Expression data from Balb/c mice kidney samples
Ontology highlight
ABSTRACT:
ORGANISM(S): Mus musculus
PROVIDER: GSE12683 | GEO | 2009/12/01
SECONDARY ACCESSION(S): PRJNA112683
REPOSITORIES: GEO
Similar Datasets
Project description:Males are 50% more likely to develop end stage kidney failure compared to women. As a model of the human condition we analyzed gene expression changes in healthy and diseased mouse kidneys. Interestingly, the set of gender biased genes in healthy kidneys were different from those in diseased kidneys indicating not only baseline gene expression differences but also that the male and female kidney respond differently to disease condition. Keywords: Gender difference We used AffymetrixM430A2.0 microarrays to determine global gene expression differences in kidneys of 10-week old healthy Balb/c male and female mice. In order to identify gene expression differences under disease conditions, animals were injected with doxorubicin, a substance that is known to induce albuminuria and glomerulosclerosis in Balb/c mice as it is directly toxic to podocytes.
2010-03-03 | E-GEOD-12683 | biostudies-arrayexpress
Project description:Males are 50% more likely to develop end stage kidney failure compared to women. In this study we wanted to find out the molecular mechanism responsible for this increased risk. We collected kidney samples from patients with and without kidney disease and performed a comprehensive gene expression analysis in healthy and diseased male and female kidneys. Interestingly, the set of gender biased genes in healthy kidneys were different from those in diseased kidneys indicating not only baseline gene expression differences but also that the male and female kidney respond differently to disease condition. Our studies indicate that men and women with kidney problems might need to be treated differently. Keywords: Gender difference
2010-04-13 | GSE12682 | GEO
Project description:Males are 50% more likely to develop end stage kidney failure compared to women. In this study we wanted to find out the molecular mechanism responsible for this increased risk. We collected kidney samples from patients with and without kidney disease and performed a comprehensive gene expression analysis in healthy and diseased male and female kidneys. Interestingly, the set of gender biased genes in healthy kidneys were different from those in diseased kidneys indicating not only baseline gene expression differences but also that the male and female kidney respond differently to disease condition. Our studies indicate that men and women with kidney problems might need to be treated differently. Keywords: Gender difference We collected 42 kidney samples from healthy living transplant donors, nephrectomies and from diagnostic kidney biopsies. Preliminary studies did not show significant gene expression differences in control kidneys based on the collection method (i.e. living kidney biopsy vs. unaffected portion of tumor nephrectomy). We grouped the tissue samples based on the histological readings of the kidney biopsies. Samples with evidence of glomerular and tubulointerstitial fibrosis were assigned into the diseased group. Characteristics of the research participants indicate diverse ethnic and disease groups and mild (StageIII) CKD. The tissue was microdissected into glomerular and tubulointerstitial fractions and expression arrays were performed separately.
2010-04-13 | E-GEOD-12682 | biostudies-arrayexpress
Project description:Understanding kidney disease relies upon defining the complexity of cell types and states, their associated molecular profiles, and interactions within tissue neighborhoods. We applied multiple single-cell or -nucleus assays (>400,000 nuclei/cells) and spatial imaging technologies to a broad spectrum of healthy reference (45 donors) and diseased (48 patients) kidneys. This has provided a high resolution cellular atlas of 51 main cell types that include rare and novel cell populations. The multi-omic approach provides detailed transcriptomic profiles, epigenomic regulatory factors, and spatial localizations spanning the entire kidney. We further define 28 cellular states across nephron segments and interstitium that were altered in kidney injury, encompassing cycling, adaptive or maladaptive repair, transitioning and degenerative states. Molecular signatures permitted localization of these states within injury neighborhoods using spatial transcriptomics, while large-scale 3D imaging analysis (~1.2 million neighborhoods) provided corresponding linkages to active immune responses. These analyses defined biological pathways relevant to injury time-course and niches, including signatures underlying epithelial repair that predicted maladaptive states associated with a decline in kidney function. This integrated multimodal spatial cell atlas of healthy and diseased human kidneys represents the most comprehensive benchmark of cellular states, neighborhoods, outcome-associated signatures, and publicly available interactive visualizations.
2022-10-10 | GSE183277 | GEO
Project description:Understanding kidney disease relies upon defining the complexity of cell types and states, their associated molecular profiles, and interactions within tissue neighborhoods. We applied multiple single-cell or -nucleus assays (>400,000 nuclei/cells) and spatial imaging technologies to a broad spectrum of healthy reference (45 donors) and diseased (48 patients) kidneys. This has provided a high resolution cellular atlas of 51 main cell types that include rare and novel cell populations. The multi-omic approach provides detailed transcriptomic profiles, epigenomic regulatory factors, and spatial localizations spanning the entire kidney. We further define 28 cellular states across nephron segments and interstitium that were altered in kidney injury, encompassing cycling, adaptive or maladaptive repair, transitioning and degenerative states. Molecular signatures permitted localization of these states within injury neighborhoods using spatial transcriptomics, while large-scale 3D imaging analysis (~1.2 million neighborhoods) provided corresponding linkages to active immune responses. These analyses defined biological pathways relevant to injury time-course and niches, including signatures underlying epithelial repair that predicted maladaptive states associated with a decline in kidney function. This integrated multimodal spatial cell atlas of healthy and diseased human kidneys represents the most comprehensive benchmark of cellular states, neighborhoods, outcome-associated signatures, and publicly available interactive visualizations.
