Yu-Ru Su, PhD
“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.
RESEARCH INTERESTS AND EXPERIENCE
Recent Publications
Hubbard RA, Su YR, Bowles EJ, Ichikawa L, Kerlikowske K, Lowry KP, Miglioretti DL, Tosteson ANA, Wernli KJ, Lee JM. Predicting five-year interval second breast cancer risk in women with prior breast cancer. LID - djae063 [pii] LID - 10.1093/jnci/djae063 [doi] J Natl Cancer Inst. 2024 Mar 11:djae063. doi: 10.1093/jnci/djae063 [Epub ahead of print] PubMed
Luce C, Palazzo L, Anderson ML, Carter-Bawa L, Gao H, Green BB, Ralston JD, Rogers K, Su YR, Tuzzio L, Triplette M, Wernli KJ. A pragmatic randomized clinical trial of multilevel interventions to improve adherence to lung cancer screening (The Larch Study): Study protocol. Contemp Clin Trials. 2024 Mar 11;140:107495. doi: 10.1016/j.cct.2024.107495 [Epub ahead of print] PubMed
Kerlikowske K, Zhu W, Su YR, Sprague BL, Stout NK, Onega T, O'Meara ES, Henderson LM, Tosteson ANA, Wernli K, Miglioretti DL. Supplemental magnetic resonance imaging plus mammography compared with magnetic resonance imaging or mammography by extent of breast density. J Natl Cancer Inst. 2023 Oct 27:djad201. doi: 10.1093/jnci/djad201. [Epub ahead of print]. PubMed
Thomas M, Su YR, Rosenthal EA, Sakoda LC, Schmit SL, Timofeeva MN, Chen Z, Fernandez-Rozadilla C, Law PJ, Murphy N, Carreras-Torres R, Diez-Obrero V, van Duijnhoven FJB, Jiang S, Shin A, Wolk A, Phipps AI, Burnett-Hartman A, Gsur A, Chan AT, Zauber AG, Wu AH, Lindblom A, Um CY, Tangen CM, Gignoux C, Newton C, Haiman CA, Qu C, Bishop DT, Buchanan DD, Crosslin DR, Conti DV, Kim DH, Hauser E, White E, Siegel E, Schumacher FR, Rennert G, Giles GG, Hampel H, Brenner H, Oze I, Oh JH, Lee JK, Schneider JL, Chang-Claude J, Kim J, Huyghe JR, Zheng J, Hampe J, Greenson J, Hopper JL, Palmer JR, Visvanathan K, Matsuo K, Matsuda K, Jung KJ, Li L, Le Marchand L, Vodickova L, Bujanda L, Gunter MJ, Matejcic M, Jenkins MA, Slattery ML, D'Amato M, Wang M, Hoffmeister M, Woods MO, Kim M, Song M, Iwasaki M, Du M, Udaltsova N, Sawada N, Vodicka P, Campbell PT, Newcomb PA, Cai Q, Pearlman R, Pai RK, Schoen RE, Steinfelder RS, Haile RW, Vandenputtelaar R, Prentice RL, Küry S, Castellví-Bel S, Tsugane S, Berndt SI, Lee SC, Brezina S, Weinstein SJ, Chanock SJ, Jee SH, Kweon SS, Vadaparampil S, Harrison TA, Yamaji T, Keku TO, Vymetalkova V, Arndt V, Jia WH, Shu XO, Lin Y, Ahn YO, Stadler ZK, Guelpen BV, Ulrich CM, Platz EA, Potter JD, Li CI, Meester RR, Moreno V, Figueiredo JC, Casey G, Vogelaar IL, Dunlop MG, Gruber SB, Hayes RB, Pharoah PD, Houlston RS, Jarvik GP, Tomlinson IP, Zheng W, Corley DA, Peters U, Hsu L. Combining Asian and European genome-wide association studies of colorectal cancer improves risk prediction across racial and ethnic populations. Nat Commun. 2023;14(1):6147. doi: 10.1038/s41467-023-41819-0. PubMed
Dimou N, Kim AE, Flanagan O, Murphy N, Diez-Obrero V, Shcherbina A, Aglago EK, Bouras E, Campbell PT, Casey G, Gallinger S, Gruber SB, Jenkins MA, Lin Y, Moreno V, Ruiz-Narvaez E, Stern MC, Tian Y, Tsilidis KK, Arndt V, Barry EL, Baurley JW, Berndt SI, Bézieau S, Bien SA, Bishop DT, Brenner H, Budiarto A, Carreras-Torres R, Cenggoro TW, Chan AT, Chang-Claude J, Chanock SJ, Chen X, Conti DV, Dampier CH, Devall M, Drew DA, Figueiredo JC, Giles GG, Gsur A, Harrison TA, Hidaka A, Hoffmeister M, Huyghe JR, Jordahl K, Kawaguchi E, Keku TO, Larsson SC, Le Marchand L, Lewinger JP, Li L, Mahesworo B, Morrison J, Newcomb PA, Newton CC, Obon-Santacana M, Ose J, Pai RK, Palmer JR, Papadimitriou N, Pardamean B, Peoples AR, Pharoah PDP, Platz EA, Potter JD, Rennert G, Scacheri PC, Schoen RE, Su YR, Tangen CM, Thibodeau SN, Thomas DC, Ulrich CM, Um CY, van Duijnhoven FJB, Visvanathan K, Vodicka P, Vodickova L, White E, Wolk A, Woods MO, Qu C, Kundaje A, Hsu L, Gauderman WJ, Gunter MJ, Peters U. Probing the diabetes and colorectal cancer relationship using gene - environment interaction analyses. Br J Cancer. 2023 Aug;129(3):511-520. doi: 10.1038/s41416-023-02312-z. Epub 2023 Jun 26. 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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Land Acknowledgment
Our Seattle offices sit on the occupied land of the Duwamish and by the shared waters of the Coast Salish people, who have been here thousands of years and remain. Learn about practicing land acknowledgment.