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Tessier AJ, Wang F, Liang L, Wittenbecher C, Haslam DE, Eliassen AH, Tobias DK, Li J, Zeleznik OA, Ascherio A, Sun Q, Stampfer MJ, Grodstein F, Rexrode KM, Manson JE, Balasubramanian R, Clish CB, Martínez-González MA, Chavarro JE, Hu FB, Guasch-Ferré M. Plasma metabolites of a healthy lifestyle in relation to mortality and longevity: Four prospective US cohort studies. MED 2024; 5:224-238.e5. [PMID: 38366602 PMCID: PMC10940196 DOI: 10.1016/j.medj.2024.01.010] [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: 06/09/2023] [Revised: 11/09/2023] [Accepted: 01/18/2024] [Indexed: 02/18/2024]
Abstract
BACKGROUND A healthy lifestyle is associated with a lower premature mortality risk and with longer life expectancy. However, the metabolic pathways of a healthy lifestyle and how they relate to mortality and longevity are unclear. We aimed to identify and replicate a healthy lifestyle metabolomic signature and examine how it is related to total and cause-specific mortality risk and longevity. METHODS In four large cohorts with 13,056 individuals and 28-year follow-up, we assessed five healthy lifestyle factors, used liquid chromatography mass spectrometry to profile plasma metabolites, and ascertained deaths with death certificates. The unique healthy lifestyle metabolomic signature was identified using an elastic regression. Multivariable Cox regressions were used to assess associations of the signature with mortality and longevity. FINDINGS The identified healthy lifestyle metabolomic signature was reflective of lipid metabolism pathways. Shorter and more saturated triacylglycerol and diacylglycerol metabolite sets were inversely associated with the healthy lifestyle score, whereas cholesteryl ester and phosphatidylcholine plasmalogen sets were positively associated. Participants with a higher healthy lifestyle metabolomic signature had a 17% lower risk of all-cause mortality, 19% for cardiovascular disease mortality, and 17% for cancer mortality and were 25% more likely to reach longevity. The healthy lifestyle metabolomic signature explained 38% of the association between the self-reported healthy lifestyle score and total mortality risk and 49% of the association with longevity. CONCLUSIONS This study identifies a metabolomic signature that measures adherence to a healthy lifestyle and shows prediction of total and cause-specific mortality and longevity. FUNDING This work was funded by the NIH, CIHR, AHA, Novo Nordisk Foundation, and SciLifeLab.
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Affiliation(s)
- Anne-Julie Tessier
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
| | - Fenglei Wang
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Liming Liang
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | | | - Danielle E Haslam
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - A Heather Eliassen
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Deirdre K Tobias
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Division of Preventive Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Jun Li
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Division of Preventive Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Oana A Zeleznik
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Alberto Ascherio
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Qi Sun
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Meir J Stampfer
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Francine Grodstein
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
| | - Kathryn M Rexrode
- Division of Women's Health, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - JoAnn E Manson
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA; Division of Preventive Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Raji Balasubramanian
- Department of Biostatistics and Epidemiology, University of Massachusetts Amherst, Amherst, MA, USA
| | - Clary B Clish
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Miguel A Martínez-González
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Department of Preventive Medicine and Public Health, University of Navarra, Pamplona, Spain
| | - Jorge E Chavarro
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Frank B Hu
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Marta Guasch-Ferré
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Department of Public Health and Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
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Wen X, Fretts AM, Miao G, Malloy KM, Zhang Y, Umans JG, Cole SA, Best LG, Fiehn O, Zhao J. Plasma lipidomic markers of diet quality are associated with incident coronary heart disease in American Indian adults: the Strong Heart Family Study. Am J Clin Nutr 2024; 119:748-755. [PMID: 38160800 DOI: 10.1016/j.ajcnut.2023.12.024] [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: 10/04/2023] [Revised: 12/15/2023] [Accepted: 12/28/2023] [Indexed: 01/03/2024] Open
Abstract
BACKGROUND Identifying lipidomic markers of diet quality is needed to inform the development of biomarkers of diet, and to understand the mechanisms driving the diet- coronary heart disease (CHD) association. OBJECTIVES This study aimed to identify lipidomic markers of diet quality and examine whether these lipids are associated with incident CHD. METHODS Using liquid chromatography-mass spectrometry, we measured 1542 lipid species from 1694 American Indian adults (aged 18-75 years, 62% female) in the Strong Heart Family Study. Participants were followed up for development of CHD through 2020. Information on the past year diet was collected using the Block Food Frequency Questionnaire, and diet quality was assessed using the Alternative Healthy Eating Index-2010 (AHEI). Mixed-effects linear regression was used to identify individual lipids cross-sectionally associated with AHEI. In prospective analysis, Cox frailty model was used to estimate the hazard ratio (HR) of each AHEI-related lipid for incident CHD. All models were adjusted for age, sex, center, education, body mass index, smoking, alcohol drinking, level of physical activity, energy intake, diabetes, hypertension, and use of lipid-lowering drugs. Multiple testing was controlled at a false discovery rate of <0.05. RESULTS Among 1542 lipid species measured, 71 lipid species (23 known), including acylcarnitine, cholesterol esters, glycerophospholipids, sphingomyelins and triacylglycerols, were associated with AHEI. Most of the identified lipids were associated with consumption of ω-3 (n-3) fatty acids. In total, 147 participants developed CHD during a mean follow-up of 17.8 years. Among the diet-related lipids, 10 lipids [5 known: cholesterol ester (CE)(22:5)B, phosphatidylcholine (PC)(p-14:0/22:1)/PC(o-14:0/22:1), PC(p-38:3)/PC(o-38:4)B, phosphatidylethanolamine (PE)(p-18:0/20:4)/PE(o-18:0/20:4), and sphingomyelin (d36:2)A] were associated with incident CHD. On average, each standard deviation increase in the baseline level of these 5 lipids was associated with 17%-23% increased risk of CHD (from HR: 1.17; 95% CI: 1, 1.36; to HR: 1.23; 95% CI: 1.05, 1.43). CONCLUSIONS In this study, lipidomic markers of diet quality in American Indian adults are found. Some diet-related lipids are associated with risk of CHD beyond established risk factors.
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Affiliation(s)
- Xiaoxiao Wen
- Department of Epidemiology, College of Public Health and Health Professions and College of Medicine, University of Florida, Gainesville, FL, United States; Center for Genetic Epidemiology and Bioinformatics, University of Florida, Gainesville, FL, United States
| | - Amanda M Fretts
- Department of Epidemiology, University of Washington, Seattle, WA, United States
| | - Guanhong Miao
- Department of Epidemiology, College of Public Health and Health Professions and College of Medicine, University of Florida, Gainesville, FL, United States; Center for Genetic Epidemiology and Bioinformatics, University of Florida, Gainesville, FL, United States
| | - Kimberly M Malloy
- Center for American Indian Health Research, Department of Biostatistics and Epidemiology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States
| | - Ying Zhang
- Center for American Indian Health Research, Department of Biostatistics and Epidemiology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States
| | - Jason G Umans
- Biomarker, Biochemistry, and Biorepository Core, MedStar Health Research Institute, Hyattsville, MD, United States; Georgetown-Howard Universities Center for Clinical and Translational Science, Washington, DC, United States
| | - Shelley A Cole
- Population Health, Texas Biomedical Research Institute, San Antonio, TX, United States
| | - Lyle G Best
- Missouri Breaks Industries Research, Timber Lake, SD, United States
| | - Oliver Fiehn
- West Coast Metabolomics Center, University of California-Davis, Davis, CA, United States
| | - Jinying Zhao
- Department of Epidemiology, College of Public Health and Health Professions and College of Medicine, University of Florida, Gainesville, FL, United States; Center for Genetic Epidemiology and Bioinformatics, University of Florida, Gainesville, FL, United States.
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3
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Hill EB, Reisdorph RM, Rasolofomanana-Rajery S, Michel C, Khajeh-Sharafabadi M, Doenges KA, Weaver N, Quinn K, Sutliff AK, Tang M, Borengasser SJ, Frank DN, O'Connor LE, Campbell WW, Krebs NF, Hendricks AE, Reisdorph NA. Salmon Food-Specific Compounds and Their Metabolites Increase in Human Plasma and Are Associated with Cardiometabolic Health Indicators Following a Mediterranean-Style Diet Intervention. J Nutr 2024; 154:26-40. [PMID: 37918675 PMCID: PMC10808825 DOI: 10.1016/j.tjnut.2023.10.024] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Revised: 09/25/2023] [Accepted: 10/19/2023] [Indexed: 11/04/2023] Open
Abstract
BACKGROUND Nutrimetabolomics allows for the comprehensive analysis of foods and human biospecimens to identify biomarkers of intake and begin to probe their associations with health. Salmon contains hundreds of compounds that may provide cardiometabolic benefits. OBJECTIVES We used untargeted metabolomics to identify salmon food-specific compounds (FSCs) and their predicted metabolites that were found in plasma after a salmon-containing Mediterranean-style (MED) diet intervention. Associations between changes in salmon FSCs and changes in cardiometabolic health indicators (CHIs) were also explored. METHODS For this secondary analysis of a randomized, crossover, controlled feeding trial, 41 participants consumed MED diets with 2 servings of salmon per week for 2 5-wk periods. CHIs were assessed, and fasting plasma was collected pre- and postintervention. Plasma, salmon, and 99 MED foods were analyzed using liquid chromatography-mass spectrometry-based metabolomics. Compounds were characterized as salmon FSCs if detected in all salmon replicates but none of the other foods. Metabolites of salmon FSCs were predicted using machine learning. For salmon FSCs and metabolites found in plasma, linear mixed-effect models were used to assess change from pre- to postintervention and associations with changes in CHIs. RESULTS Relative to the other 99 MED foods, there were 508 salmon FSCs with 237 unique metabolites. A total of 143 salmon FSCs and 106 metabolites were detected in plasma. Forty-eight salmon FSCs and 30 metabolites increased after the intervention (false discovery rate <0.05). Increases in 2 annotated salmon FSCs and 2 metabolites were associated with improvements in CHIs, including total cholesterol, low-density lipoprotein cholesterol, triglycerides, and apolipoprotein B. CONCLUSIONS A data-driven nutrimetabolomics strategy identified salmon FSCs and their predicted metabolites that were detectable in plasma and changed after consumption of a salmon-containing MED diet. Findings support this approach for the discovery of compounds in foods that may serve, upon further validation, as biomarkers or act as bioactive components influential to health. The trials supporting this work were registered at NCT02573129 (Mediterranean-style diet intervention) and NCT05500976 (ongoing clinical trial).
