Special Poster Session
Biomedical Data Sciences Summer Research Opportunity Program Students
Sarah Bennett, Jaren Bresnick, Yunju Ha, Livvy Johnson, Marley Joseph, Eric Zhou
The students participating in the Biomedical Data Sciences Summer Research Opportunity program will be presenting their research and what they learned over the ten weeks of the program.
Date: August 1, 2023
Time: 2:00-3:30 PM (drop in at your convenience)
Location: Union South (check TITU for room)
Refreshments will be served.
Past Special Seminars
Tianyuan Lu, PhD, Schmidt AI in Science Postdoctoral Fellow, Department of Statistical Sciences, University of Toronto
Date: June 30, 2023
Time: Noon to 1 pm
Zoom link: https://uwmadison.zoom.us/j/91593359262?pwd=SXA5YmtPZWdDYmJwZXdHaVJFbm1WQT09
Poster: 230630 Lu, TianyuanPoster
Title: Modeling hidden genetic risk from family history for improving polygenic risk prediction and increasing yield of diagnostic sequencing.
Abstract:
Polygenic risk scores based on common genetic variants have demonstrated significant potential in both research and clinical settings. However, it is important to consider whether family history, a traditional genetic predictor, still provides valuable information. Family history of complex traits and diseases can be influenced by various factors, including the transmission of rare pathogenic variants, shared environmental exposures within families, and a common genetic predisposition.
In this presentation, I will introduce a latent factor model that aims to quantify disease risk beyond what is captured by a common genetic variant-based polygenic risk score but inferable from family history. I will discuss how this model can enhance population-level risk stratification for complex diseases such as cardiovascular diseases, Alzheimer’s disease, and idiopathic short stature. Additionally, I will discuss its potential in prioritizing individuals who are more likely to carry clinically actionable rare pathogenic variants for diagnostic sequencing.
At the end of the presentation, I will provide an overview of other ongoing and future research directions, focusing on the development and implementation of statistical genetics methods for improving the prevention, diagnosis, and treatment of complex diseases.
Relevant publications:
Lu et al. Capturing additional genetic risk from family history for improved polygenic risk prediction. Commun Biol 2022. PMID: 35710731
Lu et al. Polygenic risk score as a possible tool for identifying familial monogenic causes of complex diseases. Genet Med 2022. PMID: 35460399
Lu et al. Individuals with common diseases but with a low polygenic risk score could be prioritized for rare variant screening. Genet Med 2021. PMID: 33110269