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Singar S, Nagpal R, Arjmandi BH, Akhavan NS. Personalized Nutrition: Tailoring Dietary Recommendations through Genetic Insights. Nutrients 2024; 16:2673. [PMID: 39203810 PMCID: PMC11357412 DOI: 10.3390/nu16162673] [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: 07/19/2024] [Revised: 08/08/2024] [Accepted: 08/09/2024] [Indexed: 09/03/2024] Open
Abstract
Personalized nutrition (PN) represents a transformative approach in dietary science, where individual genetic profiles guide tailored dietary recommendations, thereby optimizing health outcomes and managing chronic diseases more effectively. This review synthesizes key aspects of PN, emphasizing the genetic basis of dietary responses, contemporary research, and practical applications. We explore how individual genetic differences influence dietary metabolisms, thus underscoring the importance of nutrigenomics in developing personalized dietary guidelines. Current research in PN highlights significant gene-diet interactions that affect various conditions, including obesity and diabetes, suggesting that dietary interventions could be more precise and beneficial if they are customized to genetic profiles. Moreover, we discuss practical implementations of PN, including technological advancements in genetic testing that enable real-time dietary customization. Looking forward, this review identifies the robust integration of bioinformatics and genomics as critical for advancing PN. We advocate for multidisciplinary research to overcome current challenges, such as data privacy and ethical concerns associated with genetic testing. The future of PN lies in broader adoption across health and wellness sectors, promising significant advancements in public health and personalized medicine.
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Affiliation(s)
- Saiful Singar
- Department of Health, Nutrition, and Food Sciences, College of Education, Health, and Human Sciences, Florida State University, Tallahassee, FL 32306, USA; (S.S.); (R.N.); (B.H.A.)
| | - Ravinder Nagpal
- Department of Health, Nutrition, and Food Sciences, College of Education, Health, and Human Sciences, Florida State University, Tallahassee, FL 32306, USA; (S.S.); (R.N.); (B.H.A.)
| | - Bahram H. Arjmandi
- Department of Health, Nutrition, and Food Sciences, College of Education, Health, and Human Sciences, Florida State University, Tallahassee, FL 32306, USA; (S.S.); (R.N.); (B.H.A.)
| | - Neda S. Akhavan
- Department of Kinesiology and Nutrition Sciences, School of Integrated Health Sciences, University of Nevada, Las Vegas, NV 89154, USA
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Sharma S, Subrahmanyam YV, Ranjani H, Sidra S, Parmar D, Vadivel S, Kannan S, Grallert H, Usharani D, Anjana RM, Balasubramanyam M, Mohan V, Jerzy A, Panchagnula V, Gokulakrishnan K. Circulatory levels of lysophosphatidylcholine species in obese adolescents: Findings from cross-sectional and prospective lipidomics analyses. Nutr Metab Cardiovasc Dis 2024; 34:1807-1816. [PMID: 38503619 DOI: 10.1016/j.numecd.2024.02.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Revised: 02/15/2024] [Accepted: 02/19/2024] [Indexed: 03/21/2024]
Abstract
BACKGROUND AND AIMS Obesity has reached epidemic proportions, emphasizing the importance of reliable biomarkers for detecting early metabolic alterations and enabling early preventative interventions. However, our understanding of the molecular mechanisms and specific lipid species associated with childhood obesity remains limited. Therefore, the aim of this study was to investigate plasma lipidomic signatures as potential biomarkers for adolescent obesity. METHODS AND RESULTS A total of 103 individuals comprising overweight/obese (n = 46) and normal weight (n = 57) were randomly chosen from the baseline ORANGE (Obesity Reduction and Noncommunicable Disease Awareness through Group Education) cohort, having been followed up for a median of 7.1 years. Plasma lipidomic profiling was performed using the UHPLC-HRMS method. We used three different models adjusted for clinical covariates to analyze the data. Clustering methods were used to define metabotypes, which allowed for the stratification of subjects into subgroups with similar clinical and metabolic profiles. We observed that lysophosphatidylcholine (LPC) species like LPC.16.0, LPC.18.3, LPC.18.1, and LPC.20.3 were significantly (p < 0.05) associated with baseline and follow-up BMI in adolescent obesity. The association of LPC species with BMI remained consistently significant even after adjusting for potential confounders. Moreover, applying metabotyping using hierarchical clustering provided insights into the metabolic heterogeneity within the normal and obese groups, distinguishing metabolically healthy individuals from those with unhealthy metabolic profiles. CONCLUSION The specific LPC levels were found to be altered and increased in childhood obesity, particularly during the follow-up. These findings suggest that LPC species hold promise as potential biomarkers of obesity in adolescents, including healthy and unhealthy metabolic profiles.
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Affiliation(s)
- Sapna Sharma
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764, Neuherberg, Germany
| | - Yalamanchili Venkata Subrahmanyam
- CEPD Division, CSIR-National Chemical Laboratory, Dr. Homi Bhabha Road, Pune, 411008 India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India
| | - Harish Ranjani
- Madras Diabetes Research Foundation, No. 4, Conran Smith Road, Gopalapuram, Chennai, 600086 India; Department of Preventive and Digital Health Research, Madras Diabetes Research Foundation, No. 4, Conran Smith Road, Gopalapuram, Chennai, 600086 India
| | - Sidra Sidra
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764, Neuherberg, Germany
| | - Dharmeshkumar Parmar
- CEPD Division, CSIR-National Chemical Laboratory, Dr. Homi Bhabha Road, Pune, 411008 India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India
| | - Sangeetha Vadivel
- Madras Diabetes Research Foundation, No. 4, Conran Smith Road, Gopalapuram, Chennai, 600086 India
| | - Shanthini Kannan
- Madras Diabetes Research Foundation, No. 4, Conran Smith Road, Gopalapuram, Chennai, 600086 India
| | - Harald Grallert
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764, Neuherberg, Germany
| | - Dandamudi Usharani
- Department of Food Safety and Analytical Quality Control Laboratory, CSIR-Central Food Technological Research Institute (CFTRI), Mysore, Karnataka 570020, India
| | - Ranjit Mohan Anjana
- Madras Diabetes Research Foundation, No. 4, Conran Smith Road, Gopalapuram, Chennai, 600086 India
| | | | - Viswanathan Mohan
- Madras Diabetes Research Foundation, No. 4, Conran Smith Road, Gopalapuram, Chennai, 600086 India
| | - Adamski Jerzy
- Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstraße 1, 85764 Neuherberg, Germany; Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, 8 Medical Drive, 117597, Singapore; Institute of Biochemistry, Faculty of Medicine, University of Ljubljana, Vrazov trg 2, 1000 Ljubljana, Slovenia
| | - Venkateswarlu Panchagnula
- CEPD Division, CSIR-National Chemical Laboratory, Dr. Homi Bhabha Road, Pune, 411008 India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India
| | - Kuppan Gokulakrishnan
- Department of Neurochemistry, National Institute of Mental Health and Neuro Sciences (NIMHANS), Hosur Road, Bengaluru, Karnataka 560029, India.
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Thorakkattu P, Awasti N, Sajith Babu K, Khanashyam AC, Deliephan A, Shah K, Singh P, Pandiselvam R, Nirmal NP. 3D printing: trends and approaches toward achieving long-term sustainability in the food industry. Crit Rev Biotechnol 2024:1-21. [PMID: 38797671 DOI: 10.1080/07388551.2024.2344577] [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: 03/07/2023] [Accepted: 06/17/2023] [Indexed: 05/29/2024]
Abstract
Global food security has recently been under serious threat from the rapid rise in the world's population, the problems brought on by climate change, and the appearance of new pandemics. As a result, the need for novel and innovative solutions to solve the existing problems and improve food sustainability has become crucial. 3D printing is expected to play a significant role in providing tangible contributions to the food industry in achieving sustainable development goals. The 3D food printing holds the potential to produce highly customized food in terms of shape, texture, flavor, structure and nutritional value and enable us to create new unique formulations and edible alternatives. The problem of whether the cost of the printed meal and 3D printing itself can be sustainably produced is becoming more and more important due to global concerns. This review intends to provide a comprehensive overview of 3D printed foods with an overview of the current printing methodologies, illustrating the technology's influencing factors, and its applications in personalized nutrition, packaging, value addition, and valorization aspects to fully integrate sustainability concerns thus exploring the potential of 3D food printing.
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Affiliation(s)
- Priyamvada Thorakkattu
- Department of Animal Sciences and Industry, Food Science Institute, KS State University, Manhattan, USA
| | | | | | | | | | | | - Punit Singh
- Department of Mechanical Engineering, Institute of Engineering and Technology, GLA University Mathura, Chaumuhan, India
| | - R Pandiselvam
- Physiology, Biochemistry and Post-Harvest Technology Division, ICAR-Central Plantation Crops Research Institute (CPCRI), Kasaragod, India
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Skantze V, Jirstrand M, Brunius C, Sandberg AS, Landberg R, Wallman M. Data-driven analysis and prediction of dynamic postprandial metabolic response to multiple dietary challenges using dynamic mode decomposition. Front Nutr 2024; 10:1304540. [PMID: 38357465 PMCID: PMC10865386 DOI: 10.3389/fnut.2023.1304540] [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: 10/03/2023] [Accepted: 12/11/2023] [Indexed: 02/16/2024] Open
Abstract
Motivation In the field of precision nutrition, predicting metabolic response to diet and identifying groups of differential responders are two highly desirable steps toward developing tailored dietary strategies. However, data analysis tools are currently lacking, especially for complex settings such as crossover studies with repeated measures.Current methods of analysis often rely on matrix or tensor decompositions, which are well suited for identifying differential responders but lacking in predictive power, or on dynamical systems modeling, which may be used for prediction but typically requires detailed mechanistic knowledge of the system under study. To remedy these shortcomings, we explored dynamic mode decomposition (DMD), which is a recent, data-driven method for deriving low-rank linear dynamical systems from high dimensional data.Combining the two recent developments "parametric DMD" (pDMD) and "DMD with control" (DMDc) enabled us to (i) integrate multiple dietary challenges, (ii) predict the dynamic response in all measured metabolites to new diets from only the metabolite baseline and dietary input, and (iii) identify inter-individual metabolic differences, i.e., metabotypes. To our knowledge, this is the first time DMD has been applied to analyze time-resolved metabolomics data. Results We demonstrate the potential of pDMDc in a crossover study setting. We could predict the metabolite response to unseen dietary exposures on both measured (R2 = 0.40) and simulated data of increasing size (R max 2 = 0.65), as well as recover clusters of dynamic metabolite responses. We conclude that this method has potential for applications in personalized nutrition and could be useful in guiding metabolite response to target levels. Availability and implementation The measured data analyzed in this study can be provided upon reasonable request. The simulated data along with a MATLAB implementation of pDMDc is available at https://github.com/FraunhoferChalmersCentre/pDMDc.
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Affiliation(s)
- Viktor Skantze
- Fraunhofer-Chalmers Research Centre for Industrial Mathematics, Gothenburg, Sweden
- Department of Life Sciences, Division of Food and Nutrition Science, Chalmers University of Technology, Gothenburg, Sweden
| | - Mats Jirstrand
- Fraunhofer-Chalmers Research Centre for Industrial Mathematics, Gothenburg, Sweden
| | - Carl Brunius
- Department of Life Sciences, Division of Food and Nutrition Science, Chalmers University of Technology, Gothenburg, Sweden
| | - Ann-Sofie Sandberg
- Department of Life Sciences, Division of Food and Nutrition Science, Chalmers University of Technology, Gothenburg, Sweden
| | - Rikard Landberg
- Department of Life Sciences, Division of Food and Nutrition Science, Chalmers University of Technology, Gothenburg, Sweden
| | - Mikael Wallman
- Fraunhofer-Chalmers Research Centre for Industrial Mathematics, Gothenburg, Sweden
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Antwi J. Precision Nutrition to Improve Risk Factors of Obesity and Type 2 Diabetes. Curr Nutr Rep 2023; 12:679-694. [PMID: 37610590 PMCID: PMC10766837 DOI: 10.1007/s13668-023-00491-y] [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] [Accepted: 08/07/2023] [Indexed: 08/24/2023]
Abstract
PURPOSE OF REVIEW Existing dietary and lifestyle interventions and recommendations, to improve the risk factors of obesity and type 2 diabetes with the target to mitigate this double global epidemic, have produced inconsistent results due to interpersonal variabilities in response to these conventional approaches, and inaccuracies in dietary assessment methods. Precision nutrition, an emerging strategy, tailors an individual's key characteristics such as diet, phenotype, genotype, metabolic biomarkers, and gut microbiome for personalized dietary recommendations to optimize dietary response and health. Precision nutrition is suggested to be an alternative and potentially more effective strategy to improve dietary intake and prevention of obesity and chronic diseases. The purpose of this narrative review is to synthesize the current research and examine the state of the science regarding the effect of precision nutrition in improving the risk factors of obesity and type 2 diabetes. RECENT FINDINGS The results of the research review indicate to a large extent significant evidence supporting the effectiveness of precision nutrition in improving the risk factors of obesity and type 2 diabetes. Deeper insights and further rigorous research into the diet-phenotype-genotype and interactions of other components of precision nutrition may enable this innovative approach to be adapted in health care and public health to the special needs of individuals. Precision nutrition provides the strategy to make individualized dietary recommendations by integrating genetic, phenotypic, nutritional, lifestyle, medical, social, and other pertinent characteristics about individuals, as a means to address the challenges of generalized dietary recommendations. The evidence presented in this review shows that precision nutrition markedly improves risk factors of obesity and type 2 diabetes, particularly behavior change.
