The objectives of this proposal are to: (1) recruit subjects with lower urinary tract disorders (LUTDs) to validate the new patient-reported outcome (PRO) tools currently being developed by NIDDK LURN Research Network, and (2) use innovative technologies to extensively phenotype a targeted population to expand our understanding of the pathophysiology of LUTD. We have assembled a multidisciplinary team of investigators with recognized expertise in male and female LUTDs, urologic phenotyping research, bioinformatics, wireless technologies, functional MRI, and structural neuroimaging.
In Aim 1, we proposed a systematic, data-driven, targeted approach to recruit subjects with LUTDs to validate the new LURN PRO instruments.
In Aim 2, we will enroll subjects with overactive bladder (OAB), systematically collect their phenotype, symptom data and biospecimens using existing bioinformatics pipeline and wireless technologies at Washington University, and prospectively follow them up for 12 months to identify predictors of OAB progression or regression.
In Aim 3, we will use innovative neuroimaging techniques to phenotype OAB patients with and without incontinence.

Public Health Relevance

The objectives of this proposal are to: (1) recruit subjects with lower urinary tract disorders (LUTDs) to validate the new patient-reported outcome (PRO) tools currently being developed by NIDDK LURN Research Network, and (2) use innovative technologies to extensively phenotype a targeted population to expand our understanding of the pathophysiology of overactive bladder (OAB).

Agency
National Institute of Health (NIH)
Institute
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
Type
Research Project--Cooperative Agreements (U01)
Project #
5U01DK100017-03
Application #
8877509
Study Section
Special Emphasis Panel (ZDK1)
Program Officer
Kirkali, Ziya
Project Start
2013-07-15
Project End
2016-05-31
Budget Start
2015-06-01
Budget End
2016-05-31
Support Year
3
Fiscal Year
2015
Total Cost
Indirect Cost
Name
Washington University
Department
Surgery
Type
Schools of Medicine
DUNS #
068552207
City
Saint Louis
State
MO
Country
United States
Zip Code
63130
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Andreev, Victor P; Liu, Gang; Yang, Claire C et al. (2018) Symptom Based Clustering of Women in the LURN Observational Cohort Study. J Urol 200:1323-1331
Cameron, Anne P; Lewicky-Gaupp, Christina; Smith, Abigail R et al. (2018) Baseline Lower Urinary Tract Symptoms in Patients Enrolled in LURN: A Prospective, Observational Cohort Study. J Urol 199:1023-1031
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