# Identification of biomarker signatures of subtypes of LUTS and their response to treatments using samples from LURN study

> **NIH NIH R01** · ARBOR RESEARCH COLLABORATIVE FOR  HEALTH · 2021 · $214,274

## Abstract

Project Summary
Lower urinary tract symptoms (LUTS) are costly to treat and significantly affect patients' quality of life. The
identification of subtypes of LUTS is critical to the understanding of LUTS pathophysiology and effective clinical
management and treatment of patients. Novel tools that can accurately identify the presence, types, and
severity of LUTS are needed, and biological markers are one such type of tool. Recent systematic review of
biomarkers of LUTS demonstrated the existence of important knowledge gap in published research: poor
reproducibility, unclear classification of LUTS patients, and lack of adjustments for clinical covariates. The
Symptoms of Lower Urinary Tract Dysfunction Research Network (LURN) was established with the goal of
identifying and explaining clinically relevant subtypes of LUTS patients. Over 75,000 biosamples were
collected and stored at NIDDK repository, including over 1200 baseline plasma samples for patients and
controls, as well as serum samples collected longitudinally for more than 800 patients. We propose to analyze
plasma and serum samples collected in LURN to identify biomarker signatures of subtypes of LUTS and their
response to treatments. We hypothesize that: (a) subtypes of LUTS will have different biomarker signatures of
differentially abundant proteins; (b) biomarker signatures will differ not only across the subtypes of LUTS but
also in comparison of improvers and non-improvers; (c) longitudinal changes in biomarker signatures in
response to treatment will be different in improvers and non-improvers.
Our study consists of three specific aims. Aim 1. To identify protein biomarker signatures contained within
plasma of subgroups of men and women with LUTS. We propose to analyze a panel of 1306 proteins using the
highly sensitive and reproducible SomaScan assay, which we successfully used in the Biomarker Pilot Project
in LURN I. This aim serves to produce comprehensive phenotyping of LUTS by identifying differentially
abundant proteins among patients with different subtypes of LUTS. We will build upon the results of LURN I
and use biomarker data to refine our previously identified symptom-based subtypes of men and women with
LUTS. This is important for better classification, diagnosis, and personalized treatment of patients with LUTS.
Aim 2. To identify biomarkers in baseline plasma samples associated with improvement in LUTS. We will use
the results of assay performed in Aim 1 to test for significant differences between the biomarker signatures of
“best improvers” and “worst non-improvers”. This is of practical importance since it will facilitate early selection
of patients who may benefit from more intensive or alternative treatments to LUTS. Aim 3. To quantify
longitudinal changes in biomarker signatures within serum of “best improvers” and “worst non-improvers”
among men and women with LUTS. Combined with the existing biological knowledge of metabolic and
signaling pathway using enrichme...

## Key facts

- **NIH application ID:** 10226295
- **Project number:** 5R01DK125251-02
- **Recipient organization:** ARBOR RESEARCH COLLABORATIVE FOR  HEALTH
- **Principal Investigator:** Victor P. Andreev
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $214,274
- **Award type:** 5
- **Project period:** 2020-08-01 → 2023-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10226295

## Citation

> US National Institutes of Health, RePORTER application 10226295, Identification of biomarker signatures of subtypes of LUTS and their response to treatments using samples from LURN study (5R01DK125251-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10226295. Licensed CC0.

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