| Title: | Developing statistical methods and computational algorithms for identifying biomarkers at Biobank-data scale for cardio-metabolic traits |
| Lead Institution: | University of California, Los Angeles |
| Principal investigator: | Dr Jin Zhou |
Application 48152
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About
The aim of this proposal is to develop several statistical methods and computational algorithms that address challenges of large datasets for identifying biomarkers associated with cardio-metabolic related traits and study their genetic overlap with cognitive functions. We are principally interested in biomarkers and diseases related to obesity, body composition, and lipid levels. Since these circulating biomarkers are major clues to health status and disease risk, the overarching purpose of this research is to better understand the etiology of major diseases such as type-2 diabetes and heart disease. We will also explore the genetic overlap between diabetes and aging (e.g. Alzheimer disease) by using imaging markers and cognitive functions from UK biobank. We focus on four specific topics. They were listed in A2. With this improved etiological and molecular understanding, it may be possible to develop or improve therapeutics, and/or otherwise improve prediction and prevention of disease.3 Publications
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 10936 | A platform for phenotyping disease progression and associated longitudinal risk factors in large-scale EHRs, with application to incident diabetes complications in the UK Biobank | Do Hyun Kim (+10) | 2023 | JAMIA Open |
| 7186 | GWAS of longitudinal trajectories at biobank scale | Seyoon Ko (+9) | 2022 | American Journal of Human Genetics |
| 7196 | Systematic Heritability and Heritability Enrichment Analysis for Diabetes Complications in UK Biobank and ACCORD Studies. | Juhyun Kim (+9) | 2022 | Diabetes |
Enabling scientific discoveries that improve human health