DNA methylation patterns and disease activity in a longitudinal cohort of lupus patients

Epigenetic dysregulation is implicated in the pathogenesis of lupus. We performed a longitudinal analysis to assess changes in DNA methylation in lupus granulocytes over 4 years of follow up and across disease activity levels using 229 patient samples. We demonstrate that DNA methylation profiles in lupus are influenced by ancestry-specific genetic variants and are highly stable over time. DNA methylation levels in two CpG sites correlated significantly with changes in lupus disease activity. Progressive demethylation in SNX18 was observed with increasing disease activity in African-American patients. Importantly, demethylation of a CpG site located within GALNT18 was associated with the development of active lupus nephritis. Differentially methylated genes between African-American and European-American lupus patients include type I interferon-response genes such as IRF7 and IFI44, and genes related to the NFkB pathway. TREML4, which plays a vital role in toll-like receptor signaling, was hypomethylated in African-American patients and demonstrated a strong cis-meQTL association.

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Atlas of Age- and Tissue-specific DNA Methylation during Early Development of Barley (Hordeum vulgare)

10.20944/preprints201804.0328.v1 ◽

2018 ◽

Cited By ~ 1

Author(s):

Moumouni Konate ◽

Michael J. Wilkinson ◽

Banjamin Mayne ◽

Eileen Scott ◽

Bettina Berger ◽

...

Keyword(s):

Dna Methylation ◽

Hordeum Vulgare ◽

Organ Function ◽

Tissue Specific ◽

Organ Differentiation ◽

Differentiated Cells ◽

Differentially Methylated Genes ◽

Organ Specific ◽

Development And Differentiation ◽

Methylation Patterns

The barley (Hordeum vulgare) genome comprises over 32,000 genes, with differentiated cells expressing only a subset of genes; the remainder being silent. Mechanisms by which tissue-specific genes are regulated are not entirely understood, although DNA methylation is likely to be involved. DNA methylation patterns are not static during plant development, but it is still unclear whether different organs possess distinct methylation profiles. Methylation-sensitive GBS was used to generate DNA methylation profiles for roots, leaf-blades and leaf-sheaths from five barley varieties, using seedlings at the three-leaf stage. Differentially Methylated Markers (DMMs) were characterised by pairwise comparisons of roots, leaf-blades and leaf-sheaths of three different ages. While very many DMMs were found between roots and leaf parts, only a few existed between leaf-blades and leaf-sheaths, with differences decreasing with leaf rank. Organ-specific DMMs appeared to target mainly repeat regions, implying that organ differentiation partially relies on the spreading of DNA methylation from repeats to promoters of adjacent genes. Furthermore, the biological functions of differentially methylated genes in the different organs correlated with functional specialisation. Our results indicate that different organs do possess diagnostic methylation profiles and suggest that DNA methylation is important for both tissue development and differentiation and organ function.

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Stage-differentiated modelling of DNA methylation landscapes uncovers salient biomarkers and prognostic signatures in colorectal cancer progression

10.21203/rs.3.rs-244816/v1 ◽

2021 ◽

Author(s):

Sangeetha Muthamilselvan ◽

Abirami Raghavendran ◽

Ashok Palaniappan

Keyword(s):

Colorectal Cancer ◽

Dna Methylation ◽

Cpg Island ◽

Early Stage ◽

P Value ◽

Consensus Analysis ◽

One Stage ◽

Differentially Methylated Genes ◽

Methylation Patterns ◽

The Impact

Abstract Background: Aberrant DNA methylation acts epigenetically to skew the gene transcription rate up or down, with causative roles in the etiology of cancers. However research on the role of DNA methylation in driving the progression of cancers is limited. In this study, we have developed a comprehensive computational framework for the stage-differentiated modelling of DNA methylation landscapes in colorectal cancer (CRC), and unravelled significant stagewise signposts of CRC progression. Methods: The methylation β - matrix was derived from the public-domain TCGA data, converted into M-value matrix, annotated with AJCC stages, and analysed for stage-salient genes using multiple approaches involving stage-differentiated linear modelling of methylation patterns and/or expression patterns. Differentially methylated genes (DMGs) were identified using a contrast against controls (adjusted p-value <0.001 and |log fold-change of M-value| >2). These results were filtered using a series of all possible pairwise stage contrasts (p-value <0.05) to obtain stage-salient DMGs. These were then subjected to a consensus analysis, followed by Kaplan–Meier survival analysis to evaluate the impact of methylation patterns of consensus stage-salient biomarkers on disease prognosis.Results: We found significant genome-wide changes in methylation patterns in cancer cases relative to controls agnostic of stage. Our stage-differentiated analysis yielded the following stage-salient genes: one stage-I gene (FBN1), one stage-II gene (FOXG1), one stage-III gene (HCN1) and four stage-IV genes (NELL1, ZNF135, FAM123A, LAMA1). All the biomarkers were hypermethylated, indicating down-regulation and signifying a CpG island Methylator Phenotype (CIMP) manifestation. A significant prognostic signature consisting of FBN1 and FOXG1 survived all the steps of our analysis pipeline, and represents a novel early-stage biomarker. Conclusions: We have designed a workflow for stage-differentiated consensus analysis, and identified stage-salient diagnostic biomarkers and an early-stage prognostic biomarker panel. Our studies further yield a novel CIMP-like signature of potential clinical import underlying CRC progression.

