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Navratilova HF, Whetton AD, Geifman N. Artificial intelligence driven definition of food preference endotypes in UK Biobank volunteers is associated with distinctive health outcomes and blood based metabolomic and proteomic profiles. J Transl Med 2024; 22:881. [PMID: 39354608 PMCID: PMC11443809 DOI: 10.1186/s12967-024-05663-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2024] [Accepted: 09/01/2024] [Indexed: 10/03/2024] Open
Abstract
BACKGROUND Specific food preferences can determine an individual's dietary patterns and therefore, may be associated with certain health risks and benefits. METHODS Using food preference questionnaire (FPQ) data from a subset comprising over 180,000 UK Biobank participants, we employed Latent Profile Analysis (LPA) approach to identify the main patterns or profiles among participants. blood biochemistry across groups/profiles was compared using the non-parametric Kruskal-Wallis test. We applied the Limma algorithm for differential abundance analysis on 168 metabolites and 2923 proteins, and utilized the Database for Annotation, Visualization and Integrated Discovery (DAVID) to identify enriched biological processes and pathways. Relative risks (RR) were calculated for chronic diseases and mental conditions per group, adjusting for sociodemographic factors. RESULTS Based on their food preferences, three profiles were termed: the putative Health-conscious group (low preference for animal-based or sweet foods, and high preference for vegetables and fruits), the Omnivore group (high preference for all foods), and the putative Sweet-tooth group (high preference for sweet foods and sweetened beverages). The Health-conscious group exhibited lower risk of heart failure (RR = 0.86, 95%CI 0.79-0.93) and chronic kidney disease (RR = 0.69, 95%CI 0.65-0.74) compared to the two other groups. The Sweet-tooth group had greater risk of depression (RR = 1.27, 95%CI 1.21-1.34), diabetes (RR = 1.15, 95%CI 1.01-1.31), and stroke (RR = 1.22, 95%CI 1.15-1.31) compared to the other two groups. Cancer (overall) relative risk showed little difference across the Health-conscious, Omnivore, and Sweet-tooth groups with RR of 0.98 (95%CI 0.96-1.01), 1.00 (95%CI 0.98-1.03), and 1.01 (95%CI 0.98-1.04), respectively. The Health-conscious group was associated with lower levels of inflammatory biomarkers (e.g., C-reactive Protein) which are also known to be elevated in those with common metabolic diseases (e.g., cardiovascular disease). Other markers modulated in the Health-conscious group, ketone bodies, insulin-like growth factor-binding protein (IGFBP), and Growth Hormone 1 were more abundant, while leptin was less abundant. Further, the IGFBP pathway, which influences IGF1 activity, may be significantly enhanced by dietary choices. CONCLUSIONS These observations align with previous findings from studies focusing on weight loss interventions, which include a reduction in leptin levels. Overall, the Health-conscious group, with preference to healthier food options, has better health outcomes, compared to Sweet-tooth and Omnivore groups.
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Affiliation(s)
- Hana F Navratilova
- School of Biosciences, Faculty of Health and Medical Sciences, University of Surrey, Guildford, GU2 7XH, UK
- Veterinary Health Innovation Engine, School of Veterinary Medicine, University of Surrey, Guildford, GU2 7AL, UK
- Department of Community Nutrition, Faculty of Human Ecology, IPB University, Bogor, 16680, Indonesia
| | - Anthony D Whetton
- School of Biosciences, Faculty of Health and Medical Sciences, University of Surrey, Guildford, GU2 7XH, UK
- Veterinary Health Innovation Engine, School of Veterinary Medicine, University of Surrey, Guildford, GU2 7AL, UK
| | - Nophar Geifman
- Veterinary Health Innovation Engine, School of Veterinary Medicine, University of Surrey, Guildford, GU2 7AL, UK
- School of Health Sciences, Faculty of Health and Medical Sciences, University of Surrey, Guildford, GU2 7YH, UK
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Bora S, Adole PS, Vinod KV, Pillai AA, Ahmed S. GC-MS validation and analysis of targeted plasma metabolites related to carbonyl stress in type 2 diabetes mellitus patients with and without acute coronary syndrome. Biomed Chromatogr 2024; 38:e5952. [PMID: 38966927 DOI: 10.1002/bmc.5952] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2024] [Accepted: 06/18/2024] [Indexed: 07/06/2024]
