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10.7554/eLife.68832 http://scihub22266oqcxt.onion/10.7554/eLife.68832 35037854!8763401!35037854     free     free     free Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Elife 2022 ; 11 (ä): ä Nephropedia Template TP {{tp|p=35037854|t=2022. A human-based multi-gene signature enables quantitative drug repurposing for metabolic disease |pdf=|usr=}}{{35037854}} gab.com Text A human-based multi-gene signature enables quantitative drug repurposing for metabolic disease JO: Elife http://www.kidney.de/pget.php?&tw=1&pmid=35037854 #FOAvip Insulin resistance (IR) contributes to the pathophysiology of diabetes, dementia, viral infection, and cardiovascular disease. Drug repurposing (DR) may identify treatments for IR; however, barriers include uncertainty whether in vitro transcriptomic assays yield quantitative pharmacological data, or how to optimise assay design to best reflect in vivo human disease. We developed a clinical-based human tissue IR signature by combining lifestyle-mediated treatment responses (>500 human adipose and muscle biopsies) with biomarkers of disease status (fasting IR from >1200 biopsies). The assay identified a chemically diverse set of >130 positively acting compounds, highly enriched in true positives, that targeted 73 proteins regulating IR pathways. Our multi-gene RNA assay score reflected the quantitative pharmacological properties of a set of epidermal growth factor receptor-related tyrosine kinase inhibitors, providing insight into drug target specificity; an observation supported by deep learning-based genome-wide predicted pharmacology. Several drugs identified are suitable for evaluation in patients, particularly those with either acute or severe chronic IR. Twit Text FOAVip A human-based multi-gene signature enables quantitative drug repurposing for metabolic disease ????Elife http://www.kidney.de/pget.php?&tw=1&pmid=35037854 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=35037854 #FOAvip English Wikipedia <ref>{{Cite pmid|35037854}}</ref> A human-based multi-gene signature enables quantitative drug repurposing for metabolic disease #MMPMID35037854 Timmons JA; Anighoro A; Brogan RJ; Stahl J; Wahlestedt C; Farquhar DG; Taylor-King J; Volmar CH; Kraus WE; Phillips SM Elife 2022[Jan]; 11 (ä): ä PMID35037854show ga Insulin resistance (IR) contributes to the pathophysiology of diabetes, dementia, viral infection, and cardiovascular disease. Drug repurposing (DR) may identify treatments for IR; however, barriers include uncertainty whether in vitro transcriptomic assays yield quantitative pharmacological data, or how to optimise assay design to best reflect in vivo human disease. We developed a clinical-based human tissue IR signature by combining lifestyle-mediated treatment responses (>500 human adipose and muscle biopsies) with biomarkers of disease status (fasting IR from >1200 biopsies). The assay identified a chemically diverse set of >130 positively acting compounds, highly enriched in true positives, that targeted 73 proteins regulating IR pathways. Our multi-gene RNA assay score reflected the quantitative pharmacological properties of a set of epidermal growth factor receptor-related tyrosine kinase inhibitors, providing insight into drug target specificity; an observation supported by deep learning-based genome-wide predicted pharmacology. Several drugs identified are suitable for evaluation in patients, particularly those with either acute or severe chronic IR. |*Drug Repositioning[MESH] |Adipose Tissue/metabolism[MESH] |Biomarkers/metabolism[MESH] |Humans[MESH] |Insulin Resistance[MESH] |Metabolic Diseases/*drug therapy/genetics[MESH] |Muscles/metabolism[MESH]A human-based multi-gene signature enables quantitative drug repurposi(epmc).pdf DeepDyve Pubget Overpricing