# Framework to Accelerate Substance Use Disorder Genetic Studies through Customizable, EHR-Based Precision Phenotyping

> **NIH NIH DP1** · VANDERBILT UNIVERSITY MEDICAL CENTER · 2024 · $525,000

## Abstract

Project Summary/Abstract
There is a critical need for accurate, efficient, and portable substance use disorder (SUD) identification
methods that support large-scale genetic studies in uncovering biological mechanisms helpful in SUD
prevention and management. The long-term goal of this work is to support genetic discovery efforts that result
in beneficial interventions for prevention and treatment of SUD. The overall objective in this proposal is to
develop and evaluate an SUD phenotyping method that allows investigators to fine-tune phenotypes for their
specific projects. Given most large-scale SUD phenotyping for genetics studies have relied on administrative
billing codes (that undercount true cases) and binary outcome labels (that induce arbitrary dichotomization),
the rationale for this project is that a system which includes a variety of data sources and generates a
probabilistic outcome along a continuum is needed. The SUD phenotyping framework will support the inclusion
of heterogenous electronic health record data types (including administrative billing codes, medication
information, and unstructured text data) and will be evaluated in multiple organizations. Pairing these SUD
phenotypes with genetic data will enhance our understanding of SUD mechanisms among individuals. That
foundational work could ultimately result in the development of polygenic risk scores and clinical decision
support systems that we could implement prospectively in clinical care. The proposed research is significant
because researchers have a pressing need for SUD phenotyping approaches that can be customized to their
research focus and available data. This proposal’s innovation lies in the creation of a “self-service” approach to
SUD phenotype development in which a research team can specify their own phenotype definitions. The
software will have a graphical user interface that makes the highest-yield rules/heuristics the easiest to use
and can therefore be used by investigators with basic scientific programming knowledge. Through the activities
outlined above, this innovation will directly accelerate genetic studies of SUD while simultaneously developing
a precision phenotyping framework that can be applied to other disease domains.

## Key facts

- **NIH application ID:** 11263104
- **Project number:** 7DP1DA056667-04
- **Recipient organization:** VANDERBILT UNIVERSITY MEDICAL CENTER
- **Principal Investigator:** Alvin Dean Jeffery
- **Activity code:** DP1 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $525,000
- **Award type:** 7
- **Project period:** 2022-09-01 → 2027-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/11263104

## Citation

> US National Institutes of Health, RePORTER application 11263104, Framework to Accelerate Substance Use Disorder Genetic Studies through Customizable, EHR-Based Precision Phenotyping (7DP1DA056667-04). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/11263104. Licensed CC0.

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