Biological Insights from Schizophrenia-associated Loci in Ancestral Populations.

Large-scale genome-wide association studies of schizophrenia have uncovered hundreds of associated loci but with extremely limited representation of African diaspora populations. We surveyed electronic health records of 200,000 individuals of African ancestry in the Million Veteran and All of Us Research Programs, and, coupled with genotype-level data from four case-control studies, realized a combined sample size of 13,012 affected and 54,266 unaffected persons. Three genome-wide significant signals - near PLXNA4, PMAIP1, and TRPA1 - are the first to be independently identified in populations of predominantly African ancestry. Joint analyses of African, European, and East Asian ancestries across 86,981 cases and 303,771 controls, yielded 376 distinct autosomal loci, which were refined to 708 putatively causal variants via multi-ancestry fine-mapping. Utilizing single-cell functional genomic data from human brain tissue and two complementary approaches, transcriptome-wide association studies and enhancer-promoter contact mapping, we identified a consensus set of 94 genes across ancestries and pinpointed the specific cell types in which they act. We identified reproducible associations of schizophrenia polygenic risk scores with schizophrenia diagnoses and a range of other mental and physical health problems. Our study addresses a longstanding gap in the generalizability of research findings for schizophrenia across ancestral populations, underlining shared biological underpinnings of schizophrenia across global populations in the presence of broadly divergent risk allele frequencies.

Dexmedetomidine HCL (BXCL501) as a potential treatment for alcohol use disorder and comorbid PTSD: A phase 1b, placebo-controlled crossover laboratory study.

BACKGROUND AND OBJECTIVES: Noradrenergic dysregulation is important in the pathophysiology of posttraumatic stress disorder (PTSD) and alcohol use disorder (AUD); pharmacotherapies targeting adrenergic function have potential as treatment for comorbidity. Dexmedetomidine (sublingual film formulation-BXCL501; IGALMI) is a highly potent, selective ⍺2-adrenergic receptor agonist and may be superior to other pharmacotherapeutic approaches. A within subjects, phase 1b safety laboratory study was conducted to evaluate adverse effects of BXCL501 when combined with alcohol; BXCL501's potential efficacy was also explored. METHODS: Heavy drinker participants with a diagnosis of or who were at risk for PTSD participated in three separate test days which included pretreatment with BXCL501 (40 µg, 80 µg or placebo) administered in a randomized, double-blind fashion, followed by three testing conditions: alcohol cue reactivity, trauma-induced reactivity, and IV ethanol administration. Safety outcomes included blood pressure (BP) and sedation. Exploratory outcomes included alcohol craving, trauma-induced anxiety and craving and subjective effects of alcohol. RESULTS: Ten of twelve randomized participants competed the entire study. BXCL501 (80 µg) was associated with expected mild changes in BP and sedation; administration with alcohol did not affect those parameters. There were no clinically significant adverse effects. BXCL501 attenuated trauma-induced anxiety and attenuated subjective effects of alcohol. DISCUSSIONS AND CONCLUSIONS: BXCL501 is safe for use in humans who may drink alcohol while undergoing treatment. BXCL501 may be explored as a potential treatment for PTSD and AUD. SCIENTIFIC SIGNIFICANCE: This is the first study to provide scientific support for BXCL501's potential to treat PTSD and comorbid AUD.

Use of cigarettes and e-cigarettes, impulsivity and anxiety: Influences on suicidal ideation among youth and young adults in Texas.

