Novel genetic loci underlying human intracranial volume identified through genome-wide association

Type 2 diabetes, glycaemic traits, structural brain capacity and cognitive function: A Mendelian randomization analysis

AIM

To estimate the causal associations of type 2 diabetes and glycaemic traits with cognitive function, and to determine the potential mediating role of various brain imaging-derived phenotypes (IDPs) using Mendelian randomization (MR) analysis.

METHODS

Using publicly available summary data, we performed a series of univariable and multivariable MR analysis to infer causality. Two-step MR analysis was then conducted in turn to evaluate the potential mediating role of each brain IDP.

RESULTS

There was no evidence of causal associations between type 2 diabetes and cognitive function outcomes. Each 1-SD unit higher genetically predicted fasting proinsulin was associated with worse cognitive performance, as evidenced by both univariable (beta: -0.022; 95% confidence interval [CI] -0.038, -0.007) and multivariable MR analysis (beta: -0.027; 95% CI -0.048, -0.005). In addition, the univariable MR analysis identified several causal associations between fasting proinsulin and brain IDPs, and between brain IDPs and cognitive performance. The inverse association of genetically predicted fasting proinsulin with cognitive performance did not attenuate after adjusting for each of the brain IDPs in multivariable MR analysis.

CONCLUSIONS

The present MR study provided credible evidence for the causal association between genetically predicted fasting proinsulin and cognitive function, informing a potential diagnosis and intervention target for patients with cognitive impairment. No significant brain IDP included in this study was identified as lying on the causal pathway from fasting proinsulin to cognitive performance. Future research involving more specific and granular brain IDP or other brain process is warranted to explore the potential biological mechanism underlying the association.

Genetic variants for head size share genes and pathways with cancer

The size of the human head is highly heritable, but genetic drivers of its variation within the general population remain unmapped. We perform a genome-wide association study on head size (N = 80,890) and identify 67 genetic loci, of which 50 are novel. Neuroimaging studies show that 17 variants affect specific brain areas, but most have widespread effects. Gene set enrichment is observed for various cancers and the p53, Wnt, and ErbB signaling pathways. Genes harboring lead variants are enriched for macrocephaly syndrome genes (37-fold) and high-fidelity cancer genes (9-fold), which is not seen for human height variants. Head size variants are also near genes preferentially expressed in intermediate progenitor cells, neural cells linked to evolutionary brain expansion. Our results indicate that genes regulating early brain and cranial growth incline to neoplasia later in life, irrespective of height. This warrants investigation of clinical implications of the link between head size and cancer.

Unsupervised deep representation learning enables phenotype discovery for genetic association studies of brain imaging

Understanding the genetic architecture of brain structure is challenging, partly due to difficulties in designing robust, non-biased descriptors of brain morphology. Until recently, brain measures for genome-wide association studies (GWAS) consisted of traditionally expert-defined or software-derived image-derived phenotypes (IDPs) that are often based on theoretical preconceptions or computed from limited amounts of data. Here, we present an approach to derive brain imaging phenotypes using unsupervised deep representation learning. We train a 3-D convolutional autoencoder model with reconstruction loss on 6130 UK Biobank (UKBB) participants' T1 or T2-FLAIR (T2) brain MRIs to create a 128-dimensional representation known as Unsupervised Deep learning derived Imaging Phenotypes (UDIPs). GWAS of these UDIPs in held-out UKBB subjects (n = 22,880 discovery and n = 12,359/11,265 replication cohorts for T1/T2) identified 9457 significant SNPs organized into 97 independent genetic loci of which 60 loci were replicated. Twenty-six loci were not reported in earlier T1 and T2 IDP-based UK Biobank GWAS. We developed a perturbation-based decoder interpretation approach to show that these loci are associated with UDIPs mapped to multiple relevant brain regions. Our results established unsupervised deep learning can derive robust, unbiased, heritable, and interpretable brain imaging phenotypes.

Cell subtype-specific effects of genetic variation in the Alzheimer's disease brain

The relationship between genetic variation and gene expression in brain cell types and subtypes remains understudied. Here, we generated single-nucleus RNA sequencing data from the neocortex of 424 individuals of advanced age; we assessed the effect of genetic variants on RNA expression in cis (cis-expression quantitative trait loci) for seven cell types and 64 cell subtypes using 1.5 million transcriptomes. This effort identified 10,004 eGenes at the cell type level and 8,099 eGenes at the cell subtype level. Many eGenes are only detected within cell subtypes. A new variant influences APOE expression only in microglia and is associated with greater cerebral amyloid angiopathy but not Alzheimer's disease pathology, after adjusting for APOEε4, providing mechanistic insights into both pathologies. Furthermore, only a TMEM106B variant affects the proportion of cell subtypes. Integration of these results with genome-wide association studies highlighted the targeted cell type and probable causal gene within Alzheimer's disease, schizophrenia, educational attainment and Parkinson's disease loci.

Impact of adult-onset multiple sclerosis on MRI-based intracranial volume: A study in clinically discordant monozygotic twins

OBJECTIVE

Intracranial volume (ICV) represents the maximal brain volume for an individual, attained prior to late adolescence and remaining constant throughout life after. Thus, ICV serves as a surrogate marker for brain growth integrity. To assess the potential impact of adult-onset multiple sclerosis (MS) and its preceding prodromal subclinical changes on ICV in a large cohort of monozygotic twins clinically discordant for MS.

METHODS

FSL software was used to derive ICV estimates from 3D-T1-weighted-3 T-MRI images by using an atlas scaling factor method. ICV were compared between clinically affected and healthy co-twins. All twins were compared to a large healthy reference cohort using standardized ICV z-scores. Mixed models assessed the impact of age at MS diagnosis on ICV.

RESULTS

54 twin-pairs (108 individuals/80female/42.45 ± 11.98 years), 731 individuals (375 non-twins, 109/69 monozygotic/dizygotic twin-pairs; 398female/29.18 ± 0.13 years) and 35 healthy local individuals (20male/31.34 ± 1.53 years). In 45/54 (83 %) twin-pairs, both clinically affected and healthy co-twins showed negative ICV z-scores, i.e., ICVs lower than the average of the healthy reference cohort (M = -1.53 ± 0.11, P<10-5). Younger age at MS diagnosis was strongly associated with lower ICVs (t = 3.76, P = 0.0003). Stratification of twin-pairs by age at MS diagnosis of the affected co-twin (≤30 versus > 30 years) yielded lower ICVs in those twin pairs with younger age at diagnosis (P = 0.01). Comparison within individual twin-pairs identified lower ICVs in the MS-affected co-twins with younger age at diagnosis compared to their corresponding healthy co-twins (P = 0.003).

CONCLUSION

We offer for the first-time evidence for strong associations between adult-onset MS and lower ICV, which is more pronounced with younger age at diagnosis. This suggests pre-clinical alterations in early neurodevelopment associated with susceptibility to MS both in individuals with and without clinical manifestation of the disease.