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Affiliation(s)
- Janet Antwi
- Department of Agriculture, Nutrition and Human Ecology, Prairie View A&M University, Prairie View, USA.
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Zhu W, Iskandar MM, Baeghbali V, Kubow S. Three-Dimensional Printing of Foods: A Critical Review of the Present State in Healthcare Applications, and Potential Risks and Benefits. Foods 2023; 12:3287. [PMID: 37685220 PMCID: PMC10487194 DOI: 10.3390/foods12173287] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Revised: 08/24/2023] [Accepted: 08/25/2023] [Indexed: 09/10/2023] Open
Abstract
Three-dimensional printing is one of the most precise manufacturing technologies with a wide variety of applications. Three-dimensional food printing offers potential benefits for food production in terms of modifying texture, personalized nutrition, and adaptation to specific consumers' needs, among others. It could enable innovative and complex foods to be presented attractively, create uniquely textured foods tailored to patients with dysphagia, and support sustainability by reducing waste, utilizing by-products, and incorporating eco-friendly ingredients. Notable applications to date include, but are not limited to, printing novel shapes and complex geometries from candy, chocolate, or pasta, and bio-printed meats. The main challenges of 3D printing include nutritional quality and manufacturing issues. Currently, little research has explored the impact of 3D food printing on nutrient density, bioaccessibility/bioavailability, and the impact of matrix integrity loss on diet quality. The technology also faces challenges such as consumer acceptability, food safety and regulatory concerns. Possible adverse health effects due to overconsumption or the ultra-processed nature of 3D printed foods are major potential pitfalls. This review describes the state-of-the-art of 3D food printing technology from a nutritional perspective, highlighting potential applications and current limitations of this technology, and discusses the potential nutritional risks and benefits of 3D food printing.
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Affiliation(s)
- Wenxi Zhu
- School of Human Nutrition, McGill University, Montreal, QC H9X 3V9, Canada; (W.Z.); (M.M.I.)
| | - Michèle M. Iskandar
- School of Human Nutrition, McGill University, Montreal, QC H9X 3V9, Canada; (W.Z.); (M.M.I.)
| | - Vahid Baeghbali
- Food and Markets Department, Natural Resources Institute, University of Greenwich, Medway, Kent ME4 4TB, UK;
| | - Stan Kubow
- School of Human Nutrition, McGill University, Montreal, QC H9X 3V9, Canada; (W.Z.); (M.M.I.)
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de la Garza AL, Zonenszain-Laiter Y. Análisis bioético del uso de la biotecnología genómica en la nutrición traslacional. PERSONA Y BIOÉTICA 2023. [DOI: 10.5294/pebi.2022.26.2.4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/18/2023] Open
Abstract
Los avances de la biotecnología y las fascinantes perspectivas de la genómica nutricional en el escenario de la práctica clínica conducen a la consideración de distintos aspectos que impactan en el beneficio integral del ser humano. En ese sentido, la integración de la nutrición personalizada en la atención clínica requiere de un análisis bioético centrado en la unidad de la persona que, con base en su perfil nutrigenético único, contribuya al cuidado de la salud por medio del tratamiento nutricional individualizado. El análisis bioético contempla los principios de totalidad terapéutica, libertad e integridad. Además, el uso de las pruebas nutrigenéticas destaca no solo la confidencialidad de datos, que se presupone, sino que lleva a considerar el derecho a la intimidad.
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Optimized Metabotype Definition Based on a Limited Number of Standard Clinical Parameters in the Population-Based KORA Study. Life (Basel) 2022; 12:life12101460. [PMID: 36294895 PMCID: PMC9604647 DOI: 10.3390/life12101460] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Revised: 09/07/2022] [Accepted: 09/16/2022] [Indexed: 11/23/2022] Open
Abstract
The aim of metabotyping is to categorize individuals into metabolically similar groups. Earlier studies that explored metabotyping used numerous parameters, which made it less transferable to apply. Therefore, this study aimed to identify metabotypes based on a set of standard laboratory parameters that are regularly determined in clinical practice. K-means cluster analysis was used to group 3001 adults from the KORA F4 cohort into three clusters. We identified the clustering parameters through variable importance methods, without including any specific disease endpoint. Several unique combinations of selected parameters were used to create different metabotype models. Metabotype models were then described and evaluated, based on various metabolic parameters and on the incidence of cardiometabolic diseases. As a result, two optimal models were identified: a model composed of five parameters, which were fasting glucose, HDLc, non-HDLc, uric acid, and BMI (the metabolic disease model) for clustering; and a model that included four parameters, which were fasting glucose, HDLc, non-HDLc, and triglycerides (the cardiovascular disease model). These identified metabotypes are based on a few common parameters that are measured in everyday clinical practice. These metabotypes are cost-effective, and can be easily applied on a large scale in order to identify specific risk groups that can benefit most from measures to prevent cardiometabolic diseases, such as dietary recommendations and lifestyle interventions.
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Kan J, Ni J, Xue K, Wang F, Zheng J, Cheng J, Wu P, Runyon MK, Guo H, Du J. Personalized Nutrition Intervention Improves Health Status in Overweight/Obese Chinese Adults: A Randomized Controlled Trial. Front Nutr 2022; 9:919882. [PMID: 35811975 PMCID: PMC9258630 DOI: 10.3389/fnut.2022.919882] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Accepted: 05/20/2022] [Indexed: 12/21/2022] Open
Abstract
Background Overweight and obesity increase the risk of noncommunicable diseases (NCDs). Personalized nutrition (PN) approaches may provide tailored nutritional advice/service by focusing on individual's unique characteristics to prevent against NCDs. Objective We aimed to compare the effect of PN intervention with the traditional “one size fits all” intervention on health status in overweight/obese Chinese adults. Methods In this 12-week randomized controlled trial, 400 adults with BMI ≥24 kg/m2 were randomized to control group (CG, n = 200) and PN group (PNG, n = 200). The CG received conventional health guidance according to the Dietary Guidelines for Chinese Residents and Chinese DRIs Handbook, whereas the PNG experienced PN intervention that was developed by using decision trees based on the subjects' anthropometric measurements, blood samples (phenotype), buccal cells (genotype), and dietary and physical activity (PA) assessments (baseline and updated). Results Compared with the conventional intervention, PN intervention significantly improved clinical outcomes of anthropometric (e.g., body mass index (BMI), body fat percentage, waist circumference) and blood biomarkers (e.g., blood lipids, uric acid, homocysteine). The improvement in clinical outcomes was achieved through behavior change in diet and PA. The subjects in the PNG had higher China dietary guidelines index values and PA levels. Personalized recommendations of “lose weight,” “increase fiber” and “take multivitamin/mineral supplements” were the major contributors to the decrease of BMI and improvement of lipid profile. Conclusion We provided the first evidence that PN intervention was more beneficial than conventional nutrition intervention to improve health status in overweight/obese Chinese adults. This study provides a model of framework for developing personalized advice in Chinese population. Chictr.org.cn (ChiCTR1900026226).
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Affiliation(s)
- Juntao Kan
- Nutrilite Health Institute, Shanghai, China
| | - Jiayi Ni
- Research Institute of the McGill University Health Center, Montreal, QC, Canada
| | - Kun Xue
- School of Public Health, Fudan University, Shanghai, China
| | | | | | | | - Peiying Wu
- Department of Nutrition, Shanghai General Hospital, Shanghai, China
| | | | - Hongwei Guo
- School of Public Health, Fudan University, Shanghai, China
- Hongwei Guo
| | - Jun Du
- Nutrilite Health Institute, Shanghai, China
- *Correspondence: Jun Du
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Saha S, Lozano CP, Broyles S, Martin CK, Apolzan JW. Assessing initial validity of the PortionSize app to estimate dietary intake among adults: A pilot and feasibility study (Preprint). JMIR Form Res 2022; 6:e38283. [PMID: 35704355 PMCID: PMC9244674 DOI: 10.2196/38283] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Revised: 05/24/2022] [Accepted: 05/26/2022] [Indexed: 11/16/2022] Open
Abstract
Background Accurately assessing dietary intake can promote improved nutrition. The PortionSize app (Pennington Biomedical Research Center) was designed to quantify and provide real-time feedback on the intake of energy, food groups, saturated fat, and added sugar. Objective This study aimed to assess the preliminary feasibility and validity of estimating food intake via the PortionSize app among adults. Methods A total of 15 adults (aged 18-65 years) were recruited and trained to quantify the food intake from a simulated meal by using PortionSize. Trained personnel prepared 15 simulated meals and covertly weighed (weigh back) the amount of food provided to participants as well as food waste. Equivalence tests (±25% bounds) were performed to compare PortionSize to the weigh back method. Results Participants were aged a mean of 28 (SD 12) years, and 11 were female. The mean energy intake estimated with PortionSize was 742.9 (SD 328.2) kcal, and that estimated via weigh back was 659.3 (SD 190.7) kcal (energy intake difference: mean 83.5, SD 287.5 kcal). The methods were not equivalent in estimating energy intake (P=.18), and PortionSize overestimated energy intake by 83.5 kcal (12.7%) at the meal level. Estimates of portion sizes (gram weight; P=.01), total sugar (P=.049), fruit servings (P=.01), and dairy servings (P=.047) from PortionSize were equivalent to those estimated via weigh back. PortionSize was not equivalent to weigh back with regard to estimates for carbohydrate (P=.10), fat (P=.32), vegetable (P=.37), grain (P=.31), and protein servings (P=.87). Conclusions Due to power limitations, the equivalence tests had large equivalence bounds. Though preliminary, the results of this small pilot study warrant the further adaptation, development, and validation of PortionSize as a means to estimate energy intake and provide users with real-time and actionable dietary feedback.
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Affiliation(s)
- Sanjoy Saha
- Pennington Biomedical Research Center, Louisiana State University System, Baton Rouge, LA, United States
| | - Chloe Panizza Lozano
- Pennington Biomedical Research Center, Louisiana State University System, Baton Rouge, LA, United States
| | - Stephanie Broyles
- Pennington Biomedical Research Center, Louisiana State University System, Baton Rouge, LA, United States
| | - Corby K Martin
- Pennington Biomedical Research Center, Louisiana State University System, Baton Rouge, LA, United States
| | - John W Apolzan
- Pennington Biomedical Research Center, Louisiana State University System, Baton Rouge, LA, United States
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Szakály Z, Kovács B, Szakály M, T. Nagy-Pető D, Popovics P, Kiss M. Consumer acceptance of genetic-based personalized nutrition in Hungary. GENES & NUTRITION 2021; 16:3. [PMID: 33648454 PMCID: PMC7923598 DOI: 10.1186/s12263-021-00683-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Accepted: 02/06/2021] [Indexed: 01/28/2023]
Abstract
BACKGROUND Despite the increasing number of personalized nutrition services available on the market, nutrigenomics-based level of personalization is still the exception rather than a mainstream activity. This can be partly explained by various factors of consumer acceptance of the new technology. While consumer attitudes toward genetic tests aiming to reveal the risks of a predisposition to various illnesses have already been examined by several research studies worldwide; consumer acceptance of nutrigenomics-based personalized nutrition has only been examined by a significantly lower number of papers, especially in the Central and Eastern European region. OBJECTIVE The purpose of this paper is to examine consumer acceptance of genetic-based personalized nutrition in Hungary. Therefore a national representative survey was conducted involving 1000 individuals. The starting point of the model used is the assumption that the consumer acceptance of personalized nutrition is influenced by its consumer perceptions, which are affected by psychological processes that, in a more general sense, determine acceptance of food innovations. RESULTS The results show that 23.5% of respondents accept genetic test-based personalized nutrition. Women were found to reject the new technology in a significantly smaller proportion than men. The relationship between other demographic variables (i.e. age groups, education and subjective income level) and the perception of genetic-based personalized nutrition is also significant. Our results indicate that it is perceived cost/benefit that is most strongly related to genetically based personalized dietary preferences, followed by perceived risk and subjective norms. Perceived uncertainty and perceived behavioural control, however, have only a weak relationship with genetic-based personalized dietary preferences. CONCLUSIONS Compared with the magnitude of the effect of socio-demographic criteria, it can be concluded that, on the whole, psychological processes in the individual have a greater influence on the development of preferences for genetic-based personalized nutrition than any socio-demographic factor. This also confirms the trend that there are more and more value-added products or value propositions (where a significant part of the value added is to be found in product innovation), for which psychological characteristics are/should be given more emphasis among the segmentation criteria.
