Comprehensive Analysis of Individual Variation in the Urinary Proteome Revealed Significant Gender Differences[S]

• Published in: Molecular & cellular proteomics 2019-06, Vol.18 (6), p.1110-1122
• Main Authors: Shao, Chen, Zhao, Mindi, Chen, Xizhao, Sun, Haidan, Yang, Yehong, Xiao, Xiaoping, Guo, Zhengguang, Liu, Xiaoyan, Lv, Yang, Chen, Xiangmei, Sun, Wei, Wu, Di, Gao, Youhe
• Format: Article
• Language: English
• Subjects: Adult; Aged; Biofluids; Female; Humans; Label-free quantification; Male; Mass Spectrometry; Middle Aged; Protein Identification; Protein Interaction Maps; Proteinuria - urine; Proteome - metabolism; Reference Standards; Sex Characteristics; Staining and Labeling; Urine analysis; Young Adult
• ISSN: 1535-9476; 1535-9484
• DOI: 10.1074/mcp.RA119.001343

Urinary proteomes from 49 healthy adult donors were comprehensively analyzed. Besides age, gender was found to be a crucial factor contributing to individual variation. Proteins that were increased in the male urine samples include major prostate-secreted proteins, and those that were increased in the female urine samples are enriched in immunological pathways. Reference intervals of each urinary protein were estimated, providing the baseline for the discovery of abnormalities. [Display omitted] Highlights •Comprehensive analysis of inter-individual variation of normal urinary proteome.•Significant gender differences were observed.•Proteins increased in female urine are enriched in immunological pathways.•Estimated reference intervals of proteins as the baseline for biomarker discovery. Disease biomarkers are the measurable changes associated with a pathophysiological process. Without homeostatic control, urine accumulates systematic changes in the body. Thus, urine is an attractive biological material for the discovery of disease biomarkers. One of the major bottlenecks in urinary biomarker discovery is that the concentration and composition of urinary proteins are influenced by many physiological factors. To elucidate the individual variation and related factors influencing the urinary proteome, we comprehensively analyzed the urine samples from healthy adult donors (aged 20–69 years). Co-expression network analysis revealed protein clusters representing the metabolic status, gender-related differences and age-related differences in urinary proteins. In particular, we demonstrated that gender is a crucial factor contributing to individual variation. Proteins that were increased in the male urine samples include prostate-secreted proteins and TIMP1, a protein whose abundance alters under various cancers and renal diseases; however, the proteins that were increased in the female urine samples have known functions in the immune system. Nine gender-related proteins were validated on 85 independent samples by multiple reaction monitoring. Five of these proteins were further used to build a model that could accurately distinguish male and female urine samples with an area under curve value of 0.94. Based on the above results, we strongly suggest that future biomarker investigations should consider gender as a crucial factor in experimental design and data analysis. Finally, reference intervals of each urinary protein were estimated, providing a baseline for th