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Affiliation(s)
- Emily B Hill
- Department of Pediatrics, Section of Nutrition, University of Colorado Anschutz Medical Campus, Aurora, CO, United States
| | - Richard M Reisdorph
- Department of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences, University of Colorado Anschutz Medical Campus, Aurora, CO, United States
| | - Sakaiza Rasolofomanana-Rajery
- Department of Mathematical and Statistical Sciences, University of Colorado Denver, Denver, CO, United States; Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO, United States
| | - Cole Michel
- Department of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences, University of Colorado Anschutz Medical Campus, Aurora, CO, United States
| | - Mobin Khajeh-Sharafabadi
- Department of Mathematical and Statistical Sciences, University of Colorado Denver, Denver, CO, United States
| | - Katrina A Doenges
- Department of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences, University of Colorado Anschutz Medical Campus, Aurora, CO, United States
| | - Nicholas Weaver
- Department of Mathematical and Statistical Sciences, University of Colorado Denver, Denver, CO, United States
| | - Kevin Quinn
- Department of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences, University of Colorado Anschutz Medical Campus, Aurora, CO, United States
| | - Aimee K Sutliff
- Department of Pediatrics, Section of Nutrition, University of Colorado Anschutz Medical Campus, Aurora, CO, United States; Department of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences, University of Colorado Anschutz Medical Campus, Aurora, CO, United States
| | - Minghua Tang
- Department of Pediatrics, Section of Nutrition, University of Colorado Anschutz Medical Campus, Aurora, CO, United States
| | - Sarah J Borengasser
- Department of Pediatrics, Section of Nutrition, University of Colorado Anschutz Medical Campus, Aurora, CO, United States
| | - Daniel N Frank
- Division of Infectious Diseases, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, United States
| | - Lauren E O'Connor
- USDA, Agricultural Research Service, Beltsville Human Nutrition Research Center, Food Components and Health Laboratory, Beltsville, MD, United States
| | - Wayne W Campbell
- Department of Nutrition Science, Purdue University, West Lafayette, IN, United States
| | - Nancy F Krebs
- Department of Pediatrics, Section of Nutrition, University of Colorado Anschutz Medical Campus, Aurora, CO, United States
| | - Audrey E Hendricks
- Department of Mathematical and Statistical Sciences, University of Colorado Denver, Denver, CO, United States; Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO, United States.
| | - Nichole A Reisdorph
- Department of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences, University of Colorado Anschutz Medical Campus, Aurora, CO, United States.
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Mi MY, Gajjar P, Walker ME, Miller P, Xanthakis V, Murthy VL, Larson MG, Vasan RS, Shah RV, Lewis GD, Nayor M. Association of healthy dietary patterns and cardiorespiratory fitness in the community. Eur J Prev Cardiol 2023; 30:1450-1461. [PMID: 37164358 PMCID: PMC10562138 DOI: 10.1093/eurjpc/zwad113] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Revised: 04/04/2023] [Accepted: 04/07/2023] [Indexed: 05/12/2023]
Abstract
AIMS To evaluate the associations of dietary indices and quantitative cardiorespiratory fitness (CRF) measures in a large, community-based sample harnessing metabolomic profiling to interrogate shared biology. METHODS AND RESULTS Framingham Heart Study (FHS) participants underwent maximum effort cardiopulmonary exercise tests for CRF quantification (via peak VO2) and completed semi-quantitative food frequency questionnaires. Dietary quality was assessed by the Alternative Healthy Eating Index (AHEI) and Mediterranean-style Diet Score (MDS), and fasting blood concentrations of 201 metabolites were quantified. In 2380 FHS participants (54 ± 9 years, 54% female, body mass index 28 ± 5 kg/m2), 1 SD higher AHEI and MDS were associated with 5.2% (1.2 mL/kg/min, 95% CI 4.3-6.0%, P < 0.0001) and 4.5% (1.0 mL/kg/min, 95% CI 3.6-5.3%, P < 0.0001) greater peak VO2 in linear models adjusted for age, sex, total daily energy intake, cardiovascular risk factors, and physical activity. In participants with metabolite profiling (N = 1154), 24 metabolites were concordantly associated with both dietary indices and peak VO2 in multivariable-adjusted linear models (FDR < 5%). Metabolites that were associated with lower CRF and poorer dietary quality included C6 and C7 carnitines, C16:0 ceramide, and dimethylguanidino valeric acid, and metabolites that were positively associated with higher CRF and favourable dietary quality included C38:7 phosphatidylcholine plasmalogen and C38:7 and C40:7 phosphatidylethanolamine plasmalogens. CONCLUSION Higher diet quality is associated with greater CRF cross-sectionally in a middle-aged community-dwelling sample, and metabolites highlight potential shared favourable effects on cardiometabolic health.
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Affiliation(s)
- Michael Y Mi
- Division of Cardiovascular Medicine, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Priya Gajjar
- Section of Cardiovascular Medicine, Department of Medicine, Boston University School of Medicine, Suite L-516, Boston, MA 02118, USA
| | - Maura E Walker
- Section of Preventive Medicine and Epidemiology, Department of Medicine, Boston University School of Medicine, Suite L-516, Boston, MA 02118, USA
- Department of Health Sciences, Sargent College of Health and Rehabilitation Sciences, Boston University, Boston, MA, USA
| | - Patricia Miller
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Vanessa Xanthakis
- Section of Preventive Medicine and Epidemiology, Department of Medicine, Boston University School of Medicine, Suite L-516, Boston, MA 02118, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- Framingham Heart Study, Framingham, 73 Mt. Wayte Avenue, Framingham, MA 01702, USA
| | - Venkatesh L Murthy
- Division of Cardiovascular Medicine, Department of Medicine, and Frankel Cardiovascular Center, University of Michigan, Ann Arbor, MI, USA
| | - Martin G Larson
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- Framingham Heart Study, Framingham, 73 Mt. Wayte Avenue, Framingham, MA 01702, USA
| | - Ramachandran S Vasan
- Section of Cardiovascular Medicine, Department of Medicine, Boston University School of Medicine, Suite L-516, Boston, MA 02118, USA
- Section of Preventive Medicine and Epidemiology, Department of Medicine, Boston University School of Medicine, Suite L-516, Boston, MA 02118, USA
- Framingham Heart Study, Framingham, 73 Mt. Wayte Avenue, Framingham, MA 01702, USA
- University of Texas School of Public Health San Antonio, and Departments of Medicine and Population Health Sciences, University of Texas Health Science Center, San Antonio, TX, USA
| | - Ravi V Shah
- Vanderbilt Translational and Clinical Research Center, Cardiology Division, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Gregory D Lewis
- Cardiology Division and Pulmonary Critical Care Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Matthew Nayor
- Section of Cardiovascular Medicine, Department of Medicine, Boston University School of Medicine, Suite L-516, Boston, MA 02118, USA
- Section of Preventive Medicine and Epidemiology, Department of Medicine, Boston University School of Medicine, Suite L-516, Boston, MA 02118, USA
- Framingham Heart Study, Framingham, 73 Mt. Wayte Avenue, Framingham, MA 01702, USA
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Zhang T, Naudin S, Hong HG, Albanes D, Männistö S, Weinstein SJ, Moore SC, Stolzenberg-Solomon RZ. Dietary Quality and Circulating Lipidomic Profiles in 2 Cohorts of Middle-Aged and Older Male Finnish Smokers and American Populations. J Nutr 2023; 153:2389-2400. [PMID: 37328109 PMCID: PMC10493471 DOI: 10.1016/j.tjnut.2023.06.010] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2023] [Revised: 06/02/2023] [Accepted: 06/07/2023] [Indexed: 06/18/2023] Open
Abstract
BACKGROUND Higher dietary quality is associated with lower disease risks and has not been examined extensively with lipidomic profiles. OBJECTIVES Our goal was to examine associations of the Healthy Eating Index (HEI)-2015, Alternate HEI-2010 (AHEI-2010), and alternate Mediterranean Diet Index (aMED) diet quality indices with serum lipidomic profiles. METHODS We conducted a cross-sectional analysis of HEI-2015, AHEI-2010, and aMED with lipidomic profiles from 2 nested case-control studies within the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial (n = 627) and the Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study (n = 711). We used multivariable linear regression to determine associations of the indices, derived from baseline food-frequency questionnaires (Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial: 1993-2001, Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study: 1985-1988) with serum concentrations of 904 lipid species and 252 fatty acids (FAs) across 15 lipid classes and 28 total FAs, within each cohort and meta-analyzed results using fixed-effect models for lipids significant at Bonferroni-corrected threshold in common in both cohorts. RESULTS Adherence to HEI-2015, AHEI-2010, or aMED was associated positively with 31, 41, and 54 lipid species and 8, 6, and 10 class-specific FAs and inversely with 2, 8, and 34 lipid species and 1, 3, and 5 class-specific FAs, respectively. Twenty-five lipid species and 5 class-specific FAs were common to all indices, predominantly triacylglycerols, FA22:6 [docosahexaenoic acid (DHA)]-containing species, and DHA. All indices were positively associated with total FA22:6. AHEI-2010 and aMED were inversely associated with total FA18:1 (oleic acid) and total FA17:0 (margaric acid), respectively. The identified lipids were most associated with components of seafood and plant proteins and unsaturated:saturated fat ratio in HEI-2015; eicosapentaenoic acid plus DHA in AHEI-2010; and fish and monounsaturated:saturated fat ratio in aMED. CONCLUSIONS Adherence to HEI-2015, AHEI-2010, and aMED is associated with serum lipidomic profiles, mostly triacylglycerols or FA22:6-containing species, which are related to seafood and plant proteins, eicosapentaenoic acid-DHA, fish, or fat ratio index components.
