Cross-ancestry genetic investigation of schizophrenia, cannabis use disorder, and tobacco smoking.

Individuals with schizophrenia frequently experience co-occurring substance use, including tobacco smoking and heavy cannabis use, and substance use disorders. There is interest in understanding the extent to which these relationships are causal, and to what extent shared genetic factors play a role. We explored the relationships between schizophrenia (Scz; European ancestry N = 161,405; African ancestry N = 15,846), cannabis use disorder (CanUD; European ancestry N = 886,025; African ancestry N = 120,208), and ever-regular tobacco smoking (Smk; European ancestry N = 805,431; African ancestry N = 24,278) using the largest available genome-wide studies of these phenotypes in individuals of African and European ancestries. All three phenotypes were positively genetically correlated (rgs = 0.17-0.62). Genetic instrumental variable analyses suggested the presence of shared heritable factors, but evidence for bidirectional causal relationships was also found between all three phenotypes even after correcting for these shared genetic factors. We identified 327 pleiotropic loci with 439 lead SNPs in the European ancestry data, 150 of which were novel (i.e., not genome-wide significant in the original studies). Of these pleiotropic loci, 202 had lead variants which showed convergent effects (i.e., same direction of effect) on Scz, CanUD, and Smk. Genetic variants convergent across all three phenotypes showed strong genetic correlations with risk-taking, executive function, and several mental health conditions. Our results suggest that both shared genetic factors and causal mechanisms may play a role in the relationship between CanUD, Smk, and Scz, but longitudinal, prospective studies are needed to confirm a causal relationship.

Generalized genetic liability to substance use disorders.

Lifetime and temporal co-occurrence of substance use disorders (SUDs) is common and compared with individual SUDs is characterized by greater severity, additional psychiatric comorbidities, and worse outcomes. Here, we review evidence for the role of generalized genetic liability to various SUDs. Coaggregation of SUDs has familial contributions, with twin studies suggesting a strong contribution of additive genetic influences undergirding use disorders for a variety of substances (including alcohol, nicotine, cannabis, and others). GWAS have documented similarly large genetic correlations between alcohol, cannabis, and opioid use disorders. Extending these findings, recent studies have identified multiple genomic loci that contribute to common risk for these SUDs and problematic tobacco use, implicating dopaminergic regulatory and neuronal development mechanisms in the pathophysiology of generalized SUD genetic liability, with certain signals demonstrating cross-species and translational validity. Overlap with genetic signals for other externalizing behaviors, while substantial, does not explain the entirety of the generalized genetic signal for SUD. Polygenic scores (PGS) derived from the generalized genetic liability to SUDs outperform PGS for individual SUDs in prediction of serious mental health and medical comorbidities. Going forward, it will be important to further elucidate the etiology of generalized SUD genetic liability by incorporating additional SUDs, evaluating clinical presentation across the lifespan, and increasing the granularity of investigation (e.g., specific transdiagnostic criteria) to ultimately improve the nosology, prevention, and treatment of SUDs.

Alcohol milestones and internalizing, externalizing, and executive function: longitudinal and polygenic score associations.

BACKGROUND: Although the link between alcohol involvement and behavioral phenotypes (e.g. impulsivity, negative affect, executive function [EF]) is well-established, the directionality of these associations, specificity to stages of alcohol involvement, and extent of shared genetic liability remain unclear. We estimate longitudinal associations between transitions among alcohol milestones, behavioral phenotypes, and indices of genetic risk. METHODS: Data came from the Collaborative Study on the Genetics of Alcoholism (n = 3681; ages 11-36). Alcohol transitions (first: drink, intoxication, alcohol use disorder [AUD] symptom, AUD diagnosis), internalizing, and externalizing phenotypes came from the Semi-Structured Assessment for the Genetics of Alcoholism. EF was measured with the Tower of London and Visual Span Tasks. Polygenic scores (PGS) were computed for alcohol-related and behavioral phenotypes. Cox models estimated associations among PGS, behavior, and alcohol milestones. RESULTS: Externalizing phenotypes (e.g. conduct disorder symptoms) were associated with future initiation and drinking problems (hazard ratio (HR)⩾1.16). Internalizing (e.g. social anxiety) was associated with hazards for progression from first drink to severe AUD (HR⩾1.55). Initiation and AUD were associated with increased hazards for later depressive symptoms and suicidal ideation (HR⩾1.38), and initiation was associated with increased hazards for future conduct symptoms (HR = 1.60). EF was not associated with alcohol transitions. Drinks per week PGS was linked with increased hazards for alcohol transitions (HR⩾1.06). Problematic alcohol use PGS increased hazards for suicidal ideation (HR = 1.20). CONCLUSIONS: Behavioral markers of addiction vulnerability precede and follow alcohol transitions, highlighting dynamic, bidirectional relationships between behavior and emerging addiction.

