Comprehensive Analysis of the Human Urinary Peptidome Using Peptide Clustering Approach Reveals Age- and Gender-Specific Patterns.

BackgroundThe human urine peptidome reflects physiological and pathological states, making it a valuable resource for biomarker discovery. However, endogenous peptides often exist as cascades of truncated variants, complicating comparative analyses. To address this, we developed a "peptide cluster" approach, grouping overlapping peptides into representative clusters for robust statistical evaluation. MethodsUrine samples from 55 healthy volunteers (23 males, 32 females) were analyzed via LC-MS/MS. Identified peptides were assembled into clusters based on sequence overlap, with the longest peptide designated as the "precursor" and truncated variants as "truncated" ResultsWe identified 30,471 endogenous peptides, assembled into 13,163 peptide clusters--the largest urinary peptidome dataset to date. Gender-specific differences were observed in 26 clusters, while 57 clusters correlated significantly with age. Notably, male-enriched clusters included hepcidin-25 and progranulin-derived peptides, whereas female-enriched clusters were linked to immunoglobulin gamma-1. Age-associated clusters highlighted collagen degradation patterns, consistent with extracellular matrix remodeling. ConclusionOur peptide clustering approach facilitated a comprehensive characterization of the endogenous peptidome, capturing the diversity of naturally occurring truncated peptide forms. The resulting age- and sex-specific peptide clusters serve as a valuable reference framework for future investigations into disease-associated biomarkers.