Julie D. White , Melyssa S. Minto , Caryn Willis , Bryan C. Quach , Shizhong Han , Ran Tao , Amy Deep-Soboslay , Lea Zillich , Stephanie H. Witt , Rainer Spanagel , Anita C. Hansson , Shaunna L. Clark , Edwin J.C.G. van den Oord , Thomas M. Hyde , R. Dayne Mayfield , Bradley T. Webb , Eric O. Johnson , Joel E. Kleinman , Laura J. Bierut , Dana B. Hancock
{"title":"与酒精使用障碍相关的凹凸核和背外侧前额叶皮层 DNA 甲基化","authors":"Julie D. White , Melyssa S. Minto , Caryn Willis , Bryan C. Quach , Shizhong Han , Ran Tao , Amy Deep-Soboslay , Lea Zillich , Stephanie H. Witt , Rainer Spanagel , Anita C. Hansson , Shaunna L. Clark , Edwin J.C.G. van den Oord , Thomas M. Hyde , R. Dayne Mayfield , Bradley T. Webb , Eric O. Johnson , Joel E. Kleinman , Laura J. Bierut , Dana B. Hancock","doi":"10.1016/j.bpsgos.2024.100375","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><div>Alcohol use disorder (AUD) has a profound public health impact. However, understanding of the molecular mechanisms that underlie the development and progression of AUD remains limited. Here, we investigated AUD-associated DNA methylation changes within and across 2 addiction-relevant brain regions, the nucleus accumbens and dorsolateral prefrontal cortex.</div></div><div><h3>Methods</h3><div>Illumina HumanMethylation EPIC array data from 119 decedents (61 cases, 58 controls) were analyzed using robust linear regression with adjustment for technical and biological variables. Associations were characterized using integrative analyses of public annotation data and published genetic and epigenetic studies. We also tested for brain region–shared and brain region–specific associations using mixed-effects modeling and assessed implications of these results using public gene expression data from human brain.</div></div><div><h3>Results</h3><div>At a false discovery rate of ≤.05, we identified 105 unique AUD-associated CpGs (annotated to 120 genes) within and across brain regions. AUD-associated CpGs were enriched in histone marks that tag active promoters, and our strongest signals were specific to a single brain region. Some concordance was found between our results and those of earlier published alcohol use or dependence methylation studies. Of the 120 genes, 23 overlapped with previous genetic associations for substance use behaviors, some of which also overlapped with previous addiction-related methylation studies.</div></div><div><h3>Conclusions</h3><div>Our findings identify AUD-associated methylation signals and provide evidence of overlap with previous genetic and methylation studies. These signals may constitute predisposing genetic differences or robust methylation changes associated with AUD, although more work is needed to further disentangle the mechanisms that underlie these associations and their implications for AUD.</div></div>","PeriodicalId":72373,"journal":{"name":"Biological psychiatry global open science","volume":"4 6","pages":"Article 100375"},"PeriodicalIF":4.0000,"publicationDate":"2024-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Alcohol Use Disorder–Associated DNA Methylation in the Nucleus Accumbens and Dorsolateral Prefrontal Cortex\",\"authors\":\"Julie D. White , Melyssa S. Minto , Caryn Willis , Bryan C. Quach , Shizhong Han , Ran Tao , Amy Deep-Soboslay , Lea Zillich , Stephanie H. Witt , Rainer Spanagel , Anita C. Hansson , Shaunna L. Clark , Edwin J.C.G. van den Oord , Thomas M. Hyde , R. Dayne Mayfield , Bradley T. Webb , Eric O. Johnson , Joel E. Kleinman , Laura J. Bierut , Dana B. Hancock\",\"doi\":\"10.1016/j.bpsgos.2024.100375\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Background</h3><div>Alcohol use disorder (AUD) has a profound public health impact. However, understanding of the molecular mechanisms that underlie the development and progression of AUD remains limited. Here, we investigated AUD-associated DNA methylation changes within and across 2 addiction-relevant brain regions, the nucleus accumbens and dorsolateral prefrontal cortex.</div></div><div><h3>Methods</h3><div>Illumina HumanMethylation EPIC array data from 119 decedents (61 cases, 58 controls) were analyzed using robust linear regression with adjustment for technical and biological variables. Associations were characterized using integrative analyses of public annotation data and published genetic and epigenetic studies. We also tested for brain region–shared and brain region–specific associations using mixed-effects modeling and assessed implications of these results using public gene expression data from human brain.</div></div><div><h3>Results</h3><div>At a false discovery rate of ≤.05, we identified 105 unique AUD-associated CpGs (annotated to 120 genes) within and across brain regions. AUD-associated CpGs were enriched in histone marks that tag active promoters, and our strongest signals were specific to a single brain region. Some concordance was found between our results and those of earlier published alcohol use or dependence methylation studies. Of the 120 genes, 23 overlapped with previous genetic associations for substance use behaviors, some of which also overlapped with previous addiction-related methylation studies.</div></div><div><h3>Conclusions</h3><div>Our findings identify AUD-associated methylation signals and provide evidence of overlap with previous genetic and methylation studies. These signals may constitute predisposing genetic differences or robust methylation changes associated with AUD, although more work is needed to further disentangle the mechanisms that underlie these associations and their implications for AUD.</div></div>\",\"PeriodicalId\":72373,\"journal\":{\"name\":\"Biological psychiatry global open science\",\"volume\":\"4 6\",\"pages\":\"Article 100375\"},\"PeriodicalIF\":4.0000,\"publicationDate\":\"2024-08-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Biological psychiatry global open science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2667174324000880\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"NEUROSCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biological psychiatry global open science","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2667174324000880","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"NEUROSCIENCES","Score":null,"Total":0}
Alcohol Use Disorder–Associated DNA Methylation in the Nucleus Accumbens and Dorsolateral Prefrontal Cortex
Background
Alcohol use disorder (AUD) has a profound public health impact. However, understanding of the molecular mechanisms that underlie the development and progression of AUD remains limited. Here, we investigated AUD-associated DNA methylation changes within and across 2 addiction-relevant brain regions, the nucleus accumbens and dorsolateral prefrontal cortex.
Methods
Illumina HumanMethylation EPIC array data from 119 decedents (61 cases, 58 controls) were analyzed using robust linear regression with adjustment for technical and biological variables. Associations were characterized using integrative analyses of public annotation data and published genetic and epigenetic studies. We also tested for brain region–shared and brain region–specific associations using mixed-effects modeling and assessed implications of these results using public gene expression data from human brain.
Results
At a false discovery rate of ≤.05, we identified 105 unique AUD-associated CpGs (annotated to 120 genes) within and across brain regions. AUD-associated CpGs were enriched in histone marks that tag active promoters, and our strongest signals were specific to a single brain region. Some concordance was found between our results and those of earlier published alcohol use or dependence methylation studies. Of the 120 genes, 23 overlapped with previous genetic associations for substance use behaviors, some of which also overlapped with previous addiction-related methylation studies.
Conclusions
Our findings identify AUD-associated methylation signals and provide evidence of overlap with previous genetic and methylation studies. These signals may constitute predisposing genetic differences or robust methylation changes associated with AUD, although more work is needed to further disentangle the mechanisms that underlie these associations and their implications for AUD.