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.

Characteristics of women concordant and discordant for urine drug screens for cannabis exposure and self-reported cannabis use during pregnancy.

BACKGROUND: Increasing cannabis use among pregnant people and equivocal evidence linking prenatal cannabis exposure to adverse outcomes in offspring highlights the need to understand its potential impact on pregnancy and child outcomes. Assessing cannabis use during pregnancy remains a major challenge with potential influences of stigma on self-report as well as detection limitations of easily collected biological matrices. OBJECTIVE: This descriptive study examined the concordance between self-reported (SR) cannabis use and urine drug screen (UDS) detection of cannabis exposure during the first trimester of pregnancy and characterized concordant and discordant groups for sociodemographic factors, modes of use, secondhand exposure to cannabis and tobacco, and alcohol use and cotinine positivity. STUDY DESIGN: The Cannabis Use During Development and Early Life (CUDDEL) Study is an ongoing longitudinal study that recruits pregnant individuals presenting for obstetric care, who report lifetime cannabis use as well as using (n = 289) or not using cannabis (n = 169) during pregnancy. During the first trimester pregnancy visit, SR of cannabis use and a UDS for cannabis, other illicit drugs and nicotine are acquired from eligible participants, of whom 333 as of 05/01/2023 had both. RESULTS: Using available CUDDEL Study data on both SR and UDS (n = 333; age 26.6 ± 4.7; 88.6% Black; 45.4% below federal poverty threshold; 56.5% with paid employment; 89% with high school education; 22% first pregnancy; 12.3 ± 3.6 weeks gestation), we classified pregnant individuals with SR and UDS data into 4 groups based on concordance (k = 0.49 [95% C.I. 0.40-0.58]) between SR cannabis use and UDS cannabis detection during the first trimester: 1) SR+/UDS+ (n = 107); 2) SR-/UDS- (n = 142); 3) SR+/UDS- (n = 44); 4) SR-/UDS+ (n = 40). Those who were SR+/UDS- reported less frequent cannabis use and fewer hours under the influence of cannabis during their pregnancy. Those who were SR-/UDS+ were more likely to have joined the study at a lower gestational age with 62.5% reporting cannabis use during their pregnancy prior to being aware that they were pregnant. Of the 40 SR-/UDS+ women, 14 (i.e., 35%) reported past month secondhand exposure, or blunt usage. In the subset of individuals with SR and UDS available at trimester 2 (N = 160) and 3 (N = 140), concordant groups were mostly stable and > 50% of those in the discordant groups became concordant by the second trimester. Classifying individuals as exposed or not exposed who were SR+ and/or UDS+ resulted in minor changes in group status based on self-report at screening. CONCLUSION: Overall, there was moderate concordance between SR and UDS for cannabis use/exposure during pregnancy. Instances of SR+/UDS- discordancy may partially be attributable to lower levels of use that are not detected on UDS. SR-/UDS+ discordancy may arise from recent use prior to knowledge of pregnancy, extreme secondhand exposure, deception, and challenges with completing questionnaires. Acquiring both self-report and biological detection of cannabis use/exposure allows for the examination of convergent evidence. Classifying those who are SR+ and/or UDS+ as individuals who used cannabis during their first trimester after being aware of their pregnancy resulted in only a minor change in exposure status; thus, relying on self-report screening, at least in this population and within this sociocultural context likely provides an adequate approximation of cannabis use during pregnancy.

