University of Michigan BACPAC Mechanistic Research Center

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Project Summary / Abstract Individual and societal burdens from chronic low back pain (cLBP) are significant and associated with long term functional impairment, disability, and poor quality of life. There are many efficacious treatments in cLBP but the factors that predict treatment effectiveness in an individual are still not well understood. Treatments for chronic pain include several pharmacologic (e.g., duloxetine and gabapentin) and non-pharmacologic treatments such as physical therapy, acupressure, mindfulness-based interventions, and web-based self- management programs. There is an urgent need for a greater understanding of pain mechanisms and predictors of response to different therapies with a goal of matching patients based on phenotypes to therapies to which they are most likely to respond. The parent award, a HEAL Initiative award (U19 AR076734), uses a precision medicine approach to identify what treatments are likely to work in different patient endotypes. The proposed supplement will allow me, a clinical rheumatologist, to learn these skills through assessments of acupressure and the web-based self-management program on patient-reported pain in cLBP. Clinically available data (such as patient-reported outcomes) as well as state-of-the-art phenotyping methods such as functional MRI (fMRI) and Quantitative Sensory Testing (QST), will be available to mechanistically explore the proposed neurobiological effects of these treatments. This knowledge will be invaluable in my future research on evaluation of pain mechanisms and responsiveness to treatment based on phenotypes of individuals with rheumatic disease.