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Characterization of Type-I IFN subtype autoantibodies and activity in SLE serum and urine

Lupus ◽

10.1177/0961203320935976 ◽

2020 ◽

Vol 29 (9) ◽

pp. 1095-1105

Author(s):

Bethany D Harris ◽

Srilalitha Kuruganti ◽

Ashlesha Deshpande ◽

Paul A Goepfert ◽

W Winn Chatham ◽

...

Keyword(s):

Systemic Lupus Erythematosus ◽

Disease Activity ◽

Lupus Erythematosus ◽

Interferon Α ◽

Type I ◽

Activity Levels ◽

Systemic Lupus Erythematosus Disease ◽

Systemic Lupus ◽

Interferon Activity ◽

Serum And Urine

Background/objective Type-I interferons contribute to pathogenesis in systemic lupus erythematosus, including nephritis. Interferons consist of a family of 16 proteins yet are often characterized in patients without knowledge of the specific interferon subtypes involved. Different interferons may function in the kidneys, and other organs, relative to what is often measured in patient blood. Moreover, antibodies to interferons may potentially modulate systemic or organ-specific interferon activity. The aim of this study was to characterize global interferon activity levels and identify autoantibodies to the 12 interferon α subtypes in patient serum and urine. Methods Interferon activity levels in serum and urine were measured using an interferon bioassay. Anti-interferon and anti-cytokine autoantibodies were measured by ELISA. Serum and urine samples were also characterized for their ability to neutralize the biological activity of exogenously added interferons. Results Serum interferon activity was increased in 62% of systemic lupus erythematosus patient samples, relative to healthy donor controls, whereas binding interferon α autoantibodies to at least one interferon α subtype were found in 68% of the samples evaluated. High Systemic Lupus Erythematosus Disease Activity Index scores were significantly ( p = 0.001) associated with patient samples containing interferon α autoantibodies to three or more interferon α subtypes in their serum. Interferon α autoantibodies that potently block interferon activity were rare (∼5% of samples), but collectively bound to all 12 interferon α subtypes. Urine interferon activity and interferon α autoantibody profiles did not correlate with their serum counterparts, suggesting immune responses in systemic lupus erythematosus kidneys can be distinct from those measured in serum. Analysis of autoantibodies to 15 additional cytokines in serum identified higher frequencies of granulocyte-macrophage colony-stimulating factor and interleukin 17A autoantibodies, suggesting these signaling pathways may potentially contribute, with interferons, to systemic lupus erythematosus pathogenesis. Conclusions The measurement of autoantibodies to multiple interferon subtypes in serum and urine may provide an alternative method for following interferon-mediated systemic lupus erythematosus disease activity. The results suggest autoantibodies might be used for patient monitoring and/or identifying additional cytokine signaling pathways that are functioning in different systemic lupus erythematosus patients.

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Hypomethylation of STAT1 and HLA-DRB1 is associated with type-I interferon-dependent HLA-DRB1 expression in lupus CD8+ T cells

10.1101/398081 ◽

2018 ◽

Author(s):

Shaylynn Miller ◽

Patrick Coit ◽

Elizabeth Gensterblum-Miller ◽

Paul Renauer ◽

Nathan C Kilian ◽

...

