|Grant Number:||5R37CA057030-24 Interpret this number|
|Primary Investigator:||Carroll, Raymond|
|Organization:||Texas A&M University|
|Project Title:||Measurement Error, Nutrition and Breast/Colon Cancer|
Description: This proposed MERIT extension is a logical continuation of the current award, revolving around the development of new statistical methods and their application to studies involving cancer and nutrition. The following broad topics will be considered. ¿ Analysis of Dietary Intake Data: In conjunction with researchers at the NCI, we have developed access to a number of exciting dietary intake data sets, including a major biomarker study, two major surveillance studies and a major prospective cohort study. Our "NCI-Method" for estimating the usual intake of foods uses one food at a time: we will get greater efficiency by developing methods for multiple foods simultaneously. Also, issues such as the healthy eating index (HEI) motivate the need to model multiple food intakes and nutrients simultaneously: we will develop those models and also statistical methods to fit them. ¿ Diet and Colon Carcinogenesis: We will develop semiparametric statistical methods for hierar- chical functional data to analyze a series of studies, done at the cellular level, involving diet, apoptosis, cellular response and colon carcinogenesis. Our new approach, based on a novel formulation of func- tional principal components, allows understanding of the effects of cell position in the colonic crypts, as well as incorporating crypt signahng, i.e., correlations of response among the crypts themselves. ¿ Semiparametric Methods: We will develop a series of novel statistical methods motivated by issues of gene-environment interaction studies. First, in case-control studies, we have shown that great gains in efficiency can be made if one can assume that genetic and environmental factors are independent in the population, possibly after conditioning on factors to account for population strat- ification. We will develop novel shrinkage approaches that allow efficient gene-environment inference with independence given strata holds but that are robust to deviations from this assumption. Second, we will consider studies for which the main interest is in whether there are genetic effects, but there is the possibility for gene-environment interaction. We will develop novel score-type tests for genetic effects in this context, where the careful use of projection ensures efficient inference. In the case of many genes, or SNPs, we will again use shrinkage ideas to improve the performance of score-type testing. This work will be extended to additive models and repeated measures/longitudinal data.
Assessing protein conformational sampling methods based on bivariate lag-distributions of backbone angles.
Authors: Maadooliat M, Gao X, Huang JZ
Source: Brief Bioinform, 2013 Nov;14(6), p. 724-36.
EPub date: 2012 Aug 27.
Analyzing multiple-probe microarray: estimation and application of gene expression indexes.
Authors: Maadooliat M, Huang JZ, Hu J
Source: Biometrics, 2012 Sep;68(3), p. 784-92.
EPub date: 2012 Jul 26.
Regression calibration with more surrogates than mismeasured variables.
Authors: Kipnis V, Midthune D, Freedman LS, Carroll RJ
Source: Stat Med, 2012 Oct 15;31(23), p. 2713-32.
EPub date: 2012 Jun 29.
Validating an FFQ for intake of episodically consumed foods: application to the National Institutes of Health-AARP Diet and Health Study.
Authors: Midthune D, Schatzkin A, Subar AF, Thompson FE, Freedman LS, Carroll RJ, Shumakovich MA, Kipnis V
Source: Public Health Nutr, 2011 Jul;14(7), p. 1212-21.
EPub date: 2011 Apr 13.
Methods for estimation of radiation risk in epidemiological studies accounting for classical and Berkson errors in doses.
Authors: Kukush A, Shklyar S, Masiuk S, Likhtarov I, Kovgan L, Carroll RJ, Bouville A
Source: Int J Biostat, 2011 Feb 16;7(1), p. 15.
EPub date: 2011 Feb 16.
Statistical methods for comparative phenomics using high-throughput phenotype microarrays.
Authors: Sturino J, Zorych I, Mallick B, Pokusaeva K, Chang YY, Carroll RJ, Bliznuyk N
Source: Int J Biostat, 2010 Aug 24;6(1), p. Article 29.
EPub date: 2010 Aug 24.
Statistics and bioinformatics in nutritional sciences: analysis of complex data in the era of systems biology.
Authors: Fu WJ, Stromberg AJ, Viele K, Carroll RJ, Wu G
Source: J Nutr Biochem, 2010 Jul;21(7), p. 561-72.
EPub date: 2010 Mar 16.
Biclustering via sparse singular value decomposition.
Authors: Lee M, Shen H, Huang JZ, Marron JS
Source: Biometrics, 2010 Dec;66(4), p. 1087-95.
Semiparametric bayesian analysis of nutritional epidemiology data in the presence of measurement error.
Authors: Sinha S, Mallick BK, Kipnis V, Carroll RJ
Source: Biometrics, 2010 Jun;66(2), p. 444-54.
EPub date: 2009 Aug 10.
