Preclinical efficacy of potent and selective menin-KMT2A inhibitor JNJ-75276617 in KMT2A- and NPM1-altered leukemias.

The interaction between menin and histone-lysine N-methyltransferase 2A (KMT2A) is a critical dependency for KMT2A- or nucleophosmin 1 (NPM1)-altered leukemias and an emerging opportunity for therapeutic development. JNJ-75276617 is a novel, orally bioavailable, potent, and selective protein-protein interaction inhibitor of the binding between menin and KMT2A. In KMT2A-rearranged (KMT2A-r) and NPM1-mutant (NPM1c) AML cells, JNJ-75276617 inhibited the association of the menin-KMT2A complex with chromatin at target gene promoters, resulting in reduced expression of several menin-KMT2A target genes, including MEIS1 and FLT3. JNJ-75276617 displayed potent anti-proliferative activity across several AML and ALL cell lines and patient samples harboring KMT2A- or NPM1-alterations in vitro. In xenograft models of AML and ALL, JNJ-75276617 reduced leukemic burden and provided a significant dose-dependent survival benefit accompanied by expression changes of menin-KMT2A target genes. JNJ-75276617 demonstrated synergistic effects with gilteritinib in vitro in AML cells harboring KMT2A-r. JNJ-75276617 further exhibited synergistic effects with venetoclax and azacitidine in AML cells bearing KMT2A-r in vitro, and significantly increased survival in mice. Interestingly, JNJ-75276617 showed potent anti-proliferative activity in cell lines engineered with recently discovered mutations (MEN1M327I or MEN1T349M) that developed in patients refractory to the menin-KMT2A inhibitor revumenib. A co-crystal structure of menin in complex with JNJ-75276617 indicates a unique binding mode distinct from other menin-KMT2A inhibitors, including revumenib. JNJ-75276617 is being clinically investigated for acute leukemias harboring KMT2A or NPM1 alterations, as a monotherapy for relapsed/refractory (R/R) acute leukemia (NCT04811560), or in combination with AML-directed therapies (NCT05453903).

Genetic associations between alcohol phenotypes and life satisfaction: a genomic structural equation modelling approach.

Alcohol use (i.e., quantity, frequency) and alcohol use disorder (AUD) are common, associated with adverse outcomes, and genetically-influenced. Genome-wide association studies (GWAS) identified genetic loci associated with both. AUD is positively genetically associated with psychopathology, while alcohol use (e.g., drinks per week) is negatively associated or NS related to psychopathology. We wanted to test if these genetic associations extended to life satisfaction, as there is an interest in understanding the associations between psychopathology-related traits and constructs that are not just the absence of psychopathology, but positive outcomes (e.g., well-being variables). Thus, we used Genomic Structural Equation Modeling (gSEM) to analyze summary-level genomic data (i.e., effects of genetic variants on constructs of interest) from large-scale GWAS of European ancestry individuals. Results suggest that the best-fitting model is a Bifactor Model, in which unique alcohol use, unique AUD, and common alcohol factors are extracted. The genetic correlation (rg) between life satisfaction-AUD specific factor was near zero, the rg with the alcohol use specific factor was positive and significant, and the rg with the common alcohol factor was negative and significant. Findings indicate that life satisfaction shares genetic etiology with typical alcohol use and life dissatisfaction shares genetic etiology with heavy alcohol use.

Missingness adapted group informed clustered (MAGIC)-LASSO: a novel paradigm for phenotype prediction to improve power for genetic loci discovery.

Introduction: The availability of large-scale biobanks linking genetic data, rich phenotypes, and biological measures is a powerful opportunity for scientific discovery. However, real-world collections frequently have extensive missingness. While missing data prediction is possible, performance is significantly impaired by block-wise missingness inherent to many biobanks. Methods: To address this, we developed Missingness Adapted Group-wise Informed Clustered (MAGIC)-LASSO which performs hierarchical clustering of variables based on missingness followed by sequential Group LASSO within clusters. Variables are pre-filtered for missingness and balance between training and target sets with final models built using stepwise inclusion of features ranked by completeness. This research has been conducted using the UK Biobank (n > 500 k) to predict unmeasured Alcohol Use Disorders Identification Test (AUDIT) scores. Results: The phenotypic correlation between measured and predicted total score was 0.67 while genetic correlations between independent subjects was high >0.86. Discussion: Phenotypic and genetic correlations in real data application, as well as simulations, demonstrate the method has significant accuracy and utility for increasing power for genetic loci discovery.

