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.
McNabb S, Harrison TA, Albanes D, Berndt SI, Brenner H, Caan BJ, Campbell PT, Cao Y, Chang-Claude J, Chan A, Chen Z, English DR, Giles GG, Giovannucci EL, Goodman PJ, Hayes RB, Hoffmeister M, Jacobs EJ, Joshi AD, Larsson SC, Le Marchand L, Li L, Lin Y, Männistö S, Milne RL, Nan H, Newton CC, Ogino S, Parfrey PS, Petersen PS, Potter JD, Schoen RE, Slattery ML, Su YR, Tangen CM, Tucker TC, Weinstein SJ, White E, Wolk A, Woods MO, Phipps AI, Peters U. Meta-analysis of 16 studies of the association of alcohol with colorectal cancer. Int J Cancer. 2020 Feb 1;146(3):861-873. doi: 10.1002/ijc.32377. Epub 2019 Jun 7. PubMed
Bien SA, Su YR, Conti DV, Harrison TA, Qu C, Guo X, Lu Y, Albanes D, Auer PL, Banbury BL, Berndt SI, Bézieau S, Brenner H, Buchanan DD, Caan BJ, Campbell PT, Carlson CS, Chan AT, Chang-Claude J, Chen S, Connolly CM, Easton DF, Feskens EJM, Gallinger S, Giles GG, Gunter MJ, Hampe J, Huyghe JR, Hoffmeister M, Hudson TJ, Jacobs EJ, Jenkins MA, Kampman E, Kang HM, Kühn T, Küry S, Lejbkowicz F, Le Marchand L, Milne RL, Li L, Li CI, Lindblom A, Lindor NM, Martín V, McNeil CE, Melas M, Moreno V, Newcomb PA, Offit K, Pharaoh PDP, Potter JD, Qu C, Riboli E, Rennert G, Sala N, Schafmayer C, Scacheri PC, Schmit SL, Severi G, Slattery ML, Smith JD, Trichopoulou A, Tumino R, Ulrich CM, van Duijnhoven FJB, Van Guelpen B, Weinstein SJ, White E, Wolk A, Woods MO, Wu AH, Abecasis GR, Casey G, Nickerson DA, Gruber SB, Hsu L, Zheng W, Peters U. Genetic variant predictors of gene expression provide new insight into risk of colorectal cancer. Hum Genet. 2019 Apr;138(4):307-326. doi: 10.1007/s00439-019-01989-8. Epub 2019 Feb PubMed
Huyghe JR, Bien SA, Harrison TA, Kang HM, Chen S, Schmit SL, Conti DV, Qu C, Jeon J, Edlund CK, Greenside P, Wainberg M, Schumacher FR, Smith JD, Levine DM, Nelson SC, Sinnott-Armstrong NA, Albanes D, Alonso MH, Anderson K, Arnau-Collell C, Arndt V, Bamia C, Banbury BL, Baron JA, Berndt SI, Bézieau S, Bishop DT, Boehm J, Boeing H, Brenner H, Brezina S, Buch S, Buchanan DD, Burnett-Hartman A, Butterbach K, Caan BJ, Campbell PT, Carlson CS, Castellví-Bel S, Chan AT, Chang-Claude J, Chanock SJ, Chirlaque MD, Cho SH, Connolly CM, Cross AJ, Cuk K, Curtis KR, de la Chapelle A, Doheny KF, Duggan D, Easton DF, Elias SG, Elliott F, English DR, Feskens EJM, Figueiredo JC, Fischer R, FitzGerald LM, Forman D, Gala M, Gallinger S, Gauderman WJ, Giles GG, Gillanders E, Gong J, Goodman PJ, Grady WM, Grove JS, Gsur A, Gunter MJ, Haile RW, Hampe J, Hampel H, Harlid S, Hayes RB, Hofer P, Hoffmeister M, Hopper JL, Hsu WL, Huang WY, Hudson TJ, Hunter DJ, Ibañez-Sanz G, Idos GE, Ingersoll R, Jackson RD, Jacobs EJ, Jenkins MA, Joshi AD, Joshu CE, Keku TO, Key TJ, Kim HR, Kobayashi E, Kolonel LN, Kooperberg C, Kühn T, Küry S, Kweon SS, Larsson SC, Laurie CA, Le Marchand L, Leal SM, Lee SC, Lejbkowicz F, Lemire M, Li CI, Li L, Lieb W, Lin Y, Lindblom A, Lindor NM, Ling H, Louie TL, Männistö S, Markowitz SD, Martín V, Masala G, McNeil CE, Melas M, Milne RL, Moreno L, Murphy N, Myte R, Naccarati A, Newcomb PA, Offit K, Ogino S, Onland-Moret NC, Pardini B, Parfrey PS, Pearlman R, Perduca V, Pharoah PDP, Pinchev M, Platz EA, Prentice RL, Pugh E, Raskin L, Rennert G, Rennert HS, Riboli E, Rodríguez-Barranco M, Romm J, Sakoda LC, Schafmayer C, Schoen RE, Seminara D, Shah M, Shelford T, Shin MH, Shulman K, Sieri S, Slattery ML, Southey MC, Stadler ZK, Stegmaier C, Su YR, Tangen CM, Thibodeau SN, Thomas DC, Thomas SS, Toland AE, Trichopoulou A, Ulrich CM, Van Den Berg DJ, van Duijnhoven FJB, Van Guelpen B, van Kranen H, Vijai J, Visvanathan K, Vodicka P, Vodickova L, Vymetalkova V, Weigl K, Weinstein SJ, White E, Win AK, Wolf CR, Wolk A, Woods MO, Wu AH, Zaidi SH, Zanke BW, Zhang Q, Zheng W, Scacheri PC, Potter JD, Bassik MC, Kundaje A, Casey G, Moreno V, Abecasis GR, Nickerson DA, Gruber SB, Hsu L, Peters U. Discovery of common and rare risk loci for colorectal cancer. Nat Genet. 2019 Jan;51(1):76-87. doi: 10.1038/s41588-018-0286-6. Epub 2018 Dec 3. PubMed
Su YR, Di C, Bien S, Huang L, Dong X, Abecasis G, Berndt S, Bezieau S, Brenner H, Caan B, Casey G, Chang-Claude J, Chanock S, Chen S, Connolly C, Curtis K, Figueiredo J, Gala M, Gallinger S, Harrison T, Hoffmeister M, Hopper J, Huyghe JR, Jenkins M, Joshi A, Le Marchand L, Newcomb P, Nickerson D, Potter J, Schoen R, Slattery M, White E, Zanke B, Peters U, Hsu L. A mixed-effects model for powerful association tests in integrative functional genomics. Am J Hum Genet. 2018 May 3;102(5):904-919. doi: 10.1016/j.ajhg.2018.03.019. PubMed
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
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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