Abstract
Neurodegenerative diseases (NDs) such as Alzheimer's and Parkinson's disease are characterized by complex genetic and regulatory landscapes. Genome-wide association studies (GWAS) and transcriptome-wide association studies (TWAS) have become two essential and complementary methods for investigating the genetic basis of these disorders. GWAS systematically identifies genetic variants associated with disease risk, while TWAS provides functional insight by integrating expression quantitative trait loci to infer the effects of genetically regulated gene expression on complex traits. The aim of this review was to provide a comprehensive overview of methodological developments and integrative applications of GWAS and TWAS in the context of NDs research. We first conducted a bibliometric analysis that delineates evolving research trends and identifies emerging focal areas in the field. We then compared the underlying assumptions, strengths, and analytical frameworks of GWAS and TWAS. Subsequently, we highlighted recent advances in TWAS methodology, including fine-mapping strategies, multi-tissue and single-cell modeling, integration of multi-omic data layers, and applications of machine learning and artificial intelligence. Finally, current challenges related to ancestry representation, reference panel diversity, and translational generalizability were also presented. By synthesizing these perspectives, this review clarified the methodological landscape, guided future integrative analyses, and supported the broader application of transcriptome-informed genetic approaches in understanding and treating NDs.