Neuroanatomical variability associated with early substance use initiation: Results from the ABCD Study.

The extent to which neuroanatomical variability associated with substance involvement reflects pre-existing risk and/or consequences of substance exposure remains poorly understood. In the Adolescent Brain Cognitive DevelopmentSM (ABCD®) Study, we identify associations between global and regional differences in brain structure and early substance use initiation (i.e., occurring <15 years of age; nsanalytic=6,556-9,804), with evidence that associations precede initiation. Neurodevelopmental variability in brain structure may confer risk for substance involvement.

Associations between COVID-19 and putative markers of neuroinflammation: A diffusion basis spectrum imaging study.

COVID-19 remains a significant international public health concern. Yet, the mechanisms through which symptomatology emerges remain poorly understood. While SARS-CoV-2 infection may induce prolonged inflammation within the central nervous system, the evidence primarily stems from limited small-scale case investigations. To address this gap, our study capitalized on longitudinal UK Biobank neuroimaging data acquired prior to and following COVID-19 testing (N = 416 including n = 224 COVID-19 cases; Mage = 58.6). Putative neuroinflammation was assessed in gray matter structures and white matter tracts using non-invasive Diffusion Basis Spectrum Imaging (DBSI), which estimates inflammation-related cellularity (DBSI-restricted fraction; DBSI-RF) and vasogenic edema (DBSI-hindered fraction; DBSI-HF). We hypothesized that COVID-19 case status would be associated with increases in DBSI markers after accounting for potential confound (age, sex, race, body mass index, smoking frequency, and data acquisition interval) and multiple testing. COVID-19 case status was not significantly associated with DBSI-RF (|ß|'s < 0.28, pFDR >0.05), but with greater DBSI-HF in left pre- and post-central gyri and right middle frontal gyrus (ß's > 0.3, all pFDR = 0.03). Intriguingly, the brain areas exhibiting increased putative vasogenic edema had previously been linked to COVID-19-related functional and structural alterations, whereas brain regions displaying subtle differences in cellularity between COVID-19 cases and controls included regions within or functionally connected to the olfactory network, which has been implicated in COVID-19 psychopathology. Nevertheless, our study might not have captured acute and transitory neuroinflammatory effects linked to SARS-CoV-2 infection, possibly due to symptom resolution before the imaging scan. Future research is warranted to explore the potential time- and symptom-dependent neuroinflammatory relationship with COVID-19.

Clinical, genomic, and neurophysiological correlates of lifetime suicide attempts among individuals with alcohol dependence.

Research has identified clinical, genomic, and neurophysiological markers associated with suicide attempts (SA) among individuals with psychiatric illness. However, there is limited research among those with an alcohol use disorder (AUD), despite their disproportionately higher rates of SA. We examined lifetime SA in 4,068 individuals with DSM-IV alcohol dependence from the Collaborative Study on the Genetics of Alcoholism (23% lifetime suicide attempt; 53% female; 17% Admixed African American ancestries; mean age: 38). We 1) conducted a genome-wide association study (GWAS) of SA and performed downstream analyses to determine whether we could identify specific biological pathways of risk, and 2) explored risk in aggregate across other clinical conditions, polygenic scores (PGS) for comorbid psychiatric problems, and neurocognitive functioning between those with AD who have and have not reported a lifetime suicide attempt. The GWAS and downstream analyses did not produce any significant associations. Participants with an AUD who had attempted suicide had greater rates of trauma exposure, major depressive disorder, post-traumatic stress disorder, and other substance use disorders compared to those who had not attempted suicide. Polygenic scores for suicide attempt, depression, and PTSD were associated with reporting a suicide attempt (ORs = 1.22-1.44). Participants who reported a SA also had decreased right hemispheric frontal-parietal theta and decreased interhemispheric temporal-parietal alpha electroencephalogram resting-state coherences relative to those who did not, but differences were small. Overall, individuals with alcohol dependence who report SA appear to experience a variety of severe comorbidities and elevated polygenic risk for SA. Our results demonstrate the need to further investigate suicide attempts in the presence of substance use disorders.

