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Hillesheim E, Ryan MF, Gibney E, Roche HM, Brennan L. Optimisation of a metabotype approach to deliver targeted dietary advice. Nutr Metab (Lond) 2020; 17:82. [PMID: 33005208 PMCID: PMC7523294 DOI: 10.1186/s12986-020-00499-z] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2020] [Accepted: 09/08/2020] [Indexed: 12/17/2022] Open
Abstract
BACKGROUND Targeted nutrition is defined as dietary advice tailored at a group level. Groups known as metabotypes can be identified based on individual metabolic profiles. Metabotypes have been associated with differential responses to diet, which support their use to deliver dietary advice. We aimed to optimise a metabotype approach to deliver targeted dietary advice by encompassing more specific recommendations on nutrient and food intakes and dietary behaviours. METHODS Participants (n = 207) were classified into three metabotypes based on four biomarkers (triacylglycerol, total cholesterol, HDL-cholesterol and glucose) and using a k-means cluster model. Participants in metabotype-1 had the highest average HDL-cholesterol, in metabotype-2 the lowest triacylglycerol and total cholesterol, and in metabotype-3 the highest triacylglycerol and total cholesterol. For each participant, dietary advice was assigned using decision trees for both metabotype (group level) and personalised (individual level) approaches. Agreement between methods was compared at the message level and the metabotype approach was optimised to incorporate messages exclusively assigned by the personalised approach and current dietary guidelines. The optimised metabotype approach was subsequently compared with individualised advice manually compiled. RESULTS The metabotype approach comprised advice for improving the intake of saturated fat (69% of participants), fibre (66%) and salt (18%), while the personalised approach assigned advice for improving the intake of folate (63%), fibre (63%), saturated fat (61%), calcium (34%), monounsaturated fat (24%) and salt (14%). Following the optimisation of the metabotype approach, the most frequent messages assigned to address intake of key nutrients were to increase the intake of fruit and vegetables, beans and pulses, dark green vegetables, and oily fish, to limit processed meats and high-fat food products and to choose fibre-rich carbohydrates, low-fat dairy and lean meats (60-69%). An average agreement of 82.8% between metabotype and manual approaches was revealed, with excellent agreements in metabotype-1 (94.4%) and metabotype-3 (92.3%). CONCLUSIONS The optimised metabotype approach proved capable of delivering targeted dietary advice for healthy adults, being highly comparable with individualised advice. The next step is to ascertain whether the optimised metabotype approach is effective in changing diet quality.
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Affiliation(s)
- Elaine Hillesheim
- UCD Institute of Food and Health, UCD School of Agriculture and Food Science, UCD, Dublin 4, Belfield Ireland
- UCD Conway Institute of Biomolecular and Biomedical Research, UCD, Dublin 4, Belfield Ireland
| | - Miriam F. Ryan
- UCD Institute of Food and Health, UCD School of Agriculture and Food Science, UCD, Dublin 4, Belfield Ireland
| | - Eileen Gibney
- UCD Institute of Food and Health, UCD School of Agriculture and Food Science, UCD, Dublin 4, Belfield Ireland
| | - Helen M. Roche
- UCD Conway Institute of Biomolecular and Biomedical Research, UCD, Dublin 4, Belfield Ireland
- Nutrigenomics Research Group, School of Public Health, Physiotherapy and Sports Science & Diabetes Complications Research Centre, UCD, Dublin 4, Belfield Ireland
| | - Lorraine Brennan
- UCD Institute of Food and Health, UCD School of Agriculture and Food Science, UCD, Dublin 4, Belfield Ireland
- UCD Conway Institute of Biomolecular and Biomedical Research, UCD, Dublin 4, Belfield Ireland
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Bhuvaneshwar K, Belouali A, Singh V, Johnson RM, Song L, Alaoui A, Harris MA, Clarke R, Weiner LM, Gusev Y, Madhavan S. G-DOC Plus - an integrative bioinformatics platform for precision medicine. BMC Bioinformatics 2016; 17:193. [PMID: 27130330 PMCID: PMC4851789 DOI: 10.1186/s12859-016-1010-0] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2015] [Accepted: 04/04/2016] [Indexed: 01/30/2023] Open
Abstract
BACKGROUND G-DOC Plus is a data integration and bioinformatics platform that uses cloud computing and other advanced computational tools to handle a variety of biomedical BIG DATA including gene expression arrays, NGS and medical images so that they can be analyzed in the full context of other omics and clinical information. RESULTS G-DOC Plus currently holds data from over 10,000 patients selected from private and public resources including Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA) and the recently added datasets from REpository for Molecular BRAin Neoplasia DaTa (REMBRANDT), caArray studies of lung and colon cancer, ImmPort and the 1000 genomes data sets. The system allows researchers to explore clinical-omic data one sample at a time, as a cohort of samples; or at the level of population, providing the user with a comprehensive view of the data. G-DOC Plus tools have been leveraged in cancer and non-cancer studies for hypothesis generation and validation; biomarker discovery and multi-omics analysis, to explore somatic mutations and cancer MRI images; as well as for training and graduate education in bioinformatics, data and computational sciences. Several of these use cases are described in this paper to demonstrate its multifaceted usability. CONCLUSION G-DOC Plus can be used to support a variety of user groups in multiple domains to enable hypothesis generation for precision medicine research. The long-term vision of G-DOC Plus is to extend this translational bioinformatics platform to stay current with emerging omics technologies and analysis methods to continue supporting novel hypothesis generation, analysis and validation for integrative biomedical research. By integrating several aspects of the disease and exposing various data elements, such as outpatient lab workup, pathology, radiology, current treatments, molecular signatures and expected outcomes over a web interface, G-DOC Plus will continue to strengthen precision medicine research. G-DOC Plus is available at: https://gdoc.georgetown.edu .
