The Plasma Cell Signature in Autoimmune Disease
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PROVIDER: PRJNA194546 | ENA |
REPOSITORIES: ENA
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Project description:Objective: Production of pathogenic autoantibodies by self-reactive plasma cells (PC) is a hallmark of autoimmune diseases. Investigating the prevalence of PC in autoimmune disease and their relationship with known pathogenic pathways may increase our understanding of the role of PC in disease progression and treatment response. Methods: We developed a sensitive gene expression based method to overcome the challenges of measuring PC using flow cytometry. Whole genome microarray analysis of sorted cellular fractions identified a panel of genes, IGHA, IGJ, IGKC, IGKV, and TNFRSF17, expressed predominantly in PC. The sensitivity of the PC signature score created from the combined expression levels of these genes was assessed through ex vivo experiments with sorted cells. This PC gene expression signature was used for monitoring changes in PC levels following anti-CD19 therapy; evaluating the relationship between PC and other autoimmune disease-related genes; and estimating PC levels in affected blood and tissue from multiple autoimmune diseases. Results: The PC signature was highly sensitive and capable of detecting as few as 300 PCs. The PC signature was reduced over 90% in scleroderma patients following anti-CD19 treatment and this reduction was highly correlated (r = 0.77) with inhibition of collagen gene expression. Evaluation of multiple autoimmune diseases revealed 30-35% of lupus, rheumatoid arthritis, and scleroderma patients with increased PC levels. Conclusion: This newly developed PC signature provides a robust and accurate method to measure PC levels in the clinic. Our results highlight subsets of patients across multiple autoimmune diseases that may benefit from PC depleting therapy. To examine gene expression in purified cellular fractions, normal human blood was collected from 2 donors as per institutional policy. The granulocyte (CD15+), monocyte (CD14+), T cell (CD3+), B cell (Non-PC gated, CD19+), and PC (CD27++CD38++) fractions from peripheral blood were separated. White blood cells were washed with FACS buffer (PBS + 0.5%BSA + 2mM EDTA (Gibco)) and incubated with 20% heat-inactivated FBS for 10-15 minutes on ice. The following mAbs were added directly to the cells: CD15 (HI98); CD14 (M5E2), CD3 (UCHT1), CD27 (M-T271), CD38 (HB7), and DAPI (Molecular probes). Cells were sorted on a Becton Dickinson FACS Aria II flow cytometer. All sorted fractions were collected in FACS buffer, centrifuged, and the resulting cell pellet was suspended in RNA lysis buffer (Ambion).
2013-03-28 | E-GEOD-45535 | biostudies-arrayexpress
Project description:Objective: Production of pathogenic autoantibodies by self-reactive plasma cells (PC) is a hallmark of autoimmune diseases. Investigating the prevalence of PC in autoimmune disease and their relationship with known pathogenic pathways may increase our understanding of the role of PC in disease progression and treatment response. Methods: We developed a sensitive gene expression based method to overcome the challenges of measuring PC using flow cytometry. Whole genome microarray analysis of sorted cellular fractions identified a panel of genes, IGHA, IGJ, IGKC, IGKV, and TNFRSF17, expressed predominantly in PC. The sensitivity of the PC signature score created from the combined expression levels of these genes was assessed through ex vivo experiments with sorted cells. This PC gene expression signature was used for monitoring changes in PC levels following anti-CD19 therapy; evaluating the relationship between PC and other autoimmune disease-related genes; and estimating PC levels in affected blood and tissue from multiple autoimmune diseases. Results: The PC signature was highly sensitive and capable of detecting as few as 300 PCs. The PC signature was reduced over 90% in scleroderma patients following anti-CD19 treatment and this reduction was highly correlated (r = 0.77) with inhibition of collagen gene expression. Evaluation of multiple autoimmune diseases revealed 30-35% of lupus, rheumatoid arthritis, and scleroderma patients with increased PC levels. Conclusion: This newly developed PC signature provides a robust and accurate method to measure PC levels in the clinic. Our results highlight subsets of patients across multiple autoimmune diseases that may benefit from PC depleting therapy. MI-CP200 is a Phase 1, randomized, double-blind, placebo-controlled study to evaluate the safety and tolerability of escalating single IV doses of MEDI-551 in adult subjects with scleroderma. In this study, 5 cohorts of subjects (n=25) received 1 of 5 single IV doses of MEDI-551 (0.1, 0.3, 1.0, 3.0, or 10.0 mg/kg) or placebo. Twenty-four healthy donor control samples are also included.