INTRODUCTION: Cigarette use and smoking intensity increase risk of suicidal ideation. Less is known about e-cigarette use. Here we examine direct influences of cigarette versus e-cigarette use on suicidal ideation among 16-to-23-year-olds in Texas. METHODS: Since 2019 the Texas Adolescent Tobacco and Marketing Surveillance study collected data on suicidal ideation every six months covering the previous two-weeks. Youths answering that they had "thoughts that you would be better off dead, or of hurting yourself" on more than two of 14 days were categorized as having suicidal ideation. Generalized linear mixed-effects logistic regressions examined the influence of ever and past 30-day (P30D) use of cigarettes, e-cigarettes, impulsivity and anxiety on suicidal ideation, controlling for gender, race/ethnicity, SES, and grade in school. Interactions between ever and P30D use of both products and a) impulsivity and b) gender were examined. RESULTS: Of the 2,329 participants, 29.1% reported ever and 6.5% reported P30D cigarette use, 48.2% reported ever and 11.6% reported P30D e-cigarette use, and 18.5% reported suicidal ideation. Ever cigarette use among females (aOR=1.83; 95% CI: 1.36-2.46), P30D e-cigarette use (aOR=1.30; 95% CI: 1.00-1.68), and P30D cigarette use (aOR=1.47; 95% CI: 1.06-2.05) were independently associated with higher risk for suicidal ideation, after adjusting for covariates. Impulsivity and anxiety directly increased risk for suicidal ideation regardless of product type used. Hispanic youth had higher risk of suicidal ideation than white youth, while higher levels of SES were protective. CONCLUSION: Cigarette/e-cigarette use, as well as impulsivity and anxiety, directly increase the risk of suicidal ideation. IMPLICATIONS: Clinicians should ask young adults with a history of tobacco use, anxiety or impulsive behavior, about suicidal ideationNicotine prevention and cessation programs might be more effective if they simultaneously target substance use and mental healthCulturally appropriate support is needed for ethnic and racial minority youth and young adults in school, college and at workWhen evaluating and understanding risk, the role of multiple social identities (such as minority status, gender, and SES) is important.

Efficacy and Safety of Esmethadone (REL-1017) in Patients With Major Depressive Disorder and Inadequate Response to Standard Antidepressants: A Phase 3 Randomized Controlled Trial.

Objective: To test esmethadone (REL-1017) as adjunctive treatment in patients with major depressive disorder (MDD) and inadequate response to standard antidepressants.Methods: In this phase 3, double-blind, placebo-controlled trial, outpatients with MDD (DSM-5) were randomized to daily oral esmethadone (75 mg on day 1, followed by 25 mg daily on days 2 through 28) or placebo between December 2020 and December 2022. The primary efficacy measure was change from baseline (CFB) to day 28 in the Montgomery-Asberg Depression Rating Scale (MADRS) score. The intent-to-treat (ITT) population included all randomized participants. The per-protocol (PP) population included completers without major protocol deviations impacting assessment. Post hoc analyses included participants with severe depression (baseline MADRS score ≥35).Results: For the ITT analysis (n = 227), mean CFB was 15.1 (SD 11.3) for esmethadone (n = 113) and 12.9 (SD 10.4) for placebo (n = 114), with a mean difference (MD) of 2.3, which was not statistically significant (P = .154; Cohen effect size [ES] = 0.21). Remission rates were 22.1% and 13.2% (P = .076), and response rates were 39.8% and 27.2% (P = .044) with esmethadone and placebo, respectively. For the PP analysis (n = 198), mean CFB was 15.6 (SD 11.2) for esmethadone (n = 101) and 12.5 (SD 9.9) for placebo (n = 97), with an MD of 3.1 (P = .051; ES =0.29). In post hoc analyses of patients with baseline MADRS ≥35 in the ITT population (n = 112), MD was 6.9; P = .0059; ES = 0.57, and for the PP population (n = 98), MD was 7.9; P = .0015; ES = 0.69. Adverse events (AEs) were predominantly mild or moderate and transient, with no significant differences between groups.Conclusions: The primary end point was not met. Esmethadone showed stronger efficacy in PP than in ITT analyses, with the discrepancy not attributable to AEs impacting treatment adherence. Significant efficacy occurred in post hoc analyses of patients with severe depression. Esmethadone was well tolerated, consistent with prior studies.Trial Registration: ClinicalTrials.gov identifier: NCT04688164.

Ginkgo biloba for Tardive Dyskinesia and Plasma MnSOD Activity: Association with MnSOD Ala-9Val Variant: A Randomized, Double-blind Trial.

