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Genetic aetiologies for childhood speech disorder: novel pathways co-expressed during brain development.

ABSTRACT: Childhood apraxia of speech (CAS), the prototypic severe childhood speech disorder, is characterized by motor programming and planning deficits. Genetic factors make substantive contributions to CAS aetiology, with a monogenic pathogenic variant identified in a third of cases, implicating around 20 single genes to date. Here we aimed to identify molecular causation in 70 unrelated probands ascertained with CAS. We performed trio genome sequencing. Our bioinformatic analysis examined single nucleotide, indel, copy number, structural and short tandem repeat variants. We prioritised appropriate variants arising de novo or inherited that were expected to be damaging based on in silico predictions. We identified high confidence variants in 18/70 (26%) probands, almost doubling the current number of candidate genes for CAS. Three of the 18 variants affected SETBP1, SETD1A and DDX3X, thus confirming their roles in CAS, while the remaining 15 occurred in genes not previously associated with this disorder. Fifteen variants arose de novo and three were inherited. We provide further novel insights into the biology of child speech disorder, highlighting the roles of chromatin organization and gene regulation in CAS, and confirm that genes involved in CAS are co-expressed during brain development. Our findings confirm a diagnostic yield comparable to, or even higher, than other neurodevelopmental disorders with substantial de novo variant burden. Data also support the increasingly recognised overlaps between genes conferring risk for a range of neurodevelopmental disorders. Understanding the aetiological basis of CAS is critical to end the diagnostic odyssey and ensure affected individuals are poised for precision medicine trials.

SUBMITTER: Kaspi A

PROVIDER: S-EPMC10208970 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature

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Genetic aetiologies for childhood speech disorder: novel pathways co-expressed during brain development.

Kaspi Antony A Hildebrand Michael S MS Jackson Victoria E VE Braden Ruth R van Reyk Olivia O Howell Tegan T Debono Simone S Lauretta Mariana M Morison Lottie L Coleman Matthew J MJ Webster Richard R Coman David D Goel Himanshu H Wallis Mathew M Dabscheck Gabriel G Downie Lilian L Baker Emma K EK Parry-Fielder Bronwyn B Ballard Kirrie K Harrold Eva E Ziegenfusz Shaun S Bennett Mark F MF Robertson Erandee E Wang Longfei L Boys Amber A Fisher Simon E SE Amor David J DJ Scheffer Ingrid E IE Bahlo Melanie M Morgan Angela T AT

Molecular psychiatry 20230401 4

Childhood apraxia of speech (CAS), the prototypic severe childhood speech disorder, is characterized by motor programming and planning deficits. Genetic factors make substantive contributions to CAS aetiology, with a monogenic pathogenic variant identified in a third of cases, implicating around 20 single genes to date. Here we aimed to identify molecular causation in 70 unrelated probands ascertained with CAS. We performed trio genome sequencing. Our bioinformatic analysis examined single nucle ...[more]

PMID: 36117209

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Project description:Childhood apraxia of speech (CAS) is a rare, severe, persistent pediatric motor speech disorder with associated deficits in sensorimotor, cognitive, language, learning and affective processes. Among other neurogenetic origins, CAS is the disorder segregating with a mutation in FOXP2 in a widely studied, multigenerational London family. We report the first whole-exome sequencing (WES) findings from a cohort of 10 unrelated participants, ages 3 to 19 years, with well-characterized CAS.As part of a larger study of children and youth with motor speech sound disorders, 32 participants were classified as positive for CAS on the basis of a behavioral classification marker using auditory-perceptual and acoustic methods that quantify the competence, precision and stability of a speaker's speech, prosody and voice. WES of 10 randomly selected participants was completed using the Illumina Genome Analyzer IIx Sequencing System. Image analysis, base calling, demultiplexing, read mapping, and variant calling were performed using Illumina software. Software developed in-house was used for variant annotation, prioritization and interpretation to identify those variants likely to be deleterious to neurodevelopmental substrates of speech-language development.Among potentially deleterious variants, clinically reportable findings of interest occurred on a total of five chromosomes (Chr3, Chr6, Chr7, Chr9 and Chr17), which included six genes either strongly associated with CAS (FOXP1 and CNTNAP2) or associated with disorders with phenotypes overlapping CAS (ATP13A4, CNTNAP1, KIAA0319 and SETX). A total of 8 (80%) of the 10 participants had clinically reportable variants in one or two of the six genes, with variants in ATP13A4, KIAA0319 and CNTNAP2 being the most prevalent.Similar to the results reported in emerging WES studies of other complex neurodevelopmental disorders, our findings from this first WES study of CAS are interpreted as support for heterogeneous genetic origins of this pediatric motor speech disorder with multiple genes, pathways and complex interactions. We also submit that our findings illustrate the potential use of WES for both gene identification and case-by-case clinical diagnostics in pediatric motor speech disorders.

