, and if these associations were sex-specific. Methods: In total, n = 242 subjects aged 26 years from the Isle of Wight Birth Cohort were included in the study. Linear regressions were used to examine sex specific and non-specific associations of DNAm at CpGs on coronavirus related genes with asthma/rhinitis status. Associations of DNAm with gene expression in blood were assessed for functional relevance of identified CpGs. Results: Statistically significant interaction effects of asthma or rhinitis with sex were identified at 40 CpGs for asthma and 27 CpGs for rhinitis. At 21 CpGs, DNAm was associated with asthma, and at 45 CpGs with rhinitis, regardless of sex. Assessment of functional relevance of the identified CpGs indicated a potential of epigenetic regulatory functionality on gene activity at 14 CpGs for asthma and 17 CpGs for rhinitis, and of those 6 CpGs for asthma and 7 CpGs for rhinitis were likely to be sex-specific. Conclusion: Subjects with asthma/rhinitis may have altered susceptibility to COVID-19 due to changes in their DNAm associated with these conditions. Sex specificity on association of asthma/rhinitis with DNAm at certain CpGs, and on the association of DNAm at asthma/rhinitis-linked CpGs with gene expression have the potential to explain the reported sex-specificity in COVID-19 morbidity and mortality.

scholarly journals DNA methylation QTL analysis identifies new regulators of human longevity

2020 ◽  
Vol 29 (7) ◽  
pp. 1154-1167 ◽  
Author(s):  
Silke Szymczak ◽  
Janina Dose ◽  
Guillermo G Torres ◽  
Femke-Anouska Heinsen ◽  
Geetha Venkatesh ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Complex Trait ◽  
Human Longevity ◽  
Reduced Representation ◽  
Age Related ◽  
Reduced Representation Bisulfite Sequencing ◽  
Genetic And Environmental Factors ◽  
Functional Relevance ◽  
Study Participants

Abstract Human longevity is a complex trait influenced by both genetic and environmental factors, whose interaction is mediated by epigenetic mechanisms like DNA methylation. Here, we generated genome-wide whole-blood methylome data from 267 individuals, of which 71 were long-lived (90–104 years), by applying reduced representation bisulfite sequencing. We followed a stringent two-stage analysis procedure using discovery and replication samples to detect differentially methylated sites (DMSs) between young and long-lived study participants. Additionally, we performed a DNA methylation quantitative trait loci analysis to identify DMSs that underlie the longevity phenotype. We combined the DMSs results with gene expression data as an indicator of functional relevance. This approach yielded 21 new candidate genes, the majority of which are involved in neurophysiological processes or cancer. Notably, two candidates (PVRL2, ERCC1) are located on chromosome 19q, in close proximity to the well-known longevity- and Alzheimer’s disease-associated loci APOE and TOMM40. We propose this region as a longevity hub, operating on both a genetic (APOE, TOMM40) and an epigenetic (PVRL2, ERCC1) level. We hypothesize that the heritable methylation and associated gene expression changes reported here are overall advantageous for the LLI and may prevent/postpone age-related diseases and facilitate survival into very old age.

scholarly journals Risk-focused differences in molecular processes implicated in SARS-CoV-2 infection: corollaries in DNA methylation and gene expression

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Chaini Konwar ◽  
Rebecca Asiimwe ◽  
Amy M. Inkster ◽  
Sarah M. Merrill ◽  
Gian L. Negri ◽  
...  
Keyword(s):  
Gene Expression ◽  
Risk Factors ◽  
Dna Methylation ◽  
Bronchoalveolar Lavage ◽  
Molecular Basis ◽  
Expression Patterns ◽  
Data Set ◽  
Susceptibility Factors ◽  
Increased Risk ◽  
Methylation Patterns

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 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). 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 (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.

