Biology subjects

Kolevzon, A.

Publications and source records attributed to Kolevzon, A..

4 recordsLinked to original sources

bioRxiv2026

Age-Related Increases in 40Hz Neural Synchrony Are Specific to Typical Development: A Cross-Sectional Study of Autism Spectrum Disorder

Background: The 40Hz auditory steady-state response (ASSR) is a measure of gamma-band neural synchrony sensitive to excitation-inhibition (E/I) balance. Disruptions to E/I balance have been implicated in autism spectrum disorder (ASD), making ASSR an efficient tool for investigating neural synchrony development in this population. Whether age-related differences in 40Hz ASSR are detectable across development in ASD remains understudied. Phelan-McDermid syndrome (PMS), a rare genetic disorder with a phenotype overlapping with autism, caused by SHANK3 disruption, provides a genetically defined model for further investigating E/I-related neural synchrony disruptions. Methods: We examined 40Hz inter-trial phase coherence (ITPC) as an index of neural synchrony across a wide age range (2-37 years) in 127 participants from four groups: TD (n=43), ASD without intellectual disability (w/o ID; n=37), ASD with intellectual disability (w/ID; n=24), and PMS (n=23). Given the distinct age and cognitive profiles of ASD subgroups in this sample, analyses were conducted in separate models: TD vs. ASD w/o ID across all ages, and TD vs. ASD w/ID vs. PMS restricted to participants under 18. Results: For the first time in a cross-sectional sample spanning a large age range, we show that 40Hz ITPC increases significantly with age in TD individuals, while this developmental trajectory is absent in ASD without intellectual disability. Among children and adolescents under 18, 40Hz ITPC did not differ across TD, ASD w/ID, and PMS, and IQ did not predict ITPC in clinical groups. A post-hoc analysis revealed higher ITPC in TD males than females, with no sex differences in ASD or PMS. Conclusions: We demonstrate that gamma-band ITPC trajectories diverge between TD and ASD, specifically in adulthood, with no such difference detectable in childhood. No significant group differences were found among TD, ASD w/ID, and PMS individuals under 18. These findings highlight the importance of age as a critical variable when measuring ASSR, and underscore the need for lifespan studies, particularly in genetically defined conditions such as PMS, to determine whether similar divergence emerges in adulthood.

neuroscience↗

bioRxiv2026

Identifying Phelan-McDermid-Like Electrophysiological Subtypes in Autism Using EEG and Machine Learning

BackgroundPhelan McDermid syndrome (PMS), caused by SHANK3 haploinsufficiency, is a genetic form of autism spectrum disorder (ASD) that provides a genetically defined model for studying ASD-related circuit dysfunction. SHANK3 mutations disrupt synaptic organization and cortical synchrony, leading to attenuated gamma-band auditory steady-state responses (ASSRs). We investigated whether PMS-related electrophysiological signatures could be identified using machine learning and whether similar patterns are present in a subset of individuals with idiopathic ASD (iASD). MethodsEEG recorded during a 40-Hz ASSR paradigm was collected from 123 participants (42 TD aged 2-30, 56 iASD aged 3-31, 25 PMS aged 2-26). We extracted time-series, ERSP, FOOOF-derived spectral, and intertrial phase coherence (ITPC) features. XGBoost models with leave-one-out cross-validation classified PMS versus TD; the best age/sex-adjusted ITPC model was then applied to iASD participants to derive a Synchrony Atypicality Index (SAI). Unsupervised clustering of high-dimensional ITPC features was also performed. ResultsITPC-based models showed the strongest discrimination between TD and PMS participants (AUROC = 0.83). When applied to iASD participants, 35.7% exhibited elevated SAI, indicating a PMS-like gamma-band phase-locking profile. Classification of iASD versus PMS performed poorly in the full sample but improved markedly after excluding high-SAI iASD individuals, consistent with substantial heterogeneity within iASD. Unsupervised clustering of ITPC features identified PMS-enriched clusters that also captured high-SAI iASD participants. Results were consistent after controlling for age in sensitivity analyses. ConclusionsReduced 40-Hz ITPC is a mechanistically interpretable electrophysiological signature of PMS and identifies a biologically meaningful PMS-like subgroup within iASD, supporting biomarker-guided stratification.

neuroscience↗

bioRxiv2024

Blended Genome Exome (BGE) as a Cost Efficient Alternative to Deep Whole Genomes or Arrays

Genomic scientists have long been promised cheaper DNA sequencing, but deep whole genomes are still costly, especially when considered for large cohorts in population-level studies. More affordable options include microarrays + imputation, whole exome sequencing (WES), or low-pass whole genome sequencing (WGS) + imputation. WES + array + imputation has recently been shown to yield 99% of association signals detected by WGS. However, a method free from ascertainment biases of arrays or the need for merging different data types that still benefits from deeper exome coverage to enhance novel coding variant detection does not exist. We developed a new, combined, "Blended Genome Exome" (BGE) in which a whole genome library is generated, an aliquot of that genome is amplified by PCR, the exome regions are selected and enriched, and the genome and exome libraries are combined back into a single tube for sequencing (33% exome, 67% genome). This creates a single CRAM with a low-coverage whole genome (2-3x) combined with a higher coverage exome (30-40x). This BGE can be used for imputing common variants throughout the genome as well as for calling rare coding variants. We tested this new method and observed >99% r2 concordance between imputed BGE data and existing 30x WGS data for exome and genome variants. BGE can serve as a useful and cost-efficient alternative sequencing product for genomic researchers, requiring ten-fold less sequencing compared to 30x WGS without the need for complicated harmonization of array and sequencing data.

genomics↗

bioRxiv2020

Episignatures stratifying ADNP syndrome show modest correlation with phenotype

ADNP syndrome, also known as Helsmoortel-van Der Aa syndrome, is a neurodevelopmental condition associated with intellectual disability/developmental delay, autism spectrum disorder, and multiple medical comorbidities. ADNP syndrome is caused by mutations in the activity-dependent neuroprotective protein (ADNP). A recent study identified genome-wide DNA methylation changes in 22 individuals with ADNP syndrome, adding to the group of neurodevelopmental disorders with an epigenetic signature. This methylation signature segregated those with ADNP syndrome into two groups, based on the location of the mutations. Here, we conducted an independent study on 24 individuals with ADNP syndrome and replicated the existence of the two, mutation-dependent ADNP episignatures. To probe whether the two distinct episignatures correlate with clinical outcomes, we used deep behavioral and neurobiological data from two prospective cohorts of individuals with a genetic diagnosis of ADNP syndrome. We found limited phenotypic differences between the two ADNP groups, and no evidence that individuals with more widespread methylation changes are more severely affected. Also, in spite of the methylation changes, we observed no profound alterations in the blood transcriptome of individuals with ADNP syndrome. Our data warrant caution in harnessing methylation signatures in ADNP syndrome as a tool for clinical stratification, at least with regards to behavioral phenotypes.

developmental biology↗