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Li Z, Zhang Y, Hoene M, Fritsche L, Zheng S, Birkenfeld A, Fritsche A, Peter A, Liu X, Zhao X, Zhou L, Luo P, Weigert C, Lin X, Xu G, Lehmann R. Diagnostic Performance of Sex-Specific Modified Metabolite Patterns in Urine for Screening of Prediabetes. Front Endocrinol (Lausanne) 2022; 13:935016. [PMID: 35909528 PMCID: PMC9333093 DOI: 10.3389/fendo.2022.935016] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/03/2022] [Accepted: 06/13/2022] [Indexed: 12/03/2022] Open
Abstract
AIMS/HYPOTHESIS Large-scale prediabetes screening is still a challenge since fasting blood glucose and HbA1c as the long-standing, recommended analytes have only moderate diagnostic sensitivity, and the practicability of the oral glucose tolerance test for population-based strategies is limited. To tackle this issue and to identify reliable diagnostic patterns, we developed an innovative metabolomics-based strategy deviating from common concepts by employing urine instead of blood samples, searching for sex-specific biomarkers, and focusing on modified metabolites. METHODS Non-targeted, modification group-assisted metabolomics by liquid chromatography-mass spectrometry (LC-MS) was applied to second morning urine samples of 340 individuals from a prediabetes cohort. Normal (n = 208) and impaired glucose-tolerant (IGT; n = 132) individuals, matched for age and BMI, were randomly divided in discovery and validation cohorts. ReliefF, a feature selection algorithm, was used to extract sex-specific diagnostic patterns of modified metabolites for the detection of IGT. The diagnostic performance was compared with conventional screening parameters fasting plasma glucose (FPG), HbA1c, and fasting insulin. RESULTS Female- and male-specific diagnostic patterns were identified in urine. Only three biomarkers were identical in both. The patterns showed better AUC and diagnostic sensitivity for prediabetes screening of IGT than FPG, HbA1c, insulin, or a combination of FPG and HbA1c. The AUC of the male-specific pattern in the validation cohort was 0.889 with a diagnostic sensitivity of 92.6% and increased to an AUC of 0.977 in combination with HbA1c. In comparison, the AUCs of FPG, HbA1c, and insulin alone reached 0.573, 0.668, and 0.571, respectively. Validation of the diagnostic pattern of female subjects showed an AUC of 0.722, which still exceeded the AUCs of FPG, HbA1c, and insulin (0.595, 0.604, and 0.634, respectively). Modified metabolites in the urinary patterns include advanced glycation end products (pentosidine-glucuronide and glutamyl-lysine-sulfate) and microbiota-associated compounds (indoxyl sulfate and dihydroxyphenyl-gamma-valerolactone-glucuronide). CONCLUSIONS/INTERPRETATION Our results demonstrate that the sex-specific search for diagnostic metabolite biomarkers can be superior to common metabolomics strategies. The diagnostic performance for IGT detection was significantly better than routinely applied blood parameters. Together with recently developed fully automatic LC-MS systems, this opens up future perspectives for the application of sex-specific diagnostic patterns for prediabetes screening in urine.
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Affiliation(s)
- Zaifang Li
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China
- University of Chinese Academy of Sciences, Beijing, China
- Liaoning Province Key Laboratory of Metabolomics, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China
| | - Yanhui Zhang
- School of Computer Science & Technology, Dalian University of Technology, Dalian, China
| | - Miriam Hoene
- Department for Diagnostic Laboratory Medicine, Institute for Clinical Chemistry and Pathobiochemistry, University Hospital Tübingen, Tübingen, Germany
| | - Louise Fritsche
- Institute for Diabetes Research and Metabolic Diseases (IDM) of the Helmholtz Zentrum München at the University of Tuebingen, Tuebingen, Germany
- German Center for Diabetes Research (DZD), Tübingen, Germany
| | - Sijia Zheng
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China
- University of Chinese Academy of Sciences, Beijing, China
- Liaoning Province Key Laboratory of Metabolomics, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China
| | - Andreas Birkenfeld
- Institute for Diabetes Research and Metabolic Diseases (IDM) of the Helmholtz Zentrum München at the University of Tuebingen, Tuebingen, Germany
- German Center for Diabetes Research (DZD), Tübingen, Germany
- Internal Medicine 4, University Hospital Tuebingen, Tuebingen, Germany
| | - Andreas Fritsche
- Institute for Diabetes Research and Metabolic Diseases (IDM) of the Helmholtz Zentrum München at the University of Tuebingen, Tuebingen, Germany
- German Center for Diabetes Research (DZD), Tübingen, Germany
- Internal Medicine 4, University Hospital Tuebingen, Tuebingen, Germany
| | - Andreas Peter
- Department for Diagnostic Laboratory Medicine, Institute for Clinical Chemistry and Pathobiochemistry, University Hospital Tübingen, Tübingen, Germany
- Institute for Diabetes Research and Metabolic Diseases (IDM) of the Helmholtz Zentrum München at the University of Tuebingen, Tuebingen, Germany
- German Center for Diabetes Research (DZD), Tübingen, Germany
| | - Xinyu Liu
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China
- University of Chinese Academy of Sciences, Beijing, China
- Liaoning Province Key Laboratory of Metabolomics, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China
| | - Xinjie Zhao
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China
- University of Chinese Academy of Sciences, Beijing, China
- Liaoning Province Key Laboratory of Metabolomics, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China
| | - Lina Zhou
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China
- University of Chinese Academy of Sciences, Beijing, China
- Liaoning Province Key Laboratory of Metabolomics, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China
| | - Ping Luo
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China
- University of Chinese Academy of Sciences, Beijing, China
- Liaoning Province Key Laboratory of Metabolomics, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China
| | - Cora Weigert
- Department for Diagnostic Laboratory Medicine, Institute for Clinical Chemistry and Pathobiochemistry, University Hospital Tübingen, Tübingen, Germany
- Institute for Diabetes Research and Metabolic Diseases (IDM) of the Helmholtz Zentrum München at the University of Tuebingen, Tuebingen, Germany
- German Center for Diabetes Research (DZD), Tübingen, Germany
| | - Xiaohui Lin
- School of Computer Science & Technology, Dalian University of Technology, Dalian, China
- *Correspondence: Guowang Xu, ; Rainer Lehmann,
| | - Guowang Xu
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China
- University of Chinese Academy of Sciences, Beijing, China
- Liaoning Province Key Laboratory of Metabolomics, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China
- *Correspondence: Guowang Xu, ; Rainer Lehmann,
| | - Rainer Lehmann
- Department for Diagnostic Laboratory Medicine, Institute for Clinical Chemistry and Pathobiochemistry, University Hospital Tübingen, Tübingen, Germany
- Institute for Diabetes Research and Metabolic Diseases (IDM) of the Helmholtz Zentrum München at the University of Tuebingen, Tuebingen, Germany
- German Center for Diabetes Research (DZD), Tübingen, Germany
- *Correspondence: Guowang Xu, ; Rainer Lehmann,
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102
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Wang X, Yang R, Zhang W, Wang S, Mu H, Li H, Dong J, Chen W, Yu X, Ji F. Serum glutamate and glutamine-to-glutamate ratio are associated with coronary angiography defined coronary artery disease. Nutr Metab Cardiovasc Dis 2022; 32:186-194. [PMID: 34906414 DOI: 10.1016/j.numecd.2021.09.021] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Revised: 09/15/2021] [Accepted: 09/18/2021] [Indexed: 12/14/2022]
Abstract
BACKGROUND AND AIMS Serum concentrations of glutamate (Glu), Glutamine (Gln) and Gln/Glu ratio have consistently been reported to be associated with metabolic disorders and diabetes. The aim of this study was to examine the relationship between these metabolites with the presence of coronary artery disease (CAD) and CAD severity in Chinese patients. METHODS AND RESULTS 2970 Chinese patients undergoing coronary angiography (CAG) in Beijing Hospital were enrolled. Baseline demographics and medical history data was recorded by questionnaires. Serum Glu and Gln concentrations were analyzed by isotope dilution liquid chromatography-tandem mass spectrometry (LC-MS/MS). Statistical analysis showed that CAD patients had significantly higher levels of Glu and lower Gln/Glu ratios compared with non-CAD control group. Glu was significantly positively associated with body mass index (BMI), fasting blood glucose (FBG), triglycerides (TG), creatinine (Crea), and uric acid (UA), and negatively associated with high-density lipoprotein cholesterol (HDL-C), while inverse associations between Gln/Glu ratio and these risk factors were observed. Glu levels increased and Gln/Glu decreased with the increase of CAD severity as represented by either the number of stenosed vessels or the Gensini scores. Logistic regression analysis demonstrated that, after adjusting for smoking status, obesity or overweight, hypertension, dyslipidemia, diabetes, stroke and family history of premature CAD, high Glu level and low Gln/Glu ratio were positively associated with CAG defined CAD as well as CAD severity expressed by Gensini score. CONCLUSIONS We identified Glu and Gln/Glu ratio independently associated with CAG defined CAD as well as CAD severity in Chinese patients undergoing CAG.
