Heritability of EEG coherence in a large sib-pair population

Rapid dynamics of electrophysiological connectome states are heritable

Time-varying changes in whole-brain connectivity patterns, or connectome state dynamics, are a prominent feature of brain activity with broad functional implications. While infraslow (<0.1 Hz) connectome dynamics have been extensively studied with fMRI, rapid dynamics highly relevant for cognition are poorly understood. Here, we asked whether rapid electrophysiological connectome dynamics constitute subject-specific brain traits and to what extent they are under genetic influence. Using source-localized EEG connectomes during resting state (N = 928, 473 females), we quantified the heritability of multivariate (multistate) features describing temporal or spatial characteristics of connectome dynamics. States switched rapidly every ∼60-500 ms. Temporal features were heritable, particularly Fractional Occupancy (in theta, alpha, beta, and gamma bands) and Transition Probability (in theta, alpha, and gamma bands), representing the duration spent in each state and the frequency of state switches, respectively. Genetic effects explained a substantial proportion of the phenotypic variance of these features: Fractional Occupancy in beta (44.3%) and gamma (39.8%) bands and Transition Probability in theta (38.4%), alpha (63.3%), beta (22.6%), and gamma (40%) bands. However, we found no evidence for the heritability of dynamic spatial features, specifically states' Modularity and connectivity pattern. We conclude that genetic effects shape individuals' connectome dynamics at rapid timescales, specifically states' overall occurrence and sequencing.

Childhood trauma is associated with developmental trajectories of EEG coherence, alcohol-related outcomes, and PTSD symptoms

BACKGROUND

Associations between childhood trauma, neurodevelopment, alcohol use disorder (AUD), and posttraumatic stress disorder (PTSD) are understudied during adolescence.

METHODS

Using 1652 participants (51.75% female, baseline Mage = 14.3) from the Collaborative Study of the Genetics of Alcoholism, we employed latent growth curve models to (1) examine associations of childhood physical, sexual, and non-assaultive trauma (CPAT, CSAT, and CNAT) with repeated measures of alpha band EEG coherence (EEGc), and (2) assess whether EEGc trajectories were associated with AUD and PTSD symptoms. Sex-specific models accommodated sex differences in trauma exposure, AUD prevalence, and neural development.

RESULTS

In females, CSAT was associated with higher mean levels of EEGc in left frontocentral (LFC, ß = 0.13, p = 0.01) and interhemispheric prefrontal (PFI, ß = 0.16, p < 0.01) regions, but diminished growth in LFC (ß = -0.07, p = 0.02) and PFI (ß = -0.07, p = 0.02). In males, CPAT was associated with lower mean levels (ß = -0.17, p = 0.01) and increased growth (ß = 0.11, p = 0.01) of LFC EEGc. Slope of LFC EEGc was inversely associated with AUD symptoms in females (ß = -1.81, p = 0.01). Intercept of right frontocentral and PFI EEGc were associated with AUD symptoms in males, but in opposite directions. Significant associations between EEGc and PTSD symptoms were also observed in trauma-exposed individuals.

CONCLUSIONS

Childhood assaultive trauma is associated with changes in frontal alpha EEGc and subsequent AUD and PTSD symptoms, though patterns differ by sex and trauma type. EEGc findings may inform emerging treatments for PTSD and AUD.

A genome-wide association study of interhemispheric theta EEG coherence: implications for neural connectivity and alcohol use behavior