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Affiliation(s)
- Ting Zhang
- Metabolic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, Rockville, MD, United States
| | - Sabine Naudin
- Metabolic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, Rockville, MD, United States; Nutrition and Metabolism Branch, International Agency for Research on Cancer, World Health Organization, Lyon, France
| | - Hyokyoung G Hong
- Biostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, Rockville, MD, United States
| | - Demetrius Albanes
- Metabolic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, Rockville, MD, United States
| | - Satu Männistö
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Stephanie J Weinstein
- Metabolic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, Rockville, MD, United States
| | - Steven C Moore
- Metabolic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, Rockville, MD, United States
| | - Rachael Z Stolzenberg-Solomon
- Metabolic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, Rockville, MD, United States.
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6
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Näätänen M, Kårlund A, Mikkonen S, Klåvus A, Savolainen O, Lehtonen M, Karhunen L, Hanhineva K, Kolehmainen M. Metabolic profiles reflect weight loss maintenance and the composition of diet after very-low-energy diet. Clin Nutr 2023; 42:1126-1141. [PMID: 37268538 DOI: 10.1016/j.clnu.2023.05.011] [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: 12/16/2022] [Revised: 05/08/2023] [Accepted: 05/12/2023] [Indexed: 06/04/2023]
Abstract
BACKGROUND & AIMS Diet and weight loss affect circulating metabolome. However, metabolite profiles induced by different weight loss maintenance diets and underlying longer term weight loss maintenance remain unknown. Herein, we investigated after-weight-loss metabolic signatures of two isocaloric 24-wk weight maintenance diets differing in satiety value due to dietary fibre, protein and fat contents and identified metabolite features that associated with successful weight loss maintenance. METHODS Non-targeted LC-MS metabolomics approach was used to analyse plasma metabolites of 79 women and men (mean age ± SD 49.7 ± 9.0 years; BMI 34.2 ± 2.5 kg/m2) participating in a weight management study. Participants underwent a 7-week very-low-energy diet (VLED) and were thereafter randomised into two groups for a 24-week weight maintenance phase. Higher satiety food (HSF) group consumed high-fibre, high-protein, and low-fat products, while lower satiety food (LSF) group consumed isocaloric low-fibre products with average protein and fat content as a part of their weight maintenance diets. Plasma metabolites were analysed before the VLED and before and after the weight maintenance phase. Metabolite features discriminating HSF and LSF groups were annotated. We also analysed metabolite features that discriminated participants who maintained ≥10% weight loss (HWM) and participants who maintained <10% weight loss (LWM) at the end of the study, irrespective of the diet. Finally, we assessed robust linear regression between metabolite features and anthropometric and food group variables. RESULTS We annotated 126 metabolites that discriminated the HSF and LSF groups and HWM and LWM groups (p < 0.05). Compared to LSF, the HSF group had lower levels of several amino acids, e.g. glutamine, arginine, and glycine, short-, medium- and long-chain acylcarnitines (CARs), odd- and even-chain lysoglycerophospholipids, and higher levels of fatty amides. Compared to LWM, the HWM group in general showed higher levels of glycerophospholipids with a saturated long-chain and a C20:4 fatty acid tail, and unsaturated free fatty acids (FFAs). Changes in several saturated odd- and even-chain LPCs and LPEs and fatty amides were associated with the intake of many food groups, particularly grain and dairy products. Increase in several (lyso)glycerophospholipids was associated with decrease in body weight and adiposity. Increased short- and medium-chain CARs were related to decreased body fat-free mass. CONCLUSIONS Our results show that isocaloric weight maintenance diets differing in dietary fibre, protein, and fat content affected amino acid and lipid metabolism. Increased abundances of several phospholipid species and FFAs were related with greater weight loss maintenance. Our findings indicate common and distinct metabolites for weight and dietary related variables in the context of weight reduction and weight management. The study was registered in isrctn.org with identifier 67529475.
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Affiliation(s)
- Mari Näätänen
- Department of Clinical Nutrition, Institute of Public Health and Clinical Nutrition, University of Eastern Finland, 70211 Kuopio, Finland.
| | - Anna Kårlund
- Department of Clinical Nutrition, Institute of Public Health and Clinical Nutrition, University of Eastern Finland, 70211 Kuopio, Finland; Department of Life Technologies, Food Sciences Unit, University of Turku, 20014 Turku, Finland.
| | - Santtu Mikkonen
- Department of Applied Physics, University of Eastern Finland, 70211 Kuopio, Finland.
| | - Anton Klåvus
- Department of Clinical Nutrition, Institute of Public Health and Clinical Nutrition, University of Eastern Finland, 70211 Kuopio, Finland.
| | - Otto Savolainen
- Department of Clinical Nutrition, Institute of Public Health and Clinical Nutrition, University of Eastern Finland, 70211 Kuopio, Finland; Department of Biology and Biological Engineering, Chalmers Mass Spectrometry Infrastructure, Chalmers University of Technology, Sweden.
| | - Marko Lehtonen
- School of Pharmacy, University of Eastern Finland, 70211 Kuopio, Finland.
| | - Leila Karhunen
- Department of Clinical Nutrition, Institute of Public Health and Clinical Nutrition, University of Eastern Finland, 70211 Kuopio, Finland.
| | - Kati Hanhineva
- Department of Clinical Nutrition, Institute of Public Health and Clinical Nutrition, University of Eastern Finland, 70211 Kuopio, Finland; Department of Life Technologies, Food Sciences Unit, University of Turku, 20014 Turku, Finland.
| | - Marjukka Kolehmainen
- Department of Clinical Nutrition, Institute of Public Health and Clinical Nutrition, University of Eastern Finland, 70211 Kuopio, Finland.
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7
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Noerman S, Landberg R. Blood metabolite profiles linking dietary patterns with health-Toward precision nutrition. J Intern Med 2023; 293:408-432. [PMID: 36484466 DOI: 10.1111/joim.13596] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Diet is one of the most important exposures that may affect health throughout life span. Investigations on dietary patterns rather than single food components are gaining in popularity because they take the complexity of the whole dietary context into account. Adherence to such dietary patterns can be measured by using metabolomics, which allows measurements of thousands of molecules simultaneously. Derived metabolite signatures of dietary patterns may reflect the consumption of specific groups of foods or their constituents originating from the dietary pattern per se, or the physiological response toward the food-derived metabolites, their interaction with endogenous metabolism, and exogenous factors such as gut microbiota. Here, we review and discuss blood metabolite fingerprints of healthy dietary patterns. The plasma concentration of several food-derived metabolites-such as betaines from whole grains and n - 3 polyunsaturated fatty acids and furan fatty acids from fish-seems to consistently reflect the intake of common foods of several healthy dietary patterns. The metabolites reflecting shared features of different healthy food indices form biomarker panels for which specific, targeted assays could be developed. The specificity of such biomarker panels would need to be validated, and proof-of-concept feeding trials are needed to evaluate to what extent the panels may mediate the effects of dietary patterns on disease risk indicators or if they are merely food intake biomarkers. Metabolites mediating health effects may represent novel targets for precision prevention strategies of clinical relevance to be verified in future studies.
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Affiliation(s)
- Stefania Noerman
- Department of Biology and Biological Engineering, Division of Food and Nutrition Science, Chalmers University of Technology, Gothenburg, Sweden
| | - Rikard Landberg
- Department of Biology and Biological Engineering, Division of Food and Nutrition Science, Chalmers University of Technology, Gothenburg, Sweden
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8
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Mi MY, Gajjar P, Walker ME, Miller P, Xanthakis V, Murthy VL, Larson MG, Vasan RS, Shah RV, Lewis GD, Nayor M. Association of Healthy Dietary Patterns and Cardiorespiratory Fitness in the Community. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.02.09.23285714. [PMID: 36798343 PMCID: PMC9934801 DOI: 10.1101/2023.02.09.23285714] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/12/2023]
Abstract
Aims To evaluate the associations of dietary indices and quantitative CRF measures in a large, community-based sample harnessing metabolomic profiling to interrogate shared biology. Methods Framingham Heart Study (FHS) participants underwent maximum effort cardiopulmonary exercise tests for CRF quantification (via peak VO 2 ) and completed semi-quantitative FFQs. Dietary quality was assessed by the Alternative Healthy Eating Index (AHEI) and Mediterranean-style Diet Score (MDS), and fasting blood concentrations of 201 metabolites were quantified. Results In 2380 FHS participants (54±9 years, 54% female, BMI 28±5 kg/m 2 ), 1-SD higher AHEI and MDS were associated with 5.1% (1.2 ml/kg/min, p<0.0001) and 4.4% (1.0 ml/kg/min, p<0.0001) greater peak VO 2 in linear models adjusted for age, sex, total energy intake, cardiovascular risk factors, and physical activity. In participants with metabolite profiling (N=1154), 24 metabolites were concordantly associated with both dietary indices and peak VO 2 in multivariable-adjusted linear models (FDR<5%). These metabolites included C6 and C7 carnitines, C16:0 ceramide, and dimethylguanidino valeric acid, which were higher with lower CRF and poorer dietary quality and are known markers of insulin resistance and cardiovascular risk. Conversely, C38:7 phosphatidylcholine plasmalogen and C38:7 and C40:7 phosphatidylethanolamine plasmalogens were associated with higher CRF and favorable dietary quality and may link to lower cardiometabolic risk. Conclusion Higher diet quality is associated with greater CRF cross-sectionally in a middle-aged community-dwelling sample, and metabolites highlight potential shared favorable effects on health.
