Cardillo Madison, Katam Keyura, Suravajhala Prashanth
Department of Biological Sciences, Florida A&M University, Tallahassee, FL, United States.
College of Arts and Sciences, Florida State University, Tallahassee, FL, United States.
Front Aging Neurosci. 2025 Jul 23;17:1591796. doi: 10.3389/fnagi.2025.1591796. eCollection 2025.
Alzheimer's disease (AD) is a growing global challenge, representing the most common neurodegenerative disorder and affecting millions of lives. As life expectancy continues to rise and populations expand, the number of individuals coping with the cognitive declines caused by AD is projected to double in the coming years. By 2050, we may see over 115 million people diagnosed with this devastating condition. Unfortunately, while we currently lack effective cures, there are preventative measures that can slow disease progression in symptomatic patients. Thus, research has shifted toward early detection and intervention for AD in recent years. With technological advances, we are now harnessing large datasets and more efficient, minimally invasive methods for diagnosis and treatment. This review highlights critical demographic insights, health conditions that increase the risk of developing AD, and lifestyle factors in midlife that can potentially trigger its onset. Additionally, we delve into the promising role of plant-based metabolites and their sources, which may help delay the disease's progression. The innovative multi-omics research is transforming our understanding of AD. This approach enables comprehensive data analysis from diverse cell types and biological processes, offering possible biomarkers of this disease's mechanisms. We present the latest advancements in genomics, transcriptomics, Epigenomics, proteomics, and metabolomics, including significant progress in gene editing technologies. When combined with machine learning and artificial intelligence, multi-omics analysis becomes a powerful tool for uncovering the complexities of AD pathogenesis. We also explore current trends in the application of radiomics and machine learning, emphasizing how integrating multi-omics data can transform our approach to AD research and treatment. Together, these pioneering advancements promise to develop more effective preventive and therapeutic strategies soon.
阿尔茨海默病（AD）是一个日益严峻的全球性挑战，它是最常见的神经退行性疾病，影响着数百万人的生活。随着预期寿命的持续增长和人口的增加，预计在未来几年，应对由AD导致的认知衰退的人数将翻倍。到2050年，我们可能会看到超过1.15亿人被诊断患有这种毁灭性疾病。不幸的是，尽管我们目前缺乏有效的治愈方法，但有一些预防措施可以减缓症状性患者的疾病进展。因此，近年来研究已转向AD的早期检测和干预。随着技术进步，我们现在正在利用大型数据集以及更高效、微创的诊断和治疗方法。本综述重点介绍了关键的人口统计学见解、增加患AD风险的健康状况以及中年时期可能引发其发病的生活方式因素。此外深入探讨了植物源代谢产物及其来源的潜在作用，它们可能有助于延缓疾病进展。创新性的多组学研究正在改变我们对AD的理解。这种方法能够对来自不同细胞类型和生物过程的全面数据进行分析，提供有关该疾病机制的可能生物标志物。我们介绍了基因组学、转录组学、表观基因组学、蛋白质组学和代谢组学的最新进展，包括基因编辑技术的重大进展。当与机器学习和人工智能相结合时，多组学分析成为揭示AD发病机制复杂性的强大工具。我们还探讨了放射组学和机器学习应用的当前趋势，强调整合多组学数据如何能够改变我们的AD研究和治疗方法。这些开创性进展共同有望很快开发出更有效的预防和治疗策略。