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Affiliation(s)
- Zoltán Szakály
- Institute of Marketing and Commerce, Faculty of Economics and Business, University of Debrecen, Debrecen, 4032 Hungary
| | - Bence Kovács
- Institute of Marketing and Commerce, Faculty of Economics and Business, University of Debrecen, Debrecen, 4032 Hungary
| | - Márk Szakály
- Institute of Marketing and Commerce, Faculty of Economics and Business, University of Debrecen, Debrecen, 4032 Hungary
| | - Dorka T. Nagy-Pető
- Institute of Marketing and Commerce, Faculty of Economics and Business, University of Debrecen, Debrecen, 4032 Hungary
| | - Péter Popovics
- Institute of Applied Economics Sciences, Faculty of Economics and Business, University of Debrecen, Debrecen, 4032 Hungary
| | - Marietta Kiss
- Institute of Marketing and Commerce, Faculty of Economics and Business, University of Debrecen, Debrecen, 4032 Hungary
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Baumgartner S, Bruckert E, Gallo A, Plat J. The position of functional foods and supplements with a serum LDL-C lowering effect in the spectrum ranging from universal to care-related CVD risk management. Atherosclerosis 2020; 311:116-123. [PMID: 32861515 DOI: 10.1016/j.atherosclerosis.2020.07.019] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/29/2020] [Revised: 07/02/2020] [Accepted: 07/17/2020] [Indexed: 12/19/2022]
Abstract
A wealth of data demonstrates a causal link between serum low-density lipoprotein cholesterol (LDL-C) concentrations and cardiovascular disease (CVD). Any decrease in serum LDL-C concentrations is associated with a decreased CVD risk, and this benefit is similar to a comparable LDL-C reduction after drug treatment and dietary intervention. Moreover, life-long reductions in serum LDL-C levels have a large impact on CVD risk and a long-term dietary enrichment with functional foods or supplements with a proven LDL lowering efficacy is therefore a feasible and efficient approach to decrease future CVD risk. Functional foods with an LDL-C lowering effect can improve health and/or a reduce the risk of disease. However, it has not been mentioned specifically whether this concerns mainly universal prevention or whether this can also be applied to the hierarchy towards care related prevention. Therefore, we here describe the effects of a list of interesting functional food ingredients with proven benefit in LDL-C lowering. In addition, we pay particular attention to the emerging evidence that the addition of these functional ingredients and supplements is advisable as universal and selective prevention in the general population. Moreover, functional ingredients and supplements are also helpful in care related prevention, i.e. in patients with elevated LDL-C concentrations who are statin-intolerant or are not able to achieve their LDL-C target levels. Furthermore, we will highlight practical aspects regarding the use of functional foods with an LDL-C lowering effect, such as the increasing importance of shared decision making of medical doctors and dieticians with patients to ensure proper empowerment and better adherence to dietary approaches. In addition, we will address costs issues related to the use of these functional foods, which might be a barrier in some populations.
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Affiliation(s)
- Sabine Baumgartner
- Department of Nutrition and Movement Sciences, NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University Medical Center, 6200 MD, Maastricht, the Netherlands.
| | - Eric Bruckert
- Endocrinology Metabolism and Cardiovascular Prevention, E3M Institute and Cardiometabolic IHU (ICAN), Sorbonne University, Pitié Salpêtrière Hospital, Paris, France
| | - Antonio Gallo
- Endocrinology Metabolism and Cardiovascular Prevention, E3M Institute and Cardiometabolic IHU (ICAN), Sorbonne University, Pitié Salpêtrière Hospital, Paris, France
| | - Jogchum Plat
- Department of Nutrition and Movement Sciences, NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University Medical Center, 6200 MD, Maastricht, the Netherlands
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13
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Wawro N, Pestoni G, Riedl A, Breuninger TA, Peters A, Rathmann W, Koenig W, Huth C, Meisinger C, Rohrmann S, Linseisen J. Association of Dietary Patterns and Type-2 Diabetes Mellitus in Metabolically Homogeneous Subgroups in the KORA FF4 Study. Nutrients 2020; 12:nu12061684. [PMID: 32516903 PMCID: PMC7352280 DOI: 10.3390/nu12061684] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2020] [Revised: 06/02/2020] [Accepted: 06/03/2020] [Indexed: 12/16/2022] Open
Abstract
There is evidence that a change in lifestyle, especially physical activity and diet, can reduce the risk of developing type-2 diabetes mellitus (T2DM). However, the response to dietary changes varies among individuals due to differences in metabolic characteristics. Therefore, we investigated the association between dietary patterns and T2DM while taking into account these differences. For 1287 participants of the population-based KORA FF4 study (Cooperative Health Research in the Region of Augsburg), we identified three metabolically-homogenous subgroups (metabotypes) using 16 clinical markers. Based on usual dietary intake data, two diet quality scores, the Mediterranean Diet Score (MDS) and the Alternate Healthy Eating Index (AHEI), were calculated. We explored the associations between T2DM and diet quality scores. Multi-variable adjusted models, including metabotype subgroup, were fitted. In addition, analyses stratified by metabotype were carried out. We found significant interaction effects between metabotype and both diet quality scores (p < 0.05). In the analysis stratified by metabotype, significant negative associations between T2DM and both diet quality scores were detected only in the metabolically-unfavorable homogenous subgroup (Odds Ratio (OR) = 0.62, 95% confidence interval (CI) = 0.39-0.90 for AHEI and OR = 0.60, 95% CI = 0.40-0.96 for MDS). Prospective studies taking metabotype into account are needed to confirm our results, which allow for the tailoring of dietary recommendations in the prevention of T2DM.
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Affiliation(s)
- Nina Wawro
- Independent Research Group Clinical Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Ingolstädter Landstr. 1, 85764 Neuherberg, Germany; (G.P.); (A.R.); (T.A.B.); (C.M.); (J.L.)
- Chair of Epidemiology, Ludwig-Maximilians-Universität München at UNIKA-T (Universitäres Zentrum für Gesundheitswissenschaften am Klinikum Augsburg), Neusässer Str. 47, 86156 Augsburg, Germany
- Correspondence:
| | - Giulia Pestoni
- Independent Research Group Clinical Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Ingolstädter Landstr. 1, 85764 Neuherberg, Germany; (G.P.); (A.R.); (T.A.B.); (C.M.); (J.L.)
- Division of Chronic Disease Epidemiology, Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Hirschengraben 84, CH-8001 Zurich, Switzerland;
| | - Anna Riedl
- Independent Research Group Clinical Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Ingolstädter Landstr. 1, 85764 Neuherberg, Germany; (G.P.); (A.R.); (T.A.B.); (C.M.); (J.L.)
| | - Taylor A. Breuninger
- Independent Research Group Clinical Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Ingolstädter Landstr. 1, 85764 Neuherberg, Germany; (G.P.); (A.R.); (T.A.B.); (C.M.); (J.L.)
- Chair of Epidemiology, Ludwig-Maximilians-Universität München at UNIKA-T (Universitäres Zentrum für Gesundheitswissenschaften am Klinikum Augsburg), Neusässer Str. 47, 86156 Augsburg, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Ingolstädter Landstr. 1, 85764 Neuherberg, Germany; (A.P.); (C.H.)
- German Center for Diabetes Research (DZD e.V.), Ingolstädter Landstr. 1, 85764 München-Neuherberg, Germany;
| | - Wolfgang Rathmann
- German Center for Diabetes Research (DZD e.V.), Ingolstädter Landstr. 1, 85764 München-Neuherberg, Germany;
- Institute for Biometrics and Epidemiology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Auf’m Hennekamp 65, 40225 Düsseldorf, Germany
| | - Wolfgang Koenig
- DZHK (German Centre for Cardiovascular Research), Partner Site Munich Heart Alliance, Pettenkoferstr. 8a & 9, 80336 Munich, Germany;
- Deutsches Herzzentrum München, Technische Universität München, Lazarettstr. 36, 80636 Munich
- Institute of Epidemiology and Medical Biometry, University of Ulm, Helmholtzstr. 22, 89081 Ulm, Germany
| | - Cornelia Huth
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Ingolstädter Landstr. 1, 85764 Neuherberg, Germany; (A.P.); (C.H.)
- German Center for Diabetes Research (DZD e.V.), Ingolstädter Landstr. 1, 85764 München-Neuherberg, Germany;
| | - Christa Meisinger
- Independent Research Group Clinical Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Ingolstädter Landstr. 1, 85764 Neuherberg, Germany; (G.P.); (A.R.); (T.A.B.); (C.M.); (J.L.)
- Chair of Epidemiology, Ludwig-Maximilians-Universität München at UNIKA-T (Universitäres Zentrum für Gesundheitswissenschaften am Klinikum Augsburg), Neusässer Str. 47, 86156 Augsburg, Germany
| | - Sabine Rohrmann
- Division of Chronic Disease Epidemiology, Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Hirschengraben 84, CH-8001 Zurich, Switzerland;
| | - Jakob Linseisen
- Independent Research Group Clinical Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Ingolstädter Landstr. 1, 85764 Neuherberg, Germany; (G.P.); (A.R.); (T.A.B.); (C.M.); (J.L.)
- Chair of Epidemiology, Ludwig-Maximilians-Universität München at UNIKA-T (Universitäres Zentrum für Gesundheitswissenschaften am Klinikum Augsburg), Neusässer Str. 47, 86156 Augsburg, Germany
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14
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Baiano A. 3D Printed Foods: A Comprehensive Review on Technologies, Nutritional Value, Safety, Consumer Attitude, Regulatory Framework, and Economic and Sustainability Issues. FOOD REVIEWS INTERNATIONAL 2020. [DOI: 10.1080/87559129.2020.1762091] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Affiliation(s)
- Antonietta Baiano
- Dipartimento Di Scienze Agrarie, Degli Alimenti E dell’Ambiente, University of Foggia, Foggia, Italy
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15
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Palmnäs M, Brunius C, Shi L, Rostgaard-Hansen A, Torres NE, González-Domínguez R, Zamora-Ros R, Ye YL, Halkjær J, Tjønneland A, Riccardi G, Giacco R, Costabile G, Vetrani C, Nielsen J, Andres-Lacueva C, Landberg R. Perspective: Metabotyping-A Potential Personalized Nutrition Strategy for Precision Prevention of Cardiometabolic Disease. Adv Nutr 2020; 11:524-532. [PMID: 31782487 PMCID: PMC7231594 DOI: 10.1093/advances/nmz121] [Citation(s) in RCA: 43] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2019] [Revised: 09/26/2019] [Accepted: 10/14/2019] [Indexed: 12/22/2022] Open
Abstract
Diet is an important, modifiable lifestyle factor of cardiometabolic disease risk, and an improved diet can delay or even prevent the onset of disease. Recent evidence suggests that individuals could benefit from diets adapted to their genotype and phenotype: that is, personalized nutrition. A novel strategy is to tailor diets for groups of individuals according to their metabolic phenotypes (metabotypes). Randomized controlled trials evaluating metabotype-specific responses and nonresponses are urgently needed to bridge the current gap of knowledge with regard to the efficacy of personalized strategies in nutrition. In this Perspective, we discuss the concept of metabotyping, review the current literature on metabotyping in the context of cardiometabolic disease prevention, and suggest potential strategies for metabotype-based nutritional advice for future work. We also discuss potential determinants of metabotypes, including gut microbiota, and highlight the use of metabolomics to define effective markers for cardiometabolic disease-related metabotypes. Moreover, we hypothesize that people at high risk for cardiometabolic diseases have distinct metabotypes and that individuals grouped into specific metabotypes may respond differently to the same diet, which is being tested in a project of the Joint Programming Initiative: A Healthy Diet for a Healthy Life.
