Publications

Abstract

Alterations in brain size and organization represent some of the most distinctive changes in the emergence of our species. Yet, there is limited understanding of how genetic factors contributed to altered neuroanatomy during human evolution. Here, we analyze neuroimaging and genetic data from up to 30,000 people in the UK Biobank and integrate with genomic annotations for different aspects of human evolution, including those based on ancient DNA and comparative genomics. We show that previously reported signals of recent polygenic selection for cortical anatomy are not replicable in a more ancestrally homogeneous sample. We then investigate relationships between evolutionary annotations and common genetic variants shaping cortical surface area and white-matter connectivity for each hemisphere. Our analyses identify single-nucleotide polymorphism heritability enrichment in human-gained regulatory elements that are active in early brain development, affecting surface areas of several parts of the cortex, including left-hemispheric speech-associated regions. We also detect heritability depletion in genomic regions with Neanderthal ancestry for connectivity of the uncinate fasciculus; this is a white-matter tract involved in memory, language, and socioemotional processing with relevance to neuropsychiatric disorders. Finally, we show that common genetic loci associated with left-hemispheric pars triangularis surface area overlap with a human-gained enhancer and affect regulation of ZIC4, a gene implicated in neurogenesis. This work demonstrates how genomic investigations of present-day neuroanatomical variation can help shed light on the complexities of our evolutionary past.

Abstract

Purpose

Although haploinsufficiency of ANKRD11 is among the most common genetic causes of neurodevelopmental disorders, the role of rare ANKRD11 missense variation remains unclear. We characterized clinical, molecular, and functional spectra of ANKRD11 missense variants.
Methods

We collected clinical information of individuals with ANKRD11 missense variants and evaluated phenotypic fit to KBG syndrome. We assessed pathogenicity of variants through in silico analyses and cell-based experiments.
Results

We identified 20 unique, mostly de novo, ANKRD11 missense variants in 29 individuals, presenting with syndromic neurodevelopmental disorders similar to KBG syndrome caused by ANKRD11 protein truncating variants or 16q24.3 microdeletions. Missense variants significantly clustered in repression domain 2 at the ANKRD11 C-terminus. Of the 10 functionally studied missense variants, 6 reduced ANKRD11 stability. One variant caused decreased proteasome degradation and loss of ANKRD11 transcriptional activity.
Conclusion

Our study indicates that pathogenic heterozygous ANKRD11 missense variants cause the clinically recognizable KBG syndrome. Disrupted transrepression capacity and reduced protein stability each independently lead to ANKRD11 loss-of-function, consistent with haploinsufficiency. This highlights the diagnostic relevance of ANKRD11 missense variants, but also poses diagnostic challenges because the KBG-associated phenotype may be mild and inherited pathogenic ANKRD11 (missense) variants are increasingly observed, warranting stringent variant classification and careful phenotyping.

Abstract

Aim

To examine the phenomenology of stuttering across the lifespan in the largest prospective cohort to date.
Method

Participants aged 7 years and older with a history of developmental stuttering were recruited. Self-reported phenotypic data were collected online including stuttering symptomatology, co-occurring phenotypes, genetic predisposition, factors associated with stuttering severity, and impact on anxiety, education, and employment.
Results

A total of 987 participants (852 adults: 590 males, 262 females, mean age 49 years [SD = 17 years 10 months; range = 18–93 years] and 135 children: 97 males, 38 females, mean age 11 years 4 months [SD = 3 years; range = 7–17 years]) were recruited. Stuttering onset occurred at age 3 to 6 years in 64.0%. Blocking (73.2%) was the most frequent phenotype; 75.9% had sought stuttering therapy and 15.5% identified as having recovered. Half (49.9%) reported a family history. There was a significant negative correlation with age for both stuttering frequency and severity in adults. Most were anxious due to stuttering (90.4%) and perceived stuttering as a barrier to education and employment outcomes (80.7%).
Interpretation

The frequent persistence of stuttering and the high proportion with a family history suggest that stuttering is a complex trait that does not often resolve, even with therapy. These data provide new insights into the phenotype and prognosis of stuttering, information that is critically needed to encourage the development of more effective speech therapies.

