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Fu Y, Gou W, Zhong H, Tian Y, Zhao H, Liang X, Shuai M, Zhuo LB, Jiang Z, Tang J, Ordovas JM, Chen YM, Zheng JS. Diet-gut microbiome interaction and its impact on host blood glucose homeostasis: a series of nutritional n-of-1 trials. EBioMedicine 2025; 111:105483. [PMID: 39647263 PMCID: PMC11667054 DOI: 10.1016/j.ebiom.2024.105483] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2024] [Revised: 11/13/2024] [Accepted: 11/19/2024] [Indexed: 12/10/2024] Open
Abstract
BACKGROUND The interplay between diet and gut microbiome substantially influences host metabolism, but uncertainties remain regarding their relationships tailored for each subject given the huge inter-individual variability. Here we aim to investigate diet-gut microbiome interaction at single-subject resolution and explore its effects on blood glucose homeostasis. METHODS We conducted a series of nutritional n-of-1 trials (NCT04125602), in which 30 participants were assigned high-carbohydrate (HC) and low-carbohydrate (LC) diets in a randomized sequence across 3 pair of cross-over periods lasting 72 days. We used shotgun metagenomic sequencing and continuous glucose monitoring systems to profile the gut microbiome and blood glucose, respectively. An independent cohort of 1219 participants with available metagenomics data are included as a validation cohort. FINDINGS We demonstrated that the gut microbiome exhibited both intra-individually dynamic and inter-individually personalized signatures during the interventions. At the single-subject resolution, we observed person-specific response patterns of gut microbiota to interventional diets. Furthermore, we discovered a personal gut microbial signature represented by a carb-sensitivity score, which was closely correlated with glycemic phenotypes during the HC intervention, but not LC intervention. We validate the role of this score in the validation cohort and find that it reflects host glycemic sensitivity to the personal gut microbiota profile when sensing the dietary carbohydrate inputs. INTERPRETATION Our finding suggests that the HC diet modulates gut microbiota in a person-specific manner and facilitates the connection between gut microbiota and glycemic sensitivity. This study represents a new paradigm for investigating the diet-microbiome interaction in the context of precision nutrition. FUNDING This work was supported by the National Key R&D Program of China, National Natural Science Foundation of China and Zhejiang Provincial Natural Science Foundation of China.
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Affiliation(s)
- Yuanqing Fu
- Affiliated Hangzhou First People's Hospital, School of Medicine, Westlake University, Hangzhou, China; Zhejiang Key Laboratory of Multi-Omics in Infection and Immunity, School of Medicine and School of Life Sciences, Westlake University, Hangzhou, China
| | - Wanglong Gou
- Zhejiang Key Laboratory of Multi-Omics in Infection and Immunity, School of Medicine and School of Life Sciences, Westlake University, Hangzhou, China
| | - Haili Zhong
- Department of Epidemiology, Guangdong Provincial Key Laboratory of Food, Nutrition and Health, School of Public Health, Sun Yat-Sen University, Guangzhou, China
| | - Yunyi Tian
- Zhejiang Key Laboratory of Multi-Omics in Infection and Immunity, School of Medicine and School of Life Sciences, Westlake University, Hangzhou, China
| | - Hui Zhao
- Zhejiang Key Laboratory of Multi-Omics in Infection and Immunity, School of Medicine and School of Life Sciences, Westlake University, Hangzhou, China
| | - Xinxiu Liang
- Zhejiang Key Laboratory of Multi-Omics in Infection and Immunity, School of Medicine and School of Life Sciences, Westlake University, Hangzhou, China
| | - Menglei Shuai
- Zhejiang Key Laboratory of Multi-Omics in Infection and Immunity, School of Medicine and School of Life Sciences, Westlake University, Hangzhou, China
| | - Lai-Bao Zhuo
- Department of Epidemiology, Guangdong Provincial Key Laboratory of Food, Nutrition and Health, School of Public Health, Sun Yat-Sen University, Guangzhou, China
| | - Zengliang Jiang
- Zhejiang Key Laboratory of Multi-Omics in Infection and Immunity, School of Medicine and School of Life Sciences, Westlake University, Hangzhou, China; Westlake Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China
| | - Jun Tang
- Zhejiang Key Laboratory of Multi-Omics in Infection and Immunity, School of Medicine and School of Life Sciences, Westlake University, Hangzhou, China; Westlake Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China
| | - Jose M Ordovas
- Nutrition and Genomics Laboratory, Jean Mayer USDA Human Nutrition Research Center on Aging, Tufts University, Boston, MA, USA; Nutritional Genomics and Epigenomics Group, Precision Nutrition and Obesity Program, IMDEA Food, CEI UAM + CSIC, Madrid, Spain; Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, Madrid, Spain
| | - Yu-Ming Chen
- Department of Epidemiology, Guangdong Provincial Key Laboratory of Food, Nutrition and Health, School of Public Health, Sun Yat-Sen University, Guangzhou, China.
| | - Ju-Sheng Zheng
- Affiliated Hangzhou First People's Hospital, School of Medicine, Westlake University, Hangzhou, China; Zhejiang Key Laboratory of Multi-Omics in Infection and Immunity, School of Medicine and School of Life Sciences, Westlake University, Hangzhou, China; Westlake Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China; Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, China.
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2
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Bailey RL, MacFarlane AJ, Field MS, Tagkopoulos I, Baranzini SE, Edwards KM, Rose CJ, Schork NJ, Singhal A, Wallace BC, Fisher KP, Markakis K, Stover PJ. Artificial intelligence in food and nutrition evidence: The challenges and opportunities. PNAS NEXUS 2024; 3:pgae461. [PMID: 39677367 PMCID: PMC11638775 DOI: 10.1093/pnasnexus/pgae461] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/12/2024] [Accepted: 10/02/2024] [Indexed: 12/17/2024]
Abstract
Science-informed decisions are best guided by the objective synthesis of the totality of evidence around a particular question and assessing its trustworthiness through systematic processes. However, there are major barriers and challenges that limit science-informed food and nutrition policy, practice, and guidance. First, insufficient evidence, primarily due to acquisition cost of generating high-quality data, and the complexity of the diet-disease relationship. Furthermore, the sheer number of systematic reviews needed across the entire agriculture and food value chain, and the cost and time required to conduct them, can delay the translation of science to policy. Artificial intelligence offers the opportunity to (i) better understand the complex etiology of diet-related chronic diseases, (ii) bring more precision to our understanding of the variation among individuals in the diet-chronic disease relationship, (iii) provide new types of computed data related to the efficacy and effectiveness of nutrition/food interventions in health promotion, and (iv) automate the generation of systematic reviews that support timely decisions. These advances include the acquisition and synthesis of heterogeneous and multimodal datasets. This perspective summarizes a meeting convened at the National Academy of Sciences, Engineering, and Medicine. The purpose of the meeting was to examine the current state and future potential of artificial intelligence in generating new types of computed data as well as automating the generation of systematic reviews to support evidence-based food and nutrition policy, practice, and guidance.