2013-03-28 | E-GEOD-45536 | biostudies-arrayexpress
Project description:Objective: Production of pathogenic autoantibodies by self-reactive plasma cells (PC) is a hallmark of autoimmune diseases. Investigating the prevalence of PC in autoimmune disease and their relationship with known pathogenic pathways may increase our understanding of the role of PC in disease progression and treatment response. Methods: We developed a sensitive gene expression based method to overcome the challenges of measuring PC using flow cytometry. Whole genome microarray analysis of sorted cellular fractions identified a panel of genes, IGHA, IGJ, IGKC, IGKV, and TNFRSF17, expressed predominantly in PC. The sensitivity of the PC signature score created from the combined expression levels of these genes was assessed through ex vivo experiments with sorted cells. This PC gene expression signature was used for monitoring changes in PC levels following anti-CD19 therapy; evaluating the relationship between PC and other autoimmune disease-related genes; and estimating PC levels in affected blood and tissue from multiple autoimmune diseases. Results: The PC signature was highly sensitive and capable of detecting as few as 300 PCs. The PC signature was reduced over 90% in scleroderma patients following anti-CD19 treatment and this reduction was highly correlated (r = 0.77) with inhibition of collagen gene expression. Evaluation of multiple autoimmune diseases revealed 30-35% of lupus, rheumatoid arthritis, and scleroderma patients with increased PC levels. Conclusion: This newly developed PC signature provides a robust and accurate method to measure PC levels in the clinic. Our results highlight subsets of patients across multiple autoimmune diseases that may benefit from PC depleting therapy.
2013-03-28 | GSE45536 | GEO
Project description:Objective: Production of pathogenic autoantibodies by self-reactive plasma cells (PC) is a hallmark of autoimmune diseases. Investigating the prevalence of PC in autoimmune disease and their relationship with known pathogenic pathways may increase our understanding of the role of PC in disease progression and treatment response. Methods: We developed a sensitive gene expression based method to overcome the challenges of measuring PC using flow cytometry. Whole genome microarray analysis of sorted cellular fractions identified a panel of genes, IGHA, IGJ, IGKC, IGKV, and TNFRSF17, expressed predominantly in PC. The sensitivity of the PC signature score created from the combined expression levels of these genes was assessed through ex vivo experiments with sorted cells. This PC gene expression signature was used for monitoring changes in PC levels following anti-CD19 therapy; evaluating the relationship between PC and other autoimmune disease-related genes; and estimating PC levels in affected blood and tissue from multiple autoimmune diseases. Results: The PC signature was highly sensitive and capable of detecting as few as 300 PCs. The PC signature was reduced over 90% in scleroderma patients following anti-CD19 treatment and this reduction was highly correlated (r = 0.77) with inhibition of collagen gene expression. Evaluation of multiple autoimmune diseases revealed 30-35% of lupus, rheumatoid arthritis, and scleroderma patients with increased PC levels. Conclusion: This newly developed PC signature provides a robust and accurate method to measure PC levels in the clinic. Our results highlight subsets of patients across multiple autoimmune diseases that may benefit from PC depleting therapy.
2013-03-28 | GSE45535 | GEO
Project description:The Plasma Cell Signature in Autoimmune Disease (II)
| PRJNA194548 | ENA
Project description:The Plasma Cell Signature in Autoimmune Disease (I)
| PRJNA194547 | ENA
Project description:This SuperSeries is composed of the SubSeries listed below. Refer to individual Series
2013-03-28 | E-GEOD-45537 | biostudies-arrayexpress
Project description:Patients with autoimmune disorders exhibit highly reproducible gene expression profiles in their peripheral blood mononuclear cells. These signatures may result from chronic inflammation, other disease manifestations, or may reflect family resemblance. To test the latter hypothesis, we determined gene expression profiles in unaffected first-degree relatives of individuals with autoimmune disease. Gene expression profiles in unaffected first-degree relatives resembled the profiles found in individuals with autoimmune diseases. A high percentage of differentially expressed genes in unaffected first-degree relatives were previously identified as autoimmune signature genes. Examination of the linear regression relationship of gene transcript levels between parent-offspring pairs revealed that autoimmune signature genes display high levels of family resemblance. Taken together, these results support the hypothesis that these variations in gene transcript levels are associated with family resemblance rather than clinical manifestations of disease. Gene expression profiling of autoimmune families
2010-06-09 | E-GEOD-3459 | biostudies-arrayexpress
Project description:This SuperSeries is composed of the SubSeries listed below.
2013-03-28 | GSE45537 | GEO
Project description:We seek to discover small RNA biomarkers of autoimmune activity andor beta cell damage in type 1 diabetes. Pilot studies showed that heparinized plasma failed analyses, but that EDTA and citrated plasma did well, so 353 appropriate plasma samples average 11 per subject prospectively collected every 1 to 3 months from 32 high risk MAB or newly diabetic children and adolescents were collected, and the first 94 analyzed, for circulating small regulatory RNAs. 92 of 94 resulting cDNA libraries gave adequate numbers of miRNA mapped reads, but QC using spiked RNA internal standards showed abnormally high small RNA levels in 8 mildly hemolyzed plasma samples, leaving 84 of 94 with analyzable data. Equal numbers of EDTA and citrated plasma were analyzed successfully. Over the next period we will complete series on another 6 subjects, sequence the remaining 26070340 samples, and analyze the data for patterns of disease association with small RNA molecules in the prediabetic, perionset, and immediate post onset period. These patterns may identify biomarker small RNA predictive of autoimmune flares or beta cell loss, including predicting impending clinical onset.
2022-10-30 | GSE216551 | GEO