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Chen S, Chen XY, Huang ZH, Fang AP, Li SY, Huang RZ, Chen YM, Huang BX, Zhu HL. Correlation between serum trimethylamine-N-oxide and body fat distribution in middle-aged and older adults: a prospective cohort study. Nutr J 2024; 23:70. [PMID: 38982486 PMCID: PMC11234726 DOI: 10.1186/s12937-024-00974-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2024] [Accepted: 06/28/2024] [Indexed: 07/11/2024] Open
Abstract
BACKGROUND Trimethylamine-N-oxide (TMAO) is linked with obesity, while limited evidence on its relationship with body fat distribution. Herein, we investigated the associations between serum TMAO and longitudinal change of fat distribution in this prospective cohort study. METHODS Data of 1964 participants (40-75y old) from Guangzhou Nutrition and Health Study (GNHS) during 2008-2014 was analyzed. Serum TMAO concentration was quantified by HPLC-MS/MS at baseline. The body composition was assessed by dual-energy X-ray absorptiometry at each 3-y follow-up. Fat distribution parameters were fat-to-lean mass ratio (FLR) and trunk-to-leg fat ratio (TLR). Fat distribution changes were derived from the coefficient of linear regression between their parameters and follow-up duration. RESULTS After an average of 6.2-y follow-up, analysis of covariance (ANCOVA) and linear regression displayed women with higher serum TMAO level had greater increments in trunk FLR (mean ± SD: 1.47 ± 4.39, P-trend = 0.006) and TLR (mean ± SD: 0.06 ± 0.24, P-trend = 0.011). Meanwhile, for women in the highest TMAO tertile, linear mixed-effects model (LMEM) analysis demonstrated the annual estimated increments (95% CI) were 0.03 (95% CI: 0.003 - 0.06, P = 0.032) in trunk FLR and 1.28 (95% CI: -0.17 - 2.73, P = 0.083) in TLR, respectively. In men, there were no similar significant observations. Sensitivity analysis yielded consistent results. CONCLUSION Serum TMAO displayed a more profound correlation with increment of FLR and TLR in middle-aged and older community-dwelling women in current study. More and further studies are still warranted in the future. TRIAL REGISTRATION NCT03179657.
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Affiliation(s)
- Si Chen
- Department of Nutrition, Guangdong Provincial Key Laboratory of Food, Nutrition and Health, School of Public Health, Sun Yat-Sen University, 74 Zhongshan II Road, Guangzhou, 510080, PR China
| | - Xiao-Yan Chen
- Department of Nutrition, Guangdong Provincial Key Laboratory of Food, Nutrition and Health, School of Public Health, Sun Yat-Sen University, 74 Zhongshan II Road, Guangzhou, 510080, PR China
| | - Zi-Hui Huang
- Department of Nutrition, Guangdong Provincial Key Laboratory of Food, Nutrition and Health, School of Public Health, Sun Yat-Sen University, 74 Zhongshan II Road, Guangzhou, 510080, PR China
| | - Ai-Ping Fang
- Department of Nutrition, Guangdong Provincial Key Laboratory of Food, Nutrition and Health, School of Public Health, Sun Yat-Sen University, 74 Zhongshan II Road, Guangzhou, 510080, PR China
| | - Shu-Yi Li
- Department of Nutrition, Guangdong Provincial Key Laboratory of Food, Nutrition and Health, School of Public Health, Sun Yat-Sen University, 74 Zhongshan II Road, Guangzhou, 510080, PR China
| | - Rong-Zhu Huang
- Department of Nutrition, Guangdong Provincial Key Laboratory of Food, Nutrition and Health, School of Public Health, Sun Yat-Sen University, 74 Zhongshan II Road, Guangzhou, 510080, PR China
| | - Yu-Ming Chen
- Department of Epidemiology, Guangdong Provincial Key Laboratory of Food, Nutrition and Health, School of Public Health, Sun Yat-Sen University, Guangzhou, China
| | - Bi-Xia Huang
- Department of Nutrition, Guangdong Provincial Key Laboratory of Food, Nutrition and Health, School of Public Health, Sun Yat-Sen University, 74 Zhongshan II Road, Guangzhou, 510080, PR China.
| | - Hui-Lian Zhu
- Department of Nutrition, Guangdong Provincial Key Laboratory of Food, Nutrition and Health, School of Public Health, Sun Yat-Sen University, 74 Zhongshan II Road, Guangzhou, 510080, PR China.
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Florkowski M, Abiona E, Frank KM, Brichacek AL. Obesity-associated inflammation countered by a Mediterranean diet: the role of gut-derived metabolites. Front Nutr 2024; 11:1392666. [PMID: 38978699 PMCID: PMC11229823 DOI: 10.3389/fnut.2024.1392666] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2024] [Accepted: 06/03/2024] [Indexed: 07/10/2024] Open
Abstract
The prevalence of obesity has increased dramatically worldwide and has become a critical public health priority. Obesity is associated with many co-morbid conditions, including hypertension, diabetes, and cardiovascular disease. Although the physiology of obesity is complex, a healthy diet and sufficient exercise are two elements known to be critical to combating this condition. Years of research on the Mediterranean diet, which is high in fresh fruits and vegetables, nuts, fish, and olive oil, have demonstrated a reduction in numerous non-communicable chronic diseases associated with this diet. There is strong evidence to support an anti-inflammatory effect of the diet, and inflammation is a key driver of obesity. Changes in diet alter the gut microbiota which are intricately intertwined with human physiology, as gut microbiota-derived metabolites play a key role in biological pathways throughout the body. This review will summarize recent published studies that examine the potential role of gut metabolites, including short-chain fatty acids, bile acids, trimethylamine-N-oxide, and lipopolysaccharide, in modulating inflammation after consumption of a Mediterranean-like diet. These metabolites modulate pathways of inflammation through the NOD-like receptor family pyrin domain-containing 3 (NLRP3) inflammasome, toll-like receptor 4 signaling, and macrophage driven effects in adipocytes, among other mechanisms.
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Affiliation(s)
- Melanie Florkowski
- Department of Laboratory Medicine, National Institutes of Health Clinical Center, Bethesda, MD, United States
| | - Esther Abiona
- Department of Laboratory Medicine, National Institutes of Health Clinical Center, Bethesda, MD, United States
| | - Karen M Frank
- Department of Laboratory Medicine, National Institutes of Health Clinical Center, Bethesda, MD, United States
| | - Allison L Brichacek
- Department of Laboratory Medicine, National Institutes of Health Clinical Center, Bethesda, MD, United States
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Almer G, Enko D, Kartiosuo N, Niinikoski H, Lehtimäki T, Munukka E, Viikari J, Rönnemaa T, Rovio SP, Mykkänen J, Lagström H, Jula A, Herrmann M, Raitakari OT, Meinitzer A, Pahkala K. Association of Serum Trimethylamine-N-Oxide Concentration from Childhood to Early Adulthood with Age and Sex. Clin Chem 2024:hvae087. [PMID: 38906833 DOI: 10.1093/clinchem/hvae087] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2024] [Accepted: 05/30/2024] [Indexed: 06/23/2024]
Abstract
BACKGROUND Primary prevention is the cornerstone of cardiometabolic health. In the randomized, controlled Special Turku Coronary Risk Factor Intervention Project (STRIP), dietary counseling intervention was given to children from infancy to 20 years of age and a follow-up was completed at age 26 years. We investigated the associations of age, sex, gut microbiome, and dietary intervention with the gut metabolite and the cardiac biomarker trimethylamine-N-oxide (TMAO). METHODS Overall, 592 healthy participants (females 46%) from STRIP were investigated. Compared to the control group, the intervention group had received dietary counseling between ages 7 months and 20 years focused on low intakes of saturated fat and cholesterol and the promotion of fruit, vegetable, and whole-grain consumption. TMAO serum concentrations were measured by a liquid chromatography-tandem mass spectrometry method at ages 11, 13, 15, 17, 19, and 26 years. Microbiome composition was assessed using 16S rRNA gene sequencing at 26 years of age. RESULTS TMAO concentrations increased from age 11 to 26 years in both sexes. At all measurement time points, males showed significantly higher serum TMAO concentrations compared to females, but concentrations were similar between the intervention and control groups. A direct association between TMAO concentrations and reported fiber intake was found in females. Gut microbiome analysis did not reveal associations with TMAO. CONCLUSIONS TMAO concentration increased from childhood to early adulthood but was not affected by the given dietary intervention. In females, TMAO concentrations could be directly associated with higher fiber intake suggesting sex-specific differences in TMAO metabolism.
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Affiliation(s)
- Gunter Almer
- Clinical Institute of Medical and Chemical Laboratory Diagnostics, Medical University of Graz, Graz, Austria
| | - Dietmar Enko
- Clinical Institute of Medical and Chemical Laboratory Diagnostics, Medical University of Graz, Graz, Austria
- Institute of Medical and Chemical Laboratory Diagnostics, General Hospital Hochsteiermark, Leoben, Austria
| | - Noora Kartiosuo
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
- Department of Mathematics and Statistics, University of Turku, Turku, Finland
| | - Harri Niinikoski
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
- Department of Pediatrics and Adolescent Medicine, Turku University Hospital, University of Turku, Turku, Finland
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories, and Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Eveliina Munukka
- Microbiome Biobank, Institute of Biomedicine, University of Turku, Turku, Finland
| | - Jorma Viikari
- Department of Medicine, University of Turku, Turku, Finland
- Division of Medicine, Turku University Hospital, Turku, Finland
| | - Tapani Rönnemaa
- Department of Medicine, University of Turku, Turku, Finland
- Division of Medicine, Turku University Hospital, Turku, Finland
| | - Suvi P Rovio
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
- Department of Public Health, University of Turku and Turku University Hospital, Turku, Finland
| | - Juha Mykkänen
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
| | - Hanna Lagström
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
- Department of Public Health, University of Turku and Turku University Hospital, Turku, Finland
| | - Antti Jula
- Department of Public Health Solutions, Institute for Health and Welfare, Turku, Finland
| | - Markus Herrmann
- Clinical Institute of Medical and Chemical Laboratory Diagnostics, Medical University of Graz, Graz, Austria
| | - Olli T Raitakari
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
- Department of Clinical Physiology and Nuclear Medicine, University of Turku and Turku University Hospital, Turku; Finland
| | - Andreas Meinitzer
- Clinical Institute of Medical and Chemical Laboratory Diagnostics, Medical University of Graz, Graz, Austria
| | - Katja Pahkala
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
- Paavo Nurmi Centre and Unit for Health and Physical Activity, University of Turku, Turku, Finland
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Huang Y, Wu Y, Zhang Y, Bai H, Peng R, Ruan W, Zhang Q, Cai E, Ma M, Zhao Y, Lu Y, Zheng L. Dynamic Changes in Gut Microbiota-Derived Metabolite Trimethylamine-N-Oxide and Risk of Type 2 Diabetes Mellitus: Potential for Dietary Changes in Diabetes Prevention. Nutrients 2024; 16:1711. [PMID: 38892643 PMCID: PMC11174887 DOI: 10.3390/nu16111711] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2024] [Revised: 05/16/2024] [Accepted: 05/28/2024] [Indexed: 06/21/2024] Open
Abstract
BACKGROUND A gut-microbial metabolite, trimethylamine N-oxide (TMAO), has been associated with type 2 diabetes mellitus (T2DM). Few previous prospective studies have addressed associations between the changes in TMAO and T2DM incidence. METHODS Data were derived from a longitudinal cohort conducted from 2019 to 2021 in rural areas of Fuxin County, Liaoning Province, China, and 1515 diabetes-free participants aged above 35 years were included. The concentrations of serum TMAO and its precursors were measured at two time points, namely in 2019 and 2021. TMAO and TMAO changes (ΔTMAO) were separately tested in a logistic regression model. For further examination, the odds ratios (ORs) for T2DM were calculated according to a combination of TMAO levels and ΔTMAO levels. RESULTS During a median follow-up of 1.85 years, 81 incident cases of T2DM (5.35%) were identified. Baseline TMAO levels exhibited a nonlinear relationship, first decreasing and then increasing, and only at the highest quartile was it associated with the risk of T2DM. The OR for T2DM in the highest quartile of serum TMAO was 3.35 (95%CI: 1.55-7.26, p = 0.002), compared with the lowest quartile. As for its precursors, only choline level was associated with T2DM risk and the OR for T2DM in the Q3 and Q4 of serum choline was 3.37 (95%CI: 1.41-8.05, p = 0.006) and 4.72 (95%CI: 1.47-15.13, p = 0.009), respectively. When considering both baseline TMAO levels and ΔTMAO over time, participants with sustained high TMAO levels demonstrated a significantly increased risk of T2DM, with a multivariable-adjusted OR of 8.68 (95%CI: 1.97, 38.34). CONCLUSION Both initial serum TMAO levels and long-term serum TMAO changes were collectively and significantly associated with the occurrence of subsequent T2DM events. Interventions aimed at normalizing TMAO levels, such as adopting a healthy dietary pattern, may be particularly beneficial in T2DM prevention.
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Affiliation(s)
- Yuliang Huang
- Department of Acute Communicable Diseases Control and Prevention, Huangpu District Center for Disease Control and Prevention, Shanghai 200023, China;
| | - Yani Wu
- School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China; (Y.W.); (H.B.); (R.P.)
| | - Yao Zhang
- Department of Endocrinology, Shengjing Hospital of China Medical University, Shenyang 110004, China;
| | - He Bai
- School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China; (Y.W.); (H.B.); (R.P.)
| | - Ruiheng Peng
- School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China; (Y.W.); (H.B.); (R.P.)
| | - Wenli Ruan
- Department of Physical and Chemical, Changning District Center for Disease Control and Prevention, Shanghai 200051, China; (W.R.); (E.C.)
| | - Qianlong Zhang
- Ministry of Education-Shanghai Key Laboratory of Children’s Environmental Health, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200092, China;
| | - Enmao Cai
- Department of Physical and Chemical, Changning District Center for Disease Control and Prevention, Shanghai 200051, China; (W.R.); (E.C.)
| | - Mingfeng Ma
- Department of Cardiovascular Medicine, Fenyang Hospital, Shanxi Medical University, Fenyang 032200, China;
| | - Yueyang Zhao
- Library, Shengjing Hospital of China Medical University, Shenyang 110004, China
| | - Ying Lu
- Department of Physical and Chemical, Changning District Center for Disease Control and Prevention, Shanghai 200051, China; (W.R.); (E.C.)
| | - Liqiang Zheng
- School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China; (Y.W.); (H.B.); (R.P.)
- Ministry of Education-Shanghai Key Laboratory of Children’s Environmental Health, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200092, China;
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Sawicki CM, Pacheco LS, Rivas-Tumanyan S, Cao Z, Haslam DE, Liang L, Tucker KL, Joshipura K, Bhupathiraju SN. Association of Gut Microbiota-Related Metabolites and Type 2 Diabetes in Two Puerto Rican Cohorts. Nutrients 2024; 16:959. [PMID: 38612993 PMCID: PMC11013596 DOI: 10.3390/nu16070959] [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: 02/29/2024] [Revised: 03/22/2024] [Accepted: 03/24/2024] [Indexed: 04/14/2024] Open
Abstract
(1) Aims: Gut microbiota metabolites may play integral roles in human metabolism and disease progression. However, evidence for associations between metabolites and cardiometabolic risk factors is sparse, especially in high-risk Hispanic populations. We aimed to evaluate the cross-sectional and longitudinal relationships between gut microbiota related metabolites and measures of glycemia, dyslipidemia, adiposity, and incident type 2 diabetes in two Hispanic observational cohorts. (2) Methods: We included data from 670 participants of the Boston Puerto Rican Health Study (BPRHS) and 999 participants of the San Juan Overweight Adult Longitudinal Study (SOALS). Questionnaires and clinical examinations were conducted over 3 years of follow-up for SOALS and 6 years of follow-up for BPRHS. Plasma metabolites, including L-carnitine, betaine, choline, and trimethylamine N-oxide (TMAO), were measured at baseline in both studies. We used multivariable linear models to evaluate the associations between metabolites and cardiometabolic risk factors and multivariable logistic and Poisson regressions to assess associations with prevalent and incident type 2 diabetes, adjusted for potential confounding factors. Cohort-specific analyses were combined using a fixed-effects meta-analysis. (3) Results: Higher plasma betaine was prospectively associated with lower fasting glucose [-0.97 mg/dL (95% CI: -1.59, -0.34), p = 0.002], lower HbA1c [-0.02% (95% CI: -0.04, -0.01), p = 0.01], lower HOMA-IR [-0.14 (95% CI: -0.23, -0.05), p = 0.003], and lower fasting insulin [-0.27 mcU/mL (95% CI: -0.51, -0.03), p = 0.02]. Betaine was also associated with a 22% lower incidence of type 2 diabetes (IRR: 0.78, 95% CI: 0.65, 0.95). L-carnitine was associated with lower fasting glucose [-0.68 mg/dL (95% CI: -1.29, -0.07), p = 0.03] and lower HbA1c at follow-up [-0.03% (95% CI: -0.05, -0.01), p < 0.001], while TMAO was associated with higher fasting glucose [0.83 mg/dL (95% CI: 0.22, 1.44), p = 0.01] and higher triglycerides [3.52 mg/dL (95% CI: 1.83, 5.20), p < 0.0001]. Neither choline nor TMAO were associated with incident type 2 diabetes. (4) Conclusions: Higher plasma betaine showed consistent associations with a lower risk of glycemia, insulinemia, and type 2 diabetes. However, TMAO, a metabolite of betaine, was associated with higher glucose and lipid concentrations. These observations demonstrate the importance of gut microbiota metabolites for human cardiometabolic health.
