The goal of this project is to bring together an interdisciplinary team of researchers to test the hypothesis that urine metabolic and proteomic biomarkers can predict the response to therapy for human lower urinary tract symptoms (LUTS) and identify the most appropriate animal models for mechanistic studies of LUTS. Current data are most consistent with the idea that human LUTS has multiple etiologies and multiple manifestafions. Plausible etiologies for LUTS include, but are not limited to, benign prostatic hyperplasia, inflammafion in the prostate and bladder neck, changes in smooth muscle tone in the prostate and bladder neck, and neurologic changes in the lower urinary tract. Ideally, treatment for LUTS would take into account the different manifestations of disease to achieve more rapid and effecfive therapy for individual patients. Barriers to achieving this goal include the lack of adequate biomarkers to stratify the different manifestations of human LUTS and a lack of clarity regarding the most appropriate animal models for mechanistic studies ofthe different manifestations of LUTS. To address these barriers to progress in the field, this project will conduct experiments organized into three Specific Aims.
Aim 1 will identify urine biomarkers of human LUTS using proteomic and metabolomic approaches.
Aim 2 will identify changes in biomarker expression that correlate with effective treatment of LUTS symptoms.
Aim 3 will conduct interspecies comparative studies to identify biomarker similarities among human LUTS patients, mice with bacterial prostatitis, and mice with hormoneinduced urinary obstrucfion. It is anticipated that completion of these Aims will identify biomarkers that can stratify LUTS into different disease sub-types, predict response to therapy, and identify animal models that are most appropriate for investigating the underlying mechanisms associated with different sub-types of LUTS. Completion of these Aims will also create a base of knowledge needed to support a more comprehensive interdisciplinary project to determine the underiying cause(s) of LUTS using human patient data and data from animal models with different manifestations of urinary tract disease.

Public Health Relevance

; This project relevant for public health because it vvill identify new biomarkers that stratify patients with lower urinary tract symptoms (LUTS) into distinct groups, and biomarkers for LUTS that are predictive for treatment efficacy. This information will facilitate future efforts to achieve better patient outcomes through individualized treatment choices. This project will also identify animal models that are best suited to particular LUTS subtypes which will facilitate future mechanism-based investigation of LUTS in animal models.

National Institute of Health (NIH)
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
Exploratory Grants (P20)
Project #
Application #
Study Section
Special Emphasis Panel (ZDK1-GRB-6 (O3))
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
University of Wisconsin Madison
United States
Zip Code
Hao, Ling; Wang, Jingxin; Page, David et al. (2018) Comparative Evaluation of MS-based Metabolomics Software and Its Application to Preclinical Alzheimer's Disease. Sci Rep 8:9291
Thomas, Samuel; Hao, Ling; Ricke, William A et al. (2016) Biomarker discovery in mass spectrometry-based urinary proteomics. Proteomics Clin Appl 10:358-70
Keil, Kimberly P; Abler, Lisa L; Altmann, Helene M et al. (2016) Influence of animal husbandry practices on void spot assay outcomes in C57BL/6J male mice. Neurourol Urodyn 35:192-8
Hao, Ling; Greer, Tyler; Page, David et al. (2016) In-Depth Characterization and Validation of Human Urine Metabolomes Reveal Novel Metabolic Signatures of Lower Urinary Tract Symptoms. Sci Rep 6:30869
Greer, Tyler; Hao, Ling; Nechyporenko, Anatoliy et al. (2015) Custom 4-Plex DiLeu Isobaric Labels Enable Relative Quantification of Urinary Proteins in Men with Lower Urinary Tract Symptoms (LUTS). PLoS One 10:e0135415
Hao, Ling; Zhong, Xuefei; Greer, Tyler et al. (2015) Relative quantification of amine-containing metabolites using isobaric N,N-dimethyl leucine (DiLeu) reagents via LC-ESI-MS/MS and CE-ESI-MS/MS. Analyst 140:467-75
Yang, Chenxi; Zhong, Xuefei; Li, Lingjun (2014) Recent advances in enrichment and separation strategies for mass spectrometry-based phosphoproteomics. Electrophoresis 35:3418-29