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.

Differential associations of adolescent versus young adult cannabis initiation with longitudinal brain change and behavior.

Leveraging ~10 years of prospective longitudinal data on 704 participants, we examined the effects of adolescent versus young adult cannabis initiation on MRI-assessed cortical thickness development and behavior. Data were obtained from the IMAGEN study conducted across eight European sites. We identified IMAGEN participants who reported being cannabis-naïve at baseline and had data available at baseline, 5-year, and 9-year follow-up visits. Cannabis use was assessed with the European School Survey Project on Alcohol and Drugs. T1-weighted MR images were processed through the CIVET pipeline. Cannabis initiation occurring during adolescence (14-19 years) and young adulthood (19-22 years) was associated with differing patterns of longitudinal cortical thickness change. Associations between adolescent cannabis initiation and cortical thickness change were observed primarily in dorso- and ventrolateral portions of the prefrontal cortex. In contrast, cannabis initiation occurring between 19 and 22 years of age was associated with thickness change in temporal and cortical midline areas. Follow-up analysis revealed that longitudinal brain change related to adolescent initiation persisted into young adulthood and partially mediated the association between adolescent cannabis use and past-month cocaine, ecstasy, and cannabis use at age 22. Extent of cannabis initiation during young adulthood (from 19 to 22 years) had an indirect effect on psychotic symptoms at age 22 through thickness change in temporal areas. Results suggest that developmental timing of cannabis exposure may have a marked effect on neuroanatomical correlates of cannabis use as well as associated behavioral sequelae. Critically, this work provides a foundation for neurodevelopmentally informed models of cannabis exposure in humans.

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.

Glutamate imbalance in key structure of the default mode network in adults with attention-deficit/hyperactivity disorder.

The default mode network (DMN) is atypically active in patients with ADHD, likely contributing to the inattention patterns observed in patients with the disorder. Nonetheless, magnetic resonance spectroscopy (MRS) studies have rarely targeted the posterior cingulate cortex, a key DMN region, and little is known about the biochemical setting within this network in patients with ADHD. We aimed to assess the differences in metabolite profiles of the posterior cingulate cortex-a key region of the DMN-between patients with ADHD and controls. Five brain metabolites-glutamate, inositol, N-acetyl aspartate, choline, and creatine-were measured through MRS in the posterior cingulate cortex of patients and controls in a 3.0 T scanner. Between-group comparison of neurometabolite concentrations in PCC was performed using multivariate analysis of covariance. A total of 88 patients and 44 controls were included in the analysis. Patients with ADHD showed lower levels of glutamate in the posterior cingulate cortex compared to controls (p = 0.003). Lower concentrations of glutamate in the posterior cingulate cortex suggest that a glutamatergic imbalance within the posterior cingulate cortex might play a role in the pathogenesis of ADHD. Further understanding of the causes and consequences of such glutamate decrease might help explain how some glutamate-related drug effects impact on ADHD symptomatology.

Refining patterns of MEF2C effects in white matter microstructure and psychiatric features.

Several GWAS reported Myocyte Enhancer Factor 2 C (MEF2C) gene associations with white matter microstructure and psychiatric disorders, and MEF2C involvement in pathways related to neuronal development suggests a common biological factor underlying these phenotypes. We aim to refine the MEF2C effects in the brain relying on an integrated analysis of white matter and psychiatric phenotypes in an extensively characterized sample. This study included 870 Brazilian adults (47% from an attention-deficit/hyperactivity disorder outpatient clinic) assessed through standardized psychiatric interviews, 139 of which underwent a magnetic resonance imaging scan. We evaluated variants in the MEF2C region using two approaches: 1) a gene-wide analysis, which uses the sum of polymorphism effects, and 2) SNP analyses, restricted to the independent variants within the gene. The outcomes included psychiatric phenotypes and fractional anisotropy for brain images. Results: The gene-wide analyses pointed to a nominal association between MEF2C and the Temporal Portion of the Superior Longitudinal Fasciculus (SLFTEMP). The SNP analysis identified four independent variants significantly associated with SLFTEMP and one (rs4218438) with Substance Use Disorder. Our findings showing specific associations of MEF2C variants with temporal-frontal circuitry components may help to elucidate how the MEF2C gene underlies a broad range of psychiatric phenotypes since these regions are relevant to executive and cognitive functions.

Dissecting the cross-trait effects of the FOXP2 GWAS hit on clinical and brain phenotypes in adults with ADHD.