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Affiliation(s)
- Caleigh M. Sawicki
- Channing Division of Network Medicine, Brigham and Women’s Hospital and Harvard Medical School, 181 Longwood Ave, Boston, MA 02115, USA; (C.M.S.); (D.E.H.)
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA;
| | - Lorena S. Pacheco
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA;
| | - Sona Rivas-Tumanyan
- Department of Surgical Sciences, School of Dental Medicine, University of Puerto Rico, San Juan, PR 00921, USA; (S.R.-T.); (K.J.)
| | - Zheyi Cao
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA;
| | - Danielle E. Haslam
- Channing Division of Network Medicine, Brigham and Women’s Hospital and Harvard Medical School, 181 Longwood Ave, Boston, MA 02115, USA; (C.M.S.); (D.E.H.)
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA;
| | - Liming Liang
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA;
| | - Katherine L. Tucker
- Department of Biomedical and Nutritional Sciences and Center for Population Health, University of Massachusetts, Lowell, MA 01854, USA;
| | - Kaumudi Joshipura
- Department of Surgical Sciences, School of Dental Medicine, University of Puerto Rico, San Juan, PR 00921, USA; (S.R.-T.); (K.J.)
| | - Shilpa N. Bhupathiraju
- Channing Division of Network Medicine, Brigham and Women’s Hospital and Harvard Medical School, 181 Longwood Ave, Boston, MA 02115, USA; (C.M.S.); (D.E.H.)
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA;
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Mihuta MS, Paul C, Borlea A, Roi CM, Pescari D, Velea-Barta OA, Mozos I, Stoian D. Connections between serum Trimethylamine N-Oxide (TMAO), a gut-derived metabolite, and vascular biomarkers evaluating arterial stiffness and subclinical atherosclerosis in children with obesity. Front Endocrinol (Lausanne) 2023; 14:1253584. [PMID: 37850094 PMCID: PMC10577381 DOI: 10.3389/fendo.2023.1253584] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Accepted: 09/12/2023] [Indexed: 10/19/2023] Open
Abstract
Introduction Childhood obesity leads to early subclinical atherosclerosis and arterial stiffness. Studying biomarkers like trimethylamine N-oxide (TMAO), linked to cardio-metabolic disorders in adults, is crucial to prevent long-term cardiovascular issues. Methods The study involved 70 children aged 4 to 18 (50 obese, 20 normal-weight). Clinical examination included BMI, waist measurements, puberty stage, the presence of acanthosis nigricans, and irregular menstrual cycles. Subclinical atherosclerosis was assessed by measuring the carotid intima-media thickness (CIMT), and the arterial stiffness was evaluated through surrogate markers like the pulse wave velocity (PWV), augmentation index (AIx), and peripheral and central blood pressures. The blood biomarkers included determining the values of TMAO, HOMA-IR, and other usual biomarkers investigating metabolism. Results The study detected significantly elevated levels of TMAO in obese children compared to controls. TMAO presented positive correlations to BMI, waist circumference and waist-to-height ratio and was also observed as an independent predictor of all three parameters. Significant correlations were observed between TMAO and vascular markers such as CIMT, PWV, and peripheral BP levels. TMAO independently predicts CIMT, PWV, peripheral BP, and central SBP levels, even after adding BMI, waist circumference, waist-to-height ratio, puberty development and age in the regression model. Obese children with high HOMA-IR presented a greater weight excess and significantly higher vascular markers, but TMAO levels did not differ significantly from the obese with HOMA-IR Conclusion Our study provides compelling evidence supporting the link between serum TMAO, obesity, and vascular damage in children. These findings highlight the importance of further research to unravel the underlying mechanisms of this connection.
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Affiliation(s)
- Monica Simina Mihuta
- Department of Doctoral Studies, Victor Babes University of Medicine and Pharmacy, Timisoara, Romania
- Center of Molecular Research in Nephrology and Vascular Disease, Faculty of Medicine, Victor Babes University of Medicine and Pharmacy, Timisoara, Romania
| | - Corina Paul
- Department of Pediatrics, Victor Babes University of Medicine and Pharmacy, Timisoara, Romania
| | - Andreea Borlea
- Center of Molecular Research in Nephrology and Vascular Disease, Faculty of Medicine, Victor Babes University of Medicine and Pharmacy, Timisoara, Romania
- 2nd Department of Internal Medicine, Victor Babes University of Medicine and Pharmacy, Timisoara, Romania
| | - Cristina Mihaela Roi
- Department of Doctoral Studies, Victor Babes University of Medicine and Pharmacy, Timisoara, Romania
- Center of Molecular Research in Nephrology and Vascular Disease, Faculty of Medicine, Victor Babes University of Medicine and Pharmacy, Timisoara, Romania
| | - Denisa Pescari
- Department of Doctoral Studies, Victor Babes University of Medicine and Pharmacy, Timisoara, Romania
| | - Oana-Alexandra Velea-Barta
- 3rd Department of Odontotherapy and Endodontics, Faculty of Dental Medicine, Victor Babes University of Medicine and Pharmacy, Timisoara, Romania
| | - Ioana Mozos
- Department of Functional Sciences—Pathophysiology, Center for Translational Research and Systems Medicine, Victor Babes University of Medicine and Pharmacy, Timisoara, Romania
| | - Dana Stoian
- Center of Molecular Research in Nephrology and Vascular Disease, Faculty of Medicine, Victor Babes University of Medicine and Pharmacy, Timisoara, Romania
- 2nd Department of Internal Medicine, Victor Babes University of Medicine and Pharmacy, Timisoara, Romania
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Wu X, Lin D, Li Q, Cai J, Huang H, Xiang T, Tan H. Investigating causal associations among gut microbiota, gut microbiota-derived metabolites, and gestational diabetes mellitus: a bidirectional Mendelian randomization study. Aging (Albany NY) 2023; 15:8345-8366. [PMID: 37616057 PMCID: PMC10497006 DOI: 10.18632/aging.204973] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Accepted: 07/20/2023] [Indexed: 08/25/2023]
Abstract
BACKGROUND Previous studies have shown that gut microbiota (GM) and gut microbiota-derived metabolites are associated with gestational diabetes mellitus (GDM). However, the causal associations need to be treated with caution due to confounding factors and reverse causation. METHODS This study obtained genetic variants from genome-wide association study including GM (N = 18,340), GM-derived metabolites (N = 7,824), and GDM (5,687 cases and 117,89 controls). To examine the causal association, several methods were utilized, including inverse variance weighted, maximum likelihood, weighted median, MR-Egger, and MR.RAPS. Additionally, reverse Mendelian Randomization (MR) analysis and multivariable MR were conducted to confirm the causal direction and account for potential confounders, respectively. Furthermore, sensitivity analyses were performed to identify any potential heterogeneity and horizontal pleiotropy. RESULTS Greater abundance of Collinsella was detected to increase the risk of GDM. Our study also found suggestive associations among Coprobacter, Olsenella, Lachnoclostridium, Prevotella9, Ruminococcus2, Oscillibacte, and Methanobrevibacter with GDM. Besides, eight GM-derived metabolites were found to be causally associated with GDM. For the phenylalanine metabolism pathway, phenylacetic acid was found to be related to the risk of GDM. CONCLUSIONS The study first used the MR approach to explore the causal associations among GM, GM-derived metabolites, and GDM. Our findings may contribute to the prevention and treatment strategies for GDM by targeting GM and metabolites, and offer novel insights into the underlying mechanism of the disease.
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Affiliation(s)
- Xinrui Wu
- School of Medicine, Jishou University, Jishou, China
- Xiangya School of Public Health, Central South University, Changsha, China
| | - Dihui Lin
- School of Medicine, Jishou University, Jishou, China
| | - Qi Li
- Xiangxi Center for Disease Control and Prevention, Jishou, China
| | - Jiawang Cai
- School of Medicine, Jishou University, Jishou, China
| | | | - Tianyu Xiang
- Xiangya School of Public Health, Central South University, Changsha, China
| | - Hongzhuan Tan
- Xiangya School of Public Health, Central South University, Changsha, China
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8
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Zhang Y, Barupal DK, Fan S, Gao B, Zhu C, Flenniken AM, McKerlie C, Nutter LMJ, Lloyd KCK, Fiehn O. Sexual Dimorphism of the Mouse Plasma Metabolome Is Associated with Phenotypes of 30 Gene Knockout Lines. Metabolites 2023; 13:947. [PMID: 37623890 PMCID: PMC10456929 DOI: 10.3390/metabo13080947] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Revised: 08/03/2023] [Accepted: 08/08/2023] [Indexed: 08/26/2023] Open
Abstract
Although metabolic alterations are observed in many monogenic and complex genetic disorders, the impact of most mammalian genes on cellular metabolism remains unknown. Understanding the effect of mouse gene dysfunction on metabolism can inform the functions of their human orthologues. We investigated the effect of loss-of-function mutations in 30 unique gene knockout (KO) lines on plasma metabolites, including genes coding for structural proteins (11 of 30), metabolic pathway enzymes (12 of 30) and protein kinases (7 of 30). Steroids, bile acids, oxylipins, primary metabolites, biogenic amines and complex lipids were analyzed with dedicated mass spectrometry platforms, yielding 827 identified metabolites in male and female KO mice and wildtype (WT) controls. Twenty-two percent of 23,698 KO versus WT comparison tests showed significant genotype effects on plasma metabolites. Fifty-six percent of identified metabolites were significantly different between the sexes in WT mice. Many of these metabolites were also found to have sexually dimorphic changes in KO lines. We used plasma metabolites to complement phenotype information exemplified for Dhfr, Idh1, Mfap4, Nek2, Npc2, Phyh and Sra1. The association of plasma metabolites with IMPC phenotypes showed dramatic sexual dimorphism in wildtype mice. We demonstrate how to link metabolomics to genotypes and (disease) phenotypes. Sex must be considered as critical factor in the biological interpretation of gene functions.
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Affiliation(s)
- Ying Zhang
- West Coast Metabolomics Center, University of California Davis, Davis, CA 95616, USA
- Department of Chemistry, University of California Davis, Davis, CA 95616, USA
| | - Dinesh K. Barupal
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA;
| | - Sili Fan
- West Coast Metabolomics Center, University of California Davis, Davis, CA 95616, USA
| | - Bei Gao
- School of Marine Sciences, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Chao Zhu
- College of Medicine & Nursing, Dezhou University, Dezhou 253023, China
| | - Ann M. Flenniken
- The Centre for Phenogenomics, Toronto, ON M5T 3H7, Canada; (A.M.F.); (C.M.); (L.M.J.N.)
- Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, ON M5G 1X5, Canada
| | - Colin McKerlie
- The Centre for Phenogenomics, Toronto, ON M5T 3H7, Canada; (A.M.F.); (C.M.); (L.M.J.N.)
- The Hospital for Sick Children, Toronto, ON M5G 1X8, Canada
| | - Lauryl M. J. Nutter
- The Centre for Phenogenomics, Toronto, ON M5T 3H7, Canada; (A.M.F.); (C.M.); (L.M.J.N.)
- The Hospital for Sick Children, Toronto, ON M5G 1X8, Canada
| | - Kevin C. Kent Lloyd
- Department of Surgery, School of Medicine, and Mouse Biology Program, University of California Davis, Davis, CA 95616, USA;
| | - Oliver Fiehn
- West Coast Metabolomics Center, University of California Davis, Davis, CA 95616, USA
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9
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Qi S, Liu L, He S, Wang L, Li J, Sun X. Trimethylamine N-Oxide and Related Metabolites in the Serum and Risk of Type 2 Diabetes in the Chinese Population: A Case-Control Study. Diabetes Metab Syndr Obes 2023; 16:547-555. [PMID: 36874557 PMCID: PMC9983576 DOI: 10.2147/dmso.s398008] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Accepted: 02/14/2023] [Indexed: 03/03/2023] Open
Abstract
BACKGROUND Trimethylamine N-oxide (TMAO) and its precursors have an association with type 2 diabetes mellitus (T2DM); however, the evidence is unclear. The current study examined the association of serial measures of serum TMAO and related metabolite concentrations with the risk of T2DM. METHODS Our study was designed as a community case-control study with 300 participants (150 T2DM and 150 non-T2DM). We examined the association of serum concentrations of TMAO and its related metabolites [trimethylamine, choline, betaine, and L-carnitine] using UPLC-MS/MS. The association between these metabolites and the risk of T2DM was analyzed using a restricted cubic spline and binary logistic regression. RESULTS A higher serum choline concentration was significantly associated with an increased risk of T2DM. Serum choline > 22.62 μmol/L was independently associated with an increased risk of T2DM, and the odds ratio was 3.615 [95% CI: (1.453,8.993), P = 0.006]. Similarly, serum betaine and L-carnitine concentrations had a markedly decreased risk of T2DM even after adjusting for the traditional risk factors for T2DM and betaine (0.978 [95% CI:0.964-0.992], P = 0.002) and L-carnitine (0.949 [95% CI: 0.9222-0.978], P = 0.001), respectively. CONCLUSION Choline, betaine, and L-carnitine are associated with the risk of T2DM and may be appropriate risk markers to protect high-risk individuals from T2DM.
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Affiliation(s)
- Shenghong Qi
- School of Public Health and Management, Ningxia Medical University, Yinchuan, Ningxia, People’s Republic of China
- The Key Laboratory of Environmental Factors and Chronic Disease Control of Ningxia, Yinchuan, Ningxia, People’s Republic of China
| | - Lan Liu
- School of Public Health and Management, Ningxia Medical University, Yinchuan, Ningxia, People’s Republic of China
- The Key Laboratory of Environmental Factors and Chronic Disease Control of Ningxia, Yinchuan, Ningxia, People’s Republic of China
| | - Shulan He
- School of Public Health and Management, Ningxia Medical University, Yinchuan, Ningxia, People’s Republic of China
- The Key Laboratory of Environmental Factors and Chronic Disease Control of Ningxia, Yinchuan, Ningxia, People’s Republic of China
| | - Liqun Wang
- School of Public Health and Management, Ningxia Medical University, Yinchuan, Ningxia, People’s Republic of China
- The Key Laboratory of Environmental Factors and Chronic Disease Control of Ningxia, Yinchuan, Ningxia, People’s Republic of China
| | - Jiangping Li
- School of Public Health and Management, Ningxia Medical University, Yinchuan, Ningxia, People’s Republic of China
- The Key Laboratory of Environmental Factors and Chronic Disease Control of Ningxia, Yinchuan, Ningxia, People’s Republic of China
| | - Xian Sun
- School of Public Health and Management, Ningxia Medical University, Yinchuan, Ningxia, People’s Republic of China
- The Key Laboratory of Environmental Factors and Chronic Disease Control of Ningxia, Yinchuan, Ningxia, People’s Republic of China
- Correspondence: Xian Sun, Tel +86 1 370 958 4072, Email
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10
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Díez-Ricote L, San-Cristobal R, Concejo MJ, Martínez-González MÁ, Corella D, Salas-Salvadó J, Goday A, Martínez JA, Alonso-Gómez ÁM, Wärnberg J, Vioque J, Romaguera D, López-Miranda J, Estruch R, Tinahones FJ, Lapetra J, Serra-Majem L, Bueno-Cavanillas A, Tur JA, Martín Sánchez V, Pintó X, Gaforio JJ, Matía-Martín P, Vidal J, Mas Fontao S, Ros E, Vázquez-Ruiz Z, Ortega-Azorín C, García-Gavilán JF, Malcampo M, Martínez-Urbistondo D, Tojal-Sierra L, García Rodríguez A, Gómez-Bellvert N, Chaplin A, García-Ríos A, Bernal-López RM, Santos-Lozano JM, Basterra-Gortari J, Sorlí JV, Murphy M, Gasulla G, Micó V, Salaverria-Lete I, Goñi Ochandorena E, Babio N, Herraiz X, Ordovás JM, Daimiel L. One-year longitudinal association between changes in dietary choline or betaine intake and cardiometabolic variables in the PREvención con DIeta MEDiterránea-Plus (PREDIMED-Plus) trial. Am J Clin Nutr 2022; 116:1565-1579. [PMID: 36124652 PMCID: PMC9761742 DOI: 10.1093/ajcn/nqac255] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Accepted: 09/09/2022] [Indexed: 02/01/2023] Open
Abstract
BACKGROUND Choline and betaine intakes have been related to cardiovascular health. OBJECTIVES We aimed to explore the relation between 1-y changes in dietary intake of choline or betaine and 1-y changes in cardiometabolic and renal function traits within the frame of the PREDIMED (PREvención con DIeta MEDiterránea)-Plus trial. METHODS We used baseline and 1-y follow-up data from 5613 participants (48.2% female and 51.8% male; mean ± SD age: 65.01 ± 4.91 y) to assess cardiometabolic traits, and 3367 participants to assess renal function, of the Spanish PREDIMED-Plus trial. Participants met ≥3 criteria of metabolic syndrome and had overweight or obesity [BMI (in kg/m2) ≥27 and ≤40]. These criteria were similar to those of the PREDIMED parent study. Dietary intakes of choline and betaine were estimated from the FFQ. RESULTS The greatest 1-y increase in dietary choline or betaine intake (quartile 4) was associated with improved serum glucose concentrations (-3.39 and -2.72 mg/dL for choline and betaine, respectively) and HbA1c levels (-0.10% for quartile 4 of either choline or betaine intake increase). Other significant changes associated with the greatest increase in choline or betaine intake were reduced body weight (-2.93 and -2.78 kg, respectively), BMI (-1.05 and -0.99, respectively), waist circumference (-3.37 and -3.26 cm, respectively), total cholesterol (-4.74 and -4.52 mg/dL, respectively), and LDL cholesterol (-4.30 and -4.16 mg/dL, respectively). Urine creatinine was reduced in quartile 4 of 1-y increase in choline or betaine intake (-5.42 and -5.74 mg/dL, respectively). CONCLUSIONS Increases in dietary choline or betaine intakes were longitudinally related to improvements in cardiometabolic parameters. Markers of renal function were also slightly improved, and they require further investigation.This trial was registered at https://www.isrctn.com/ as ISRCTN89898870.
