Publications

Abstract

Language is supported by a distributed network of brain regions with a particular contribution from the left hemisphere. A multi-level understanding of this network requires studying the genetic architecture of its functional connectivity and hemispheric asymmetry. We used resting state functional imaging data from 29,681 participants from the UK Biobank to measure functional connectivity between 18 left-hemisphere regions implicated in multimodal sentence-level processing, as well as their homotopic regions in the right-hemisphere, and interhemispheric connections. Multivariate genome-wide association analysis of this total network, based on common genetic variants (with population frequencies above 1%), identified 14 loci associated with network functional connectivity. Three of these loci were also associated with hemispheric differences of intrahemispheric connectivity. Polygenic dispositions to lower language-related abilities, dyslexia and left-handedness were associated with generally reduced leftward asymmetry of functional connectivity, but with some trait- and connection-specific exceptions. Exome-wide association analysis based on rare, protein-altering variants (frequencies < 1%) suggested 7 additional genes. These findings shed new light on the genetic contributions to language network connectivity and its asymmetry based on both common and rare genetic variants, and reveal genetic links to language-related traits and hemispheric dominance for hand preference.

Abstract

Subcortical brain structures are involved in developmental, psychiatric and neurological disorders. Here we performed genome-wide association studies meta-analyses of intracranial and nine subcortical brain volumes (brainstem, caudate nucleus, putamen, hippocampus, globus pallidus, thalamus, nucleus accumbens, amygdala and the ventral diencephalon) in 74,898 participants of European ancestry. We identified 254 independent loci associated with these brain volumes, explaining up to 35% of phenotypic variance. We observed gene expression in specific neural cell types across differentiation time points, including genes involved in intracellular signaling and brain aging-related processes. Polygenic scores for brain volumes showed predictive ability when applied to individuals of diverse ancestries. We observed causal genetic effects of brain volumes with Parkinson’s disease and attention-deficit/hyperactivity disorder. Findings implicate specific gene expression patterns in brain development and genetic variants in comorbid neuropsychiatric disorders, which could point to a brain substrate and region of action for risk genes implicated in brain diseases.

Abstract

Only a small number of studies have assessed structural differences between the two hemispheres during childhood and adolescence. However, the existing findings lack consistency or are restricted to a particular brain region, a specific brain feature, or a relatively narrow age range. Here, we investigated associations between brain asymmetry and age as well as sex in one of the largest pediatric samples to date (n = 4265), aged 1–18 years, scanned at 69 sites participating in the ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) consortium. Our study revealed that significant brain asymmetries already exist in childhood, but their magnitude and direction depend on the brain region examined and the morphometric measurement used (cortical volume or thickness, regional surface area, or subcortical volume). With respect to effects of age, some asymmetries became weaker over time while others became stronger; sometimes they even reversed direction. With respect to sex differences, the total number of regions exhibiting significant asymmetries was larger in females than in males, while the total number of measurements indicating significant asymmetries was larger in males (as we obtained more than one measurement per cortical region). The magnitude of the significant asymmetries was also greater in males. However, effect sizes for both age effects and sex differences were small. Taken together, these findings suggest that cerebral asymmetries are an inherent organizational pattern of the brain that manifests early in life. Overall, brain asymmetry appears to be relatively stable throughout childhood and adolescence, with some differential effects in males and females.

