Phenotyping Men With Lower Urinary Tract Symptoms: Results From the Symptoms of Lower Urinary Tract Dysfunction Research Network

Abstract

Aims: Men with lower urinary tract symptoms (LUTS) represent a heterogeneous group, and treatment decisions are often based on severity of symptoms and physical examination findings. Identification of clinically meaningful subtypes could allow for more personalized care. This study advances phenotyping efforts from the Symptoms of Lower Urinary Tract Dysfunction Research Network (LURN) by adding data domains to previous phenotyping using urologic symptoms alone.

Methods: Two-hundred-seventeen LUTS, demographics, medical history, and physical examination datapoints from the LURN Observational Cohort study were assessed among 519 men with at least one bothersome LUTS, using weighted Tanimoto indices, semi-supervised learning, and resampling-based consensus clustering to identify distinct clusters of participants. Differentially abundant serum proteins of 220 men were compared across identified clusters.

Results: Five refined male clusters (RM1-RM5) were identified. Two clusters reported mild LUTS (RM1: n = 66; RM2: n = 84). RM1 was older than RM2 (70.3 vs. 56.1 years), had more comorbidities (functional comorbidity index 2.4 vs. 1.5) and erectile dysfunction. Two benign prostatic hyperplasia-like symptom clusters were identified (RM3: n = 64; RM4: n = 188). RM3 has the largest postvoid residual volume (275 mL); RM4 reported more urinary frequency, urgency, urinary incontinence, pain, and psychosocial symptoms. RM5 (n = 119) was characterized by urgency urinary incontinence, frequency, and significant comorbidities and psychosocial symptoms. Fifteen (RM2) to 87 (RM1) differentially abundant proteins were identified within each cluster. Minimal overlap was observed between affected proteins and pathways across clusters.

Conclusions: Protein signatures across newly discovered subgroups suggest identified subtypes are biochemically distinct. Findings should be validated, but may represent populations with separate pathophysiology and therapeutic needs.

Clinical trial registration: The LURN ClinicalTrials.gov Identifier is NCT02485808.

Keywords: lower urinary tract symptoms; pathophysiology; phenotypes; postvoid residual urine volume; psychosocial.

Figure 1

Radar plots of identified clusters. The most statistically significant different across clusters variables were identified and built into a radar plot to give a visual representation of the distinct symptom signatures for each cluster. Variables were normalized to the mean (SD) of the full cohort of male participants. The mean of the full cohort is represented as the black circle on the radar plots. Values outside of the circle indicate higher levels of symptoms than the full cohort, while values inside the circle indicate lower levels of symptoms than the full cohort. All values have been scaled so higher values represent worse or more severe symptoms.

Figure 2

Frequency of treatments received by patients within each cluster, across their 12‐month follow‐up, stratified by the proportion of patients within each treatment who were classified as having improved LUTS at 12 months, no change in LUTS at 12 months, and worse LUTS at 12 months. Treatments reported by less than five patients within a cluster were shaded in gray.

Figure 3

Volcano plots presenting statistical significance (p‐value) versus the magnitude of difference between cases and controls (mean logarithm of protein abundance level of cases, minus the mean logarithm of protein abundance level of controls) for each protein. Reference line is set at p‐value = 0.05. (A) Volcano plots for all cases compared with all controls. (B) Volcano plots for RM1 compared with all controls. (C) Volcano plots for RM2 compared with all controls. (D) Volcano plots for RM3 compared with all controls. (E) Volcano plots for RM4 compared with all controls. (F) Volcano plots for RM5 compared with all controls.

Figure 4

Affected pathways and affected gene ontology processes highlighted by differentially abundant proteins, as defined in a MetaCore enrichment analysis.