Yu-Ru Su, PhD

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“Leveraging individuals’ genetic, environmental, and clinical information in risk modeling promotes risk stratification for complex health outcomes. My research focuses on statistical methods for addressing complexity in data and the development of personalized strategies in disease prevention and interventions.”

Yu-Ru Su, PhD

Associate Biostatistics Investigator, Kaiser Permanente Washington Health Research Institute

YuRu.Su@kp.org
206-287-2948
LinkedIn

Biography

Yu-Ru Su, PhD, specializes in statistical genetics, survival analysis, and functional/longitudinal data analysis. Her research interests cover a wide spectrum of statistical methods for modern biomedical studies, especially in cancer prevention and precision medicine. Her current research focuses on integrating information in genetics, environmental, and clinical data to develop precise risk models of cancers with a goal of promoting personalized prevention/surveillance strategies. 

Before joining Kaiser Permanente Washington Health Research Institute, Dr. Su received her postdoctoral research training at Fred Hutchinson Cancer Research Center, where she was promoted to a staff scientist position. During her time at Fred Hutch, she was part of the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO), one of the world’s leading collaborations in colorectal cancer research. At GECCO, she conducted complex analyses aiming to discover genetic risk factors and interactions between genetics and environmental factors for colorectal cancer. These findings are essential for developing risk prediction models. She also developed novel and computationally feasible statistical methods via the kernel machine framework for detecting novel genetic associations with complex diseases by bringing in functional information from multi-omics data. Another field of her methods research focuses on statistical approaches for functional association between functional exposures and a scalar outcome. Dr. Su developed a new dimension reduction technique and a testing approach for inferences on the infinite-dimensional association. The application of these methods in modern genetic and aging studies is leading to a better understanding of underlying mechanism of complex diseases, including cancer and dementia.

Dr. Su received her PhD in biostatistics from the University of California, Davis. Her dissertation focused on statistical estimating procedures used to infer associations of survival outcomes and complex exposures. An example is time-varying covariates, based on incomplete data such as intermittently measured longitudinal covariates and left-truncation or doubly-censored survival outcomes. She investigated asymptotic properties of the proposed methods via modern semiparametric theory and proposed complex algorithms for handling incompleteness in data. 

At Kaiser Permanente Washington Health Research Institute, Dr. Su collaborates with scientists from multiple disciplines to pursue answers and solutions to scientific questions related to breast cancer, Alzheimer’s disease and dementia, and opioid use disorders. She actively collaborates with the Breast Cancer Surveillance Consortium to investigate the screening performance of multiple screening modalitiesin women with and without breast cancer history, to build reliable risk prediction models and personalized strategies for screening and surveillance strategies. She also closely works with the Adult Change in Thought (ACT) study to understand the connection between dementia and other clinical and health conditions.

Recent Publications

Su YR, Di CZ, Hsu L. Hypothesis testing in functional linear models. Biometrics. 2017 Jun;73(2):551-561. doi: 10.1111/biom.12624. Epub 2017 Mar 10. PubMed

Su YR, Di CZ, Hsu L; Genetics and Epidemiology of Colorectal Cancer Consortium. A unified powerful set-based test for sequencing data analysis of GxE interactions. Biostatistics. 2017 Jan;18(1):119-131. doi: 10.1093/biostatistics/kxw034. Epub 2016 Jul 28. PubMed

Su YR, Wang JL. Semiparametric efficient estimation for shared-frailty models with doubly-censored clustered data. Ann Statist. 2016, Vol. 44, No. 3, 1298-1331. DOI: 10.1214/15-AOS1406.

Chang WT, Lee WH, Lee WT, Chen PS, Su YR, Liu PY, Liu YW, Tsai WC. Left ventricular global longitudinal strain is independently associated with mortality in septic shock patients. Intensive Care Med. 2015 Oct;41(10):1791-9. doi: 10.1007/s00134-015-3970-3. Epub 2015 Jul 17. PubMed

Sung JM, Su CT, Chang YT, Su YR, Tsai WC, Wang SP, Yang CS, Tsai LM, Chen JH, Liu YW. Independent value of cardiac troponin T and left ventricular global longitudinal strain in predicting all-cause mortality among stable hemodialysis patients with preserved left ventricular ejection fraction. Biomed Res Int. 2014;2014:217290. doi: 10.1155/2014/217290. Epub 2014 May 7. PubMed

 

Breast Cancer Surveillance

Kaiser Permanente Washington Breast Cancer Surveillance Registry

Kaiser Permanente Washington has been part of the national Breast Cancer Surveillance Consortium since 1994. Learn about the Kaiser Permanente Washington Breast Cancer Surveillance Registry here.

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aging and geriatrics

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The ACT Study: Looking toward the future

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