Projects and Grants

This pilot project aims to lay the foundation for a NIDA Center of Excellence with a focus on advancing precision medicine strategies for substance use disorders. The project will focus on gathering initial data and establishing collaborations across newly integrated university centers and investigators at Rutgers, recruited as part of a strategic expansion in addiction and biomedical research over the last five years. Bringing together expertise in neuroscience, genetics, neuroimaging, computational psychiatry, digital phenotyping, and clinical research, this project aims to create a holistic approach to develop targeted treatments and interventions for substance use disorders. The specific aims are as follows:

1. Establish the Rutgers addiction research registry and begin patient enrollment
2. Collect phenotypic, genotypic, neuroimaging, digital phenotypes, and treatment outcome data from a subset of patients enrolled in the registry to serve as pilot data 
3. Establish processes for integrating human project results with model organism work 
4. Establish processes for data management/sharing, and integrative data analysis
5. Establish a history of regular meetings and collaboration among the leadership team 
6. Identify early career investigators whose research aligns with overarching center aims 

This administrative supplement, submitted in response to NOT-DA-24-003 Rapid Translation of Substance Use and Addiction Epidemiology and Prevention Intervention Research, proposes to translate the findings emerging from the parent project R01DA050721 “Using the genetic architecture of substance use disorders to advance gene identification and understanding of pathways of risk” to study the application of our genetic epidemiological findings as a novel prevention intervention to reduce risky patterns of substance use among emerging adults.

The parent project has two complementary goals:

(1) to advance discovery of genes involved in substance use disorders using new multivariate genomic techniques, and

(2) to characterize the risk associated with identified variants in diverse longitudinal samples, across development, and in conjunction with the environment.

We have made tremendous advances in gene identification since the initiation of the parent R01, with the results from our most recent genome-wide association study accounting for ~10% of the variance in substance use and related outcomes in independent samples. We have integrated the resulting polygenic scores with epidemiological information on behavioral and environmental risk factors, using data from multiple diverse longitudinal cohorts, to create individual risk estimates, finding that the combination of epidemiological risk information and genetic data meaningfully contribute to predicting who is at elevated risk of substance use disorders in emerging adulthood. The rationale for this line of work is that it will lay the foundation for personalized medicine, with the provision of personalized risk information helping prevent the development of problems and/or allow for earlier intervention.

With administrative funds from this supplement, we propose to:

Aim 1: create a new prevention/intervention program, consisting of an on-line platform for individuals to receive their personalized risk estimates for addiction risk, generated by integrating information about their genetic, behavioral, and environmental risk factors based on research from the parent grant, followed by information about how to reduce risk, developed with the addition of new collaborators with expertise in behavior change; and

Aim 2: conduct a small RCT (N=400) with emerging adults (18-25yrs), who are entering the high-risk period for escalation of risky substance use and the development of problems, to test whether completion of the personalized feedback program is associated with reductions in risky substance use. This project represents a critical first step in translating genetic epidemiological findings to prevention intervention.

 

Link to NIH RePORT: 3R01DA050721 (Dick)

This competing continuation of our original Finnish Twin Studies R01 will expand our earlier work on gene-environment interplay in adolescence and young adulthood to characterize alcohol misuse into early midlife; to test hypotheses about risk and protective factors (accumulated across development) associated with trajectories of alcohol misuse from adolescence through early midlife; to examine the health-related correlates of these trajectories; and to translate and disseminate our findings to the public.

New data from older Finnish twin cohorts that suggest early midlife (ages 30-40) drinking is a far more robust predictor of long-term later-life drinking and consequences than drinking measured earlier in development. Our project will use data from two longitudinal population-based Finnish twin studies to understand the correlates and consequences of alcohol misuse from adolescence through early midlife:

• FinnTwin12 (FT12) consists of ~5200 Finnish twin individuals (50% female) who were assessed at multiple time points beginning in early adolescence (ages 12, 14, 17, and 22) to which we will add an early midlife (mid 30s) assessment as part of this proposal.
• FinnTwin16 (FT16) includes another ~5500 individuals (52% female) initially recruited in middle adolescence who were assessed at ages 16, 17, 18, 25, and 35. In parallel to our data collection with the FT12 sample, we will analyze existing data from FT16.

This proposal is the next step in a program of research that has played a central role in delineating how genetic and environmental risk and protective factors impact the development of substance use and related behaviors.

Link to NIH RePORT: R01AA015416 (Salvatore / Dick)

This project has two complementary goals:

1. to advance discovery of genes involved in substance use disorders using new multivariate genomic techniques, and
2. to characterize the risk associated with identified variants in diverse longitudinal samples in order to understand the spectrum of phenotypes associated with identified variants, across development, and in conjunction with the environment.

Each of these areas represents critical steps in using genetic data to improve prevention, intervention, and treatment for substance use disorders (SUDs), and will lay the foundation as we move into an era of personalized medicine.

This project will:

• apply new multivariate genetic methods to capitalize on genetic sharing between substance use phenotypes and related traits in order to boost power to detect common variants associated with substance use outcomes, and to characterize the latent pathways by which genetic variants operate.
• map these behavioral phenotypes associated with the genetic risk scores across adolescence and emerging adulthood
• test for pathways of risk specific to sex and racial/ethnic background, and
• test for moderation of genetic risk by key environmental factors

Jointly, these analyses will advance our understanding of how genetic variation contributes to risk for substance use disorders.

