A high-resolution PheWAS approach to alcohol-related polygenic risk scores reveals mechanistic influences of alcohol reinforcing value and drinking motives.

AIMS: This study uses a high-resolution phenome-wide approach to evaluate the motivational mechanisms of polygenic risk scores (PRSs) that have been robustly associated with coarse alcohol phenotypes in large-scale studies. METHODS: In a community-based sample of 1534 Europeans, we examined genome-wide PRSs for the Alcohol Use Disorders Identification Test (AUDIT), drinks per week, alcohol use disorder (AUD), problematic alcohol use (PAU), and general addiction, in relation to 42 curated phenotypes. The curated phenotypes were in seven categories: alcohol consumption, alcohol reinforcing value, drinking motives, other addictive behaviors, commonly comorbid psychiatric syndromes, impulsivity, and personality traits. RESULTS: The PRS for each alcohol phenotype was validated via its within-sample association with the corresponding phenotype (adjusted R2s = 0.35-1.68%, Ps = 0.012-3.6 × 10-7) with the exception of AUD. All PRSs were positively associated with alcohol reinforcing value and drinking motives, with the strongest effects from AUDIT-consumption (adjusted R2s = 0.45-1.33%, Ps = 0.006-3.6 × 10-5) and drinks per week PRSs (adjusted R2s = 0.52-2.28%, Ps = 0.004-6.6 × 10-9). Furthermore, the PAU and drinks per week PRSs were positively associated with adverse childhood experiences (adjusted R2s = 0.6-0.7%, Ps = 0.0001-4.8 × 10-4). CONCLUSIONS: These results implicate alcohol reinforcing value and drinking motives as genetically-influenced mechanisms using PRSs for the first time. The findings also highlight the value of dissecting genetic influence on alcohol involvement through diverse phenotypic risk pathways but also the need for future studies with both phenotypic richness and larger samples.

Longitudinal Associations Between Perceived Discrimination and Suicidality in Youth.

Research among adults reveals robust associations between discrimination and suicidality. However, the relationship between discrimination and suicidality is understudied in youth. Participants in the Adolescent Brain Cognitive Development study (n = 10  312) completed a measure of discrimination based on multiple attributes. The Kiddie Schedule for Affective Disorders and Schizophrenia was administered 1 year later to assess depressive disorders and suicidality (ideation and behavior). Logistic regressions, adjusting for age, sex, race/ethnicity, family income, lifetime depressive disorders, and body composition were conducted. Adjusting for covariates, discrimination based on weight (OR: 2.19), race/ethnicity/color (OR: 3.21), and sexual orientation (OR: 3.83) were associated with greater odds of reporting suicidality 1 year later (ps < 0.025). Nationality-based discrimination was not significantly associated with suicidality. Compared with those reporting no discrimination, youths reporting discrimination based on 2 or more attributes had nearly 5 times greater odds of recent suicidality (OR: 4.72; P < .001). The current study highlights the deleterious impacts of discrimination on mental health among youths reporting multiple forms of discrimination.

Resting-state network analysis of suicide attempt history in the UK Biobank.

BACKGROUND: Prior research has identified altered brain structure and function in individuals at risk for self-directed violence thoughts and behaviors. However, these studies have largely utilized healthy controls and findings have been inconsistent. Thus, this study examined differences in resting-state functional network connectivity among individuals with lifetime suicide attempt(s) v. lifetime self-directed violence thoughts alone. METHODS: Using data from the UK Biobank, this study utilized a series of linear regressions to compare individuals with lifetime suicide attempt(s) (n = 566) v. lifetime self-directed violence thoughts alone (n = 3447) on within- and between- network resting-state functional connectivity subnetworks. RESULTS: There were no significant between-group differences for between-network, within-network, or whole-brain functional connectivity after adjusting for age, sex, ethnicity, and body mass index and performing statistical corrections for multiple comparisons. Resting-state network measures may not differentiate between individuals with lifetime suicide attempt(s) and lifetime self-directed violence thoughts alone. CONCLUSIONS: Null findings diverge from results reported in smaller neuroimaging studies of suicide risk, but are consistent with null findings in other large-scale studies and meta-analyses. Strengths of the study include its large sample size and stringent control group. Future research on a wider array of imaging, genetic, and psychosocial risk factors can clarify relative contributions of individual and combined variables to suicide risk and inform scientific understanding of ideation-to-action framework.