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Affiliation(s)
- Regan L Bailey
- Department of Nutrition, Texas A&M University, Cater-Mattil Hall, 373 Olsen Blvd Room 130, College Station, TX 77843, USA
- Institute for Advancing Health Through Agriculture, Texas A&M University, Borlaug Building, College Station, TX 77843, USA
| | - Amanda J MacFarlane
- Department of Nutrition, Texas A&M University, Cater-Mattil Hall, 373 Olsen Blvd Room 130, College Station, TX 77843, USA
- Texas A&M Agriculture, Food, and Nutrition Evidence Center, 801 Cherry Street, Fort Worth, TX 76102, USA
| | - Martha S Field
- Division of Nutritional Sciences, Cornell University, Savage Hall, Ithaca, NY 14850, USA
| | - Ilias Tagkopoulos
- Department of Computer Science and Genome Center, University of California, Davis, One Shields Avenue, Davis, CA 95616, USA
- USDA/NSF AI Institute for Next Generation Food Systems, University of California, Davis, One Shields Avenue, Davis, CA 95616, USA
| | - Sergio E Baranzini
- Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, 1651 4th St, San Francisco, CA 94158, USA
| | - Kristen M Edwards
- Department of Mechanical Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA
| | - Christopher J Rose
- Cluster for Reviews and Health Technology Assessments, Norwegian Institute of Public Health, PO Box 222 Skøyen, 0213 Oslo, Norway
- Centre for Epidemic Interventions Research, Norwegian Institute of Public Health, Lovisenberggata 8 0456, 0213 Oslo, Norway
| | - Nicholas J Schork
- Translational Genomics Research Institute, City of Hope National Medical Center, 445 N. Fifth Street, Phoenix, AZ 85004, USA
| | - Akshat Singhal
- Department of Computer Science and Engineering, University of California San Diego, 9500 Gilman Drive, San Diego, CA 92093, USA
| | - Byron C Wallace
- Khoury College of Computer Sciences, Northeastern University, #202, West Village Residence Complex H, 440 Huntington Ave, Boston, MA 02115, USA
| | - Kelly P Fisher
- Institute for Advancing Health Through Agriculture, Texas A&M University, Borlaug Building, College Station, TX 77843, USA
| | - Konstantinos Markakis
- Department of Computer Science and Genome Center, University of California, Davis, One Shields Avenue, Davis, CA 95616, USA
| | - Patrick J Stover
- Department of Nutrition, Texas A&M University, Cater-Mattil Hall, 373 Olsen Blvd Room 130, College Station, TX 77843, USA
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3
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Roseti L, Borciani G, Grassi F, Desando G, Gambari L, Grigolo B. Nutraceuticals in osteoporosis prevention. Front Nutr 2024; 11:1445955. [PMID: 39416651 PMCID: PMC11479890 DOI: 10.3389/fnut.2024.1445955] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2024] [Accepted: 09/03/2024] [Indexed: 10/19/2024] Open
Abstract
Nutraceuticals are gaining popularity as they can contribute to bone health by delaying the onset or slowing down the progression of pathological bone loss. Osteoporosis's bone loss is a concern for older adults and a crucial aspect of aging. Maintaining healthy bones is the key to living a full and active life. Our review explores the current knowledge on the role of nutraceuticals in preventing osteoporosis by focusing on three main aspects. First, we provide an overview of osteoporosis. Second, we discuss the latest findings on natural nutraceuticals and their efficacy in reducing bone loss, emphasizing clinical trials. Third, we conduct a structured analysis to evaluate nutraceuticals' pros and cons and identify translational gaps. In conclusion, we must address several challenges to consolidate our knowledge, better support clinicians in their prescriptions, and provide people with more reliable nutritional recommendations to help them lead healthier lives.
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Affiliation(s)
| | - Giorgia Borciani
- RAMSES Laboratory, Rizzoli RIT-Research, Innovation & Technology Department, Istituto di Ricerca Codivilla Putti, IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy
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4
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Hinojosa-Nogueira D, Subiri-Verdugo A, Díaz-Perdigones CM, Rodríguez-Muñoz A, Vilches-Pérez A, Mela V, Tinahones FJ, Moreno-Indias I. Precision or Personalized Nutrition: A Bibliometric Analysis. Nutrients 2024; 16:2922. [PMID: 39275239 PMCID: PMC11397555 DOI: 10.3390/nu16172922] [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] [Received: 07/14/2024] [Revised: 08/16/2024] [Accepted: 08/26/2024] [Indexed: 09/16/2024] Open
Abstract
Food systems face the challenge of maintaining adequate nutrition for all populations. Inter-individual responses to the same diet have made precision or personalized nutrition (PN) an emerging and relevant topic. The aim of this study is to analyze the evolution of the PN field, identifying the principal actors and topics, and providing a comprehensive overview. Therefore, a bibliometric analysis of the scientific research available through the Web of Science (WOS) database was performed, revealing 2148 relevant papers up to June 2024. VOSviewer and the WOS platform were employed for the processing and analysis, and included an evaluation of diverse data such as country, author or most frequent keywords, among others. The analysis revealed a period of exponential growth from 2015 to 2023, with the USA, Spain, and England as the top contributors. The field of "Nutrition and Dietetics" is particularly significant, comprising nearly 33% of the total publications. The most highly cited institutions are the universities of Tufts, College Dublin, and Navarra. The relationship between nutrition, genetics, and omics sciences, along with dietary intervention studies, has been a defining factor in the evolution of PN. In conclusion, PN represents a promising field of research with significant potential for further advancement and growth.
