Funded Projects

Migraine is the most common neurological disorder. Currently available treatments fail to effectively manage migraine in most patients. Development of new therapeutics has been slow due in large part to a poor understanding of the underlying pathology of migraine. Endogenous proteases, released in the meninges by resident mast cells, have been proposed as a potential driver of migraine pain via an action on protease activated receptor type 2 (PAR2). The central hypothesis is that PAR2 expression in nociceptors that project to the meninges plays a key role in the pathogenesis of migraine pain. The aims are to: 1) use the established PAR2 development pipeline to design new PAR2 antagonists with improved drug-like properties; 2) use pharmacological tools in a novel mouse migraine model to further understand the potential role of PAR2 in migraine; and 3) use mouse genetics to study the cell type–specific role of PAR2 in migraine pain.

This study aims to determine whether a subset of understudied genes that are expressed in human and mouse dorsal root ganglia (DRG) tissues (critical for relaying the sensation of pain from the body to the central nervous system), are also expressed in human induced pluripotent stem cell DRG mimetics. The study will also determine if these genes are involved in neuronal excitability changes under inflammatory conditions and compare these responses to those of primary DRG neurons. Third and finally, the study will optimize genetic depletion of target genes enabling future fundamental and preclinical research studies.

High-quality parent-infant interactions set the stage for secure parent-child attachment, self-reliance, and children’s ability to flexibly solve problems and “bounce back” from difficulties. This constellation of behaviors reduces the risk of developing substance use disorders later in life. This project will develop algorithms that use data from wearable sensors, trained separately for English- and Spanish-speaking families, to assess the quality of early mother-infant interactions objectively, automatically, and remotely in natural home environments, with the goal of developing tools to facilitate identification and prevention of early risks for substance use disorders.

Buprenorphine-naloxone is known to work for the treatment of Opioid Use Disorder (OUD). However, despite its success in treating OUD, retention for these kinds of medication-assisted treatments (MATs) for OUD is notoriously low, having a dropout rate of approximately 50 percent within the first 6 months. One factor known to negatively impact a person?s adherence to treatment is stigma. This includes, not only stigma associated with having OUD, but also that of multiple stigmatized identities, including stigma associated with race. The goal of this supplement award is to decrease OUD- and race-related stigma in low income African American communities using a Behavioral Economics Stigma Reduction intervention that functions at the intrapersonal, interpersonal, and community levels. The investigators will work at the individual level to address stigma in untreated individuals who present with OUD at local community or faith organizations through stigma reduction counseling and tangible rewards for treatment uptake. To assess the interpersonal stigma, referred family members or support persons of these individuals will also be enrolled to receive stigma reduction and supportive skills counseling. Finally, a stigma reduction campaign will be developed and administered to the community via social media and billboards. Community members? substance use stigma will be compared before and after the campaign.

Osteoarthritis is a degenerative joint disease marked by progressively worsening chronic joint pain that affects function and quality of life. Non-opioid, alternative medications are needed for people with this condition. Joint inflammation, damage, and pain involve signaling through the interleukin-6/glycoprotein 130 pathway. This project will test blocking this pathway in rodents with a new molecule with improved drug-like properties, toward developing an oral medication for osteoarthritis. 

Opioids affect the body by attaching to certain types of receptors that attach to G-proteins (particularly, a subtype called G-alpha). Opioids vary in their ability to provide pain relief as well as in their ability to require more drug to provide a response, known as tolerance. This project will explore the potential of various G-alpha subunits to increase or decrease opioid receptor signaling. The research findings will lay the groundwork for tailoring G-alpha related opioid effects to provide more pain relief while being less addictive.

Enhancing the workforce of pain investigators and practitioners is a key goal of the NIH HEAL Initiative. This mentoring award leverages the resources at one of EPPIC-Net’s Specialized Clinical Centers to encourage interest in clinical pain management, in particular through multidisciplinary pain research projects. A selected investigator will train early career clinical researchers on how to develop and validate relevant pain measures and outcomes in chronic pain conditions, including chemotherapy-induced peripheral neuropathy and neuropathic chronic low back pain. Mentoring activities will include formal research and analysis, active inclusion in EPPIC-Net working groups, and collaborative writing experiences.

Cerebral palsy (CP), the leading cause of childhood disabilities in the United States, refers to a group of neurological disorders that appear in infancy or early childhood and permanently affect body movement and muscle coordination. The experience of pain is one of the most common, poorly understood, and inadequately treated conditions in CP, impairing health and quality of life for both patients and caregivers. To understand why pain and motor dysfunction occur together, a model that accurately replicates both is needed. This project will validate an established, rabbit model of CP motor dysfunction for use in studying and developing effective treatments for CP-associated pain.

Identifying optimal chronic low back pain treatments on a patient-specific basis is an important and unresolved challenge. Tailoring interventions according to patient movement characteristics is one option. This research is characterizing patients based on spinal motion during functional tasks and daily activities and will use artificial intelligence to objectively characterize motions of the spine during both clinical assessments and day-to-day life. During clinical assessments, participants will be asked to perform functional tasks while wearing motion sensors. Data collected from the sensors will be used to identify tasks of interest, such as activities of daily living and aberrant/painful motions. An artificial intelligence approach will then interpret data collected continuously during assessment in patients’ homes over a 7-day testing period. Ultimately, this data could be used to help clinicians tailor treatments that are responsive to a patient’s real-world functional impairments.

Medications have proven to be effective for treating opioid use disorder (OUD). Increasing accessibility to buprenorphine provides an opportunity for many with OUD to benefit from its proven effectiveness. Adherence to medication-based treatments however is low, in part because of the stigma associated with use of this and other effective drugs and as such, leads to inadequate treatment and poor outcomes. This study aims to understand the effects of stigma on patient engagement, retention, and outcomes of buprenorphine treatment. Knowledge drawn from the HIV Stigma Theory and tools developed to reduce HIV associated stigma will be used to assess OUD stigma and to develop interventions to reduce it in the context of buprenorphine treatment. The study findings may provide resources to address stigma and thus maximize treatment adherence among those affected by OUD.

The Appalachian Node of NIDA Clinical Trials Network (CTN) will address clinical research questions that arise from Central Appalachia, an epicenter of the current opioid epidemic. Its rural geography, culture of independence, strained economy, and lack of access to substance use treatment have all contributed to the epidemic. The three aims of the node are to (1) conduct multi-site trials that address the current opioid crisis, with an emphasis on conducting studies among rural and other underserved populations; (2) propose studies to test innovative uses of existing resources to implement evidence-based practices that will extend state-of-the-art care into resource-poor regions, both rural and urban; and (3) disseminate CTN findings to regional payers and policymakers, practitioners, and the community. Proposed studies built on the work of node investigators include “Serious Bacterial Infections Related to Injection Drug Use: Quality Metrics and Intervention” and “Pharmacist-Assisted Buprenorphine Treatment,” among others.

Identifying optimal chronic low back pain treatments on a patient-specific basis is an important and unresolved challenge. Tailoring interventions according to patient movement characteristics is one option. This research is characterizing patients based on spinal motion during functional tasks and daily activities and will use artificial intelligence to objectively characterize motions of the spine during both clinical assessments and day-to-day life. During clinical assessments, participants will be asked to perform functional tasks while wearing motion sensors. Data collected from the sensors will be used to identify tasks of interest, such as activities of daily living and aberrant/painful motions. An artificial intelligence approach will then interpret data collected continuously during assessment in patients’ homes over a 7-day testing period. Ultimately, this data could be used to help clinicians tailor treatments that are responsive to a patient’s real-world functional impairments.