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Affiliation(s)
- Marie Palmnäs
- Department of Biology and Biological Engineering, Division of Food and Nutrition Science, Chalmers University of Technology, Gothenburg, Sweden
| | - Carl Brunius
- Department of Biology and Biological Engineering, Division of Food and Nutrition Science, Chalmers University of Technology, Gothenburg, Sweden
| | - Lin Shi
- Department of Biology and Biological Engineering, Division of Food and Nutrition Science, Chalmers University of Technology, Gothenburg, Sweden
- School of Food Engineering and Nutritional Science, Shaanxi Normal University, Xi'an, China
| | - Agneta Rostgaard-Hansen
- Department of Biology and Biological Engineering, Division of Food and Nutrition Science, Chalmers University of Technology, Gothenburg, Sweden
- Diet, Genes, and Environment, Danish Cancer Society Research Center, Copenhagen, Denmark
| | - Núria Estanyol Torres
- Biomarkers and Nutrimetabolomics Laboratory, Department of Nutrition, Food Sciences, and Gastronomy, Institute for Research on Nutrition and Food Safety, Faculty of Pharmacy and Food Sciences, University of Barcelona, Barcelona, Spain
- Centro de Investigacion Biomedica en Red (CIBER) of Frailty and Healthy Aging (CIBERFES), Instituto de Salud Carlos III, Barcelona, Spain
| | - Raúl González-Domínguez
- Biomarkers and Nutrimetabolomics Laboratory, Department of Nutrition, Food Sciences, and Gastronomy, Institute for Research on Nutrition and Food Safety, Faculty of Pharmacy and Food Sciences, University of Barcelona, Barcelona, Spain
- Centro de Investigacion Biomedica en Red (CIBER) of Frailty and Healthy Aging (CIBERFES), Instituto de Salud Carlos III, Barcelona, Spain
| | - Raul Zamora-Ros
- Biomarkers and Nutrimetabolomics Laboratory, Department of Nutrition, Food Sciences, and Gastronomy, Institute for Research on Nutrition and Food Safety, Faculty of Pharmacy and Food Sciences, University of Barcelona, Barcelona, Spain
- Unit of Nutrition and Cancer, Cancer Epidemiology Research Prgramme, Catalan Institute of Oncology (ICO), Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de LLobregat, Barcelona, Spain
| | - Ye Lingqun Ye
- Department of Biology and Biological Engineering, Division of Systems and Synthetic Biology, Chalmers University of Technology, Gothenburg, Sweden
| | - Jytte Halkjær
- Diet, Genes, and Environment, Danish Cancer Society Research Center, Copenhagen, Denmark
| | - Anne Tjønneland
- Diet, Genes, and Environment, Danish Cancer Society Research Center, Copenhagen, Denmark
| | - Gabriele Riccardi
- Department of Clinical Medicine and Surgery, University of Naples Federico II, Naples, Italy
| | - Rosalba Giacco
- Institute of Food Science, Italian National Research Council, Avellino, Italy
| | - Giuseppina Costabile
- Department of Clinical Medicine and Surgery, University of Naples Federico II, Naples, Italy
| | - Claudia Vetrani
- Department of Clinical Medicine and Surgery, University of Naples Federico II, Naples, Italy
| | - Jens Nielsen
- Department of Biology and Biological Engineering, Division of Systems and Synthetic Biology, Chalmers University of Technology, Gothenburg, Sweden
| | - Cristina Andres-Lacueva
- Biomarkers and Nutrimetabolomics Laboratory, Department of Nutrition, Food Sciences, and Gastronomy, Institute for Research on Nutrition and Food Safety, Faculty of Pharmacy and Food Sciences, University of Barcelona, Barcelona, Spain
- Centro de Investigacion Biomedica en Red (CIBER) of Frailty and Healthy Aging (CIBERFES), Instituto de Salud Carlos III, Barcelona, Spain
| | - Rikard Landberg
- Department of Biology and Biological Engineering, Division of Food and Nutrition Science, Chalmers University of Technology, Gothenburg, Sweden
- Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
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16
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Riedl A, Hillesheim E, Wawro N, Meisinger C, Peters A, Roden M, Kronenberg F, Herder C, Rathmann W, Völzke H, Reincke M, Koenig W, Wallaschofski H, Daniel H, Hauner H, Brennan L, Linseisen J. Evaluation of the Metabotype Concept Identified in an Irish Population in the German KORA Cohort Study. Mol Nutr Food Res 2020; 64:e1900918. [PMID: 32048458 DOI: 10.1002/mnfr.201900918] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2019] [Revised: 01/13/2020] [Indexed: 11/11/2022]
Abstract
SCOPE Previous work identified three metabolically homogeneous subgroups of individuals ("metabotypes") using k-means cluster analysis based on fasting serum levels of triacylglycerol, total cholesterol, HDL cholesterol, and glucose. The aim is to reproduce these findings and describe metabotype groups by dietary habits and by incident disease occurrence. METHODS AND RESULTS 1744 participants from the KORA F4 study and 2221 participants from the KORA FF4 study are assigned to the three metabotype clusters previously identified by minimizing the Euclidean distances. In both KORA studies, the assignment of participants results in three metabolically distinct clusters, with cluster 3 representing the group of participants with the most unfavorable metabolic characteristics. Individuals of cluster 3 are further characterized by the highest incident disease occurrence during follow-up; they also reveal the most unfavorable diet with significantly lowest intakes of vegetables, dairy products, and fibers, and highest intakes of total, red, and processed meat. CONCLUSION The three metabotypes originally identified in an Irish population are successfully reproduced. In addition to this validation approach, the observed differences in disease incidence across metabotypes represent an important new finding that strongly supports the metabotyping approach as a tool for risk stratification.
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Affiliation(s)
- Anna Riedl
- Independent Research Group Clinical Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Ingolstädter Landstr. 1, 85764, Neuherberg, Germany.,Chair of Epidemiology, Ludwig-Maximilians-Universität München, at UNIKA-T, Neusässer Str. 47, 86156, Augsburg, Germany
| | - Elaine Hillesheim
- Institute of Food and Health, UCD School of Agriculture and Food Science, UCD, Stillorgan Rd, Belfield, Dublin, 4, Ireland
| | - Nina Wawro
- Independent Research Group Clinical Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Ingolstädter Landstr. 1, 85764, Neuherberg, Germany.,Chair of Epidemiology, Ludwig-Maximilians-Universität München, at UNIKA-T, Neusässer Str. 47, 86156, Augsburg, Germany
| | - Christa Meisinger
- Independent Research Group Clinical Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Ingolstädter Landstr. 1, 85764, Neuherberg, Germany.,Chair of Epidemiology, Ludwig-Maximilians-Universität München, at UNIKA-T, Neusässer Str. 47, 86156, Augsburg, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Ingolstädter Landstr. 1, 85764, Neuherberg, Germany.,German Center for Diabetes Research (DZD e.V.), Ingolstädter Landstr. 1, 85764, Neuherberg, Germany
| | - Michael Roden
- German Center for Diabetes Research (DZD e.V.), Ingolstädter Landstr. 1, 85764, Neuherberg, Germany.,Division of Endocrinology and Diabetology, Medical Faculty, Heinrich Heine University Düsseldorf, Auf'm Hennekamp 65, 40225, Düsseldorf, Germany.,Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Auf'm Hennekamp 65, 40225, Düsseldorf, Germany
| | - Florian Kronenberg
- Institute of Genetic Epidemiology, Department of Genetics and Pharmacology, Medical University of Innsbruck, Schöpfstr. 41, 6020, Innsbruck, Austria
| | - Christian Herder
- German Center for Diabetes Research (DZD e.V.), Ingolstädter Landstr. 1, 85764, Neuherberg, Germany.,Division of Endocrinology and Diabetology, Medical Faculty, Heinrich Heine University Düsseldorf, Auf'm Hennekamp 65, 40225, Düsseldorf, Germany.,Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Auf'm Hennekamp 65, 40225, Düsseldorf, Germany
| | - Wolfgang Rathmann
- German Center for Diabetes Research (DZD e.V.), Ingolstädter Landstr. 1, 85764, Neuherberg, Germany.,Institute for Biometrics and Epidemiology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Auf'm Hennekamp 65, 40225, Düsseldorf, Germany
| | - Henry Völzke
- German Center for Diabetes Research (DZD e.V.), Ingolstädter Landstr. 1, 85764, Neuherberg, Germany.,DZHK (German Centre for Cardiovascular Research), Partner Site Munich Heart Alliance, Pettenkoferstr. 8a & 9, 80336, Munich, Germany.,Institute for Community Medicine, University Medicine Greifswald, Walther-Rathenau-Str. 48, 17475, Greifswald, Germany
| | - Martin Reincke
- Medizinische Klinik und Poliklinik IV, Klinikum der Universität München, Ludwig-Maximilians-Universität München, Ziemssenstr. 1, 80336, Munich, Germany
| | - Wolfgang Koenig
- DZHK (German Centre for Cardiovascular Research), Partner Site Munich Heart Alliance, Pettenkoferstr. 8a & 9, 80336, Munich, Germany.,Deutsches Herzzentrum München, Technische Universität München, Lazarettstr. 36, 80636, Munich, Germany.,Institute of Epidemiology and Medical Biometry, University of Ulm, Helmholtzstr. 22, 89081, Ulm, Germany
| | - Henri Wallaschofski
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Ferdinand-Sauerbruch-Str., 17489, Greifswald, Germany
| | - Hannelore Daniel
- Chair of Nutritional Physiology, Technical University of Munich, Gregor-Mendel-Str. 2, 85354, Freising-Weihenstephan, Germany
| | - Hans Hauner
- Else Kröner-Fresenius Centre for Nutritional Medicine, Technical University of Munich, Gregor-Mendel-Str. 2, 85354, Freising-Weihenstephan, Germany.,ZIEL - Institute for Food and Health, Technical University of Munich, Weihenstephaner Berg 1, 85354, Freising, Germany.,Institute of Nutritional Medicine, Klinikum rechts der Isar, Technical University of Munich, Georg-Brauchle-Ring 62, 80992, Munich, Germany
| | - Lorraine Brennan
- Institute of Food and Health, UCD School of Agriculture and Food Science, UCD, Stillorgan Rd, Belfield, Dublin, 4, Ireland
| | - Jakob Linseisen
- Independent Research Group Clinical Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Ingolstädter Landstr. 1, 85764, Neuherberg, Germany.,Chair of Epidemiology, Ludwig-Maximilians-Universität München, at UNIKA-T, Neusässer Str. 47, 86156, Augsburg, Germany.,ZIEL - Institute for Food and Health, Technical University of Munich, Weihenstephaner Berg 1, 85354, Freising, Germany
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17
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de Roos B, Aura AM, Bronze M, Cassidy A, Conesa MTG, Gibney ER, Greyling A, Kaput J, Kerem Z, Knežević N, Kroon P, Landberg R, Manach C, Milenkovic D, Rodriguez-Mateos A, Tomás-Barberán FA, van de Wiele T, Morand C. Targeting the delivery of dietary plant bioactives to those who would benefit most: from science to practical applications. Eur J Nutr 2019; 58:65-73. [PMID: 31637468 PMCID: PMC6851046 DOI: 10.1007/s00394-019-02075-5] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2019] [Accepted: 08/02/2019] [Indexed: 03/19/2023]
Abstract
Background A healthy diet and optimal lifestyle choices are amongst the most important actions for the prevention of cardiometabolic diseases. Despite this, it appears difficult to convince consumers to select more nutritious foods. Furthermore, the development and production of healthier foods do not always lead to economic profits for the agro-food sector. Most dietary recommendations for the general population represent a “one-size-fits-all approach” which does not necessarily ensure that everyone has adequate exposure to health-promoting constituents of foods. Indeed, we now know that individuals show a high variability in responses when exposed to specific nutrients, foods, or diets. Purpose This review aims to highlight our current understanding of inter-individual variability in response to dietary bioactives, based on the integration of findings of the COST Action POSITIVe. We also evaluate opportunities for translation of scientific knowledge on inter-individual variability in response to dietary bioactives, once it becomes available, into practical applications for stakeholders, such as the agro-food industry. The potential impact from such applications will form an important impetus for the food industry to develop and market new high quality and healthy foods for specific groups of consumers in the future. This may contribute to a decrease in the burden of diet-related chronic diseases. Individual differences in ADME (Absorption, Digestion, Metabolism and Excretion) is believed to underpin much of the inter-individual variation in responses. Recent developments in the area of food metabolome databases and fast improvements in innovative metabotyping technologies hold great promise for improved profiling of dietary intake, exposure to individual ingredients, foods and dietary patterns, as well as our ability to identify individual responsiveness. The food industry needs well-defined population clusters or targets in order to be able to design “personalized products”. There are indeed excellent industrial opportunities for foods that modulate gut microbiota, and thereby enable the delivery of food bioactive metabolites. It is currently not clear whether knowledge on individual nutrient needs, based on genetic or metagenomic data, would affect long-term dietary and health behaviours. Data to support the development of dietary recommendations may need to be generated by new n-of-1-based study designs in the future.