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9
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Kang JH, Zeleznik O, Frueh L, Lasky-Su J, Eliassen AH, Clish C, Rosner BA, Pasquale LR, Wiggs JL. Prediagnostic Plasma Metabolomics and the Risk of Exfoliation Glaucoma. Invest Ophthalmol Vis Sci 2022; 63:15. [PMID: 35951322 PMCID: PMC9386645 DOI: 10.1167/iovs.63.9.15] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/05/2022] Open
Abstract
Purpose The etiology of exfoliation glaucoma (XFG) is poorly understood. We aimed to identify a prediagnostic plasma metabolomic signature associated with XFG. Methods We conducted a 1:1 matched case-control study nested within the Nurses' Health Study and Health Professionals Follow-up Study. We collected blood samples in 1989-1990 (Nurses' Health Study) and 1993-1995 (Health Professionals Follow-up Study). We identified 205 incident XFG cases through 2016 (average time to diagnosis from blood draw = 11.8 years) who self-reported glaucoma and were confirmed as XFG cases with medical records. We profiled plasma metabolites using liquid chromatography-mass spectrometry. We evaluated 379 known metabolites (transformed for normality using probit scores) using multiple conditional logistic models. Metabolite set enrichment analysis was used to identify metabolite classes associated with XFG. To adjust for multiple comparisons, we used number of effective tests (NEF) and the false discovery rate (FDR). Results Mean age of cases (n = 205) at diagnosis was 71 years; 85% were women and more than 99% were Caucasian; controls (n = 205) reported eye examinations as of the matched cases' index date. Thirty-three metabolites were nominally significantly associated with XFG (P < 0.05), and 4 metabolite classes were FDR-significantly associated. We observed positive associations for lysophosphatidylcholines (FDR = 0.02) and phosphatidylethanolamine plasmalogens (FDR = 0.004) and inverse associations for triacylglycerols (FDR < 0.0001) and steroids (FDR = 0.03). In particular, the multivariable-adjusted odds ratio with each 1 standard deviation higher plasma cortisone levels was 0.49 (95% confidence interval, 0.32-0.74; NEF = 0.05). Conclusions In plasma from a decade before diagnosis, lysophosphatidylcholines and phosphatidylethanolamine plasmalogens were positively associated and triacylglycerols and steroids (e.g., cortisone) were inversely associated with XFG risk.
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Affiliation(s)
- Jae H Kang
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, United States
| | - Oana Zeleznik
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, United States
| | - Lisa Frueh
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, United States
| | - Jessica Lasky-Su
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, United States
| | - A Heather Eliassen
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, United States
- Departments of Nutrition and Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States
| | - Clary Clish
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, Massachusetts, United States
| | - Bernard A Rosner
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, United States
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States
| | - Louis R Pasquale
- Department of Ophthalmology, Icahn School of Medicine at Mount Sinai, New York, New York, United States
| | - Janey L Wiggs
- Department of Ophthalmology, Massachusetts Eye and Ear, Harvard Medical School, Boston, Massachusetts, United States
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10
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Castellano-Escuder P, González-Domínguez R, Vaillant MF, Casas-Agustench P, Hidalgo-Liberona N, Estanyol-Torres N, Wilson T, Beckmann M, Lloyd AJ, Oberli M, Moinard C, Pison C, Borel JC, Joyeux-Faure M, Sicard M, Artemova S, Terrisse H, Dancer P, Draper J, Sánchez-Pla A, Andres-Lacueva C. Assessing Adherence to Healthy Dietary Habits Through the Urinary Food Metabolome: Results From a European Two-Center Study. Front Nutr 2022; 9:880770. [PMID: 35757242 PMCID: PMC9219016 DOI: 10.3389/fnut.2022.880770] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2022] [Accepted: 05/16/2022] [Indexed: 11/13/2022] Open
Abstract
Background Diet is one of the most important modifiable lifestyle factors in human health and in chronic disease prevention. Thus, accurate dietary assessment is essential for reliably evaluating adherence to healthy habits. Objectives The aim of this study was to identify urinary metabolites that could serve as robust biomarkers of diet quality, as assessed through the Alternative Healthy Eating Index (AHEI-2010). Design We set up two-center samples of 160 healthy volunteers, aged between 25 and 50, living as a couple or family, with repeated urine sampling and dietary assessment at baseline, and 6 and 12 months over a year. Urine samples were subjected to large-scale metabolomics analysis for comprehensive quantitative characterization of the food-related metabolome. Then, lasso regularized regression analysis and limma univariate analysis were applied to identify those metabolites associated with the AHEI-2010, and to investigate the reproducibility of these associations over time. Results Several polyphenol microbial metabolites were found to be positively associated with the AHEI-2010 score; urinary enterolactone glucuronide showed a reproducible association at the three study time points [false discovery rate (FDR): 0.016, 0.014, 0.016]. Furthermore, other associations were found between the AHEI-2010 and various metabolites related to the intake of coffee, red meat and fish, whereas other polyphenol phase II metabolites were associated with higher AHEI-2010 scores at one of the three time points investigated (FDR < 0.05 or β ≠ 0). Conclusion We have demonstrated that urinary metabolites, and particularly microbiota-derived metabolites, could serve as reliable indicators of adherence to healthy dietary habits. Clinical Trail Registration www.ClinicalTrials.gov, Identifier: NCT03169088.
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Affiliation(s)
- Pol Castellano-Escuder
- Nutrimetabolomics Laboratory, Department of Nutrition, Food Sciences and Gastronomy, XIA, INSA, Faculty of Pharmacy and Food Sciences, University of Barcelona, Barcelona, Spain.,CIBER Fragilidad y Envejecimiento Saludable (CIBERfes), Instituto de Salud Carlos III, Madrid, Spain.,Statistics and Bioinformatics Research Group, Department of Genetics, Microbiology and Statistics, University of Barcelona, Barcelona, Spain
| | - Raúl González-Domínguez
- Nutrimetabolomics Laboratory, Department of Nutrition, Food Sciences and Gastronomy, XIA, INSA, Faculty of Pharmacy and Food Sciences, University of Barcelona, Barcelona, Spain.,CIBER Fragilidad y Envejecimiento Saludable (CIBERfes), Instituto de Salud Carlos III, Madrid, Spain
| | - Marie-France Vaillant
- Laboratory of Fundamental and Applied Bioenergetics, Inserm1055, Grenoble, France.,Service Hospitalier Universitaire Pneumologie Physiologie, CHU Grenoble Alpes, Grenoble, France
| | - Patricia Casas-Agustench
- Nutrimetabolomics Laboratory, Department of Nutrition, Food Sciences and Gastronomy, XIA, INSA, Faculty of Pharmacy and Food Sciences, University of Barcelona, Barcelona, Spain.,CIBER Fragilidad y Envejecimiento Saludable (CIBERfes), Instituto de Salud Carlos III, Madrid, Spain
| | - Nicole Hidalgo-Liberona
- Nutrimetabolomics Laboratory, Department of Nutrition, Food Sciences and Gastronomy, XIA, INSA, Faculty of Pharmacy and Food Sciences, University of Barcelona, Barcelona, Spain.,CIBER Fragilidad y Envejecimiento Saludable (CIBERfes), Instituto de Salud Carlos III, Madrid, Spain
| | - Núria Estanyol-Torres
- Nutrimetabolomics Laboratory, Department of Nutrition, Food Sciences and Gastronomy, XIA, INSA, Faculty of Pharmacy and Food Sciences, University of Barcelona, Barcelona, Spain.,CIBER Fragilidad y Envejecimiento Saludable (CIBERfes), Instituto de Salud Carlos III, Madrid, Spain
| | - Thomas Wilson
- Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Aberystwyth, United Kingdom
| | - Manfred Beckmann
- Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Aberystwyth, United Kingdom
| | - Amanda J Lloyd
- Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Aberystwyth, United Kingdom
| | | | - Christophe Moinard
- Laboratory of Fundamental and Applied Bioenergetics, Inserm1055, Grenoble, France
| | - Christophe Pison
- Laboratory of Fundamental and Applied Bioenergetics, Inserm1055, Grenoble, France.,Service Hospitalier Universitaire Pneumologie Physiologie, CHU Grenoble Alpes, Grenoble, France.,Université Grenoble Alpes, Grenoble, France
| | - Jean-Christian Borel
- Laboratory of Fundamental and Applied Bioenergetics, Inserm1055, Grenoble, France
| | | | | | | | - Hugo Terrisse
- Laboratory of Fundamental and Applied Bioenergetics, Inserm1055, Grenoble, France.,TIMC-MESP Laboratory, University of Grenoble Alpes, Grenoble, France
| | | | - John Draper
- Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Aberystwyth, United Kingdom
| | - Alex Sánchez-Pla
- CIBER Fragilidad y Envejecimiento Saludable (CIBERfes), Instituto de Salud Carlos III, Madrid, Spain.,Statistics and Bioinformatics Research Group, Department of Genetics, Microbiology and Statistics, University of Barcelona, Barcelona, Spain
| | - Cristina Andres-Lacueva
- Nutrimetabolomics Laboratory, Department of Nutrition, Food Sciences and Gastronomy, XIA, INSA, Faculty of Pharmacy and Food Sciences, University of Barcelona, Barcelona, Spain.,CIBER Fragilidad y Envejecimiento Saludable (CIBERfes), Instituto de Salud Carlos III, Madrid, Spain
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11
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Tanaka T, Talegawkar SA, Jin Y, Candia J, Tian Q, Moaddel R, Simonsick EM, Ferrucci L. Metabolomic Profile of Different Dietary Patterns and Their Association with Frailty Index in Community-Dwelling Older Men and Women. Nutrients 2022; 14:2237. [PMID: 35684039 PMCID: PMC9182888 DOI: 10.3390/nu14112237] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Revised: 05/23/2022] [Accepted: 05/25/2022] [Indexed: 11/28/2022] Open
Abstract
Diet quality has been associated with slower rates of aging; however, the mechanisms underlying the role of a healthy diet in aging are not fully understood. To address this question, we aimed to identify plasma metabolomic biomarkers of dietary patterns and explored whether these metabolites mediate the relationship between diet and healthy aging, as assessed by the frailty index (FI) in 806 participants of the Baltimore Longitudinal Study of Aging. Adherence to different dietary patterns was evaluated using the Mediterranean diet score (MDS), Mediterranean-DASH Diet Intervention for Neurodegenerative Delay (MIND) score, and Alternate Healthy Eating Index-2010 (AHEI). Associations between diet, FI, and metabolites were assessed using linear regression models. Higher adherence to these dietary patterns was associated with lower FI. We found 236, 218, and 278 metabolites associated with the MDS, MIND, and AHEI, respectively, with 127 common metabolites, which included lipids, tri/di-glycerides, lyso/phosphatidylcholine, amino acids, bile acids, ceramides, cholesterol esters, fatty acids and acylcarnitines, indoles, and sphingomyelins. Metabolomic signatures of diet explained 28%, 37%, and 38% of the variance of the MDS, MIND, and AHEI, respectively. Signatures of MIND and AHEI mediated 55% and 61% of the association between each dietary pattern with FI, while the mediating effect of MDS signature was not statistically significant. The high number of metabolites associated with the different dietary patterns supports the notion of common mechanisms that underly the relationship between diet and frailty. The identification of multiple metabolite classes suggests that the effect of diet is complex and not mediated by any specific biomarkers. Furthermore, these metabolites may serve as biomarkers for poor diet quality to identify individuals for targeted dietary interventions.