Genome-Wide Association Studies of Impulsive Personality Traits (BIS-11 and UPPS-P) and Drug Experimentation in up to 22,861 Adult Research Participants Identify Loci in the CACNA1I and CADM2 genes.

Impulsive personality traits are complex heritable traits that are governed by frontal-subcortical circuits and are associated with numerous neuropsychiatric disorders, particularly drug abuse and attention-deficit/hyperactivity disorder (ADHD). In collaboration with the genetics company 23andMe, we performed 10 genome-wide association studies on measures of impulsive personality traits [the short version of the UPPS-P Impulsive Behavior Scale, and the Barratt Impulsiveness Scale (BIS-11)] and drug experimentation (the number of drug classes an individual had tried in their lifetime) in up to 22,861 male and female adult human research participants of European ancestry. Impulsive personality traits and drug experimentation showed single nucleotide polymorphism heritabilities that ranged from 5 to 11%. Genetic variants in the CADM2 locus were significantly associated with UPPS-P Sensation Seeking (p = 8.3 × 10-9, rs139528938) and showed a suggestive association with Drug Experimentation (p = 3.0 × 10-7, rs2163971; r2 = 0.68 with rs139528938). Furthermore, genetic variants in the CACNA1I locus were significantly associated with UPPS-P Negative Urgency (p = 3.8 × 10-8; rs199694726). The role of these genes was supported by single variant, gene- and transcriptome-based analyses. Multiple subscales from both UPPS-P and BIS showed strong genetic correlations (>0.5) with Drug Experimentation and other substance use traits measured in independent cohorts, including smoking initiation, and lifetime cannabis use. Several UPPS-P and BIS subscales were genetically correlated with ADHD (rg = 0.30-0.51), supporting their validity as endophenotypes. Our findings demonstrate a role for common genetic contributions to individual differences in impulsivity. Furthermore, our study is the first to provide a genetic dissection of the relationship between different types of impulsive personality traits and various psychiatric disorders.SIGNIFICANCE STATEMENT Impulsive personality traits (IPTs) are heritable traits that are governed by frontal-subcortical circuits and are associated with neuropsychiatric disorders, particularly substance use disorders. We have performed genome-wide association studies of IPTs to identify regions and genes that account for this heritable variation. IPTs and drug experimentation were modestly heritable (5-11%). We identified an association between single nucleotide polymorphisms in CADM2 and both sensation seeking and drug experimentation; and between variants in CACNA1I and negative urgency. The role of these genes was supported by single variant, gene- and transcriptome-based analyses. This study provides evidence that impulsivity can be genetically separated into distinct components. We showed that IPT are genetically associated with substance use and ADHD, suggesting impulsivity is an endophenotype contributing to these psychiatric conditions.

Demographic, psychological, behavioral, and cognitive correlates of BMI in youth: Findings from the Adolescent Brain Cognitive Development (ABCD) study.

