Transancestral GWAS of alcohol dependence reveals common genetic underpinnings with psychiatric disorders

Polygenic dissection of treatment-resistant depression with proxy phenotypes in the UK Biobank

BACKGROUND

Treatment-resistant depression (TRD) affects one-third of major depressive disorder (MDD) patients. Previous pharmacogenetic studies suggest genetic variation may influence medication response but findings are heterogeneous. We conducted a comprehensive genetic investigation using proxy TRD phenotypes (TRDp) that mirror the treatment options of MDD from UK Biobank primary care records.

METHODS

Among 15,125 White British MDD patients, we identified TRDp with medication changes (switching or receiving multiple antidepressants [AD]); augmentation therapy (antipsychotics; mood stabilizers; valproate; lithium); or electroconvulsive therapy (ECT). Hospitalized TRDp patients (HOSP-TRDp) were also identified. We conducted genome-wide association analysis, estimated SNP-heritability (hg2), and assessed the genetic burden for nine psychiatric diseases using polygenic risk scores (PRS).

RESULTS

TRDp patients were more often female, unemployed, less educated, and had higher BMI, with hospitalization rates twice as high as non-TRDp. While no credible risk variants emerged, heritability analysis showed significant genetic influence on TRDp (liability hg2 21-24 %), particularly for HOSP-TRDp (28-31 %). TRDp classified by AD changes and augmentation carried an elevated yet varied polygenic burden for MDD, ADHD, BD, and SCZ. Higher BD PRS increased the likelihood of receiving ECT, lithium, and valproate by 1.27-1.80 fold. Patients in the top 10 % PRS relative to the average had a 12-36 % and 24-51 % higher risk of TRDp and HOSP-TRDp, respectively.

CONCLUSIONS

Our findings support a significant polygenic basis for TRD, highlighting genetic and phenotypic distinctions from non-TRD. We demonstrate that different TRDp endpoints are enriched with various spectra of psychiatric genetic liability, offering insights into pharmacogenomics and TRD's complex genetic architecture.

The Genetic Architecture of Differentiating Behavioral and Emotional Problems in Early Life

BACKGROUND

Early in life, behavioral and cognitive traits associated with risk for developing a psychiatric condition are broad and undifferentiated. As children develop, these traits differentiate into characteristic clusters of symptoms and behaviors that ultimately form the basis of diagnostic categories. Understanding this differentiation process-in the context of genetic risk for psychiatric conditions, which is highly generalized-can improve early detection and intervention.

METHODS

We modeled the differentiation of behavioral and emotional problems from age 1.5 to 5 years (behavioral problems - emotional problems = differentiation score) in a preregistered study of ∼79,000 children from the population-based Norwegian Mother, Father, and Child Cohort Study. We used genomic structural equation modeling to identify genetic signal in differentiation and total problems, investigating their links with 11 psychiatric and neurodevelopmental conditions. We examined associations of polygenic scores (PGS) with both outcomes and assessed the relative contributions of direct and indirect genetic effects in ∼33,000 family trios.

RESULTS

Differentiation was primarily genetically correlated with psychiatric conditions via a neurodevelopmental factor. Total problems were primarily associated with the neurodevelopmental factor and p-factor. PGS analyses revealed an association between liability to attention-deficit/hyperactivity disorder and differentiation (β = 0.11; 95% CI, 0.10 to 0.12) and a weaker association with total problems (β = 0.06; 95% CI, 0.04 to 0.07). Trio-PGS analyses showed predominantly direct genetic effects on both outcomes.

CONCLUSIONS

We uncovered genomic signal in the differentiation process, mostly related to common variants associated with neurodevelopmental conditions. Investigating the differentiation of early-life behavioral and emotional problems may enhance our understanding of the developmental emergence of different psychiatric and neurodevelopmental conditions.

Mental Health, Substance Use, and Related Factors Associated with Recent Use of Cannabis for Sleep: A Co-Twin Control Study

OBJECTIVES

To examine: 1) cross-sectional associations between past-month use of cannabis for sleep with mental health, substance use, and related factors in adults and 2) the role of genetic and early environmental factors shared by twins (familial confounds) in explaining significant associations.

METHODS

In a population-based sample of adult twins (n = 3,165, Mage36.7) we ran regression (phenotypic) and multilevel (co-twin control) models examining associations between past-month use of cannabis for sleep without comes of interest. We controlled for cannabis frequency and sleep quality except when each was the outcome of interest.

RESULTS

Recent use of cannabis for sleep was associated with multiple mental health, substance use, and related factors in phenotypic models. In co-twincontrol models, within-family effects were significant between using cannabis for sleep with more problems from cannabis use, higher cannabis frequency, worse sleep quality, and more frequent use of alcohol and medication for sleep.

CONCLUSIONS

Familial confounds may explain many, but not all, associations between recent use of cannabis for sleep and mental health, substance use, and related factors. Longitudinal work is needed to clarify the directionality of associations not explained by familial confounds, and whether they are risks of using cannabis for sleep.

The effects of alcohol use severity and polygenic risk on gray matter volumes in young adults

Introduction

Genetic factors contribute to alcohol misuse. Chronic alcohol consumption is associated with decreases in gray matter volumes (GMVs) of the brain. However, it remains unclear whether or how genetic risks may alter GMVs independent of the effects of alcohol exposure.

Methods

Here, we employed the Human Connectome Project data of neurotypical adults (n = 995; ages 22-35; 534 women) and, with voxel-based morphometry analysis, computed the GMVs of 166 regions in the automated anatomical atlas 3. Alcohol use behaviors were assessed with the Semi-Structured Assessment for the Genetics of Alcoholism. Alcohol use severity was quantified by the first principal component (PC1) identified of principal component analysis of 15 drinking measures. Polygenic risk scores (PRS) for alcohol dependence were computed for all subjects using the Psychiatric Genomics Consortium study of alcohol dependence as the base sample. With age, sex, race, and total intracranial volume as covariates, we evaluated the relationships of regional GMVs with PC1 and PRS together in a linear regression.

Results

PC1 was negatively correlated with GMVs of right insula and Heschl's gyrus, and PRS was positively correlated with GMVs of left posterior orbitofrontal cortex, bilateral intralaminar nuclei of the thalamus and lingual gyri.

Discussion

These findings suggest distinct volumetric neural markers of drinking severity and genetic risks of alcohol misuse. Notably, in contrast to volumetric reduction, the genetic risks of dependent drinking may involve larger regional volumes in the reward, emotion, and saliency circuits.

Genome-wide analyses identify 30 loci associated with obsessive-compulsive disorder

Obsessive-compulsive disorder (OCD) affects ~1% of children and adults and is partly caused by genetic factors. We conducted a genome-wide association study (GWAS) meta-analysis combining 53,660 OCD cases and 2,044,417 controls and identified 30 independent genome-wide significant loci. Gene-based approaches identified 249 potential effector genes for OCD, with 25 of these classified as the most likely causal candidates, including WDR6, DALRD3 and CTNND1 and multiple genes in the major histocompatibility complex (MHC) region. We estimated that ~11,500 genetic variants explained 90% of OCD genetic heritability. OCD genetic risk was associated with excitatory neurons in the hippocampus and the cortex, along with D1 and D2 type dopamine receptor-containing medium spiny neurons. OCD genetic risk was shared with 65 of 112 additional phenotypes, including all the psychiatric disorders we examined. In particular, OCD shared genetic risk with anxiety, depression, anorexia nervosa and Tourette syndrome and was negatively associated with inflammatory bowel diseases, educational attainment and body mass index.

Genomic approaches to explore susceptibility and pathogenesis of alcohol use disorder and alcohol-associated liver disease

Excessive alcohol use is a major risk factor for the development of an alcohol use disorder (AUD) and contributes to a wide variety of other medical illnesses, including alcohol-associated liver disease (ALD). Both AUD and ALD are complex and causally interrelated diseases, and multiple factors other than alcohol consumption are implicated in the disease pathogenesis. While the underlying pathophysiology of AUD and ALD is complex, there is substantial evidence for a genetic susceptibility of both diseases. Current genome-wide association studies indicate that the genes associated with clinical AUD only poorly overlap with the genes identified for heavy drinking and, in turn, neither overlap with the genes identified for ALD. Uncovering the main genetic factors will enable us to identify molecular drivers underlying the pathogenesis, discover potential targets for therapy, and implement patient care early in disease progression. In this review, we described multiple genomic approaches and their implications to investigate the susceptibility and pathogenesis of both AUD and ALD. We concluded our review with a discussion of the knowledge gaps and future research on genomic studies in these 2 diseases.

Are Depressive and Anxiety Symptoms Differentially Associated with Alcohol Use Behaviors: Multivariate Behavioral Genetic Analyses

This study examined whether adolescent depressive and anxiety symptoms were differentially associated with alcohol use behaviors, and how these associations were explained by genetic, shared, and nonshared environmental influences. Participants were from the Nonshared Environment and Adolescent Development project of same-sex twin/sibling pairs from 720 families. Twin/sibling depressive and anxiety symptoms were measured by self-report at Time 1 (Mage = 13.71 years, range = 9-18 years). Alcohol initiation and alcohol use severity were measured by self-report three years after Time 1 (age range = 12-21 years). Phenotypic Cholesky models were used to estimate the variance of depressive symptoms and the unique variance of anxiety symptoms (independent of depressive symptoms), and how these variances were associated with alcohol initiation and alcohol use severity. Biometric Cholesky models then estimated contributions of genetic, shared and nonshared environmental influences to these variances and covariances. Antisocial behaviors were included in all analyses to account for their associations with depressive symptoms, anxiety symptoms and alcohol use behaviors. Analyses were conducted using the full, the younger half, and the older half of the sample to explore age differences in all associations. Depressive or anxiety symptoms were not associated with alcohol use behaviors after controlling for variance shared with antisocial behaviors, although age-specific analyses suggested some potential effects to explore in future studies for late adolescence. To conclude, longitudinal associations between depressive or anxiety symptoms and alcohol use behaviors during adolescence were mainly driven by the general psychopathology factor shared between internalizing and externalizing problems.

