Genetic Risk Architecture of Late-Onset Alzheimer’s Disease: Mapping Single-Nucleotide Polymorphisms to Disease-Defining Molecular Pathways

Late-onset Alzheimer’s disease (LOAD) is increasingly recognized as a complex, multifactorial disorder driven by the convergence of genetic susceptibility and interconnected molecular pathways, rather than a single linear pathogenic cascade. In this review, we integrate evidence from genome-wide association studies, sequencing analyses, and experimental research to map disease-associated single-nucleotide polymorphisms (SNPs) onto key biological processes underlying LOAD pathogenesis. Converging data consistently implicate a limited number of core domains, including amyloid-β metabolism, tau pathology, neuroinflammation, lipid homeostasis, endosomal–lysosomal trafficking, mitochondrial dysfunction, and synaptic impairment. Importantly, genetic risk variants are not randomly distributed, but cluster within these pathways, exerting coordinated effects across multiple biological systems and supporting a network-based organization of disease. We further examine how these pathways interact at a systems level, highlighting key interfaces such as the amyloid–tau, lipid–immune, inflammation–proteostasis, and mitochondria–synaptic dysfunction axes. These interconnected processes form self-reinforcing feedback loops that amplify neurodegeneration and contribute to disease progression. From a translational perspective, this integrated framework provides a mechanistic basis for the limited efficacy of single-target therapies and supports the development of multi-target and pathway-oriented strategies, as well as precision medicine approaches based on genetic and biomarker integration. Collectively, this review supports a unified model of LOAD as a polygenic network disorder and underscores the importance of pathway convergence in understanding disease heterogeneity and guiding future therapeutic development.