Abstract
Methylglyoxal (MG) is responsible for advanced glycation end-product formation, the mechanisms leading to diabetes pathogenesis and complications like acute coronary syndrome (ACS). Sugar metabolites, amino acids and fatty acids are possible substrates for MG. The study aimed to measure plasma MG substrate levels using a validated gas chromatography-mass spectrometry (GC-MS) method and explore their association with ACS risk in type 2 diabetes mellitus (T2DM). The study included 150 T2DM patients with ACS as cases and 150 T2DM without ACS as controls for the analysis of glucose, fructose, ribulose, sorbitol, glycerol, pyruvate, lactate, glycine, serine, threonine, C16:0, C16:1, C18:0, C18:1, C18:2, C18:3, C20:0 and C22:6 by GC-MS. Validated GC-MS methods were accurate, precise and sensitive. Cases significantly differed in plasma MG and metabolite levels except for lactate, C16:0, C18:0, C18:2, and C18:3 levels compared with controls. On multivariable logistic regression, plasma C20:0, C18:1, glycine and glycerol levels had increased odds of ACS risk. On multivariate receiver operating characteristic analysis, a model containing plasma C20:0, C16:1, C18:1, C18:2, serine, glycerol, lactate and threonine levels had the highest area under the curve value (0.932) for ACS diagnosis. In conclusion, plasma C20:0, C16:1, C18:1, glycine, glycerol and sorbitol levels were associated with ACS risk in T2DM.
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Affiliation(s)
- Sushmita Bora
- Department of Biochemistry, Jawaharlal Institute of Postgraduate Medical Education and Research, Pondicherry, India
| | - Prashant Shankarrao Adole
- Department of Biochemistry, Jawaharlal Institute of Postgraduate Medical Education and Research, Pondicherry, India
| | - Kolar Vishwanath Vinod
- Department of Medicine, Jawaharlal Institute of Postgraduate Medical Education and Research, Pondicherry, India
| | - Ajith Ananthakrishna Pillai
- Department of Cardiology, Jawaharlal Institute of Postgraduate Medical Education and Research, Pondicherry, India
| | - Shaheer Ahmed
- Department of Cardiology, Jawaharlal Institute of Postgraduate Medical Education and Research, Pondicherry, India
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Myrmel LS, Fjære E, Han M, Jensen BAH, Rolle-Kampczyk U, Danneskiold-Samsøe NB, Ho QT, Smette A, von Bergen M, Xiao L, Kristiansen K, Madsen L. The Food Sources in Western Diets Modulate Obesity Development, Insulin Sensitivity, and the Plasma and Cecal Metabolome in Mice. Mol Nutr Food Res 2024; 68:e2400246. [PMID: 39107912 DOI: 10.1002/mnfr.202400246] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2024] [Revised: 07/10/2024] [Indexed: 08/29/2024]
Abstract
SCOPE Dietary constituents modulate development of obesity and type 2 diabetes. The metabolic impact from different food sources in western diets (WD) on obesity development is not fully elucidated. This study aims to identify dietary sources that differentially affect obesity development and the metabolic processes involved. METHODS AND RESULTS Mice were fed isocaloric WDs with protein and fat from different food groups, including egg and dairy, terrestrial meat, game meat, marine, vegetarian, and a mixture of all. This study evaluates development of obesity, glucose tolerance, insulin sensitivity, and plasma and cecal metabolome. WD based on marine or vegetarian food sources protects male mice from obesity development and insulin resistance, whereas meat-based diets promote obesity. The intake of different food sources induces marked differences in the lipid-related plasma metabolome, particularly impacting phosphatidylcholines. Fifty-nine lipid-related plasma metabolites are positively associated with adiposity and a distinct cecal metabolome is found in mice fed a marine diet. CONCLUSION This study demonstrates differences in obesity development between the food groups. Diet specific metabolomic signatures in plasma and cecum associated with adiposity, where a marine based diet modulates the level of plasma and cecal phosphatidylcholines in addition to preventing obesity development.
