Activation of the Interferon Pathway is Dependent upon Autoantibodies in African-American SLE Patients, but not in European-American SLE Patients
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE50635 | GEO | 2013/11/15
SECONDARY ACCESSION(S): PRJNA218139
REPOSITORIES: GEO
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Project description:Systemic lupus erythematosus (SLE) is a heterogeneous disease which leads to different levels of serum autoantibodies to RNA-binding proteins (anti-RBP) and interferon-α (IFN-α), which plays an important pathogenic role in SLE, between European-American (EA) and African-American (AA) patients. We aimed to explore how IFN-related gene expression pathways differ in patients according to their ancestry and anti-RBP profile Whole blood from 33 female SLE patients and 16 matched controls from EA and AA ancestral backgrounds was analyzed through Affymetrix Gene 1.0 ST gene expression arrays and the data were further studied through Ingenuity Pathways Analysis for canonical pathway comparison. An independent replication cohort of more than 100 SLE patient samples and 30 controls was used to test the hypotheses generated by the microarray data, using qPCR to quantify gene expression.
2013-11-15 | E-GEOD-50635 | biostudies-arrayexpress
Project description:Systemic lupus erythematosus (SLE) affects 1 in 537 of African American (AA) women, which is >2-fold more than European American (EA) women. AA patients also develop the disease at a younger age, have more severe symptoms, and a greater chance of early mortality. We used a multi-omics approach to uncover ancestry-specific immune alterations in SLE patients and healthy controls that may contribute to disease disparities. Cell composition, signaling, and epigenetics were evaluated by mass cytometry; droplet-based single cell transcriptomics and paired proteogenomics (scRNA-Seq/scCITE-Seq). Soluble mediator levels were measured in plasma and stimulated whole blood. TLR3/4/7/8/9 gene expression pathways in B cells and monocytes were enhanced in AA SLE patients compared to EA patients. TLR7/8/9 and IFN phospho-signaling responses were also heightened in healthy AA versus EA controls. Exposure of AA and EA healthy control cells to TLR7/8/9 agonists or IFN resulted in altered immune cell compositions that recapitulated the ancestry-associated differences in SLE patients. These data support that ancestry-based differences in TLR7/8, TLR9, and IFN responses that can be detected in healthy individuals could influence lupus disease course and severity.
2023-10-11 | GSE189050 | GEO
Project description:Background/Purpose: Systemic lupus erythematosus (SLE) is a complex multi-system autoimmune disease of uncertain etiology. Patients from different ancestral backgrounds demonstrate differences in clinical manifestations and autoantibody profiles. In this study we examined genome-wide transcriptional patterns in major immune cell subsets across different ancestral backgrounds. Methods: Peripheral blood was collected from 21 African-American (AA) and 21 European-American (EA) SLE patients, 5 AA controls, and 5 EA controls. CD4+ T-cells, CD8+ T-cells, monocytes and B cells were purified by flow sorting. Each cell subset from each subject was run on an Illumina HumanHT-12 V4 expression BeadChip array (n=208 arrays). Differentially expressed genes (DEGs) were determined by comparing cases and controls of the same ancestral background. Results: The overlap in DEG lists between different cell types from the same ancestral background was very modest (<1%). Typically between 5-10% of DEGs were shared when comparing the same cell type between different ancestral backgrounds (for ex. CD20 AA vs. CD20 EA). Quantitative measurement of global IFN-stimulated gene (ISG) expression revealed that AA subjects demonstrated more concordance across all studied cell types. Two subgroups of patients were identified based on the ISG expression profiles. One subgroup showed higher ISGs expression in all cell types, and the other subgroup had higherISG expression only in T and B lymphocytes but not in monocytes. The correlation of ISG expression with medication data revealed that only the B cells had lower ISG expression in patients taking immunosuppressants, while ISG expression in the other cell types did not differ based upon medication use. Conclusion: We find striking differences in gene expression between different immune cell subsets and between ancestral backgrounds in SLE patients. The IFN signature is diverse, with different transcripts represented in different cell populations, and signature-positive cell subsets differed in EA vs. AA patients. We also find that treatment with the immunosuppressive agents correlates with the down-regulation of B cell ISG expression, and this was not observed in other cell types. Peripheral blood was collected from 21 African-American (AA) and 21 European-American (EA) SLE patients, 5 AA controls, and 5 EA controls. CD4+ T-cells, CD8+ T-cells, monocytes and B cells were purified by flow sorting. Each cell subset from each subject was run on an Illumina HumanHT-12 V4 expression BeadChip array (n=208 arrays).
