The LURN Study-What Have We "LURN"ed So Far?

Area of Science:

• Urology
• Neuroscience
• Psychiatry

Background:

• The Lower Urinary Tract Symptoms Research Network (LURN) was established by the NIDDK to holistically study lower urinary tract symptoms (LUTS), with a focus on urinary urgency.
• LURN has developed patient-reported outcome instruments, including the LURN Symptom Index (SI)-29 for clinical research and the LURN SI-10 for clinical practice, offering advantages over existing measures.
• The LURN SI-10 assesses a broader range of symptoms than the AUA-SI, including stress urinary incontinence (SUI), urge urinary incontinence (UUI), painful bladder filling, and post-void dribbling.

Purpose of the Study:

• To develop and validate patient-reported outcome instruments for measuring LUTS.
• To investigate the influence of non-urologic factors on LUTS.
• To explore the neurobiological underpinnings of urinary urgency and subgroup LUTS patients.

Main Methods:

• Development and validation of the LURN SI-29 and LURN SI-10 instruments.
• Cross-sectional studies examining associations between non-urologic factors (e.g., obesity, depression, childhood trauma) and LUTS.
• Neuroimaging studies (functional connectivity, white matter microstructure) in individuals with urinary urgency.
• Application of machine learning and clustering algorithms for LUTS patient subgrouping.
• Creation of a large biorepository with over 100,000 biospecimens linked to clinical data.

Main Results:

• The LURN SI-10 demonstrates advantages over the AUA-SI by including a wider array of lower urinary tract symptoms.
• Non-urologic factors such as central obesity, high BMI, depression, sleep disturbance, poor physical function, and childhood sexual trauma are associated with worsened LUTS, including UUI and SUI.
• Neuroimaging revealed increased functional connectivity in specific brain networks and microstructural disruption in white matter tracts in patients with urinary urgency compared to controls.
• Data-driven clustering identified five distinct male and five distinct female subgroups of LUTS patients.

Conclusions:

• LURN has significantly advanced the understanding and measurement of LUTS, particularly urinary urgency.
• Patient-reported outcomes and non-urologic factors play crucial roles in the experience and severity of LUTS.
• Neurobiological differences exist in individuals experiencing urinary urgency, suggesting central nervous system involvement.
• Novel subgrouping of LUTS patients using machine learning holds promise for personalized treatment approaches.