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Affiliation(s)
- Baukje de Roos
- The Rowett Institute, University of Aberdeen, Foresterhill, Aberdeen, AB25 2ZD, UK.
| | - Anna-Marja Aura
- VTT Technical Research Centre of Finland, PO Box 1000, Tietotie 2, Espoo, Finland
| | - Maria Bronze
- Instituto de Biologia Experimental e Tecnológica, Apartado 12, Oeiras, Portugal
| | - Aedin Cassidy
- Department of Nutrition and Preventive Medicine, Norwich Medical School, University of East Anglia, Norwich, UK
| | - María-Teresa Garcia Conesa
- Food and Health Laboratory. Research Group on Quality, Safety, and Bioactivity of Plant Foods, CEBAS-CSIC, Campus de Espinardo, Murcia, Spain
| | - Eileen R Gibney
- UCD Institute of Food and Health, School of Agriculture and Food Science, University College Dublin, Dublin, Ireland
| | - Arno Greyling
- Unilever Research and Development Vlaardingen, Vlaardingen, The Netherlands
| | | | - Zohar Kerem
- R.H. Smith Faculty of Agriculture, Food and Environment, The Hebrew University of Jerusalem, Jerusalem, Israel
| | | | - Paul Kroon
- Quadram Institute Bioscience, Norwich Research Park, Norwich, UK
| | - Rikard Landberg
- Division of Food and Nutrition Science, Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden
| | - Claudine Manach
- INRA, UNH, Unité de Nutrition Humaine, CRNH Auvergne, Université Clermont Auvergne, Clermont-Ferrand, France
| | - Dragan Milenkovic
- INRA, UNH, Unité de Nutrition Humaine, CRNH Auvergne, Université Clermont Auvergne, Clermont-Ferrand, France
| | - Ana Rodriguez-Mateos
- Department of Nutritional Sciences, Faculty of Life Sciences and Medicine, School of Life Course Sciences, King's College London, London, UK
| | - Francisco A Tomás-Barberán
- Food and Health Laboratory. Research Group on Quality, Safety, and Bioactivity of Plant Foods, CEBAS-CSIC, Campus de Espinardo, Murcia, Spain
| | - Tom van de Wiele
- Faculty of Bioscience Engineering, Center for Microbial Ecology and Technology, Ghent University, Ghent, Belgium
| | - Christine Morand
- INRA, UNH, Unité de Nutrition Humaine, CRNH Auvergne, Université Clermont Auvergne, Clermont-Ferrand, France
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18
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Limon-Miro AT, Lopez-Teros V, Astiazaran-Garcia H. Dynamic Macronutrient Meal-Equivalent Menu Method: Towards Individual Nutrition Intervention Programs. Methods Protoc 2019; 2:E78. [PMID: 31491882 PMCID: PMC6789454 DOI: 10.3390/mps2030078] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2019] [Revised: 08/24/2019] [Accepted: 09/03/2019] [Indexed: 11/23/2022] Open
Abstract
Nutrition interventions should reflect the state of the art in science and dietetics to meet each patient's requirements. Incorporating new knowledge into individualized food-based nutrition interventions is a major challenge, and health care professionals constantly search for novel approaches through specific and standardized methods. The dynamic macronutrient meal-equivalent menu method involves individuals making informed food choices that match their requirements, schedule, and food availability and affinity, helping them maintain a sense of control and motivation to adhere to a nutrition intervention program. This protocol includes the steps required to prepare a nutrition plan containing equivalent meal options consistent with the patient's needs and preferences. Standard food servings are planned according to population specific dietary guidelines and individual characteristics. Servings are distributed at required mealtimes, and are all equivalent in energy and macronutrient content, providing every patient with interchangeable choices within each mealtime. This empowers individuals to select foods in a guided format whilst adhering to a dietary plan. Acceptable variations for calculated energy and macronutrient content are as follows: protein ±1 g/day, fat ±1 g/day, carbohydrate ±2 g/day, and energy ±15 kcal/day. Following this method, health care professionals can develop individualized nutrition intervention programs that may improve patients' adherence, nutritional status, and health.
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Affiliation(s)
- Ana Teresa Limon-Miro
- Department of Nutrition, Centro de Investigacion en Alimentacion y Desarrollo A.C. (CIAD), Carretera Gustavo Enrique Astiazaran Rosas 46, Hermosillo 83304, Sonora, Mexico
| | - Veronica Lopez-Teros
- Department of Chemical and Biological Sciences, Universidad de Sonora, Hermosillo 83000, Sonora, Mexico
| | - Humberto Astiazaran-Garcia
- Department of Nutrition, Centro de Investigacion en Alimentacion y Desarrollo A.C. (CIAD), Carretera Gustavo Enrique Astiazaran Rosas 46, Hermosillo 83304, Sonora, Mexico.
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Modifying effect of metabotype on diet-diabetes associations. Eur J Nutr 2019; 59:1357-1369. [PMID: 31089867 PMCID: PMC7230059 DOI: 10.1007/s00394-019-01988-5] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2018] [Accepted: 05/05/2019] [Indexed: 12/18/2022]
Abstract
Purpose Inter-individual metabolic differences may be a reason for previously inconsistent results in diet–diabetes associations. We aimed to investigate associations between dietary intake and diabetes for metabolically homogeneous subgroups (‘metabotypes’) in a large cross-sectional study. Methods We used data of 1517 adults aged 38–87 years from the German population-based KORA FF4 study (2013/2014). Dietary intake was estimated based on the combination of a food frequency questionnaire and multiple 24-h food lists. Glucose tolerance status was classified based on an oral glucose tolerance test in participants without a previous diabetes diagnosis using American Diabetes Association criteria. Logistic regression was applied to examine the associations between dietary intake and diabetes for two distinct metabotypes, which were identified based on 16 biochemical and anthropometric parameters. Results A low intake of fruits and a high intake of total meat, processed meat and sugar-sweetened beverages (SSB) were significantly associated with diabetes in the total study population. Stratified by metabotype, associations with diabetes remained significant for intake of total meat (OR 1.67, 95% CI 1.04–2.67) and processed meat (OR 2.23, 95% CI 1.24–4.04) in the metabotypes with rather favorable metabolic characteristics, and for intake of fruits (OR 0.83, 95% CI 0.68–0.99) and SSB (OR:1.21, 95% CI 1.09–1.35) in the more unfavorable metabotype. However, only the association between SSB intake and diabetes differed significantly by metabotype (p value for interaction = 0.01). Conclusions Our findings suggest an influence of metabolic characteristics on diet–diabetes associations, which may help to explain inconsistent previous results. The causality of the observed associations needs to be confirmed in prospective and intervention studies. Electronic supplementary material The online version of this article (10.1007/s00394-019-01988-5) contains supplementary material, which is available to authorized users.
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Primers on nutrigenetics and nutri(epi)genomics: Origins and development of precision nutrition. Biochimie 2019; 160:156-171. [PMID: 30878492 DOI: 10.1016/j.biochi.2019.03.006] [Citation(s) in RCA: 48] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2018] [Accepted: 03/08/2019] [Indexed: 12/11/2022]
Abstract
Understanding the relationship between genotype and phenotype is a central goal not just for genetics but also for medicine and biological sciences. Despite outstanding technological progresses, genetics alone is not able to completely explain phenotypes, in particular for complex diseases. Given the existence of a "missing heritability", growing attention has been given to non-mendelian mechanisms of inheritance and to the role of the environment. The study of interaction between gene and environment represents a challenging but also a promising field with high potential for health prevention, and epigenetics has been suggested as one of the best candidate to mediate environmental effects on the genome. Among environmental factors able to interact with both genome and epigenome, nutrition is one of the most impacting. Not just our genome influences the responsiveness to food and nutrients, but vice versa, nutrition can also modify gene expression through epigenetic mechanisms. In this complex picture, nutrigenetics and nutrigenomics represent appealing disciplines aimed to define new prospectives of personalized nutrition. This review introduces to the study of gene-environment interactions and describes how nutrigenetics and nutrigenomics modulate health, promoting or affecting healthiness through life-style, thus playing a pivotal role in modulating the effect of genetic predispositions.
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O'Connor S, Rudkowska I. Dietary Fatty Acids and the Metabolic Syndrome: A Personalized Nutrition Approach. ADVANCES IN FOOD AND NUTRITION RESEARCH 2019; 87:43-146. [PMID: 30678820 DOI: 10.1016/bs.afnr.2018.07.004] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/10/2023]
Abstract
Dietary fatty acids are present in a wide variety of foods and appear in different forms and lengths. The different fatty acids are known to have various effects on metabolic health. The metabolic syndrome (MetS) is a constellation of risk factors of chronic diseases. The etiology of the MetS is represented by a complex interplay of genetic and environmental factors. Dietary fatty acids can be important contributors of the evolution or in prevention of the MetS; however, great interindividual variability exists in the response to fatty acids. The identification of genetic variants interacting with fatty acids might explain this heterogeneity in metabolic responses. This chapter reviews the mechanisms underlying the interactions between the different components of the MetS, dietary fatty acids and genes. Challenges surrounding the implementation of personalized nutrition are also covered.
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Affiliation(s)
- Sarah O'Connor
- CHU de Québec Research Center, Université Laval, Québec, QC, Canada; Department of Kinesiology, Faculty of Medicine, Université Laval, Québec, QC, Canada
| | - Iwona Rudkowska
- CHU de Québec Research Center, Université Laval, Québec, QC, Canada; Department of Kinesiology, Faculty of Medicine, Université Laval, Québec, QC, Canada.
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Arena R, Ozemek C, Laddu D, Campbell T, Rouleau CR, Standley R, Bond S, Abril EP, Hills AP, Lavie CJ. Applying Precision Medicine to Healthy Living for the Prevention and Treatment of Cardiovascular Disease. Curr Probl Cardiol 2018; 43:448-483. [DOI: 10.1016/j.cpcardiol.2018.06.001] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
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23
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Sikalidis AK. From Food for Survival to Food for Personalized Optimal Health: A Historical Perspective of How Food and Nutrition Gave Rise to Nutrigenomics. J Am Coll Nutr 2018; 38:84-95. [PMID: 30280996 DOI: 10.1080/07315724.2018.1481797] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Human nutrition has progressed impressively from the hunter-gatherer mode to that of promising personalized nutrition for health optimization through advanced and sophisticated omics technologies. The contemporary major diseases, while having strong genetic components, do not conform to Mendelian genetics; hence, their expression/manifestation is not controlled by a single gene. Noncommunicable diseases such as obesity, cancer, type 2 diabetes mellitus, and cardiovascular disease are attributed to a series of chronic anomalies closely related to dietary, among other, environmental factors, and consistent deregulation of one or more groups of genes (polygenic). Collectively, these diseases constitute the main cause of death globally and pose tremendous financial burden on healthcare systems. Dietary interventions offer significant possibilities for cost-effective strategies to reduce risk of a series of metabolic diseases and/or improve the outcome of prognosis. In recent decades, the ability of particular nutrients to influence certain cellular functions as well as the regulation of several metabolic pathways via genomic interplay has been demonstrated. Nutrients can influence cellular responses and hence exert an effect on health parameters and outcomes. Several nutrients have been documented to extend their regulatory capacity at various levels including gene expression profile signatures' modulation. In addition, specific nutrients can modulate expression/activation of genes that encode regulatory hormones, which in turn are signaling agents strongly affecting metabolism and subsequently risk levels for certain metabolic diseases. The field of nutrigenomics attempts to revolutionize modern thinking on diet, food, and health; whether it will deliver is still an open matter of debate Key teaching points: A brief, yet comprehensive account on how food and nutrition evolved to give rise to nutrigenomics. Discusses potential of nutrigenomics for public health contribution in noncommunicable diseases. Debates credibility of nutrigenomics' commercial products versus the bio-hype in the field. Presents experts' and stakeholders' opinions for future directions of nutrigenomics.