Cross-Sensitization between Binge Eating and Binge Drinking in a Novel C57BL/6NJ Murine Model of Disease Comorbidity Requires PDE4B Activation

There is a high rate of comorbidity between binge eating (BE) and binge drinking (BD) behaviors, suggesting a common neuropathology. Recently, phosphodiesterase 4B (PDE4B) was identified as a pleiotropic gene associated with comorbid alcohol use disorder (AUD) and anorexia nervosa with BE in a genome-wide association study, implicating PDE4B as a potential contributor to shared genetic risk between these disorders. Here, we developed a novel mouse model of comorbid BE and BD in C57BL/6NJ mice in which mice underwent 10 d of BE, followed by 10 d of BD. Females exhibited cross-sensitization from BE to BD, which was apparent on the first day of ethanol access, whereas cross-sensitization emerged in males over multiple trials of BD. Accordingly immunoblotting of the nucleus accumbens tissue indicated a female-selective increase in PDE4B protein expression that was apparent on both the first and last day of BD in mice with a prior BE history. Acute pretreatment with the selective PDE4B inhibitor A33 (1.0 mg/kg) reduced the expression of cross-sensitization to BD in females on Day 1, and this effect was maintained during a 5 d A33 treatment regimen. The 5 d A33 treatment regimen also reduced expression of cross-sensitization to BD that had emerged in males over repeated sessions. These results provide preclinical, functional validation of PDE4B as a driver of food-ethanol cross-sensitization in a novel model for BE and BD comorbidity and support PDE4B in the shared genetic risk for these behavioral pathologies and as a target for pharmacotherapeutic intervention in comorbid AUD and BE behaviors.

Cell type-specific multi-omics analysis of cocaine use disorder in the human caudate nucleus

Structural and functional alterations in the brain's reward circuitry are present in cocaine use disorder (CocUD), but their molecular underpinnings remain unclear. To investigate these mechanisms, we performed single-nuclei multiome profiling on postmortem caudate nucleus tissue from six individuals with CocUD and eight controls. We profiled 30,030 nuclei, identifying 13 cell types including D1- and D2-medium spiny neurons (MSNs) and glial cells. We observed 1485 differentially regulated genes and 10,342 differentially accessible peaks, with alterations in MSNs and astrocytes related to neurotransmitter activity and synapse organization. Gene regulatory network analysis identified transcription factors including ZEB1 as exhibiting distinct CocUD-specific subclusters, activating downstream expression of ion- and calcium-channels in MSNs. Further, PDE10A emerged as a potential drug target, showing conserved effects in a rat model. This study highlights cell type-specific molecular alterations in CocUD and provides targets for further investigation, demonstrating the value of multi-omics approaches in addiction research.

Smoking, alcohol and risk of sarcopenia: a Mendelian randomisation study

OBJECTIVE

Observational studies have found that cigarette smoking increased the prevalence and incidence of sarcopenia, whereas alcohol consumption appeared to decrease the risk. These findings, however, may be susceptible to either confounding bias or reverse causation. We conducted a Mendelian randomisation (MR) study to appraise the causal relation of cigarette smoking and alcohol consumption to the risk of sarcopenia.

METHODS

Genetic instruments associated with cigarette smoking (cigarettes per day) and alcohol consumption (drinks per week) were retrieved from the publicly available genome-wide association data. Individual-level, electronic medical record-linked data on sarcopenia, grip strength and appendicular lean mass were obtained from the UK Biobank. We performed two-sample univariable and multivariable MR analyses to examine the relation of genetically determined cigarette smoking and alcohol consumption to the risk of sarcopenia and its indices.

RESULTS

One SD increase of genetically determined cigarette smoking was associated with an increased risk of sarcopenia (OR=2.51, 95% CI: 1.26 to 5.01, p=0.001), decreased grip strength (β=-0.63 kg, 95% CI: -1.13 to -0.13, p=0.01) and less appendicular lean mass (β=-0.22 kg, 95% CI: -0.44 to -0.01, p=0.04). Although one SD increase of genetically determined alcohol consumption was associated with decreased grip strength (β=-1.15 kg, 95% CI: -2.09 to -0.10, p=0.02), no statistically significant causal association was observed between genetically determined alcohol consumption and either sarcopenia (OR=0.96, 95% CI: 0.35 to 2.62, p=0.94) or appendicular lean mass (β=-0.23 kg, 95% CI: -0.91 to 0.45, p=0.51).

CONCLUSIONS

Our findings showed that genetically determined cigarette smoking, but not alcohol consumption, was causally associated with the risk of sarcopenia.

GSK3B inhibition partially reverses brain ethanol-induced transcriptomic changes in C57BL/6J mice: Expression network co-analysis with human genome-wide association studies

Alcohol use disorder (AUD) is a chronic behavioral disease with greater than 50% of its risk due to complex genetic contributions. Existing pharmacological and behavioral treatments for AUD are minimally effective and underutilized. Animal model behavioral genetics and human genome-wide association studies have begun to identify individual genes contributing to the progressive compulsive consumption of ethanol that occurs with AUD, promising possible new therapeutic targets. Our laboratory has previously identified Gsk3b as a central member in a network of ethanol-responsive genes in mouse prefrontal cortex, which altered ethanol consumption with genetic manipulation and was also significantly associated with risk for alcohol dependence in human genome-wide association studies. Here we perform detailed brain RNA sequencing transcriptomic studies to characterize a highly specific and clinically available GSK3B pharmacological inhibitor, tideglusib, as a possible therapeutic for clinical trials on treatment of AUD. A model of chronic intermittent ethanol consumption was used to study gene expression changes in prefrontal cortex and nucleus accumbens in the presence or absence of tideglusib treatment. Multivariate analysis of differentially expressed genes showed that tideglusib largely reversed ethanol- induced expression changes for two prominent clusters of genes in both prefrontal cortex and nucleus accumbens. Bioinformatic analysis showed these genes to have prominent roles in neuronal functioning and synaptic activity. Additionally, mouse brain differential gene expression data was analyzed together with human protein-protein interaction and genome-wide association studies on AUD to derive networks responding to tideglusib and relevant to human genetic risk for alcohol dependence. These studies identified discrete networks significantly enriched with genes provisionally associated with AUD, and provide key information on central hubs of such networks. Together these studies document tideglusib as a major modulator of chronic ethanol consumption-evoked brain gene expression signatures, and identify possible new targets for therapeutic modulation of AUD.

History of mental comorbidities and their relationships with drinking milestones, hazardous drug use, suicide attempts, and the ADH1B and ALDH2 genotypes in 4116 Japanese men with alcohol dependence: An exploratory study

BACKGROUND

Alcohol dependence (AD) is often comorbid with other mental disorders. We assessed how comorbidities are associated with the clinical features of AD.

METHODS

Information on the history of mental comorbidities, hazardous drug use, suicide attempts, and drinking milestones was collected on a semi-structured medical history form from 4116 Japanese male AD inpatients (2007-2018); the subjects' ADH1B and ALDH2 genotypes (rs1229984/rs671) were also determined.

RESULTS

Of the total, 889 (21.60%) patients reported a history of mental comorbidities, including mood disorders (15.48%) and insomnia (2.89%); 202 (4.91%) reported a history of hazardous drug use, and 614 (14.92%) reported suicide attempts. Comorbidities were most commonly diagnosed around the time of onset of advanced alcohol use disorder (aAUD). Patients with comorbidities who began drinking regularly showed more rapid progression to aAUD and to the start of treatment for AD. Multivariate odds ratios (MORs [95%CI]) for the fast-metabolizing ADH1B*1/*2 and ADH1B*2/*2, protective against AD, were higher in patients with comorbidities [1.43 (1.16-1.76) and 1.35 (1.11-1.66)], drug use [1.64 (1.09-2.46) and 1.60 (1.07-2.38)], and suicide attempts [1.45 (1.13-1.85) and 1.49 (1.17-1.88)] compared with the ADH1B*1/*1. MORs for the inactive protective ALDH2*1/*2 were increased only in patients with insomnia [2.65 (1.75-4.02)] compared with the ALDH2*1/*1. MORs for smoking [0.74 (0.58-0.94)] and for age ≤15 years at first drink [0.66 (0.54-0.81)] were lower in patients with comorbidities. MORs for suicide attempts were 2.87 (2.36-3.48) in patients with comorbidities and 3.38 (2.47-4.62) in patients with drug use.

CONCLUSIONS

Mental comorbidities and a history of suicide attempts were frequent in Japanese patients with AD. Risk factors for AD (ADH1B*1/*1, smoking, early initiation of drinking) were negatively associated with the risk of comorbidities, suggesting interactions between comorbidities and AD risk factors. Insomnia was positively associated with the inactive ALDH2*1/*2. AD patients with mental comorbidities require multifaceted interventions, including suicide prevention.

