Survival and Neurologic Outcomes From Pharmacologic Peptide Administration During Cardiopulmonary Resuscitation of Pulseless Electrical Activity.

BACKGROUND: Outcomes from cardiopulmonary resuscitation (CPR) following sudden cardiac arrest are suboptimal. Postresuscitation targeted temperature management has been shown to have benefit in subjects with sudden cardiac arrest due to ventricular fibrillation, but there are few data for outcomes from sudden cardiac arrest due to pulseless electrical activity. In addition, intra-CPR cooling is more effective than postresuscitation cooling. Physical cooling is associated with increased protein kinase B activity. Therefore, our group developed a novel peptide, TAT-PHLPP9c, which regulates protein kinase B. We hypothesized that when given during CPR, TAT-PHLPP9c would improve survival and neurologic outcomes following pulseless electrical activity arrest. METHODS AND RESULTS: In 24 female pigs, pulseless electrical activity was induced by inflating balloon catheters in the right coronary and left anterior descending arteries for ≈7 minutes. Advanced life support was initiated. In 12 control animals, epinephrine was given after 1 and 3 minutes. In 12 peptide-treated animals, 7.5 mg/kg TAT-PHLPP9c was also administered at 1 and 3 minutes of CPR. The balloons were removed after 2 minutes of support. Animals were recovered and neurologically scored 24 hours after return of spontaneous circulation. Return of spontaneous circulation was more common in the peptide group, but this difference was not significant (8/12 control versus 12/12 peptide; P=0.093), while fully intact neurologic survival was significantly more common in the peptide group (0/12 control versus 11/12 peptide; P<0.00001). TAT-PHLPP9c significantly increased myocardial nicotinamide adenine dinucleotide levels. CONCLUSIONS: TAT-PHLPP9c resulted in improved survival with full neurologic function after sudden cardiac arrest in a swine model of pulseless electrical activity, and the peptide shows potential as an intra-CPR pharmacologic agent.

A single-nucleus transcriptomic atlas of medium spiny neurons in the rat nucleus accumbens.

Neural processing of rewarding stimuli involves several distinct regions, including the nucleus accumbens (NAc). The majority of NAc neurons are GABAergic projection neurons known as medium spiny neurons (MSNs). MSNs are broadly defined by dopamine receptor expression, but evidence suggests that a wider array of subtypes exist. To study MSN heterogeneity, we analyzed single-nucleus RNA sequencing data from the largest available rat NAc dataset. Analysis of 48,040 NAc MSN nuclei identified major populations belonging to the striosome and matrix compartments. Integration with mouse and human data indicated consistency across species and disease-relevance scoring using genome-wide association study results revealed potentially differential roles for MSN populations in substance use disorders. Additional high-resolution clustering identified 34 transcriptomically distinct subtypes of MSNs definable by a limited number of marker genes. Together, these data demonstrate the diversity of MSNs in the NAc and provide a basis for more targeted genetic manipulation of specific populations.

Comparing the psychometric properties of reward and relief drinking measures.

Previous work examining the extent to which individuals seek alcohol to enhance positive experiences (reward drinking) or relieve aversive states (relief drinking) has shown that reward/relief drinking predicts response to naltrexone and acamprosate treatment for alcohol use disorder. Yet, various measures of reward/relief drinking have been used in prior research, and the comparative psychometric properties of these measures are unknown. Evaluating and comparing the psychometric properties of these reward/relief drinking measures could identify measures with the most promise for translating precision medicine findings to clinical practice. In a community sample of 65 individuals with heavy/hazardous alcohol use on the Alcohol Use Disorder Identification Test, we showed good internal consistency reliability, test-retest reliability, and concurrent validity for theoretically aligned measures (e.g., reward drinking and reward responsiveness, relief drinking and depression/anxiety symptoms) of the reward and relief subscales across the six measures. We then used ecological momentary assessment to determine whether reward and relief drinking subscales predicted within-person associations between contextual factors of interest (e.g., negative affect, positive affect, distress intolerance, physical pain, hangover symptoms, social drinking situations, alcohol cues) and same-moment alcohol craving. All six measures demonstrated limited predictive validity for alcohol craving contexts in daily life as assessed via ecological momentary assessment. Despite these findings, reward and relief drinking measures show good reliability and concurrent validity and previously demonstrated clinical utility for predicting response to alcohol use disorder treatments, including naltrexone. Future research should aim to elucidate the mechanisms underlying the association between responses to reward/relief drinking measures and pharmacotherapy outcomes. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Gene × environment effects and mediation involving adverse childhood events, mood and anxiety disorders, and substance dependence.