Patients with alcohol-related liver disease hospitalized during the COVID-19 pandemic experienced worse outcomes.

INTRODUCTION AND OBJECTIVES: Psychosocial stressors related to the coronavirus-19 (COVID-19) pandemic increased alcohol consumption. The effect on patients with alcohol-related liver diseases remains unclear. MATERIALS AND METHODS: Hospitalizations at a tertiary care center due to alcohol-related liver disease from March 1 through August 31 in 2019 (pre-pandemic cohort) and 2020 (pandemic cohort) were reviewed retrospectively. Differences in patient demographics, disease features, and outcomes were estimated in patients with alcoholic hepatitis utilizing T-tests, Mann-Whitney tests, Chi-square and Fisher Exact Tests and Anova models and logistic regression models in patients with alcoholic cirrhosis. RESULTS: 146 patients with alcoholic hepatitis and 305 patients with alcoholic cirrhosis were admitted during the pandemic compared to 75 and 396 in the pre-pandemic cohort. Despite similar median Maddrey Scores (41.20 vs. 37.45, p=0.57), patients were 25% less likely to receive steroids during the pandemic. Patients with alcoholic hepatitis admitted during the pandemic were more likely to have hepatic encephalopathy (0.13; 95% CI:0.01, 0.25), variceal hemorrhage (0.14; 95% CI:0.04, 0.25), require oxygen (0.11; 95% CI:0.01, 0.21), vasopressors (OR:3.49; 95% CI:1.27, 12.01) and hemodialysis (OR:3.70; 95% CI:1.22, 15.13). On average, patients with alcoholic cirrhosis had MELD-Na scores 3.77 points higher (95% CI:1.05, 13.46) as compared to the pre-pandemic and had higher odds of experiencing hepatic encephalopathy (OR:1.34; 95% CI:1.04, 1.73), spontaneous bacterial peritonitis (OR:1.88; 95% CI:1.03, 3.43), ascites (OR:1.40, 95% CI:1.10, 1.79), vasopressors (OR:1.68, 95% CI:1.14, 2.46) or inpatient mortality (OR:2.00, 95% CI:1.33, 2.99) than the pre-pandemic. CONCLUSIONS: Patients with alcohol-related liver disease experienced worse outcomes during the pandemic.

Relationship between polygenic risk scores and symptom dimensions of schizophrenia and schizotypy in multiplex families with schizophrenia.

BACKGROUND: Psychotic disorders and schizotypal traits aggregate in the relatives of probands with schizophrenia. It is currently unclear how variability in symptom dimensions in schizophrenia probands and their relatives is associated with polygenic liability to psychiatric disorders. AIMS: To investigate whether polygenic risk scores (PRSs) can predict symptom dimensions in members of multiplex families with schizophrenia. METHOD: The largest genome-wide data-sets for schizophrenia, bipolar disorder and major depressive disorder were used to construct PRSs in 861 participants from the Irish Study of High-Density Multiplex Schizophrenia Families. Symptom dimensions were derived using the Operational Criteria Checklist for Psychotic Disorders in participants with a history of a psychotic episode, and the Structured Interview for Schizotypy in participants without a history of a psychotic episode. Mixed-effects linear regression models were used to assess the relationship between PRS and symptom dimensions across the psychosis spectrum. RESULTS: Schizophrenia PRS is significantly associated with the negative/disorganised symptom dimension in participants with a history of a psychotic episode (P = 2.31 × 10-4) and negative dimension in participants without a history of a psychotic episode (P = 1.42 × 10-3). Bipolar disorder PRS is significantly associated with the manic symptom dimension in participants with a history of a psychotic episode (P = 3.70 × 10-4). No association with major depressive disorder PRS was observed. CONCLUSIONS: Polygenic liability to schizophrenia is associated with higher negative/disorganised symptoms in participants with a history of a psychotic episode and negative symptoms in participants without a history of a psychotic episode in multiplex families with schizophrenia. These results provide genetic evidence in support of the spectrum model of schizophrenia, and support the view that negative and disorganised symptoms may have greater genetic basis than positive symptoms, making them better indices of familial liability to schizophrenia.

Sex differences in sleep quality and psychological distress: Insights from a middle-aged twin sample from Spain.

