Novel perspective on particulate matter and Alzheimer's disease: insights from adverse outcome pathway framework

Alzheimer's disease (AD) is a neurodegenerative disease, that accounts for 50-75% of all dementia cases. Evidence demonstrates the link between particulate matter (PM) exposure and AD. However, there are still considerable research gaps. This review aims to clarify the mechanism between PM and AD from different levels (subcellular/cellular/system/population) by using an adverse outcome pathway (AOP) framework. We applied a chemical-phenotype interaction network-based workflow to integrate diverse genes and phenotypes. The interactions among PM, genes, phenotypes, and AD were retrieved from the Comparative Toxicogenomics Database (CTD), DisGeNET, MalaCards, Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG), which are publicly available databases. The filtered genes and phenotypes were assembled as molecular initiating events (MIEs) and key events (KEs) according to the upstream and downstream relationships, generating a predictive PM-Gene-Phenotype-AD AOP network. According to the Organization for Economic Co-operation and Development handbook (OECD), a verified AOP network was assessed and applied to determine the effects of PM on AD. PM could increase APP and GSK3B, increase apoptosis, impair cognition and memory, and ultimately lead to AD. Overall, chemical-phenotype interactions are expressed in a formal structured notation using controlled terms for chemicals, phenotypes, taxons, and anatomical descriptors. To our knowledge, this is the first AOP framework focusing on the underlying mechanism of exposure to PM on AD. Our network-based approach not only fills mechanism gaps in PM and AD but sheds light on constructing AOP frameworks for new chemicals.