The Forkhead box P2 (FOXP2) encodes for a transcription factor with a broad role in embryonic development. It is especially represented among GWAS hits for neurodevelopmental disorders and related traits, including attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder, neuroticism, and risk-taking behaviors. While several functional studies are underway to understand the consequences of FOXP2 variation, this study aims to expand previous findings to clinically and genetically related phenotypes and neuroanatomical features among subjects with ADHD. The sample included 407 adults with ADHD and 463 controls. Genotyping was performed on the Infinium PsychArray-24 BeadChip, and the FOXP2 gene region was extracted. A gene-wide approach was adopted to evaluate the combined effects of FOXP2 variants (n = 311) on ADHD status, severity, comorbidities, and personality traits. Independent risk variants presenting potential functional effects were further tested for association with cortical surface areas in a subsample of cases (n = 87). The gene-wide analyses within the ADHD sample showed a significant association of the FOXP2 gene with harm avoidance (P = 0.001; PFDR = 0.015) and nominal associations with hyperactivity symptoms (P = 0.026; PFDR = 0.130) and antisocial personality disorder (P = 0.026; PFDR = 0.130). An insertion/deletion variant (rs79622555) located downstream of FOXP2 was associated with the three outcomes and nominally with the surface area of superior parietal and anterior cingulate cortices. Our results extend and refine previous GWAS findings pointing to a role of FOXP2 in several neurodevelopment-related phenotypes, mainly those involving underlying symptomatic domains of self-regulation and inhibitory control. Taken together, the available evidence may constitute promising insights into the puzzle of the FOXP2-related pathophysiology.

Emerging findings of glutamate-glutamine imbalance in the medial prefrontal cortex in attention deficit/hyperactivity disorder: systematic review and meta-analysis of spectroscopy studies.

One of the main challenges in investigating the neurobiology of ADHD is our limited capacity to study its neurochemistry in vivo. Magnetic resonance spectroscopy (MRS) estimates metabolite concentrations within the brain, but approaches and findings have been heterogeneous. To assess differences in brain metabolites between patients with ADHD and healthy controls, we searched 12 databases screening for MRS studies. Studies were divided into 'children and adolescents' and 'adults' and meta-analyses were performed for each brain region with more than five studies. The quality of studies was assessed by the Newcastle-Ottawa Scale. Thirty-three studies met our eligibility criteria, including 874 patients with ADHD. Primary analyses revealed that the right medial frontal area of children with ADHD presented higher concentrations of a composite of glutamate and glutamine (p = 0.02, SMD = 0.53). Glutamate might be implicated in pruning and neurodegenerative processes as an excitotoxin, while glutamine excess might signal a glutamate depletion that could hinder neurotrophic activity. Both neuro metabolites could be implicated in the differential cortical thinning observed in patients with ADHD across all ages. Notably, more homogeneous designs and reporting guidelines are the key factors to determine how suitable MRS is for research and, perhaps, for clinical psychiatry. Results of this meta-analysis provided an overall map of the brain regions evaluated so far, addressed the role of glutamatergic metabolites in the pathophysiology of ADHD, and pointed to new perspectives for consistent use of the tool in the field.

The course of attention-deficit/hyperactivity disorder through midlife.

The course of ADHD from childhood up to young adulthood has been characterized in several studies. However, little is known about the course of symptoms into middle age and beyond. This study aims to evaluate predictors of ADHD trajectories in midlife based on three assessments. The follow-up sample comprised 323 adults with ADHD, evaluated at baseline and seven and thirteen years later, from the average ages of 34 up to 47 years old. ADHD status at reassessments was used to characterize trajectories. Demographics, ADHD features, comorbidities, and polygenic scores for ADHD and genetically correlated psychiatric disorders were evaluated to predict ADHD trajectories. Study retention rate was 67% at T2 (n = 216) and 62% at T3 (n = 199). Data from patients evaluated three times showed that 68.8% coursed stable, 25.5% unstable, and 5.7% remission trajectory of ADHD. Women, individuals with more severe syndromes, higher frequency of comorbidities at reassessments, and genetic liability to depression present a higher probability of a stable trajectory. Our findings shed light on midlife ADHD trajectories and their gender, genomic and clinical correlates.

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.

Association between cognitive performance and SYT1-rs2251214 among women with cocaine use disorder.

