Vernone Annamaria, Stura Ilaria, Guiot Caterina, D'Agata Federico, Silvagno Francesca
Department of Neurosciences, University of Turin, Via Cherasco 15, 10125 Torino, Italy.
Department of Oncology, University of Turin, Via Santena 5 bis, 10126 Torino, Italy.
Int J Mol Sci. 2025 Aug 4;26(15):7536. doi: 10.3390/ijms26157536.
The search for the biomarkers of Alzheimer's disease (AD) may prove essential in the diagnosis and prognosis of the pathology, and the differential expression of key proteins may assist in identifying new therapeutic targets. In this proof-of-concept (POC) study, a new approach of data mining and matching combined with the biochemical analysis of proteins was applied to AD investigation. Three influential online open databases (UniProt, AlzGene, and Allen Human Brain Atlas) were explored to identify the genes and encoded proteins involved in AD linked to mitochondrial and iron dysmetabolism. The databases were searched using specific keywords to collect information about protein composition, and function, and meta-analysis data about their correlation with AD. The extracted datasets were matched to yield a list of relevant proteins in AD. The biochemical analysis of their amino acid content suggested a defective synthesis of these proteins in poorly oxygenated brain tissue, supporting their relevance in AD progression. The result of our POC study revealed several potential new markers of AD that deserve further molecular and clinical investigation. This novel database search approach can be a valuable strategy for biomarker search that can be exploited in many diseases.
寻找阿尔茨海默病（AD）的生物标志物可能对该疾病的诊断和预后至关重要，关键蛋白的差异表达可能有助于确定新的治疗靶点。在这项概念验证（POC）研究中，一种将数据挖掘与匹配和蛋白质生化分析相结合的新方法被应用于AD研究。研究人员探索了三个有影响力的在线开放数据库（UniProt、AlzGene和艾伦人脑图谱），以识别与线粒体和铁代谢紊乱相关的AD相关基因和编码蛋白。通过使用特定关键词搜索数据库，收集有关蛋白质组成、功能以及它们与AD相关性的荟萃分析数据。对提取的数据集进行匹配，以生成AD相关蛋白列表。对其氨基酸含量的生化分析表明，这些蛋白质在缺氧脑组织中合成存在缺陷，这支持了它们在AD进展中的相关性。我们的POC研究结果揭示了几个潜在的AD新标志物，值得进一步进行分子和临床研究。这种新颖的数据库搜索方法可能是一种有价值的生物标志物搜索策略，可用于多种疾病的研究。
