Genome-wide association studies of lifetime and frequency cannabis use in 131,895 individuals.

Cannabis is one of the most widely used drugs globally. Decriminalization of cannabis is further increasing cannabis consumption. We performed genome-wide association studies ( GWASs ) of lifetime ( N= 131,895) and frequency ( N= 73,374) of cannabis use. Lifetime cannabis use GWAS identified two loci, one near CADM2 (rs11922956, p =2.40E-11) and another near GRM3 (rs12673181, p =6.90E-09). Frequency of use GWAS identified one locus near CADM2 (rs4856591, p =8.10E-09; r 2 =0.76 with rs11922956). Both traits were heritable and genetically correlated with previous GWASs of lifetime use and cannabis use disorder ( CUD ), as well as other substance use and cognitive traits. Polygenic scores ( PGSs ) for lifetime and frequency of cannabis use associated cannabis use phenotypes in AllofUs participants. Phenome-wide association study of lifetime cannabis use PGS in a hospital cohort replicated associations with substance use and mood disorders, and uncovered associations with celiac and infectious diseases. This work demonstrates the value of GWASs of CUD transition risk factors.

A phenome-wide association and Mendelian randomisation study of alcohol use variants in a diverse cohort comprising over 3 million individuals.

BACKGROUND: Alcohol consumption is associated with numerous negative social and health outcomes. These associations may be direct consequences of drinking, or they may reflect common genetic factors that influence both alcohol consumption and other outcomes. METHODS: We performed exploratory phenome-wide association studies (PheWAS) of three of the best studied protective single nucleotide polymorphisms (SNPs) in genes encoding ethanol metabolising enzymes (ADH1B: rs1229984-T, rs2066702-A; ADH1C: rs698-T) using up to 1109 health outcomes across 28 phenotypic categories (e.g., substance-use, mental health, sleep, immune, cardiovascular, metabolic) from a diverse 23andMe cohort, including European (N ≤ 2,619,939), Latin American (N ≤ 446,646) and African American (N ≤ 146,776) populations to uncover new and perhaps unexpected associations. These SNPs have been consistently implicated by both candidate gene studies and genome-wide association studies of alcohol-related behaviours but have not been investigated in detail for other relevant phenotypes in a hypothesis-free approach in such a large cohort of multiple ancestries. To provide insight into potential causal effects of alcohol consumption on the outcomes significant in the PheWAS, we performed univariable two-sample and one-sample Mendelian randomisation (MR) analyses. FINDINGS: The minor allele rs1229984-T, which is protective against alcohol behaviours, showed the highest number of PheWAS associations across the three cohorts (N = 232, European; N = 29, Latin American; N = 7, African American). rs1229984-T influenced multiple domains of health. We replicated associations with alcohol-related behaviours, mental and sleep conditions, and cardio-metabolic health. We also found associations with understudied traits related to neurological (migraines, epilepsy), immune (allergies), musculoskeletal (fibromyalgia), and reproductive health (preeclampsia). MR analyses identified evidence of causal effects of alcohol consumption on liability for 35 of these outcomes in the European cohort. INTERPRETATION: Our work demonstrates that polymorphisms in genes encoding alcohol metabolising enzymes affect multiple domains of health beyond alcohol-related behaviours. Understanding the underlying mechanisms of these effects could have implications for treatments and preventative medicine. FUNDING: MVJ, NCK, SBB, SSR and AAP were supported by T32IR5226 and 28IR-0070. SSR was also supported by NIDA DP1DA054394. NCK and RBC were also supported by R25MH081482. ASH was supported by funds from NIAAA K01AA030083. JLMO was supported by VA 1IK2CX002095. JLMO and JJMM were also supported by NIDA R21DA050160. JJMM was also supported by the Kavli Postdoctoral Award for Academic Diversity. EGA was supported by K01MH121659 from the NIMH/NIH, the Caroline Wiess Law Fund for Research in Molecular Medicine and the ARCO Foundation Young Teacher-Investigator Fund at Baylor College of Medicine. MSA was supported by the Instituto de Salud Carlos III and co-funded by the European Union Found: Fondo Social Europeo Plus (FSE+) (P19/01224, PI22/00464 and CP22/00128).

Unraveling the molecular relevance of brain phenotypes: A comparative analysis of null models and test statistics.