BACKGROUND: Excessive free radicals are implicated in the pathophysiology of tardive dyskinesia (TD), and Ginkgo biloba extract (EGb761) scavenges free radicals, thereby enhancing antioxidant enzymes such as mitochondrial manganese superoxide dismutase (MnSOD). This study examined whether EGb761 treatment would improve TD symptoms and increase MnSOD activity, particularly in TD patients with specific MnSOD Val-9Ala genotype. METHODS: An EGb761 (240 mg/day) 12-week double-blind clinical trial with 157 TD patients was randomized. The severity of TD was measured by the Abnormal Involuntary Movement Scale (AIMS) and plasma MnSOD activity was assayed before and after 12 weeks of treatment. Further, in an expanded sample, we compared MnSOD activity in 159 TD, 227 non-TD and 280 healthy controls, as well as the allele frequencies and genotypes for the MnSOD Ala-9Val polymorphism in 352 TD, 486 non-TD and 1150 healthy controls. RESULTS: EGb761 significantly reduced TD symptoms and increased MnSOD activity in TD patients compared to placebo (both p < 0.01). Moreover, we found an interaction between genotype and treatment response (p < 0.001). Furthermore, in the EGb761 group, patients carrying the Ala allele displayed a significantly lower AIMS total score than patients with the Val/Val genotype. In addition, MnSOD activity was significantly lower at baseline in TD patients compared with healthy controls or non-TD patients. CONCLUSION: EGb761 treatment enhanced low MnSOD activity in TD patients and produced greater improvement in TD symptoms in patients with the Ala allele of the MnSOD Ala-9Val polymorphism.

Cognitive enhancing effect of rTMS combined with tDCS in patients with major depressive disorder: a double-blind, randomized, sham-controlled study.

BACKGROUND: Cognitive dysfunction is one of the common symptoms in patients with major depressive disorder (MDD). Repetitive transcranial magnetic stimulation (rTMS) and transcranial direct current stimulation (tDCS) have been studied separately in the treatment of cognitive dysfunction in MDD patients. We aimed to investigate the effectiveness and safety of rTMS combined with tDCS as a new therapy to improve neurocognitive impairment in MDD patients. METHODS: In this brief 2-week, double-blind, randomized, and sham-controlled trial, a total of 550 patients were screened, and 240 MDD inpatients were randomized into four groups (active rTMS + active tDCS, active rTMS + sham tDCS, sham rTMS + active tDCS, sham rTMS + sham tDCS). Finally, 203 patients completed the study and received 10 treatment sessions over a 2-week period. The Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) was performed to assess patients' cognitive function at baseline and week 2. Also, we applied the 24-item Hamilton Depression Rating Scale (HDRS-24) to assess patients' depressive symptoms at baseline and week 2. RESULTS: After 10 sessions of treatment, the rTMS combined with the tDCS group showed more significant improvements in the RBANS total score, immediate memory, and visuospatial/constructional index score (all p < 0.05). Moreover, post hoc tests revealed a significant increase in the RBANS total score and Visuospatial/Constructional in the combined treatment group compared to the other three groups but in the immediate memory, the combined treatment group only showed a better improvement than the sham group. The results also showed the RBANS total score increased significantly higher in the active rTMS group compared with the sham group. However, rTMS or tDCS alone was not superior to the sham group in terms of other cognitive performance. In addition, the rTMS combined with the tDCS group showed a greater reduction in HDRS-24 total score and a better depression response rate than the other three groups. CONCLUSIONS: rTMS combined with tDCS treatment is more effective than any single intervention in treating cognitive dysfunction and depressive symptoms in MDD patients. TRIAL REGISTRATION: Chinese Clinical Trial Registry (ChiCTR2100052122).

Enhancing post-traumatic stress disorder patient assessment: leveraging natural language processing for research of domain criteria identification using electronic medical records.