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Affiliation(s)
- Daniel Hinojosa-Nogueira
- Instituto de Investigación Biomédica de Málaga y Plataforma en Nanomedicina-IBIMA Plataforma BIONAND, 29590 Malaga, Spain
- Unidad de Gestión Clínica de Endocrinología y Nutrición, Hospital Universitario Virgen de la Victoria, 29010 Malaga, Spain
| | - Alba Subiri-Verdugo
- Instituto de Investigación Biomédica de Málaga y Plataforma en Nanomedicina-IBIMA Plataforma BIONAND, 29590 Malaga, Spain
- Unidad de Gestión Clínica de Endocrinología y Nutrición, Hospital Universitario Virgen de la Victoria, 29010 Malaga, Spain
- Department of Medicine and Dermatology, Faculty of Medicine, University of Málaga, 29010 Malaga, Spain
| | - Cristina Mª Díaz-Perdigones
- Instituto de Investigación Biomédica de Málaga y Plataforma en Nanomedicina-IBIMA Plataforma BIONAND, 29590 Malaga, Spain
- Unidad de Gestión Clínica de Endocrinología y Nutrición, Hospital Universitario Virgen de la Victoria, 29010 Malaga, Spain
| | - Alba Rodríguez-Muñoz
- Instituto de Investigación Biomédica de Málaga y Plataforma en Nanomedicina-IBIMA Plataforma BIONAND, 29590 Malaga, Spain
- Unidad de Gestión Clínica de Endocrinología y Nutrición, Hospital Universitario Virgen de la Victoria, 29010 Malaga, Spain
- Department of Medicine and Dermatology, Faculty of Medicine, University of Málaga, 29010 Malaga, Spain
| | - Alberto Vilches-Pérez
- Instituto de Investigación Biomédica de Málaga y Plataforma en Nanomedicina-IBIMA Plataforma BIONAND, 29590 Malaga, Spain
- Unidad de Gestión Clínica de Endocrinología y Nutrición, Hospital Universitario Virgen de la Victoria, 29010 Malaga, Spain
| | - Virginia Mela
- Instituto de Investigación Biomédica de Málaga y Plataforma en Nanomedicina-IBIMA Plataforma BIONAND, 29590 Malaga, Spain
- Unidad de Gestión Clínica de Endocrinología y Nutrición, Hospital Universitario Virgen de la Victoria, 29010 Malaga, Spain
- Department of Medicine and Dermatology, Faculty of Medicine, University of Málaga, 29010 Malaga, Spain
- CIBER Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto Salud Carlos III, 28029 Madrid, Spain
| | - Francisco J Tinahones
- Instituto de Investigación Biomédica de Málaga y Plataforma en Nanomedicina-IBIMA Plataforma BIONAND, 29590 Malaga, Spain
- Unidad de Gestión Clínica de Endocrinología y Nutrición, Hospital Universitario Virgen de la Victoria, 29010 Malaga, Spain
- Department of Medicine and Dermatology, Faculty of Medicine, University of Málaga, 29010 Malaga, Spain
- CIBER Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto Salud Carlos III, 28029 Madrid, Spain
| | - Isabel Moreno-Indias
- Instituto de Investigación Biomédica de Málaga y Plataforma en Nanomedicina-IBIMA Plataforma BIONAND, 29590 Malaga, Spain
- Unidad de Gestión Clínica de Endocrinología y Nutrición, Hospital Universitario Virgen de la Victoria, 29010 Malaga, Spain
- CIBER Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto Salud Carlos III, 28029 Madrid, Spain
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5
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de Roos B. How good are we at predicting the individual response to personalized diets? Am J Clin Nutr 2024; 120:3-4. [PMID: 38960577 DOI: 10.1016/j.ajcnut.2024.04.031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2024] [Accepted: 04/26/2024] [Indexed: 07/05/2024] Open
Affiliation(s)
- Baukje de Roos
- The Rowett Institute, University of Aberdeen, Foresterhill, Aberdeen, United Kingdom.
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6
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Hickson M, Papoutsakis C, Madden AM, Smith MA, Whelan K. Nature of the evidence base and approaches to guide nutrition interventions for individuals: a position paper from the Academy of Nutrition Sciences. Br J Nutr 2024; 131:1754-1773. [PMID: 38305040 DOI: 10.1017/s0007114524000291] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2024]
Abstract
This Position Paper from the Academy of Nutrition Sciences is the third in a series which describe the nature of the scientific evidence and frameworks that underpin nutrition recommendations for health. This paper focuses on evidence which guides the application of dietary recommendations for individuals. In some situations, modified nutrient intake becomes essential to prevent deficiency, optimise development and health, or manage symptoms and disease progression. Disease and its treatment can also affect taste, appetite and ability to access and prepare foods, with associated financial impacts. Therefore, the practice of nutrition and dietetics must integrate and apply the sciences of food, nutrition, biology, physiology, behaviour, management, communication and society to achieve and maintain human health. Thus, there is huge complexity in delivering evidence-based nutrition interventions to individuals. This paper examines available frameworks for appraising the quality and certainty of nutrition research evidence, the development nutrition practice guidelines to support evidence implementation in practice and the influence of other sources of nutrition information and misinformation. The paper also considers major challenges in applying research evidence to an individual and suggests consensus recommendations to begin to address these challenges in the future. Our recommendations target three groups; those who deliver nutrition interventions to individuals, those funding, commissioning or undertaking research aimed at delivering evidence-based nutrition practice, and those disseminating nutritional information to individuals.
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Affiliation(s)
- Mary Hickson
- University of Plymouth, Plymouth, PL4 6ABDevon, UK
- British Dietetic Association, Birmingham, UK
| | - Constantina Papoutsakis
- Academy of Nutrition and Dietetics, Nutrition and Dietetics Data Science Centre, Research, International, and Scientific Affairs (RISA), Chicago, USA
| | | | | | - Kevin Whelan
- King's College London, Department of Nutritional Sciences, London, UK
- Academy of Nutrition Sciences, London, UK
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7
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Zoh RS, Esteves BH, Yu X, Fairchild AJ, Vazquez AI, Chapple AG, Brown AW, George B, Gordon D, Landsittel D, Gadbury GL, Pavela G, de Los Campos G, Mestre LM, Allison DB. Design, analysis, and interpretation of treatment response heterogeneity in personalized nutrition and obesity treatment research. Obes Rev 2023; 24:e13635. [PMID: 37667550 PMCID: PMC10825777 DOI: 10.1111/obr.13635] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/02/2022] [Revised: 03/29/2023] [Accepted: 07/24/2023] [Indexed: 09/06/2023]
Abstract
It is increasingly assumed that there is no one-size-fits-all approach to dietary recommendations for the management and treatment of chronic diseases such as obesity. This phenomenon that not all individuals respond uniformly to a given treatment has become an area of research interest given the rise of personalized and precision medicine. To conduct, interpret, and disseminate this research rigorously and with scientific accuracy, however, requires an understanding of treatment response heterogeneity. Here, we define treatment response heterogeneity as it relates to clinical trials, provide statistical guidance for measuring treatment response heterogeneity, and highlight study designs that can quantify treatment response heterogeneity in nutrition and obesity research. Our goal is to educate nutrition and obesity researchers in how to correctly identify and consider treatment response heterogeneity when analyzing data and interpreting results, leading to rigorous and accurate advancements in the field of personalized medicine.
