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Porjesz, B.

Publications and source records attributed to Porjesz, B..

15 recordsLinked to original sources

Lifespan Trajectories of Resting State Bipolar EEG Power

Normative trajectories of resting state bipolar EEG power over the lifespan were derived from a sample of 5781 participants from the Collaborative Study on the Genetics of Alcoholism (COGA), a large multi site study, using 12,906 observations from ages 12 through 70. Trajectories were analyzed using the means, variances, and correlations of data in seven frequency bands (from low theta to high beta) and 24 bipolar channels obtained from 17 electrodes of the 10-20 system. In order to make the study more useful for understanding EEG in the general population, only subjects never having an alcohol use disorder (AUD) diagnosis were included in the study. Bipolar EEG data is derived from the differencing of the signals in adjacent electrodes, either in a lateral (left-right) or sagittal (anterior-posterior) orientation; each difference is called a channel. The power values for the individual observations were calculated by standard Fourier transform based methods. In all cases there are sharp decreases in EEG power from ages 12 to the early 20s after which there are number of divergent patterns: general increases in the beta frequencies, and mixed patterns of increase and subsequent decrease in the theta and alpha frequencies. In these characteristics the lifespan trajectories presented here are similar to the monopolar trajectories described in our previous study \citet{Cho2026}. Sagittal and lateral bipolar trajectories are similar within each sex and between sexes; the primary difference is the much lower degree of regional difference in the sagittal trajectories as compared to the lateral trajectories. The pairwise inter-frequency (within channel) correlation trajectories between the four theta and alpha frequency bands and the four high alpha and beta frequency bands at each channel show striking sex differences unlike the corresponding monopolar correlations. There are a number of features in the bipolar power trajectories that suggest that the differencing procedure reduces not only local phase synchrony, but also effects of global and regional phase synchrony present in the monopolar data from which the bipolar signals are derived. The inter-frequency correlations at the individual channels are much higher in the bipolar data than the monopolar data, suggesting that global and regional phase synchrony components retained in the monopolar data have greater frequency specificity than the more purely local components in the bipolar data. Further analyses to examine many other features of the data will be undertaken in our subsequent work.

neuroscience↗

Lifespan Trajectories of Resting State EEG power

Trajectories of resting state monopolar EEG power were analyzed using the means, variances, and correlations of data in seven frequency bands obtained from 17 electrodes of the 10-20 system from a sample of 5238 participants from the Collaborative Study on the Genetics of Alcoholism (COGA) with 11906 observations from ages 12 through 70. The values for the individual observations were calculated by standard Fourier transform based methods. In order to make the study more useful for understanding EEG in the general population only subjects who were never diagnosed with alcohol use disorder were included in the study. The trajectories of power show a clear pattern of decrease in all frequency bands and both sexes from ages 12 to 20. Subsequently there is considerable amount of variation between frequency bands and between males and females. In females, the generally lower rate of decrease after age 20 is reversed at age 35 in anterior and central regions in the alpha and beta bands, and stabilized in the theta bands. In males, the decreases continue in the theta and high alpha bands, but there are elements of the reversal in the low alpha and beta bands. Examination of the derivatives of the trajectories show that sex differences begin in the mid-twenties in alpha and beta but not until the mid-thirties in theta. In contrast to the varied power value trajectories, the trajectories of inter-frequency correlation show a pervasive increase with age of the correlation between high alpha and each of the other frequency bands except high beta. This increase is primarily anterior in the alpha-theta correlations and more regionally uniform in the alpha-beta correlations. Sex differences are very small. Trajectories of intra-frequency correlations for comparable between region pairs and within region pairs were generally high and stable across age. This is the first of a series of studies which will provide similar analyses of bipolar EEG power and bipolar EEG coherence in this sample. We know of no other study of resting state EEG power which combines the analysis of power with the analysis of both inter-frequency and intra-frequency correlation of power values.

neuroscience↗

Leveraging Pretrained Vision Transformers for classifying Alcohol Use Disorder using Raw Resting-State EEG