Genetic architecture of the structural connectome

Myelinated axons form long-range connections that enable rapid communication between distant brain regions, but how genetics governs the strength and organization of these connections remains unclear. We perform genome-wide association studies of 206 structural connectivity measures derived from diffusion magnetic resonance imaging tractography of 26,333 UK Biobank participants, each representing the density of myelinated connections within or between a pair of cortical networks, subcortical structures or cortical hemispheres. We identify 30 independent genome-wide significant variants after Bonferroni correction for the number of measures studied (126 variants at nominal genome-wide significance) implicating genes involved in myelination (SEMA3A), neurite elongation and guidance (NUAK1, STRN, DPYSL2, EPHA3, SEMA3A, HGF, SHTN1), neural cell proliferation and differentiation (GMNC, CELF4, HGF), neuronal migration (CCDC88C), cytoskeletal organization (CTTNBP2, MAPT, DAAM1, MYO16, PLEC), and brain metal transport (SLC39A8). These variants have four broad patterns of spatial association with structural connectivity: some have disproportionately strong associations with corticothalamic connectivity, interhemispheric connectivity, or both, while others are more spatially diffuse. Structural connectivity measures are highly polygenic, with a median of 9.1 percent of common variants estimated to have non-zero effects on each measure, and exhibited signatures of negative selection. Structural connectivity measures have significant genetic correlations with a variety of neuropsychiatric and cognitive traits, indicating that connectivity-altering variants tend to influence brain health and cognitive function. Heritability is enriched in regions with increased chromatin accessibility in adult oligodendrocytes (as well as microglia, inhibitory neurons and astrocytes) and multiple fetal cell types, suggesting that genetic control of structural connectivity is partially mediated by effects on myelination and early brain development. Our results indicate pervasive, pleiotropic, and spatially structured genetic control of white-matter structural connectivity via diverse neurodevelopmental pathways, and support the relevance of this genetic control to healthy brain function.

Intracranial Volume Is Driven by Both Genetics and Early Life Exposures: The SOL-INCA-MRI Study

Intracranial volume (ICV) reflects maximal brain development and is associated with later-life cognitive abilities. We quantified ICV among first- and second-generation Hispanic and Latino adults from the Study of Latinos-Investigation of Cognitive Aging - MRI (SOL-INCA-MRI), estimated ICV heritability, and tested its associations with previously reported genetic variants, both individually and as a genetic risk score (GRS). We also estimated the association of ICV with early life environmental measures: nativity or age of immigration and parental education. The estimated heritability of ICV was 19% (95% CI, 0.1%-56%) in n=1781 unrelated SOL-INCA-MRI individuals. Four of 10 tested genetic variants were associated with ICV and an increase of 1 SD of the ICV-GRS was associated with an increase of 10.37 cm3 in the ICV (95% CI, 5.29-15.45). Compared to being born in the continental United States, immigrating to the United States at age 11 years or older was associated with 24 cm3 smaller ICV (95% CI, -39.97 to -8.06). Compared to both parents having less than high-school education, at least 1 parent completing high-school education was associated with 15.4 cm3 greater ICV (95% CI, 4.46-26.39). These data confirm the importance of early life health on brain development.

Quantitative relationships of FAM50B and PTCHD3 methylation with reduced intelligence quotients in school aged children exposed to lead: Evidence from epidemiological and in vitro studies

At present, the application of DNA methylation (DNAm) biomarkers in environmental health risk assessment (EHRA) is more challenging due to the unclearly quantitative relationship between them. We aimed to explore the role of FAM50B and PTCHD3 at the level of signaling pathways, and establish the quantitative relationship between them and children's intelligence quotients (IQs). DNAm of target regions was measured in multiple cell models and was compared with the human population data. Then the dose-response relationships of lead exposure with neurotoxicity and DNAm were established by benchmark dose (BMD) model, followed by potential signaling pathway screening. Results showed that there was a quantitative linear relationship between children's IQs and FAM50B/PTCHD3 DNAm (DNAm between 51.40 % - 78.78 % and 31.41 % - 74.19 % for FAM50B and PTCHD3, respectively), and this relationship was more significant when children's IQs > 90. The receiver operating characteristic (ROC) and calibration curves showed that FAM50B/PTCHD3 DNAm had a satisfying accuracy and consistency in predicting children's IQs, which was confirmed by sensitivity analysis of gender and CpG site grouping data. In cell experiments, there was also a quantitative linear relationship between FAM50B DNAm and reactive oxygen species (ROS) production, which was mediated by PI3K-AKT signaling pathway. In addition, the lead BMD of ROS was close to that of FAM50B DNAm, suggesting that FAM50B DNAm was a suitable biomarker for the risk assessments of adverse outcomes induced by lead. Taken collectively, these results suggest that FAM50B/PTCHD3 can be applied to EHRA and the prevention/intervention of adverse effects of lead on children's IQs.

Proxy-analysis of the genetics of cognitive decline in Parkinson's disease through polygenic scores

Cognitive decline is common in Parkinson's disease (PD) and its genetic risk factors are not well known to date, besides variants in the GBA and APOE genes. However, variation in complex traits is caused by numerous variants and is usually studied with genome-wide association studies (GWAS), requiring a large sample size, which is difficult to achieve for outcome measures in PD. Taking an alternative approach, we computed 100 polygenic scores (PGS) related to cognitive, dementia, stroke, and brain anatomical phenotypes and investigated their association with cognitive decline in six longitudinal cohorts. The analysis was adjusted for age, sex, genetic ancestry, follow-up duration, GBA and APOE status. Then, we meta-analyzed five of these cohorts, comprising a total of 1702 PD participants with 6156 visits, using the Montreal Cognitive Assessment as a cognitive outcome measure. After correction for multiple comparisons, we found four PGS significantly associated with cognitive decline: intelligence (p = 5.26e-13), cognitive performance (p = 1.46e-12), educational attainment (p = 8.52e-10), and reasoning (p = 3.58e-5). Survival analyses highlighted an offset of several years between the first and last quartiles of PGS, with significant differences for the PGS of cognitive performance (5 years) and educational attainment (7 years). In conclusion, we found four PGS associated with cognitive decline in PD, all associated with general cognitive phenotypes. This study highlights the common genetic factors between cognitive decline in PD and the general population, and the importance of the participant's cognitive reserve for cognitive outcome in PD.

A global multicohort study to map subcortical brain development and cognition in infancy and early childhood

The human brain grows quickly during infancy and early childhood, but factors influencing brain maturation in this period remain poorly understood. To address this gap, we harmonized data from eight diverse cohorts, creating one of the largest pediatric neuroimaging datasets to date focused on birth to 6 years of age. We mapped the developmental trajectory of intracranial and subcortical volumes in ∼2,000 children and studied how sociodemographic factors and adverse birth outcomes influence brain structure and cognition. The amygdala was the first subcortical volume to mature, whereas the thalamus exhibited protracted development. Males had larger brain volumes than females, and children born preterm or with low birthweight showed catch-up growth with age. Socioeconomic factors exerted region- and time-specific effects. Regarding cognition, males scored lower than females; preterm birth affected all developmental areas tested, and socioeconomic factors affected visual reception and receptive language. Brain-cognition correlations revealed region-specific associations.

Genetic relationship between the immune system and autism

Autism spectrum disorder (ASD) is a common and complex neurodevelopmental condition. The pathophysiology of ASD is poorly defined; however, it includes a strong genetic component and there is increasing evidence to support a role of immune dysregulation. Nonetheless, it is unclear which immune phenotypes link to ASD through genetics. Hence, we investigated the genetic correlation between ASD and diverse classes of immune conditions and markers; and if these immune-related genetic factors link to specific autistic-like traits in the population. We estimated global and local genetic correlations between ASD (n = 55,420) and 11 immune phenotypes (n = 14,256-755,406) using genome-wide association study summary statistics. Subsequently, polygenic scores (PGS) for these immune phenotypes were calculated in a population-based sample (n = 2487) and associated to five autistic-like traits (i.e., attention to detail, childhood behaviour, imagination, rigidity, social skills), and a total autistic-like traits score. Sex-stratified PGS analyses were also performed. At the genome-wide level, ASD was positively correlated with allergic diseases (ALG), and negatively correlated with lymphocyte count, rheumatoid arthritis (RA), and systemic lupus erythematosus (SLE) (FDR-p = 0.01-0.02). At the local genetic level, ASD was correlated with RA, C-reactive protein, and granulocytes and lymphocyte counts (p = 5.8 × 10-6-0.002). In the general population sample, increased genetic liability for SLE, RA, ALG, and lymphocyte levels, captured by PGS, was associated with the total autistic score and with rigidity and childhood behaviour (FDR-p = 0.03). In conclusion, we demonstrated a genetic relationship between ASD and immunity that depends on the type of immune phenotype considered; some increase likelihood whereas others may potentially help build resilience. Also, this relationship may be restricted to specific genetic loci and link to specific autistic dimensions (e.g., rigidity).