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Affiliation(s)
- Roger S Zoh
- Department of Epidemiology and Biostatistics, Indiana University School of Public Health-Bloomington, Bloomington, Indiana, USA
| | | | - Xiaoxin Yu
- Department of Epidemiology and Biostatistics, Indiana University School of Public Health-Bloomington, Bloomington, Indiana, USA
| | - Amanda J Fairchild
- Department of Psychology, University of South Carolina, Columbia, South Carolina, USA
| | - Ana I Vazquez
- Department of Epidemiology and Biostatistics, Michigan State University, Lansing, Michigan, USA
| | - Andrew G Chapple
- Biostatistics Program, School of Public Health, LSU Health Sciences Center, New Orleans, Louisiana, USA
| | - Andrew W Brown
- Department of Applied Health Science, Indiana University School of Public Health-Bloomington, Bloomington, Indiana, USA
| | - Brandon George
- College of Population Health, Thomas Jefferson University, Philadelphia, Pennsylvania, USA
| | - Derek Gordon
- Department of Genetics, Rutgers Robert Wood Johnson Medical School, New Brunswick, New Jersey, USA
| | - Douglas Landsittel
- Department of Epidemiology and Biostatistics, Indiana University School of Public Health-Bloomington, Bloomington, Indiana, USA
| | - Gary L Gadbury
- Department of Statistics, Kansas State University, Manhattan, Kansa, USA
| | - Greg Pavela
- Department of Health Behavior, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Gustavo de Los Campos
- Departments of Epidemiology & Biostatistics and Statistics & Probability, IQ - Institute for Quantitative Health Science and Engineering, Michigan State University, Lansing, Michigan, USA
| | - Luis M Mestre
- Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut, USA
| | - David B Allison
- Department of Epidemiology and Biostatistics, Indiana University School of Public Health-Bloomington, Bloomington, Indiana, USA
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8
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Gou W, Miao Z, Deng K, Zheng JS. Nutri-microbiome epidemiology, an emerging field to disentangle the interplay between nutrition and microbiome for human health. Protein Cell 2023; 14:787-806. [PMID: 37099800 PMCID: PMC10636640 DOI: 10.1093/procel/pwad023] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2023] [Accepted: 04/02/2023] [Indexed: 04/28/2023] Open
Abstract
Diet and nutrition have a substantial impact on the human microbiome, and interact with the microbiome, especially gut microbiome, to modulate various diseases and health status. Microbiome research has also guided the nutrition field to a more integrative direction, becoming an essential component of the rising area of precision nutrition. In this review, we provide a broad insight into the interplay among diet, nutrition, microbiome, and microbial metabolites for their roles in the human health. Among the microbiome epidemiological studies regarding the associations of diet and nutrition with microbiome and its derived metabolites, we summarize those most reliable findings and highlight evidence for the relationships between diet and disease-associated microbiome and its functional readout. Then, the latest advances of the microbiome-based precision nutrition research and multidisciplinary integration are described. Finally, we discuss several outstanding challenges and opportunities in the field of nutri-microbiome epidemiology.
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Affiliation(s)
- Wanglong Gou
- Westlake Intelligent Biomarker Discovery Lab, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou 310024, China
- Research Center for Industries of the Future, Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou 310030, China
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou 310024, China
| | - Zelei Miao
- Westlake Intelligent Biomarker Discovery Lab, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou 310024, China
- Research Center for Industries of the Future, Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou 310030, China
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou 310024, China
| | - Kui Deng
- Westlake Intelligent Biomarker Discovery Lab, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou 310024, China
- Research Center for Industries of the Future, Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou 310030, China
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou 310024, China
| | - Ju-Sheng Zheng
- Westlake Intelligent Biomarker Discovery Lab, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou 310024, China
- Research Center for Industries of the Future, Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou 310030, China
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou 310024, China
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9
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Brennan L, de Roos B. Role of metabolomics in the delivery of precision nutrition. Redox Biol 2023; 65:102808. [PMID: 37423161 PMCID: PMC10461186 DOI: 10.1016/j.redox.2023.102808] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2023] [Revised: 06/14/2023] [Accepted: 07/04/2023] [Indexed: 07/11/2023] Open
Abstract
Precision nutrition aims to deliver personalised dietary advice to individuals based on their personal genetics, metabolism and dietary/environmental exposures. Recent advances have demonstrated promise for the use of omic technologies for furthering the field of precision nutrition. Metabolomics in particular is highly attractive as measurement of metabolites can capture information on food intake, levels of bioactive compounds and the impact of diets on endogenous metabolism. These aspects contain useful information for precision nutrition. Furthermore using metabolomic profiles to identify subgroups or metabotypes is attractive for the delivery of personalised dietary advice. Combining metabolomic derived metabolites with other parameters in prediction models is also an exciting avenue for understanding and predicting response to dietary interventions. Examples include but not limited to role of one carbon metabolism and associated co-factors in blood pressure response. Overall, while evidence exists for potential in this field there are also many unanswered questions. Addressing these and clearly demonstrating that precision nutrition approaches enable adherence to healthier diets and improvements in health will be key in the near future.
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Affiliation(s)
- Lorraine Brennan
- Institute of Food and Health and Conway Institute, UCD School of Agriculture and Food Science, UCD, Belfield, Dublin 4, Ireland.
| | - Baukje de Roos
- The Rowett Institute, University of Aberdeen, Foresterhill, Aberdeen, AB25 2ZD, United Kingdom
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Allman-Farinelli M, Boljevac B, Vuong T, Hekler E. Nutrition-Related N-of-1 Studies Warrant Further Research to Provide Evidence for Dietitians to Practice Personalized (Precision) Medical Nutrition Therapy: A Systematic Review. Nutrients 2023; 15:1756. [PMID: 37049595 PMCID: PMC10097352 DOI: 10.3390/nu15071756] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2023] [Revised: 03/28/2023] [Accepted: 03/31/2023] [Indexed: 04/14/2023] Open
Abstract
N-of-1 trials provide a higher level of evidence than randomized controlled trials for determining which treatment works best for an individual, and the design readily accommodates testing of personalized nutrition. The aim of this systematic review was to synthesize nutrition-related studies using an N-of-1 design. The inclusion criterion was adult participants; the intervention/exposure was any nutrient, food, beverage, or dietary pattern; the comparators were baseline values, a control condition untreated or placebo, or an alternate treatment, alongside any outcomes such as changes in diet, body weight, biochemical outcomes, symptoms, quality of life, or a disease outcome resulting from differences in nutritional conditions. The information sources used were Medline, Embase, Scopus, Cochrane Central, and PsychInfo. The quality of study reporting was assessed using the Consort Extension for N-of-1 trials (CENT) statement or the STrengthening Reporting of OBservational Studies in Epidemiology (STROBE) guidelines, as appropriate. From 211 articles screened, a total of 7 studies were included and were conducted in 5 countries with a total of 83 participants. The conditions studied included prediabetes, diabetes, irritable bowel syndrome, weight management, and investigation of the effect of diet in healthy people. The quality of reporting was mostly adequate, and dietary assessment quality varied from poor to good. The evidence base is small, but served to illustrate the main characteristics of N-of-1 study designs and considerations for moving research forward in the era of personalized medical nutrition therapy.