Keyword(s):

Dna Methylation ◽

T Cells ◽

T Cell ◽

Cd8 T Cells ◽

Type I Interferon ◽

Interferon Response ◽

Type I ◽

Mrna Levels ◽

Healthy Controls ◽

Genome Wide

AbstractObjectiveWe examined genome-wide DNA methylation changes in CD8+ T cells from lupus patients and controls, and investigated the functional relevance of some of these changes in lupus.MethodsGenome-wide DNA methylation of lupus and age, sex, and ethnicity-matched control CD8+ T cells was measured using the Infinium MethylationEPIC arrays. Measurement of relevant cell subsets was performed via flow cytometry. Gene expression was quantified by qPCR.ResultsLupus CD8+ T cells had 188 hypomethylated CpG sites compared to healthy matched controls. Among the most hypomethylated were sites associated with HLA-DRB1. Genes involved in the type-I interferon response, including STAT1, were also found to be hypomethylated. IFNα upregulated HLA-DRB1 expression on lupus but not control CD8+ T cells. Lupus and control CD8+ T cells significantly increased STAT1 mRNA levels after treatment with IFNα. The expression of CIITA, a key interferon/STAT1 dependent MHC-class II regulator, is induced by IFNα in lupus CD8+ T cells, but not healthy controls. Co-incubation of naïve CD4+ T cells with IFNα-treated CD8+ T cells led to CD4+ T cell activation, determined by increased expression of CD69, in lupus patients but not in healthy controls. This can be blocked by neutralizing antibodies targeting HLA-DR.ConclusionsLupus CD8+ T cells are epigenetically primed to respond to type-I interferon. We describe an HLA-DRB1+ CD8+ T cell subset that can be induced by IFNα in lupus patients. A possible pathogenic role for CD8+ T cells in lupus that is dependent upon a high type-I interferon environment and epigenetic priming warrants further characterization.

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Epigenome-Wide Association Study of Prostate Cancer in African Americans Identifies DNA Methylation Biomarkers for Aggressive Disease

Biomolecules ◽

10.3390/biom11121826 ◽

2021 ◽

Vol 11 (12) ◽

pp. 1826

Author(s):

Yifan Xu ◽

Chia-Wen Tsai ◽

Wen-Shin Chang ◽

Yuyan Han ◽

Maosheng Huang ◽

...

Keyword(s):

Prostate Cancer ◽

Dna Methylation ◽

African American ◽

African Americans ◽

Zinc Finger Protein ◽

African American Men ◽

Pathway Enrichment Analysis ◽

Cpg Sites ◽

Differentially Methylated Genes ◽

Incidence And Mortality

DNA methylation plays important roles in prostate cancer (PCa) development and progression. African American men have higher incidence and mortality rates of PCa than other racial groups in U.S. The goal of this study was to identify differentially methylated CpG sites and genes between clinically defined aggressive and nonaggressive PCa in African Americans. We performed genome-wide DNA methylation profiling in leukocyte DNA from 280 African American PCa patients using Illumina MethylationEPIC array that contains about 860K CpG sties. There was a slight increase of overall methylation level (mean β value) with the increasing Gleason scores (GS = 6, GS = 7, GS ≥ 8, P for trend = 0.002). There were 78 differentially methylated CpG sites with P < 10−4 and 9 sites with P < 10−5 in the trend test. We also found 77 differentially methylated regions/genes (DMRs), including 10 homeobox genes and six zinc finger protein genes. A gene ontology (GO) molecular pathway enrichment analysis of these 77 DMRs found that the main enriched pathway was DNA-binding transcriptional factor activity. A few representative DMRs include HOXD8, SOX11, ZNF-471, and ZNF-577. Our study suggests that leukocyte DNA methylation may be valuable biomarkers for aggressive PCa and the identified differentially methylated genes provide biological insights into the modulation of immune response by aggressive PCa.

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Dysregulation of DNA Methylation and Epigenetic Clocks in Prostate Cancer among Puerto Rican Men

Biomolecules ◽

10.3390/biom12010002 ◽

2021 ◽

Vol 12 (1) ◽

pp. 2

Author(s):

Anders Berglund ◽

Jaime Matta ◽

Jarline Encarnación-Medina ◽

Carmen Ortiz-Sanchéz ◽

Julie Dutil ◽

...

