Publications

Abstract

Cortical asymmetry is a ubiquitous feature of brain organization that is altered in neurodevelopmental disorders and aging. Achieving consensus on cortical asymmetries in humans is necessary to uncover the genetic-developmental mechanisms that shape them and factors moderating cortical lateralization. Here, we delineate population-level asymmetry in cortical thickness and surface area vertex-wise in 7 datasets and chart asymmetry trajectories across life (4-89 years; observations = 3937; 70% longitudinal). We reveal asymmetry interrelationships, heritability, and test associations in UK Biobank (N=∼37,500). Cortical asymmetry was robust across datasets. Whereas areal asymmetry is predominantly stable across life, thickness asymmetry grows in development and declines in aging. Areal asymmetry correlates in specific regions, whereas thickness asymmetry is globally interrelated across cortex and suggests high directional variability in global thickness lateralization. Areal asymmetry is moderately heritable (max h2SNP ∼19%), and phenotypic correlations are reflected by high genetic correlations, whereas heritability of thickness asymmetry is low. Finally, we detected an asymmetry association with cognition and confirm recently-reported handedness links. Results suggest areal asymmetry is developmentally stable and arises in early life, whereas developmental changes in thickness asymmetry may lead to directional variability of global thickness lateralization. Our results bear enough reproducibility to serve as a standard for future brain asymmetry studies.

Abstract

Left–right asymmetry is an important organizing feature of the healthy brain that may be altered in schizophrenia, but most studies have used relatively small samples and heterogeneous approaches, resulting in equivocal findings. We carried out the largest case–control study of structural brain asymmetries in schizophrenia, with MRI data from 5,080 affected individuals and 6,015 controls across 46 datasets, using a single image analysis protocol. Asymmetry indexes were calculated for global and regional cortical thickness, surface area, and subcortical volume measures. Differences of asymmetry were calculated between affected individuals and controls per dataset, and effect sizes were meta-analyzed across datasets. Small average case–control differences were observed for thickness asymmetries of the rostral anterior cingulate and the middle temporal gyrus, both driven by thinner left-hemispheric cortices in schizophrenia. Analyses of these asymmetries with respect to the use of antipsychotic medication and other clinical variables did not show any significant associations. Assessment of age- and sex-specific effects revealed a stronger average leftward asymmetry of pallidum volume between older cases and controls. Case–control differences in a multivariate context were assessed in a subset of the data (N = 2,029), which revealed that 7% of the variance across all structural asymmetries was explained by case–control status. Subtle case–control differences of brain macrostructural asymmetry may reflect differences at the molecular, cytoarchitectonic, or circuit levels that have functional relevance for the disorder. Reduced left middle temporal cortical thickness is consistent with altered left-hemisphere language network organization in schizophrenia.

Abstract

White matter tracts form the structural basis of large-scale brain networks. We applied brain-wide tractography to diffusion images from 30,810 adults (U.K. Biobank) and found significant heritability for 90 node-level and 851 edge-level network connectivity measures. Multivariate genome-wide association analyses identified 325 genetic loci, of which 80% had not been previously associated with brain metrics. Enrichment analyses implicated neurodevelopmental processes including neurogenesis, neural differentiation, neural migration, neural projection guidance, and axon development, as well as prenatal brain expression especially in stem cells, astrocytes, microglia, and neurons. The multivariate association profiles implicated 31 loci in connectivity between core regions of the left-hemisphere language network. Polygenic scores for psychiatric, neurological, and behavioral traits also showed significant multivariate associations with structural connectivity, each implicating distinct sets of brain regions with trait-relevant functional profiles. This large-scale mapping study revealed common genetic contributions to variation in the structural connectome of the human brain.

Abstract

Laterality indices (LIs) quantify the left-right asymmetry of brain and behavioural variables and provide a measure that is statistically convenient and seemingly easy to interpret. Substantial variability in how structural and functional asymmetries are recorded, calculated, and reported, however, suggest little agreement on the conditions required for its valid assessment. The present study aimed for consensus on general aspects in this context of laterality research, and more specifically within a particular method or technique (i.e., dichotic listening, visual half-field technique, performance asymmetries, preference bias reports, electrophysiological recording, functional MRI, structural MRI, and functional transcranial Doppler sonography). Experts in laterality research were invited to participate in an online Delphi survey to evaluate consensus and stimulate discussion. In Round 0, 106 experts generated 453 statements on what they considered good practice in their field of expertise. Statements were organised into a 295-statement survey that the experts then were asked, in Round 1, to independently assess for importance and support, which further reduced the survey to 241 statements that were presented again to the experts in Round 2. Based on the Round 2 input, we present a set of critically reviewed key recommendations to record, assess, and report laterality research for various methods.

