Using High-Throughput Animal or Cell-Based Models to Functionally Characterize GWAS Signals.

Area of Science:

• Genetics and Genomics
• Neuroscience
• Biotechnology

Background:

• Genome-wide association studies (GWASs) have revolutionized the understanding of multifactorial disease genetics.
• Over 20 risk loci for Alzheimer's disease (AD) have been identified, but functional characterization remains a challenge.
• Key challenges include identifying functional single nucleotide polymorphisms (SNPs), causal genes, and their pathogenic mechanisms.

Purpose of the Study:

• To review high-throughput strategies for functionally characterizing GWAS signals in Alzheimer's disease.
• To discuss the application of these methods in cell-based and whole-animal models.
• To highlight the potential of these strategies in translating GWAS findings into clinical applications.

Main Methods:

• Review of high-throughput screening techniques.
• Review of high-content screening approaches.
• Application of the Drosophila model for functional genomics studies relevant to AD.

Main Results:

• These high-throughput strategies have been successfully employed to functionally characterize genes within GWAS-defined risk loci.
• The Drosophila model offers a powerful platform for dissecting the functional roles of AD-associated genes.
• Cell-based and whole-animal models facilitate the investigation of gene function and pathogenic contributions.

Conclusions:

• Functional characterization of GWAS signals is crucial for understanding disease pathogenesis.
• High-throughput screening and model systems provide effective tools for this characterization.
• These strategies hold promise for advancing knowledge and developing treatments for Alzheimer's disease.