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Affiliation(s)
- Margaret Allman-Farinelli
- Discipline of Nutrition and Dietetics, Susan Wakil School of Nursing and Midwifery, Faculty of Medicine and Health, The University of Sydney, Camperdown, NSW 2006, Australia
- The Charles Perkins Centre, The University of Sydney, Camperdown, NSW 2006, Australia
| | - Brianna Boljevac
- Discipline of Nutrition and Dietetics, Susan Wakil School of Nursing and Midwifery, Faculty of Medicine and Health, The University of Sydney, Camperdown, NSW 2006, Australia
| | - Tiffany Vuong
- Discipline of Nutrition and Dietetics, Susan Wakil School of Nursing and Midwifery, Faculty of Medicine and Health, The University of Sydney, Camperdown, NSW 2006, Australia
| | - Eric Hekler
- The Design Lab, University of California San Diego, San Diego, CA 92093, USA
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, San Diego, CA 92093, USA
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11
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Ramos Meyers G, Samouda H, Bohn T. Short Chain Fatty Acid Metabolism in Relation to Gut Microbiota and Genetic Variability. Nutrients 2022; 14:5361. [PMID: 36558520 PMCID: PMC9788597 DOI: 10.3390/nu14245361] [Citation(s) in RCA: 55] [Impact Index Per Article: 18.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2022] [Revised: 12/12/2022] [Accepted: 12/13/2022] [Indexed: 12/23/2022] Open
Abstract
It is widely accepted that the gut microbiota plays a significant role in modulating inflammatory and immune responses of their host. In recent years, the host-microbiota interface has gained relevance in understanding the development of many non-communicable chronic conditions, including cardiovascular disease, cancer, autoimmunity and neurodegeneration. Importantly, dietary fibre (DF) and associated compounds digested by the microbiota and their resulting metabolites, especially short-chain fatty acids (SCFA), were significantly associated with health beneficial effects, such as via proposed anti-inflammatory mechanisms. However, SCFA metabolic pathways are not fully understood. Major steps include production of SCFA by microbiota, uptake in the colonic epithelium, first-pass effects at the liver, followed by biodistribution and metabolism at the host's cellular level. As dietary patterns do not affect all individuals equally, the host genetic makeup may play a role in the metabolic fate of these metabolites, in addition to other factors that might influence the microbiota, such as age, birth through caesarean, medication intake, alcohol and tobacco consumption, pathogen exposure and physical activity. In this article, we review the metabolic pathways of DF, from intake to the intracellular metabolism of fibre-derived products, and identify possible sources of inter-individual variability related to genetic variation. Such variability may be indicative of the phenotypic flexibility in response to diet, and may be predictive of long-term adaptations to dietary factors, including maladaptation and tissue damage, which may develop into disease in individuals with specific predispositions, thus allowing for a better prediction of potential health effects following personalized intervention with DF.
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Affiliation(s)
- Guilherme Ramos Meyers
- Nutrition and Health Research Group, Department of Precision Health, Luxembourg Institute of Health, 1 A-B, Rue Thomas Edison, 1445 Strassen, Luxembourg
- Doctoral School in Science and Engineering, University of Luxembourg, 2, Avenue de l'Université, 4365 Esch-sur-Alzette, Luxembourg
| | - Hanen Samouda
- Nutrition and Health Research Group, Department of Precision Health, Luxembourg Institute of Health, 1 A-B, Rue Thomas Edison, 1445 Strassen, Luxembourg
| | - Torsten Bohn
- Nutrition and Health Research Group, Department of Precision Health, Luxembourg Institute of Health, 1 A-B, Rue Thomas Edison, 1445 Strassen, Luxembourg
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12
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Merino J. Precision nutrition in diabetes: when population-based dietary advice gets personal. Diabetologia 2022; 65:1839-1848. [PMID: 35593923 DOI: 10.1007/s00125-022-05721-6] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/07/2022] [Accepted: 03/01/2022] [Indexed: 12/12/2022]
Abstract
Diet plays a fundamental role in maintaining long-term health, with healthful diets being endorsed by current dietary guidelines for the prevention and management of type 2 diabetes. However, the response to dietary interventions varies widely, highlighting the need for refinement and personalisation beyond population-based 'one size fits all'. This article reviews the clinical evidence supporting precision nutrition as a fundamental approach for dietary advice in diabetes. Further, it proposes a framework for the eventual implementation of precision nutrition and discusses key challenges for the application of this approach in the prevention of diabetes. One implication of this approach is that precision nutrition would not exclude the parallel goal of population-based healthy dietary advice. Nevertheless, the shift in prioritising precision nutrition is needed to reflect the dynamic nature of responses to dietary interventions that vary among individuals and change over the life course.
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Affiliation(s)
- Jordi Merino
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Department of Medicine, Harvard Medical School, Boston, MA, USA.
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13
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Potter TIT, Horgan GW, Wanders AJ, Zandstra EH, Zock PL, Fisk HL, Minihane AM, Calder PC, Mathers JC, de Roos B. Models predict change in plasma triglyceride concentrations and long-chain n-3 polyunsaturated fatty acid proportions in healthy participants after fish oil intervention. Front Nutr 2022; 9:989716. [PMID: 36386924 PMCID: PMC9641003 DOI: 10.3389/fnut.2022.989716] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Accepted: 09/30/2022] [Indexed: 11/29/2022] Open
Abstract
Introduction Substantial response heterogeneity is commonly seen in dietary intervention trials. In larger datasets, this variability can be exploited to identify predictors, for example genetic and/or phenotypic baseline characteristics, associated with response in an outcome of interest. Objective Using data from a placebo-controlled crossover study (the FINGEN study), supplementing with two doses of long chain n-3 polyunsaturated fatty acids (LC n-3 PUFAs), the primary goal of this analysis was to develop models to predict change in concentrations of plasma triglycerides (TG), and in the plasma phosphatidylcholine (PC) LC n-3 PUFAs eicosapentaenoic acid (EPA) + docosahexaenoic acid (DHA), after fish oil (FO) supplementation. A secondary goal was to establish if clustering of data prior to FO supplementation would lead to identification of groups of participants who responded differentially. Methods To generate models for the outcomes of interest, variable selection methods (forward and backward stepwise selection, LASSO and the Boruta algorithm) were applied to identify suitable predictors. The final model was chosen based on the lowest validation set root mean squared error (RMSE) after applying each method across multiple imputed datasets. Unsupervised clustering of data prior to FO supplementation was implemented using k-medoids and hierarchical clustering, with cluster membership compared with changes in plasma TG and plasma PC EPA + DHA. Results Models for predicting response showed a greater TG-lowering after 1.8 g/day EPA + DHA with lower pre-intervention levels of plasma insulin, LDL cholesterol, C20:3n-6 and saturated fat consumption, but higher pre-intervention levels of plasma TG, and serum IL-10 and VCAM-1. Models also showed greater increases in plasma PC EPA + DHA with age and female sex. There were no statistically significant differences in PC EPA + DHA and TG responses between baseline clusters. Conclusion Our models established new predictors of response in TG (plasma insulin, LDL cholesterol, C20:3n-6, saturated fat consumption, TG, IL-10 and VCAM-1) and in PC EPA + DHA (age and sex) upon intervention with fish oil. We demonstrate how application of statistical methods can provide new insights for precision nutrition, by predicting participants who are most likely to respond beneficially to nutritional interventions.
