Leveraging Biomedical Ontologies to Decipher the Genetic and Molecular Landscape of Alzheimer’s Disease 

Alzheimer’s disease (AD) is a complex neurodegenerative disorder characterized by progressive cognitive decline, amyloid-beta plaque accumulation, and tau protein tangles. Understanding its multifactorial nature requires integrating genetic, molecular, and phenotypic data across multiple studies. Biomedical ontologies, such as the Gene Ontology (GO), Human Phenotype Ontology (HPO), and specialized Alzheimer’s Disease Ontology (ADO), provide a structured framework to represent this knowledge systematically. By encoding genes, proteins, biological processes, and clinical phenotypes along with their interrelationships, ontologies enable researchers to analyze large datasets, identify novel gene-disease associations, map disease-relevant pathways, and support computational predictions. Leveraging ontologies in Alzheimer’s research not only facilitates knowledge integration and standardization but also enhances the discovery of potential biomarkers and therapeutic targets, ultimately accelerating our understanding of disease mechanisms and progression.