Adverse childhood events (ACEs) contribute to the development of mood and anxiety disorders and substance dependence. However, the extent to which these effects are direct or indirect and whether genetic risk moderates them is unclear. We examined associations among ACEs, mood/anxiety disorders and substance dependence in 12,668 individuals (44.9% female, 42.5% African American/Black, 42.1% European American/white). Using latent variables for each phenotype, we modelled direct and indirect associations of ACEs with substance dependence, mediated by mood/anxiety disorders (the forward or 'self-medication' model) and of ACEs with mood/anxiety disorders, mediated by substance dependence (the reverse or 'substance-induced' model). In a subsample, we tested polygenic scores for the substance dependence and mood/anxiety disorder factors as moderators in the mediation models. Although there were significant indirect paths in both directions, mediation by mood/anxiety disorders (the forward model) was greater than that by substance dependence (the reverse model). Greater genetic risk for substance use disorders was associated with a weaker direct association between ACEs and substance dependence in both ancestry groups (reflecting gene × environment interactions) and a weaker indirect association in European-ancestry individuals (reflecting moderated mediation). We found greater evidence that substance dependence reflects self-medication of mood/anxiety disorders than that mood/anxiety disorders are substance induced. Among individuals at higher genetic risk for substance dependence, ACEs were less associated with that outcome. Following exposure to ACEs, multiple pathways appear to underlie the associations between mood/anxiety disorders and substance dependence. Specification of these pathways could inform individually targeted prevention and treatment approaches.

Candidate Genes from an FDA-Approved Algorithm Fail to Predict Opioid Use Disorder Risk in Over 450,000 Veterans.

Importance: Recently, the Food and Drug Administration gave pre-marketing approval to algorithm based on its purported ability to identify genetic risk for opioid use disorder. However, the clinical utility of the candidate genes comprising the algorithm has not been independently demonstrated. Objective: To assess the utility of 15 variants in candidate genes from an algorithm intended to predict opioid use disorder risk. Design: This case-control study examined the association of 15 candidate genetic variants with risk of opioid use disorder using available electronic health record data from December 20, 1992 to September 30, 2022. Setting: Electronic health record data, including pharmacy records, from Million Veteran Program participants across the United States. Participants: Participants were opioid-exposed individuals enrolled in the Million Veteran Program (n = 452,664). Opioid use disorder cases were identified using International Classification of Disease diagnostic codes, and controls were individuals with no opioid use disorder diagnosis. Exposures: Number of risk alleles present across 15 candidate genetic variants. Main Outcome and Measures: Predictive performance of 15 genetic variants for opioid use disorder risk assessed via logistic regression and machine learning models. Results: Opioid exposed individuals (n=33,669 cases) were on average 61.15 (SD = 13.37) years old, 90.46% male, and had varied genetic similarity to global reference panels. Collectively, the 15 candidate genetic variants accounted for 0.4% of variation in opioid use disorder risk. The accuracy of the ensemble machine learning model using the 15 genes as predictors was 52.8% (95% CI = 52.1 - 53.6%) in an independent testing sample. Conclusions and Relevance: Candidate genes that comprise the approved algorithm do not meet reasonable standards of efficacy in predicting opioid use disorder risk. Given the algorithm's limited predictive accuracy, its use in clinical care would lead to high rates of false positive and negative findings. More clinically useful models are needed to identify individuals at risk of developing opioid use disorder.