Alcohol Use Disorder (AUD) is a prevalent and debilitating neuropsychiatric condition characterized by compulsive alcohol consumption, impaired control, and negative emotional states, affecting about 28 million adults in the United States. Despite its significant public health burden, there are few objective biomarkers and no reliable neurophysiological tools to assist in its clinical diagnosis. In this study, we investigated the potential of deep learning to classify individuals with AUD using raw resting-state electroencephalogram (EEG) data. EEG recordings were obtained from the Collaborative Study on the Genetics of Alcoholism (COGA), a large, longitudinal, multi-site dataset. The initial cohort included a total of 5,402 recordings from 2,710 participants (aged 12-83, mean age 24; 1,338 males and 1,372 females). To reduce confounding factors, we applied demographic matching, and to address class imbalance, we applied undersampling. Minimal preprocessing was applied to preserve the raw EEG features. We utilized EEGViT, a hybrid deep learning architecture that combines convolutional patch embedding with a Vision Transformer (ViT) pretrained on ImageNet, thereby enabling end-to-end learning directly from raw EEG input. The analysis was stratified by sex and age, and all groups were age-matched. To validate the generalization of the model, models were also trained for Cannabis Use Disorder (CUD) and Opioid Use Disorder (OUD). Results for the AUD model showed a classification accuracy of approximately 56% in the overall dataset, 54% for males, and 58% for females. The CUD model showed an accuracy of about 63% with 59% for females and 69% for males. The OUD model showed an accuracy of about 63% with 61% for females and 65% for males. Temporal analysis indicated that the models performance varied across time intervals, with higher accuracy observed in later minutes compared to earlier ones. While modest, these findings underscore the potential of transformer-based models in psychiatric classification using raw EEG data and provide a foundation for future development of EEG-based diagnostic tools for AUD.

neuroscience↗

Neuroanatomical features reveal accelerated brain age in alcohol use disorder

Background/ObjectivesBrain age is a novel measure to characterize the integrity of neurocognitive functioning and brain health in various psychiatric and neurological disorders. Although there is a literature suggesting premature aging of the brain in individuals with alcohol use disorder (AUD), studies directly examining brain age are rare. Therefore, the current study was designed to estimate brain age in AUD individuals using brain morphological features, such as cortical thickness and brain volume. MethodsThe sample included a group of 30 adult males with a history of AUD but maintaining abstinence and a group of 30 male controls without any history of AUD. Brain age was computed using an XGBoost regression model with 187 brain morphological features of cortical thickness and brain volume as predictors. An exploratory correlational analysis between brain age measures and features of neuropsychological performance, impulsivity, and alcohol consumption was also performed. ResultsFindings revealed that AUD individuals showed an increase of 1.70 years in their brain age relative to their chronological age. Further, in the AUD group, higher brain age was significantly associated with poor executive functioning, while a larger gap between brain age and actual age was associated with lower non-planning impulsivity and later age of onset for regular drinking in those with AUD. ConclusionsAUD individuals manifested accelerated brain aging, possibly representing compromised brain health. Brain age measures were found to be associated with some of the measures of neurocognition, impulsivity, and alcohol consumption. These findings may have important implications for the early identification, prevention, and treatment of AUD. However, future studies with larger sample sizes are needed to confirm these preliminary findings.

neuroscience↗

Alcohol use disorder is associated with increases in frontocentral phase-amplitude coupling strength during resting state

Considerable evidence from functional neuroimaging and EEG coherence studies indicates that individuals afflicted with alcohol use disorder (AUD) manifest aberrant patterns of connectivity, particularly in frontal brain regions. Phase-amplitude coupling (PAC) is another form of functional connectivity, reflecting the association between the phase at one frequency and amplitude changes at a higher frequency. Significant PAC differences have been reported for other substance use disorders, but it has not yet been investigated in AUD. We compared frontomedial PAC strength during resting state, eyes closed, in adult participants with severe AUD and age-matched unaffected controls from the Collaborative Study on the Genetics of Alcoholism (COGA). Comodulograms of PAC estimates between phase frequencies (0.1-13 Hz) and amplitude frequencies (4-50 Hz) were calculated for all participants. PAC differences between AUD and unaffected groups were assessed at each phase-amplitude frequency pair in comodulograms to identify clusters of significant test results, reporting only those clusters satisfying all validation and significance testing steps. Severe AUD was associated with clusters of significantly greater PAC in alpha-gamma domains of both men and women. Candidate clusters were found in theta-gamma domains of both sexes, but were only significant greater in men with AUD. Significant PAC clusters were found in the delta-gamma domain of both sexes, though women with AUD showed significant decreases in contrast to greater PAC found in men with AUD. The significant PAC clusters identified in this exploratory study could provide new insights into the dysregulation of brain connectivity underlying AUD.