Project description:BackgroundAlthough attention deficit hyperactivity disorder (ADHD) is thought to reflect a continuously distributed quantitative trait, it is assessed through binary diagnosis or skewed measures biased towards its high, symptomatic extreme. A growing trend is to study the positive tail of normally distributed traits, a promising avenue, for example, to study high intelligence to increase power for gene-hunting for intelligence. However, the emergence of such a 'positive genetics' model has been tempered for ADHD due to poor phenotypic resolution at the low extreme. Overcoming this methodological limitation, we conduct the first study to assess the aetiologies of low extreme ADHD traits.MethodsIn a population-representative sample of 2,143 twins, the Strength and Weaknesses of ADHD Symptoms and Normal behaviour (SWAN) questionnaire was used to assess ADHD traits on a continuum from low to high. Aetiological influences on extreme ADHD traits were estimated using DeFries-Fulker extremes analysis. ADHD traits were related to behavioural, cognitive and home environmental outcomes using regression.ResultsLow extreme ADHD traits were significantly influenced by shared environmental factors (23-35%) but were not significantly heritable. In contrast, high-extreme ADHD traits showed significant heritability (39-51%) but no shared environmental influences. Compared to individuals with high extreme or with average levels of ADHD traits, individuals with low extreme ADHD traits showed fewer internalizing and externalizing behaviour problems, better cognitive performance and more positive behaviours and positive home environmental outcomes.ConclusionsShared environmental influences on low extreme ADHD traits may reflect passive gene-environment correlation, which arises because parents provide environments as well as passing on genes. Studying the low extreme opens new avenues to study mechanisms underlying previously neglected positive behaviours. This is different from the current deficit-based model of intervention, but congruent with a population-level approach to improving youth wellbeing.

Project description:BackgroundChildhood sleep problems are common and among the most frequent and impairing comorbidities of childhood psychiatric disorders. In adults, sleep disturbances are heritable and show strong genetic associations with brain morphology; however, little is known about the genetic architecture of childhood sleep and potential etiological links between sleep, brain development, and pediatric-onset psychiatric symptoms.MethodsUsing data from the Adolescent Brain Cognitive Development Study (n Phenotype = 4428 for discovery/replication, n Genetics = 4728; age 9-10 years), we assessed phenotypic relationships, heritability, and genetic correlations between childhood sleep disturbances (insomnia, arousal, breathing, somnolence, hyperhidrosis, sleep-wake transitions), brain size (surface area, cortical thickness, volume), and dimensional psychopathology.ResultsSleep disturbances showed widespread positive associations with multiple domains of childhood psychopathology; however, only insomnia showed replicable associations with smaller brain surface area. Among the sleep disturbances assessed, only insomnia showed significant heritability (h 2 SNP = 0.15, p < .05) and showed substantial genetic correlations with externalizing and attention-deficit/hyperactivity disorder symptomatology (r G s > 0.80, ps < .05). We found no evidence of genetic correlation between childhood insomnia and brain size. Furthermore, polygenic risk scores calculated from genome-wide association studies of adult insomnia and adult brain size did not predict childhood insomnia; instead, polygenic risk scores trained using attention-deficit/hyperactivity disorder genome-wide association studies predicted decreased surface area at baseline as well as insomnia and externalizing symptoms longitudinally.ConclusionsFindings demonstrate a distinct genetic architecture underlying childhood insomnia and brain size and suggest genetic overlap between childhood insomnia and attention-deficit/hyperactivity disorder symptomatology. Additional research is needed to examine how genetic risk manifests in altered developmental trajectories and comorbid sleep/psychiatric symptoms across adolescence.

Project description:BackgroundGene co-expression, the similarity of gene expression profiles under various experimental conditions, has been used as an indicator of functional relationships between genes, and many co-expression databases have been developed for predicting gene functions. These databases usually provide users with a co-expression network and a list of strongly co-expressed genes for a query gene. Several of these databases also provide functional information on a set of strongly co-expressed genes (i.e., provide biological processes and pathways that are enriched in these strongly co-expressed genes), which is generally analyzed via over-representation analysis (ORA). A limitation of this approach may be that users can predict gene functions only based on the strongly co-expressed genes.ResultsIn this study, we developed a new co-expression database that enables users to predict the function of tomato genes from the results of functional enrichment analyses of co-expressed genes while considering the genes that are not strongly co-expressed. To achieve this, we used the ORA approach with several thresholds to select co-expressed genes, and performed gene set enrichment analysis (GSEA) applied to a ranked list of genes ordered by the co-expression degree. We found that internal correlation in pathways affected the significance levels of the enrichment analyses. Therefore, we introduced a new measure for evaluating the relationship between the gene and pathway, termed the percentile (p)-score, which enables users to predict functionally relevant pathways without being affected by the internal correlation in pathways. In addition, we evaluated our approaches using receiver operating characteristic curves, which concluded that the p-score could improve the performance of the ORA.ConclusionsWe developed a new database, named Co-expressed Pathways DataBase for Tomato, which is available at http://cox-path-db.kazusa.or.jp/tomato . The database allows users to predict pathways that are relevant to a query gene, which would help to infer gene functions.

