Dissection of multiple sclerosis genetics identifies B and CD4+ T cells as driver cell subsets
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE202087 | GEO | 2022/05/06
REPOSITORIES: GEO
Similar Datasets
Project description:BackgroundMultiple sclerosis (MS) is an autoimmune condition of the central nervous system with a well-characterized genetic background. Prior analyses of MS genetics have identified broad enrichments across peripheral immune cells, yet the driver immune subsets are unclear.ResultsWe utilize chromatin accessibility data across hematopoietic cells to identify cell type-specific enrichments of MS genetic signals. We find that CD4 T and B cells are independently enriched for MS genetics and further refine the driver subsets to Th17 and memory B cells, respectively. We replicate our findings in data from untreated and treated MS patients and find that immunomodulatory treatments suppress chromatin accessibility at driver cell types. Integration of statistical fine-mapping and chromatin interactions nominate numerous putative causal genes, illustrating complex interplay between shared and cell-specific genes.ConclusionsOverall, our study finds that open chromatin regions in CD4 T cells and B cells independently drive MS genetic signals. Our study highlights how careful integration of genetics and epigenetics can provide fine-scale insights into causal cell types and nominate new genes and pathways for disease.
| S-EPMC9175345 | biostudies-literature
Project description:The purpose of this study was to analyze the transcriptional effects induced by glatiramer acetate treatment (GA; Copaxone, 20 mg injected subcutaneously once daily) in blood monocytes of patients with relapsing-remitting form of multiple sclerosis (MS). By using Affymetrix DNA microarrays, we obtained genome-wide expression profiles of monocytes from 8 MS patients within the first two months of GA administration.
2012-12-07 | GSE42763 | GEO
Project description:For decades, policies regarding generic medicines have sought to provide patients with economical access to safe and effective drugs, while encouraging the development of new therapies. This balance is becoming more challenging for physicians and regulators as biologics and non-biological complex drugs (NBCDs) such as glatiramer acetate demonstrate remarkable efficacy, because generics for these medicines are more difficult to assess. We sought to develop computational methods that use transcriptional profiles to compare branded medicines to generics, robustly characterizing differences in biological impact. We combined multiple computational methods to determine whether differentially expressed genes result from random variation, or point to consistent differences in biological impact of the generic compared to the branded medicine. We applied these methods to analyze gene expression data from mouse splenocytes exposed to either branded glatiramer acetate or a generic. The computational methods identified extensive evidence that branded glatiramer acetate has a more consistent biological impact across batches than the generic, and has a distinct impact on regulatory T cells and myeloid lineage cells. In summary, we developed a computational pipeline that integrates multiple methods to compare two medicines in an innovative way. This pipeline, and the specific findings distinguishing branded glatiramer acetate from a generic, can help physicians and regulators take appropriate steps to ensure safety and efficacy.
2014-10-01 | GSE61901 | GEO
Project description:Glatopa is a generic glatiramer acetate recently approved for the treatment of patients with relapsing forms of multiple sclerosis. Gene expression profiling was performed as a means to evaluate equivalence of Glatopa and Copaxone. Microarray analysis containing 39,429 unique probes across the entire genome was performed in murine glatiramer acetate–responsive Th2-polarized T cells, a test system highly relevant to the biology of glatiramer acetate. A closely related but nonequivalent glatiramoid molecule was used as a control to establish assay sensitivity. Multiple probe-level (Student’s t-test) and sample-level (principal component analysis, multidimensional scaling, and hierarchical clustering) statistical analyses were utilized to look for differences in gene expression induced by the test articles. The analyses were conducted across all genes measured, as well as across a subset of genes that were shown to be modulated by Copaxone. The following observations were made across multiple statistical analyses: the expression of numerous genes was significantly changed by treatment with Copaxone when compared against media-only control; gene expression profiles induced by Copaxone and Glatopa were not significantly different; and gene expression profiles induced by Copaxone and the nonequivalent glatiramoid were significantly different, underscoring the sensitivity of the test system and the multiple analysis methods. Comparative analysis was also performed on sets of transcripts relevant to T-cell biology and antigen presentation, among others that are known to be modulated by glatiramer acetate. No statistically significant differences were observed between Copaxone and Glatopa in the expression levels (magnitude and direction) of these glatiramer acetate-regulated genes. In conclusion, multiple methods consistently supported equivalent gene expression profiles between Copaxone and Glatopa.
2015-09-26 | GSE73465 | GEO
Project description:In order to investigate the effects of Glatiramer acetate (GA) in treatment-naïve RR-MS female patients’ B cells we performed Affymetrix Gene-Chip Human Genome HG-U133A_2 hybridization experiments Transcriptome analysis before and after acute (six hours in vitro) and chronic (six months in vivo) treatment with GA. We compared the transcriptional profiles of B cells, from the above-mentioned patients, treated or not with GA for 6 hours in vitro, and before and after six months of GA treatment in vivo.
