This review discusses the genetic risk factors for late-onset Alzheimer's disease (LOAD) and their role in disease pathogenesis. Recent advances in genome-wide association studies (GWAS) have identified numerous genes associated with LOAD, including ABCA7, BIN1, CASS4, CD33, CD2AP, CELF1, CLU, CR1, DSG2, EPHA1, FERM2, HLA-DRB5-DBR1, INPP5D, MS4A, MEF2C, NME8, PICALM, PTK2B, SLC24H4 RIN3, SORL1, and ZCWPW1. Emerging technologies have also revealed coding variants that increase LOAD risk, such as PLD3 and TREM2. The review explores the relationship between these AD risk genes and cellular and neuropathological features of the disease. Understanding the mechanisms underlying the association of these genes with risk will provide valuable targets for therapeutic development. The review highlights the importance of Aβ production and clearance in AD pathogenesis and discusses the role of genes involved in cholesterol metabolism, immune response, and endocytosis. It also examines the impact of rare coding variants in genes like TREM2 and PLD3 on LOAD risk. The integration of genetic, expression, and epigenetic data into molecular networks may facilitate a better understanding of the underlying disease mechanisms.This review discusses the genetic risk factors for late-onset Alzheimer's disease (LOAD) and their role in disease pathogenesis. Recent advances in genome-wide association studies (GWAS) have identified numerous genes associated with LOAD, including ABCA7, BIN1, CASS4, CD33, CD2AP, CELF1, CLU, CR1, DSG2, EPHA1, FERM2, HLA-DRB5-DBR1, INPP5D, MS4A, MEF2C, NME8, PICALM, PTK2B, SLC24H4 RIN3, SORL1, and ZCWPW1. Emerging technologies have also revealed coding variants that increase LOAD risk, such as PLD3 and TREM2. The review explores the relationship between these AD risk genes and cellular and neuropathological features of the disease. Understanding the mechanisms underlying the association of these genes with risk will provide valuable targets for therapeutic development. The review highlights the importance of Aβ production and clearance in AD pathogenesis and discusses the role of genes involved in cholesterol metabolism, immune response, and endocytosis. It also examines the impact of rare coding variants in genes like TREM2 and PLD3 on LOAD risk. The integration of genetic, expression, and epigenetic data into molecular networks may facilitate a better understanding of the underlying disease mechanisms.