Identification of human glucocorticoid response markers using integrated multi-omic analysis
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PROVIDER: PRJNA625259 | ENA |
REPOSITORIES: ENA
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Project description:Identification of human glucocorticoid response markers using integrated multi-omic analysis [Adipose Tissue]
| PRJNA625266 | ENA
Project description:A multi-omic approach in a clinical experimental study identified circulating biomarkers reflecting glucocorticoid exposure. Background: Endogenous glucocorticoids (GC) are mechanistically linked to common diseases and are important as drugs in the treatment of many disorders. There is no marker that can measure and quantify GC action. Our aim was to identify circulating biomarkers of GC action using a clinical experimental study. Methods: In a randomized, crossover, single-blind trial, subjects with primary adrenal insufficiency received intravenous hydrocortisone infusion in a circadian pattern (physiological GC exposure) or isotonic saline (GC withdrawal) over 22 hours. Samples were collected at 7 AM (end of infusion). Integrated multi-omic analysis was used because of the complexity in GC action and the low number of subjects. The transcriptome in peripheral blood mononuclear cells (PBMCs) and adipose tissue, plasma miRNAomic, and serum metabolomics were compared between the interventions. Replication of the plasma miRNA findings was performed in three independent studies. Results: During GC withdrawal, overnight urinary cortisol and cortisone excretion were undetectable. Correlation and hypernetwork analyses identified a transcriptomic profile derived from PBMCs and adipose tissue predictive of GC exposure, and a multi-omic cluster predictive of GC exposure. From the circulating ‘omic data, decreased expression of plasma miR-122-5p was associated with increased GC exposure. This finding was reproduced in three independent studies. Conclusion: We developed a human experimental model for physiological GC exposure and withdrawal. The integrated multi-omic data identified circulating miRNAs and metabolites associated with GC-responsive genes. In independent studies, miR-122-5p was shown to be associated with GC exposure. Background: Endogenous glucocorticoids (GC) are mechanistically linked to common diseases and are important as drugs in the treatment of many disorders. There is no marker that can measure and quantify GC action. Our aim was to identify circulating biomarkers of GC action using a clinical experimental study.
2021-04-02 | GSE148640 | GEO
Project description:A multi-omic approach in a clinical experimental study identified circulating biomarkers reflecting glucocorticoid exposure. Background: Endogenous glucocorticoids (GC) are mechanistically linked to common diseases and are important as drugs in the treatment of many disorders. There is no marker that can measure and quantify GC action. Our aim was to identify circulating biomarkers of GC action using a clinical experimental study. Methods: In a randomized, crossover, single-blind trial, subjects with primary adrenal insufficiency received intravenous hydrocortisone infusion in a circadian pattern (physiological GC exposure) or isotonic saline (GC withdrawal) over 22 hours. Samples were collected at 7 AM (end of infusion). Integrated multi-omic analysis was used because of the complexity in GC action and the low number of subjects. The transcriptome in peripheral blood mononuclear cells (PBMCs) and adipose tissue, plasma miRNAomic, and serum metabolomics were compared between the interventions. Replication of the plasma miRNA findings was performed in three independent studies. Results: During GC withdrawal, overnight urinary cortisol and cortisone excretion were undetectable. Correlation and hypernetwork analyses identified a transcriptomic profile derived from PBMCs and adipose tissue predictive of GC exposure, and a multi-omic cluster predictive of GC exposure. From the circulating ‘omic data, decreased expression of plasma miR-122-5p was associated with increased GC exposure. This finding was reproduced in three independent studies. Conclusion: We developed a human experimental model for physiological GC exposure and withdrawal. The integrated multi-omic data identified circulating miRNAs and metabolites associated with GC-responsive genes. In independent studies, miR-122-5p was shown to be associated with GC exposure. Background: Endogenous glucocorticoids (GC) are mechanistically linked to common diseases and are important as drugs in the treatment of many disorders. There is no marker that can measure and quantify GC action. Our aim was to identify circulating biomarkers of GC action using a clinical experimental study.
2021-04-02 | GSE148639 | GEO
Project description:Identification of human glucocorticoid response markers using integrated multi-omic analysis [Peripheral blood mononuclear cells]
| PRJNA625267 | ENA
Project description:This SuperSeries is composed of the SubSeries listed below.
2021-04-02 | GSE148642 | GEO
Project description:The combination of multi-omic techniques, e.g. genomics, transcriptomics, proteomics, metabolomics and epigenomics has revolutionised studies in medical research. These are employed to support biomarker discovery, better understand molecular pathways and identify novel drug targets. Despite concerted efforts in integrating omic datasets, there is an absence for the integration of all four biomolecules in a single extraction protocol. Here, we demonstrate for the first time a novel, minimally destructive integrated protocol for the simultaneous extraction of artificially degraded DNA, proteins, lipids and metabolites from pig brain samples. We used an MTBE-based approach to separate lipids and metabolites, followed by subsequent isolation of DNA and proteins. We have validated this protocol against standalone extraction protocols and show comparable or higher yield of all four biomolecules. This integrated protocol is key towards facilitating preservation of irreplaceable samples while promoting downstream analyses and successful data integration by removing bias from univariate dataset noise and varied distribution characteristics. Keywords: deg
2024-08-09 | PXD047606 | Pride
Project description:Integrated Multi-omic Analysis of Esthesioneuroblastomas Identifies Two Subgroups Linked to Cell Ontogeny
| PRJNA487796 | ENA
Project description:A novel integrated extraction protocol for multi-omic studies in heavily degraded samples
| PRJEB61253 | ENA
Project description:BackgroundGlucocorticoids are among the most commonly prescribed drugs, but there is no biomarker that can quantify their action. The aim of the study was to identify and validate circulating biomarkers of glucocorticoid action.MethodsIn a randomized, crossover, single-blind, discovery study, 10 subjects with primary adrenal insufficiency (and no other endocrinopathies) were admitted at the in-patient clinic and studied during physiological glucocorticoid exposure and withdrawal. A randomization plan before the first intervention was used. Besides mild physical and/or mental fatigue and salt craving, no serious adverse events were observed. The transcriptome in peripheral blood mononuclear cells and adipose tissue, plasma miRNAomic, and serum metabolomics were compared between the interventions using integrated multi-omic analysis.ResultsWe identified a transcriptomic profile derived from two tissues and a multi-omic cluster, both predictive of glucocorticoid exposure. A microRNA (miR-122-5p) that was correlated with genes and metabolites regulated by glucocorticoid exposure was identified (p=0.009) and replicated in independent studies with varying glucocorticoid exposure (0.01 ≤ p≤0.05).ConclusionsWe have generated results that construct the basis for successful discovery of biomarker(s) to measure effects of glucocorticoids, allowing strategies to individualize and optimize glucocorticoid therapy, and shedding light on disease etiology related to unphysiological glucocorticoid exposure, such as in cardiovascular disease and obesity.FundingThe Swedish Research Council (Grant 2015-02561 and 2019-01112); The Swedish federal government under the LUA/ALF agreement (Grant ALFGBG-719531); The Swedish Endocrinology Association; The Gothenburg Medical Society; Wellcome Trust; The Medical Research Council, UK; The Chief Scientist Office, UK; The Eva Madura's Foundation; The Research Foundation of Copenhagen University Hospital; and The Danish Rheumatism Association.Clinical trial numberNCT02152553.
| S-EPMC8024021 | biostudies-literature