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Affiliation(s)
| | - Even Fjære
- Institute of Marine Research, Bergen, 5817, Norway
| | - Mo Han
- BGI Research, Shenzhen, 518083, China
- China National GeneBank, BGI Research, Shenzhen, 518120, China
| | | | - Ulrike Rolle-Kampczyk
- Department of Molecular Toxicology, UFZ-Helmholtz Centre for Environmental Research, 04318, Leipzig, Germany
| | | | - Quang Tri Ho
- Institute of Marine Research, Bergen, 5817, Norway
| | - Anita Smette
- Institute of Marine Research, Bergen, 5817, Norway
| | - Martin von Bergen
- Department of Molecular Toxicology, UFZ-Helmholtz Centre for Environmental Research, 04318, Leipzig, Germany
- Institute of Biochemistry, University of Leipzig, 04103, Leipzig, Germany
| | - Liang Xiao
- BGI Research, Shenzhen, 518083, China
- China National GeneBank, BGI Research, Shenzhen, 518120, China
| | - Karsten Kristiansen
- BGI Research, Shenzhen, 518083, China
- Department of Biology, University of Copenhagen, 2100, Copenhagen, Denmark
| | - Lise Madsen
- Institute of Marine Research, Bergen, 5817, Norway
- Department of Clinical Medicine, University of Bergen, Bergen, 5200, Norway
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Navratilova HF, Lanham-New S, Whetton AD, Geifman N. Associations of Diet with Health Outcomes in the UK Biobank: A Systematic Review. Nutrients 2024; 16:523. [PMID: 38398847 PMCID: PMC10892867 DOI: 10.3390/nu16040523] [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: 01/17/2024] [Revised: 02/09/2024] [Accepted: 02/12/2024] [Indexed: 02/25/2024] Open
Abstract
The UK Biobank is a cohort study that collects data on diet, lifestyle, biomarkers, and health to examine diet-disease associations. Based on the UK Biobank, we reviewed 36 studies on diet and three health conditions: type 2 diabetes (T2DM), cardiovascular disease (CVD), and cancer. Most studies used one-time dietary data instead of repeated 24 h recalls, which may lead to measurement errors and bias in estimating diet-disease associations. We also found that most studies focused on single food groups or macronutrients, while few studies adopted a dietary pattern approach. Several studies consistently showed that eating more red and processed meat led to a higher risk of lung and colorectal cancer. The results suggest that high adherence to "healthy" dietary patterns (consuming various food types, with at least three servings/day of whole grain, fruits, and vegetables, and meat and processed meat less than twice a week) slightly lowers the risk of T2DM, CVD, and colorectal cancer. Future research should use multi-omics data and machine learning models to account for the complexity and interactions of dietary components and their effects on disease risk.
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Affiliation(s)
- Hana F. Navratilova
- School of Biosciences, Faculty of Health and Medical Sciences, University of Surrey, Guildford GU2 7XH, UK; (H.F.N.); (S.L.-N.); (A.D.W.)
- School of Health Sciences, Faculty of Health and Medical Sciences, University of Surrey, Guildford GU2 7YH, UK
- Department of Community Nutrition, Faculty of Human Ecology, IPB University, Bogor 16680, Indonesia
| | - Susan Lanham-New
- School of Biosciences, Faculty of Health and Medical Sciences, University of Surrey, Guildford GU2 7XH, UK; (H.F.N.); (S.L.-N.); (A.D.W.)
| | - Anthony D. Whetton
- School of Biosciences, Faculty of Health and Medical Sciences, University of Surrey, Guildford GU2 7XH, UK; (H.F.N.); (S.L.-N.); (A.D.W.)