Isoform-level transcriptome-wide association uncovers genetic risk mechanisms for neuropsychiatric disorders in the human brain

Methods integrating genetics with transcriptomic reference panels prioritize risk genes and mechanisms at only a fraction of trait-associated genetic loci, due in part to an overreliance on total gene expression as a molecular outcome measure. This challenge is particularly relevant for the brain, in which extensive splicing generates multiple distinct transcript-isoforms per gene. Due to complex correlation structures, isoform-level modeling from cis-window variants requires methodological innovation. Here we introduce isoTWAS, a multivariate, stepwise framework integrating genetics, isoform-level expression and phenotypic associations. Compared to gene-level methods, isoTWAS improves both isoform and gene expression prediction, yielding more testable genes, and increased power for discovery of trait associations within genome-wide association study loci across 15 neuropsychiatric traits. We illustrate multiple isoTWAS associations undetectable at the gene-level, prioritizing isoforms of AKT3, CUL3 and HSPD1 in schizophrenia and PCLO with multiple disorders. Results highlight the importance of incorporating isoform-level resolution within integrative approaches to increase discovery of trait associations, especially for brain-relevant traits.

Cerebellar Volume and Disease Staging in Parkinson's Disease: An ENIGMA-PD Study

BACKGROUND

Increasing evidence points to a pathophysiological role for the cerebellum in Parkinson's disease (PD). However, regional cerebellar changes associated with motor and non-motor functioning remain to be elucidated.

OBJECTIVE

To quantify cross-sectional regional cerebellar lobule volumes using three dimensional T1-weighted anatomical brain magnetic resonance imaging from the global ENIGMA-PD working group.

METHODS

Cerebellar parcellation was performed using a deep learning-based approach from 2487 people with PD and 1212 age and sex-matched controls across 22 sites. Linear mixed effects models compared total and regional cerebellar volume in people with PD at each Hoehn and Yahr (HY) disease stage, to an age- and sex- matched control group. Associations with motor symptom severity and Montreal Cognitive Assessment scores were investigated.

RESULTS

Overall, people with PD had a regionally smaller posterior lobe (dmax  = -0.15). HY stage-specific analyses revealed a larger anterior lobule V bilaterally (dmax  = 0.28) in people with PD in HY stage 1 compared to controls. In contrast, smaller bilateral lobule VII volume in the posterior lobe was observed in HY stages 3, 4, and 5 (dmax  = -0.76), which was incrementally lower with higher disease stage. Within PD, cognitively impaired individuals had lower total cerebellar volume compared to cognitively normal individuals (d = -0.17).

CONCLUSIONS

We provide evidence of a dissociation between anterior "motor" lobe and posterior "non-motor" lobe cerebellar regions in PD. Whereas less severe stages of the disease are associated with larger motor lobe regions, more severe stages of the disease are marked by smaller non-motor regions. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

The molecular genetic landscape of human brain size variation

Human brain size changes dynamically through early development, peaks in adolescence, and varies up to 2-fold among adults. However, the molecular genetic underpinnings of interindividual variation in brain size remain unknown. Here, we leveraged postmortem brain RNA sequencing and measurements of brain weight (BW) in 2,531 individuals across three independent datasets to identify 928 genome-wide significant associations with BW. Genes associated with higher or lower BW showed distinct neurodevelopmental trajectories and spatial patterns that mapped onto functional and cellular axes of brain organization. Expression of BW genes was predictive of interspecies differences in brain size, and bioinformatic annotation revealed enrichment for neurogenesis and cell-cell communication. Genome-wide, transcriptome-wide, and phenome-wide association analyses linked BW gene sets to neuroimaging measurements of brain size and brain-related clinical traits. Cumulatively, these results represent a major step toward delineating the molecular pathways underlying human brain size variation in health and disease.

The bidirectional effects between cognitive ability and brain morphology: A life course Mendelian randomization analysis

Introduction

Little is understood about the dynamic interplay between brain morphology and cognitive ability across the life course. Additionally, most existing research has focused on global morphology measures such as estimated total intracranial volume, mean thickness, and total surface area.

Methods

Mendelian randomization was used to estimate the bidirectional effects between cognitive ability, global and regional measures of cortical thickness and surface area, estimated total intracranial volume, total white matter, and the volume of subcortical structures (N=37,864). Analyses were stratified for developmental periods (childhood, early adulthood, mid-to-late adulthood; age range: 8-81 years).

Results

The earliest effects were observed in childhood and early adulthood in the frontoparietal lobes. A bidirectional relationship was identified between higher cognitive ability, larger estimated total intracranial volume (childhood, mid-to-late adulthood) and total surface area (all life stages). A thicker posterior cingulate cortex and a larger surface area in the caudal middle frontal cortex and temporal pole were associated with greater cognitive ability. Contrary, a thicker temporal pole was associated with lower cognitive ability.

Discussion

Stable effects of cognitive ability on brain morphology across the life course suggests that childhood is potentially an important window for intervention.

Heritability of cerebral blood flow in adolescent and young adult twins: an arterial spin labeling perfusion imaging study

Blood perfusion is a fundamental physiological property of all organs and is closely linked to brain metabolism. Genetic factors were reported to have important influences on cerebral blood flow. However, the profile of genetic contributions to cerebral blood flow in adolescents or young adults was underexplored. In this study, we recruited a sample of 65 pairs of same-sex adolescent or young adult twins undergoing resting arterial spin labeling imaging to conduct heritability analyses. Our findings indicate that genetic factors modestly affect cerebral blood flow in adolescents or young adults in the territories of left anterior cerebral artery and right posterior cerebral artery, with the primary contribution being to the frontal regions, cingulate gyrus, and striatum, suggesting a profile of genetic contributions to specific brain regions. Notably, the regions in the left hemisphere demonstrate the highest heritability in most regions examined. These results expand our knowledge of the genetic basis of cerebral blood flow in the developing brain and emphasize the importance of regional analysis in understanding the heritability of cerebral blood flow. Such insights may contribute to our understanding of the underlying genetic mechanism of brain functions and altered cerebral blood flow observed in youths with brain disorders.

