Genetic architecture of subcortical brain structures in 38,851 individuals

Replicable brain-phenotype associations require large-scale neuroimaging data

Numerous neuroimaging studies have investigated the neural basis of interindividual differences but the replicability of brain-phenotype associations remains largely unknown. We used the UK Biobank neuroimaging dataset (N = 37,447) to examine associations with six variables related to physical and mental health: age, body mass index, intelligence, memory, neuroticism and alcohol consumption, and assessed the improvement of replicability for brain-phenotype associations with increasing sampling sizes. Age may require only 300 individuals to provide highly replicable associations but other phenotypes required 1,500 to 3,900 individuals. The required sample size showed a negative power law relation with the estimated effect size. When only comparing the upper and lower quarters, the minimally required sample sizes for imaging decreased by 15-75%. Our findings demonstrate that large-scale neuroimaging data are required for replicable brain-phenotype associations, that this can be mitigated by preselection of individuals and that small-scale studies may have reported false positive findings.

Causal association of COVID-19 with brain structure changes: Findings from a non-overlapping 2-sample Mendelian randomization study

Recent cohort studies suggested that SARS-CoV-2 infection is associated with changes in brain structure. However, the potential causal relationship remains unclear. We performed a two-sample Mendelian randomization analysis to determine whether genetic susceptibility of COVID-19 is causally associated with changes in cortical and subcortical areas of the brain. This 2-sample MR (Mendelian Randomization) study is an instrumental variable analysis of data from the COVID-19 Host Genetics Initiative (HGI) meta-analyses round 5 excluding UK Biobank participants (COVID-19 infection, N=1,348,701; COVID-19 severity, N=1,557,411), the Enhancing NeuroImaging Genetics through Meta Analysis (ENIGMA) Global and regional cortical measures, N=33,709; combined hemispheric subcortical volumes, N=38,851), and UK Biobank (left/right subcortical volumes, N=19,629). A replication analysis was performed on summary statistics from different COVID-19 GWAS study (COVID-19 infection, N=80,932; COVID-19 severity, N=72,733). We found that the genetic susceptibility of COVID-19 was not significantly associated with changes in brain structures, including cortical and subcortical brain structure. Similar results were observed for different (1) MR estimates, (2) COVID-19 GWAS summary statistics, and (3) definitions of COVID-19 infection and severity. This study suggests that the genetic susceptibility of COVID-19 is not causally associated with changes in cortical and subcortical brain structure.

Neurogenetic and multi-omic sources of overlap among sensation seeking, alcohol consumption, and alcohol use disorder

Sensation seeking is bidirectionally associated with levels of alcohol consumption in both adult and adolescent samples and shared neurobiological and genetic influences may in part explain this association. Links between sensation seeking and alcohol use disorder (AUD) may primarily manifest via increased alcohol consumption rather than through direct effects on increasing problems and consequences. Here the overlap between sensation seeking, alcohol consumption, and AUD was examined using multivariate modeling approaches for genome-wide association study (GWAS) summary statistics in conjunction with neurobiologically-informed analyses at multiple levels of investigation. Meta-analytic and genomic structural equation modeling (GenomicSEM) approaches were used to conduct GWAS of sensation seeking, alcohol consumption, and AUD. Resulting summary statistics were used in downstream analyses to examine shared brain tissue enrichment of heritability and genome-wide evidence of overlap (e.g., stratified GenomicSEM, RRHO, genetic correlations with neuroimaging phenotypes) and to identify genomic regions likely contributing to observed genetic overlap across traits (e.g., HMAGMA, LAVA). Across approaches, results supported shared neurogenetic architecture between sensation seeking and alcohol consumption characterized by overlapping enrichment of genes expressed in midbrain and striatal tissues and variants associated with increased cortical surface area. Alcohol consumption and AUD evidenced overlap in relation to variants associated with decreased frontocortical thickness. Finally, genetic mediation models provided evidence of alcohol consumption mediating associations between sensation seeking and AUD. This study extends previous research by examining critical sources of neurogenetic and multi-omic overlap among sensation seeking, alcohol consumption, and AUD which may underlie observed phenotypic associations.

Genetic heart-brain connections

Multiorgan imaging unveils the intertwined nature of the human heart and brain.

Heart-brain connections: Phenotypic and genetic insights from magnetic resonance images

Cardiovascular health interacts with cognitive and mental health in complex ways, yet little is known about the phenotypic and genetic links of heart-brain systems. We quantified heart-brain connections using multiorgan magnetic resonance imaging (MRI) data from more than 40,000 subjects. Heart MRI traits displayed numerous association patterns with brain gray matter morphometry, white matter microstructure, and functional networks. We identified 80 associated genomic loci (P < 6.09 × 10-10) for heart MRI traits, which shared genetic influences with cardiovascular and brain diseases. Genetic correlations were observed between heart MRI traits and brain-related traits and disorders. Mendelian randomization suggests that heart conditions may causally contribute to brain disorders. Our results advance a multiorgan perspective on human health by revealing heart-brain connections and shared genetic influences.

Shared molecular genetic factors influence subcortical brain morphometry and Parkinson's disease risk

Parkinson's disease (PD) is a late-onset and genetically complex neurodegenerative disorder. Here we sought to identify genes and molecular pathways underlying the associations between PD and the volume of ten brain structures measured through magnetic resonance imaging (MRI) scans. We leveraged genome-wide genetic data from several cohorts, including the International Parkinson's Disease Genomics Consortium (IPDG), the UK Biobank, the Adolescent Brain Cognitive Development (ABCD) study, the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE), the Enhancing Neuroimaging Genetics through Meta-Analyses (ENIGMA), and 23andMe. We observed significant positive genetic correlations between PD and intracranial and subcortical brain volumes. Genome-wide association studies (GWAS) - pairwise analyses identified 210 genomic segments with shared aetiology between PD and at least one of these brain structures. Pathway enrichment results highlight potential links with chronic inflammation, the hypothalamic-pituitary-adrenal pathway, mitophagy, disrupted vesicle-trafficking, calcium-dependent, and autophagic pathways. Investigations for putative causal genetic effects suggest that a larger putamen volume could influence PD risk, independently of the potential causal genetic effects of intracranial volume (ICV) on PD. Our findings suggest that genetic variants influencing larger intracranial and subcortical brain volumes, possibly during earlier stages of life, influence the risk of developing PD later in life.

Heritability of cognitive abilities and regional brain structures in middle-aged to elderly East Asians

This study examined the single-nucleotide polymorphism heritability and genetic correlations of cognitive abilities and brain structural measures (regional subcortical volume and cortical thickness) in middle-aged and elderly East Asians (Korean) from the Gwangju Alzheimer's and Related Dementias cohort study. Significant heritability was found in memory function, caudate volume, thickness of the entorhinal cortices, pars opercularis, superior frontal gyri, and transverse temporal gyri. There were 3 significant genetic correlations between (i) the caudate volume and the thickness of the entorhinal cortices, (ii) the thickness of the superior frontal gyri and pars opercularis, and (iii) the thickness of the superior frontal and transverse temporal gyri. This is the first study to describe the heritability and genetic correlations of cognitive and neuroanatomical traits in middle-aged to elderly East Asians. Our results support the previous findings showing that genetic factors play a substantial role in the cognitive and neuroanatomical traits in middle to advanced age. Moreover, by demonstrating shared genetic effects on different brain regions, it gives us a genetic insight into understanding cognitive and brain changes with age, such as aging-related cognitive decline, cortical atrophy, and neural compensation.

Educational attainment, structural brain reserve and Alzheimer's disease: a Mendelian randomization analysis

Higher educational attainment is observationally associated with lower risk of Alzheimer's disease. However, the biological mechanisms underpinning this association remain unclear. The protective effect of education on Alzheimer's disease may be mediated via increased brain reserve. We used two-sample Mendelian randomization to explore putative causal relationships between educational attainment, structural brain reserve as proxied by MRI phenotypes and Alzheimer's disease. Summary statistics were obtained from genome-wide association studies of educational attainment (n = 1 131 881), late-onset Alzheimer's disease (35 274 cases, 59 163 controls) and 15 measures of grey or white matter macro- or micro-structure derived from structural or diffusion MRI (nmax = 33 211). We conducted univariable Mendelian randomization analyses to investigate bidirectional associations between (i) educational attainment and Alzheimer's disease; (ii) educational attainment and imaging-derived phenotypes; and (iii) imaging-derived phenotypes and Alzheimer's disease. Multivariable Mendelian randomization was used to assess whether brain structure phenotypes mediated the effect of education on Alzheimer's disease risk. Genetically proxied educational attainment was inversely associated with Alzheimer's disease (odds ratio per standard deviation increase in genetically predicted years of schooling = 0.70, 95% confidence interval 0.60, 0.80). There were positive associations between genetically predicted educational attainment and four cortical metrics (standard deviation units change in imaging phenotype per one standard deviation increase in genetically predicted years of schooling): surface area 0.30 (95% confidence interval 0.20, 0.40); volume 0.29 (95% confidence interval 0.20, 0.37); intrinsic curvature 0.18 (95% confidence interval 0.11, 0.25); local gyrification index 0.21 (95% confidence interval 0.11, 0.31)]; and inverse associations with cortical intracellular volume fraction [-0.09 (95% confidence interval -0.15, -0.03)] and white matter hyperintensities volume [-0.14 (95% confidence interval -0.23, -0.05)]. Genetically proxied levels of surface area, cortical volume and intrinsic curvature were positively associated with educational attainment [standard deviation units change in years of schooling per one standard deviation increase in respective genetically predicted imaging phenotype: 0.13 (95% confidence interval 0.10, 0.16); 0.15 (95% confidence interval 0.11, 0.19) and 0.12 (95% confidence interval 0.04, 0.19)]. We found no evidence of associations between genetically predicted imaging-derived phenotypes and Alzheimer's disease. The inverse association of genetically predicted educational attainment with Alzheimer's disease did not attenuate after adjusting for imaging-derived phenotypes in multivariable analyses. Our results provide support for a protective causal effect of educational attainment on Alzheimer's disease risk, as well as potential bidirectional causal relationships between education and brain macro- and micro-structure. However, we did not find evidence that these structural markers affect risk of Alzheimer's disease. The protective effect of education on Alzheimer's disease may be mediated via other measures of brain reserve not included in the present study, or by alternative mechanisms.