2018-11-30 | GSE110023 | GEO
Project description:Dissection of multiple sclerosis genetics identifies B and CD4+ T cells as driver cell subsets
| PRJNA834633 | ENA
Project description:The purpose of this study was to analyze the transcriptional effects induced by glatiramer acetate treatment (GA; Copaxone, 20 mg injected subcutaneously once daily) in blood monocytes of patients with relapsing-remitting form of multiple sclerosis (MS). By using Affymetrix DNA microarrays, we obtained genome-wide expression profiles of monocytes from 8 MS patients within the first two months of GA administration. EDTA blood samples were taken from all patients immediately before first and second GA injection as well as after 1 week, 1 month and 2 months. Total RNA of CD14+ monocytes isolated by magnetic-activated cell sorting (MACS) from each sample was extracted, labeled and hybridized to Affymetrix Human Genome U133 Plus 2.0 arrays to quantify the mRNA levels. This GEO entry provides the U133 Plus 2.0 microarray data.
2012-12-07 | E-GEOD-42763 | biostudies-arrayexpress
Project description:Genetic risk variants identified in genome-wide association studies (GWAS) of complex disease are primarily non-coding, and translating risk variants into mechanistic insight requires detailed gene regulatory maps in disease-relevant cell types. Here, we combined a GWAS of type 1 diabetes (T1D) in 520,580 samples with candidate cis-regulatory elements (cCREs) in pancreas and peripheral blood mononuclear cell types defined using single nucleus ATAC-seq (snATAC-seq) of 131,554 nuclei. T1D risk variants were enriched in cCREs active in T cells and additional cell types, including acinar and ductal cells of the exocrine pancreas. Risk variants at multiple T1D signals overlapped exocrine-specific cCREs linked to genes with exocrine-specific expression. At the CFTR locus, T1D risk variant rs7795896 mapped in a ductal-specific cCRE which regulated CFTR, and the risk allele reduced transcription factor binding, enhancer activity and CFTR expression in ductal cells. These findings support a role for the exocrine pancreas in T1D pathogenesis and highlight the power of large-scale GWAS and single cell epigenomics for understanding the cellular origins of complex disease.
2021-03-15 | GSE163160 | GEO
Project description:For decades, policies regarding generic medicines have sought to provide patients with economical access to safe and effective drugs, while encouraging the development of new therapies. This balance is becoming more challenging for physicians and regulators as biologics and non-biological complex drugs (NBCDs) such as glatiramer acetate demonstrate remarkable efficacy, because generics for these medicines are more difficult to assess. We sought to develop computational methods that use transcriptional profiles to compare branded medicines to generics, robustly characterizing differences in biological impact. We combined multiple computational methods to determine whether differentially expressed genes result from random variation, or point to consistent differences in biological impact of the generic compared to the branded medicine. We applied these methods to analyze gene expression data from mouse splenocytes exposed to either branded glatiramer acetate or a generic. The computational methods identified extensive evidence that branded glatiramer acetate has a more consistent biological impact across batches than the generic, and has a distinct impact on regulatory T cells and myeloid lineage cells. In summary, we developed a computational pipeline that integrates multiple methods to compare two medicines in an innovative way. This pipeline, and the specific findings distinguishing branded glatiramer acetate from a generic, can help physicians and regulators take appropriate steps to ensure safety and efficacy. Glatiramoid samples for SPL cell activation were grouped into four categories: 1) Verified GA, which included GA-RS (22 biological samples) and GA drug product (GA-DP, 34 biological samples from 30 batches) manufactured by Teva; 2) Deliberately Modified GA (DM-GA; 9 biological samples), which included glatiramoids made by Teva that were similar to GA but modified in a variety of ways: prepared with different ingredients (e.g., missing a constituent amino acid); prepared with the same amino acids in the same molar ratio as GA, but with defined amino acid sequences and different molecular weights (referred to as peptide markers TV-35 and TV-66); synthesized by a different process (e.g., changing acetolytic cleavage conditions, alternating polymerization initiator); exposed to destabilizing conditions (e.g., degradation by acid, base, and heat); 3) Unverified Glatiramoids, which included 4 biological samples, TV-5010 and 3 glatiramoids synthesized to be similar to GA but not manufactured using the Teva-patented manufacturing process; and 4) Unverified Generic GA, which included samples from 2 glatiramoids (M-bM-^@M-^\GA-QM-bM-^@M-^] 11 biological samples from 5 different batches, and 2 M-bM-^@M-^\GA-CM-bM-^@M-^] samples from a single batch) marketed as generic GA manufactured by companies other than Teva.
2014-10-01 | E-GEOD-61901 | biostudies-arrayexpress
Project description:Long-term Glatiramer Acetate Treatment Induces Subtle Changes in Microglial Transcriptome
| PRJNA715728 | ENA