BACKGROUND: Extracting research of domain criteria (RDoC) from high-risk populations like those with post-traumatic stress disorder (PTSD) is crucial for positive mental health improvements and policy enhancements. The intricacies of collecting, integrating, and effectively leveraging clinical notes for this purpose introduce complexities. METHODS: In our study, we created a natural language processing (NLP) workflow to analyze electronic medical record (EMR) data and identify and extract research of domain criteria using a pre-trained transformer-based natural language model, all-mpnet-base-v2. We subsequently built dictionaries from 100,000 clinical notes and analyzed 5.67 million clinical notes from 38,807 PTSD patients from the University of Pittsburgh Medical Center. Subsequently, we showcased the significance of our approach by extracting and visualizing RDoC information in two use cases: (i) across multiple patient populations and (ii) throughout various disease trajectories. RESULTS: The sentence transformer model demonstrated high F1 macro scores across all RDoC domains, achieving the highest performance with a cosine similarity threshold value of 0.3. This ensured an F1 score of at least 80% across all RDoC domains. The study revealed consistent reductions in all six RDoC domains among PTSD patients after psychotherapy. We found that 60.6% of PTSD women have at least one abnormal instance of the six RDoC domains as compared to PTSD men (51.3%), with 45.1% of PTSD women with higher levels of sensorimotor disturbances compared to men (41.3%). We also found that 57.3% of PTSD patients have at least one abnormal instance of the six RDoC domains based on our records. Also, veterans had the higher abnormalities of negative and positive valence systems (60% and 51.9% of veterans respectively) compared to non-veterans (59.1% and 49.2% respectively). The domains following first diagnoses of PTSD were associated with heightened cue reactivity to trauma, suicide, alcohol, and substance consumption. CONCLUSIONS: The findings provide initial insights into RDoC functioning in different populations and disease trajectories. Natural language processing proves valuable for capturing real-time, context dependent RDoC instances from extensive clinical notes.

Vaccines as Immunotherapies for Substance Use Disorders.

Substance use disorders (SUD) present a worldwide challenge with few effective therapies except for the relative efficacy of opioid pharmacotherapies, despite limited treatment access. However, the proliferation of illicit fentanyl use initiated a dramatic and cascading epidemic of lethal overdoses. This rise in fentanyl overdoses regenerated an interest in vaccine immunotherapy, which, despite an optimistic start in animal models over the past 50 years, yielded disappointing results in human clinical trials of vaccines against nicotine, stimulants (cocaine and methamphetamine), and opioids. After a brief review of clinical and selected preclinical vaccine studies, the "lessons learned" from the previous vaccine clinical trials are summarized, and then the newest challenge of a vaccine against fentanyl and its analogs is explored. Animal studies have made significant advances in vaccine technology for SUD treatment over the past 50 years, and the resulting anti-fentanyl vaccines show remarkable promise for ending this epidemic of fentanyl deaths.

Efficacy and safety of psychedelics for the treatment of mental disorders: A systematic review and meta-analysis.

We aim to systematically review and meta-analyze the effectiveness and safety of psychedelics [psilocybin, ayahuasca (active component DMT), LSD and MDMA] in treating symptoms of various mental disorders. Web of Science, Embase, EBSCO, and PubMed were searched up to February 2024 and 126 articles were finally included. Results showed that psilocybin has the largest number of articles on treating mood disorders (N = 28), followed by ayahuasca (N = 7) and LSD (N = 6). Overall, psychedelics have therapeutic effects on mental disorders such as depression and anxiety. Specifically, psilocybin (Hedges' g = -1.49, 95% CI [-1.67, -1.30]) showed the strongest therapeutic effect among four psychedelics, followed by ayahuasca (Hedges' g = -1.34, 95% CI [-1.86, -0.82]), MDMA (Hedges' g = -0.83, 95% CI [-1.33, -0.32]), and LSD (Hedges' g = -0.65, 95% CI [-1.03, -0.27]). A small amount of evidence also supports psychedelics improving tobacco addiction, eating disorders, sleep disorders, borderline personality disorder, obsessive-compulsive disorder, and body dysmorphic disorder. The most common adverse event with psychedelics was headache. Nearly a third of the articles reported that no participants reported lasting adverse effects. Our analyses suggest that psychedelics reduce negative mood, and have potential efficacy in other mental disorders, such as substance-use disorders and PTSD.

Deep sequencing of candidate genes identified 14 variants associated with smoking abstinence in an ethnically diverse sample.

Despite the large public health toll of smoking, genetic studies of smoking cessation have been limited with few discoveries of risk or protective loci. We investigated common and rare variant associations with success in quitting smoking using a cohort from 8 randomized controlled trials involving 2231 participants and a total of 10,020 common and 24,147 rare variants. We identified 14 novel markers including 6 mapping to genes previously related to psychiatric and substance use disorders, 4 of which were protective (CYP2B6 (rs1175607105), HTR3B (rs1413172952; rs1204720503), rs80210037 on chr15), and 2 of which were associated with reduced cessation (PARP15 (rs2173763), SCL18A2 (rs363222)). The others mapped to areas associated with cancer including FOXP1 (rs1288980) and ZEB1 (rs7349). Network analysis identified significant canonical pathways for the serotonin receptor signaling pathway, nicotine and bupropion metabolism, and several related to tumor suppression. Two novel markers (rs6749438; rs6718083) on chr2 are flanked by genes associated with regulation of bodyweight. The identification of novel loci in this study can provide new targets of pharmacotherapy and inform efforts to develop personalized treatments based on genetic profiles.

