Application of predictive biomarkers of sugars and animal protein intake for investigation of dietary measurement error and its effect on diet-disease associations

应用糖和动物蛋白摄入量的预测生物标志物研究饮食测量误差及其对饮食与疾病关联的影响

• 批准号: 10705720
• 负责人: Natasha Tasevska
• 金额: $ 44.72万
• 依托单位: ARIZONA STATE UNIVERSITY-TEMPE CAMPUS
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-16 至 2026-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10705720
• 关键词: Animals; Biological; Biological Markers; Biomarker of Dietary Intake; Calibration; Carbon Isotopes; Cardiovascular Diseases; Characteristics; Chronic Disease; Data; Dental caries; Diet; Dietary Assessment; Dietary Sugars; Dietary intake; Disease; Energy Intake; Equation; Ethnic Population; Evaluation; Food; Frequencies; Fructose; Future; Health; Hispanic Community Health Study; Hispanic Community Health Study/Study of Latinos; Intake; Intervention; Investigation; Malignant Neoplasms; Measurement; Measures; Methods; Nitrogen; Non-Insulin-Dependent Diabetes Mellitus; Nutritional Study; Obesity; Outcome; Participant; Patient Self-Report; Plant Proteins; Play; Population; Population Heterogeneity; Population Study; Prospective cohort; Prospective, cohort study; Proteins; Protocols documentation; Questionnaires; Recommendation; Records; Recovery; Resources; Risk; Role; Sampling; Serum; Source; Strategic Planning; Structure; Sucrose; Testing; Total Sugar; United States National Institutes of Health; Validation; aged; biomarker performance; burden of illness; cardiovascular disorder risk; cohort; diabetes risk; dietary; disorder risk; epidemiology study; ethnic diversity; evidence based guidelines; feeding; health disparity; improved; instrument; mortality; novel; novel marker; novel strategies; nutrition; nutritional epidemiology; parent project; population based; predictive marker; protein biomarkers; protein intake; racial diversity; sugar; urinary; validation studies

Project Summary Developing new approaches for obtaining accurate estimates of dietary intake is crucial for revealing true associations between dietary intakes and disease risk, with the ultimate aim of establishing evidence-based guidelines. While the evidence on dietary sugars and increased risks of dental caries and obesity have been stronger, the association between sugars and increased risk of cardiovascular disease (CVD), type 2 diabetes (T2D), and cancer remains inconclusive. The findings on total and animal protein (AP) intake in relation to T2D risk and CVD or all-cause mortality have also been inconsistent. Dietary biomarkers alleviate the problem of measurement errors (ME) associated with self-reporting dietary instruments commonly used in nutritional epidemiology, and have been used to validate and calibrate self-reported diet or to adjust for ME in self- reports, and reveal important associations. In the parent project of this renewal application, (SugarsBio study, U01-CA197902), we confirmed 24-h urinary sucrose and fructose (24uSF) as a predictive biomarker of total sugars (TS) intake, and demonstrated the transportability of the biomarker equation for estimating biomarker- based TS intake and its use across different populations. Furthermore, we have identified serum carbon isotope ratio (CIR) as a candidate predictive biomarker of the AP to total protein intake ratio (APR), a novel biomarker of protein quality, and developed a biomarker equation that can be used to generate biomarker- based APR in studies with available biological samples. The aim of this proposal is to investigate the utility and application of 24uSF and serum CIR biomarkers in diverse populations in two prospective cohorts. For this purpose, we will leverage data from two large dietary validation studies with comprehensive validation protocols (IDATA and SOLNAS) nested within cohorts, the NIH-AARP Diet and Health (AARP) Study and the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). First, we will study the ME in self-reported TS, and APR, AP and plant protein (PP) intake, using 24uSF and serum CIR biomarkers. Second, we will develop regression calibration equations for self-reported intake, based on biomarkers, in IDATA and SOLNAS that we will apply in their respective cohorts. Third, we will investigate uncalibrated and calibrated (i.e., ME- corrected) self-reported intakes of TS, AP, PP and APR in relation to CVD mortality in the AARP, and T2D risk in the HCHS/SOL cohort. Our study will be the first study that applies the newly developed US population- based sugars and protein intake biomarkers and their calibration equations to race/ethnically diverse US population-based studies and evaluates ME-corrected dietary intakes in relation to chronic diseases. By informing the best practices for applying these biomarkers in future diet validation studies and studies of diet-disease associations, this proposal will significantly contribute to improving dietary assessments and enhancing scientific rigor of nutritional epidemiologic studies.

项目概要 开发新方法来准确估计膳食摄入量对于揭示真实的饮食摄入量至关重要 饮食摄入量与疾病风险之间的关联，最终目标是建立基于证据的 指导方针。虽然饮食中的糖分会增加龋齿和肥胖风险的证据 糖与心血管疾病 (CVD)、2 型糖尿病风险增加之间的关联性更强 (T2D)，而癌症仍然没有定论。总蛋白和动物蛋白 (AP) 摄入量与 T2D 相关的研究结果 风险和心血管疾病或全因死亡率也不一致。膳食生物标志物缓解了以下问题 与营养学领域常用的自我报告饮食仪器相关的测量误差（ME） 流行病学，并已用于验证和校准自我报告的饮食或调整自我报告中的 ME 报告，并揭示重要的关联。在此更新应用程序的父项目中，（SugarsBio 研究， U01-CA197902），我们确认 24 小时尿蔗糖和果糖 (24uSF) 作为总尿糖和果糖的预测生物标志物 糖（TS）摄入量，并证明了生物标志物方程用于估计生物标志物的可移植性 基于 TS 的摄入量及其在不同人群中的使用。此外，我们还鉴定出血清碳 同位素比率（CIR）作为 AP 与总蛋白质摄入比率（APR）的候选预测生物标志物，一种新型的 蛋白质质量的生物标志物，并开发了可用于生成生物标志物的生物标志物方程 基于可用生物样本研究中的 APR。该提案的目的是调查实用性 以及 24uSF 和血清 CIR 生物标志物在两个前瞻性队列中不同人群中的应用。 为此，我们将利用两项大型饮食验证研究的数据进行全面验证 嵌套在队列中的协议（IDATA 和 SOLNAS）、NIH-AARP 饮食与健康 (AARP) 研究和 西班牙裔社区健康研究/拉丁裔研究 (HCHS/SOL)。首先，我们将研究自我报告中的ME TS、APR、AP 和植物蛋白 (PP) 摄入量，使用 24uSF 和血清 CIR 生物标志物。其次，我们将 根据 IDATA 和 SOLNAS 中的生物标志物，开发自我报告摄入量的回归校准方程 我们将在他们各自的群体中应用。第三，我们将调查未校准和校准的（即 ME- 自我报告的 TS、AP、PP 和 APR 摄入量与 AARP 中 CVD 死亡率以及 T2D 风险的关系 在 HCHS/SOL 队列中。我们的研究将是第一个应用新开发的美国人口的研究—— 基于糖和蛋白质摄入量的生物标志物及其校准方程，以适应美国种族/民族多元化 基于人群的研究和评估与慢性疾病相关的 ME 校正饮食摄入量。经过 告知在未来饮食验证研究和研究中应用这些生物标志物的最佳实践 饮食与疾病协会，该提案将大大有助于改善饮食评估和 提高营养流行病学研究的科学严谨性。