Statistics and Data Science Seminar
Yongzhao Shao
New York University
Causal inference on biological clocks as personalized biomarkers for Alzheimer’s disease
Abstract: Alzheimer’s disease (AD) stands as the leading cause of dementia and related death. Presently, there is no cure or an effective prevention. AD pathology is highly heterogeneous which may begin 20 years before clinical diagnoses. Effective blood-based biomarkers are desired for early diagnosis and monitoring. Epigenetic clocks and mitotic clocks are individual-level biomarkers of aging and often referred as biological ages. Advanced age is known as the most impactful risk factor for late-onset AD, thus, biological ages have the potential to be the blood-based biomarkers of AD for diagnosis and monitoring in personalized medicine. In this talk, we will discuss the derivation of the epigenetic clocks based on DNA methylation profiles and the accelerations of biological ages as well as the mitotic clocks based on lymphocyte telomere lengths (LTLs). We will discuss causal analyses of the relationships between the epigenetic clocks, mitotic clocks and the risk of AD using Mendelian randomization (MR) analysis. The MR-based analyses using selected variants from genome-wide association studies as instrument variables are largely free of biases due to numerous measured and unmeasured confounding factors. If time permits, we will also discuss some MR-based causal analyses of the utility of heart failure medications in reducing the risk of AD among heart failure survivors. This talk is based on joint research with Dr. Yibeltal Ashebir and Jiehui Xu at NYU Grossman School of Medicine.
Wednesday March 13, 2024 at 4:00 PM in 636 SEO