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Affiliation(s)
- Angelos K Sikalidis
- a Department of Nutrition and Dietetics, Faculty of Health Sciences , Istanbul Yeni Yuzyil University , Istanbul , Turkey
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Impact of Mechanical and Microstructural Properties of Potato Puree-Food Additive Complexes on Extrusion-Based 3D Printing. FOOD BIOPROCESS TECH 2018. [DOI: 10.1007/s11947-018-2159-5] [Citation(s) in RCA: 38] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
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25
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Riedl A, Wawro N, Gieger C, Meisinger C, Peters A, Roden M, Kronenberg F, Herder C, Rathmann W, Völzke H, Reincke M, Koenig W, Wallaschofski H, Hauner H, Daniel H, Linseisen J. Identification of Comprehensive Metabotypes Associated with Cardiometabolic Diseases in the Population-Based KORA Study. Mol Nutr Food Res 2018; 62:e1800117. [PMID: 29939495 DOI: 10.1002/mnfr.201800117] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2018] [Revised: 05/24/2018] [Indexed: 12/17/2022]
Abstract
SCOPE "Metabotyping" describes the grouping of metabolically similar individuals. We aimed to identify valid metabotypes in a large cohort for targeted dietary intervention, for example, for disease prevention. METHODS AND RESULTS We grouped 1729 adults aged 32-77 years of the German population-based KORA F4 study (2006-2008) using k-means cluster analysis based on 34 biochemical and anthropometric parameters. We identified three metabolically distinct clusters showing significantly different biochemical parameter concentrations. Cardiometabolic disease status was determined at baseline in the F4 study and at the 7 year follow-up termed FF4 (2013/2014) to compare disease prevalence and incidence between clusters. Cluster 3 showed the most unfavorable marker profile with the highest prevalence of cardiometabolic diseases. Also, disease incidence was higher in cluster 3 compared to clusters 2 and 1, respectively, for hypertension (41.2%/25.3%/18.2%), type 2 diabetes (28.3%/5.1%/2.0%), hyperuricemia/gout (10.8%/2.3%/0.7%), dyslipidemia (19.2%/18.3%/5.6%), all metabolic (54.5%/36.8%/19.7%), and all cardiovascular (6.3%/5.5%/2.3%) diseases together. CONCLUSION Cluster analysis based on an extensive set of biochemical and anthropometric parameters allows the identification of comprehensive metabotypes that were distinctly different in cardiometabolic disease occurrence. As a next step, targeted dietary strategies should be developed with the goal of preventing diseases, especially in cluster 3.
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Affiliation(s)
- Anna Riedl
- Independent Research Group Clinical Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764, Neuherberg, Germany.,Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764, Neuherberg, Germany.,German Center for Diabetes Research, Ingolstädter Landstr. 1, 85764, Neuherberg, Germany.,Chair of Epidemiology, Ludwig-Maximilians-Universität München, at UNIKA-T (Universitäres Zentrum für Gesundheitswissenschaften am Klinikum Augsburg), Neusässer Str. 47, 86156, Augsburg, Germany
| | - Nina Wawro
- Independent Research Group Clinical Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764, Neuherberg, Germany.,Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764, Neuherberg, Germany.,German Center for Diabetes Research, Ingolstädter Landstr. 1, 85764, Neuherberg, Germany.,Chair of Epidemiology, Ludwig-Maximilians-Universität München, at UNIKA-T (Universitäres Zentrum für Gesundheitswissenschaften am Klinikum Augsburg), Neusässer Str. 47, 86156, Augsburg, Germany
| | - Christian Gieger
- Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764, Neuherberg, Germany.,German Center for Diabetes Research, Ingolstädter Landstr. 1, 85764, Neuherberg, Germany.,Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Ingolstädter Landstr. 1, 85764, Neuherberg, Germany
| | - Christa Meisinger
- Independent Research Group Clinical Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764, Neuherberg, Germany.,Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764, Neuherberg, Germany.,Chair of Epidemiology, Ludwig-Maximilians-Universität München, at UNIKA-T (Universitäres Zentrum für Gesundheitswissenschaften am Klinikum Augsburg), Neusässer Str. 47, 86156, Augsburg, Germany
| | - Annette Peters
- Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764, Neuherberg, Germany.,German Center for Diabetes Research, Ingolstädter Landstr. 1, 85764, Neuherberg, Germany
| | - Michael Roden
- German Center for Diabetes Research, Ingolstädter Landstr. 1, 85764, Neuherberg, Germany.,Division of Endocrinology and Diabetology, Medical Faculty, Heinrich Heine University Düsseldorf, Auf'm Hennekamp 65, 40225, Düsseldorf, Germany.,Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Auf'm Hennekamp 65, 40225, Düsseldorf, Germany
| | - Florian Kronenberg
- Division of Genetic Epidemiology, Department of Medical Genetics, Molecular and Clinical Pharmacology, Medical University of Innsbruck, Schöpfstr. 41, 6020, Innsbruck, Austria
| | - Christian Herder
- German Center for Diabetes Research, Ingolstädter Landstr. 1, 85764, Neuherberg, Germany.,Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Auf'm Hennekamp 65, 40225, Düsseldorf, Germany
| | - Wolfgang Rathmann
- German Center for Diabetes Research, Ingolstädter Landstr. 1, 85764, Neuherberg, Germany.,Institute for Biometrics and Epidemiology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Auf'm Hennekamp 65, 40225, Düsseldorf, Germany
| | - Henry Völzke
- German Center for Diabetes Research, Ingolstädter Landstr. 1, 85764, Neuherberg, Germany.,DZHK - German Centre for Cardiovascular Research, Partner Site Munich Heart Alliance, Pettenkoferstr. 8a & 9, 80336, Munich, Germany.,Institute for Community Medicine, University Medicine Greifswald, Walther-Rathenau-Str. 48, 17475, Greifswald, Germany
| | - Martin Reincke
- Medizinische Klinik und Poliklinik IV, Klinikum der Universität München, Ludwig-Maximilians-Universität München, Ziemssenstr. 1, 81377, Munich, Germany
| | - Wolfgang Koenig
- DZHK - German Centre for Cardiovascular Research, Partner Site Munich Heart Alliance, Pettenkoferstr. 8a & 9, 80336, Munich, Germany.,Deutsches Herzzentrum München, Technische Universität München, Lazarettstr. 36, 80636, Munich, Germany.,Department of Internal Medicine II-Cardiology, University of Ulm Medical Center, Albert-Einstein-Allee 23, 89081, Ulm, Germany
| | - Henri Wallaschofski
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Ferdinand-Sauerbruch-Str., 17489, Greifswald, Germany
| | - Hans Hauner
- Else Kröner-Fresenius Centre for Nutritional Medicine, Technical University of Munich, Gregor-Mendel-Str. 2, 85354, Freising-Weihenstephan, Germany.,ZIEL - Institute for Food and Health, Technical University of Munich, Weihenstephaner Berg 1, 85354, Freising, Germany.,Institute of Nutritional Medicine, Klinikum rechts der Isar, Technical University of Munich, Uptown München Campus D, Georg-Brauchle-Ring 60/62, 80992, Munich, Germany.,Technical University of Munich, Gregor-Mendel-Str. 2, 85354, Freising-Weihenstephan, Germany
| | - Hannelore Daniel
- Technical University of Munich, Gregor-Mendel-Str. 2, 85354, Freising-Weihenstephan, Germany
| | - Jakob Linseisen
- Independent Research Group Clinical Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764, Neuherberg, Germany.,Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764, Neuherberg, Germany.,Chair of Epidemiology, Ludwig-Maximilians-Universität München, at UNIKA-T (Universitäres Zentrum für Gesundheitswissenschaften am Klinikum Augsburg), Neusässer Str. 47, 86156, Augsburg, Germany.,ZIEL - Institute for Food and Health, Technical University of Munich, Weihenstephaner Berg 1, 85354, Freising, Germany
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Abstract
OBJECTIVE The present study explored associations between food choice motives, attitudes towards and intention to adopt personalised nutrition, to inform communication strategies based on consumer priorities and concerns.Design/SettingA survey was administered online which included the Food Choice Questionnaire (FCQ) and items assessing attitudes towards and intention to adopt personalised nutrition. SUBJECTS Nationally representative samples were recruited in nine EU countries (n 9381). RESULTS Structural equation modelling indicated that the food choice motives 'weight control', 'mood', 'health' and 'ethical concern' had a positive association and 'price' had a negative association with attitude towards, and intention to adopt, personalised nutrition. 'Health' was positively associated and 'familiarity' negatively associated with attitude towards personalised nutrition. The effects of 'weight control', 'ethical concern', 'mood' and 'price' on intention to adopt personalised nutrition were partially mediated by attitude. The effects of 'health' and 'familiarity' were fully mediated by attitude. 'Sensory appeal' was negatively and directly associated with intention to adopt personalised nutrition. CONCLUSIONS Personalised nutrition providers may benefit from taking into consideration the importance of underlying determinants of food choice in potential users, particularly weight control, mood and price, when promoting services and in tailoring communications that are motivationally relevant.
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Dankar I, Haddarah A, Omar FE, Sepulcre F, Pujolà M. 3D printing technology: The new era for food customization and elaboration. Trends Food Sci Technol 2018. [DOI: 10.1016/j.tifs.2018.03.018] [Citation(s) in RCA: 165] [Impact Index Per Article: 27.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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Schutyser M, Houlder S, de Wit M, Buijsse C, Alting A. Fused deposition modelling of sodium caseinate dispersions. J FOOD ENG 2018. [DOI: 10.1016/j.jfoodeng.2017.02.004] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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Beckett EL, Jones PR, Veysey M, Lucock M. Nutrigenetics—Personalized Nutrition in the Genetic Age. EXPLORATORY RESEARCH AND HYPOTHESIS IN MEDICINE 2017; 2:1-8. [DOI: 10.14218/erhm.2017.00027] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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Personalised Interventions-A Precision Approach for the Next Generation of Dietary Intervention Studies. Nutrients 2017; 9:nu9080847. [PMID: 28792454 PMCID: PMC5579640 DOI: 10.3390/nu9080847] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2017] [Revised: 07/23/2017] [Accepted: 08/01/2017] [Indexed: 12/13/2022] Open
Abstract
Diet is a key modifiable risk factor for non-communicable diseases. However, we currently are not benefitting from the full potential of its protective effects. This is due to a number of reasons, including high individual variability in response to certain diets. It is now well acknowledged that in order to gain the full benefit of dietary regimes it is essential to take into account individual responses. With this in mind, the present review examines the concept of precision nutrition and the performance of n-of-1 studies, and discusses the development of certain approaches that will be critical for development of the concepts.
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Abstract
AbstractMetabolic diversity leads to differences in nutrient requirements and responses to diet and medication between individuals. Using the concept of metabotyping – that is, grouping metabolically similar individuals – tailored and more efficient recommendations may be achieved. The aim of this study was to review the current literature on metabotyping and to explore its potential for better targeted dietary intervention in subjects with and without metabolic diseases. A comprehensive literature search was performed in PubMed, Google and Google Scholar to find relevant articles on metabotyping in humans including healthy individuals, population-based samples and patients with chronic metabolic diseases. A total of thirty-four research articles on human studies were identified, which established more homogeneous subgroups of individuals using statistical methods for analysing metabolic data. Differences between studies were found with respect to the samples/populations studied, the clustering variables used, the statistical methods applied and the metabotypes defined. According to the number and type of the selected clustering variables, the definitions of metabotypes differed substantially; they ranged between general fasting metabotypes, more specific fasting parameter subgroups like plasma lipoprotein or fatty acid clusters and response groups to defined meal challenges or dietary interventions. This demonstrates that the term ‘metabotype’ has a subjective usage, calling for a formalised definition. In conclusion, this literature review shows that metabotyping can help identify subgroups of individuals responding differently to defined nutritional interventions. Targeted recommendations may be given at such metabotype group levels. Future studies should develop and validate definitions of generally valid metabotypes by exploiting the increasingly available metabolomics data sets.
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de Luca A, Hankard R, Borys JM, Sinnett D, Marcil V, Levy E. Nutriepigenomics and malnutrition. Epigenomics 2017; 9:893-917. [DOI: 10.2217/epi-2016-0168] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022] Open
Abstract
Epigenetics is defined as the modulation of gene expression without changes to the underlying DNA sequence. Epigenetic alterations, as a consequence of in utero malnutrition, may play a role in susceptibility to develop adulthood diseases and inheritance. However, the mechanistic link between epigenetic modifications and abnormalities in nutrition remains elusive. This review provides an update on the association of suboptimal nutritional environment and the high propensity to produce adult-onset chronic illnesses with a particular focus on modifications in genome functions that occur without alterations to the DNA sequence. We will mention the drivers of the phenotype and pattern of epigenetic markers set down during the reprogramming along with novel preventative and therapeutic strategies. New knowledge of epigenetic alterations is opening a gate toward personalized medicine.