Aberrant connectivity of large-scale brain networks has been observed among individuals with alcohol use disorders (AUDs) as well as in those at risk, suggesting deficits in neural communication between brain regions in the liability to develop AUD. Electroencephalographical (EEG) coherence, which measures the degree of synchrony between brain regions, may be a useful measure of connectivity patterns in neural networks for studying the genetics of AUD. In 8810 individuals (6644 of European and 2166 of African ancestry) from the Collaborative Study on the Genetics of Alcoholism (COGA), we performed a Multi-Trait Analyses of genome-wide association studies (MTAG) on parietal resting-state theta (3-7 Hz) EEG coherence, which previously have been associated with AUD. We also examined developmental effects of GWAS findings on trajectories of neural connectivity in a longitudinal subsample of 2316 adolescent/young adult offspring from COGA families (ages 12-30) and examined the functional and clinical significance of GWAS variants. Six correlated single nucleotide polymorphisms located in a brain-expressed lincRNA (ENSG00000266213) on chromosome 18q23 were associated with posterior interhemispheric low theta EEG coherence (3-5 Hz). These same variants were also associated with alcohol use behavior and posterior corpus callosum volume, both in a subset of COGA and in the UK Biobank. Analyses in the subsample of COGA offspring indicated that the association of rs12954372 with low theta EEG coherence occurred only in females, most prominently between ages 25 and 30 (p < 2 × 10-9). Converging data provide support for the role of genetic variants on chromosome 18q23 in regulating neural connectivity and alcohol use behavior, potentially via dysregulated myelination. While findings were less robust, genome-wide associations were also observed with rs151174000 and parieto-frontal low theta coherence, rs14429078 and parieto-occipital interhemispheric high theta coherence, and rs116445911 with centro-parietal low theta coherence. These novel genetic findings highlight the utility of the endophenotype approach in enhancing our understanding of mechanisms underlying addiction susceptibility.

Large-scale collaboration in ENIGMA-EEG: A perspective on the meta-analytic approach to link neurological and psychiatric liability genes to electrophysiological brain activity

BACKGROUND AND PURPOSE

The ENIGMA-EEG working group was established to enable large-scale international collaborations among cohorts that investigate the genetics of brain function measured with electroencephalography (EEG). In this perspective, we will discuss why analyzing the genetics of functional brain activity may be crucial for understanding how neurological and psychiatric liability genes affect the brain.

METHODS

We summarize how we have performed our currently largest genome-wide association study of oscillatory brain activity in EEG recordings by meta-analyzing the results across five participating cohorts, resulting in the first genome-wide significant hits for oscillatory brain function located in/near genes that were previously associated with psychiatric disorders. We describe how we have tackled methodological issues surrounding genetic meta-analysis of EEG features. We discuss the importance of harmonizing EEG signal processing, cleaning, and feature extraction. Finally, we explain our selection of EEG features currently being investigated, including the temporal dynamics of oscillations and the connectivity network based on synchronization of oscillations.

RESULTS

We present data that show how to perform systematic quality control and evaluate how choices in reference electrode and montage affect individual differences in EEG parameters.

CONCLUSION

The long list of potential challenges to our large-scale meta-analytic approach requires extensive effort and organization between participating cohorts; however, our perspective shows that these challenges are surmountable. Our perspective argues that elucidating the genetic of EEG oscillatory activity is a worthwhile effort in order to elucidate the pathway from gene to disease liability.

Environmental Factors Shape Sleep EEG Connectivity During Early Adolescence

Quantifying the degree to which genetic and environmental factors shape brain network connectivity is critical to furthering our understanding of the developing human brain. Sleep, a state of sensory disengagement, provides a unique opportunity to study brain network activity noninvasively by means of sleep electroencephalography (EEG) coherence. We conducted a high-density sleep EEG study in monozygotic (MZ; n = 38; mean age = 12.46; 20 females) and dizygotic (DZ; n = 24; mean age = 12.50; 12 females) twins to assess the heritability of sleep EEG coherence in early adolescence—a period of significant brain rewiring. Structural equation modeling was used to estimate three latent factors: genes, environmental factors shared between twins and environmental factors unique to each twin. We found a strong contribution of unique environmental factors (66% of the variance) and moderate genetic influence (19% of the variance) on sleep EEG coherence across frequencies and sleep states. An exception to this was sleep spindle activity, an index of the thalamocortical network, which showed on average a genetic contribution of 48% across connections. Furthermore, we observed high intraindividual stability of coherence across two consecutive nights suggesting that despite only a modest genetic contribution, sleep EEG coherence is like a trait. Our findings in adolescent humans are in line with earlier findings in animals that show the primordial cerebral map and its connections are plastic and it is through interaction with the environment that the pattern of brain network connectivity is shaped. Therefore, even in twins living together, small differences in the environment may cascade into meaningful differences in brain connectivity.