neuroscience↗

Reward Network Activations of Win versus Loss in a Monetary Gambling Task

Reward processing is a vital function for health and survival and is impaired in various psychiatric and neurological disorders. Using a monetary gambling task, the current study aims to elucidate neural substrates in the reward network underlying evaluation of win versus loss outcomes, and their association with behavioral characteristics, such as impulsivity and task performance, and neuropsychological functioning. Functional MRI was recorded in thirty healthy, male community volunteers (mean age = 27.4 years) while they performed a monetary gambling task in which they bet with either 10 or 50 tokens and received feedback of whether they won or lost the bet amount. Results showed that a set of key brain structures in the reward network, including putamen, caudate nucleus, superior and inferior parietal lobule, angular gyrus, and Rolandic operculum, had greater blood oxygenation level dependent (BOLD) signal during win relative to loss trials, and the BOLD signals in most of these regions were highly correlated with one another. Further, exploratory bivariate analyses between these reward related regions and behavioral and neuropsychological domains showed significant correlations with moderate effect sizes, including: (i) negative correlations between non-planning impulsivity and activations in putamen and caudate regions, (ii) positive correlations between risky bets and right putamen activation, (iii) negative correlations between safer bets and right putamen activation, (iv) a negative correlation between short-term memory capacity and right putamen activity, and (v) a negative correlation between poor planning skills and left inferior occipital cortex activation. These findings contribute to our understanding of the neural underpinnings of monetary reward processing and their relationships to aspects of behavior and cognitive function. Future studies may confirm these findings with larger samples of healthy controls and extend these findings by investigating various clinical groups with impaired reward processing.

neuroscience↗

Non-linear development of EEG coherence in adolescents and young adults shown by the analysis of neurophysiological trajectories and their covariance

To contribute to the understanding of changes in the factors governing the development of neural connectivity, the developmental structure of EEG coherence in adolescents and young adults was analyzed using the means, variances, and covariances of high alpha frequency band coherence measures from a set of 27 coherence pairs obtained from a sample of 1426 participants from the COGA study with 5006 observations over ages 12 through 31. Means and covariances were calculated at 96 age centers by a LOESS method. In the current study, trajectories of covariance matrices considered as individual units were determined by tensorial analysis: calculation of Riemannian geodesic (non-Euclidean) distances between matrices and application of both linear and non-linear dimension reduction techniques to these distances. Results were evaluated by bootstrap methods. Mean coherence trajectories for males and females were very similar, showing a steady upward trend from ages 12 to 20 which diminishes gradually from 20 to 25 and reaches stability from 25 to 31. In contrast, the individual covariance trajectories of males and female differed, with the male covariance levels becoming greater than that of females during the developmental process. Tensorial determination of the distances from the initial covariance matrix of subsequent covariance matrices to age 20 had the same trajectory as the mean coherence values. Tensorial determination of the trajectories of the covariance matrices of males and females based on their all pairs geodesic distances revealed a non-linear pattern in the multi-dimensional space of each of the trajectories: A steady increase in one dimension is accompanied by deviations from it peaking at age 20 which have both transient and lasting effects. There is a precise temporal parallelism of this pattern of covariance in males and females, while there is a consistent distance between the male and female covariance structures throughout the developmental process. Between region differences (anterior-posterior) within each sex are greater than between sex differences within regions. Examining development using multiple methods provides unique insight into the developmental process.

developmental biology↗

Prediction of brain age in individuals with and at risk for alcohol use disorder using brain morphological features

Brain age measures predicted from structural and functional brain features are increasingly being used to understand brain integrity, disorders, and health. While there is a vast literature showing aberrations in both structural and functional brain measures in individuals with and at risk for alcohol use disorder (AUD), few studies have investigated brain age in these groups. The current study examines brain age measures predicted using brain morphological features, such as cortical thickness and brain volume, in individuals with a lifetime diagnosis of AUD as well as in those at higher risk to develop AUD from families with multiple members affected with AUD (i.e., higher family history density (FHD) scores). The AUD dataset included a group of 30 adult males (mean age = 41.25 years) with a lifetime diagnosis of AUD and currently abstinent and a group of 30 male controls (mean age = 27.24 years) without any history of AUD. A second dataset of young adults who were categorized based on their FHD scores comprised a group of 40 individuals (20 males) with high FHD of AUD (mean age = 25.33 years) and a group of 31 individuals (18 males) with low FHD (mean age = 25.47 years). Brain age was predicted using 187 brain morphological features of cortical thickness and brain volume in an XGBoost regression model; a bias-correction procedure was applied to the predicted brain age. Results showed that both AUD and high FHD individuals showed an increase of 1.70 and 0.09 years (1.08 months), respectively, in their brain age relative to their chronological age, suggesting accelerated brain aging in AUD and risk for AUD. Increased brain age was associated with poor performance on neurocognitive tests of executive functioning in both AUD and high FHD individuals, indicating that brain age can also serve as a proxy for cognitive functioning and brain health. These findings on brain aging in these groups may have important implications for the prevention and treatment of AUD and ensuing cognitive decline.

