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A longitudinal and transancestral analysis of DNA methylation patterns and disease activity in lupus patients.

ABSTRACT: Epigenetic dysregulation is implicated in the pathogenesis of lupus. We performed a longitudinal analysis to assess changes in DNA methylation in lupus neutrophils over 4 years of follow-up and across disease activity levels using 229 patient samples. We demonstrate that DNA methylation profiles in lupus are partly determined by ancestry-associated genetic variations and are highly stable over time. DNA methylation levels in 2 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 IFN-response genes such as IRF7 and IFI44, and genes related to the NF-?B pathway. TREML4, which plays a vital role in TLR signaling, was hypomethylated in African American patients and demonstrated a strong cis-methylation quantitative trait loci (cis-meQTL) effect among 8855 cis-meQTL associations identified in our study.

SUBMITTER: Coit P

PROVIDER: S-EPMC7710270 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

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A longitudinal and transancestral analysis of DNA methylation patterns and disease activity in lupus patients.

Coit Patrick P Ortiz-Fernandez Lourdes L Lewis Emily E EE McCune W Joseph WJ Maksimowicz-McKinnon Kathleen K Sawalha Amr H AH

JCI insight 20201119 22

Epigenetic dysregulation is implicated in the pathogenesis of lupus. We performed a longitudinal analysis to assess changes in DNA methylation in lupus neutrophils over 4 years of follow-up and across disease activity levels using 229 patient samples. We demonstrate that DNA methylation profiles in lupus are partly determined by ancestry-associated genetic variations and are highly stable over time. DNA methylation levels in 2 CpG sites correlated significantly with changes in lupus disease acti ...[more]

PMID: 33108347

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Project description:BackgroundEarly life is a period of drastic epigenetic remodeling in which the epigenome is especially sensitive to extrinsic and intrinsic influence. However, the epigenome-wide dynamics of the DNA methylation changes that occur during this period have not been sufficiently characterized in longitudinal studies.MethodsTo this end, we studied the DNA methylation status of more than 750,000 CpG sites using Illumina MethylationEPIC arrays on 33 paired blood samples from 11 subjects at birth and at 5 and 10 years of age, then characterized the chromatin context associated with these loci by integrating our data with histone, chromatin-state and enhancer-element external datasets, and, finally, validated our results through bisulfite pyrosequencing in two independent longitudinal cohorts of 18 additional subjects.ResultsWe found abundant DNA methylation changes (110,726 CpG sites) during the first lustrum of life, while far fewer alterations were observed in the subsequent 5 years (460 CpG sites). However, our analysis revealed persistent DNA methylation changes at 240 CpG sites, indicating that there are genomic locations of considerable epigenetic change beyond immediate birth. The chromatin context of hypermethylation changes was associated with repressive genomic locations and genes with developmental and cell signaling functions, while hypomethylation changes were linked to enhancer regions and genes with immunological and mRNA and protein metabolism functions. Significantly, our results show that genes that suffer simultaneous hyper- and hypomethylation are functionally distinct from exclusively hyper- or hypomethylated genes, and that enhancer-associated methylation is different in hyper- and hypomethylation scenarios, with hypomethylation being more associated to epigenetic changes at blood tissue-specific enhancer elements.ConclusionsThese data show that epigenetic remodeling is dramatically reduced after the first 5 years of life. However, there are certain loci which continue to manifest DNA methylation changes, pointing towards a possible functionality beyond early development. Furthermore, our results deepen the understanding of the genomic context associated to hyper- or hypomethylation alterations during time, suggesting that hypomethylation of blood tissue-specific enhancer elements could be of importance in the establishment of functional states in blood tissue during early-life.

Project description:BackgroundDNA methylation is a key epigenetic regulator contributing to cancer development. To understand the role of DNA methylation in tumorigenesis, it is important to investigate and compare differential methylation (DM) patterns between normal and case samples across different cancer types. However, current pan-cancer analyses call DM separately for each cancer, which suffers from lower statistical power and fails to provide a comprehensive view for patterns across cancers.MethodsIn this work, we propose a rigorous statistical model, PanDM, to jointly characterize DM patterns across diverse cancer types. PanDM uses the hidden correlations in the combined dataset to improve statistical power through joint modeling. PanDM takes summary statistics from separate analyses as input and performs methylation site clustering, differential methylation detection, and pan-cancer pattern discovery. We demonstrate the favorable performance of PanDM using simulation data. We apply our model to 12 cancer methylome data collected from The Cancer Genome Atlas (TCGA) project. We further conduct ontology- and pathway-enrichment analyses to gain new biological insights into the pan-cancer DM patterns learned by PanDM.ResultsPanDM outperforms two types of separate analyses in the power of DM calling in the simulation study. Application of PanDM to TCGA data reveals 37 pan-cancer DM patterns in the 12 cancer methylomes, including both common and cancer-type-specific patterns. These 37 patterns are in turn used to group cancer types. Functional ontology and biological pathways enriched in the non-common patterns not only underpin the cancer-type-specific etiology and pathogenesis but also unveil the common environmental risk factors shared by multiple cancer types. Moreover, we also identify PanDM-specific DM CpG sites that the common strategy fails to detect.ConclusionsPanDM is a powerful tool that provides a systematic way to investigate aberrant methylation patterns across multiple cancer types. Results from real data analyses suggest a novel angle for us to understand the common and specific DM patterns in different cancers. Moreover, as PanDM works on the summary statistics for each cancer type, the same framework can in principle be applied to pan-cancer analyses of other functional genomic profiles. We implement PanDM as an R package, which is freely available at http://www.sta.cuhk.edu.hk/YWei/PanDM.html .

Dataset Information

A longitudinal and transancestral analysis of DNA methylation patterns and disease activity in lupus patients.

Publications

A longitudinal and transancestral analysis of DNA methylation patterns and disease activity in lupus patients.

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