GenomeMUSter mouse genetic variation service enables multitrait, multipopulation data integration and analysis.

Hundreds of inbred mouse strains and intercross populations have been used to characterize the function of genetic variants that contribute to disease. Thousands of disease-relevant traits have been characterized in mice and made publicly available. New strains and populations including consomics, the collaborative cross, expanded BXD, and inbred wild-derived strains add to existing complex disease mouse models, mapping populations, and sensitized backgrounds for engineered mutations. The genome sequences of inbred strains, along with dense genotypes from others, enable integrated analysis of trait-variant associations across populations, but these analyses are hampered by the sparsity of genotypes available. Moreover, the data are not readily interoperable with other resources. To address these limitations, we created a uniformly dense variant resource by harmonizing multiple data sets. Missing genotypes were imputed using the Viterbi algorithm with a data-driven technique that incorporates local phylogenetic information, an approach that is extendable to other model organisms. The result is a web- and programmatically accessible data service called GenomeMUSter, comprising single-nucleotide variants covering 657 strains at 106.8 million segregating sites. Interoperation with phenotype databases, analytic tools, and other resources enable a wealth of applications, including multitrait, multipopulation meta-analysis. We show this in cross-species comparisons of type 2 diabetes and substance use disorder meta-analyses, leveraging mouse data to characterize the likely role of human variant effects in disease. Other applications include refinement of mapped loci and prioritization of strain backgrounds for disease modeling to further unlock extant mouse diversity for genetic and genomic studies in health and disease.

Cross-ancestry genetic investigation of schizophrenia, cannabis use disorder, and tobacco smoking.

Individuals with schizophrenia frequently experience co-occurring substance use, including tobacco smoking and heavy cannabis use, and substance use disorders. There is interest in understanding the extent to which these relationships are causal, and to what extent shared genetic factors play a role. We explored the relationships between schizophrenia (Scz), cannabis use disorder (CanUD), and ever-regular tobacco smoking (Smk) using the largest available genome-wide studies of these phenotypes in individuals of African and European ancestries. All three phenotypes were positively genetically correlated (rgs = 0.17 - 0.62). Causal inference analyses suggested the presence of horizontal pleiotropy, but evidence for bidirectional causal relationships was also found between all three phenotypes even after correcting for horizontal pleiotropy. We identified 439 pleiotropic loci in the European ancestry data, 150 of which were novel (i.e., not genome-wide significant in the original studies). Of these pleiotropic loci, 202 had lead variants which showed convergent effects (i.e., same direction of effect) on Scz, CanUD, and Smk. Genetic variants convergent across all three phenotypes showed strong genetic correlations with risk-taking, executive function, and several mental health conditions. Our results suggest that both horizontal pleiotropy and causal mechanisms may play a role in the relationship between CanUD, Smk, and Scz, but longitudinal, prospective studies are needed to confirm a causal relationship.

Genetic and shared environmental factors explain the association between adolescent polysubstance use and high school noncompletion.