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Affiliation(s)
- Xinyue Wang
- Department of Cardiology, Beijing Hospital, National Center of Gerontology, Beijing, 100730, PR China
| | - Ruiyue Yang
- The Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, PR China
| | - Wenduo Zhang
- Department of Cardiology, Beijing Hospital, National Center of Gerontology, Beijing, 100730, PR China
| | - Siming Wang
- The Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, PR China
| | - Hongna Mu
- The Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, PR China
| | - Hongxia Li
- The Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, PR China
| | - Jun Dong
- The Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, PR China
| | - Wenxiang Chen
- The Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, PR China
| | - Xue Yu
- Department of Cardiology, Beijing Hospital, National Center of Gerontology, Beijing, 100730, PR China.
| | - Fusui Ji
- Department of Cardiology, Beijing Hospital, National Center of Gerontology, Beijing, 100730, PR China.
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103
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Ikeda H. The Effect of Mild Renal Dysfunction on the Assessment of Plasma Amino Acid Concentration and Insulin Resistance in Patients with Type 2 Diabetes Mellitus. J Diabetes Res 2022; 2022:2048300. [PMID: 35734236 PMCID: PMC9208954 DOI: 10.1155/2022/2048300] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Revised: 05/23/2022] [Accepted: 05/25/2022] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND An increase in the levels of branched-chain amino acids (BCAAs) and certain aromatic amino acids, such as alanine, in plasma is correlated with insulin resistance (IR) in type 2 diabetes mellitus (T2DM). T2DM is a leading risk factor for chronic kidney disease. Meanwhile, renal dysfunction causes changes in plasma amino acid levels. To date, no study has examined how mild renal dysfunction and IR interact with plasma amino acid levels. This study examines the effects of IR and renal dysfunction on plasma amino acid concentrations in T2DM. METHODS Data were collected from healthy male participants (controls) and male patients with T2DM between May 2018 and February 2022. Blood samples were collected after overnight fasting. IR and renal function were evaluated using the homeostasis model assessment of IR (HOMA-IR) and serum cystatin C (CysC), respectively. RESULTS A total of 49 and 93 participants were included in the control and T2DM groups, respectively. In the T2DM group, eight amino acids (alanine, glutamic acid, glutamine, glycine, isoleucine, leucine, tyrosine, and valine) and total BCAA showed a significant correlation with HOMA-IR (p < 0.01), whereas six amino acids (γ-aminobutyric acid, citrulline, cysteine, glycine, methionine, and valine) and total BCAA showed a significant correlation with 1/CysC (p < 0.02). However, only alanine, glutamic acid, and each BCAA showed significant differences between the control group and the IR T2DM subgroup. Increases in the BCAA levels with T2DM were canceled by renal dysfunction (CysC ≥ 0.93) in patients with intermediate IR. CONCLUSION To use plasma BCAA concentration as a marker of IR, renal function must be considered, even in mild renal dysfunction. Increased alanine and glutamic acid levels indicate IR, regardless of mild renal dysfunction.
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Affiliation(s)
- Hideki Ikeda
- Department of Internal Medicine, Sanyudo Hospital, Chuo 6 Chome-1-219, Yonezawa, Yamagata 992-0045, Japan
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104
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Lim SY, Selvaraji S, Lau H, Li SFY. Application of omics beyond the central dogma in coronary heart disease research: A bibliometric study and literature review. Comput Biol Med 2022; 140:105069. [PMID: 34847384 DOI: 10.1016/j.compbiomed.2021.105069] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2021] [Revised: 11/22/2021] [Accepted: 11/22/2021] [Indexed: 12/12/2022]
Abstract
Despite remarkable progress in disease diagnosis and treatment, coronary heart disease (CHD) remains the number one leading cause of death worldwide. Many practical challenges still faced in clinical settings necessitates the pursuit of omics studies to identify alternative/orthogonal biomarkers, as well as to discover novel insights into disease mechanisms. Albeit relatively nascent as compared to the omics frontrunners (genomics, transcriptomics, and proteomics), omics beyond the central dogma (OBCD; e.g., metabolomics, lipidomics, glycomics, and metallomics) have undeniable contributions and prospects in CHD research. In this bibliometric study, we characterised the global trends in publication/citation outputs, collaborations, and research hotspots concerning OBCD-CHD, with a focus on the more prolific fields of metabolomics and lipidomics. As for glycomics and metallomics, there were insufficient publication records on their applications in CHD research for quantitative bibliometrics analysis. Thus, we reviewed their applications in health/disease research in general, discussed and justified their potential in CHD research, and suggested important/promising research avenues. By summarising evidence obtained both quantitatively and qualitatively, this study offers a first and comprehensive picture of OBCD applications in CHD, facilitating the establishment of future research directions.
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Affiliation(s)
- Si Ying Lim
- Integrative Sciences & Engineering Programme, NUS Graduate School, National University of Singapore, University Hall, Tan Chin Tuan Wing, Singapore 119077, Singapore; Department of Chemistry, National University of Singapore, 3 Science Drive 3, Singapore 117543, Singapore
| | - Sharmelee Selvaraji
- Integrative Sciences & Engineering Programme, NUS Graduate School, National University of Singapore, University Hall, Tan Chin Tuan Wing, Singapore 119077, Singapore; Department of Physiology, Yong Loo Lin School of Medicine, 2 Medical Drive MD9, National University of Singapore, Singapore 117593, Singapore
| | - Hazel Lau
- Department of Chemistry, National University of Singapore, 3 Science Drive 3, Singapore 117543, Singapore
| | - Sam Fong Yau Li
- Integrative Sciences & Engineering Programme, NUS Graduate School, National University of Singapore, University Hall, Tan Chin Tuan Wing, Singapore 119077, Singapore; Department of Chemistry, National University of Singapore, 3 Science Drive 3, Singapore 117543, Singapore.
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105
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Sudar-Milovanovic E, Gluvic Z, Obradovic M, Zaric B, Isenovic ER. Tryptophan Metabolism in Atherosclerosis and Diabetes. Curr Med Chem 2022; 29:99-113. [PMID: 34269660 DOI: 10.2174/0929867328666210714153649] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2021] [Revised: 06/07/2021] [Accepted: 06/11/2021] [Indexed: 02/08/2023]
Abstract
The essential amino acid tryptophan (Trp) undergoes catabolism through several pathways, producing biologically active metabolites that significantly impact physiological processes. The metabolic pathway responsible for the majority of Trp catabolism is the kynurenine synthesis pathway (KP). Serotonin and melatonin are among the most essential Trp pathways degradation products. It has emerged that a strong relationship exists between alterations in Trp metabolism and the onset and progression of atherosclerosis and diabetes. Atherosclerosis is a chronic inflammatory disease of the small and medium arteries wall caused by maladaptive local immune responses, which underpins several cardiovascular diseases (CVD). Systemic low-grade immune-mediated inflammation is implicated in atherosclerosis where pro-inflammatory cytokines, such as interferon-γ (IFN-γ), play a significant role. IFN-γ upregulates the enzyme indoleamine 2,3-dioxygenase (IDO), decreasing serum levels of the Trp and increasing metabolite levels of kynurenine. Increased IDO expression and activity could accelerate the atherosclerosis process. Therefore, activated IDO inhibition could offer possible treatment options regarding atherosclerosis management. Diabetes is a chronic metabolic disease characterized by hyperglycemia that, over time, leads to severe damage to the heart, blood vessels, eyes, kidneys, and peripheral nerves. Trp serum levels and lower activity of IDO were higher in future type 2 diabetes (T2DM) patients. This article reviews recent findings on the link between mammalian Trp metabolism and its role in atherosclerosis and diabetes and outlines the intervention strategies.
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Affiliation(s)
- Emina Sudar-Milovanovic
- Department of Radiobiology and Molecular Genetics, VINČA Institute of Nuclear Sciences - National Institute of the Republic of Serbia, University of Belgrade, Belgrade,Serbia
| | - Zoran Gluvic
- Clinic for Internal Medicine, Department of Endocrinology and Diabetes, Zemun Clinical Hospital, School of Medicine, University of Belgrade, Belgrade,Serbia
| | - Milan Obradovic
- Department of Radiobiology and Molecular Genetics, VINČA Institute of Nuclear Sciences - National Institute of the Republic of Serbia, University of Belgrade, Belgrade,Serbia
| | - Bozidarka Zaric
- Department of Radiobiology and Molecular Genetics, VINČA Institute of Nuclear Sciences - National Institute of the Republic of Serbia, University of Belgrade, Belgrade,Serbia
| | - Esma R Isenovic
- Department of Radiobiology and Molecular Genetics, VINČA Institute of Nuclear Sciences - National Institute of the Republic of Serbia, University of Belgrade, Belgrade,Serbia
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106
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Purdel C, Ungurianu A, Margina D. Metabolic and Metabolomic Insights Regarding the Omega-3 PUFAs Intake in Type 1 Diabetes Mellitus. Front Mol Biosci 2021; 8:783065. [PMID: 34926582 PMCID: PMC8678113 DOI: 10.3389/fmolb.2021.783065] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2021] [Accepted: 11/22/2021] [Indexed: 12/16/2022] Open
Abstract
Type 1 diabetes mellitus (T1DM) is currently considered an autoimmune disease characterized by the destruction of pancreatic β-cells, insulin deficiency, and dysglycemia. Dietary factors, including omega-3 polyunsaturated fatty acids (ω-3 PUFAs), were reported to influence T1DM. Therefore, a better understanding of the potential role of ω-3 PUFAs in the development and progression of T1DM will help to improve the clinical management of the disease. In this review, we explored the current understanding of molecular mechanisms and signaling pathways induced by ω-3 PUFAs and the beneficial effects of ω-3 PUFAs intake in the prevention and treatment of T1DM, as well as the underlying possible metabolomic (lipidomics) changes.
