Predicting risk for Alcohol Use Disorder using longitudinal data with multimodal biomarkers and family history: a machine learning study.

Predictive models have succeeded in distinguishing between individuals with Alcohol use Disorder (AUD) and controls. However, predictive models identifying who is prone to develop AUD and the biomarkers indicating a predisposition to AUD are still unclear. Our sample (n = 656) included offspring and non-offspring of European American (EA) and African American (AA) ancestry from the Collaborative Study of the Genetics of Alcoholism (COGA) who were recruited as early as age 12 and were unaffected at first assessment and reassessed years later as AUD (DSM-5) (n = 328) or unaffected (n = 328). Machine learning analysis was performed for 220 EEG measures, 149 alcohol-related single nucleotide polymorphisms (SNPs) from a recent large Genome-wide Association Study (GWAS) of alcohol use/misuse and two family history (mother DSM-5 AUD and father DSM-5 AUD) features using supervised, Linear Support Vector Machine (SVM) classifier to test which features assessed before developing AUD predict those who go on to develop AUD. Age, gender, and ancestry stratified analyses were performed. Results indicate significant and higher accuracy rates for the AA compared with the EA prediction models and a higher model accuracy trend among females compared with males for both ancestries. Combined EEG and SNP features model outperformed models based on only EEG features or only SNP features for both EA and AA samples. This multidimensional superiority was confirmed in a follow-up analysis in the AA age groups (12-15, 16-19, 20-30) and EA age group (16-19). In both ancestry samples, the youngest age group achieved higher accuracy score than the two other older age groups. Maternal AUD increased the model's accuracy in both ancestries' samples. Several discriminative EEG measures and SNPs features were identified, including lower posterior gamma, higher slow wave connectivity (delta, theta, alpha), higher frontal gamma ratio, higher beta correlation in the parietal area, and 5 SNPs: rs4780836, rs2605140, rs11690265, rs692854, and rs13380649. Results highlight the significance of sampling uniformity followed by stratified (e.g., ancestry, gender, developmental period) analysis, and wider selection of features, to generate better prediction scores allowing a more accurate estimation of AUD development

The association of polygenic risk for schizophrenia, bipolar disorder, and depression with neural connectivity in adolescents and young adults: examining developmental and sex differences

Neurodevelopmental abnormalities in neural connectivity have been long implicated in the etiology of schizophrenia (SCZ); however, it remains unclear whether these neural connectivity patterns are associated with genetic risk for SCZ in unaffected individuals (i.e., an absence of clinical features of SCZ or a family history of SCZ). We examine whether polygenic risk scores (PRS) for SCZ are associated with functional neural connectivity in adolescents and young adults without SCZ, whether this association is moderated by sex and age, and if similar associations are observed for genetically related neuropsychiatric PRS. One-thousand four-hundred twenty-six offspring from 913 families, unaffected with SCZ, were drawn from the Collaborative Study of the Genetics of Alcoholism (COGA) prospective cohort (median age at first interview = 15.6 (12-26), 51.6% female, 98.1% European American, 41% with a family history of alcohol dependence). Participants were followed longitudinally with resting-state EEG connectivity (i.e., coherence) assessed every two years. Higher SCZ PRS were associated with elevated theta (3-7 Hz) and alpha (7-12 Hz) EEG coherence. Associations differed by sex and age; the most robust associations were observed between PRS and parietal-occipital, central-parietal, and frontal-parietal alpha coherence among males between ages 15-19 (B: 0.15-0.21, p < 10-4). Significant associations among EEG coherence and Bipolar and Depression PRS were observed, but differed from SCZ PRS in terms of sex, age, and topography. Findings reveal that polygenic risk for SCZ is robustly associated with increased functional neural connectivity among young adults without a SCZ diagnosis. Striking differences were observed between men and women throughout development, mapping onto key periods of risk for the onset of psychotic illness and underlining the critical importance of examining sex differences in associations with neuropsychiatric PRS across development

Parsing genetically influenced risk pathways: genetic loci impact problematic alcohol use via externalizing and specific risk

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Electrical fingerprint of the amygdala guides neurofeedback training for stress resilience

Real-time functional magnetic resonance imaging (rt-fMRI) has revived the translational perspective of neurofeedback (NF)1. Particularly for stress management, targeting deeply located limbic areas involved in stress processing2 has paved new paths for brain-guided interventions. However, the high cost and immobility of fMRI constitute a challenging drawback for the scalability (accessibility and cost-effectiveness) of the approach, particularly for clinical purposes3. The current study aimed to overcome the limited applicability of rt-fMRI by using an electroencephalography (EEG) model endowed with improved spatial resolution, derived from simultaneous EEG–fMRI, to target amygdala activity (termed amygdala electrical fingerprint (Amyg-EFP))4,5,6. Healthy individuals (n = 180) undergoing a stressful military training programme were randomly assigned to six Amyg-EFP-NF sessions or one of two controls (control-EEG-NF or NoNF), taking place at the military training base. The results demonstrated specificity of NF learning to the targeted Amyg-EFP signal, which led to reduced alexithymia and faster emotional Stroop, indicating better stress coping following Amyg-EFP-NF relative to controls. Neural target engagement was demonstrated in a follow-up fMRI-NF, showing greater amygdala blood-oxygen-level-dependent downregulation and amygdala–ventromedial prefrontal cortex functional connectivity following Amyg-EFP-NF relative to NoNF. Together, these results demonstrate limbic specificity and efficacy of Amyg-EFP-NF during a stressful period, pointing to a scalable non-pharmacological yet neuroscience-based training to prevent stress-induced psychopathology