OBJECTIVE: Examine the nature of the relationship between adolescent polysubstance use and high school noncompletion. METHOD: Among a sample of 9,579 adult Australian twins (58.63% female, Mage = 30.59), we examined the association between the number of substances used in adolescence and high school noncompletion within a discordant twin design and bivariate twin analysis. RESULTS: In individual-level models controlling for parental education, conduct disorder symptoms, childhood major depression, sex, zygosity, and cohort, each additional substance used in adolescence was associated with a 30% increase in the odds of high school noncompletion (OR = 1.30 [1.18, 1.42]). Discordant twin models found that the potentially causal effect of adolescent use on high school noncompletion was nonsignificant (OR = 1.19 [0.96, 1.47]). Follow-up bivariate twin models suggested genetic (35.4%, 95% CI [24.5%, 48.7%]) and shared environmental influences (27.8%, 95% CI [12.7%, 35.1%]) each contributed to the covariation in adolescent polysubstance use and early school dropout. CONCLUSIONS: The association between polysubstance use and early school dropout was largely accounted for by genetic and shared environmental factors, with nonsignificant evidence for a potentially causal association. Future research should examine whether underlying shared risk factors reflect a general propensity for addiction, a broader externalizing liability, or a combination of the two. More evidence using finer measurement of substance use is needed to rule out a causal association between adolescent polysubstance use and high school noncompletion. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Associations between alcohol use disorder polygenic score and remission in participants from high-risk families and the Indiana Biobank.

BACKGROUND: In the United States, ~50% of individuals who meet criteria for alcohol use disorder (AUD) during their lifetimes do not remit. We previously reported that a polygenic score for AUD (PGSAUD ) was positively associated with AUD severity as measured by DSM-5 lifetime criterion count, and AUD severity was negatively associated with remission. Thus, we hypothesized that PGSAUD would be negatively associated with remission. METHODS: Individuals of European (EA) and African ancestry (AA) from the Collaborative Study on the Genetics of Alcoholism (COGA) who met lifetime criteria for AUD, and two EA cohorts ascertained for studies of liver diseases and substance use disorders from the Indiana Biobank were included. In COGA, 12-month remission was defined as any period of ≥12 consecutive months without meeting AUD criteria except craving and was further categorized as abstinent and non-abstinent. In the Indiana Biobank, remission was defined based on ICD codes and could not be further distinguished as abstinent or non-abstinent. Sex and age were included as covariates. COGA analyses included additional adjustment for AUD severity, family history of remission, and AUD treatment history. RESULTS: In COGA EA, PGSAUD was negatively associated with 12-month and non-abstinent remission (p ≤ 0.013, ßs between -0.15 and -0.10) after adjusting for all covariates. In contrast to the COGA findings, PGSAUD was positively associated with remission (p = 0.004, ß = 0.28) in the Indiana Biobank liver diseases cohort but not in the Indiana Biobank substance use disorder cohort (p = 0.17, ß = 0.15). CONCLUSIONS: PGSAUD was negatively associated with 12-month and non-abstinent remission in COGA EA, independent of behavioral measures of AUD severity and family history of remission. The discrepant results in COGA and the Indiana Biobank could reflect different ascertainment strategies: the Indiana Biobank participants were older and had higher rates of liver disease, suggesting that these individuals remitted due to alcohol-related health conditions that manifested in later life.

Shared and unique heritability of hippocampal subregion volumes in children and adults.

Behavioral genetic analyses have not demonstrated robust, unique, genetic correlates of hippocampal subregion volume. Genetic differentiation of hippocampal longitudinal axis subregion volume has not yet been investigated in population-based samples, although this has been demonstrated in rodent and post-mortem human tissue work. The following study is the first population-based investigation of genetic factors that contribute to gray matter volume along the hippocampal longitudinal axis. Twin-based biometric analyses demonstrated that longitudinal axis subregions are associated with significant, unique, genetic variance, and that longitudinal axis subregions are also associated with significant shared, hippocampus-general, genetic factors. Our study's findings suggest that genetic differences in hippocampal longitudinal axis structure can be detected in individual differences in gray matter volume in population-level research designs.

Multi-ancestry study of the genetics of problematic alcohol use in over 1 million individuals.

