Professor and Director of the Northwest Metabolomics Research Center, University of Washington; and Professor, Fred Hutchinson Cancer Research Center, Translational Research Program

Dan Raftery and his research group focus on the development of new methods in, and applications of, metabolite profiling using a combination of mass spectrometry and NMR platforms which provide a broad-based approach for biomarker discovery and systems biology research. Dr. Raftery has worked closely with many scientific and clinical collaborators and biostatisticians on various metabolomics projects such as the identification of cancer biomarkers for early detection, recurrence monitoring and therapy prediction. He is also involved in studies of diabetes and heart diseases as well as nutrition-based disease prevention and aging. He has extensive experience in the quantitative determination of metabolite concentrations in a variety of samples including serum/plasma, urine, cells and tissue extracts. In conjunction with the Northwest Metabolomics Research Center, he has developed assays and approaches for metabolite profiling, utilizing a range of platforms including targeted LC-MS/MS for broad-based and quantitative profiling and targeted pathway assays, LC-MS for global aqueous profiling and lipidomics, and GC-MS and NMR global profiling methods that provide excellent coverage of the metabolome.

Professor, Vaccine and Infectious Disease Division and Public Health Sciences Divisions, Fred Hutchinson Cancer Research Center; and Affiliate Professor, Department of Biostatistics, University of Washington

Ying Huang is an acknowledged expert in biomarker research with a long track record of statistical methodology development and collaborative work for evaluating biomarkers’ performance towards disease early detection, treatment selection, and measurement error correction. She is currently PI of an NIH statistical methodology grant on “Statistical Methods for Biomarker Selection and Evaluation.” In the past ten years, Dr. Huang has been a co-investigator and key statistician in several Women’s Health Initiative (WHI) studies for evaluating nutritional and genetic markers and a co-investigator of the Nutritional and Physical Activity Assessment Study for assessing the association between self-reported dietary intake and diseases in the presence of measurement error and developing candidate biomarkers of foods using urinary and blood metabolomics. She has long-standing experience working with high-dimensional data including the analysis of WHI breast cancer genome-wide association studies and the development of machine learning techniques for feature selection and model building.

Professor, Department of Biostatistics, University of Washington

Ali Shojaie is Professor of Biostatistics and Adjunct Professor of Statistics at the University of Washington. He has extensive expertise in developing new methodologies for analysis of high-dimensional biological networks, as well as integrative analysis of omics data from diverse platforms. Results of his projects have been made available to the scientific community through several award-winning papers, as well as R-packages that have incorporated the developed methodology. His interest is in developing statistical methods for analysis of large, complex systems, particularly biological and social systems. The main characteristic of these systems is that they are often comprised of numerous interacting components, and the behavior of the system may not be evident from that of individual components. Networks offer a convenient framework for analyzing large, complex systems. Dr. Shojaie also develops statistical machine learning methods for estimation and inference in high-dimensional problems (i.e., when there are more variables than observations), particularly, when variables and/or observations are correlated with each other. This intersection of statistical machine learning, network analysis is an emerging research area with many interesting methodological and applied problems.

Acting Instructor and Researcher at Department of Anesthesiology & Pain Medicine, School of Medicine, University of Washington

Fausto Carnevale-Neto has over 10 years of experience in MS and NMR based analysis, including both LC-MS and GC-MS, unknown identification, and advanced data processing and statistical analyses. His research achievements involve developing methods for untargeted analysis of complex mixtures using ion mobility mass spectrometry and high-resolution mass spectrometry with electrospray ionization. He has experience in mass spectrometry fundamentals including gas-phase fragmentation reactions, structural elucidation by mass spectrometry and nuclear magnetic resonance, targeted metabolomics assays, and computational strategies for analysis of large-scale data sets. His long-standing scientific interests are focused on the application of MS and NMR to study metabolism in biology, chemical ecology, and medicine.

Research Scientist and Lab Manager, Northwest Metabolomics Research Center, University of Washington

Danijel Djukovic is an expert in the development and application of quantitative MS-based technologies for small molecule analysis in complex biological matrices. He joined the Northwest Metabolomics Research Center at its founding in 2013, helping to build the Center’s capabilities. Dr. Djukovic has developed several targeted LC-MS/MS assays including a robust, highly reproducible assay that current provides measurements of over 350 metabolites, which has been utilized in many studies.

Professor, Department of Epidemiology and Population Health, Albert Einstein College of Medicine

Robert Kaplan is an epidemiologist and PI of the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) cohort of 16,425 Hispanic/Latino adults. As PI of HCHS/SOL, he has primary responsibility for leading the team at the Bronx Field Center, which has over 4,000 study participants in active follow-up for this long-term cohort study. In addition to HCHS/SOL, Dr. Kaplan has extensive experience with longitudinal cohort studies on diabetes and cardiovascular disease funded by NIH/NHLBI/NIDDK: e.g., Cardiovascular Health Study, CHS, on which he has collaborated since 1995; Women's Interagency HIV Study, WIHS, which he has led for well over a decade as Chair of the Cardiovascular Disease Working Group and R01 ancillary study PI; Women's Health Initiative, WHI, Co-investigator and ancillary study Co-PI. Other projects where Dr. Kaplan also has important leadership roles include the GUARDIAN collaboration on the genetics of type 2 diabetes in Hispanics (sub-PI), the NHLBI TOPMed whole genome sequencing collaboration, and the CHARGE consortium on the genetics of cardiovascular, metabolic and aging traits (Working Group Chair, Insulin-like Growth Factors).

