Urinary peptidomic liquid biopsy for non-invasive differential diagnosis of chronic kidney disease.

ABSTRACT:

Background and hypothesis

Specific urinary peptides hold information on disease pathophysiology, which, in combination with artificial intelligence, could enable non-invasive assessment of chronic kidney disease (CKD) aetiology. Existing approaches are generally specific for the diagnosis of single aetiologies. We present the development of models able to simultaneously distinguish and spatially visualize multiple CKD aetiologies.

Methods

The urinary peptide data of 1850 healthy control (HC) and CKD [diabetic kidney disease (DKD), immunoglobulin A nephropathy (IgAN) and vasculitis] participants were extracted from the Human Urinary Proteome Database. Uniform manifold approximation and projection (UMAP) coupled to a support vector machine algorithm was used to generate multi-

SUBMITTER: Mavrogeorgis E 

PROVIDER: S-EPMC10899775 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature