Discovery and Analytical Validation of Inflammatory Bio-signatures of the Human Pain Experience

Lack of precision in tools that quantify risk and assess presentation of post-operative pain poses substantial burden to prevention and treatment and is a major contributor to the nationwide opioid epidemic. Enhanced precision in post- operative pain care requires quantitative tools that individualize assessment of widely variant human pain experiences, accounting for variance in intensity, threshold, and in both affective and sensory components of pain. No currently available measure is sufficiently sensitive, accurate, and reliable to account for the wide variance in risk or clinical presentation of post-operative pain that is required to impact best practices. To address this unmet need, we will discover (R61 phase) and validate (R33 phase) a novel, fit-for-purpose, objective bio-signature that is sensitive, accurate, and reliable in predicting risk (and presentation) of post-operative pain states following a elective cosmetic surgery (e.g. abdominoplasty), a body contouring surgery frequently performed and associated with post-operative pain.

Evidence suggests it is biologically plausible to develop a bio-signature of the human pain experience that derives from IL-1 family cytokine activity. In animal models, imbalance between pro- and anti-nociceptive IL-1 family cytokines is readily induced pharmacologically and surgically, enhancing pain behavior, central endogenous opioid release, and tolerance to opioid analgesics, all factors that contribute to chronicity. Pharmacologic blockade of pro-nociceptive IL-1 cytokines with soluble IL-1ra reverses the pro-nociceptive effects. Evidence suggests similar relationships exist in humans. Concentration of IL-1b sampled intra-operatively from wound site blood revealed predicts surgical complications and post-operative pain. However, IL-1b (on its own) has not proven sufficiently accurate, sensitive, or reliable to account for the broad inter-individual variance in risk and clinical presentation of human post-operative pain states. In preliminary data from separate regression analyses, neither IL-1b nor IL-1ra significantly predicted pain (intensity or threshold). However, regression models incorporating both IL-1b and IL-1ra showed that imbalance between these 2 factors (pro-nociceptive IL-1bias) synergistically enhanced prediction of pain (intensity and threshold) and underlying endogenous opioid release during a standardized pain challenge, accounting for 20% of the pain variance. IL-1b (pro-nociceptive) was a positive predictor and IL-1ra (anti-nociceptive) a negative predictor of pain. Including additional variance factors (sex, mu-opioid receptor polymorphism, neuroticism) in the model accounted for another 5% of the pain variance. Pain variance factors can impact concentration of additional IL-1 cytokines that regulate IL-1 signaling, suggesting it is both biologically and statistically plausible that incorporating a wide array of IL-1 family cytokines (IL-1b, IL-1ra, IL-1a, sIL-1r1, IL-1RAcP, IL-18, IL-18bp, IL-18Ra, IL-18Rb, IL-36, IL-38, IL-33, sTLR4) into a broader bio-signature of IL-1 family cytokine activity will perform superior to simple measures of IL-1bias (that include only IL-1b and IL-1ra) in predicting the highly heterogeneous human post-operative pain experience.

This study phase focuses on discovery (and analytic validation) of a novel, bio-signature of risk for post-operative pain states and underlying opioid-cytokine interactions. Performance (accuracy, sensitivity, dynamic range) in predicting experimental and post-operative pain will be tested in n=70 healthy humans following elective abdominoplasty.

More Specifically, The first objective of the study is to evaluate whether a novel bio-signature (derived from a wide range of pro- and anti-nociceptive IL-1 family cytokine activity) will predict pain experienced and also release of underlying endogenous opioid neurotransmitters during an experimental nociceptive pain challenge, which will be performed while simultaneously quantifying mu-opioid receptor activity in the brain via [11C]-carfentanil PET neuroimaging in healthy subjects. Another objective is to evaluate whether an anti-inflammatory drug that reduces activation of IL-1b (anakinra) will perturb the balance between pro- and anti-nociceptive IL-1 cytokines and effect a reduction in pain experienced (and endogenous opioids released) during the experimental, nociceptive pain challenge. A final objective is to evaluate performance characteristics (sensitivity, accuracy, dynamic range) of the biosignature for the purpose of predicting post-operative pain.