Genotype determining aerobic exercise capacity associates with behavioral plasticity in middle-aged rats

Good aerobic fitness associates positively with cognitive performance and brain health and conversely, low aerobic fitness predisposes to neurodegenerative diseases. To study how genotype together with exercise, started at older age, affects brain and behavior, we utilized rats that differ in inherited aerobic fitness. Rats bred for Low Capacity for Running (LCR) are shown to display less synaptic plasticity and more inflammation in the hippocampus and perform worse than rats bred for a High Capacity for Running (HCR) in tasks requiring flexible cognition. Here we used middle-aged (∼ 16 months) HCR and LCR rats to study how genotype and sex associate with anxiety and neural information filtering, termed sensory gating. Further, we assessed how inherited aerobic capacity associates with hippocampus-dependent learning, measured with contextual fear conditioning task. In females, we also investigated the effects of voluntary wheel running (5 weeks) on these characteristics. Our results indicate that independent of sex or voluntary running, HCR rats were more anxious in open-field tasks, exhibited lower sensory gating and learned more efficiently in contextual fear conditioning task than LCR rats. Voluntary running did not markedly affect innate behavior but slightly decreased the differences between female LCR and HCR rats in fear learning. In conclusion, inherited fitness seems to determine cognitive and behavioral traits independent of sex. Although the traits proved to be rather resistant to change at adult age, learning was slightly improved following exercise in LCR females, prone to obesity and poor fitness.

Multiomic approach and Mendelian randomization analysis identify causal associations between blood biomarkers and subcortical brain structure volumes

Alterations in subcortical brain structure volumes have been found to be associated with several neurodegenerative and psychiatric disorders. At the same time, genome-wide association studies (GWAS) have identified numerous common variants associated with brain structure. In this study, we integrate these findings, aiming to identify proteins, metabolites, or microbes that have a putative causal association with subcortical brain structure volumes via a two-sample Mendelian randomization approach. This method uses genetic variants as instrument variables to identify potentially causal associations between an exposure and an outcome. The exposure data that we analyzed comprised genetic associations for 2,994 plasma proteins, 237 metabolites, and 103 microbial genera. The outcome data included GWAS data for seven subcortical brain structure volumes including accumbens, amygdala, caudate, hippocampus, pallidum, putamen, and thalamus. Eleven proteins and six metabolites were found to have a significant association with subcortical structure volumes. We found causal associations between amygdala volume and granzyme A as well as association between accumbens volume and plasma protease c1 inhibitor. Among metabolites, urate had the strongest association with thalamic volume. No significant associations were detected between the microbial genera and subcortical brain structure volumes. We also observed significant enrichment for biological processes such as proteolysis, regulation of the endoplasmic reticulum apoptotic signaling pathway, and negative regulation of DNA binding. Our findings provide insights to the mechanisms through which brain volumes may be affected in the pathogenesis of neurodevelopmental and psychiatric disorders and point to potential treatment targets for disorders that are associated with subcortical brain structure volumes.

Genome-wide DNA methylation analysis of aggressive behaviour: a longitudinal population-based study

BACKGROUND

Human aggression is influenced by an interplay between genetic predisposition and experience across the life span. This interaction is thought to occur through epigenetic mechanisms, inducing differential gene expression, thereby moderating neuronal cell and circuit function, and thus shaping aggressive behaviour.

METHODS

Genome-wide DNA methylation (DNAm) levels were measured in peripheral blood obtained from 95 individuals participating in the Estonian Children Personality Behaviours and Health Study (ECPBHS) at 15 and 25 years of age. We examined the association between aggressive behaviour, as measured by Life History of Aggression (LHA) total score and DNAm levels both assessed at age 25. We further examined the pleiotropic effect of genetic variants regulating LHA-associated differentially methylated positions (DMPs) and multiple traits related to aggressive behaviours. Lastly, we tested whether the DNA methylomic loci identified in association with LHA at age 25 were also present at age 15.

RESULTS

We found one differentially methylated position (DMP) (cg17815886; p = 1.12 × 10^-8 ) and five differentially methylated regions (DMRs) associated with LHA after multiple testing adjustments. The DMP annotated to the PDLIM5 gene, and DMRs resided in the vicinity of four protein-encoding genes (TRIM10, GTF2H4, SLC45A4, B3GALT4) and a long intergenic non-coding RNA (LINC02068). We observed evidence for the colocalization of genetic variants associated with top DMPs and general cognitive function, educational attainment and cholesterol levels. Notably, a subset of the DMPs associated with LHA at age 25 also displayed altered DNAm patterns at age 15 with high accuracy in predicting aggression.

CONCLUSIONS

Our findings highlight the potential role of DNAm in the development of aggressive behaviours. We observed pleiotropic genetic variants associated with identified DMPs, and various traits previously established to be relevant in shaping aggression in humans. The concordance of DNAm signatures in adolescents and young adults may have predictive value for inappropriate and maladaptive aggression later in life.

The genetic architecture of human amygdala volumes and their overlap with common brain disorders

The amygdala is a crucial interconnecting structure in the brain that performs several regulatory functions, yet its genetic architectures and involvement in brain disorders remain largely unknown. We carried out the first multivariate genome-wide association study (GWAS) of amygdala subfield volumes in 27,866 UK Biobank individuals. The whole amygdala was segmented into nine nuclei groups using Bayesian amygdala segmentation. The post-GWAS analysis allowed us to identify causal genetic variants in phenotypes at the SNP, locus, and gene levels, as well as genetic overlap with brain health-related traits. We further generalized our GWAS in Adolescent Brain Cognitive Development (ABCD) cohort. The multivariate GWAS identified 98 independent significant variants within 32 genomic loci associated (P < 5 × 10^-8) with amygdala volume and its nine nuclei. The univariate GWAS identified significant hits for eight of the ten volumes, tagging 14 independent genomic loci. Overall, 13 of the 14 loci identified in the univariate GWAS were replicated in the multivariate GWAS. The generalization in ABCD cohort supported the GWAS results with the 12q23.2 (RNA gene RP11-210L7.1) being discovered. All of these imaging phenotypes are heritable, with heritability ranging from 15% to 27%. Gene-based analyses revealed pathways relating to cell differentiation/development and ion transporter/homeostasis, with the astrocytes found to be significantly enriched. Pleiotropy analyses revealed shared variants with neurological and psychiatric disorders under the conjFDR threshold of 0.05. These findings advance our understanding of the complex genetic architectures of amygdala and their relevance in neurological and psychiatric disorders.

A significant, functional and replicable risk KTN1 variant block for schizophrenia

Cortical and subcortical structural alteration has been extensively reported in schizophrenia, including the unusual expansion of gray matter volumes (GMVs) of basal ganglia (BG), especially putamen. Previous genome-wide association studies pinpointed kinectin 1 gene (KTN1) as the most significant gene regulating the GMV of putamen. In this study, the role of KTN1 variants in risk and pathogenesis of schizophrenia was explored. A dense set of SNPs (n = 849) covering entire KTN1 was analyzed in three independent European- or African-American samples (n = 6704) and one mixed European and Asian Psychiatric Genomics Consortium sample (n = 56,418 cases vs. 78,818 controls), to identify replicable SNP-schizophrenia associations. The regulatory effects of schizophrenia-associated variants on the KTN1 mRNA expression in 16 cortical or subcortical regions in two European cohorts (n = 138 and 210, respectively), the total intracranial volume (ICV) in 46 European cohorts (n = 18,713), the GMVs of seven subcortical structures in 50 European cohorts (n = 38,258), and the surface areas (SA) and thickness (TH) of whole cortex and 34 cortical regions in 50 European cohorts (n = 33,992) and eight non-European cohorts (n = 2944) were carefully explored. We found that across entire KTN1, only 26 SNPs within the same block (r2 > 0.85) were associated with schizophrenia across ≥ 2 independent samples (7.5 × 10-5 ≤ p ≤ 0.048). The schizophrenia-risk alleles, which increased significantly risk for schizophrenia in Europeans (q < 0.05), were all minor alleles (f < 0.5), consistently increased (1) the KTN1 mRNA expression in 12 brain regions significantly (5.9 × 10-12 ≤ p ≤ 0.050; q < 0.05), (2) the ICV significantly (6.1 × 10-4 ≤ p ≤ 0.008; q < 0.05), (3) the SA of whole (9.6 × 10-3 ≤ p ≤ 0.047) and two regional cortices potentially (2.5 × 10-3 ≤ p ≤ 0.042; q > 0.05), and (4) the TH of eight regional cortices potentially (0.006 ≤ p ≤ 0.050; q > 0.05), and consistently decreased (1) the BG GMVs significantly (1.8 × 10-19 ≤ p ≤ 0.050; q < 0.05), especially putamen GMV (1.8 × 10-19 ≤ p ≤ 1.0 × 10-4; q < 0.05, (2) the SA of four regional cortices potentially (0.010 ≤ p ≤ 0.048), and (3) the TH of four regional cortices potentially (0.015 ≤ p ≤ 0.049) in Europeans. We concluded that we identified a significant, functional, and robust risk variant block covering entire KTN1 that might play a critical role in the risk and pathogenesis of schizophrenia.

