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Sawicki C, Haslam D, Bhupathiraju S. Utilising the precision nutrition toolkit in the path towards precision medicine. Proc Nutr Soc 2023; 82:359-369. [PMID: 37475596 DOI: 10.1017/s0029665123003038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/22/2023]
Abstract
The overall aim of precision nutrition is to replace the 'one size fits all' approach to dietary advice with recommendations that are more specific to the individual in order to improve the prevention or management of chronic disease. Interest in precision nutrition has grown with advancements in technologies such as genomics, proteomics, metabolomics and measurement of the gut microbiome. Precision nutrition initiatives have three major applications in precision medicine. First, they aim to provide more 'precision' dietary assessments through artificial intelligence, wearable devices or by employing omic technologies to characterise diet more precisely. Secondly, precision nutrition allows us to understand the underlying mechanisms of how diet influences disease risk and identify individuals who are more susceptible to disease due to gene-diet or microbiota-diet interactions. Third, precision nutrition can be used for 'personalised nutrition' advice where machine-learning algorithms can integrate data from omic profiles with other personal and clinical measures to improve disease risk. Proteomics and metabolomics especially provide the ability to discover new biomarkers of food or nutrient intake, proteomic or metabolomic signatures of diet and disease, and discover potential mechanisms of diet-disease interactions. Although there are several challenges that must be overcome to improve the reproducibility, cost-effectiveness and efficacy of these approaches, precision nutrition methodologies have great potential for nutrition research and clinical application.
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Affiliation(s)
- Caleigh Sawicki
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Danielle Haslam
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Shilpa Bhupathiraju
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
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Sierra JA, Escobar JS, Corrales-Agudelo V, Lara-Guzmán OJ, Velásquez-Mejía EP, Henao-Rojas JC, Caro-Quintero A, Vaillant F, Muñoz-Durango K. Consumption of golden berries (Physalis peruviana L.) might reduce biomarkers of oxidative stress and alter gut permeability in men without changing inflammation status or the gut microbiota. Food Res Int 2022; 162:111949. [DOI: 10.1016/j.foodres.2022.111949] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2022] [Revised: 09/07/2022] [Accepted: 09/13/2022] [Indexed: 11/04/2022]
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Beckmann M, Wilson T, Lloyd AJ, Torres D, Goios A, Willis ND, Lyons L, Phillips H, Mathers JC, Draper J. Challenges Associated With the Design and Deployment of Food Intake Urine Biomarker Technology for Assessment of Habitual Diet in Free-Living Individuals and Populations-A Perspective. Front Nutr 2020; 7:602515. [PMID: 33344495 PMCID: PMC7745244 DOI: 10.3389/fnut.2020.602515] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2020] [Accepted: 10/29/2020] [Indexed: 12/27/2022] Open
Abstract
Improvement of diet at the population level is a cornerstone of national and international strategies for reducing chronic disease burden. A critical challenge in generating robust data on habitual dietary intake is accurate exposure assessment. Self-reporting instruments (e.g., food frequency questionnaires, dietary recall) are subject to reporting bias and serving size perceptions, while weighed dietary assessments are unfeasible in large-scale studies. However, secondary metabolites derived from individual foods/food groups and present in urine provide an opportunity to develop potential biomarkers of food intake (BFIs). Habitual dietary intake assessment in population surveys using biomarkers presents several challenges, including the need to develop affordable biofluid collection methods, acceptable to participants that allow collection of informative samples. Monitoring diet comprehensively using biomarkers requires analytical methods to quantify the structurally diverse mixture of target biomarkers, at a range of concentrations within urine. The present article provides a perspective on the challenges associated with the development of urine biomarker technology for monitoring diet exposure in free-living individuals with a view to its future deployment in "real world" situations. An observational study (n = 95), as part of a national survey on eating habits, provided an opportunity to explore biomarker measurement in a free-living population. In a second food intervention study (n = 15), individuals consumed a wide range of foods as a series of menus designed specifically to achieve exposure reflecting a diversity of foods commonly consumed in the UK, emulating normal eating patterns. First Morning Void urines were shown to be suitable samples for biomarker measurement. Triple quadrupole mass spectrometry, coupled with liquid chromatography, was used to assess simultaneously the behavior of a panel of 54 potential BFIs. This panel of chemically diverse biomarkers, reporting intake of a wide range of commonly-consumed foods, can be extended successfully as new biomarker leads are discovered. Towards validation, we demonstrate excellent discrimination of eating patterns and quantitative relationships between biomarker concentrations in urine and the intake of several foods. In conclusion, we believe that the integration of information from BFI technology and dietary self-reporting tools will expedite research on the complex interactions between dietary choices and health.
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Affiliation(s)
- Manfred Beckmann
- Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Aberystwyth, United Kingdom
| | - Thomas Wilson
- Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Aberystwyth, United Kingdom
| | - Amanda J. Lloyd
- Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Aberystwyth, United Kingdom
| | - Duarte Torres
- Faculty of Nutrition and Food Sciences, University of Porto, Porto, Portugal
- Epidemiology Research Unit (EPIUnit), Institute of Public Health, University of Porto, Porto, Portugal
| | - Ana Goios
- Faculty of Nutrition and Food Sciences, University of Porto, Porto, Portugal
- Epidemiology Research Unit (EPIUnit), Institute of Public Health, University of Porto, Porto, Portugal
| | - Naomi D. Willis
- Human Nutrition Research Centre, Population Health Sciences Institute, William Leech Building, Newcastle University, Newcastle-upon-Tyne, United Kingdom
| | - Laura Lyons
- Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Aberystwyth, United Kingdom
| | - Helen Phillips
- Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Aberystwyth, United Kingdom
| | - John C. Mathers
- Human Nutrition Research Centre, Population Health Sciences Institute, William Leech Building, Newcastle University, Newcastle-upon-Tyne, United Kingdom
| | - John Draper
- Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Aberystwyth, United Kingdom
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