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Affiliation(s)
- Carmen Purdel
- Department of Toxicology, Faculty of Pharmacy, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania
| | - Anca Ungurianu
- Department of Biochemistry, Faculty of Pharmacy, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania
| | - Denisa Margina
- Department of Biochemistry, Faculty of Pharmacy, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania
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107
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Metabolic profiling of charged metabolites in association with menopausal status in Japanese community-dwelling midlife women: Tsuruoka Metabolomic Cohort Study. Maturitas 2021; 155:54-62. [PMID: 34876249 DOI: 10.1016/j.maturitas.2021.10.004] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2020] [Revised: 09/27/2021] [Accepted: 10/07/2021] [Indexed: 11/21/2022]
Abstract
BACKGROUND Emerging evidence has shown that charged metabolites, such as amino acids, may play an important role in the pathogenesis of various metabolic disorders, many of which women in the postmenopausal period are at high risk of developing. This study examined the metabolic profile of middle-aged Japanese women to investigate alterations in charged metabolites induced by menopausal transition. METHODS The participants were 1193 female residents aged 40-60 at the baseline survey of the Tsuruoka Metabolomics Cohort Study. We investigated the cross-sectional association of menopausal status with 94 metabolomic biomarkers assayed in fasting plasma samples via capillary electrophoresis time-of-flight mass spectrometry using linear regression analysis. RESULTS Among the participants, 529 were premenopausal, 132 were in menopausal transition (MT), and 532 were postmenopausal. Significant differences were found in age, blood pressure, glucose and lipid levels, and smoking and drinking habits among the three groups. The concentrations of 5 metabolites in the MT group and 15 metabolites in the postmenopausal group were significantly higher than those in the premenopausal group after adjusting for confounding factors. When classified into pathways, these metabolites were related to the tricarboxylic cycle, urea cycle, and homocysteine metabolism, some of which are linked to arteriosclerosis. CONCLUSION Multiple charged metabolites were associated with women's menopausal status, showing a gradual increase as women shifted from pre-, to peri-, to postmenopause. These findings might reflect the early changes behind the increased risk of dyslipidemia, diabetes, cardiovascular disease, and osteoporosis in later life.
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108
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Chevli PA, Freedman BI, Hsu FC, Xu J, Rudock ME, Ma L, Parks JS, Palmer ND, Shapiro MD. Plasma metabolomic profiling in subclinical atherosclerosis: the Diabetes Heart Study. Cardiovasc Diabetol 2021; 20:231. [PMID: 34876126 PMCID: PMC8653597 DOI: 10.1186/s12933-021-01419-y] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Accepted: 11/15/2021] [Indexed: 11/29/2022] Open
Abstract
BACKGROUND Incidence rates of cardiovascular disease (CVD) are increasing, partly driven by the diabetes epidemic. Novel prediction tools and modifiable treatment targets are needed to enhance risk assessment and management. Plasma metabolite associations with subclinical atherosclerosis were investigated in the Diabetes Heart Study (DHS), a cohort enriched for type 2 diabetes (T2D). METHODS The analysis included 700 DHS participants, 438 African Americans (AAs), and 262 European Americans (EAs), in whom coronary artery calcium (CAC) was assessed using ECG-gated computed tomography. Plasma metabolomics using liquid chromatography-mass spectrometry identified 853 known metabolites. An ancestry-specific marginal model incorporating generalized estimating equations examined associations between metabolites and CAC (log-transformed (CAC + 1) as outcome measure). Models were adjusted for age, sex, BMI, diabetes duration, date of plasma collection, time between plasma collection and CT exam, low-density lipoprotein cholesterol (LDL-C), and statin use. RESULTS At an FDR-corrected p-value < 0.05, 33 metabolites were associated with CAC in AAs and 36 in EAs. The androgenic steroids, fatty acid, phosphatidylcholine, and bile acid metabolism subpathways were associated with CAC in AAs, whereas fatty acid, lysoplasmalogen, and branched-chain amino acid (BCAA) subpathways were associated with CAC in EAs. CONCLUSIONS Strikingly different metabolic signatures were associated with subclinical coronary atherosclerosis in AA and EA DHS participants.
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Affiliation(s)
- Parag Anilkumar Chevli
- Section on Hospital Medicine, Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Barry I Freedman
- Section on Nephrology, Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Fang-Chi Hsu
- Department of Biostatistics and Data Science, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Jianzhao Xu
- Department of Biochemistry, Wake Forest School of Medicine, 1 Medical Center Blvd, Winston-Salem, NC, 27157, USA
| | - Megan E Rudock
- Department of Biochemistry, Wake Forest School of Medicine, 1 Medical Center Blvd, Winston-Salem, NC, 27157, USA
| | - Lijun Ma
- Section on Nephrology, Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - John S Parks
- Section on Molecular Medicine, Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Nicholette D Palmer
- Department of Biochemistry, Wake Forest School of Medicine, 1 Medical Center Blvd, Winston-Salem, NC, 27157, USA.
| | - Michael D Shapiro
- Section of Cardiovascular Medicine, Center for Preventive Cardiology, Wake Forest School of Medicine, 1 Medical Center Blvd, Winston-Salem, NC, 27157, USA.
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Gao A, Su J, Liu R, Zhao S, Li W, Xu X, Li D, Shi J, Gu B, Zhang J, Li Q, Wang X, Zhang Y, Xu Y, Lu J, Ning G, Hong J, Bi Y, Gu W, Wang J, Wang W. Sexual dimorphism in glucose metabolism is shaped by androgen-driven gut microbiome. Nat Commun 2021; 12:7080. [PMID: 34873153 PMCID: PMC8648805 DOI: 10.1038/s41467-021-27187-7] [Citation(s) in RCA: 44] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2020] [Accepted: 11/02/2021] [Indexed: 12/25/2022] Open
Abstract
Males are generally more susceptible to impaired glucose metabolism and type 2 diabetes (T2D) than females. However, the underlying mechanisms remain to be determined. Here, we revealed that gut microbiome depletion abolished sexual dimorphism in glucose metabolism. The transfer of male donor microbiota into antibiotics-treated female mice led the recipients to be more insulin resistant. Depleting androgen via castration changed the gut microbiome of male mice to be more similar to that of females and improved glucose metabolism, while reintroducing dihydrotestosterone (DHT) reversed these alterations. More importantly, the effects of androgen on glucose metabolism were largely abolished when the gut microbiome was depleted. Next, we demonstrated that androgen modulated circulating glutamine and glutamine/glutamate (Gln/Glu) ratio partially depending on the gut microbiome, and glutamine supplementation increases insulin sensitivity in vitro. Our study identifies the effects of androgen in deteriorating glucose homeostasis partially by modulating the gut microbiome and circulating glutamine and Gln/Glu ratio, thereby contributing to the difference in glucose metabolism between the two sexes.
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Affiliation(s)
- Aibo Gao
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- Shanghai National Clinical Research Center for metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Junlei Su
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- Shanghai National Clinical Research Center for metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Ruixin Liu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- Shanghai National Clinical Research Center for metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Shaoqian Zhao
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- Shanghai National Clinical Research Center for metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Wen Li
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- Shanghai National Clinical Research Center for metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | | | - Danjie Li
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- Shanghai National Clinical Research Center for metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Juan Shi
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- Shanghai National Clinical Research Center for metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Bin Gu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- Shanghai National Clinical Research Center for metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Juan Zhang
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- Shanghai National Clinical Research Center for metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Qi Li
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, China
| | - Xiaolin Wang
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, China
| | - Yifei Zhang
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- Shanghai National Clinical Research Center for metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Yu Xu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- Shanghai National Clinical Research Center for metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Jieli Lu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- Shanghai National Clinical Research Center for metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Guang Ning
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- Shanghai National Clinical Research Center for metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Jie Hong
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- Shanghai National Clinical Research Center for metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Yufang Bi
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- Shanghai National Clinical Research Center for metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Weiqiong Gu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
- Shanghai National Clinical Research Center for metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
| | - Jiqiu Wang
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
- Shanghai National Clinical Research Center for metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
| | - Weiqing Wang
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
- Shanghai National Clinical Research Center for metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
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Cruz DE, Tahir UA, Hu J, Ngo D, Chen ZZ, Robbins JM, Katz D, Balasubramanian R, Peterson B, Deng S, Benson MD, Shi X, Dailey L, Gao Y, Correa A, Wang TJ, Clish CB, Rexrode KM, Wilson JG, Gerszten RE. Metabolomic Analysis of Coronary Heart Disease in an African American Cohort From the Jackson Heart Study. JAMA Cardiol 2021; 7:184-194. [PMID: 34851361 DOI: 10.1001/jamacardio.2021.4925] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Importance African American individuals have disproportionate rates of coronary heart disease (CHD) but lower levels of coronary artery calcium (CAC), a marker of subclinical CHD, than non-Hispanic White individuals. African American individuals may have distinct metabolite profiles associated with incident CHD risk compared with non-Hispanic White individuals, and examination of these differences could highlight important processes that differ between them. Objectives To identify novel biomarkers of incident CHD and CAC among African American individuals and to replicate incident CHD findings in a multiethnic cohort. Design, Setting, and Participants This analysis targeted plasma metabolomic profiling of 2346 participants in the Jackson Heart Study (JHS), a prospective population-based cohort study that included 5306 African American participants who were examined at baseline (2000-2004) and 2 follow-up visits. Replication of CHD-associated metabolites was sought among 1588 multiethnic participants from the Women's Health Initiative (WHI), a prospective population-based multiethnic cohort study of 161 808 postmenopausal women who were examined at baseline (1991-1995) and ongoing follow-up visits. Regression analyses were performed for each metabolite to examine the associations with incident CHD and CAC scores. Data were collected from the WHI between 1994 and 2009 and from the JHS between 2000 and 2015. All data were analyzed from November 2020 to August 2021. Exposures Plasma metabolites. Main Outcomes and Measures Incident CHD was defined as definite or probable myocardial infarction or definite fatal CHD in both the JHS and WHI cohorts. In the JHS cohort, silent myocardial infarction between examinations (as determined by electrocardiography) and coronary revascularization were included in the incident CHD analysis. Coronary artery calcium was measured using a 16-channel computed tomographic system and reported as an Agatston score. Results Among 2346 African American individuals in the JHS cohort, the mean (SD) age was 56 (13) years, and 1468 individuals (62.6%) were female. Among 1588 postmenopausal women in the WHI cohort, the mean (SD) age was 67 (7) years; 217 individuals (13.7%) self-identified as African American, 1219 (76.8%) as non-Hispanic White, and 152 (9.6%) as other races or ethnicities. In the fully adjusted model including 1876 individuals, 46 of 303 targeted metabolites were associated with incident CHD (false discovery rate q <0.100). Data for 32 of the 46 metabolites were available in the WHI cohort, and 13 incident CHD-associated metabolites from the JHS cohort were replicated in the WHI cohort. A total of 1439 participants from the JHS cohort with available CAC scores received metabolomic profiling. Nine metabolites were associated with CAC scores. Minimal overlap was found between the results from the incident CHD and CAC analyses, with only 3 metabolites shared between the 2 analyses. Conclusions and Relevance This cohort study identified metabolites that were associated with incident CHD among African American individuals, including 13 incident CHD-associated metabolites that were replicated in a multiethnic population and 9 novel metabolites that included N-acylamides, leucine, and lipid species. These findings may help to elucidate common and distinct metabolic processes that may be associated with CHD among individuals with different self-identified race.