Correlating transcriptional profiles with imaging-derived phenotypes has the potential to reveal possible molecular architectures associated with cognitive functions, brain development and disorders. Competitive null models built by resampling genes and self-contained null models built by spinning brain regions, along with varying test statistics, have been used to determine the significance of transcriptional associations. However, there has been no systematic evaluation of their performance in imaging transcriptomics analyses. Here, we evaluated the performance of eight different test statistics (mean, mean absolute value, mean squared value, max mean, median, Kolmogorov-Smirnov (KS), Weighted KS and the number of significant correlations) in both competitive null models and self-contained null models. Simulated brain maps (n = 1,000) and gene sets (n = 500) were used to calculate the probability of significance (Psig) for each statistical test. Our results suggested that competitive null models may result in false positive results driven by co-expression within gene sets. Furthermore, we demonstrated that the self-contained null models may fail to account for distribution characteristics (e.g., bimodality) of correlations between all available genes and brain phenotypes, leading to false positives. These two confounding factors interacted differently with test statistics, resulting in varying outcomes. Specifically, the sign-sensitive test statistics (i.e., mean, median, KS, Weighted KS) were influenced by co-expression bias in the competitive null models, while median and sign-insensitive test statistics were sensitive to the bimodality bias in the self-contained null models. Additionally, KS-based statistics produced conservative results in the self-contained null models, which increased the risk of false negatives. Comprehensive supplementary analyses with various configurations, including realistic scenarios, supported the results. These findings suggest utilizing sign-insensitive test statistics such as mean absolute value, max mean in the competitive null models and the mean as the test statistic for the self-contained null models. Additionally, adopting the confounder-matched (e.g., coexpression-matched) null models as an alternative to standard null models can be a viable strategy. Overall, the present study offers insights into the selection of statistical tests for imaging transcriptomics studies, highlighting areas for further investigation and refinement in the evaluation of novel and commonly used tests.

Brain structural covariance network features are robust markers of early heavy alcohol use.

BACKGROUND AND AIMS: Recently, we demonstrated that a distinct pattern of structural covariance networks (SCN) from magnetic resonance imaging (MRI)-derived measurements of brain cortical thickness characterized young adults with alcohol use disorder (AUD) and predicted current and future problematic drinking in adolescents relative to controls. Here, we establish the robustness and value of SCN for identifying heavy alcohol users in three additional independent studies. DESIGN AND SETTING: Cross-sectional and longitudinal studies using data from the Pediatric Imaging, Neurocognition and Genetics (PING) study (n = 400, age range = 14-22 years), the National Consortium on Alcohol and Neurodevelopment in Adolescence (NCANDA) (n = 272, age range = 17-22 years) and the Human Connectome Project (HCP) (n = 375, age range = 22-37 years). CASES: Cases were defined based on heavy alcohol use patterns or former alcohol use disorder (AUD) diagnoses: 50, 68 and 61 cases were identified. Controls had none or low alcohol use or absence of AUD: 350, 204 and 314 controls were selected. MEASUREMENTS: Graph theory metrics of segregation and integration were used to summarize SCN. FINDINGS: Mirroring our prior findings, and across the three data sets, cases had a lower clustering coefficient [area under the curve (AUC) = -0.029, P = 0.002], lower modularity (AUC = -0.14, P = 0.004), lower average shortest path length (AUC = -0.078, P = 0.017) and higher global efficiency (AUC = 0.007, P = 0.010). Local efficiency differences were marginal (AUC = -0.017, P = 0.052). That is, cases exhibited lower network segregation and higher integration, suggesting that adjacent nodes (i.e. brain regions) were less similar in thickness whereas spatially distant nodes were more similar. CONCLUSION: Structural covariance network (SCN) differences in the brain appear to constitute an early marker of heavy alcohol use in three new data sets and, more generally, demonstrate the utility of SCN-derived metrics to detect brain-related psychopathology.

Cortical profiles of numerous psychiatric disorders and normal development share a common pattern.

