Fatal demyelinating disease is induced by monocyte-derived macrophages in the absence of TGF-ß signaling.

The cytokine transforming growth factor-ß (TGF-ß) regulates the development and homeostasis of several tissue-resident macrophage populations, including microglia. TGF-ß is not critical for microglia survival but is required for the maintenance of the microglia-specific homeostatic gene signature1,2. Under defined host conditions, circulating monocytes can compete for the microglial niche and give rise to long-lived monocyte-derived macrophages residing in the central nervous system (CNS)3-5. Whether monocytes require TGF-ß for colonization of the microglial niche and maintenance of CNS integrity is unknown. We found that abrogation of TGF-ß signaling in CX3CR1+ monocyte-derived macrophages led to rapid onset of a progressive and fatal demyelinating motor disease characterized by myelin-laden giant macrophages throughout the spinal cord. Tgfbr2-deficient macrophages were characterized by high expression of genes encoding proteins involved in antigen presentation, inflammation and phagocytosis. TGF-ß is thus crucial for the functional integration of monocytes into the CNS microenvironment.

DNA Methylation Signatures of Multiple Sclerosis Occur Independently of Known Genetic Risk and Are Primarily Attributed to B Cells and Monocytes.

Epigenetic mechanisms can regulate how DNA is expressed independently of sequence and are known to be associated with various diseases. Among those epigenetic mechanisms, DNA methylation (DNAm) is influenced by genotype and the environment, making it an important molecular interface for studying disease etiology and progression. In this study, we examined the whole blood DNA methylation profiles of a large group of people with (pw) multiple sclerosis (MS) compared to those of controls. We reveal that methylation differences in pwMS occur independently of known genetic risk loci and show that they more strongly differentiate disease (AUC = 0.85, 95% CI 0.82-0.89, p = 1.22 × 10-29) than known genetic risk loci (AUC = 0.72, 95% CI: 0.66-0.76, p = 9.07 × 10-17). We also show that methylation differences in MS occur predominantly in B cells and monocytes and indicate the involvement of cell-specific biological pathways. Overall, this study comprehensively characterizes the immune cell-specific epigenetic architecture of MS.

GeneSetCluster: a tool for summarizing and integrating gene-set analysis results.

BACKGROUND: Gene-set analysis tools, which make use of curated sets of molecules grouped based on their shared functions, aim to identify which gene-sets are over-represented in the set of features that have been associated with a given trait of interest. Such tools are frequently used in gene-centric approaches derived from RNA-sequencing or microarrays such as Ingenuity or GSEA, but they have also been adapted for interval-based analysis derived from DNA methylation or ChIP/ATAC-sequencing. Gene-set analysis tools return, as a result, a list of significant gene-sets. However, while these results are useful for the researcher in the identification of major biological insights, they may be complex to interpret because many gene-sets have largely overlapping gene contents. Additionally, in many cases the result of gene-set analysis consists of a large number of gene-sets making it complicated to identify the major biological insights. RESULTS: We present GeneSetCluster, a novel approach which allows clustering of identified gene-sets, from one or multiple experiments and/or tools, based on shared genes. GeneSetCluster calculates a distance score based on overlapping gene content, which is then used to cluster them together and as a result, GeneSetCluster identifies groups of gene-sets with similar gene-set definitions (i.e. gene content). These groups of gene-sets can aid the researcher to focus on such groups for biological interpretations. CONCLUSIONS: GeneSetCluster is a novel approach for grouping together post gene-set analysis results based on overlapping gene content. GeneSetCluster is implemented as a package in R. The package and the vignette can be downloaded at https://github.com/TranslationalBioinformaticsUnit.

Hypermethylation of MIR21 in CD4+ T cells from patients with relapsing-remitting multiple sclerosis associates with lower miRNA-21 levels and concomitant up-regulation of its target genes.

