Jain Mukul, Dhariwal Rupal, Patil Nil, Ojha Sandhya, Tendulkar Reshma, Tendulkar Mugdha, Dhanda Parmdeep Singh, Yadav Alpa, Kaushik Prashant
Cell and Developmental Biology Laboratory, Research and Development Cell, Parul University, Vadodara 391760, India.
Department of Life Sciences, Parul Institute of Applied Sciences, Parul University, Vadodara 391760, India.
Proteomes. 2023 Oct 16;11(4):33. doi: 10.3390/proteomes11040033.
Alzheimer's disease (AD) is a devastating neurodegenerative disorder characterized by progressive cognitive decline and memory loss. Early and accurate diagnosis of AD is crucial for implementing timely interventions and developing effective therapeutic strategies. Proteome-based biomarkers have emerged as promising tools for AD diagnosis and prognosis due to their ability to reflect disease-specific molecular alterations. There is of great significance for biomarkers in AD diagnosis and management. It emphasizes the limitations of existing diagnostic approaches and the need for reliable and accessible biomarkers. Proteomics, a field that comprehensively analyzes the entire protein complement of cells, tissues, or bio fluids, is presented as a powerful tool for identifying AD biomarkers. There is a diverse range of proteomic approaches employed in AD research, including mass spectrometry, two-dimensional gel electrophoresis, and protein microarrays. The challenges associated with identifying reliable biomarkers, such as sample heterogeneity and the dynamic nature of the disease. There are well-known proteins implicated in AD pathogenesis, such as amyloid-beta peptides, tau protein, Apo lipoprotein E, and clusterin, as well as inflammatory markers and complement proteins. Validation and clinical utility of proteome-based biomarkers are addressing the challenges involved in validation studies and the diagnostic accuracy of these biomarkers. There is great potential in monitoring disease progression and response to treatment, thereby aiding in personalized medicine approaches for AD patients. There is a great role for bioinformatics and data analysis in proteomics for AD biomarker research and the importance of data preprocessing, statistical analysis, pathway analysis, and integration of multi-omics data for a comprehensive understanding of AD pathophysiology. In conclusion, proteome-based biomarkers hold great promise in the field of AD research. They provide valuable insights into disease mechanisms, aid in early diagnosis, and facilitate personalized treatment strategies. However, further research and validation studies are necessary to harness the full potential of proteome-based biomarkers in clinical practice.
阿尔茨海默病（AD）是一种毁灭性的神经退行性疾病，其特征为进行性认知衰退和记忆丧失。AD的早期准确诊断对于实施及时干预和制定有效的治疗策略至关重要。基于蛋白质组的生物标志物因其能够反映疾病特异性分子改变，已成为AD诊断和预后的有前景的工具。生物标志物在AD诊断和管理中具有重要意义。它强调了现有诊断方法的局限性以及对可靠且可获取的生物标志物的需求。蛋白质组学作为一个全面分析细胞、组织或生物体液中整个蛋白质组的领域，被视为识别AD生物标志物的强大工具。AD研究中采用了多种蛋白质组学方法，包括质谱分析、二维凝胶电泳和蛋白质微阵列。与识别可靠生物标志物相关的挑战，如样本异质性和疾病的动态性质。有一些众所周知的与AD发病机制相关的蛋白质，如β-淀粉样肽、tau蛋白、载脂蛋白E和簇集蛋白，以及炎症标志物和补体蛋白。基于蛋白质组的生物标志物的验证和临床实用性正在应对验证研究中涉及的挑战以及这些生物标志物的诊断准确性。在监测疾病进展和治疗反应方面具有巨大潜力，从而有助于针对AD患者的个性化医疗方法。生物信息学和数据分析在AD生物标志物研究的蛋白质组学中具有重要作用，以及数据预处理、统计分析、通路分析和多组学数据整合对于全面理解AD病理生理学的重要性。总之，基于蛋白质组的生物标志物在AD研究领域具有巨大潜力。它们为疾病机制提供了有价值的见解，有助于早期诊断，并促进个性化治疗策略。然而，需要进一步的研究和验证研究来充分发挥基于蛋白质组的生物标志物在临床实践中的潜力。