Correlates of suicidal behaviors and genetic risk among United States veterans with schizophrenia or bipolar I disorder.

Persons diagnosed with schizophrenia (SCZ) or bipolar I disorder (BPI) are at high risk for self-injurious behavior, suicidal ideation, and suicidal behaviors (SB). Characterizing associations between diagnosed health problems, prior pharmacological treatments, and polygenic scores (PGS) has potential to inform risk stratification. We examined self-reported SB and ideation using the Columbia Suicide Severity Rating Scale (C-SSRS) among 3,942 SCZ and 5,414 BPI patients receiving care within the Veterans Health Administration (VHA). These cross-sectional data were integrated with electronic health records (EHRs), and compared across lifetime diagnoses, treatment histories, follow-up screenings, and mortality data. PGS were constructed using available genomic data for related traits. Genome-wide association studies were performed to identify and prioritize specific loci. Only 20% of the veterans who reported SB had a corroborating ICD-9/10 EHR code. Among those without prior SB, more than 20% reported new-onset SB at follow-up. SB were associated with a range of additional clinical diagnoses, and with treatment with specific classes of psychotropic medications (e.g., antidepressants, antipsychotics, etc.). PGS for externalizing behaviors, smoking initiation, suicide attempt, and major depressive disorder were associated with SB. The GWAS for SB yielded no significant loci. Among individuals with a diagnosed mental illness, self-reported SB were strongly associated with clinical variables across several EHR domains. Analyses point to sequelae of substance-related and psychiatric comorbidities as strong correlates of prior and subsequent SB. Nonetheless, past SB was frequently not documented in health records, underscoring the value of regular screening with direct, in-person assessments, especially among high-risk individuals.

Enhancing post-traumatic stress disorder patient assessment: Leveraging Natural Language Processing for Research of Domain Criteria Identification using electronic medical records.

Background: Extracting research of domain criteria (RDoC) from high-risk populations like those with post-traumatic stress disorder (PTSD) is crucial for positive mental health improvements and policy enhancements. The intricacies of collecting, integrating, and effectively leveraging clinical notes for this purpose introduce complexities. Methods: In our study, we created an NLP workflow to analyze electronic medical record (EMR) data, and identify and extract research of domain criteria using a pre-trained transformer-based natural language model, allmpnet-base-v2. We subsequently built dictionaries from 100,000 clinical notes and analyzed 5.67 million clinical notes from 38,807 PTSD patients from the University of Pittsburgh Medical Center. Subsequently, we showcased the significance of our approach by extracting and visualizing RDoC information in two use cases: (i) across multiple patient populations and (ii) throughout various disease trajectories. Results: The sentence transformer model demonstrated superior F1 macro scores across all RDoC domains, achieving the highest performance with a cosine similarity threshold value of 0.3. This ensured an F1 score of at least 80% across all RDoC domains. The study revealed consistent reductions in all six RDoC domains among PTSD patients after psychotherapy. Women had the highest abnormalities of sensorimotor systems, while veterans had the highest abnormalities of negative and positive valence systems. The domains following first diagnoses of PTSD were associated with heightened cue reactivity to trauma, suicide, alcohol, and substance consumption. Conclusions: The findings provide initial insights into RDoC functioning in different populations and disease trajectories. Natural language processing proves valuable for capturing real-time, context dependent RDoC instances from extensive clinical notes.

DeepBiomarker2: Prediction of Alcohol and Substance Use Disorder Risk in Post-Traumatic Stress Disorder Patients Using Electronic Medical Records and Multiple Social Determinants of Health.