2022-10-10 | GSE183276 | GEO
Project description:Understanding kidney disease relies upon defining the complexity of cell types and states, their associated molecular profiles, and interactions within tissue neighborhoods. We applied multiple single-cell or -nucleus assays (>400,000 nuclei/cells) and spatial imaging technologies to a broad spectrum of healthy reference (45 donors) and diseased (48 patients) kidneys. This has provided a high resolution cellular atlas of 51 main cell types that include rare and novel cell populations. The multi-omic approach provides detailed transcriptomic profiles, epigenomic regulatory factors, and spatial localizations spanning the entire kidney. We further define 28 cellular states across nephron segments and interstitium that were altered in kidney injury, encompassing cycling, adaptive or maladaptive repair, transitioning and degenerative states. Molecular signatures permitted localization of these states within injury neighborhoods using spatial transcriptomics, while large-scale 3D imaging analysis (~1.2 million neighborhoods) provided corresponding linkages to active immune responses. These analyses defined biological pathways relevant to injury time-course and niches, including signatures underlying epithelial repair that predicted maladaptive states associated with a decline in kidney function. This integrated multimodal spatial cell atlas of healthy and diseased human kidneys represents the most comprehensive benchmark of cellular states, neighborhoods, outcome-associated signatures, and publicly available interactive visualizations.
2022-10-10 | GSE199711 | GEO
Project description:Understanding kidney disease relies upon defining the complexity of cell types and states, their associated molecular profiles, and interactions within tissue neighborhoods. We applied multiple single-cell or -nucleus assays (>400,000 nuclei/cells) and spatial imaging technologies to a broad spectrum of healthy reference (45 donors) and diseased (48 patients) kidneys. This has provided a high resolution cellular atlas of 51 main cell types that include rare and novel cell populations. The multi-omic approach provides detailed transcriptomic profiles, epigenomic regulatory factors, and spatial localizations spanning the entire kidney. We further define 28 cellular states across nephron segments and interstitium that were altered in kidney injury, encompassing cycling, adaptive or maladaptive repair, transitioning and degenerative states. Molecular signatures permitted localization of these states within injury neighborhoods using spatial transcriptomics, while large-scale 3D imaging analysis (~1.2 million neighborhoods) provided corresponding linkages to active immune responses. These analyses defined biological pathways relevant to injury time-course and niches, including signatures underlying epithelial repair that predicted maladaptive states associated with a decline in kidney function. This integrated multimodal spatial cell atlas of healthy and diseased human kidneys represents the most comprehensive benchmark of cellular states, neighborhoods, outcome-associated signatures, and publicly available interactive visualizations.
2022-10-10 | GSE183274 | GEO
Project description:Understanding kidney disease relies upon defining the complexity of cell types and states, their associated molecular profiles, and interactions within tissue neighborhoods. We applied multiple single-cell or -nucleus assays (>400,000 nuclei/cells) and spatial imaging technologies to a broad spectrum of healthy reference (45 donors) and diseased (48 patients) kidneys. This has provided a high resolution cellular atlas of 51 main cell types that include rare and novel cell populations. The multi-omic approach provides detailed transcriptomic profiles, epigenomic regulatory factors, and spatial localizations spanning the entire kidney. We further define 28 cellular states across nephron segments and interstitium that were altered in kidney injury, encompassing cycling, adaptive or maladaptive repair, transitioning and degenerative states. Molecular signatures permitted localization of these states within injury neighborhoods using spatial transcriptomics, while large-scale 3D imaging analysis (~1.2 million neighborhoods) provided corresponding linkages to active immune responses. These analyses defined biological pathways relevant to injury time-course and niches, including signatures underlying epithelial repair that predicted maladaptive states associated with a decline in kidney function. This integrated multimodal spatial cell atlas of healthy and diseased human kidneys represents the most comprehensive benchmark of cellular states, neighborhoods, outcome-associated signatures, and publicly available interactive visualizations.
2022-10-10 | GSE183273 | GEO
Project description:To explore genes and pathways that were differently regulated in the progression of diabetic nephrology in different gender mice, we performed RNA-seq of kidney from BTBRob/ob (diabetic nephrology) mice and wild type (WT) mice. We then performed gene expression profiling analysis using data obtained from RNA-seq of 2 different gender groups.
2023-09-08 | GSE229193 | GEO
Project description:To obtain an unbiased characterization of the resident and infiltrating immune cell populations of mouse kidneys in healthy and diseased states, we performed single cell RNA-seq of facs-sorted CD45+ immune cells and CD4+ T cells from naïve and injured kidneys, at selected time points.
2020-01-31 | E-MTAB-8002 | biostudies-arrayexpress