Abstract

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.

Abstract

Lateralization is a fundamental characteristic of many behaviors and the organization of the brain, and atypical lateralization has been suggested to be linked to various brain-related disorders such as autism and schizophrenia. Right-handedness is one of the most prominent markers of human behavioural lateralization, yet its neurobiological basis remains to be determined. Here, we present a large-scale analysis of handedness, as measured by self-reported direction of hand preference, and its variability related to brain structural and functional organization in the UK Biobank (N = 36,024). A multivariate machine learning approach with multi-modalities of brain imaging data was adopted, to reveal how well brain imaging features could predict individual's handedness (i.e., right-handedness vs. non-right-handedness) and further identify the top brain signatures that contributed to the prediction. Overall, the results showed a good prediction performance, with an area under the receiver operating characteristic curve (AUROC) score of up to 0.72, driven largely by resting-state functional measures. Virtual lesion analysis and large-scale decoding analysis suggested that the brain networks with the highest importance in the prediction showed functional relevance to hand movement and several higher-level cognitive functions including language, arithmetic, and social interaction. Genetic analyses of contributions of common DNA polymorphisms to the imaging-derived handedness prediction score showed a significant heritability (h2=7.55%, p <0.001) that was similar to and slightly higher than that for the behavioural measure itself (h2=6.74%, p <0.001). The genetic correlation between the two was high (rg=0.71), suggesting that the imaging-derived score could be used as a surrogate in genetic studies where the behavioural measure is not available. This large-scale study using multimodal brain imaging and multivariate machine learning has shed new light on the neural correlates of human handedness.

Abstract

Age has a major effect on brain volume. However, the normative studies available are constrained by small sample sizes, restricted age coverage and significant methodological variability. These limitations introduce inconsistencies and may obscure or distort the lifespan trajectories of brain morphometry. In response, we capitalized on the resources of the Enhancing Neuroimaging Genetics through Meta‐Analysis (ENIGMA) Consortium to examine age‐related trajectories inferred from cross‐sectional measures of the ventricles, the basal ganglia (caudate, putamen, pallidum, and nucleus accumbens), the thalamus, hippocampus and amygdala using magnetic resonance imaging data obtained from 18,605 individuals aged 3–90 years. All subcortical structure volumes were at their maximum value early in life. The volume of the basal ganglia showed a monotonic negative association with age thereafter; there was no significant association between age and the volumes of the thalamus, amygdala and the hippocampus (with some degree of decline in thalamus) until the sixth decade of life after which they also showed a steep negative association with age. The lateral ventricles showed continuous enlargement throughout the lifespan. Age was positively associated with inter‐individual variability in the hippocampus and amygdala and the lateral ventricles. These results were robust to potential confounders and could be used to examine the functional significance of deviations from typical age‐related morphometric patterns.

Abstract

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.

Abstract

The use of spoken and written language is a fundamental human capacity. Individual differences in reading- and language-related skills are influenced by genetic variation, with twin-based heritability estimates of 30 to 80% depending on the trait. The genetic architecture is complex, heterogeneous, and multifactorial, but investigations of contributions of single-nucleotide polymorphisms (SNPs) were thus far underpowered. We present a multicohort genome-wide association study (GWAS) of five traits assessed individually using psychometric measures (word reading, nonword reading, spelling, phoneme awareness, and nonword repetition) in samples of 13,633 to 33,959 participants aged 5 to 26 y. We identified genome-wide significant association with word reading (rs11208009, P = 1.098 × 10−8) at a locus that has not been associated with intelligence or educational attainment. All five reading-/language-related traits showed robust SNP heritability, accounting for 13 to 26% of trait variability. Genomic structural equation modeling revealed a shared genetic factor explaining most of the variation in word/nonword reading, spelling, and phoneme awareness, which only partially overlapped with genetic variation contributing to nonword repetition, intelligence, and educational attainment. A multivariate GWAS of word/nonword reading, spelling, and phoneme awareness maximized power for follow-up investigation. Genetic correlation analysis with neuroimaging traits identified an association with the surface area of the banks of the left superior temporal sulcus, a brain region linked to the processing of spoken and written language. Heritability was enriched for genomic elements regulating gene expression in the fetal brain and in chromosomal regions that are depleted of Neanderthal variants. Together, these results provide avenues for deciphering the biological underpinnings of uniquely human traits.

