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Your Environment. Your Health.

Shanshan Zhao, Ph.D.

Biostatistics & Computational Biology Branch

Shanshan Zhao
Shanshan Zhao, Ph.D.
Principal Investigator
Tel 984-287-3702
111 T W Alexander Dr
Rall Building
Research Triangle Park, NC 27709

Research Summary

Shanshan Zhao, Ph.D., joined the NIEHS Biostatistics and Computational Biology Branch as a principal investigator in January 2015. She holds a secondary appointment in the NIEHS Epidemiology Branch, and an adjunct assistant professorship at the Department of Biostatistics, University of North Carolina at Chapel Hill. Her main research interest is in developing statistical methods for disease risk assessment and risk prediction. Her research areas include survival data analysis, risk modeling, biomarker evaluation and cancer research.

Zhao is focusing on statistical methods for analyzing multiple time-to-disease outcomes, to facilitate risk assessment of multiple diseases across individual’s lifespan. Although the analysis of univariate failure time has been well developed, there are still big gaps in multivariate failure time methodology. In practice with rare diseases, we could use the information on related disease to fill in information about the main study outcome on censored participants. In addition, her research allows one to characterize the dependency between diseases through risk factors.

Zhao is interested in breast cancer risk assessment and prediction. Breast cancer is the most commonly diagnosed cancer among U.S. women. Many risk factors have been identified, including personal/behavior factors, genetic factors, environmental factors and family history. The NIEHS Sister Study, which enrolled over 50,000 women with at least one sister with breast cancer, provided a rich dataset to explore breast cancer risk. Zhao recently developed a risk prediction model based on detailed family history data. Zhao is also working on characterizing the spatial and temporal distribution of breast cancer incidence and mortality, in order to identify important environmental risk factors for breast cancer.

Zhao has also developed statistical methods related to biomarker evaluation. She developed correction methods for the Cox model in the mediation analysis setting, when the mediator biomarker is measured with error. She has proposed a sequential method to evaluate biomarkers to save specimens. She is involved in collaborative projects to identify epigenetic biomarkers for various health outcomes, which serve as potential mediators between environmental factors and these health outcomes.

Zhao and her group believe that with powerful statistical tools, the current population-based data have the power to assess disease risks in the population and to provide personalized risk prediction.

