The Biostatistics Core for this program project grant is responsible for developing and performing the large and small scale statistical analysis required for meeting the aims of each of the individual projects in this program project grant. This involves: (1) Choosing appropriate statistical methods and software for each project and when necessary developing additional software relating to the implementation of the selected methods. In some cases this may also include development of new statistical methods (2) Designing and developing analysis files for each of the projects in the program project application. This includes assisting in the selection of samples for analysis from the Multiethnic Cohort (MEC) biorepository for study in Projects 1 - 4 , and participating in the design and analysis of quality control data to determine laboratory variation, and between and within person-variation in the smoking-related biomarkers of concern in all projects(3) Performing and/or guiding data analysis for each project using the analysis files from (2).

Public Health Relevance

The Biostatistical Core is a service core for the main projects in the program project grant. In some cases new computer software or statisfical methods developed may be applicable more widely beyond the scope of just this grant, i.e. in other epidemiological studies ofthe efiology of disease

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Program Projects (P01)
Project #
5P01CA138338-05
Application #
8637009
Study Section
Special Emphasis Panel (ZCA1-RPRB-7)
Project Start
Project End
Budget Start
2014-04-01
Budget End
2015-03-31
Support Year
5
Fiscal Year
2014
Total Cost
$225,731
Indirect Cost
Name
University of Minnesota Twin Cities
Department
Type
DUNS #
555917996
City
Minneapolis
State
MN
Country
United States
Zip Code
55455
Patel, Yesha M; Park, Sunghim L; Han, Younghun et al. (2016) Novel Association of Genetic Markers Affecting CYP2A6 Activity and Lung Cancer Risk. Cancer Res 76:5768-5776
Park, Sungshim L; Tiirikainen, Maarit I; Patel, Yesha M et al. (2016) Genetic determinants of CYP2A6 activity across racial/ethnic groups with different risks of lung cancer and effect on their smoking intensity. Carcinogenesis 37:269-79
Ma, Bin; Ruszczak, Chris; Jain, Vipin et al. (2016) Optimized Liquid Chromatography Nanoelectrospray-High-Resolution Tandem Mass Spectrometry Method for the Analysis of 4-Hydroxy-1-(3-pyridyl)-1-butanone-Releasing DNA Adducts in Human Oral Cells. Chem Res Toxicol 29:1849-1856
Zanetti, Krista A; Wang, Zhaoming; Aldrich, Melinda et al. (2016) Genome-wide association study confirms lung cancer susceptibility loci on chromosomes 5p15 and 15q25 in an African-American population. Lung Cancer 98:33-42
Patel, Yesha M; Park, Sungshim L; Carmella, Steven G et al. (2016) Metabolites of the Polycyclic Aromatic Hydrocarbon Phenanthrene in the Urine of Cigarette Smokers from Five Ethnic Groups with Differing Risks for Lung Cancer. PLoS One 11:e0156203
Haiman, Christopher A; Patel, Yesha M; Stram, Daniel O et al. (2016) Benzene Uptake and Glutathione S-transferase T1 Status as Determinants of S-Phenylmercapturic Acid in Cigarette Smokers in the Multiethnic Cohort. PLoS One 11:e0150641
Kotapati, Srikanth; Esades, Amanda; Matter, Brock et al. (2015) High throughput HPLC-ESI(-)-MS/MS methodology for mercapturic acid metabolites of 1,3-butadiene: Biomarkers of exposure and bioactivation. Chem Biol Interact 241:23-31
Zarth, Adam T; Murphy, Sharon E; Hecht, Stephen S (2015) Benzene oxide is a substrate for glutathione S-transferases. Chem Biol Interact 242:390-5
Kotandeniya, Delshanee; Carmella, Steven G; Ming, Xun et al. (2015) Combined analysis of the tobacco metabolites cotinine and 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol in human urine. Anal Chem 87:1514-7
Park, Sungshim L; Carmella, Steven G; Ming, Xun et al. (2015) Variation in levels of the lung carcinogen NNAL and its glucuronides in the urine of cigarette smokers from five ethnic groups with differing risks for lung cancer. Cancer Epidemiol Biomarkers Prev 24:561-9

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