# The neurobiological mechanisms of untreated pain and depression to relapse risk in substance dependence

> **NIH VA IK2** · VETERANS ADMIN PALO ALTO HEALTH CARE SYS · 2021 · —

## Abstract

It is well known that alcohol use disorder (AUD) is highly co-morbid with both depression and
chronic pain. Chronic pain and depression are particularly high and debilitating in the veteran
population. The majority of research in AUD has been in samples of participants without co-
occurring disorders since research typically excludes common co-morbidities from recruitment.
Therefore, we would benefit enormously from studies where we include these co-morbidities,
examine them, and build a neural signature (constellation of neuroimaging and clinical
symptoms) of chronic pain and depression in AUD as a model to test with advanced machine
learning algorithms. What is currently unknown is the neurobiological and neurochemical
patterns that form a brain signature (the neural circuitry) of depression and of chronic pain within
AUD. This study will use multi-modal neuroimaging data and behavioral symptomology
measures to attain the overall objective of this proposal, which is to delineate the separate and
overlapping contributions of co-morbid depression and chronic pain brain signatures on the
neural signature of AUD. We will use advanced computational modeling algorithms (machine
learning) of clinical and multi-modality neuroimaging data. Results from this proposal will
provide a deeper understanding of AUD neurobiology and will identify a pattern of neural
circuitry that signifies depression versus chronic pain in AUD neurobiology as the scientific basis
for individualized precision medicine treatment approaches that target AUD co-morbidities of
depression and chronic pain.
My overarching career goal as an independent investigator is to build a multidisciplinary
research program on neuroimaging of substance use disorders. I will achieve this by clarifying
brain mechanisms contributing to co-occurring symptomology (depression, chronic pain) that
often presents in substance use disorders and particularly high and debilitating in Veterans. A
better understanding of to what extent behavior and co-morbid symptomatology relates to brain
neurobiology could facilitate more accurate predictive modeling of individual treatment response
and relapse using multi-modal imaging and advanced computational analyses methods.
My short-term research goals for this career mentored proposal are to identify the separate
and overlapping neural mechanisms of co-morbidities (depression and chronic pain) prevalent
in alcohol use disorders, and relate these mechanisms to behavior and relapse risk in Veterans.
These goals will be accomplished using state-of-the art multi-modal neuroimaging techniques
(whole-brain magnetic resonance (MR) spectroscopic imaging, resting state functional MR
imaging) which will be directly related to clinical/behavioral measures and self-report
questionnaires of depression and pain, combined with the use of advanced computational
analysis methods such as machine learning techniques of neuroimaging and clinical measures.

## Key facts

- **NIH application ID:** 10131579
- **Project number:** 5IK2CX001914-02
- **Recipient organization:** VETERANS ADMIN PALO ALTO HEALTH CARE SYS
- **Principal Investigator:** Donna Murray
- **Activity code:** IK2 (R01, R21, SBIR, etc.)
- **Funding institute:** VA
- **Fiscal year:** 2021
- **Award amount:** —
- **Award type:** 5
- **Project period:** 2020-04-01 → 2025-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10131579

## Citation

> US National Institutes of Health, RePORTER application 10131579, The neurobiological mechanisms of untreated pain and depression to relapse risk in substance dependence (5IK2CX001914-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10131579. Licensed CC0.

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