Funded Projects

Temporomandibular joint (TMJ) disorders, which affect the joint connecting the lower jaw and the skull, are common and difficult chronic pain conditions. Pain management strategies that harness the body’s own pain relief mechanisms (including placebo effects in which pain relief cannot be attributed to a specific treatment), can reduce the severity and duration of TMJ-related chronic pain. Although research suggests that placebo effects may have a genetic basis, few, if any, genetic studies have examined this possibility in individuals with TMJ disorders. This project will use in-depth genetic, sociodemographic, clinical, and psychological data collected from adults with chronic TMJ disorders to better understand how the placebo effect works.

The science of recovery support services for individuals choosing to take medications for opioid use disorder as part of their recovery pathway is gaining momentum and will benefit from a dedicated, sustainable cross-project research infrastructure. This project enhances research in the existing Consortium on Addiction Recovery Research Science. This effort coordinates varied research and training efforts across recovery support research projects, amplifies communication and dissemination channels for their activities, and is organizing the first national meetings on addiction recovery support services science.

This project aims to develop a new way to stimulate the delta opioid receptor to treat withdrawal and abstinence from chronic opioid use. Withdrawal can cause pain, depression, and anxiety, which contribute to relapse. The research will test promising drug candidates in animal models with the intention of bringing at least one effective and safe compound to the final stage of drug development before human clinical trials can begin.

There are currently few effective therapies available for chronic nerve injury-induced pain, associated anxiety, and depression. This project aims to extend previous research aiming to uncover the mechanism of action of artificially modified immune molecules (humanized cholecystokinin-2 receptor [CCKBR] single-chain variable fragments [scFv]) on human neurons and how it reverses chronic pain and anxiety-like behaviors in mouse models. This potential treatment approach offers important advantages over existing therapies, including extreme specificity, higher affinity, brain/nerve penetrance, safety, and reduced self-immunogenicity.

The medication monomethyl fumarate, approved for treating multiple sclerosis, has pain-relieving properties, but it also has side effects that affect the digestive tract and decrease levels of white blood cells, a problem known as leukopenia. This project will limit the availability of monomethyl fumarate to areas in the central nervous system associated with pain. Targeting the delivery of this drug to pain-related regions may improve its safety profile for treating neuropathic pain.

Pain in the muscles and surrounding connective tissue (myofascial pain) is a significant and poorly understood health concern affecting hundreds of millions of Americans. There is a great need for tools to assess changes to myofascial tissues in individuals with chronic pain as well as to measure the effect of commonly used therapies. This project will use three imaging tools to look at differences between shoulder tissue in people with myofascial pain compared to those without pain. Using a machine learning approach, this research aims to develop a biomarker signature for myofascial pain, which will be evaluated in a randomized controlled clinical trial based on its ability to predict patient responses to myofascial pain treatments.

Little is known about what motivates people to use multiple drugs. Understanding these factors is important for tailoring treatment services. Behavioral economic theory, which determines how much value individuals assign to drugs and potential negative consequences, provides a framework to understand the choices people make. This project will identify patterns, motivating factors, and long-term trajectories of opioid-involved polysubstance use behaviors and treatment. This research will use a range of methods to analyze substance use episodes as well as examine motives and preferences associated with polysubstance use behaviors and how they change over time. The findings will be combined into a toolkit to inform timing, type, and tailoring of interventions and policies to guide implementation of effective clinical strategies and policies for managing polysubstance use in healthcare systems.

A key component to addressing the current opioid overdose crisis is the ability to track dangerous opioid use in a timely manner so that public health agencies can plan accordingly. Direct reports about drug use and overdoses from social media might provide a useful early warning system that when combined with other sources, can provide policy makers and public health officials with powerful tools for monitoring this public health crisis. This project will explore the usefulness of Twitter and Reddit as a social media component of opioid use surveillance – in particular by monitoring mentions of fentanyl and synthetic opioids at various geographic levels (e.g., local or regional) and over time.

Despite the significance of spine disorders, there are few reliable methods to determine appropriate patient care and evaluate intervention effectiveness. The Back Pain Consortium Research Program
(BACPAC) is developing machine learning-based methods to obtain disease-related features from biological images. This project supports a scientist from a group underrepresented in biomedicine to expand ongoing research to improve ways to interpret medical data about spine disorders and associated pain.

Safe and effective options are urgently needed to prevent and treat opioid use disorder and polysubstance use disorders. Previous research in humans and animals suggests that activating the calcium-activated potassium channel KCa2.2 is a promising therapeutic approach for treating substance use disorders and associated health conditions. This project will perform a virtual high-throughput screen using novel machine learning approaches to discover new molecules that interact with the KCa2.2 channel. The newly discovered molecules help develop novel drugs for the treatment of opioid use disorder and associated health conditions.

High-voltage-gated calcium channels convert electrical signals into physiological responses. After a nerve injury, levels of these channels go down in some neurons in the dorsal root ganglia that communicates pain signals to and from the brain. This decline results in reduced flow of calcium that may underlie pain. This project will develop novel approaches to block these calcium channels p to further study their roles in controlling pain.

Sickle cell disease is an inherited blood disorder affecting about 100,000 Americans and more than 20 million people worldwide. It is caused by a mutation in the gene for beta-globin that results in the characteristic sickled shape of red blood cells, life-long severe pain, and shortened lifespan. Sickle cell disease pain episodes are usually unanticipated, making it hard for people with the condition to manage their pain and putting them at risk for increased use of opioids and poor health outcomes. This project will use existing real-time health data to identify factors that can predict onset, severity, and worsening of daily pain in children with sickle cell disease.

Overdose fatality review teams review cases of overdose deaths to identify system gaps and innovative prevention and intervention strategies. With the rise in overdose deaths, these multidisciplinary teams require more timely population-level data to inform their recommendations. This project will develop the Overdose Touchpoints Dashboard that uses real-time data and records from multiple sources to help visualize common “overdose touchpoints” for harm reduction services and treatment opportunities. This research will compare use of the dashboard to standard overdose fatality review practices. The project will assess multiple aspects related to use of the dashboard, including process, staff attitudes, implementation successes, and usability.