Abstract

Delineating the association of age and cortical thickness in healthy individuals is critical given the association of cortical thickness with cognition and behavior. Previous research has shown that robust estimates of the association between age and brain morphometry require large‐scale studies. In response, we used cross‐sectional data from 17,075 individuals aged 3–90 years from the Enhancing Neuroimaging Genetics through Meta‐Analysis (ENIGMA) Consortium to infer age‐related changes in cortical thickness. We used fractional polynomial (FP) regression to quantify the association between age and cortical thickness, and we computed normalized growth centiles using the parametric Lambda, Mu, and Sigma method. Interindividual variability was estimated using meta‐analysis and one‐way analysis of variance. For most regions, their highest cortical thickness value was observed in childhood. Age and cortical thickness showed a negative association; the slope was steeper up to the third decade of life and more gradual thereafter; notable exceptions to this general pattern were entorhinal, temporopolar, and anterior cingulate cortices. Interindividual variability was largest in temporal and frontal regions across the lifespan. Age and its FP combinations explained up to 59% variance in cortical thickness. These results may form the basis of further investigation on normative deviation in cortical thickness and its significance for behavioral and cognitive outcomes.

Abstract

Most people have a right-ear advantage for the perception of spoken syllables, consistent with left hemisphere dominance for speech processing. However, there is considerable variation, with some people showing left-ear advantage. The extent to which this variation is reflected in brain structure remains unclear. We tested for relations between hemispheric asymmetries of auditory processing and of grey matter in 281 adults, using dichotic listening and voxel-based morphometry. This was the largest study of this issue to date. Per-voxel asymmetry indexes were derived for each participant following registration of brain magnetic resonance images to a template that was symmetrized. The asymmetry index derived from dichotic listening was related to grey matter asymmetry in clusters of voxels corresponding to the amygdala and cerebellum lobule VI. There was also a smaller, non-significant cluster in the posterior superior temporal gyrus, a region of auditory cortex. These findings contribute to the mapping of asymmetrical structure–function links in the human brain and suggest that subcortical structures should be investigated in relation to hemispheric dominance for speech processing, in addition to auditory cortex.

Abstract

The problem of poor reproducibility of scientific findings has received much attention over recent years, in a variety of fields including psychology and neuroscience. The problem has been partly attributed to publication bias and unwanted practices such as p‐hacking. Low statistical power in individual studies is also understood to be an important factor. In a recent multisite collaborative study, we mapped brain anatomical left–right asymmetries for regional measures of surface area and cortical thickness, in 99 MRI datasets from around the world, for a total of over 17,000 participants. In the present study, we revisited these hemispheric effects from the perspective of reproducibility. Within each dataset, we considered that an effect had been reproduced when it matched the meta‐analytic effect from the 98 other datasets, in terms of effect direction and significance threshold. In this sense, the results within each dataset were viewed as coming from separate studies in an “ideal publishing environment,” that is, free from selective reporting and p hacking. We found an average reproducibility rate of 63.2% (SD = 22.9%, min = 22.2%, max = 97.0%). As expected, reproducibility was higher for larger effects and in larger datasets. Reproducibility was not obviously related to the age of participants, scanner field strength, FreeSurfer software version, cortical regional measurement reliability, or regional size. These findings constitute an empirical illustration of reproducibility in the absence of publication bias or p hacking, when assessing realistic biological effects in heterogeneous neuroscience data, and given typically‐used sample sizes.

