Integration of small RNAs from plasma and cerebrospinal fluid for classification of multiple sclerosis.

Multiple Sclerosis (MS) is an autoimmune, neurological disease, commonly presenting with a relapsing-remitting form, that later converts to a secondary progressive stage, referred to as RRMS and SPMS, respectively. Early treatment slows disease progression, hence, accurate and early diagnosis is crucial. Recent advances in large-scale data processing and analysis have progressed molecular biomarker development. Here, we focus on small RNA data derived from cell-free cerebrospinal fluid (CSF), cerebrospinal fluid cells, plasma and peripheral blood mononuclear cells as well as CSF cell methylome data, from people with RRMS (n = 20), clinically/radiologically isolated syndrome (CIS/RIS, n = 2) and neurological disease controls (n = 14). We applied multiple co-inertia analysis (MCIA), an unsupervised and thereby unbiased, multivariate method for simultaneous data integration and found that the top latent variable classifies RRMS status with an Area Under the Receiver Operating Characteristics (AUROC) score of 0.82. Variable selection based on Lasso regression reduced features to 44, derived from the small RNAs from plasma (20), CSF cells (8) and cell-free CSF (16), with a marginal reduction in AUROC to 0.79. Samples from SPMS patients (n = 6) were subsequently projected on the latent space and differed significantly from RRMS and controls. On contrary, we found no differences between relapse and remission or between inflammatory and non-inflammatory disease controls, suggesting that the latent variable is not prone to inflammatory signals alone, but could be MS-specific. Hence, we here showcase that integration of small RNAs from plasma and CSF can be utilized to distinguish RRMS from SPMS and neurological disease controls.

Comparison of EM-seq and PBAT methylome library methods for low-input DNA.

DNA methylation is the most studied epigenetic mark involved in regulation of gene expression. For low input samples, a limited number of methods for quantifying DNA methylation genome-wide has been evaluated. Here, we compared a series of input DNA amounts (1-10ng) from two methylome library preparation protocols, enzymatic methyl-seq (EM-seq) and post-bisulfite adaptor tagging (PBAT) adapted from single-cell PBAT. EM-seq takes advantage of enzymatic activity while PBAT relies on conventional bisulfite conversion for detection of DNA methylation. We found that both methods accurately quantified DNA methylation genome-wide. They produced expected distribution patterns around genomic features, high C-T transition efficiency at non-CpG sites and high correlation between input amounts. However, EM-seq performed better in regard to library and sequencing quality, i.e. EM-seq produced larger insert sizes, higher alignment rates and higher library complexity with lower duplication rate compared to PBAT. Moreover, EM-seq demonstrated higher CpG coverage, better CpG site overlap and higher consistency between input series. In summary, our data suggests that EM-seq overall performed better than PBAT in whole-genome methylation quantification of low input samples.

Small noncoding RNA profiling across cellular and biofluid compartments and their implications for multiple sclerosis immunopathology.

Multiple sclerosis (MS) is a chronic inflammatory demyelinating disease affecting the central nervous system (CNS). Small non-coding RNAs (sncRNAs) and, in particular, microRNAs (miRNAs) have frequently been associated with MS. Here, we performed a comprehensive analysis of all classes of sncRNAs in matching samples of peripheral blood mononuclear cells (PBMCs), plasma, cerebrospinal fluid (CSF) cells, and cell-free CSF from relapsing-remitting (RRMS, n = 12 in relapse and n = 11 in remission) patients, secondary progressive (SPMS, n = 6) MS patients, and noninflammatory and inflammatory neurological disease controls (NINDC, n = 11; INDC, n = 5). We show widespread changes in miRNAs and sncRNA-derived fragments of small nuclear, nucleolar, and transfer RNAs. In CSF cells, 133 out of 133 and 115 out of 117 differentially expressed sncRNAs were increased in RRMS relapse compared to remission and RRMS compared to NINDC, respectively. In contrast, 65 out of 67 differentially expressed PBMC sncRNAs were decreased in RRMS compared to NINDC. The striking contrast between the periphery and CNS suggests that sncRNA-mediated mechanisms, including alternative splicing, RNA degradation, and mRNA translation, regulate the transcriptome of pathogenic cells primarily in the CNS target organ.

Small non-coding RNAs as important players, biomarkers and therapeutic targets in multiple sclerosis: A comprehensive overview.

Multiple sclerosis (MS) is a leading cause of progressive disability among young adults caused by inflammation, demyelination and axonal loss in the central nervous system. Small non-coding RNAs (sncRNAs) are important regulators of various biological processes and could therefore play important roles in MS. Over the past decade, a large number of studies investigated sncRNAs in MS patients, focusing primarily on microRNAs (miRNAs). Overwhelming 500 miRNAs have been reported as dysregulated in MS. Nevertheless, owing to a large heterogeneity between studies it is challenging to evaluate the reproducibility of findings, in turn hampering our knowledge about the functional roles of miRNAs in disease. We systematically searched main databases and evaluated results from all studies that examined sncRNAs in MS to date (n = 61) and provided a detailed overview of experimental design and findings of these studies. We focused on the mechanisms of the most dysregulated sncRNAs and used predicted targets of the most dysregulated sncRNAs as input for functional enrichment analysis to highlight affected pathways. The prime affected pathway was TGF-ß signaling. This multifunctional cytokine is important in the differentiation and function of T helper type 17 (Th17) and regulatory T (Treg) cells, with opposing functions in the disease. Recent studies demonstrate the importance of miRNAs in controlling the balance between Th17/Th1 cells and Tregs and, importantly, the potential to exploit this paradigm for therapeutic purposes. Additionally, some of the discussed miRNAs could potentially serve as biomarkers of disease. In order to assist researchers in evaluating the evidence of a particular sncRNA in the pathogenesis of MS, we provide a detailed overview of experimental design and findings of these studies to date.