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.

Abstract

OBJECTIVE: Recent research has provided evidence for a genetically mediated association between language or reading-related cognitive deficits and impaired motor coordination. Other studies have identified relationships between lateralization of hand skill and cognitive abilities. With a large sample, the authors aimed to investigate genetic relationships between measures of reading-related cognition, hand motor skill, and hand skill lateralization.

METHOD: The authors applied univariate and bivariate correlation and familiality analyses to a range of measures. They also performed genomewide linkage analysis of hand motor skill in a subgroup of 195 sibling pairs.

RESULTS: Hand motor skill was significantly familial (maximum heritability=41%), as were reading-related measures. Hand motor skill was weakly but significantly correlated with reading-related measures, such as nonword reading and irregular word reading. However, these correlations were not significantly familial in nature, and the authors did not observe linkage of hand motor skill to any chromosomal regions implicated in susceptibility to dyslexia. Lateralization of hand skill was not correlated with reading or cognitive ability.

CONCLUSIONS: The authors confirmed a relationship between lower motor ability and poor reading performance. However, the genetic effects on motor skill and reading ability appeared to be largely or wholly distinct, suggesting that the correlation between these traits may have arisen from environmental influences. Finally, the authors found no evidence that reading disability and/or low general cognitive ability were associated with ambidexterity.

Abstract

Schizophrenia and non-right-handedness are moderately associated, and both traits are often accompanied by abnormalities of asymmetrical brain morphology or function. We have found linkage previously of chromosome 2p12-q11 to a quantitative measure of handedness, and we have also found linkage of schizophrenia/schizoaffective disorder to this same chromosomal region in a separate study. Now, we have found that in one of our samples (191 reading-disabled sibling pairs), the relative hand skill of siblings was correlated more strongly with paternal than maternal relative hand skill. This led us to re-analyse 2p12-q11 under parent-of-origin linkage models. We found linkage of relative hand skill in the RD siblings to 2p12-q11 with P=0.0000037 for paternal identity-by-descent sharing, whereas the maternally inherited locus was not linked to the trait (P>0.2). Similarly, in affected-sib-pair analysis of our schizophrenia dataset (241 sibling pairs), we found linkage to schizophrenia for paternal sharing with LOD=4.72, P=0.0000016, within 3 cM of the peak linkage to relative hand skill. Maternal linkage across the region was weak or non-significant. These similar paternal-specific linkages suggest that the causative genetic effects on 2p12-q11 are related. The linkages may be due to a single maternally imprinted influence on lateralized brain development that contains common functional polymorphisms.

Abstract

Replication of linkage results for complex traits has been exceedingly difficult, owing in part to the inability to measure the precise underlying phenotype, small sample sizes, genetic heterogeneity, and statistical methods employed in analysis. Often, in any particular study, multiple correlated traits have been collected, yet these have been analyzed independently or, at most, in bivariate analyses. Theoretical arguments suggest that full multivariate analysis of all available traits should offer more power to detect linkage; however, this has not yet been evaluated on a genomewide scale. Here, we conduct multivariate genomewide analyses of quantitative-trait loci that influence reading- and language-related measures in families affected with developmental dyslexia. The results of these analyses are substantially clearer than those of previous univariate analyses of the same data set, helping to resolve a number of key issues. These outcomes highlight the relevance of multivariate analysis for complex disorders for dissection of linkage results in correlated traits. The approach employed here may aid positional cloning of susceptibility genes in a wide spectrum of complex traits.

Abstract

Attention-deficit/hyperactivity disorder (ADHD [MIM 143465]) is a common, highly heritable neurobehavioral disorder of childhood onset, characterized by hyperactivity, impulsivity, and/or inattention. As part of an ongoing study of the genetic etiology of ADHD, we have performed a genomewide linkage scan in 204 nuclear families comprising 853 individuals and 270 affected sibling pairs (ASPs). Previously, we reported genomewide linkage analysis of a “first wave” of these families composed of 126 ASPs. A follow-up investigation of one region on 16p yielded significant linkage in an extended sample. The current study extends the original sample of 126 ASPs to 270 ASPs and provides linkage analyses of the entire sample, using polymorphic microsatellite markers that define an ∼10-cM map across the genome. Maximum LOD score (MLS) analysis identified suggestive linkage for 17p11 (MLS=2.98) and four nominal regions with MLS values >1.0, including 5p13, 6q14, 11q25, and 20q13. These data, taken together with the fine mapping on 16p13, suggest two regions as highly likely to harbor risk genes for ADHD: 16p13 and 17p11. Interestingly, both regions, as well as 5p13, have been highlighted in genomewide scans for autism.