Genomic Structural Equation Modeling Reveals Latent Phenotypes in the Human Cortex with Distinct Genetic Architecture

Genetic contributions to human cortical structure manifest pervasive pleiotropy. This pleiotropy may be harnessed to identify unique genetically-informed parcellations of the cortex that are neurobiologically distinct from functional, cytoarchitectural, or other cortical parcellation schemes. We investigated genetic pleiotropy by applying genomic structural equation modeling (SEM) to map the genetic architecture of cortical surface area (SA) and cortical thickness (CT) for the 34 brain regions recently reported in the ENIGMA cortical GWAS. Genomic SEM uses the empirical genetic covariance estimated from GWAS summary statistics with LD score regression (LDSC) to discover factors underlying genetic covariance, which we are denoting genetically informed brain networks (GIBNs). Genomic SEM can fit a multivariate GWAS from summary statistics for each of the GIBNs, which can subsequently be used for LD score regression (LDSC). We found the best-fitting model of cortical SA identified 6 GIBNs and CT identified 4 GIBNs. The multivariate GWASs of these GIBNs identified 74 genome-wide significant (GWS) loci (p<5×10-8), including many previously implicated in neuroimaging phenotypes, behavioral traits, and psychiatric conditions. LDSC of GIBN GWASs found that SA-derived GIBNs had a positive genetic correlation with bipolar disorder (BPD), and cannabis use disorder, indicating genetic predisposition to a larger SA in the specific GIBN is associated with greater genetic risk of these disorders. A negative genetic correlation was observed with attention deficit hyperactivity disorder (ADHD), major depressive disorder (MDD), and insomnia, indicating genetic predisposition to a larger SA in the specific GIBN is associated with lower genetic risk of these disorders. CT GIBNs displayed a negative genetic correlation with alcohol dependence. Jointly modeling the genetic architecture of complex traits and investigating multivariate genetic links across phenotypes offers a new vantage point for mapping the cortex into genetically informed networks.

Pleiotropic Association of CACNA1C Variants With Neuropsychiatric Disorders

BACKGROUND

Neuropsychiatric disorders are highly heritable and have overlapping genetic underpinnings. Single nucleotide polymorphisms (SNPs) in the gene CACNA1C have been associated with several neuropsychiatric disorders, across multiple genome-wide association studies.

METHOD

A total of 70,711 subjects from 37 independent cohorts with 13 different neuropsychiatric disorders were meta-analyzed to identify overlap of disorder-associated SNPs within CACNA1C. The differential expression of CACNA1C mRNA in five independent postmortem brain cohorts was examined. Finally, the associations of disease-sharing risk alleles with total intracranial volume (ICV), gray matter volumes (GMVs) of subcortical structures, cortical surface area (SA), and average cortical thickness (TH) were tested.

RESULTS

Eighteen SNPs within CACNA1C were nominally associated with more than one neuropsychiatric disorder (P < .05); the associations shared among schizophrenia, bipolar disorder, and alcohol use disorder survived false discovery rate correction (five SNPs with P < 7.3 × 10-4 and q < 0.05). CACNA1C mRNA was differentially expressed in brains from individuals with schizophrenia, bipolar disorder, and Parkinson's disease, relative to controls (three SNPs with P < .01). Risk alleles shared by schizophrenia, bipolar disorder, substance dependence, and Parkinson's disease were significantly associated with ICV, GMVs, SA, or TH (one SNP with P ≤ 7.1 × 10-3 and q < 0.05).

CONCLUSION

Integrating multiple levels of analyses, we identified CACNA1C variants associated with multiple psychiatric disorders, and schizophrenia and bipolar disorder were most strongly implicated. CACNA1C variants may contribute to shared risk and pathophysiology in these conditions.

Uncovering Diverse Mechanistic Spreading Pathways in Disease Progression of Alzheimer's Disease

Background

The AT[N] research framework focuses on three major biomarkers in Alzheimer's disease (AD): amyloid-β deposition (A), pathologic tau (T), and neurodegeneration [N].

Objective

We hypothesize that the diverse mechanisms such as A⟶T and A⟶[N] pathways from one brain region to others, may underlie the wide variation in clinical symptoms. We aim to uncover the causal-like effect of regional AT[N] biomarkers on cognitive decline as well as the interaction with non-modifiable risk factors such as age and APOE4.

Methods

We apply multi-variate statistical inference to uncover all possible mechanistic spreading pathways through which the aggregation of an upstream biomarker (e.g., increased amyloid level) in a particular brain region indirectly impacts cognitive decline, via the cascade build-up of a downstream biomarker (e.g., reduced metabolism level) in another brain region. Furthermore, we investigate the survival time for each identified region-to-region pathological pathway toward the AD onset.

Results

We have identified a collection of critical brain regions on which the amyloid burdens exert an indirect effect on the decline in memory and executive function (EF) domain, being mediated by the reduction of metabolism level at other brain regions. APOE4 status has been found not only involved in many A⟶N mechanistic pathways but also significantly contributes to the risk of developing AD.

Conclusion

Our major findings include 1) the region-to-region A⟶N⟶MEM and A⟶N⟶MEM pathways exhibit distinct spatial patterns; 2) APOE4 is significantly associated with both direct and indirect effects on the cognitive decline while sex difference has not been identified in the mediation analysis.

Causal associations of brain structure with bone mineral density: a large-scale genetic correlation study

In this study, we aimed to investigate the causal associations of brain structure with bone mineral density (BMD). Based on the genome-wide association study (GWAS) summary statistics of 1 325 brain imaging-derived phenotypes (BIDPs) of brain structure from the UK Biobank and GWAS summary datasets of 5 BMD locations, including the total body, femoral neck, lumbar spine, forearm, and heel from the GEFOS Consortium, linkage disequilibrium score regression (LDSC) was conducted to determine the genetic correlations, and Mendelian randomization (MR) was then performed to explore the causal relationship between the BIDPs and BMD. Several sensitivity analyses were performed to verify the strength and stability of the present MR outcomes. To increase confidence in our findings, we also performed confirmatory MR between BIDPs and osteoporosis. LDSC revealed that 1.93% of BIDPs, with a false discovery rate (FDR) < 0.01, were genetically correlated with BMD. Additionally, we observed that 1.31% of BIDPs exhibited a significant causal relationship with BMD (FDR < 0.01) through MR. Both the LDSC and MR results demonstrated that the BIDPs "Volume of normalized brain," "Volume of gray matter in Left Inferior Frontal Gyrus, pars opercularis," "Volume of Estimated Total Intra Cranial" and "Volume-ratio of brain segmentation/estimated total intracranial" had strong associations with BMD. Interestingly, our results showed that more left BIDPs were causally associated with BMD, especially within and around the left frontal region. In conclusion, a part of the brain structure causally influences BMD, which may provide important perspectives for the prevention of osteoporosis and offer valuable insights for further research on the brain-bone axis.

Genetic Influences on the Developing Young Brain and Risk for Neuropsychiatric Disorders

Imaging genetics provides an opportunity to discern associations between genetic variants and brain imaging phenotypes. Historically, the field has focused on adults and adolescents; very few imaging genetics studies have focused on brain development in infancy and early childhood (from birth to age 6 years). This is an important knowledge gap because developmental changes in the brain during the prenatal and early postnatal period are regulated by dynamic gene expression patterns that likely play an important role in establishing an individual's risk for later psychiatric illness and neurodevelopmental disabilities. In this review, we summarize findings from imaging genetics studies spanning from early infancy to early childhood, with a focus on studies examining genetic risk for neuropsychiatric disorders. We also introduce the Organization for Imaging Genomics in Infancy (ORIGINs), a working group of the ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) consortium, which was established to facilitate large-scale imaging genetics studies in infancy and early childhood.

Brain structure and allelic associations in Alzheimer's disease

BACKGROUND

Alzheimer's disease (AD), the most prevalent form of dementia, affects 6.5 million Americans and over 50 million people globally. Clinical, genetic, and phenotypic studies of dementia provide some insights of the observed progressive neurodegenerative processes, however, the mechanisms underlying AD onset remain enigmatic.

AIMS

This paper examines late-onset dementia-related cognitive impairment utilizing neuroimaging-genetics biomarker associations.

