Biology subjects

Bolte, S.

Publications and source records attributed to Bolte, S..

10 recordsLinked to original sources

bioRxiv2025

Functional connectivity in infants' visual cortex: Links to motion processing and autism

In a previously published study, we found atypical visual cortical laterality patterns during global motion perception in 5-month-old infants who showed high levels of autistic symptoms in toddlerhood. Here, using data from a separate experiment, we examined whether these results could reflect altered visual cortical functional connectivity in theta, alpha, and gamma rhythms. We assessed this in a sample of 5- month- old infants (n = 59; 39 elevated familial likelihood of autism) by means of electroencephalography (EEG) when they were watching videos showing social and non-social scenes. Gamma connectivity between midline and far-lateral visual cortex when viewing social scenes was linked to both later autism symptoms and global motion visual cortical laterality we reported in the previous study. This may indicate a shared integrative mechanism underlying social perception and global motion processing. Further, we found that higher midline-to-lateral theta connectivity in the visual cortex when perceiving non-social scenes in infancy was strongly associated with having more autistic symptoms at follow up, but uncorrelated with concurrent motion perception. Our study points to atypical functional connectivity in the visual cortex as a potential early marker of autistic symptoms and highlights a probable link between motion processing and social perception.

neuroscience↗

bioRxiv2021

Excitatory/inhibitory imbalance in autism: the role of glutamate and GABA gene-sets in symptoms and cortical brain structure

BackgroundThe excitatory/inhibitory (E/I) imbalance hypothesis posits that an imbalance between excitatory (glutamatergic) and inhibitory (GABAergic) mechanisms underlies the behavioral characteristics of autism spectrum disorder (autism). However, how E/I imbalance arises and how it may differ across autism symptomatology and brain regions is not well understood. MethodsWe used innovative analysis methods - combining competitive gene-set analysis and gene-expression profiles in relation to cortical thickness (CT)- to investigate the relationship between genetic variance, brain structure and autism symptomatology of participants from the EU-AIMS LEAP cohort (autism=360, male/female=259/101; neurotypical control participants=279, male/female=178/101) aged 6 to 30 years. Competitive gene-set analysis investigated associations between glutamatergic and GABAergic signaling pathway gene-sets and clinical measures, and CT. Additionally, we investigated expression profiles of the genes within those sets throughout the brain and how those profiles relate to differences in CT between autistic and neurotypical control participants in the same regions. ResultsThe glutamate gene-set was associated with all autism symptom severity scores on the Autism Diagnostic Observation Schedule-2 (ADOS-2) and the Autism Diagnostic Interview-Revised (ADI-R) within the autistic group, while the GABA set was associated with sensory processing measures (using the SSP subscales) across all participants. Brain regions with greater gene expression of both glutamate and GABA genes showed greater differences in CT between autistic and neurotypical control participants. ConclusionsOur results suggest crucial roles for glutamate and GABA genes in autism symptomatology as well as CT, where GABA is more strongly associated with sensory processing and glutamate more with autism symptom severity.

neuroscience↗

bioRxiv2021

A framework for evaluating edited cell libraries created by massively parallel genome engineering

Genome engineering methodologies are transforming biological research and discovery. Approaches based on CRISPR technology have been broadly adopted and there is growing interest in the generation of massively parallel edited cell libraries. Comparing the libraries generated by these varying approaches is challenging and researchers lack a common framework for defining and assessing the characteristics of these libraries. Here we describe a framework for evaluating massively parallel libraries of edited genomes based on established methods for sampling complex populations. We define specific attributes and metrics that are informative for describing a complex cell library and provide examples for estimating these values. We also connect this analysis to generic phenotyping approaches, using either pooled (typically via a selection assay) or isolate (often referred to as screening) phenotyping approaches. We approach this from the context of creating massively parallel, precisely edited libraries with one edit per cell, though the approach holds for other types of modifications, including libraries containing multiple edits per cell (combinatorial editing). This framework is a critical component for evaluating and comparing new technologies as well as understanding how a massively parallel edited cell library will perform in a given phenotyping approach.

genomics↗

bioRxiv2021

Subtly altered topological asymmetry of brain structural covariance networks in autism spectrum disorder across 43 datasets from the ENIGMA consortium

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. Although these alterations affect multiple and widespread cortical regional asymmetries, the extent to which specific structural networks might be affected remains unknown. Inter-regional morphological covariance analysis can capture network connectivity relations between different cortical areas at the macroscale level. Here, we used cortical thickness data from 1,455 individuals with ASD and 1,560 controls, across 43 independent datasets of the ENIGMA consortiums 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 asymmetry of hemispheric networks involving the fusiform, rostral middle frontal, and medial orbitofrontal cortex, driven by shifts toward 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 working memory, executive functions, language, reading, and sensorimotor processes. Taken together, these findings provide new insights into how altered brain left-right asymmetry in ASD affects specific structural and functional brain networks. Altered asymmetrical brain development in ASD may be partly propagated among spatially distant regions through structural connectivity.