BACKGROUND: Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system caused by genetic and environmental factors. DNA methylation, an epigenetic mechanism that controls genome activity, may provide a link between genetic and environmental risk factors. OBJECTIVE: We sought to identify DNA methylation changes in CD4+ T cells in patients with relapsing-remitting (RR-MS) and secondary-progressive (SP-MS) disease and healthy controls (HC). METHODS: We performed DNA methylation analysis in CD4+ T cells from RR-MS, SP-MS, and HC and associated identified changes with the nearby risk allele, smoking, age, and gene expression. RESULTS: We observed significant methylation differences in the VMP1/MIR21 locus, with RR-MS displaying higher methylation compared to SP-MS and HC. VMP1/MIR21 methylation did not correlate with a known MS risk variant in VMP1 or smoking but displayed a significant negative correlation with age and the levels of mature miR-21 in CD4+ T cells. Accordingly, RR-MS displayed lower levels of miR-21 compared to SP-MS, which might reflect differences in age between the groups, and healthy individuals and a significant enrichment of up-regulated miR-21 target genes. CONCLUSION: Disease-related changes in epigenetic marking of MIR21 in RR-MS lead to differences in miR-21 expression with a consequence on miR-21 target genes.

Usability of human Infinium MethylationEPIC BeadChip for mouse DNA methylation studies.

BACKGROUND: The advent of array-based genome-wide DNA methylation methods has enabled quantitative measurement of single CpG methylation status at relatively low cost and sample input. Whereas the use of Infinium Human Methylation BeadChips has shown great utility in clinical studies, no equivalent tool is available for rodent animal samples. We examined the feasibility of using the new Infinium MethylationEPIC BeadChip for studying DNA methylation in mouse. RESULTS: In silico, we identified 19,420 EPIC probes (referred as mEPIC probes), which align with a unique best alignment score to the bisulfite converted reference mouse genome mm10. Further annotation revealed that 85% of mEPIC probes overlapped with mm10.refSeq genes at different genomic features including promoters (TSS1500 and TSS200), 1st exons, 5'UTRs, 3'UTRs, CpG islands, shores, shelves, open seas and FANTOM5 enhancers. Hybridization of mouse samples to Infinium Human MethylationEPIC BeadChips showed successful measurement of mEPIC probes and reproducibility between inter-array biological replicates. Finally, we demonstrated the utility of mEPIC probes for data exploration such as hierarchical clustering. CONCLUSIONS: Given the absence of cost and labor convenient genome-wide technologies in the murine system, our findings show that the Infinium MethylationEPIC BeadChip platform is suitable for investigation of the mouse methylome. Furthermore, we provide the "mEPICmanifest" with genomic features, available to users of Infinium Human MethylationEPIC arrays for mouse samples.

Epigenetic research in multiple sclerosis: progress, challenges, and opportunities.

Multiple sclerosis (MS) is a chronic inflammatory and demyelinating disease of the central nervous system. MS likely results from a complex interplay between predisposing causal gene variants (the strongest influence coming from HLA class II locus) and environmental risk factors such as smoking, infectious mononucleosis, and lack of sun exposure/vitamin D. However, little is known about the mechanisms underlying MS development and progression. Moreover, the clinical heterogeneity and variable response to treatment represent additional challenges to a comprehensive understanding and efficient treatment of disease. Epigenetic processes, such as DNA methylation and histone posttranslational modifications, integrate influences from the genes and the environment to regulate gene expression accordingly. Studying epigenetic modifications, which are stable and reversible, may provide an alternative approach to better understand and manage disease. We here aim to review findings from epigenetic studies in MS and further discuss the challenges and clinical opportunities arising from epigenetic research, many of which apply to other diseases with similar complex etiology. A growing body of evidence supports a role of epigenetic processes in the mechanisms underlying immune pathogenesis and nervous system dysfunction in MS. However, disparities between studies shed light on the need to consider possible confounders and methodological limitations for a better interpretation of the data. Nevertheless, translational use of epigenetics might offer new opportunities in epigenetic-based diagnostics and therapeutic tools for a personalized care of MS patients.

Clinical validation study of genetic markers for capecitabine efficacy in metastatic colorectal cancer patients.