Anhedonia and dysregulation of an angular gyrus-centred and dynamic functional network in adolescent-onset depression

BACKGROUND

Anhedonia is an important aspect of adolescent-onset major depressive disorder (MDD) and is associated with increased risk of suicidal behaviors and poor treatment outcomes. However, the neural circuitry underlying this deficit has not been well defined. This study aims to identify the relationships between anhedonia and changes in static and dynamic functional connectivity (FC) in adolescent-onset MDD patients compared with healthy control subjects (HCs) and adult-onset MDD patients.

METHODS

A total of 157 participants completed the Snaith-Hamilton Pleasure Scale (SHAPS) to assess hedonic capacity. Resting-state functional imaging scans were analysed using graph theoretical analysis, network-based statistics (NBS) and sliding window correlation analysis to explore the potential patterns of neural network brain disruptions in adolescent-onset MDD. Pearson correlations and support vector machines regression (SVR) were used to explore correlations and predict network measures with SHAPS scores.

RESULTS

Compared with those with adult-onset MDD, adolescent-onset MDD patients showed decreased FC in 7 nodes and 6 connections, with the right angular gyrus (AG), left AG and left paracentral lobule having the largest number of connected edges (P = 0.0396, NBS-corrected). Their average FC and SHAPS scores were positively correlated (r = 0.309, P = 0.035). Regarding dynamic FC, compared with HCs, adolescent-onset MDD patients showed a tendency towards a decreased frequency in moderate-intensity brain FC states (P = 0.014), which was significantly and positively correlated with SHAPS scores (r = 0.425, P = 0.003). SVR also revealed AG-centred FC and dynamic FC could predict SHAPS scores (MSE = 27.233, P = 0.001).

CONCLUSIONS

These findings provide distinct evidence on the physiological mechanisms of adolescent-onset MDD and anhedonia.

Multisite test-retest reliability and compatibility of brain metrics derived from FreeSurfer versions 7.1, 6.0, and 5.3

Automatic neuroimaging processing tools provide convenient and systematic methods for extracting features from brain magnetic resonance imaging scans. One tool, FreeSurfer, provides an easy-to-use pipeline to extract cortical and subcortical morphometric measures. There have been over 25 stable releases of FreeSurfer, with different versions used across published works. The reliability and compatibility of regional morphometric metrics derived from the most recent version releases have yet to be empirically assessed. Here, we used test-retest data from three public data sets to determine within-version reliability and between-version compatibility across 42 regional outputs from FreeSurfer versions 7.1, 6.0, and 5.3. Cortical thickness from v7.1 was less compatible with that of older versions, particularly along the cingulate gyrus, where the lowest version compatibility was observed (intraclass correlation coefficient 0.37-0.61). Surface area of the temporal pole, frontal pole, and medial orbitofrontal cortex, also showed low to moderate version compatibility. We confirm low compatibility between v6.0 and v5.3 of pallidum and putamen volumes, while those from v7.1 were compatible with v6.0. Replication in an independent sample showed largely similar results for measures of surface area and subcortical volumes, but had lower overall regional thickness reliability and compatibility. Batch effect correction may adjust for some inter-version effects when most sites are run with one version, but results vary when more sites are run with different versions. Age associations in a quality controlled independent sample (N = 106) revealed version differences in results of downstream statistical analysis. We provide a reference to highlight the regional metrics that may yield recent version-related inconsistencies in published findings. An interactive viewer is provided at http://data.brainescience.org/Freesurfer_Reliability/.

Eye-brain connections revealed by multimodal retinal and brain imaging genetics in the UK Biobank

As an anatomical extension of the brain, the retina of the eye is synaptically connected to the visual cortex, establishing physiological connections between the eye and the brain. Despite the unique opportunity retinal structures offer for assessing brain disorders, less is known about their relationship to brain structure and function. Here we present a systematic cross-organ genetic architecture analysis of eye-brain connections using retina and brain imaging endophenotypes. Novel phenotypic and genetic links were identified between retinal imaging biomarkers and brain structure and function measures derived from multimodal magnetic resonance imaging (MRI), many of which were involved in the visual pathways, including the primary visual cortex. In 65 genomic regions, retinal imaging biomarkers shared genetic influences with brain diseases and complex traits, 18 showing more genetic overlaps with brain MRI traits. Mendelian randomization suggests that retinal structures have bidirectional genetic causal links with neurological and neuropsychiatric disorders, such as Alzheimer's disease. Overall, cross-organ imaging genetics reveals a genetic basis for eye-brain connections, suggesting that the retinal images can elucidate genetic risk factors for brain disorders and disease-related changes in intracranial structure and function.

Dual-systems models of the genetic architecture of impulsive personality traits: Neurogenetic evidence of distinct but related factors

Background

Dual-systems models provide a parsimonious framework for understanding the interplay between cortical and subcortical brain regions relevant to impulsive personality traits (IPTs) and their associations with psychiatric disorders. Despite recent developments in multivariate analysis of genome-wide association studies (GWAS), molecular genetic investigations of these models have not been conducted.

Methods

Using extant IPT GWAS, we conducted confirmatory genomic structural equation models (GenomicSEM) to empirically evaluate dual-systems models of the genetic architecture of IPTs. Genetic correlations between results of multivariate GWAS of dual-systems factors and GWAS of relevant cortical and subcortical neuroimaging phenotypes (regional/structural volume, cortical surface area, cortical thickness) were calculated and compared.

Results

Evaluation of GenomicSEM model fit indices for dual-systems models suggested that these models highlight important sources of shared and unique genetic variance between top-down and bottom-up constructs. Specifically, a dual-systems genomic model consisting of sensation seeking and lack of self-control factors demonstrated distinct but related sources of genetic influences ( r g =.60). Genetic correlation analyses provided evidence of differential associations between dual-systems factors and cortical neuroimaging phenotypes (e.g., lack of self-control negatively associated with cortical thickness, sensation seeking positively associated with cortical surface area). However, no significant associations were observed for subcortical phenotypes inconsistent with hypothesized functional localization of dual-systems constructs.

Conclusions

Dual-systems models of the genetic architecture of IPTs tested here demonstrate evidence of shared and unique genetic influences and associations with relevant neuroimaging phenotypes. These findings emphasize potential advantages in utilizing dual-systems models to study genetic influences for IPTs and transdiagnostic associations with psychiatric disorders.

Polygenic risk score association with multiple sclerosis susceptibility and phenotype in Europeans

Polygenic inheritance plays a pivotal role in driving multiple sclerosis susceptibility, an inflammatory demyelinating disease of the CNS. We developed polygenic risk scores (PRS) of multiple sclerosis and assessed associations with both disease status and severity in cohorts of European descent. The largest genome-wide association dataset for multiple sclerosis to date (n = 41 505) was leveraged to generate PRS scores, serving as an informative susceptibility marker, tested in two independent datasets, UK Biobank [area under the curve (AUC) = 0.73, 95% confidence interval (CI): 0.72-0.74, P = 6.41 × 10-146] and Kaiser Permanente in Northern California (KPNC, AUC = 0.8, 95% CI: 0.76-0.82, P = 1.5 × 10-53). Individuals within the top 10% of PRS were at higher than 5-fold increased risk in UK Biobank (95% CI: 4.7-6, P = 2.8 × 10-45) and 15-fold higher risk in KPNC (95% CI: 10.4-24, P = 3.7 × 10-11), relative to the median decile. The cumulative absolute risk of developing multiple sclerosis from age 20 onwards was significantly higher in genetically predisposed individuals according to PRS. Furthermore, inclusion of PRS in clinical risk models increased the risk discrimination by 13% to 26% over models based only on conventional risk factors in UK Biobank and KPNC, respectively. Stratifying disease risk by gene sets representative of curated cellular signalling cascades, nominated promising genetic candidate programmes for functional characterization. These pathways include inflammatory signalling mediation, response to viral infection, oxidative damage, RNA polymerase transcription, and epigenetic regulation of gene expression to be among significant contributors to multiple sclerosis susceptibility. This study also indicates that PRS is a useful measure for estimating susceptibility within related individuals in multicase families. We show a significant association of genetic predisposition with thalamic atrophy within 10 years of disease progression in the UCSF-EPIC cohort (P < 0.001), consistent with a partial overlap between the genetics of susceptibility and end-organ tissue injury. Mendelian randomization analysis suggested an effect of multiple sclerosis susceptibility on thalamic volume, which was further indicated to be through horizontal pleiotropy rather than a causal effect. In summary, this study indicates important, replicable associations of PRS with enhanced risk assessment and radiographic outcomes of tissue injury, potentially informing targeted screening and prevention strategies.