Gene expression differences associated with alcohol use disorder in human brain

Excessive alcohol consumption is a leading cause of preventable death worldwide. To improve understanding of neurobiological mechanisms associated with alcohol use disorder (AUD) in humans, we compared gene expression data from deceased individuals with and without AUD across two addiction-relevant brain regions: the nucleus accumbens (NAc) and dorsolateral prefrontal cortex (DLPFC). Bulk RNA-seq data from NAc and DLPFC (N ≥50 with AUD, ≥46 non-AUD) were analyzed for differential gene expression using modified negative binomial regression adjusting for technical and biological covariates. The region-level results were meta-analyzed with those from an independent dataset (NNAc = 28 AUD, 29 non-AUD; NPFC = 66 AUD, 77 non-AUD). We further tested for heritability enrichment of AUD-related phenotypes, gene co-expression networks, gene ontology enrichment, and drug repurposing. We identified 176 differentially expressed genes (DEGs; 12 in both regions, 78 in NAc only, 86 in DLPFC only) for AUD in our new dataset. After meta-analyzing with published data, we identified 476 AUD DEGs (25 in both regions, 29 in NAc only, 422 in PFC only). Of these DEGs, 17 were significant when looked up in GWAS of problematic alcohol use or drinks per week. Gene co-expression analysis showed both concordant and unique gene networks across brain regions. We also identified 29 and 436 drug compounds that target DEGs from our meta-analysis in NAc and PFC, respectively. This study identified robust AUD-associated DEGs, contributing novel neurobiological insights into AUD and highlighting genes targeted by known drug compounds, generating opportunity for drug repurposing to treat AUD.

Cell-free DNA from clinical testing as a resource of population genetic analysis

As a noninvasive biomarker, cell-free DNA (cfDNA) has achieved remarkable success in clinical applications. Notably, cfDNA is essentially DNA, and conducting whole-genome sequencing (WGS) can yield a wealth of genetic information. These invaluable data should not be confined to one-time use; instead, they should be leveraged for more comprehensive population genetic analysis, including genetic variation spectrum, population structure and genetic selection, and genome-wide association studies (GWASs), among others. Such research findings can, in turn, facilitate clinical practice, enabling more advanced and accurate disease predictions. This review explores the advantages, challenges, and current research areas of cfDNA in population genetics. We hope that this review can serve as a new chapter in the repurposing of cfDNA sequence data generated from clinical testing in population genetics.

Polygenic overlap of substance use behaviors and disorders with externalizing and internalizing problems independent of genetic correlations

BACKGROUND

Externalizing and internalizing pathways may lead to the development of substance use behaviors (SUBs) and substance use disorders (SUDs), which are all heritable phenotypes. Genetic correlation studies have indicated differences in the genetic susceptibility between SUBs and SUDs. We investigated whether these substance use phenotypes are differently related to externalizing and internalizing problems at a genetic level.

METHODS

We analyzed data from genome-wide association studies (GWAS) of four SUBs and SUDs, five externalizing traits, and five internalizing traits using the bivariate causal mixture model (MiXeR) to estimate genetic overlap beyond genetic correlation.

RESULTS

Two distinct patterns were found. SUBs demonstrated high genetic overlap but low genetic correlation of shared variants with internalizing traits, suggesting a pattern of mixed effect directions of shared genetic variants. Conversely, SUDs and externalizing traits exhibited considerable genetic overlap with moderate to high positive genetic correlation of shared variants, suggesting concordant effect direction of shared risk variants.

CONCLUSIONS

These results highlight the importance of the externalizing pathway in SUDs as well as the limited role of the internalizing pathway in SUBs. As MiXeR is not intended for the identification of specific genes, further studies are needed to reveal the underlying shared mechanisms of these traits.

The causal role of male pubertal timing for the development of externalizing and internalizing traits: results from Mendelian randomization studies

BACKGROUND

Preexisting epidemiological studies suggest that early pubertal development in males is associated with externalizing (e.g. conduct problems, risky behavior, and aggression) and internalizing (e.g. depression and anxiety) traits and disorders. However, due to problems inherent to observational studies, especially of residual confounding, it remains unclear whether these associations are causal. Mendelian randomization (MR) studies take advantage of the random allocation of genes at conception and can establish causal relationships.

METHODS

In this study, N = 76 independent genetic variants for male puberty timing (MPT) were derived from a large genome-wide association study (GWAS) on 205,354 participants and used as an instrumental variable in MR studies on 17 externalizing and internalizing traits and psychopathologies utilizing outcome GWAS with 16,400-1,045,957 participants.

RESULTS

In these MR studies, earlier MPT was significantly associated with higher scores for the overarching phenotype of 'Externalizing Traits' (b = -0.03, 95% CI [-0.06, -0.01]). However, this effect was likely driven by an earlier age at first sexual contact (b = -0.17, 95% CI [-0.21, -0.13]), without evidence for an effect on further externalizing phenotypes. Regarding internalizing phenotypes, earlier MPT was associated with higher levels of the 'Depressed Affect' subdomain of neuroticism (b = -0.04, 95% CI [-0.07, -0.01]). Late MPT was related to higher scores of internalizing traits in early life (b = 0.04, 95% CI [0.01, 0.08]).

CONCLUSIONS

This comprehensive MR study supports a causal effect of MPT on specific traits and behaviors. However, no evidence for an effect of MPT on long-term clinical outcomes (depression, anxiety disorders, alcohol dependency, cannabis abuse) was found.

Trajectories of genetic risk across dimensions of alcohol use behaviors

Background

Alcohol use behaviors (AUBs) manifest in a variety of normative and problematic ways across the life course, all of which are heritable. Twin studies show that genetic influences on AUBs change across development, but this is usually not considered in research identifying and investigating the genes linked to AUBs.

Aims

Understanding the dynamics of how genes shape AUBs could point to critical periods in which interventions may be most effective and provide insight into the mechanisms behind AUB-related genes. In this project, we investigate how genetic associations with AUBs unfold across development using longitudinal modelling of polygenic scores (PGSs).

Design

Using results from genome-wide association studies (GWASs), we created PGSs to index individual-level genetic risk for multiple AUB-related dimensions: Consumption, Problems, a variable pattern of drinking associated with a preference for beer (BeerPref), and externalizing behavior (EXT). We created latent growth curve models and tested PGSs as predictors of latent growth factors (intercept, slope, quadratic) underlying trajectories of AUBs.

Setting

PGSs were derived in six longitudinal epidemiological cohorts from the US, UK, and Finland.

Participants

Participant data were obtained from AddHealth, ALSPAC, COGA, FinnTwin12, the older Finnish Twin Cohort, and Spit for Science (total N = 19,194). These cohorts included individuals aged 14 to 67, with repeated measures collected over a span of 4 to 36 years.

Measurements

Primary measures included monthly frequency of typical alcohol consumption (CON) and heavy episodic drinking (HED).

Findings

Results indicated that higher PGSs for all AUBs are robustly associated with higher mean levels of CON and/or HED (B = 0.064-0.333, p < 3.09E-04). However, these same genetic indices were largely not associated with drinking trajectories across cohorts. In the meta-analysis, only PGSs for chronic alcohol Problems consistently predicted a steeper slope (increasing trajectory) of CON across time (B = 0.470, p = 4.20E-06).

Conclusions

The results indicate that genetic associations with AUBs not only differ between behaviors, but also across developmental time points and across cohorts. Genetic studies that take such heterogeneity into account are needed to better represent the underlying etiology of AUBs. Individual-level genetic profiles may be useful to point to personalized intervention timelines, particularly for individuals with high alcohol Problems genetic risk scores.

Elucidating neuroepigenetic mechanisms to inform targeted therapeutics for brain disorders

The evolving field of neuroepigenetics provides important insights into the molecular foundations of brain function. Novel sequencing technologies have identified patient-specific mutations and gene expression profiles involved in shaping the epigenetic landscape during neurodevelopment and in disease. Traditional methods to investigate the consequences of chromatin-related mutations provide valuable phenotypic insights but often lack information on the biochemical mechanisms underlying these processes. Recent studies, however, are beginning to elucidate how structural and/or functional aspects of histone, DNA, and RNA post-translational modifications affect transcriptional landscapes and neurological phenotypes. Here, we review the identification of epigenetic regulators from genomic studies of brain disease, as well as mechanistic findings that reveal the intricacies of neuronal chromatin regulation. We then discuss how these mechanistic studies serve as a guideline for future neuroepigenetics investigations. We end by proposing a roadmap to future therapies that exploit these findings by coupling them to recent advances in targeted therapeutics.

Sexual assault experience, depression, and heavy substance use among German adults: an exploratory mediation analysis

BACKGROUND

The experience of sexual assault may be associated with numerous adverse outcomes, including depressive disorders and heavy substance use. We aimed to examine the relationship between heavy substance use and depression in victims of sexual assault.

METHODS

We used nationally representative data from the German Health and Sexuality Survey (GeSiD) with N = 4,955 women and men aged 18-75 years. We assessed (i) the potential effect of sexual assault experience on depression mediated through hazardous alcohol, heavy tobacco, and frequent cannabis use and (ii) sexual assault experience on heavy substance use mediated through depression using logistic regression analysis to estimate proportion mediated (PM).

RESULTS

We found some evidence of mediation between sexual assault as a lifetime event and depression by heavy tobacco use (PM = 1.6%) and frequent cannabis use (PM = 14.7%) among women. We also observed mediation by hazardous alcohol use (PM = 35.5%) and heavy tobacco use (PM = 48.6%) among men who experienced childhood sexual assault. Focusing on depression as a potential mediator, we found some evidence of mediation between sexual assault as a lifetime event and heavy tobacco use among women (PM = 17.6%) and men (PM = 13.3%), and between sexual assault as a lifetime event and frequent cannabis use (PM = 26.9%) among women.

CONCLUSIONS

Our findings suggest that public health specialists, clinicians, and therapists should develop early interventions to prevent addiction and the development of depression after experiencing sexual assault.