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Affiliation(s)
- Laura Díez-Ricote
- Nutritional Control of the Epigenome Group, Precision Nutrition and Obesity Program, IMDEA Food, CEI UAM + CSIC, Madrid, Spain
| | - Rodrigo San-Cristobal
- Cardiometabolic Health Group, Precision Nutrition and Cardiometabolic Health Program, IMDEA Food, CEI UAM + CSIC, Madrid, Spain
| | | | - Miguel Á Martínez-González
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, Madrid, Spain
- Department of Preventive Medicine and Public Health, Navarra Institute of Health Research (IdISNA), University of Navarra, Pamplona, Spain
- Department of Nutrition, Harvard TH Chan School of Public Health, Boston, MA, USA
| | - Dolores Corella
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, Madrid, Spain
- Department of Preventive Medicine, University of Valencia, Valencia, Spain
| | - Jordi Salas-Salvadó
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, Madrid, Spain
- Universitat Rovira i Virgili, Departament of Biochemistry and Biotechnology, Human Nutrition Unit, Reus, Spain
- Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain
- Nutrition Unit, University Hospital of Sant Joan de Reus, Reus, Spain
- Unit of Preventive Medicine & Public Health, Faculty of Medicine & Health Sciences, Universitat Rovira i Virgili, Reus, Spain
| | - Albert Goday
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, Madrid, Spain
- Unit of Cardiovascular Risk and Nutrition, Institut Hospital del Mar d`Investigació Médica (IMIM), Barcelona, Spain
- Department of Medicine, Universitat Autonoma de Barcelona, Barcelona, Spain
| | - J Alfredo Martínez
- Cardiometabolic Health Group, Precision Nutrition and Cardiometabolic Health Program, IMDEA Food, CEI UAM + CSIC, Madrid, Spain
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, Madrid, Spain
- Center for Nutrition Research, Department of Nutrition, Food Sciences, and Physiology, University of Navarra, Pamplona, Spain
| | - Ángel M Alonso-Gómez
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, Madrid, Spain
- Cardiovascular, Respiratory and Metabolic Area, Bioaraba Health Research Institute; Araba University Hospital, Osakidetza Basque Health Service; University of the Basque Country UPV/EHU, Vitoria-Gasteiz, Spain
| | - Julia Wärnberg
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, Madrid, Spain
- Department of Nursing, University of Málaga, Institute of Biomedical Research in Malaga (IBIMA), Málaga, Spain
| | - Jesús Vioque
- CIBER de Epidemiología y Salud Pública (CIBERESP), Carlos III Institute of Health (ISCIII), Madrid, Spain
- Institute of Health and Biomedical Research of Alicante, Miguel Hernández University (ISABIAL-UMH), Alicante, Spain
| | - Dora Romaguera
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, Madrid, Spain
- Research Group on Nutritional Epidemiology & Cardiovascular Physiopathology, Health Research Institute of the Balearic Islands (IdISBa), Palma de Mallorca, Spain
| | - José López-Miranda
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, Madrid, Spain
- Department of Internal Medicine, Maimonides Biomedical Research Institute of Cordoba (IMIBIC), Reina Sofia University Hospital, University of Cordoba, Cordoba, Spain
| | - Ramon Estruch
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, Madrid, Spain
- Department of Internal Medicine, Institut d’Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), Hospital Clinic, University of Barcelona, Barcelona, Spain
| | - Francisco J Tinahones
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, Madrid, Spain
- Department of Endocrinology, Virgen de la Victoria Hospital, Málaga Biomedical Research Institute (IBIMA), University of Málaga, Málaga, Spain
| | - José Lapetra
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, Madrid, Spain
- Research Unit, Department of Family Medicine, Sevilla Primary Care Health District, Sevilla, Spain
| | - Lluís Serra-Majem
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, Madrid, Spain
- Research Institute of Biomedical and Health Sciences (IUIBS), University of Las Palmas de Gran Canaria and Maternal and Child Insular University Hospital Center (CHUIMI), Canarian Health Service, Las Palmas de Gran Canaria, Spain
| | - Aurora Bueno-Cavanillas
- CIBER de Epidemiología y Salud Pública (CIBERESP), Carlos III Institute of Health (ISCIII), Madrid, Spain
- Department of Preventive Medicine and Public Health, University of Granada, Granada, Spain
| | - Josep A Tur
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, Madrid, Spain
- Research Group on Community Nutrition & Oxidative Stress, University of the Balearic Islands, Palma de Mallorca, Spain
| | - Vicente Martín Sánchez
- CIBER de Epidemiología y Salud Pública (CIBERESP), Carlos III Institute of Health (ISCIII), Madrid, Spain
- Institute of Biomedicine (IBIOMED), University of León, León, Spain
| | - Xavier Pintó
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, Madrid, Spain
- Lipids and Vascular Risk Unit, Internal Medicine, Bellvitge University Hospital, Barcelona, Spain
| | - José J Gaforio
- CIBER de Epidemiología y Salud Pública (CIBERESP), Carlos III Institute of Health (ISCIII), Madrid, Spain
- Department of Health Sciences, University Institute for Research on Olives and Olive Oils, University of Jaén, Jaén, Spain
| | - Pilar Matía-Martín
- Department of Endocrinology and Nutrition, San Carlos Clinical Hospital Institute of Health Research (IdISSC), Madrid, Spain
| | - Josep Vidal
- CIBER Diabetes y Enfermedades Metabólicas (CIBERDEM), Carlos III Institute of Health (ISCIII), Madrid, Spain
- Department of Endocrinology, Institut d` Investigacions Biomédiques August Pi Sunyer (IDIBAPS), Hospital Clinic, University of Barcelona, Barcelona, Spain
| | - Sebastián Mas Fontao
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, Madrid, Spain
- Department of Endocrinology and Nutrition, Jimenez Díaz Foundation Hospital Biomedical Research Institute (IISFJD), Autonomous University of Madrid, Madrid, Spain
| | - Emilio Ros
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, Madrid, Spain
- Lipid Clinic, Department of Endocrinology and Nutrition, Institut d’Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), Hospital Clínic, Barcelona, Spain
| | - Zenaida Vázquez-Ruiz
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, Madrid, Spain
- Department of Preventive Medicine and Public Health, Navarra Institute of Health Research (IdISNA), University of Navarra, Pamplona, Spain
- Endocrinology Service, Navarra Hospital Complex, Osasunbidea, Navarro Health Service, Pamplona, Spain
| | - Carolina Ortega-Azorín
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, Madrid, Spain
- Department of Preventive Medicine, University of Valencia, Valencia, Spain
| | - Jesús F García-Gavilán
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, Madrid, Spain
- Universitat Rovira i Virgili, Departament of Biochemistry and Biotechnology, Human Nutrition Unit, Reus, Spain
- Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain
- Nutrition Unit, University Hospital of Sant Joan de Reus, Reus, Spain
| | - Mireia Malcampo
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, Madrid, Spain
- Unit of Cardiovascular Risk and Nutrition, Institut Hospital del Mar d`Investigació Médica (IMIM), Barcelona, Spain
| | | | - Lucas Tojal-Sierra
- Cardiovascular, Respiratory and Metabolic Area, Bioaraba Health Research Institute; Araba University Hospital, Osakidetza Basque Health Service; University of the Basque Country UPV/EHU, Vitoria-Gasteiz, Spain
| | - Antonio García Rodríguez
- Division of Preventive Medicine and Public Health, University of Malaga, Institute of Biomedical Research in Málaga (IBIMA-University of Malaga), Málaga, Spain
| | | | - Alice Chaplin
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, Madrid, Spain
- Research Group on Nutritional Epidemiology & Cardiovascular Physiopathology, Health Research Institute of the Balearic Islands (IdISBa), Palma de Mallorca, Spain
| | - Antonio García-Ríos
- Department of Internal Medicine, Maimonides Biomedical Research Institute of Cordoba (IMIBIC), Reina Sofia University Hospital, University of Cordoba, Cordoba, Spain
| | - Rosa M Bernal-López
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, Madrid, Spain
- Department of Endocrinology, Virgen de la Victoria Hospital, Málaga Biomedical Research Institute (IBIMA), University of Málaga, Málaga, Spain
| | - José M Santos-Lozano
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, Madrid, Spain
- Research Unit, Department of Family Medicine, Sevilla Primary Care Health District, Sevilla, Spain
| | - Javier Basterra-Gortari
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, Madrid, Spain
- Department of Preventive Medicine and Public Health, Navarra Institute of Health Research (IdISNA), University of Navarra, Pamplona, Spain
- Endocrinology Service, Navarra Hospital Complex, Osasunbidea, Navarro Health Service, Pamplona, Spain
| | - José V Sorlí
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, Madrid, Spain
- Department of Preventive Medicine, University of Valencia, Valencia, Spain
| | - Michelle Murphy
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, Madrid, Spain
- Universitat Rovira i Virgili, Departament of Biochemistry and Biotechnology, Human Nutrition Unit, Reus, Spain
- Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain
- Nutrition Unit, University Hospital of Sant Joan de Reus, Reus, Spain
| | - Griselda Gasulla
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, Madrid, Spain
- Unit of Cardiovascular Risk and Nutrition, Institut Hospital del Mar d`Investigació Médica (IMIM), Barcelona, Spain
| | - Víctor Micó
- Cardiometabolic Health Group, Precision Nutrition and Cardiometabolic Health Program, IMDEA Food, CEI UAM + CSIC, Madrid, Spain
| | - Itziar Salaverria-Lete
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, Madrid, Spain
- Cardiovascular, Respiratory and Metabolic Area, Bioaraba Health Research Institute; Araba University Hospital, Osakidetza Basque Health Service; University of the Basque Country UPV/EHU, Vitoria-Gasteiz, Spain
| | - Estibaliz Goñi Ochandorena
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, Madrid, Spain
- Department of Preventive Medicine and Public Health, Navarra Institute of Health Research (IdISNA), University of Navarra, Pamplona, Spain
| | - Nancy Babio
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, Madrid, Spain
- Universitat Rovira i Virgili, Departament of Biochemistry and Biotechnology, Human Nutrition Unit, Reus, Spain
- Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain
- Nutrition Unit, University Hospital of Sant Joan de Reus, Reus, Spain
| | - Xavier Herraiz
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, Madrid, Spain
- Unit of Cardiovascular Risk and Nutrition, Institut Hospital del Mar d`Investigació Médica (IMIM), Barcelona, Spain
| | - José M Ordovás
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, Madrid, Spain
- Nutritional Genomics and Epigenomics Group, Precision Nutrition and Obesity Program, IMDEA Food, CEI UAM + CSIC, Madrid, Spain
- Nutrition and Genomics Laboratory, Jean Mayer USDA Human Nutrition Research Center on Aging, Tufts University, Boston, MA, USA
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11
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Canyelles M, Pérez A, Junza A, Miñambres I, Yanes O, Sardà H, Rotllan N, Julve J, Sánchez-Quesada JL, Tondo M, Escolà-Gil JC, Blanco-Vaca F. Divergent Effects of Glycemic Control and Bariatric Surgery on Circulating Concentrations of TMAO in Newly Diagnosed T2D Patients and Morbidly Obese. Diagnostics (Basel) 2022; 12:diagnostics12112783. [PMID: 36428843 PMCID: PMC9689652 DOI: 10.3390/diagnostics12112783] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Revised: 11/07/2022] [Accepted: 11/10/2022] [Indexed: 11/16/2022] Open
Abstract
High circulating concentrations of the gut microbiota-derived metabolite trimethylamine N-oxide (TMAO) are significantly associated with the risk of obesity and type 2 diabetes (T2D). We aimed at evaluating the impact of glycemic control and bariatric surgery on circulating concentrations of TMAO and its microbiota-dependent intermediate, γ-butyrobetaine (γBB), in newly diagnosed T2D patients and morbidly obese subjects following a within-subject design. Based on HbA1c concentrations, T2D patients achieved glycemic control. However, the plasma TMAO and γBB concentrations were significantly increased, without changes in estimated glomerular filtration rate. Bariatric surgery was very effective in reducing weight in obese subjects. Nevertheless, the surgery reduced plasma γBB concentrations without affecting TMAO concentrations and the estimated glomerular filtration rate. Considering these results, an additional experiment was carried out in male C57BL/6J mice fed a Western-type diet for twelve weeks. Neither diet-induced obesity nor insulin resistance were associated with circulating TMAO and γBB concentrations in these genetically defined mice strains. Our findings do not support that glycemic control or bariatric surgery improve the circulating concentrations of TMAO in newly diagnosed T2D and morbidly obese patients.
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Affiliation(s)
- Marina Canyelles
- Institut de Recerca de l’Hospital Santa Creu i Sant Pau, Institut d’Investigacions Biomèdiques IIB Sant Pau, 08041 Barcelona, Spain
- CIBER de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), 28029 Madrid, Spain
| | - Antonio Pérez
- CIBER de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), 28029 Madrid, Spain
- Department of Endocrinology and Nutrition, Hospital de la Santa Creu i Sant Pau, IIB Sant Pau, 08041 Barcelona, Spain
| | - Alexandra Junza
- CIBER de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), 28029 Madrid, Spain
- Metabolomics Platform, Department of Electronic Engineering, Universitat Rovira i Virgili, 43204 Reus, Spain
| | - Inka Miñambres
- CIBER de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), 28029 Madrid, Spain
- Department of Endocrinology and Nutrition, Hospital de la Santa Creu i Sant Pau, IIB Sant Pau, 08041 Barcelona, Spain
| | - Oscar Yanes
- CIBER de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), 28029 Madrid, Spain
- Metabolomics Platform, Department of Electronic Engineering, Universitat Rovira i Virgili, 43204 Reus, Spain
| | - Helena Sardà
- Department of Endocrinology and Nutrition, Hospital de la Santa Creu i Sant Pau, IIB Sant Pau, 08041 Barcelona, Spain
| | - Noemí Rotllan
- Institut de Recerca de l’Hospital Santa Creu i Sant Pau, Institut d’Investigacions Biomèdiques IIB Sant Pau, 08041 Barcelona, Spain
- CIBER de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), 28029 Madrid, Spain
| | - Josep Julve
- Institut de Recerca de l’Hospital Santa Creu i Sant Pau, Institut d’Investigacions Biomèdiques IIB Sant Pau, 08041 Barcelona, Spain
- CIBER de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), 28029 Madrid, Spain
| | - José Luis Sánchez-Quesada
- Institut de Recerca de l’Hospital Santa Creu i Sant Pau, Institut d’Investigacions Biomèdiques IIB Sant Pau, 08041 Barcelona, Spain
- CIBER de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), 28029 Madrid, Spain
| | - Mireia Tondo
- CIBER de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), 28029 Madrid, Spain
- Department of Clinical Biochemistry, Hospital de la Santa Creu i Sant Pau, IIB Sant Pau, 08041 Barcelona, Spain
- Correspondence: (M.T.); (F.B.-V.)
| | - Joan Carles Escolà-Gil
- Institut de Recerca de l’Hospital Santa Creu i Sant Pau, Institut d’Investigacions Biomèdiques IIB Sant Pau, 08041 Barcelona, Spain
- CIBER de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), 28029 Madrid, Spain
| | - Francisco Blanco-Vaca
- CIBER de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), 28029 Madrid, Spain
- Department of Clinical Biochemistry, Hospital de la Santa Creu i Sant Pau, IIB Sant Pau, 08041 Barcelona, Spain
- Department de Bioquímica i Biologia Molecular, Universitat Autònoma de Barcelona, 08041 Barcelona, Spain
- Correspondence: (M.T.); (F.B.-V.)