Abstract

Handedness is a manifestation of brain hemispheric specialization. Left-handedness occurs at increased rates in neurodevelopmental disorders. Genome-wide association studies have identified common genetic effects on handedness or brain asymmetry, which mostly involve variants outside protein-coding regions and may affect gene expression. Implicated genes include several that encode tubulins (microtubule components) or microtubule-associated proteins. Here we examine whether left-handedness is also influenced by rare coding variants (frequencies ≤ 1%), using exome data from 38,043 left-handed and 313,271 right-handed individuals from the UK Biobank. The beta-tubulin gene TUBB4B shows exome-wide significant association, with a rate of rare coding variants 2.7 times higher in left-handers than right-handers. The TUBB4B variants are mostly heterozygous missense changes, but include two frameshifts found only in left-handers. Other TUBB4B variants have been linked to sensorineural and/or ciliopathic disorders, but not the variants found here. Among genes previously implicated in autism or schizophrenia by exome screening, DSCAM and FOXP1 show evidence for rare coding variant association with left-handedness. The exome-wide heritability of left-handedness due to rare coding variants was 0.91%. This study reveals a role for rare, protein-altering variants in left-handedness, providing further evidence for the involvement of microtubules and disorder-relevant genes.

Abstract

Dyslexia is a common condition that impacts reading ability. Identifying affected brain networks has been hampered by limited sample sizes of imaging case-control studies. We focused instead on brain structural correlates of genetic disposition to dyslexia in large-scale population data. In over 30,000 adults (UK Biobank), higher polygenic disposition to dyslexia was associated with lower head and brain size, and especially reduced volume and/or altered fiber density in networks involved in motor control, language and vision. However, individual genetic variants disposing to dyslexia often had quite distinct patterns of association with brain structural features. Independent component analysis applied to brain-wide association maps for thousands of dyslexia-disposing genetic variants revealed multiple impact modes on the brain, that corresponded to anatomically distinct areas with their own genomic profiles of association. Polygenic scores for dyslexia-related cognitive and educational measures, as well as attention-deficit/hyperactivity disorder, showed similarities to dyslexia polygenic disposition in terms of brain-wide associations, with microstructure of the internal capsule consistently implicated. In contrast, lower volume of the primary motor cortex was only associated with higher dyslexia polygenic disposition among all traits. These findings robustly reveal heterogeneous neurobiological aspects of dyslexia genetic disposition, and whether they are shared or unique with respect to other genetically correlated traits.

Abstract

The language network of the human brain has core components in the inferior frontal cortex and superior/middle temporal cortex, with left-hemisphere dominance in most people. Functional specialization and interconnectivity of these neocortical regions is likely to be reflected in their molecular and cellular profiles. Excitatory connections between cortical regions arise and innervate according to layer-specific patterns. Here we generated a new gene expression dataset from human postmortem cortical tissue samples from core language network regions, using spatial transcriptomics to discriminate gene expression across cortical layers. Integration of these data with existing single-cell expression data identified 56 genes that showed differences in laminar expression profiles between frontal and temporal language cortex together with upregulation in layer II/III and/or layer V/VI excitatory neurons. Based on data from large-scale genome-wide screening in the population, DNA variants within these 56 genes showed set-level associations with inter-individual variation in structural connectivity between left-hemisphere frontal and temporal language cortex, and with predisposition to dyslexia. The axon guidance genes SLIT1 and SLIT2 were consistently implicated. These findings identify region-specific patterns of laminar gene expression as a feature of the brain’s language network.

Abstract

Intracranial volume reflects the maximally attained brain size during development, and remains stable with loss of tissue in late
life. It is highly heritable, but the underlying genes remain largely undetermined. In a genome-wide association study of 32,438
adults, we discovered five previously unknown loci for intracranial volume and confirmed two known signals. Four of the loci were
also associated with adult human stature, but these remained associated with intracranial volume after adjusting for height.
We found a high genetic correlation with child head circumference (genetic = 0.748), which indicates a similar genetic
background and allowed us to identify four additional loci through meta-analysis (Ncombined = 37,345). Variants for intracranial
volume were also related to childhood and adult cognitive function, and Parkinson’s disease, and were enriched near genes
involved in growth pathways, including PI3K-AKT signaling. These findings identify the biological underpinnings of intracranial
volume and provide genetic support for theories on brain reserve and brain overgrowth.