Modeling data with excess zeros and measurement error: application to evaluating relationships between episodically consumed foods and health outcomes.
Authors: Kipnis V, Midthune D, Buckman DW, Dodd KW, Guenther PM, Krebs-Smith SM, Subar AF, Tooze JA, Carroll RJ, Freedman LS
Source: Biometrics, 2009 Dec;65(4), p. 1003-10.
Haplotype-based regression analysis and inference of case-control studies with unphased genotypes and measurement errors in environmental exposures.
Authors: Lobach I, Carroll RJ, Spinka C, Gail MH, Chatterjee N
Source: Biometrics, 2008 Sep;64(3), p. 673-84.
EPub date: 2007 Nov 12.
Dietary fish oil and pectin enhance colonocyte apoptosis in part through suppression of PPARdelta/PGE2 and elevation of PGE3.
Authors: Vanamala J, Glagolenko A, Yang P, Carroll RJ, Murphy ME, Newman RA, Ford JR, Braby LA, Chapkin RS, Turner ND, Lupton JR
Source: Carcinogenesis, 2008 Apr;29(4), p. 790-6.
EPub date: 2007 Nov 16.
Aberrant crypt foci and semiparametric modeling of correlated binary data.
Authors: Apanasovich TV, Ruppert D, Lupton JR, Popovic N, Turner ND, Chapkin RS, Carroll RJ
Source: Biometrics, 2008 Jun;64(2), p. 490-500.
EPub date: 2007 Aug 28.
Exploring the information in p-values for the analysis and planning of multiple-test experiments.
Authors: Ruppert D, Nettleton D, Hwang JT
Source: Biometrics, 2007 Jun;63(2), p. 483-95.
Bayesian hierarchical spatially correlated functional data analysis with application to colon carcinogenesis.
Authors: Baladandayuthapani V, Mallick BK, Young Hong M, Lupton JR, Turner ND, Carroll RJ
Source: Biometrics, 2008 Mar;64(1), p. 64-73.
EPub date: 2007 Jun 30.
Statistical models in assessing fold change of gene expression in real-time RT-PCR experiments.
Authors: Fu WJ, Hu J, Spencer T, Carroll R, Wu G
Source: Comput Biol Chem, 2006 Feb;30(1), p. 21-6.
Fish oil decreases oxidative DNA damage by enhancing apoptosis in rat colon.
Authors: Hong MY, Bancroft LK, Turner ND, Davidson LA, Murphy ME, Carroll RJ, Chapkin RS, Lupton JR
Source: Nutr Cancer, 2005;52(2), p. 166-75.
Differential response to DNA damage may explain different cancer susceptibility between small and large intestine.
Authors: Hong MY, Turner ND, Carroll RJ, Chapkin RS, Lupton JR
Source: Exp Biol Med (Maywood), 2005 Jul;230(7), p. 464-71.
Estimating misclassification error with small samples via bootstrap cross-validation.
Authors: Fu WJ, Carroll RJ, Wang S
Source: Bioinformatics, 2005 May 1;21(9), p. 1979-86.
EPub date: 2005 Feb 2.
An increase in reactive oxygen species by dietary fish oil coupled with the attenuation of antioxidant defenses by dietary pectin enhances rat colonocyte apoptosis.
Authors: Sanders LM, Henderson CE, Hong MY, Barhoumi R, Burghardt RC, Wang N, Spinka CM, Carroll RJ, Turner ND, Chapkin RS, Lupton JR
Source: J Nutr, 2004 Dec;134(12), p. 3233-8.
Chemopreventive n-3 polyunsaturated fatty acids reprogram genetic signatures during colon cancer initiation and progression in the rat.
Authors: Davidson LA, Nguyen DV, Hokanson RM, Callaway ES, Isett RB, Turner ND, Dougherty ER, Wang N, Lupton JR, Carroll RJ, Chapkin RS
Source: Cancer Res, 2004 Sep 15;64(18), p. 6797-804.
How many samples are needed to build a classifier: a general sequential approach.
Authors: Fu WJ, Dougherty ER, Mallick B, Carroll RJ
Source: Bioinformatics, 2005 Jan 1;21(1), p. 63-70.
EPub date: 2004 Aug 5.
Pro-oxidant environment of the colon compared to the small intestine may contribute to greater cancer susceptibility.
Authors: Sanders LM, Henderson CE, Hong MY, Barhoumi R, Burghardt RC, Carroll RJ, Turner ND, Chapkin RS, Lupton JR
Source: Cancer Lett, 2004 May 28;208(2), p. 155-61.
Understanding the relationship between carcinogen-induced DNA adduct levels in distal and proximal regions of the colon.
Authors: Morris JS, Wang N, Lupton JR, Chapkin RS, Turner ND, Hong MY, Carroll RJ
Source: Adv Exp Med Biol, 2003;537, p. 105-16.