Genetic underpinnings of brain structural connectome for young adults

With distinct advantages in power over behavioral phenotypes, brain imaging traits have become emerging endophenotypes to dissect molecular contributions to behaviors and neuropsychiatric illnesses. Among different imaging features, brain structural connectivity (i.e., structural connectome) which summarizes the anatomical connections between different brain regions is one of the most cutting edge while under-investigated traits; and the genetic influence on the structural connectome variation remains highly elusive. Relying on a landmark imaging genetics study for young adults, we develop a biologically plausible brain network response shrinkage model to comprehensively characterize the relationship between high dimensional genetic variants and the structural connectome phenotype. Under a unified Bayesian framework, we accommodate the topology of brain network and biological architecture within the genome; and eventually establish a mechanistic mapping between genetic biomarkers and the associated brain sub-network units. An efficient expectation-maximization algorithm is developed to estimate the model and ensure computing feasibility. In the application to the Human Connectome Project Young Adult (HCP-YA) data, we establish the genetic underpinnings which are highly interpretable under functional annotation and brain tissue eQTL analysis, for the brain white matter tracts connecting the hippocampus and two cerebral hemispheres. We also show the superiority of our method in extensive simulations.

Genetic associations between bipolar disorder and brain structural phenotypes

Patients with bipolar disorder (BD) and their first-degree relatives exhibit alterations in brain volume and cortical structure, whereas the underlying genetic mechanisms remain unclear. In this study, based on the published genome-wide association studies (GWAS), the extent of polygenic overlap between BD and 15 brain structural phenotypes was investigated using linkage disequilibrium score regression and MiXeR tool, and the shared genomic loci were discovered by conjunctional false discovery rate (conjFDR) and expression quantitative trait loci (eQTL) analyses. MiXeR estimated the overall measure of polygenic overlap between BD and brain structural phenotypes as 4-53% on a 0-100% scale (as quantified by the Dice coefficient). Subsequent conjFDR analyses identified 54 independent loci (71 risk single-nucleotide polymorphisms) jointly associated with BD and brain structural phenotypes with a conjFDR < 0.05, among which 33 were novel that had not been reported in the previous BD GWAS. Follow-up eQTL analyses in respective brain regions both confirmed well-known risk genes (e.g. CACNA1C, NEK4, GNL3, MAPK3) and discovered novel risk genes (e.g. LIMK2 and CAMK2N2). This study indicates a substantial shared genetic basis between BD and brain structural phenotypes, and provides novel insights into the developmental origin of BD and related biological mechanisms.

Male-specific, replicable and functional roles of genetic variants and cerebral gray matter volumes in ADHD: a gene-wide association study across KTN1 and a region-wide functional validation across brain

Attention deficit hyperactivity disorder (ADHD) is associated with reduction of cortical and subcortical gray matter volumes (GMVs). The kinectin 1 gene (KTN1) has recently been reported to significantly regulate GMVs and ADHD risk. In this study, we aimed to identify sex-specific, replicable risk KTN1 alleles for ADHD and to explore their regulatory effects on mRNA expression and cortical and subcortical GMVs. We examined a total of 1020 KTN1 SNPs in one discovery sample (ABCD cohort: 5573 males and 5082 females) and three independent replication European samples (Samples #1 and #2 each with 802/122 and 472/141 male/female offspring with ADHD; and Sample #3 with 14,154/4945 ADHD and 17,948/16,246 healthy males/females) to identify replicable associations within each sex. We examined the regulatory effects of ADHD-risk alleles on the KTN1 mRNA expression in two European brain cohorts (n = 348), total intracranial volume (TIV) in 46 European cohorts (n = 18,713) and the ABCD cohort, as well as the GMVs of seven subcortical structures in 50 European cohorts (n = 38,258) and of 118 cortical and subcortical regions in the ABCD cohort. We found that four KTN1 variants significantly regulated the risk of ADHD with the same direction of effect in males across discovery and replication samples (0.003 ≤ p ≤ 0.041), but none in females. All four ADHD-risk alleles significantly decreased KTN1 mRNA expression in all brain regions examined (1.2 × 10^-5 ≤ p ≤ 0.039). The ADHD-risk alleles significantly increased basal ganglia (2.8 × 10^-22 ≤ p ≤ 0.040) and hippocampus (p = 0.010) GMVs but reduced amygdala GMV (p = 0.030) and TIV (0.010 < p ≤ 0.013). The ADHD-risk alleles also significantly reduced some cortical (right superior temporal pole, right rectus) and cerebellar but increased other cortical (0.007 ≤ p ≤ 0.050) GMVs. To conclude, we identified a set of replicable and functional risk KTN1 alleles for ADHD, specifically in males. KTN1 may play a critical role in the pathogenesis of ADHD, and the reduction of specific cortical and subcortical, including amygdalar but not basal ganglia or hippocampal, GMVs may serve as a neural marker of the genetic effects.

Mapping gene by early life stress interactions on child subcortical brain structures: A genome-wide prospective study

Background

Although it is well-established that both genetics and the environment influence brain development, they are typically examined separately. Here, we aimed to prospectively investigate the interactive effects of genetic variants-from a genome-wide approach-and early life stress (ELS) on child subcortical brain structures, and their association with subsequent mental health problems.

Method

Primary analyses were conducted using data from the Generation R Study (N = 2257), including genotype and cumulative prenatal and postnatal ELS scores (encompassing life events, contextual risk, parental risk, interpersonal risk, direct victimisation). Neuroimaging data were collected at age 10 years, including intracranial and subcortical brain volumes (accumbens, amygdala, caudate, hippocampus, pallidum, putamen, thalamus). Genome-wide association and genome-wide-by-environment interaction analyses (GWEIS, run separately for prenatal/postnatal ELS) were conducted for eight brain outcomes (i.e., 24 genome-wide analyses) in the Generation R Study (discovery). Polygenic scores (PGS) using the resulting weights were calculated in an independent (target) cohort (adolescent brain cognitive development Study; N = 10,751), to validate associations with corresponding subcortical volumes and examine links to later mother-reported internalising and externalising problems.

Results

One GWEIS-prenatal stress locus was associated with caudate volume (rs139505895, mapping onto PRSS12 and NDST3) and two GWEIS-postnatal stress loci with the accumbens (rs2397823 and rs3130008, mapping onto CUTA, SYNGAP1, and TABP). Functional annotation revealed that these genes play a role in neuronal plasticity and synaptic function, and have been implicated in neuro-developmental phenotypes, for example, intellectual disability, autism, and schizophrenia. None of these associations survived a more stringent correction for multiple testing across all analysis sets. In the validation sample, all PGSgenotype were associated with their respective brain volumes, but no PGSGxE associated with any subcortical volume. None of the PGS associated with internalising or externalising problems.

Conclusions

This study lends novel suggestive insights into gene-environment interplay on the developing brain as well as pointing to promising candidate loci for future replication and mechanistic studies.

Mapping the current trends and hotspots of vascular cognitive impairment from 2000-2021: A bibliometric analysis

AIMS

To visualize the trends and hotspots in the scientific research related to vascular cognitive impairment (VCI) quantitatively and qualitatively.

METHODS

Cross-sectional bibliometric analysis of publications that related to VCI was conducted. Publications were found by searching in the Web of Science Core Collection database (WoSCC) - Edition: Science Citation Index Expanded (SCI-Expanded) from January 2000 to December 2021. Publication type was restricted to article and review in the English language. The downloaded data were screened and analyzed in January 2022.

RESULTS

In total, 16,264 publications were identified, with a steady increase in annual publications. The United States was the leading country in VCI research regarding publication numbers and national influence. National Institute of Aging had the highest influence among all the institutes in the field of VCI. Philip Scheltens was the most active author. The top five active authors' publications focused on pathobiology, neuroimaging standards, risk factors, prevention, and the standard diagnosis of vascular dementia (VaD). A co-cited publication clustering resulted in 19 main clusters, and the prevention, blood-brain barrier, cholesterol, cerebral amyloid angiopathy, and VaD were the top 5 clusters. Moreover, burst keywords detection revealed that the "small vessel disease" is the current hotspot in the field of VCI.

CONCLUSIONS

This bibliometric analysis mapped the overall research structure of VCI and analyzed the current research trends and hotspots for future studies orientation. Neuroimaging, risk factors detection, and pathobiology are the current trends in VCI research. Small vessel disease and its mechanisms are the current hotspots of VCI research.

Heritability of Subcortical Grey Matter Structures

Background and Objectives: Subcortical grey matter structures play essential roles in cognitive, affective, social, and motoric functions in humans. Their volume changes with age, and decreased volumes have been linked with many neuropsychiatric disorders. The aim of our study was to examine the heritability of six subcortical brain volumes (the amygdala, caudate nucleus, pallidum, putamen, thalamus, and nucleus accumbens) and four general brain volumes (the total intra-cranial volume and the grey matter, white matter, and cerebrospinal fluid (CSF) volume) in twins. Materials and Methods: A total of 118 healthy adult twins from the Hungarian Twin Registry (86 monozygotic and 32 dizygotic; median age 50 ± 27 years) underwent brain magnetic resonance imaging. Two automated volumetry pipelines, Computational Anatomy Toolbox 12 (CAT12) and volBrain, were used to calculate the subcortical and general brain volumes from three-dimensional T1-weighted images. Age- and sex-adjusted monozygotic and dizygotic intra-pair correlations were calculated, and the univariate ACE model was applied. Pearson's correlation test was used to compare the results obtained by the two pipelines. Results: The age- and sex-adjusted heritability estimates, using CAT12 for the amygdala, caudate nucleus, pallidum, putamen, and nucleus accumbens, were between 0.75 and 0.95. The thalamus volume was more strongly influenced by common environmental factors (C = 0.45-0.73). The heritability estimates, using volBrain, were between 0.69 and 0.92 for the nucleus accumbens, pallidum, putamen, right amygdala, and caudate nucleus. The left amygdala and thalamus were more strongly influenced by common environmental factors (C = 0.72-0.85). A strong correlation between CAT12 and volBrain (r = 0.74-0.94) was obtained for all volumes. Conclusions: The majority of examined subcortical volumes appeared to be strongly heritable. The thalamus was more strongly influenced by common environmental factors when investigated with both segmentation methods. Our results underline the importance of identifying the relevant genes responsible for variations in the subcortical structure volume and associated diseases.

Morphological development of the human fetal striatum during the second trimester

The morphological development of the fetal striatum during the second trimester has remained poorly described. We manually segmented the striatum using 7.0-T MR images of the fetal specimens ranging from 14 to 22 gestational weeks. The global development of the striatum was evaluated by volume measurement. The absolute volume (Vabs) of the caudate nucleus (CN) increased linearly with gestational age, while the relative volume (Vrel) showed a quadratic growth. Both Vabs and Vrel of putamen increased linearly. Through shape analysis, the changes of local structure in developing striatum were specifically demonstrated. Except for the CN tail, the lateral and medial parts of the CN grew faster than the middle regions, with a clear rostral-caudal growth gradient as well as a distinct "outside-in" growth gradient. For putamen, the dorsal and ventral regions grew obviously faster than the other regions, with a dorsal-ventral bidirectional developmental pattern. The right CN was larger than the left, whereas there was no significant hemispheric asymmetry in the putamen. By establishing the developmental trajectories, spatial heterochrony, and hemispheric dimorphism of human fetal striatum, these data bring new insight into the fetal striatum development and provide detailed anatomical references for future striatal studies.

Discovery of 42 genome-wide significant loci associated with dyslexia

Reading and writing are crucial life skills but roughly one in ten children are affected by dyslexia, which can persist into adulthood. Family studies of dyslexia suggest heritability up to 70%, yet few convincing genetic markers have been found. Here we performed a genome-wide association study of 51,800 adults self-reporting a dyslexia diagnosis and 1,087,070 controls and identified 42 independent genome-wide significant loci: 15 in genes linked to cognitive ability/educational attainment, and 27 new and potentially more specific to dyslexia. We validated 23 loci (13 new) in independent cohorts of Chinese and European ancestry. Genetic etiology of dyslexia was similar between sexes, and genetic covariance with many traits was found, including ambidexterity, but not neuroanatomical measures of language-related circuitry. Dyslexia polygenic scores explained up to 6% of variance in reading traits, and might in future contribute to earlier identification and remediation of dyslexia.

The relationship between metabolic control and basal ganglia morphometry and function in individuals with early-treated phenylketonuria

Abnormalities of the cortical white matter are the most prominent and widely-reported neurological findings in individuals with early-treated phenylketonuria (ETPKU). Much less is known regarding the effects of ETPKU on gray matter structures in the brain such as the basal ganglia. Previous findings on basal ganglia in ETPKU have been mixed. The current study was designed to further elucidate the effects of ETPKU and elevated phe levels on the morphometry of basal ganglia structures (i.e., putamen, caudate nucleus, nucleus accumbens, and globus pallidus). High resolution magnetic resonance imaging (MRI) data was collected from a sample of 37 adults with ETPKU and a demographically-matched comparison group of 33 individuals without PKU. No overall group differences (ETPKU vs. non-PKU) in basal ganglia volumes were observed. However, within the ETPKU group, poorer metabolic control (as reflected by higher blood phenylalanine levels) was associated with larger putamen volume. Vertex-wise shape analysis revealed that the volume increase was accompanied by shape changes in the middle left putamen. Consistent with this area's role in motor control, a significant correlation between left putamen volume and motor performance was also observed. Additional research is needed to fully understand the cellular level processes underlying this effect as well as to better understand the clinical impact of these morphometric changes and their potential relation to treatment response.

Genome-wide meta-analyses reveal novel loci for verbal short-term memory and learning

Understanding the genomic basis of memory processes may help in combating neurodegenerative disorders. Hence, we examined the associations of common genetic variants with verbal short-term memory and verbal learning in adults without dementia or stroke (N = 53,637). We identified novel loci in the intronic region of CDH18, and at 13q21 and 3p21.1, as well as an expected signal in the APOE/APOC1/TOMM40 region. These results replicated in an independent sample. Functional and bioinformatic analyses supported many of these loci and further implicated POC1. We showed that polygenic score for verbal learning associated with brain activation in right parieto-occipital region during working memory task. Finally, we showed genetic correlations of these memory traits with several neurocognitive and health outcomes. Our findings suggest a role of several genomic loci in verbal memory processes.

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 (β, -2.52; 95% CI, -4.13 to -0.91) and DPW (β, -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.

Derivation and utility of schizophrenia polygenic risk associated multimodal MRI frontotemporal network

Schizophrenia is a highly heritable psychiatric disorder characterized by widespread functional and structural brain abnormalities. However, previous association studies between MRI and polygenic risk were mostly ROI-based single modality analyses, rather than identifying brain-based multimodal predictive biomarkers. Based on schizophrenia polygenic risk scores (PRS) from healthy white people within the UK Biobank dataset (N = 22,459), we discovered a robust PRS-associated brain pattern with smaller gray matter volume and decreased functional activation in frontotemporal cortex, which distinguished schizophrenia from controls with >83% accuracy, and predicted cognition and symptoms across 4 independent schizophrenia cohorts. Further multi-disease comparisons demonstrated that these identified frontotemporal alterations were most severe in schizophrenia and schizo-affective patients, milder in bipolar disorder, and indistinguishable from controls in autism, depression and attention-deficit hyperactivity disorder. These findings indicate the potential of the identified PRS-associated multimodal frontotemporal network to serve as a trans-diagnostic gene intermediated brain biomarker specific to schizophrenia.

Shared mechanisms across the major psychiatric and neurodegenerative diseases

Several common psychiatric and neurodegenerative diseases share epidemiologic risk; however, whether they share pathophysiology is unclear and is the focus of our investigation. Using 25 GWAS results and LD score regression, we find eight significant genetic correlations between psychiatric and neurodegenerative diseases. We integrate the GWAS results with human brain transcriptomes (n = 888) and proteomes (n = 722) to identify cis- and trans- transcripts and proteins that are consistent with a pleiotropic or causal role in each disease, referred to as causal proteins for brevity. Within each disease group, we find many distinct and shared causal proteins. Remarkably, 30% (13 of 42) of the neurodegenerative disease causal proteins are shared with psychiatric disorders. Furthermore, we find 2.6-fold more protein-protein interactions among the psychiatric and neurodegenerative causal proteins than expected by chance. Together, our findings suggest these psychiatric and neurodegenerative diseases have shared genetic and molecular pathophysiology, which has important ramifications for early treatment and therapeutic development.

transferGWAS: GWAS of images using deep transfer learning

MOTIVATION

Medical images can provide rich information about diseases and their biology. However, investigating their association with genetic variation requires non-standard methods. We propose transferGWAS, a novel approach to perform genome-wide association studies directly on full medical images. First, we learn semantically meaningful representations of the images based on a transfer learning task, during which a deep neural network is trained on independent but similar data. Then, we perform genetic association tests with these representations.

RESULTS

We validate the type I error rates and power of transferGWAS in simulation studies of synthetic images. Then we apply transferGWAS in a genome-wide association study of retinal fundus images from the UK Biobank. This first-of-a-kind GWAS of full imaging data yielded 60 genomic regions associated with retinal fundus images, of which 7 are novel candidate loci for eye-related traits and diseases.

AVAILABILITY AND IMPLEMENTATION

Our method is implemented in Python and available at https://github.com/mkirchler/transferGWAS/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Gray matter volumetric correlates of attention deficit and hyperactivity traits in emerging adolescents

Previous research has demonstrated reduction in cortical and subcortical, including basal ganglia (BG), gray matter volumes (GMV) in individuals with attention deficit hyperactivity disorder (ADHD), a neurodevelopmental condition that is more prevalent in males than in females. However, the volumetric deficits vary across studies. Whether volumetric reductions are more significant in males than females; to what extent these neural markers are heritable and relate to cognitive dysfunction in ADHD remain unclear. To address these questions, we followed published routines and performed voxel-based morphometry analysis of a data set (n = 11,502; 5,464 girls, 9-10 years) curated from the Adolescent Brain Cognition Development project, a population-based study of typically developing children. Of the sample, 634 and 2,826 were identified as monozygotic twins and dizygotic twins/siblings, respectively. In linear regressions, a cluster in the hypothalamus showed larger GMV, and bilateral caudate and putamen, lateral orbitofrontal and occipital cortex showed smaller GMVs, in correlation with higher ADHD scores in girls and boys combined. When examined separately, boys relative to girls showed more widespread (including BG) and stronger associations between GMV deficits and ADHD scores. ADHD traits and the volumetric correlates demonstrated heritability estimates (a2) between 0.59 and 0.79, replicating prior findings of the genetic basis of ADHD. Further, ADHD traits and the volumetric correlates (except for the hypothalamus) were each negatively and positively correlated with N-back performance. Together, these findings confirm volumetric deficits in children with more prominent ADHD traits. Highly heritable in both girls and boys and potentially more significant in boys than in girls, the structural deficits underlie diminished capacity in working memory and potentially other cognitive deficits in ADHD.

