Proteomic signature associated with chronic kidney disease (CKD) progression identified by data-independent acquisition mass spectrometry.

ABSTRACT:

Background

Halting progression of chronic kidney disease (CKD) to established end stage kidney disease is a major goal of global health research. The mechanism of CKD progression involves pro-inflammatory, pro-fibrotic, and vascular pathways, but pathophysiological differentiation is currently lacking.

Methods

Plasma samples of 414 non-dialysis CKD patients, 170 fast progressors (with ∂ eGFR-3 ml/min/1.73 m²/year or worse) and 244 stable patients (∂ eGFR of - 0.5 to + 1 ml/min/1.73 m²/year) with a broad range of kidney disease aetiologies, were obtained and interrogated for proteomic signals with SWATH-MS. We applied a machine learning approach to feature selection of proteins quantifiable in at least 20% of the samples, using the Boruta algorithm. Biol

SUBMITTER: Ramirez Medina CR 

PROVIDER: S-EPMC10116780 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature