E-GEOD-77598
Ontology highlight
ABSTRACT:
PROVIDER: E-GEOD-77598 | ExpressionAtlas | 2019-05-14
REPOSITORIES: ExpressionAtlas
Similar Datasets
Project description:This SuperSeries is composed of the following subset Series: GSE39642: NanoString nCounter immune-related gene expression in blood sorted CD14+CD16- monocytes from sALS, fALS and HC subjects GSE39643: NanoString miRNA profiling of peripheral blood sorted CD14+CD16- monocytes from amyotrophic lateral sclerosis, multiple sclerosis and healthy control subjects Refer to individual Series
2012-07-25 | E-GEOD-39644 | biostudies-arrayexpress
Project description:This experiment was carried out in the context of a whole-genome sequencing study in 4 affected and 4 unaffected relatives of a consanguineous Italian family characterized by the high prevalence of multiple sclerosis. These data were used to evaluate differences in GRAMD1B gene expression in whole blood comparing healthy and affected subjects of the family. Functional experiments have been subsequently performed to evaluate the involvement of this gene in multiple sclerosis.
2018-08-01 | GSE103005 | GEO
Project description:This study compared whole transcriptome signatures of 6 immune cell subsets and whole blood from patients with an array of immune-associated diseases. Fresh blood samples were collected from healthy subjects and subjects diagnosed type 1 diabetes, amyotrophic lateral sclerosis, and sepsis, as well as multiple sclerosis patients before and 24 hours after the first treatment with IFN-beta. At the time of blood draw, an aliquot of whole blood was collected into a Tempus tube (Invitrogen), while the remainder of the primary fresh blood sample was processed to highly pure populations of neutrophils, monocytes, B cells, CD4 T cells, CD8 T cells, and natural killer cells. RNA was extracted from each of these cell subsets, as well as the whole blood samples, and processed into RNA sequencing (RNAseq) libraries (Illumina TruSeq). Sequencing libraries were analyzed on an Illumina HiScan, with a target read depth of ~20M reads. Reads were demultiplexed, mapped to human gene models (ENSEMBL), and tabulated using HTSeq. Read count data were normalized by the TMM procedure (edgeR package). We performed whole genome RNAseq profiling of immune cell subsets and whole blood from subjects with an array of immune-associated diseases.
2015-01-06 | E-GEOD-60424 | biostudies-arrayexpress
Project description:Whole transcriptome RNA-seq analysis to measure group-wise RNA expression level of the MERTK gene in 3 healthy controls (known to be homozygous non-risk haplotype at MERTK gene locus) and to compare this to the group-wise RNA expression level of the MERTK gene in 5 Multiple Sclerosis-affected (MS-affected) individuals (known to be homozygous for the MS risk haplotype at the MERTK gene locus). We sequenced the whole transcriptome of 3 healthy control samples which were all homozygous for the MS non-risk haplotype at the MERTK gene. We also did the same RNA-seq protocol on 5 MS-affected subjects that were all homozygous for the Risk haplotype at the MERTK gene. All 8 samples were sequenced evenly across 3 lanes of an Illumina HiSeq NGS machine to remove any batch-type effects that could be caused by sequencing e.g. all cases in one lane and all controls in another lane.
2016-02-06 | E-GEOD-77598 | biostudies-arrayexpress
Project description:Systemic sclerosis (SSc) is a chronic autoimmune disease that mainly affects the connective tissue. Monocytes have been shown to be an important cell type involved in the pathogenesis of SSc. By performing RNA-sequencing analysis on whole RNA isolated from peripheral blood CD14+ monocytes obtained from SSc patients, together with healthy controls matched for sex and age, obtained from the University Medical Center Utrecht (definite SSc cohort), and the University of Milan (non-fibrotic SSc cohort), we aimed to characterize the transcriptomic landscape of monocytes of patients with (pre-clinical) systemic sclerosis. Moreover, ChIPseq data was available for a part of the subjects included in the RNA-seq analysis and the correlation between the histone marks and gene expression was studied. The samples used in this study are part of the SYSCLASS cohort.
2019-03-06 | GSE124073 | GEO
Project description:Using the Illumina 450K array and a stringent statistical analysis with age and gender correction, we report genome-wide differences in DNA methylation between pathology-free regions derived from human multiple sclerosis–affected and control brains. Differences were subtle, but widespread and reproducible in an independent validation cohort. The transcriptional consequences of differential DNA methylation were further defined by genome-wide RNA-sequencing analysis and validated in two independent cohorts. Genes regulating oligodendrocyte survival, such as BCL2L2 and NDRG1, were hypermethylated and expressed at lower levels in multiple sclerosis–affected brains than in controls, while genes related to proteolytic processing (for example, LGMN, CTSZ) were hypomethylated and expressed at higher levels. These results were not due to differences in cellular composition between multiple sclerosis and controls. Thus, epigenomic changes in genes affecting oligodendrocyte susceptibility to damage are detected in pathology-free areas of multiple sclerosis–affected brains.
2013-11-24 | GSE40360 | GEO
Project description:This study compared whole transcriptome signatures of 6 immune cell subsets and whole blood from patients with an array of immune-associated diseases. Fresh blood samples were collected from healthy subjects and subjects diagnosed type 1 diabetes, amyotrophic lateral sclerosis, and sepsis, as well as multiple sclerosis patients before and 24 hours after the first treatment with IFN-beta. At the time of blood draw, an aliquot of whole blood was collected into a Tempus tube (Invitrogen), while the remainder of the primary fresh blood sample was processed to highly pure populations of neutrophils, monocytes, B cells, CD4 T cells, CD8 T cells, and natural killer cells. RNA was extracted from each of these cell subsets, as well as the whole blood samples, and processed into RNA sequencing (RNAseq) libraries (Illumina TruSeq). Sequencing libraries were analyzed on an Illumina HiScan, with a target read depth of ~20M reads. Reads were demultiplexed, mapped to human gene models (ENSEMBL), and tabulated using HTSeq. Read count data were normalized by the TMM procedure (edgeR package).
2015-01-06 | GSE60424 | GEO
Project description:NanoString miRNA profiling of peripheral blood sorted CD14+CD16- monocytes from amyotrophic lateral sclerosis, multiple sclerosis and healthy control subjects
| PRJNA171318 | ENA
Project description:Human serum samples from Multiple Sclerosis (MS) subjects and healthy control subjects were probed onto human protein microarrays in order to identify differentially expressed autoantibody biomarkers that could be used as diagnostic indicators. Other neurodegenerative and non-neurodegenerative diseases were also used to help measure the specificity of the selected biomarkers.
2017-07-26 | GSE95718 | GEO