Prediction of high-risk events amongst patients with mental disorders is critical for personalized interventions. We developed DeepBiomarker2 by leveraging deep learning and natural language processing to analyze lab tests, medication use, diagnosis, social determinants of health (SDoH) parameters, and psychotherapy for outcome prediction. To increase the model's interpretability, we further refined our contribution analysis to identify key features by scaling with a factor from a reference feature. We applied DeepBiomarker2 to analyze the EMR data of 38,807 patients from the University of Pittsburgh Medical Center diagnosed with post-traumatic stress disorder (PTSD) to determine their risk of developing alcohol and substance use disorder (ASUD). DeepBiomarker2 predicted whether a PTSD patient would have a diagnosis of ASUD within the following 3 months with an average c-statistic (receiver operating characteristic AUC) of 0.93 and average F1 score, precision, and recall of 0.880, 0.895, and 0.866 in the test sets, respectively. Our study found that the medications clindamycin, enalapril, penicillin, valacyclovir, Xarelto/rivaroxaban, moxifloxacin, and atropine and the SDoH parameters access to psychotherapy, living in zip codes with a high normalized vegetative index, Gini index, and low-income segregation may have potential to reduce the risk of ASUDs in PTSD. In conclusion, the integration of SDoH information, coupled with the refined feature contribution analysis, empowers DeepBiomarker2 to accurately predict ASUD risk. Moreover, the model can further identify potential indicators of increased risk along with medications with beneficial effects.

Prediction of adverse events risk in patients with comorbid post-traumatic stress disorder and alcohol use disorder using electronic medical records by deep learning models.

BACKGROUND: Identifying co-occurring mental disorders and elevated risk is vital for optimization of healthcare processes. In this study, we will use DeepBiomarker2, an updated version of our deep learning model to predict the adverse events among patients with comorbid post-traumatic stress disorder (PTSD) and alcohol use disorder (AUD), a high-risk population. METHODS: We analyzed electronic medical records of 5565 patients from University of Pittsburgh Medical Center to predict adverse events (opioid use disorder, suicide related events, depression, and death) within 3 months at any encounter after the diagnosis of PTSD+AUD by using DeepBiomarker2. We integrated multimodal information including: lab tests, medications, co-morbidities, individual and neighborhood level social determinants of health (SDoH), psychotherapy and veteran data. RESULTS: DeepBiomarker2 achieved an area under the receiver operator curve (AUROC) of 0.94 on the prediction of adverse events among those PTSD+AUD patients. Medications such as vilazodone, dronabinol, tenofovir, suvorexant, modafinil, and lamivudine showed potential for risk reduction. SDoH parameters such as cognitive behavioral therapy and trauma focused psychotherapy lowered risk while active veteran status, income segregation, limited access to parks and greenery, low Gini index, limited English-speaking capacity, and younger patients increased risk. CONCLUSIONS: Our improved version of DeepBiomarker2 demonstrated its capability of predicting multiple adverse event risk with high accuracy and identifying potential risk and beneficial factors.

A double-blind, randomized controlled study of the effects of celecoxib on clinical symptoms and cognitive impairment in patients with drug-naïve first episode schizophrenia: pharmacogenetic impact of cyclooxygenase-2 functional polymorphisms.

Chronic low-grade peripheral and central nervous system inflammation may have a role in the pathogenesis of schizophrenia (SCZ). Inhibition of cyclooxygenase-2 (COX2), the arachidonic acid pathway, may inhibit cytokine responses and minimize inflammation. In this study, we added the COX2 inhibitor celecoxib to risperidone monotherapy to examine its efficacy on clinical symptoms and cognitive deficits in drug-naïve first episode (DNFE) SCZ patients. First, we genotyped two polymorphisms (rs5275 and rs689466) in the COX-2 gene in a case-control study of 353 SCZ patients and 422 healthy controls. Ninety patients participated in a 12-week, double-blind, randomized, placebo-controlled trial of celecoxib 400 mg/day. We used the Positive and Negative Syndrome Scale (PANSS) and the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) to assess clinical symptoms and cognition. Our results show that the COX2 rs5275 polymorphism was significantly correlated with SCZ and positive symptoms. After 12-week treatment, celecoxib significantly improved the PANSS total and three subscale scores of SCZ patients. Furthermore, patients with the rs5275 TT genotype had greater improvement in PANSS total score than patients carrying the C allele. However, no significant difference in RBANS total and subscale scores existed between the celecoxib and placebo groups at week 12. Our findings suggest that COX2 inhibitors may be promising therapeutics for clinical symptoms rather than cognitive impairment in first episode SCZ patients. COX2 rs5275 gene polymorphism may be implicated in the development and the efficacy of treating clinical symptoms in SCZ.Trial Registration Number: The trial was registered with www.clinicaltrials.gov (NCT00686140).

