Identifies five biomarkers in synaptic interneurons of autism, indicating potential for targeted intervention.
Background: Autism Spectrum Disorder (ASD) is a highly heterogeneous neurodevelopmental condition. Single-cell RNA sequencing (scRNA-seq) has revealed transcriptional disruptions, particularly in interneurons, yet their subtypes and molecular signatures remain poorly understood. Methods: It was analyzed scRNA-seq data from the human Prefrontal Cortex (PFC). Key cell types were identified using Scissor and ROGUE methods, followed by secondary clustering for subtype annotation. A signature matrix was established using CIBERSORTx to deconvolute the bulk transcriptomes and estimate cell type-specific proportions. Differential subtype proportions between ASD and control samples were compared to identify key cell subtypes. Differentially Expressed Genes (DEGs) from both the key subtype and bulk data were intersected to determine subtypespecific biomarkers, which were further assessed via molecular docking. Results: Interneurons were identified as the most heterogeneous cell population in ASD-affected PFC and were further categorized into five subtypes. A signature matrix was then developed with CIBERSORTx to reflect the proportion of each cell type and subtype. Among the cell subtypes, synaptic membrane-integrating interneurons (SMI-IN) emerged as the key subtypes, which exhibited notable distinctions between the ASD and control samples. Furthermore, five potential biomarkers (PRELID2, MYO1B, LRCH2, LIFR, and RERG) were identified from the SMI-IN subtype. Finally, quercetin and coumestrol were predicted as potential therapeutic compounds targeting these biomarkers. Nevertheless, as all findings were obtained via computational analysis, further cellular and clinical experiments are required to validate these identified biomarkers and candidate compounds. Discussion: This study focused on interneurons and identified SMI-IN as a key cell subtype and its potential biomarkers (PRELID2, MYO1B, LRCH2, LIFR, and RERG). Conclusion: The present findings provided new insights for ASD intervention.
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Zhang et al. (2026) studied this question.
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