Rapidly evolved genomic regions shape individual language abilities in present-day humans

1Minor genetic changes have produced profound differences in cognitive abilities between humans and our closest relatives, particularly in language. Despite decades of research, ranging from single-gene studies to broader evolutionary analyses[1, 2, 3, 4, 5], key questions about the genomic foundations of human language have persisted, including which sequences are involved, how they evolved, and whether similar changes occur in other vocal learning species. Here we provide the first evidence directly linking rapidly evolved genomic regions to language abilities in contemporary humans. Through extensive analysis of 65 million years of evolutionary events in over 30,000 individuals, we demonstrate that Human Ancestor Quickly Evolved Regions (HAQERs)[5] - sequences that rapidly accumulated mutations after the human-chimpanzee split - specifically influence language but not general cognition. These regions evolved to shape language development by altering binding of Forkhead domain transcription factors, including FOXP2. Strikingly, language-associated HAQER variants show higher prevalence in Neanderthals than modern humans, have been stable throughout recent human history, and show evidence of convergent evolution across other mammalian vocal learners. An unexpected pattern of balancing selection acting on these apparently beneficial alleles is explained by their pleiotropic effects on prenatal brain development contributing to birth complications, reflecting an evolutionary trade-off between language capability and reproductive fitness. By developing the Evolution Stratified-Polygenic Score analysis, we show that language capabilities likely emerged before the human-Neanderthal split - far earlier than previously thought[3, 6, 7]. Our findings establish the first direct link between ancient genomic divergence and present-day variation in language abilities, while revealing how evolutionary constraints continue to shape human cognitive development.

Tangent space functional reconfigurations in individuals at risk for alcohol use disorder

Human brain function dynamically adjusts to ever-changing stimuli from the external environment. Studies characterizing brain functional reconfiguration are, nevertheless, scarce. Here, we present a principled mathematical framework to quantify brain functional reconfiguration when engaging and disengaging from a stop signal task (SST). We apply tangent space projection (a Riemannian geometry mapping technique) to transform the functional connectomes (FCs) of 54 participants and quantify functional reconfiguration using the correlation distance of the resulting tangent-FCs. Our goal was to compare functional reconfigurations in individuals at risk for alcohol use disorder (AUD). We hypothesized that functional reconfigurations when transitioning to/from a task would be influenced by family history of AUD (FHA) and other AUD risk factors. Multilinear regression models showed that engaging and disengaging functional reconfiguration were associated with FHA and recent drinking. When engaging in the SST after a rest condition, functional reconfiguration was negatively associated with recent drinking, while functional reconfiguration when disengaging from the SST was negatively associated with FHA. In both models, several other factors contributed to the functional reconfiguration. This study demonstrates that tangent-FCs can characterize task-induced functional reconfiguration and that it is related to AUD risk.

Comparison of the multivariate genetic architecture of eight major psychiatric disorders across sex

Differences in the patterning of genetic sharing between groups of individuals may arise from biological pathways, social mechanisms, phenotyping and ascertainment. We expand genomic structural equation modeling to allow for testing genomic structural invariance (GSI), that is, the formal comparison of multivariate genetic architecture across groups. We apply GSI to compare the autosomal multivariate genetic architecture of eight psychiatric disorders spanning three factors (psychotic, neurodevelopmental and internalizing) between cisgender males and females. We find that the genetic factor structure is largely similar across sex, permitting meaningful comparisons of associations at the level of the factors. However, in females, problematic alcohol use and posttraumatic stress disorder loaded more strongly on the internalizing factor, while the neurodevelopmental disorder factor exhibited weaker genetic correlations with the other factors. Four phenotypes (educational attainment, insomnia, smoking and deprivation) showed significant, albeit small, sex-differentiated associations with the psychotic factor. As genome-wide association study samples grow and diversify, GSI will become increasingly valuable for comparing multivariate genetic architecture across groups.

Advancing Mental Health Research Through Strategic Integration of Transdiagnostic Dimensions and Genomics

Genome-wide studies are yielding a growing catalog of common and rare variants that confer risk for psychopathology. However, despite representing unprecedented progress, emerging data also indicate that the full promise of psychiatric genetics-including understanding pathophysiology and improving personalized care-will not be fully realized by targeting traditional dichotomous diagnostic categories. The current article provides reflections on themes that emerged from a 2021 National Institute of Mental Health-sponsored conference convened to address strategies for the evolving field of psychiatric genetics. As anticipated by the National Institute of Mental Health's Research Domain Criteria framework, multilevel investigations of dimensional and transdiagnostic phenotypes, particularly when integrated with biobanks and big data, will be critical to advancing knowledge. The path forward will also require more diverse representation in source studies. Additionally, progress will be catalyzed by a range of converging approaches, including capitalizing on computational methods, pursuing biological insights, working within a developmental framework, and engaging health care systems and patient communities.

2025 Heart Disease and Stroke Statistics: A Report of US and Global Data From the American Heart Association

BACKGROUND

The American Heart Association (AHA), in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, nutrition, sleep, and obesity) and health factors (cholesterol, blood pressure, glucose control, and metabolic syndrome) that contribute to cardiovascular health. The AHA Heart Disease and Stroke Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, brain health, complications of pregnancy, kidney disease, congenital heart disease, rhythm disorders, sudden cardiac arrest, subclinical atherosclerosis, coronary heart disease, cardiomyopathy, heart failure, valvular disease, venous thromboembolism, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The AHA, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States and globally to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2025 AHA Statistical Update is the product of a full year's worth of effort in 2024 by dedicated volunteer clinicians and scientists, committed government professionals, and AHA staff members. This year's edition includes a continued focus on health equity across several key domains and enhanced global data that reflect improved methods and incorporation of ≈3000 new data sources since last year's Statistical Update.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Genetic risk for trait aggression and alcohol use predict unique facets of alcohol-related aggression

OBJECTIVE

A propensity for aggression or alcohol use may be associated with alcohol-related aggression. Previous research has shown genetic overlap between alcohol use and aggression but has not looked at how alcohol-related aggression may be uniquely influenced by genetic risk for aggression or alcohol use. The present study examined the associations of genetic risk for trait aggression, alcohol use, and alcohol use disorder (AUD) with alcohol-related aggression using a polygenic risk score (PRS) approach.

METHOD

Using genome-wide association study summary statistics, PRSs were created for trait aggression, alcohol consumption, and AUD. These PRSs were used to predict the phenotype of alcohol-related aggression among drinkers in two independent samples: the University of California at San Francisco (UCSF) Family Alcoholism Study (n = 1,162) and the National Longitudinal Study of Adolescent to Adult Health (Add Health; n = 4,291).

RESULTS

There were significant associations between the AUD PRS and lifetime alcohol-related aggression in the UCSF study sample. Additionally, the trait aggression PRS was associated with three or more experiences of hitting anyone else and getting into physical fights while under the influence of alcohol, along with a composite score of three or more experiences of alcohol-related aggression, in the UCSF study sample. No significant associations were observed in the Add Health sample. Limited sex-specific genetic effects were observed.

CONCLUSIONS

These results provide preliminary evidence that genetic influences underlying alcohol use and aggression are uniquely associated with alcohol-related aggression and suggest that these associations may differ by type and frequency of alcohol-related aggression incidents. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

Genetic architecture of RNA editing, splicing and gene expression in schizophrenia

Genome wide association studies (GWAS) have been conducted over the past decades to investigate the underlying genetic origin of neuropsychiatric diseases, such as schizophrenia (SCZ). While these studies demonstrated the significance of disease-phenotype associations, there is a pressing need to fully characterize the functional relevance of disease-associated genetic variants. Functional genetic loci can affect transcriptional and post-transcriptional phenotypes that may contribute to disease pathology. Here, we investigate the associations between genetic variation and RNA editing, splicing, and overall gene expression through identification of quantitative trait loci (QTL) in the CommonMind Consortium SCZ cohort. We find that editing QTL (edQTL), splicing QTL (sQTL) and expression QTL (eQTL) possess both unique and common gene targets, which are involved in many disease-relevant pathways, including brain function and immune response. We identified two QTL that fall into all three QTL categories (seedQTL), one of which, rs146498205, targets the lincRNA gene, RP11-156P1.3. In addition, we observe that the RNA binding protein AKAP1, with known roles in neuronal regulation and mitochondrial function, had enriched binding sites among edQTL, including the seedQTL, rs146498205. We conduct colocalization with various brain disorders and find that all QTL have top colocalizations with SCZ and related neuropsychiatric diseases. Furthermore, we identify QTL within biologically relevant GWAS loci, such as in ELA2, an important tRNA processing gene associated with SCZ risk. This work presents the investigation of multiple QTL types in parallel and demonstrates how they target both distinct and overlapping SCZ-relevant genes and pathways.

Identification of risk variants and cross-disorder pleiotropy through multi-ancestry genome-wide analysis of alcohol use disorder

Alcohol use disorder (AUD) is highly heritable and burdensome worldwide. Genome-wide association studies (GWASs) can provide new evidence regarding the aetiology of AUD. We report a multi-ancestry GWAS focusing on a narrow AUD phenotype, using novel statistical tools in a total sample of 1,041,450 individuals [102,079 cases; European, 75,583; African, 20,689 (mostly African-American); Hispanic American, 3,449; East Asian, 2,254; South Asian, 104; descent]. Cross-ancestry functional analyses were performed with European and African samples. Thirty-seven genome-wide significant loci (105 variants) were identified, of which seven were novel for AUD and six for other alcohol phenotypes. Loci were mapped to genes, which show altered expression in brain regions relevant for AUD (striatum, hypothalamus, and prefrontal cortex) and encode potential drug targets (GABAergic, dopaminergic and serotonergic neurons). African-specific analysis yielded a unique pattern of immune-related gene sets. Polygenic overlap and positive genetic correlations showed extensive shared genetic architecture between AUD and both mental and general medical phenotypes, suggesting they are not only complications of alcohol use but also share genetic liability with AUD. Leveraging a cross-ancestry approach allowed identification of novel genetic loci for AUD and underscores the value of multi-ancestry genetic studies. These findings advance our understanding of AUD risk and clinically-relevant comorbidities.

