Imaging genetics of language network functional connectivity reveals links with language-related abilities, dyslexia and handedness.

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 its genetic architecture. We used resting-state imaging data from 29,681 participants (UK Biobank) to measure connectivity between 18 left-hemisphere regions involved in multimodal sentence-level processing, as well as their right-hemisphere homotopes, and interhemispheric connections. Multivariate genome-wide association analysis of this total network, based on genetic variants with population frequencies  >1%, identified 14 genomic loci, of which three were also associated with asymmetry of intrahemispheric connectivity. Polygenic dispositions to lower language-related abilities, dyslexia and left-handedness were associated with generally reduced leftward asymmetry of functional connectivity. Exome-wide association analysis based on rare, protein-altering variants (frequencies <1%) suggested 7 additional genes. These findings shed new light on genetic contributions to language network organization and related behavioural traits.

Pathogenic SATB2 missense variants affecting p.Gly392 have variable functional implications and result in diverse clinical phenotypes.

SATB2-associated syndrome (SAS) is caused by pathogenic variants in SATB2, which encodes an evolutionarily conserved transcription factor. Despite the broad range of phenotypic manifestations and variable severity related to this syndrome, haploinsufficiency has been assumed to be the primary molecular explanation.In this study, we describe eight individuals with SATB2 variants that affect p.Gly392 (four women, age range 2-16 years; p.Gly392Arg, p.Gly392Glu and p.Gly392Val). Of these, individuals with p.Gly392Arg substitutions were found to have more severe neurodevelopmental phenotypes based on an established rubric scoring system when compared with individuals with p.Gly392Glu, p.Gly392Val and other previously reported causative SATB2 missense variants. Consistent with the observations at the phenotypic level, using human cell-based and model organism functional data, we documented that while all three described p.Gly392 variants affect the same residue and seem to all have a partial loss-of-function effect, some effects on SATB2 protein function appear to be variant-specific. Our results indicate that genotype-phenotype correlations in SAS are more complex than originally thought, and variant-specific genotype-phenotype correlations are needed.

Preschool musicality is associated with school-age communication abilities through genes related to rhythmicity.

Early-life musical engagement is an understudied but developmentally important and heritable precursor of later (social) communication and language abilities. This study aims to uncover the aetiological mechanisms linking musical to communication abilities. We derived polygenic scores (PGS) for self-reported beat synchronisation abilities (PGSrhythmicity) in children (N≤6,737) from the Avon Longitudinal Study of Parents and Children and tested their association with preschool musical (0.5-5 years) and school-age (social) communication and cognition-related abilities (9-12 years). We further assessed whether relationships between preschool musicality and school-age communication are shared through PGSrhythmicity, using structural equation modelling techniques. PGSrhythmicity were associated with preschool musicality (Nagelkerke-R2=0.70-0.79%), and school-age communication and cognition-related abilities (R2=0.08-0.41%), but not social communication. We identified links between preschool musicality and school-age speech- and syntax-related communication abilities as captured by known genetic influences underlying rhythmicity (shared effect ß=0.0065(SE=0.0021), p=0.0016), above and beyond general cognition, strengthening support for early music intervention programmes.

The neocortical infrastructure for language involves region-specific patterns of laminar gene expression.

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 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 the 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 interindividual variation in structural connectivity between the left-hemisphere frontal and temporal language cortex, and with the brain-related disorders dyslexia and schizophrenia which often involve affected language. These findings identify region-specific patterns of laminar gene expression as a feature of the brain's language network.

Brain-age prediction: Systematic evaluation of site effects, and sample age range and size.

Structural neuroimaging data have been used to compute an estimate of the biological age of the brain (brain-age) which has been associated with other biologically and behaviorally meaningful measures of brain development and aging. The ongoing research interest in brain-age has highlighted the need for robust and publicly available brain-age models pre-trained on data from large samples of healthy individuals. To address this need we have previously released a developmental brain-age model. Here we expand this work to develop, empirically validate, and disseminate a pre-trained brain-age model to cover most of the human lifespan. To achieve this, we selected the best-performing model after systematically examining the impact of seven site harmonization strategies, age range, and sample size on brain-age prediction in a discovery sample of brain morphometric measures from 35,683 healthy individuals (age range: 5-90 years; 53.59% female). The pre-trained models were tested for cross-dataset generalizability in an independent sample comprising 2101 healthy individuals (age range: 8-80 years; 55.35% female) and for longitudinal consistency in a further sample comprising 377 healthy individuals (age range: 9-25 years; 49.87% female). This empirical examination yielded the following findings: (1) the accuracy of age prediction from morphometry data was higher when no site harmonization was applied; (2) dividing the discovery sample into two age-bins (5-40 and 40-90 years) provided a better balance between model accuracy and explained age variance than other alternatives; (3) model accuracy for brain-age prediction plateaued at a sample size exceeding 1600 participants. These findings have been incorporated into CentileBrain (https://centilebrain.org/#/brainAGE2), an open-science, web-based platform for individualized neuroimaging metrics.