[Molecular-genetic and electroencephalographic markers of neurocognitive processes in depressive disorders]

Perspectives of molecular-genetic approaches to the establishment of mechanisms of development and causes of heterogeneity of neurocognitive impairment are discussed. The current results indicate that candidate genes for depression can contribute to the variance of memory and regulatory functions in patients. At the same time, these genes are closely related to affective information processing and .cortisol level. By that fact, it can't be excluded that affective processes moderate the association between cognition and genes. EEG parameters could be useful phenotypes in the search for and understanding of genetic mechanisms of cognitive deficit in depression. Parameters of resting EEG and its reactive changes are known to reflect the certain cognitive processes. They are influenced by genetic factors and are sensitive indicators of mechanisms that might underlie cognitive impairment in depressive patients. Accumulating data on molecular-genetic correlates of normal electric brain activity may be a source of choosing new candidate genes for cognitive impairment in depression.

Advances in Electrophysiological Research

Electrophysiological measures of brain function are effective tools to understand neurocognitive phenomena and sensitive indicators of pathophysiological processes associated with various clinical conditions, including alcoholism. Individuals with alcohol use disorder (AUD) and their high-risk offspring have consistently shown dysfunction in several electrophysiological measures in resting state (i.e., electroencephalogram) and during cognitive tasks (i.e., event-related potentials and event-related oscillations). Researchers have recently developed sophisticated signal-processing techniques to characterize different aspects of brain dynamics, which can aid in identifying the neural mechanisms underlying alcoholism and other related complex disorders.These quantitative measures of brain function also have been successfully used as endophenotypes to identify and help understand genes associated with AUD and related disorders. Translational research also is examining how brain electrophysiological measures potentially can be applied to diagnosis, prevention, and treatment.

Understanding alcohol use disorders with neuroelectrophysiology

Neurocognitive deficits associated with impairments in various brain regions and neural circuitries, particularly involving frontal lobes, have been associated with chronic alcoholism, as well as with a predisposition to develop alcohol use and related disorders (AUDs). AUD is a multifactorial disorder caused by complex interactions between behavioral, genetic, and environmental liabilities. Neuroelectrophysiologic techniques are instrumental in understanding brain and behavior relationships and have also proved very useful in evaluating the genetic diathesis of alcoholism. This chapter describes findings from neuroelectrophysiologic measures (electroencephalogram, event-related potentials, and event-related oscillations) related to acute and chronic effects of alcohol on the brain and those that reflect underlying deficits related to a predisposition to develop AUDs and related disorders. The utility of these measures as effective endophenotypes to identify and understand genes associated with brain electrophysiology, cognitive networks, and AUDs has also been discussed.

The genetics of alcohol dependence: advancing towards systems-based approaches

BACKGROUND

Personalized treatment for psychopathologies, in particular alcoholism, is highly dependent upon our ability to identify patterns of genetic and environmental effects that influence a person's risk. Unfortunately, array-based whole genome investigations into heritable factors that explain why one person becomes dependent upon alcohol and another does not, have indicated that alcohol's genetic architecture is highly complex. That said, uncovering and interpreting the missing heritability in alcohol genetics research has become all the more important, especially since the problem may extend to our inability to model the cumulative and combinatorial relationships between common and rare genetic variants. As numerous studies begin to illustrate the dependency of alcohol pharmacotherapies on an individual's genotype, the field is further challenged to identify new ways to transcend agnostic genomewide association approaches. We discuss insights from genetic studies of alcohol related diseases, as well as issues surrounding alcohol's genetic complexity and etiological heterogeneity. Finally, we describe the need for innovative systems-based approaches (systems genetics) that can provide additional statistical power that can enhance future gene-finding strategies and help to identify heretofore-unrealized mechanisms that may provide new targets for prevention/treatments efforts. Emerging evidence from early studies suggest that systems genetics has the potential to organize our neurological, pharmacological, and genetic understanding of alcohol dependence into a biologically plausible framework that represents how perturbations across evolutionarily robust biological systems determine susceptibility to alcohol dependence.

Molecular genetics of alcohol dependence and related endophenotypes

Alcohol dependence is a worldwide public health problem, and involves both environmental and genetic vulnerability factors. The heritability of alcohol dependence is rather high, ranging between 50% and 60%, although alcohol dependence is a polygenic, complex disorder.

