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An integrated multimodal model of alcohol use disorder generated by data-driven causal discovery analysis
Alcohol use disorder (AUD) has high prevalence and adverse societal impacts, but our understanding of the factors driving AUD is hampered by a lack of studies that describe the complex neurobehavioral mechanisms driving AUD. We analyzed causal pathways to AUD severity using Causal Discovery Analysis...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8012376/ https://www.ncbi.nlm.nih.gov/pubmed/33790384 http://dx.doi.org/10.1038/s42003-021-01955-z |
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author | Rawls, Eric Kummerfeld, Erich Zilverstand, Anna |
author_facet | Rawls, Eric Kummerfeld, Erich Zilverstand, Anna |
author_sort | Rawls, Eric |
collection | PubMed |
description | Alcohol use disorder (AUD) has high prevalence and adverse societal impacts, but our understanding of the factors driving AUD is hampered by a lack of studies that describe the complex neurobehavioral mechanisms driving AUD. We analyzed causal pathways to AUD severity using Causal Discovery Analysis (CDA) with data from the Human Connectome Project (HCP; n = 926 [54% female], 22% AUD [37% female]). We applied exploratory factor analysis to parse the wide HCP phenotypic space (100 measures) into 18 underlying domains, and we assessed functional connectivity within 12 resting-state brain networks. We then employed data-driven CDA to generate a causal model relating phenotypic factors, fMRI network connectivity, and AUD symptom severity, which highlighted a limited set of causes of AUD. The model proposed a hierarchy with causal influence propagating from brain connectivity to cognition (fluid/crystalized cognition, language/math ability, & working memory) to social (agreeableness/social support) to affective/psychiatric function (negative affect, low conscientiousness/attention, externalizing symptoms) and ultimately AUD severity. Our data-driven model confirmed hypothesized influences of cognitive and affective factors on AUD, while underscoring that addiction models need to be expanded to highlight the importance of social factors, amongst others. |
format | Online Article Text |
id | pubmed-8012376 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-80123762021-04-16 An integrated multimodal model of alcohol use disorder generated by data-driven causal discovery analysis Rawls, Eric Kummerfeld, Erich Zilverstand, Anna Commun Biol Article Alcohol use disorder (AUD) has high prevalence and adverse societal impacts, but our understanding of the factors driving AUD is hampered by a lack of studies that describe the complex neurobehavioral mechanisms driving AUD. We analyzed causal pathways to AUD severity using Causal Discovery Analysis (CDA) with data from the Human Connectome Project (HCP; n = 926 [54% female], 22% AUD [37% female]). We applied exploratory factor analysis to parse the wide HCP phenotypic space (100 measures) into 18 underlying domains, and we assessed functional connectivity within 12 resting-state brain networks. We then employed data-driven CDA to generate a causal model relating phenotypic factors, fMRI network connectivity, and AUD symptom severity, which highlighted a limited set of causes of AUD. The model proposed a hierarchy with causal influence propagating from brain connectivity to cognition (fluid/crystalized cognition, language/math ability, & working memory) to social (agreeableness/social support) to affective/psychiatric function (negative affect, low conscientiousness/attention, externalizing symptoms) and ultimately AUD severity. Our data-driven model confirmed hypothesized influences of cognitive and affective factors on AUD, while underscoring that addiction models need to be expanded to highlight the importance of social factors, amongst others. Nature Publishing Group UK 2021-03-31 /pmc/articles/PMC8012376/ /pubmed/33790384 http://dx.doi.org/10.1038/s42003-021-01955-z Text en © The Author(s) 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Rawls, Eric Kummerfeld, Erich Zilverstand, Anna An integrated multimodal model of alcohol use disorder generated by data-driven causal discovery analysis |
title | An integrated multimodal model of alcohol use disorder generated by data-driven causal discovery analysis |
title_full | An integrated multimodal model of alcohol use disorder generated by data-driven causal discovery analysis |
title_fullStr | An integrated multimodal model of alcohol use disorder generated by data-driven causal discovery analysis |
title_full_unstemmed | An integrated multimodal model of alcohol use disorder generated by data-driven causal discovery analysis |
title_short | An integrated multimodal model of alcohol use disorder generated by data-driven causal discovery analysis |
title_sort | integrated multimodal model of alcohol use disorder generated by data-driven causal discovery analysis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8012376/ https://www.ncbi.nlm.nih.gov/pubmed/33790384 http://dx.doi.org/10.1038/s42003-021-01955-z |
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