BACKGROUND AND AIM: Pharmacogenetic studies continue to search for pretreatment predictors of chemotherapeutic efficacy and toxicity in metastatic colorectal cancer. Both genome-wide association studies and candidate gene studies have yielded potential genetic markers for chemosensitivity. We conducted a clinical association study, validating the effect of specific genetic markers cited in recently published papers on the efficacy of the oral 5-fluoro-uracil prodrug capecitabine. PATIENTS AND METHODS: Germline DNA was collected for 268 metastatic colorectal cancer patients from the CAIRO trial, a multicenter phase III trial, randomizing between combined or sequential first-line treatment with capecitabine, irinotecan, and oxaliplatin. Genotyping was performed for eight single-nucleotide polymorphisms (SNPs), using high-resolution melting curves. Four SNPs are located in the MTRR gene, and another four SNPs showed significant association with 5-fluoro-uracil cytotoxicity in a recent in-vitro genome-wide association study. The primary endpoint was progression-free survival (PFS); secondary endpoints were objective response and overall survival. RESULTS: In patients receiving capecitabine monotherapy, rs4702484, located in ADCY2 and close to MTRR, was associated with slightly reduced PFS for homozygous wild-type patients (CC 6.2 vs. CT 8.0 months; P=0.018). For the other selected genetic markers, we found no association with PFS, overall survival, or radiologic response upon treatment with capecitabine, either in the total study population or in the capecitabine monotherapy subgroup. CONCLUSION: With the exception of rs4702484, we found no evidence of an effect on capecitabine chemosensitivity for any of the studied SNPs. More specifically, variants in methionine synthase reductase (MTRR) are not likely associated with capecitabine efficacy.

Anti-citrullinated protein antibodies acquire a pro-inflammatory Fc glycosylation phenotype prior to the onset of rheumatoid arthritis.

OBJECTIVE: To determine whether anticitrullinated protein antibodies (ACPA) exhibit specific changes in Fc glycosylation prior to the onset of arthritis. METHODS: Serum samples of patients with ACPA-positive arthralgia (n=183) were collected at baseline and at various time points of follow-up. 105 patients developed arthritis after a median of 12 months (IQR 6-24) and were classified as having either rheumatoid arthritis (RA, n=48) or undifferentiated arthritis (UA, n=57) based on the 1987 American College of Rheumatology (ACR) criteria. ACPA and total serum IgG were isolated by affinity purification and cleaved by trypsin. ACPA-IgG1 Fc-glycopeptides were subsequently analysed by nano-liquid chromatography mass spectrometry and compared to those of total IgG1. RESULTS: At baseline, ACPA-IgG1 and total IgG1 from arthralgia patients displayed similar Fc glycosylation patterns. By contrast, at the onset of arthritis, ACPA exhibited a decrease in galactose residues in RA patients, but not in UA patients. This decrease occurred around 3 months prior to diagnosis and was paralleled by an increase in systemic inflammation (erythrocyte sedimentation rate). Galactosylation of total IgG1 was also decreased in RA, but this did not precede the onset of arthritis. Interestingly, we additionally noted a higher degree of ACPA-IgG1 Fc core fucosylation at baseline as compared with total IgG1, which further increased prior to diagnosis. CONCLUSIONS: ACPA display significant changes in Fc galactosylation and fucosylation prior to the onset of RA. These changes towards a more pro-inflammatory phenotype could be involved in driving the disease process.

Auto-STEED: A data mining tool for automated extraction of experimental parameters and risk of bias items from in vivo publications.

Background: Systematic reviews, i.e., research summaries that address focused questions in a structured and reproducible manner, are a cornerstone of evidence-based medicine and research. However, certain systematic review steps such as data extraction are labour-intensive which hampers their applicability, not least with the rapidly expanding body of biomedical literature. Objective: To bridge this gap, we aimed at developing a data mining tool in the R programming environment to automate data extraction from neuroscience in vivo publications. The function was trained on a literature corpus (n=45 publications) of animal motor neuron disease studies and tested in two validation corpora (motor neuron diseases, n=31 publications; multiple sclerosis, n=244 publications). Results: Our data mining tool Auto-STEED (Automated and STructured Extraction of Experimental Data) was able to extract key experimental parameters such as animal models and species as well as risk of bias items such as randomization or blinding from in vivo studies. Sensitivity and specificity were over 85 and 80%, respectively, for most items in both validation corpora. Accuracy and F-scores were above 90% and 0.9 for most items in the validation corpora. Time savings were above 99%. Conclusions: Our developed text mining tool Auto-STEED is able to extract key experimental parameters and risk of bias items from the neuroscience in vivo literature. With this, the tool can be deployed to probe a field in a research improvement context or to replace one human reader during data extraction resulting in substantial time-savings and contribute towards automation of systematic reviews. The function is available on Github.

Simultaneous detection of DNA variation and methylation at HLA class II locus and immune gene promoters using targeted SureSelect Methyl-Sequencing.

