The goal of the MAPP Research Network is to provide new insights into underlying etiology, natural history, and risk factors of UCPPS in order to provide a translational foundation to facilitate future clinical intervention efforts and improv clinical management of the syndromes. The UCLA MAPP-II proposal builds on the significant insights gained from MAPP-I studies into symptom patterns, UCPPS subtypes and various biomarkers, including brain signatures. In addition to be continued analysis of data sets generated in MAPP-I, it aims to identify factors associated with and predictive of symptom change, in both UCPPS subjects and in a rodent model. The UCLA proposal addresses these goals in four specific aims, all of which, if funded, are expected to be addressed collaboratively in transMAPP studies:
Aim 1. To conduct a symptom pattern study across the MAPP Research Network which will form the backbone for Aims 2 and 3.
Aim 2. To determine functional and structural brain correlates of patient subgroups, symptom fluctuations, and natural history.
Aim 3. To develop and apply enhanced functional assessments for UCPPS, including assessment of endogenous pain modulation systems.
Aim 4. To evaluate central mechanisms underlying symptom fluctuations, including stress mechanisms and related molecular brain changes in a rodent model of UCPPS. It is expected that the proposed studies will provide an unprecedented wealth of data, which will facilitate major breakthroughs in our understanding of UCPPS pathophysiology and identification of novel treatment approaches.
This project as part of the MAPP Research Network will provide new insights into causes progression, and risk factors for Urological Chronic Pelvic Pain. The proposed studies expand on the insights gained from successful initial MAPP funding cycle and will address symptom patterns, patient subtypes and various biomarkers, including brain signatures in addition to identification of factors associated with and predictive of symptom change, The studies will provide an unprecedented wealth of data, which will allow for a breakthrough in our understanding of the pathophysiology and identification of novel treatment approaches for these disorders.
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