Omics-based biomarkers discovery for Alzheimer's disease

Area of Science:

• Neuroscience
• Biomarker Discovery
• Genomics

Background:

• Alzheimer's disease (AD) is a common neurodegenerative disorder characterized by amyloid plaques and tau tangles.
• Identifying reliable biomarkers is crucial for early diagnosis and effective management of AD.
• Current diagnostic tools for AD require improvement to accurately reflect disease complexity.

Purpose of the Study:

• To review the role of high-throughput omics technologies in Alzheimer's disease biomarker discovery.
• To explore how genomics, transcriptomics, proteomics, and metabolomics contribute to understanding AD pathophysiology.
• To highlight the potential of multi-omics data for improving clinical AD diagnosis and management.

Main Methods:

• Review of current literature on Alzheimer's disease pathology and biomarkers.
• Analysis of high-throughput omics data (genomics, transcriptomics, proteomics, metabolomics).
• Examination of interaction networks between different molecular levels in AD.

Main Results:

• Omics technologies provide unbiased, multi-level data for detecting complex AD etiology.
• Multi-omics approaches reveal interaction networks crucial for understanding AD.
• Genomics, transcriptomics, proteomics, and metabolomics are all contributing to the discovery of reliable AD biomarkers.

Conclusions:

• High-throughput omics technologies are essential for identifying robust Alzheimer's disease biomarkers.
• Multi-omics integration enhances the understanding of AD pathophysiology.
• These biomarkers hold promise for improved clinical diagnosis and management of Alzheimer's disease.