Proteomics analysis of extracellular vesicles for biomarkers of autism spectrum disorder.

IF 3.9 3区生物学 Q2 BIOCHEMISTRY & MOLECULAR BIOLOGY Frontiers in Molecular Biosciences Pub Date : 2024-11-11 eCollection Date: 2024-01-01 DOI:10.3389/fmolb.2024.1467398

Houda Yasmine Ali Moussa, Kyung Chul Shin, Alberto de la Fuente, Ilham Bensmail, Houari B Abdesselem, Janarthanan Ponraj, Said Mansour, Fouad A Al-Shaban, Lawrence W Stanton, Sara A Abdulla, Yongsoo Park

{"title":"Proteomics analysis of extracellular vesicles for biomarkers of autism spectrum disorder.","authors":"Houda Yasmine Ali Moussa, Kyung Chul Shin, Alberto de la Fuente, Ilham Bensmail, Houari B Abdesselem, Janarthanan Ponraj, Said Mansour, Fouad A Al-Shaban, Lawrence W Stanton, Sara A Abdulla, Yongsoo Park","doi":"10.3389/fmolb.2024.1467398","DOIUrl":null,"url":null,"abstract":"Background: Autism 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.Methods: To 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.Results: No 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.Conclusion: We identified the top five downregulated proteins in ASD EVs and examined that a combination of EV proteins could serve as biomarkers for ASD diagnosis.","PeriodicalId":12465,"journal":{"name":"Frontiers in Molecular Biosciences","volume":"11 ","pages":"1467398"},"PeriodicalIF":3.9000,"publicationDate":"2024-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11599737/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in Molecular Biosciences","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.3389/fmolb.2024.1467398","RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}

引用次数: 0

Abstract

Background: Autism 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.

Methods: To 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.

Results: No 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.

Conclusion: We identified the top five downregulated proteins in ASD EVs and examined that a combination of EV proteins could serve as biomarkers for ASD diagnosis.

查看原文

微信好友朋友圈 QQ好友复制链接

本刊更多论文

对细胞外囊泡进行蛋白质组学分析，寻找自闭症谱系障碍的生物标志物。

背景：自闭症谱系障碍（ASD）是一种神经发育障碍，其症状包括社交互动障碍、语言障碍和局限性重复行为。通过药物和行为疗法进行早期干预，可以消除自闭症谱系障碍的部分相关症状，显著改善患者的生活质量。目前，对 ASD 的诊断非常有限：为了研究早期诊断 ASD 的可行性，我们检测了从 ASD 病例中获得的细胞外囊泡 (EVs) 蛋白质。首先，我们分离了健康对照组（HCs）和ASD患者的血浆EVs，并利用近距离延伸测定（PEA）技术分析了1196种蛋白质的表达水平。其次，应用机器学习分析和生物信息学方法探讨如何将EV蛋白组合作为诊断ASD的生物标志物：结果：HCs和ASD的EV形态和EV大小分布无明显差异，但ASD血浆中的EV数量略低。我们确定了从ASD个体分离的血浆EV中五大下调蛋白：含 WW 结构域的蛋白 2（WWP2）、热休克蛋白 27（HSP27）、C 型凝集素结构域家族 1 成员 B（CLEC1B）、分化簇 40（CD40）和叶酸受体α（FRalpha）。机器学习分析和相关性分析支持了这五种EV蛋白可作为ASD潜在生物标志物的观点：结论：我们确定了 ASD EV 中前五种下调蛋白，并研究了 EV 蛋白的组合可作为诊断 ASD 的生物标记物。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文去求助

来源期刊

Frontiers in Molecular Biosciences Biochemistry, Genetics and Molecular Biology-Biochemistry

CiteScore

7.20

自引率

4.00%

发文量

1361

审稿时长

14 weeks

期刊介绍： Much of contemporary investigation in the life sciences is devoted to the molecular-scale understanding of the relationships between genes and the environment — in particular, dynamic alterations in the levels, modifications, and interactions of cellular effectors, including proteins. Frontiers in Molecular Biosciences offers an international publication platform for basic as well as applied research; we encourage contributions spanning both established and emerging areas of biology. To this end, the journal draws from empirical disciplines such as structural biology, enzymology, biochemistry, and biophysics, capitalizing as well on the technological advancements that have enabled metabolomics and proteomics measurements in massively parallel throughput, and the development of robust and innovative computational biology strategies. We also recognize influences from medicine and technology, welcoming studies in molecular genetics, molecular diagnostics and therapeutics, and nanotechnology. Our ultimate objective is the comprehensive illustration of the molecular mechanisms regulating proteins, nucleic acids, carbohydrates, lipids, and small metabolites in organisms across all branches of life. In addition to interesting new findings, techniques, and applications, Frontiers in Molecular Biosciences will consider new testable hypotheses to inspire different perspectives and stimulate scientific dialogue. The integration of in silico, in vitro, and in vivo approaches will benefit endeavors across all domains of the life sciences.