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Affiliation(s)
- Daniel E Cruz
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts
| | - Usman A Tahir
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts
| | - Jie Hu
- Division of Women's Health, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
| | - Debby Ngo
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts
| | - Zsu-Zsu Chen
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts
| | - Jeremy M Robbins
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts
| | - Daniel Katz
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts
| | - Raji Balasubramanian
- Division of Women's Health, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
| | - Bennet Peterson
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts
| | - Shuliang Deng
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts
| | - Mark D Benson
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts
| | - Xu Shi
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts
| | - Lucas Dailey
- Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, Massachusetts
| | - Yan Gao
- Department of Medicine, University of Mississippi Medical Center, Jackson
| | - Adolfo Correa
- Department of Medicine, University of Mississippi Medical Center, Jackson
| | - Thomas J Wang
- Department of Medicine, University of Texas Southwestern Medical Center, Dallas
| | - Clary B Clish
- Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, Massachusetts
| | - Kathryn M Rexrode
- Division of Women's Health, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
| | - James G Wilson
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts
| | - Robert E Gerszten
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts.,Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, Massachusetts
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Matsuyama T, Yoshinaga SK, Shibue K, Mak TW. Comorbidity-associated glutamine deficiency is a predisposition to severe COVID-19. Cell Death Differ 2021; 28:3199-3213. [PMID: 34663907 PMCID: PMC8522258 DOI: 10.1038/s41418-021-00892-y] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2021] [Revised: 09/30/2021] [Accepted: 10/04/2021] [Indexed: 12/15/2022] Open
Abstract
SARS-CoV-2 vaccinations have greatly reduced COVID-19 cases, but we must continue to develop our understanding of the nature of the disease and its effects on human immunity. Previously, we suggested that a dysregulated STAT3 pathway following SARS-Co-2 infection ultimately leads to PAI-1 activation and cascades of pathologies. The major COVID-19-associated metabolic risks (old age, hypertension, cardiovascular diseases, diabetes, and obesity) share high PAI-1 levels and could predispose certain groups to severe COVID-19 complications. In this review article, we describe the common metabolic profile that is shared between all of these high-risk groups and COVID-19. This profile not only involves high levels of PAI-1 and STAT3 as previously described, but also includes low levels of glutamine and NAD+, coupled with overproduction of hyaluronan (HA). SARS-CoV-2 infection exacerbates this metabolic imbalance and predisposes these patients to the severe pathophysiologies of COVID-19, including the involvement of NETs (neutrophil extracellular traps) and HA overproduction in the lung. While hyperinflammation due to proinflammatory cytokine overproduction has been frequently documented, it is recently recognized that the immune response is markedly suppressed in some cases by the expansion and activity of MDSCs (myeloid-derived suppressor cells) and FoxP3+ Tregs (regulatory T cells). The metabolomics profiles of severe COVID-19 patients and patients with advanced cancer are similar, and in high-risk patients, SARS-CoV-2 infection leads to aberrant STAT3 activation, which promotes a cancer-like metabolism. We propose that glutamine deficiency and overproduced HA is the central metabolic characteristic of COVID-19 and its high-risk groups. We suggest the usage of glutamine supplementation and the repurposing of cancer drugs to prevent the development of severe COVID-19 pneumonia.
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Affiliation(s)
- Toshifumi Matsuyama
- Department of Pathology, Nagasaki University Graduate School of Biomedical Sciences, 1-12-4 Sakamoto, Nagasaki, 852-8523, Japan.
| | | | - Kimitaka Shibue
- Tazuke Kofukai Medical Research Institute, Kitano Hospital, Osaka, Japan
| | - Tak W Mak
- Princess Margaret Cancer Centre, University Health Network, 610 University Avenue, Toronto, ON, M5G 2M9, Canada
- Department of Medical Biophysics, University of Toronto, 101 College Street, Toronto, ON, M5G 1L7, Canada
- Department of Immunology, University of Toronto, 101 College Street, Toronto, ON, M5G 1L7, Canada
- Department of Pathology, University of Hong Kong, Hong Kong, Pok Fu Lam, 999077, Hong Kong
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Sriboonvorakul N, Pan-Ngum W, Poovorawan K, Muangnoicharoen S, Quinn LM, Tan BK. Low Branched Chain Amino Acids and Tyrosine in Thai Patients with Type 2 Diabetes Mellitus Treated with Metformin and Metformin-Sulfonylurea Combination Therapies. J Clin Med 2021; 10:5424. [PMID: 34830706 PMCID: PMC8621185 DOI: 10.3390/jcm10225424] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2021] [Revised: 11/09/2021] [Accepted: 11/18/2021] [Indexed: 12/15/2022] Open
Abstract
Type 2 diabetes mellitus (T2DM) is a growing public health challenge for Thailand (current prevalence ~10.0%). Amino acids offer novel biomarkers to predict risk of T2DM and indicate sub-optimal disease management, which could facilitate earlier treatment. We studied amino acid profiles in a Thai cohort comprising of individuals with T2DM (n = 65 single-drug-treated; n = 38 multi-drug-treated) compared to healthy controls (n = 104) using liquid chromatography-mass spectrometry. Age and BMI were significantly lower in the healthy controls compared to the single or multi-treated T2DM groups. The BCAA (leucine and valine) were significantly lower in the single and multi-treated T2DM groups compared to healthy controls (p < 0.001 and p < 0.001) and isoleucine was significantly lower in the single-treated compared to the healthy controls (p = 0.014). These findings beg the question whether BCAAs supplementation be beneficial in T2DM patients treated with single or multi-drug therapy? Tyrosine was significantly lower in the single and multi-treated T2DM groups compared to healthy controls (p < 0.001 and p = 0.002), whereas phenylalanine was significantly higher in the multi-treated T2DM group compared to the single treated T2DM group (p = 0.045). We provide novel insights into the effects of diabetes treatments on these amino acids in insulin resistant states such as T2DM in a unique but understudied Thai population.
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Affiliation(s)
- Natthida Sriboonvorakul
- Department of Clinical Tropical Medicine, Faculty of Tropical Medicine, Mahidol University, Bangkok 10400, Thailand; (N.S.); (K.P.); (S.M.)
| | - Wirichada Pan-Ngum
- Department of Tropical Hygiene, Faculty of Tropical Medicine, Mahidol University, Bangkok 10400, Thailand;
| | - Kittiyod Poovorawan
- Department of Clinical Tropical Medicine, Faculty of Tropical Medicine, Mahidol University, Bangkok 10400, Thailand; (N.S.); (K.P.); (S.M.)
| | - Sant Muangnoicharoen
- Department of Clinical Tropical Medicine, Faculty of Tropical Medicine, Mahidol University, Bangkok 10400, Thailand; (N.S.); (K.P.); (S.M.)
| | - Lauren M. Quinn
- Department of Immunology and Immunotherapy, University of Birmingham, Birmingham B15 2TT, UK;
| | - Bee K. Tan
- Department of Clinical Tropical Medicine, Faculty of Tropical Medicine, Mahidol University, Bangkok 10400, Thailand; (N.S.); (K.P.); (S.M.)
