Autism Spectrum Disorder Research

This study uses pupillometry to show that autistic children have more variable and idiosyncratic pupil responses compared to typically developing children, with significant classification accuracy.

This study identifies genetic variants associated with fetal ultrasound anomalies in children with autism spectrum disorder using whole exome sequencing and a bioinformatics pipeline.

This study shows that DSCAM heterozygosity in mice produces autistic-like behaviors, supporting its role in ASD and suggesting it as a model for research.

The paper compares genetic and cellular differences between autism and schizophrenia using GWAS and iPSC-derived neurons, finding shared SNPs and similar synaptic deficits.

The paper uses multi-parametric behavioral assays to capture sex- and environment-dependent behavioral differences in autism mouse models, showing improved classification accuracy compared to classical tests.

This study examines predictive coding irregularities in a non-human primate ASD model, finding sensory hypersensitivity and unstable predictions across brain hierarchies with diverse error configurations.

This study uses high-density electrophysiological mapping to compare somatosensory temporal sensitivity between autistic and neurotypical adults using the MMN paradigm, finding no group differences in discrimination but subtle amplitude differences.

This study finds delayed feedback in autism spectrum disorder (ASD) during visual contour integration, suggesting weakened predictive mechanisms in sensory processing.

The paper investigates spindle chirp and other sleep oscillatory features in young children with and without autism, finding significant differences in chirp negativity and coupling angles.

This study identifies ASD-like transcriptomic changes in oligodendrocytes and microglia of C58/J mice amygdala, dependent on sex and sociability, using bulk RNA-Seq and snRNA-Seq.

The paper examines genetic and phenotypic heterogeneity in early neurodevelopmental traits using data from the Norwegian Mother, Father, and Child Cohort Study, identifying 11 latent factors and trait-specific genetic correlations with autism, ADHD, and schizophrenia.

EAGER establishes a registry of autistic individuals and those with rare genetic conditions for genomic and phenotypic research, aiming to improve clinical trials and health outcomes through data sharing.

This study shows that loss of Pcdh10 in interneurons affects socio-affective communication in mice, with heterozygous pups showing more pronounced behavioral changes.

The paper uses single nuclear RNAseq and epigenetic profiling to identify molecular changes and cell-type specific signatures in ASD, linking them to genetic risk factors.

The paper examines hemispheric lateralization differences in autistic males compared to neurotypical individuals, finding reduced lateralization in specific brain networks and a link to language delay.

This study shows that rare CNVs and PRS-IQ increase ASD risk independently of their effects on cognitive ability, suggesting ASD risk and cognitive ability are distinct outcomes of these variants.

The paper uses structural equation modeling to identify three genetic factors linked to language/cognition, behavior, and motor development in ASD, revealing novel associations and simplex-specific genetic overlaps.

The paper identifies impaired cerebellar plasticity as a mechanism underlying hypersensitized sensory reflexes in SCN2A-associated ASD, showing that increasing Scn2a expression rescues VOR plasticity in mice.

The paper investigates structural connectome asymmetry in autism, finding atypical asymmetry in specific brain networks and associations with communication symptoms and intelligence.

This study found no significant differences in cerebral glutathione or GABA levels between autistic children and typically developing children, but found a positive correlation between GABA levels and ADHD inattention scores.

The paper examines morphological differences in tertiary sulci between individuals with autism spectrum disorder and neurotypical controls, finding altered cortical thickness and length in specific regions and correlations with cognitive scores.

The paper curates causal gene-protein interactions linked to autism and develops tools to explore their functional relationships with phenotypes and pathways.

This study identifies miRNAs downregulated in ASD patients and uses machine learning to predict prognostic biomarkers for improved ASD diagnosis.

The paper analyzes longitudinal eye-tracking data to show divergent gaze patterns in children with autism compared to typically developing peers during social interaction viewing, with differences increasing over time.

This study uses multimodal imaging and connectivity modeling to show that polysynaptic mechanisms are implicated in autism spectrum disorder, with reduced structure-function coupling in transmodal networks.

The paper introduces a multi-polygenic risk score approach to study ASD's genetic architecture, finding that multi-PRSs capture similar risk as traditional PRS-ASD but reveal developmental mirroring effects.

This study shows that elevated body temperature without inflammation improves behavioral signs in two ASD animal models.

This study compares neurodevelopmental disorders and cancer, finding shared pathways but differing in signaling strength and outcomes.