Problematic alcohol use (PAU), a trait that combines alcohol use disorder and alcohol-related problems assessed with a questionnaire, is a leading cause of death and morbidity worldwide. Here we conducted a large cross-ancestry meta-analysis of PAU in 1,079,947 individuals (European, N = 903,147; African, N = 122,571; Latin American, N = 38,962; East Asian, N = 13,551; and South Asian, N = 1,716 ancestries). We observed a high degree of cross-ancestral similarity in the genetic architecture of PAU and identified 110 independent risk variants in within- and cross-ancestry analyses. Cross-ancestry fine mapping improved the identification of likely causal variants. Prioritizing genes through gene expression and chromatin interaction in brain tissues identified multiple genes associated with PAU. We identified existing medications for potential pharmacological studies by a computational drug repurposing analysis. Cross-ancestry polygenic risk scores showed better performance of association in independent samples than single-ancestry polygenic risk scores. Genetic correlations between PAU and other traits were observed in multiple ancestries, with other substance use traits having the highest correlations. This study advances our knowledge of the genetic etiology of PAU, and these findings may bring possible clinical applicability of genetics insights-together with neuroscience, biology and data science-closer.

Polygenic Contributions to Suicidal Thoughts and Behaviors in a Sample Ascertained for Alcohol Use Disorders.

Introduction: Suicidal thoughts and behaviors have partially distinct genetic etiologies. Methods: We used PRS-CS to create polygenic risk scores (PRSs) from GWAS of non-suicidal self-injury, broad-sense self-harm ideation, nonfatal suicide attempt, death by suicide, and depression. Using mixed-effect models, we estimated whether these PRSs were associated with a range of suicidal thoughts and behaviors in the Collaborative Study on the Genetics of Alcoholism (N = 7,526). Results: All PRSs were significantly associated with suicidal ideation and suicide attempt (betas = 0.08-0.44, false discovery rate [FDR] <0.023). All PRSs except non-suicidal self-injury PRS were associated with active suicidal ideation (betas = 0.14-0.22, FDR <0.003). Several associations remained significant in models where all significant PRSs were included as simultaneous predictors, and when all PRSs predicted suicide attempt, the PRS together explained 6.2% of the variance in suicide attempt. Significant associations were also observed between some PRSs and persistent suicidal ideation, non-suicidal self-injury, compounded suicide attempt, and desire to die. Conclusion: Our findings suggest that PRS for depression does not explain the entirety of the variance in suicidal thoughts and behaviors, with PRS specifically for suicidal thoughts and behaviors making additional and sometimes unique contributions.

Differential genetic associations between dimensions of eating disorders and alcohol involvement in late adolescent twins.

BACKGROUND: Twin studies have demonstrated shared genetic and environmental effects between eating disorders and alcohol involvement in adults and middle adolescents. However, fewer studies have focused on late adolescents or investigated a wide range of eating disorder dimensions and alcohol involvement subscales in both sexes. We examined genetic and environmental correlations among three eating disorder dimensions and two alcohol involvement subscale scores in late adolescent twins using bivariate twin models. METHODS: Participants were 3568 female and 2526 male same-sex twins aged 18 years old from the Child and Adolescent Twin Study in Sweden. The Eating Disorder Inventory-2 (EDI) assessed the drive for thinness, bulimia, and body dissatisfaction. Alcohol involvement was assessed with the Alcohol Use Disorder Identification Test consumption (AUDIT-C) and problem (AUDIT-P) subscales. RESULTS: Only phenotypic and twin correlations in female twins met our threshold for twin modeling. The proportion of total variance for each trait accounted for by additive genetic factors ranged from 0.50 to 0.64 in female twins, with the rest explained by nonshared environmental factors and measurement error. Shared environmental factors played a minimal role in the variance of each trait. The strongest genetic correlation (ra ) emerged between EDI bulimia and AUDIT-P (ra = 0.46, 95% confidence interval: 0.37, 0.55), indicating that the proportion of genetic variance of one trait that was shared with the other trait was 0.21. Nonshared environmental correlations between eating disorder dimensions and alcohol involvement ranged from 0.03 to 0.13. CONCLUSIONS: We observed distinct patterns of genetic and environmental effects for co-occurring eating disorder dimensions and alcohol involvement in female vs. male twins, supporting sex-specific treatment strategies for late adolescents with comorbid eating disorders and alcohol use disorder. Our findings emphasize the importance of assessing family history of multiple eating disorder dimensions while treating late adolescents with problematic alcohol use, and vice versa, to improve detection and treatment.