Genetic neurodevelopmental clustering and dyslexia.

Dyslexia is a learning difficulty with neurodevelopmental origins, manifesting as reduced accuracy and speed in reading and spelling. It is substantially heritable and frequently co-occurs with other neurodevelopmental conditions, particularly attention deficit-hyperactivity disorder (ADHD). Here, we investigate the genetic structure underlying dyslexia and a range of psychiatric traits using results from genome-wide association studies of dyslexia, ADHD, autism, anorexia nervosa, anxiety, bipolar disorder, major depressive disorder, obsessive compulsive disorder, schizophrenia, and Tourette syndrome. Genomic Structural Equation Modelling (GenomicSEM) showed heightened support for a model consisting of five correlated latent genomic factors described as: F1) compulsive disorders (including obsessive-compulsive disorder, anorexia nervosa, Tourette syndrome), F2) psychotic disorders (including bipolar disorder, schizophrenia), F3) internalising disorders (including anxiety disorder, major depressive disorder), F4) neurodevelopmental traits (including autism, ADHD), and F5) attention and learning difficulties (including ADHD, dyslexia). ADHD loaded more strongly on the attention and learning difficulties latent factor (F5) than on the neurodevelopmental traits latent factor (F4). The attention and learning difficulties latent factor (F5) was positively correlated with internalising disorders (.40), neurodevelopmental traits (.25) and psychotic disorders (.17) latent factors, and negatively correlated with the compulsive disorders (-.16) latent factor. These factor correlations are mirrored in genetic correlations observed between the attention and learning difficulties latent factor and other cognitive, psychological and wellbeing traits. We further investigated genetic variants underlying both dyslexia and ADHD, which implicated 49 loci (40 not previously found in GWAS of the individual traits) mapping to 174 genes (121 not found in GWAS of individual traits) as potential pleiotropic variants. Our study confirms the increased genetic relation between dyslexia and ADHD versus other psychiatric traits and uncovers novel pleiotropic variants affecting both traits. In future, analyses including additional co-occurring traits such as dyscalculia and dyspraxia will allow a clearer definition of the attention and learning difficulties latent factor, yielding further insights into factor structure and pleiotropic effects.

The Association Between Stuttering Burden and Psychosocial Aspects of Life in Adults.

PURPOSE: Stuttering is a speech condition that can have a major impact on a person's quality of life. This descriptive study aimed to identify subgroups of people who stutter (PWS) based on stuttering burden and to investigate differences between these subgroups on psychosocial aspects of life. METHOD: The study included 618 adult participants who stutter. They completed a detailed survey examining stuttering symptomatology, impact of stuttering on anxiety, education and employment, experience of stuttering, and levels of depression, anxiety, and stress. A two-step cluster analytic procedure was performed to identify subgroups of PWS, based on self-report of stuttering frequency, severity, affect, and anxiety, four measures that together inform about stuttering burden. RESULTS: We identified a high- (n = 230) and a low-burden subgroup (n = 372). The high-burden subgroup reported a significantly higher impact of stuttering on education and employment, and higher levels of general depression, anxiety, stress, and overall impact of stuttering. These participants also reported that they trialed more different stuttering therapies than those with lower burden. CONCLUSIONS: Our results emphasize the need to be attentive to the diverse experiences and needs of PWS, rather than treating them as a homogeneous group. Our findings also stress the importance of personalized therapeutic strategies for individuals with stuttering, considering all aspects that could influence their stuttering burden. People with high-burden stuttering might, for example, have a higher need for psychological therapy to reduce stuttering-related anxiety. People with less emotional reactions but severe speech distortions may also have a moderate to high burden, but they may have a higher need for speech techniques to communicate with more ease. Future research should give more insights into the therapeutic needs of people highly burdened by their stuttering. SUPPLEMENTAL MATERIAL: https://doi.org/10.23641/asha.25582980.

Auditory discrimination learning and acoustic cue weighing in female zebra finches with localized FoxP1 knockdowns.