Correlates of Risk for Disinhibited Behaviors in the Million Veteran Program Cohort.

Importance: Many psychiatric outcomes share a common etiologic pathway reflecting behavioral disinhibition, generally referred to as externalizing (EXT) disorders. Recent genome-wide association studies (GWASs) have demonstrated the overlap between EXT disorders and important aspects of veterans' health, such as suicide-related behaviors and substance use disorders (SUDs). Objective: To explore correlates of risk for EXT disorders within the Veterans Health Administration (VA) Million Veteran Program (MVP). Design, Setting, and Participants: A series of phenome-wide association studies (PheWASs) of polygenic risk scores (PGSs) for EXT disorders was conducted using electronic health records. First, ancestry-specific PheWASs of EXT PGSs were conducted in the African, European, and Hispanic or Latin American ancestries. Next, a conditional PheWAS, covarying for PGSs of comorbid psychiatric problems (depression, schizophrenia, and suicide attempt; European ancestries only), was performed. Lastly, to adjust for unmeasured confounders, a within-family analysis of significant associations from the main PheWAS was performed in full siblings (European ancestries only). This study included the electronic health record data from US veterans from VA health care centers enrolled in MVP. Analyses took place from February 2022 to August 2023 covering a period from October 1999 to January 2020. Exposures: PGSs for EXT, depression, schizophrenia, and suicide attempt. Main Outcomes and Measures: Phecodes for diagnoses derived from the International Statistical Classification of Diseases, Ninth and Tenth Revisions, Clinical Modification, codes from electronic health records. Results: Within the MVP (560 824 patients; mean [SD] age, 67.9 [14.3] years; 512 593 male [91.4%]), the EXT PGS was associated with 619 outcomes, of which 188 were independent of risk for comorbid problems or PGSs (from odds ratio [OR], 1.02; 95% CI, 1.01-1.03 for overweight/obesity to OR, 1.44; 95% CI, 1.42-1.47 for viral hepatitis C). Of the significant outcomes, 73 (11.9%) were significant in the African results and 26 (4.5%) were significant in the Hispanic or Latin American results. Within-family analyses uncovered robust associations between EXT PGS and consequences of SUDs, including liver disease, chronic airway obstruction, and viral hepatitis C. Conclusions and Relevance: Results of this cohort study suggest a shared polygenic basis of EXT disorders, independent of risk for other psychiatric problems. In addition, this study found associations between EXT PGS and diagnoses related to SUDs and their sequelae. Overall, this study highlighted the potential negative consequences of EXT disorders for health and functioning in the US veteran population.

Prediction of Adverse Events Risk in Patients with Comorbid Post- Traumatic Stress Disorder and Alcohol Use Disorder Using Electronic Medical Records by Deep Learning Models.

Background: Prediction of high-risk events in mental disorder patients is crucial. In our previous study, we developed a deep learning model: DeepBiomarker by using electronic medical records (EMR) to predict suicide related event (SRE) risk in post-traumatic stress disorder (PTSD) patients. Methods: We applied DeepBiomarker2 through data integration of multimodal information: lab test, medication, co-morbidities, and social determinants of health. We analyzed EMRs of 5,565 patients from University of Pittsburgh Medical Center with a diagnosis of PTSD and alcohol use disorder (AUD) on risk of developing an adverse event (opioid use disorder, SREs, depression and death). Results: DeepBiomarker2 predicted whether a PTSD + AUD patient will have a diagnosis of any adverse events (SREs, opioid use disorder, depression, death) within 3 months with area under the receiver operator curve (AUROC) of 0.94. We found piroxicam, vilazodone, dronabinol, tenofovir, suvorexant, empagliflozin, famciclovir, veramyst, amantadine, sulfasalazine, and lamivudine to have potential to reduce risk. Conclusions: DeepBiomarker2 can predict multiple adverse event risk with high accuracy and identify potential risk and beneficial factors. Our results offer suggestions for personalized interventions in a variety of clinical and diverse populations.

miR-124-3p target genes identify globus pallidus role in suicide ideation recovery in borderline personality disorder.

