Transcriptomics of Pain in Sickle Cell Disease

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PROJECT SUMMARY/ABSTRACT Patients with sickle cell disease (SCD) exhibit marked inter-individual heterogeneity in frequency of acute pain events, or vaso-occlusive crises (VOC) and development of chronic pain. The nidus of a VOC is typically the adhesion of a leukocyte to the endothelium, bringing with it a red cell which deoxygenates and sickles, resulting in vaso-occlusion, ischemia, and pain. We therefore collected SCD patient RNA from CD71+ cells (red cell precursors that still retain RNA) and CD45+, leukocytes from individuals with and without chronic pain, and longitudinal collections obtained at steady state, in VOC, and VOC resolution, and submitted these samples to TOPMed for RNASeq analysis. We propose to leverage this transcriptome data from a well phenotyped pediatric SCD cohort to address the unmet need of objective, quantifiable markers of acute and chronic pain, and evaluate in the context of the germline and somatic mutations found in the same subjects’ whole genome sequencing (WGS) data, also in TOPMed. Short term goals are to 1) identify genes and pathways altered in the chronic pain state, 2) identify transcriptome changes associated with pain events and their resolution, 3) generate a transcriptional risk score for the development of chronic pain, and 4) determine which variants associated with chronic pain development are likely to be causative through transcriptome wide association studies. Long term goals are to use these findings to 1) develop targeted therapies to prevent and treat VOC, 2) therapies to treat chronic pain in SCD, and 3) biomarkers to distinguish acute pain events from chronic pain. The ability to do so will allow providers to manage VOC appropriately and aggressively, without inadvertently confusing chronic pain with an acute pain episode. Our inability to distinguish between acute and chronic pain harms our patients, as the opioids that are the mainstay for VOC treatment often worsen chronic pain through opioid induced hyperalgesia. Our work will leverage TOPMed samples via our innovative transcriptomics analysis to identify risk factors, therapeutic targets, and biomarkers of chronic pain, in order to improve the care and quality of life of individuals living with SCD.