Genetic evidence of the causal relationships between psychiatric disorders and cardiovascular diseases

OBJECTIVE

Our primary objective is to investigate the causal relationships between 12 psychiatric disorders (PDs) and atrial fibrillation (AF), coronary artery disease (CAD), myocardial infarction (MI), and heart failure (HF).

METHODS

Firstly, we used linkage disequilibrium score regression to calculate the genetic correlations between 12 PDs and 4 cardiovascular diseases (CVDs). Subsequently, we performed two-sample and bidirectional Mendelian randomization (MR) analyses of phenotypes with significant genetic correlations to explore the causal relationships between PDs and CVDs. Inverse variance weighted with modified weights (MW-IVW), Robust Adjusted Profile Score, Inverse Variance Weighted, weighted median and weighted mode were used to evaluate causal effects, with MW-IVW being the main analysis method. And to validate the MR results, we conducted the replicate analyses using data from the FinnGen database.

RESULTS

Conducting MR analyses in phenotypes with significant genetic correlations, we identified bidirectional causal relationships between depression (DEP) and MI (DEP as exposure: OR = 1.1324, 95 % confidence interval (CI): 1.0984-1.1663, P < 0.0001; MI as exposure: OR = 1.0268, 95 % CI: 1.0160-1.0375, P < 0.0001). Similar relationships were observed in Attention Deficit/Hyperactivity Disorder (ADHD) and HF (ADHD as exposure: OR = 1.0270, 95 % CI: 1.0144-1.0395, P < 0.0001; HF as exposure: OR = 1.0980, 95 % CI: 1.0502-1.1458, P < 0.0001).

CONCLUSIONS

In our study, we conducted the comprehensive analyses between 12 PDs and CVDs. By bidirectional MR analysis, we observed significant causal relationships between MI and DEP, HF and ADHD. These findings suggest possible complex causal relationships between PDs and CVDs.

Investigating the Contribution of Coding Variants in Alcohol Use Disorder Using Whole-Exome Sequencing Across Ancestries

BACKGROUND

Alcohol use disorder (AUD) is a leading cause of death and disability worldwide. There has been substantial progress in identifying genetic variants that underlie AUD. However, whole-exome sequencing studies of AUD have been hampered by the lack of available samples.

METHODS

We analyzed whole-exome sequencing data of 4530 samples from the Yale-Penn cohort and 469,835 samples from the UK Biobank, which represent an unprecedented resource for exploring the contribution of coding variants in AUD. After quality control, 1750 African-ancestry (1142 cases) and 2039 European-ancestry (1420 cases) samples from the Yale-Penn and 6142 African-ancestry (130 cases), 415,617 European-ancestry (12,861‬ cases), and 4607 South Asian (130 cases) samples from the UK Biobank cohorts were included in the analyses.

RESULTS

We confirmed the well-known functional variant rs1229984 in ADH1B (p = 4.88 × 10-31) and several other variants in ADH1C. Gene-based collapsing tests that considered the high allelic heterogeneity revealed the previously unreported genes CNST (p = 1.19 × 10-6), attributable to rare variants with allele frequency < 0.001, and IFIT5 (p = 3.74 × 10-6), driven by the burden of both common and rare loss-of-function and missense variants.

CONCLUSIONS

This study extends our understanding of the genetic architecture of AUD by providing insights into the contribution of rare coding variants, separately and convergently with common variants in AUD.

Genetic associations between orexin genes and phenotypes related to behavioral regulation in humans, including substance use

The hypothalamic neuropeptide system of orexin (hypocretin) neurons provides projections throughout the neuraxis and has been linked to sleep regulation, feeding and motivation for salient rewards including drugs of abuse. However, relatively little has been done to examine genes associated with orexin signaling and specific behavioral phenotypes in humans. Here, we tested for association of twenty-seven genes involved in orexin signaling with behavioral phenotypes in humans. We tested the full gene set, functional subsets, and individual genes involved in orexin signaling. Our primary phenotype of interest was Externalizing, a composite factor comprised of behaviors and disorders associated with reward-seeking, motivation, and behavioral regulation. We also tested for association with additional phenotypes that have been related to orexin regulation in model organism studies, including alcohol consumption, problematic alcohol use, daytime sleepiness, insomnia, cigarettes per day, smoking initiation, and body mass index. The composite set of 27 genes corresponding to orexin function was highly associated with Externalizing, as well as with alcohol consumption, insomnia, cigarettes per day, smoking initiation and BMI. In addition, all gene subsets (except the OXR2/HCRTR2 subset) were associated with Externalizing. BMI was significantly associated with all gene subsets. The "validated factors for PPOX/HCRT" and "PPOX/HCRT upregulation" gene subsets also were associated with alcohol consumption. Individually, 8 genes showed a strong association with Externalizing, 12 with BMI, 7 with smoking initiation, 3 with alcohol consumption, and 2 with problematic alcohol use, after correction for multiple testing. This study indicates that orexin genes are associated with multiple behaviors and disorders related to self-regulation in humans. This is consistent with prior work in animals that implicated orexin signaling in motivational activation induced by salient stimuli, and supports the hypothesis that orexin signaling is an important potential therapeutic target for numerous behavioral disorders.

Heterogeneity analysis provides evidence for a genetically homogeneous subtype of bipolar-disorder

BACKGROUND

Bipolar Disorder (BD) is a complex disease. It is heterogeneous, both at the phenotypic and genetic level, although the extent and impact of this heterogeneity is not fully understood. One way to assess this heterogeneity is to look for patterns in the subphenotype data. Because of the variability in how phenotypic data was collected by the various BD studies over the years, homogenizing this subphenotypic data is a challenging task, and so is replication. An alternative methodology, taken here, is to set aside the intricacies of subphenotype and allow the genetic data itself to determine which subjects define a homogeneous genetic subgroup (termed 'bicluster' below).

RESULTS

In this paper, we leverage recent advances in heterogeneity analysis to look for genetically-driven subgroups (i.e., biclusters) within the broad phenotype of Bipolar Disorder. We first apply this covariate-corrected biclustering algorithm to a cohort of 2524 BD cases and 4106 controls from the Bipolar Disease Research Network (BDRN) within the Psychiatric Genomics Consortium (PGC). We find evidence of genetic heterogeneity delineating a statistically significant bicluster comprising a subset of BD cases which exhibits a disease-specific pattern of differential-expression across a subset of SNPs. This disease-specific genetic pattern (i.e., 'genetic subgroup') replicates across the remaining data-sets collected by the PGC containing 5781/8289, 3581/7591, and 6825/9752 cases/controls, respectively. This genetic subgroup (discovered without using any BD subtype information) was more prevalent in Bipolar type-I than in Bipolar type-II.

CONCLUSIONS

Our methodology has successfully identified a replicable homogeneous genetic subgroup of bipolar disorder. This subgroup may represent a collection of correlated genetic risk-factors for BDI. By investigating the subgroup's bicluster-informed polygenic-risk-scoring (PRS), we find that the disease-specific pattern highlighted by the bicluster can be leveraged to eliminate noise from our GWAS analyses and improve risk prediction. This improvement is particularly notable when using only a relatively small subset of the available SNPs, implying improved SNP replication. Though our primary focus is only the analysis of disease-related signal, we also identify replicable control-related heterogeneity.

The left amygdala is genetically sexually-dimorphic: multi-omics analysis of structural MRI volumes

Brain anatomy plays a key role in complex behaviors and mental disorders that are sexually divergent. While our understanding of the sex differences in the brain anatomy remains relatively limited, particularly of the underlying genetic and molecular mechanisms that contribute to these differences. We performed the largest study of sex differences in brain volumes (N = 33,208) by examining sex differences both in the raw brain volumes and after controlling the whole brain volumes. Genetic correlation analysis revealed sex differences only in the left amygdala. We compared transcriptome differences between males and females using data from GTEx and characterized cell-type compositions using GTEx bulk amygdala RNA-seq data and LIBD amygdala single-cell reference profiles. We also constructed polygenic risk scores (PRS) to investigate sex-specific genetic correlations between left amygdala volume and mental disorders (N = 25,576~105,318) of Psychiatric Genomics Consortium and other traits of UKB (N = 347,996). Although there were pronounced sex differences in brain volumes, there was no difference in the heritability between sexes. There was a significant sex-specific genetic correlation between male and female left amygdala. We identified sex-differentiated genetic effects of PRSs for schizophrenia on left amygdala volume, as well as significant sex-differentiated genetic correlations between PRSs of left amygdala and six traits in UKB. We also found several sex-differentially expressed genes in the amygdala. These findings not only advanced the current knowledge of genetic basis of sex differences in brain anatomy, but also presented an important clue for future research on the mechanism of sex differences in mental disorders and targeted treatments.