- Veterinary Health Innovation Engine, School of Veterinary Medicine, University of Surrey, Guildford GU2 7XH, UK
| | - Nophar Geifman
- School of Health Sciences, Faculty of Health and Medical Sciences, University of Surrey, Guildford GU2 7YH, UK
- Veterinary Health Innovation Engine, School of Veterinary Medicine, University of Surrey, Guildford GU2 7XH, UK
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Singh A, Kinnebrew G, Hsu PC, Weng DY, Song MA, Reisinger SA, McElroy JP, Keller-Hamilton B, Ferketich AK, Freudenheim JL, Shields PG. Untargeted Metabolomics and Body Mass in Adolescents: A Cross-Sectional and Longitudinal Analysis. Metabolites 2023; 13:899. [PMID: 37623843 PMCID: PMC10456720 DOI: 10.3390/metabo13080899] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2023] [Revised: 07/25/2023] [Accepted: 07/27/2023] [Indexed: 08/26/2023] Open
Abstract
Obesity in children and adolescents has increased globally. Increased body mass index (BMI) during adolescence carries significant long-term adverse health outcomes, including chronic diseases such as cardiovascular disease, stroke, diabetes, and cancer. Little is known about the metabolic consequences of changes in BMI in adolescents outside of typical clinical parameters. Here, we used untargeted metabolomics to assess changing BMI in male adolescents. Untargeted metabolomic profiling was performed on urine samples from 360 adolescents using UPLC-QTOF-MS. The study includes a baseline of 235 subjects in a discovery set and 125 subjects in a validation set. Of them, a follow-up of 81 subjects (1 year later) as a replication set was studied. Linear regression analysis models were used to estimate the associations of metabolic features with BMI z-score in the discovery and validation sets, after adjusting for age, race, and total energy intake (kcal) at false-discovery-rate correction (FDR) ≤ 0.1. We identified 221 and 16 significant metabolic features in the discovery and in the validation set, respectively. The metabolites associated with BMI z-score in validation sets are glycylproline, citrulline, 4-vinylsyringol, 3'-sialyllactose, estrone sulfate, carnosine, formiminoglutamic acid, 4-hydroxyproline, hydroxyprolyl-asparagine, 2-hexenoylcarnitine, L-glutamine, inosine, N-(2-Hydroxyphenyl) acetamide glucuronide, and galactosylhydroxylysine. Of those 16 features, 9 significant metabolic features were associated with a positive change in BMI in the replication set 1 year later. Histidine and arginine metabolism were the most affected metabolic pathways. Our findings suggest that obesity and its metabolic outcomes in the urine metabolome of children are linked to altered amino acids, lipid, and carbohydrate metabolism. These identified metabolites may serve as biomarkers and aid in the investigation of obesity's underlying pathological mechanisms. Whether these features are associated with the development of obesity, or a consequence of changing BMI, requires further study.
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Affiliation(s)
- Amarnath Singh
- Comprehensive Cancer Center, The Ohio State University, Columbus, OH 43210-1240, USA; (A.S.); (D.Y.W.)
| | - Garrett Kinnebrew
- Department of Biomedical Informatics, Biomedical Informatics Shared Resources (BISR), The Ohio State University, Columbus, OH 43210-1240, USA;
| | - Ping-Ching Hsu
- Department of Environmental Health Sciences, Fay W. Boozman College of Public Health, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA;
| | - Daniel Y. Weng
- Comprehensive Cancer Center, The Ohio State University, Columbus, OH 43210-1240, USA; (A.S.); (D.Y.W.)
| | - Min-Ae Song
- College of Public Health, The Ohio State University, Columbus, OH 43210-1240, USA; (M.-A.S.); (A.K.F.)
| | - Sarah A. Reisinger
- Center for Tobacco Research, Comprehensive Cancer Center, The Ohio State University, Columbus, OH 43210-1240, USA; (S.A.R.); (B.K.-H.)
| | - Joseph P. McElroy
- Center for Biostatistics, Department of Biomedical Informatics, The Ohio State University, Columbus, OH 43210-1240, USA;
| | - Brittney Keller-Hamilton
- Center for Tobacco Research, Comprehensive Cancer Center, The Ohio State University, Columbus, OH 43210-1240, USA; (S.A.R.); (B.K.-H.)
- Department of Internal Medicine, College of Medicine, The Ohio State University, Columbus, OH 43210-1240, USA
| | - Amy K. Ferketich
- College of Public Health, The Ohio State University, Columbus, OH 43210-1240, USA; (M.-A.S.); (A.K.F.)
| | - Jo L. Freudenheim
- Department of Epidemiology and Environmental Health, University at Buffalo, Buffalo, NY 14214, USA;
| | - Peter G. Shields
- Comprehensive Cancer Center, The Ohio State University, Columbus, OH 43210-1240, USA; (A.S.); (D.Y.W.)
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Affiliation(s)
- Rajavel Elango
- Department of Pediatrics, University of British Columbia
- BC Children's Hospital Research Institute, Vancouver
- School of Population and Public Health, University of British Columbia, British Columbia, Canada
| | - Francois Mariotti
- Université Paris-Saclay, AgroParisTech, INRAE, UMR PNCA, Paris, France
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