neuroscience↗

bioRxiv2021

Babytwins Study Sweden (BATSS): A multi-method infant twin study of genetic and environmental factors influencing infant brain and behavioral development

Twin studies can help us understand the relative contributions of genes and environment to phenotypic trait variation including attentional and brain activation measures. In terms of applying methodologies like electroencephalography (EEG) and eye tracking, which are key methods in developmental neuroscience, infant twin studies are almost non-existent. Here we describe the Babytwins Study Sweden (BATSS), a multi-method longitudinal twin study of 177 MZ and 134 DZ twin pairs (i.e. 622 individual infants) covering the 5 - 36 month time period. The study includes EEG, eye tracking and genetics, together with more traditional measures based on in-person testing, direct observation and questionnaires. The results show that interest in participation in research among twin parents is high, despite the comprehensive protocol. DNA analysis from saliva samples was possible in virtually all participants, allowing for both zygosity confirmation and polygenic score analyses. Combining a longitudinal twin design with advanced technologies in developmental cognitive neuroscience and genomics, BATSS represents a new approach in infancy research, which we hope to have impact across multiple disciplines in the coming years.

neuroscience↗

bioRxiv2020

Differential functional neural circuitry behind autism subtypes with marked imbalance between social-communicative and restricted repetitive behavior symptom domains

Social-communication (SC) and restricted repetitive behaviors (RRB) are autism diagnostic symptom domains. SC and RRB severity can markedly differ within and between individuals and may be underpinned by different neural circuitry and genetic mechanisms. Modeling SC-RRB balance could help identify how neural circuitry and genetic mechanisms map onto such phenotypic heterogeneity. Here we developed a phenotypic stratification model that makes highly accurate (97-99%) out-of-sample SC=RRB, SC>RRB, and RRB>SC subtype predictions. Applying this model to resting state fMRI data from the EU-AIMS LEAP dataset (n=509), we find that while the phenotypic subtypes share many commonalities in terms of intrinsic functional connectivity, they also show replicable differences within some networks compared to a typically-developing group (TD). Specifically, the somatomotor network is hypoconnected with perisylvian circuitry in SC>RRB and visual association circuitry in SC=RRB. The SC=RRB subtype show hyperconnectivity between medial motor and anterior salience circuitry. Genes that are highly expressed within these networks show a differential enrichment pattern with known autism-associated genes, indicating that such circuits are affected by differing autism-associated genomic mechanisms. These results suggest that SC-RRB imbalance subtypes share many commonalities, but also express subtle differences in functional neural circuitry and the genomic underpinnings behind such circuitry.

neuroscience↗

bioRxiv2019

Presynaptic dysfunction in CASK-related neurodevelopmental disorders

CASK-related disorders are a genetically defined group of neurodevelopmental syndromes. There is limited information about the effects of CASK mutations in human neurons. Therefore, we sought to delineate CASK mutation consequences and neuronal level effects using induced pluripotent stem cell-derived neurons from two mutation carriers; one male diagnosed with ASD and a female with MICPCH. We show a reduction of the CASK protein in maturing neurons from the mutation carriers, which leads to significant downregulation of gene sets involved in presynaptic development and CASK protein interactors. Furthermore, CASK-deficient neurons showed decreased inhibitory presynapse size as indicated by VGAT staining, which may alter the excitatory-inhibitory (E/I) balance in developing neural circuitries. Using in vivo magnetic resonance spectroscopy quantification of GABA in the male mutation carrier, we further highlight the possibility to validate in vitro cellular data in brain. Our data shows that future pharmacological and clinical studies on targeting presynapses and E/I imbalance could lead to specific treatments for CASK-related disorders. HighlightsModelling of CASK-related disorders using iPSC-derived human neuronal cells CASK mutations cause dysregulation of its protein interactor partners Reduced CASK levels primarily affect inhibitory presynapse development In vitro GABAergic phenotype predicts in vivo neurotransmitter levels

genetics↗

bioRxiv2018

Dissecting the heterogeneous cortical anatomy of autism spectrum disorder using normative models