Shapes of subcortical structures in adolescents with and without familial history of substance use disorder

It has been suggested that intergenerational transmission of risk for substance use disorder (SUD) manifests in the brain anatomy of substance naïve adolescents. While volume and shapes of subcortical structures (SSS) have been shown to be heritable, these structures, especially the pallidum, putamen, nucleus accumbens, and hippocampus, have also been associated with substance use disorders. However, it is not clear if those anatomical differences precede substance use or are the result of that use. Therefore, we examined if volume and SSS of adolescents with a family history (FH+) of SUD differed from adolescents without such a history (FH-). Because risk for SUD is associated with anxiety and impulsivity, we also examined correlations between these psychological characteristics and volume/SSS. Using structural MRI and FSL software, we segmented subcortical structures and obtained indices of SSS and volumes of 64 FH+ and 58 FH- adolescents. We examined group differences in volume and SSS, and the correlations between volume/SSS and trait anxiety and impulsivity. FH+ adolescents had a significant inward deformation in the shape of the right anterior hippocampus compared to FH- adolescents, while the volume of this structure did not differ between groups. Neither shape nor volume of the other subcortical structures differed between groups. In the FH+ adolescents, the left hippocampus shape was positively correlated with both trait anxiety and impulsivity, while in FH- adolescents a negative correlation pattern of SSS was seen in the hippocampus. SSS appears to capture local anatomical features that traditional volumetric analysis does not. The inward shape deformation in the right anterior hippocampus in FH+ adolescents may be related to the known increased risk for behavioral dysregulation leading to SUD in FH+ offspring. Hippocampus shape also exhibits opposite patterns of correlation with anxiety and impulsivity scores across the FH+ and FH- adolescents. These novel findings may reveal neural correlates, not captured by traditional volumetric analysis, of familial transmission of increased vulnerability to SUD.

Sex-different interrelationships of rs945270, cerebral gray matter volumes, and attention deficit hyperactivity disorder: a region-wide study across brain

Previous genome-wide association studies (GWAS) reported that the allele C of rs945270 of the kinectin 1 gene (KTN1) most significantly increased the gray matter volume (GMV) of the putamen and modestly regulated the risk for attention deficit hyperactivity disorder (ADHD). On the other hand, ADHD is known to be associated with a reduction in subcortical and cortical GMVs. Here, we examined the interrelationships of the GMVs, rs945270 alleles, and ADHD symptom scores in the same cohort of children. With data of rs945270 genotypes, GMVs of 118 brain regions, and ADHD symptom scores of 3372 boys and 3129 girls of the Adolescent Brain Cognition Development project, we employed linear regression analyses to examine the pairwise correlations adjusted for the third of the three traits and other relevant covariates, and examine their mediation effects. We found that the major allele C of rs945270 modestly increased risk for ADHD in males only when controlling for the confounding effects of the GMV of any one of the 118 cerebral regions (0.026 ≤ p ≤ 0.059: Top two: left and right putamen). This allele also significantly increased putamen GMV in males alone (left p = 2.8 × 10-5, and right p = 9.4 × 10-5; α = 2.1 × 10-4) and modestly increased other subcortical and cortical GMVs in both sexes (α < p < 0.05), whether or not adjusted for ADHD symptom scores. Both subcortical and cortical GMVs were significantly or suggestively reduced in ADHD when adjusted for rs945270 alleles, each more significantly in females (3.6 × 10-7 ≤ p < α; Top two: left pallidum and putamen) and males (3.5 × 10-6 ≤ p < α), respectively. Finally, the left and right putamen GMVs reduced 14.0% and 11.7% of the risk effects of allele C on ADHD, and allele C strengthened 4.5% (left) and 12.2% (right) of the protective effects of putamen GMVs on ADHD risk, respectively. We concluded that the rs945270-GMVs-ADHD relationships were sex-different. In males, the major allele C of rs945270 increased risk for ADHD, which was compromised by putamen GMVs; this allele also but only significantly increased putamen GMVs that then significantly protected against ADHD risk. In females, the top two GMVs significantly decreasing ADHD risk were left pallidum and putamen GMVs. Basal ganglia the left putamen in particular play the most critical role in the pathogenesis of ADHD.

Genomic Studies Across the Lifespan Point to Early Mechanisms Determining Subcortical Volumes

BACKGROUND

Subcortical brain structures play a key role in pathological processes of age-related neurodegenerative disorders. Mounting evidence also suggests that early-life factors may have an impact on the development of common late-life neurological diseases, including genetic factors that can influence both brain maturation and neurodegeneration.

METHODS

Using large population-based brain imaging datasets across the lifespan (N ≤ 40,628), we aimed to 1) estimate the heritability of subcortical volumes in young (18-35 years), middle (35-65 years), and older (65+ years) age, and their genetic correlation across age groups; 2) identify whether genetic loci associated with subcortical volumes in older persons also show associations in early adulthood, and explore underlying genes using transcriptome-wide association studies; and 3) explore their association with neurological phenotypes.

RESULTS

Heritability of subcortical volumes consistently decreased with increasing age. Genetic risk scores for smaller caudate nucleus, putamen, and hippocampus volume in older adults were associated with smaller volumes in young adults. Individually, 10 loci associated with subcortical volumes in older adults also showed associations in young adults. Within these loci, transcriptome-wide association studies showed that expression of several genes in brain tissues (especially MYLK2 and TUFM) was associated with subcortical volumes in both age groups. One risk variant for smaller caudate nucleus volume (TUFM locus) was associated with lower cognitive performance. Genetically predicted Alzheimer's disease was associated with smaller subcortical volumes in middle and older age.

CONCLUSIONS

Our findings provide novel insights into the genetic determinants of subcortical volumes across the lifespan. More studies are needed to decipher the underlying biology and clinical impact.

The effects of age, sex, weight, and breed on canid methylomes

Unlike genomes, which are static throughout the lifespan of an organism, DNA methylomes are dynamic. To study these dynamics, we developed quantitative models that measure the effect of multiple factors on DNA methylomes including, age, sex, weight, and genetics. We conducted our study in canids, which prove to be an ideal species to assess epigenetic moderators due to their extreme variability in size and well-characterized genetic structure. We collected buccal swabs from 217 canids (207 domestic dogs and 10 grey wolves) and used targeted bisulphite sequencing to measure methylomes. We also measured genotypes at over one thousand single nucleotide polymorphisms (SNPs). As expected, we found that DNA methylomes are strongly associated with age, enabling the construction of epigenetic clocks. However, we also identify novel associations between methylomes and sex, weight, and sterilization status, leading to accurate models that predict these factors. Methylomes are also affected by genetics, and we observe multiple associations between SNP loci and methylated CpGs. Finally, we show that several factors moderate the relationship between epigenetic ages and real ages, such as body weight, which increases epigenetic ageing. In conclusion, we demonstrate that the plasticity of DNA methylomes is impacted by myriad genetics and physiological factors, and that DNA methylation biomarkers are accurate predictors of age, sex and sterilization status.

Multivariate genome-wide association study on tissue-sensitive diffusion metrics highlights pathways that shape the human brain

The molecular determinants of tissue composition of the human brain remain largely unknown. Recent genome-wide association studies (GWAS) on this topic have had limited success due to methodological constraints. Here, we apply advanced whole-brain analyses on multi-shell diffusion imaging data and multivariate GWAS to two large scale imaging genetic datasets (UK Biobank and the Adolescent Brain Cognitive Development study) to identify and validate genetic association signals. We discover 503 unique genetic loci that have impact on multiple regions of human brain. Among them, more than 79% are validated in either of two large-scale independent imaging datasets. Key molecular pathways involved in axonal growth, astrocyte-mediated neuroinflammation, and synaptogenesis during development are found to significantly impact the measured variations in tissue-specific imaging features. Our results shed new light on the biological determinants of brain tissue composition and their potential overlap with the genetic basis of neuropsychiatric disorders.

