Search papers, labs, and topics across Lattice.
This review article examines the genetic and gender-related factors influencing Alzheimer's Disease (AD), highlighting the limitations of traditional precision medicine due to the complexity of sporadic late-onset AD genetics. It discusses the role of genome-wide association studies (GWAS) in developing genetic risk scores (GRS) and explores the potential of Artificial Intelligence (AI) for personalized prevention strategies. The review emphasizes the need for a precision-medicine approach to AD that considers genetic, sex, and gender-specific factors.
Genetic and gender-related factors significantly influence Alzheimer's Disease risk, necessitating a shift towards precision medicine approaches incorporating advanced genetic risk scores and AI-driven personalized prevention strategies.
Alzheimer's disease (AD) represents a critical global health challenge, with its prevalence and associated costs expected to double significantly by 2030 and 2050. While lifestyle interventions are crucial, sporadic late-onset AD has a substantial genetic component (40-80% heritability), though known variants limit the scope of traditional precision medicine. Crucially, sex and gender are significant risk determinants, with women accounting for two-thirds of cases due to a complex interplay of biological and sociocultural factors. This review focuses on the influence of genetic and gender-related factors, examining large-scale genome-wide association studies (GWASs) and their role in developing advanced genetic risk scores (GRS) for precision genomics. We also explore the potential of Artificial Intelligence (AI) for multimodal big data analysis and digital health tools to promote personalized prevention and emerging concerns about ethics, privacy and data treatment. The convergence of these findings underscores the urgent need for a genetic-, sex- and gender-informed precision-medicine approach to AD.