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Affiliation(s)
- Arnaud de Luca
- Research Center, Sainte-Justine University Hospital Center, Montreal, Quebec H3T 1C5, Canada
- INSERM, U 1069, F-37044 Tours, France
| | - Regis Hankard
- INSERM, U 1069, F-37044 Tours, France
- François Rabelais University, F-37000 Tours, France
| | | | - Daniel Sinnett
- Research Center, Sainte-Justine University Hospital Center, Montreal, Quebec H3T 1C5, Canada
- Department of Pediatrics, Faculty of Medicine, University of Montreal, Montreal, Quebec H3T 1J4, Canada
| | - Valérie Marcil
- Research Center, Sainte-Justine University Hospital Center, Montreal, Quebec H3T 1C5, Canada
- Department of Nutrition, Faculty of Medicine, University of Montréal, Montreal, Quebec H3T 1J4, Canada
| | - Emile Levy
- Research Center, Sainte-Justine University Hospital Center, Montreal, Quebec H3T 1C5, Canada
- EPODE International Network, F-75017 Paris, France
- Department of Nutrition, Faculty of Medicine, University of Montréal, Montreal, Quebec H3T 1J4, Canada
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Phenotypic factors influencing the variation in response of circulating cholesterol level to personalised dietary advice in the Food4Me study. Br J Nutr 2017; 116:2011-2019. [DOI: 10.1017/s0007114516004256] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
AbstractIndividual response to dietary interventions can be highly variable. The phenotypic characteristics of those who will respond positively to personalised dietary advice are largely unknown. The objective of this study was to compare the phenotypic profiles of differential responders to personalised dietary intervention, with a focus on total circulating cholesterol. Subjects from the Food4Me multi-centre study were classified as responders or non-responders to dietary advice on the basis of the change in cholesterol level from baseline to month 6, with lower and upper quartiles defined as responder and non-responder groups, respectively. There were no significant differences between demographic and anthropometric profiles of the groups. Furthermore, with the exception of alcohol, there was no significant difference in reported dietary intake, at baseline. However, there were marked differences in baseline fatty acid profiles. The responder group had significantly higher levels of stearic acid (18 : 0, P=0·034) and lower levels of palmitic acid (16 : 0, P=0·009). Total MUFA (P=0·016) and total PUFA (P=0·008) also differed between the groups. In a step-wise logistic regression model, age, baseline total cholesterol, glucose, five fatty acids and alcohol intakes were selected as factors that successfully discriminated responders from non-responders, with sensitivity of 82 % and specificity of 83 %. The successful delivery of personalised dietary advice may depend on our ability to identify phenotypes that are responsive. The results demonstrate the potential use of metabolic profiles in identifying response to an intervention and could play an important role in the development of precision nutrition.
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Rizzi F, Conti C, Dogliotti E, Terranegra A, Salvi E, Braga D, Ricca F, Lupoli S, Mingione A, Pivari F, Brasacchio C, Barcella M, Chittani M, D’Avila F, Turiel M, Lazzaroni M, Soldati L, Cusi D, Barlassina C. Interaction between polyphenols intake and PON1 gene variants on markers of cardiovascular disease: a nutrigenetic observational study. J Transl Med 2016; 14:186. [PMID: 27338244 PMCID: PMC4918189 DOI: 10.1186/s12967-016-0941-6] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2016] [Accepted: 06/11/2016] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND Paraoxonase 1 (PON1) gene polymorphisms and polyphenols intake have been reported independently associated to lipid profile and susceptibility to atherosclerosis and cardiovascular disease. However, the interaction between these factors remains to be investigated. We performed an observational nutrigenetic study to examine whether the interaction between polyphenols and anthocyanins intake and PON1 genetic variants can modulate biomarkers of cardiovascular health in an Italian healthy population. METHODS We recruited 443 healthy volunteers who participated in the EC funded ATHENA project (AnThocyanin and polyphenols bioactive for Health Enhancement through Nutritional Advancement). Data collection included detailed demographic, clinical, dietary, lifestyle, biochemical and genetic data. Polyphenols and anthocyanins intake was measured by 24 h dietary recall repeated three times a year in order to get seasonal variations. We tested the interaction between 18 independent tagging SNPs in PON1 gene and polyphenols intake on HDL, LDL, cholesterol, triglycerides and atherogenic index of plasma. RESULTS Without considering the genetic background, we could not observe significant differences in the lipid profile between high and low polyphenols and anthocyanins intake. Using a nutrigenetic approach, we identified protective genotypes in four independent polymorphisms that, at Bonferroni level (p ≤ 0.0028), present a significant association with increased HDL level under high polyphenols and anthocyanins intake, compared to risk genotypes (rs854549, Beta = 4.7 per C allele; rs854552, Beta = 5.6 per C allele; rs854571, Beta = 3.92 per T allele; rs854572, Beta = 3.94 per C allele). CONCLUSIONS We highlight the protective role of genetic variants in PON1 towards cardiovascular risk under high polyphenols and anthocyanins consumption. PON1 variants could represent novel biomarkers to stratify individuals who might benefit from targeted dietary recommendation for health promotion and strategies of preventive medicine.
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Affiliation(s)
- Federica Rizzi
- />Genomics and Bionformatics Unit, Department of Health Sciences, Università degli Studi di Milano, viale Ortles 22/4, Milan, Italy
| | - Costanza Conti
- />Genomics and Bionformatics Unit, Department of Health Sciences, Università degli Studi di Milano, viale Ortles 22/4, Milan, Italy
- />Kos Genetic srl, Milan, Italy
| | - Elena Dogliotti
- />Division of Nephrology, ASST Santi Paolo e Carlo, Via Antonio di Rudinì 8, Milan, Italy
- />Fondazione Umberto Veronesi, Milan, Italy
| | - Annalisa Terranegra
- />Division of Translational Medicine, Sidra Medical Research Center, Doha, Qatar
| | - Erika Salvi
- />Genomics and Bionformatics Unit, Department of Health Sciences, Università degli Studi di Milano, viale Ortles 22/4, Milan, Italy
| | - Daniele Braga
- />Genomics and Bionformatics Unit, Department of Health Sciences, Università degli Studi di Milano, viale Ortles 22/4, Milan, Italy
| | - Flavia Ricca
- />Division of Nephrology, ASST Santi Paolo e Carlo, Via Antonio di Rudinì 8, Milan, Italy
- />Sport Medicine Division, Department of Public Health, University Federico II, Naples, Italy
| | - Sara Lupoli
- />Genomics and Bionformatics Unit, Department of Health Sciences, Università degli Studi di Milano, viale Ortles 22/4, Milan, Italy
| | - Alessandra Mingione
- />Department of Health Sciences, Università degli Studi di Milano, Via Antonio di Rudinì 8, Milan, Italy
| | - Francesca Pivari
- />Department of Health Sciences, Università degli Studi di Milano, Via Antonio di Rudinì 8, Milan, Italy
| | - Caterina Brasacchio
- />Department of Health Sciences, Università degli Studi di Milano, Via Antonio di Rudinì 8, Milan, Italy
| | - Matteo Barcella
- />Genomics and Bionformatics Unit, Department of Health Sciences, Università degli Studi di Milano, viale Ortles 22/4, Milan, Italy
| | - Martina Chittani
- />Genomics and Bionformatics Unit, Department of Health Sciences, Università degli Studi di Milano, viale Ortles 22/4, Milan, Italy
| | - Francesca D’Avila
- />Genomics and Bionformatics Unit, Department of Health Sciences, Università degli Studi di Milano, viale Ortles 22/4, Milan, Italy
| | - Maurizio Turiel
- />IRCCS Galeazzi Orthopedic Institute, Via Riccardo Galeazzi, 4, Milan, Italy
| | - Monica Lazzaroni
- />Laboratory of Clinical Pathology and Medical Genetics, Foundation IRCCS Neurological Institute C. Besta, Milan, Italy
| | - Laura Soldati
- />Genomics and Bionformatics Unit, Department of Health Sciences, Università degli Studi di Milano, viale Ortles 22/4, Milan, Italy
| | - Daniele Cusi
- />Division of Nephrology, ASST Santi Paolo e Carlo, Via Antonio di Rudinì 8, Milan, Italy
- />Department of Health Sciences, Università degli Studi di Milano, Via Antonio di Rudinì 8, Milan, Italy
- />Institute of Biomedical Technologies, Italian National Centre of Research, Segrate, Milan, Italy
| | - Cristina Barlassina
- />Genomics and Bionformatics Unit, Department of Health Sciences, Università degli Studi di Milano, viale Ortles 22/4, Milan, Italy
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Kohlmeier M, De Caterina R, Ferguson LR, Görman U, Allayee H, Prasad C, Kang JX, Nicoletti CF, Martinez JA. Guide and Position of the International Society of Nutrigenetics/Nutrigenomics on Personalized Nutrition: Part 2 - Ethics, Challenges and Endeavors of Precision Nutrition. JOURNAL OF NUTRIGENETICS AND NUTRIGENOMICS 2016; 9:28-46. [PMID: 27286972 DOI: 10.1159/000446347] [Citation(s) in RCA: 51] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Abstract
Nutrigenetics considers the influence of individual genetic variation on differences in response to dietary components, nutrient requirements and predisposition to disease. Nutrigenomics involves the study of interactions between the genome and diet, including how nutrients affect the transcription and translation process plus subsequent proteomic and metabolomic changes, and also differences in response to dietary factors based on the individual genetic makeup. Personalized characteristics such as age, gender, physical activity, physiological state and social status, and special conditions such as pregnancy and risk of disease can inform dietary advice that more closely meets individual needs. Precision nutrition has a promising future in treating the individual according to their phenotype and genetic characteristics, aimed at both the treatment and prevention of disease. However, many aspects are still in progress and remain as challenges for the future of nutrition. The integration of the human genotype and microbiome needs to be better understood. Further advances in data interpretation tools are also necessary, so that information obtained through newer tests and technologies can be properly transferred to consumers. Indeed, precision nutrition will integrate genetic data with phenotypical, social, cultural and personal preferences and lifestyles matters to provide a more individual nutrition, but considering public health perspectives, where ethical, legal and policy aspects need to be defined and implemented.
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Affiliation(s)
- Martin Kohlmeier
- Department of Nutrition, School of Public Health, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, N.C., USA
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Bouchard-Mercier A, Desroches S, Robitaille J, Vohl MC. Factors Associated with the Intention of Registered Dietitians to Discuss Nutrigenetics with their Patients/Clients. CAN J DIET PRACT RES 2016; 77:163-169. [PMID: 27182816 DOI: 10.3148/cjdpr-2016-005] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
PURPOSE The objective of this study was to investigate factors affecting the intention of Registered Dietitians (RDs) to discuss nutrigenetics with their patients/clients. METHODS A survey based on the theory of planned behaviour (TPB; attitude, subjective norm, and perceived behavioural control) was developed and sent by email to RD members of the Ordre professionnel des diététistes du Québec. Multiple regression analyses were performed to examine the determinants of intention and behaviour. RESULTS A total of 141 RDs completed the questionnaire (5.8% response rate). On a scale from -2 to 2 (from strongly disagree to strongly agree), the intention of discussing nutrigenetics with patients/clients was neutral (mean of -0.07 ± 0.92). The TPB construct of attitude was the most strongly associated with intention (β = 0.66, P < 0.0001) followed by perceived behavioural control (β = 0.33, P < 0.0001) and subjective norm (β = 0.21, P = 0.03). Finally, 13 out of 141 RDs (~9%) actually practiced the behaviour, which was to have discussed nutrigenetics with their patients/clients in the last 3 months. Only perceived behavioural control contributed to explain the behaviour (β = 0.17, P < 0.0001). CONCLUSIONS Main determinants of the intention of RDs to discuss nutrigenetics with their patients/clients were determined. This knowledge will help inform the design of future educational content about nutrigenetics.
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Affiliation(s)
- Annie Bouchard-Mercier
- a Institute of Nutrition and Functional Foods (INAF), Laval University, Quebec, QC.,b Department of Food Science and Nutrition, Laval University, Quebec, QC
| | - Sophie Desroches
- a Institute of Nutrition and Functional Foods (INAF), Laval University, Quebec, QC.,b Department of Food Science and Nutrition, Laval University, Quebec, QC
| | - Julie Robitaille
- a Institute of Nutrition and Functional Foods (INAF), Laval University, Quebec, QC.,b Department of Food Science and Nutrition, Laval University, Quebec, QC
| | - Marie-Claude Vohl
- a Institute of Nutrition and Functional Foods (INAF), Laval University, Quebec, QC.,b Department of Food Science and Nutrition, Laval University, Quebec, QC
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Ferguson LR, De Caterina R, Görman U, Allayee H, Kohlmeier M, Prasad C, Choi MS, Curi R, de Luis DA, Gil Á, Kang JX, Martin RL, Milagro FI, Nicoletti CF, Nonino CB, Ordovas JM, Parslow VR, Portillo MP, Santos JL, Serhan CN, Simopoulos AP, Velázquez-Arellano A, Zulet MA, Martinez JA. Guide and Position of the International Society of Nutrigenetics/Nutrigenomics on Personalised Nutrition: Part 1 - Fields of Precision Nutrition. Lifestyle Genom 2016; 9:12-27. [DOI: 10.1159/000445350] [Citation(s) in RCA: 106] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
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Loria-Kohen V, Espinosa-Salinas I, Marcos-Pasero H, Lourenço-Nogueira T, Herranz J, Molina S, Reglero G, Ramirez de Molina A. Polymorphism in the CLOCK gene may influence the effect of fat intake reduction on weight loss. Nutrition 2016; 32:453-60. [DOI: 10.1016/j.nut.2015.10.013] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2015] [Revised: 10/04/2015] [Accepted: 10/17/2015] [Indexed: 11/30/2022]
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Abstract
Food records or diaries, dietary recalls and FFQ are methods traditionally used to measure dietary intake; however, advancing technologies and growing awareness in personalised health have heightened interest in the application of new technologies to assess dietary intake. Dietary intake data can be used in epidemiology, dietary interventions and in the delivery of personalised nutrition advice. Compared with traditional dietary assessment methods, new technologies have many advantages, including their ability to automatically process data and provide personalised dietary feedback advice. This review examines the new technologies presently under development for the assessment of dietary intakes, and their utilisation and efficacy for personalising dietary advice. New technology-based methods of dietary assessment can broadly be categorised into three key areas: online (web-based) methods, mobile methods and sensor technologies. Several studies have demonstrated that utilising new technologies to provide tailored advice can result in positive dietary changes and have a significant impact on selected nutrient and food group intakes. However, comparison across studies indicates that the magnitude of change is variable and may be influenced by several factors, including the frequency and type of feedback provided. Future work should establish the most effective combinations of these factors in facilitating dietary changes across different population groups.