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Affiliation(s)
- Toshiko Tanaka
- Longitudinal Studies Section, National Institute on Aging, Baltimore, MD 21224, USA; (J.C.); (Q.T.); (E.M.S.); (L.F.)
| | - Sameera A. Talegawkar
- Department of Exercise and Nutrition Sciences, Milken Institute School of Public Health, The George Washington University, Washington, DC 20052, USA; (S.A.T.); (Y.J.)
| | - Yichen Jin
- Department of Exercise and Nutrition Sciences, Milken Institute School of Public Health, The George Washington University, Washington, DC 20052, USA; (S.A.T.); (Y.J.)
| | - Julián Candia
- Longitudinal Studies Section, National Institute on Aging, Baltimore, MD 21224, USA; (J.C.); (Q.T.); (E.M.S.); (L.F.)
| | - Qu Tian
- Longitudinal Studies Section, National Institute on Aging, Baltimore, MD 21224, USA; (J.C.); (Q.T.); (E.M.S.); (L.F.)
| | - Ruin Moaddel
- Laboratory of Clinical Investigation, National Institute on Aging, Baltimore, MD 21224, USA;
| | - Eleanor M. Simonsick
- Longitudinal Studies Section, National Institute on Aging, Baltimore, MD 21224, USA; (J.C.); (Q.T.); (E.M.S.); (L.F.)
| | - Luigi Ferrucci
- Longitudinal Studies Section, National Institute on Aging, Baltimore, MD 21224, USA; (J.C.); (Q.T.); (E.M.S.); (L.F.)
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12
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Wang S, Wang W, Mao H, Zhu M, Xu Z, Wang J, Zhang X, Li B, Xiang X, Wang Z. Lipidomics Reveals That Rice or Flour as a Single Source of Carbohydrates Cause Adverse Health Effects in Rats. Front Nutr 2022; 9:887757. [PMID: 35673359 PMCID: PMC9167423 DOI: 10.3389/fnut.2022.887757] [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: 03/01/2022] [Accepted: 04/20/2022] [Indexed: 11/13/2022] Open
Abstract
The type of diet is very important for the maintenance of health and nutrition. How the sole source of carbohydrates from rice- or flour-based diet affect blood sugar has not been elucidated for a long time. In order to explore the effects of these diets, sixty SD rats were randomly divided into three groups: control group (C group, AIN-93, standard diet), rice diet group (R group), and flour diet group (F group). All the rats were fed for 7 weeks in total by the assigned diets for 4 weeks (stage 1, S1) and all by the AIN-93 diet for 3 weeks (stage 2, S2). The body weights of all the rats were monitored and serum samples were taken for testing blood glucose, biochemical indicators and untargeted lipidome. It was found that both rice and flour-based diets caused weight gain, but the flour diet had a significant increase in blood sugar and low-density lipoprotein (LDL), while a significant decrease in albumin (ALB) and triglycerides (TG). Twenty-three and 148 lipids were changed by lipidomics in the rice diet group and flour diet group, respectively, and two lipids showed the same changes in the two groups, all belonging to TGs, namely TG (16:0/16:0/16:1) and TG (16:0/16:1/18:2), which showed that a single diet source had a significant effect on the health of rats. Fortunately, we can recover this effect through the subsequent standard diet, allowing the rats to return to normal blood sugar, weight and biochemical indicators. A model can predict the diet types through the logistic regression method. Finally, we proposed that a single diet increased blood sugar and weight through a decrease in TGs, and blood sugar and weight returned to normal after a standard diet. Taken together, the short-term negative effects caused by a single diet can be recovered by a standard diet and further proves the importance of diet types.
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Affiliation(s)
- Siyu Wang
- Key Laboratory of Trace Element Nutrition of National Health Commission, National Institute for Nutrition and Health, Chinese Center for Diseases Control and Prevention, Beijing, China
| | - Wenjun Wang
- Beijing Junfeix Technology Co., Ltd., Beijing, China
| | - Hongmei Mao
- Key Laboratory of Trace Element Nutrition of National Health Commission, National Institute for Nutrition and Health, Chinese Center for Diseases Control and Prevention, Beijing, China
| | - Mingyu Zhu
- Key Laboratory of Trace Element Nutrition of National Health Commission, National Institute for Nutrition and Health, Chinese Center for Diseases Control and Prevention, Beijing, China
| | - Zihan Xu
- Key Laboratory of Trace Element Nutrition of National Health Commission, National Institute for Nutrition and Health, Chinese Center for Diseases Control and Prevention, Beijing, China
| | - Jun Wang
- Shenzhen Polytechnic, School of Food and Drug, Shenzhen, China
| | - Xuesong Zhang
- Key Laboratory of Trace Element Nutrition of National Health Commission, National Institute for Nutrition and Health, Chinese Center for Diseases Control and Prevention, Beijing, China
| | - Baolong Li
- Key Laboratory of Trace Element Nutrition of National Health Commission, National Institute for Nutrition and Health, Chinese Center for Diseases Control and Prevention, Beijing, China
| | - Xuesong Xiang
- Key Laboratory of Trace Element Nutrition of National Health Commission, National Institute for Nutrition and Health, Chinese Center for Diseases Control and Prevention, Beijing, China
- *Correspondence: Xuesong Xiang
| | - Zhu Wang
- Key Laboratory of Trace Element Nutrition of National Health Commission, National Institute for Nutrition and Health, Chinese Center for Diseases Control and Prevention, Beijing, China
- Zhu Wang
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13
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Plasma Metabolite Profiles Following Consumption of Animal Protein and Soybean-Based Diet in Hypercholesterolemic Postmenopausal Women. Metabolites 2022; 12:metabo12030209. [PMID: 35323651 PMCID: PMC8952012 DOI: 10.3390/metabo12030209] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2022] [Revised: 02/09/2022] [Accepted: 02/23/2022] [Indexed: 02/05/2023] Open
Abstract
Subjective reporting of food intake can be unreliable. No objective method is available to distinguish between diets differing in protein type. To address this gap, a secondary analysis of a randomized controlled cross-over feeding trial was conducted. Assessed were fasting plasma metabolite profiles and their associations with cardiometabolic risk factors (CMRFs). Hypercholesterolemic post-menopausal women (N = 11) were provided with diets containing predominantly animal protein (AP) and soy protein (SP). Untargeted metabolomics were used to determine the plasma metabolite profiles at the end of each diet phase. Concentrations of identified metabolites (N = 829) were compared using paired t-tests adjusted for false discovery rate, partial least square-discrimination analysis (PLS-DA) and receiver operating characteristics (ROC). Among the identified metabolites, 58 differed significantly between the AP and SP diets; the majority were phospholipids (n = 36), then amino acids (n = 10), xenobiotics (n = 7), vitamin/vitamin-related (n = 3) and lipids (n = 2). Of the top 10 metabolites, amino acid-derived metabolites, phospholipids and xenobiotics comprised the main categories differing due to dietary protein type. ROC curves confirmed that the top 10 metabolites were potential discriminating biomarkers for AP- and SP-rich diets. In conclusion, amino acid-derived metabolites, phosphatidylethanolamine-derived metabolites and isoflavones were identified as potential metabolite biomarkers distinguishing between dietary protein type.
