Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

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Tissue Transcriptome Driven Identification of Epidermal Growth Factor as a Chronic Kidney Disease Biomarker

ABSTRACT: We identified EGF as the top candidates predicting kidney function through an intrarenal transcriptome-driven approach, and demonstrated it is an independent risk predictor of CKD progression and can significantly improve prediction of renal outcome by established clinical parameters in diverse populations with CKD from a wide spectrum of causes and stages Chronic Kidney Disease, Lupus nephritis, Focal and Segmental Glomerulosclerosis, Nephropathies, Membranous Glomerulonephritis. This dataset is part of the TransQST collection.

ORGANISM(S): Homo sapiens

SUBMITTER: Viji Nair 

PROVIDER: E-GEOD-69438 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Tissue transcriptome-driven identification of epidermal growth factor as a chronic kidney disease biomarker.

Ju Wenjun W   Nair Viji V   Smith Shahaan S   Zhu Li L   Shedden Kerby K   Song Peter X K PXK   Mariani Laura H LH   Eichinger Felix H FH   Berthier Celine C CC   Randolph Ann A   Lai Jennifer Yi-Chun JY   Zhou Yan Y   Hawkins Jennifer J JJ   Bitzer Markus M   Sampson Matthew G MG   Thier Martina M   Solier Corinne C   Duran-Pacheco Gonzalo C GC   Duchateau-Nguyen Guillemette G   Essioux Laurent L   Schott Brigitte B   Formentini Ivan I   Magnone Maria C MC   Bobadilla Maria M   Cohen Clemens D CD   Bagnasco Serena M SM   Barisoni Laura L   Lv Jicheng J   Zhang Hong H   Wang Hai-Yan HY   Brosius Frank C FC   Gadegbeku Crystal A CA   Kretzler Matthias M  

Science translational medicine 20151201 316

Chronic kidney disease (CKD) affects 8 to 16% people worldwide, with an increasing incidence and prevalence of end-stage kidney disease (ESKD). The effective management of CKD is confounded by the inability to identify patients at high risk of progression while in early stages of CKD. To address this challenge, a renal biopsy transcriptome-driven approach was applied to develop noninvasive prognostic biomarkers for CKD progression. Expression of intrarenal transcripts was correlated with the bas  ...[more]

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