949f94d7-cb8a-4291-9b11-211d751a5c9c - samples
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ABSTRACT:
PROVIDER: EGAD00001009268 | EGA |
REPOSITORIES: EGA
Similar Datasets
Project description:Background: Many circulating proteins are associated with risk of ESKD but their source and the biological pathways/disease processes they represent are unclear. Methods: Using OLINK proteomics platform, concentrations of 455 proteins were measured in plasma specimens obtained at baseline from 399 individuals with diabetes. Results: Elevated concentrations of 46 circulating proteins were associated (p <10-5) with development of ESKD (n=149) during 7-15 years of follow-up. Twenty of these proteins enriched apoptosis/TNF receptors signaling pathways. A subset (5-7), summarized as an apoptosis score, together with clinical variables accurately predicted risk of ESKD. Expression of genes encoding the 46 proteins in peripheral white blood cells showed no difference between cells from individuals who did or did not develop ESKD. In contrast, plasma concentration of many of the 46 proteins differed by this outcome. In snRNA-seq analysis of kidney biopsies, the majority of genes encoding for the 20 apoptosis/TNF receptors proteins were overexpressed in injured versus healthy proximal tubule cells. Expression of these 20 genes also correlated with the overall index of apoptosis in these cells. Conclusion: Elevated levels of circulating proteins flagging apoptotic processes/TNF receptors signaling pathways, and likely originating from injured/apoptotic proximal tubular cells, preceded the development of ESKD.
2024-10-21 | GSE271708 | GEO
Project description:Proteomics data was measured by using the Olink Explore 1536 panel from baseline plasma sample. The project is also supported by Themistocles L Assimes (Stanford University tassimes@stanford.edu) and Fahim Abbasi (Stanford University, fahim@stanford.edu).
2025-03-31 | PAD000001 | Pride
Project description:Plasma proteome is the ultimate target for the biomarker discovery. It stores an endless amount of information on the pathophysiological status of a living organism, which however is still difficult to comprehensively access. The high structural complexity of the plasma proteome can be addressed by using a system-wide and unbiased tool such as mass spectrometry (LC-MS/MS) or highly sensitive targeted immunoassays as Olink Proximity Extension Assays. We have tested the performance of LC-MS/MS in data –dependent and -independent acquisition modes and Olink PEA to measure circulating plasma proteins in 173 human plasma samples from a southern Germany population-cohort. More than 300 proteins were measured by both LC-MS/MS approaches, mainly including high abundance functional plasma proteins. By using the Olink PEA technology we measured 728 plasma proteins, covering a broad dynamic range with high sensitivity down to pg/ml levels. We found 35 overlapping proteins in all three analytical platforms, predominantly secreted and highly abundant in plasma. The complementarity of the platforms was assessed by veryfing the reproducibility of data distributions, statistical correlation of measurements and gender-based differential expression analysis. Our work highlights the limitations and the advantages of both targeted and untargeted approaches and prove their complementarity. We demostrated that by combining the results of the three platforms we gain in depth proteome coverage as well as biological insights.
2022-03-10 | PXD020261 | Pride
Project description:Matrix of normalized values from Olink assay performed on baseline BM Plasma. The Olink Immuno-Oncology multiplex proteomic Panel included 92 proteins associated with human inflammatory conditions. Data is analyzed using real-time PCR analysis software via the Ct method and Normalized Protein Expression (NPX) manager. Data were normalized using internal controls in every single sample, inter-plate controls, negative controls and a correction factor and expressed as Log2 scale, which was proportional to the protein concentration. One NPX difference equals the doubling of the protein concentration.
| EGAD00001011147 | EGA
Project description:The dataset consists of longitudinal plasma proteomic data was generated using the Olink proteomics platform in plasma from transgender individuals receiving feminizing gender-affirming hormone therapy (GAHT). There were two treatment arms in the clinical trial that received different anti-androgens to inhibit testosterone. This included a cyproterone acetate ("CPA") group (n=20) and a spironolactone ("SPIRO") group (n=20). Proteomics was measured in plasma at baseline and 6 months following feminizing GAHT. Additionally data in a cross-sectional pregnancy cohort at first and third trimester, as well as a cis female and cis male control were generated.
