Multiomic Network Analysis Identifies Dysregulated Neurobiological Pathways in Opioid Addiction

Sullivan, Kyle A.; Kainer, David; Lane, Matthew; Cashman, Mikaela; Miller, J. Izaak; Garvin, Michael R.; Townsend, Alice; Quach, Bryan C.; Willis, Caryn; Kruse, Peter; Gaddis, Nathan C.; Mathur, Ravi; Corradin, Olivia; Maher, Brion S.; Scacheri, Peter C.; Sanchez-Roige, Sandra; Palmer, Abraham A.; Troiani, Vanessa; Chesler, Elissa J.; Kember, Rachel L.; Kranzler, Henry R.; Justice, Amy C.; Xu, Ke; Aouizerat, Bradley E.; Hancock, Dana B.; Johnson, Eric O.; Jacobson, Daniel A.

doi:10.1016/j.biopsych.2024.11.013

Multiomic Network Analysis Identifies Dysregulated Neurobiological Pathways in Opioid Addiction

Journal Article · Fri Nov 29 00:00:00 EST 2024 · Biological Psychiatry

DOI:https://doi.org/10.1016/j.biopsych.2024.11.013· OSTI ID:2538461

^[1]; Kainer, David ^[1]; Lane, Matthew ^[2]; ^[3]; Miller, J. Izaak ^[1]; ^[1]; Townsend, Alice ^[2]; Quach, Bryan C. ^[4]; Willis, Caryn ^[4]; Kruse, Peter ^[2]; Gaddis, Nathan C. ^[4]; Mathur, Ravi ^[4]; Corradin, Olivia ^[5]; Maher, Brion S. ^[6]; Scacheri, Peter C. ^[7]; Sanchez-Roige, Sandra ^[8]; Palmer, Abraham A. ^[9]; Troiani, Vanessa ^[10]; Chesler, Elissa J. ^[11]; Kember, Rachel L. ^[12] more »

Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
Univ. of Tennessee, Knoxville, TN (United States)
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States); Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
RTI International, Research Triangle Park, NC (United States)
Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)
Johns Hopkins Bloomberg School of Public Health, Baltimore, MD (United States)
Case Western Reserve Univ., Cleveland, OH (United States)
Univ. of California, San Diego, CA (United States); Vanderbilt University Medical Center, Nashville, TN (United States)
Univ. of California, San Diego, La Jolla, CA (United States)
Geisinger College of Health Sciences, Scranton, PA (United States)
The Jackson Laboratory, Bar Harbor, ME (United States)
Crescenz Veterans Affairs Medical Center, Philadelphia, PA (United States); Univ. of Pennsylvania, Philadelphia, PA (United States). Perelman School of Medicine
Crescenz Veterans Affairs Medical Center, Philadelphia, PA (United States); Univ. of Pennsylvania, Philadelphia, PA (United States)
Veterans Affairs Connecticut Healthcare System, West Haven, CT (United States); Yale University, New Haven, CT (United States)
Veterans Affairs Connecticut Healthcare System, West Haven, CT (United States); Yale Univ., New Haven, CT (United States)
New York Univ. (NYU), NY (United States)

BACKGROUND: Opioid addiction is a worldwide public health crisis. In the United States, for example, opioids cause more drug overdose deaths than any other substance. However, opioid addiction treatments have limited efficacy, meaning that additional treatments are needed. METHODS: To help address this problem, we used network-based machine learning techniques to integrate results from genome-wide association studies of opioid use disorder and problematic prescription opioid misuse with transcriptomic, proteomic, and epigenetic data from the dorsolateral prefrontal cortex of people who died of opioid overdose and control individuals. RESULTS: Here we identified 211 highly interrelated genes identified by genome-wide association studies or dysregulation in the dorsolateral prefrontal cortex of people who died of opioid overdose that implicated the Akt, BDNF (brain-derived neurotrophic factor), and ERK (extracellular signal-regulated kinase) pathways, identifying 414 drugs targeting 48 of these opioid addiction–associated genes. Some of the identified drugs are approved to treat other substance use disorders or depression. CONCLUSIONS: Our synthesis of multiomics using a systems biology approach revealed key gene targets that could contribute to drug repurposing, genetics-informed addiction treatment, and future discovery.

View Accepted Manuscript (DOE)

Research Organization:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility (OLCF)

Sponsoring Organization:: Department of Veterans Affairs; National Institutes of Health (NIH); USDOE Office of Science (SC); Veterans Health Administration

Grant/Contract Number:: AC05-00OR22725

OSTI ID:: 2538461

Journal Information:: Biological Psychiatry, Journal Name: Biological Psychiatry Journal Issue: 1 Vol. 98; ISSN 0006-3223

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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60 APPLIED LIFE SCIENCES
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