- Department of Cardiovascular Sciences and Diabetes Research Centre, University of Leicester, Leicester LE1 7RH, UK
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McClain KM, Friedenreich CM, Matthews CE, Sampson JN, Check DP, Brenner DR, Courneya KS, Murphy RA, Moore SC. Body Composition and Metabolomics in the Alberta Physical Activity and Breast Cancer Prevention Trial. J Nutr 2021; 152:419-428. [PMID: 34791348 PMCID: PMC8826845 DOI: 10.1093/jn/nxab388] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2021] [Revised: 08/06/2021] [Accepted: 11/11/2021] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Obesity is correlated with many biomarkers, but the extent to which these correlate with underlying body composition is poorly understood. OBJECTIVES Our objectives were to 1) describe/compare distinct contributions of fat/lean mass with BMI-metabolite correlations and 2) identify novel metabolite biomarkers of fat/lean mass. METHODS The Alberta Physical Activity and Breast Cancer Prevention Trial was a 2-center randomized trial of healthy, inactive, postmenopausal women (n = 304). BMI (in kg/m2) was calculated using weight and height, whereas DXA estimated fat/lean mass. Ultra-performance liquid chromatography and mass spectrometry measured relative concentrations of serum metabolite concentrations. We estimated partial Pearson correlations between 1052 metabolites and BMI, adjusting for age, smoking, and site. Fat mass index (FMI; kg/m2) and lean mass index (LMI; kg/m2) correlations were estimated similarly, with mutual adjustment to evaluate independent effects. RESULTS Using a Bonferroni-corrected α level <4.75 × 10-5, we observed 53 BMI-correlated metabolites (|r| = 0.24-0.42). Of those, 21 were robustly correlated with FMI (|r| > 0.20), 25 modestly (0.10 ≤ |r| ≤ 0.20), and 7 virtually null (|r| < 0.10). Ten of 53 were more strongly correlated with LMI than with FMI. Examining non-BMI-correlated metabolites, 6 robustly correlated with FMI (|r| = 0.24-0.31) and 2 with LMI (r = 0.25-0.26). For these, correlations for fat and lean mass were in opposing directions compared with BMI-correlated metabolites, in which correlations were mostly in the same direction. CONCLUSIONS Our results demonstrate how a thorough evaluation of the components of fat and lean mass, along with BMI, provides a more accurate assessment of the associations between body composition and metabolites than BMI alone. Such an assessment makes evident that some metabolites correlated with BMI predominantly reflect lean mass rather than fat, and some metabolites related to body composition are not correlated with BMI. Correctly characterizing these relations is important for an accurate understanding of how and why obesity is associated with disease.
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Affiliation(s)
| | - Christine M Friedenreich
- Department of Cancer Epidemiology and Prevention Research, Cancer Care Alberta, Alberta Health Services, Edmonton, AB, Canada,Departments of Oncology and Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Charles E Matthews
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | - Joshua N Sampson
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | - David P Check
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | - Darren R Brenner
- Departments of Oncology and Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Kerry S Courneya
- Faculty of Kinesiology, Sport, and Recreation, University of Alberta, Edmonton, AB, Canada
| | - Rachel A Murphy
- School of Population and Public Health, The University of British Columbia, Vancouver, BC, Canada,Cancer Control Research, BC Cancer, Vancouver, BC, Canada
| | - Steven C Moore
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
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Abstract
Background Cardiorespiratory fitness (CRF) is a potent health marker, the improvement of which is associated with a reduced incidence of non-communicable diseases and all-cause mortality. Identifying metabolic signatures associated with CRF could reveal how CRF fosters human health and lead to the development of novel health-monitoring strategies. Objective This article systematically reviewed reported associations between CRF and metabolites measured in human tissues and body fluids. Methods PubMed, EMBASE, and Web of Science were searched from database inception to 3 June, 2021. Metabolomics studies reporting metabolites associated with CRF, measured by means of cardiopulmonary exercise test, were deemed eligible. Backward and forward citation tracking on eligible records were used to complement the results of database searching. Risk of bias at the study level was assessed using QUADOMICS. Results Twenty-two studies were included and 667 metabolites, measured in plasma (n = 619), serum (n = 18), skeletal muscle (n = 16), urine (n = 11), or sweat (n = 3), were identified. Lipids were the metabolites most commonly positively (n = 174) and negatively (n = 274) associated with CRF. Specific circulating glycerophospholipids (n = 85) and cholesterol esters (n = 17) were positively associated with CRF, while circulating glycerolipids (n = 152), glycerophospholipids (n = 42), acylcarnitines (n = 14), and ceramides (n = 12) were negatively associated with CRF. Interestingly, muscle acylcarnitines were positively correlated with CRF (n = 15). Conclusions Cardiorespiratory fitness was associated with circulating and muscle lipidome composition. Causality of the revealed associations at the molecular species level remains to be investigated further. Finally, included studies were heterogeneous in terms of participants’ characteristics and analytical and statistical approaches. PROSPERO Registration Number CRD42020214375. Supplementary Information The online version contains supplementary material available at 10.1007/s40279-021-01590-y.
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Piras C, Noto A, Ibba L, Deidda M, Fanos V, Muntoni S, Leoni VP, Atzori L. Contribution of Metabolomics to the Understanding of NAFLD and NASH Syndromes: A Systematic Review. Metabolites 2021; 11:metabo11100694. [PMID: 34677409 PMCID: PMC8541039 DOI: 10.3390/metabo11100694] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Revised: 10/03/2021] [Accepted: 10/06/2021] [Indexed: 12/20/2022] Open
Abstract
Several differential panels of metabolites have been associated with the presence of metabolic syndrome and its related conditions, namely non-alcoholic fatty liver disease (NAFLD) and non-alcoholic steatohepatitis (NASH). This study aimed to perform a systematic review to summarize the most recent finding in terms of circulating biomarkers following NAFLD/NASH syndromes. Hence, the research was focused on NAFLD/NASH studies analysed by metabolomics approaches. Following Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines, a systematic search was conducted on the PubMed database. The inclusion criteria were (i) publication date between 2010 and 2021, (ii) presence of the combination of terms: metabolomics and NAFLD/NASH, and (iii) published in a scholarly peer-reviewed journal. Studies were excluded from the review if they were (i) single-case studies, (ii) unpublished thesis and dissertation studies, and (iii) not published in a peer-reviewed journal. Following these procedures, 10 eligible studies among 93 were taken into consideration. The metabolisms of amino acids, fatty acid, and vitamins were significantly different in patients affected by NAFLD and NASH compared to healthy controls. These findings suggest that low weight metabolites are an important indicator for NAFLD/NASH syndrome and there is a strong overlap between NAFLD/NASH and the metabolic syndrome. These findings may lead to new perspectives in early diagnosis, identification of novel biomarkers, and providing novel targets for pharmacological interventions.
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Affiliation(s)
- Cristina Piras
- Department of Biomedical Sciences, University of Cagliari, 09042 Monserrato, Italy; (C.P.); (L.I.); (S.M.); (V.P.L.); (L.A.)
| | - Antonio Noto
- Department of Biomedical Sciences, University of Cagliari, 09042 Monserrato, Italy; (C.P.); (L.I.); (S.M.); (V.P.L.); (L.A.)
- Correspondence:
| | - Luciano Ibba
- Department of Biomedical Sciences, University of Cagliari, 09042 Monserrato, Italy; (C.P.); (L.I.); (S.M.); (V.P.L.); (L.A.)
| | - Martino Deidda
- Department of Medical Sciences and Public Health, University of Cagliari, 09042 Monserrato, Italy;
| | - Vassilios Fanos
- Neonatal Intensive Care Unit, Department of Surgical Sciences, University of Cagliari, 09042 Monserrato, Italy;
| | - Sandro Muntoni
- Department of Biomedical Sciences, University of Cagliari, 09042 Monserrato, Italy; (C.P.); (L.I.); (S.M.); (V.P.L.); (L.A.)
| | - Vera Piera Leoni
- Department of Biomedical Sciences, University of Cagliari, 09042 Monserrato, Italy; (C.P.); (L.I.); (S.M.); (V.P.L.); (L.A.)
| | - Luigi Atzori
- Department of Biomedical Sciences, University of Cagliari, 09042 Monserrato, Italy; (C.P.); (L.I.); (S.M.); (V.P.L.); (L.A.)
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Zhang Y, Yang Y, Ding L, Wang Z, Xiao Y, Xiao W. Emerging Applications of Metabolomics to Assess the Efficacy of Traditional Chinese Medicines for Treating Type 2 Diabetes Mellitus. Front Pharmacol 2021; 12:735410. [PMID: 34603052 PMCID: PMC8486080 DOI: 10.3389/fphar.2021.735410] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Accepted: 09/08/2021] [Indexed: 12/14/2022] Open
Abstract
Diabetes is a common and complex disease that can exacerbate the complications related to cardiovascular disease, and this is especially true for type 2 diabetes mellitus (T2DM). In addition to the standard pharmacological therapies, T2DM has also been treated with nonconventional regimens such as traditional Chinese medicine (TCM), e.g., herbal medicines and TCM prescriptions, although the mechanisms underlying the therapeutic benefits remain unclear. In this regard, many studies have used metabolomics technology to elucidate the basis for the efficacy of TCM for T2DM. Metabolomics has recently attracted much attention with regard to drug discovery and pharmacologically relevant natural products. In this review, we summarize the application of metabolomics to the assessment of TCM efficacy for treating T2DM. Increasing evidence suggests that the metabolic profile of an individual patient may reflect a specific type of T2DM syndrome, which may provide a new perspective for disease diagnosis. In addition, TCM has proved effective for countering the metabolic disorders related to T2DM, and this may constitute the basis for TCM efficacy. Therefore, further determining how TCM contributes to the reversal of metabolic disorders, such as using network pharmacology or by assessing the contribution of host–gut microbiota interactions, will also provide researchers with new potential targets for pharmacologic-based therapies.
