Kyle A Sullivan, David Kainer, Matthew Lane, Mikaela Cashman, J Izaak Miller, Michael R Garvin, Alice Townsend, Bryan C Quach, Caryn Willis, Peter Kruse, Nathan C Gaddis, Ravi Mathur, Olivia Corradin, Brion S Maher, Peter C Scacheri, Sandra Sanchez-Roige, Abraham A Palmer, Vanessa Troiani, Elissa J Chesler, Rachel L Kember, Henry R Kranzler, Amy C Justice, Ke Xu, Bradley E Aouizerat, Dana B Hancock, Eric O Johnson, Daniel A Jacobson
{"title":"多组学网络分析确定阿片类药物成瘾失调的神经生物学途径。","authors":"Kyle A Sullivan, David Kainer, Matthew Lane, Mikaela Cashman, J Izaak Miller, Michael R Garvin, Alice Townsend, Bryan C Quach, Caryn Willis, Peter Kruse, Nathan C Gaddis, Ravi Mathur, Olivia Corradin, Brion S Maher, Peter C Scacheri, Sandra Sanchez-Roige, Abraham A Palmer, Vanessa Troiani, Elissa J Chesler, Rachel L Kember, Henry R Kranzler, Amy C Justice, Ke Xu, Bradley E Aouizerat, Dana B Hancock, Eric O Johnson, Daniel A Jacobson","doi":"10.1016/j.biopsych.2024.11.013","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Opioid addiction is a worldwide public health crisis. In the United States, for example, opioids cause more drug overdose deaths than any other substance. Yet, opioid addiction treatments have limited efficacy, meaning that additional treatments are needed.</p><p><strong>Methods: </strong>To help address this problem, we used network-based machine learning techniques to integrate results from genome-wide association studies (GWAS) of opioid use disorder (OUD) and problematic prescription opioid misuse with transcriptomic, proteomic, and epigenetic data from the dorsolateral prefrontal cortex (dlPFC) of opioid overdose victims and controls.</p><p><strong>Results: </strong>We identified 211 highly interrelated genes identified by GWAS or dysregulation in the dlPFC of opioid overdose victims that implicated the Akt, BDNF, and ERK 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 (SUDs) or depression.</p><p><strong>Conclusions: </strong>Our synthesis of multi-omics using a systems biology approach revealed key gene targets that could contribute to drug repurposing, genetics-informed addiction treatment, and future discovery.</p>","PeriodicalId":8918,"journal":{"name":"Biological Psychiatry","volume":" ","pages":""},"PeriodicalIF":9.6000,"publicationDate":"2024-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Multi-omic network analysis identifies dysregulated neurobiological pathways in opioid addiction.\",\"authors\":\"Kyle A Sullivan, David Kainer, Matthew Lane, Mikaela Cashman, J Izaak Miller, Michael R Garvin, Alice Townsend, Bryan C Quach, Caryn Willis, Peter Kruse, Nathan C Gaddis, Ravi Mathur, Olivia Corradin, Brion S Maher, Peter C Scacheri, Sandra Sanchez-Roige, Abraham A Palmer, Vanessa Troiani, Elissa J Chesler, Rachel L Kember, Henry R Kranzler, Amy C Justice, Ke Xu, Bradley E Aouizerat, Dana B Hancock, Eric O Johnson, Daniel A Jacobson\",\"doi\":\"10.1016/j.biopsych.2024.11.013\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Opioid addiction is a worldwide public health crisis. In the United States, for example, opioids cause more drug overdose deaths than any other substance. Yet, opioid addiction treatments have limited efficacy, meaning that additional treatments are needed.</p><p><strong>Methods: </strong>To help address this problem, we used network-based machine learning techniques to integrate results from genome-wide association studies (GWAS) of opioid use disorder (OUD) and problematic prescription opioid misuse with transcriptomic, proteomic, and epigenetic data from the dorsolateral prefrontal cortex (dlPFC) of opioid overdose victims and controls.</p><p><strong>Results: </strong>We identified 211 highly interrelated genes identified by GWAS or dysregulation in the dlPFC of opioid overdose victims that implicated the Akt, BDNF, and ERK 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 (SUDs) or depression.</p><p><strong>Conclusions: </strong>Our synthesis of multi-omics using a systems biology approach revealed key gene targets that could contribute to drug repurposing, genetics-informed addiction treatment, and future discovery.</p>\",\"PeriodicalId\":8918,\"journal\":{\"name\":\"Biological Psychiatry\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":9.6000,\"publicationDate\":\"2024-11-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Biological Psychiatry\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1016/j.biopsych.2024.11.013\",\"RegionNum\":1,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"NEUROSCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biological Psychiatry","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1016/j.biopsych.2024.11.013","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"NEUROSCIENCES","Score":null,"Total":0}
Multi-omic network analysis identifies dysregulated neurobiological pathways in opioid addiction.
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. Yet, 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 (GWAS) of opioid use disorder (OUD) and problematic prescription opioid misuse with transcriptomic, proteomic, and epigenetic data from the dorsolateral prefrontal cortex (dlPFC) of opioid overdose victims and controls.
Results: We identified 211 highly interrelated genes identified by GWAS or dysregulation in the dlPFC of opioid overdose victims that implicated the Akt, BDNF, and ERK 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 (SUDs) or depression.
Conclusions: Our synthesis of multi-omics using a systems biology approach revealed key gene targets that could contribute to drug repurposing, genetics-informed addiction treatment, and future discovery.
期刊介绍：
Biological Psychiatry is an official journal of the Society of Biological Psychiatry and was established in 1969. It is the first journal in the Biological Psychiatry family, which also includes Biological Psychiatry: Cognitive Neuroscience and Neuroimaging and Biological Psychiatry: Global Open Science. The Society's main goal is to promote excellence in scientific research and education in the fields related to the nature, causes, mechanisms, and treatments of disorders pertaining to thought, emotion, and behavior. To fulfill this mission, Biological Psychiatry publishes peer-reviewed, rapid-publication articles that present new findings from original basic, translational, and clinical mechanistic research, ultimately advancing our understanding of psychiatric disorders and their treatment. The journal also encourages the submission of reviews and commentaries on current research and topics of interest.
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