Rare disruptions of the transcription factor FOXP1 are implicated in a human neurodevelopmental disorder characterized by autism and/or intellectual disability with prominent problems in speech and language abilities. Avian orthologues of this transcription factor are evolutionarily conserved and highly expressed in specific regions of songbird brains, including areas associated with vocal production learning and auditory perception. Here, we investigated possible contributions of FoxP1 to song discrimination and auditory perception in juvenile and adult female zebra finches. They received lentiviral knockdowns of FoxP1 in one of two brain areas involved in auditory stimulus processing, HVC (proper name) or CMM (caudomedial mesopallium). Ninety-six females, distributed over different experimental and control groups were trained to discriminate between two stimulus songs in an operant Go/Nogo paradigm and subsequently tested with an array of stimuli. This made it possible to assess how well they recognized and categorized altered versions of training stimuli and whether localized FoxP1 knockdowns affected the role of different features during discrimination and categorization of song. Although FoxP1 expression was significantly reduced by the knockdowns, neither discrimination of the stimulus songs nor categorization of songs modified in pitch, sequential order of syllables or by reversed playback were affected. Subsequently, we analyzed the full dataset to assess the impact of the different stimulus manipulations for cue weighing in song discrimination. Our findings show that zebra finches rely on multiple parameters for song discrimination, but with relatively more prominent roles for spectral parameters and syllable sequencing as cues for song discrimination.NEW & NOTEWORTHY In humans, mutations of the transcription factor FoxP1 are implicated in speech and language problems. In songbirds, FoxP1 has been linked to male song learning and female preference strength. We found that FoxP1 knockdowns in female HVC and caudomedial mesopallium (CMM) did not alter song discrimination or categorization based on spectral and temporal information. However, this large dataset allowed to validate different cue weights for spectral over temporal information for song recognition.

Exome-wide analysis implicates rare protein-altering variants in human handedness.

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.

Notes from Beethoven's genome.

Rapid advances over the last decade in DNA sequencing and statistical genetics enable us to investigate the genomic makeup of individuals throughout history. In a recent notable study, Begg et al.1 used Ludwig van Beethoven's hair strands for genome sequencing and explored genetic predispositions for some of his documented medical issues. Given that it was arguably Beethoven's skills as a musician and composer that made him an iconic figure in Western culture, we here extend the approach and apply it to musicality. We use this as an example to illustrate the broader challenges of individual-level genetic predictions.

Neuroimaging genomics as a window into the evolution of human sulcal organization.

Primate brain evolution has involved prominent expansions of the cerebral cortex, with largest effects observed in the human lineage. Such expansions were accompanied by fine-grained anatomical alterations, including increased cortical folding. However, the molecular bases of evolutionary alterations in human sulcal organization are not yet well understood. Here, we integrated data from recently completed large-scale neuroimaging genetic analyses with annotations of the human genome relevant to various periods and events in our evolutionary history. These analyses identified single-nucleotide polymorphism (SNP) heritability enrichments in fetal brain human-gained enhancer (HGE) elements for a number of sulcal structures, including the central sulcus, which is implicated in human hand dexterity. We zeroed in on a genomic region that harbors DNA variants associated with left central sulcus shape, an HGE element, and genetic loci involved in neurogenesis including ZIC4, to illustrate the value of this approach for probing the complex factors contributing to human sulcal evolution.

Normative modelling of brain morphometry across the lifespan with CentileBrain: algorithm benchmarking and model optimisation.

The value of normative models in research and clinical practice relies on their robustness and a systematic comparison of different modelling algorithms and parameters; however, this has not been done to date. We aimed to identify the optimal approach for normative modelling of brain morphometric data through systematic empirical benchmarking, by quantifying the accuracy of different algorithms and identifying parameters that optimised model performance. We developed this framework with regional morphometric data from 37 407 healthy individuals (53% female and 47% male; aged 3-90 years) from 87 datasets from Europe, Australia, the USA, South Africa, and east Asia following a comparative evaluation of eight algorithms and multiple covariate combinations pertaining to image acquisition and quality, parcellation software versions, global neuroimaging measures, and longitudinal stability. The multivariate fractional polynomial regression (MFPR) emerged as the preferred algorithm, optimised with non-linear polynomials for age and linear effects of global measures as covariates. The MFPR models showed excellent accuracy across the lifespan and within distinct age-bins and longitudinal stability over a 2-year period. The performance of all MFPR models plateaued at sample sizes exceeding 3000 study participants. This model can inform about the biological and behavioural implications of deviations from typical age-related neuroanatomical changes and support future study designs. The model and scripts described here are freely available through CentileBrain.

Structural models of genome-wide covariance identify multiple common dimensions in autism.