Keyword(s):

Prostate Cancer ◽

Dna Methylation ◽

Stem Cell ◽

The United States ◽

Epigenetic Clock ◽

Normal Tissues ◽

Differentially Methylated Genes ◽

Stem Cell Divisions ◽

Methylation Patterns ◽

Ancestry Proportions

In 2021, approximately 248,530 new prostate cancer (PCa) cases are estimated in the United States. Hispanic/Latinos (H/L) are the second largest racial/ethnic group in the US. The objective of this study was to assess DNA methylation patterns between aggressive and indolent PCa along with ancestry proportions in 49 H/L men from Puerto Rico (PR). Prostate tumors were classified as aggressive (n = 17) and indolent (n = 32) based on the Gleason score. Genomic DNA samples were extracted by macro-dissection. DNA methylation patterns were assessed using the Illumina EPIC DNA methylation platform. We used ADMIXTURE to estimate global ancestry proportions. We identified 892 differentially methylated genes in prostate tumor tissues as compared with normal tissues. Based on an epigenetic clock model, we observed that the total number of stem cell divisions (TNSC) and stem cell division rate (SCDR) were significantly higher in tumor than adjacent normal tissues. Regarding PCa aggressiveness, 141 differentially methylated genes were identified. Ancestry proportions of PR men were estimated as African, European, and Indigenous American; these were 24.1%, 64.2%, and 11.7%, respectively. The identification of DNA methylation profiles associated with risk and aggressiveness of PCa in PR H/L men will shed light on potential mechanisms contributing to PCa disparities in PR population.

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THU0022 DIFFERENTIAL DNA METHYLATION AS A PREDICTOR OF TOCILIZUMAB RESPONSE IN RHEUMATOID ARTHRITIS PATIENTS

Annals of the Rheumatic Diseases ◽

10.1136/annrheumdis-2020-eular.4394 ◽

2020 ◽

Vol 79 (Suppl 1) ◽

pp. 224.1-224

Author(s):

N. Nair ◽

D. Plant ◽

J. Isaacs ◽

A. Morgan ◽

K. Hyrich ◽

...

Keyword(s):

Rheumatoid Arthritis ◽

Dna Methylation ◽

Disease Activity ◽

Whole Blood ◽

Differential Methylation ◽

Poor Responders ◽

Research Support ◽

Response Status ◽

Pre Treatment ◽

Methylation Patterns

Background:Tocilizumab (TCZ) is a biological disease-modifying antirheumatic drug that blocks IL-6 signalling and is effective in ameliorating disease activity in rheumatoid arthritis (RA). However, approximately 50% of patients do not respond adequately to TCZ and some patients report adverse events. Considering there is growing evidence that DNA methylation is implicated in RA susceptibility and response to some biologics (1, 2), we investigated DNA methylation as a candidate biomarker for response to TCZ in RA.Objectives:To identify differential DNA methylation signatures in whole blood associated with TCZ response in patients with RA.Methods:Epigenome-wide DNA methylation patterns were measured using the Infinium EPIC BeadChip (Illumina) in whole blood-derived DNA samples from patients with RA. DNA was extracted from blood samples taken pre-treatment and following 3 months on therapy, and response was determined at 6 months using the Clinical Disease Activity Index (CDAI). Patients who had good response (n=10) or poor response (n=10) to TCZ by 6 months were selected. Samples from secondary poor responders (n=10) (patients who had an improvement of CDAI and were in remission at 3 months, followed by a worsening of CDAI at 6 months) were also analysed. Differentially methylated positions and regions (DMPs/DMRs) were identified using linear regression, adjusting for gender, age, cell composition, smoking status, and glucocorticoid use. Gene Set Enrichment Analysis (GSEA) was used to identify significant pathways associated with response and Functional Epigenetic Module analysis of interactome hotspots in regions of differential methylation.Results:20 DMPs were significantly associated with response status at 6 months in the pre-treatment samples. Another 21 DMPs were associated with response in the 3 month samples. Within good responders, 10 DMPs showed significant change in methylation level between pre-treatment and the 3 month samples (unadjusted P-value <10-6). One DMP, cg03121467, was significantly less methylated in good responders compared to poor responders in the pre-treatment samples. This DMP is close toEPB41L4Aand thought to have a role in β–catenin signalling. GSEA of DMRs in non- and secondary non- responders identified histone acetyltransferase pathways and included theKAT2Agene, which is a repressor of NF-κB. Additional analysis of interaction hotspots of differential methylation identified significant interactions withSTAMBPandPTPN12associated with response status.Conclusion:These preliminary results provide evidence that DNA methylation patterns may predict response to TCZ. Validation of these findings in other larger data sets is required.References:[1]Liu,Y., Aryee,M.J., Padyukov,L., Fallin,M.D., Hesselberg,E., Runarsson,A., Reinius,L., Acevedo,N., Taub,M., Ronninger,M.,et al.(2013) Epigenome-wide association data implicate DNA methylation as an intermediary of genetic risk in rheumatoid arthritis.Nat. Biotechnol.,31, 142–147.[2]Plant,D., Webster,A., Nair,N., Oliver,J., Smith,S.L., Eyre,S., Hyrich,K.L., Wilson,A.G., Morgan,A.W., Isaacs,J.D.,et al.(2016) Differential Methylation as a Biomarker of Response to Etanercept in Patients With Rheumatoid Arthritis.Arthritis Rheumatol. (Hoboken, N.J.),68, 1353–60.Disclosure of Interests:Nisha Nair: None declared, Darren Plant: None declared, John Isaacs Consultant of: AbbVie, Bristol-Myers Squibb, Eli Lilly, Gilead, Janssen, Merck, Pfizer, Roche, Ann Morgan Grant/research support from: I have received a grant from Roche Products Ltd to establish a registry for GCA patients treated with tocilizumab., Consultant of: I have undertaken consultancy work for Roche, Chugai, Regeneron, Sanofi and GSK in the area of GCA therapeutics., Speakers bureau: I have presented on tocilizumab therapy for GCA and glucocorticoid toxicity on behalf of Roche products ltd., Kimme Hyrich Grant/research support from: Pfizer, UCB, BMS, Speakers bureau: Abbvie, Anne Barton Consultant of: AbbVie, Anthony G Wilson: None declared