3D-Printed Hydrogel for Diverse Applications: A Review.

Hydrogels have emerged as a versatile and promising class of materials in the field of 3D printing, offering unique properties suitable for various applications. This review delves into the intersection of hydrogels and 3D printing, exploring current research, technological advancements, and future directions. It starts with an overview of hydrogel basics, including composition and properties, and details various hydrogel materials used in 3D printing. The review explores diverse 3D printing methods for hydrogels, discussing their advantages and limitations. It emphasizes the integration of 3D-printed hydrogels in biomedical engineering, showcasing its role in tissue engineering, regenerative medicine, and drug delivery. Beyond healthcare, it also examines their applications in the food, cosmetics, and electronics industries. Challenges like resolution limitations and scalability are addressed. The review predicts future trends in material development, printing techniques, and novel applications.

Multi-ancestry genome-wide association study of cannabis use disorder yields insight into disease biology and public health implications.

As recreational use of cannabis is being decriminalized in many places and medical use widely sanctioned, there are growing concerns about increases in cannabis use disorder (CanUD), which is associated with numerous medical comorbidities. Here we performed a genome-wide association study of CanUD in the Million Veteran Program (MVP), followed by meta-analysis in 1,054,365 individuals (ncases = 64,314) from four broad ancestries designated by the reference panel used for assignment (European n = 886,025, African n = 123,208, admixed American n = 38,289 and East Asian n = 6,843). Population-specific methods were applied to calculate single nucleotide polymorphism-based heritability within each ancestry. Statistically significant single nucleotide polymorphism-based heritability for CanUD was observed in all but the smallest population (East Asian). We discovered genome-wide significant loci unique to each ancestry: 22 in European, 2 each in African and East Asian, and 1 in admixed American ancestries. A genetically informed causal relationship analysis indicated a possible effect of genetic liability for CanUD on lung cancer risk, suggesting potential unanticipated future medical and psychiatric public health consequences that require further study to disentangle from other known risk factors such as cigarette smoking.

Associations Between Polygenic Scores for Cognitive and Non-cognitive Factors of Educational Attainment and Measures of Behavior, Psychopathology, and Neuroimaging in the Adolescent Brain Cognitive Development Study.

Background: Both cognitive and non-cognitive (e.g., traits like curiosity) factors are critical for social and emotional functioning and independently predict educational attainment. These factors are heritable and genetically correlated with a range of health-relevant traits and behaviors in adulthood (e.g., risk-taking, psychopathology). However, whether these associations are present during adolescence, and to what extent these relationships diverge, could have implications for adolescent health and well-being. Methods: Using data from 5,517 youth of European ancestry from the ongoing Adolescent Brain Cognitive DevelopmentSM Study, we examined associations between polygenic scores (PGS) for cognitive and non-cognitive factors and outcomes related to cognition, socioeconomic status, risk tolerance and decision-making, substance initiation, psychopathology, and brain structure. Results: Cognitive and non-cognitive PGSs were both positively associated with cognitive performance and family income, and negatively associated with ADHD and severity of psychotic-like experiences. The cognitive PGS was also associated with greater risk-taking, delayed discounting, and anorexia, as well as lower likelihood of nicotine initiation. The cognitive PGS was further associated with cognition scores and anorexia in within-sibling analyses, suggesting these results do not solely reflect the effects of assortative mating or passive gene-environment correlations. The cognitive PGS showed significantly stronger associations with cortical volumes than the non-cognitive PGS and was associated with right hemisphere caudal anterior cingulate and pars-orbitalis in within-sibling analyses, while the non-cognitive PGS showed stronger associations with white matter fractional anisotropy and a significant within-sibling association for right superior corticostriate-frontal cortex. Conclusions: Our findings suggest that PGSs for cognitive and non-cognitive factors show similar associations with cognition and socioeconomic status as well as other psychosocial outcomes, but distinct associations with regional neural phenotypes in this adolescent sample.