Funded Projects

For individuals with moderate to severe opioid use disorder (OUD), medication-assisted treatments (MATs) such as oral methadone and extended-release naltrexone (XR-NTX) are the gold standard in initiating and maintaining long-term recovery. Still, many patients struggle with persistent sleep disturbance and stress reactivity in the early stages of recovery, which drive relapse behaviors. This proposal constitutes a novel mechanistic approach to understanding the role of the orexin system in sleep disturbance and circadian rhythms of stress in OUD patients who are maintained on MATs and are early in recovery. This study will determine whether the FDA-approved sleep medication suvorexant (SUVO) improves sleep continuity and decreases diurnal measures of stress, and whether improvement of sleep/stress processes translates to improved OUD treatment outcomes. Its findings will fill critical gaps in our understanding of the role of the orexin system in sleep disturbance and circadian rhythms of stress that impact OUD recovery.

Pain is the most common symptom of sickle cell disease (SCD), contributing to poor physical and emotional health outcomes and exacerbating socially determined health disparities at significant societal cost. PRESENCE will be the first study to compare the effectiveness of a cognitive behavioral therapy (CBT) program with and without peer support to usual care as a non-pharmaceutical option for pain management in adolescents and young adults living with SCD. CBT is delivered through an innovative digital app that is accessed on a mobile device with one group receiving self-guided CBT, a second group receiving CBT plus peer support, and a third group receiving usual SCD care. The PRESENCE program is comprised of strong community partnerships that provide the peer support component of the intervention. Measured outcomes will include pain and emotional health.

To enhance availability of cognitive behavioral therapy for chronic pain (CBT-CP), this study will 1) refine strategies to identify and recruit patients, finalize intervention procedures, and ensure data infrastructure and quality; 2) determine the effectiveness of online and telephonic CBT-CP on patients and pain severity and secondary outcomes, including depression, sleep, quality of life, and pain-related health care utilization, from the electronic health record; and 3) assess the cost and incremental cost-effectiveness of online and telephonic CBT-CP compared with usual care. Eligible participants will be randomized to one of two painTRAINER interventions or usual care. Interventions will be eight weekly 45-minute sessions of the online program or telehealth-style phone coaching by trained behavioral health specialists. Self-reported pain severity and secondary outcomes will be assessed at baseline and at three, six, and 12 months.

Chronic pain is a persistent source of disability and reduced quality of life for aging adults. Chronic pain-related outcomes are disproportionately worse for aging African Americans, who report greater pain severity and worse pain-related disability compared to White peers. A significant pain risk factor for African Americans is chronic stress (including family-related stress), which is worsened by structural inequities that affect this population. Although many African Americans identify family support as critical for pain self-management, this influence has not been studied thoroughly. This project will study how pain conditions develop and persist for aging African Americans by analyzing existing data from African American participants in two large aging studies: Midlife in the U.S. (721 participants) and the Health and Retirement Study (2,698 participants). The research aims to determine how family emotional climate affects pain risk, taking into account structural factors like discrimination, socioeconomic disparity, and the influence of various neighborhood settings.

Chronic pain affects millions of Americans and remains poorly understood and challenging to manage. Researchers do not fully understand brain processes involved in chronic pain, which can vary considerably from person to person. This project will analyze brain function using magnetic resonance imaging (MRI) in individuals with and without chronic pain. The research will also directly determine the degree of pain-related brain imaging changes by using a large database of brain imaging data.

Substance use disorders (SUDs) can have devastating consequences for people with serious mental illness (SMI). SUDs can increase morbidity and mortality and are associated with higher healthcare and social costs, homelessness, and incarceration. Unfortunately, despite the availability of effective treatments, most individuals with co-occurring SMI and SUD (COD) never receive SUD treatment. We propose to evaluate system, provider, and patient-level facilitators and barriers and develop an implementation strategy and toolkit to promote the use of medication-assisted treatment (MAT) for people with COD. Aims 1–3 seek to assess organizational capacity (at the system and provider level); organizational readiness (at the provider level); and perceived needs, attitudes, and preferences (at the patient level) to identify barriers and facilitators. In Aim 4, we will use findings from Aims 1–3 to guide development of the implementation strategy and toolkit, using stakeholder input and a systematic process for strategy development.