The Human Leukocyte Antigen (HLA) locus associates with a variety of complex diseases, particularly autoimmune and inflammatory conditions. The HLA-DR15 haplotype, for example, confers the major risk for developing Multiple Sclerosis in Caucasians, pinpointing an important role in the etiology of this chronic inflammatory disease of the central nervous system. In addition to the protein-coding variants that shape the functional HLA-antigen-T cell interaction, recent studies suggest that the levels of HLA molecule expression, that are epigenetically controlled, also play a role in disease development. However, deciphering the exact molecular mechanisms of the HLA association has been hampered by the tremendous genetic complexity of the locus and a lack of robust approaches to investigate it. Here, we developed a method to specifically enrich the genomic DNA from the HLA class II locus (chr6:32,426,802-34,167,129) and proximal promoters of 2,157 immune-relevant genes, utilizing the Agilent RNA-based SureSelect Methyl-Seq Capture related method, followed by sequencing to detect genetic and epigenetic variation. We demonstrated successful simultaneous detection of the genetic variation and quantification of DNA methylation levels in HLA locus. Moreover, by the detection of differentially methylated positions in promoters of immune-related genes, we identified relevant pathways following stimulation of cells. Taken together, we present a method that can be utilized to study the interplay between genetic variance and epigenetic regulation in the HLA class II region, potentially, in a wide disease context.

Evaluation of Cell-Specific Epigenetic Age Acceleration in People With Multiple Sclerosis.

BACKGROUND AND OBJECTIVES: In multiple sclerosis (MS), accelerated aging of the immune system (immunosenescence) may be associated with disease onset or drive progression. DNA methylation (DNAm) is an epigenetic factor that varies among lymphocyte subtypes, and cell-specific DNAm is associated with MS. DNAm varies across the life span and can be used to accurately estimate biological age acceleration, which has been linked to a range of morbidities. The objective of this study was to test for cell-specific epigenetic age acceleration (EAA) in people with MS. METHODS: This was a case-control study of EAA using existing DNAm data from several independent previously published studies. Data were included if .idat files from Illumina 450K or EPIC arrays were available for both a case with MS and an age-matched and sex-matched control, from the same study. Multifactor statistical modeling was performed to assess the primary outcome of EAA. We explored the relationship of EAA and MS, including interaction terms to identify immune cell-specific effects. Cell-sorted DNA methylation data from 3 independent datasets were used to validate findings. RESULTS: We used whole blood DNA methylation data from 583 cases with MS and 643 non-MS controls to calculate EAA using the GrimAge algorithm. The MS group exhibited an increased EAA compared with controls (approximately 9 mths, 95% CI 3.6-14.4), p = 0.001). Statistical deconvolution showed that EAA is associated with MS in a B cell-dependent manner (ß int = 1.7, 95% CI 0.3-2.8), p = 0.002), irrespective of B-cell proportions. Validation analysis using 3 independent datasets enriched for B cells showed an EAA increase of 5.1 years in cases with MS compared with that in controls (95% CI 2.8-7.4, p = 5.5 × 10-5). By comparison, there was no EAA difference in MS in a T cell-enriched dataset. We found that EAA was attributed to the DNAm surrogates for Beta-2-microglobulin (difference = 47,546, 95% CI 10,067-85,026; p = 7.2 × 10-5), and smoking pack-years (difference = 8.1, 95% CI 1.9-14.2, p = 0.002). DISCUSSION: This study provides compelling evidence that B cells exhibit marked EAA in MS and supports the hypothesis that premature B-cell immune senescence plays a role in MS. Future MS studies should focus on age-related molecular mechanisms in B cells.

Transcriptomic Profiling Reveals That HMGB1 Induces Macrophage Polarization Different from Classical M1.

Macrophages are key inflammatory immune cells that display dynamic phenotypes and functions in response to their local microenvironment. In different conditions, macrophage polarization can be induced by high-mobility group box 1 (HMGB1), a nuclear DNA-binding protein that activates innate immunity via the Toll-like receptor (TLR) 4, the receptor for advanced glycation end products (RAGE), and C-X-C chemokine receptor (CXCR) 4. This study investigated the phenotypes of murine bone-marrow-derived macrophages (BMDMs) stimulated with different HMGB1 redox isoforms using bulk RNA sequencing (RNA-Seq). Disulfide HMGB1 (dsHMGB1)-stimulated BMDMs showed a similar but distinct transcriptomic profile to LPS/IFNγ- and LPS-stimulated BMDMs. Fully reduced HMGB1 (frHMGB1) did not induce any significant transcriptomic change. Interestingly, compared to LPS/IFNγ- and LPS-, dsHMGB1-stimulated BMDMs showed lipid metabolism and foam cell differentiation gene set enrichment, and oil red O staining revealed that both dsHMGB1 and frHMGB1 alleviated oxidized low-density lipoprotein (oxLDL)-induced foam cells formation. Overall, this work, for the first time, used transcriptomic analysis by RNA-Seq to investigate the impact of HMGB1 stimulation on BMDM polarization. Our results demonstrated that dsHMGB1 and frHMGB1 induced distinct BMDM polarization phenotypes compared to LPS/IFNγ- and LPS- induced phenotypes.

