DNA methylation modifications associated with chronic fatigue syndrome

Abstract

Chronic Fatigue Syndrome (CFS), also known as myalgic encephalomyelitis, is a complex multifactorial disease that is characterized by the persistent presence of fatigue and other particular symptoms for a minimum of 6 months. Symptoms fail to dissipate after sufficient rest and have major effects on the daily functioning of CFS sufferers. CFS is a multi-system disease with a heterogeneous patient population showing a wide variety of functional disabilities and its biological basis remains poorly understood. Stable alterations in gene function in the immune system have been reported in several studies of CFS. Epigenetic modifications have been implicated in long-term effects on gene function, however, to our knowledge, genome-wide epigenetic modifications associated with CFS have not been explored. We examined the DNA methylome in peripheral blood mononuclear cells isolated from CFS patients and healthy controls using the Illumina HumanMethylation450 BeadChip array, controlling for invariant probes and probes overlapping polymorphic sequences. Gene ontology (GO) and network analysis of differentially methylated genes was performed to determine potential biological pathways showing changes in DNA methylation in CFS. We found an increased abundance of differentially methylated genes related to the immune response, cellular metabolism, and kinase activity. Genes associated with immune cell regulation, the largest coordinated enrichment of differentially methylated pathways, showed hypomethylation within promoters and other gene regulatory elements in CFS. These data are consistent with evidence of multisystem dysregulation in CFS and implicate the involvement of DNA modifications in CFS pathology.

Figure 1. Distribution of differentially methylated regions in CFS.

Distribution of hyper- and hypo-methylated CpG regions in CFS patients compared to healthy control subjects according to (a) genic location 1500 bp and 200 bp relative to the transcription start site (TSS), in the 5′ UTR, 3′ UTR, and within gene bodies and (b) location relative to CpG islands, including 2 kb upstream and downstream of CpG islands (N, S Shore respectively), and 2 kb upstream and downstream of CpG shores (N, S Shelf respectively). No significant differences were found within CpG islands.

Figure 2. Validation of microarray data by pyrosequencing.

Validation of significant methylation differences identified by microarray (450 K) by pyrosequencing (PS), showing the average methylation level of CpG sites within the following genes (probe ID, genic location): (a) LY86 (cg02212836, first exon), (b) HIPK3 (cg25600606, gene body), and (c) LCN2 (cg14615559, TSS200). * = FDR<0.05, 450 K; * = p<0.05, PS, Wilcoxon rank-sum test. Error bars represent the standard error of the mean.

Figure 3. Clustering of DAVID GO results.

Network map showing the clustering of DAVID GO results as produced by the Enrichment Map plugin in Cytoscape 2.8.2. Significant GO term clusters were named according to textual attributes generated by the WordCloud plugin. Node size (red circles) corresponds to the number of genes within the GO terms. Edge thickness (green lines) represents genes in common between GO terms.

Figure 4. Distribution of differentially methylated sites in CFS according to GO clusters and functional relevance.

Relative proportions of hyper- and hypo-methylated CpG sites between CFS patients and healthy control subjects for genes associated with the immune cell regulation cluster group (immune GO) compared to all four GO term cluster groups (all GO). Results are shown for each genic region, consisting of promoter regions within 1500 bp and 200 bp of the transcription start sites (TSS), gene regulatory elements (regulatory: TSS1500, TSS200, 5′ UTR, 3′ UTR), the coding regions of genes (gene body), as well as all regions combined (total: regulatory, gene body). * = p<0.0125, Pearson Chi-Squared Test.