Phenotyping Evoked Central Sensitivity to Painful Stimuli

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Project Summary/ Abstract Chronic musculoskeletal pain affects more Americans than diabetes, heart disease, and cancer combined according to the recent 2011 Institute of Medicine Pain Report. Pain is not simply a direct link between peripheral injury and the brain; both peripheral and central nervous system (CNS) modulation contribute to highly complex pain processing. Increasingly central sensitization of pain pathways is being recognized as an important component of persistent pain, but as central sensitization is a neuronal response, in humans it can only be indirectly assessed through psychophysical testing. Various evoked measures believed to be centrally-mediated; either through facilitated excitation (e.g., temporal summation of pain) or disinhibition (e.g., conditioned pain modulation, CPM) have been used to test for central mechanisms in a variety of musculoskeletal patient populations. Unfortunately, little has been done to characterize these central sensitivity assessments, thus it is unclear whether a single measure is equally representative of central involvement. While peripheral pain sensitivity phenotypes are modality-specific, e.g., individuals sensitive to heat pain are not necessarily sensitive to ischemic or cold pain, central sensitivity phenotypes have yet to be systematically examined. We are able to model central sensitization in humans using experimental muscle pain: referred pain and hyperalgesia at the ankle occurs in ~60% of individuals with intramuscular acidic infusion of the anterior tibialis. Thus we can use this model to test whether central sensitivity assessments are predictive of the development of referred pain. The first aim will characterize multiple central sensitivity phenotypes in humans: temporal summation of pain (i.e., punctate, deep-pressure and heat) and conditioned pain modulation (CPM, i.e., hypoalgesia to pressure and heat pain following noxious cold conditioning stimulus) and use cluster analyses to subgroup individuals based on their responses. The second aim will determine the likelihood that central sensitivity phenotypes are predictive of a model of central sensitization (i.e. referred pain). We will use logistic regression to determine the odd ratios of experiencing this reversible form of central sensitization between central sensitivity clusters. This study will either validate or challenge the common practice of using one or more of these assessments as equivalent markers of central sensitization in patient populations. When completed, these data can be used to direct and inform future studies as well as interpret previous findings in clinical populations. Long-term this information will be valuable for optimizing personalized therapies for patients with persistent pain conditions.