The effects of alcohol use severity and polygenic risk on gray matter volumes in young adults

Genetic factors contribute to alcohol misuse. Chronic alcohol consumption is associated with decreases in gray matter volumes (GMVs) of the brain. However, it remains unclear whether or how genetic risks may alter GMVs independent of the effects of alcohol exposure. Here, we employed the Human Connectome Project data of neurotypical adults (n = 995; age 22-35; 618 women) and, with voxel-based morphometry analysis, computed the GMVs of 166 regions in the automated anatomical atlas 3. Alcohol use behaviors were assessed with the Semi-Structured Assessment for the Genetics of Alcoholism. Alcohol use severity was quantified by the first principal component (PC1) identified of principal component analysis of 15 drinking measures. Polygenic risk scores (PRS) for alcohol dependence were computed for all subjects using the Psychiatric Genomics Consortium study of alcohol dependence as the base sample. With age, sex, race, and total intracranial volume as covariates, we evaluated the relationships of regional GMVs with PC1 and PRS together in a linear regression. PC1 was negatively correlated with GMVs of right insula and Heschl's gyrus, and PRS was positively correlated with GMVs of left posterior orbitofrontal cortex, bilateral intralaminar nuclei of the thalamus and lingual gyri. These findings suggest distinct volumetric neural markers of drinking severity and genetic risks of alcohol misuse. Notably, in contrast to volumetric reduction, the genetic risks of dependent drinking may involve larger regional volumes in the reward, emotion, and saliency circuits.

A genetic exploration of the relationship between posttraumatic stress disorder and cardiovascular diseases

Experiencing a traumatic event may lead to Posttraumatic Stress Disorder (PTSD), including symptoms such as flashbacks and hyperarousal. Individuals suffering from PTSD are at increased risk of cardiovascular disease (CVD), but it is unclear why. This study assesses shared genetic liability and potential causal pathways between PTSD and CVD. We leveraged summary-level data of genome-wide association studies (PTSD: N = 1,222,882; atrial fibrillation (AF): N = 482,409; coronary artery disease (CAD): N = 1,165,690; hypertension (HT): N = 458,554; heart failure (HF): N = 977,323). First, we estimated genetic correlations and utilized genomic structural equation modeling to identify a common genetic factor for PTSD and CVD. Next, we assessed biological, behavioural, and psychosocial factors as potential mediators. Finally, we employed multivariable Mendelian randomization to examine causal pathways between PTSD and CVD, incorporating the same potential mediators. Significant genetic correlations were found between PTSD and CAD, HT, and HF (rg = 0.21-0.32, p ≤ 3.08 · 10-16), but not between PTSD and AF. Insomnia, smoking, alcohol dependence, waist-to-hip ratio, and inflammation (IL6, C-reactive protein) partly mediated these associations. Mendelian randomization indicated that PTSD causally increases CAD (IVW OR = 1.53, 95% CIs = 1.19-1.96, p = 0.001), HF (OR = 1.44, CIs = 1.08-1.92, p = 0.012), and to a lesser degree HT (OR = 1.25, CIs = 1.05-1.49, p = 0.012). While insomnia, smoking, alcohol, and inflammation were important mediators, independent causal effects also remained. In addition to shared genetic liability between PTSD and CVD, we present strong evidence for causal effects of PTSD on CVD. Crucially, we implicate specific lifestyle and biological mediators (insomnia, substance use, inflammation) which has important implications for interventions to prevent CVD in PTSD patients.

Prevalence and correlates of common mental disorders among participants of the Uganda Genome Resource: Opportunities for psychiatric genetics research

Genetics research has potential to alleviate the burden of mental disorders in low- and middle-income-countries through identification of new mechanistic pathways which can lead to efficacious drugs or new drug targets. However, there is currently limited genetics data from Africa. The Uganda Genome Resource provides opportunity for psychiatric genetics research among underrepresented people from Africa. We aimed at determining the prevalence and correlates of major depressive disorder (MDD), suicidality, post-traumatic stress disorder (PTSD), alcohol abuse, generalised anxiety disorder (GAD) and probable attention-deficit hyperactivity disorder (ADHD) among participants of the Uganda Genome Resource. Standardised tools assessed for each mental disorder. Prevalence of each disorder was calculated with 95% confidence intervals. Multivariate logistic regression models evaluated the association between each mental disorder and associated demographic and clinical factors. Among 985 participants, prevalence of the disorders were: current MDD 19.3%, life-time MDD 23.3%, suicidality 10.6%, PTSD 3.1%, alcohol abuse 5.7%, GAD 12.9% and probable ADHD 9.2%. This is the first study to determine the prevalence of probable ADHD among adult Ugandans from a general population. We found significant association between sex and alcohol abuse (adjusted odds ratio [AOR] = 0.26 [0.14,0.45], p < 0.001) and GAD (AOR = 1.78 [1.09,2.49], p = 0.019) respectively. We also found significant association between body mass index and suicidality (AOR = 0.85 [0.73,0.99], p = 0.041), alcohol abuse (AOR = 0.86 [0.78,0.94], p = 0.003) and GAD (AOR = 0.93 [0.87,0.98], p = 0.008) respectively. We also found a significant association between high blood pressure and life-time MDD (AOR = 2.87 [1.08,7.66], p = 0.035) and probable ADHD (AOR = 1.99 [1.00,3.97], p = 0.050) respectively. We also found a statistically significant association between tobacco smoking and alcohol abuse (AOR = 3.2 [1.56,6.67], p = 0.002). We also found ever been married to be a risk factor for probable ADHD (AOR = 2.12 [0.88,5.14], p = 0.049). The Uganda Genome Resource presents opportunity for psychiatric genetics research among underrepresented people from Africa.

Next-generation biomarkers for alcohol consumption and alcohol use disorder diagnosis, prognosis, and treatment: A critical review

This critical review summarizes the current state of omics-based biomarkers in the alcohol research field. We first provide definitions and background information on alcohol and alcohol use disorder (AUD), biomarkers, and "omic" technologies. We next summarize using (1) genetic information as risk/prognostic biomarkers for the onset of alcohol-related problems and the progression from regular drinking to problematic drinking (including AUD), (2) epigenetic information as diagnostic biomarkers for AUD and risk biomarkers for alcohol consumption, (3) transcriptomic information as diagnostic biomarkers for AUD, risk biomarkers for alcohol consumption, and (4) metabolomic information as diagnostic biomarkers for AUD, risk biomarkers for alcohol consumption, and predictive biomarkers for response to acamprosate in subjects with AUD. In the final section, the clinical implications of the findings are discussed, and recommendations are made for future research.

Clinical, Genomic, and Neurophysiological Correlates of Lifetime Suicide Attempts among Individuals with an Alcohol Use Disorder

Introduction

Research has identified multiple risk factors associated with suicide attempt (SA) among individuals with psychiatric illness. However, there is limited research among those with an alcohol use disorder (AUD), despite their disproportionately higher rates of SA.

Methods

We examined lifetime SA in 4,068 individuals with an AUD from the Collaborative Study on the Genetics of Alcoholism (23% lifetime SA; 53% female; mean age: 38). We explored risk for lifetime SA across other clinical conditions ascertained from a clinical interview, polygenic scores for comorbid psychiatric problems, and neurocognitive functioning.

Results

Participants with an AUD who attempted suicide had greater rates of trauma exposure, major depressive disorder, post-traumatic stress disorder, other substance use disorders (SUDs), and suicidal ideation. Polygenic scores for SA, depression, and PTSD were associated with increased odds of reporting an SA (ORs = 1.22-1.44). Participants who reported an SA also had decreased right hemispheric frontal-parietal theta and decreased interhemispheric temporal-parietal alpha electroencephalogram resting-state coherences relative to those who did not, but differences were small.

Conclusions

Overall, individuals with an AUD who report lifetime SA experience greater levels of trauma, have more severe comorbidities, and carry increased polygenic risk for other psychiatric problems. Our results demonstrate the need to further investigate SAs in the presence of SUDs.

A multi-omics Mendelian randomization study identifies new therapeutic targets for alcohol use disorder and problem drinking

Integrating proteomic and transcriptomic data with genetic architectures of problematic alcohol use and alcohol consumption behaviours can advance our understanding and help identify therapeutic targets. We conducted systematic screens using genome-wise association study data from ~3,500 cortical proteins (N = 722) and ~6,100 genes in 8 canonical brain cell types (N = 192) with 4 alcohol-related outcomes (N ≤ 537,349), identifying 217 cortical proteins and 255 cell-type genes associated with these behaviours, with 36 proteins and 37 cell-type genes being new. Although there was limited overlap between proteome and transcriptome targets, downstream neuroimaging revealed shared neurophysiological pathways. Colocalization with independent genome-wise association study data further prioritized 16 proteins, including CAB39L and NRBP1, and 12 cell-type genes, implicating mechanisms such as mTOR signalling. In addition, genes such as SAMHD1, VIPAS39, NUP160 and INO80E were identified as having favourable neuropsychiatric profiles. These findings provide insights into the genetic landscapes governing problematic alcohol use and alcohol consumption behaviours, highlighting promising therapeutic targets for future research.

Identification of gene co-expression modules from zebrafish brain data: Applications in psychiatry illustrated through alcohol-related traits

Cumulative evidence suggests that zebrafish is a useful model in psychiatric research. Weighted Gene Co-expression Network Analysis (WGCNA) enables the reduction of genome-wide expression data to modules of highly co-expressed genes, which are hypothesized to interact within molecular networks. In this study, we first applied WGCNA to zebrafish brain expression data across different experimental conditions. Then, we characterized the different co-expression modules by gene-set enrichment analysis and hub gene-phenotype association. Finally, we analyzed association of polygenic risk scores (PRSs) based on genes of some interesting co-expression modules with alcohol dependence in 524 patients and 729 controls from Galicia, using competitive tests. Our approach revealed 34 co-expression modules in the zebrafish brain, with some showing enrichment in human synaptic genes, brain tissues, or brain developmental stages. Moreover, certain co-expression modules were enriched in psychiatry-related GWAS and comprised hub genes associated with psychiatry-related traits in both human GWAS and zebrafish models. Expression patterns of some co-expression modules were associated with the tested experimental conditions, mainly with substance withdrawal and cold stress. Notably, a PRS based on genes from co-expression modules exclusively associated with substance withdrawal in zebrafish showed a stronger association with human alcohol dependence than PRSs based on randomly selected brain-expressed genes. In conclusion, our analysis led to the identification of co-expressed gene modules that may model human brain gene networks involved in psychiatry-related traits. Specifically, we detected a cluster of co-expressed genes whose expression was exclusively associated with substance withdrawal in zebrafish, which significantly contributed to alcohol dependence susceptibility in humans.

