Epigenomics and transcriptomics analyses of multiple system atrophy brain tissue supports a role for inflammatory processes in disease pathogenesis
Acta Neuropathologica Communications volume 8, Article number: 71 (2020)
To the Editors,
Multiple system atrophy (MSA) is a fatal neurodegenerative disease and its aetiology remains elusive. The pathological hallmark of MSA is the presence of glial cytoplasmic inclusions (GCIs) containing fibrillar α-synuclein in oligodendrocytes [3, 6], but the regional vulnerability of the brain to these GCIs remains poorly understood. We read with interest the paper by Rydbirk and colleagues recently published in Acta Neuropathologica Communications . They investigated DNA methylation (5mC) and hydroxymethylation (5hmC) changes in prefrontal cortex samples from MSA patients. We reported previously  total DNA methylation (5mC + 5hmC) changes in MSA, and this work by Rydbirk et al.  further supports a contribution of epigenetic factors, namely DNA methylation, to MSA brain pathophysiology.
Given the differentially methylated CpGs (e.g. in AREL1 and KTN1), regions (DMRs) and blocks reported for the 5mC fraction by Rydbirk and colleagues , we performed additional loci-specific analysis of our MSA DNA methylation data . We used data from our discovery cohort , which was composed of neuropathologically confirmed MSA mixed cases and controls, and investigated multiple brain regions characterized by different degrees of GCI burden in MSA, including the cerebellum, and the frontal and occipital lobes. In the frontal lobe, no changes were detected in AREL1 nor in the reported intergenic CpGs (Supplementary Table S1.1). Although with small effects (absolute delta betas < 5%), two CpGs in KTN1 were nominally significant (cg14002714 and cg21059882; p < 0.05). Regarding the block covering PHF3, two CpGs were nominally significant (cg16049132 and cg10435600; p < 0.05). Additionally, 52 CpGs in the DMR genes were nominally significant in our data, 14 of which (in 5 genes: FUT4, BCAR1, CTSZ, ZIC4 and FERMT3) demonstrated absolute delta betas of ≥5%. With the exception of cg18023065 in FUT4, none of these changes passed multiple testing correction (p < 9.07 × 10− 5 [0.05/551 CpGs]). Some of those CpGs and additional CpGs were also nominally significant in the other brain regions analysed (Supplementary Table S1.1). Interestingly, the DMR in the FUT4/PIWIL4 promoter (chromosome 11: 94278407–94,279,068), replicates a DMR we found in the frontal lobe and cross-region analyses of our previous study (Supplementary Tables S3.1 and S3.3 from ).
The study by Rydbirk et al.  and ours  have markedly different designs: a) Rydbirk et al.  included white and grey matter from the frontal lobe, whilst we carefully dissected white matter to enrich for oligodendrocytes and analysed different brain regions; and b) they investigated the contributions of 5mC and 5hmC separately. We are aware that in our data alterations in the 5mC and 5hmC proportions can counteract each other and mask the detection of significant changes in total methylation. As an example, the AREL1 shift from 5mC to 5hmC reported by Rydbirk et al.  is masked in our total DNA methylation data, highlighting an advantage of analysing 5mC and 5hmC separately. In addition, distinct cell type compositions in the brain tissue samples may contribute to discordant findings. According to RNAseq data from major brain cell types (data from Zhang et al. , Supplementary Fig. 1), our results support methylation changes in genes that are highly expressed in oligodendrocytes, including KTN1 and PHF3, or more highly expressed in microglia/macrophages, including FUT4, CTSZ, and FERMT3 (Supplementary Fig. 1). Conversely, genes more highly expressed in neurons and/or with low expression in oligodendrocytes, such as AREL1, were less susceptible to DNA methylation changes in our dataset.
Findings from Rydbirk et al.  also report increased AREL1 and MHC class I HLA gene expression in MSA brains. We therefore investigated in our MSA cerebellar white matter RNAseq data  gene expression changes in all of the genes reported by Rydbirk et al. . Our study includes two independent cohorts of 66 MSA and 66 healthy controls and laser captured oligodendrocytes . Although we did not find differential expression for AREL1 or PHF3, we found a nominally significant (p < 0.05) downregulation of KTN1 (log2 FC = − 0.465), and upregulation of CTSZ (log2 FC = 0.817), NCS1 (log2 FC = 0.813) and ZIC4 (log2 FC = 1.520) in some groups of our cohort 1 (Supplementary Table S2). The upregulation of ZIC4 was replicated in cohort 2 of our study (log2 FC = 1.551) and remained significant when accounting for multiple testing adjustments in the combined analysis of both cohorts 1 and 2 (log2 FC = 1.536; adjusted-p = 0.022). In our RNAseq data, MHC class I HLA genes have shown inconsistent results across cohorts/groups, with only HLA-A showing nominally significant upregulation in one group of cohort 1 (log2 FC = 1.156 in MSA-P; p = 0.002) and HLA-F in oligodendrocytes (log2 FC = 1.982; p = 0.032). Some of the MHC class I HLA genes, including HLA-A, have also shown nominally significant DNA methylation changes in our data (Supplementary Table S1.2).