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Comparison of Surrogate Markers of the Type I Interferon Response and Their Ability to Mirror Disease Activity in Systemic Lupus Erythematosus

Frontiers in Immunology ◽

10.3389/fimmu.2021.688753 ◽

2021 ◽

Vol 12 ◽

Author(s):

Helena Enocsson ◽

Jonas Wetterö ◽

Maija-Leena Eloranta ◽

Birgitta Gullstrand ◽

Cecilia Svanberg ◽

...

Keyword(s):

Systemic Lupus Erythematosus ◽

Disease Activity ◽

Immune Complex ◽

Lupus Erythematosus ◽

Interferon Response ◽

Type I ◽

Surrogate Markers ◽

Type I Ifn ◽

Systemic Lupus ◽

Cross Sectional

ObjectivesType I interferons (IFNs) are central and reflective of disease activity in systemic lupus erythematosus (SLE). However, IFN-α levels are notoriously difficult to measure and the type I IFN gene signature (IGS) is not yet available in clinical routine. This study evaluates galectin-9 and an array of chemokines/cytokines in their potential as surrogate markers of type I IFN and/or SLE disease activity.MethodsHealthy controls and well-characterized Swedish SLE patients from two cross-sectional cohorts (n=181; n=59) were included, and a subgroup (n=21) was longitudinally followed. Chemokine/cytokine responses in immune complex triggered IFN-α activity was studied in healthy donor peripheral blood mononuclear cells (PBMC). Levels of chemokines/cytokines and galectin-9 were measured by immunoassays. Gene expression was quantified by qPCR.ResultsThe IGS was significantly (p<0.01) correlated with galectin-9 (rho=0.54) and CXCL10 (rho=0.37) levels whereas serum IFN-α correlated with galectin-9 (rho=0.36), CXCL10 (rho=0.39), CCL19 (rho=0.26) and CCL2 (rho=0.19). The strongest correlation was observed between galectin-9 and TNF (rho=0.56). IFN-α and disease activity (SLEDAI-2K) were correlated (rho=0.20) at cross-sectional analysis, but no significant associations were found between SLEDAI-2K and galectin-9 or chemokines. Several inflammatory mediators increased at disease exacerbation although CCL19, CXCL11, CXCL10, IL-10 and IL-1 receptor antagonist were most pronounced. Immune complex-stimulation of PBMC increased the production of CCL2, CXCL8 and TNF.ConclusionGalectin-9 and CXCL10 were associated with type I IFN in SLE but correlated stronger with TNF. None of the investigated biomarkers showed a convincing association with disease activity, although CXCL10 and CCL19 performed best in this regard.

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Genome-Wide DNA Methylation Pattern in Whole Blood Associated With Primary Intracerebral Hemorrhage

Frontiers in Immunology ◽

10.3389/fimmu.2021.702244 ◽

2021 ◽

Vol 12 ◽

Author(s):

Yupeng Zhang ◽

Hongyu Long ◽

Sai Wang ◽

Wenbiao Xiao ◽

Meishan Xiong ◽

...

