Table 1_Proteomics analysis of extracellular vesicles for biomarkers of autism spectrum disorder.xlsx

BackgroundAutism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by symptoms that include social interaction deficits, language difficulties and restricted, repetitive behavior. Early intervention through medication and behavioral therapy can eliminate some ASD-related symptoms and significantly improve the life-quality of the affected individuals. Currently, the diagnosis of ASD is highly limited.
MethodsTo investigate the feasibility of early diagnosis of ASD, we tested extracellular vesicles (EVs) proteins obtained from ASD cases. First, plasma EVs were isolated from healthy controls (HCs) and ASD individuals and were analyzed using proximity extension assay (PEA) technology to quantify 1,196 protein expression level. Second, machine learning analysis and bioinformatic approaches were applied to explore how a combination of EV proteins could serve as biomarkers for ASD diagnosis.
ResultsNo significant differences in the EV morphology and EV size distribution between HCs and ASD were observed, but the EV number was slightly lower in ASD plasma. We identified the top five downregulated proteins in plasma EVs isolated from ASD individuals: WW domain-containing protein 2 (WWP2), Heat shock protein 27 (HSP27), C-type lectin domain family 1 member B (CLEC1B), Cluster of differentiation 40 (CD40), and folate receptor alpha (FRalpha). Machine learning analysis and correlation analysis support the idea that these five EV proteins can be potential biomarkers for ASD.
ConclusionWe identified the top five downregulated proteins in ASD EVs and examined that a combination of EV proteins could serve as biomarkers for ASD diagnosis.

背景：自闭症谱系障碍（Autism spectrum disorder, ASD）是一类以社交互动缺陷、语言障碍以及局限重复性行为为核心特征的神经发育障碍。通过药物干预与行为疗法开展的早期诊疗，可减轻部分ASD相关症状，显著改善患者的生活质量。当前，ASD的临床诊断仍存在较大局限性。
方法：为探究ASD早期诊断的可行性，本研究对自闭症患者来源的细胞外囊泡（extracellular vesicles, EVs）蛋白进行了检测。首先，我们从健康对照（healthy controls, HCs）与自闭症个体中分离血浆EVs，并采用邻近延伸测定（proximity extension assay, PEA）技术对1196种蛋白质的表达水平进行定量分析；其次，通过机器学习分析与生物信息学方法，探索EVs蛋白组合作为ASD诊断生物标志物的可能性。
结果：未观察到健康对照与自闭症患者的EVs形态及粒径分布存在显著差异，但自闭症患者血浆中的EVs数量略有降低。本研究在自闭症个体分离的血浆EVs中鉴定出排名前五的下调蛋白：含WW结构域蛋白2（WW domain-containing protein 2, WWP2）、热休克蛋白27（Heat shock protein 27, HSP27）、C型凝集素结构域家族1成员B（C-type lectin domain family 1 member B, CLEC1B）、分化簇40（Cluster of differentiation 40, CD40）以及叶酸受体α（folate receptor alpha, FRα）。机器学习分析与相关性分析结果证实，这5种EVs蛋白可作为ASD诊断的潜在生物标志物。
结论：本研究在自闭症患者的EVs中鉴定出5种显著下调的蛋白，并验证了EVs蛋白组合可作为ASD诊断的生物标志物。