Abstract

Left-right asymmetry of the human brain is one of its cardinal features, and also a complex, multivariate trait. Decades of research have suggested that brain asymmetry may be altered in psychiatric disorders. However, findings have been inconsistent and often based on small sample sizes. There are also open questions surrounding which structures are asymmetrical on average in the healthy population, and how variability in brain asymmetry relates to basic biological variables such as age and sex. Over the last four years, the ENIGMA-Laterality Working Group has published six studies of grey matter morphological asymmetry based on total sample sizes from roughly 3,500 to 17,000 individuals, which were between one and two orders of magnitude larger than those published in previous decades. A population-level mapping of average asymmetry was achieved, including an
intriguing fronto-occipital gradient of cortical thickness asymmetry in healthy brains. ENIGMA’s multidataset approach also supported an empirical illustration of reproducibility of hemispheric differences across datasets. Effect sizes were estimated for grey matter asymmetry based on large, international,
samples in relation to age, sex, handedness, and brain volume, as well as for three psychiatric disorders:Autism Spectrum Disorder was associated with subtly reduced asymmetry of cortical thickness at regions spread widely over the cortex; Pediatric Obsessive-Compulsive Disorder was associated with altered subcortical asymmetry; Major Depressive Disorder was not significantly associated with changes
of asymmetry. Ongoing studies are examining brain asymmetry in other disorders. Moreover, a groundwork has been laid for possibly identifying shared genetic contributions to brain asymmetry and disorders.

Abstract

Using individual differences approaches, a growing body of literature finds positive associations between musicality and language-related abilities, complementing prior findings of links between musical training and language skills. Despite these associations, musicality has been often overlooked in mainstream models of individual differences in language acquisition and development. To better understand the biological basis of these individual differences, we propose the Musical Abilities, Pleiotropy, Language, and Environment (MAPLE) framework. This novel integrative framework posits that musical and language-related abilities likely share some common genetic architecture (i.e., genetic pleiotropy) in addition to some degree of overlapping neural endophenotypes, and genetic influences on musically and linguistically enriched environments. Drawing upon recent advances in genomic methodologies for unraveling pleiotropy, we outline testable predictions for future research on language development and how its underlying neurobiological substrates may be supported by genetic pleiotropy with musicality. In support of the MAPLE framework, we review and discuss findings from over seventy behavioral and neural studies, highlighting that musicality is robustly associated with individual differences in a range of speech-language skills required for communication and development. These include speech perception-in-noise, prosodic perception, morphosyntactic skills, phonological skills, reading skills, and aspects of second/foreign language learning. Overall, the current work provides a clear agenda and framework for studying musicality-language links using individual differences approaches, with an emphasis on leveraging advances in the genomics of complex musicality and language traits.

Abstract

Temporal lobe epilepsy (TLE), a common drug-resistant epilepsy in adults, is primarily a limbic network disorder associated with predominant unilateral hippocampal pathology. Structural MRI has provided an in vivo window into whole-brain grey matter structural alterations in TLE relative to controls, by either mapping (i) atypical inter-hemispheric asymmetry or (ii) regional atrophy. However, similarities and differences of both atypical asymmetry and regional atrophy measures have not been systematically investigated.

Here, we addressed this gap using the multi-site ENIGMA-Epilepsy dataset comprising MRI brain morphological measures in 732 TLE patients and 1,418 healthy controls. We compared spatial distributions of grey matter asymmetry and atrophy in TLE, contextualized their topographies relative to spatial gradients in cortical microstructure and functional connectivity calculated using 207 healthy controls obtained from Human Connectome Project and an independent dataset containing 23 TLE patients and 53 healthy controls, and examined clinical associations using machine learning.