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12
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Wang S, Li M, Lin H, Wang G, Xu Y, Zhao X, Hu C, Zhang Y, Zheng R, Hu R, Shi L, Du R, Su Q, Wang J, Chen Y, Yu X, Yan L, Wang T, Zhao Z, Liu R, Wang X, Li Q, Qin G, Wan Q, Chen G, Xu M, Dai M, Zhang D, Tang X, Gao Z, Shen F, Luo Z, Qin Y, Chen L, Huo Y, Li Q, Ye Z, Zhang Y, Liu C, Wang Y, Wu S, Yang T, Deng H, Zhao J, Lai S, Mu Y, Chen L, Li D, Xu G, Ning G, Wang W, Bi Y, Lu J. Amino acids, microbiota-related metabolites, and the risk of incident diabetes among normoglycemic Chinese adults: Findings from the 4C study. Cell Rep Med 2022; 3:100727. [PMID: 35998626 PMCID: PMC9512668 DOI: 10.1016/j.xcrm.2022.100727] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Revised: 06/16/2022] [Accepted: 07/22/2022] [Indexed: 11/26/2022]
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13
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Li SY, Chen S, Lu XT, Fang AP, Chen YM, Huang RZ, Lin XL, Huang ZH, Ma JF, Huang BX, Zhu HL. Serum trimethylamine-N-oxide is associated with incident type 2 diabetes in middle-aged and older adults: a prospective cohort study. Lab Invest 2022; 20:374. [PMID: 35982495 PMCID: PMC9389664 DOI: 10.1186/s12967-022-03581-7] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Accepted: 08/07/2022] [Indexed: 11/17/2022]
Abstract
Background The role of trimethylamine-N-oxide (TMAO) in the development of diabetes remains controversial, and prospective data are few. We aimed to investigate the association between serum TMAO and incident type 2 diabetes in middle-aged and older adults. Methods This study was based on the Guangzhou Nutrition and Health Study (GNHS), a community-based prospective cohort study in China. A total of 2088 diabetes-free participants aged 40–75 years were included from 2008 to 2010. Incident type 2 diabetes was ascertained during follow-up visits. Baseline serum TMAO was measured by high-performance liquid chromatography with online electrospray ionization tandem mass spectrometry. Hazard ratios (HRs) and 95% confidence intervals (95% CIs) for diabetes across tertiles of serum TMAO were calculated using Cox proportional hazard models. Prospective associations of serum TMAO with changes in glycemic traits (fasting glucose, HbA1c, insulin, HOMA-IR) over time were estimated using linear mixed-effects models (LMEMs). Results We ascertained 254 incident type 2 diabetes cases during a median follow-up of 8.9 years. The median (interquartile range) of serum TMAO was 1.54 (0.86–2.91) μmol/L. From the first to the third tertile of serum TMAO, the multivariable-adjusted HRs for diabetes were 1.00 (reference), 1.17 (95% CI: 0.84–1.61), and 1.42 (95% CI: 1.03–1.96) (P-trend = 0.031). LMEMs showed that the estimated yearly change in fasting glucose was 0.011 (0.001–0.022) mmol/L/y in the highest tertile of serum TMAO, compared with the lowest tertile (P-interaction = 0.044). Serum TMAO was not associated with longitudinal changes in HbA1c, insulin or HOMA-IR. Conclusions Our findings suggested that higher serum TMAO was associated with a higher risk of type 2 diabetes and an increase in fasting glucose among middle-aged and older Chinese adults. Trial registration: NCT03179657. https://clinicaltrials.gov/ct2/show/NCT03179657?term=NCT03179657&draw=2&rank=1 Supplementary Information The online version contains supplementary material available at 10.1186/s12967-022-03581-7.
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Affiliation(s)
- Shu-Yi Li
- Department of Nutrition, School of Public Health, Sun Yat-Sen University, Guangzhou, 510080, People's Republic of China
| | - Si Chen
- Department of Nutrition, School of Public Health, Sun Yat-Sen University, Guangzhou, 510080, People's Republic of China
| | - Xiao-Ting Lu
- Department of Nutrition, School of Public Health, Sun Yat-Sen University, Guangzhou, 510080, People's Republic of China
| | - Ai-Ping Fang
- Department of Nutrition, School of Public Health, Sun Yat-Sen University, Guangzhou, 510080, People's Republic of China.,Guangdong Provincial Key Laboratory of Food, Nutrition and Health, School of Public Health, Sun Yat-Sen University, Guangzhou, People's Republic of China
| | - Yu-Ming Chen
- Department of Medical Statistics & Epidemiology, School of Public Health, Sun Yat-Sen University, Guangzhou, People's Republic of China
| | - Rong-Zhu Huang
- Department of Nutrition, School of Public Health, Sun Yat-Sen University, Guangzhou, 510080, People's Republic of China
| | - Xin-Lei Lin
- Department of Nutrition, School of Public Health, Sun Yat-Sen University, Guangzhou, 510080, People's Republic of China
| | - Zi-Hui Huang
- Department of Nutrition, School of Public Health, Sun Yat-Sen University, Guangzhou, 510080, People's Republic of China
| | - Jing-Fei Ma
- Department of Nutrition, School of Public Health, Sun Yat-Sen University, Guangzhou, 510080, People's Republic of China
| | - Bi-Xia Huang
- Department of Nutrition, School of Public Health, Sun Yat-Sen University, Guangzhou, 510080, People's Republic of China.
| | - Hui-Lian Zhu
- Department of Nutrition, School of Public Health, Sun Yat-Sen University, Guangzhou, 510080, People's Republic of China. .,Guangdong Provincial Key Laboratory of Food, Nutrition and Health, School of Public Health, Sun Yat-Sen University, Guangzhou, People's Republic of China.
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14
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Association between Plasma Trimethylamine N-Oxide Levels and Type 2 Diabetes: A Case Control Study. Nutrients 2022; 14:nu14102093. [PMID: 35631234 PMCID: PMC9148165 DOI: 10.3390/nu14102093] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Revised: 05/13/2022] [Accepted: 05/16/2022] [Indexed: 02/06/2023] Open
Abstract
Animal and human studies have reported conflicting results on the relationship between circulating trimethylamine N-oxide (TMAO) levels and risk of Type 2 diabetes (T2D). This study aimed to compare plasma TMAO levels in people with or without T2D and explore the association of TMAO and T2D. A prospective case-control study of 297 participants, 164 healthy controls and 133 patients with T2D, was conducted. TMAO levels were quantified by UPLC-MS/MS. Comorbidities, dietary patterns, physical activity, and blood biomarkers were assessed. Median (IQR) plasma TMAO levels were significantly higher in diabetes cases (4.95 (2.84−8.35) µmol/L) compared to healthy controls (3.07 (2.05−4.82) µmol/L) (p < 0.001). The association between TMAO and T2D was significant in the non-adjusted Model 1 (p < 0.001) and after adjusting for confounders of diabetes including age, BMI, and level of education in Model 2 (p = 0.04). When the association was further adjusted for physical activity and diet in Model 3, plasma TMAO levels at only the highest quartile (>6.40 µmol/L) were associated with the risk of diabetes (OR = 3.36, 95% CI [1.26, 9.04], p = 0.02). The results presented suggest an association between plasma TMAO levels and T2D. A significant correlation was found between red meat consumption and increased levels of TMAO in T2D patients. A longitudinal study is warranted to further evaluate the correlation between TMAO and T2D.
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15
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Morze J, Wittenbecher C, Schwingshackl L, Danielewicz A, Rynkiewicz A, Hu FB, Guasch-Ferré M. Metabolomics and Type 2 Diabetes Risk: An Updated Systematic Review and Meta-analysis of Prospective Cohort Studies. Diabetes Care 2022; 45:1013-1024. [PMID: 35349649 PMCID: PMC9016744 DOI: 10.2337/dc21-1705] [Citation(s) in RCA: 85] [Impact Index Per Article: 42.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Accepted: 01/20/2022] [Indexed: 02/03/2023]
Abstract
BACKGROUND Due to the rapidly increasing availability of metabolomics data in prospective studies, an update of the meta evidence on metabolomics and type 2 diabetes risk is warranted. PURPOSE To conduct an updated systematic review and meta-analysis of plasma, serum, and urine metabolite markers and incident type 2 diabetes. DATA SOURCES We searched PubMed and Embase until 6 March 2021. STUDY SELECTION We selected prospective observational studies where investigators used high-throughput techniques to investigate the relationship between plasma, serum, or urine metabolites and incident type 2 diabetes. DATA EXTRACTION Baseline metabolites per-SD risk estimates and 95% CIs for incident type 2 diabetes were extracted from all eligible studies. DATA SYNTHESIS A total of 61 reports with 71,196 participants and 11,771 type 2 diabetes cases/events were included in the updated review. Meta-analysis was performed for 412 metabolites, of which 123 were statistically significantly associated (false discovery rate-corrected P < 0.05) with type 2 diabetes risk. Higher plasma and serum levels of certain amino acids (branched-chain, aromatic, alanine, glutamate, lysine, and methionine), carbohydrates and energy-related metabolites (mannose, trehalose, and pyruvate), acylcarnitines (C4-DC, C4-OH, C5, C5-OH, and C8:1), the majority of glycerolipids (di- and triacylglycerols), (lyso)phosphatidylethanolamines, and ceramides included in meta-analysis were associated with higher risk of type 2 diabetes (hazard ratio 1.07-2.58). Higher levels of glycine, glutamine, betaine, indolepropionate, and (lyso)phosphatidylcholines were associated with lower type 2 diabetes risk (hazard ratio 0.69-0.90). LIMITATIONS Substantial heterogeneity (I2 > 50%, τ2 > 0.1) was observed for some of the metabolites. CONCLUSIONS Several plasma and serum metabolites, including amino acids, lipids, and carbohydrates, are associated with type 2 diabetes risk.
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Affiliation(s)
- Jakub Morze
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA
- Department of Cardiology and Internal Medicine, School of Medicine, University of Warmia and Mazury in Olsztyn, Olsztyn, Poland
- Department of Human Nutrition, Faculty of Food Sciences, University of Warmia and Mazury in Olsztyn, Olsztyn, Poland
| | - Clemens Wittenbecher
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA
- Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany
| | - Lukas Schwingshackl
- Institute for Evidence in Medicine, Medical Centre—University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Anna Danielewicz
- Department of Human Nutrition, Faculty of Food Sciences, University of Warmia and Mazury in Olsztyn, Olsztyn, Poland
| | - Andrzej Rynkiewicz
- Department of Cardiology and Internal Medicine, School of Medicine, University of Warmia and Mazury in Olsztyn, Olsztyn, Poland
| | - Frank B. Hu
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA
- Channing Division for Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA
| | - Marta Guasch-Ferré
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA
- Channing Division for Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA
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16
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Li Y, Wang F, Li J, Ivey KL, Wilkinson JE, Wang DD, Li R, Liu G, Eliassen HA, Chan AT, Clish CB, Huttenhower C, Hu FB, Sun Q, Rimm EB. Dietary lignans, plasma enterolactone levels, and metabolic risk in men: exploring the role of the gut microbiome. BMC Microbiol 2022; 22:82. [PMID: 35350985 PMCID: PMC8966171 DOI: 10.1186/s12866-022-02495-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Accepted: 03/17/2022] [Indexed: 01/22/2023] Open
Abstract
BACKGROUND The conversion of plant lignans to bioactive enterolignans in the gastrointestinal tract is mediated through microbial processing. The goal of this study was to examine the relationships between lignan intake, plasma enterolactone concentrations, gut microbiome composition, and metabolic risk in free-living male adults. RESULTS In 303 men participating in the Men's Lifestyle Validation Study (MLVS), lignan intake was assessed using two sets of 7-day diet records, and gut microbiome was profiled through shotgun sequencing of up to 2 pairs of fecal samples (n = 911). A score was calculated to summarize the abundance of bacteria species that were significantly associated with plasma enterolactone levels. Of the 138 filtered species, plasma enterolactone levels were significantly associated with the relative abundances of 18 species at FDR < 0.05 level. Per SD increment of lignan intake was associated with 20.7 nM (SEM: 2.3 nM) higher enterolactone concentrations among participants with a higher species score, whereas the corresponding estimate was 4.0 nM (SEM: 1.7 nM) among participants with a lower species score (P for interaction < 0.001). A total of 12 plasma metabolites were also significantly associated with these enterolactone-predicting species. Of the association between lignan intake and metabolic risk, 19.8% (95%CI: 7.3%-43.6%) was explained by the species score alone, 54.5% (95%CI: 21.8%-83.7%) by both species score and enterolactone levels, and 79.8% (95%CI: 17.7%-98.6%) by further considering the 12 plasma metabolites. CONCLUSION We identified multiple gut bacteria species that were enriched or depleted at higher plasma levels of enterolactone in men. These species jointly modified the associations of lignan intake with plasma enterolactone levels and explained the majority of association between lignan intake and metabolic risk along with enterolactone levels and certain plasma metabolites.
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Affiliation(s)
- Yanping Li
- grid.38142.3c000000041936754XDepartment of Nutrition, Harvard T.H. Chan School of Public Health, 665 Huntington Avenue, Boston, MA 02115 USA
| | - Fenglei Wang
- grid.38142.3c000000041936754XDepartment of Nutrition, Harvard T.H. Chan School of Public Health, 665 Huntington Avenue, Boston, MA 02115 USA
| | - Jun Li
- grid.38142.3c000000041936754XDepartment of Nutrition, Harvard T.H. Chan School of Public Health, 665 Huntington Avenue, Boston, MA 02115 USA
| | - Kerry L. Ivey
- grid.38142.3c000000041936754XDepartment of Nutrition, Harvard T.H. Chan School of Public Health, 665 Huntington Avenue, Boston, MA 02115 USA ,grid.430453.50000 0004 0565 2606Microbiome and Host Health Programme, South Australian Health and Medical Research Institute, North Terrace, Adelaide, SA 5000 Australia ,grid.1014.40000 0004 0367 2697Department of Nutrition and Dietetics, College of Nursing and Health Sciences, Flinders University, Adelaide, Australia
| | - Jeremy E. Wilkinson
- grid.38142.3c000000041936754X Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA USA
| | - Dong D. Wang
- grid.38142.3c000000041936754XDepartment of Nutrition, Harvard T.H. Chan School of Public Health, 665 Huntington Avenue, Boston, MA 02115 USA ,grid.62560.370000 0004 0378 8294Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA USA
| | - Ruifeng Li
- grid.38142.3c000000041936754XDepartment of Nutrition, Harvard T.H. Chan School of Public Health, 665 Huntington Avenue, Boston, MA 02115 USA
| | - Gang Liu
- grid.38142.3c000000041936754XDepartment of Nutrition, Harvard T.H. Chan School of Public Health, 665 Huntington Avenue, Boston, MA 02115 USA
| | - Heather A. Eliassen
- grid.62560.370000 0004 0378 8294Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA USA ,grid.38142.3c000000041936754XDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA USA
| | - Andrew T. Chan
- grid.62560.370000 0004 0378 8294Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA USA ,grid.38142.3c000000041936754XDepartment of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA USA ,grid.66859.340000 0004 0546 1623Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA USA ,grid.32224.350000 0004 0386 9924Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA USA
| | - Clary B. Clish
- grid.66859.340000 0004 0546 1623Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA USA
| | - Curtis Huttenhower
- grid.38142.3c000000041936754X Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA USA ,grid.66859.340000 0004 0546 1623Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA USA
| | - Frank B. Hu
- grid.38142.3c000000041936754XDepartment of Nutrition, Harvard T.H. Chan School of Public Health, 665 Huntington Avenue, Boston, MA 02115 USA ,grid.62560.370000 0004 0378 8294Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA USA ,grid.38142.3c000000041936754XDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA USA
| | - Qi Sun
- grid.38142.3c000000041936754XDepartment of Nutrition, Harvard T.H. Chan School of Public Health, 665 Huntington Avenue, Boston, MA 02115 USA ,grid.62560.370000 0004 0378 8294Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA USA ,grid.38142.3c000000041936754XDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA USA
| | - Eric B. Rimm
- grid.38142.3c000000041936754XDepartment of Nutrition, Harvard T.H. Chan School of Public Health, 665 Huntington Avenue, Boston, MA 02115 USA ,grid.62560.370000 0004 0378 8294Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA USA ,grid.38142.3c000000041936754XDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA USA
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17
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Li D, Lu Y, Yuan S, Cai X, He Y, Chen J, Wu Q, He D, Fang A, Bo Y, Song P, Bogaert D, Tsilidis K, Larsson SC, Yu H, Zhu H, Theodoratou E, Zhu Y, Li X. Gut microbiota-derived metabolite trimethylamine-N-oxide and multiple health outcomes: an umbrella review and updated meta-analysis. Am J Clin Nutr 2022; 116:230-243. [PMID: 35348578 PMCID: PMC9257469 DOI: 10.1093/ajcn/nqac074] [Citation(s) in RCA: 35] [Impact Index Per Article: 17.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2022] [Accepted: 03/24/2022] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Trimethylamine-N-oxide (TMAO) is a gut microbiota-derived metabolite produced from dietary nutrients. Many studies have discovered that circulating TMAO concentrations are linked to a wide range of health outcomes. OBJECTIVES This study aimed to summarize health outcomes related to circulating TMAO concentrations. METHODS We searched the Embase, Medline, Web of Science, and Scopus databases from inception to 15 February, 2022 to identify and update meta-analyses examining the associations between TMAO and multiple health outcomes. For each health outcome, we estimated the summary effect size, 95% prediction CI, between-study heterogeneity, evidence of small-study effects, and evidence of excess-significance bias. These metrics were used to evaluate the evidence credibility of the identified associations. RESULTS This umbrella review identified 24 meta-analyses that investigated the association between circulating TMAO concentrations and health outcomes including all-cause mortality, cardiovascular diseases (CVDs), diabetes mellitus (DM), cancer, and renal function. We updated these meta-analyses by including a total of 82 individual studies on 18 unique health outcomes. Among them, 14 associations were nominally significant. After evidence credibility assessment, we found 6 (33%) associations (i.e., all-cause mortality, CVD mortality, major adverse cardiovascular events, hypertension, DM, and glomerular filtration rate) to present highly suggestive evidence. CONCLUSIONS TMAO might be a novel biomarker related to human health conditions including all-cause mortality, hypertension, CVD, DM, cancer, and kidney function. Further studies are needed to investigate whether circulating TMAO concentrations could be an intervention target for chronic disease.This review was registered at www.crd.york.ac.uk/prospero/ as CRD42021284730.
