Indigophoton
Senior Member (Voting Rights)
This is a preprint - made available by the authors on bioRxiv before publication while the paper is still in peer review.
Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is an example of a complex disease of unknown etiology. Multiple studies point to disruptions in immune functioning in ME/CFS patients as well as with specific genetic polymorphisms and alterations of the DNA methylome in lymphocytes. However, the association between DNA methylation and genetic background in relation to the ME/CFS is currently unknown. In this study we explored this association by characterizing the genomic (~4.3 million SNPs) and epigenomic (~480 thousand CpG loci) variability between populations of ME/CFS patients and healthy controls. We found significant associations of methylation states in T-lymphocytes at several CpG loci and regions with ME/CFS phenotype. These methylation anomalies are in close proximity to genes involved with immune function and cellular metabolism. Finally, we found significant correlations of genotypes with methylation phenotypes associated with ME/CFS. The findings from this study highlight the role of epigenetic and genetic interactions in complex diseases, and suggest several genetic and epigenetic elements potentially involved in the mechanisms of disease in ME/CFS.
T-cell lymphocytes appear to be a primary cell type underlying immune and neuroendocrine abnormalities observed in ME/CFS patients. Functional impairment in T-cell glucocorticoid receptor and increased dexamethasone sensitivity are characteristic of some
ME/CFS patients (14,20). Furthermore, genetic polymorphisms within non-coding regions of T-cell receptor loci (15), as well as differential methylation in CD4+ 51 T helper lymphocyte cells (Brenu et al., 2014), have been associated with the disease. The possible interactions between genomic and T-cell epigenomic variation in ME/CFS remain unknown.
In this study, we aimed to explore the association between DNA methylation profiles of T-cells and single nucleotide polymorphisms (SNPs) in ME/CFS patients. We quantified lymphocyte proportions and isolated CD3+ T-cells (including both CD4+ T helper cells and CD8+ T killer cells) via fluorescence activated cell sorting. We characterized the variation in genomic(~4.3 million SNPs) and epigenomic (~480 thousand CpG loci) variability among ME/CFS patients and healthy controls.
Using this approach, we: 1) tested the association of genome-wide SNP genotypes with ME/CFS disease status; 2) tested the association of differentially methylated CpG loci and regions in CD3+ T-cells with ME/CFS disease status; 3) performed a methylation quantitative trait analysis to investigate the possible interactions between genetic background and methylation phenotypes of CD3+ T-cells associated with ME/CFS disease status.
Conclusions
We identified over one hundred differentially methylated CpG loci associated with ME/CFS in T lymphocytes. Approximately half of these were clustered in differentially methylated regions of 500bp in size or less. Our data and analyses suggest that there is an indirect role of genotype influencing DNA methylation patterns associated with ME/CFS. We found no substantial large-effect direct associations of specific genotypes with ME/CFS disease phenotype. Larger scale genome wide association studies are necessary to test for potential small-effect associations between genotype and ME/CFS phenotype.
All of the methylation values at differentially methylated loci in T lymphocytes had significant correlations with specific genotypes at neighboring SNPs (within a window of 1 Mbp), indicating that particular genetic backgrounds may influence methylation levels differently in ME/CFS patients than in controls. The genomic elements associated with genetic and epigenetic variants characteristic of ME/CFS patients in this study constitute targets for future research. Understanding the molecular mechanisms of genetic-epigenetic interactions of these targets will be key to develop new treatments for ME/CFS, and can serve as a model to understand the molecular basis of related complex diseases.