Alcohol Use Disorder Polygenic Score Compared With Family History and ADH1B

Importance

Identification of individuals at high risk of alcohol use disorder (AUD) and subsequent application of prevention and intervention programs has been reported to decrease the incidence of AUD. The polygenic score (PGS), which measures an individual's genetic liability to a disease, can potentially be used to evaluate AUD risk.

Objective

To assess the estimability and generalizability of the PGS, compared with family history and ADH1B, in evaluating the risk of AUD among populations of European ancestry.

Design, Setting, and Participants

This genetic association study was conducted between October 1, 2023, and May 21, 2024. A 2-stage design was used. First, the pruning and thresholding method was used to calculate PGSs in the screening stage. Second, the estimability and generalizability of the best PGS was determined using 2 independent samples in the testing stage. Three cohorts ascertained to study AUD were used in the screening stage: the Collaborative Study on the Genetics of Alcoholism (COGA), the Study of Addiction: Genetics and Environment (SAGE), and the Australian Twin-Family Study of Alcohol Use Disorder (OZALC). The All of Us Research Program (AOU), which comprises participants with diverse backgrounds and conditions, and the Indiana Biobank (IB), consisting of Indiana University Health system patients, were used to test the best PGS. For the COGA, SAGE, and OZALC cohorts, cases with AUD were determined using Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) or Fifth Edition (DSM-5) criteria; controls did not meet any criteria or did not have any other substance use disorders. For the AOU and IB cohorts, cases with AUD were identified using International Classification of Diseases, Ninth Revision (ICD-9) or International Classification of Diseases, Tenth Revision (ICD-10) codes; controls were aged 21 years or older and did not have AUD.

Exposure

The PGS was calculated using single-nucleotide variants with concordant effects in 3 large-scale genome-wide association studies of AUD-related phenotypes.

Main Outcomes and Measures

The main outcome was AUD determined with DSM-IV or DSM-5 criteria and ICD-9 or ICD-10 codes. Generalized linear mixed models and logistic regression models were used to analyze related and unrelated samples, respectively.

Results

The COGA, SAGE, and OZALC cohorts included a total of 8799 samples (6323 cases and 2476 controls; 50.6% were men). The AOU cohort had a total of 116 064 samples (5660 cases and 110 404 controls; 60.4% were women). The IB cohort had 6373 samples (936 cases and 5437 controls; 54.9% were women). The 5% of samples with the highest PGS in the AOU and IB cohorts were approximately 2 times more likely to develop AUD (odds ratio [OR], 1.96 [95% CI, 1.78-2.16]; P = 4.10 × 10-43; and OR, 2.07 [95% CI, 1.59-2.71]; P = 9.15 × 10-8, respectively) compared with the remaining 95% of samples; these ORs were comparable to family history of AUD. For the 5% of samples with the lowest PGS in the AOU and IB cohorts, the risk of AUD development was approximately half (OR, 0.53 [95% CI, 0.45-0.62]; P = 6.98 × 10-15; and OR, 0.57 [95% CI, 0.39-0.84]; P = 4.88 × 10-3) compared with the remaining 95% of samples; these ORs were comparable to the protective effect of ADH1B. PGS had similar estimabilities in male and female individuals.

Conclusions and Relevance

In this study of AUD risk among populations of European ancestry, PGSs were calculated using concordant single-nucleotide variants and the best PGS was tested in targeted datasets. The findings suggest that the PGS may potentially be used to evaluate AUD risk. More datasets with similar AUD prevalence as in general populations are needed to further test the generalizability of PGS.

Identification of novel genetic loci and candidate genes for progressive ethanol consumption in diversity outbred mice

Mouse behavioral genetic mapping studies can identify genomic intervals modulating complex traits under well-controlled environmental conditions and have been used to study ethanol behaviors to aid in understanding genetic risk and the neurobiology of alcohol use disorder (AUD). However, historically such studies have produced large confidence intervals, thus complicating identification of potential causal candidate genes. Diversity Outbred (DO) mice offer the ability to perform high-resolution quantitative trait loci (QTL) mapping on a very genetically diverse background, thus facilitating identification of candidate genes. Here, we studied a population of 636 male DO mice with four weeks of intermittent ethanol access via a three-bottle choice procedure, producing a progressive ethanol consumption phenotype. QTL analysis identified 3 significant (Chrs 3, 4, and 12) and 13 suggestive loci for ethanol-drinking behaviors with narrow confidence intervals (1-4 Mbp for significant QTLs). Results suggested that genetic influences on initial versus progressive ethanol consumption were localized to different genomic intervals. A defined set of positional candidate genes were prioritized using haplotype analysis, identified coding polymorphisms, prefrontal cortex transcriptomics data, human GWAS data and prior rodent gene set data for ethanol or other misused substances. These candidates included Car8, the lone gene with a significant cis-eQTL within a Chr 4 QTL for week four ethanol consumption. These results represent the highest-resolution genetic mapping of ethanol consumption behaviors in mice to date, providing identification of novel loci and candidate genes for study in relation to the neurobiology of AUD.

Alcohol Use Disorder-Associated DNA Methylation in the Nucleus Accumbens and Dorsolateral Prefrontal Cortex

Background

Alcohol use disorder (AUD) has a profound public health impact. However, understanding of the molecular mechanisms that underlie the development and progression of AUD remains limited. Here, we investigated AUD-associated DNA methylation changes within and across 2 addiction-relevant brain regions, the nucleus accumbens and dorsolateral prefrontal cortex.

Methods

Illumina HumanMethylation EPIC array data from 119 decedents (61 cases, 58 controls) were analyzed using robust linear regression with adjustment for technical and biological variables. Associations were characterized using integrative analyses of public annotation data and published genetic and epigenetic studies. We also tested for brain region-shared and brain region-specific associations using mixed-effects modeling and assessed implications of these results using public gene expression data from human brain.

Results

At a false discovery rate of ≤.05, we identified 105 unique AUD-associated CpGs (annotated to 120 genes) within and across brain regions. AUD-associated CpGs were enriched in histone marks that tag active promoters, and our strongest signals were specific to a single brain region. Some concordance was found between our results and those of earlier published alcohol use or dependence methylation studies. Of the 120 genes, 23 overlapped with previous genetic associations for substance use behaviors, some of which also overlapped with previous addiction-related methylation studies.

Conclusions

Our findings identify AUD-associated methylation signals and provide evidence of overlap with previous genetic and methylation studies. These signals may constitute predisposing genetic differences or robust methylation changes associated with AUD, although more work is needed to further disentangle the mechanisms that underlie these associations and their implications for AUD.

A multi-ancestry cerebral cortex transcriptome-wide association study identifies genes associated with smoking behaviors

Transcriptome-wide association studies (TWAS) have provided valuable insight in identifying genes that may impact cigarette smoking. Most of previous studies, however, mainly focused on European ancestry. Limited TWAS studies have been conducted across multiple ancestries to explore genes that may impact smoking behaviors. In this study, we used cis-eQTL data of cerebral cortex from multiple ancestries in MetaBrain, including European, East Asian, and African samples, as reference panels to perform multi-ancestry TWAS analyses on ancestry-matched GWASs of four smoking behaviors including smoking initiation, smoking cessation, age of smoking initiation, and number of cigarettes per day in GWAS & Sequencing Consortium of Alcohol and Nicotine use (GSCAN). Multiple-ancestry fine-mapping approach was conducted to identify credible gene sets associated with these four traits. Enrichment and module network analyses were further performed to explore the potential roles of these identified gene sets. A total of 719 unique genes were identified to be associated with at least one of the four smoking traits across ancestries. Among those, 249 genes were further prioritized as putative causal genes in multiple ancestry-based fine-mapping approach. Several well-known smoking-related genes, including PSMA4, IREB2, and CHRNA3, showed high confidence across ancestries. Some novel genes, e.g., TSPAN3 and ANK2, were also identified in the credible sets. The enrichment analysis identified a series of critical pathways related to smoking such as synaptic transmission and glutamate receptor activity. Leveraging the power of the latest multi-ancestry GWAS and eQTL data sources, this study revealed hundreds of genes and relevant biological processes related to smoking behaviors. These findings provide new insights for future functional studies on smoking behaviors.

Genetic Heterogeneity Across Dimensions of Alcohol Use Behaviors

OBJECTIVE

Increasingly large samples in genome-wide association studies (GWASs) for alcohol use behaviors (AUBs) have led to an influx of implicated genes, yet the clinical and functional understanding of these associations remains low, in part because most GWASs do not account for the complex and varied manifestations of AUBs. This study applied a multidimensional framework to investigate the latent genetic structure underlying heterogeneous dimensions of AUBs.

METHODS

Multimodal assessments (self-report, interview, electronic health records) were obtained from approximately 400,000 UK Biobank participants. GWAS was conducted for 18 distinct AUBs, including consumption, drinking patterns, alcohol problems, and clinical sequelae. Latent genetic factors were identified and carried forward to GWAS using genomic structural equation modeling, followed by functional annotation, genetic correlation, and enrichment analyses to interpret the genetic associations.