This project is one of many that supports the Externalizing Consortium, launched in 2017 by Danielle Dick, Ph.D., in partnership with Philipp Koellinger, Ph.D. The Externalizing Consortium is focused on multivariate analyses aimed at gene identification for externalizing outcomes, and characterizing the risk associated with identified variants across development and in conjunction with the environment

Link to NIH Report: R01DA050721 (Dick)

The VCU Alcohol Research Center (ARC) is a collaborative effort aimed at identifying genes and gene networks associated with ethanol-related phenotypes by cross-species validation. ARC researchers work with data collected from humans, mice, rats, C. Elegans, and drosophila. TPG Lab Director, Dr. Dick leads Project 4 of the ARC, which is using multivariate genomic analyses to advance gene identification for alcohol use outcomes, with bidirectional interactions with the model organism projects: genes identified in Project 4 are advanced for further study in the model organisms to characterize mechanism, and genes identified in model organism studies are examined across diverse human datasets in order to characterize behavioral effects in humans.

Link to NIH RePORT: P50AA022537 (Dick)

The Collaborative Study on the Genetics of Alcoholism (COGA) is a tightly integrated and interdisciplinary project that involves participation of investigators from multiple sites spanning a broad range of expertise. The goals of COGA are to identify and characterize genes in which variations confer risk for, or protection from, the development of Alcohol Use Disorders (AUDs) and related phenotypes; to understand the mechanisms by which these variants work at the molecular and cellular level; and to understand how genetic, environmental, and neurocognitive factors interact to influence the developmental trajectories of alcohol use and AUDs through an ongoing prospective study of at-risk individuals. COGA has assembled a unique sample of large, ethnically diverse families densely affected by AUDs and a set of comparison families, with rich phenotypic assessments in multiple domains: clinical, behavioral, neurophysiological, neuropsychological and environmental.

The study has three inter-dependent projects and three essential cores.

The three projects are each focused on different aspects of COGA’s core aims:

• Genetic and Functional Studies of Alcohol Use Disorders and Related Phenotypes – Using a range of alcohol-related phenotypes, identifies variants across allelic spectrum and studies their mechanisms of action.
• Prospective Study of Genetic and Environmental Influences on Alcohol Use and Disorders Across Development – Longitudinally studies genetic and environmental influences and their interaction on development of AUDs during adolescence and emerging adulthood.
• Neurophysiological Phenotypes, Brain Maturation and Development of Alcohol Use and Related Disorders – Identifies genes related to novel neurocognitive phenotypes and their effects on trajectories of neurocognitive development and AUDs.

The cores (Administrative Core, Data Management Core, and NIAAA/COGA Sharing Repository Core (NCSR)) provide critical support to each project, ensuring that key cross-study and cross site functions are centralized.

Through tight coordination of this interdisciplinary study, we will go from identifying genes, in which variants affect risk for AUDs and related phenotypes to understanding how they act at multiple levels, from molecular and cellular, to behavioral, neurophysiological, cognitive phenotypic, as a function of development. The delineation of the pathways and genes contributing to alcohol use and AUDs will impact treatment and prevention of AUDs in those at greatest risk.

Other sites (PIs): University of Connecticut (V. Hesselbrock); Indiana University (H.J. Edenberg, J. Nurnberger Jr., T. Foroud); University of Iowa (S. Kuperman, J. Kramer); SUNY Downstate (B. Porjesz); Washington University in St. Louis (L. Bierut, A. Agrawal, J. Rice, K. Bucholz); University of California at San Diego (M. Schuckit); Rutgers University (J. Tischfield, D. Dick); University of Texas Medical Center in San Antonio (L. Almasy); Mount Sinai School of Medicine (A. Goate); Howard University (R. Taylor).

Link to NIH RePORT:  U10AA008401 (Porjesz)

Youth that engage in antisocial behavior (i.e., behaviors that violate social norms and the rights of others) exact a costly psychological and financial toll on their families, peers, and community. While non-compliance and antisocial behavior are leading causes of treatment referral, conduct disorder (CD) is acutely understudied, resulting in treatments that have limited efficacy and generalizability. Research on the mechanistic processes that uniquely contribute to antisocial behavior are needed to inform our understanding of etiology, risk and protective factors, and provide targets for prevention and treatment. Socioemotional functioning (SEF)–the ability to appropriately orient to, process, and respond to emotional cues–is a collection of psychological processes that distinguishes antisocial behavior from other externalizing disorders. While SEF processes can promote prosocial emotions (e.g., empathy) and behavior (e.g., rule conformity), SEF dysfunction contributes to a callous-unemotional and aggressive personality style, making it easier to hurt others. Known neurobiological correlates implicate structural, functional, and connectomic deficits in regions of the brain involved in emotional response. However, much of the small research literature on SEF has been limited by linking psychometric measures that target extreme deficits in SEF to brain responses in small, clinically referred samples using extreme group designs, which have failed to replicate in representative samples. In this highly innovative project, using data from the Adolescent Brain Cognitive Development (ABCD) study and ABCD-Social Development (ABCD-SD) sub-study, we will first improve the measurement of SEF using advanced statistical methods to develop a dimensional index psychometric of SEF and then evaluate this index for measurement bias related to race and/or sex, examining how bias may impact associations with criterion variables. We will also use a multivariate network neuroscience approach to distill key components across multimodal (structural, resting state, functional) neuroimaging data to produce a reliable neural index of SEF. Using these new psychometric and neural indices of SEF we will examine associations with delinquency, comorbid psychopathology, and social functioning, as well as the interplay with known environmental risk and protective factors (e.g., parent-child relationship, victimization) for antisocial behavior. Consistent with NIMH Strategic Objective 2.2, (to “identify clinically useful biomarkers and behavioral indicators that predict change across the trajectory of illness”), completion of this project will yield reliable and unbiased psychometric and multimodal neural indicators of early SEF in a large, diverse sample, which can be used to determine individual risk factors for antisocial behavior both cross-sectionally and in future waves of data collection.

Link to NIH RePORT: R21MH126130 (Brislin)