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Affiliation(s)
- Yumeng Zhang
- The Ministry of Education (MOE) Key Laboratory for Standardization of Chinese Medicines, Institute of Chinese Materia Medica, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Yingbo Yang
- The Ministry of Education (MOE) Key Laboratory for Standardization of Chinese Medicines, Institute of Chinese Materia Medica, Shanghai University of Traditional Chinese Medicine, Shanghai, China.,Jiangsu Kanion Pharmaceutical Co., Ltd., Lianyungang, China
| | - Lili Ding
- The Ministry of Education (MOE) Key Laboratory for Standardization of Chinese Medicines, Institute of Chinese Materia Medica, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Zhengtao Wang
- The Ministry of Education (MOE) Key Laboratory for Standardization of Chinese Medicines, Institute of Chinese Materia Medica, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Ying Xiao
- The Ministry of Education (MOE) Key Laboratory for Standardization of Chinese Medicines, Institute of Chinese Materia Medica, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Wei Xiao
- The Ministry of Education (MOE) Key Laboratory for Standardization of Chinese Medicines, Institute of Chinese Materia Medica, Shanghai University of Traditional Chinese Medicine, Shanghai, China.,Jiangsu Kanion Pharmaceutical Co., Ltd., Lianyungang, China
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Duan Y, Sun H, Yao Y, Han L, Chen L. Perturbation of serum metabolome in relation to type 2 diabetes mellitus and urinary levels of phthalate metabolites and bisphenols. ENVIRONMENT INTERNATIONAL 2021; 155:106609. [PMID: 33965767 DOI: 10.1016/j.envint.2021.106609] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/05/2021] [Revised: 04/08/2021] [Accepted: 04/26/2021] [Indexed: 06/12/2023]
Abstract
BACKGROUND Emerging evidence has proved the associations between exposure to phthalates (PAEs) and bisphenols and type 2 diabetes mellitus (T2DM), but the underlying mechanisms for these associations are poorly understood. Metabolomics is a powerful tool to identify differential metabolites and metabolic pathways related to diseases and chemical exposure, which may reveal underlying mechanisms. However, little is known about the roles of metabolism in the associations for PAE and bisphenol exposure with T2DM. OBJECTIVES The purpose of the study was to investigate the roles of metabolism in the associations for exposure to PAEs and bisphenols with T2DM. METHODS In this study, 60 T2DM cases and 60 controls, who were matched in age, sex, and body mass index (BMI), were selected from the total study population in our previous studies. Fasting blood and spot urine samples of the volunteers were used for non-targeted metabolomics analysis and determination of phthalate metabolites (mPAEs) and bisphenols, respectively. The associations of urinary mPAEs and bisphenols with screened metabolic biomarkers in metabolomics analysis were analyzed using multiple linear regression models. RESULTS Based on non-targeted metabolomics, 19 serum metabolic biomarkers were screened between T2DM cases and controls, mostly related to galactose metabolism, amino acid metabolism, and pyrimidine metabolism. More than half of mPAEs were mostly positively associated with up-regulated metabolic biomarkers and negatively associated with down-regulated biomarkers. Different from PAEs, no evident results suggested the roles of metabolism in the associations between bisphenol exposure and T2DM. CONCLUSIONS Combined with the positive associations between most urinary mPAEs and T2DM in our previous study, our findings indicated that PAE exposure may contribute to T2DM risk through disturbing galactose metabolism, amino acid metabolism (especially arginine biosynthesis and alanine, aspartate and glutamate metabolism), and pyrimidine metabolism.
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Affiliation(s)
- Yishuang Duan
- Hubei Key Laboratory of Environmental and Health Effects of Persistent Toxic Substances, Institute of Environment and Health, Jianghan University, Wuhan, China; Ministry of Education Key Laboratory of Pollution Processes and Environmental Criteria, College of Environmental Science and Engineering, Nankai University, Tianjin, China.
| | - Hongwen Sun
- Ministry of Education Key Laboratory of Pollution Processes and Environmental Criteria, College of Environmental Science and Engineering, Nankai University, Tianjin, China.
| | - Yiming Yao
- Ministry of Education Key Laboratory of Pollution Processes and Environmental Criteria, College of Environmental Science and Engineering, Nankai University, Tianjin, China.
| | - Liping Han
- Tianjin Medical University Metabolic Diseases Hospital, Tianjin, China.
| | - Liming Chen
- Tianjin Medical University Metabolic Diseases Hospital, Tianjin, China.
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Bucher M, Montaniel KRC, Myatt L, Weintraub S, Tavori H, Maloyan A. Dyslipidemia, insulin resistance, and impairment of placental metabolism in the offspring of obese mothers. J Dev Orig Health Dis 2021; 12:738-747. [PMID: 33185172 PMCID: PMC8606174 DOI: 10.1017/s2040174420001026] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Obesity is a chronic condition associated with dyslipidemia and insulin resistance. Here, we show that the offspring of obese mothers are dyslipidemic and insulin resistant from the outset.Maternal and cord blood and placental tissues were collected following C-section at term. Patients were grouped as being normal weight (NW, BMI = 18-24.9) or obese (OB, BMI ≥ 30), and separated by fetal sex. We measured plasma lipids, insulin, and glucose in maternal and cord blood. Insulin resistance was quantified using the HOMA-IR. Placental markers of lipid and energy metabolism and relevant metabolites were measured by western blot and metabolomics, respectively.For OB women, total cholesterol was decreased in both maternal and cord blood, while HDL was decreased only in cord blood, independent of sex. In babies born to OB women, cord blood insulin and insulin resistance were increased. Placental protein expression of the energy and lipid metabolism regulators PGC1α, and SIRT3, ERRα, CPT1α, and CPT2 decreased with maternal obesity in a sex-dependent manner (P < 0.05). Metabolomics showed lower levels of acylcarnitines C16:0, C18:2, and C20:4 in OB women's placentas, suggesting a decrease in β-oxidation. Glutamine, glutamate, alpha-ketoglutarate (αKG), and 2-hydroxyglutarate (2-HG) were increased, and the glutamine-to-glutamate ratio decreased (P < 0.05), in OB placentas, suggesting induction of glutamate into αKG conversion to maintain a normal metabolic flux.Newly-born offspring of obese mothers begin their lives dyslipidemic and insulin resistant. If not inherited genetically, such major metabolic perturbations might be explained by abnormal placental metabolism with potential long-term adverse consequences for the offspring's health and wellbeing.
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Affiliation(s)
- Matthew Bucher
- Knight Cardiovascular Institute, School of Medicine, Oregon Health & Science University, Portland, OR, USA
- Department of OB/GYN, Oregon Health & Science University, Portland, OR, USA
| | - Kim Ramil C. Montaniel
- Knight Cardiovascular Institute, School of Medicine, Oregon Health & Science University, Portland, OR, USA
- The Graduate Program in Biomedical Sciences (PBMS), Oregon Health & Science University, Portland, OR, USA
| | - Leslie Myatt
- Department of OB/GYN, Oregon Health & Science University, Portland, OR, USA
| | - Susan Weintraub
- Department of Biochemistry, The Metabolomics Core Facility, Institutional Mass Spectrometry Laboratory, University of Texas Health, San Antonio, TX, USA
| | - Hagai Tavori
- Knight Cardiovascular Institute, School of Medicine, Oregon Health & Science University, Portland, OR, USA
| | - Alina Maloyan
- Knight Cardiovascular Institute, School of Medicine, Oregon Health & Science University, Portland, OR, USA
- The Graduate Program in Biomedical Sciences (PBMS), Oregon Health & Science University, Portland, OR, USA
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Muresan AA, Rusu A, Roman G, Bala C. METABOLOMIC ANALYSIS OF NORMAL WEIGHT, HEALTHY AND UNHEALTHY OBESITY: AMINO ACID CHANGE ACROSS THE SPECTRUM OF METABOLIC WELLBEING IN WOMEN. ACTA ENDOCRINOLOGICA (BUCHAREST, ROMANIA : 2005) 2021; 17:427-431. [PMID: 35747872 DOI: 10.4183/aeb.2021.427] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Context Obesity is a complex and heterogeneous disorder with multiple phenotypes described. Although metabolomic biomarkers of obesity have been extensively studied, biomarkers of obesity phenotypes and differences between these phenotypes and normal-weight (NW) persons have been less investigated. Objective The objective of this cross-sectional analysis was to investigate serum amino acids (AA) as markers of metabolic alterations in obesity phenotypes and NW. Design Cross-sectional. Subjects and Methods By targeted metabolomics we analyzed serum samples of 70 women using ultrahigh-performance liquid chromatography/mass spectrometry. Participants were divided into 3 groups: NW, metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUHO). Results Five AAs were significantly different between study groups: cysteine, methionine, asparagine, glutamine, and lysine (p-value <0.05 and variable importance in the projection >1). Cysteine increased linearly with metabolic unwellness from NW to MUHO. Lysine and glutamine were significantly higher, and asparagine was significantly lower in NW and MHO than in MUHO. Conclusions By trend and group analysis we identified specific changes in serum AAs along with the progression of metabolically unwellness.