MATERIALS AND METHODS

The participants, ages 65-85, included 266 healthy controls (HC), 572 volunteers with mild cognitive impairment (MCI), and 188 Alzheimer's disease (AD) patients. Genotype dosage data for AD-associated single nucleotide polymorphisms (SNPs) were extracted from the imputed ADNI genetics archive using sample-major additive coding. Such 29 SNPs were selected, representing a subset of independent SNPs reported to be highly associated with AD in a recent AD meta-GWAS study by Jansen and colleagues.

RESULTS

We identified the significant correlations between the 29 genomic markers (GMs) and the 200 neuroimaging markers (NIMs). The odds ratios and relative risks for AD and MCI (relative to HC) were predicted using multinomial linear models.

DISCUSSION

In the HC and MCI cohorts, mainly cortical thickness measures were associated with GMs, whereas the AD cohort exhibited different GM-NIM relations. Network patterns within the HC and AD groups were distinct in cortical thickness, volume, and proportion of White to Gray Matter (pct), but not in the MCI cohort. Multinomial linear models of clinical diagnosis showed precisely the specific NIMs and GMs that were most impactful in discriminating between AD and HC, and between MCI and HC.

CONCLUSION

This study suggests that advanced analytics provide mechanisms for exploring the interrelations between morphometric indicators and GMs. The findings may facilitate further clinical investigations of phenotypic associations that support deep systematic understanding of AD pathogenesis.

Autism spectrum disorder and brain volume link through a set of mTOR-related genes

BACKGROUND

Larger than average head and brain sizes are often observed in individuals with autism spectrum disorders (ASDs). ASD and brain volume are both highly heritable, with multiple genetic variants contributing. However, it is unclear whether ASD and brain volume share any genetic mechanisms. Genes from the mammalian target of rapamycin (mTOR) pathway influence brain volume, and variants are found in rare genetic syndromes that include ASD features. Here we investigated whether variants in mTOR-related genes are also associated with ASD and if they constitute a genetic link between large brains and ASD.

METHODS

We extended our analyses between large heads (macrocephaly) and rare de novo mTOR-related variants in an intellectual disability cohort (N = 2,258). Subsequently using Fisher's exact tests we investigated the co-occurrence of mTOR-related de novo variants and ASD in the de-novo-db database (N = 23,098). We next selected common genetic variants within a set of 96 mTOR-related genes in genome-wide genetic association data of ASD (N = 46,350) to test gene-set association using MAGMA. Lastly, we tested genetic correlation between genome-wide genetic association data of ASD (N = 46,350) and intracranial volume (N = 25,974) globally using linkage disequilibrium score regression as well as mTOR specific by restricting the genetic correlation to the mTOR-related genes using GNOVA.

RESULTS

Our results show that both macrocephaly and ASD occur above chance level in individuals carrying rare de novo variants in mTOR-related genes. We found a significant mTOR gene-set association with ASD (p = .0029) and an mTOR-stratified positive genetic correlation between ASD and intracranial volume (p = .027), despite the absence of a significant genome-wide correlation (p = .81).

CONCLUSIONS

This work indicates that both rare and common variants in mTOR-related genes are associated with brain volume and ASD and genetically correlate them in the expected direction. We demonstrate that genes involved in mTOR signalling are potential mediators of the relationship between having a large brain and having ASD.

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.

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.

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.

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.

A comparison of intracranial volume estimation methods and their cross-sectional and longitudinal associations with age

Intracranial volume (ICV) is frequently used in volumetric magnetic resonance imaging (MRI) studies, both as a covariate and as a variable of interest. Findings of associations between ICV and age have varied, potentially due to differences in ICV estimation methods. Here, we compared five commonly used ICV estimation methods and their associations with age. T1-weighted cross-sectional MRI data was included for 651 healthy individuals recruited through the NORMENT Centre (mean age = 46.1 years, range = 12.0-85.8 years) and 2410 healthy individuals recruited through the UK Biobank study (UKB, mean age = 63.2 years, range = 47.0-80.3 years), where longitudinal data was also available. ICV was estimated with FreeSurfer (eTIV and sbTIV), SPM12, CAT12, and FSL. We found overall high correlations across ICV estimation method, with the lowest observed correlations between FSL and eTIV (r = .87) and between FSL and CAT12 (r = .89). Widespread proportional bias was found, indicating that the agreement between methods varied as a function of head size. Body weight, age, sex, and mean ICV across methods explained the most variance in the differences between ICV estimation methods, indicating possible confounding for some estimation methods. We found both positive and negative cross-sectional associations with age, depending on dataset and ICV estimation method. Longitudinal ICV reductions were found for all ICV estimation methods, with annual percentage change ranging from -0.293% to -0.416%. This convergence of longitudinal results across ICV estimation methods offers strong evidence for age-related ICV reductions in mid- to late adulthood.

Genetic map of regional sulcal morphology in the human brain from UK biobank data

Genetic associations with macroscopic brain structure can provide insights into brain function and disease. However, specific associations with measures of local brain folding are largely under-explored. Here, we conducted large-scale genome- and exome-wide associations of regional cortical sulcal measures derived from magnetic resonance imaging scans of 40,169 individuals in UK Biobank. We discovered 388 regional brain folding associations across 77 genetic loci, with genes in associated loci enriched for expression in the cerebral cortex, neuronal development processes, and differential regulation during early brain development. We integrated brain eQTLs to refine genes for various loci, implicated several genes involved in neurodevelopmental disorders, and highlighted global genetic correlations with neuropsychiatric phenotypes. We provide an interactive 3D visualisation of our summary associations, emphasising added resolution of regional analyses. Our results offer new insights into the genetic architecture of brain folding and provide a resource for future studies of sulcal morphology in health and disease.

Is intracranial volume a risk factor for IDH-mutant low-grade glioma? A case-control study

Purpose

Risk of cancer has been associated with body or organ size in several studies. We sought to investigate the relationship between intracranial volume (ICV) (as a proxy for lifetime maximum brain size) and risk of IDH-mutant low-grade glioma.

Methods

In a multicenter case–control study based on population-based data, we included 154 patients with IDH-mutant WHO grade 2 glioma and 995 healthy controls. ICV in both groups was calculated from 3D MRI brain scans using an automated reverse brain mask method, and then compared using a binomial logistic regression model.

Results

We found a non-linear association between ICV and risk of glioma with increasing risk above and below a threshold of 1394 ml (p < 0.001). After adjusting for ICV, sex was not a risk factor for glioma.

Conclusion

Intracranial volume may be a risk factor for IDH-mutant low-grade glioma, but the relationship seems to be non-linear with increased risk both above and below a threshold in intracranial volume.

Nomograms of human hippocampal volume shifted by polygenic scores

Nomograms are important clinical tools applied widely in both developing and aging populations. They are generally constructed as normative models identifying cases as outliers to a distribution of healthy controls. Currently used normative models do not account for genetic heterogeneity. Hippocampal volume (HV) is a key endophenotype for many brain disorders. Here, we examine the impact of genetic adjustment on HV nomograms and the translational ability to detect dementia patients. Using imaging data from 35,686 healthy subjects aged 44-82 from the UK Biobank (UKB), we built HV nomograms using Gaussian process regression (GPR), which - compared to a previous method - extended the application age by 20 years, including dementia critical age ranges. Using HV polygenic scores (HV-PGS), we built genetically adjusted nomograms from participants stratified into the top and bottom 30% of HV-PGS. This shifted the nomograms in the expected directions by ~100 mm3 (2.3% of the average HV), which equates to 3 years of normal aging for a person aged ~65. Clinical impact of genetically adjusted nomograms was investigated by comparing 818 subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database diagnosed as either cognitively normal (CN), having mild cognitive impairment (MCI) or Alzheimer's disease (AD) patients. While no significant change in the survival analysis was found for MCI-to-AD conversion, an average of 68% relative decrease was found in intra-diagnostic-group variance, highlighting the importance of genetic adjustment in untangling phenotypic heterogeneity.

