Predicting alcohol-related memory problems in older adults: A machine learning study with multi-domain features

Author:

Kamarajan ChellaORCID,Pandey Ashwini K.,Chorlian David B.ORCID,Meyers Jacquelyn L.ORCID,Kinreich SivanORCID,Pandey GayathriORCID,Subbie-Saenz de Viteri StaceyORCID,Zhang Jian,Kuang Weipeng,Barr Peter B.ORCID,Aliev FazilORCID,Anokhin Andrey P.ORCID,Plawecki Martin H.ORCID,Kuperman SamuelORCID,Almasy LauraORCID,Merikangas AlisonORCID,Brislin Sarah J.ORCID,Bauer LanceORCID,Hesselbrock VictorORCID,Chan GraceORCID,Kramer John,Lai DongbingORCID,Hartz SarahORCID,Bierut Laura J.ORCID,McCutcheon Vivia V.ORCID,Bucholz Kathleen K.ORCID,Dick Danielle M.ORCID,Schuckit Marc A.ORCID,Edenberg Howard J.ORCID,Porjesz BerniceORCID

Abstract

AbstractMemory problems are common among older adults with a history of alcohol use disorder (AUD). Employing a machine learning framework, the current study investigates the use of multi-domain features to classify individuals with and without alcohol-induced memory problems. A group of 94 individuals (ages 50-81 years) with alcohol-induced memory problems (Memorygroup) were compared with a matchedControlgroup who did not have memory problems. The Random Forests model identified specific features from each domain that contributed to the classification of Memory vs. Control group (AUC=88.29%). Specifically, individuals from the Memory group manifested a predominant pattern of hyperconnectivity across the default mode network regions except some connections involving anterior cingulate cortex which were predominantly hypoconnected. Other significant contributing features were (i) polygenic risk scores for AUD, (ii) alcohol consumption and related health consequences during the past 5 years, such as health problems, past negative experiences, withdrawal symptoms, and the largest number of drinks in a day during the past 12 months, and (iii) elevated neuroticism and increased harm avoidance, and fewer positive “uplift” life events. At the neural systems level, hyperconnectivity across the default mode network regions, including the connections across the hippocampal hub regions, in individuals with memory problems may indicate dysregulation in neural information processing. Overall, the study outlines the importance of utilizing multidomain features, consisting of resting-state brain connectivity collected ∼18 years ago, together with personality, life experiences, polygenic risk, and alcohol consumption and related consequences, to predict alcohol-related memory problems that arise in later life.

Publisher

Cold Spring Harbor Laboratory

Reference168 articles.

1. Myths about the treatment of addiction

2. Neurocircuitry of alcohol addiction

3. Oscar-Berman M (2000) Neuropsychological vulnerabilities in chronic alcoholism. In: Noronha A , Eckardt MJ , Warren K (eds.): Review of NIAAA’s Neuroscience and Behavioral Research Portfolio. National Institute on Alcohol Abuse and Alcoholism (NIAAA) Research Monograph No. 34, NIAAA, Bethesda, MD, pp. 437–471. https://ia800209.us.archive.org/5/items/reviewofniaaasne00noro/reviewofniaaasne00noro.pdf

4. Genuine Episodic Memory Deficits and Executive Dysfunctions in Alcoholic Subjects Early in Abstinence

5. The contribution of executive functions deficits to impaired episodic memory in individuals with alcoholism

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3