Notably, healthy, physically active adults display a fat distribution with a relatively low level of visceral adiposity - regardless of their overall adiposity. The heterogeneity in level and types of obesity that exists among the five ethnic groups in the MEC offers a unique research setting to better understand the ill effects of increases in BMI and shifts in distribution of fat, including its relationship to cancer. More specifically, we propose a general viewpoint in which: (i) Fat deposition in various body fat storage compartments carries different risks of cancer;(ii) Amount and body distribution of lean and fat tissue vary across the five ethnic groups and explain some of the observed ethnic differences in cancer risk (particularly for breast and colorectal cancer) observed in the MEC population;(iii) Body fat amount and distribution act on cancer promofion through the same biological mechanisms but to different extents in the five ethnic groups of the MEC. In the context of this view, we propose to test the hypothesis that biomarkers of fat distribution are sufficiently robust biomarkers of disease risk that they predict disease risk across ethnic groups.
The Aims :
Aim 1 : To develop, optimize, and validate a defined series of nested plasma metabolomic biomarker profiles that reflect relative and absolute fat distribution in the context of overall body fat.
Aim 2 : To determine the similarities, differences, and interactions between the systemic metabolomic profiles of adiposity and body fat distribution and previously developed metabolomic profile(s) for caloric intake and dietary inter- and intra-class differences in macronutrient composition.
Aim 3 : To test the associations of these predictors of body fat amount and distribution with cancer risk in nested case-control studies using the prospectively collected biospecimens from the MEC (breast, colon) and the NHS (breast).
Aim 4 : To integrate results with those of the other projects in order to gain a better understanding of the underlying biology and better predict adiposity phenotypes and cancer risk. These data will improve public health by refining risk estimates of the links between adiposity and cancer risk. These data will improve public health by refining risk esfimates of the links between adiposity and cancer.
Excess body fat, especially in the abdomen, contributes to cancer risk. Most past studies relied on inaccurate proxies (e.g., BMI, waist circumference) and could not test potential similarities/differences among races. We will identify, optimize, and validate metabolomics-based biomarker profiles to assess overall adiposity, its distribution, and its associated effects on cancer risk in a multiethnic population.
|Lim, Unhee; Monroe, Kristine R; Buchthal, Steve et al. (2018) Propensity for Intra-abdominal and Hepatic Adiposity Varies Among Ethnic Groups. Gastroenterology :|
|Gathungu, Rose M; Larrea, Pablo; Sniatynski, Matthew J et al. (2018) Optimization of Electrospray Ionization Source Parameters for Lipidomics To Reduce Misannotation of In-Source Fragments as Precursor Ions. Anal Chem 90:13523-13532|
|Gathungu, Rose M; Kautz, Roger; Kristal, Bruce S et al. (2018) The integration of LC-MS and NMR for the analysis of low molecular weight trace analytes in complex matrices. Mass Spectrom Rev :|
|Citronberg, Jessica S; Wilkens, Lynne R; Le Marchand, Loic et al. (2018) Plasma lipopolysaccharide-binding protein and colorectal cancer risk: a nested case-control study in the Multiethnic Cohort. Cancer Causes Control 29:115-123|
|Randolph, Timothy W; Zhao, Sen; Copeland, Wade et al. (2018) KERNEL-PENALIZED REGRESSION FOR ANALYSIS OF MICROBIOME DATA. Ann Appl Stat 12:540-566|
|Maskarinec, Gertraud; Lim, Unhee; Jacobs, Simone et al. (2017) Diet Quality in Midadulthood Predicts Visceral Adiposity and Liver Fatness in Older Ages: The Multiethnic Cohort Study. Obesity (Silver Spring) 25:1442-1450|
|Fu, Benjamin C; Randolph, Timothy W; Lim, Unhee et al. (2016) Characterization of the gut microbiome in epidemiologic studies: the multiethnic cohort experience. Ann Epidemiol 26:373-9|
|Utzschneider, Kristina M; Kratz, Mario; Damman, Chris J et al. (2016) Mechanisms Linking the Gut Microbiome and Glucose Metabolism. J Clin Endocrinol Metab 101:1445-54|
|Gathungu, Rose M; Stavrovskaya, Irina G; Larrea, Pablo et al. (2016) Simple LC-MS Method for Differentiation of Isobaric Phosphatidylserines and Phosphatidylcholines with Deuterated Mobile Phase Additives. Anal Chem 88:9103-10|
|Citronberg, Jessica S; Wilkens, Lynne R; Lim, Unhee et al. (2016) Reliability of plasma lipopolysaccharide-binding protein (LBP) from repeated measures in healthy adults. Cancer Causes Control 27:1163-6|
Showing the most recent 10 out of 15 publications