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14
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His M, Viallon V, Dossus L, Schmidt JA, Travis RC, Gunter MJ, Overvad K, Kyrø C, Tjønneland A, Lécuyer L, Rothwell JA, Severi G, Johnson T, Katzke V, Schulze MB, Masala G, Sieri S, Panico S, Tumino R, Macciotta A, Boer JMA, Monninkhof EM, Olsen KS, Nøst TH, Sandanger TM, Agudo A, Sánchez MJ, Amiano P, Colorado-Yohar SM, Ardanaz E, Vidman L, Winkvist A, Heath AK, Weiderpass E, Huybrechts I, Rinaldi S. Lifestyle correlates of eight breast cancer-related metabolites: a cross-sectional study within the EPIC cohort. BMC Med 2021; 19:312. [PMID: 34886862 PMCID: PMC8662901 DOI: 10.1186/s12916-021-02183-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/09/2021] [Accepted: 11/09/2021] [Indexed: 12/29/2022] Open
Abstract
BACKGROUND Metabolomics is a promising molecular tool for identifying novel etiological pathways leading to cancer. In an earlier prospective study among pre- and postmenopausal women not using exogenous hormones, we observed a higher risk of breast cancer associated with higher blood concentrations of one metabolite (acetylcarnitine) and a lower risk associated with higher blood concentrations of seven others (arginine, asparagine, phosphatidylcholines (PCs) aa C36:3, ae C34:2, ae C36:2, ae C36:3, and ae C38:2). METHODS To identify determinants of these breast cancer-related metabolites, we conducted a cross-sectional analysis to identify their lifestyle and anthropometric correlates in 2358 women, who were previously included as controls in case-control studies nested within the European Prospective Investigation into Cancer and Nutrition cohort and not using exogenous hormones at blood collection. Associations of each metabolite concentration with 42 variables were assessed using linear regression models in a discovery set of 1572 participants. Significant associations were evaluated in a validation set (n = 786). RESULTS For the metabolites previously associated with a lower risk of breast cancer, concentrations of PCs ae C34:2, C36:2, C36:3, and C38:2 were negatively associated with adiposity and positively associated with total and saturated fat intakes. PC ae C36:2 was also negatively associated with alcohol consumption and positively associated with two scores reflecting adherence to a healthy lifestyle. Asparagine concentration was negatively associated with adiposity. Arginine and PC aa C36:3 concentrations were not associated to any of the factors examined. For the metabolite previously associated with a higher risk of breast cancer, acetylcarnitine, a positive association with age was observed. CONCLUSIONS These associations may indicate possible mechanisms underlying associations between lifestyle and anthropometric factors, and risk of breast cancer. Further research is needed to identify potential non-lifestyle correlates of the metabolites investigated.
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Affiliation(s)
- Mathilde His
- International Agency for Research on Cancer (IARC/WHO), Nutrition and Metabolism Branch, 150 cours Albert Thomas, 69372, CEDEX 08, Lyon, France
| | - Vivian Viallon
- International Agency for Research on Cancer (IARC/WHO), Nutrition and Metabolism Branch, 150 cours Albert Thomas, 69372, CEDEX 08, Lyon, France
| | - Laure Dossus
- International Agency for Research on Cancer (IARC/WHO), Nutrition and Metabolism Branch, 150 cours Albert Thomas, 69372, CEDEX 08, Lyon, France
| | - Julie A Schmidt
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Ruth C Travis
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Marc J Gunter
- International Agency for Research on Cancer (IARC/WHO), Nutrition and Metabolism Branch, 150 cours Albert Thomas, 69372, CEDEX 08, Lyon, France
| | - Kim Overvad
- Department of Public Health, Aarhus University, Aarhus, Denmark
| | - Cecilie Kyrø
- Danish Cancer Society Research Center, Copenhagen, Denmark
| | - Anne Tjønneland
- Danish Cancer Society Research Center, Copenhagen, Denmark
- Department of Public Health, Section of Environmental Health, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Lucie Lécuyer
- Université Paris-Saclay, UVSQ, Inserm, CESP U1018, "Exposome and Heredity" team, Gustave Roussy, Villejuif, France
| | - Joseph A Rothwell
- Université Paris-Saclay, UVSQ, Inserm, CESP U1018, "Exposome and Heredity" team, Gustave Roussy, Villejuif, France
| | - Gianluca Severi
- Université Paris-Saclay, UVSQ, Inserm, CESP U1018, "Exposome and Heredity" team, Gustave Roussy, Villejuif, France
- Department of Statistics, Computer Science, Applications "G. Parenti", University of Florence, Florence, Italy
| | - Theron Johnson
- Department of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Verena Katzke
- Department of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Matthias B Schulze
- Department of Molecular Epidemiology, German Institute of Human Nutrition, Nuthetal, Germany
- Institute of Nutritional Science, University of Potsdam, Potsdam, Germany
| | - Giovanna Masala
- Institute for Cancer Research, Prevention and Clinical Network (ISPRO), Florence, Italy
| | - Sabina Sieri
- Epidemiology and Prevention Unit, Fondazione IRCCS Instituto Nazionale dei Tumori di Milano, Milan, Italy
| | - Salvatore Panico
- Dipartimento Di Medicina Clinica E Chirurgia, Federico Ii University, Naples, Italy
| | - Rosario Tumino
- Cancer Registry and Histopathology Department, Provincial Health Authority (ASP 7) Ragusa, Ragusa, Italy
| | - Alessandra Macciotta
- Department of Clinical and Biological Sciences, University of Turin, Turin, Italy
| | - Jolanda M A Boer
- Center for Nutrition, Prevention, and Health Services, National Institute for Public Health and the Environment (RIVM), Bilthoven, 3720, BA, the Netherlands
| | - Evelyn M Monninkhof
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Karina Standahl Olsen
- Department of Community Medicine, Faculty of Health Sciences, UiT The Arctic University of Norway, NO-9037, Tromsø, Norway
| | - Therese H Nøst
- Department of Community Medicine, Faculty of Health Sciences, UiT The Arctic University of Norway, NO-9037, Tromsø, Norway
| | - Torkjel M Sandanger
- Department of Community Medicine, Faculty of Health Sciences, UiT The Arctic University of Norway, NO-9037, Tromsø, Norway
| | - Antonio Agudo
- Unit of Nutrition and Cancer, Catalan Institute of Oncology - ICO, L'Hospitalet de Llobregat, Spain
- Nutrition and Cancer Group; Epidemiology, Public Health, Cancer Prevention and Palliative Care Program; Bellvitge Biomedical Research Institute - IDIBELL, L'Hospitalet de Llobregat, Spain
| | - Maria-Jose Sánchez
- Escuela Andaluza de Salud Pública (EASP), Granada, Spain
- Instituto de Investigación Biosanitaria ibs.GRANADA, Granada, Spain
- Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
- Department of Preventive Medicine and Public Health, University of Granada, Granada, Spain
| | - Pilar Amiano
- Ministry of Health of the Basque Government, Sub-Directorate for Public Health and Addictions of Gipuzkoa, San Sebastián, Spain
- Biodonostia Health Research Institute, Group of Epidemiology of Chronic and Communicable Diseases, San Sebastián, Spain
- CIBER Epidemiology and Public Health (CIBERESP), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
| | - Sandra M Colorado-Yohar
- CIBER Epidemiology and Public Health (CIBERESP), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Department of Epidemiology, Murcia Regional Health Council, IMIB-Arrixaca, Murcia, Spain
- Research Group on Demography and Health, National Faculty of Public Health, University of Antioquia, Medellín, Colombia
| | - Eva Ardanaz
- CIBER Epidemiology and Public Health (CIBERESP), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Navarra Public Health Institute, Pamplona, Spain
- IdiSNA, Navarra Institute for Health Research, Pamplona, Spain
| | - Linda Vidman
- Department of Radiation Sciences, Oncology, Umeå University, Umeå, Sweden
| | - Anna Winkvist
- Sustainable Health, Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
| | - Alicia K Heath
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Elisabete Weiderpass
- International Agency for Research on Cancer (IARC/WHO), Office of the Director, Lyon, France
| | - Inge Huybrechts
- International Agency for Research on Cancer (IARC/WHO), Nutrition and Metabolism Branch, 150 cours Albert Thomas, 69372, CEDEX 08, Lyon, France
| | - Sabina Rinaldi
- International Agency for Research on Cancer (IARC/WHO), Nutrition and Metabolism Branch, 150 cours Albert Thomas, 69372, CEDEX 08, Lyon, France.