Common genetic variation has been associated with multiple phenotypic features in Autism Spectrum Disorder (ASD). However, our knowledge of shared genetic factor structures contributing to this highly heterogeneous phenotypic spectrum is limited. Here, we developed and implemented a structural equation modelling framework to directly model genomic covariance across core and non-core ASD phenotypes, studying autistic individuals of European descent with a case-only design. We identified three independent genetic factors most strongly linked to language performance, behaviour and developmental motor delay, respectively, studying an autism community sample (N = 5331). The three-factorial structure was largely confirmed in independent ASD-simplex families (N = 1946), although we uncovered, in addition, simplex-specific genetic overlap between behaviour and language phenotypes. Multivariate models across cohorts revealed novel associations, including links between language and early mastering of self-feeding. Thus, the common genetic architecture in ASD is multi-dimensional with overarching genetic factors contributing, in combination with ascertainment-specific patterns, to phenotypic heterogeneity.

Genetic effects on variability in visual aesthetic evaluations are partially shared across visual domains.

The aesthetic values that individuals place on visual images are formed and shaped over a lifetime. However, whether the formation of visual aesthetic value is solely influenced by environmental exposure is still a matter of debate. Here, we considered differences in aesthetic value emerging across three visual domains: abstract images, scenes, and faces. We examined variability in two major dimensions of ordinary aesthetic experiences: taste-typicality and evaluation-bias. We build on two samples from the Australian Twin Registry where 1547 and 1231 monozygotic and dizygotic twins originally rated visual images belonging to the three domains. Genetic influences explained 26% to 41% of the variance in taste-typicality and evaluation-bias. Multivariate analyses showed that genetic effects were partially shared across visual domains. Results indicate that the heritability of major dimensions of aesthetic evaluations is comparable to that of other complex social traits, albeit lower than for other complex cognitive traits. The exception was taste-typicality for abstract images, for which we found only shared and unique environmental influences. Our study reveals that diverse sources of genetic and environmental variation influence the formation of aesthetic value across distinct visual domains and provides improved metrics to assess inter-individual differences in aesthetic value.

Genome-Wide Analyses of Vocabulary Size in Infancy and Toddlerhood: Associations With Attention-Deficit/Hyperactivity Disorder, Literacy, and Cognition-Related Traits.

BACKGROUND: The number of words children produce (expressive vocabulary) and understand (receptive vocabulary) changes rapidly during early development, partially due to genetic factors. Here, we performed a meta-genome-wide association study of vocabulary acquisition and investigated polygenic overlap with literacy, cognition, developmental phenotypes, and neurodevelopmental conditions, including attention-deficit/hyperactivity disorder (ADHD). METHODS: We studied 37,913 parent-reported vocabulary size measures (English, Dutch, Danish) for 17,298 children of European descent. Meta-analyses were performed for early-phase expressive (infancy, 15-18 months), late-phase expressive (toddlerhood, 24-38 months), and late-phase receptive (toddlerhood, 24-38 months) vocabulary. Subsequently, we estimated single nucleotide polymorphism-based heritability (SNP-h2) and genetic correlations (rg) and modeled underlying factor structures with multivariate models. RESULTS: Early-life vocabulary size was modestly heritable (SNP-h2 = 0.08-0.24). Genetic overlap between infant expressive and toddler receptive vocabulary was negligible (rg = 0.07), although each measure was moderately related to toddler expressive vocabulary (rg = 0.69 and rg = 0.67, respectively), suggesting a multifactorial genetic architecture. Both infant and toddler expressive vocabulary were genetically linked to literacy (e.g., spelling: rg = 0.58 and rg = 0.79, respectively), underlining genetic similarity. However, a genetic association of early-life vocabulary with educational attainment and intelligence emerged only during toddlerhood (e.g., receptive vocabulary and intelligence: rg = 0.36). Increased ADHD risk was genetically associated with larger infant expressive vocabulary (rg = 0.23). Multivariate genetic models in the ALSPAC (Avon Longitudinal Study of Parents and Children) cohort confirmed this finding for ADHD symptoms (e.g., at age 13; rg = 0.54) but showed that the association effect reversed for toddler receptive vocabulary (rg = -0.74), highlighting developmental heterogeneity. CONCLUSIONS: The genetic architecture of early-life vocabulary changes during development, shaping polygenic association patterns with later-life ADHD, literacy, and cognition-related traits.

Beyond the Global Brain Differences: Intraindividual Variability Differences in 1q21.1 Distal and 15q11.2 BP1-BP2 Deletion Carriers.

