Funded Projects

Neonatal abstinence syndrome (NAS) rates have increased since 2000. To determine multifactorial genetic, psychosocial predictors of opioid-related maternal and infant outcomes using rigorous prospective longitudinal design, innovative combinatorial pharmacogenetic approach, fetal MRI, and neonatal brain resting state functional MRI analysis, we hypothesize that a combination of maternal and infant genetic profiles, maternal psychosocial factors, maternal opioid treatment response, fetal and neonatal neurodevelopment, and NAS treatment will affect maternal and childhood outcomes with prenatal opioid exposure. The specific aims are to (1) Identify high-risk genetic profiles and psychosocial factors in pregnant women with opioid use disorder (OUD) and predisposing to poor maternal opioid maintenance treatment outcomes; (2) Determine maternal-infant genetic profiles and maternal opioid treatment factors predicting adverse fetal development, severity of NAS, and neonatal brain function; and (3) Develop predictive models for maternal opioid relapse and poor long-term neurodevelopmental outcomes in children with in utero opioid exposure.

The incidence of Neonatal Opioid Withdrawal Syndrome (NOWS) in the United States has increased more than fivefold since 2004 to almost 7 per 1,000 hospital births. It is unknown how these effects are modulated by associated maternal, neonatal, and environmental factors and how the environment, maternal health, and parenting styles modify trajectories of brain connectivity and neurodevelopment. This study leverages the established infrastructure and longstanding collaborations of four clinical sites and the data coordinating center of the Eunice Kennedy Shriver National Institute of Child Health and Human Development Neonatal Research Network to address current critical knowledge gaps in childhood brain structure and connectivity and on medical, developmental, and behavioral trajectories in early childhood. The study will analyze a well-characterized observational cohort using clinical and neuroimaging measures to improve understanding of the structural and functional sequelae resulting from prenatal opioid exposure and NOWS and their interactions with the maternal-infant dyad.

Rapid technological advances are leading to field-deployable mobile sensing devices that can quantify complex dynamics of key physical, biological, behavioral, social, and environmental factors, enabling us to understand causation in complex disorders. Significant new investment is needed to develop and disseminate data analytics tools. The Center of Excellence for Mobile Sensor Data-to-Knowledge (MD2K) will generate generalizable theory, methods, tools, and software to address major barriers to processing complex mobile sensor data and its use in biomedical knowledge discovery and just-in-time care delivery. We will develop and implement a standards-based, interoperable, extensible, and open-source big data software platform for efficient implementation of MD2K data analytics. MD2K will demonstrate the feasibility, utility, and generalizability of this approach by implementing the entire MD2K data analytics system in the context of two biomedical applications: reducing relapse among abstinent daily smokers and reducing readmission among congestive heart failure patients

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

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.

There is a great deal of research aimed at better understanding transitions in alcohol and other drug (AOD) use patterns from early to late adolescence and from late adolescence to emerging adulthood. However, no studies to date have (a) assessments of AOD use from ages 10 to 24 across all developmental periods (middle school, high school, and emerging adulthood); (b) a large sample with substantial racial and ethnic diversity, particularly among Hispanic and Asian youth; (c) in-depth coverage of 10 areas of functioning across three key domains; (d) subjective and objective neighborhood data; or (e) the capacity to examine developmental trajectories for more than one substance. The current proposal is a continuation of previous projects that assessed AOD use across nine waves of data from age 10 to age 19. The proposed study capitalizes on the longitudinal data on protective and risk factors we have collected since age 10 in an ethnically diverse cohort by continuing to annually assess these youth in order to capture important transitions to emerging adulthood (through age 24). By advancing the epidemiology of alcohol use during adolescence and emerging adulthood, our findings can affect prevention and intervention programming for young people and address critical issues of public health policy.

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.