There is a moderate association between poor sleep and psychological distress. There are marked sex differences in the prevalence of both variables, with females outnumbering males. However, the origin of these sex differences remains unclear. The objectives of this study were to: (1) study genetic and environmental influences on the relationship between poor sleep quality and psychological distress; and (2) test possible sex differences in this relationship. The sample comprised 3544 participants from the Murcia Twin Registry. Univariate and multivariate twin models were fitted to estimate the magnitude of genetic and environmental influences on both individual variance and covariance between poor sleep quality and psychological distress. Sleep quality and psychological distress were measured using the Pittsburgh Sleep Quality Index and the EuroQol five-dimensions questionnaire, respectively. The results reveal a strong genetic association between poor sleep quality and psychological distress, which accounts for 44% (95%CI: 27%-61%) of the association between these two variables. Substantial genetic (rA = 0.50; 95%CI: 0.32, 0.67) and non-shared environmental (rE = 0.41; 95%CI: 0.30, 0.52) correlations were also found, indicating a moderate overlap between genetic (and non-shared environmental) factors influencing both phenotypes. Equating sexes in sex-limitation models did not result in significant decreases in model fit. Despite the remarkable sex differences in the prevalence of both poor sleep quality and psychological distress, there were no sex differences in the genetic and environmental influences on these variables. This suggests that genetic factors play a similar role for men and women in explaining individual differences in both phenotypes and their relationship.

Examining the source of increased bipolar disorder and major depressive disorder common risk variation burden in multiplex schizophrenia families.

Psychotic and affective disorders often aggregate in the relatives of probands with schizophrenia, and genetic studies show substantial genetic correlation among schizophrenia, bipolar disorder, and major depressive disorder. In this study, we examined the polygenic risk burden of bipolar disorder and major depressive disorder in 257 multiplex schizophrenia families (N = 1005) from the Irish Study of High-Density Multiplex Schizophrenia Families versus 2205 ancestry-matched controls. Our results indicate that members of multiplex schizophrenia families have an increased polygenic risk for bipolar disorder and major depressive disorder compared to population controls. However, this observation is largely attributable to the part of the genetic risk that bipolar disorder or major depressive disorder share with schizophrenia due to genetic correlation, rather than the affective portion of the genetic risk unique to them. These findings suggest that a complete interpretation of cross-disorder polygenic risks in multiplex families requires an assessment of the relative contribution of shared versus unique genetic factors to account for genetic correlations across psychiatric disorders.

Structure of human spermine oxidase in complex with a highly selective allosteric inhibitor.

Human spermine oxidase (hSMOX) plays a central role in polyamine catabolism. Due to its association with several pathological processes, including inflammation and cancer, hSMOX has garnered interest as a possible therapeutic target. Therefore, determination of the structure of hSMOX is an important step to enable drug discovery and validate hSMOX as a drug target. Using insights from hydrogen/deuterium exchange mass spectrometry (HDX-MS), we engineered a hSMOX construct to obtain the first crystal structure of hSMOX bound to the known polyamine oxidase inhibitor MDL72527 at 2.4 Å resolution. While the overall fold of hSMOX is similar to its homolog, murine N1-acetylpolyamine oxidase (mPAOX), the two structures contain significant differences, notably in their substrate-binding domains and active site pockets. Subsequently, we employed a sensitive biochemical assay to conduct a high-throughput screen that identified a potent and selective hSMOX inhibitor, JNJ-1289. The co-crystal structure of hSMOX with JNJ-1289 was determined at 2.1 Å resolution, revealing that JNJ-1289 binds to an allosteric site, providing JNJ-1289 with a high degree of selectivity towards hSMOX. These results provide crucial insights into understanding the substrate specificity and enzymatic mechanism of hSMOX, and for the design of highly selective inhibitors.

Determining the stability of genome-wide factors in BMI between ages 40 to 69 years.

Genome-wide association studies (GWAS) have successfully identified common variants associated with BMI. However, the stability of aggregate genetic variation influencing BMI from midlife and beyond is unknown. By analysing 165,717 men and 193,073 women from the UKBiobank, we performed BMI GWAS on six independent five-year age intervals between 40 and 72 years. We then applied genomic structural equation modeling to test competing hypotheses regarding the stability of genetic effects for BMI. LDSR genetic correlations between BMI assessed between ages 40 to 73 were all very high and ranged 0.89 to 1.00. Genomic structural equation modeling revealed that molecular genetic variance in BMI at each age interval could not be explained by the accumulation of any age-specific genetic influences or autoregressive processes. Instead, a common set of stable genetic influences appears to underpin genome-wide variation in BMI from middle to early old age in men and women alike.