DNA methylation changes in glial cells of the normal-appearing white matter in Multiple Sclerosis patients.

Multiple Sclerosis (MS), the leading cause of non-traumatic neurological disability in young adults, is a chronic inflammatory and neurodegenerative disease of the central nervous system (CNS). Due to the poor accessibility to the target organ, CNS-confined processes underpinning the later progressive form of MS remain elusive thereby limiting treatment options. We aimed to examine DNA methylation, a stable epigenetic mark of genome activity, in glial cells to capture relevant molecular changes underlying MS neuropathology. We profiled DNA methylation in nuclei of non-neuronal cells, isolated from 38 post-mortem normal-appearing white matter (NAWM) specimens of MS patients (n = 8) in comparison to white matter of control individuals (n = 14), using Infinium MethylationEPIC BeadChip. We identified 1,226 significant (genome-wide adjusted P-value < 0.05) differentially methylated positions (DMPs) between MS patients and controls. Functional annotation of the altered DMP-genes uncovered alterations of processes related to cellular motility, cytoskeleton dynamics, metabolic processes, synaptic support, neuroinflammation and signaling, such as Wnt and TGF-ß pathways. A fraction of the affected genes displayed transcriptional differences in the brain of MS patients, as reported by publically available transcriptomic data. Cell type-restricted annotation of DMP-genes attributed alterations of cytoskeleton rearrangement and extracellular matrix remodelling to all glial cell types, while some processes, including ion transport, Wnt/TGF-ß signaling and immune processes were more specifically linked to oligodendrocytes, astrocytes and microglial cells, respectively. Our findings strongly suggest that NAWM glial cells are highly altered, even in the absence of lesional insult, collectively exhibiting a multicellular reaction in response to diffuse inflammation.

Epigenetic clock indicates accelerated aging in glial cells of progressive multiple sclerosis patients.

Background: Multiple sclerosis (MS) is a chronic inflammatory neurodegenerative disease of the central nervous system (CNS) characterized by irreversible disability at later progressive stages. A growing body of evidence suggests that disease progression depends on age and inflammation within the CNS. We aimed to investigate epigenetic aging in bulk brain tissue and sorted nuclei from MS patients using DNA methylation-based epigenetic clocks. Methods: We applied Horvath's multi-tissue and Shireby's brain-specific Cortical clock on bulk brain tissue (n = 46), sorted neuronal (n = 54), and glial nuclei (n = 66) from post-mortem brain tissue of progressive MS patients and controls. Results: We found a significant increase in age acceleration residuals, corresponding to 3.6 years, in glial cells of MS patients compared to controls (P = 0.0024) using the Cortical clock, which held after adjustment for covariates (P adj = 0.0263). The 4.8-year age acceleration found in MS neurons (P = 0.0054) did not withstand adjustment for covariates and no significant difference in age acceleration residuals was observed in bulk brain tissue between MS patients and controls. Conclusion: While the findings warrant replication in larger cohorts, our study suggests that glial cells of progressive MS patients exhibit accelerated biological aging.

STATegra: Multi-Omics Data Integration - A Conceptual Scheme With a Bioinformatics Pipeline.

Technologies for profiling samples using different omics platforms have been at the forefront since the human genome project. Large-scale multi-omics data hold the promise of deciphering different regulatory layers. Yet, while there is a myriad of bioinformatics tools, each multi-omics analysis appears to start from scratch with an arbitrary decision over which tools to use and how to combine them. Therefore, it is an unmet need to conceptualize how to integrate such data and implement and validate pipelines in different cases. We have designed a conceptual framework (STATegra), aiming it to be as generic as possible for multi-omics analysis, combining available multi-omic anlaysis tools (machine learning component analysis, non-parametric data combination, and a multi-omics exploratory analysis) in a step-wise manner. While in several studies, we have previously combined those integrative tools, here, we provide a systematic description of the STATegra framework and its validation using two The Cancer Genome Atlas (TCGA) case studies. For both, the Glioblastoma and the Skin Cutaneous Melanoma (SKCM) cases, we demonstrate an enhanced capacity of the framework (and beyond the individual tools) to identify features and pathways compared to single-omics analysis. Such an integrative multi-omics analysis framework for identifying features and components facilitates the discovery of new biology. Finally, we provide several options for applying the STATegra framework when parametric assumptions are fulfilled and for the case when not all the samples are profiled for all omics. The STATegra framework is built using several tools, which are being integrated step-by-step as OpenSource in the STATegRa Bioconductor package.