Selected Publications

  1. Carroll R., Lawson A.B., Zhao S. (2017). Spatial accelerated failure time model for mortality following breast cancer diagnosis. In Press. Social Science & Medicine. 
  2. Zhao S., Geybels M.S., Leonardson A., Rubicz R., Kolb S., Yan Q., Klotzle B., Bibikova M., Hurtado-Coll A., Troyer D., Lance R., Lin D.W., Wright J.L., Ostrander E.A., Fan J.B., Feng Z., Stanford J.L. (2017). Epigenome-wide Tumor DNA Methylation Profiling Identifies Novel Prognostic Biomarkers of Metastatic-lethal Progression in Men Diagnosed with Clinically Localized Prostate Cancer. Clinical Cancer Research, 23: 311-319. PMID: 27358489; PMCID: PMC5199634; DOI: 10.1158/10780432.CCR-16-0549. [Abstract] 
  3. Rubicz R., Zhao S.*, Wright J.L., Coleman I., Grasso C., Geybels M., Leonardson, A., Kolb S., April C., Bibikova M., Troyer D., Lance R, Lin D.W., Ostrander E.A., Nelson P.S., Fan J., Feng Z., Stanford J.L. (2017). Gene Expression Panel Predicts Metastatic-Lethal Prostate Cancer Outcomes in Men Diagnosed with Clinically Localized Prostate Cancer. Molecular Oncology, 11: 140-150. PMID: 28145099; PMCID: PMC5510189; DOI: 10.1002/1878-0261.12014. (*co-first authors) [Full Text] 
  4. Reese S.E., Zhao S., Wu M.C., Joubert B.R., Parr C.L., H˚aberg S.E., Ueland P.M., Nilsen R.M., Midttun Ø., Vollset S.E., Peddada, S.D., NystadW., London S.J. (2017). DNA Methylation Score as a Biomarker in Newborns for Sustained Maternal Smoking during Pregnancy. Environmental Health Perspectives. PMID: 27323799; PMCID: PMC5391987. DOI: 10.1289/EHP333. [Abstract] 
  5. Stanford J.L., FitzGerald L.M., Zhao S., Leonardson A., Geybels M., Kolb S., Lin D.W., Wright J., Eeles R., Kote-Jarai Z., Giles G.G., Southey M.C., Schleutker J., Tammela T.L., Sipeky C., Penney K.L., Stampfer M.J., Gronberg H., Wiklund F., Stattin P., Hugosson J., Karyadi D.M., Ostrander E.A., Feng Z.. Germline Variants in IL4 and MGMT are Associated with Prostate Cancer Mortality: A Meta-analysis of 12,082 Patients from Seven International Cohorts. In Press. Prostate Cancer and Prostatic Diseases. 
  6. Park Y.M., O’Brien K.M., Zhao S., Weinberg C.R., Baird, D.D., Sandler, D.P. (2017). Gestational Diabetes Mellitus May be Associated With an Increased Risk of Breast Cancer. British Journal of Cancer, 116: 960-960. PMID: 28208154; PMCID: PMC5379146; DOI: 10.1038/bjc.2017.34. [Abstract] 
  7. Sharp G.C., Arathimos R., Reese S.E., Page C.M., Felix J., Kupers L.K., Rifas-Shiman S.L., Liu C., The Cohorts for Heart and Aging Research in Genomic Epidemiology Plus Methylation AlcohoWorking Group, Burrows K., Zhao S., Magnus M.C., Duijts L., Corpeleijn E., DeMeo D.L., Litonjua A., Baccarelli A., Hivert M., Oken E., Snieder H., Jaddoe V., Nystad W., London S.J., Relton C.L., Zuccolo L. (2017). Maternal Alcohol Consumption and Offspring DNA Methylation: Findings from Six General Population-Based Birth Cohorts. In Press. Epigenomics. 
  8. Felix J.F., Joubert B.R., Baccarelli A.A, Sharp G.C., [multiple contributing authors in alphabetical order including Zhao.S, Agha G., Relton C.L., Jaddoe V.W.V, London S.J. (2017). Cohort Profile: Pregnancy And Childhood Epigenetics (PACE) Consortium. International Journal of Epidemiology, 1-23. DOI: 10.1093/ije/dyx190. [Full Text] 
  9. Prentice R.L., Zhao S. (2016). Nonparametric Estimation of the Multivariate Survivor Function: the Multivariate Kaplan-Meier Estimator. Lifetime Data Analysis. PMID: 27677472; PMCID: PMC5373162; DOI: 10.1007/s10985-016-93830y. [Abstract] 
  10. Shui I.M., Wong C., Zhao S., Kolb S., Ebot E.M., Geybels M., Rubicz R., Wright J.L., Lin D.W., Klotzle B., Bibikova M., Fan J., Ostrander E.A., Feng Z., Stanford J.L.. Prostate tumor DNA methylation is associated with cigarette smoking and adverse prostate cancer outcomes. Cancer. In press.
  11. Rubicz R., Zhao S., Geybels M., Wright J.L., Kolb S., Klotzled B., Bibikova M., Troyer D., Lance R., Ostrander E.A., Feng Z., Fan J.B., Stanford J.L. (2016). DNA Methylation Profiles in African American Prostate Cancer Patients in Relation to Disease Progression. Genomics. doi: 10.1016.j.ygeno.2016.02.004. PMID: 26902887; PMCID: PMC4992660. [Abstract]
  12. Valeri L., Reese S.L., Zhao S., Page C.M., Nystad W., Coull B.A., London S.J. (2016). Misclassified Exposure in Epigenetic Mediation Analyses. Does DNA Methylation Mediate Effects of Smoking on Birthweight? Epigenomics, 9: 253-265. PMID: 28234025 PMCID: PMC5331915; DOI: 10.2217/epi-2016-0145. [Abstract] 
  13. Geybels M.S., Wright J.L., Bibikova M., Klotzle B., Fan J.B., Zhao S., Feng Z., Ostrander E.A., Lin D.W., Nelson P.S., Stanford J.L. (2016). Epigenetic Signature of Gleason Score and Prostate Cancer Recurrence after Radical Prostatectomy. Clinical Epigenetics, 8:97. PMID: 27651837; PMCID: PMC5024414; DOI: 10.1186/s13148016-0260-z. [Abstract] 