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Ryan NM, O'Donovan CB, Forster H, Woolhead C, Walsh MC. New tools for personalised nutrition: The Food4Me project. NUTR BULL 2015. [DOI: 10.1111/nbu.12143] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- N. M. Ryan
- UCD Institute of Food and Health; University College Dublin; Republic of Ireland
| | - C. B. O'Donovan
- UCD Institute of Food and Health; University College Dublin; Republic of Ireland
| | - H. Forster
- UCD Institute of Food and Health; University College Dublin; Republic of Ireland
| | - C. Woolhead
- UCD Institute of Food and Health; University College Dublin; Republic of Ireland
| | - M. C. Walsh
- UCD Institute of Food and Health; University College Dublin; Republic of Ireland
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Martinez JA, Navas-Carretero S, Saris WHM, Astrup A. Personalized weight loss strategies-the role of macronutrient distribution. Nat Rev Endocrinol 2014; 10:749-60. [PMID: 25311395 DOI: 10.1038/nrendo.2014.175] [Citation(s) in RCA: 56] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
A large number of different dietary approaches have been studied in an attempt to achieve healthy, sustainable weight loss among individuals with overweight and obesity. Restriction of energy intake is the primary method of producing a negative energy balance leading to weight loss. However, owing to the different metabolic roles of proteins, carbohydrates and lipids in energy homeostasis, diets of similar overall energy content but with different macronutrient distribution can differentially affect metabolism, appetite and thermogenesis. Evidence increasingly suggests that the fuel values of calories provided by distinct macronutrients should be considered separately, as metabolism of specific molecular components generates differences in energy yield. The causes of variation in individual responses to various diets are currently under debate, and some evidence suggests that differences are associated with specific genotypes. This Review discusses all available systematic reviews and meta-analyses, and summarizes the results of relevant randomized controlled intervention trials assessing the influence of macronutrient composition on weight management. The initial findings of research into personalized nutrition, based on the interactions of macronutrient intake and genetic background and its potential influence on dietary intervention strategies, are also discussed.
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Affiliation(s)
- J Alfredo Martinez
- Centre for Nutrition Research, CIBERobn (Fisiopatología de la obesidad), University of Navarra, c/Irunlarrea 1, 31008 Pamplona, Navarra, Spain
| | - Santiago Navas-Carretero
- Centre for Nutrition Research, CIBERobn (Fisiopatología de la obesidad), University of Navarra, c/Irunlarrea 1, 31008 Pamplona, Navarra, Spain
| | - Wim H M Saris
- Nutrition and Toxicology Research Institute Maastricht (NUTRIM), Maastricht University Medical Centre, P.O. Box 616, 6200 MD Maastricht, Netherlands
| | - Arne Astrup
- Department of Nutrition, Exercise and Sports (NEXS), Faculty of Science, University of Copenhagen, Rolighedsvej 26 Frederiksberg C, DK-1958, Denmark
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Mosconi L, Murray J, Davies M, Williams S, Pirraglia E, Spector N, Tsui WH, Li Y, Butler T, Osorio RS, Glodzik L, Vallabhajosula S, McHugh P, Marmar CR, de Leon MJ. Nutrient intake and brain biomarkers of Alzheimer's disease in at-risk cognitively normal individuals: a cross-sectional neuroimaging pilot study. BMJ Open 2014; 4:e004850. [PMID: 24961717 PMCID: PMC4078781 DOI: 10.1136/bmjopen-2014-004850] [Citation(s) in RCA: 59] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
OBJECTIVE There is increasing evidence to suggest that diet, one of the most important modifiable environmental factors, may play a role in preventing or delaying cognitive decline and Alzheimer's disease (AD). This study examines the relationship between dietary nutrients and brain biomarkers of AD in cognitively normal individuals (NL) with and without AD risk factors. DESIGN As part of an ongoing brain imaging study, participants received clinical and laboratory examinations, a neurocognitive test battery, positron emission tomography (PET) with (11)C-Pittsburgh Compound-B (PiB; a measure of amyloid-β (Aβ) load) and (18)F-fluorodeoxyglucose (FDG; a proxy of neuronal activity), and completed semiquantitative food frequency questionnaires. SETTING Research centre affiliated with the Alzheimer's disease Core Center at New York University School of Medicine. PARTICIPANTS 49 NL individuals (age 25-72 years, 69% women) with dietary information, (11)C-PiB and (18)F-FDG PET scans were examined. RESULTS Controlling for age and total caloric intake, higher intake of vitamin B12, vitamin D and ω-3 polyunsaturated fatty acid (PUFA) was associated with lower Aβ load in AD regions on PiB-PET, while higher intake of β-carotene and folate was associated with higher glucose metabolism on FDG-PET. β-carotene and folate were associated with reduced glucose metabolism for women, apolipoprotein E epsilon 4 (APOE4) carriers and participants with positive AD family history, but not for their risk-free counterparts. The associations of vitamin B12, vitamin D and ω-3 PUFA with PiB retention were independent of gender, APOE and family history. The identified nutrient combination was associated with higher intake of vegetables, fruit, whole grains, fish and legumes, and lower intake of high-fat dairies, meat and sweets. CONCLUSIONS Our data provide a potential pathophysiological mechanism for epidemiological findings showing that dietary interventions may play a role in the prevention of AD. Longitudinal studies are needed to determine whether there is a direct link between nutrient intake, brain biomarkers and risk of AD.
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Affiliation(s)
- Lisa Mosconi
- Department of Psychiatry, New York University School of Medicine, New York, USA
| | - John Murray
- Department of Psychiatry, New York University School of Medicine, New York, USA
| | - Michelle Davies
- Department of Psychiatry, New York University School of Medicine, New York, USA
| | - Schantel Williams
- Department of Psychiatry, New York University School of Medicine, New York, USA
| | - Elizabeth Pirraglia
- Department of Psychiatry, New York University School of Medicine, New York, USA
| | - Nicole Spector
- Department of Psychiatry, New York University School of Medicine, New York, USA
| | - Wai H Tsui
- Department of Psychiatry, New York University School of Medicine, New York, USA
| | - Yi Li
- Department of Psychiatry, New York University School of Medicine, New York, USA
| | - Tracy Butler
- Department of Psychiatry, New York University School of Medicine, New York, USA
| | - Ricardo S Osorio
- Department of Psychiatry, New York University School of Medicine, New York, USA
| | - Lidia Glodzik
- Department of Psychiatry, New York University School of Medicine, New York, USA
| | - Shankar Vallabhajosula
- Department of Radiology, Citigroup Biomedical Imaging Center (CBIC), Weill Cornell Medical College, New York, New York, USA
| | - Pauline McHugh
- Department of Psychiatry, New York University School of Medicine, New York, USA
| | - Charles R Marmar
- Department of Psychiatry, New York University School of Medicine, New York, USA
- Steven and Alexandra Cohen Veterans Center for PTSD and TBI, New York, New York, USA
| | - Mony J de Leon
- Department of Psychiatry, New York University School of Medicine, New York, USA
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Berezowska A, Fischer ARH, Ronteltap A, Kuznesof S, Macready A, Fallaize R, van Trijp HCM. Understanding consumer evaluations of personalised nutrition services in terms of the privacy calculus: a qualitative study. Public Health Genomics 2014; 17:127-40. [PMID: 24732571 DOI: 10.1159/000358851] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2013] [Accepted: 01/15/2014] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND Personalised nutrition (PN) may provide major health benefits to consumers. A potential barrier to the uptake of PN is consumers' reluctance to disclose sensitive information upon which PN is based. This study adopts the privacy calculus to explore how PN service attributes contribute to consumers' privacy risk and personalisation benefit perceptions. METHODS Sixteen focus groups (n = 124) were held in 8 EU countries and discussed 9 PN services that differed in terms of personal information, communication channel, service provider, advice justification, scope, frequency, and customer lock-in. Transcripts were content analysed. RESULTS The personal information that underpinned PN contributed to both privacy risk perception and personalisation benefit perception. Disclosing information face-to-face mitigated the perception of privacy risk and amplified the perception of personalisation benefit. PN provided by a qualified expert and justified by scientific evidence increased participants' value perception. Enhancing convenience, offering regular face-to face support, and employing customer lock-in strategies were perceived as beneficial. CONCLUSION This study suggests that to encourage consumer adoption, PN has to account for face-to-face communication, expert advice providers, support, a lifestyle-change focus, and customised offers. The results provide an initial insight into service attributes that influence consumer adoption of PN.
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Affiliation(s)
- Aleksandra Berezowska
- Department of Social Sciences, Marketing and Consumer Behaviour Group, Wageningen University and Research Centre, Wageningen, The Netherlands
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Schwartz B. New criteria for supplementation of selected micronutrients in the era of nutrigenetics and nutrigenomics. Int J Food Sci Nutr 2014; 65:529-38. [PMID: 24625102 DOI: 10.3109/09637486.2014.898258] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
Advances in molecular biology, emergence of novel techniques and huge amount of information generated in the post-Human Genome Project era have fostered the emergence of new disciplines in the field of nutritional research: Nutrigenomics deals with the effect of diet on gene expression whereas nutrigenetics refers to the impact of inherited traits on the response to a specific dietary pattern, functional food or supplement. Understanding the role of micronutrient supplementation with specific genetic backgrounds may provide an important contribution to a new optimum health strategy based on individualized nutritional treatment and may provide the strategies for the development of safer and more effective dietary interventions. This overview of the various aspects of supplementation of micronutrients in the era of nutrigenetics and nutrigenomics may provide a better understanding of novel nutritional research approach and provide an additional insight that can be applied to the daily dietary practice.
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Affiliation(s)
- Betty Schwartz
- The Robert H. Smith Faculty of Agriculture, Food and Environment, Institute of Biochemistry, Food Science and Nutrition, The Hebrew University of Jerusalem , Rehovot , Israel
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Hurlimann T, Menuz V, Graham J, Robitaille J, Vohl MC, Godard B. Risks of nutrigenomics and nutrigenetics? What the scientists say. GENES AND NUTRITION 2013; 9:370. [PMID: 24293399 DOI: 10.1007/s12263-013-0370-6] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/20/2013] [Accepted: 10/18/2013] [Indexed: 01/12/2023]
Abstract
Nutrigenomics and nutrigenetics (hereafter NGx) have stimulated expectations for beneficial applications in public health and individuals. Yet, the potential achievability of such promise is not without socioethical considerations that challenge NGx implementation. This paper focuses on the opinions of NGx researchers about potential risks raised by NGx. The results of an online survey show that these researchers (n = 126) are fairly confident about the potential benefits of NGx, and that most downplay its potential risks. Researchers in this field do not believe that NGx will reconfigure foods as medication or transform the conception of eating into a health hazard. The majority think that NGx will produce no added burden on individuals to get tested or to remain compliant with NGx recommendations, nor that NGx will threaten individual autonomy in daily food choice. The majority of researchers do not think that NGx will lead to discrimination against and/or stigmatization of people who do not comply with NGx dietary recommendations. Despite this optimism among NGx researchers, we suggest that key risk factors raised by the socioethical context in which NGx applications will be implemented need to be considered.
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Affiliation(s)
- T Hurlimann
- Department of Social and Preventive Medicine, Bioethics Programmes, School of Public Health (ESPUM), University of Montreal, C.P. 6128, succursale Centre-ville, Montreal, QC, H3C 3J7, Canada
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