Senior Scientific Director in the Department of Population Science at the American Cancer Society.

Marji McCullough has over 30 years of experience in nutrition, diet assessment and epidemiology, and has published over 240 articles in peer-reviewed scientific journals. As Senior Scientific Director of Epidemiology Research, she oversees nutrition research initiatives and diet assessment in the Population Science department at the American Cancer Society (ACS). Her research focuses on investigating the role of diet on cancer risk and prognosis, using both survey data and blood-based biological markers. She is co-principal investigator of the ACS’s Cancer Prevention Study-II cohort, a prospective cohort of 1.2 million adults in the United States. She also serves on the Guidelines on Nutrition and Physical Activity for Cancer Prevention and for Cancer Survivors committees at the ACS. She has led a study to identify metabolic features characterizing four a priori dietary patterns in a cross-sectional dataset from the CPS-II Nutrition Cohort.

Associate Professor, Dept. of Epidemiology & Population Health, Albert Einstein College of Medicine, Bronx, New York

Yasmin Mossavar-Rahmani is a nutrition scientist with a background in anthropology. She is particularly interested in using objective measures to assess measures of diet, physical activity, cognition, and sleep in multicultural populations. Her goal is to understand the sources of measurement error and to improve precision of assessment to better understand the association of diet with health-related outcomes. She serves as the PI for the NIA-funded study: “Multicultural Healthy Diet to Reduce Cognitive Decline & Alzheimer Disease Risk,” a randomized controlled trial that assesses the impact of an anti-inflammatory dietary pattern on cognition using ambulatory methods to assess both diet and cognition. She has served as PI for a multi-site study in the US as well as local site investigator for several NIH-funded studies, most recently as nationwide PI for the Study of Latinos: Nutrition & Physical Activity Assessment Study (SOLNAS); site PI for the Sueño Study of Latinos Sleep study, site PI for the Women’s Health Initiative Nutrition & Physical Activity Assessment Study (NPAAS) and co-investigator (Nutrition) for the New York City Clinical Center Women’s Health Initiative Dietary Modification Trial.

Senior Staff Scientist, Cancer Prevention Program, Public Health Sciences Division, Fred Hutchinson Cancer Research Center

Sandi Navarro is a nutritional biochemist with expertise in the evaluation and interpretation of metabolomics data from controlled feeding studies. Her ongoing research interest is in understanding the mechanisms through which dietary components alter gene expression and other downstream signaling pathways involved in chronic disease. Her research involves the conduct of controlled trials in humans and evaluation of intermediate biomarkers of disease risk and alterations in metabolism, e.g., inflammation and oxidative stress, and biotransformation enzyme induction, in response to dietary exposures. Over the past 6 years, she has been using omics platforms, such as metabolomics and proteomics, to provide a comprehensive metabolic fingerprint of the metabolic effects of diet and drug exposures.

Professor, Cancer Prevention Program, Public Health Sciences Division, Fred Hutchinson Cancer Research Center

Ross Prentice, former senior vice president and director of Fred Hutch’s Public Health Sciences Division, is a biostatistician who develops methods used in the design and analysis of clinical and population studies. He is particularly interested in research dedicated to the prevention of chronic diseases, with an emphasis on dietary and hormonal changes that may reduce the risk of cancer and cardiovascular disease. He and Fred Hutch colleagues established the Clinical Coordinating Center for the Women’s Health Initiative, a national program launched in 1993 that enrolled more than 161,000 postmenopausal women to evaluate the effectiveness of dietary change and menopausal hormone therapy on reducing chronic disease risk. Dr. Prentice initiated the WHI Nutritional Biomarkers Study and the WHI Nutrition and Physical Activity Assessment Study (now led by Drs. Neuhouser and Lampe). Dr. Prentice’s research interests include analytic strategies for nutritional and physical activity epidemiology and development of related statistical methods, including those that accommodate the measurement error properties of self-reported dietary and physical activity assessments.

Senior Staff Scientist, Cancer Prevention Program, Public Health Sciences Division, Fred Hutchinson Cancer Research Center

Jeannette Schenk is a nutritional epidemiologist with extensive experience in the design and conduct of observational and intervention studies of diet, lifestyle and cancer. She has led the design of dietary modification trials and controlled interventions to evaluate the performance of image-based dietary assessment methods and has been involved in the development and evaluation of dietary assessment and supplement use instruments. In addition, Dr. Schenk serves as a member-elect on the National Cancer Institute Cohort Consortium steering committee.

Senior Principal Scientist in the Department of Population Science at the American Cancer Society (ACS).

Ying Wang has over 10 years of experience conducting studies in nutritional epidemiology, including understanding phytochemicals and individual foods in relation to cancer incidence and survival, and has a strong background in biostatistics. She also played a significant role in modifying the ACS CPS-3 FFQ. She is leading research using state-of-the-art technology—metabolomics—to study food-based biomarkers, cancer risk and mechanisms in the Population Science Department at the ACS. Her research has used metabolomics to test technical reproducibility of metabolites, identify biomarkers of lifestyle factors including foods and dietary patterns in the CPS-II and CPS-3, and to identify metabolic features associated with cancer risk.

Associate Professor, University of Nebraska Medical Center, Department of Biostatistics

Cheng Zheng has extensive experience in health research and developing new methods in causal inference and measurement error modeling. He has over ten years of consulting experience serving as a biostatistician for many applied projects including modeling high-dimensional data such as accelerometer-based physical activity data, air pollution data over time, radiomics data, and metabolomics data.