Comparison Between a Single-Lead ECG Garment Device and a Holter Monitor: A Signal Quality Assessment.

Wearable electronics are increasingly common and useful as health monitoring devices, many of which feature the ability to record a single-lead electrocardiogram (ECG). However, recording the ECG commonly requires the user to touch the device to complete the lead circuit, which prevents continuous data acquisition. An alternative approach to enable continuous monitoring without user initiation is to embed the leads in a garment. This study assessed ECG data obtained from the YouCare device (a novel sensorized garment) via comparison with a conventional Holter monitor. A cohort of thirty patients (age range: 20-82 years; 16 females and 14 males) were enrolled and monitored for twenty-four hours with both the YouCare device and a Holter monitor. ECG data from both devices were qualitatively assessed by a panel of three expert cardiologists and quantitatively analyzed using specialized software. Patients also responded to a survey about the comfort of the YouCare device as compared to the Holter monitor. The YouCare device was assessed to have 70% of its ECG signals as "Good", 12% as "Acceptable", and 18% as "Not Readable". The R-wave, independently recorded by the YouCare device and Holter monitor, were synchronized within measurement error during 99.4% of cardiac cycles. In addition, patients found the YouCare device more comfortable than the Holter monitor (comfortable 22 vs. 5 and uncomfortable 1 vs. 18, respectively). Therefore, the quality of ECG data collected from the garment-based device was comparable to a Holter monitor when the signal was sufficiently acquired, and the garment was also comfortable.

The Complex Latent Structure of Attenuated Psychotic Symptoms: Hierarchical and Bifactor Models of SIPS Symptoms Replicated in Two Large Samples at Clinical High Risk for Psychosis.

BACKGROUND AND HYPOTHESIS: The Structured Interview for Psychosis-Risk Syndromes (SIPS) and other assessments of psychosis risk define clinical high risk for psychosis (CHR) by the presence of attenuated psychotic symptoms. Despite extensive research on attenuated psychotic symptoms, substantial questions remain about their internal psychometric structure and relationships to comorbid non-psychotic symptoms. STUDY DESIGN: Hierarchical and bifactor models were developed for the SIPS in a large CHR sample (NAPLS-3, N = 787) and confirmed through preregistered replication in an independent sample (NAPLS-2, N = 1043). Criterion validity was tested through relationships with CHR status, comorbid symptoms/diagnoses, functional impairment, demographics, neurocognition, and conversion to psychotic disorders. STUDY RESULTS: Most variance in SIPS items (75%-77%) was attributable to a general factor. Hierarchical and bifactor models included a general factor and five specific/lower-order factors (positive symptoms, eccentricity, avolition, lack of emotion, and deteriorated thought process). CHR participants were elevated on the general factor and the positive symptoms factor. The general factor was associated with depressive symptoms; functional impairment; and mood, anxiety, and schizotypal personality diagnoses. The general factor was the best predictor of psychotic disorders (d ≥ 0.50). Positive symptoms and eccentricity had specific effects on conversion outcomes. The deteriorated thought process was least meaningful/replicable. CONCLUSIONS: Attenuated psychotic symptoms, measured by the SIPS, have a complex hierarchical structure with a strong general factor. The general factor relates to internalizing symptoms and functional impairment, emphasizing the roles of general psychopathological distress/impairment in psychosis risk. Shared symptom variance complicates the interpretation of raw symptom scores. Broad transdiagnostic assessment is warranted to model psychosis risk accurately.

Longitudinal Trajectories of Premorbid Social and Academic Adjustment in Youth at Clinical High Risk for Psychosis: Implications for Conversion.