Evaluating the role of common risk variation in the recurrence risk of schizophrenia in multiplex schizophrenia families.

Multiplex families have higher recurrence risk of schizophrenia compared to the families of sporadic cases, but the source of this increased recurrence risk is unknown. We used schizophrenia genome-wide association study data (N = 156,509) to construct polygenic risk scores (PRS) in 1005 individuals from 257 multiplex schizophrenia families, 2114 ancestry-matched sporadic cases, and 2205 population controls, to evaluate whether increased PRS can explain the higher recurrence risk of schizophrenia in multiplex families compared to ancestry-matched sporadic cases. Using mixed-effects logistic regression with family structure modeled as a random effect, we show that SCZ PRS in familial cases does not differ significantly from sporadic cases either with, or without family history (FH) of psychotic disorders (All sporadic cases p = 0.90, FH+ cases p = 0.88, FH- cases p = 0.82). These results indicate that increased burden of common schizophrenia risk variation as indexed by current SCZ PRS, is unlikely to account for the higher recurrence risk of schizophrenia in multiplex families. In the absence of elevated PRS, segregation of rare risk variation or environmental influences unique to the families may explain the increased familial recurrence risk. These findings also further validate a genetically influenced psychosis spectrum, as shown by a continuous increase of common SCZ risk variation burden from unaffected relatives to schizophrenia cases in multiplex families. Finally, these results suggest that common risk variation loading are unlikely to be predictive of schizophrenia recurrence risk in the families of index probands, and additional components of genetic risk must be identified and included in order to improve recurrence risk prediction.

Hospital Trends of Acute Pancreatitis During the Coronavirus Disease 2019 Pandemic.

OBJECTIVE: The coronavirus disease 2019 pandemic led to changes in individuals' behaviors and healthcare delivery. We examined the impact of these changes on the rates and clinical course of acute pancreatitis (AP). METHODS: Hospitalizations for AP from March 1 through August 31 in 2019 (baseline group) and the same period in 2020 (pandemic group) were retrospectively reviewed. Univariate and multivariate analyses were used for demographics and outcomes. RESULTS: Two hundred eighty subjects (315 admissions) were identified in 2019 and 237 subjects (264 admissions) in 2020. Subjects in the pandemic group were more likely to have systemic inflammatory response syndrome (40% vs 25%, P < 0.01), pancreatic necrosis (14% vs 10%, P = 0.03), and persistent organ failure (17% vs 9%, P = 0.01) compared with prepandemic. There was no difference in etiology of AP. A multivariable model indicates that increased comorbidities, prior pancreatitis, pancreatic necrosis, and prescription of opiates at discharge were associated with 30-day readmissions during the pandemic. CONCLUSIONS: Fewer patients were admitted for AP during the pandemic, suggesting that patients with milder symptoms avoided hospital interaction. Practices followed during the pandemic, especially avoidance of hospitalization and improved efficiency of hospital management, may reduce the burden of pancreatitis care in the future.

Alcohol use and alcohol use disorder differ in their genetic relationships with PTSD: A genomic structural equation modelling approach.

PURPOSE: Posttraumatic Stress Disorder (PTSD) is associated with increased alcohol use and alcohol use disorder (AUD), which are all moderately heritable. Studies suggest the genetic association between PTSD and alcohol use differs from that of PTSD and AUD, but further analysis is needed. BASIC PROCEDURES: We used genomic Structural Equation Modeling (genomicSEM) to analyze summary statistics from large-scale genome-wide association studies (GWAS) of European Ancestry participants to investigate the genetic relationships between PTSD (both diagnosis and re-experiencing symptom severity) and a range of alcohol use and AUD phenotypes. MAIN FINDINGS: When we differentiated genetic factors for alcohol use and AUD we observed improved model fit relative to models with all alcohol-related indicators loading onto a single factor. The genetic correlations (rG) of PTSD were quite discrepant for the alcohol use and AUD factors. This was true when modeled as a three-correlated-factor model (PTSD-AUD rG:.36, p < .001; PTSD-alcohol use rG: -0.17, p < .001) and as a Bifactor model, in which the common and unique portions of alcohol phenotypes were pulled out into an AUD-specific factor (rG with PTSD:.40, p < .001), AU-specific factor (rG with PTSD: -0.57, p < .001), and a common alcohol factor (rG with PTSD:.16, NS). PRINCIPAL CONCLUSIONS: These results indicate the genetic architecture of alcohol use and AUD are differentially associated with PTSD. When the portions of variance unique to alcohol use and AUD are extracted, their genetic associations with PTSD vary substantially, suggesting different genetic architectures of alcohol phenotypes in people with PTSD.