Cross disorder comparisons of brain structure in schizophrenia, bipolar disorder, major depressive disorder, and 22q11.2 deletion syndrome: A review of ENIGMA findings

This review compares the main brain abnormalities in schizophrenia (SZ), bipolar disorder (BD), major depressive disorder (MDD), and 22q11.2 Deletion Syndrome (22q11DS) determined by ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) consortium investigations. We obtained ranked effect sizes for subcortical volumes, regional cortical thickness, cortical surface area, and diffusion tensor imaging abnormalities, comparing each of these disorders relative to healthy controls. In addition, the studies report on significant associations between brain imaging metrics and disorder-related factors such as symptom severity and treatments. Visual comparison of effect size profiles shows that effect sizes are generally in the same direction and scale in severity with the disorders (in the order SZ > BD > MDD). The effect sizes for 22q11DS, a rare genetic syndrome that increases the risk for psychiatric disorders, appear to be much larger than for either of the complex psychiatric disorders. This is consistent with the idea of generally larger effects on the brain of rare compared to common genetic variants. Cortical thickness and surface area effect sizes for 22q11DS with psychosis compared to 22q11DS without psychosis are more similar to those of SZ and BD than those of MDD; a pattern not observed for subcortical brain structures and fractional anisotropy effect sizes. The observed similarities in effect size profiles for cortical measures across the psychiatric disorders mimic those observed for shared genetic variance between these disorders reported based on family and genetic studies and are consistent with shared genetic risk for SZ and BD and structural brain phenotypes.

The Impact of Genes and Environment on Brain Ageing in Males Aged 51 to 72 Years

Magnetic resonance imaging data are being used in statistical models to predicted brain ageing (PBA) and as biomarkers for neurodegenerative diseases such as Alzheimer's Disease. Despite their increasing application, the genetic and environmental etiology of global PBA indices is unknown. Likewise, the degree to which genetic influences in PBA are longitudinally stable and how PBA changes over time are also unknown. We analyzed data from 734 men from the Vietnam Era Twin Study of Aging with repeated MRI assessments between the ages 51-72 years. Biometrical genetic analyses "twin models" revealed significant and highly correlated estimates of additive genetic heritability ranging from 59 to 75%. Multivariate longitudinal modeling revealed that covariation between PBA at different timepoints could be explained by a single latent factor with 73% heritability. Our results suggest that genetic influences on PBA are detectable in midlife or earlier, are longitudinally very stable, and are largely explained by common genetic influences.

Genetic and environment effects on structural neuroimaging endophenotype for bipolar disorder: a novel molecular approach

We investigated gene-environment effects on structural brain endophenotype in bipolar disorder (BD) using a novel method of combining polygenic risk scores with epigenetic signatures since traditional methods of examining the family history and trauma effects have significant limitations. The study enrolled 119 subjects, including 55 BD spectrum (BDS) subjects diagnosed with BD or major depressive disorder (MDD) with subthreshold BD symptoms and 64 non-BDS subjects comprising 32 MDD subjects without BD symptoms and 32 healthy subjects. The blood samples underwent genome-wide genotyping and methylation quantification. We derived polygenic risk score (PRS) and methylation profile score (MPS) as weighted summations of risk single nucleotide polymorphisms and methylation probes, respectively, which were considered as molecular measures of genetic and environmental risks for BD. Linear regression was used to relate PRS, MPS, and their interaction to 44 brain structure measures quantified from magnetic resonance imaging (MRI) on 47 BDS subjects, and the results were compared with those based on family history and childhood trauma. After multiplicity corrections using false discovery rate (FDR), MPS was found to be negatively associated with the volume of the medial geniculate thalamus (FDR = 0.059, partial R² = 0.208). Family history, trauma scale, and PRS were not associated with any brain measures. PRS and MPS show significant interactions on whole putamen (FDR = 0.09, partial R² = 0.337). No significant gene-environment interactions were identified for the family history and trauma scale. PRS and MPS generally explained greater proportions of variances of the brain measures (range of partial R² = [0.008, 0.337]) than the clinical risk factors (range = [0.004, 0.228]).

Genetic variants associated with longitudinal changes in brain structure across the lifespan

Human brain structure changes throughout the lifespan. Altered brain growth or rates of decline are implicated in a vast range of psychiatric, developmental and neurodegenerative diseases. In this study, we identified common genetic variants that affect rates of brain growth or atrophy in what is, to our knowledge, the first genome-wide association meta-analysis of changes in brain morphology across the lifespan. Longitudinal magnetic resonance imaging data from 15,640 individuals were used to compute rates of change for 15 brain structures. The most robustly identified genes GPR139, DACH1 and APOE are associated with metabolic processes. We demonstrate global genetic overlap with depression, schizophrenia, cognitive functioning, insomnia, height, body mass index and smoking. Gene set findings implicate both early brain development and neurodegenerative processes in the rates of brain changes. Identifying variants involved in structural brain changes may help to determine biological pathways underlying optimal and dysfunctional brain development and aging.

An independent, replicable, functional and significant risk variant block at intron 3 of CACNA1C for schizophrenia

OBJECTIVES

Genome-wide association studies have identified a significant risk gene, CACNA1C, for schizophrenia. In this study, we comprehensively investigated a large set of CACNA1C single-nucleotide polymorphisms (SNPs) to identify the replicable risk alleles for schizophrenia and explore their biological functions.

METHODS

One Jewish (1044 cases vs 2052 controls), one European (1350 cases vs 1378 controls) and one exploratory African American samples (98 cases vs 20 controls) were analyzed to identify replicable single-nucleotide polymorphism-schizophrenia associations. The regulatory effects of risk alleles on CACNA1C messenger RNA expression were examined. The most robust risk tagSNP (rs1006737) was meta-analyzed on 17 studies (74,122 cases vs 109,062 controls), and associated with the gray matter volumes of seven subcortical structures in 38,258 Europeans, and the surface areas and thickness of 34 cortical regions in 33,992 Europeans and 2944 non-Europeans.

RESULTS

Forty-seven replicable risk single-nucleotide polymorphisms, including a 20-single-nucleotide polymorphism haplotype block, were identified in our samples (1.8 × 10^-4 ⩽ p ⩽ 0.049). This variant block was consistently associated with schizophrenia across four independent Psychiatric Genomics Consortium cohorts (79,645 cases vs 109,590 controls; 2.5 × 10^-17 ⩽ p ⩽ 0.017). This block showed significant expression quantitative trait loci in three independent European brain cohorts (5.1 × 10^-12 ⩽ p ⩽ 8.3 × 10^-3) and could be tagged by the most significant risk single-nucleotide polymorphism rs1006737. The minor allele A of rs1006737 significantly increased risk for schizophrenia across the Jewish and European samples (p = 0.029 and 0.004, respectively), and this association was highly significant in the meta-analysis (p = 1.62 × 10^-42). This allele also significantly altered the CACNA1C messenger RNA expression in five brain regions (5.1 × 10^-12 ⩽ p ⩽ 0.05), decreased the gray matter volume of thalamus (p = 0.010), the surface area of isthmus cingulate cortex (p = 0.013) and the thickness of transverse temporal and superior temporal sulcus cortexes (0.005 ⩽ p ⩽ 0.043).

CONCLUSION

We identified an independent, replicable, functional, and significant risk variant block at CACNA1C for schizophrenia, which could be tagged by the most robust risk marker rs1006737, suggesting an important role of CACNA1C in the pathogenesis of schizophrenia.

Genetic common variants associated with cerebellar volume and their overlap with mental disorders: a study on 33,265 individuals from the UK-Biobank

Interest in the cerebellum is expanding given evidence of its contributions to cognition and emotion, and dysfunction in various psychopathologies. However, research into its genetic architecture and shared influences with liability for mental disorders is lacking. We conducted a genome-wide association study (GWAS) of total cerebellar volume and underlying cerebellar lobe volumes in 33,265 UK-Biobank participants. Total cerebellar volume was heritable (h2SNP = 50.6%), showing moderate genetic homogeneity across lobes (h2SNP from 35.4% to 57.1%; mean genetic correlation between lobes rg ≈ 0.44). We identified 33 GWAS signals associated with total cerebellar volume, of which 6 are known to alter protein-coding gene structure, while a further five mapped to genomic regions known to alter cerebellar tissue gene expression. Use of summary data-based Mendelian randomisation further prioritised genes whose change in expression appears to mediate the SNP-trait association. In total, we highlight 21 unique genes of greatest interest for follow-up analyses. Using LD-regression, we report significant genetic correlations between total cerebellar volume and brainstem, pallidum and thalamus volumes. While the same approach did not result in significant correlations with psychiatric phenotypes, we report enrichment of schizophrenia, bipolar disorder and autism spectrum disorder associated signals within total cerebellar GWAS results via conditional and conjunctional-FDR analysis. Via these methods and GWAS catalogue, we identify which of our cerebellar genomic regions also associate with psychiatric traits. Our results provide important insights into the common allele architecture of cerebellar volume and its overlap with other brain volumes and psychiatric phenotypes.

Multivariate Genetic Structure of Externalizing Behavior and Structural Brain Development in a Longitudinal Adolescent Twin Sample

Externalizing behavior in its more extreme form is often considered a problem to the individual, their families, teachers, and society as a whole. Several brain structures have been linked to externalizing behavior and such associations may arise if the (co)development of externalizing behavior and brain structures share the same genetic and/or environmental factor(s). We assessed externalizing behavior with the Child Behavior Checklist and Youth Self Report, and the brain volumes and white matter integrity (fractional anisotropy [FA] and mean diffusivity [MD]) with magnetic resonance imaging in the BrainSCALE cohort, which consisted of twins and their older siblings from 112 families measured longitudinally at ages 10, 13, and 18 years for the twins. Genetic covariance modeling based on the classical twin design, extended to also include siblings of twins, showed that genes influence externalizing behavior and changes therein (h² up to 88%). More pronounced externalizing behavior was associated with higher FA (observed correlation r_ph up to +0.20) and lower MD (r_ph up to −0.20), with sizeable genetic correlations (FA r_a up to +0.42; MD r_a up to −0.33). The cortical gray matter (CGM; r_ph up to −0.20) and cerebral white matter (CWM; r_ph up to +0.20) volume were phenotypically but not genetically associated with externalizing behavior. These results suggest a potential mediating role for global brain structures in the display of externalizing behavior during adolescence that are both partially explained by the influence of the same genetic factor.