BACKGROUND AND HYPOTHESIS: Social and academic adjustment deteriorate in the years preceding a psychotic disorder diagnosis. Analyses of premorbid adjustment have recently been extended into the clinical high risk for psychosis (CHR) syndrome to identify risk factors and developmental pathways toward psychotic disorders. Work so far has been at the between-person level, which has constrained analyses of premorbid adjustment, clinical covariates, and conversion to psychosis. STUDY DESIGN: Growth-curve models examined longitudinal trajectories in retrospective reports of premorbid social and academic adjustment from youth at CHR (n = 498). Interaction models tested whether known covariates of premorbid adjustment problems (attenuated negative symptoms, cognition, and childhood trauma) were associated with different premorbid adjustment trajectories in converters vs non-converters (ie, participants who did/did not develop psychotic disorders within 2-year follow-up). STUDY RESULTS: Converters reported poorer social adjustment throughout the premorbid period. Converters who developed psychosis with an affective component reported poorer academic adjustment throughout the premorbid period than those who developed non-affective psychosis. Tentatively, baseline attenuated negative symptoms may have been associated with worsening social adjustment in the premorbid period for non-converters only. Childhood trauma impact was associated with fewer academic functioning problems among converters. Cognition effects did not differ based on conversion status. CONCLUSIONS: Premorbid social function is an important factor in risk for conversion to psychosis. Negative symptoms and childhood trauma had different relationships to premorbid functioning in converters vs non-converters. Mechanisms linking symptoms and trauma to functional impairment may be different in converters vs non-converters, suggesting possible new avenues for risk assessment.

Emotional tone in clinical high risk for psychosis: novel insights from a natural language analysis approach.

Background: Individuals at clinical high risk (CHR) for psychosis experience subtle emotional disturbances that are traditionally difficult to assess, but natural language processing (NLP) methods may provide novel insight into these symptoms. We predicted that CHR individuals would express more negative emotionality and less emotional language when compared to controls. We also examined associations with symptomatology. Methods: Participants included 49 CHR individuals and 42 healthy controls who completed a semi-structured narrative interview. Interview transcripts were analyzed using Linguistic Inquiry and Word Count (LIWC) to assess the emotional tone of the language (tone -the ratio of negative to positive language) and count positive/negative words used. Participants also completed clinical symptom assessments to determine CHR status and characterize symptoms (i.e., positive and negative symptom domains). Results: The CHR group had more negative emotional tone compared to healthy controls (t=2.676, p=.009), which related to more severe positive symptoms (r2=.323, p=.013). The percentages of positive and negative words did not differ between groups (p's>.05). Conclusions: Language analyses provided accessible, ecologically valid insight into affective dysfunction and psychosis risk symptoms. Natural language processing analyses unmasked differences in language for CHR that captured language tendencies that were more nuanced than the words that are chosen.

Combining Transdiagnostic and Disorder-Level GWAS Enhances Precision of Psychiatric Genetic Risk Profiles in a Multi-Ancestry Sample.

The etiology of substance use disorders (SUDs) and psychiatric disorders reflects a combination of both transdiagnostic (i.e., common) and disorder-level (i.e., independent) genetic risk factors. We applied genomic structural equation modeling to examine these genetic factors across SUDs, psychotic, mood, and anxiety disorders using genome-wide association studies (GWAS) of European- (EUR) and African-ancestry (AFR) individuals. In EUR individuals, transdiagnostic genetic factors represented SUDs (143 lead single nucleotide polymorphisms [SNPs]), psychotic (162 lead SNPs), and mood/anxiety disorders (112 lead SNPs). We identified two novel SNPs for mood/anxiety disorders that have probable regulatory roles on FOXP1, NECTIN3, and BTLA genes. In AFR individuals, genetic factors represented SUDs (1 lead SNP) and psychiatric disorders (no significant SNPs). The SUD factor lead SNP, although previously significant in EUR- and cross-ancestry GWAS, is a novel finding in AFR individuals. Shared genetic variance accounted for overlap between SUDs and their psychiatric comorbidities, with second-order GWAS identifying up to 12 SNPs not significantly associated with either first-order factor in EUR individuals. Finally, common and independent genetic effects showed different associations with psychiatric, sociodemographic, and medical phenotypes. For example, the independent components of schizophrenia and bipolar disorder had distinct associations with affective and risk-taking behaviors, and phenome-wide association studies identified medical conditions associated with tobacco use disorder independent of the broader SUDs factor. Thus, combining transdiagnostic and disorder-level genetic approaches can improve our understanding of co-occurring conditions and increase the specificity of genetic discovery, which is critical for psychiatric disorders that demonstrate considerable symptom and etiological overlap.