Expanding Bromodomain Targeting into Neglected Parasitic Diseases.

This Perspective discusses the published data and recent developments in the research area of bromodomains in parasitic protozoa. Further work is needed to evaluate the tractability of this target class in the context of infectious diseases and launch drug discovery campaigns to identify and develop antiparasite drugs that can offer differentiated mechanisms of action.

Are Different Individuals Sensitive to Different Environments? Individual Differences in Sensitivity to the Effects of the Parent, Peer and School Environment on Externalizing Behavior and its Genetic and Environmental Etiology.

Externalizing behavior is substantially affected by genetic effects, which are moderated by environmental exposures. However, little is known about whether these moderation effects differ depending on individual characteristics, and whether moderation of environmental effects generalizes across different environmental domains. With a large sample (N = 1,441 individuals) of early adolescent twins (ages 11 and 13), using a longitudinal multi-informant design, we tested interaction effects between negative emotionality and both positive and negative aspects of three key social domains: parents, peers, and schools, on the phenotypic variance as well as the etiology of externalizing. Negative emotionality moderated some of the environmental effects on the phenotypic, genetic, and environmental variance in externalizing, with adolescents at both ends of the negative emotionality distribution showing different patterns of sensitivity to the tested environmental influences. This is the first use of gene-environment interaction twin models to test individual differences in environmental sensitivity, offering a new approach to study such effects.

Combining Structural-Equation Modeling with Genomic-Relatedness-Matrix Restricted Maximum Likelihood in OpenMx.

There is a long history of fitting biometrical structural-equation models (SEMs) in the pregenomic behavioral-genetics literature of twin, family, and adoption studies. Recently, a method has emerged for estimating biometrical variance-covariance components based not upon the expected degree of genetic resemblance among relatives, but upon the observed degree of genetic resemblance among unrelated individuals for whom genome-wide genotypes are available-genomic-relatedness-matrix restricted maximum-likelihood (GREML). However, most existing GREML software is concerned with quickly and efficiently estimating heritability coefficients, genetic correlations, and so on, rather than with allowing the user to fit SEMs to multitrait samples of genotyped participants. We therefore introduce a feature in the OpenMx package, "mxGREML", designed to fit the biometrical SEMs from the pregenomic era in present-day genomic study designs. We explain the additional functionality this new feature has brought to OpenMx, and how the new functionality works. We provide an illustrative example of its use. We discuss the feature's current limitations, and our plans for its further development.

Does parental education influence child educational outcomes? A developmental analysis in a full-population sample and adoptee design.

Children's educational outcomes are strongly correlated with their parents' educational attainment. This finding is often attributed to the family environment-assuming, for instance, that parents' behavior and resources affect their children's educational outcomes. However, such inferences of a causal role of the family environment depend on the largely untested assumption that such relationships do not simply reflect genes shared between parent and child. We examine this assumption with an adoptee design in full-population cohorts from Danish administrative data. We test whether parental education predicts children's educational outcomes in both biological and adopted children, looking at four components of the child's educational development: (I) the child's conscientiousness during compulsory schooling, (II) academic performance in those same years, (III) enrollment in academically challenging high schools, and (IV) graduation success. Parental education was a substantial predictor of each of these child outcomes in the full population. However, little intergenerational correlation in education was observed in the absence of genetic similarity between parent and child-that is, among adoptees. Further analysis showed that what links adoptive parents' education did have with later-occurring components such as educational attainment (IV) and enrollment (III) appeared to be largely attributable to effects identifiable earlier in development, namely early academic performance (II). The primary nongenetic mechanisms by which education is transmitted across generations may thus have their effects on children early in their educational development, even as the consequences of those early effects persist throughout the child's educational development. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Using Multimodel Inference/Model Averaging to Model Causes of Covariation Between Variables in Twins.