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Affiliation(s)
| | - Graham W. Horgan
- Biomathematics and Statistics Scotland, Aberdeen, United Kingdom
| | | | - Elizabeth H. Zandstra
- Unilever Foods Innovation Centre, Wageningen, Netherlands
- Division of Human Nutrition and Health, Wageningen University and Research, Wageningen, Netherlands
| | - Peter L. Zock
- Division of Human Nutrition and Health, Wageningen University and Research, Wageningen, Netherlands
| | - Helena L. Fisk
- Faculty of Medicine, University of Southampton, Southampton, United Kingdom
| | - Anne M. Minihane
- Norwich Medical School, University of East Anglia, Norwich, United Kingdom
| | - Philip C. Calder
- Faculty of Medicine, University of Southampton, Southampton, United Kingdom
- NIHR Southampton Biomedical Research Centre, University Hospital Southampton NHS Foundation Trust, University of Southampton, Southampton, United Kingdom
| | - John C. Mathers
- Human Nutrition Research Centre, Population Health Sciences Institute, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Baukje de Roos
- The Rowett Institute, University of Aberdeen, Aberdeen, United Kingdom
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14
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Evans M, Lewis ED, Antony JM, Crowley DC, Guthrie N, Blumberg JB. Breaking new frontiers: Assessment and re-evaluation of clinical trial design for nutraceuticals. Front Nutr 2022; 9:958753. [PMID: 36211523 PMCID: PMC9540398 DOI: 10.3389/fnut.2022.958753] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Accepted: 08/31/2022] [Indexed: 11/13/2022] Open
Abstract
Despite sophisticated study designs and measurement tools, we have yet to create an innovative space for diet and dietary supplements in the health care system. The path is challenging due to current hierarchies of scientific evidence and regulatory affairs. The role of the randomized, double-blind, placebo-controlled clinical trial (RCT) as a research approach functions well to characterize the benefits and risks of drugs but lacks the sensitivity to capture the efficacy and safety of nutraceuticals. While some facets of RCTs can be relevant and useful when applied to nutraceuticals, other aspects are limiting and potentially misleading when taken in their entirety. A differentiation between guidelines for evidence-based medicine and the evidence required for nutrition spotlight the need to reconceptualize constituents of the RCT and their applicability with relevance to health promotion. This perspective identifies the limitations of the traditional RCT to capture the complexities of nutraceuticals and proposes the N-of-1 as Level 1 evidence better suited for the proof of efficacy of nutraceuticals.
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Affiliation(s)
- Malkanthi Evans
- KGK Science Inc., London, ON, Canada
- *Correspondence: Malkanthi Evans
| | | | | | | | | | - Jeffrey B. Blumberg
- Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA, United States
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15
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Berciano S, Figueiredo J, Brisbois TD, Alford S, Koecher K, Eckhouse S, Ciati R, Kussmann M, Ordovas JM, Stebbins K, Blumberg JB. Precision nutrition: Maintaining scientific integrity while realizing market potential. Front Nutr 2022; 9:979665. [PMID: 36118748 PMCID: PMC9481417 DOI: 10.3389/fnut.2022.979665] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Accepted: 08/15/2022] [Indexed: 11/24/2022] Open
Abstract
Precision Nutrition (PN) is an approach to developing comprehensive and dynamic nutritional recommendations based on individual variables, including genetics, microbiome, metabolic profile, health status, physical activity, dietary pattern, food environment as well as socioeconomic and psychosocial characteristics. PN can help answer the question “What should I eat to be healthy?”, recognizing that what is healthful for one individual may not be the same for another, and understanding that health and responses to diet change over time. The growth of the PN market has been driven by increasing consumer interest in individualized products and services coupled with advances in technology, analytics, and omic sciences. However, important concerns are evident regarding the adequacy of scientific substantiation supporting claims for current products and services. An additional limitation to accessing PN is the current cost of diagnostic tests and wearable devices. Despite these challenges, PN holds great promise as a tool to improve healthspan and reduce healthcare costs. Accelerating advancement in PN will require: (a) investment in multidisciplinary collaborations to enable the development of user-friendly tools applying technological advances in omics, sensors, artificial intelligence, big data management, and analytics; (b) engagement of healthcare professionals and payers to support equitable and broader adoption of PN as medicine shifts toward preventive and personalized approaches; and (c) system-wide collaboration between stakeholders to advocate for continued support for evidence-based PN, develop a regulatory framework to maintain consumer trust and engagement, and allow PN to reach its full potential.
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Affiliation(s)
- Silvia Berciano
- Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA, United States
| | - Juliana Figueiredo
- Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA, United States
| | - Tristin D. Brisbois
- Advanced Personalization Ideation Center, PepsiCo Inc., Purchase, New York, NY, United States
| | - Susan Alford
- Novo Nordisk Inc., Plainsboro Township, NJ, United States
| | - Katie Koecher
- Bell Institute of Health and Nutrition, General Mills, Inc., Minneapolis, MN, United States
| | | | | | | | - Jose M. Ordovas
- Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA, United States
- Nutrition and Genomics Laboratory, JM-USDA-Human Nutrition Research Center on Aging, Tufts University, Boston, MA, United States
| | - Katie Stebbins
- Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA, United States
| | - Jeffrey B. Blumberg
- Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA, United States
- *Correspondence: Jeffrey B. Blumberg
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16
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Grammatikopoulou MG, Gkouskou KK, Gkiouras K, Bogdanos DP, Eliopoulos AG, Goulis DG. The Niche of n-of-1 Trials in Precision Medicine for Weight Loss and Obesity Treatment: Back to the Future. Curr Nutr Rep 2022; 11:133-145. [PMID: 35174475 DOI: 10.1007/s13668-022-00404-5] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/02/2022] [Indexed: 12/18/2022]
Abstract
PURPOSE OF REVIEW The n-of-1 clinical trials are considered the epitome of individualized health care. They are employed to address differences in treatment response and adverse events between patients, in a comparative effectiveness manner, extending beyond the delivery of horizontal recommendations for all. RECENT FINDINGS The n-of-1 design has been applied to deliver precision exercise interventions, through eHealth and mHealth technologies. Regarding personalized and precision medical nutrition therapy, few trials have implemented dietary manipulations and one series of n-of-1 trials has applied comprehensive genetic data to improve body weight. With regard to anti-obesity medication, pharmacogenetic data could be applied using the n-of-1 trial design, although none have been implemented yet. The n-of-1 clinical trials consist of the only tool for the delivery of evidence-based, personalized obesity treatment (lifestyle and pharmacotherapy), reducing non-responders, while tailoring the best intervention to each patient, through "trial and error". Their application is expected to improve obesity treatment and mitigate the epidemic.
