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 participants' habitual diets was conducted among 153 postmenopausal women from the Women's Health Initiative (WHI). Fasting serum metabolomic profiles were analyzed using a targeted liquid chromatography-tandem mass spectrometry (LC-MS/MS) assay for aqueous metabolites and a direct-injection-based quantitative lipidomics platform. Urinary metabolites were analyzed using 1H nuclear magnetic resonance (NMR) spectroscopy at 800 MHz and by untargeted gas chromatography-mass spectrometry (GC-MS). Variable selection was performed to build prediction models for each dietary variable. RESULTS: The highest cross-validated multiple correlation coefficients (CV-R2) for protein intake (%E) and carbohydrate intake (%E) using metabolites only were 36.3 and 37.1%, respectively. With the addition of established dietary biomarkers (doubly labeled water for energy and urinary nitrogen for protein), the CV-R2 reached 55.5% for energy (kcal/d), 52.0 and 45.0% for protein (g/d, %E), 55.9 and 37.0% for carbohydrate (g/d, %E). CONCLUSION: Selected panels of serum and urine metabolites, without the inclusion of doubly labeled water and urinary nitrogen biomarkers, give a reliable and robust prediction of daily intake of energy from protein and carbohydrate.
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 participants' habitual diets was conducted among 153 postmenopausal women from the Women's Health Initiative (WHI). Fasting serum metabolomic profiles were analyzed using a targeted liquid chromatography-tandem mass spectrometry (LC-MS/MS) assay for aqueous metabolites and a direct-injection-based quantitative lipidomics platform. Urinary metabolites were analyzed using 1H nuclear magnetic resonance (NMR) spectroscopy at 800 MHz and by untargeted gas chromatography-mass spectrometry (GC-MS). Variable selection was performed to build prediction models for each dietary variable. RESULTS: The highest cross-validated multiple correlation coefficients (CV-R2) for protein intake (%E) and carbohydrate intake (%E) using metabolites only were 36.3 and 37.1%, respectively. With the addition of established dietary biomarkers (doubly labeled water for energy and urinary nitrogen for protein), the CV-R2 reached 55.5% for energy (kcal/d), 52.0 and 45.0% for protein (g/d, %E), 55.9 and 37.0% for carbohydrate (g/d, %E). CONCLUSION: Selected panels of serum and urine metabolites, without the inclusion of doubly labeled water and urinary nitrogen biomarkers, give a reliable and robust prediction of daily intake of energy from protein and carbohydrate.
Authors: Xiaoling Song; Ying Huang; Marian L Neuhouser; Lesley F Tinker; Mara Z Vitolins; Ross L Prentice; Johanna W Lampe Journal: Am J Clin Nutr Date: 2017-04-26 Impact factor: 7.045
Authors: Ross L Prentice; Mary Pettinger; Cheng Zheng; Marian L Neuhouser; Daniel Raftery; G A Nagana Gowda; Ying Huang; Lesley F Tinker; Barbara V Howard; JoAnn E Manson; Linda Van Horn; Robert Wallace; Yasmin Mossavar-Rahmani; Karen C Johnson; Linda Snetselaar; Johanna W Lampe Journal: J Nutr Date: 2022-04-01 Impact factor: 4.798
Authors: Cheng Zheng; Mary Pettinger; G A Nagana Gowda; Johanna W Lampe; Daniel Raftery; Lesley F Tinker; Ying Huang; Sandi L Navarro; Diane M O'Brien; Linda Snetselaar; Simin Liu; Robert B Wallace; Marian L Neuhouser; Ross L Prentice Journal: J Nutr Date: 2022-07-06 Impact factor: 4.687
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Authors: Nathan Hwangbo; Xinyu Zhang; Daniel Raftery; Haiwei Gu; Shu-Ching Hu; Thomas J Montine; Joseph F Quinn; Kathryn A Chung; Amie L Hiller; Dongfang Wang; Qiang Fei; Lisa Bettcher; Cyrus P Zabetian; Elaine R Peskind; Ge Li; Daniel E L Promislow; Marie Y Davis; Alexander Franks Journal: Metabolites Date: 2022-03-22