2019
DOI: 10.3390/brainsci9100280
|View full text |Cite
|
Sign up to set email alerts
|

Association of Polygenic Liability for Alcohol Dependence and EEG Connectivity in Adolescence and Young Adulthood

Abstract: Differences in the connectivity of large-scale functional brain networks among individuals with alcohol use disorders (AUD), as well as those at risk for AUD, point to dysfunctional neural communication and related cognitive impairments. In this study, we examined how polygenic risk scores (PRS), derived from a recent GWAS of DSM-IV Alcohol Dependence (AD) conducted by the Psychiatric Genomics Consortium, relate to longitudinal measures of interhemispheric and intrahemispheric EEG connectivity (alpha, theta, a… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1

Citation Types

1
19
0

Year Published

2021
2021
2024
2024

Publication Types

Select...
7
2
1

Relationship

3
7

Authors

Journals

citations
Cited by 18 publications
(20 citation statements)
references
References 68 publications
1
19
0
Order By: Relevance
“…Recently, Lai et al [67] reported that individuals with AUD had higher PRS than controls and the PRS magnitude increased as the number of DSM-5 diagnostic criteria increased. Further, PRS for alcohol dependence was found to be associated with neural connectivity [36, 157] and cognitive functions, such as verbal fluency, vocabulary, digit-symbol coding, and logical memory [158], as well as brain structure [159]. Unfortunately, PRS related to neurocognitive phenotypes, which could have improved the predictive model, were not included in the study due to a lack of neurocognitive GWAS on AA populations for calculating PRS-CSx for the study sample.…”
Section: Discussionmentioning
confidence: 99%
“…Recently, Lai et al [67] reported that individuals with AUD had higher PRS than controls and the PRS magnitude increased as the number of DSM-5 diagnostic criteria increased. Further, PRS for alcohol dependence was found to be associated with neural connectivity [36, 157] and cognitive functions, such as verbal fluency, vocabulary, digit-symbol coding, and logical memory [158], as well as brain structure [159]. Unfortunately, PRS related to neurocognitive phenotypes, which could have improved the predictive model, were not included in the study due to a lack of neurocognitive GWAS on AA populations for calculating PRS-CSx for the study sample.…”
Section: Discussionmentioning
confidence: 99%
“…Machine learning studies support the role of brain functions and structures to determine the profiles of and risk factors for alcohol misuse among adolescents and young adults (Gowin et al, 2021;Ruan et al, 2019;Whelan et al, 2014) and indicate roles for early drinking onset, family history of AUD, and stressful life events. Critically, longitudinal studies showed that childhood trauma predicts binge drinking (De Bellis et al, 2020), alcohol-related problems (Hagborg et al, 2020), disturbed brain FC (Silveira et al, 2020), and neural oscillations (Meyers et al, 2019). An underappreciated caveat in longitudinal performance testing is a learning effect, also known as the prior testing experience effect (Salthouse, 2014), which needs to be quantified in the context of change expected from developmental advancement (Sullivan et al, 2017).…”
Section: Brain Structural and Functional Declines Related To Hazardou...mentioning
confidence: 99%
“…In normal population studies, PGS for alcohol dependence has been found to be negatively associated with cognitive function [3,4]. No evidence was found for a causal association of cognitive impairment for rs1229984 in Alcohol Dehydrogenase 1B (ADH1B) [5,6] ( Almeida et al 2014, Kumari M et al 2014 or rs671 in Alcohol Dehydrogenase 2 (ALDH2) [7] in the normal population [8].…”
Section: Introductionmentioning
confidence: 99%