DNA Methylation Inhibites ANXA1 Gene Expression in Nasopharyngeal Carcinoma Cell Lines*

2009 ◽  
Vol 36 (10) ◽  
pp. 1319-1326 ◽  
Author(s):  
Shuang-Xiang TAN ◽  
Rui-Cheng HU ◽  
Ai-Guo DAI ◽  
Cen-E TANG ◽  
Hong YI ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Nasopharyngeal Carcinoma ◽  
Cell Lines ◽  
Carcinoma Cell ◽  
Nasopharyngeal Carcinoma Cell ◽  
Carcinoma Cell Lines

scholarly journals Epigenetic Changes During Mechanically Induced Osteogenic Lineage Commitment

2015 ◽  
Vol 137 (2) ◽  
Author(s):  
Julia C. Chen ◽  
Mardonn Chua ◽  
Raymond B. Bellon ◽  
Christopher R. Jacobs
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Shear Stress ◽  
Fluid Shear Stress ◽  
Methylation Status ◽  
Lineage Commitment ◽  
Fluid Shear ◽  
Osteogenic Lineage ◽  
Osteogenic Markers ◽  
Heterochromatin Structure

Osteogenic lineage commitment is often evaluated by analyzing gene expression. However, many genes are transiently expressed during differentiation. The availability of genes for expression is influenced by epigenetic state, which affects the heterochromatin structure. DNA methylation, a form of epigenetic regulation, is stable and heritable. Therefore, analyzing methylation status may be less temporally dependent and more informative for evaluating lineage commitment. Here we analyzed the effect of mechanical stimulation on osteogenic differentiation by applying fluid shear stress for 24 hr to osteocytes and then applying the osteocyte-conditioned medium (CM) to progenitor cells. We analyzed gene expression and changes in DNA methylation after 24 hr of exposure to the CM using quantitative real-time polymerase chain reaction and bisulfite sequencing. With fluid shear stress stimulation, methylation decreased for both adipogenic and osteogenic markers, which typically increases availability of genes for expression. After only 24 hr of exposure to CM, we also observed increases in expression of later osteogenic markers that are typically observed to increase after seven days or more with biochemical induction. However, we observed a decrease or no change in early osteogenic markers and decreases in adipogenic gene expression. Treatment of a demethylating agent produced an increase in all genes. The results indicate that fluid shear stress stimulation rapidly promotes the availability of genes for expression, but also specifically increases gene expression of later osteogenic markers.

scholarly journals DNA methylation and gene expression integration in cardiovascular disease

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Guillermo Palou-Márquez ◽  
Isaac Subirana ◽  
Lara Nonell ◽  
Alba Fernández-Sanlés ◽  
Roberto Elosua
Keyword(s):  
Gene Expression ◽  
Cardiovascular Disease ◽  
Dna Methylation ◽  
Cardiovascular Diseases ◽  
Disease Risk ◽  
Cardiovascular Disease Risk ◽  
Risk Function ◽  
Predictive Biomarkers ◽  
Independent Study ◽  
Cell Type

Abstract Background The integration of different layers of omics information is an opportunity to tackle the complexity of cardiovascular diseases (CVD) and to identify new predictive biomarkers and potential therapeutic targets. Our aim was to integrate DNA methylation and gene expression data in an effort to identify biomarkers related to cardiovascular disease risk in a community-based population. We accessed data from the Framingham Offspring Study, a cohort study with data on DNA methylation (Infinium HumanMethylation450 BeadChip; Illumina) and gene expression (Human Exon 1.0 ST Array; Affymetrix). Using the MOFA2 R package, we integrated these data to identify biomarkers related to the risk of presenting a cardiovascular event. Results Four independent latent factors (9, 19, 21—only in women—and 27), driven by DNA methylation, were associated with cardiovascular disease independently of classical risk factors and cell-type counts. In a sensitivity analysis, we also identified factor 21 as associated with CVD in women. Factors 9, 21 and 27 were also associated with coronary heart disease risk. Moreover, in a replication effort in an independent study three of the genes included in factor 27 were also present in a factor identified to be associated with myocardial infarction (CDC42BPB, MAN2A2 and RPTOR). Factor 9 was related to age and cell-type proportions; factor 19 was related to age and B cells count; factor 21 pointed to human immunodeficiency virus infection-related pathways and inflammation; and factor 27 was related to lifestyle factors such as alcohol consumption, smoking and body mass index. Inclusion of factor 21 (only in women) improved the discriminative and reclassification capacity of the Framingham classical risk function and factor 27 improved its discrimination. Conclusions Unsupervised multi-omics data integration methods have the potential to provide insights into the pathogenesis of cardiovascular diseases. We identified four independent factors (one only in women) pointing to inflammation, endothelium homeostasis, visceral fat, cardiac remodeling and lifestyles as key players in the determination of cardiovascular risk. Moreover, two of these factors improved the predictive capacity of a classical risk function.

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