Genetic risk in Alzheimer’s disease

Key Points

• The aim is to summarize the genetic factors influencing Alzheimer's disease and discuss predictive methodologies.
• Review of genome-wide association studies identifying risk loci
• Discussion of polygenic risk score methodologies
• Examination of machine learning approaches for risk prediction
• Analysis of challenges like population bias and functional validation
• Identification of numerous genetic loci associated with Alzheimer’s disease risk
• Description of machine learning-enhanced polygenic risk scores
• Highlighting the necessity for integrating multi-omics to improve predictions
• Challenges in validating non-coding variants remain a significant barrier