A Module-Level Polygenic Risk Score-Based NetWAS Framework for Identifying AD Genetic Modules Mediated by Amygdala:...

Area of Science:

• Neuroscience
• Genetics
• Medical Imaging

Background:

• Network-based Genome-Wide Association Studies (NetWAS) identify genetic modules linked to brain changes.
• The functional role of imaging risk genes and their mediation via imaging quantitative traits (iQTs) in brain diseases is not well understood.

Purpose of the Study:

• To develop and validate a module-level polygenic risk score (MPRS)-based NetWAS framework.
• To uncover genetic modules associated with Alzheimer's disease (AD) through the mediation of an iQT, using amygdala density as a case study.

Main Methods:

• Integrated genotype data, brain imaging phenotypes, AD diagnosis, and protein-protein interaction (PPI) networks.
• Conducted a GWAS for amygdala density and mapped associated variants onto a PPI network.
• Calculated MPRS for AD using meta-GWAS data to identify AD-relevant modules (ADMs).

Main Results:

• Identified four significant ADMs that showed differences in MPRS between AD patients and controls.
• These ADMs demonstrated strong modularity, were sensitive to early AD stages, and mediated the link between genetics and AD progression via the amygdala.
• The identified modules showed high tissue specificity in the amygdala and were enriched in AD-related biological pathways.

Conclusions:

• The MPRS-based NetWAS framework effectively bridges genetics, intermediate traits (iQTs), and clinical outcomes in AD research.
• This framework offers a novel approach for identifying disease-associated genetic modules and can be adapted for other biomedical applications.