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◆ Psychiatry and Clinical Neurosciences2026-04-14· Transcriptome

Integrated transcriptomic and clinical analysis of autism spectrum disorder reveals structured heterogeneity and links <i>Methyl‐CpG Binding Domain Protein 2</i> expression with symptom severity

Wasana Yuwattana, Chayanit Poolcharoen, Thanit Saeliw, Marlieke Lisanne van Erp, Songphon Kanlayaprasit, Natchaya Vanwong, Valerie W. Hu, Pon Trairatvorakul, Weerasak Chonchaiya, Kim‐Anh Lê Cao, Tewarit Sarachana

原始摘要(英文原文)· Original abstract
AIM: Autism spectrum disorder (ASD) remains underexplored in Southeast Asia, with limited characterization of its molecular underpinnings and clinical heterogeneity. This study investigated transcriptomic variation and its relationship to clinical diversity in Thai children with ASD using integrated molecular and phenotypic analyses. METHOD: Peripheral blood transcriptomic profiling was performed in 150 ASD and 70 typically developing (TD) children to identify differentially expressed transcripts (DETs), followed by pathway enrichment, unsupervised molecular clustering, and integrative multiomics modeling. Clinical data from 200 ASD and 110 TD participants were analyzed in parallel to evaluate screening performance and derive phenotype-based subgroups. RESULTS: Differential expression analysis identified 1,407 DETs with significant enrichment of autism-associated genes. Pathway analysis consistently implicated dysregulation of protein-synthesis machinery. Unsupervised transcriptome-based clustering revealed three molecular subgroups characterized by translational, innate-immune, and interferon-associated signatures, which did not directly correspond to clinical severity, age, or cognitive level, indicating structured biological heterogeneity beyond symptom-based classification. Integration of transcriptomic and phenotypic data demonstrated moderate cross-domain correspondence. Among recurrent molecular signals, MBD2 showed consistent upregulation across subgroups and strong associations with social-interaction measures (r = 0.74). In parallel, clinical machine-learning models showed high within-cohort screening performance, while a refined 17-transcript panel achieved robust discriminative accuracy, supporting the complementary role of molecular features in ASD stratification. CONCLUSION: Transcriptomic stratification reveals biologically structured heterogeneity in ASD that is only partially reflected in clinical presentation, supporting a multilayered framework integrating molecular and phenotypic dimensions.
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Integrated transcriptomic and clinical analysis of autism spectrum disorder reveals structured heterogeneity and links <i>Methyl‐CpG Binding Domain Protein 2</i> expression with symptom severity — 科研速览 Science Skim