Alterations in Cortical-Subcortical Metabolism in Temporal Lobe Epilepsy With Impaired Awareness Seizures

Objective

The features of cerebral metabolism associated with loss of consciousness in patients with temporal lobe epilepsy (TLE) have not been fully elucidated. We aim to investigate the alterations in cortical-subcortical metabolism in temporal lobe epilepsy with impaired awareness seizures (IAS).

Methods

Regional cerebral metabolism was measured using fluorine-18-fluorodeoxyglucose positron emission tomography (18F-FDG PET) in patients with TLE-IAS and healthy controls. All patients had a comprehensive evaluation to confirm their seizure origin and lateralization. Videos of all seizures were viewed and rated by at least two epileptologists to identify the state of consciousness when a seizure occurred. By synthesizing the seizure history, semeiology, and video EEG of all patients, as long as the patients had one seizure with impaired awareness, she/he will be included. 76 patients with TLE-IAS and 60 age-matched healthy controls were enrolled in this study. Regional cerebral metabolic patterns were analyzed for TLE-IAS and healthy control groups using statistical parametric mapping. Besides, we compared the MRI-negative patients and MRI-positive patients with healthy controls, respectively.

Results

There were no significant differences in the age and sex of TLE-IAS patients and healthy control. TLE-IAS patients showed extensive bilateral hypermetabolism in the frontoparietal regions, cingulate gyrus, corpus callosum, occipital lobes, basal ganglia, thalamus, brainstem, and cerebellum. The region of metabolic change was more extensive in right TLE-IAS than that of the left, including extensive hypometabolism in the ipsilateral temporal, frontal, parietal, and insular lobes. And contralateral temporal lobe, bilateral frontoparietal regions, occipital lobes, the anterior and posterior regions of the cingulate gyrus, bilateral thalamus, bilateral basal ganglia, brainstem, and bilateral cerebellum showed hypermetabolism. The TLE patients with impaired awareness seizure showed hypermetabolism in the cortical-subcortical network including the arousal system. Additionally, 48 MRI-positive and 28 MRI-negative TLE-IAS patients were included in our study. TLE-IAS patients with MRI-negative and MRI-positive were both showed hypermetabolism in the cingulate gyrus. Hypometabolism in the bilateral temporal lobe was showed in the TLE-IAS with MRI-positive.

Conclusion

These findings suggested that the repetitive consciousness impairing ictal events may have an accumulative effect on brain metabolism, resulting in abnormal interictal cortical-subcortical metabolic disturbance in TLE patients with impaired awareness seizure. Understanding these metabolic mechanisms may guide future clinical treatments to prevent seizure-related awareness deficits and improve quality of life in people with TLE.

Exploring the genetic correlation between obesity-related traits and regional brain volumes: Evidence from UK Biobank cohort

OBJECTIVE

To determine whether there is a correlation between obesity-related variants and regional brain volumes.

METHODS

Based on a mixed linear model (MLM), we analyzed the association between 1,498 obesity-related SNPs in the GWAS Catalog and 164 regional brain volumes from 29,420 participants (discovery cohort N = 19,997, validation cohort N = 9,423) in UK Biobank. The statistically significant brain regions in association analysis were classified into 6 major neural networks (dopamine (DA) motive system, central autonomic network (CAN), cognitive emotion regulation, visual object recognition network, auditory object recognition network, and sensorimotor system). We summarized the association between obesity-related variants (metabolically healthy obesity variants, metabolically unhealthy obesity variants, and unclassified obesity-related variants) and neural networks.

RESULTS

From association analysis, we determined that 17 obesity-related SNPs were associated with 51 regional brain volumes. Several single SNPs (e.g., rs13107325-T (SLC39A8), rs1876829-C (CRHR1), and rs1538170-T (CENPW)) were associated with multiple regional brain volumes. In addition, several single brain regions (e.g., the white matter, the grey matter in the putamen, subcallosal cortex, and insular cortex) were associated with multiple obesity-related variants. The metabolically healthy obesity variants were mainly associated with the regional brain volumes in the DA motive system, sensorimotor system and cognitive emotion regulation neural networks, while metabolically unhealthy obesity variants were mainly associated with regional brain volumes in the CAN and total tissue volumes. In addition, unclassified obesity-related variants were mainly associated with auditory object recognition network and total tissue volumes. The results of MeSH (medical subject headings) enrichment analysis showed that obesity genes associated with brain structure pointed to the functional relatedness with 5-Hydroxytryptamine receptor 4 (5-HT4), growth differentiation factor 5 (GDF5), and high mobility group protein AT-hook 2 (HMGA2 protein).

CONCLUSION

In summary, we found that obesity-related variants were associated with different brain volume measures. On the basis of the multiple SNPs, we found that metabolically healthy and unhealthy obesity-related SNPs were associated with different brain neural networks. Based on our enrichment analysis, modifications of the 5-HT4 pathway might be a promising therapeutic strategy for obesity.

Differences in subcortical brain volumes among patients with schizophrenia and bipolar disorder and healthy controls

BACKGROUND

Patients with schizophrenia and bipolar disorder have an overlapping polygenic architecture and clinical similarities, although the 2 disorders are distinct diagnoses with clinical dissimilarities. It remains unclear whether there are specific differences in subcortical volumes between schizophrenia and bipolar disorder, and whether the subcortical differences are affected by any clinical characteristics. We investigated differences in subcortical volumes bilaterally among patients with schizophrenia, patients with bipolar disorder and healthy controls. We also investigated the influences of clinical characteristics on specific subcortical volumes in these patient groups.

METHODS

We collected 3 T T ₁-weighted MRI brain scans from 413 participants (157 with schizophrenia, 51 with bipolar disorder and 205 controls) with a single scanner at a single institute. We used FreeSurfer version 6.0 for processing the T ₁-weighted images to segment the following subcortical brain volumes: thalamus, caudate, putamen, globus pallidus, hippocampus, amygdala and nucleus accumbens. Differences in the 7 subcortical volumes were investigated among the groups. We also evaluated correlations between subcortical volumes and clinical variables in these patient groups.

RESULTS

Of 7 subcortical regions, patients with schizophrenia had significantly smaller volumes in the left thalamus (Cohen d = -0.29, p = 5.83 × 10^-3), bilateral hippocampi (left, d = -0.36, p = 8.85 × 10^-4; right, d = -0.41, p = 1.15 × 10^-4) and left amygdala (d = -0.31, p = 4.02 × 10^-3) than controls. Compared with controls, patients with bipolar disorder had bilateral reductions only in the hippocampal volumes (left, d = -0.52, p = 1.12 × 10^-3; right, d = -0.58, p = 0.30 × 10^-4). We also found that patients with schizophrenia had significantly smaller volumes in the bilateral amygdalae (left, d = -0.43, p = 4.22 × 10^-3; right, d = -0.45, p = 4.56 × 10^-3) than patients with bipolar disorder. We did not find any significant volumetric differences in the other 6 subcortical structures between patient groups (p > 0.05). Smaller left amygdalar volumes were significantly correlated with younger onset age only in patients with schizophrenia (r = 0.22, p = 5.78 × 10^-3).

LIMITATIONS

We did not evaluate the differences in subcortical volumes between patients stratified based on clinical bipolar disorder subtype and a history of psychotic episodes because our sample size of patients with bipolar disorder was limited.

CONCLUSION

Our findings suggest that volumetric differences in the amygdala between patients with schizophrenia and those with bipolar disorder may be a putative biomarker for distinguishing 2 clinically similar diagnoses.

Shared Genetic Etiology between Cortical Brain Morphology and Tobacco, Alcohol, and Cannabis Use

Genome-wide association studies (GWAS) have identified genetic variants associated with brain morphology and substance use behaviors (SUB). However, the genetic overlap between brain structure and SUB has not been well characterized. We leveraged GWAS summary data of 71 brain imaging measures and alcohol, tobacco, and cannabis use to investigate their genetic overlap using linkage disequilibrium score regression. We used genomic structural equation modeling to model a "common SUB genetic factor" and investigated its genetic overlap with brain structure. Furthermore, we estimated SUB polygenic risk scores (PRS) and examined whether they predicted brain imaging traits using the Adolescent Behavior and Cognitive Development (ABCD) study. We identified 8 significant negative genetic correlations, including between (1) alcoholic drinks per week and average cortical thickness, and (2) intracranial volume with age of smoking initiation. We observed 5 positive genetic correlations, including those between (1) insula surface area and lifetime cannabis use, and (2) the common SUB genetic factor and pericalcarine surface area. SUB PRS were associated with brain structure variation in ABCD. Our findings highlight a shared genetic etiology between cortical brain morphology and SUB and suggest that genetic variants associated with SUB may be causally related to brain structure differences.