BACKGROUND: Previous research has implicated demographic, psychological, behavioral, and cognitive variables in the onset and maintenance of pediatric overweight/obesity. No adequately-powered study has simultaneously modeled these variables to assess their relative associations with body mass index (BMI; kg/m2) in a nationally representative sample of youth. METHODS: Multiple machine learning regression approaches were employed to estimate the relative importance of 43 demographic, psychological, behavioral, and cognitive variables previously associated with BMI in youth to elucidate the associations of both fixed (e.g. demographics) and potentially modifiable (e.g. psychological/behavioral) variables with BMI in a diverse representative sample of youth. The primary analyses consisted of 9-10 year olds divided into a training (n = 2724) and test (n = 1123) sets. Secondary analyses were conducted by sex, ethnicity, and race. RESULTS: The full sample model captured 12% of the variance in both the training and test sets, suggesting good generalizability. Stimulant medications and demographic factors were most strongly associated with BMI. Lower attention problems and matrix reasoning (i.e. nonverbal abstract problem solving and inductive reasoning) and higher social problems and screen time were robust positive correlates in the primary analyses and in analyses separated by sex. CONCLUSIONS: Beyond demographics and stimulant use, this study highlights abstract reasoning as an important cognitive variable and reaffirms social problems and screen time as significant correlates of BMI and as modifiable therapeutic targets. Prospective data are needed to understand the predictive power of these variables for BMI gain.

Genome-wide association study of alcohol use disorder identification test (AUDIT) scores in 20 328 research participants of European ancestry.

Genetic factors contribute to the risk for developing alcohol use disorder (AUD). In collaboration with the genetics company 23andMe, Inc., we performed a genome-wide association study of the alcohol use disorder identification test (AUDIT), an instrument designed to screen for alcohol misuse over the past year. Our final sample consisted of 20 328 research participants of European ancestry (55.3% females; mean age = 53.8, SD = 16.1) who reported ever using alcohol. Our results showed that the 'chip-heritability' of AUDIT score, when treated as a continuous phenotype, was 12%. No loci reached genome-wide significance. The gene ADH1C, which has been previously implicated in AUD, was among our most significant associations (4.4 × 10-7 ; rs141973904). We also detected a suggestive association on chromosome 1 (2.1 × 10-7 ; rs182344113) near the gene KCNJ9, which has been implicated in mouse models of high ethanol drinking. Using linkage disequilibrium score regression, we identified positive genetic correlations between AUDIT score, high alcohol consumption and cigarette smoking. We also observed an unexpected positive genetic correlation between AUDIT and educational attainment and additional unexpected negative correlations with body mass index/obesity and attention-deficit/hyperactivity disorder. We conclude that conducting a genetic study using responses to an online questionnaire in a population not ascertained for AUD may represent a cost-effective strategy for elucidating aspects of the etiology of AUD.

Predictors of Topiramate Tolerability in Heavy Cannabis-Using Adolescents and Young Adults: A Secondary Analysis of a Randomized, Double-Blind, Placebo-Controlled Trial.

PURPOSE/BACKGROUND: Cannabis is the most commonly abused illicit drug and accounts for the greatest number of adolescent substance abuse treatment admissions. Despite urgent need for effective interventions, the best available psychosocial treatment options yield only modest effects. Topiramate showed promise as an adjunctive pharmacotherapy to a psychosocial intervention for cannabis misuse among adolescents and young adults in a recent clinical trial, but it was not well tolerated. This study investigated associations between clinical characteristics and side effects and dropout among adolescents and young adults randomized to topiramate. METHODS: This study involved secondary data analysis of a randomized placebo-controlled trial of topiramate for treating cannabis misuse (ages, 15-24 years; 50% female). We explored the interaction effects of baseline characteristics and medication condition (topiramate vs placebo) on treatment dropout. We also explored the relationship between side effects and dropout. FINDINGS/RESULTS: Higher cannabis problems were significantly associated with reduced hazard of dropout in the topiramate group (P = 0.048) and were nonsignificantly associated with increased hazard of dropout in the placebo group (P = 0.062). Results also showed that memory difficulties were an overwhelming predictor of dropout in the topiramate condition; 42% of participants who dropped out experienced memory difficulties, whereas none of those who remained in the study experienced these effects. IMPLICATIONS/CONCLUSIONS: By identifying who may most benefit from and tolerate this medication, treatment for substance use disorders can become more individualized and positive outcomes may be enhanced.

Neural correlates of tobacco cue reactivity predict duration to lapse and continuous abstinence in smoking cessation treatment.