Abstract

Genome-wide association screens aim to identify common genetic variants contributing to the phenotypic variability of complex traits, such as human height or brain morphology. The identified genetic variants are mostly within noncoding genomic regions and the biology of the genotype–phenotype association typically remains unclear. In this article, we propose a complementary targeted strategy to reveal the genetic underpinnings of variability in subcortical brain volumes, by specifically selecting genomic loci that are experimentally validated forebrain enhancers, active in early embryonic development. We hypothesized that genetic variation within these enhancers may affect the development and ultimately the structure of subcortical brain regions in adults. We tested whether variants in forebrain enhancer regions showed an overall enrichment of association with volumetric variation in subcortical structures of >13,000 healthy adults. We observed significant enrichment of genomic loci that affect the volume of the hippocampus within forebrain enhancers (empirical P = 0.0015), a finding which robustly passed the adjusted threshold for testing of multiple brain phenotypes (cutoff of P < 0.0083 at an alpha of 0.05). In analyses of individual single nucleotide polymorphisms (SNPs), we identified an association upstream of the ID2 gene with rs7588305 and variation in hippocampal volume. This SNP-based association survived multiple-testing correction for the number of SNPs analyzed but not for the number of subcortical structures. Targeting known regulatory regions offers a way to understand the underlying biology that connects genotypes to phenotypes, particularly in the context of neuroimaging genetics. This biology-driven approach generates testable hypotheses regarding the functional biology of identified associations.

Abstract

Recent genome wide association scans (GWAS) for reading and language abilities have pin-pointed promising new candidate loci. However, the potential contributions of these loci remain to be validated. In the present study, we tested 17 of the most significantly associated single nucleotide polymorphisms (SNPs) from these GWAS studies (p < 10−6 in the original studies) in a new independent population dataset from the Netherlands: known as FIOLA (Familial Influences On Literacy Abilities). This dataset comprised 483 children from 307 nuclear families, plus 505 adults (including parents of participating children), and provided adequate statistical power to detect the effects that were previously reported. The following measures of reading and language performance were collected: word reading fluency, nonword reading fluency, phonological awareness, and rapid automatized naming. Two SNPs (rs12636438, rs7187223) were associated with performance in multivariate and univariate testing, but these did not remain significant after correction for multiple testing. Another SNP (rs482700) was only nominally associated in the multivariate test. For the rest of the SNPs we did not find supportive evidence of association. The findings may reflect differences between our study and the previous investigations in respects such as the language of testing, the exact tests used, and the recruitment criteria. Alternatively, most of the prior reported associations may have been false positives. A larger scale GWAS meta-analysis than those previously performed will likely be required to obtain robust insights into the genomic architecture underlying reading and language.

Abstract

Schizophrenia is a devastating psychiatric illness with high heritability. Brain structure and function differ, on average, between people with schizophrenia and healthy individuals. As common genetic associations are emerging for both schizophrenia and brain imaging phenotypes, we can now use genome-wide data to investigate genetic overlap. Here we integrated results from common variant studies of schizophrenia (33,636 cases, 43,008 controls) and volumes of several (mainly subcortical) brain structures (11,840 subjects). We did not find evidence of genetic overlap between schizophrenia risk and subcortical volume measures either at the level of common variant genetic architecture or for single genetic markers. These results provide a proof of concept (albeit based on a limited set of structural brain measures) and define a roadmap for future studies investigating the genetic covariance between structural or functional brain phenotypes and risk for psychiatric disorders

Abstract

Background

Reading and language skills have overlapping genetic bases, most of which are still unknown. Part of the missing heritability may be caused by copy number variants (CNVs).
Methods

In a dataset of children recruited for a history of reading disability (RD, also known as dyslexia) or attention deficit hyperactivity disorder (ADHD) and their siblings, we investigated the effects of CNVs on reading and language performance. First, we called CNVs with PennCNV using signal intensity data from Illumina OmniExpress arrays (~723,000 probes). Then, we computed the correlation between measures of CNV genomic burden and the first principal component (PC) score derived from several continuous reading and language traits, both before and after adjustment for performance IQ. Finally, we screened the genome, probe-by-probe, for association with the PC scores, through two complementary analyses: we tested a binary CNV state assigned for the location of each probe (i.e., CNV+ or CNV−), and we analyzed continuous probe intensity data using FamCNV.
Results