Social big data analysis of publicly available user data on social media platforms is a promising approach for attaining organic observations of behavior that can monitor and predict real-world public health problems, such as HIV incidence. In preliminary research, our team identified and collected tweets suggesting HIV risk behaviors (e.g., drug use, high-risk sexual behaviors), modeled them alongside CDC statistics on HIV diagnoses, and found a significant positive relationship between HIV-related tweets and county-level HIV cases. We propose to create a single automated platform that collects social media data, identifies and labels tweets that suggest HIV-related behaviors, and predicts regional HIV incidence. We will interview staff and participants at local and regional HIV organizations to understand ethical issues associated with mining people’s data. The software developed from this application will be shared with HIV researchers and health care workers to combat the spread of HIV.

High rates of relapse and overdose deaths pose significant challenges to the treatment of Opioid Use Disorder (OUD). Anti-opioid immunotherapies (i.e., vaccines and monoclonal antibodies) have great potential to reduce long-term opioid use and overdose, with minimal risk of side effects, when used in conjunction with pharmacological treatments and/or behavioral therapies. The ability of an anti-opioid vaccine to induce antibodies that render an opioid less effective, or less rewarding, and protect from accidental overdose could provide an important therapeutic option for patients undergoing treatment for OUD. The goal of this collaborative study is to design, develop, and evaluate vaccines for use in the treatment of opioid use disorder

Current diagnostics and treatments of chronic low back pain (cLBP) rely primarily on subjective metrics and do not target all the multidimensional biopsychosocial mechanisms. This multidisciplinary effort will develop and validate a digital health platform and provide meaningful data-driven metrics that enable an integrated approach to clinical evaluation and treatment of cLBP. This platform will facilitate the use of quantitative spinal motion metrics (function), patient-reported outcomes, and patient preference information to enable deep patient phenotyping and inform clinical decision making on personalized treatments in order to improve outcomes. This effort will involve software and hardware development to enable data collection, analysis, and visualization in clinical settings. The outcome of this project will be a digital health platform with data to support regulatory submission for clinical use. At the end of this effort, the researchers will have a validated tool for integration in clinical research studies supported by the BACPAC Consortium.

Chronic overlapping pain conditions represent up to half of all chronic pain cases and can be more debilitating than other forms of chronic pain. These conditions include but are not limited to the following: temporomandibular disorders, fibromyalgia, irritable bowel syndrome, vulvodynia, interstitial cystitis/painful bladder syndrome, painful endometriosis, chronic tension type headache, migraine headache, chronic low back pain, and chronic fatigue syndrome. Common neurobiological mechanisms have been suspected to account for the overlap between these conditions, but until recently it has been difficult to efficiently classify each condition within individual patients. A digital classification tool for clinicians has been developed for this purpose, but access to the tool remains limited. Here we propose converting this chronic overlapping pain conditions classification tool into a common web-based application format.

The NIH Back Pain Consortium (BACPAC) Research Program brings together leading centers with expertise in studying and treating chronic low back pain to advance understanding of the mechanisms that underlie the condition and to identify novel treatment strategies. BACPAC is undertaking a multisite precision medicine clinical trial taking into account patient-specific information to understand which patients with chronic low back pain respond best to various nonopioid, evidence-based treatments. The trial seeks to enroll a racially, ethnically, and socioeconomically diverse patient population to ensure that the results are applicable to all Americans with chronic low back pain. This project aims to develop comprehensive recruitment and retention plans for study sites that can recruit from historically underrepresented populations in clinical research (e.g., Black and Hispanic populations) and to provide dedicated financial resources to engage patients from these populations using tailored, culturally appropriate strategies.

Knee osteoarthritis is one of the leading causes of disability worldwide, particularly among older adults. Despite multiple guidelines for care, most patients do not receive adequate treatment, and about 30% are prescribed long-term opioids. This award will be used to recruit and support an early career faculty member from a group underrepresented in biomedicine. This research, part of the Pain Management Effectiveness Research Network will evaluate conservative and more aggressive treatments for knee osteoarthritis and determine which individual-level factors contribute to treatment outcomes.

The University of Michigan (UM) will lead a Mechanistic Research Center (MRC) as part of the broader BACPAC initiative that will take patients with chronic low back pain (cLBP) and use a patient-centric, SMART design study to follow these individuals longitudinally as they try several different evidence-based therapies while mechanistic studies are overlaid to draw crucial inferences about what treatments will work in what patient endotypes. Interventional Response Phenotyping describes the need in any precision medicine initiative to phenotype participants based on what therapies they do and do not respond to so that one can later link mechanistically distinct disease endophenotypes with those who preferentially respond to therapies targeting those mechanisms.