Rare Variant Polygenic Risk Scores for Alzheimer's Disease in Hispanic/Latinx Populations

Late-onset Alzheimer’s Disease (LOAD) affects over 46 million people worldwide and is expected to double by 2030 and triple by 2050. Accumulating evidence supports a strong genetic component underpinning AD etiology. However, genetic studies of AD have focused primarily on assessing the impact of common variants (either in the APOE epsilon 4 allele or traditional polygenic scores) in European populations. Indeed, there is a sparsity of evidence demarcating the role of rare coding variants on LOAD in European and non-European populations alike, which could provide invaluable insight toward the genetic determinants of LOAD since rare variants are collectively numerous and more deleterious relative to common variants. Using the ethnically diverse ADSP WES data, we aim to systematically demarcate the effect of rare variants on LOAD by constructing a rare variant polygenic risk score (rvPRS), which captures the gene-based burden of rare variants across the genome. The Rare Variant EXome CALIBration using External Repositories (RV-EXCALIBER) method will be used to conduct case-control exome-wide association study using gene burden testing to delineate genes that harbour an enrichment of rare, deleterious variants in LOAD cases relative to controls from the genome aggregation database (gnomAD). Gene-based effect sizes will be used to construct an rvPRS in an independent ADSP validation population, which will be used in multivariable logistic regression models to to predict LOAD status after adjusting for age, sex, APOE epsilon-4-allele, and principal components of ancestry. We also aim to assess the transferability for the predictive power of the rvPRS across the European, African, and Hispanic ancestries present within the ADSP.

Late-onset Alzheimer’s Disease (LOAD) affects over 46 million people worldwide and is expected to double by 2030 and triple by 2050. There is evidence supports that genetic factors underlie AD development. To date, genetic studies of primarily focussed on a small subset of all genetic variants that occur commonly in the population. However, it has been shown that variants that are rare can aid in disease prediction and are better at identifying genes that cause disease. Using the ADSP population, we aim to develop a score based on rare variants that can help identify individuals at high risk for AD from various different ethnic backgrounds.