The SNP rs2251214 of the SYT1 gene was recently associated with externalizing phenotypes, including ADHD and cocaine use disorder (CUD). Here, we investigated whether SYT1-rs2251214 could also be implicated with cognitive performance variations among women with CUD. Results showed that G homozygous (n = 146) have lower cognitive performance in the Stroop, Trail Making and Matrix Reasoning tests compared with A-allele carriers (n = 64), suggesting that rs2251214 may influence the severity of cognitive impairments in 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.

SNARE complex in developmental psychiatry: neurotransmitter exocytosis and beyond.

Multiple biological processes throughout development require intracellular vesicular trafficking, where the SNARE (soluble N-ethylmaleimide-sensitive factor (NSF) attachment protein (SNAP) receptors) complex plays a major role. The core proteins forming the SNARE complex are SNAP-25 (synaptosomal-associated protein 25), VAMP (vesicle-associated membrane protein) and Syntaxins, besides its regulatory proteins, such as Synaptotagmin. Genes encoding these proteins (SNAP25, VAMP1, VAMP2, STX1A, SYT1 and SYT2) have been studied in relation to psychiatric disorders susceptibility. Here, we review physiological aspects of SNARE complex and genetic association results reported for attention deficit hyperactivity disorder, both in children and adults, autism spectrum disorders, major depressive disorder, bipolar disorder and schizophrenia. Moreover, we included findings from expression, pharmacogenetics and animal model studies regarding these clinical phenotypes. The overall scenario depicted here suggests that the SNARE complex may exert distinct roles throughout development, with age-specific effects of genetic variants in psychiatric disorders. Such perspective should be considered in future studies regarding SNARE complex genes.

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; r2 =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.

Exploring Neuroimaging Association Scores in adulthood ADHD and middle-age trajectories.

Attention-Deficit/Hyperactivity Disorder (ADHD) is a neurodevelopmental disorder associated with brain differences in children, but not in adults. A combined evaluation of the regional brain differences could improve statistical power and, consequently, allow the detection of possible effects in adults. Thus, our aim is to verify whether Neuroimaging Association Scores (NAS) are associated with adulthood ADHD and clinical trajectories of the disorder in midlife. Clinical and neuroimaging data were collected for 121 subjects with ADHD (mean age: 47.1 ± 10.5; 43% male) and 82 controls (mean age: 38.2 ± 9.0; 54.9% male). Cases were assessed seven and thirteen years after baseline diagnosis, and their clinical trajectories were classified as stable if they fulfilled ADHD diagnosis in all assessments or unstable if they presented remission and recurrence of symptoms. Neuroimaging data were acquired in the last clinical assessment (thirteen years after baseline) and NAS were calculated as a weighted sum of the associations previously reported by meta-analyses for three types of structural brain modalities: cortical thickness, cortical surface area, and subcortical volume. The NAS for cortical surface area was higher in cases compared to controls. No association was found for NAS and number of symptoms of ADHD or clinical trajectories. The fact that differences were restricted to ADHD diagnostic status suggests a susceptibility effect that is not extended to subtle aspects of the disorder. Our results also suggest that evaluating overall effects may have advantages especially when applied to adult ADHD samples.

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.

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).

MR and GR functional SNPs may modulate tobacco smoking susceptibility.

A number of studies have demonstrated that stress is involved in all aspects of smoking behavior, including initiation, maintenance and relapse. The mineralocorticoid (MR) and glucocorticoid (GR) receptors are expressed in several brain areas and play a key role in negative feedback of the hypothalamic-pituitary-adrenal (HPA) axis. As nicotine increases the activation of the HPA axis, we wondered if functional SNPs (single nucleotide polymorphisms) in MR and GR coding genes (NR3C2 rs5522 and NR3C1 rs6198, respectively) may be involved in smoking susceptibility. The sample included 627 volunteers, of which 514 were never-smokers and 113 lifetime smokers. We report an interaction effect between rs5522 and rs6198 SNPs. The odds ratio (OR) for the presence of the NR3C2 rs5522 Val allele in NR3C1 rs6198 G carriers was 0.18 (P = 0.007), while in rs6198 G noncarriers the OR was 1.83 (P = 0.027). We also found main effects of the NR3C1 rs6198 G allele on number of cigarettes smoked per day (P = 0.027) and in total score of the Fagerström Test for Nicotine Dependence (P = 0.007). These findings are consistent with a possible link between NR3C2 and NR3C1 polymorphisms and smoking behavior and provide a first partial replication for a nominally significant GWAS finding between NR3C2 and tobacco smoking.

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.