  14. Schade G.R., Holt S., Zhang X., Wright J.L., Zhao S., Kolb S., Lam H.M., Song D., Levin L., Leung Y.K., Ho S.M., Stanford J.L. (2016). Prostate Cancer Expression Profiles of Cytoplasmic ERβ1 and Nuclear ERβ2 are Associated with Poor Outcomes Following Radical Prostatectomy. Journal of Urology.doi:10.1016/j.juro.2015.12.101. [Abstract]
  15. Zhao S., Zheng Y., Prentice R.L., Feng, Z. (2015). Estimation from a Two-Stage Biomarker Study Allowing Early Termination for Futility. Biostatistics. doi: 10.1093/biostatistics/kxv017.
  16. Geybels M.S., Alumkal J.J., Luedeke M., Rinckleb A., Zhao S., Shui I.M., Bibikova M., Klotzle B., van den Brandt P.A., Ostrander E.A., Fan J., Feng Z., Maier C., Stanford J.L. (2015). Epigenomic profiling of prostate cancer identifies differentially methylated genes in TMPRSS2:ERG fusion positive versus negative tumors. Clinical Epigenetics. doi: 10.1186/s13148-015-0161-6.
  17. Geybels M.S., Zhao S., Wong C., Bibikova M., Klotzle, B., Wu, M., Ostrander E.A., Fan J., Feng Z., Stnaford J.L. (2015). Epigenome-wide profiling of DNA methylation in paired prostate cancer versus adjacent benign tissue. Prostate. doi: 10.1002/pros.23093.
  18. Rubicz R., Zhao S.*, April C., Wright J.L., Kolb S., Coleman I., Lin D.W., Nelson P.S., Ostrander, E.A., Feng Z., Fan J., Stanford J.L. (2015). Expression of cell cycle-regulated genes and prostate cancer prognosis in a population-based cohort. Prostate, 75: 1354-1362 . (*co-first authors)
  19. Karyadi, D. M., Zhao S.*, He C., McIntosh, L., Wright, J.L., Ostrander, E.A., Feng, Z., Stanford J.L. (2015) Confirmation of Genetic Variants Associated with Lethal Prostate Cancer in a Cohort of Men from Hereditary Prostate Cancer Families. International Journal of Cancer, doi: 10.1002/ijc.29241. (*co-first authors) [Abstract]
  20. Zhao S., Prentice R.L. (2014). Covariate Measurement Error Correction Methods in Mediation Analysis with Failure Time Outcome. Biometrics, 70: 835-844. doi: 10.1111/biom.12205. 
    (An earlier version won the 2014 ASA biometrics section David P. Byar travel award.) [Abstract]
  21. Zhao S., Chlebowski R.T., Anderson G., Kuller L.H., Manson J.E., Gass M., Patterson R., Rohan T.E., Lane D.S., Beresford S.A.A, Lavasani, S., Rossouw, J.E., Prentice R.L. (2014). Sex Hormone Associations with Breast Cancer Risk and the Mediation of Randomized Trial Postmenopausal Hormone Therapy Effect. Breast Cancer Research. 16: R30. doi:10.1186/bcr3632. [Abstract]
  22. Stott-Miller, M., Zhao S.*, Wright, J.L., Bibikova, M., Klotzle, B., Fan, J., Ostrander, E.A., Feng, Z., and Stanford, J.L. (2014). Validation Study of Candidate Genes with Hypermethylated Promoter Regions Associated with Prostate Cancer Recurrence. Cancer Epidemiology, Biomarkers & Prevention, 23: 1331-1339. doi: 10.1158/1055-9965.EPI-13-1000. (*co-first authors) [Abstract]
  23. Prentice, R.L., Zhao S., Johnson, M., Aragaki, A., Hsia, J., Jackson, R.D., Rossouw, J.E., Manson, J.E., Hanash, S.M. (2013). Proteomic Risk Markers for Coronary Heart Disease and Stroke: Validation and Mediation of Postmenopausal Hormone Therapy Effects. Genome Medicine. 5: 112. doi:10.1186/gm517. [Abstract]
  24. Zhao, S., Cook, A.J., Jackson, L.A., and Nelson, J.C. (2012). Statistical Performance of Group Sequential Methods for Post-Licensure Medical Product Safety Surveillance: A Simulation Study. Statistics and Its Interface. 5: 381-390. doi:
  25. Prentice R.L., Zhao S. (2012) On the Use of Biomarkers to Elucidate Clinical Trial Results: Examples from the Women's Health Initiative. Proceedings of the Fourth Seattle Symposium in Biostatistics: Clinical Trials, Springer.
  26. Nelson J.C., Cook A.J., Yu O., Zhao S., Dominguez C., Fireman B., Greene S., Jacobsen S.J., Weintraub E., Jackson L.A. (2012) Challenges in the Design and Analysis of Sequentially-Monitored Post-Licensure Safety Surveillance Studies Using Observational Health Care Utilization Data. Pharmacoepidemiology and Drug Safety. 21 Suppl 1:62-71. [Abstract]
  27. Nelson J.C., Cook A.J., Yu O., Zhao S., Jackson L.A., Psaty B.M., Kulldorff  M. (2011) Methods for Observational Post-Licensure Medical Product Safety Surveillance. Statistical Methods in Medical Research. doi: 10.1177/0962280211413452. [Abstract]
  28. Nelson J.C., Bittner R.C., Bounds L., Zhao S., Baggs J., Donahue J.G., Hambidge S.J., Jacobsen S.J., Klein N.P., Naleway A.L., Zangwill K.M., Jackson L.A. (2009) Compliance with Multiple-Dose Vaccine Schedules Among Older Children, Adolescents, and Adults: Results From a Vaccine Safety Datalink Study. American Journal of Public Health, 99(S2): S389-S397. [Abstract]
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