The neurobiological bases of the association between development and psychopathology remain poorly understood. Here, we identify a shared spatial pattern of cortical thickness (CT) in normative development and several psychiatric and neurological disorders. Principal component analysis (PCA) was applied to CT of 68 regions in the Desikan-Killiany atlas derived from three large-scale datasets comprising a total of 41,075 neurotypical participants. PCA produced a spatially broad first principal component (PC1) that was reproducible across datasets. Then PC1 derived from healthy adult participants was compared to the pattern of CT differences associated with psychiatric and neurological disorders comprising a total of 14,886 cases and 20,962 controls from seven ENIGMA disease-related working groups, normative maturation and aging comprising a total of 17,697 scans from the ABCD Study® and the IMAGEN developmental study, and 17,075 participants from the ENIGMA Lifespan working group, as well as gene expression maps from the Allen Human Brain Atlas. Results revealed substantial spatial correspondences between PC1 and widespread lower CT observed in numerous psychiatric disorders. Moreover, the PC1 pattern was also correlated with the spatial pattern of normative maturation and aging. The transcriptional analysis identified a set of genes including KCNA2, KCNS1 and KCNS2 with expression patterns closely related to the spatial pattern of PC1. The gene category enrichment analysis indicated that the transcriptional correlations of PC1 were enriched to multiple gene ontology categories and were specifically over-represented starting at late childhood, coinciding with the onset of significant cortical maturation and emergence of psychopathology during the prepubertal-to-pubertal transition. Collectively, the present study reports a reproducible latent pattern of CT that captures interregional profiles of cortical changes in both normative brain maturation and a spectrum of psychiatric disorders. The pubertal timing of the expression of PC1-related genes implicates disrupted neurodevelopment in the pathogenesis of the spectrum of psychiatric diseases emerging during adolescence.

Recalibrating single-study effect sizes using hierarchical Bayesian models.

Introduction: There are growing concerns about commonly inflated effect sizes in small neuroimaging studies, yet no study has addressed recalibrating effect size estimates for small samples. To tackle this issue, we propose a hierarchical Bayesian model to adjust the magnitude of single-study effect sizes while incorporating a tailored estimation of sampling variance. Methods: We estimated the effect sizes of case-control differences on brain structural features between individuals who were dependent on alcohol, nicotine, cocaine, methamphetamine, or cannabis and non-dependent participants for 21 individual studies (Total cases: 903; Total controls: 996). Then, the study-specific effect sizes were modeled using a hierarchical Bayesian approach in which the parameters of the study-specific effect size distributions were sampled from a higher-order overarching distribution. The posterior distribution of the overarching and study-specific parameters was approximated using the Gibbs sampling method. Results: The results showed shrinkage of the posterior distribution of the study-specific estimates toward the overarching estimates given the original effect sizes observed in individual studies. Differences between the original effect sizes (i.e., Cohen's d) and the point estimate of the posterior distribution ranged from 0 to 0.97. The magnitude of adjustment was negatively correlated with the sample size (r = -0.27, p < 0.001) and positively correlated with empirically estimated sampling variance (r = 0.40, p < 0.001), suggesting studies with smaller samples and larger sampling variance tended to have greater adjustments. Discussion: Our findings demonstrate the utility of the hierarchical Bayesian model in recalibrating single-study effect sizes using information from similar studies. This suggests that Bayesian utilization of existing knowledge can be an effective alternative approach to improve the effect size estimation in individual studies, particularly for those with smaller samples.

Association Between Brain Structure and Alcohol Use Behaviors in Adults: A Mendelian Randomization and Multiomics Study.