OBJECTIVE: To explore and apply multimodel inference to test the relative contributions of latent genetic, environmental and direct causal factors to the covariation between two variables with data from the classical twin design by estimating model-averaged parameters. METHODS: Behavior genetics is concerned with understanding the causes of variation in phenotypes and the causes of covariation between two or more phenotypes. Two variables may correlate as a result of genetic, shared environmental or unique environmental factors contributing to variation in both variables. Two variables may also correlate because one or both directly cause variation in the other. Furthermore, covariation may result from any combination of these sources, leading to 25 different identified structural equation models. OpenMx was used to fit all these models to account for covariation between two variables collected in twins. Multimodel inference and model averaging were used to summarize the key sources of covariation, and estimate the magnitude of these causes of covariance. Extensions of these models to test heterogeneity by sex are discussed. RESULTS: We illustrate the application of multimodel inference by fitting a comprehensive set of bivariate models to twin data from the Virginia Twin Study of Psychiatric and Substance Use Disorders. Analyses of body mass index and tobacco consumption data show sufficient power to reject distinct models, and to estimate the contribution of each of the five potential sources of covariation, irrespective of selecting the best fitting model. Discrimination between models on sample size, type of variable (continuous versus binary or ordinal measures) and the effect size of sources of variance and covariance. CONCLUSIONS: We introduce multimodel inference and model averaging approaches to the behavior genetics community, in the context of testing models for the causes of covariation between traits in term of genetic, environmental and causal explanations.

Mendelian randomization study of maternal influences on birthweight and future cardiometabolic risk in the HUNT cohort.

There is a robust observational relationship between lower birthweight and higher risk of cardiometabolic disease in later life. The Developmental Origins of Health and Disease (DOHaD) hypothesis posits that adverse environmental factors in utero increase future risk of cardiometabolic disease. Here, we explore if a genetic risk score (GRS) of maternal SNPs associated with offspring birthweight is also associated with offspring cardiometabolic risk factors, after controlling for offspring GRS, in up to 26,057 mother-offspring pairs (and 19,792 father-offspring pairs) from the Nord-Trøndelag Health (HUNT) Study. We find little evidence for a maternal (or paternal) genetic effect of birthweight associated variants on offspring cardiometabolic risk factors after adjusting for offspring GRS. In contrast, offspring GRS is strongly related to many cardiometabolic risk factors, even after conditioning on maternal GRS. Our results suggest that the maternal intrauterine environment, as proxied by maternal SNPs that influence offspring birthweight, is unlikely to be a major determinant of adverse cardiometabolic outcomes in population based samples of individuals.

Adolescent Externalizing Psychopathology and Its Prospective Relationship to Marijuana Use Development from Age 14 to 30: Replication Across Independent Longitudinal Twin Samples.

Externalizing psychopathology in early adolescence is a highly heritable risk factor for drug use, yet how it relates to marijuana use development is not well-characterized. We evaluate this issue in independent twin samples from Colorado (N = 2608) and Minnesota (N = 3630), assessed from adolescence to early adulthood. We used a biometric latent growth model of marijuana use frequency with data from up to five waves of assessment from ages 14 to 30, to examine change in marijuana use and its relationship with a factor model of adolescent externalizing psychopathology. The factor structure of adolescent externalizing psychopathology was similar across samples, as was the association between that common factor and early marijuana use (Minnesota r = 0.67 [0.60, 0.75]; Colorado r = 0.69 [0.59, 0.78]), and increase in use (Minnesota r = 0.18 [0.10, 0.26]; Colorado r = 0.20 [0.07, 0.34]). Early use was moderately heritable in both samples (Minnesota h2 = 0.57 [0.37, 0.79]; Colorado h2 = 0.42 [0.14, 0.73]). Increase in use was highly heritable in Minnesota (h2 = 0.82 [0.72, 0.88]), less so in Colorado (h2 = 0.22 [0.01, 0.66]), and shared environmental effects were larger in Colorado (c2 = 0.55 [0.14, 0.83]) than Minnesota (c2 = 0 [0, 0.06]). We found moderate genetic correlations between externalizing psychopathology and early use in both samples. Finally, additional analyses in the Minnesota sample indicated that marijuana use decreased during the late 20s. This decline is strongly heritable (h2 = 0.73 [0.49, 0.91]) and moderately negatively correlated with adolescent externalizing psychopathology (r = - 0.41 [- 0.54, - 0.28]). Adolescent externalizing psychopathology is genetically correlated with change in late adolescent marijuana use (late teens, early 20s), as well as maintenance of use in early adulthood (late 20 s) even after controlling for the effects of early use.