Alcohol Use Disorder, Psychiatric Comorbidities, Marriage and Divorce in a High-Risk Sample

ObjectiveTo examine associations between alcohol use disorder (AUD), its psychiatric comorbidities, and their interactions, with marital outcomes in a diverse high-risk, genetically informative sample.MethodParticipants included European ancestry (EA; n = 4,045) and African ancestry (AA; n = 1,550) individuals from the multigenerational Collaborative Study on the Genetics of Alcoholism (COGA) sample (56% female, Mage ∼ 41 years). Outcomes were lifetime marriage and divorce. Predictors included lifetime AUD, an alcohol problems polygenic score (PRS), and AUD comorbidities, including conduct or antisocial personality disorder (ASP), cannabis dependence/abuse (CAN), frequent tobacco use (TOB), and major depressive disorder (MDD). Mixed effect Cox models and generalized linear mixed effects models were fit.ResultsAmong EA participants, those with AUD and CAN were less likely to marry (hazard ratios [HRs] 0.70-0.83, ps &lt; 0.01). Among AA participants, those with AUD and TOB were less likely to marry (HRs 0.66-0.82, ps &lt; 0.05) and those with MDD were more likely to marry (HR = 1.34, ps &lt; 0.01). Among EA participants, AUD, CAN, TOB, and MDD were associated with higher odds of divorce (odds ratios [ORs] 1.59-2.21, ps &lt; 0.01). Among AA participants, no predictors were significantly associated with divorce. Significant random effects indicated genetic and environmental influences on marriage, but only environmental factors on divorce.ConclusionsIn a high-risk sample, AUD was associated with reduced likelihood of marriage in EA and AA individuals and increased risk of divorce in EA individuals. These associations were largely independent of comorbidities. Genetic and environmental background factors contributed to marriage, while only environmental background factors contributed to divorce. (PsycInfo Database Record (c) 2022 APA, all rights reserved)

High Polygenic Risk Scores Are Associated With Early Age of Onset of Alcohol Use Disorder in Adolescents and Young Adults at Risk

BackgroundGenome-wide association studies have been conducted in alcohol use disorder (AUD), and they permit the use of polygenic risk scores (PRSs), in combination with clinical variables, to predict the onset of AUD in vulnerable populations.MethodsA total of 2794 adolescent/young adult subjects from the Collaborative Study on the Genetics of Alcoholism were followed, with clinical assessments every 2 years. Subjects were genotyped using a genome-wide chip. Separate PRS analyses were performed for subjects of European ancestry and African ancestry. Age of onset of DSM-5 AUD was evaluated using the Cox proportional hazard model. Predictive power was assessed using receiver operating characteristic curves and by analysis of the distribution of PRS.ResultsEuropean ancestry subjects with higher than median PRSs were at greater risk for onset of AUD than subjects with lower than median PRSs (p&nbsp;= 3&nbsp;× 10-7). Area under the curve for the receiver operating characteristic analysis peaked at 0.88 to 0.95 using PRS plus sex, family history, comorbid disorders, age at first drink, and peer drinking; predictive power was primarily driven by clinical variables. In this high-risk sample, European ancestry subjects with a PRS score in the highest quartile showed a 72% risk for developing AUD and a 35% risk of developing severe AUD (compared with risks of 54% and 16%, respectively, in the lowest quartile).ConclusionsPredictive power for PRSs in the extremes of the distribution suggests that these may have future clinical utility. Uncertainties in interpretation at the individual level still preclude current application

The Collaborative Study on the Genetics of Alcoholism: Overview

Alcohol use disorders (AUD) are commonly occurring, heritable and polygenic disorders with etiological origins in the brain and the environment. To outline the causes and consequences of alcohol-related milestones, including AUD, and their related psychiatric comorbidities, the Collaborative Study on the Genetics of Alcoholism (COGA) was launched in 1989 with a gene-brain-behavior framework. COGA is a family based, diverse (~25% self-identified African American, ~52% female) sample, including data on 17,878 individuals, ages 7-97 years, in 2246 families of which a proportion are densely affected for AUD. All participants responded to questionnaires (e.g., personality) and the Semi-Structured Assessment for the Genetics of Alcoholism (SSAGA) which gathers information on psychiatric diagnoses, conditions and related behaviors (e.g., parental monitoring). In addition, 9871 individuals have brain function data from electroencephalogram (EEG) recordings while 12,009 individuals have been genotyped on genome-wide association study (GWAS) arrays. A series of functional genomics studies examine the specific cellular and molecular mechanisms underlying AUD. This overview provides the framework for the development of COGA as a scientific resource in the past three decades, with individual reviews providing in-depth descriptions of data on and discoveries from behavioral and clinical, brain function, genetic and functional genomics data. The value of COGA also resides in its data sharing policies, its efforts to communicate scientific findings to the broader community via a project website and its potential to nurture early career investigators and to generate independent research that has broadened the impact of gene-brain-behavior research into AUD