Plasma Extracellular Vesicle-Associated Proteins as Promising Diagnostic Biomarkers of Age-Related Macular Degeneration.

Rouan Chen, Yuxuan Wu, Yiming Fang, Tian Lan, Wei Shi
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Abstract

Background: Age-related macular degeneration (AMD) is a significant factor causing blindness in adults. However, the clinical diagnosis of AMD is relatively challenging, due to the shortcomings of the existing clinical examination methods and the latent period of retinal damage before macular degeneration becomes apparent. This study aims to explore the potential of extracellular vesicles (EVs) protein chips for early diagnosis of AMD using patients' plasma samples.

Methods: To achieve early diagnosis of AMD, this study utilized a high-throughput platform for liquid biopsy based on EVs protein chips. Forty AMD patients and 41 normal individuals were recruited. Through machine learning methods, we identified that ATP-binding cassette transporter A1 (ABCA1) is an EVs protein marker for diagnosing AMD. Additionally, a validation set was constructed using the random forest method for verification.

Results: The results of the study indicated that ABCA1 is a reliable biomarker for diagnosing AMD. The validation using the random forest method confirmed the robustness and reliability of ABCA1 as a diagnostic marker. This finding suggested that ABCA1 can serve as a new promising liquid biopsy-based marker for diagnosing macular degeneration.

Conclusion: The utilization of EVs protein chips, combined with machine learning methods, can effectively identify ABCA1 as a biomarker for the early diagnosis of AMD. This approach offers a promising new method for liquid biopsy diagnostics, potentially improving the clinical diagnosis and management of macular degeneration.

血浆细胞外囊泡相关蛋白有望成为老年性黄斑变性的诊断生物标志物。
背景:年龄相关性黄斑变性(AMD)是导致成人失明的重要因素。然而,由于现有临床检查方法的不足,以及黄斑变性前视网膜损伤的潜伏期变得明显,AMD的临床诊断相对具有挑战性。本研究旨在探讨细胞外囊泡(EVs)蛋白芯片在利用患者血浆样本进行AMD早期诊断中的潜力。方法:为了实现AMD的早期诊断,本研究利用基于EVs蛋白芯片的高通量液体活检平台。招募了40名AMD患者和41名正常人。通过机器学习方法,我们发现atp结合盒转运蛋白A1 (ABCA1)是诊断AMD的ev蛋白标记物。另外,利用随机森林方法构造验证集进行验证。结果:本研究结果提示ABCA1是诊断AMD的可靠生物标志物。随机森林方法验证了ABCA1作为诊断标记的稳健性和可靠性。这一发现提示ABCA1可以作为一种新的有前景的基于液体活检的黄斑变性诊断标志物。结论:利用EVs蛋白芯片,结合机器学习方法,可有效识别ABCA1作为AMD早期诊断的生物标志物。该方法为液体活检诊断提供了一种有前途的新方法,有可能改善黄斑变性的临床诊断和治疗。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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