No significant correlation was found between measures of CNV burden and PC scores, and no genome-wide significant associations were detected in probe-by-probe screening. Nominally significant associations were detected (p~10−2–10−3) within CNTN4 (contactin 4) and CTNNA3 (catenin alpha 3). These genes encode cell adhesion molecules with a likely role in neuronal development, and they have been previously implicated in autism and other neurodevelopmental disorders. A further, targeted assessment of candidate CNV regions revealed associations with the PC score (p~0.026–0.045) within CHRNA7 (cholinergic nicotinic receptor alpha 7), which encodes a ligand-gated ion channel and has also been implicated in neurodevelopmental conditions and language impairment. FamCNV analysis detected a region of association (p~10−2–10−4) within a frequent deletion ~6 kb downstream of ZNF737 (zinc finger protein 737, uncharacterized protein), which was also observed in the association analysis using CNV calls.
Conclusions

These data suggest that CNVs do not underlie a substantial proportion of variance in reading and language skills. Analysis of additional, larger datasets is warranted to further assess the potential effects that we found and to increase the power to detect CNV effects on reading and language.

Abstract

Pinpointing genes involved in non-right-handedness has the potential to clarify developmental contributions to human brain lateralization. Major-gene models have been considered for human handedness which allow for phenocopy and reduced penetrance, i.e. an imperfect correspondence between genotype and phenotype. However, a recent genome-wide association scan did not detect any common polymorphisms with substantial genetic effects. Previous linkage studies in families have also not yielded significant findings. Genetic heterogeneity and/or polygenicity are therefore indicated, but it remains possible that relatively rare, or even unique, major-genetic effects may be detectable in certain extended families with many non-right-handed members. Here we applied whole exome sequencing to 17 members from a single, large consanguineous family from Pakistan. Multipoint linkage analysis across all autosomes did not yield clear candidate genomic regions for involvement in the trait and single-point analysis of exomic variation did not yield clear candidate mutations/genes. Any genetic contribution to handedness in this unusual family is therefore likely to have a complex etiology, as at the population level.

Abstract

Genes of the Major Histocompatibility Complex (MHC) have recently been shown to have neuronal functions in the thalamus and hippocampus. Common genetic variants in the Human Leukocyte Antigens (HLA) region, human homologue of the MHC locus, are associated with small effects on susceptibility to schizophrenia, while volumetric changes of the thalamus and hippocampus have also been linked to schizophrenia. We therefore investigated whether common variants of the HLA would affect volumetric variation of the thalamus and hippocampus. We analyzed thalamus and hippocampus volumes, as measured using structural magnetic resonance imaging, in 1.265 healthy participants. These participants had also been genotyped using genome-wide single nucleotide polymorphism (SNP) arrays. We imputed genotypes for single nucleotide polymorphisms at high density across the HLA locus, as well as HLA allotypes and HLA amino acids, by use of a reference population dataset that was specifically targeted to the HLA region. We detected a significant association of the SNP rs17194174 with thalamus volume (nominal P=0.0000017, corrected P=0.0039), as well as additional SNPs within the same region of linkage disequilibrium. This effect was largely lateralized to the left thalamus and is localized within a genomic region previously associated with schizophrenia. The associated SNPs are also clustered within a potential regulatory element, and a region of linkage disequilibrium that spans genes expressed in the thalamus, including HLA-A. Our data indicate that genetic variation within the HLA region influences the volume and asymmetry of the human thalamus. The molecular mechanisms underlying this association may relate to HLA influences on susceptibility to schizophrenia

