
About
Cynthia Renn, PhD, RN, FAAN is a Professor and Chair of the Pain and Translational Symptom Science department at the University of Maryland, Baltimore School of Nursing. She also serves as Co-Director of the UMB Center to Advance Chronic Pain Research. Her office is located in Room 731 of the School of Nursing Building.
Dr. Renn's research focuses on chronic pain of various etiologies, studying the underlying mechanisms associated with the development and persistence of chronic pain through both preclinical and clinical research. Her work examines physiological, psychological, and genomic factors that predict chronic pain development, particularly in patients with traumatic lower extremity fractures and chronic low back pain. She has ongoing investigations into the physiological mechanisms underlying aromatase inhibitor-induced arthralgia using mouse models.
Her research portfolio includes multiple NIH-funded projects, including the Omics Associated with Self-Management Interventions for Symptoms (OASIS) study (2016-2021), research on physiological predictors of chronic pain after lower extremity fracture (2018-2023), and the NEAT Study on neurophysiological and transcriptomic predictors of chronic low back pain. Her publications span topics from molecular pain mechanisms to clinical pain management and health disparities in pain sensitivity.
- Fellow of the American Academy of Nursing (FAAN)
Dr. Renn has served on numerous committees including the Faculty Council (2018-2020), Faculty Senate (2016-2019), and PhD Curriculum Committee (2016-2019, Chair 2017-2018). She has been an active member of the Center to Advance Chronic Pain Research Executive Committee since 2014. Professionally, she has served as a grant reviewer for NIH-NINR and the Medical Research Council, and as a manuscript reviewer for numerous journals including Nursing Research, Supportive Care in Cancer, and Nursing Outlook.
Her laboratory work focuses on understanding the physiological mechanisms of chronic pain conditions using both preclinical models and clinical studies, with particular emphasis on translational approaches to pain management.
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