Differential DNA methylation marks and gene comethylation of COPD in African-Americans with COPD exacerbations

Abstract

BackgroundChronic obstructive pulmonary disease (COPD) is the third-leading cause of death worldwide. Identifying COPD-associated DNA methylation marks in African-Americans may contribute to our understanding of racial disparities in COPD susceptibility. We determined differentially methylated genes and co-methylation network modules associated with COPD in African-Americans recruited during exacerbations of COPD and smoking controls from the Pennsylvania Study of Chronic Obstructive Pulmonary Exacerbations (PA-SCOPE) cohort.MethodsWe assessed DNA methylation from whole blood samples in 362 African-American smokers in the PA-SCOPE cohort using the Illumina Infinium HumanMethylation27 BeadChip Array. Final analysis included 19302 CpG probes annotated to the nearest gene transcript after quality control. We tested methylation associations with COPD case-control status using mixed linear models. Weighted gene comethylation networks were constructed using weighted gene coexpression network analysis (WGCNA) and network modules were analyzed for association with COPD.ResultsThere were five differentially methylated CpG probes significantly associated with COPD among African-Americans at an FDR less than 5 %, and seven additional probes that approached significance at an FDR less than 10 %. The top ranked gene association was MAML1, which has been shown to affect NOTCH-dependent angiogenesis in murine lung. Network modeling yielded the “yellow” and “blue” comethylation modules which were significantly associated with COPD (p-value 4 × 10-10 and 4 × 10-9, respectively). The yellow module was enriched for gene sets related to inflammatory pathways known to be relevant to COPD. The blue module contained the top ranked genes in the concurrent differential methylation analysis (FXYD1/LGI4, gene significance p-value 1.2 × 10-26; MAML1, p-value 2.0 × 10-26; CD72, p-value 2.1 × 10-25; and LPO, p-value 7.2 × 10-25), and was significantly associated with lung development processes in Gene Ontology gene-set enrichment analysis.ConclusionWe identified 12 differentially methylated CpG sites associated with COPD that mapped to biologically plausible genes. Network module comethylation patterns have identified candidate genes that may be contributing to racial differences in COPD susceptibility and severity. COPD-associated comethylation modules contained genes previously associated with lung disease and inflammation and recapitulated known COPD-associated genes. The genes implicated by differential methylation and WGCNA analysis may provide mechanistic targets contributing to COPD susceptibility, exacerbations, and outcomes among African-Americans.Trial registrationTrial Registration: NCT00774176, Registry: ClinicalTrials.gov, URL: www.clinicaltrials.gov, Date of Enrollment of First Participant: June 2004, Date Registered: 04 January 2008 (retrospectively registered).Electronic supplementary materialThe online version of this article (doi:10.1186/s12931-016-0459-8) contains supplementary material, which is available to authorized users.

DNA methylation modules associate with incident cardiovascular disease and cumulative risk factor exposure

“…The finding of immune-related processes is intuitive given that DNA from blood measures primarily immune cells, while the development-related enrichment could possibly reflect influences during early life [28]. Notably, these two module "types" (immune and development) have been uncovered in a prior network-based DNA methylation analysis related to asthma [19], suggesting that similar module types are a potentially general feature of blood-based methylation patterns and that these patterns may not be fully cardiovascular-specific, reflecting instead a predisposition toward general inflammatory disease processes. Both in WHI and in replication in FHS, two modules (blue and brown) showed strong relationships with incident CVD that were attenuated after adjustment for age (direct correlations of these modules with age are presented in Fig.…”

“…An alternative grouping strategy is to search for correlation-based clusters, which may boost biological signal and improve the interpretability of results [17]. This approach was originally developed for use with gene expression data, but has been successfully applied to higher-dimensional DNA methylation microarray datasets [18,19].…”

Changes of DNA methylation are associated with changes in lung function during adolescence

“…It regulates gene function through the modulation of gene expression. Imboden et al 2019 [11] and others have demonstrated that DNA-M in whole blood is associated with lung function [12][13][14][15][16], risk of asthma [17], and chronic obstructive pulmonary disease (COPD) [12,13,15,16]. When assessing the association of DNA-M with lung function, most previous studies have been cross-sectional with both lung function and DNA-M measured at single time points [12][13][14][15][16], although DNA-M at some CpGs changes over time [18][19][20][21][22].…”

Pleiotropic and Epistatic Network-Based Discovery: Integrated Networks for Target Gene Discovery

“…A methylation matrix M was then formed, in which rows represented genes, columns represented tissues and each entry ij represented the methylation score (TPM) of gene i in tissue j. A co-methylation network (see references (Busch et al, 2016;Akulenko and Helms, 2013;Davies et al, 2012)) was then constructed by calculating the Spearman correlation coefficient between the methylation profiles of all pairs of genes using mcxarray and mcxdump programs from the MCL-edge package (Van Dongen, 2008, 2001 http://micans.org/mcl/. Supplementary Figure S1B shows the distribution of Spearman Correlation values.…”