RESULTS

Four latent factors were identified: Problems, Consumption, BeerPref (declining alcohol consumption with a preference for drinking beer), and AtypicalPref (drinking fortified wine and spirits). The latent factors were moderately correlated (rg values, 0.12-0.57) and had distinct patterns of associations, with BeerPref in particular implicating many novel genomic regions. Patterns of regional and cell type-specific gene expression in the brain also differed between the latent factors.

CONCLUSIONS

Deep phenotyping is an important next step to improve understanding of the genetic etiology of AUBs, in addition to increasing sample size. Further effort is required to uncover the genetic heterogeneity underlying AUBs using methods that account for their complex, multidimensional nature.

Interactive effects of genetic liability and combat exposure on risk of alcohol use disorder among US service members

BACKGROUND

An improved understanding of pathways to alcohol use disorder (AUD) among service members may inform efforts to reduce the substantial impact of AUD on this population. This study examined whether the relationship between a service-related risk factor (combat exposure) and later AUD varied based on individual differences in genetic liability to AUD.

METHODS

The sample consisted of 1203 US Army soldiers of genetically determined European ancestry who provided survey and genomic data in the Army STARRS Pre/Post Deployment Study (PPDS; 2012-2014) and follow-up survey data in wave 1 of the STARRS Longitudinal Study (2016-2018). Logistic regression was used to estimate the conditional effect of combat exposure level (self-reported in PPDS) on odds of probable AUD diagnosis at follow-up, as a function of a soldier's polygenic risk score (PRS) for AUD.

RESULTS

The direct effect of combat exposure on AUD risk was non-significant (AOR=1.12, 95 % CI=1.00-1.26, p=.051); however, a significant combat exposure x PRS interaction was observed (AOR=1.60, 95 % CI=1.03-2.46, p=.033). Higher combat exposure was more strongly associated with elevated AUD risk among soldiers with heightened genetic liability to AUD.

CONCLUSIONS

The effect of combat exposure on AUD risk appeared to vary based on a service member's level of genetic risk for AUD. Continued investigation is warranted to determine whether PRS can help stratify AUD risk within stress-exposed groups such as combat-deployed soldiers. Such efforts might reveal opportunities to focus prevention efforts on smaller subgroups at the intersection of having both environmental exposures and genetic vulnerability to AUD.

The genetic landscape of substance use disorders

Substance use disorders represent a significant public health concern with considerable socioeconomic implications worldwide. Twin and family-based studies have long established a heritable component underlying these disorders. In recent years, genome-wide association studies of large, broadly phenotyped samples have identified regions of the genome that harbour genetic risk variants associated with substance use disorders. These regions have enabled the discovery of putative causal genes and improved our understanding of genetic relationships among substance use disorders and other traits. Furthermore, the integration of these data with clinical information has yielded promising insights into how individuals respond to medications, allowing for the development of personalized treatment approaches based on an individual's genetic profile. This review article provides an overview of recent advances in the genetics of substance use disorders and demonstrates how genetic data may be used to reduce the burden of disease and improve public health outcomes.

Integrated Single-Cell Multiomic Profiling of Caudate Nucleus Suggests Key Mechanisms in Alcohol Use Disorder

Alcohol use disorder (AUD) induces complex transcriptional and regulatory changes across multiple brain regions including the caudate nucleus, which remains understudied. Using paired single-nucleus RNA-seq and ATAC-seq on caudate samples from 143 human postmortem brains, including 74 with AUD, we identified 17 distinct cell types. We found that a significant portion of the alcohol-induced changes in gene expression occurred through altered chromatin accessibility. Notably, we identified novel transcriptional and chromatin accessibility differences in medium spiny neurons, impacting pathways such as RNA metabolism and immune response. A small cluster of D1/D2 hybrid neurons showed distinct differences, suggesting a unique role in AUD. Microglia exhibited distinct activation states deviating from classical M1/M2 designations, and astrocytes entered a reactive state partially regulated by JUND , affecting glutamatergic synapse pathways. Oligodendrocyte dysregulation, driven in part by OLIG2 , was linked to demyelination and increased TGF-β1 signaling from microglia and astrocytes. We also observed increased microglia-astrocyte communication via the IL-1β pathway. Leveraging our multiomic data, we performed cell type-specific expression quantitative trait loci analysis, integrating that with public genome-wide association studies to identify AUD risk genes such as ADAL and PPP2R3C , providing a direct link between genetic variants, chromatin accessibility, and gene expression in AUD. These findings not only provide new insights into the genetic and cellular mechanisms in the caudate related to AUD but also demonstrate the broader utility of large-scale multiomic studies in uncovering complex gene regulation across diverse cell types, which has implications beyond the substance use field.

Heterogeneity analysis provides evidence for a genetically homogeneous subtype of bipolar-disorder

Background

Bipolar Disorder (BD) is a complex disease. It is heterogeneous, both at the phenotypic and genetic level, although the extent and impact of this heterogeneity is not fully understood. One way to assess this heterogeneity is to look for patterns in the subphenotype data. Because of the variability in how phenotypic data was collected by the various BD studies over the years, homogenizing this subphenotypic data is a challenging task, and so is replication. An alternative methodology, taken here, is to set aside the intricacies of subphenotype and allow the genetic data itself to determine which subjects define a homogeneous genetic subgroup (termed 'bicluster' below).

Results

In this paper, we leverage recent advances in heterogeneity analysis to look for genetically-driven subgroups (i.e., biclusters) within the broad phenotype of Bipolar Disorder. We first apply this covariate-corrected biclustering algorithm to a cohort of 2524 BD cases and 4106 controls from the Bipolar Disease Research Network (BDRN) within the Psychiatric Genomics Consortium (PGC). We find evidence of genetic heterogeneity delineating a statistically significant bicluster comprising a subset of BD cases which exhibits a disease-specific pattern of differential-expression across a subset of SNPs. This disease-specific genetic pattern (i.e., 'genetic subgroup') replicates across the remaining data-sets collected by the PGC containing 5781/8289, 3581/7591, and 6825/9752 cases/controls, respectively. This genetic subgroup (discovered without using any BD subtype information) was more prevalent in Bipolar type-I than in Bipolar type-II.

Conclusions

Our methodology has successfully identified a replicable homogeneous genetic subgroup of bipolar disorder. This subgroup may represent a collection of correlated genetic risk-factors for BDI. By investigating the subgroup's bicluster-informed polygenic-risk-scoring (PRS), we find that the disease-specific pattern highlighted by the bicluster can be leveraged to eliminate noise from our GWAS analyses and improve risk prediction. This improvement is particularly notable when using only a relatively small subset of the available SNPs, implying improved SNP replication. Though our primary focus is only the analysis of disease-related signal, we also identify replicable control-related heterogeneity.

Genomic structural equation modeling reveals latent phenotypes in the human cortex with distinct genetic architecture

Genetic contributions to human cortical structure manifest pervasive pleiotropy. This pleiotropy may be harnessed to identify unique genetically-informed parcellations of the cortex that are neurobiologically distinct from functional, cytoarchitectural, or other cortical parcellation schemes. We investigated genetic pleiotropy by applying genomic structural equation modeling (SEM) to map the genetic architecture of cortical surface area (SA) and cortical thickness (CT) for 34 brain regions recently reported in the ENIGMA cortical GWAS. Genomic SEM uses the empirical genetic covariance estimated from GWAS summary statistics with LD score regression (LDSC) to discover factors underlying genetic covariance, which we are denoting genetically informed brain networks (GIBNs). Genomic SEM can fit a multivariate GWAS from summary statistics for each of the GIBNs, which can subsequently be used for LD score regression (LDSC). We found the best-fitting model of cortical SA identified 6 GIBNs and CT identified 4 GIBNs, although sensitivity analyses indicated that other structures were plausible. The multivariate GWASs of the GIBNs identified 74 genome-wide significant (GWS) loci (p < 5 × 10-8), including many previously implicated in neuroimaging phenotypes, behavioral traits, and psychiatric conditions. LDSC of GIBN GWASs found that SA-derived GIBNs had a positive genetic correlation with bipolar disorder (BPD), and cannabis use disorder, indicating genetic predisposition to a larger SA in the specific GIBN is associated with greater genetic risk of these disorders. A negative genetic correlation was observed between attention deficit hyperactivity disorder (ADHD) and major depressive disorder (MDD). CT GIBNs displayed a negative genetic correlation with alcohol dependence. Even though we observed model instability in our application of genomic SEM to high-dimensional data, jointly modeling the genetic architecture of complex traits and investigating multivariate genetic links across neuroimaging phenotypes offers new insights into the genetics of cortical structure and relationships to psychopathology.

Identification and validation of a novel gene ARVCF associated with alcohol dependence among Chinese population

Alcohol dependence is a heritable disorder, yet its genetic basis and underlying mechanisms remain poorly understood, especially in Chinese population. In this study, we conducted gene-based and transcript-based association tests and found a significant association between ARVCF expression in the cortex and hippocampus of the brain and alcohol use in a cohort of 1,329 individuals with Chinese ancestry. Further analysis using the effective-median-based Mendelian randomization framework for inferring the causal genes (EMIC) revealed a causal relationship between ARVCF expression in the frontal cortex and alcohol use. Moreover, leveraging extensive European alcohol dependence data, our gene association tests and EMIC analysis showed that ARVCF expression in the nucleus accumbens was significantly associated with alcohol dependence. Finally, animal studies indicated that Arvcf knockout mice lacked conditioned place preference for alcohol. Together, our combined human genetic and animal studies indicate that ARVCF plays a crucial role in alcohol dependence.