Alzheimer’s Disease (AD) is the most common form of dementia and the 5th leading cause of death of adults over the age of 65. As the American population ages, the number of Alzheimer’s cases is expected to rise significantly. Unfortunately, symptoms don’t present until years after disease pathology begins in the brain, emphasizing the need for a better understanding of the biological basis of the disease. There have been many efforts to address this using genetic studies of higher-level population groupings, including multiple GWA studies, which have yielded informative results. In this work, we use these studies as a jumping off point for further analysis of the genetic architecture of Alzheimer’s Disease, specifically taking advantage of polygenic risk score (PRS) models and isolate populations. In Chapter 3 we incorporated Alzheimer’s-associated traits into a predictive model to stratify samples into cases and controls. Chapter 4, driven by the immune system implication of recent AD GWAS, explored the ability of PRS to uncover shared genetic etiology between Alzheimer’s and various autoimmune traits. Despite the stability of the AD GWAS immune association, our results indicate that this association does not explain the comorbidity of AD autoimmune diseases. Overall, our findings suggest promising directions to better understand the genetic drivers of Alzheimer’s Disease. In Chapter 5 we took a step back and reevaluated the utility of GWAS calculated on high-level population groupings. We identified and characterized an Icelandic population with whole-genome sequencing information. After confirming that the properties of this dataset were as expected, including a genetic similarity to the general European population but a distinctiveness from European populations, we set forth a plan to conduct a GWAS on this isolate population with our Icelandic collaborators.