Importance: Past studies have identified associations between brain macrostructure and alcohol use behaviors. However, identifying directional associations between these phenotypes is difficult due to the limitations of observational studies. Objective: To use mendelian randomization (MR) to identify directional associations between brain structure and alcohol use and elucidate the transcriptomic and cellular underpinnings of identified associations. Design, Setting, and Participants: The main source data comprised summary statistics from population-based and case-control genome-wide association studies (GWAS) of neuroimaging, behavioral, and clinical phenotypes (N = 763 874). Using these data, bidirectional and multivariable MR was performed analyzing associations between brain macrostructure and alcohol use. Downstream transcriptome-wide association studies (TWAS) and cell-type enrichment analyses investigated the biology underlying identified associations. The study approach was data driven and did not test any a priori hypotheses. Data were analyzed August 2021 to May 2022. Main Outcomes and Measures: Brain structure phenotypes (global cortical thickness [GCT] and global cortical surface area [GCSA] in 33 709 individuals and left-right subcortical volumes in 19 629 individuals) and alcohol use behaviors (alcoholic drinks per week [DPW] in 537 349 individuals, binge drinking frequency in 143 685 individuals, and alcohol use disorder in 8845 individuals vs 20 657 control individuals [total of 29 502]). Results: The main bidirectional MR analyses were performed in samples totaling 763 874 individuals, among whom more than 94% were of European ancestry, 52% to 54% were female, and the mean cohort ages were 40 to 63 years. Negative associations were identified between genetically predicted GCT and binge drinking (ß, -2.52; 95% CI, -4.13 to -0.91) and DPW (ß, -0.88; 95% CI, -1.37 to -0.40) at a false discovery rate (FDR) of 0.05. These associations remained significant in multivariable MR models that accounted for neuropsychiatric phenotypes, substance use, trauma, and neurodegeneration. TWAS of GCT and alcohol use behaviors identified 5 genes at the 17q21.31 locus oppositely associated with GCT and binge drinking or DPW (FDR = 0.05). Cell-type enrichment analyses implicated glutamatergic cortical neurons in alcohol use behaviors. Conclusions and Relevance: The findings in this study show that the associations between GCT and alcohol use may reflect a predispositional influence of GCT and that 17q21.31 genes and glutamatergic cortical neurons may play a role in this association. While replication studies are needed, these findings should enhance the understanding of associations between brain structure and alcohol use.

Bayesian causal network modeling suggests adolescent cannabis use accelerates prefrontal cortical thinning.

While there is substantial evidence that cannabis use is associated with differences in human brain development, most of this evidence is correlational in nature. Bayesian causal network (BCN) modeling attempts to identify probable causal relationships in correlational data using conditional probabilities to estimate directional associations between a set of interrelated variables. In this study, we employed BCN modeling in 637 adolescents from the IMAGEN study who were cannabis naïve at age 14 to provide evidence that the accelerated prefrontal cortical thinning found previously in adolescent cannabis users by Albaugh et al. [1] is a result of cannabis use causally affecting neurodevelopment. BCNs incorporated data on cannabis use, prefrontal cortical thickness, and other factors related to both brain development and cannabis use, including demographics, psychopathology, childhood adversity, and other substance use. All BCN algorithms strongly suggested a directional relationship from adolescent cannabis use to accelerated cortical thinning. While BCN modeling alone does not prove a causal relationship, these results are consistent with a body of animal and human research suggesting that adolescent cannabis use adversely affects brain development.

White matter microstructure differences in individuals with dependence on cocaine, methamphetamine, and nicotine: Findings from the ENIGMA-Addiction working group.

BACKGROUND: Nicotine and illicit stimulants are very addictive substances. Although associations between grey matter and dependence on stimulants have been frequently reported, white matter correlates have received less attention. METHODS: Eleven international sites ascribed to the ENIGMA-Addiction consortium contributed data from individuals with dependence on cocaine (n = 147), methamphetamine (n = 132) and nicotine (n = 189), as well as non-dependent controls (n = 333). We compared the fractional anisotropy (FA), axial diffusivity (AD), radial diffusivity (RD) and mean diffusivity (MD) of 20 bilateral tracts. Also, we compared the performance of various machine learning algorithms in deriving brain-based classifications on stimulant dependence. RESULTS: The cocaine and methamphetamine groups had lower regional FA and higher RD in several association, commissural, and projection white matter tracts. The methamphetamine dependent group additionally showed lower regional AD. The nicotine group had lower FA and higher RD limited to the anterior limb of the internal capsule. The best performing machine learning algorithm was the support vector machine (SVM). The SVM successfully classified individuals with dependence on cocaine (AUC = 0.70, p < 0.001) and methamphetamine (AUC = 0.71, p < 0.001) relative to non-dependent controls. Classifications related to nicotine dependence proved modest (AUC = 0.62, p = 0.014). CONCLUSIONS: Stimulant dependence was related to FA disturbances within tracts consistent with a role in addiction. The multivariate pattern of white matter differences proved sufficient to identify individuals with stimulant dependence, particularly for cocaine and methamphetamine.

Characterizing reward system neural trajectories from adolescence to young adulthood.