Genome-wide investigation of DNA methylation in congenital adrenal hyperplasia.

Patients with congenital adrenal hyperplasia (CAH) are at risk of long-term cognitive and metabolic sequelae with some of the effects being attributed to the chronic glucocorticoid treatment that they receive. Our pilot study investigates genome-wide DNA methylation in patients with CAH to determine whether there is preliminary evidence for epigenomic reprogramming as well as any relationship to patient outcome. Here, we analysed CD4 + T cell DNA from 28 patients with CAH (mean age = 18.5 ±â€¯6.5 years [y]) and 37 population controls (mean age = 17.0 ±â€¯6.1 y) with the Infinium-HumanMethylation450 BeadChip array to measure genome-wide locus-specific DNA methylation levels. Effects of CAH, phenotype and CYP21A2 genotype on methylation were investigated as well as the association between differentially methylated CpGs and glucose homeostasis, blood lipid profile, and cognitive functions. In addition, we report data on a small cohort of 11 patients (mean age = 19.1, ±6.0 y) with CAH who were treated prenatally with dexamethasone (DEX) in addition to postnatal glucocorticoid treatment. We identified two CpGs to be associated with patient phenotype: cg18486102 (located in the FAIM2 gene; rho = 0.58, adjusted p = 0.027) and cg02404636 (located in the SFI1 gene; rho = 0.58, adjusted p = 0.038). cg02404636 was also associated with genotype (rho = 0.59, adjusted p = 0.024). Higher levels of serum C-peptide was also observed in patients with CAH (p = 0.044). Additionally, levels of C-peptide and HbA1c were positively correlated with patient phenotype (p = 0.044 and p = 0.034) and genotype (p = 0.044 and p = 0.033), respectively. No significant association was found between FAIM2 methylation and cognitive or metabolic outcome. However, SFI1 TSS methylation was associated with fasting plasma HDL cholesterol levels (p = 0.035). In conclusion, in this pilot study, higher methylation levels in CpG sites covering FAIM2 and SFI1 were associated with disease severity. Hypermethylation in these genes may have implications for long-term cognitive and metabolic outcome in patients with CAH, although the data must be interpreted with caution due to the small sample size. Additional studies in larger cohorts are therefore warranted.

Microglial autophagy-associated phagocytosis is essential for recovery from neuroinflammation.

Multiple sclerosis (MS) is a leading cause of incurable progressive disability in young adults caused by inflammation and neurodegeneration in the central nervous system (CNS). The capacity of microglia to clear tissue debris is essential for maintaining and restoring CNS homeostasis. This capacity diminishes with age, and age strongly associates with MS disease progression, although the underlying mechanisms are still largely elusive. Here, we demonstrate that the recovery from CNS inflammation in a murine model of MS is dependent on the ability of microglia to clear tissue debris. Microglia-specific deletion of the autophagy regulator Atg7, but not the canonical macroautophagy protein Ulk1, led to increased intracellular accumulation of phagocytosed myelin and progressive MS-like disease. This impairment correlated with a microglial phenotype previously associated with neurodegenerative pathologies. Moreover, Atg7-deficient microglia showed notable transcriptional and functional similarities to microglia from aged wild-type mice that were also unable to clear myelin and recover from disease. In contrast, induction of autophagy in aged mice using the disaccharide trehalose found in plants and fungi led to functional myelin clearance and disease remission. Our results demonstrate that a noncanonical form of autophagy in microglia is responsible for myelin degradation and clearance leading to recovery from MS-like disease and that boosting this process has a therapeutic potential for age-related neuroinflammatory conditions.

Gsta4 controls apoptosis of differentiating adult oligodendrocytes during homeostasis and remyelination via the mitochondria-associated Fas-Casp8-Bid-axis.