It has been hypothesized that neural reactivity to drug cues in certain limbic/paralimbic regions of the brain is an indicator of addiction severity and a marker for likelihood of success in treatment. To address this question, in the current study, 32 participants (44 percent female) completed a functional magnetic resonance imaging cigarette cue exposure paradigm 2 hours after smoking, and then enrolled in a 9-week smoking cessation treatment program. Neural activation to smoking cues was measured in five a priori defined limbic/paralimbic regions previously implicated with cue reactivity across substances. These included regions of the ventral striatum, anterior cingulate cortex and amygdala. Cox proportional hazard modeling was conducted to predict the number of days to first smoking lapse by using neural activation in these regions. Greater neural activation during pre-treatment exposure to smoking cues in the right ventral striatum, the left amygdala, and the anterior cingulate was associated with longer periods of abstinence following cessation. A similar pattern was present for continuous abstinence for the full duration of treatment. While baseline levels of nicotine dependence were strongly associated with treatment outcome, activation in the right ventral striatum predicted duration of abstinence beyond level of nicotine dependence. These results suggest that pre-treatment reactivity to smoking cues in areas associated with cue reactivity may be associated with successfully maintaining abstinence during treatment. This is consistent with models that propose that as addiction becomes more severe, motivational processing shifts from regions that subserve reward salience and learning to regions responsible motor behavior and habit learning.

Neuroanatomical foundations of delayed reward discounting decision making.

Resolving tradeoffs between smaller immediate rewards and larger delayed rewards is ubiquitous in daily life and steep discounting of future rewards is associated with several psychiatric conditions. This form of decision-making is referred to as delayed reward discounting (DRD) and the features of brain structure associated with DRD are not well understood. The current study characterized the relationship between gray matter volume (GMV) and DRD in a sample of 1038 healthy adults (54.7% female) using cortical parcellation, subcortical segmentation, and voxelwise cortical surface-based group analyses. The results indicate that steeper DRD was significantly associated with lower total cortical GMV, but not subcortical GMV. In parcellation analyses, less GMV in 20 discrete cortical regions was associated with steeper DRD. Of these regions, only GMV in the middle temporal gyrus (MTG) and entorhinal cortex (EC) were uniquely associated with DRD. Voxelwise surface-based analyses corroborated these findings, again revealing significant associations between steeper DRD and less GMV in the MTG and EC. To inform the roles of MTG and EC in DRD, connectivity analysis of resting state data (N = 1003) using seed regions from the structural findings was conducted. This revealed that spontaneous activity in the MTG and EC was correlated with activation in the ventromedial prefrontal cortex, posterior cingulate cortex, and inferior parietal lobule, regions associated with the default mode network, which involves prospection, self-reflective thinking and mental simulation. Furthermore, meta-analytic co-activation analysis using Neurosynth revealed a similar pattern across 11,406 task-fMRI studies. Collectively, these findings provide robust evidence that morphometric characteristics of the temporal lobe are associated with DRD preferences and suggest it may be because of their role in mental activities in common with default mode activity.

Genetic influences on ADHD symptom dimensions: Examination of a priori candidates, gene-based tests, genome-wide variation, and SNP heritability.

