Human Imaging Studies of Brain Circuitry Disrupted by Alcoholism

Sullivan, Edith V.; Pfefferbaum, Adolf

doi:10.1016/b978-0-12-405941-2.00008-0

Cited by 4 publications

(7 citation statements)

References 204 publications

(237 reference statements)

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“…In fact, different studies have shown that semen parameters may be affected by various lifestyles, advancements in technology, environmental pollution (Boeri et al, 2019), alcohol intake, smoking (Amor et al, 2021; Hammadeh et al, 2010; Jensen, Gottschau, et al, 2014), and psychological stress (Barazani et al, 2014; Rakhit et al, 2013; Sullivan & Pfefferbaum, 2014). Obesity and dietary factors are also keys and important factors, as reported earlier (Afeiche et al, 2013; Ying Li et al, 2011; Mendiola et al, 2009).…”

Section: Discussionmentioning

confidence: 99%

Impact of heavy alcohol consumption and cigarette smoking on sperm DNA integrity

et al. 2022

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The purposes of the presents study were to investigate the impact of alcohol consumption and cigarette smoking on semen parameters and sperm DNA quality, as well as to determine whether tobacco smoking, or alcohol consumption causes more deterioration of sperm quality. Two hundred and eleven semen samples of men were included in this study. Four groups were studied: heavy smokers (N = 48), heavy drinkers (N = 52), non‐smokers (n = 70), and non‐drinkers (n = 41). Semen parameters were determined according to WHO guidelines, protamine deficiency assessed by chromomycin (CMA3) staining, and sperm DNA fragmentation (sDF) evaluated by TUNEL assay. Sperm parameters were significantly higher in non‐smokers versus smokers and in non‐drinkers versus drinkers (p < 0.005). However, protamine deficiency and sDF were significantly lower in non‐smokers versus smokers and in non‐drinkers versus drinkers (p < 0.0001). No significant difference in the semen analysis parameters was observed between heavy smokers and heavy drinkers (semen volume: 3.20 ± 1.43 vs. 2.81 ± 1.56 ml, semen count: 65.75 ± 31.32 vs. 53.51 ± 32.67 mill/ml, total motility: 24.27 ± 8.18 vs. 23.75 ± 1.75%, sperm vitality: 36.15 ± 18.57 vs. 34.62 ± 16.65%, functional integrity: 41.56 ± 18.57 vs. 45.96 ± 17.98% and the morphologically normal spermatozoa: 28.77 ± 11.82 vs. 27.06 ± 13.13%, respectively). However, protamine deficiency was significantly higher among drinkers than smokers (37.03 ± 9.75 vs. 33.27 ± 8.56%, p = 0.020). The sDF was also significantly higher among drinkers than smokers (22.37 ± 7.60 vs. 15.55 ± 3.33%, p < 0.0001). Thus, cigarette smoking, and heavy alcohol intake can deteriorate sperm quality. However, alcohol consumption deteriorates sperm maturity and damages DNA integrity at significantly higher rates than cigarette smoking.

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Section: Discussionmentioning

confidence: 99%

Impact of heavy alcohol consumption and cigarette smoking on sperm DNA integrity

et al. 2022

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“…Recent fMRI studies have reported restricted PCC connectivity with right medial frontal gyrus during resting state [26] as well as cue-elicited prefrontal hypoactivation in abstinent AUD individuals [146]. These findings suggest that hypoconnectivity of the prefrontal sub-network may indicate a fractured prefrontal network and associated dysfunction in executive functioning and reward/affective processing in AUD individuals [20,147].…”

Section: Hypoconnectivity Of Prefrontal Nodes In Audmentioning

confidence: 89%

Random Forest Classification of Alcohol Use Disorder Using EEG Source Functional Connectivity, Neuropsychological Functioning, and Impulsivity Measures

Kamarajan

Ardekani

Pandey

et al. 2020

Behavioral Sciences

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Individuals with alcohol use disorder (AUD) manifest a variety of impairments that can be attributed to alterations in specific brain networks. The current study aims to identify features of EEG-based functional connectivity, neuropsychological performance, and impulsivity that can classify individuals with AUD (N = 30) from unaffected controls (CTL, N = 30) using random forest classification. The features included were: (i) EEG source functional connectivity (FC) of the default mode network (DMN) derived using eLORETA algorithm, (ii) neuropsychological scores from the Tower of London test (TOLT) and the visual span test (VST), and (iii) impulsivity factors from the Barratt impulsiveness scale (BIS). The random forest model achieved a classification accuracy of 80% and identified 29 FC connections (among 66 connections per frequency band), 3 neuropsychological variables from VST (total number of correctly performed trials in forward and backward sequences and average time for correct trials in forward sequence) and all four impulsivity scores (motor, non-planning, attentional, and total) as significantly contributing to classifying individuals as either AUD or CTL. Although there was a significant age difference between the groups, most of the top variables that contributed to the classification were not significantly correlated with age. The AUD group showed a predominant pattern of hyperconnectivity among 25 of 29 significant connections, indicating aberrant network functioning during resting state suggestive of neural hyperexcitability and impulsivity. Further, parahippocampal hyperconnectivity with other DMN regions was identified as a major hub region dysregulated in AUD (13 connections overall), possibly due to neural damage from chronic drinking, which may give rise to cognitive impairments, including memory deficits and blackouts. Furthermore, hypoconnectivity observed in four connections (prefrontal nodes connecting posterior right-hemispheric regions) may indicate a weaker or fractured prefrontal connectivity with other regions, which may be related to impaired higher cognitive functions. The AUD group also showed poorer memory performance on the VST task and increased impulsivity in all factors compared to controls. Features from all three domains had significant associations with one another. These results indicate that dysregulated neural connectivity across the DMN regions, especially relating to hyperconnected parahippocampal hub as well as hypoconnected prefrontal hub, may potentially

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“…This rs-fMRI connectivity analysis has been combined with a MEMRI activity analysis seeking to address the question of how brain network homeostatic mechanisms arise in the onset of alcohol dependency. Identification of rs-FC alterations between RSNs proves that disruption of any brain region can disturb functions in distantly related brain areas [9] and MEMRI findings reveal behavioral aspects.…”

Section: Discussionmentioning

confidence: 97%

“…Alcoholism affects some brain networks but leaves others practically intact, becoming alternative neural pathways for that function. Fortunately, neural repair is possible with prolonged abstinence [9].…”

Section: Chapter 2 2 Effects Of Alcohol Use Disorders On the Brainmentioning

confidence: 99%

“…This century, neuroimaging techniques applied to fMRI, especially to rs-fMRI, have made a breakthrough in revealing functional brain alterations driven by excessive alcohol consumption [9,49]. Rs-fMRI is a powerful tool to measure spontaneous low-frequency fluctuations in BOLD signals and find spatially distributed networks with synchronous fluctuations at rest, i.e.…”

Section: Introductionmentioning

confidence: 99%

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Characterizing functional and structural brain alterations driven by chronic alcohol drinking: a resting-state fMRI connectivity and voxel-based morphometry analysis

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Human Imaging Studies of Brain Circuitry Disrupted by Alcoholism

Cited by 4 publications

References 204 publications

Impact of heavy alcohol consumption and cigarette smoking on sperm DNA integrity

Impact of heavy alcohol consumption and cigarette smoking on sperm DNA integrity

Random Forest Classification of Alcohol Use Disorder Using EEG Source Functional Connectivity, Neuropsychological Functioning, and Impulsivity Measures

Characterizing functional and structural brain alterations driven by chronic alcohol drinking: a resting-state fMRI connectivity and voxel-based morphometry analysis

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