Arrest of oligodendrocyte (OL) differentiation and remyelination following myelin damage in multiple sclerosis (MS) is associated with neurodegeneration and clinical worsening. We show that Glutathione S-transferase 4α (Gsta4) is highly expressed during adult OL differentiation and that Gsta4 loss impairs differentiation into myelinating OLs in vitro. In addition, we identify Gsta4 as a target of both dimethyl fumarate, an existing MS therapy, and clemastine fumarate, a candidate remyelinating agent in MS. Overexpression of Gsta4 reduces expression of Fas and activity of the mitochondria-associated Casp8-Bid-axis in adult oligodendrocyte precursor cells, leading to improved OL survival during differentiation. The Gsta4 effect on apoptosis during adult OL differentiation was corroborated in vivo in both lysolecithin-induced demyelination and experimental autoimmune encephalomyelitis models, where Casp8 activity was reduced in Gsta4-overexpressing OLs. Our results identify Gsta4 as an intrinsic regulator of OL differentiation, survival and remyelination, as well as a potential target for future reparative MS therapies.

Epigenetic Alterations Associated With Early Prenatal Dexamethasone Treatment.

Prenatal treatment with dexamethasone (DEX) reduces virilization in girls with congenital adrenal hyperplasia (CAH). It has potential short- and long-term risks and has been shown to affect cognitive functions. Here, we investigate whether epigenetic modification of DNA during early developmental stages may be a key mediating mechanism by which prenatal DEX treatment could result in poor outcomes in the offspring. We analyzed genome-wide CD4+ T cell DNA methylation, assessed using the Infinium HumanMethylation450 BeadChip array in 29 individuals (mean age = 16.4 ± 5.9 years) at risk for CAH and treated with DEX during the first trimester and 37 population controls (mean age = 17.0 years, SD = 6.1 years). We identified 9672 differentially methylated probes (DMPs) associated with DEX treatment and 7393 DMPs associated with a DEX × sex interaction. DMPs were enriched in intergenic regions located near epigenetic markers for active enhancers. Functional enrichment of DMPs was mostly associated with immune functioning and inflammation but also with nonimmune-related functions. DEX-associated DMPs enriched near single nucleotide polymorphisms (SNPs) associated with inflammatory bowel disease, and DEX × sex-associated DMPs enriched near SNPs associated with asthma. DMPs in genes involved in the regulation and maintenance of methylation and steroidogenesis were identified as well. Methylation in the BDNF, FKBP5, and NR3C1 genes were associated with the performance on several Wechsler Adult Intelligence Scale-Fourth Edition subscales. In conclusion, this study indicates that DNA methylation is altered after prenatal DEX treatment. This finding may have implications for the future health of the exposed individual.

Combining evidence from four immune cell types identifies DNA methylation patterns that implicate functionally distinct pathways during Multiple Sclerosis progression.

BACKGROUND: Multiple Sclerosis (MS) is a chronic inflammatory disease and a leading cause of progressive neurological disability among young adults. DNA methylation, which intersects genes and environment to control cellular functions on a molecular level, may provide insights into MS pathogenesis. METHODS: We measured DNA methylation in CD4+ T cells (n = 31), CD8+ T cells (n = 28), CD14+ monocytes (n = 35) and CD19+ B cells (n = 27) from relapsing-remitting (RRMS), secondary progressive (SPMS) patients and healthy controls (HC) using Infinium HumanMethylation450 arrays. Monocyte (n = 25) and whole blood (n = 275) cohorts were used for validations. FINDINGS: B cells from MS patients displayed most significant differentially methylated positions (DMPs), followed by monocytes, while only few DMPs were detected in T cells. We implemented a non-parametric combination framework (omicsNPC) to increase discovery power by combining evidence from all four cell types. Identified shared DMPs co-localized at MS risk loci and clustered into distinct groups. Functional exploration of changes discriminating RRMS and SPMS from HC implicated lymphocyte signaling, T cell activation and migration. SPMS-specific changes, on the other hand, implicated myeloid cell functions and metabolism. Interestingly, neuronal and neurodegenerative genes and pathways were also specifically enriched in the SPMS cluster. INTERPRETATION: We utilized a statistical framework (omicsNPC) that combines multiple layers of evidence to identify DNA methylation changes that provide new insights into MS pathogenesis in general, and disease progression, in particular. FUND: This work was supported by the Swedish Research Council, Stockholm County Council, AstraZeneca, European Research Council, Karolinska Institutet and Margaretha af Ugglas Foundation.