Mixed findings exist in studies comparing brain responses to reward in adolescents and adults. Here we examined the trajectories of brain response, functional connectivity and task-modulated network properties during reward processing with a large-sample longitudinal design. Participants from the IMAGEN study performed a Monetary Incentive Delay task during fMRI at timepoint 1 (T1; n = 1304, mean age=14.44 years old) and timepoint 2 (T2; n = 1241, mean age=19.09 years). The Alcohol Use Disorders Identification Test (AUDIT) was administrated at both T1 and T2 to assess a participant's alcohol use during the past year. Voxel-wise linear mixed effect models were used to compare whole brain response as well as functional connectivity of the ventral striatum (VS) during reward anticipation (large reward vs no-reward cue) between T1 and T2. In addition, task-modulated networks were constructed using generalized psychophysiological interaction analysis and summarized with graph theory metrics. To explore alcohol use in relation to development, participants with no/low alcohol use at T1 but increased alcohol use to hazardous use level at T2 (i.e., participants with AUDIT≤2 at T1 and ≥8 at T2) were compared against those with consistently low scores (i.e., participants with AUDIT≤2 at T1 and ≤7 at T2). Across the whole sample, lower brain response during reward anticipation was observed at T2 compared with T1 in bilateral caudate nucleus, VS, thalamus, midbrain, dorsal anterior cingulate as well as left precentral and postcentral gyrus. Conversely, greater response was observed bilaterally in the inferior and middle frontal gyrus and right precentral and postcentral gyrus at T2 (vs. T1). Increased functional connectivity with VS was found in frontal, temporal, parietal and occipital regions at T2. Graph theory metrics of the task-modulated network showed higher inter-regional connectivity and topological efficiency at T2. Interactive effects between time (T1 vs. T2) and alcohol use group (low vs. high) on the functional connectivity were observed between left middle temporal gyrus and right VS and the characteristic shortest path length of the task-modulated networks. Collectively, these results demonstrate the utility of the MID task as a probe of typical brain response and network properties during development and of differences in these features related to adolescent drinking, a reward-related behaviour associated with heightened risk for future negative health outcomes.

The role of glucocorticoid receptor gene in the association between attention deficit-hyperactivity disorder and smaller brain structures.

ADHD is associated with smaller subcortical brain volumes and cortical surface area, with greater effects observed in children than adults. It is also associated with dysregulation of the HPA axis. Considering the effects of the glucocorticoid receptor (NR3C1) in neurophysiology, we hypothesize that the blurred relationships between brain structures and ADHD in adults could be partly explained by NR3C1 gene variation. Structural T1-weighted images were acquired on a 3 T scanner (N = 166). Large-scale genotyping was performed, and it was followed by quality control and pruning procedures, which resulted in 48 independent NR3C1 gene variants analyzed. After a stringent Bonferroni correction, two SNPs (rs2398631 and rs72801070) moderated the association between ADHD and accumbens and amygdala volumes in adults. The significant SNPs that interacted with ADHD appear to have a role in gene expression regulation, and they are in linkage disequilibrium with NR3C1 variants that present well-characterized physiological functions. The literature-reported associations of ADHD with accumbens and amygdala were only observed for specific NR3C1 genotypes. Our findings reinforce the influence of the NR3C1 gene on subcortical volumes and ADHD. They suggest a genetic modulation of the effects of a pivotal HPA axis component in the neuroanatomical features of ADHD.

Analysis of structural brain asymmetries in attention-deficit/hyperactivity disorder in 39 datasets.

OBJECTIVE: Some studies have suggested alterations of structural brain asymmetry in attention-deficit/hyperactivity disorder (ADHD), but findings have been contradictory and based on small samples. Here, we performed the largest ever analysis of brain left-right asymmetry in ADHD, using 39 datasets of the ENIGMA consortium. METHODS: We analyzed asymmetry of subcortical and cerebral cortical structures in up to 1,933 people with ADHD and 1,829 unaffected controls. Asymmetry Indexes (AIs) were calculated per participant for each bilaterally paired measure, and linear mixed effects modeling was applied separately in children, adolescents, adults, and the total sample, to test exhaustively for potential associations of ADHD with structural brain asymmetries. RESULTS: There was no evidence for altered caudate nucleus asymmetry in ADHD, in contrast to prior literature. In children, there was less rightward asymmetry of the total hemispheric surface area compared to controls (t = 2.1, p = .04). Lower rightward asymmetry of medial orbitofrontal cortex surface area in ADHD (t = 2.7, p = .01) was similar to a recent finding for autism spectrum disorder. There were also some differences in cortical thickness asymmetry across age groups. In adults with ADHD, globus pallidus asymmetry was altered compared to those without ADHD. However, all effects were small (Cohen's d from -0.18 to 0.18) and would not survive study-wide correction for multiple testing. CONCLUSION: Prior studies of altered structural brain asymmetry in ADHD were likely underpowered to detect the small effects reported here. Altered structural asymmetry is unlikely to provide a useful biomarker for ADHD, but may provide neurobiological insights into the trait.

