# Leveraging complementary big data methods and patient intervention designs to optimize neural markers of adolescent cannabis use

> **NIH NIH K23** · UNIVERSITY OF MINNESOTA · 2024 · $195,542

## Abstract

ABSTRACT/PROJECT SUMMARY
Cannabis initiation during adolescence confers four-fold greater risk for cannabis use disorder (CUD) than
initiation in adulthood and is associated with increased risk for negative psychiatric outcomes. No effective
pharmacologic treatment exists for adolescent cannabis use or CUD, and most adolescents do not achieve
sustained abstinence with psychosocial interventions. Functional MRI (fMRI) holds promise for identifying new
intervention targets and/or clarifying mechanisms of existing treatments but has yet to lead to clinical translation.
New, large-scale neuroimaging data and complementary patient intervention designs with precision
neuroimaging can begin to address remaining questions on the cause vs. effect between neural markers and
cannabis use, the extent to which putative neural markers of cannabis use instead reflect psychiatric, familial,
and/or social determinants of substance use disorders (SUDs), and whether neural markers normalize with
abstinence. Through this 4-year K23 award, I will build upon my existing skillset in developmental neuroscience
and big data neuroimaging with new training in addiction phenotyping in population studies (e.g., Adolescent
Brain Cognitive Development [ABCD] study) and mentored implementation of complementary precision
neuroimaging approaches within patient intervention designs for adolescents with CUD. The proposed research
aims will (1) utilize existing ABCD Study data to validate known and identify new functional MRI markers of
cannabis use initiation and (2) leverage a precision neuroimaging study within a CUD patient intervention design
to test the modifiability of functional MRI markers of cannabis use during the transition from regular use to
abstinence. Matched neuroimaging protocols, out-of-sample validation, design approaches to increase reliability,
and high frequency scanning in the precision neuroimaging study (3 scans over 6 weeks in adolescents with
CUD randomized to cannabis abstinence (n=24) or cannabis monitoring (n=20), and matched controls (n=20))
provide key innovations towards rigor and reproducibility. With these methods, we will test the overarching
hypothesis that hyperfunction of fronto-striatal reward circuitry is both a trait-level risk-factor and modifiable
consequence of adolescent cannabis use. Recognizing the need for both neural and phenotypic specificity, we
will compare hypothesis-driven, fronto-striatal circuit markers to data-driven, whole-brain effects and also
examine the potential moderating role of psychiatric, environmental, and social determinants of SUD. Through
these scientific aims, associated training goals, and guidance from an exceptional multidisciplinary mentorship
team, I will gain the necessary skills to address the current methodological issues facing my field and contribute
to improved translational research on the neurodevelopment of SUDs. Complementary skillsets in large-scale
neuroimaging and clinically relevant, patien...

## Key facts

- **NIH application ID:** 10916449
- **Project number:** 5K23DA057486-02
- **Recipient organization:** UNIVERSITY OF MINNESOTA
- **Principal Investigator:** Brenden Craig Tervo-Clemmens
- **Activity code:** K23 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $195,542
- **Award type:** 5
- **Project period:** 2023-09-01 → 2027-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10916449

## Citation

> US National Institutes of Health, RePORTER application 10916449, Leveraging complementary big data methods and patient intervention designs to optimize neural markers of adolescent cannabis use (5K23DA057486-02). Retrieved via AI Analytics 2026-05-28 from https://api.ai-analytics.org/grant/nih/10916449. Licensed CC0.

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