neuroscience↗

Upregulated GIRK2 counteracts ethanol-induced changes in excitability and respiration in human neurons

Genome-wide association analysis (GWAS) of electroencephalographic endophenotypes for alcohol use disorder (AUD) has identified non-coding polymorphisms within the KCNJ6 gene. KCNJ6 encodes GIRK2, a subunit of a G protein-coupled inwardly-rectifying potassium channel that regulates neuronal excitability. How changes in GIRK2 affect human neuronal excitability and the response to repeated ethanol exposure is poorly understood. Here, we studied the effect of upregulating KCNJ6 using an isogenic approach with human glutamatergic neurons derived from induced pluripotent stem cells (male and female donors). Using multi-electrode-arrays, population calcium imaging, single-cell patch-clamp electrophysiology, and mitochondrial stress tests, we find that elevated GIRK2 acts in concert with 7-21 days of ethanol exposure to inhibit neuronal activity, to counteract ethanol-induced increases in glutamate response, and to promote an increase intrinsic excitability. Furthermore, elevated GIRK2 prevented ethanol-dependent changes in basal and activity-dependent mitochondrial respiration. These data support a role for GIRK2 in mitigating the effects of ethanol and a previously unknown connection to mitochondrial function in human glutamatergic neurons. SIGNIFICANCE STATEMENTAlcohol use disorder (AUD) is a major health problem that has worsened since COVID, affecting over 100 million people worldwide. While it is known that heritability contributes to AUD, specific genes and their role in neuronal function remain poorly understood, especially in humans. In the current manuscript, we focused on the inwardly-rectifying potassium channel GIRK2, which has been identified in an AUD-endophenotype genome-wide association study. We used human excitatory neurons derived from healthy donors to study the impact of GIRK2 expression. Our results reveal that elevated GIRK2 counteracts ethanol-induced increases in glutamate response and intracellular calcium, as well as deficits in activity-dependent mitochondrial respiration. The role of GIRK2 in mitigating ethanol-induced hyper-glutamatergic and mitochondrial offers therapeutic promise for treating AUD.

neuroscience↗

Genetic influences vary by age and sex: Trajectories of the association of cholinergic system variants and theta band event related oscillations

To characterize systemic changes in genetic effects on brain development, the age variation of the associations of cholinergic genetic variants and theta band event-related oscillations (EROs) was studied in a sample of 2140 adolescents and young adults, ages 12 to 25 from the COGA prospective study. The theta band EROs were elicited in visual and auditory oddball (target detection) tasks and measured by EEG recording. Associations were found to vary with age, sex, task modality (auditory or visual), and scalp locality. Seven of the twenty-one muscarinic and nicotinic cholinergic SNPs studied in the analysis, from CHRM2, CHRNA3, CHRNA5, and CHRNB4, had significant effects on theta band EROs with considerable age spans for some sex-modality combination. No SNP-age-modality combination had significant effects in the same direction for males and females. Results suggest that nicotinic receptor associations are stronger before age 18, while muscarinic receptor associations are stronger after age 18.

neuroscience↗

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

Memory 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 (Memory group) were compared with a matched Control group 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.

neuroscience↗

Alcohol reverses the effects of KCNJ6 (GIRK2) noncoding variants on excitability of human glutamatergic neurons

Synonymous and noncoding single nucleotide polymorphisms (SNPs) in the KCNJ6 gene, encoding G protein-gated inwardly rectifying potassium (GIRK2) channel subunit 2, have been linked with increased electroencephalographic frontal theta event-related oscillations (ERO) in subjects diagnosed with alcohol use disorder (AUD). To identify molecular and cellular mechanisms while retaining the appropriate genetic background, we generated induced excitatory glutamatergic neurons (iN) from iPSCs derived from four AUD-diagnosed subjects with KCNJ6 variants ( Affected: AF) and four control subjects without variants ( Unaffected: UN). Neurons were analyzed for changes in gene expression, morphology, excitability and physiological properties. Single cell RNA sequencing suggests that KCNJ6 AF variant neurons have altered patterns of synaptic transmission and cell projection morphogenesis. Results confirm that AF neurons express lower levels of GIRK2, have greater neurite area, and elevated excitability. Interestingly, exposure to intoxicating concentrations of ethanol induces GIRK2 expression and reverses functional effects in AF neurons. Ectopic overexpression of GIRK2 alone mimics the effect of ethanol to normalize induced excitability. We conclude that KCNJ6 variants decrease GIRK2 expression and increase excitability and that this effect can be minimized or reduced with ethanol.

