Large-scale gene-expression studies and the challenge of multiple sclerosis.

In multiple sclerosis, a complex neurodegenerative disorder, a combination of genetic and environmental factors results in inflammation and myelin damage. Recent transcription-profiling studies have found distinct gene-expression patterns in diseased tissue; such large-scale studies at different stages of the disease are contributing to understanding multiple sclerosis and developing effective therapy

Integrating biomedical research and electronic health records to create knowledge-based biologically meaningful machine-readable embeddings.

In order to advance precision medicine, detailed clinical features ought to be described in a way that leverages current knowledge. Although data collected from biomedical research is expanding at an almost exponential rate, our ability to transform that information into patient care has not kept at pace. A major barrier preventing this transformation is that multi-dimensional data collection and analysis is usually carried out without much understanding of the underlying knowledge structure. Here, in an effort to bridge this gap, Electronic Health Records (EHRs) of individual patients are connected to a heterogeneous knowledge network called Scalable Precision Medicine Oriented Knowledge Engine (SPOKE). Then an unsupervised machine-learning algorithm creates Propagated SPOKE Entry Vectors (PSEVs) that encode the importance of each SPOKE node for any code in the EHRs. We argue that these results, alongside the natural integration of PSEVs into any EHR machine-learning platform, provide a key step toward precision medicine

The Gut Microbiome in Neuromyelitis Optica.

Neuromyelitis optica (NMO) is a rare, disabling, sometimes fatal central nervous system inflammatory demyelinating disease that is associated with antibodies ("NMO IgG") that target the water channel protein aquaporin-4 (AQP4) expressed on astrocytes. There is considerable interest in identifying environmental triggers that may elicit production of NMO IgG by AQP4-reactive B cells. Although NMO is considered principally a humoral autoimmune disease, antibodies of NMO IgG are IgG1, a T-cell-dependent immunoglobulin subclass, indicating that AQP4-reactive T cells have a pivotal role in NMO pathogenesis. When AQP4-specific proliferative T cells were first identified in patients with NMO it was discovered that T cells recognizing the dominant AQP4 T-cell epitope exhibited a T helper 17 (Th17) phenotype and displayed cross-reactivity to a homologous peptide sequence within a protein of Clostridium perfringens, a commensal bacterium found in human gut flora. The initial analysis of gut microbiota in NMO demonstrated that, in comparison to healthy controls (HC) and patients with multiple sclerosis, the microbiome of NMO is distinct. Remarkably, C. perfringens was the second most significantly enriched taxon in NMO, and among bacteria identified at the species level, C. perfringens was the one most highly associated with NMO. Those discoveries, along with evidence that certain Clostridia in the gut can regulate the balance between regulatory T cells and Th17 cells, indicate that gut microbiota, and possibly C. perfringens itself, could participate in NMO pathogenesis. Collectively, the evidence linking microbiota to humoral and cellular immunity in NMO underscores the importance for further investigating this relationship

Mononuclear cell transcriptome changes associated with dimethyl fumarate in MS.

ObjectiveTo identify short-term changes in gene expression in peripheral blood mononuclear cells (PBMCs) associated with treatment response to dimethyl fumarate (DMF, Tecfidera) in patients with relapsing-remitting MS (RRMS).MethodsBlood samples were collected from 24 patients with RRMS (median Expanded Disability Status Scale score, 2.0; range 1-7) at baseline, 6 weeks, and 15 months after the initiation of treatment with DMF (BG-12; Tecfidera). Seven healthy controls were also recruited, and blood samples were collected over the same time intervals. PBMCs were extracted from blood samples and sequenced using next-generation RNA sequencing. Treatment responders were defined using the composite outcome measure "no evidence of disease activity" (NEDA-4). Time-course and cross-sectional differential expression analyses were performed to identify transcriptomic markers of treatment response.ResultsTreatment responders (NEDA-4 positive, 8/24) over the 15-month period had 478 differentially expressed genes (DEGs) 6 weeks after the start of treatment. These were enriched for nuclear factor (erythroid-derived 2)-like 2 (Nrf2) and inhibition of nuclear factor κB (NFκB) pathway transcripts. For patients who showed signs of disease activity, there were no DEGs at 6 weeks relative to their (untreated) baseline. Contrasting transcriptomes expressed at 6 weeks with those at 15 months of treatment, 0 and 1,264 DEGs were found in the responder and nonresponder groups, respectively. Transcripts in the nonresponder group (NEDA-4 negative, 18/24) were enriched for T-cell signaling genes.ConclusionShort-term PBMC transcriptome changes reflecting activation of the Nrf2 and inhibition of NFκB pathways distinguish patients who subsequently show a medium-term treatment response with DMF. Relative stabilization of gene expression patterns may accompany treatment-associated suppression of disease activity