Genomic architecture and functional effects of potential human inversion supergenes

Supergenes are involved in adaptation in multiple organisms, but they are little known in humans. Genomic inversions are the most common mechanism of supergene generation and maintenance. Here, we review the information about two large inversions that are the best examples of potential human supergenes. In addition, we do an integrative analysis of the newest data to understand better their functional effects and underlying genetic changes. We have found that the highly divergent haplotypes of the 17q21.31 inversion of approximately 1.5 Mb have multiple phenotypic associations, with consistent effects in brain-related traits, red and white blood cells, lung function, male and female characteristics and disease risk. By combining gene expression and nucleotide variation data, we also analysed the molecular differences between haplotypes, including gene duplications, amino acid substitutions and regulatory changes, and identify CRHR1, KANLS1 and MAPT as good candidates to be responsible for these phenotypes. The situation is more complex for the 8p23.1 inversion, where there is no clear genetic differentiation. However, the inversion is associated with several related phenotypes and gene expression differences that could be linked to haplotypes specific of one orientation. Our work, therefore, contributes to the characterization of both exceptional variants and illustrates the important role of inversions. This article is part of the theme issue 'Genomic architecture of supergenes: causes and evolutionary consequences'.

Are Brain and Cognitive Reserve Shaped by Early Life Circumstances?

When growing older, many people are faced with cognitive deterioration, which may even amount to a form of dementia at some point in time. Although neuropathological signs of dementia disorders can often be demonstrated in brains of patients, the degree to which clinical symptoms are present does mostly not accurately reflect the amount of neuropathology that is present. Sometimes existent pathology even goes without any obvious clinical presentation. An explanation for this phenomenon may be found in the concept of reserve capacity. Reserve capacity refers to the ability of the brain to effectively buffer changes that are associated with normal aging processes and to cope with pathological damage. A larger reserve capacity has been suggested to increase resilience against age-associated cognitive deterioration and dementia disorders. Traditionally, a division has been made between brain reserve, which is based on morphological characteristics of the brain, and cognitive reserve, which is based on functional characteristics of the brain. The present review discusses the premises that brain and cognitive reserve capacity are shaped by prenatal and early postnatal factors. Evidence is accumulating that circumstances during the first 1,000 days of life are of the utmost importance for the lifelong health of an individual. Cognitive deterioration and dementia disorders may also have their origin in early life and a potentially important pathway by which the early environment affects the risk for neurodegenerative diseases is by developmental programming of the reserve capacity of the brain. The basic idea behind developmental programming of brain and cognitive reserve is explained and an overview of studies that support this idea is presented. The review is concluded by a discussion of potential mechanisms, synthesis of the evidence and relevance and future directions in the field of developmental origins of reserve capacity.

Genetics of early-life head circumference and genetic correlations with neurological, psychiatric and cognitive outcomes

BACKGROUND

Head circumference is associated with intelligence and tracks from childhood into adulthood.

METHODS

We performed a genome-wide association study meta-analysis and follow-up of head circumference in a total of 29,192 participants between 6 and 30 months of age.

RESULTS

Seven loci reached genome-wide significance in the combined discovery and replication analysis of which three loci near ARFGEF2, MYCL1, and TOP1, were novel. We observed positive genetic correlations for early-life head circumference with adult intracranial volume, years of schooling, childhood and adult intelligence, but not with adult psychiatric, neurological, or personality-related phenotypes.

CONCLUSIONS

The results of this study indicate that the biological processes underlying early-life head circumference overlap largely with those of adult head circumference. The associations of early-life head circumference with cognitive outcomes across the life course are partly explained by genetics.

Meta-analysis of genome-wide association studies identifies ancestry-specific associations underlying circulating total tau levels

Circulating total-tau levels can be used as an endophenotype to identify genetic risk factors for tauopathies and related neurological disorders. Here, we confirmed and better characterized the association of the 17q21 MAPT locus with circulating total-tau in 14,721 European participants and identified three novel loci in 953 African American participants (4q31, 5p13, and 6q25) at P < 5 × 10-8. We additionally detected 14 novel loci at P < 5 × 10-7, specific to either Europeans or African Americans. Using whole-exome sequence data in 2,279 European participants, we identified ten genes associated with circulating total-tau when aggregating rare variants. Our genetic study sheds light on genes reported to be associated with neurological diseases including stroke, Alzheimer's, and Parkinson's (F5, MAP1B, and BCAS3), with Alzheimer's pathological hallmarks (ADAMTS12, IL15, and FHIT), or with an important function in the brain (PARD3, ELFN2, UBASH3B, SLIT3, and NSD3), and suggests that the genetic architecture of circulating total-tau may differ according to ancestry.

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.

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.

What we learn about bipolar disorder from large-scale neuroimaging: Findings and future directions from the ENIGMA Bipolar Disorder Working Group

MRI-derived brain measures offer a link between genes, the environment and behavior and have been widely studied in bipolar disorder (BD). However, many neuroimaging studies of BD have been underpowered, leading to varied results and uncertainty regarding effects. The Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) Bipolar Disorder Working Group was formed in 2012 to empower discoveries, generate consensus findings and inform future hypothesis-driven studies of BD. Through this effort, over 150 researchers from 20 countries and 55 institutions pool data and resources to produce the largest neuroimaging studies of BD ever conducted. The ENIGMA Bipolar Disorder Working Group applies standardized processing and analysis techniques to empower large-scale meta- and mega-analyses of multimodal brain MRI and improve the replicability of studies relating brain variation to clinical and genetic data. Initial BD Working Group studies reveal widespread patterns of lower cortical thickness, subcortical volume and disrupted white matter integrity associated with BD. Findings also include mapping brain alterations of common medications like lithium, symptom patterns and clinical risk profiles and have provided further insights into the pathophysiological mechanisms of BD. Here we discuss key findings from the BD working group, its ongoing projects and future directions for large-scale, collaborative studies of mental illness.

Enhancing neuroimaging genetics through meta-analysis for Tourette syndrome (ENIGMA-TS): A worldwide platform for collaboration

Tourette syndrome (TS) is characterized by multiple motor and vocal tics, and high-comorbidity rates with other neuropsychiatric disorders. Obsessive compulsive disorder (OCD), attention deficit hyperactivity disorder (ADHD), autism spectrum disorders (ASDs), major depressive disorder (MDD), and anxiety disorders (AXDs) are among the most prevalent TS comorbidities. To date, studies on TS brain structure and function have been limited in size with efforts mostly fragmented. This leads to low-statistical power, discordant results due to differences in approaches, and hinders the ability to stratify patients according to clinical parameters and investigate comorbidity patterns. Here, we present the scientific premise, perspectives, and key goals that have motivated the establishment of the Enhancing Neuroimaging Genetics through Meta-Analysis for TS (ENIGMA-TS) working group. The ENIGMA-TS working group is an international collaborative effort bringing together a large network of investigators who aim to understand brain structure and function in TS and dissect the underlying neurobiology that leads to observed comorbidity patterns and clinical heterogeneity. Previously collected TS neuroimaging data will be analyzed jointly and integrated with TS genomic data, as well as equivalently large and already existing studies of highly comorbid OCD, ADHD, ASD, MDD, and AXD. Our work highlights the power of collaborative efforts and transdiagnostic approaches, and points to the existence of different TS subtypes. ENIGMA-TS will offer large-scale, high-powered studies that will lead to important insights toward understanding brain structure and function and genetic effects in TS and related disorders, and the identification of biomarkers that could help inform improved clinical practice.