Genome-wide scans on large cohorts of multiplex families, including the collaborative study on genetics of alcoholism (COGA), emphasized the role of many chromosome regions and some candidate genes. The genes encoding the alcohol-metabolizing enzymes, or those involved in brain reward pathways, have been involved. Since dopamine is the main neurotransmitter in the reward circuit, genes involved in the dopaminergic pathway represent candidates of interest. Furthermore, gamma-amino-butyric acid (GABA) neurotransmitter mediates the acute actions of alcohol and is involved in withdrawal symptomatology. Numerous studies showed an association between variants within GABA receptors genes and the risk of alcohol dependence.

In accordance with the complexity of the “alcohol dependence” phenotype, another field of research, related to the concept of endophenotypes, received more recent attention. The role of vulnerability genes in alcohol dependence is therefore re-assessed focusing on different phenotypes and endophenotypes. The latter include brain oscillations, EEG alpha and beta variants and alpha power, and amplitude of P300 amplitude elicited from a visual oddball task.

Recent enhancement on global characterizations of the genome by high-throughput approach for genotyping of polymorphisms and studies of transcriptomics and proteomics in alcohol dependence is also reviewed.

Electrophysiological markers of genetic risk for attention deficit hyperactivity disorder

Attention deficit hyperactivity disorder (ADHD) is a highly heritable neurodevelopmental disorder with complex genetic aetiology. The identification of candidate intermediate phenotypes may facilitate the detection of susceptibility genes and neurobiological mechanisms underlying the disorder. Electroencephalography (EEG) is an ideal neuroscientific approach, providing a direct measurement of neural activity that demonstrates reliability, developmental stability and high heritability. This systematic review evaluates the utility of a subset of electrophysiological measures as potential intermediate phenotypes for ADHD: quantitative EEG indices of arousal and intraindividual variability, and functional investigations of attention, inhibition and performance monitoring using the event-related potential (ERP) technique. Each measure demonstrates consistent and meaningful associations with ADHD, a degree of genetic overlap with ADHD and potential links to specific genetic variants. Investigations of the genetic and environmental contributions to EEG/ERP and shared genetic overlap with ADHD might enhance molecular genetic studies and provide novel insights into aetiology. Such research will aid in the precise characterisation of the clinical deficits seen in ADHD and guide the development of novel intervention and prevention strategies for those at risk.

The genetic and molecular regulation of sleep: from fruit flies to humans

It has been known for a long time that genetic factors affect sleep quantity and quality. Genetic screens have identified several mutations that affect sleep across species, pointing to an evolutionary conserved regulation of sleep. Moreover, it has also been recognized that sleep affects gene expression. These findings have given valuable insights into the molecular underpinnings of sleep regulation and function that might lead the way to more efficient treatments for sleep disorders.

Uncovering genes for cognitive (dys)function and predisposition for alcoholism spectrum disorders: a review of human brain oscillations as effective endophenotypes

Brain oscillations provide a rich source of potentially useful endophenotypes (intermediate phenotypes) for psychiatric genetics, as they represent important correlates of human information processing and are associated with fundamental processes from perception to cognition. These oscillations are highly heritable, are modulated by genes controlling neurotransmitters in the brain, and provide links to associative and integrative brain functions. These endophenotypes represent traits that are less complex and more proximal to gene function than either diagnostic labels or traditional cognitive measures, providing a powerful strategy in searching for genes in psychiatric disorders. These intermediate phenotypes identify both affected and unaffected members of an affected family, including offspring at risk, providing a more direct connection with underlying biological vulnerability. Our group has utilized heritable neurophysiological features (i.e., brain oscillations) as endophenotypes, making it possible to identify susceptibility genes that may be difficult to detect with diagnosis alone. We have discussed our findings of significant linkage and association between brain oscillations and genes in GABAergic, cholinergic and glutamatergic systems (GABRA2, CHRM2, and GRM8). We have also shown that some oscillatory indices from both resting and active cognitive states have revealed a common subset of genetic foci that are shared with the diagnosis of alcoholism and related disorders. Implications of our findings have been discussed in the context of physiological and pharmacological studies on receptor function. These findings underscore the utility of quantitative neurophysiological endophenotypes in the study of the genetics of brain function and the genetic diathesis underlying complex psychiatric disorders.