Mapping cortical and subcortical asymmetries in substance dependence: Findings from the ENIGMA Addiction Working Group.

Brain asymmetry reflects left-right hemispheric differentiation, which is a quantitative brain phenotype that develops with age and can vary with psychiatric diagnoses. Previous studies have shown that substance dependence is associated with altered brain structure and function. However, it is unknown whether structural brain asymmetries are different in individuals with substance dependence compared with nondependent participants. Here, a mega-analysis was performed using a collection of 22 structural brain MRI datasets from the ENIGMA Addiction Working Group. Structural asymmetries of cortical and subcortical regions were compared between individuals who were dependent on alcohol, nicotine, cocaine, methamphetamine, or cannabis (n = 1,796) and nondependent participants (n = 996). Substance-general and substance-specific effects on structural asymmetry were examined using separate models. We found that substance dependence was significantly associated with differences in volume asymmetry of the nucleus accumbens (NAcc; less rightward; Cohen's d = 0.15). This effect was driven by differences from controls in individuals with alcohol dependence (less rightward; Cohen's d = 0.10) and nicotine dependence (less rightward; Cohen's d = 0.11). These findings suggest that disrupted structural asymmetry in the NAcc may be a characteristic of substance dependence.

The association between SYT1-rs2251214 and cocaine use disorder further supports its role in psychiatry.

Synaptotagmin-1 is an essential regulator of synaptic vesicle exocytosis, and its encoding gene (SYT1) is a genome and transcriptome-wide association hit in cognitive performance, personality and cocaine use disorder (CUD) studies. Additionally, in candidate gene studies the specific variant rs2251214 has been associated with attention-deficit/hyperactivity disorder (ADHD), antisocial personality disorder and other externalizing phenotypes in adults with ADHD, as well as with response to methylphenidate (MPH) treatment. In this context, we sought to evaluate, in an independent sample, the association of this variant with CUD, a phenotype that shares common biological underpinnings with the previously associated traits. We tested the association between SYT1-rs2251214 and CUD susceptibility and severity (addiction severity index) in a sample composed by 315 patients addicted to smoked cocaine and 769 non-addicted volunteers. SYT1-rs2251214 was significantly associated with susceptibility to CUD, where the G allele presented increased risk for the disorder in the genetic models tested (P = 0.0021, OR = 1.44, allelic; P = 0.0012, OR = 1.48, additive; P = 0.0127, OR = 1.41, dominant). This is the same allele that was associated with increased risk for ADHD and other externalizing behaviors, as well as poor response to MPH treatment in previous studies. These findings suggest that the neurotransmitter exocytosis pathway might play a critical role in the liability for psychiatric disorders, especially externalizing behaviors and CUD.

Effects of DRD2 splicing-regulatory polymorphism and DRD4 48 bp VNTR on crack cocaine addiction.

There is evidence that dopamine receptors D2 (DRD2) and D4 (DRD4) polymorphisms may influence substance use disorders (SUD) susceptibility both individually and through their influence in the formation of DRD2-DRD4 heteromers. The dopaminergic role on the vulnerability to addiction appears to be influenced by sex. A cross-sectional study with 307 crack cocaine addicts and 770 controls was conducted. The influence of DRD2 rs2283265 and DRD4 48 bp VNTR in exon 3 variants, as well as their interaction on crack cocaine addiction susceptibility and severity were evaluated in women and men separately. An association between the DRD2 T allele and crack cocaine addiction was found in women. In this same group, interaction analysis demonstrated that the presence of DRD2-T allele and concomitant absence of DRD4-7R allele were associated with risk for crack cocaine addiction. No influence of DRD2 and DRD4 variants was observed in men regarding addiction severity. This study reinforces the role of dopaminergic genes in externalizing behaviors, especially the influence of DRD2-DRD4 interaction on SUD. This is the fourth sample that independently associated the DRD2-DRD4 interaction with SUD itself or related disorders. In addition, our findings point out to a potential difference of dopaminergic neurotransmission across sex influencing addiction susceptibility.