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15
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Bagheri M, Shah RD, Mosley JD, Ferguson JF. A metabolome and microbiome wide association study of healthy eating index points to the mechanisms linking dietary pattern and metabolic status. Eur J Nutr 2021; 60:4413-4427. [PMID: 34057579 PMCID: PMC8572162 DOI: 10.1007/s00394-021-02599-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2021] [Accepted: 05/21/2021] [Indexed: 01/07/2023]
Abstract
BACKGROUND Healthy eating index (HEI), a measure of diet quality, associates with metabolic health outcomes; however, the molecular basis is unclear. We conducted a multi-omic study to examine whether HEI associates with the circulatory and gut metabolome and investigated the gut microbiome-HEI interaction on circulating and gut metabolites. METHODS Through a cross-sectional study, we evaluated diet quality in healthy individuals [the ABO Glycoproteomics in Platelets and Endothelial Cells (ABO) Study, n = 73], metabolites (measured at Metabolon Inc.) in plasma (n = 800) and gut (n = 767) and the gut microbiome at enterotype and microbial taxa (n = 296) levels. Pathway analysis was conducted using Metaboanalyst 4.0. We performed multi-variable linear regression to explore both the HEI-metabolites and HEI-microbiome associations and how metabolites were affected by the HEI-microbiome interaction. In the Fish oils and Adipose Inflammation Reduction (FAIR) Study (n = 25), analyses on HEI and plasma metabolites were replicated. Estimates of findings from both studies were pooled in random-effects meta-analysis. RESULTS The HEI-2015 was associated with 74 plasma and 73 gut metabolites (mostly lipids) and with 47 metabolites in the meta-analysis of the ABO and FAIR Studies. Compared to Enterotype-1 participants, those with Enterotype-2 had higher diet quality (p = 0.01). We also identified 9 microbial genera associated with HEI, and 35 plasma and 40 gut metabolites linked to the HEI-gut microbiome interaction. Pathways involved in the metabolism of polar lipids, amino acids and caffeine strongly associated with diet quality. However, the HEI-microbiome interaction not only influenced the pathways involved in the metabolism of branch-chain amino acids, it also affected upstream pathways including nucleotide metabolism and amino acids biosynthesis. CONCLUSIONS Our multi-omic analysis demonstrated that changes in metabolism, measured by either circulatory/gut metabolites or metabolic pathways, are influenced by not only diet quality but also gut microbiome alterations shaped by the quality of diet consumed. Future work is needed to explore the causality in the interplay between HEI and gut-microbiome composition in metabolism.
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Affiliation(s)
- Minoo Bagheri
- Division of Cardiovascular Medicine, Department of Medicine, Vanderbilt University Medical Center, 2220 Pierce Ave, PRB 354B, Nashville, TN, 37232, USA
| | - Rachana D Shah
- Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Jonathan D Mosley
- Division of Clinical Pharmacology, Department of Medicine and Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Jane F Ferguson
- Division of Cardiovascular Medicine, Department of Medicine, Vanderbilt University Medical Center, 2220 Pierce Ave, PRB 354B, Nashville, TN, 37232, USA.
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16
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Xiao J, Shi J, Li R, Her L, Wang X, Li J, Sorensen MJ, Bhatt-Mehta V, Zhu HJ. Developing a SWATH capillary LC-MS/MS method for simultaneous therapeutic drug monitoring and untargeted metabolomics analysis of neonatal plasma. J Chromatogr B Analyt Technol Biomed Life Sci 2021; 1179:122865. [PMID: 34365292 DOI: 10.1016/j.jchromb.2021.122865] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2021] [Revised: 07/13/2021] [Accepted: 07/17/2021] [Indexed: 12/22/2022]
Abstract
Most medications prescribed to neonatal patients are off-label uses. The pharmacokinetics and pharmacodynamics of drugs differ significantly between neonates and adults. Therefore, personalized pharmacotherapy guided by therapeutic drug monitoring (TDM) and drug response biomarkers are particularly beneficial to neonatal patients. Herein, we developed a capillary LC-MS/MS metabolomics method using a SWATH-based data-independent acquisition strategy for simultaneous targeted and untargeted metabolomics analysis of neonatal plasma samples. We applied the method to determine the global plasma metabolomics profiles and quantify the plasma concentrations of five drugs commonly used in neonatal intensive care units, including ampicillin, caffeine, fluconazole, vancomycin, and midazolam and its active metabolite α-hydroxymidazolam, in neonatal patients. The method was successfully validated and found to be suitable for the TDM of the drugs of interest. Moreover, the global metabolomics analysis revealed plasma metabolite features that could differentiate preterm and full-term neonates. This study demonstrated that the SWATH-based capillary LC-MS/MS metabolomics approach could be a powerful tool for simultaneous TDM and the discovery of neonatal plasma metabolite biomarkers.
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Affiliation(s)
- Jingcheng Xiao
- Department of Pharmaceutical Sciences, University of Michigan, Ann Arbor, MI 48109, United States
| | - Jian Shi
- Department of Clinical Pharmacy, University of Michigan, Ann Arbor, MI 48109, United States
| | - Ruiting Li
- Department of Pharmaceutical Sciences, University of Michigan, Ann Arbor, MI 48109, United States
| | - Lucy Her
- Department of Pharmaceutical Sciences, University of Michigan, Ann Arbor, MI 48109, United States
| | - Xinwen Wang
- Department of Pharmaceutical Sciences, Northeast Ohio Medical University, Rootstown, OH 44272, United States
| | - Jiapeng Li
- Department of Clinical Pharmacy, University of Michigan, Ann Arbor, MI 48109, United States
| | - Matthew J Sorensen
- Department of Chemistry, University of Michigan, Ann Arbor, MI 48109, United States
| | - Varsha Bhatt-Mehta
- Department of Clinical Pharmacy, University of Michigan, Ann Arbor, MI 48109, United States; Department of Pediatrics and Communicable Diseases, Michigan Medicine, University of Michigan, Ann Arbor, MI 48109, United States
| | - Hao-Jie Zhu
- Department of Clinical Pharmacy, University of Michigan, Ann Arbor, MI 48109, United States.
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17
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Food for Thought or Feeding a Dogma? Diet and Coronary Artery Disease: a Clinician's Perspective. Curr Cardiol Rep 2021; 23:127. [PMID: 34279741 DOI: 10.1007/s11886-021-01557-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 04/08/2021] [Indexed: 10/20/2022]
Abstract
PURPOSE OF REVIEW To provide an overview of nutrition studies evaluating the association of dietary saturated fat and meat intake with the development of coronary artery disease (CAD) and discuss implications of recent data. RECENT FINDINGS Recent studies have led to the re-evaluation of the role of saturated fat in CAD. Randomized controlled trials (RCTs) support Mediterranean diet to reduce cardiovascular risk. Recent data revealed significant association of intake of meat or poultry with increased risk, but fish consumption was associated with lower risk of incident CAD. In this review, we provide a brief overview of the studies and data that have led to the re-evaluation of the link between saturated fat and CAD. Due to conflicting data from long-term prospective cohort studies and significant heterogeneity, associations of unprocessed meat with CAD are less clear compared to the role of processed meat. Pooled data from prospective cohort studies have overcome some of these limitations and show association of both processed and unprocessed meat and poultry intake but not fish consumption with incident CAD. These findings were also validated recently in a large UK Biobank prospective study. While recognizing the limitations of these cohort studies, we discuss relevant landmark RCTs. We finally consider the challenges with RCTs in nutrition research to improve the quality of evidence and need for evidence-based dietary guidelines with respect to saturated fat intake from a clinical perspective.
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18
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Kim H, Anderson CA, Hu EA, Zheng Z, Appel LJ, He J, Feldman HI, Anderson AH, Ricardo AC, Bhat Z, Kelly TN, Chen J, Vasan RS, Kimmel PL, Grams ME, Coresh J, Clish CB, Rhee EP, Rebholz CM. Plasma Metabolomic Signatures of Healthy Dietary Patterns in the Chronic Renal Insufficiency Cohort (CRIC) Study. J Nutr 2021; 151:2894-2907. [PMID: 34195833 PMCID: PMC8485904 DOI: 10.1093/jn/nxab203] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2021] [Revised: 05/05/2021] [Accepted: 06/01/2021] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND In individuals with chronic kidney disease (CKD), healthy dietary patterns are inversely associated with CKD progression. Metabolomics, an approach that measures many small molecules in biofluids, can identify biomarkers of healthy dietary patterns. OBJECTIVES We aimed to identify known metabolites associated with greater adherence to 4 healthy dietary patterns in CKD patients. METHODS We examined associations between 486 known plasma metabolites and Healthy Eating Index (HEI)-2015, Alternative Healthy Eating Index (AHEI)-2010, the Dietary Approaches to Stop Hypertension (DASH) diet, and alternate Mediterranean diet (aMED) in 1056 participants (aged 21-74 y at baseline) in the Chronic Renal Insufficiency Cohort (CRIC) Study. Usual dietary intake was assessed using a semiquantitative FFQ. We conducted multivariable linear regression models to study associations between healthy dietary patterns and individual plasma metabolites, adjusting for sociodemographic characteristics, health behaviors, and clinical factors. We used principal component analysis to identify groups of metabolites associated with individual food components within healthy dietary patterns. RESULTS After Bonferroni correction, we identified 266 statistically significant diet-metabolite associations (HEI: n = 60; AHEI: n = 78; DASH: n = 77; aMED: n = 51); 78 metabolites were associated with >1 dietary pattern. Lipids with a longer acyl chain length and double bonds (unsaturated) were positively associated with all 4 dietary patterns. A metabolite pattern low in saturated diacylglycerols and triacylglycerols, and a pattern high in unsaturated triacylglycerols was positively associated with intake of healthy food components. Plasmalogens were negatively associated with the consumption of nuts and legumes and healthy fat, and positively associated with the intake of red and processed meat. CONCLUSIONS We identified many metabolites associated with healthy dietary patterns, indicative of food consumption. If replicated, these metabolites may be considered biomarkers of healthy dietary patterns in patients with CKD.