We identified a marked divergence in the spatial distribution of atypical inter-hemispheric asymmetry and regional atrophy mapping. The former revealed a temporo-limbic disease signature while the latter showed diffuse and bilateral patterns. Our findings were robust across individual sites and patients. Cortical atrophy was significantly correlated with disease duration and age at seizure onset, while degrees of asymmetry did not show a significant relationship to these clinical variables.

Our findings highlight that the mapping of atypical inter-hemispheric asymmetry and regional atrophy tap into two complementary aspects of TLE-related pathology, with the former revealing primary substrates in ipsilateral limbic circuits and the latter capturing bilateral disease effects. These findings refine our notion of the neuropathology of TLE and may inform future discovery and validation of complementary MRI biomarkers in TLE.

Abstract

Reading Disability (RD) is often characterized by difficulties in the phonology of the language. While the molecular mechanisms underlying it are largely undetermined, loci are being revealed by genome-wide association studies (GWAS). In a previous GWAS for word reading (Price, 2020), we observed that top single-nucleotide polymorphisms (SNPs) were located near to or in genes involved in neuronal migration/axon guidance (NM/AG) or loci implicated in autism spectrum disorder (ASD). A prominent theory of RD etiology posits that it involves disturbed neuronal migration, while potential links between RD-ASD have not been extensively investigated. To improve power to identify associated loci, we up-weighted variants involved in NM/AG or ASD, separately, and performed a new Hypothesis-Driven (HD)–GWAS. The approach was applied to a Toronto RD sample and a meta-analysis of the GenLang Consortium. For the Toronto sample (n = 624), no SNPs reached significance; however, by gene-set analysis, the joint contribution of ASD-related genes passed the threshold (p~1.45 × 10–2, threshold = 2.5 × 10–2). For the GenLang Cohort (n = 26,558), SNPs in DOCK7 and CDH4 showed significant association for the NM/AG hypothesis (sFDR q = 1.02 × 10–2). To make the GenLang dataset more similar to Toronto, we repeated the analysis restricting to samples selected for reading/language deficits (n = 4152). In this GenLang selected subset, we found significant association for a locus intergenic between BTG3-C21orf91 for both hypotheses (sFDR q < 9.00 × 10–4). This study contributes candidate loci to the genetics of word reading. Data also suggest that, although different variants may be involved, alleles implicated in ASD risk may be found in the same genes as those implicated in word reading. This finding is limited to the Toronto sample suggesting that ascertainment influences genetic associations.

Abstract

Many mental health conditions present a spectrum of social difficulties that overlaps with social behaviour in the general population including shared but little characterised genetic links. Here, we systematically investigate heterogeneity in shared genetic liabilities with attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorders (ASD), bipolar disorder (BP), major depression (MD) and schizophrenia across a spectrum of different social symptoms. Longitudinally assessed low-prosociality and peer-problem scores in two UK population-based cohorts (4–17 years; parent- and teacher-reports; Avon Longitudinal Study of Parents and Children(ALSPAC): N ≤ 6,174; Twins Early Development Study(TEDS): N ≤ 7,112) were regressed on polygenic risk scores for disorder, as informed by genome-wide summary statistics from large consortia, using negative binomial regression models. Across ALSPAC and TEDS, we replicated univariate polygenic associations between social behaviour and risk for ADHD, MD and schizophrenia. Modelling variation in univariate genetic effects jointly using random-effect meta-regression revealed evidence for polygenic links between social behaviour and ADHD, ASD, MD, and schizophrenia risk, but not BP. Differences in age, reporter and social trait captured 45–88% in univariate effect variation. Cross-disorder adjusted analyses demonstrated that age-related heterogeneity in univariate effects is shared across mental health conditions, while reporter- and social trait-specific heterogeneity captures disorder-specific profiles. In particular, ADHD, MD, and ASD polygenic risk were more strongly linked to peer problems than low prosociality, while schizophrenia was associated with low prosociality only. The identified association profiles suggest differences in the social genetic architecture across mental disorders when investigating polygenic overlap with population-based social symptoms spanning 13 years of child and adolescent development.