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Affiliation(s)
- Doudou Li
- Department of Big Data in Health Science, School of Public Health, Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Ying Lu
- Department of Big Data in Health Science, School of Public Health, Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Shuai Yuan
- Department of Big Data in Health Science, School of Public Health, Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China,Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institute, Stockholm, Sweden
| | - Xiaxia Cai
- Department of Nutrition and Food Hygiene, Beijing Key Laboratory of Environmental Toxicology, School of Public Health, Capital Medical University, Beijing, China
| | - Yuan He
- National Research Institute for Health and Family Planning, Beijing, China
| | - Jie Chen
- Department of Big Data in Health Science, School of Public Health, Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Qiong Wu
- Department of Epidemiology & Biostatistics, School of Public Health, Zhejiang University School of Medicine, Hangzhou, China
| | - Di He
- Department of Epidemiology & Biostatistics, School of Public Health, Zhejiang University School of Medicine, Hangzhou, China
| | - Aiping Fang
- Department of Nutrition, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Yacong Bo
- Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, China
| | - Peige Song
- School of Public Health and Women's Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Debby Bogaert
- Centre for Inflammation Research, University of Edinburgh, Edinburgh, United Kingdom
| | - Kostas Tsilidis
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom,Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece
| | - Susanna C Larsson
- Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institute, Stockholm, Sweden,Unit of Medical Epidemiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
| | - Huanling Yu
- Department of Nutrition and Food Hygiene, Beijing Key Laboratory of Environmental Toxicology, School of Public Health, Capital Medical University, Beijing, China
| | - Huilian Zhu
- Department of Nutrition, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Evropi Theodoratou
- Centre for Global Health, Usher Institute, University of Edinburgh, Edinburgh, United Kingdom,Cancer Research UK Edinburgh Centre, Medical Research Council Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom
| | - Yimin Zhu
- Department of Epidemiology & Biostatistics, School of Public Health, Zhejiang University School of Medicine, Hangzhou, China
| | - Xue Li
- Address correspondence to XL (E-mail: )
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18
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Associations between Serum Betaine, Methyl-Metabolizing Genetic Polymorphisms and Risk of Incident Type 2 Diabetes: A Prospective Cohort Study in Community-Dwelling Chinese Adults. Nutrients 2022; 14:nu14020362. [PMID: 35057543 PMCID: PMC8778868 DOI: 10.3390/nu14020362] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Revised: 01/06/2022] [Accepted: 01/11/2022] [Indexed: 12/21/2022] Open
Abstract
Previous studies have explored associations between betaine and diabetes, but few have considered the effects of genes on them. We aimed to examine associations between serum betaine, methyl-metabolizing genetic polymorphisms and the risk of type 2 diabetes in Chinese adults. This prospective study comprised 1565 subjects aged 40–75 without type 2 diabetes at baseline. Serum betaine was measured by high-performance liquid chromatography tandem mass spectrometry. Genotyping of methyl-metabolizing genes was detected by Illumina ASA-750K arrays. Cox proportional hazards model was used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). During a median of 8.9 years of follow-up, 213 participants developed type 2 diabetes. Compared with participants in the lowest quartile of serum betaine, those in the highest quartile had lower risk of type 2 diabetes, adjusted HRs (95%CIs) was 0.46 (0.31, 0.69). For methylenetetrahydrofolate reductase (MTHFR) G1793A (rs2274976) and MTHFR A1298C (rs1801131), participants carrying 1793GA + AA and 1298AC + CC had lower risk of type 2 diabetes. Interactions of serum betaine and genotype of MTHFR G1793A and MTHFR A1298C could be found influencing type 2 diabetes risk. Our findings indicate that higher serum betaine, mutations of MTHFR G1793A and A1298C, as well as the joint effects of them, are associated with lower risk of type 2 diabetes.
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19
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Krishnan S, O’Connor LE, Wang Y, Gertz ER, Campbell WW, Bennett BJ. Adopting a Mediterranean-style eating pattern with low, but not moderate, unprocessed, lean red meat intake reduces fasting serum trimethylamine N-oxide (TMAO) in adults who are overweight or obese. Br J Nutr 2021; 128:1-21. [PMID: 34823615 PMCID: PMC9133270 DOI: 10.1017/s0007114521004694] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2021] [Revised: 10/27/2021] [Accepted: 11/11/2021] [Indexed: 11/13/2022]
Abstract
A Mediterranean-style eating pattern (MED-EP) may include moderate red meat intake. However, it is unknown if the pro-atherogenic metabolite trimethylamine N-oxide (TMAO) is affected by the amount of red meat consumed with a MED-EP. The results presented are from a secondary, retrospective objective of an investigator-blinded, randomized, crossover, controlled feeding trial (two 5-wk interventions separated by a 4-wk washout) to determine if a MED-EP with 200g unprocessed lean red meat/wk (MED-CONTROL) reduces circulating TMAO concentrations compared to a MED-EP with 500g unprocessed lean red meat/wk (MED-RED). Participants were 27 women and 12 men (n=39 total) who were either overweight or obese (BMI: 30.5 ± 0.3 kg/m2 mean ± SEM). Serum samples were obtained following an overnight fast both before (pre) and after (post) each intervention. Fasting serum TMAO, choline, carnitine, and betaine concentrations were measured using a targeted Liquid chromatography-mass spectrometry. Data were analyzed to assess if (a) TMAO and related metabolites differed by intervention, and (b) if changes in TMAO were associated with changes in Framingham 10-year risk score. Serum TMAO was lower post-intervention following MED-CONTROL compared to MED-RED intervention (post-MED-CONTROL 3.1 ± 0.2 µM vs. post-MED-RED 5.0 ± 0.5 µM, p<0.001), and decreased following MED-CONTROL (pre- vs post-MED-CONTROL, p = 0.025). Exploratory analysis using mixed model analysis of covariance identified a positive association between changes in TMAO and changes in HOMA-IR (p = 0.036). These results suggest that lower amounts of red meat intake leads to lower TMAO concentrations in the context of a MED-EP.
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Affiliation(s)
- Sridevi Krishnan
- Department of Nutrition, University of California-Davis, Davis, CA, USA
| | - Lauren E. O’Connor
- Department of Nutrition Science, Purdue University, West Lafayette, IN, USA
- Division of Cancer Prevention, National Cancer Institute, National Institutes of Health, Rockville, MD, USA
| | - Yu Wang
- Department of Nutrition Science, Purdue University, West Lafayette, IN, USA
| | - Erik R. Gertz
- USDA-Western Human Nutrition Research Center, Davis, CA, USA
| | - Wayne W. Campbell
- Department of Nutrition Science, Purdue University, West Lafayette, IN, USA
| | - Brian J. Bennett
- Department of Nutrition, University of California-Davis, Davis, CA, USA
- USDA-Western Human Nutrition Research Center, Davis, CA, USA
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20
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Flores‐Guerrero JL, Post A, van Dijk PR, Connelly MA, Garcia E, Navis G, Bakker SJL, Dullaart RPF. Circulating trimethylamine-N-oxide is associated with all-cause mortality in subjects with nonalcoholic fatty liver disease. Liver Int 2021; 41:2371-2382. [PMID: 33993608 PMCID: PMC8518486 DOI: 10.1111/liv.14963] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/18/2021] [Revised: 04/16/2021] [Accepted: 05/03/2021] [Indexed: 12/13/2022]
Abstract
BACKGROUND AND AIMS Trimethylamine-N-oxide (TMAO), a gut microbiota-liver metabolite, has been associated with cardiometabolic disease. However, whether TMAO is associated with nonalcoholic fatty liver disease (NAFLD) and NAFLD-related health outcomes remains unclear. We aimed to investigate the association of TMAO with NAFLD and to assess the extent to which the association of TMAO with all-cause mortality is dependent on the presence of NAFLD in the general population. METHODS We included 5292 participants enrolled in the Prevention of Renal and Vascular End-stage Disease (PREVEND) cohort study. Cox proportional-hazards regression analyses were performed to study the association of TMAO with all-cause mortality in subjects with and without a fatty liver index (FLI) ≥60, which was used as a proxy of NAFLD. RESULTS During a median follow-up of 8.2 years, 307 subjects died, of whom 133 were classified with NAFLD. TMAO was positively and independently associated with baseline FLI (Std β 0.08, 95% CI 0.05, 0.11, P < .001). Higher TMAO was associated with increased risk of all-cause mortality in subjects with NAFLD, in crude analysis (hazard ratio [HR] per 1 SD, 2.55, 95% CI 1.60, 4.05, P < .001) and after full adjustment (adj HR 1.90, 95% CI 1.18, 3.04, P = .008). Such an association was not present in subjects without NAFLD (crude HR 1.14, 95% CI 0.81, 1.71, P = .39; adj HR 0.95, 95% CI 0.65, 1.39, P = .78). CONCLUSION This prospective study revealed that plasma concentrations of TMAO were associated with all-cause mortality in subjects with NAFLD, independently of traditional risk factors.
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Affiliation(s)
- Jose L. Flores‐Guerrero
- Department of Internal MedicineDivision of NephrologyUniversity of GroningenUniversity Medical Center GroningenGroningenThe Netherlands
| | - Adrian Post
- Department of Internal MedicineDivision of NephrologyUniversity of GroningenUniversity Medical Center GroningenGroningenThe Netherlands
| | - Peter R. van Dijk
- Department of Internal MedicineDivision of EndocrinologyUniversity of GroningenUniversity Medical Center GroningenGroningenThe Netherlands
| | | | - Erwin Garcia
- Laboratory Corporation of America Holdings (Labcorp)MorrisvilleNCUSA
| | - Gerjan Navis
- Department of Internal MedicineDivision of NephrologyUniversity of GroningenUniversity Medical Center GroningenGroningenThe Netherlands
| | - Stephan J. L. Bakker
- Department of Internal MedicineDivision of NephrologyUniversity of GroningenUniversity Medical Center GroningenGroningenThe Netherlands
| | - Robin P. F. Dullaart
- Department of Internal MedicineDivision of EndocrinologyUniversity of GroningenUniversity Medical Center GroningenGroningenThe Netherlands
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21
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Krueger ES, Lloyd TS, Tessem JS. The Accumulation and Molecular Effects of Trimethylamine N-Oxide on Metabolic Tissues: It's Not All Bad. Nutrients 2021; 13:nu13082873. [PMID: 34445033 PMCID: PMC8400152 DOI: 10.3390/nu13082873] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2021] [Revised: 08/15/2021] [Accepted: 08/19/2021] [Indexed: 02/07/2023] Open
Abstract
Since elevated serum levels of trimethylamine N-oxide (TMAO) were first associated with increased risk of cardiovascular disease (CVD), TMAO research among chronic diseases has grown exponentially. We now know that serum TMAO accumulation begins with dietary choline metabolism across the microbiome-liver-kidney axis, which is typically dysregulated during pathogenesis. While CVD research links TMAO to atherosclerotic mechanisms in vascular tissue, its molecular effects on metabolic tissues are unclear. Here we report the current standing of TMAO research in metabolic disease contexts across relevant tissues including the liver, kidney, brain, adipose, and muscle. Since poor blood glucose management is a hallmark of metabolic diseases, we also explore the variable TMAO effects on insulin resistance and insulin production. Among metabolic tissues, hepatic TMAO research is the most common, whereas its effects on other tissues including the insulin producing pancreatic β-cells are largely unexplored. Studies on diseases including obesity, diabetes, liver diseases, chronic kidney disease, and cognitive diseases reveal that TMAO effects are unique under pathologic conditions compared to healthy controls. We conclude that molecular TMAO effects are highly context-dependent and call for further research to clarify the deleterious and beneficial molecular effects observed in metabolic disease research.
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Affiliation(s)
- Emily S. Krueger
- Department of Nutrition, Dietetics and Food Science, Brigham Young University, Provo, UT 84602, USA; (E.S.K.); (T.S.L.)
| | - Trevor S. Lloyd
- Department of Nutrition, Dietetics and Food Science, Brigham Young University, Provo, UT 84602, USA; (E.S.K.); (T.S.L.)
- Medical Education Program, David Geffen School of Medicine at UCLA, Los Angeles, CA 90095, USA
| | - Jeffery S. Tessem
- Department of Nutrition, Dietetics and Food Science, Brigham Young University, Provo, UT 84602, USA; (E.S.K.); (T.S.L.)
- Correspondence: ; Tel.: +1-801-422-9082
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22
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Lemaitre RN, Jensen PN, Wang Z, Fretts AM, McKnight B, Nemet I, Biggs ML, Sotoodehnia N, de Oliveira Otto MC, Psaty BM, Siscovick DS, Hazen SL, Mozaffarian D. Association of Trimethylamine N-Oxide and Related Metabolites in Plasma and Incident Type 2 Diabetes: The Cardiovascular Health Study. JAMA Netw Open 2021; 4:e2122844. [PMID: 34448864 PMCID: PMC8397925 DOI: 10.1001/jamanetworkopen.2021.22844] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
IMPORTANCE Although rodent studies suggest that trimethylamine N-oxide (TMAO) influences glucose homeostasis and risk of type 2 diabetes, evidence in humans is limited. OBJECTIVE To examine the associations of serial measures of plasma TMAO and related metabolite concentrations with incident type 2 diabetes, fasting plasma insulin and glucose levels, and the Gutt insulin sensitivity index (ISI). DESIGN, SETTING, AND PARTICIPANTS This prospective cohort design assessed the association of plasma TMAO and related metabolite concentrations with diabetes outcome, whereas a cross-sectional design assessed the association with insulin and glucose levels and Gutt ISI. The participants were a cohort of older US adults from the Cardiovascular Health Study (CHS). Data from June 1989 to May 1990, from November 1992 to June 1993, and from June 1995 to June 1997 were included, with follow-up through June 2010. Levels of TMAO and related metabolites were measured in CHS plasma samples. Data were analyzed from July 2019 to September 2020. EXPOSURES Plasma concentrations of TMAO, carnitine, betaine, choline, crotonobetaine, and γ-butyrobetaine, measured by high-performance liquid chromatography and mass spectrometry. MAIN OUTCOMES AND MEASURES Linear regression for associations of TMAO and related metabolites with insulin and glucose levels and Gutt ISI, and proportional hazards regression for associations with diabetes. RESULTS The study included 4442 participants without diabetes at baseline (mean [SD] age, 73 [6] years at entry; 2710 [61%] women). In multivariable analyses, plasma TMAO, carnitine, crotonobetaine, and γ-butyrobetaine concentrations were positively associated with fasting insulin level (insulin mean geometric ratio comparing fifth with first quintiles of metabolite concentration: 1.07 [95% CI, 1.04-1.10] for TMAO; 1.07 [95% CI, 1.03-1.10] for carnitine; 1.05 [95% CI, 1.02-1.08] for crotonobetaine; and 1.06 [95% CI, 1.02-1.09] for γ-butyrobetaine). In contrast, betaine and choline concentrations were associated with greater insulin sensitivity (mean difference in Gutt ISI comparing fifth with first quintiles: 6.46 [95% CI, 4.32-8.60] and 2.27 [95% CI, 0.16-4.38], respectively). Incident diabetes was identified in 661 participants during a median 12.1 (interquartile range, 6.9-17.1) years of follow-up. In multivariable analyses, TMAO and metabolites were not significantly associated with type 2 diabetes risk (hazard ratios of diabetes comparing fifth with first quintile: 1.20 [95% CI, 0.94-1.55] for TMAO; 0.96 [95% CI, 0.74-1.24] for choline; 0.88 [95% CI, 0.67-1.15] for betaine; 1.07 [95% CI, 0.83-1.37] for carnitine; 0.79 [95% CI, 0.60-1.04] for γ-butyrobetaine; and 1.06 [95% CI, 0.83-1.35] for crotonobetaine). CONCLUSIONS AND RELEVANCE Plasma TMAO and related metabolites were not significantly associated with type 2 diabetes among older adults. The metabolites TMAO, carnitine, γ-butyrobetaine, and crotonobetaine may be associated with insulin resistance, and betaine and choline may be associated with greater insulin sensitivity, but temporality of the associations was not established.
