Clinical correlates of quantitative EEG alterations in alcoholic patients

Coutin-Churchman, Pedro; Moreno, Rocío Segovia; Añez, Yelitza; Vergara, F

doi:10.1016/j.clinph.2005.12.021

Cited by 74 publications

(67 citation statements)

References 33 publications

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“…EEG also has moderate predictive value for personality variation and psychiatric disease including depression (7), bipolar disorder (8), attention-deficit/hyperactivity disorder (9), and obsessive-compulsive disorder (10). Increased β power is associated with both alcoholism and family history of alcoholism (11,12), θ power is altered in alcoholics (13)(14)(15), and reduced α power has been associated with a family history of alcoholism and with alcoholism with comorbid anxiety disorders (16,17). However, the EEG is not clinically useful for diagnosis of any specific psychiatric disorder.…”

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confidence: 99%

Genome-wide association identifies candidate genes that influence the human electroencephalogram

Hodgkinson

Enoch

Srivastava

et al. 2010

Proc. Natl. Acad. Sci. U.S.A.

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Complex psychiatric disorders are resistant to whole-genome analysis due to genetic and etiological heterogeneity. Variation in resting electroencephalogram (EEG) is associated with common, complex psychiatric diseases including alcoholism, schizophrenia, and anxiety disorders, although not diagnostic for any of them. EEG traits for an individual are stable, variable between individuals, and moderately to highly heritable. Such intermediate phenotypes appear to be closer to underlying molecular processes than are clinical symptoms, and represent an alternative approach for the identification of genetic variation that underlies complex psychiatric disorders. We performed a whole-genome association study on alpha (α), beta (β), and theta (θ) EEG power in a Native American cohort of 322 individuals to take advantage of the genetic and environmental homogeneity of this population isolate. We identified three genes (SGIP1, ST6GALNAC3, and UGDH) with nominal association to variability of θ or α power. SGIP1 was estimated to account for 8.8% of variance in θ power, and this association was replicated in US Caucasians, where it accounted for 3.5% of the variance. Bayesian analysis of prior probability of association based upon earlier linkage to chromosome 1 and enrichment for vesicle-related transport proteins indicates that the association of SGIP1 with θ power is genuine. We also found association of SGIP1 with alcoholism, an effect that may be mediated via the same brain mechanisms accessed by θ EEG, and which also provides validation of the use of EEG as an endophenotype for alcoholism.alcoholism | electroencephalogram | endophenotype | genetics | whole-genome association G enetic studies of behavior and psychiatric disorders are hampered by etiologic heterogeneity of these complex phenotypes. Addiction vulnerability arises from both internalizing (emotional) and externalizing (dyscontrol) behavioral dimensions (1), and both of these broad aspects of behavior are strongly influenced by early life trauma and other gene/environment interactions (2). Etiologic heterogeneity dilutes power to detect genetic effects, and is a reason for failures to detect and replicate genome-wide associations (GWAS) in complex disorders. Increasing sample size does not remove underlying heterogeneity and can introduce additional confounds. In neuropsychiatry, these considerations have led to the use of intermediate phenotypes (or endophenotypes) that are heritable, relevant to disease, and have good measurement properties and assay variation more closely related to gene function (3) as surrogates to probe the underlying biology of complex disorders.

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confidence: 99%

Genome-wide association identifies candidate genes that influence the human electroencephalogram

Hodgkinson

Enoch

Srivastava

et al. 2010

Proc. Natl. Acad. Sci. U.S.A.

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“…EEG δ wave power is the parameter used to model process S in the two-process model of sleep, 1 although EEG δ waves can correlate with processes seemingly unrelated to sleep, e.g., cerebral atrophy. 2 It is used because in many circumstances it is a good correlate of sleep duration and intensity. For instance, after sleep loss both EEG δ power during NREMS episodes and duration of NREMS are enhanced.…”

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confidence: 99%

Delta Wave Power: An Independent Sleep Phenotype or Epiphenomenon?

Davis

Clinton

Jewett

et al. 2011

Journal of Clinical Sleep Medicine

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“…Increased arousal reported by the participants in the VAS as well as the hyperarousal seen in the coregistered EEG have been interpreted as an imbalance of excitation and inhibition [44] or indicated overexcitement of the cortex [45] in previous studies. Increased CNS arousal is also associated with increased likelihood of relapse [46].…”

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confidence: 99%

Impact of Alcohol-Related Video Sequences on Functional MRI in Abstinent Alcoholics

Krienke

Nikesch²,

Spiegelhalder³

et al. 2013

Eur Addict Res

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The object of this study was the identification of brain areas that were significantly more connected than other regions with a previously identified reference region, the posterior cingulate cortex, during the presentation of visual cues in alcoholics. Alcohol-related and neutral video sequences were presented to 30 alcoholics who had been abstinent for at least 4 days. Participants underwent a psychometric assessment before and after the presentation of the video sequences. Functional MRI data were acquired. Psychophysiological interaction analyses were carried out. Participants reported a significant increase in craving and arousal after the presentation of alcohol-related video sequences. The simple contrast alcohol versus neutral was found not to be significantly different in the present study. The brain regions that were found to correlate significantly more with the posterior cingulate cortex under the alcohol-related condition were the inferior parietal lobe, the medial temporal lobe, the inferior frontal gyrus, the postcentral gyrus, and the precuneus. The involvement of these regions in processes of memory, self-control, and self-reflection with a particular focus on alcohol dependence and craving will be discussed.

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Clinical correlates of quantitative EEG alterations in alcoholic patients

Cited by 74 publications

References 33 publications

Genome-wide association identifies candidate genes that influence the human electroencephalogram

Genome-wide association identifies candidate genes that influence the human electroencephalogram

Delta Wave Power: An Independent Sleep Phenotype or Epiphenomenon?

Impact of Alcohol-Related Video Sequences on Functional MRI in Abstinent Alcoholics

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