2015-05-15 | E-GEOD-55447 | biostudies-arrayexpress
Project description:Background/Purpose: Systemic lupus erythematosus (SLE) is a complex multi-system autoimmune disease of uncertain etiology. Patients from different ancestral backgrounds demonstrate differences in clinical manifestations and autoantibody profiles. In this study we examined genome-wide transcriptional patterns in major immune cell subsets across different ancestral backgrounds. Methods: Peripheral blood was collected from 21 African-American (AA) and 21 European-American (EA) SLE patients, 5 AA controls, and 5 EA controls. CD4+ T-cells, CD8+ T-cells, monocytes and B cells were purified by flow sorting. Each cell subset from each subject was run on an Illumina HumanHT-12 V4 expression BeadChip array (n=208 arrays). Differentially expressed genes (DEGs) were determined by comparing cases and controls of the same ancestral background. Results: The overlap in DEG lists between different cell types from the same ancestral background was very modest (<1%). Typically between 5-10% of DEGs were shared when comparing the same cell type between different ancestral backgrounds (for ex. CD20 AA vs. CD20 EA). Quantitative measurement of global IFN-stimulated gene (ISG) expression revealed that AA subjects demonstrated more concordance across all studied cell types. Two subgroups of patients were identified based on the ISG expression profiles. One subgroup showed higher ISGs expression in all cell types, and the other subgroup had higherISG expression only in T and B lymphocytes but not in monocytes. The correlation of ISG expression with medication data revealed that only the B cells had lower ISG expression in patients taking immunosuppressants, while ISG expression in the other cell types did not differ based upon medication use. Conclusion: We find striking differences in gene expression between different immune cell subsets and between ancestral backgrounds in SLE patients. The IFN signature is diverse, with different transcripts represented in different cell populations, and signature-positive cell subsets differed in EA vs. AA patients. We also find that treatment with the immunosuppressive agents correlates with the down-regulation of B cell ISG expression, and this was not observed in other cell types.
2015-05-15 | GSE55447 | GEO
Project description:Anti-nuclear antibody (ANA) positivity is a principal feature of individuals with an autoimmune disease, yet up to one in five healthy individuals are ANA+ and most will never develop clinical autoimmunity. Here, we show that immune profiles in ANA+ healthy individuals are altered, and differ by race. A suppressive immune signature distinguished by reduced T cell numbers and altered gene expression of HLA class I, IFN-associated, and apoptosis pathways, characterized European American (EA) ANA+ healthy individuals. In contrast, African American (AA) ANA+ healthy individuals had more elements of activation with increased CD69 gene expression on T cells and heightened pro-inflammatory cytokines. Increases in STAT4, IFNGR2 and STAT1 T cell transcripts and decreases in TGFBR1 gene expression in monocytes correlated with T cell expansion and clinical SLE. Thus, a suppressive immune signature in EA ANA+ healthy individuals may avert clinical autoimmune disease, which is associated with activation of Type I and II IFN pathways and T cell expansion.
2020-11-27 | GSE138400 | GEO
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2018-06-06 | GSE95726 | GEO
Project description:Prostate cancer (PCa) tends to be more aggressive and lethal in African Americans (AA) compared to European Americans (EA). To further understand the thebiological risk factors associated with PCa disparities observed in AA and EA patients, we performed microRNA profiling using Agilent Human miRNA arrays to identify the differentially expressed microRNAs beween: 1) AA and EA PCa patients; 2) AA PCa vs. AA normal; and 3) EA PCa vs. EA normal. 54 prostate biopsy specimens (tumor and adjacent normal tissues) were collected from 14 African American and 13 European American prostate cancer patients. 54 RNA samples, purified from the collected biopy specimens using Qiagen miRNeasy kit, were process and applied to Agilent human miRNA arrays. Array data was normalized and analyzed using Agilent GeneSpring program.
2015-07-27 | E-GEOD-64318 | biostudies-arrayexpress
Project description:Prostate cancer (PCa) tends to be more aggressive and lethal in African Americans (AA) compared to European Americans (EA). To further understand the biological factors accounting for the PCa disparities observed in AA and EA patients, we performed gene profiling analysis using Affymetrix human exon 1.0 ST arrays to identify the differentially expressed genes in AA and EA patients. 35 prostate biopsy specimens (tumor and adjacent normal tissues) were collected from 20 African American and 15 European American prostate cancer patients. RNA samples, purified from the collected biopy specimens, were process and applied to Affymetrix human exon ST 1.0 arrays. Array data was normalized, batch corrected and analyzed (1-way ANOVA) using Partek Genomics Suite program.
2015-07-27 | E-GEOD-64331 | biostudies-arrayexpress
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