Effects of copy number variations on brain structure and risk for psychiatric illness: Large-scale studies from the ENIGMA working groups on CNVs

The Enhancing NeuroImaging Genetics through Meta-Analysis copy number variant (ENIGMA-CNV) and 22q11.2 Deletion Syndrome Working Groups (22q-ENIGMA WGs) were created to gain insight into the involvement of genetic factors in human brain development and related cognitive, psychiatric and behavioral manifestations. To that end, the ENIGMA-CNV WG has collated CNV and magnetic resonance imaging (MRI) data from ~49,000 individuals across 38 global research sites, yielding one of the largest studies to date on the effects of CNVs on brain structures in the general population. The 22q-ENIGMA WG includes 12 international research centers that assessed over 533 individuals with a confirmed 22q11.2 deletion syndrome, 40 with 22q11.2 duplications, and 333 typically developing controls, creating the largest-ever 22q11.2 CNV neuroimaging data set. In this review, we outline the ENIGMA infrastructure and procedures for multi-site analysis of CNVs and MRI data. So far, ENIGMA has identified effects of the 22q11.2, 16p11.2 distal, 15q11.2, and 1q21.1 distal CNVs on subcortical and cortical brain structures. Each CNV is associated with differences in cognitive, neurodevelopmental and neuropsychiatric traits, with characteristic patterns of brain structural abnormalities. Evidence of gene-dosage effects on distinct brain regions also emerged, providing further insight into genotype-phenotype relationships. Taken together, these results offer a more comprehensive picture of molecular mechanisms involved in typical and atypical brain development. This "genotype-first" approach also contributes to our understanding of the etiopathogenesis of brain disorders. Finally, we outline future directions to better understand effects of CNVs on brain structure and behavior.

Consortium neuroscience of attention deficit/hyperactivity disorder and autism spectrum disorder: The ENIGMA adventure

Neuroimaging has been extensively used to study brain structure and function in individuals with attention deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) over the past decades. Two of the main shortcomings of the neuroimaging literature of these disorders are the small sample sizes employed and the heterogeneity of methods used. In 2013 and 2014, the ENIGMA-ADHD and ENIGMA-ASD working groups were respectively, founded with a common goal to address these limitations. Here, we provide a narrative review of the thus far completed and still ongoing projects of these working groups. Due to an implicitly hierarchical psychiatric diagnostic classification system, the fields of ADHD and ASD have developed largely in isolation, despite the considerable overlap in the occurrence of the disorders. The collaboration between the ENIGMA-ADHD and -ASD working groups seeks to bring the neuroimaging efforts of the two disorders closer together. The outcomes of case-control studies of subcortical and cortical structures showed that subcortical volumes are similarly affected in ASD and ADHD, albeit with small effect sizes. Cortical analyses identified unique differences in each disorder, but also considerable overlap between the two, specifically in cortical thickness. Ongoing work is examining alternative research questions, such as brain laterality, prediction of case-control status, and anatomical heterogeneity. In brief, great strides have been made toward fulfilling the aims of the ENIGMA collaborations, while new ideas and follow-up analyses continue that include more imaging modalities (diffusion MRI and resting-state functional MRI), collaborations with other large databases, and samples with dual diagnoses.

Evaluating brain structure traits as endophenotypes using polygenicity and discoverability

Human brain structure traits have been hypothesized to be broad endophenotypes for neuropsychiatric disorders, implying that brain structure traits are comparatively "closer to the underlying biology." Genome-wide association studies from large sample sizes allow for the comparison of common variant genetic architectures between traits to test the evidence supporting this claim. Endophenotypes, compared to neuropsychiatric disorders, are hypothesized to have less polygenicity, with greater effect size of each susceptible SNP, requiring smaller sample sizes to discover them. Here, we compare polygenicity and discoverability of brain structure traits, neuropsychiatric disorders, and other traits (91 in total) to directly test this hypothesis. We found reduced polygenicity (FDR = 0.01) and increased discoverability (FDR = 3.68 × 10-9 ) of cortical brain structure traits, as compared to aggregated estimates of multiple neuropsychiatric disorders. We predict that ~8 M individuals will be required to explain the full heritability of cortical surface area by genome-wide significant SNPs, whereas sample sizes over 20 M will be required to explain the full heritability of depression. In conclusion, our findings are consistent with brain structure satisfying the higher power criterion of endophenotypes.

Intracranial and subcortical volumes in adolescents with early-onset psychosis: A multisite mega-analysis from the ENIGMA consortium

Early-onset psychosis disorders are serious mental disorders arising before the age of 18 years. Here, we investigate the largest neuroimaging dataset, to date, of patients with early-onset psychosis and healthy controls for differences in intracranial and subcortical brain volumes. The sample included 263 patients with early-onset psychosis (mean age: 16.4 ± 1.4 years, mean illness duration: 1.5 ± 1.4 years, 39.2% female) and 359 healthy controls (mean age: 15.9 ± 1.7 years, 45.4% female) with magnetic resonance imaging data, pooled from 11 clinical cohorts. Patients were diagnosed with early-onset schizophrenia (n = 183), affective psychosis (n = 39), or other psychotic disorders (n = 41). We used linear mixed-effects models to investigate differences in intracranial and subcortical volumes across the patient sample, diagnostic subgroup and antipsychotic medication, relative to controls. We observed significantly lower intracranial (Cohen's d = -0.39) and hippocampal (d = -0.25) volumes, and higher caudate (d = 0.25) and pallidum (d = 0.24) volumes in patients relative to controls. Intracranial volume was lower in both early-onset schizophrenia (d = -0.34) and affective psychosis (d = -0.42), and early-onset schizophrenia showed lower hippocampal (d = -0.24) and higher pallidum (d = 0.29) volumes. Patients who were currently treated with antipsychotic medication (n = 193) had significantly lower intracranial volume (d = -0.42). The findings demonstrate a similar pattern of brain alterations in early-onset psychosis as previously reported in adult psychosis, but with notably low intracranial volume. The low intracranial volume suggests disrupted neurodevelopment in adolescent early-onset psychosis.

Thirty novel sequence variants impacting human intracranial volume

Intracranial volume, measured through magnetic resonance imaging and/or estimated from head circumference, is heritable and correlates with cognitive traits and several neurological disorders. We performed a genome-wide association study meta-analysis of intracranial volume (n = 79 174) and found 64 associating sequence variants explaining 5.0% of its variance. We used coding variation, transcript and protein levels, to uncover 12 genes likely mediating the effect of these variants, including GLI3 and CDK6 that affect cranial synostosis and microcephaly, respectively. Intracranial volume correlates genetically with volumes of cortical and sub-cortical regions, cognition, learning, neonatal and neurological traits. Parkinson's disease cases have greater and attention deficit hyperactivity disorder cases smaller intracranial volume than controls. Our Mendelian randomization studies indicate that intracranial volume associated variants either increase the risk of Parkinson's disease and decrease the risk of attention deficit hyperactivity disorder and neuroticism or correlate closely with a confounder.