Although the heritability of ADHD is estimated to be high, identifying specific genetic markers remains challenging. Most studies to date have examined the genetic basis of ADHD by employing dichotomous diagnostic phenotypes, but, as ADHD symptoms tend to be phenotypically dimensional, an alternative and potentially informative approach is to examine continuous indices of inattention and hyperactivity-impulsivity symptoms. The current study aimed to identify genetic effects on dimensionally-focused adult ADHD-related phenotypes in 990 individuals of European ancestry with intentionally low levels of substance misuse to avoid confounding. The study used four complementary approaches: (1) analysis of a priori candidate loci identified in prior meta-analytic work; (2) gene-based analysis; (3) hypothesis-free genome-wide association testing; and (4) single nucleotide polymorphism (SNP) heritability via genomic-relatedness-matrix restricted maximum likelihood analysis (GREML). The GREML analysis included a bivariate model to test whether the ADHD symptom dimensions index the same genetic liability. The results revealed significant differential associations between two a priori loci and ADHD phenotypes, rs6296 in HTR1B with inattention and rs3746544 in SNAP-25 with hyperactivity-impulsivity. No significant gene-based or genome-wide associations were detected, but SNP heritability revealed that a large portion of genetic variance was accounted for by common SNPs (44%, 55%, and 59% for inattention, hyperactivity-impulsivity, and total ADHD, respectively) and substantial shared genetic variance across inattention and hyperactivity-impulsivity (86%). These findings reveal both unique and common patterns of genetic influences across dimensional ADHD-related phenotypes. More broadly, these findings reveal the value in using multiple methods to understand the genetic etiology of ADHD.

Diagnostic profiles associated with long-term opioid therapy in active duty servicemembers.

INTRODUCTION: Over-prescription of opioids has diminished in recent years; however, certain populations remain at high risk. There is a dearth of research evaluating prescription rates using specific multimorbidity patterns. OBJECTIVE: To identify distinct clinical profiles associated with opioid prescription and evaluate their relative odds of receiving long-term opioid therapy. DESIGN: Retrospective analysis of the complete military electronic health record. We assessed demographics and 26 physiological, psychological, and pain conditions present during initial opioid prescription. Latent class analysis (LCA) identified unique clinical profiles using diagnostic data. Logistic regression measured the odds of these classes receiving long-term opioid therapy. SETTING: All electronic health data under the TRICARE network. PARTICIPANTS: All servicemembers on active duty during fiscal years 2016 through 2019 who filled at least one opioid prescription. MAIN OUTCOME MEASURES: Number and qualitative characteristics of LCA classes; odds ratios (ORs) from logistic regression. We hypothesized that LCA classes characterized by high-risk contraindications would have significantly higher odds of long-term opioid therapy. RESULTS: A total of N = 714,446 active duty servicemembers were prescribed an opioid during the study window, with 12,940 (1.8%) receiving long-term opioid therapy. LCA identified five classes: Relatively Healthy (82%); Musculoskeletal Acute Pain and Substance Use Disorders (6%); High Pain, Low Mental Health Burden (9%); Low Pain, High Mental Health Burden (2%), and Multisystem Multimorbid (1%). Logistic regression found that, compared to the Relatively Healthy reference, the Multisystem Multimorbid class, characterized by multiple opioid contraindications, had the highest odds of receiving long-term opioid therapy (OR = 9.24; p < .001; 95% confidence interval [CI]: 8.56, 9.98). CONCLUSION: Analyses demonstrated that classes with greater multimorbidity at the time of prescription, particularly co-occurring psychiatric and pain disorders, had higher likelihood of long-term opioid therapy. Overall, this study helps identify patients most at risk for long-term opioid therapy and has implications for health care policy and patient care.

N-acetylcysteine as a treatment for substance use cravings: A meta-analysis.

N-acetylcysteine (NAC) may serve as a novel pharmacotherapy for substance use and substance craving in individuals with substance use disorders (SUDs), possibly through its potential to regulate glutamate. Though prior meta-analyses generally support NAC's efficacy in reducing symptoms of craving, individual trials have found mixed results. The aims of the this updated meta-analysis were to (1) examine the efficacy of NAC in treating symptoms of craving in individuals with a SUD and (2) explore subgroup differences, risk of bias, and publication bias across trials. Database searches of PubMed, Cochrane Library, and ClinicalTrials.gov were conducted in June and July of 2023 to identify relevant randomized control trials (RCTs). The meta-analysis consisted of 9 trials which analyzed data from a total of 623 participants. The most targeted substance in the clinical trials was alcohol (3/9; 33.3%), followed by tobacco (2/9; 22.2%) and multiple substances (2/9; 22.2%). Meta-analysis, subgroup analyses, and leave-one-out analyses were conducted to examine treatment effect on craving symptoms and adverse events (AEs). Risk of bias assessments, Egger's tests, and funnel plot tests were conducted to examine risk of bias and publication bias. NAC did not significantly outperform placebo in reducing symptoms of craving in the meta-analysis (SMD = 0.189, 95% CI = -0.015 - 0.393). Heterogeneity was very high in the meta-analysis (99.26%), indicating that findings may have been influenced by clinical or methodological differences in the study protocols. Additionally, results indicate that there may be publication bias present. Overall, our findings are contrary to those of prior meta-analyses, suggesting limited impact of NAC on substance craving. However, the high heterogeneity and presence of publication bias identified warrants cautious interpretation of the meta-analytic outcomes.