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Affiliation(s)
- Rozenn N. Lemaitre
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle
| | - Paul N. Jensen
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle
| | - Zeneng Wang
- Department of Cardiovascular and Metabolic Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio
| | | | | | - Ina Nemet
- Department of Cardiovascular and Metabolic Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio
| | - Mary L. Biggs
- Department of Biostatistics, University of Washington, Seattle
| | - Nona Sotoodehnia
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle
- Division of Cardiology, University of Washington, Seattle
| | - Marcia C. de Oliveira Otto
- Division of Epidemiology, Human Genetics and Environmental Science, School of Public Health, The University of Texas Health Science Center at Houston
| | - Bruce M. Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle
- Department of Epidemiology, University of Washington, Seattle
- Kaiser Permanente Washington Health Research Institute, Seattle
| | | | - Stanley L. Hazen
- Department of Cardiovascular and Metabolic Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio
- Department of Cardiovascular Medicine, Heart, Vascular and Thoracic Institute, Cleveland Clinic, Cleveland, Ohio
| | - Dariush Mozaffarian
- Friedman School of Nutrition Science and Policy, Tufts University, Boston, Massachusetts
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23
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He S, Jiang H, Zhuo C, Jiang W. Trimethylamine/Trimethylamine-N-Oxide as a Key Between Diet and Cardiovascular Diseases. Cardiovasc Toxicol 2021; 21:593-604. [PMID: 34003426 DOI: 10.1007/s12012-021-09656-z] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/23/2021] [Accepted: 04/27/2021] [Indexed: 02/08/2023]
Abstract
Trimethylamine (TMA) is a gut microbiota-derived metabolite which comes from diets rich of choline, betaine or L-carnitine and could be further converted to Trimethylamine-N-oxide (TMAO) in the liver. As the function of gut microbiota and its metabolites being explored so far, studies suggest that TMAO may be a potential risk factor of cardiovascular diseases independent of other traditional risk factors. However, the precise role of TMAO is controversial as some converse results were discovered. In recent studies, it is hypothesized that TMA may also participate in the progression of cardiovascular diseases and some cytotoxic effect of TMA has been discovered. Thus, exploring the relationship between TMA, TMAO and CVD may bring a novel insight into the diagnosis and therapy of cardiovascular diseases. In this review, we discussed the factors which influence the TMA/TMAO's process of metabolism in the human body. We have also summarized the pathogenic effect of TMA/TMAO in cardiovascular diseases, as well as the limitation of some controversial discoveries.
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Affiliation(s)
- Siyu He
- West China School of Medicine, West China Hospital, Sichuan University, Chengdu, 610041, People's Republic of China
| | - Hong Jiang
- West China School of Medicine, West China Hospital, Sichuan University, Chengdu, 610041, People's Republic of China
| | - Caili Zhuo
- The Laboratory of Cardiovascular Diseases, Molecular Medicine Research Center, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, 610041, Sichuan, People's Republic of China
| | - Wei Jiang
- The Laboratory of Cardiovascular Diseases, Molecular Medicine Research Center, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, 610041, Sichuan, People's Republic of China.
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24
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Galié S, García-Gavilán J, Papandreou C, Camacho-Barcía L, Arcelin P, Palau-Galindo A, Rabassa A, Bulló M. Effects of Mediterranean Diet on plasma metabolites and their relationship with insulin resistance and gut microbiota composition in a crossover randomized clinical trial. Clin Nutr 2021; 40:3798-3806. [PMID: 34130026 DOI: 10.1016/j.clnu.2021.04.028] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2021] [Revised: 04/14/2021] [Accepted: 04/17/2021] [Indexed: 12/18/2022]
Abstract
BACKGROUND & AIMS The Mediterranean Diet (MedDiet) may decrease the cardiometabolic risk through modulation of metabolic pathways. Furthermore, the interplay between MedDiet, metabolites and microbial metabolism may improve our understanding on the metabolic effects of this diet. We aimed to evaluate the effect of the MedDiet compared to nuts supplementation on circulating metabolites and their relationship with cardiometabolic health. We further examined whether changes in the metabolomic profiles were associated with changes in gut microbiota composition in a multi-omics integrative approach. METHODS Forty-four adults with Metabolic Syndrome (MetS), (aged 37-65) participated in a randomized controlled, crossover 2-months dietary-intervention trial with a 1-month wash-out period, consuming a MedDiet or a non MedDiet plus nuts (50 g/day). Nutritional data were collected at the beginning and the end of each intervention period using 3-day dietary records, as well as fasting blood and fecal samples. Plasma metabolites (m = 378) were profiled using targeted metabolomics. Associations of these metabolites with the interventions were assessed with elastic net regression analyses. Gut microbiota composition was assessed by 16S rRNA sequencing. A sparse least regression analysis combined with a canonical correlation analysis was conducted between the plasma selected metabolites and genera in order to identify the relevant dual-omics signatures discriminating the dietary interventions. RESULTS Changes in 65 circulating metabolites were significantly associated with the MedDiet (mainly lipids, acylcarnitines, amino acids, steroids and TCA intermediates). Importantly, these changes were associated with decreases in glucose, insulin and HOMA-IR. The network analysis identified two main clusters of genera with an opposite behaviour towards selected metabolites, mainly PC species, ChoE(20:5), TGs and medium/long-chain acylcarnitines. CONCLUSION Following a MedDiet, rather than consuming nuts in the context of a non-MedDiet was associated with a specific plasma metabolomic profile, which was also related to metabolic improvements in adults with MetS. The identified correlated network between specific bacteria and metabolites suggests interplay between diet, circulating metabolites and gut microbiota. The trial was registered in the ISRCTN with identifier ISRCTN88780852, https://doi.org/10.1186/ISRCTN88780852.
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Affiliation(s)
- Serena Galié
- Department of Biochemistry and Biotechnology, Faculty of Medicine and Health Sciences, University Rovira i Virgili (URV), Reus, Spain; Institute of Health Pere Virgili, IISPV, University Hospital Sant Joan, Reus, Spain; Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain
| | - Jesús García-Gavilán
- Department of Biochemistry and Biotechnology, Faculty of Medicine and Health Sciences, University Rovira i Virgili (URV), Reus, Spain; Institute of Health Pere Virgili, IISPV, University Hospital Sant Joan, Reus, Spain; Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain
| | - Christopher Papandreou
- Department of Biochemistry and Biotechnology, Faculty of Medicine and Health Sciences, University Rovira i Virgili (URV), Reus, Spain; Institute of Health Pere Virgili, IISPV, University Hospital Sant Joan, Reus, Spain; Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain.
| | - Lucía Camacho-Barcía
- Department of Biochemistry and Biotechnology, Faculty of Medicine and Health Sciences, University Rovira i Virgili (URV), Reus, Spain; Institute of Health Pere Virgili, IISPV, University Hospital Sant Joan, Reus, Spain; Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain
| | - Pierre Arcelin
- ABS Reus V. Centre d'Assistència Primària Marià Fortuny, SAGESSA, Reus, Spain
| | | | - Antoni Rabassa
- Institute of Health Pere Virgili, IISPV, University Hospital Sant Joan, Reus, Spain
| | - Mònica Bulló
- Department of Biochemistry and Biotechnology, Faculty of Medicine and Health Sciences, University Rovira i Virgili (URV), Reus, Spain; Institute of Health Pere Virgili, IISPV, University Hospital Sant Joan, Reus, Spain; Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain.
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25
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Bulló M, Papandreou C, Ruiz-Canela M, Guasch-Ferré M, Li J, Hernández-Alonso P, Toledo E, Liang L, Razquin C, Corella D, Estruch R, Ros E, Fitó M, Arós F, Fiol M, Serra-Majem L, Clish CB, Becerra-Tomás N, Martínez-González MA, Hu FB, Salas-Salvadó J. Plasma Metabolomic Profiles of Glycemic Index, Glycemic Load, and Carbohydrate Quality Index in the PREDIMED Study. J Nutr 2021; 151:50-58. [PMID: 33296468 PMCID: PMC7779218 DOI: 10.1093/jn/nxaa345] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2020] [Revised: 09/10/2020] [Accepted: 10/07/2020] [Indexed: 12/18/2022] Open
Abstract
BACKGROUND The quality of carbohydrate consumed, assessed by the glycemic index (GI), glycemic load (GL), or carbohydrate quality index (CQI), affects the postprandial glycemic and insulinemic responses, which have been implicated in the etiology of several chronic diseases. However, it is unclear whether plasma metabolites involved in different biological pathways could provide functional insights into the role of carbohydrate quality indices in health. OBJECTIVES We aimed to identify plasma metabolomic profiles associated with dietary GI, GL, and CQI. METHODS The present study is a cross-sectional analysis of 1833 participants with overweight/obesity (mean age = 67 y) from 2 case-cohort studies nested within the PREDIMED (Prevención con Dieta Mediterránea) trial. Data extracted from validated FFQs were used to estimate the GI, GL, and CQI. Plasma concentrations of 385 metabolites were profiled with LC coupled to MS and associations of these metabolites with those indices were assessed with elastic net regression analyses. RESULTS A total of 58, 18, and 57 metabolites were selected for GI, GL, and CQI, respectively. Choline, cotinine, γ-butyrobetaine, and 36:3 phosphatidylserine plasmalogen were positively associated with GI and GL, whereas they were negatively associated with CQI. Fructose-glucose-galactose was negatively and positively associated with GI/GL and CQI, respectively. Consistent associations of 21 metabolites with both GI and CQI were found but in opposite directions. Negative associations of kynurenic acid, 22:1 sphingomyelin, and 38:6 phosphatidylethanolamine, as well as positive associations of 32:1 phosphatidylcholine with GI and GL were also observed. Pearson correlation coefficients between GI, GL, and CQI and the metabolomic profiles were 0.30, 0.22, and 0.27, respectively. CONCLUSIONS The GI, GL, and CQI were associated with specific metabolomic profiles in a Mediterranean population at high cardiovascular disease risk. Our findings may help in understanding the role of dietary carbohydrate indices in the development of cardiometabolic disorders. This trial was registered at isrctn.com as ISRCTN35739639.
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Affiliation(s)
- Mònica Bulló
- Universitat Rovira i Virgili, Biochemistry and Biotechnology Department, Human Nutrition Unit, Reus, Spain
- Pere i Virgili Health Research Institute (IISPV), Reus, Spain
- CIBER Physiopathology of Obesity and Nutrition (CIBERobn), Institute of Health Carlos III, Madrid, Spain
- Nutrition Unit, University Hospital of Sant Joan de Reus, Reus, Spain
| | - Christopher Papandreou
- Universitat Rovira i Virgili, Biochemistry and Biotechnology Department, Human Nutrition Unit, Reus, Spain
- Pere i Virgili Health Research Institute (IISPV), Reus, Spain
- CIBER Physiopathology of Obesity and Nutrition (CIBERobn), Institute of Health Carlos III, Madrid, Spain
- Nutrition Unit, University Hospital of Sant Joan de Reus, Reus, Spain
| | - Miguel Ruiz-Canela
- CIBER Physiopathology of Obesity and Nutrition (CIBERobn), Institute of Health Carlos III, Madrid, Spain
- Department of Preventive Medicine and Public Health, University of Navarra, Pamplona, Spain
- Navarra Institute for Health Research (IdiSNA), Pamplona, Navarra, Spain
| | - Marta Guasch-Ferré
- Department of Nutrition, Harvard TH Chan School of Public Health, Boston, MA, USA
| | - Jun Li
- Department of Nutrition, Harvard TH Chan School of Public Health, Boston, MA, USA
- Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA, USA
| | - Pablo Hernández-Alonso
- Universitat Rovira i Virgili, Biochemistry and Biotechnology Department, Human Nutrition Unit, Reus, Spain
- Pere i Virgili Health Research Institute (IISPV), Reus, Spain
- CIBER Physiopathology of Obesity and Nutrition (CIBERobn), Institute of Health Carlos III, Madrid, Spain
- Nutrition Unit, University Hospital of Sant Joan de Reus, Reus, Spain
- Department of Endocrinology and Nutrition, Virgen de la Victoria University Hospital, University of Malaga (IBIMA), Malaga, Spain
| | - Estefania Toledo
- CIBER Physiopathology of Obesity and Nutrition (CIBERobn), Institute of Health Carlos III, Madrid, Spain
- Department of Preventive Medicine and Public Health, University of Navarra, Pamplona, Spain
- Navarra Institute for Health Research (IdiSNA), Pamplona, Navarra, Spain
| | - Liming Liang
- Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA, USA
- Department of Statistics, Harvard TH Chan School of Public Health, Boston, MA, USA
| | - Cristina Razquin
- CIBER Physiopathology of Obesity and Nutrition (CIBERobn), Institute of Health Carlos III, Madrid, Spain
- Department of Preventive Medicine and Public Health, University of Navarra, Pamplona, Spain
- Navarra Institute for Health Research (IdiSNA), Pamplona, Navarra, Spain
| | - Dolores Corella
- CIBER Physiopathology of Obesity and Nutrition (CIBERobn), Institute of Health Carlos III, Madrid, Spain
- Department of Preventive Medicine, University of Valencia, Valencia, Spain
| | - Ramon Estruch
- CIBER Physiopathology of Obesity and Nutrition (CIBERobn), Institute of Health Carlos III, Madrid, Spain
- Department of Internal Medicine, Hospital Clínic, University of Barcelona, Barcelona, Spain
- August Pi i Sunyer Biomedical Research Institute (IDIBAPS), Hospital Clinic, University of Barcelona, Barcelona, Spain
| | - Emilio Ros
- CIBER Physiopathology of Obesity and Nutrition (CIBERobn), Institute of Health Carlos III, Madrid, Spain
- August Pi i Sunyer Biomedical Research Institute (IDIBAPS), Hospital Clinic, University of Barcelona, Barcelona, Spain
- Lipid Clinic, Department of Endocrinology and Nutrition, Hospital Clínic, University of Barcelona, Barcelona, Spain
| | - Montserrat Fitó
- CIBER Physiopathology of Obesity and Nutrition (CIBERobn), Institute of Health Carlos III, Madrid, Spain
- Cardiovascular and Nutrition Research Group, Hospital del Mar Medical Research Institute, Barcelona, Spain
| | - Fernando Arós
- CIBER Physiopathology of Obesity and Nutrition (CIBERobn), Institute of Health Carlos III, Madrid, Spain
- Department of Cardiology, University Hospital of Alava, Vitoria, Spain
| | - Miquel Fiol
- CIBER Physiopathology of Obesity and Nutrition (CIBERobn), Institute of Health Carlos III, Madrid, Spain
- Institute of Health Sciences (IUNICS), University of Balearic Islands and Hospital Son Espases, Palma de Mallorca, Spain
| | - Lluís Serra-Majem
- CIBER Physiopathology of Obesity and Nutrition (CIBERobn), Institute of Health Carlos III, Madrid, Spain
- Research Institute of Biomedical and Health Sciences (IUIBS), University of Las Palmas de Gran Canaria, Las Palmas, Spain
| | - Clary B Clish
- Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA, USA
| | - Nerea Becerra-Tomás
- Universitat Rovira i Virgili, Biochemistry and Biotechnology Department, Human Nutrition Unit, Reus, Spain
- Pere i Virgili Health Research Institute (IISPV), Reus, Spain
- CIBER Physiopathology of Obesity and Nutrition (CIBERobn), Institute of Health Carlos III, Madrid, Spain
- Nutrition Unit, University Hospital of Sant Joan de Reus, Reus, Spain
| | - Miguel A Martínez-González
- CIBER Physiopathology of Obesity and Nutrition (CIBERobn), Institute of Health Carlos III, Madrid, Spain
- Department of Preventive Medicine and Public Health, University of Navarra, Pamplona, Spain
- Navarra Institute for Health Research (IdiSNA), Pamplona, Navarra, Spain
- Department of Nutrition, Harvard TH Chan School of Public Health, Boston, MA, USA
| | - Frank B Hu
- Department of Nutrition, Harvard TH Chan School of Public Health, Boston, MA, USA
- Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA, USA
- Channing Division for Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Jordi Salas-Salvadó
- Universitat Rovira i Virgili, Biochemistry and Biotechnology Department, Human Nutrition Unit, Reus, Spain
- Pere i Virgili Health Research Institute (IISPV), Reus, Spain
- CIBER Physiopathology of Obesity and Nutrition (CIBERobn), Institute of Health Carlos III, Madrid, Spain
- Nutrition Unit, University Hospital of Sant Joan de Reus, Reus, Spain
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Gong X, Du Y, Li X, Yang J, Zhang X, Wei Y, Zhao Y. Maternal Plasma Betaine in Middle Pregnancy Was Associated with Decreased Risk of GDM in Twin Pregnancy: A Cohort Study. Diabetes Metab Syndr Obes 2021; 14:2495-2504. [PMID: 34113141 PMCID: PMC8184138 DOI: 10.2147/dmso.s312334] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/23/2021] [Accepted: 05/08/2021] [Indexed: 11/23/2022] Open
Abstract
PURPOSE Although previous studies have shown that choline-related metabolites in one carbon metabolism (OCM) were related to gestational diabetes mellitus (GDM) risk in singleton pregnancy, their role in twin gestations remains unclear. We aimed to investigate the associations between choline, betaine, methionine, dimethylglycine (DMG), trimethylamine N-oxide (TMAO) and GDM risk among women with twin gestations. PATIENTS AND METHODS This hospital-based cohort study included 187 women with dichorionic twin gestations. Blood samples were collected during pregnancy at a median of 16.1 weeks of gestation (IQR: 13.9 -17.9). Concentrations of plasma metabolites were measured by HPLC-triple quadrupole MS. Log-binomial regression models were applied to estimate the associations between plasma metabolites and the risk of GDM. RESULTS A total of 57 (30.5%) GDM cases were diagnosed over the study follow-up. Eighty-seven percent of women conceived through ART. Plasma betaine had an inverse association with GDM risk, and the adjusted RR of GDM comparing the highest tertile with the lowest tertile was 0.41 (95% CI: 0.19-0.86, P trend=0.015). Women with a high betaine/choline ratio or a low DMG/betaine ratio were at decreased GDM risk (P trend=0.031 or 0.001, respectively). Plasma choline, methionine, DMG and TMAO were not associated with GDM risk. CONCLUSION Among women with dichorionic twin gestations, higher plasma level of betaine in the second trimester was associated with lower risk of GDM. This finding needs further confirmation.