Evidence of sexual dimorphism of HTR1B gene on major adult ADHD comorbidities.

Attention-deficit/hyperactivity disorder (ADHD) is a very common psychiatric disorder across the life cycle and frequently presents comorbidities. Since ADHD is highly heritable, several studies have focused in the underlying genetic factors involved in its etiology. One of the major challenges in this search is the phenotypic heterogeneity, which could be partly attributable to the sexual dimorphism frequently seen in psychiatric disorders. Taking into account the well-known sexual dimorphic effect observed in serotonergic system characteristics, we differentially tested the influence of HTR1B SNPs (rs11568817, rs130058, rs6296 and rs13212041) on ADHD susceptibility and on its major comorbidities according to sex. The sample comprised 564 adults with ADHD diagnosed according to DSM-IV criteria and 635 controls. There was no association of any HTR1B SNPs tested in relation to ADHD susceptibility. As for the comorbidities evaluated, after correction for multiple tests, significant associations were observed for both rs11568817 and rs130058 with substance use disorders (Pcorr = 0.009 and Pcorr = 0.018, respectively) and for rs11568817 with nicotine dependence (Pcorr = 0.025) in men with ADHD. In women with ADHD, the same rs11568817 was associated with generalized anxiety disorder (Pcorr = 0.031). The observed effects of rs11568817 G allele presence conferring risk to either substance use disorders or generalized anxiety disorder according to sex, suggest an overall scenario where a higher transcriptional activity of HTR1B, resulting from the presence of this allele, is related to externalizing behaviors in men and internalizing behaviors in women. These results are consistent with and expand previous evidence of sexual dimorphism of the serotoninergic system.

Further replication of the synergistic interaction between LPHN3 and the NTAD gene cluster on ADHD and its clinical course throughout adulthood.

Attention-Deficit/Hyperactivity Disorder (ADHD) is a common and highly heritable neuropsychiatric disorder. Despite the high heritability, the unraveling of specific genetic factors related to ADHD is hampered by its considerable genetic complexity. Recent evidence suggests that gene-gene interactions can explain part of this complexity. We examined the impact of strongly supported interaction effects between the LPHN3 gene and the NTAD gene cluster (NCAM1-TTC12-ANKK1-DRD2) in a 7-year follow-up of a clinical sample of adults with ADHD, addressing associations with susceptibility, symptomatology and stability of diagnosis. The sample comprises 548 adults with ADHD and 643 controls. Entropy-based analysis indicated a potential interaction between the LPHN3-rs6551665 and TTC12-rs2303380 SNPs influencing ADHD symptom counts. Further analyses revealed significant interaction effects on ADHD total symptoms (p=0.002), and with hyperactivity/impulsivity symptom counts (p=0.005). In the group composed by predominantly hyperactive/impulsive and combined presentation, the presence of LPHN3-rs6551665 G allele was related to increased ADHD risk only in individuals carrying the TTC12-rs2303380 AA genotype (p=0.026). Also, the same allelic constellation is involved in maintenance of ADHD in a predominantly hyperactive/impulsive or combined presentation after a 7-year follow-up (p=0.008). These observations reinforce and replicate previous evidence suggesting that an interaction effect between the LPHN3 gene and the NTAD cluster may have a role in the genetic substrate associated to ADHD also in adults. Moreover, it is possible that the interactions between LPHN3 and NTAD are specific factors contributing to the development of an ADHD phenotype with increased hyperactivity/impulsivity that is maintained throughout adulthood.

Effects of corticotropin-releasing hormone receptor 1 SNPs on major depressive disorder are influenced by sex and smoking status.