Healthcare utilization and readiness outcomes among soldiers with post-deployment at-risk drinking, by multimorbidity class.

Although alcohol use disorder (AUD) regularly co-occurs with other conditions, there has not been investigation of specific multimorbidity classes among military members with at-risk alcohol use. We used latent class analysis (LCA) to cluster 138,929 soldiers with post-deployment at-risk drinking based on their co-occurring psychological and physical health conditions and indicators of alcohol severity. We examined the association of these multimorbidity classes with healthcare utilization and military readiness outcomes. Latent class analysis was conducted on 31 dichotomous indicators capturing alcohol use severity, mental health screens, psychological and physical health diagnoses, and tobacco use. Longitudinal survival analysis was used to examine the relative hazards of class membership regarding healthcare utilization (e.g., emergency department visit, inpatient stay) and readiness outcomes (e.g., early separation for misconduct). Latent class analysis identified five classes: Class 1 -Relatively Healthy (51.6 %); Class 2 - Pain/Tobacco (17.3 %); Class 3 - Heavy Drinking/Pain/Tobacco (13.1 %); Class 4 - Mental Health/Pain/Tobacco (12.7 %); and Class 5 - Heavy Drinking/Mental Health/Pain/Tobacco (5.4 %). Musculoskeletal pain and tobacco use were prevalent in all classes, though highest in Classes 2, 4, and 5. Classes 4 and 5 had the highest hazards of all outcomes. Class 5 generally exhibited slightly higher hazards of all outcomes than Class 4, demonstrating the exacerbation of risk among those with heavy drinking/AUD in combination with mental health conditions and other multimorbidity. This study provides new information about the most common multimorbidity presentations of at-risk drinkers in the military so that targeted, individualized care may be employed. Future research is needed to determine whether tailored prevention and treatment approaches for soldiers in different multimorbidity classes is associated with improved outcomes.

Evaluating the Acceptability and Feasibility of Collecting Passive Smartphone Data to Estimate Psychological Functioning in U.S. Service Members and Veterans: A Pilot Study.

INTRODUCTION: This study investigated the acceptability and feasibility of digital phenotyping in a military sample with a history of traumatic brain injury and co-occurring psychological and cognitive symptoms. The first aim was to evaluate the acceptability of digital phenotyping by (1a) quantifying the proportion of participants willing to download the app and rates of dropout and app discontinuation and (1b) reviewing the stated reasons for both refusing and discontinuing use of the app. The second aim was to investigate technical feasibility by (2a) characterizing the amount and frequency of transferred data and (2b) documenting technical challenges. Exploratory aim 3 sought to leverage data on phone and keyboard interactions to predict if a participant (a) is depressed and (b) has depression that improves over the course of the study. MATERIALS AND METHODS: A passive digital phenotyping app (Mindstrong Discovery) functioned in the background of the participants' smartphones and passively collected phone usage and typing kinematics data. RESULTS: Fifteen out of 16 participants (93.8%) consented to install the app on their personal smartphone devices. Four participants (26.7%) discontinued the use of the app partway through the study, primarily because of keyboard usability and technical issues. Fourteen out of 15 participants (93.3%) had at least one data transfer, and the median number of days with data was 40 out of a possible 57 days. The exploratory machine learning models predicting depression status and improvement in depression performed better than chance. CONCLUSIONS: The findings of this pilot study suggest that digital phenotyping is acceptable and feasible in a military sample and provides support for future larger investigations of this technology.