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Affiliation(s)
- A A Muresan
- "Iuliu Hatieganu" University of Medicine and Pharmacy - Diabetes, Nutrition and Metabolic Diseases, Cluj-Napoca, Romania
| | - A Rusu
- "Iuliu Hatieganu" University of Medicine and Pharmacy - Diabetes, Nutrition and Metabolic Diseases, Cluj-Napoca, Romania
| | - G Roman
- "Iuliu Hatieganu" University of Medicine and Pharmacy - Diabetes, Nutrition and Metabolic Diseases, Cluj-Napoca, Romania
| | - C Bala
- "Iuliu Hatieganu" University of Medicine and Pharmacy - Diabetes, Nutrition and Metabolic Diseases, Cluj-Napoca, Romania
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Das SK, Ainsworth HC, Dimitrov L, Okut H, Comeau ME, Sharma N, Ng MCY, Norris JM, Chen YDI, Wagenknecht LE, Bowden DW, Hsu FC, Taylor KD, Langefeld CD, Palmer ND. Metabolomic architecture of obesity implicates metabolonic lactone sulfate in cardiometabolic disease. Mol Metab 2021; 54:101342. [PMID: 34563731 PMCID: PMC8640864 DOI: 10.1016/j.molmet.2021.101342] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/09/2021] [Accepted: 09/17/2021] [Indexed: 12/28/2022] Open
Abstract
OBJECTIVE Identify and characterize circulating metabolite profiles associated with adiposity to inform precision medicine. METHODS Untargeted plasma metabolomic profiles in the Insulin Resistance Atherosclerosis Family Study (IRASFS) Mexican American cohort (n = 1108) were analyzed for association with anthropometric (body mass index, BMI; waist circumference, WC; waist-to-hip ratio, WHR) and computed tomography measures (visceral adipose tissue, VAT; subcutaneous adipose tissue, SAT; visceral-to-subcutaneous ratio, VSR) of adiposity. Genetic data, inclusive of genome-wide array-based genotyping, whole exome sequencing (WES) and whole genome sequencing (WGS), were evaluated to identify the genetic contributors. Phenotypic and genetic association signals were replicated across ancestries. Transcriptomic data were analyzed to explore the relationship between genetic and metabolomic data. RESULTS A partially characterized metabolite, tentatively named metabolonic lactone sulfate (X-12063), was consistently associated with BMI, WC, WHR, VAT, and SAT in IRASFS Mexican Americans (PMA <2.02 × 10-27). Trait associations were replicated in IRASFS African Americans (PAA < 1.12 × 10-07). Expanded analyses revealed associations with multiple phenotypic measures of cardiometabolic health, e.g. insulin sensitivity (SI), triglycerides (TG), diastolic blood pressure (DBP) and plasminogen activator inhibitor-1 (PAI-1) in both ancestries. Metabolonic lactone sulfate levels were heritable (h2 > 0.47), and a significant genetic signal at the ZSCAN25/CYP3A5 locus (PMA = 9.00 × 10-41, PAA = 2.31 × 10-10) was observed, highlighting a putative functional variant (rs776746, CYP3A5∗3). Transcriptomic analysis in the African American Genetics of Metabolism and Expression (AAGMEx) cohort supported the association of CYP3A5 with metabolonic lactone sulfate levels (PFDR = 6.64 × 10-07). CONCLUSIONS Variant rs776746 is associated with a decrease in the transcript levels of CYP3A5, which in turn is associated with increased metabolonic lactone sulfate levels and poor cardiometabolic health.
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Affiliation(s)
- Swapan K Das
- Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Hannah C Ainsworth
- Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Latchezar Dimitrov
- Department of Epidemiology and Prevention, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Hayrettin Okut
- Office of Research, University of Kansas Medical Center, Wichita, Kansas, USA
| | - Mary E Comeau
- Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Neeraj Sharma
- Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Maggie C Y Ng
- Division of Genetic Medicine, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Jill M Norris
- Department of Epidemiology, Colorado School of Public Health, Aurora, CO, USA
| | - Yii-der I Chen
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Lynne E Wagenknecht
- Department of Epidemiology and Prevention, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Donald W Bowden
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Fang-Chi Hsu
- Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Kent D Taylor
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Carl D Langefeld
- Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Nicholette D Palmer
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA.
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Qing Q, Huang L, Sun W, Chen J, Yu N, Chen Y, Xu D, Zhao M. Maternal and fetal metabolomic alterations in maternal lipopolysaccharide exposure-induced male offspring glucose metabolism disorders. Biomed Chromatogr 2021; 36:e5234. [PMID: 34477231 DOI: 10.1002/bmc.5234] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2021] [Revised: 08/20/2021] [Accepted: 08/24/2021] [Indexed: 11/06/2022]
Abstract
Maternal lipopolysaccharide (LPS) exposure during pregnancy induces metabolic abnormalities in male offspring, but the underlying mechanisms remain unclear. The purpose of this study was to investigate the effects of maternal LPS exposure during pregnancy on metabolic profiling of maternal serum and male fetal liver using Liquid Chromatograph Mass Spectrometer techniques. From day 15 to day 17 of gestation, pregnant mice were administered intraperitoneal LPS (experimental group) (50 μg/kg/d) or saline (control group). On day 18 of gestation, maternal serum and male fetal liver were collected. After LPS exposure, levels of 38 and 75 metabolites, mainly glycerophospholipid and fatty acid metabolites, were altered in maternal serum and male fetal liver, respectively. It was found that in maternal serum and male fetal livers, the glycerophospholipids containing saturated fatty acids (SFAs) and the SFAs were upregulated, while the glycerophospholipids containing polyunsaturated fatty acids (PUFAs) and the PUFAs were downregulated. This concordance between maternal and fetal alterations in glycerophospholipid and fatty acid metabolites may be a metabolomic signature of the early intrauterine period and may provide insight into the mechanisms by which maternal LPS exposure induces disorders of glucose metabolism in male offspring.
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Affiliation(s)
- Qiting Qing
- School of Nursing, Anhui Medical University, Hefei, China
| | - Lili Huang
- School of Nursing, Anhui Medical University, Hefei, China
| | - Wanxiao Sun
- School of Nursing, Anhui Medical University, Hefei, China
| | - Jing Chen
- School of Nursing, Anhui Medical University, Hefei, China
| | - Ningning Yu
- School of Nursing, Anhui Medical University, Hefei, China
| | - Yuanhua Chen
- Department of Histology and Embryology, Anhui Medical University, Hefei, China
| | - Dexiang Xu
- Department of Toxicology, Anhui Medical University, Hefei, China
| | - Mei Zhao
- School of Nursing, Anhui Medical University, Hefei, China
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Liu C, Sun YV. Anticipation of Precision Diabetes and Promise of Integrative Multi-Omics. Endocrinol Metab Clin North Am 2021; 50:559-574. [PMID: 34399961 DOI: 10.1016/j.ecl.2021.05.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Precision diabetes is a concept of customizing delivery of health practices based on variability of diabetes. The authors reviewed recent research on type 2 diabetes heterogeneity and -omic biomarkers, including genomic, epigenomic, and metabolomic markers associated with type 2 diabetes. The emerging multiomics approach integrates complementary and interconnected molecular layers to provide systems level understanding of disease mechanisms and subtypes. Although the multiomic approach is not currently ready for routine clinical applications, future studies in the context of precision diabetes, particular in populations from diverse ethnic and demographic groups, may lead to improved diagnosis, treatment, and management of diabetes and diabetic complications.
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Affiliation(s)
- Chang Liu
- Department of Epidemiology, Emory University Rollins School of Public Health, 1518 Clifton Road Northeast, Atlanta, GA 30322, USA
| | - Yan V Sun
- Department of Epidemiology, Emory University Rollins School of Public Health, 1518 Clifton Road Northeast, Atlanta, GA 30322, USA; Atlanta VA Healthcare System, 1670 Clairmont Road, Decatur, GA 30033, USA.
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Molsberry S, Bjornevik K, Hughes KC, Zhang ZJ, Jeanfavre S, Clish C, Healy B, Schwarzschild M, Ascherio A. Plasma Metabolomic Markers of Insulin Resistance and Diabetes and Rate of Incident Parkinson's Disease. JOURNAL OF PARKINSONS DISEASE 2021; 10:1011-1021. [PMID: 32250318 DOI: 10.3233/jpd-191896] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
BACKGROUND Although there is evidence of shared dysregulated pathways between diabetes and Parkinson's disease, epidemiologic research on an association between the two diseases has produced inconsistent results. OBJECTIVE We aimed to assess whether known metabolomic markers of insulin resistance and diabetes are also associated with Parkinson's disease development. METHODS We conducted a nested case-control study among Nurses' Health Study and Health Professionals Follow-up Study participants who had provided blood samples up to twenty years prior to Parkinson's diagnosis. Cases were matched to risk-set sampled controls by age, sex, fasting status, and time of blood collection. Participants provided covariate information via regularly collected cohort questionnaires. We used conditional logistic regression models to assess whether plasma levels of branched chain amino acids, acylcarnitines, glutamate, or glutamine were associated with incident development of Parkinson's disease. RESULTS A total of 349 case-control pairs were included in this analysis. In the primary analyses, none of the metabolites of interest were associated with Parkinson's disease development. In investigations of the association between each metabolite and Parkinson's disease at different time intervals prior to diagnosis, some metabolites showed marginally significant association but, after correction for multiple testing, only C18 : 2 acylcarnitine was significantly associated with Parkinson's disease among subjects for whom blood was collected less than 60 months prior to case diagnosis. CONCLUSIONS Plasma levels of diabetes-related metabolites did not contribute to predict risk of Parkinson's disease. Further investigation of the relationship between pre-diagnostic levels of diabetes-related metabolites and Parkinson's disease in other populations is needed to confirm these findings.