Borderline personality disorder (BPD) is characterized by patterns of unstable affect, unstable interpersonal relationships, and chronic suicidal tendencies. Research on the genetics, epigenetics, and brain function of BPD is lacking. MicroRNA-124-3p (miR-124-3p) was recently identified in a Genome-Wide Association Study as likely associated with BPD. Here, we identified the anatomical brain expression of genes likely modulated by miR-124-3p and compared morphometry in those brain regions in BPD inpatients vs. controls matched for psychiatric comorbidities. We isolated lists of targets likely modulated by miR-124-3p from TargetScan (v 8.0) by their preferentially conserved targeting (Aggregate PCT > 0.99, see Supplementary Table 1). We applied Process Genes List (PGL) to identify regions of interest associated with the co-expression of miR-124-3p target genes. We compared the gray matter volume of the top region of interest co-expressing those genes between BPD inpatients (n = 111, 46% female) and psychiatric controls (n = 111, 54% female) at The Menninger Clinic in Houston, Texas. We then correlated personality measures, suicidal ideation intensity, and recovery from suicidal ideation with volumetrics. Gene targets of miR-124-3p were significantly co-expressed in the left Globus Pallidus (GP), which was smaller in BPD than in psychiatric controls. Smaller GP volume was negatively correlated with agreeableness and with recovery from suicidal ideation post-treatment. In BPD, GP volume may be reduced through miR-124-3p regulation and suppression of its target genes. Importantly, we identified that a reduction of the GP in BPD could serve as a potential biomarker for recovery from suicidal ideation.

Comorbid alcohol use disorder and posttraumatic stress disorder: A proof-of-concept randomized placebo-controlled trial of buprenorphine and naltrexone combination treatment.

BACKGROUND: Effective pharmacologic treatments for comorbid alcohol use disorder (AUD) and posttraumatic stress disorder (PTSD) are lacking. Kappa (κ) opioid receptor antagonists may address this unmet need. Buprenorphine is a κ-opioid antagonist and a partial agonist of mu (µ) opioid receptors. Whereas naltrexone blocks all µ-mediated effects combining it with buprenorphine yields a pharmacologic net effect of opioid receptor antagonism. Because no κ-opioid receptor antagonist it available for clinical use, we tested this combination in a proof-of-concept study. METHODS: Consenting participants were enrolled in a Phase II, multisite, double-blind, randomized, placebo-controlled trial evaluating the effectiveness of sublingual (SL) buprenorphine combined with extended-release (XR) injectable naltrexone for the treatment of comorbid AUD and PTSD. Eligible participants (n = 75) were randomized (1:1:1) to receive either buprenorphine 2 mg/day plus naltrexone-XR (n = 35), buprenorphine 8 mg/day plus naltrexone-XR (n = 6) or SL plus injectable placebo (n = 34) for 12 weeks. The buprenorphine 8 mg/day plus naltrexone-XR arm was dropped early in the trial due to the negative impact of COVID-19 on enrollment. A binary primary outcome of response at week 8 was defined as a decrease from baseline of ≥10 points on the past week Clinician-Administered PTSD Scale (CAPS-5) and a reduction of ≥1 of past month alcohol risk level, as defined by the World Health Organization (WHO) and measured by the Timeline Follow-Back. RESULTS: Based on the results of a futility analysis, enrollment was stopped prior to reaching the initial goal of 90 participants. At the week eight primary timepoint, there were no statistically significant differences between buprenorphine plus naltrexone-XR and placebo group for the primary composite outcome (OR = 0.63; p-value = 0.52), or the subcomponents of the PTSD outcome (OR = 0.76; p-value = 0.69) and AUD outcome (OR = 0.17; p-value = 0.08). The placebo arm had a significantly higher proportion of participants with ≥1 WHO risk level reduction than the buprenorphine plus naltrexone-XR arm (OR = 0.18, p value = 0.02). CONCLUSIONS: This is the first study to evaluate the potential of κ-opioid receptor antagonism for the treatment of comorbid AUD and PTSD. The combination of buprenorphine and naltrexone-XR showed no significant improvement over placebo for the composite, PTSD, or alcohol measures.