Project description:Autism Spectrum Disorder (ASD) and Childhood Apraxia of Speech (CAS) are developmental disorders with distinct diagnostic criteria and different epidemiology. However, a common genetic background as well as overlapping clinical features between ASD and CAS have been recently reported. To date, brain structural language-related abnormalities have been detected in both the conditions, but no study directly compared young children with ASD, CAS and typical development (TD). In the current work, we aim: (i) to test the hypothesis that ASD and CAS display neurostructural differences in comparison with TD through morphometric Magnetic Resonance Imaging (MRI)-based measures (ASD vs. TD and CAS vs. TD); (ii) to investigate early possible disease-specific brain structural patterns in the two clinical groups (ASD vs. CAS); (iii) to evaluate predictive power of machine-learning (ML) techniques in differentiating the three samples (ASD, CAS, TD). We retrospectively analyzed the T1-weighted brain MRI scans of 68 children (age range: 34-74 months) grouped into three cohorts: (1) 26 children with ASD (mean age ± standard deviation: 56 ± 11 months); (2) 24 children with CAS (57 ± 10 months); (3) 18 children with TD (55 ± 13 months). Furthermore, a ML analysis based on a linear-kernel Support Vector Machine (SVM) was performed. All but one brain structures displayed significant higher volumes in both ASD and CAS children than TD peers. Specifically, ASD alterations involved fronto-temporal regions together with basal ganglia and cerebellum, while CAS alterations are more focused and shifted to frontal regions, suggesting a possible speech-related anomalies distribution. Caudate, superior temporal and hippocampus volumes directly distinguished the two conditions in terms of greater values in ASD compared to CAS. The ML analysis identified significant differences in brain features between ASD and TD children, whereas only some trends in the ML classification capability were detected in CAS as compared to TD peers. Similarly, the MRI structural underpinnings of two clinical groups were not significantly different when evaluated with linear-kernel SVM. Our results may represent the first step towards understanding shared and specific neural substrate in ASD and CAS conditions, which subsequently may contribute to early differential diagnosis and tailoring specific early intervention.

Project description:BackgroundChildren with autism spectrum disorder (ASD) often have co-occurring symptoms of attention-deficit/hyperactivity disorder (ADHD) and/or anxiety. It is unclear whether these disorders arise from shared or distinct developmental pathways. We explored this question by testing the specificity of early-life (infant and toddler) predictors of mid-childhood ADHD and anxiety symptoms compared to ASD symptoms.MethodsInfants (n = 104) at high and low familial risk for ASD took part in research assessments at 7, 14, 24 and 38 months, and 7 years of age. Symptoms of ASD, ADHD and anxiety were measured by parent report at age 7. Activity levels and inhibitory control, also measured by parent report, in infancy and toddlerhood were used as early-life predictors of ADHD symptoms. Fearfulness and shyness measured in infancy and toddlerhood were used as early-life predictors of anxiety symptoms. Correlations and path analysis models tested associations between early-life predictors and mid-childhood ADHD and anxiety symptoms compared to mid-childhood ASD symptoms, and the influence of controlling for ASD symptoms on those associations.ResultsIncreased activity levels and poor inhibitory control were correlated with ADHD symptoms and not ASD or anxiety; these associations were unchanged in path models controlling for risk-group and ASD symptoms. Increased fearfulness and shyness were correlated with anxiety symptoms, but also ASD symptoms. When controlling for risk-group in path analysis, the association between shyness and anxiety became nonsignificant, and when further controlling for ASD symptoms the association between fearfulness and anxiety became marginal.ConclusionsThe specificity of early-life predictors to ADHD symptoms suggests early developmental pathways to ADHD might be distinct from ASD. The overlap in early-life predictors of anxiety and ASD suggests that these disorders are difficult to differentiate early in life, which could reflect the presence of common developmental pathways or convergence in early behavioural manifestations of these disorders.

Dataset Information

Genetic aetiologies for childhood speech disorder: novel pathways co-expressed during brain development.

Publications

Genetic aetiologies for childhood speech disorder: novel pathways co-expressed during brain development.

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