BackgroundThe neuroanatomical basis of autism spectrum disorder (ASD) has remained elusive, mostly due to high biological and clinical heterogeneity among diagnosed individuals. Despite considerable effort towards understanding ASD using neuroimaging biomarkers, heterogeneity remains a barrier, partly because studies mostly employ case-control approaches, which assume that the clinical group is homogeneous.\n\nMethodsHere, we used an innovative normative modelling approach to parse biological heterogeneity in ASD. We aimed to dissect the neuroanatomy of ASD by mapping the deviations from a typical pattern of neuroanatomical development at the level of the individual and to show the necessity to look beyond the case-control paradigm to understand the neurobiology of ASD. We first estimated a vertex-wise normative model of cortical thickness development using Gaussian process regression, then mapped the deviation of each participant from the typical pattern. For this we employed a heterogeneous cross-sectional sample of 206 typically developing (TD) individuals (127 male), and 321 individuals (232 male) with ASD (aged 6-31).\n\nResultsWe found few case-control differences but the ASD cohort showed highly individualized patterns of deviations in cortical thickness that were widespread across the brain. These deviations correlated with severity of repetitive behaviors and social communicative symptoms, although only repetitive behaviors survived corrections for multiple testing.\n\nConclusionsOur results: (i) reinforce the notion that individuals with ASD show distinct, highly individualized trajectories of brain development and (ii) show that by focusing on common effects (i.e. the average ASD participant), the case-control approach disguises considerable inter-individual variation crucial for precision medicine.

neuroscience↗

bioRxiv2018

Association Between Rare Copy Number Variation and Response to Social Skills Training in Autism Spectrum Disorder

Challenges in social communication and interaction are core symptoms in autism spectrum disorder (ASD) for which social skills group training (SSGT) is a commonly used intervention. SSGT has shown modest but heterogeneous effects in clinical trials, and therefore identification of effect moderators could enable more precise intervention decisions. One of the major genetic risk factors in ASD are rare copy number variation (CNV). However, limited information exists whether rare CNVs profiles can be used to aid in intervention decisions. Therefore, we conducted the first study to date analyzing rare CNVs as genetic moderators in the outcome of SSGT in ASD. For this, we analyzed rare genic CNV carrier status of 207 children of which 105 received SSGT and 102 standard care as part of a recent randomized clinical trial for 12-weeks SSGT. We used mixed linear models to assess the association of being a CNV carrier, grouped by the effect and size of the CNVs and the primary response to SSGT, the parent-report Social Responsiveness Scale (SRS) measured at post-intervention and 3-months follow-up. Additionally, we analyzed the secondary outcome assessments included parent-rated adaptive behaviors (ABAS-II) and trainer-rated clinical global impression (CGI). We show that being a carrier of any size rare genic CNV did not impact on the SSGT outcome. However, when stratifying the groups by size of the CNVs, we identified that carriers of large CNVs (>500 kb) showed inferior SRS outcomes at post-intervention ({beta} = 15.35, 95% CI 2.86-27.84, P=0.017) and follow-up ({beta} = 14.19, 95% CI 1.68-26.70, P=0.028). Similar results were shown for the parent-rated secondary outcome. In contrast, the carriers of small CNVs had better outcome at post-intervention ({beta} = -1.20, 95 % CI - 2.0 - -0.4 P = 0.003) but not at follow-up for the trainer-rated secondary outcome CGI. These results remained when we tested the specificity of the effect by including the standard care group and adjusting for IQ levels. While our study suggests that being a carrier of any size rare genic CNV did not impact the outcome, it provides preliminary evidence that carriers of high-risk CNVs might not benefit on SSGT as much as non-carriers. Our results indicate that genetic information eventually might help guide personalized intervention planning in ASD. We additionally highlight that more research is needed to understand the intervention needs of autistic individuals with specified molecular alterations.

genetics↗

bioRxiv2017

Copy Number Variation Analysis of 100 Twin Pairs Enriched for Neurodevelopmental Disorders

Hundreds of penetrant risk loci have been identified across different neurodevelopmental disorders (NDDs), and these often involve rare (<1% frequency) copy number variations (CNVs), which can involve one or more genes. Monozygotic (MZ) twin pairs are long thought to share 100% of their genomic information. However, genetic differences in the form of postzygotic somatic variants have been reported recently both in typically developing (TD) and in clinically discordant MZ pairs. Here, we sought to investigate the contribution of CNVs in 100 twin pairs enriched for NDD phenotypes with a particular focus on MZ pairs discordant for autism spectrum disorder (ASD) using the PsychChip array. In our collection, no postzygotic de novo CNVs were found in 55 MZ twin pairs, including the 13 pairs discordant for ASD. When analyzing the burden of rare CNVs among pairs concordant and discordant for ASD/NDD in comparison with typically developed (TD) pairs, no differences were found. However, we did detect a higher rate of CNVs overlapping genes involved in disorders of the nervous system in MZ pairs discordant and concordant for ASD in comparison with TD pairs (p=0.02). Our results are in concordance with earlier findings that postzygotic de novo CNV events are typically rare in genomic DNA derived from saliva or blood and, in the majority of MZ twins, do not explain the discordance of NDDs. Still, studies investigating postzygotic variation in MZ discordant twins using DNA from different tissues and single cells and higher resolution genomics are needed in the future.

genetics↗