2025-09-17 | PAD000016 | Pride
Project description:The miR-17-92 microRNA cluster is often activated in cancer cells, but the identity of its targets remains largely elusive. Here we examined the effects of activation of the entire miR-17-92 cluster on global protein expression in neuroblastoma cells. In this dataset we deposit global mRNA expression data obtained form primary neuroblastoma tumour cells. This data was used to demonstrate negative correlation between TGFB target gene expression and expression of the miR-17-92 cluster.
2010-12-01 | GSE21713 | GEO
Project description:Objectives Juvenile dermatomyositis (JDM) is a heterogeneous autoimmune condition needing targeted treatment approaches and improved understanding of molecular mechanisms driving clinical phenotypes. We utilised exploratory proteomics from a longitudinal North American cohort of patients with new-onset JDM to identify biological pathways at disease onset and follow-up, tissue-specific disease activity, and myositis-specific autoantibody (MSA) status. Methods We measured 3072 plasma proteins (Olink panel) in 56 patients with JDM within 12 weeks of starting treatment (from the Childhood Arthritis and Rheumatology Research Alliance Registry and 3 additional sites) and 8 paediatric controls. Twenty-four patients with JDM who had 6-month follow-up samples were assessed. We identified differentially expressed proteins (DEPs) between groups by fitting linear mixed effects models and associated DEPs with validated disease activity measures. We assessed for cell/tissue specificity using the Human Protein Atlas and JDM muscle single nuclei and skin single-cell transcriptomic datasets. Differences within MSA subgroups were also analysed. Results We uncovered persistent dysregulation of innate immune activation, cell death, and redox signalling at 6 months despite multidrug immunosuppression. By leveraging tissue and cell-specific proteomes, we identified overrepresentation of circulating endothelial proteins associated with disease activity and verified endothelial cell marker expression in JDM muscle and skin. We discovered pathways associated with MSA subtypes that reflect JDM phenotypes. NXP2+ JDM-associated proteins reflected angiogenesis and extracellular matrix remodelling and were expressed in endothelial cells and fibroblasts. MDA5+ JDM was associated with circulating type III interferon and surfactant proteins. Conclusions These proteomic findings will inform future biomarker and treatment development considering the unique tissue- and autoantibody-associated inflammation in JDM.
2025-09-22 | GSE308711 | GEO
Project description:metabolite levels measured by Brainshake Metabolomics/Nightingale Health metabolic platform (log2)
| EGAD00010002150 | EGA
Project description:The miR-17-92 microRNA cluster is often activated in cancer cells, but the identity of its targets remains largely elusive. Here we examined the effects of activation of the entire miR-17-92 cluster on global protein expression in neuroblastoma cells. In this dataset we deposit global mRNA expression data obtained form primary neuroblastoma tumour cells. This data was used to demonstrate negative correlation between TGFB target gene expression and expression of the miR-17-92 cluster. Expression of different TGFB target genes was correlated to miR-17-92 expression using Spearman's Rank statistics in 40 tumours. A correlation heatmap was calculated to visualize the inverse relation between miR-17-92 expression and TGFB target gene expression.
2010-12-01 | E-GEOD-21713 | biostudies-arrayexpress
Project description:The dataset comprises of circulating miRNAs in human subjects with various types of liver impairments. In our study, we analyzed a total 48 serum samples from a group of 42 subjects that included subjects with accidental acetaminophen overdose (APAP), hepatitis B infection (HBV), liver cirrhosis (LC) and type 2 diabetes mellitus (T2DM) subjects with alanine amino transference (ALT) elevation. As a control 16 sex and age matched healthy controls from subjects with no evidence of liver disease were analyzed. The miRNA profiles were measured using next-generation sequencing platform.
2017-06-09 | GSE90028 | GEO