Integrated Molecular Profiling of Vascular Disorders for Biomarker Discovery and Therapeutic Target Discovery

Abstract

The disease is predominantly associated with pathological features, including the deposition of extracellular amyloid-β plaques, the formation of intracellular neurofibrillary tangles composed of hyperphosphorylated tau protein, synaptic dysfunction, and progressive neuronal loss. In addition to these classical hallmarks, the progression of the disease is significantly influenced by processes such as neuroinflammation, oxidative stress, metabolic imbalance, and lipid dysregulation. The necessity for more sensitive molecular approaches for early diagnosis is underscored by the fact that traditional diagnostic methods, such as clinical assessment, neuroimaging, and cerebrospinal fluid biomarkers, frequently detect the disease at relatively advanced stages. In the past few years, omics technologies, such as proteomics, lipidomic, glycemic, and integrated multi-omics approaches, have become potent instruments for comprehending the intricate molecular mechanisms that underlie Alzheimer's disease. These technologies facilitate the identification of disease-specific molecular signatures and potential biomarkers by enabling the large-scale analysis of proteins, lipids, and glycans. These integrative strategies have the potential to identify therapeutic targets for drug development and discover novel biomarkers for early diagnosis. Additionally, the implementation of precision medicine methodologies that are predicated on multi-omics data may facilitate the development of personalized treatment strategies for patients. This review provides a concise summary of the current state of knowledge regarding the pathophysiology of Alzheimer's disease and emphasizes the importance of proteomics, lipidomic, glycemic, and integrated multi-omics approaches in the exploration of biomarkers, the enhancement of early diagnosis, and the support of the development of targeted therapeutic strategies for Alzheimer's disease.