Keyword(s):

Dna Methylation ◽

Intracerebral Hemorrhage ◽

Whole Blood ◽

Peripheral Blood ◽

Methylation Status ◽

Methylation Pattern ◽

Healthy Controls ◽

Differentially Methylated Genes ◽

Dna Methylation Pattern ◽

Methylation Patterns

Primary intracerebral hemorrhage (ICH) is a significant cause of morbidity and mortality throughout the world. ICH is a multifactorial disease that emerges from interactions among multiple genetic and environmental factors. DNA methylation plays an important role in the etiology of complex traits and diseases. We used the Illumina Infinium Human Methylation 850k BeadChip to detect changes in DNA methylation in peripheral blood samples from patients with ICH and healthy controls to explore DNA methylation patterns in ICH. Here, we compared genomic DNA methylation patterns in whole blood from ICH patients (n = 30) and controls (n = 34). The ICH and control groups showed significantly different DNA methylation patterns at 1530 sites (p-value < 5.92E-08), with 1377 hypermethylated sites and 153 hypomethylated sites in ICH patients compared to the methylation status in healthy controls. A total of 371 hypermethylated sites and 35 hypomethylated sites were in promoters, while 738 hypermethylated sites and 67 hypomethylated sites were in coding regions. Furthermore, the differentially methylated genes between ICH patients and controls were largely related to inflammatory pathways. Abnormalities in the DNA methylation pattern identified in the peripheral blood of ICH patients may play an important role in the development of ICH and warranted further investigation.

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Mild SARS-CoV-2 infection modifies DNA methylation of peripheral blood mononuclear cells from COVID-19 convalescents

10.1101/2021.07.05.21260014 ◽

2021 ◽

Author(s):

Johanna Huoman ◽

Shumaila Sayyab ◽

Eirini Apostolou ◽

Lovisa Karlsson ◽

Lucas Porcile ◽

...

Keyword(s):

Dna Methylation ◽

Peripheral Blood Mononuclear Cells ◽

Mononuclear Cells ◽

Peripheral Blood Mononuclear ◽

Network Analyses ◽

Differentially Methylated Genes ◽

Blood Mononuclear Cells ◽

Methylation Patterns

Background: Coronaviruses such as SARS-CoV-2 may circumvent host defence mechanisms by hijacking host proteins, possibly by altering DNA methylation patterns in host cells. While most epigenetic studies have been performed in severely ill COVID-19 patients, studies on individuals who have recovered from mild-to-moderate disease remain scarce. The aim of this study was to assess epigenome-wide DNA methylation patterns in COVID-19 convalescents compared to uninfected controls from before and after the pandemic outbreak began. Methods: DNA was extracted from peripheral blood mononuclear cells originating from uninfected controls before (Pre20, n=5) and after (Con, n=18) 2020, COVID-19 convalescents (CC19, n=14) and symptom-free individuals with a SARS-CoV-2-specific T cell response (SFT, n=6), as well as from Pre20 (n=4) samples stimulated in vitro with SARS-CoV-2. Subsequently, epigenome-wide DNA methylation analyses were performed using the Illumina MethylationEPIC 850K array, and statistical and bioinformatic analyses comprised differential DNA methylation, pathway over-representation and module identification network analyses. Results: DNA methylation patterns of COVID-19 convalescents were altered as compared to uninfected controls, with similar results observed in in vitro stimulations of PBMC with SARS-CoV-2. Differentially methylated genes from the in vivo comparison constituted the foundation for the identification of a possibly SARS-CoV-2-induced module, containing 66 genes of which six could also be identified in corresponding analyses of the in vitro data (TP53, INS, HSPA4, SP1, ESR1 and FAS). Pathway over-representation analyses revealed involvement of Wnt, cadherin and apoptosis signalling pathways amongst others. Furthermore, numerous interactions were found between the obtained differentially methylated genes from both settings and the network analyses when overlaying the data unto the SARS-CoV-2 interactome. Conclusions: Epigenome-wide DNA methylation patterns of individuals that have recovered from mild-to-moderate COVID-19 are different from those of non-infected controls. The observed alterations during both in vivo and in vitro exposure to SARS-CoV-2 showed involvement in interactions and pathways that are highly relevant to COVID-19. The present study provides indications that DNA methylation is one of several epigenetic mechanisms that is altered upon SARS-CoV-2 infection. Further studies on the mechanistic underpinnings should determine whether the observed effects are reflecting host-protective antiviral defence or targeted viral hijacking to evade host defence.

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