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Affiliation(s)
- Krithika Bhuvaneshwar
- />Innovation Center for Biomedical Informatics, Georgetown University Medical Center, Washington, DC USA
| | - Anas Belouali
- />Innovation Center for Biomedical Informatics, Georgetown University Medical Center, Washington, DC USA
| | - Varun Singh
- />Innovation Center for Biomedical Informatics, Georgetown University Medical Center, Washington, DC USA
| | - Robert M. Johnson
- />Innovation Center for Biomedical Informatics, Georgetown University Medical Center, Washington, DC USA
| | - Lei Song
- />Innovation Center for Biomedical Informatics, Georgetown University Medical Center, Washington, DC USA
| | - Adil Alaoui
- />Innovation Center for Biomedical Informatics, Georgetown University Medical Center, Washington, DC USA
| | - Michael A. Harris
- />Innovation Center for Biomedical Informatics, Georgetown University Medical Center, Washington, DC USA
| | - Robert Clarke
- />Department of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC USA
| | - Louis M. Weiner
- />Department of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC USA
| | - Yuriy Gusev
- />Innovation Center for Biomedical Informatics, Georgetown University Medical Center, Washington, DC USA
- />Department of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC USA
| | - Subha Madhavan
- />Innovation Center for Biomedical Informatics, Georgetown University Medical Center, Washington, DC USA
- />Department of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC USA
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Blaise BJ, Gouel-Chéron A, Floccard B, Monneret G, Plaisant F, Chassard D, Javouhey E, Claris O, Allaouchiche B. [Nuclear magnetic resonance based metabolic phenotyping for patient evaluations in operating rooms and intensive care units]. ACTA ACUST UNITED AC 2014; 33:167-75. [PMID: 24456616 DOI: 10.1016/j.annfar.2013.12.005] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2013] [Accepted: 12/02/2013] [Indexed: 12/27/2022]
Abstract
Metabolic phenotyping consists in the identification of subtle and coordinated metabolic variations associated with various pathophysiological stimuli. Different analytical methods, such as nuclear magnetic resonance, allow the simultaneous quantification of a large number of metabolites. Statistical analyses of these spectra thus lead to the discrimination between samples and the identification of a metabolic phenotype corresponding to the effect under study. This approach allows the extraction of candidate biomarkers and the recovery of perturbed metabolic networks, driving to the generation of biochemical hypotheses (pathophysiological mechanisms, diagnostic tests, therapeutic targets…). Metabolic phenotyping could be useful in anaesthesiology and intensive care medicine for the evaluation, monitoring or diagnosis of life-threatening situations, to optimise patient managements. This review introduces the physical and statistical fundamentals of NMR-based metabolic phenotyping, describes the work already achieved by this approach in anaesthesiology and intensive care medicine. Finally, potential areas of interest are discussed for the perioperative and intensive management of patients, from newborns to adults.