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Affiliation(s)
- Maria G Grammatikopoulou
- Department of Nutritional Sciences and Dietetics, Faculty of Health Sciences, Alexander Campus, International Hellenic University, Sindos, PO Box 141, 57400, Thessaloniki, Greece.
| | - Kalliopi K Gkouskou
- Department of Biology, School of Medicine, National and Kapodistrian University of Athens, Mikras Asias 75, 11527, Athens, Greece
- Embiodiagnostics Biology Research Company, 1 Melissinon and Damvergidon Street, Konstantinou Papadaki, 71305, Heraklion, Crete, Greece
| | - Konstantinos Gkiouras
- Department of Rheumatology and Clinical Immunology, Faculty of Medicine, School of Health Sciences, University of Thessaly, Biopolis, 41334, Larissa, Greece
| | - Dimitrios P Bogdanos
- Department of Rheumatology and Clinical Immunology, Faculty of Medicine, School of Health Sciences, University of Thessaly, Biopolis, 41334, Larissa, Greece
| | - Aristides G Eliopoulos
- Department of Biology, School of Medicine, National and Kapodistrian University of Athens, Mikras Asias 75, 11527, Athens, Greece
- Biomedical Research Foundation of the Academy of Athens, 4 Soranou Ephessiou Street, 11527, Athens, Greece
| | - Dimitrios G Goulis
- Unit of Reproductive Endocrinology, 1St Department of Obstetrics and Gynecology, Medical School, Faculty of Health Sciences, Aristotle University of Thessaloniki, Thessaloniki, Greece
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17
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Cahoon DS, Shertukde SP, Nirmala N, Lau J, Lichtenstein AH. Perspective: Appraisal of the Evidence Base to Update DRI Values-Lessons from the Past, Thoughts for the Future. Adv Nutr 2022; 13:975-981. [PMID: 35404437 PMCID: PMC9340966 DOI: 10.1093/advances/nmac041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Revised: 02/10/2022] [Accepted: 04/08/2022] [Indexed: 11/12/2022] Open
Abstract
Updating evidence-based nutrient guidance is challenging. One set of recommendations for which a robust evidence base is essential is the DRIs. In the past 10 y, DRI values for 4 essential nutrients have been re-evaluated in 2 groups: vitamin D and calcium, and sodium and potassium. To support the work of the committees tasked with evaluating the available evidence, the federal agencies that sponsor the DRI reviews contracted with the Agency for Healthcare Research and Quality to perform systematic reviews on predefined questions for these nutrient groups. Our aims were to tabulate the studies included in these systematic reviews and then, within the context of prespecified outcomes, summarize the totality of the available evidence and identify areas for consideration to maximize the value of the end products for future DRI committees. For the outcomes of interest, the available studies did not tend to report age data consistent with the current DRI categories. For some life stage categories, particularly pregnancy and lactation, there is a dearth of data. A wide range of study interventions were used, making it challenging to combine data to accurately derive or re-evaluate DRI values. There is also an under-representation of data on race/ethnicity and overweight/obesity, which is of concern, given the shifting demographic in the US and Canadian populations. Moving forward, it may be advantageous to develop a process to prospectively target research funding for studies designed to generate data that will most closely support re-evaluation of DRI values.
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Affiliation(s)
- Danielle S Cahoon
- Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA, USA,Jean Mayer USDA Human Nutrition Research Center on Aging, Tufts University, Boston, MA, USA
| | - Shruti P Shertukde
- Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA, USA
| | - Nanguneri Nirmala
- Institute for Clinical Research and Health Policy Studies, Tufts Medical Center, Boston, MA, USA
| | - Joseph Lau
- Center for Evidence Synthesis in Health, Brown University, Providence, RI, USA
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18
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Gkouskou KK, Grammatikopoulou MG, Lazou E, Sanoudou D, Goulis DG, Eliopoulos AG. Genetically-Guided Medical Nutrition Therapy in Type 2 Diabetes Mellitus and Pre-diabetes: A Series of n-of-1 Superiority Trials. Front Nutr 2022; 9:772243. [PMID: 35265654 PMCID: PMC8899711 DOI: 10.3389/fnut.2022.772243] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2021] [Accepted: 01/12/2022] [Indexed: 12/12/2022] Open
Abstract
Type 2 diabetes mellitus (T2DM) is a heterogeneous metabolic disorder of multifactorial etiology that includes genetic and dietary influences. By addressing the latter, medical nutrition therapy (MNT) contributes to the management of T2DM or pre-diabetes toward achieving glycaemic control and improved insulin sensitivity. However, the clinical outcomes of MNT vary and may further benefit from personalized nutritional plans that take into consideration genetic variations associated with individual responses to macronutrients. The aim of the present series of n-of-1 trials was to assess the effects of genetically-guided vs. conventional MNT on patients with pre-diabetes or T2DM. A quasi-experimental, cross-over design was adopted in three Caucasian adult men with either diagnosis. Complete diet, bioclinical and anthropometric assessment was performed and a conventional MNT, based on the clinical practice guidelines was applied for 8 weeks. After a week of “wash-out,” a precision MNT was prescribed for an additional 8-week period, based on the genetic characteristics of each patient. Outcomes of interest included changes in body weight (BW), fasting plasma glucose (FPG), and blood pressure (BP). Collectively, the trials indicated improvements in BW, FPG, BP, and glycosylated hemoglobin (HbA1c) following the genetically-guided precision MNT intervention. Moreover, both patients with pre-diabetes experienced remission of the condition. We conclude that improved BW loss and glycemic control can be achieved in patients with pre-diabetes/T2DM, by coupling MNT to their genetic makeup, guiding optimal diet, macronutrient composition, exercise and oral nutrient supplementation in a personalized manner.
