William F. Li
Eric and Wendy Schmidt Center Funded Research and Innovation Scholar
Polygenic Dissection of Phenotypic Heterogeneity in Alzheimer' s Disease
2022–2023
Electrical Engineering and Computer Science
- Artificial Intelligence for Healthcare and Life Sciences
Manolis Kellis
Alzheimer’s Disease (AD) is highly heterogeneous in clinical presentation and pathology. We will characterize this heterogeneity by performing cross-trait associations between clinical markers of AD and polygenic risk scores (PRS) for 400 individuals in the Religious Orders Study/Memory and Aging Project (ROSMAP). The PRS models are trained using the UK Biobank cohort of 500,000 individuals. By using PRS models trained on the large UK Biobank cohort, we overcome the statistical limitations that arise from performing population genetics on a smaller dataset. The resulting cross-trait associations will allow us to subtype AD patients and predict clinical markers based on genetics alone.
I am participating in SuperUROP to gain research experience in computational genomics. I have taken courses in the area, and I enjoyed the research-based final projects. I’m excited to learn more about statistical genetics, genomic medicine, and Alzheimer’s Disease.