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Affiliation(s)
- B J Blaise
- Service de réanimation, hôpital Édouard-Herriot, hospices civils de Lyon, 5, place d'Arsonval, 69437 Lyon cedex 03, France; Service de néonatalogie, hôpital Femme-Mère-Enfant, hospices civils de Lyon, 59, boulevard Pinel, 69500 Bron, France.
| | - A Gouel-Chéron
- Service de réanimation, hôpital Édouard-Herriot, hospices civils de Lyon, 5, place d'Arsonval, 69437 Lyon cedex 03, France
| | - B Floccard
- Service de réanimation, hôpital Édouard-Herriot, hospices civils de Lyon, 5, place d'Arsonval, 69437 Lyon cedex 03, France
| | - G Monneret
- Laboratoire d'immunologie cellulaire, hôpital Édouard-Herriot, hospices civils de Lyon, 5, place d'Arsonval, 69437 Lyon cedex 03, France
| | - F Plaisant
- Service de néonatalogie, hôpital Femme-Mère-Enfant, hospices civils de Lyon, 59, boulevard Pinel, 69500 Bron, France
| | - D Chassard
- Service d'anesthésie et de réanimation, hôpital Femme-Mère-Enfant, hospices civils de Lyon, 59, boulevard Pinel, 69500 Bron, France
| | - E Javouhey
- Service de réanimation pédiatrique, hôpital Femme-Mère-Enfant, hospices civils de Lyon, 59, boulevard Pinel, 69500 Bron, France
| | - O Claris
- Service de néonatalogie, hôpital Femme-Mère-Enfant, hospices civils de Lyon, 59, boulevard Pinel, 69500 Bron, France
| | - B Allaouchiche
- Service de réanimation, hôpital Édouard-Herriot, hospices civils de Lyon, 5, place d'Arsonval, 69437 Lyon cedex 03, France
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Blaise BJ, Gouel-Chéron A, Floccard B, Monneret G, Allaouchiche B. Metabolic Phenotyping of Traumatized Patients Reveals a Susceptibility to Sepsis. Anal Chem 2013; 85:10850-5. [DOI: 10.1021/ac402235q] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Affiliation(s)
- Benjamin J. Blaise
- Hospices
Civils de Lyon, Service de réanimation, Hôpital Edouard Herriot, 5 place d’Arsonval, 69437 Lyon Cedex 03, France
- Hospices
Civils de Lyon, Service de néonatalogie et réanimation
néonatale, Hôpital Femme Mère Enfant, 56 boulevard
Pinel, 69500 Bron, France
| | - Aurélie Gouel-Chéron
- Hospices
Civils de Lyon, Service de réanimation, Hôpital Edouard Herriot, 5 place d’Arsonval, 69437 Lyon Cedex 03, France
| | - Bernard Floccard
- Hospices
Civils de Lyon, Service de réanimation, Hôpital Edouard Herriot, 5 place d’Arsonval, 69437 Lyon Cedex 03, France
| | - Guillaume Monneret
- Hospices
Civils de Lyon, Laboratoire d’immunologie cellulaire, Hôpital Edouard Herriot, 5 place d’Arsonval, 69437 Lyon Cedex 03, France
| | - Bernard Allaouchiche
- Hospices
Civils de Lyon, Service de réanimation, Hôpital Edouard Herriot, 5 place d’Arsonval, 69437 Lyon Cedex 03, France
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Beger RD. A review of applications of metabolomics in cancer. Metabolites 2013; 3:552-74. [PMID: 24958139 PMCID: PMC3901293 DOI: 10.3390/metabo3030552] [Citation(s) in RCA: 168] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2013] [Revised: 05/17/2013] [Accepted: 06/24/2013] [Indexed: 12/17/2022] Open
Abstract
Cancer is a devastating disease that alters the metabolism of a cell and the surrounding milieu. Metabolomics is a growing and powerful technology capable of detecting hundreds to thousands of metabolites in tissues and biofluids. The recent advances in metabolomics technologies have enabled a deeper investigation into the metabolism of cancer and a better understanding of how cancer cells use glycolysis, known as the “Warburg effect,” advantageously to produce the amino acids, nucleotides and lipids necessary for tumor proliferation and vascularization. Currently, metabolomics research is being used to discover diagnostic cancer biomarkers in the clinic, to better understand its complex heterogeneous nature, to discover pathways involved in cancer that could be used for new targets and to monitor metabolic biomarkers during therapeutic intervention. These metabolomics approaches may also provide clues to personalized cancer treatments by providing useful information to the clinician about the cancer patient’s response to medical interventions.
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Affiliation(s)
- Richard D Beger
- National Center for Toxicological Research, US Food and Drug Administration, 3900 NCTR Road, Jefferson, AR 72079, USA.
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