Proof-of-Concept Workflow for Establishing Reference Intervals of Human Urine Proteome for Monitoring Physiological and Pathological Changes

• Main Authors: Wenchuan Leng, Xiaotian Ni, Changqing Sun, Tianyuan Lu, Anna Malovannaya, Sung Yun Jung, Yin Huang, Yang Qiu, Guannan Sun, Matthew V. Holt, Chen Ding, Wei Sun, Xuebo Men, Tieliu Shi, Weimin Zhu, Yi Wang, Fuchu He, Bei Zhen, Guangshun Wang, Jun Qin
• Format: Article
• Language: English
• Published: Elsevier 2017-04-01
• Series: EBioMedicine
• Subjects: Reference intervals; Urine proteome; Cancer; Biomarker; Mass spectrometry
• Online Access: http://www.sciencedirect.com/science/article/pii/S235239641730124X

Urine as a true non-invasive sampling source holds great potential for biomarker discovery. While approximately 2000 proteins can be detected by mass spectrometry in urine from healthy people, the amount of these proteins vary considerably. A systematic evaluation of a large number of samples is needed to determine the range of the variations. Current biomarker studies often measure limited number of urine samples in the discovery phase, which makes it difficult to determine whether proteins differentially expressed between control and disease groups represent actual difference, or are just physiological variations among the individuals, leads to failures in the validation phase with the increased sample numbers. Here, we report a streamlined workflow with capacity of measuring 8 urine proteomes per day at the coverage of >1500 proteins. With this workflow, we evaluated variations in 497 urine proteomes from 167 healthy donors, establishing reference intervals (RIs) that covered urine protein variations. We demonstrated that RIs could be used to monitor physiological changes by detecting transient outlier proteins. Furthermore, we provided a RIs-based algorithm for biomarker discovery and validation to screen for diseases such as cancer. This study provided a proof-of-principle workflow for the use of urine proteome for health monitoring and disease screening.