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Affiliation(s)
- Xiaoli Gong
- Department of Obstetrics and Gynecology, National Clinical Research Center for Obstetrics and Gynecology, National Center for Healthcare Quality Management in Obstetrics, Peking University Third Hospital, Beijing, 100191, People’s Republic of China
| | - Yufeng Du
- Department of Epidemiology and Statistics, School of Public Health, Lanzhou University, Lanzhou, 730000, People’s Republic of China
| | - Xiaona Li
- Department of Pharmacy, Peking University Third Hospital, Beijing, 100191, People’s Republic of China
| | - Jing Yang
- Department of Obstetrics and Gynecology, National Clinical Research Center for Obstetrics and Gynecology, National Center for Healthcare Quality Management in Obstetrics, Peking University Third Hospital, Beijing, 100191, People’s Republic of China
| | - Xinyuan Zhang
- Department of Obstetrics and Gynecology, National Clinical Research Center for Obstetrics and Gynecology, National Center for Healthcare Quality Management in Obstetrics, Peking University Third Hospital, Beijing, 100191, People’s Republic of China
| | - Yuan Wei
- Department of Obstetrics and Gynecology, National Clinical Research Center for Obstetrics and Gynecology, National Center for Healthcare Quality Management in Obstetrics, Peking University Third Hospital, Beijing, 100191, People’s Republic of China
| | - Yangyu Zhao
- Department of Obstetrics and Gynecology, National Clinical Research Center for Obstetrics and Gynecology, National Center for Healthcare Quality Management in Obstetrics, Peking University Third Hospital, Beijing, 100191, People’s Republic of China
- Correspondence: Yangyu Zhao; Yuan Wei Email ;
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Gut microbiota-derived metabolite trimethylamine N-oxide as a biomarker in early Parkinson's disease. Nutrition 2020; 83:111090. [PMID: 33418492 DOI: 10.1016/j.nut.2020.111090] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2020] [Revised: 11/07/2020] [Accepted: 11/09/2020] [Indexed: 12/19/2022]
Abstract
OBJECTIVES This study aimed to investigate the potential of using changes in the plasma levels of trimethylamine N-oxide (TMAO), a gut microbiota-derived metabolite, as a biomarker in early Parkinson's disease (PD). METHODS Plasma TMAO levels were measured in 85 patients with drug-naïve early stage PD and 20 healthy controls. A linear mixed model was used to assess longitudinal changes in levodopa-equivalent dose (LED) during follow-up (>2 y) in three tertile PD groups according to plasma TMAO levels. Additionally, a Cox regression analysis was performed to assess the effect of plasma TMAO levels on dementia conversion. RESULTS Plasma TMAO levels of patients with PD were lower than those of healthy controls. A linear mixed model demonstrated that patients with PD and lower levels of TMAO (<4.75 μmol/L; i.e., lowest tertile group) exhibited faster increases in LED over time. The Cox regression model did not reveal that plasma TMAO level was associated with the risk for dementia conversion (P = 0.488). However, when we divided patients with PD into two subgroups according to bet cutoff TMAO level to maximize the log-rank statistics, the PD group with a low plasma TMAO level (<6.92 μmol/L) had a higher risk (with borderline statistical significance) for PD-dementia conversion than the group with a high TMAO level (hazard ratio: 7.565; 95% confidence interval, 1.004-57.019; P = 0.050). CONCLUSIONS The results demonstrate that lower baseline plasma TMAO levels are associated with faster increases in LED and tend to increase the risk for PD-dementia conversion, suggesting the prognostic implications of TMAO in early stage PD.
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Gut microbiota-dependent Trimethylamine N-Oxide are related with hip fracture in postmenopausal women: a matched case-control study. Aging (Albany NY) 2020; 12:10633-10641. [PMID: 32482913 PMCID: PMC7346070 DOI: 10.18632/aging.103283] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2019] [Accepted: 04/27/2020] [Indexed: 12/11/2022]
Abstract
The study evaluates the serum levels of Trimethylamine N-Oxide (TMAO), a gut microbial metabolite, in 286 postmenopausal women with hip fracture. From January 1, 2018 to December 31, 2018, eligible patients were included. Same women without fracture mated age were enrolled. TMAO serum levels were tested by ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS). The serum levels of TMAO were significantly higher in patients with hip fracture than in those controls (P<0.001). The serum levels of TMAO were also higher in patients with hip fracture only than in those who also had upper limb fracture (P=0.001). High level of TMAO was proved a predictor of both hip fracture and had upper limb fracture combined hip fracture, after the adjustment of other existing risk factors [e.g., for each 1 uM increase of TMAO, odd ratio 1.16 (95% CI, 1.07–1.25), P < 0.001; and 1.12 (95% CI, 1.03–1.26), P=0.008, respectively]. In summary, increased TMAO serum levels associated with high risk of hip fracture, suggesting that increase TMAO may contribute to osteoporosis and fracture in postmenopausal women.
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29
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Papandreou C, Moré M, Bellamine A. Trimethylamine N-Oxide in Relation to Cardiometabolic Health-Cause or Effect? Nutrients 2020; 12:E1330. [PMID: 32392758 PMCID: PMC7284902 DOI: 10.3390/nu12051330] [Citation(s) in RCA: 74] [Impact Index Per Article: 18.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2020] [Revised: 04/29/2020] [Accepted: 05/04/2020] [Indexed: 12/19/2022] Open
Abstract
Trimethylamine-N-oxide (TMAO) is generated in a microbial-mammalian co-metabolic pathway mainly from the digestion of meat-containing food and dietary quaternary amines such as phosphatidylcholine, choline, betaine, or L-carnitine. Fish intake provides a direct significant source of TMAO. Human observational studies previously reported a positive relationship between plasma TMAO concentrations and cardiometabolic diseases. Discrepancies and inconsistencies of recent investigations and previous studies questioned the role of TMAO in these diseases. Several animal studies reported neutral or even beneficial effects of TMAO or its precursors in cardiovascular disease model systems, supporting the clinically proven beneficial effects of its precursor, L-carnitine, or a sea-food rich diet (naturally containing TMAO) on cardiometabolic health. In this review, we summarize recent preclinical and epidemiological evidence on the effects of TMAO, in order to shed some light on the role of TMAO in cardiometabolic diseases, particularly as related to the microbiome.
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30
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Virtanen JK, Tuomainen TP, Voutilainen S. Dietary intake of choline and phosphatidylcholine and risk of type 2 diabetes in men: The Kuopio Ischaemic Heart Disease Risk Factor Study. Eur J Nutr 2020; 59:3857-3861. [PMID: 32198672 PMCID: PMC7669791 DOI: 10.1007/s00394-020-02223-2] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2019] [Accepted: 03/09/2020] [Indexed: 11/27/2022]
Abstract
PURPOSE To investigate associations of total dietary choline intake and its major dietary form, phosphatidylcholine, with type 2 diabetes risk. METHODS We included 2332 men aged 42-60 years at baseline in 1984-1989 from the Kuopio Ischaemic Heart Disease Risk Factor Study in eastern Finland. Dietary intakes were assessed with 4-d food recording at baseline. Type 2 diabetes diagnosis was based on self-administered questionnaires, fasting and 2-h oral glucose tolerance test blood glucose measurements, or by record linkage to national health registries. Multivariable-adjusted Cox proportional hazards regression models were used for statistical analysis. RESULTS During the mean 19.3-year follow-up, 432 men had type 2 diabetes diagnosis. After multivariable adjustments, those in the highest vs. lowest choline intake quartile had 25% (95% CI 2-43%) lower relative risk (P trend across quartiles = 0.02) and those in the highest vs. lowest phosphatidylcholine quartile had 41% (95% CI 22-55%) lower relative risk (P trend < 0.001) of type 2 diabetes. CONCLUSIONS Higher choline intake, especially phosphatidylcholine, was associated with lower type 2 diabetes risk among men.
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Affiliation(s)
- Jyrki K Virtanen
- Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland.
| | - Tomi-Pekka Tuomainen
- Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland
| | - Sari Voutilainen
- Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland
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31
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Gibson R, Lau CHE, Loo RL, Ebbels TMD, Chekmeneva E, Dyer AR, Miura K, Ueshima H, Zhao L, Daviglus ML, Stamler J, Van Horn L, Elliott P, Holmes E, Chan Q. The association of fish consumption and its urinary metabolites with cardiovascular risk factors: the International Study of Macro-/Micronutrients and Blood Pressure (INTERMAP). Am J Clin Nutr 2020; 111:280-290. [PMID: 31782492 PMCID: PMC6997096 DOI: 10.1093/ajcn/nqz293] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2019] [Accepted: 10/30/2019] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND Results from observational studies regarding associations between fish (including shellfish) intake and cardiovascular disease risk factors, including blood pressure (BP) and BMI, are inconsistent. OBJECTIVE To investigate associations of fish consumption and associated urinary metabolites with BP and BMI in free-living populations. METHODS We used cross-sectional data from the International Study of Macro-/Micronutrients and Blood Pressure (INTERMAP), including 4680 men and women (40-59 y) from Japan, China, the United Kingdom, and United States. Dietary intakes were assessed by four 24-h dietary recalls and BP from 8 measurements. Urinary metabolites (2 timed 24-h urinary samples) associated with fish intake acquired from NMR spectroscopy were identified. Linear models were used to estimate BP and BMI differences across categories of intake and per 2 SD higher intake of fish and its biomarkers. RESULTS No significant associations were observed between fish intake and BP. There was a direct association with fish intake and BMI in the Japanese population sample (P trend = 0.03; fully adjusted model). In Japan, trimethylamine-N-oxide (TMAO) and taurine, respectively, demonstrated area under the receiver operating characteristic curve (AUC) values of 0.81 and 0.78 in discriminating high against low fish intake, whereas homarine (a metabolite found in shellfish muscle) demonstrated an AUC of 0.80 for high/nonshellfish intake. Direct associations were observed between urinary TMAO and BMI for all regions except Japan (P < 0.0001) and in Western populations between TMAO and BP (diastolic blood pressure: mean difference 1.28; 95% CI: 0.55, 2.02 mmHg; P = 0.0006, systolic blood pressure: mean difference 1.67; 95% CI: 0.60, 2.73 mmHg; P = 0.002). CONCLUSIONS Urinary TMAO showed a stronger association with fish intake in the Japanese compared with the Western population sample. Urinary TMAO was directly associated with BP in the Western but not the Japanese population sample. Associations between fish intake and its biomarkers and downstream associations with BP/BMI appear to be context specific. INTERMAP is registered at www.clinicaltrials.gov as NCT00005271.
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Affiliation(s)
- Rachel Gibson
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom
- Department of Nutritional Sciences, School of Life Course Sciences, King's College London, London, United Kingdom
| | - Chung-Ho E Lau
- Division of Diabetes Endocrinology and Metabolism, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, United Kingdom
| | - Ruey Leng Loo
- Institute of Health Futures, Murdoch University, Perth, Western Australia, Australia
| | - Timothy M D Ebbels
- Division of System Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, United Kingdom
| | - Elena Chekmeneva
- National Institute for Health Research–British Research Council, Clinical Phenotyping Centre, Department of Surgery and Cancer, Imperial College London, London, United Kingdom
| | - Alan R Dyer
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Katsuyuki Miura
- Department of Public Health, Shiga University of Medical Science, Otsu, Shiga, Japan
| | - Hirotsugu Ueshima
- Department of Public Health, Shiga University of Medical Science, Otsu, Shiga, Japan
| | - Liancheng Zhao
- Department of Epidemiology, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China
| | - Martha L Daviglus
- Institute for Minority Health Research, University of Illinois at Chicago, Chicago, IL, USA
| | - Jeremiah Stamler
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Linda Van Horn
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Paul Elliott
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom
- Health Data Research UK London, Imperial College London, London, United Kingdom
| | - Elaine Holmes
- Division of Diabetes Endocrinology and Metabolism, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, United Kingdom
- Institute of Health Futures, Murdoch University, Perth, Western Australia, Australia
| | - Queenie Chan
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom
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32
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Roy S, Yuzefpolskaya M, Nandakumar R, Colombo PC, Demmer RT. Plasma Trimethylamine-N-oxide and impaired glucose regulation: Results from The Oral Infections, Glucose Intolerance and Insulin Resistance Study (ORIGINS). PLoS One 2020; 15:e0227482. [PMID: 31940332 PMCID: PMC6961885 DOI: 10.1371/journal.pone.0227482] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2019] [Accepted: 12/19/2019] [Indexed: 01/05/2023] Open
Abstract
Trimethylamine-N-oxide (TMAO)–a gut-microbiota metabolite–is a biomarker of cardiometabolic risk. No studies have investigated TMAO as an early biomarker of longitudinal glucose increase or prevalent impaired glucose regulation. In a longitudinal cohort study, 300 diabetes-free men and women (77%) aged 20–55 years (mean = 34±10) were enrolled at baseline and re-examined at 2-years to investigate the association between TMAO and biomarkers of diabetes risk. Plasma TMAO was measured using Ultra Performance Liquid Chromatography-Mass Spectrometry. After an overnight fast, FPG was measured longitudinally, HbA1C and insulin were measured only at baseline. Insulin resistance was defined using HOMA-IR. Multivariable generalized linear models regressed; i) FPG change (year 2 minus baseline) on baseline TMAO tertiles; and ii) HOMA-IR and HbA1c on TMAO tertiles. Multivariable relative risk regressions modeled prevalent prediabetes across TMAO tertiles. Mean values of 2-year longitudinal FPG±SE across tertiles of TMAO were 86.6±0.9, 86.7±0.9, 86.4±0.9 (p = 0.98). Trends were null for FPG, HbA1c, HOMA-IR, cross-sectionally. The prevalence ratio of prediabetes among participants in 2nd and 3rd TMAO tertiles (vs. the 1st) were 1.94 [95%CI 1.09–3.48] and 1.41 [95%CI: 0.76–2.61]. TMAO levels are associated with increased prevalence of prediabetes in a nonlinear fashion but not with insulin resistance or longitudinal FPG change.