Abstract

Lateralizations of brain structure and motor behavior have been observed in humans as early as the first trimester of gestation, and are likely to arise from asymmetrical genetic–developmental programs, as in other animals. Studies of gene expression levels in postmortem tissue samples, comparing the left and right sides of the human cerebral cortex, have generally not revealed striking transcriptional differences between the hemispheres. This is likely due to lateralization of gene expression being subtle and quantitative. However, a recent re-analysis and meta-analysis of gene expression data from the adult superior temporal and auditory cortex found lateralization of transcription of genes involved in synaptic transmission and neuronal electrophysiology. Meanwhile, human subcortical mid- and hindbrain structures have not been well studied in relation to lateralization of gene activity, despite being potentially important developmental origins of asymmetry. Genetic polymorphisms with small effects on adult brain and behavioral asymmetries are beginning to be identified through studies of large datasets, but the core genetic mechanisms of lateralized human brain development remain unknown. Identifying subtly lateralized genetic networks in the brain will lead to a new understanding of how neuronal circuits on the left and right are differently fine-tuned to preferentially support particular cognitive and behavioral functions.

Abstract

The genetic determinants of cerebral asymmetries are unknown. Sex differences in asymmetry of the planum temporale, that overlaps Wernicke’s classical language area, have been inconsistently reported. Meta-analysis of previous studies has suggested that publication bias established this sex difference in the literature. Using probabilistic definitions of cortical regions we screened over the cerebral cortex for sexual dimorphisms of asymmetry in 2337 healthy subjects, and found the planum temporale to show the strongest sex-linked asymmetry of all regions, which was supported by two further datasets, and also by analysis with the Freesurfer package that performs automated parcellation of cerebral cortical regions. We performed a genome-wide association scan meta-analysis of planum temporale asymmetry in a pooled sample of 3095 subjects, followed by a candidate-driven approach which measured a significant enrichment of association in genes of the ´steroid hormone receptor activity´ and 'steroid metabolic process' pathways. Variants in the genes and pathways identified may affect the role of the planum temporale in language cognition.

Abstract

The highly complex structure of the human brain is strongly shaped by genetic influences. Subcortical brain regions form circuits with cortical areas to coordinate movement, learning, memory and motivation, and altered circuits can lead to abnormal behaviour and disease. To investigate how common genetic variants affect the structure of these brain regions, here we conduct genome-wide association studies of the volumes of seven subcortical regions and the intracranial volume derived from magnetic resonance images of 30,717 individuals from 50 cohorts. We identify five novel genetic variants influencing the volumes of the putamen and caudate nucleus. We also find stronger evidence for three loci with previously established influences on hippocampal volume and intracranial volume. These variants show specific volumetric effects on brain structures rather than global effects across structures. The strongest effects were found for the putamen, where a novel intergenic locus with replicable influence on volume (rs945270; P = 1.08 × 10-33; 0.52% variance explained) showed evidence of altering the expression of the KTN1 gene in both brain and blood tissue. Variants influencing putamen volume clustered near developmental genes that regulate apoptosis, axon guidance and vesicle transport. Identification of these genetic variants provides insight into the causes of variability in human brain development, and may help to determine mechanisms of neuropsychiatric dysfunction

Abstract

Lateralization is an important aspect of the functional brain architecture for language and other cognitive faculties. The molecular genetic basis of human brain lateralization is unknown, and recent studies have suggested that gene expression in the cerebral cortex is bilaterally symmetrical. Here we have re-analyzed two transcriptomic datasets derived from post mortem human cerebral cortex, with a specific focus on superior temporal and auditory language cortex in adults. We applied an empirical Bayes approach to model differential left-right expression, together with gene ontology analysis and meta-analysis. There was robust and reproducible lateralization of individual genes and gene ontology groups that are likely to fine-tune the electrophysiological and neurotransmission properties of cortical circuits, most notably synaptic transmission, nervous system development and glutamate receptor activity. Our findings anchor the cerebral biology of language to the molecular genetic level. Future research in model systems may determine how these molecular signatures of neurophysiological lateralization effect fine-tuning of cerebral cortical function, differently in the two hemispheres.