SNP imputation bias reduces effect size determination

Imputation is a commonly used technique that exploits linkage disequilibrium to infer missing genotypes in genetic datasets, using a well characterized reference population. While there is agreement that the reference population has to match the ethnicity of the query dataset, it is common practice to use the same reference to impute genotypes for a wide variety of phenotypes. We hypothesized that using a reference composed of samples with a different phenotype than the query dataset would introduce imputation bias.To test this hypothesis we used GWAS datasets from amyotrophic lateral sclerosis, Parkinson disease, and Crohn disease. First, we masked and then performed imputation of 100 disease-associated markers and 100 non-associated markers from each study. Two references for imputation were used in parallel: one consisting of healthy controls and another consisting of patients with the same disease. We assessed the discordance (imprecision) and bias (inaccuracy) of imputation by comparing predicted genotypes to those assayed by SNP-chip. We also assessed the bias on the observed effect size when the predicted genotypes were used in a GWAS study.When healthy controls were used as reference for imputation, a significant bias was observed, particularly in the disease-associated markers. Using cases as reference significantly attenuated this bias. For nearly all markers, the direction of the bias favored the non-risk allele. In GWAS studies of the three diseases (with healthy reference controls from the 1000 genomes as reference), the mean OR for disease-associated markers obtained by imputation was lower than that obtained using original assayed genotypes.We found that the bias is inherent to imputation as using different methods did not alter the results. In conclusion, imputation is a powerful method to predict genotypes and estimate genetic risk for GWAS. However, a careful choice of reference population is needed to minimize biases inherent to this approac

Peroxisome proliferator-activated receptor (PPAR)alpha expression in T cells mediates gender differences in development of T cell-mediated autoimmunity.

Peroxisome proliferator-activated receptor (PPAR)alpha is a nuclear receptor that mediates gender differences in lipid metabolism. PPARalpha also functions to control inflammatory responses by repressing the activity of nuclear factor kappaB (NF-kappaB) and c-jun in immune cells. Because PPARalpha is situated at the crossroads of gender and immune regulation, we hypothesized that this gene may mediate sex differences in the development of T cell-mediated autoimmune disease. We show that PPARalpha is more abundant in male as compared with female CD4(+) cells and that its expression is sensitive to androgen levels. Genetic ablation of this gene selectively removed the brake on NF-kappaB and c-jun activity in male T lymphocytes, resulting in higher production of interferon gamma and tumor necrosis factor (but not interleukin 17), and lower production of T helper (Th)2 cytokines. Upon induction of experimental autoimmune encephalomyelitis, male but not female PPARalpha(-/-) mice developed more severe clinical signs that were restricted to the acute phase of disease. These results suggest that males are less prone to develop Th1-mediated autoimmunity because they have higher T cell expression of PPARalpha

Aberrant oligodendroglial-vascular interactions disrupt the blood-brain barrier, triggering CNS inflammation.

Disruption of the blood-brain barrier (BBB) is critical to initiation and perpetuation of disease in multiple sclerosis (MS). We report an interaction between oligodendroglia and vasculature in MS that distinguishes human white matter injury from normal rodent demyelinating injury. We find perivascular clustering of oligodendrocyte precursor cells (OPCs) in certain active MS lesions, representing an inability to properly detach from vessels following perivascular migration. Perivascular OPCs can themselves disrupt the BBB, interfering with astrocyte endfeet and endothelial tight junction integrity, resulting in altered vascular permeability and an associated CNS inflammation. Aberrant Wnt tone in OPCs mediates their dysfunctional vascular detachment and also leads to OPC secretion of Wif1, which interferes with Wnt ligand function on endothelial tight junction integrity. Evidence for this defective oligodendroglial-vascular interaction in MS suggests that aberrant OPC perivascular migration not only impairs their lesion recruitment but can also act as a disease perpetuator via disruption of the BBB

The molecular signature of therapeutic mesenchymal stem cells exposes the architecture of the hematopoietic stem cell niche synapse

BACKGROUND: The hematopoietic stem cells (HSCs) niche of the bone marrow is comprised of HSCs, osteoblasts, endothelial cells and a stromal component of non-hematopoietic multipotent cells of mesenchymal origin named "mesenchymal stem cells" (MSCs). RESULTS: Here we studied the global transcriptional profile of murine MSCs with immuno-therapeutic potential and compared it with that of 486 publicly available microarray datasets from 12 other mouse tissues or cell types. Principal component analysis and hierarchical clustering identified a unique pattern of gene expression capable of distinctively classifying MSCs from other tissues and cells. We then performed an analysis aimed to identify absolute and relative abundance of transcripts in all cell types. We found that the set of transcripts uniquely expressed by MSCs is enriched in transcription factors and components of the Wnt signaling pathway. The analysis of differentially expressed genes also identified a set of genes specifically involved in the HSC niche and is complemented by functional studies that confirm the findings. Interestingly, some of these genes play a role in the maintenance of HSCs in a quiescent state supporting their survival and preventing them from proliferating and differentiating. We also show that MSCs modulate T cell functions in vitro and, upon in vivo administration, ameliorate experimental autoimmune encephalomyelitis (EAE). CONCLUSION: Altogether, these findings provide novel and important insights on the mechanisms of T cell function regulation by MSCs and help to cement the rationale for their application in the treatment of autoimmune diseases