Overall, we consider that these recent studies by Bettencourt et al. , Piras et al. , and Rydbirk et al.  are complementary, and bring important insights into the brain pathophysiology of MSA. All show changes in DNA methylation or in gene expression levels of genes that are more highly expressed in microglia/macrophages, therefore supporting previous studies highlighting the involvement of inflammatory processes in MSA (e.g. ).
Availability of data and materials
Data generated during this study are included in this published article and its supplementary information files. The datasets used for the analyses during the current study available from the corresponding author on reasonable request.
Differentially methylated regions
Glial cytoplasmic inclusions
Multiple system atrophy
Clinical subtype of multiple system atrophy with a predominant cerebellar phenotype
Clinical subtype of multiple system atrophy with a predominant parkinsonian phenotype
Whole-transcriptome data obtained by next-generation sequencing
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The authors would like to thank Ms. Gaganjit Kaur Madhan (MSc) for sample processing and the UCL Genomics centre for advice and processing of the EPIC arrays. Geidy Serrano, Lucia Sue, and Thomas Beach for providing MSA case and control tissue, and Christiane Bleul, Isabelle Schrauwen, Lorida Llaci, Matthew De Both, and Marcus Naymik for aiding in the generation and analysis of the RNA data.
Queen Square Brain Bank for Neurological Disorders receives support from the Reta Lila Weston Institute of Neurological Studies and the Medical Research Council (MRC). CB is supported by the Multiple System Atrophy Trust, the British Neuropathological Society, and an Alzheimer’s Research UK Research Fellowship. TL is supported by an Alzheimer’s Research UK Senior Fellowship. TTW is supported by the Reta Lila Weston Trust and the MRC (N013255/1). JLH is supported by the Multiple System Atrophy Trust; the Multiple System Atrophy Coalition; Fund Sophia, managed by the King Baudouin Foundation and Karin & Sten Mortstedt CBD Solutions. This research was supported by the National Institute for Health Research University College London Hospitals Biomedical Research Centre. The authors also acknowledge funding support from the NIH National Institute of Neurological Disorders and Stroke (R21-NS093222 to MJH), Tissue from The Brain and Body Donation Program at the Banner Sun Health Research Institute is supported by the National Institute of Neurological Disorders and Stroke (U24 NS072026 National Brain and Tissue Resource for Parkinsons Disease and Related Disorders), the National Institute on Aging (P30 AG19610 Arizona Alzheimers Disease Core Center), the Arizona Department of Health Services (contract 211002, Arizona Alzheimers Research Center), and the Arizona Biomedical Research Commission (contracts 4001, 0011, 05–901 and 1001 to the Arizona Parkinson’s Disease Consortium).
Ethics approval and consent to participate
All brain tissue from brains donated to the Queen Square Brain Bank (QSBB) archives (UK), including the tissue used for the DNA methylation study, is stored under a licence from the Human Tissue authority (No. 12198). The QSBB brain donation programme and protocols have received ethical approval for donation and research by the NRES Committee London – Central [18/LO/0721]. For the RNAseq study, conducted in the USA, all human samples were derived from autopsy tissue and were classified as non-human subject research material according to local regulations.
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Loci-specific analysis of differentially methylated CpGs, regions and blocks identified by Rydbirk et al. 2020. Supplementary Table S1.2. Loci-specific analysis of differential methylation in MHC class I HLA genes.
Loci-specific analysis of cerebellar white matter gene expression for genes reported to be differentially methylated and/or differentially expressed by Rydbirk et al. 2020.
Boxplots of normalized counts in different brain cell types  for the most relevant genes detected in [1, 5]. Raw data were downloaded from Sequencing Reads Archive (#SRP064454), pseudoalignment was conducted with Kallisto v0.46.1, and counts were normalized with DESeq2 v1.26.0. Data were from hippocampus, temporal lobe and fetal cortex. Tumor samples were excluded from the dataset. FA: fetal astrocytes. A: astrocytes. N: neurons. O: oligodendrocytes. M: microglia. E: endothelial cells.
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Bettencourt, C., Piras, I.S., Foti, S.C. et al. Epigenomics and transcriptomics analyses of multiple system atrophy brain tissue supports a role for inflammatory processes in disease pathogenesis. acta neuropathol commun 8, 71 (2020). https://doi.org/10.1186/s40478-020-00946-1
- DNA methylation
- Gene expression