Alcohol use disorder and body mass index show genetic pleiotropy and shared neural associations.

Background: The prevalence of co-occurring heavy alcohol consumption and obesity is increasing in the United States. Despite neurobiological overlap in the regulation of alcohol consumption and eating behavior, alcohol- and body mass index (BMI)-related phenotypes show no or minimal genetic correlation. We hypothesized that the lack of genetic correlation is due to mixed effect directions of variants shared by AUD and BMI. Methods: We applied MiXeR, to investigate shared genetic architecture between AUD and BMI in individuals of European ancestry. We used conjunctional false discovery rate (conjFDR) analysis to detect loci associated with both phenotypes and their directional effect, Functional Mapping and Annotation (FUMA) to identify lead single nucleotide polymorphisms (SNPs), Genotype-Tissue Expression (GTEx) samples to examine gene expression enrichment across tissue types, and BrainXcan to evaluate the shared associations of AUD and BMI with brain image-derived phenotypes. Results: MiXeR analysis indicated polygenic overlap of 80.9% between AUD and BMI, despite a genetic correlation (r g ) of -.03. ConjFDR analysis yielded 56 lead SNPs with the same effect direction and 76 with the opposite direction. Of the 132 shared lead SNPs, 53 were novel for both AUD and BMI. GTEx analyses identified significant overexpression in the frontal cortex (BA9), hypothalamus, cortex, anterior cingulate cortex (BA24), hippocampus, and amygdala. Amygdala and caudate nucleus gray matter volumes were significantly associated with both AUD and BMI in BrainXcan analyses. Conclusions: More than half of variants significantly associated with AUD and BMI had opposite directions of effect for the traits, supporting our hypothesis that this is the basis for their lack of genetic correlation. Follow-up analyses identified brain regions implicated in executive functioning, reward, homeostasis, and food intake regulation. Together, these findings clarify the extensive polygenic overlap between AUD and BMI and elucidate several overlapping neurobiological mechanisms.

Topiramate Versus Naltrexone for Alcohol Use Disorder: A Genotype-Stratified Double-Blind Randomized Controlled Trial.

OBJECTIVE: There have been no well-controlled and well-powered comparative trials of topiramate with other pharmacotherapies for alcohol use disorder (AUD), such as naltrexone. Moreover, the literature is mixed on the effects of two polymorphisms-rs2832407 (in GRIK1) and rs1799971 (in OPRM1)-on response to topiramate and naltrexone, respectively. The authors sought to examine the comparative effectiveness of topiramate and naltrexone in improving outcomes in AUD and to examine the role of the rs2832407 and rs1799971 polymorphisms, respectively, on response to these medications. METHODS: In a 12-week, double-blind, placebo-controlled, randomized, multisite, genotype-stratified (rs2832407 and rs1799971) clinical trial comparing topiramate and naltrexone in treating AUD, 147 patients with AUD were randomly assigned to treatment with topiramate or naltrexone, stratified by genotype (rs2832407*CC and *AC/AA genotypes and rs1799971*AA and *AG/GG genotypes). The predefined primary outcome was number of heavy drinking days per week. Predefined secondary outcomes included standard drinks per drinking day per week, body mass index (BMI), craving, markers of liver injury, mood, and adverse events. RESULTS: For the number of heavy drinking days per week, there was a near-significant time-by-treatment interaction. For the number of standard drinks per drinking day per week, there was a significant time-by-treatment interaction, which favored topiramate. There were significant time-by-treatment effects, with greater reductions observed with topiramate than naltrexone for BMI, craving, and gamma-glutamyltransferase level. Withdrawal due to side effects occurred in 8% and 5% of the topiramate and naltrexone groups, respectively. Neither polymorphism showed an effect on treatment response. CONCLUSIONS: Topiramate is at least as effective and safe as the first-line medication, naltrexone, in reducing heavy alcohol consumption, and superior in reducing some clinical outcomes. Neither rs2832407 nor rs1799971 had effects on topiramate and naltrexone treatments, respectively.