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.

Uncommon Protein-Coding Variants Associated With Suicide Attempt in a Diverse Sample of U.S. Army Soldiers.

BACKGROUND: Suicide is a societal and public health concern of global scale. Identifying genetic risk factors for suicide attempt can characterize underlying biology and enable early interventions to prevent deaths. Recent studies have described common genetic variants for suicide-related behaviors. Here, we advance this search for genetic risk by analyzing the association between suicide attempt and uncommon variation exome-wide in a large, ancestrally diverse sample. METHODS: We sequenced whole genomes of 13,584 soldiers from the Army STARRS (Army Study to Assess Risk and Resilience in Servicemembers), including 979 individuals with a history of suicide attempt. Uncommon, nonsilent protein-coding variants were analyzed exome-wide for association with suicide attempt using gene-collapsed and single-variant analyses. RESULTS: We identified 19 genes with variants enriched in individuals with history of suicide attempt, either through gene-collapsed or single-variant analysis (Bonferroni padjusted < .05). These genes were CIB2, MLF1, HERC1, YWHAE, RCN2, VWA5B1, ATAD3A, NACA, EP400, ZNF585A, LYST, RC3H2, PSD3, STARD9, SGMS1, ACTR6, RGS7BP, DIRAS2, and KRTAP10-1. Most genes had variants across multiple genomic ancestry groups. Seventeen of these genes were expressed in healthy brain tissue, with 9 genes expressed at the highest levels in the brain versus other tissues. Brains from individuals deceased from suicide aberrantly expressed RGS7BP (padjusted = .035) in addition to nominally significant genes including YWHAE and ACTR6, all of which have reported associations with other mental disorders. CONCLUSIONS: These results advance the molecular characterization of suicide attempt behavior and support the utility of whole-genome sequencing for complementing the findings of genome-wide association studies in suicide research.

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.

The Mediating Role of Family Acceptance and Conflict on Suicidality among Sexual and Gender Minority Youth.

INTRODUCTION: Prior research suggests sexual and gender minority (SGM) youth are profoundly impacted by levels of parental support. This study assessed mediating effects of generalized family acceptance and conflict on lifetime suicidal behaviors among a large diverse sample comprising both SGM and non-SGM youth in early adolescence, when intervention to optimize family dynamics may be critical. MATERIALS: Using data from the first-year follow-up of the Adolescent Brain Cognitive Development Study based in the United States, mediation was tested using a binary logistic regression model fitted with a generalized structural equation. Models included SGM status as the independent variable, family acceptance or family conflict sum score as the mediator, and the presence of lifetime suicidal behaviors as the dependent variable. Models adjusted for age, birth-assigned sex (as reported by the parent/guardian), and race/ethnicity. RESULTS: Of 11,235 youths, lifetime suicidal behaviors were reported by 1.5% (n = 164). Youths with SGM identities reported 40% less parental acceptance and 47% greater family conflict, compared to non-SGM peers. Both parental acceptance and family conflict partially mediated associations between SGM identification and odds of lifetime suicidal behavior (ps = .001). CONCLUSIONS: Identification of modifiable risk factors for suicidality in this vulnerable population, including parental acceptance and family conflict, is critical to improving health outcomes. Clinicians should work with SGM youth and their families starting in childhood to optimize family dynamics and bolster acceptance to potentially reduce adverse health outcomes. HIGHLIGHTSYouths with SGM identity reported 40% less parental acceptance than non-SGM peers.Parental acceptance was associated with lower odds of lifetime suicidal behaviors.Family factors partially mediated associations between SGM status and suicidal behaviors.

