Laura A. Frey Law, Ph.D. - US grants

DESCRIPTION (provided by applicant): Pain, an unpleasant sensory and emotional experience, is a significant often under-recognized medical problem spanning numerous patient populations. One of the leading causes for individuals to seek medical attention is musculoskeletal pain. Indeed, pain is now considered the 5th vital sign. Unfortunately, pain is highly variable between individuals. In both acute and chronic pain conditions, there is often a dissociation of pain perception and the underlying pathology in a variety of conditions such as low back pain, osteoporosis or osteoarthritis. Significant pain that is disproportionate to the physical findings is challenging to treat and can result in decreased quality of life and greater disability. Thus, pain heterogeneity associated with common clinical conditions Interferes with diagnosis and adequate treatment, ultimately compromising healthcare. The biopsychosocial model of pain suggests pain perception is a complex process that involves a myriad of physical, social, and emotional components. While no one factor can explain pain heterogeneity, individual differences in gender, genotype, and psychological traits may play a significant role. Unfortunately, it is difficult to find individuals with adequate multidisciplinary training to investigate pain from a multi-factorial perspective. Thus, the goal of the proposed research and training is to gain the expertise to determine the degree to which measurable Individual differences, e.g. sex, genotype and personality traits, predict high and low pain responses. This translational study approach utilizes a controlled, deep-tissue, algesic stimulus in human subjects to critically examine factors that contribute to pain heterogeneity. The Intramuscular infusion of an acidic phosphate buffer provides a clinically-relevant nociceptive stimulus of deep-tissue pain. This novel model provides a unique opportunity to study the Influence of baseline individual differences without the confounding factors associated with clinical pain syndromes. RELEVANCE: Musculoskeletal pain is a prevalent problem in our society and pain heterogeneity between individuals may result from multiple factors. This research plan will assess the role of normal personality traits, sex, and genotype on muscle pain sensitivity. This information may improve diagnosis and treatment strategies for musculoskeletal pain, advancing healthcare through increasingly individualized patient care approaches.

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.

PROJECT SUMMARY/ABSTRACT The transition from acute to chronic pain has eluded researchers for years, likely due to its complex nature and the inherent individual variability. The ability to identify individuals at risk, and those with reduced risk, for the transition to chronic pain using biomarkers will advance personalized acute pain treatment strategies, reduce reliance on opioid pharmacotherapy, and help identify novel therapeutic targets, thereby transforming the management of acute pain events. The Acute to Chronic Pain Signatures (A2CPS) Program aims to identify biomarkers and their collective biosignatures (a combination of several individual biomarkers) that predict susceptibility or resilience to the development of chronic pain after an acute pain event through the development of a large consortium. The advantage of multisite observational studies is their ability to comprehensively phenotype large population cohorts across multiple biopsychosocial domains in a relatively short time. This application describes a partnership between a strong group of pain scientists (Sluka, Frey Law) and the Clinical Trials Statistical and Data Management Center (Coffey, Ecklund) at the University of Iowa. The proposed CCC applies thorough and well-organized principles to facilitate, support and enhance the scientific rigor and effectiveness of key stakeholders for the identification of critical biomarkers for the acute to chronic pain transition, using the following task-based specific aims: 1) Lead the development and implementation of clinical protocols. 2) Provide oversight and management of collaborative activities across the consortium to support the overall goals of A2CPS. And 3) Facilitate transparent and effective communication between consortium members. The CCC will support study design, bringing expertise in pain and adaptive designs to help identify biomarkers for study inclusion; promote efficiency and quality through development of milestones, Standard Operating Procedures (SOPs), individualized recruitment plans, and staff training protocols. The CCC will be responsible for regulatory procedures including: standardizing the electronic health record; coordinating a central Institutional Review Board (cIRB); and convening a Data Safety and Monitoring Board (DSMB). The CCC will track protocol quality control procedures and safety monitoring; perform central monitoring and on-site monitoring visits; and monitor progress towards A2CPS milestones, particularly site- specific enrollment and retention targets, a critical component in the success of the A2CPS initiative. The success of the A2CPS Program is dependent on effective management and coordination of activities across the Consortium. We have assembled a team with expertise spanning pain science, clinical trials in patients with pain and other conditions, and successful large multi-site trial coordination. The University of Iowa has a highly collaborative environment with strong pain science researchers, making us well prepared to successfully perform the many needed roles of the A2CPS Clinical Coordination Center.

Project Summary Fibromyalgia (FM) is a complex condition characterized by widespread pain and fatigue that is associated with sleep dysfunction and reduced function that affects 2-4% of the population (Heidari et al., 2017). Current 2016 diagnostic criteria are by symptomology only, as there are no validated chronic pain biomarkers to assist with diagnosis, or treatment evaluation endpoints (Wolfe et al., 2016). Diagnosing FM often takes years with patients seeing multiple physicians, which delays treatment (Choy, 2010). This delayed diagnosis and treatment initiation would be dramatically reduced with the identification of FM biomarkers. The long-term goal of this line of research is to identify unique biomarkers for FM to improve the diagnosis and/or develop therapeutic targets for individuals with widespread pain. Using a semi-targeted metabolomics approach, our preliminary data from women with FM (n=59), compared to healthy controls (n=38), show 18 potential candidates that differ significantly between cohorts with several metabolites showing good-excellent sensitivity (>90%) and specificity (>90%). The primary goal of this proposed research is to assess and validate candidate metabolic biomarkers in a new, larger cohort of individuals and compared to other chronic pain populations. The proposed study will use a multi-site, cross-sectional design to identify and characterize metabolic biomarkers, biosignatures, and their associations with multiple symptomology domains to address the following two specific aims: Aim 1: We will characterize diagnostic test metrics for candidate biomarkers using receiver operating curves (ROCs), i.e. sensitivity and specificity, and test-retest reliability, to correctly identify individuals with FM from healthy controls and other chronic pain conditions: osteoarthritis, carpal tunnel syndrome, and rheumatoid arthritis. Aim 2: We will determine associations between putative metabolic biomarkers and multiple self-reported symptom domains in those with FM: a) pain; b) fatigue; c) sleep; d) physical function; e) psychological factors, and f) disease impact/disability. We have identified several promising metabolic biomarkers that may serve as diagnostic or within-disease phenotype identifiers. Once completed, we will examine potential mechanistic and therapeutic targets for the candidate biomarkers in subsequent studies. These novel studies have the potential to identify a diagnostic, and potentially a therapeutic, biomarker of FM associated with cell metabolism. To accomplish this study, we have developed a strong multidisciplinary and multi-site team, leveraging blood samples and phenotype data collected as part of an on-going funded study, as well as additional data collection for repeatability analyses. The study team has the necessary expertise in human, basic science and metabolomics investigations to successfully complete these aims.