Multi-ancestry meta-analysis of tobacco use disorder identifies 461 potential risk genes and reveals associations with multiple health outcomes.

Tobacco use disorder (TUD) is the most prevalent substance use disorder in the world. Genetic factors influence smoking behaviours and although strides have been made using genome-wide association studies to identify risk variants, most variants identified have been for nicotine consumption, rather than TUD. Here we leveraged four US biobanks to perform a multi-ancestral meta-analysis of TUD (derived via electronic health records) in 653,790 individuals (495,005 European, 114,420 African American and 44,365 Latin American) and data from UK Biobank (ncombined = 898,680). We identified 88 independent risk loci; integration with functional genomic tools uncovered 461 potential risk genes, primarily expressed in the brain. TUD was genetically correlated with smoking and psychiatric traits from traditionally ascertained cohorts, externalizing behaviours in children and hundreds of medical outcomes, including HIV infection, heart disease and pain. This work furthers our biological understanding of TUD and establishes electronic health records as a source of phenotypic information for studying the genetics of TUD.

A regulatory focus theory perspective on the dynamics between action and power.

Building on the strong consensus that the experience of power motivates individuals to take action, prior research postulates a positively reinforcing cycle wherein taking action leads to power, which in turn leads to subsequent actions. Applying regulatory focus theory, we differentiate between promotion-oriented and prevention-oriented actions to develop a within-person theory of when and why promotion-oriented and prevention-oriented actions should relate to power, and vice-versa. Across two studies, we find that when employees engaged in promotive voice behaviors, they were more likely to experience a sense of power; this effect was amplified for employees with trait promotion focus. When employees engaged in prohibitive voice behaviors, employees with trait prevention focus were less likely to experience a sense of power. The experience of power subsequently motivated employees to engage in promotive voice behaviors, but not prohibitive voice behaviors. By elucidating the differences between promotion and prevention pathways of action and power, our research challenges the notion that action and power positively reinforce each other. We discuss the theoretical and practical implications of our findings. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Mapping Psychosis Risk States onto the Hierarchical Taxonomy of Psychopathology Using Hierarchical Symptom Dimensions.

Clinical high risk for psychosis (CHR) is a transdiagnostic risk state. However, it is unclear how risk states such as CHR fit within broad transdiagnostic models such as the Hierarchical Taxonomy of Psychopathology (HiTOP). In this study, a hierarchical dimensional symptom structure was defined by unfolding factor analysis of self-report data from 3,460 young adults (mage=20.3). A subsample (n=436) completed clinical interviews, 85 of whom met CHR criteria. Regression models examined relationships between symptom dimensions, CHR status, and clinician-rated symptoms. CHR status was best explained by a reality distortion dimension, with contributions from internalizing dimensions. Positive and negative attenuated psychotic symptoms were best explained by multiple psychotic and nonpsychotic symptom dimensions including reality distortion, distress, fear, detachment, and mania. Attenuated psychotic symptoms are a complex presenting problem warranting comprehensive assessment. HiTOP can provide both diagnostic precision and broad transdiagnostic coverage, making it a valuable resource for use with at-risk individuals.

Protein codes promote selective subcellular compartmentalization.