A Positively Selected MAGEE2 LoF Allele Is Associated with Sexual Dimorphism in Human Brain Size and Shows Similar Phenotypes in Magee2 Null Mice

A nonsense allele at rs1343879 in human MAGEE2 on chromosome X has previously been reported as a strong candidate for positive selection in East Asia. This premature stop codon causing ∼80% protein truncation is characterized by a striking geographical pattern of high population differentiation: common in Asia and the Americas (up to 84% in the 1000 Genomes Project East Asians) but rare elsewhere. Here, we generated a Magee2 mouse knockout mimicking the human loss-of-function mutation to study its functional consequences. The Magee2 null mice did not exhibit gross abnormalities apart from enlarged brain structures (13% increased total brain area, P = 0.0022) in hemizygous males. The area of the granular retrosplenial cortex responsible for memory, navigation, and spatial information processing was the most severely affected, exhibiting an enlargement of 34% (P = 3.4×10-6). The brain size in homozygous females showed the opposite trend of reduced brain size, although this did not reach statistical significance. With these insights, we performed human association analyses between brain size measurements and rs1343879 genotypes in 141 Chinese volunteers with brain MRI scans, replicating the sexual dimorphism seen in the knockout mouse model. The derived stop gain allele was significantly associated with a larger volume of gray matter in males (P = 0.00094), and smaller volumes of gray (P = 0.00021) and white (P = 0.0015) matter in females. It is unclear whether or not the observed neuroanatomical phenotypes affect behavior or cognition, but it might have been the driving force underlying the positive selection in humans.

Between-Group Mean Differences in Intelligence in the United States Are >0% Genetically Caused: Five Converging Lines of Evidence

The past 30 years of research in intelligence has produced a wealth of knowledge about the causes and consequences of differences in intelligence between individuals, and today mainstream opinion is that individual differences in intelligence are caused by both genetic and environmental influences. Much more contentious is the discussion over the cause of mean intelligence differences between racial or ethnic groups. In contrast to the general consensus that interindividual differences are both genetic and environmental in origin, some claim that mean intelligence differences between racial groups are completely environmental in origin, whereas others postulate a mix of genetic and environmental causes. In this article I discuss 5 lines of research that provide evidence that mean differences in intelligence between racial and ethnic groups are partially genetic. These lines of evidence are findings in support of Spearman’s hypothesis, consistent results from tests of measurement invariance across American racial groups, the mathematical relationship that exists for between-group and within-group sources of heritability, genomic data derived from genome-wide association studies of intelligence and polygenic scores applied to diverse samples, and admixture studies. I also discuss future potential lines of evidence regarding the causes of average group differences across racial groups. However, the data are not fully conclusive, and the exact degree to which genes influence intergroup mean differences in intelligence is not known. This discussion applies only to native English speakers born in the United States and not necessarily to any other human populations.

Patterns of Fetal and Infant Growth and Brain Morphology at Age 10 Years

IMPORTANCE

Preterm birth and low birth weight are associated with brain developmental and neurocognitive outcomes in childhood; however, not much is known about the specific critical periods in fetal life and infancy for these outcomes.

OBJECTIVE

To examine the associations of fetal and infant growth patterns with brain morphology in children at school age.

DESIGN, SETTING, AND PARTICIPANTS

This population-based, prospective cohort study was conducted from February 1 to April 16, 2021, as a part of the Generation R Study in Rotterdam, the Netherlands. The study included 3098 singleton children born between April 1, 2002, and January 31, 2006.

EXPOSURES

Fetal weight was estimated in the second and third trimesters of pregnancy by ultrasonography. Infant weight was measured at birth and at 6, 12, and 24 months. Fetal and infant weight acceleration or deceleration were defined as a change in SD scores greater than 0.67 between time points. Infant measurements also included peak weight velocity, and age and body mass index reached at adiposity peak.

MAIN OUTCOMES AND MEASURES

Brain structure, including global and regional brain volumes, was quantified by magnetic resonance imaging at age 10 years.

RESULTS

The study evaluated 3098 children (mean [SD] age at follow-up, 10.1 [0.6] years; 1557 girls [50.3%]; and 1753 Dutch [57.8%]). One SD score-higher weight gain until the second and third trimesters, birth, and 6, 12, and 24 months was associated with larger total brain volume independently of growth during any other age windows (second trimester: 5.7 cm3; 95% CI, 1.2-10.2 cm3; third trimester: 15.3 cm3; 95% CI, 11.0-19.6 cm3; birth: 20.8 cm3; 95% CI, 16.4-25.1 cm3; 6 months: 15.6 cm3; 95% CI, 11.2-19.9 cm3; 12 months: 11.3 cm3; 95% CI, 7.0-15.6 cm3; and 24 months: 11.1 cm3; 95% CI, 6.8-15.4 cm3). Compared with children with normal fetal and infant growth, those with fetal and infant growth deceleration had the smallest total brain volume (-32.5 cm3; 95% CI, -53.2 to -11.9 cm3). Children with fetal weight deceleration followed by infant catch-up growth had similar brain volumes as children with normal growth. Higher peak weight velocity and body mass index reached at adiposity peak were associated with larger brain volumes. Similar results were observed for cerebral and cerebellar gray and white matter volumes.

CONCLUSIONS AND RELEVANCE

This cohort study's findings suggest that both fetal and infant weight growth might be critical for cerebral and cerebellar brain volumes during childhood. Whether these associations link to neurocognitive outcomes should be further studied.

Twin studies to GWAS: there and back again

The field of human behavioral genetics has come full circle. It began by using twin/family studies to estimate the relative importance of genetic and environmental influences. As large-scale genotyping became cost-effective, genome-wide association studies (GWASs) yielded insights about the nature of genetic influences and new methods that use GWAS data to estimate heritability and genetic correlations invigorated the field. Yet these newer GWAS methods have not replaced twin/family studies. In this review, we discuss the strengths and weaknesses of the two approaches with respect to characterizing genetic and environmental influences, measurement of behavioral phenotypes, and evaluation of causal models, with a particular focus on cognitive neuroscience. This discussion highlights how twin/family studies and GWAS complement and mutually reinforce one another.

Genomics and proteomics combined analysis revealed the toxicity response of silkworm Bombyx mori to the environmental pathogen Bacillus cereus ZJ-4

Bacterial contamination has caused a major public health problem worldwide. Bacillus cereus is a conditional environmental pathogenic bacteria that can cause food poisoning. Whether environmental pathogens can cause widespread transmission in the insect kingdom is unclear. In this study, a Bacillus cereus ZJ-4 was isolated from the hospital environment of Zhenjiang City, Jiangsu Province, China. It was fatal by injection into the silkworm hemolymph. To investigated the potential toxic factors of ZJ-4 and clarified the toxicity response mechanism of silkworm by the ZJ-4 infection. Then, the whole genome of ZJ-4 was sequenced, and the immune mechanism of silkworm fat body to ZJ-4 pathogen was studied by HE pathological section and proteomics. Bacterial genome sequencing indicated that ZJ-4 had 352 drug resistance genes and 6 virulence genes. After 36 h of subcutaneous puncture with ZJ-4 suspension, the pathological changes were obviously found in HE pathological sections of fat body tissue. Comparative proteomic results indicated that differentially expressed proteins are mainly involved in stress reactions, biological regulation, and innate immunity. The qRT-PCR analysis showed that the expressions of β-GRP, Spaetzle, MyD88, Tube and Dorsal genes in Toll pathway were up-regulated, while Pell and Cactus genes were down-regulated; in the antimicrobial peptide pathway, Glv2, Lzm, Mor, and Leb3 genes were up-regulated, while attacin1 and defensin genes were down-regulated; Sod gene was up-regulated, while Cat gene was down-regulated in the antioxidant pathway; Ldh, Sdh, and Mdh genes were down-regulated in glucose metabolism pathway. These results indicated that ZJ-4 can damage the innate immune pathway of silkworm, and also affect the normal immune function of fat body cells.