BACKGROUND: The corticotropin-releasing hormone receptor 1 (CRHR1) gene has been repeatedly implicated in Major Depressive Disorder (MDD) in humans and animal models; however, the findings are not absolutely convergent. Since recent evidence from genome-wide association studies suggests that narrowing the phenotypic heterogeneity may be crucial in genetic studies of MDD, the aim of this study was to evaluate the effects of CRHR1 polymorphisms on MDD while addressing the influence of sex and smoking status. METHODS: The association of the CRHR1 SNPs rs12944712, rs110402, and rs878886 with MDD was evaluated in 629 Brazilian adults of European descent recruited from the general population [180 (28.6%) with lifetime MDD]. The sample was subdivided according to sex and smoking status RESULTS: Among nonsmokers, there were nominal associations between MDD and all tested SNPs (rs12944712, P=0.042; rs110402, P=0.031, and rs878886, P=0.040), regardless of sex. In addition, there were significant effects of rs110402 in women (Pcorr=0.034) and rs878886 in men (Pcorr=0.013). Among lifetime smokers, there were no significant associations between CRHR1 SNPs and MDD LIMITATIONS: The lack of a depression rating scale; scarcity of information on the functionality of the CRHR1 SNPs; and relatively small sample sizes in some subgroups. CONCLUSIONS: Our results strengthen the evidence for the role of CRHR1 SNPs in MDD susceptibility and suggest that their effects may be modulated by sex and smoking status. These findings suggest the perspective that reducing phenotypic heterogeneity is warranted in genetic studies of MDD.

Pleiotropic effects of Chr15q25 nicotinic gene cluster and the relationship between smoking, cognition and ADHD.

Polymorphisms in the CHRNA5-CHRNA3-CHRNB4 gene cluster (Chr15q25) have been robustly associated with nicotine dependence, including genome-wide studies, as well as with cognitive and neuropsychological measures. In addition, cognitive processes can be influenced by nicotine use through nicotinic acetylcholine receptors (nAChRs). Here, we evaluated the effect of polymorphisms in CHRNA5-CHRNA3-CHRNB4 gene cluster and their interaction with tobacco smoking status on cognition in patients with Attention Deficit/Hyperactivity Disorder (ADHD). Eight SNPs from the CHRNA5-CHRNA3-CHRNB4 gene cluster were evaluated on a clinical sample of 403 adults with ADHD. Cognitive performance was assessed using the Wechsler Adult Intelligence Scale-Revised (WAIS-R). Analyses of covariance were used to assess the influence of single markers and their interaction with smoking status in the Vocabulary and Block Design subtests of WAIS-R. Correction for multiple comparisons was applied. Lifetime smoking was associated to Vocabulary subtest. The TT genotypes of CHRNA5 SNPs rs588765 and rs514743 showed a trend towards association with, respectively, higher and lower scores on the Vocabulary subtest. There was a significant interaction between intergenic SNP rs8023462 and smoking on Vocabulary scores. Our results are consistent with an influence of variants in the CHRNA5-CHRNA3-CHRNB4 gene cluster on cognitive measures. The overall scenario suggests a pleiotropic role of Chr15q25 nicotinic gene cluster with complex influences in ADHD, tobacco smoking and cognitive performance, characteristics that can be partially interdependent and may share underlying genetic factors.

NOS1 and SNAP25 polymorphisms are associated with Attention-Deficit/Hyperactivity Disorder symptoms in adults but not in children.

Several investigations documented that Attention-Deficit/Hyperactivity Disorder (ADHD) is better conceptualized as a dimensional disorder. At the same time, the disorder seems to have different neurobiological underpinnings and phenotypic presentation in children compared to adults. Neurodevelopmental genes could explain, at least partly these differences. The aim of the present study was to examine possible associations between polymorphisms in SNAP25, MAP1B and NOS1 genes and ADHD symptoms in Brazilian samples of children/adolescents and adults with ADHD. The youth sample consisted of 301 patients whereas the adult sample comprises 485 individuals with ADHD. Diagnoses of ADHD and comorbidities were based on the Diagnostic and Statistical Manual of Mental Disorders-4th edition criteria. The Swanson, Nolan and Pelham Scale-Version IV (SNAP-IV) was applied by psychiatrists blinded to genotype. The total SNAP-IV scores were compared between genotypes. Impulsivity SNAP-IV scores were also compared according to NOS1 genotypes. Adult patients homozygous for the C allele at SNAP25 rs8636 showed significantly higher total SNAP-IV scores (F = 11.215; adjusted P-value = 0.004). Impulsivity SNAP-IV scores were also significantly different according to NOS1 rs478597 polymorphisms in adults with ADHD (F = 6.282; adjusted P-value = 0.026). These associations were not observed in children and adolescents with ADHD. These results suggest that SNAP25 and NOS1 genotypes influence ADHD symptoms only in adults with ADHD. Our study corroborates previous evidences for differences in the genetic contribution to adult ADHD compared with childhood ADHD.