Cells have evolved mechanisms to distribute ~10 billion protein molecules to subcellular compartments where diverse proteins involved in shared functions must efficiently assemble. Here, we demonstrate that proteins with shared functions share amino acid sequence codes that guide them to compartment destinations. A protein language model, ProtGPS, was developed that predicts with high performance the compartment localization of human proteins excluded from the training set. ProtGPS successfully guided generation of novel protein sequences that selectively assemble in targeted subcellular compartments. ProtGPS also identified pathological mutations that change this code and lead to altered subcellular localization of proteins. Our results indicate that protein sequences contain not only a folding code, but also a previously unrecognized code governing their distribution in specific cellular compartments.

Reductions in World Health Organization risk drinking level are associated with improvements in sleep problems among individuals with alcohol use disorder.

AIMS: Among individuals with alcohol use disorder (AUD), sleep disturbances are pervasive and contribute to the etiology and maintenance of AUD. However, despite increased attention toward the relationship between alcohol use and sleep, limited empirical research has systematically examined whether reductions in drinking during treatment for AUD are associated with improvements in sleep problems. METHODS: We used data from a multisite, randomized, controlled trial that compared 6 months of treatment with gabapentin enacarbil extended-release with placebo for adults with moderate-to-severe AUD (N = 346). The Timeline Follow-back was used to assess WHO risk drinking level reductions and the Pittsburgh Sleep Quality Index was used to assess sleep quality over the prior month at baseline and the end of treatment. RESULTS: Sleep problem scores in the active medication and placebo groups improved equally. Fewer sleep problems were noted among individuals who achieved at least a 1-level reduction (B = -0.99, 95% confidence interval (CI) [-1.77, -0.20], P = .014) or at least a 2-level reduction (B = -0.80, 95% CI [-1.47, -0.14], P = .018) in WHO risk drinking levels at the end of treatment. Reductions in drinking, with abstainers excluded from the analysis, also predicted fewer sleep problems at the end of treatment (1-level: B = -1.01, 95% CI [-1.83, -0.20], P = .015; 2-level: B = -0.90, 95% CI [-1.59, -0.22], P = .010). CONCLUSIONS: Drinking reductions, including those short of abstinence, are associated with improvements in sleep problems during treatment for AUD. Additional assessment of the causal relationships between harm-reduction approaches to AUD and improvements in sleep is warranted.

A Multivariate Genome-Wide Association Study Reveals Neural Correlates and Common Biological Mechanisms of Psychopathology Spectra.

There is considerable comorbidity across externalizing and internalizing behavior dimensions of psychopathology. We applied genomic structural equation modeling (gSEM) to genome-wide association study (GWAS) summary statistics to evaluate the factor structure of externalizing and internalizing psychopathology across 16 traits and disorders among European-ancestry individuals (n's = 16,400 to 1,074,629). We conducted GWAS on factors derived from well-fitting models. Downstream analyses served to identify biological mechanisms, explore drug repurposing targets, estimate genetic overlap between the externalizing and internalizing spectra, and evaluate causal effects of psychopathology liability on physical health. Both a correlated factors model, comprising two factors of externalizing and internalizing risk, and a higher-order single-factor model of genetic effects contributing to both spectra demonstrated acceptable fit. GWAS identified 409 lead single nucleotide polymorphisms (SNPs) associated with externalizing and 85 lead SNPs associated with internalizing, while the second-order GWAS identified 256 lead SNPs contributing to broad psychopathology risk. In bivariate causal mixture models, nearly all externalizing and internalizing causal variants overlapped, despite a genetic correlation of only 0.37 (SE = 0.02) between them. Externalizing genes showed cell-type specific expression in GABAergic, cortical, and hippocampal neurons, and internalizing genes were associated with reduced subcallosal cortical volume, providing insight into the neurobiological underpinnings of psychopathology. Genetic liability for externalizing, internalizing, and broad psychopathology exerted causal effects on pain, general health, cardiovascular diseases, and chronic illnesses. These findings underscore the complex genetic architecture of psychopathology, identify potential biological pathways for the externalizing and internalizing spectra, and highlight the physical health burden of psychiatric comorbidity.