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Affiliation(s)
- Hyunju Kim
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, MD, USA,Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Cheryl Am Anderson
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, San Diego, CA, USA
| | | | - Zihe Zheng
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA, USA
| | - Lawrence J Appel
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, MD, USA,Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Jiang He
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA,Department of Medicine, Tulane University, New Orleans, LA, USA
| | - Harold I Feldman
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA, USA
| | - Amanda H Anderson
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA
| | - Ana C Ricardo
- Department of Medicine, University of Illinois, Chicago, IL, USA
| | - Zeenat Bhat
- Department of Medicine, Wayne State University, Detroit, MI, USA
| | - Tanika N Kelly
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA,Department of Medicine, Tulane University, New Orleans, LA, USA
| | - Jing Chen
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA,Department of Medicine, Tulane University, New Orleans, LA, USA
| | | | - Paul L Kimmel
- Division of Kidney, Urologic, and Hematologic Diseases, National Institute of Diabetes and Digestive and Kidney Diseases, NIH, Bethesda, MD, USA
| | - Morgan E Grams
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, MD, USA,Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Josef Coresh
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, MD, USA,Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Clary B Clish
- The Broad Institute of Harvard and Massachusetts Institute of Technology
, Boston, MA, USA
| | - Eugene P Rhee
- Nephrology Division and Endocrine Unit, Massachusetts General Hospital, Boston, MA, USA
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19
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Jakubczyk A, Kiersnowska K, Ömeroğlu B, Gawlik-Dziki U, Tutaj K, Rybczyńska-Tkaczyk K, Szydłowska-Tutaj M, Złotek U, Baraniak B. The Influence of Hypericum perforatum L. Addition to Wheat Cookies on Their Antioxidant, Anti-Metabolic Syndrome, and Antimicrobial Properties. Foods 2021; 10:1379. [PMID: 34203621 PMCID: PMC8232325 DOI: 10.3390/foods10061379] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2021] [Accepted: 06/08/2021] [Indexed: 12/17/2022] Open
Abstract
The aim of this study was to characterize wheat cookies enriched with 0.5% and 1.0% of Hypericum perforatum L. (St. John's wort, SJW) and determine their pro-health properties in vitro after hydrolysis in simulated gastrointestinal conditions. The results indicated that 1.0 SJW was characterized by the highest content of polyphenols, flavonoids, and phenolic acids (2.32 mg mL-1, 4.93 µg mL-1, and 12.35 µg mL-1, respectively). The enriching cookies had no effect on water absorption capacity (WAC) and oil absorption capacity (OAC). After in vitro hydrolysis, the highest peptide content was noted in 1.0 SJW (0.52 mg mL-1), and the bioactive compounds were characterized by high potential bioaccessibility (PAC), but poor bioavailability (PAV). The addition of SJW increased the ACE, α-amylase, and LOX inhibitory effect, but reduced the inhibition of pancreatic lipase. The highest antioxidant activity was noted for 1.0 SJW. The results showed that only 0.5 SJW and 1.0 SJW had slight antimicrobial activity against E. coli ATCC 25922 and B. cereus ATCC 14579 with MIC = 12.5 mg mL-1. Fractions with molecular mass <3.0 kDa were characterized with the highest p-coumaric acid content. The results show that SJW cookies had a higher content of bioactive compounds and more potent anti-metabolic syndrome effects.
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Affiliation(s)
- Anna Jakubczyk
- Department of Biochemistry and Food Chemistry, University of Life Sciences in Lublin, Skromna 8, 20-704 Lublin, Poland; (A.J.); (U.G.-D.); (M.S.-T.); (B.B.)
| | - Kaja Kiersnowska
- Scientific Students Group of Food Biochemistry and Nutrition, Department of Biochemistry and Food Chemistry, University of Life Sciences in Lublin, 20-704 Lublin, Poland;
| | - Begümhan Ömeroğlu
- Department of Nutrition and Dietetics, Marmara Üniversitesi Göztepe Yerleşkesi, Kadıköy/İstanbul 34722, Turkey;
| | - Urszula Gawlik-Dziki
- Department of Biochemistry and Food Chemistry, University of Life Sciences in Lublin, Skromna 8, 20-704 Lublin, Poland; (A.J.); (U.G.-D.); (M.S.-T.); (B.B.)
| | - Krzysztof Tutaj
- Department of Biochemistry and Toxicology, Faculty of Animal Sciences and Bioeconomy, University of Life Sciences in Lublin, Akademicka 13, 20-950 Lublin, Poland;
| | - Kamila Rybczyńska-Tkaczyk
- Department of Environmental Microbiology, University of Life Sciences in Lublin, St. Leszczyńskiego 7, 20-069 Lublin, Poland;
| | - Magdalena Szydłowska-Tutaj
- Department of Biochemistry and Food Chemistry, University of Life Sciences in Lublin, Skromna 8, 20-704 Lublin, Poland; (A.J.); (U.G.-D.); (M.S.-T.); (B.B.)
| | - Urszula Złotek
- Department of Biochemistry and Food Chemistry, University of Life Sciences in Lublin, Skromna 8, 20-704 Lublin, Poland; (A.J.); (U.G.-D.); (M.S.-T.); (B.B.)
| | - Barbara Baraniak
- Department of Biochemistry and Food Chemistry, University of Life Sciences in Lublin, Skromna 8, 20-704 Lublin, Poland; (A.J.); (U.G.-D.); (M.S.-T.); (B.B.)
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20
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Rebholz CM, Gao Y, Talegawkar S, Tucker KL, Colantonio LD, Muntner P, Ngo D, Chen ZZ, Cruz D, Katz D, Tahir UA, Clish C, Gerszten RE, Wilson JG. Metabolomic Markers of Southern Dietary Patterns in the Jackson Heart Study. Mol Nutr Food Res 2021; 65:e2000796. [PMID: 33629508 PMCID: PMC8192080 DOI: 10.1002/mnfr.202000796] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2020] [Revised: 01/07/2021] [Indexed: 02/02/2023]
Abstract
SCOPE New biomarkers are needed that are representative of dietary intake. METHODS AND RESULTS We assess metabolites associated with Southern dietary patterns in 1401 Jackson Heart Study participants. Three dietary patterns are empirically derived using principal component analysis: meat and fast food, fish and vegetables, and starchy foods. We randomly select two subsets of the study population: two-third sample for discovery (n = 934) and one-third sample for replication (n = 467). Among the 327 metabolites analyzed, 14 are significantly associated with the meat and fast food dietary pattern, four are significantly associated with the fish and vegetables dietary pattern, and none are associated with the starchy foods dietary pattern in the discovery sample. In the replication sample, nine remain associated with the meat and fast food dietary pattern [indole-3-propanoic acid, C24:0 lysophosphatidylcholine (LPC), N-methyl proline, proline betaine, C34:2 phosphatidylethanolamine (PE) plasmalogen, C36:5 PE plasmalogen, C38:5 PE plasmalogen, cotinine, hydroxyproline] and three remain associated with the fish and vegetables dietary pattern [1,7-dimethyluric acid, C22:6 lysophosphatidylethanolamine, docosahexaenoic acid (DHA)]. CONCLUSION Twelve metabolites are discovered and replicated in association with dietary patterns detected in a Southern U.S. African-American population, which could be useful as biomarkers of Southern dietary patterns.
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Affiliation(s)
- Casey M. Rebholz
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Yan Gao
- The Jackson Heart Study, University of Mississippi Medical Center, Jackson, Mississippi
| | - Sameera Talegawkar
- Department of Exercise and Nutrition Sciences, Milken Institute School of Public Health, George Washington University, Washington, DC
| | - Katherine L. Tucker
- Department of Biomedical and Nutritional Sciences, University of Massachusetts Lowell, Lowell, Massachusetts
| | - Lisandro D. Colantonio
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Alabama
| | - Paul Muntner
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Alabama
| | - Debby Ngo
- Division of Cardiology, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts
| | - Zsu Zsu Chen
- Division of Cardiology, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts
| | - Daniel Cruz
- Division of Cardiology, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts
| | - Daniel Katz
- Division of Cardiology, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts
| | - Usman A. Tahir
- Division of Cardiology, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts
| | | | - Robert E. Gerszten
- Division of Cardiology, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts
| | - James G. Wilson
- Division of Cardiology, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts
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21
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Metabolomic Biomarkers of Healthy Dietary Patterns and Cardiovascular Outcomes. Curr Atheroscler Rep 2021; 23:26. [PMID: 33782776 DOI: 10.1007/s11883-021-00921-8] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/09/2021] [Indexed: 02/07/2023]
Abstract
PURPOSE OF REVIEW Healthy dietary patterns are recommended for prevention of CVD. Recently, metabolomics has been used to identify biomarkers of healthy dietary patterns and elucidate mechanisms underlying diet-disease associations. This review provides an overview of approaches to define healthy dietary patterns, discusses important issues related to using metabolomics to describe healthy dietary patterns, and summarizes studies identifying blood metabolites associated with hypothesis-driven healthy dietary patterns and cardiovascular risk factors and incident CVD. RECENT FINDINGS We identified 17 studies which reported on blood metabolomic signatures of 5 healthy dietary patterns (Healthy Eating Index, Alternative Healthy Eating Index, the Dietary Approaches to Stop Hypertension diet, Mediterranean diet, vegetarian diet). Four of these studies evaluated associations between diet-related metabolites and cardiovascular outcomes. Many metabolites replicated across different healthy dietary patterns, which suggest that they may represent biomarkers of generally healthy diets. Unsaturated lipids positively associated with healthy dietary patterns were inversely associated with incident CVD, suggesting that they may be a pathway through which diet is associated with a lower risk of CVD. Although many metabolites replicated across cross-sectional studies, few metabolites identified as candidate biomarkers of healthy diets in feeding studies replicated in observational studies. Additionally, limited evidence exists on the ability of diet-related metabolites to predict cardiovascular outcomes. Replication of candidate biomarkers of dietary patterns in different study designs and more studies evaluating the associations between diet-related metabolites and cardiovascular outcomes are needed.
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