neuroscience↗

Multi-omics integration analysis identifies novel genes for alcoholism with potential link to neurodegenerative diseases

SignificanceIdentification of causal variants and genes underlying genome-wide association study (GWAS) loci is essential to understanding the biology of alcohol use disorder (AUD). MethodsIntegration of "multi-omics" data is often necessary to nominate candidate causal variants and genes and prioritize them for follow up studies. Here, we used Mendelian randomization to integrate AUD and drinks per week (DPW) GWAS summary statistics with the gene expression and methylation quantitative trait loci (eQTLs and mQTLs) in the largest brain and myeloid datasets. We also used AUD-related single cell epigenetic data to nominate candidate causal variants and genes associated with DPW and AUD. ResultsOur multi-omics integration analyses prioritized unique as well as shared genes and pathways among AUD and DPW. The GWAS variants associated with both AUD and DPW showed significant enrichment in the promoter regions of fetal and adult brains. The integration of GWAS SNPs with mQTLs from fetal brain prioritized variants on chromosome 11 in both AUD and DPW GWASs. The co-localized variants were found to be overlapping with promoter marks for SPI1, specifically in human microglia, the myeloid cells of the brain. The co-localized SNPs were also strongly associated with SPI1 mRNA expression in myeloid cells from peripheral blood. The prioritized variant at this locus is predicted to alter the binding site for a transcription factor, RXRA, a key player in the regulation of myeloid cell function. Our analysis also identified MAPT as a candidate causal gene specifically associated with DPW. mRNA expression of MAPT was also correlated with daily amounts of alcohol intake in post-mortem brains (frontal cortex) from alcoholics and controls (N = 92). Results may be queried and visualized in an online public resource of these integrative analysis (https://lcad.shinyapps.io/alc_multiomics/). These results highlight overlap between causal genes for neurodegenerative diseases, alcohol use disorder and alcohol consumption. In conclusionintegrating GWAS summary statistics with multi-omics datasets from multiple sources identified biological similarities and differences between typical alcohol intake and disordered drinking highlighting molecular heterogeneity that might inform future targeted functional and cross-species studies. Interestingly, overlap was also observed with causal genes for neurodegenerative diseases.

genomics↗

Analysis of whole genome-transcriptomic organization in brain to identify genes associated with alcoholism

Alcohol exposure triggers changes in gene expression and biological pathways in human brain. We explored alterations in gene expression in the Pre-Frontal Cortex (PFC) of 65 alcoholics and 73 controls of European descent, and identified 129 genes that showed altered expression (FDR < 0.05) in subjects with alcohol dependence. Differentially expressed genes were enriched for pathways related to interferon signaling and Growth Arrest and DNA Damage-inducible 45 (GADD45) signaling. A coexpression module (thistle2) identified by weighted gene co-expression network analysis (WGCNA) was significantly correlated with alcohol dependence, alcohol consumption, and AUDIT scores. Genes in the thistle2 module were enriched with genes related to calcium signaling pathways and showed significant downregulation of these pathways, as well as enrichment for biological processes related to nicotine response and opioid signaling. A second module (brown4) showed significant upregulation of pathways related to immune signaling. Expression quantitative trait loci (eQTLs) for genes in the brown4 module were also enriched for genetic associations with alcohol dependence and alcohol consumption in large genome-wide studies included in the Psychiatric Genetic Consortium and the UK Biobanks alcohol consumption dataset. By leveraging multi-omics data, this transcriptome analysis has identified genes and biological pathways that could provide insight for identifying therapeutic targets for alcohol dependence.

neuroscience↗

Genome-wide association analysis links multiple psychiatric liability genes to oscillatory brain activity

Oscillations in neuronal activity are widely thought to play a crucial role in information processing and cortical communication 1-8. Brain oscillations have been widely investigated as biomarkers of psychiatric disorders and variation in normal human behavior 9, 10, including intelligence 11, 12, schizophrenia 13, 14, attentional deficits 15, 16, and substance use 17, 18. Beyond the biomarker, oscillatory activity may indeed cause variation in behavior, as it has been shown that disrupting oscillatory activity by blocking GABAergic fast-spiking interneurons in the frontal cortex of mice impairs behavioral flexibility8, consistent with ...

genetics↗