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Affiliation(s)
- Kalliopi K Gkouskou
- Department of Biology, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece.,Embiodiagnostics Biology Research Company, Heraklion, Greece
| | - Maria G Grammatikopoulou
- Unit of Reproductive Endocrinology, First Department of Obstetrics and Gynecology, Faculty of Health Sciences, Medical School, Aristotle University of Thessaloniki, Thessaloniki, Greece.,Department of Nutritional Sciences and Dietetics, Faculty of Health Sciences, International Hellenic University, Thessaloniki, Greece
| | - Evgenia Lazou
- Department of Biology, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece
| | - Despina Sanoudou
- Clinical Genomics and Pharmacogenomics Unit, Fourth Department of Internal Medicine, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece.,Center of Basic Research, Biomedical Research Foundation of the Academy of Athens, Athens, Greece
| | - Dimitrios G Goulis
- Unit of Reproductive Endocrinology, First Department of Obstetrics and Gynecology, Faculty of Health Sciences, Medical School, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Aristides G Eliopoulos
- Department of Biology, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece.,Center of Basic Research, Biomedical Research Foundation of the Academy of Athens, Athens, Greece
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19
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Individual behavioural factors are associated with compliance and response to a wholegrains and nuts intervention - a proof of principle interventional N-of-1 study. Proc Nutr Soc 2022. [DOI: 10.1017/s0029665122001963] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
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20
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Zheng JS, Ordovás JM. Precision nutrition for gut microbiome and diabetes research: Application of nutritional n-of-1 clinical trials. J Diabetes 2021; 13:1059-1061. [PMID: 34453774 DOI: 10.1111/1753-0407.13220] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/25/2021] [Revised: 08/11/2021] [Accepted: 08/14/2021] [Indexed: 11/26/2022] Open
Affiliation(s)
- Ju-Sheng Zheng
- School of Life Sciences, Westlake University, Hangzhou, China
- Westlake Intelligent Biomarker Lab, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China
| | - José M Ordovás
- Jean Mayer USDA Human Nutrition Research Center on Aging at Tufts University, Boston, Massachusetts, USA
- IMDEA Food Institute, Madrid, Spain
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21
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de Roos B. Diet, blood pressure, and heart disease-precision nutrition approaches to understand response to diet and predict disease risk. Am J Clin Nutr 2021; 114:1581-1582. [PMID: 34637492 DOI: 10.1093/ajcn/nqab313] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022] Open
Affiliation(s)
- Baukje de Roos
- Rowett Institute, University of Aberdeen, Foresterhill, Aberdeen, United Kingdom
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22
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Ma Y, Fu Y, Tian Y, Gou W, Miao Z, Yang M, Ordovás JM, Zheng JS. Individual Postprandial Glycemic Responses to Diet in n-of-1 Trials: Westlake N-of-1 Trials for Macronutrient Intake (WE-MACNUTR). J Nutr 2021; 151:3158-3167. [PMID: 34255080 PMCID: PMC8485912 DOI: 10.1093/jn/nxab227] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2020] [Revised: 03/17/2021] [Accepted: 06/18/2021] [Indexed: 12/16/2022] Open
Abstract
BACKGROUND The role of different types and quantities of macronutrients on human health has been controversial, and the individual response to dietary macronutrient intake needs more investigation. OBJECTIVES We aimed to use an 'n-of-1' study design to investigate the individual variability in postprandial glycemic response when eating diets with different macronutrient distributions among apparently healthy adults. METHODS Thirty apparently healthy young Chinese adults (women, 68%) aged between 22 and 34 y, with BMI between 17.2 and 31.9 kg/m2, were provided with high-fat, low-carbohydrate (HF-LC, 60-70% fat, 15-25% carbohydrate, 15% protein, of total energy) and low-fat, high-carbohydrate (LF-HC, 10-20% fat, 65-75% carbohydrate, 15% protein) diets, for 6 d wearing continuous glucose monitoring systems, respectively, in a randomized sequence, interspersed by a 6-d wash-out period. Three cycles were conducted. The primary outcomes were the differences of maximum postprandial glucose (MPG), mean amplitude of glycemic excursions (MAGE), and AUC24 between intervention periods of LF-HC and HF-LC diets. A Bayesian model was used to predict responders with the posterior probability of any 1 of the 3 outcomes reaching a clinically meaningful difference. RESULTS Twenty-eight participants were included in the analysis. Posterior probability of reaching a clinically meaningful difference of MPG (0.167 mmol/L), MAGE (0.072 mmol/L), and AUC24 (13.889 mmol/L·h) between LF-HC and HF-LC diets varied among participants, and those with posterior probability >80% were identified as high-carbohydrate responders (n = 9) or high-fat responders (n = 6). Analyses of the Bayesian-aggregated n-of-1 trials among all participants showed a relatively low posterior probability of reaching a clinically meaningful difference of the 3 outcomes between LF-HC and HF-LC diets. CONCLUSIONS N-of-1 trials are feasible to characterize personal response to dietary intervention in young Chinese adults.
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Affiliation(s)
- Yue Ma
- Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China
- Westlake Intelligent Biomarker Discovery Lab, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, China
| | - Yuanqing Fu
- Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China
- Westlake Intelligent Biomarker Discovery Lab, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, China
| | - Yunyi Tian
- Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China
- Westlake Intelligent Biomarker Discovery Lab, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China
| | - Wanglong Gou
- Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China
- Westlake Intelligent Biomarker Discovery Lab, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China
| | - Zelei Miao
- Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China
- Westlake Intelligent Biomarker Discovery Lab, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China
| | - Min Yang
- Chronic Disease Research Institute, Department of Nutrition and Food Hygiene, Zhejiang University School of Public Health, Hangzhou, China
| | - José M Ordovás
- Jean Mayer USDA Human Nutrition Research Center on Aging at Tufts University, Boston, MA, USA
- IMDEA Food Institute, Madrid, Spain
| | - Ju-Sheng Zheng
- Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China
- Westlake Intelligent Biomarker Discovery Lab, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, China
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23
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Kaput J. Developing the Pathway to Personalized Health: The Potential of N-of-1 Studies for Personalizing Nutrition. J Nutr 2021; 151:2863-2864. [PMID: 34293136 DOI: 10.1093/jn/nxab243] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
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Witkamp RF. Nutrition to Optimise Human Health-How to Obtain Physiological Substantiation? Nutrients 2021; 13:2155. [PMID: 34201670 PMCID: PMC8308379 DOI: 10.3390/nu13072155] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2021] [Revised: 06/19/2021] [Accepted: 06/21/2021] [Indexed: 12/12/2022] Open
Abstract
Demonstrating in an unambiguous manner that a diet, let alone a single product, 'optimizes' health, presents an enormous challenge. The least complicated is when the starting situation is clearly suboptimal, like with nutritional deficiencies, malnutrition, unfavourable lifestyle, or due to disease or ageing. Here, desired improvements and intervention strategies may to some extent be clear. However, even then situations require approaches that take into account interactions between nutrients and other factors, complex dose-effect relationships etc. More challenging is to substantiate that a diet or a specific product optimizes health in the general population, which comes down to achieve perceived, 'non-medical' or future health benefits in predominantly healthy persons. Presumed underlying mechanisms involve effects of non-nutritional components with subtle and slowly occurring physiological effects that may be difficult to translate into measurable outcomes. Most promising strategies combine classical physiological concepts with those of 'multi-omics' and systems biology. Resilience-the ability to maintain or regain homeostasis in response to stressors-is often used as proxy for a particular health domain. Next to this, quantifying health requires personalized strategies, measurements preferably carried out remotely, real-time and in a normal living environment, and experimental designs other than randomized controlled trials (RCTs), for example N-of-1 trials.
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Affiliation(s)
- Renger F Witkamp
- Division of Human Nutrition and Health, Wageningen University & Research (WUR), 6700 AA Wageningen, The Netherlands
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