AS417 - Dietary metabolite profiling of nutrition and physical assessment

Investigator Names and Contact Information

Dan Raftery (draftery@uw.edu)

Introduction/Intent

Hypothesis/Statement of Study Goal

Metabolite profiling, both targeted and untargeted, has potential to contribute novel knowledge when applied to dietary and disease studies. In this pilot study we propose to use blood and urine specimens collected in the WHI core Nutrition and Physical Activity Assessment Study (NPAAS) to examine the extent to which metabolite profiling can recover variation among participants in their provided nutrients/foods in the current (feeding study) phase of NPAAS. The goal of these analyses is to identify biomarkers/objective markers for the consumption of specific nutrients or foods. Any novel biomarkers that emerge will then be used to develop calibration equations using dietary self-report data and study subject characteristics for the development of nutritional epidemiology association studies of uncommon reliability in WHI cohorts. Self-reported dietary information is notoriously inaccurate and reduces the confidence of studies that rely solely on this information. Our hypothesis is that metabolite profiling will allow a quantifiable and verifiable assessment with which to correct and enhance self-reporting. This pilot study will take advantage of the expertise of Dan Raftery's group in metabolite profiling, and the NPAAS investigator group in nutrition, epidemiology and data analysis.

Specific Aim of Proposed Study

We aim to identify specific metabolite biomarkers from both the ongoing human feeding study phase of NPAAS to identify novel consumption biomarkers from which biomarker-calibrated nutrient/food consumption estimates throughout the WHI cohorts can be developed, for use in novel disease-association studies.

Related Papers

Using controlled feeding study for biomarker development in regression calibration for disease association estimation

Cheng Zheng et al., 2023/4 PubMed #37324058 MSID: 3607
Correction for systematic measurement error in self-reported data is an important challenge in association studies of dietary intake and chronic disease risk. The regression calibration method has been used for this purpose when an objectively measured biomarker is available. However, a big limitation of the regression calibration method is that biomarkers have only been developed for a few dietary components. We propose new methods to use controlled feeding studies to develop valid biomarkers f...
Keywords: Measurement Error; Regression Calibration; Feeding Study; Biomarker; Cvd
Related Studies: 272, 417, 498

Evaluation of potential metabolomic-based biomarkers of protein, carbohydrate and fat intakes using a controlled feeding study

Cheng Zheng et al., 2021/5 PubMed #33991228 MSID: 3171
Purpose: Objective biomarkers of dietary exposure are needed to establish reliable diet-disease associations. Unfortunately, robust biomarkers of macronutrient intakes are scarce. We aimed to assess the utility of serum, 24-h urine and spot urine high-dimensional metabolites for the development of biomarkers of daily intake of total energy, protein, carbohydrate and fat, and the percent of energy from these macronutrients (%E). Methods: A 2-week controlled feeding study mimicking the participant...
Keywords: Biomarker; Diet; Feeding Study; Metabolomics; Postmenopausal Women; Carbohydrate
Related Studies: 417, 498

Using simultaneous regression calibration to study the effect of multiple error-prone exposures on disease risk utilizing biomarkers developed from a controlled feeding study

Yiwen Zhang et al., 2024/2 PubMed #38313601 MSID: 3912
Systematic measurement error in self-reported data creates important challenges in association studies between dietary intakes and chronic disease risks, especially when multiple dietary components are studied jointly. The joint regression calibration method has been developed for measurement error correction when objectively measured biomarkers are available for all dietary components of interest. Unfortunately, objectively measured biomarkers are only available for very few dietary components,...
Keywords: Measurement Error; Regression Calibration; Feeding Study; Biomarker; Cvd
Related Studies: 272, 417, 498

Regression calibration utilizing biomarkers developed from high-dimensional metabolites

Yiwen Zhang et al., 2023/8 PubMed #37599686 MSID: 3913
Addressing systematic measurement errors in self-reported data is a critical challenge in association studies of dietary intake and chronic disease risk. The regression calibration method has been utilized for error correction when an objectively measured biomarker is available; however, biomarkers for only a few dietary components have been developed. This paper proposes to use high-dimensional objective measurements to construct biomarkers for many more dietary components and to estimate the d...
Keywords: Measurement Error; Regression Calibration; High-Dimensional Data; Biomarker; Diabetes
Related Studies: 272, 417, 498

Demographic, Health and Lifestyle Factors Associated with the Metabolome in Older Women

Daniel Raftery et al., 2023/4 PubMed #37110172 MSID: 3613
Demographic and clinical factors influence the metabolome. The discovery and validation of disease biomarkers are often challenged by potential confounding effects from such factors. To address this challenge, we investigated the magnitude of the correlation between serum and urine metabolites and demographic and clinical parameters in a well-characterized observational cohort of 444 post-menopausal women participating in the Women's Health Initiative (WHI). Using LC-MS and lipidomics, we measur...
Keywords: Metabolomics; Confounding Factors; Diet; Physical Activity; Age; Bmi; Biomarkers
Related Studies: 417, 498