# Neurophysiological and transcriptomic predictors of chronic low back pain: towards precision pain management (NEAT Study) > **NIH NIH R01** · UNIVERSITY OF MARYLAND BALTIMORE · 2022 · $618,963 ## Abstract PROJECT SUMMARY One of the most common and costly chronic pain conditions is low back pain (LBP), which produces more global disability than any other condition. Up to 39% of patients with an acute LBP episode report chronic LBP (pain lasting >3 months) and long-term disability for 2 years or longer. Increased mechanistic understanding of the transition from acute to chronic LBP will enable us to identify biomarkers early in the transition period and new therapeutic targets at critical windows of opportunity to prevent and/or better manage chronic LBP. In this study, we will test the hypothesis that neurophysiological and gene expression differences can be used to build a predictive model that will define the chronic LBP phenotype and transcriptome and identify those LBP patients who will transition from acute to chronic pain phenotypes. We will prospectively follow a cohort of 380 LBP patients and 40 healthy controls (for comparison with LBP patients and to track gene expression stability over time) for two years following the initial clinic visit for report of LBP. We will rigorously phenotype the participants, including measurement of neurophysiological factors, and analyze gene expression at baseline and regular intervals during the first year and at 18 and 24 months. We will accomplish these goals via two specific aims: Aim 1: To examine neurophysiological predictors of the transition from acute to chronic pain at baseline and over time following initial clinic visit for report of LBP. We will enroll participants at time of initial LBP and follow them 6, 8, 10, 12, 16, 20, 24, and 52 weeks, as well as 18 and 24 months’ post onset. At timepoints that correspond with blood draws for RNA-seq we will conduct neurophysiological testing to characterize peripheral sensory nerve function, temporal summation (wind up) and conditioned pain modulation (intactness of the descending inhibitory pain modulatory system). At other timepoints, participants will fill out online questionnaires about pain and psychosocial constructs. Aim 2: To test the hypothesis that differential expression of MHC locus genes at baseline and over time will be associated with the risk for chronic pain, while differential expression of known pain genes will define the chronic LBP transcriptome. In this aim, we will isolate total RNA from whole blood for sequencing at baseline and 6, 12, 24, 52 weeks, and 2 years. We will examine how changes in gene expression differs in extreme phenotypes from three groups (n=20 healthy participants, n=50 acute LBP, n=50 chronic LBP) at each of the six timepoints. In addition to biomarker identification, we will conduct non-biased pathway analysis of the differentially expressed genes to gain mechanistic insight into potential novel therapeutic targets for chronic pain prevention and/or management. This study is highly aligned with NINR’s strategic plan and mission, the National Pain Strategy, IOM report, and the NIH’s HEAL Initiative to identify... ## Key facts - **NIH application ID:** 10424412 - **Project number:** 5R01NR018595-04 - **Recipient organization:** UNIVERSITY OF MARYLAND BALTIMORE - **Principal Investigator:** SUSAN G DORSEY - **Activity code:** R01 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2022 - **Award amount:** $618,963 - **Award type:** 5 - **Project period:** 2019-09-23 → 2024-03-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10424412 ## Citation > US National Institutes of Health, RePORTER application 10424412, Neurophysiological and transcriptomic predictors of chronic low back pain: towards precision pain management (NEAT Study) (5R01NR018595-04). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10424412. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*