Abstract

Small average differences in the left-right asymmetry of cerebral cortical thickness have been reported in individuals with autism spectrum disorder (ASD) compared to typically developing controls, affecting widespread cortical regions. The possible impacts of these regional alterations in terms of structural network effects have not previously been characterized. Inter-regional morphological covariance analysis can capture network connectivity between different cortical areas at the macroscale level. Here, we used cortical thickness data from 1455 individuals with ASD and 1560 controls, across 43 independent datasets of the ENIGMA consortium’s ASD Working Group, to assess hemispheric asymmetries of intra-individual structural covariance networks, using graph theory-based topological metrics. Compared with typical features of small-world architecture in controls, the ASD sample showed significantly altered average asymmetry of networks involving the fusiform, rostral middle frontal, and medial orbitofrontal cortex, involving higher randomization of the corresponding right-hemispheric networks in ASD. A network involving the superior frontal cortex showed decreased right-hemisphere randomization. Based on comparisons with meta-analyzed functional neuroimaging data, the altered connectivity asymmetry particularly affected networks that subserve executive functions, language-related and sensorimotor processes. These findings provide a network-level characterization of altered left-right brain asymmetry in ASD, based on a large combined sample. Altered asymmetrical brain development in ASD may be partly propagated among spatially distant regions through structural connectivity.

Abstract

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.

Abstract

Despite the substantial heritability of antisocial behavior (ASB), specific genetic variants robustly associated with the trait have not been identified. The present study by the Broad Antisocial Behavior Consortium (BroadABC) meta-analyzed data from 28 discovery samples (N = 85,359) and five independent replication samples (N = 8058) with genotypic data and broad measures of ASB. We identified the first significant genetic associations with broad ASB, involving common intronic variants in the forkhead box protein P2 (FOXP2) gene (lead SNP rs12536335, p = 6.32 × 10−10). Furthermore, we observed intronic variation in Foxp2 and one of its targets (Cntnap2) distinguishing a mouse model of pathological aggression (BALB/cJ strain) from controls (BALB/cByJ strain). Polygenic risk score (PRS) analyses in independent samples revealed that the genetic risk for ASB was associated with several antisocial outcomes across the lifespan, including diagnosis of conduct disorder, official criminal convictions, and trajectories of antisocial development. We found substantial genetic correlations of ASB with mental health (depression rg = 0.63, insomnia rg = 0.47), physical health (overweight rg = 0.19, waist-to-hip ratio rg = 0.32), smoking (rg = 0.54), cognitive ability (intelligence rg = −0.40), educational attainment (years of schooling rg = −0.46) and reproductive traits (age at first birth rg = −0.58, father’s age at death rg = −0.54). Our findings provide a starting point toward identifying critical biosocial risk mechanisms for the development of ASB.

Abstract

Purpose

Common diagnostic next-generation sequencing strategies are not optimized to identify inherited variants in genes associated with dominant neurodevelopmental disorders as causal when the transmitting parent is clinically unaffected, leaving a significant number of cases with neurodevelopmental disorders undiagnosed.
Methods

We characterized 21 families with inherited heterozygous missense or protein-truncating variants in CHD3, a gene in which de novo variants cause Snijders Blok-Campeau syndrome.
Results

Computational facial and Human Phenotype Ontology–based comparisons showed that the phenotype of probands with inherited CHD3 variants overlaps with the phenotype previously associated with de novo CHD3 variants, whereas heterozygote parents are mildly or not affected, suggesting variable expressivity. In addition, similarly reduced expression levels of CHD3 protein in cells of an affected proband and of healthy family members with a CHD3 protein-truncating variant suggested that compensation of expression from the wild-type allele is unlikely to be an underlying mechanism. Notably, most inherited CHD3 variants were maternally transmitted.
Conclusion

Our results point to a significant role of inherited variation in Snijders Blok-Campeau syndrome, a finding that is critical for correct variant interpretation and genetic counseling and warrants further investigation toward understanding the broader contributions of such variation to the landscape of human disease.