Beliefs and Perceived Barriers Regarding Psychedelic-assisted Therapy in a Pilot Study of Service Members and Veterans With a History of Traumatic Brain Injury.

INTRODUCTION: Posttraumatic stress disorder (PTSD) and depression are common in service members and veterans, and the response to currently available treatments is often modest at best. Recent studies suggest potential benefit with psychedelic-assisted therapies (PATs), particularly 3,4-methylenedioxymethamphetamine-assisted therapy for PTSD and psilocybin-assisted therapy for depression. This study examined beliefs and perceived barriers regarding PAT among service members and veterans to inform the delivery of these treatments if they are approved by the FDA. MATERIALS AND METHODS: Twenty-one service members and veterans (67% male, 81% White, and 43% active duty) with a history of traumatic brain injury and co-occurring cognitive and psychological symptoms completed a measure assessing baseline knowledge and views of PAT, read a brief psychoeducation regarding PAT, and then responded to questions related to their beliefs and perceived barriers to PAT. RESULTS: Before psychoeducation, participants reported a neutral view of psychedelic drugs (M = 2.76; range: 1-5), PAT (M = 3.33), and interest in PAT (M = 3.10). After psychoeducation, participants reported a significantly more positive view of psychedelic drugs (M = 3.24, P = .014) and interest in PAT (M = 3.67, P = .016). Overall, participants indicated that they would support PAT availability in medical settings if proven beneficial (M = 4.52; 5 = "agree strongly") and they would support a loved one engaging in PAT (M = 4.29). The most frequently reported health concerns were concern of long-term effects (43%), fear of losing their mind (33%), fear of personality changes (33%), and fear of traumatic brain injury complications (24%). The most frequently endorsed barriers were time commitment, transportation, financial concerns, work, and childcare (33%-19%), with 48% reporting no barriers. CONCLUSIONS: This is the first study to explore beliefs and perceived barriers regarding PAT among service members and veterans. These results indicate that military populations may be interested in PAT, particularly if psychoeducation and outreach regarding these treatments occurred. If FDA approved, it will be important to facilitate command support and address logistical barriers to ensure appropriate access within military contexts.

Leveraging related health phenotypes for polygenic prediction of impulsive choice, impulsive action, and impulsive personality traits in 1534 European ancestry community adults.

Impulsivity refers to a number of conceptually related phenotypes reflecting self-regulatory capacity that are considered promising endophenotypes for mental and physical health. Measures of impulsivity can be broadly grouped into three domains, namely, impulsive choice, impulsive action, and impulsive personality traits. In a community-based sample of ancestral Europeans (n = 1534), we conducted genome-wide association studies (GWASs) of impulsive choice (delay discounting), impulsive action (behavioral inhibition), and impulsive personality traits (UPPS-P), and evaluated 11 polygenic risk scores (PRSs) of phenotypes previously linked to self-regulation. Although there were no individual genome-wide significant hits, the neuroticism PRS was positively associated with negative urgency (adjusted R2 = 1.61%, p = 3.6 × 10-7 ) and the educational attainment PRS was inversely associated with delay discounting (adjusted R2 = 1.68%, p = 2.2 × 10-7 ). There was also evidence implicating PRSs of attention-deficit/hyperactivity disorder, externalizing, risk-taking, smoking cessation, smoking initiation, and body mass index with one or more impulsivity phenotypes (adjusted R2 s: 0.35%-1.07%; FDR adjusted ps = 0.05-0.0006). These significant associations between PRSs and impulsivity phenotypes are consistent with established genetic correlations. The combined PRS explained 0.91%-2.46% of the phenotypic variance for individual impulsivity measures, corresponding to 8.7%-32.5% of their reported single-nucleotide polymorphism (SNP)-based heritability, suggesting a non-negligible portion of the SNP-based heritability can be recovered by PRSs. These results support the predictive validity and utility of PRSs, even derived from related phenotypes, to inform the genetics of impulsivity phenotypes.