BACKGROUND: Carriers of the 1q21.1 distal and 15q11.2 BP1-BP2 copy number variants exhibit regional and global brain differences compared with noncarriers. However, interpreting regional differences is challenging if a global difference drives the regional brain differences. Intraindividual variability measures can be used to test for regional differences beyond global differences in brain structure. METHODS: Magnetic resonance imaging data were used to obtain regional brain values for 1q21.1 distal deletion (n = 30) and duplication (n = 27) and 15q11.2 BP1-BP2 deletion (n = 170) and duplication (n = 243) carriers and matched noncarriers (n = 2350). Regional intra-deviation scores, i.e., the standardized difference between an individual's regional difference and global difference, were used to test for regional differences that diverge from the global difference. RESULTS: For the 1q21.1 distal deletion carriers, cortical surface area for regions in the medial visual cortex, posterior cingulate, and temporal pole differed less and regions in the prefrontal and superior temporal cortex differed more than the global difference in cortical surface area. For the 15q11.2 BP1-BP2 deletion carriers, cortical thickness in regions in the medial visual cortex, auditory cortex, and temporal pole differed less and the prefrontal and somatosensory cortex differed more than the global difference in cortical thickness. CONCLUSIONS: We find evidence for regional effects beyond differences in global brain measures in 1q21.1 distal and 15q11.2 BP1-BP2 copy number variants. The results provide new insight into brain profiling of the 1q21.1 distal and 15q11.2 BP1-BP2 copy number variants, with the potential to increase understanding of the mechanisms involved in altered neurodevelopment.

Normative Modeling of Brain Morphometry Across the Lifespan Using CentileBrain: Algorithm Benchmarking and Model Optimization.

We present an empirically benchmarked framework for sex-specific normative modeling of brain morphometry that can inform about the biological and behavioral significance of deviations from typical age-related neuroanatomical changes and support future study designs. This framework was developed using regional morphometric data from 37,407 healthy individuals (53% female; aged 3-90 years) following a comparative evaluation of eight algorithms and multiple covariate combinations pertaining to image acquisition and quality, parcellation software versions, global neuroimaging measures, and longitudinal stability. The Multivariate Factorial Polynomial Regression (MFPR) emerged as the preferred algorithm optimized using nonlinear polynomials for age and linear effects of global measures as covariates. The MFPR models showed excellent accuracy across the lifespan and within distinct age-bins, and longitudinal stability over a 2-year period. The performance of all MFPR models plateaued at sample sizes exceeding 3,000 study participants. The model and scripts described here are freely available through CentileBrain (https://centilebrain.org/).

Self-Reported Stuttering Severity Is Accurate: Informing Methods for Large-Scale Data Collection in Stuttering.

PURPOSE: To our knowledge, there are no data examining the agreement between self-reported and clinician-rated stuttering severity. In the era of big data, self-reported ratings have great potential utility for large-scale data collection, where cost and time preclude in-depth assessment by a clinician. Equally, there is increasing emphasis on the need to recognize an individual's experience of their own condition. Here, we examined the agreement between self-reported stuttering severity compared to clinician ratings during a speech assessment. As a secondary objective, we determined whether self-reported stuttering severity correlated with an individual's subjective impact of stuttering. METHOD: Speech-language pathologists conducted face-to-face speech assessments with 195 participants (137 males) aged 5-84 years, recruited from a cohort of people with self-reported stuttering. Stuttering severity was rated on a 10-point scale by the participant and by two speech-language pathologists. Participants also completed the Overall Assessment of the Subjective Experience of Stuttering (OASES). Clinician and participant ratings were compared. The association between stuttering severity and the OASES scores was examined. RESULTS: There was a strong positive correlation between speech-language pathologist and participant-reported ratings of stuttering severity. Participant-reported stuttering severity correlated weakly with the four OASES domains and with the OASES overall impact score. CONCLUSIONS: Participants were able to accurately rate their stuttering severity during a speech assessment using a simple one-item question. This finding indicates that self-report stuttering severity is a suitable method for large-scale data collection. Findings also support the collection of self-report subjective experience data using questionnaires, such as the OASES, which add vital information about the participants' experience of stuttering that is not captured by overt speech severity ratings alone.

The shared genetic architecture and evolution of human language and musical rhythm.

Rhythm and language-related traits are phenotypically correlated, but their genetic overlap is largely unknown. Here, we leveraged two large-scale genome-wide association studies performed to shed light on the shared genetics of rhythm (N=606,825) and dyslexia (N=1,138,870). Our results reveal an intricate shared genetic and neurobiological architecture, and lay groundwork for resolving longstanding debates about the potential co-evolution of human language and musical traits.