Abstract

For many traits, males show greater variability than females, with possible implications for understanding sex differences in health and disease. Here, the ENIGMA (Enhancing Neuro Imaging Genetics through Meta‐Analysis) Consortium presents the largest‐ever mega‐analysis of sex differences in variability of brain structure, based on international data spanning nine decades of life. Subcortical volumes, cortical surface area and cortical thickness were assessed in MRI data of 16,683 healthy individuals 1‐90 years old (47% females). We observed significant patterns of greater male than female between‐subject variance for all subcortical volumetric measures, all cortical surface area measures, and 60% of cortical thickness measures. This pattern was stable across the lifespan for 50% of the subcortical structures, 70% of the regional area measures, and nearly all regions for thickness. Our findings that these sex differences are present in childhood implicate early life genetic or gene‐environment interaction mechanisms. The findings highlight the importance of individual differences within the sexes, that may underpin sex‐specific vulnerability to disorders.

Abstract

Family and twin studies consistently demonstrate a significant role for genetic factors in the aetiology of the reading disorder dyslexia. However, dyslexia is complex at both the genetic and phenotypic levels, and currently the nature of the core deficit or deficits remains uncertain. Traditional approaches for mapping disease genes, originally developed for single-gene disorders, have limited success when there is not a simple relationship between genotype and phenotype. Recent advances in high-throughput genotyping technology and quantitative statistical methods have made a new approach to identifying genes involved in complex disorders possible. The method involves assessing the genetic similarity of many sibling pairs along the lengths of all their chromosomes and attempting to correlate this similarity with that of their phenotypic scores. We are adopting this approach in an ongoing genome-wide search for genes involved in dyslexia susceptibility, and have already successfully applied the method by replicating results from previous studies suggesting that a quantitative trait locus at 6p21.3 influences reading disability.

Abstract

The KE family is a large three-generation pedigree in which half the members are affected with a severe speech and language disorder that is transmitted as an autosomal dominant monogenic trait. In previously published work, we localized the gene responsible (SPCH1) to a 5.6-cM region of 7q31 between D7S2459 and D7S643. In the present study, we have employed bioinformatic analyses to assemble a detailed BAC-/PAC-based sequence map of this interval, containing 152 sequence tagged sites (STSs), 20 known genes, and >7.75 Mb of completed genomic sequence. We screened the affected chromosome 7 from the KE family with 120 of these STSs (average spacing <100 kb), but we did not detect any evidence of a microdeletion. Novel polymorphic markers were generated from the sequence and were used to further localize critical recombination breakpoints in the KE family. This allowed refinement of the SPCH1 interval to a region between new markers 013A and 330B, containing ∼6.1 Mb of completed sequence. In addition, we have studied two unrelated patients with a similar speech and language disorder, who have de novo translocations involving 7q31. Fluorescence in situ hybridization analyses with BACs/PACs from the sequence map localized the t(5;7)(q22;q31.2) breakpoint in the first patient (CS) to a single clone within the newly refined SPCH1 interval. This clone contains the CAGH44 gene, which encodes a brain-expressed protein containing a large polyglutamine stretch. However, we found that the t(2;7)(p23;q31.3) breakpoint in the second patient (BRD) resides within a BAC clone mapping >3.7 Mb distal to this, outside the current SPCH1 critical interval. Finally, we investigated the CAGH44 gene in affected individuals of the KE family, but we found no mutations in the currently known coding sequence. These studies represent further steps toward the isolation of the first gene to be implicated in the development of speech and language.