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Affiliation(s)
- Sumith Roy
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, United States of America
| | - Melana Yuzefpolskaya
- Division of Cardiology, Department of Medicine, New York Presbyterian Hospital, Columbia University, New York, NY, United States of America
| | - Renu Nandakumar
- Irving Institute for Clinical and Translational Research, Columbia University Medical Center, New York, NY, United States of America
| | - Paolo C. Colombo
- Division of Cardiology, Department of Medicine, New York Presbyterian Hospital, Columbia University, New York, NY, United States of America
| | - Ryan T. Demmer
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, United States of America
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, United States of America
- * E-mail:
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High Betaine, a Trimethylamine N-Oxide Related Metabolite, Is Prospectively Associated with Low Future Risk of Type 2 Diabetes Mellitus in the PREVEND Study. J Clin Med 2019; 8:jcm8111813. [PMID: 31683780 PMCID: PMC6912391 DOI: 10.3390/jcm8111813] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2019] [Revised: 10/25/2019] [Accepted: 10/29/2019] [Indexed: 12/17/2022] Open
Abstract
Background: Gut microbiota-related metabolites, trimethylamine-N-oxide (TMAO), choline, and betaine, have been shown to be associated with cardiovascular disease (CVD) risk. Moreover, lower plasma betaine concentrations have been reported in subjects with type 2 diabetes mellitus (T2DM). However, few studies have explored the association of betaine with incident T2DM, especially in the general population. The goals of this study were to evaluate the performance of a newly developed betaine assay and to prospectively explore the potential clinical associations of betaine and future risk of T2DM in a large population-based cohort. Methods: We developed a high-throughput, nuclear magnetic resonance (NMR) spectroscopy procedure for acquiring spectra that allow for the accurate quantification of plasma/serum betaine and TMAO. Assay performance for betaine quantification was assessed and Cox proportional hazards regression was employed to evaluate the association of betaine with incident T2DM in 4336 participants in the Prevention of Renal and Vascular End-Stage Disease (PREVEND) study. Results: Betaine assay results were linear (y = 1.02X − 3.75) over a wide range of concentrations (26.0–1135 µM). The limit of blank (LOB), limit of detection (LOD) and limit of quantitation (LOQ) were 6.4, 8.9, and 13.2 µM, respectively. Coefficients of variation for intra- and inter-assay precision ranged from 1.5–4.3% and 2.5–5.5%, respectively. Deming regression analysis of results produced by NMR and liquid chromatography coupled to tandem mass spectrometry(LC-MS/MS) revealed an R2 value of 0.94 (Y = 1.08x – 1.89) and a small bias for higher values by NMR. The reference interval, in a cohort of apparently healthy adult participants (n = 501), was determined to be 23.8 to 74.7 µM (mean of 42.9 ± 12.6 µM). In the PREVEND study (n = 4336, excluding subjects with T2DM at baseline), higher betaine was associated with older age and lower body mass index, total cholesterol, triglycerides, and hsCRP. During a median follow-up of 7.3 (interquartile range (IQR), 5.9–7.7) years, 224 new T2DM cases were ascertained. Cox proportional hazards regression models revealed that the highest tertile of betaine was associated with a lower incidence of T2DM. Hazard ratio (HR) for the crude model was 0.61 (95% CI: 0.44–0.85, p = 0.004). The association remained significant even after adjusting for multiple clinical covariates and T2DM risk factors, including fasting glucose. HR for the fully-adjusted model was 0.50 (95% CI: 0.32–0.80, p = 0.003). Conclusions: The newly developed NMR-based betaine assay exhibits performance characteristics that are consistent with usage in the clinical laboratory. Betaine levels may be useful for assessing the risk of future T2DM.
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Kanitsoraphan C, Rattanawong P, Charoensri S, Senthong V. Trimethylamine N-Oxide and Risk of Cardiovascular Disease and Mortality. Curr Nutr Rep 2019; 7:207-213. [PMID: 30362023 DOI: 10.1007/s13668-018-0252-z] [Citation(s) in RCA: 58] [Impact Index Per Article: 11.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
PURPOSE OF REVIEW Trimethylamine N-oxide (TMAO) is a gut microbiota-dependent metabolite produced from choline and phosphatidylcholine. Trimethylamine N-oxide was found associated with enhanced atherosclerosis and thrombosis in vitro and in vivo. We summarized available clinical studies which investigated TMAO's role in predicting prognostic outcomes, including mortality, in patients with cardiovascular diseases. RECENT FINDINGS In chronic kidney disease cohorts, higher TMAO levels were significantly associated with higher mortality from 1.18 to 4.32 folds. Higher TMAO levels were not significantly associated with mortality in patient undergoing dialysis. In patients with peripheral artery disease, higher TMAO levels were associated with higher overall mortality from 1.38 to 2.06 folds. In patients with type 2 diabetes, higher TMAO levels were significantly associated with higher overall mortality 2.07 to 2.7 folds. In patients with heart failure, higher TMAO levels were associated with higher mortality or cardiac transplantation 1.18 to 1.79 folds. TMAO levels could potentially be integrated to existed risk stratification tools and could lead to novel prevention and treatment approaches to cardiovascular disease. Nonetheless, more studies would be needed to clarify predictive value of TMAO to specific groups of patients. Mechanisms how TMAO affect atherosclerosis and confounding effects of TMAO with traditional cardiovascular parameters should also be further investigated.
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Affiliation(s)
| | | | - Suranut Charoensri
- Division of Endocrinology and Metabolism, Department of Medicine, Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand
| | - Vichai Senthong
- Cardiovascular Unit, Department of Medicine, Faculty of Medicine, Khon Kaen University, Khon Kaen, 40002, Thailand.
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Nam HS. Gut Microbiota and Ischemic Stroke: The Role of Trimethylamine N-Oxide. J Stroke 2019; 21:151-159. [PMID: 31161760 PMCID: PMC6549071 DOI: 10.5853/jos.2019.00472] [Citation(s) in RCA: 90] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2019] [Accepted: 04/18/2019] [Indexed: 12/17/2022] Open
Abstract
Trimethylamine N-oxide (TMAO) is produced when trimethylamine, a waste product of gut microbes, is converted via hepatic flavin monooxygenases. As TMAO is a potential causative factor in various cardiovascular diseases (CVDs) considerable research interest has arisen on its use as a biomarker. Higher TMAO levels are associated with future risk of both incident CVD in the general population and established CVD, including stroke. The addition of TMAO into models with traditional risk factors significantly improved the prediction of future CVD risk. TMAO promotes atherosclerosis and is associated with platelet hyperreactivity and inflammation, which are in turn associated with the development of stroke and its secondary consequences. Additionally, TMAO may play a key mediator role in the relationship between the diet, gut microbiota, and CVD development. Compelling evidence suggesting that TMAO is both a risk factor and prognostic marker of stroke and CVD. Potential therapeutic strategy of diet and drugs in reducing TMAO levels have emerged. Thus, TMAO is a novel biomarker and target in stroke and CVD prevention.
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Affiliation(s)
- Hyo Suk Nam
- Department of Neurology, Yonsei University College of Medicine, Seoul, Korea
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36
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Papandreou C, Hernández-Alonso P, Bulló M, Ruiz-Canela M, Yu E, Guasch-Ferré M, Toledo E, Dennis C, Deik A, Clish C, Razquin C, Corella D, Estruch R, Ros E, Fitó M, Arós F, Fiol M, Lapetra J, Ruano C, Liang L, Martínez-González MA, Hu FB, Salas-Salvadó J. Plasma Metabolites Associated with Coffee Consumption: A Metabolomic Approach within the PREDIMED Study. Nutrients 2019; 11:E1032. [PMID: 31072000 PMCID: PMC6566346 DOI: 10.3390/nu11051032] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2019] [Revised: 05/02/2019] [Accepted: 05/03/2019] [Indexed: 02/07/2023] Open
Abstract
Few studies have examined the association of a wide range of metabolites with total and subtypes of coffee consumption. The aim of this study was to investigate associations of plasma metabolites with total, caffeinated, and decaffeinated coffee consumption. We also assessed the ability of metabolites to discriminate between coffee consumption categories. This is a cross-sectional analysis of 1664 participants from the PREDIMED study. Metabolites were semiquantitatively profiled using a multiplatform approach. Consumption of total coffee, caffeinated coffee and decaffeinated coffee was assessed by using a validated food frequency questionnaire. We assessed associations between 387 metabolite levels with total, caffeinated, or decaffeinated coffee consumption (≥50 mL coffee/day) using elastic net regression analysis. Ten-fold cross-validation analyses were used to estimate the discriminative accuracy of metabolites for total and subtypes of coffee. We identified different sets of metabolites associated with total coffee, caffeinated and decaffeinated coffee consumption. These metabolites consisted of lipid species (e.g., sphingomyelin, phosphatidylethanolamine, and phosphatidylcholine) or were derived from glycolysis (alpha-glycerophosphate) and polyphenol metabolism (hippurate). Other metabolites included caffeine, 5-acetylamino-6-amino-3-methyluracil, cotinine, kynurenic acid, glycocholate, lactate, and allantoin. The area under the curve (AUC) was 0.60 (95% CI 0.56-0.64), 0.78 (95% CI 0.75-0.81) and 0.52 (95% CI 0.49-0.55), in the multimetabolite model, for total, caffeinated, and decaffeinated coffee consumption, respectively. Our comprehensive metabolic analysis did not result in a new, reliable potential set of metabolites for coffee consumption.
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Affiliation(s)
- Christopher Papandreou
- Human Nutrition Unit, Faculty of Medicine and Health Sciences, Institut d'Investigació Sanitària Pere Virgili, Rovira i Virgili University, 43201 Reus, Spain.
- CIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain.
| | - Pablo Hernández-Alonso
- Human Nutrition Unit, Faculty of Medicine and Health Sciences, Institut d'Investigació Sanitària Pere Virgili, Rovira i Virgili University, 43201 Reus, Spain.
- CIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain.
| | - Mònica Bulló
- Human Nutrition Unit, Faculty of Medicine and Health Sciences, Institut d'Investigació Sanitària Pere Virgili, Rovira i Virgili University, 43201 Reus, Spain.
- CIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain.
| | - Miguel Ruiz-Canela
- CIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain.
- University of Navarra, Department of Preventive Medicine and Public Health, IdiSNA, 31009 Pamplona, Spain.
| | - Edward Yu
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA.
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA.
| | - Marta Guasch-Ferré
- Human Nutrition Unit, Faculty of Medicine and Health Sciences, Institut d'Investigació Sanitària Pere Virgili, Rovira i Virgili University, 43201 Reus, Spain.
- CIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain.
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA.
| | - Estefanía Toledo
- CIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain.
- University of Navarra, Department of Preventive Medicine and Public Health, IdiSNA, 31009 Pamplona, Spain.
| | - Courtney Dennis
- Broad Institute of MIT and Harvard University, Cambridge, MA 02142, USA.
| | - Amy Deik
- Broad Institute of MIT and Harvard University, Cambridge, MA 02142, USA.
| | - Clary Clish
- Broad Institute of MIT and Harvard University, Cambridge, MA 02142, USA.
| | - Cristina Razquin
- CIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain.
- University of Navarra, Department of Preventive Medicine and Public Health, IdiSNA, 31009 Pamplona, Spain.
| | - Dolores Corella
- CIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain.
- Department of Preventive Medicine, University of Valencia, 46010 Valencia, Spain.
| | - Ramon Estruch
- CIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain.
- Department of Internal Medicine, Department of Endocrinology and Nutrition Institut d' Investigacions Biomediques August Pi Sunyer (IDIBAPS), Hospital Clinic, University of Barcelona, 08007 Barcelona, Spain.
| | - Emilio Ros
- CIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain.
- Lipid Clinic, Department of Endocrinology and Nutrition Institut d'Investigacions Biomediques August Pi Sunyer (IDIBAPS), Hospital Clinic, University of Barcelona, 08007 Barcelona, Spain.
| | - Montserrat Fitó
- CIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain.
- Cardiovascular Risk and Nutrition Research Group (CARIN), Hospital del Mar Research Institute (IMIM), 08003 Barcelona, Spain.
| | - Fernando Arós
- CIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain.
- Department of Cardiology, University Hospital of Álava, 01009 Vitoria, Spain.
| | - Miquel Fiol
- CIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain.
- Illes Balears Health Research Institute (IdISBa), Hospital Son Espases, 07120 Palma de Mallorca, Spain.
| | - José Lapetra
- CIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain.
- Department of Family, Research Unit, Distrito Sanitario Atención Primaria Sevilla, 41013 Sevilla, Spain.
| | - Cristina Ruano
- CIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain.
- Department of Clinical Sciences, University of Las Palmas de Gran Canaria, 35001 Las Palmas, Spain.
| | - Liming Liang
- CIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain.
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA.
| | - Miguel A Martínez-González
- CIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain.
- University of Navarra, Department of Preventive Medicine and Public Health, IdiSNA, 31009 Pamplona, Spain.
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA.
| | - Frank B Hu
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA.
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA.
- Channing Division for Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, MA 02115, USA.
| | - Jordi Salas-Salvadó
- Human Nutrition Unit, Faculty of Medicine and Health Sciences, Institut d'Investigació Sanitària Pere Virgili, Rovira i Virgili University, 43201 Reus, Spain.
- CIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain.
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Metabolomics and Microbiomes as Potential Tools to Evaluate the Effects of the Mediterranean Diet. Nutrients 2019; 11:nu11010207. [PMID: 30669673 PMCID: PMC6356665 DOI: 10.3390/nu11010207] [Citation(s) in RCA: 56] [Impact Index Per Article: 11.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2018] [Revised: 01/12/2019] [Accepted: 01/17/2019] [Indexed: 02/07/2023] Open
Abstract
The approach to studying diet–health relationships has progressively shifted from individual dietary components to overall dietary patterns that affect the interaction and balance of low-molecular-weight metabolites (metabolome) and host-enteric microbial ecology (microbiome). Even though the Mediterranean diet (MedDiet) has been recognized as a powerful strategy to improve health, the accurate assessment of exposure to the MedDiet has been a major challenge in epidemiological and clinical studies. Interestingly, while the effects of individual dietary components on the metabolome have been described, studies investigating metabolomic profiles in response to overall dietary patterns (including the MedDiet), although limited, have been gaining attention. Similarly, the beneficial effects of the MedDiet on cardiometabolic outcomes may be mediated through gut microbial changes. Accumulating evidence linking food ingestion and enteric microbiome alterations merits the evaluation of the microbiome-mediated effects of the MedDiet on metabolic pathways implicated in disease. In this narrative review, we aimed to summarize the current evidence from observational and clinical trials involving the MedDiet by (1) assessing changes in the metabolome and microbiome for the measurement of diet pattern adherence and (2) assessing health outcomes related to the MedDiet through alterations to human metabolomics and/or the microbiome.
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Effects of Lifestyle Intervention on Plasma Trimethylamine N-Oxide in Obese Adults. Nutrients 2019; 11:nu11010179. [PMID: 30654453 PMCID: PMC6356515 DOI: 10.3390/nu11010179] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2018] [Revised: 01/10/2019] [Accepted: 01/11/2019] [Indexed: 01/06/2023] Open
Abstract
Accumulating evidence linking trimethylamine N-oxide (TMAO) to cardiovascular disease (CVD) risk has prompted interest in developing therapeutic strategies to reduce its production. We compared two lifestyle intervention approaches: hypocaloric versus eucaloric diet, combined with exercise, on TMAO levels in relation to CVD risk factors. Sixteen obese adults (66.1 ± 4.4 years, BMI (body mass index): 35.9 ± 5.3 kg/m2, fasting glucose: 106 ± 16 mg/dL, 2-h PPG (postprandial glucose): 168 ± 37 mg/dL) were randomly assigned to 12 weeks of exercise (5 days/week, 80–85% HRmax (maximal heart rate)) plus either a hypocaloric (HYPO) (−500 kcal) or a eucaloric (EU) diet. Outcomes included plasma TMAO, glucose metabolism (oral glucose tolerance test (OGTT) and euglycemic-hyperinsulinemic clamps for glucose disposal rates (GDR)), exercise capacity (VO2max, maximal oxygen consumption), abdominal adiposity (computed tomography scans), cholesterol, and triglycerides. Results showed that body composition (body weight, subcutaneous adiposity), insulin sensitivity, VO2max, and cholesterol all improved (p < 0.05). HYPO decreased the percentage change in TMAO compared to an increase after EU (HYPO: −31 ± 0.4% vs. EU: 32 ± 0.6%, p = 0.04). Absolute TMAO levels were not impacted (HYPO: p = 0.09 or EU: p = 0.53 group). The change in TMAO after intervention was inversely correlated with baseline visceral adipose tissue (r = −0.63, p = 0.009) and GDR (r = 0.58, p = 0.002). A hypocaloric diet and exercise approach appears to be effective in reducing TMAO. Larger trials are needed to support this observation.
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