Among the most common symptoms experienced by individuals suffering with opioid use disorder (OUD) are severe sleep and circadian disruptions. The relationship between opioid dependence and sleep and circadian systems is not well understood. A circadian-dependent mechanism has been shown to modulate fentanyl reward-related behaviors in the nucleus accumbens (NAc). The study team will use a combination of behavioral, slice electrophysiology, and molecular approaches to 1) investigate the role of the circadian transcription factor NPAS2 in medium spiny neurons with dopamine 1 (D1R-MSNs); 2) assess the impact of fentanyl on synaptic plasticity at D1R-MSNs and investigate whether NPAS2 mediates the potentiation of excitatory synapses at specific diurnal phases; 3) elucidate the cell-type-specific NPAS2-dependent transcriptional mechanisms of fentanyl-seeking and relapse behaviors; and 4) investigate whether NPAS2 rescue and buprenorphine medication-assisted treatment (MAT) improve fentanyl-induced sleep disturbances. This study will define the role for circadian-dependent transcriptional mechanisms and uncover the therapeutic potential of NPAS2 for opioid dependence and relapse.

Profound sleep disturbances during abstinence have long been suspected of perpetuating vulnerability to relapse of people who misuse or are addicted to opioids. An animal model has shown that long-term sleep deficiency results in a persistent state of physiological dysregulation that is expected to modify the biology of abstinence and increase relapse potential. This study seeks to discover how persistent sleep restriction during withdrawal from opioid use increases vulnerability to relapse in the animal model by testing whether persistent sleep restriction during abstinence from opioid use is sufficient to increase opioid drug seeking. The functional outcome measure will be the degree of mitigation of opioid seeking. These studies will provide a basis for novel translational approaches to target mechanisms that are demonstrated to cause increased vulnerability to relapse.

Chronic pain and opioid use disorders (OUD) are burgeoning interrelated epidemics. Sleep disturbances are prevalent, treatable, and increasingly recognized as risk factors for both chronic pain and OUD. Sleep disruption impairs endogenous pain inhibition, linked to analgesic efficacy and rewarding properties of mu-opioid receptor (MOR) agonists. It is not known, however, whether sleep disturbance causally alters mechanisms that contribute to OUD risk. Sleep continuity disruption (SCD) and/or sleep fragmentation (SF) may alter cerebral MOR availability, and these forms of sleep disruption may increase OUD risk. This study aims to 1) evaluate whether experimental SCD and/or SF alter resting or pain-evoked MOR binding potential (BP) in brain regions associated with pain inhibition; 2) examine whether SCD and/or SF alters the analgesic response; and 3) determine whether MOR BP in brain regions of interest are associated with analgesia and abuse liability.

Opioid use disorder (OUD) is a chronic and relapsing brain disease that affects over 2 million Americans. Despite effective evidence-based treatments in the form of behavioral interventions and FDA-approved medication for addiction treatment (MAT), relapse rates are high. The Collaboration Linking Opioid Use Disorder and Sleep Study will investigate patients on MAT to elucidate potential causal mechanisms between sleep deficiency and OUD. The aims of this study are to 1) test whether there are different neurocognitive connectivity patterns between patients with adequate vs. deficient sleep in brain systems involved in addiction and assess the extent to which these “neural fingerprints” predict ongoing opioid use; 2) evaluate the potential biologic, psychiatric, and pharmacologic mechanisms that explain the causal pathway between sleep deficiency and opioid use; and 3) test ecologic factors such as psychosocial, family, and neighborhood contextual factors associated with OUD and their contribution to sleep deficiency among patients in MAT.

This study proposes to test the delivery of a comprehensive cognitive behavioral therapy, reSET, to determine whether it can improve treatment adherence and long-term outcome among patients with opioid use disorder initiating medication-assisted treatment within a community-based"Hub and Spoke” Model of buprenorphine maintenance in central Pennsylvania. reSET (Pear Therapeutics, Inc.) is a commercially available version of the web-based Therapeutic Education System (TES) delivered as a mobile app and recently approved by the FDA as the first digital therapeutic adjunct for the treatment of substance use disorders. Through a series of interactive therapy lessons, the program teaches patients cognitive-behavioral coping skills to resist drug use and to address factors such as craving, depression, and other mood problems and relationship issues that are associated with risk of relapse. The CM component provides concrete rewards contingent on performance of key target behaviors.

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.