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Affiliation(s)
- Samantha Molsberry
- Population Health Sciences Program, Harvard University, Cambridge, MA, USA
| | - Kjetil Bjornevik
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Katherine C Hughes
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Zhongli Joel Zhang
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Sarah Jeanfavre
- Metabolomics Platform, Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA, USA
| | - Clary Clish
- Metabolomics Platform, Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA, USA
| | - Brian Healy
- Partners Multiple Sclerosis Center, Brigham and Women's Hospital, Boston, MA, USA
| | | | - Alberto Ascherio
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA.,Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.,Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
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Difference in the metabolome of colostrum from healthy mothers and mothers with type 2 diabetic mellitus. Eur Food Res Technol 2021. [DOI: 10.1007/s00217-021-03814-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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Dossus L, Kouloura E, Biessy C, Viallon V, Siskos AP, Dimou N, Rinaldi S, Merritt MA, Allen N, Fortner R, Kaaks R, Weiderpass E, Gram IT, Rothwell JA, Lécuyer L, Severi G, Schulze MB, Nøst TH, Crous-Bou M, Sánchez MJ, Amiano P, Colorado-Yohar SM, Gurrea AB, Schmidt JA, Palli D, Agnoli C, Tumino R, Sacerdote C, Mattiello A, Vermeulen R, Heath AK, Christakoudi S, Tsilidis KK, Travis RC, Gunter MJ, Keun HC. Prospective analysis of circulating metabolites and endometrial cancer risk. Gynecol Oncol 2021; 162:475-481. [PMID: 34099314 PMCID: PMC8336647 DOI: 10.1016/j.ygyno.2021.06.001] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2021] [Accepted: 06/01/2021] [Indexed: 12/24/2022]
Abstract
BACKGROUND Endometrial cancer is strongly associated with obesity and dysregulation of metabolic factors such as estrogen and insulin signaling are causal risk factors for this malignancy. To identify additional novel metabolic pathways associated with endometrial cancer we performed metabolomic analyses on pre-diagnostic plasma samples from 853 case-control pairs from the European Prospective Investigation into Cancer and Nutrition (EPIC). METHODS A total of 129 metabolites (acylcarnitines, amino acids, biogenic amines, glycerophospholipids, hexoses, and sphingolipids) were measured by liquid chromatography-mass spectrometry. Conditional logistic regression estimated the associations of metabolites with endometrial cancer risk. An analysis focusing on clusters of metabolites using the bootstrap lasso method was also employed. RESULTS After adjustment for body mass index, sphingomyelin [SM] C18:0 was positively (OR1SD: 1.18, 95% CI: 1.05-1.33), and glycine, serine, and free carnitine (C0) were inversely (OR1SD: 0.89, 95% CI: 0.80-0.99; OR1SD: 0.89, 95% CI: 0.79-1.00 and OR1SD: 0.91, 95% CI: 0.81-1.00, respectively) associated with endometrial cancer risk. Serine, C0 and two sphingomyelins were selected by the lasso method in >90% of the bootstrap samples. The ratio of esterified to free carnitine (OR1SD: 1.14, 95% CI: 1.02-1.28) and that of short chain to free acylcarnitines (OR1SD: 1.12, 95% CI: 1.00-1.25) were positively associated with endometrial cancer risk. Further adjustment for C-peptide or other endometrial cancer risk factors only minimally altered the results. CONCLUSION These findings suggest that variation in levels of glycine, serine, SM C18:0 and free carnitine may represent specific pathways linked to endometrial cancer development. If causal, these pathways may offer novel targets for endometrial cancer prevention.
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Affiliation(s)
- Laure Dossus
- Nutrition and Metabolism Section, International Agency for Research on Cancer, Lyon, France.
| | - Eirini Kouloura
- Cancer Metabolism and Systems Toxicology Group, Division of Cancer, Department of Surgery and Cancer, Imperial College, London, UK; European Food Safety Authority, Via Carlo Magno 1A, 43126 Parma, Italy
| | - Carine Biessy
- Nutrition and Metabolism Section, International Agency for Research on Cancer, Lyon, France
| | - Vivian Viallon
- Nutrition and Metabolism Section, International Agency for Research on Cancer, Lyon, France
| | - Alexandros P Siskos
- Cancer Metabolism and Systems Toxicology Group, Division of Cancer, Department of Surgery and Cancer, Imperial College, London, UK
| | - Niki Dimou
- Nutrition and Metabolism Section, International Agency for Research on Cancer, Lyon, France
| | - Sabina Rinaldi
- Nutrition and Metabolism Section, International Agency for Research on Cancer, Lyon, France
| | - Melissa A Merritt
- Cancer Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI, USA
| | - Naomi Allen
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Renee Fortner
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Rudolf Kaaks
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Elisabete Weiderpass
- Office of the Director, International Agency for Research on Cancer, Lyon, France
| | - Inger T Gram
- Department of Community Medicine, Faculty of Health Sciences, University of Tromsø, The Arctic University of Norway, Troms, Norway
| | - Joseph A Rothwell
- Centre for Research in Epidemiology and Population Health, CESP, Université Paris-Saclay, UVSQ, Inserm U1018, Villejuif, France; Gustave Roussy, Villejuif, France
| | - Lucie Lécuyer
- Centre for Research in Epidemiology and Population Health, CESP, Université Paris-Saclay, UVSQ, Inserm U1018, Villejuif, France; Gustave Roussy, Villejuif, France
| | - Gianluca Severi
- Centre for Research in Epidemiology and Population Health, CESP, Université Paris-Saclay, UVSQ, Inserm U1018, Villejuif, France; Gustave Roussy, Villejuif, France; Department of Statistics, Computer Science and Applications "G. Parenti" (DISIA), University of Florence, Italy
| | - Matthias B Schulze
- Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany; Institute of Nutritional Science, University of Potsdam, Potsdam, Germany
| | - Therese Haugdahl Nøst
- Department of Community Medicine, Faculty of Health Sciences, University of Tromsø, The Arctic University of Norway, Troms, Norway
| | - Marta Crous-Bou
- Unit of Nutrition and Cancer, Cancer Epidemiology Research Program, Catalan Institute of Oncology (ICO), Barcelona, Spain; Nutrition and Cancer Group, Bellvitge Biomedical Research Institute (IDIBELL), Barcelona, Spain; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston,USA
| | - Maria-Jose Sánchez
- Escuela Andaluza de Salud Pública (EASP), Granada, Spain; Instituto de Investigación Biosanitaria ibs.GRANADA, Granada, Spain; Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain; Department of Preventive Medicine and Public Health, University of Granada, Granada, Spain
| | - Pilar Amiano
- Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain; Public Health Division of Gipuzkoa, BioDonostia Research Institute, Donostia-San Sebastian, Spain
| | - Sandra M Colorado-Yohar
- Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain; Department of Epidemiology, Murcia Regional Health Council, IMIB-Arrixaca, Murcia, Spain; Research Group on Demography and Health, National Faculty of Public Health, University of Antioquia, Medellín, Colombia
| | - Aurelio Barricarte Gurrea
- Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain; Navarra Public Health Institute, Pamplona, Spain; Navarra Institute for Health Research (IdiSNA) Pamplona, Spain
| | - Julie A Schmidt
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Domenico Palli
- Institute for Cancer Research, Prevention and Clinical Network - ISPRO, Cancer Risk Factors and Life-Style Epidemiology Unit, Florence, Italy
| | - Claudia Agnoli
- Epidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale dei Tumori di Milano, Milano, Italy
| | - Rosario Tumino
- Cancer Registry and Histopathology Department, Provincial Health Authority (ASP) Ragusa, Italy
| | - Carlotta Sacerdote
- Unit of Cancer Epidemiology, Città della Salute e della Scienza University-Hospital and Center for Cancer Prevention (CPO), Turin, Italy
| | - Amalia Mattiello
- Dipartimento di Medicina Clinica e Chirurgia, Federico II University, Naples, Italy
| | - Roel Vermeulen
- Institute for Risk Assessment Sciences, Utrecht University, Utrecht, the Netherlands
| | - Alicia K Heath
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Sofia Christakoudi
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK; MRC Centre for Transplantation, King's College London, London, UK
| | - Konstantinos K Tsilidis
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK; Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece
| | - Ruth C Travis
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Marc J Gunter
- Nutrition and Metabolism Section, International Agency for Research on Cancer, Lyon, France
| | - Hector C Keun
- Cancer Metabolism and Systems Toxicology Group, Division of Cancer, Department of Surgery and Cancer, Imperial College, London, UK
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Nayor M, Shah SH, Murthy V, Shah RV. Molecular Aspects of Lifestyle and Environmental Effects in Patients With Diabetes: JACC Focus Seminar. J Am Coll Cardiol 2021; 78:481-495. [PMID: 34325838 DOI: 10.1016/j.jacc.2021.02.070] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/04/2020] [Revised: 01/07/2021] [Accepted: 02/01/2021] [Indexed: 01/04/2023]
Abstract
Diabetes is characterized as an integrated condition of dysregulated metabolism across multiple tissues, with well-established consequences on the cardiovascular system. Recent advances in precision phenotyping in biofluids and tissues in large human observational and interventional studies have afforded a unique opportunity to translate seminal findings in models and cellular systems to patients at risk for diabetes and its complications. Specifically, techniques to assay metabolites, proteins, and transcripts, alongside more recent assessment of the gut microbiome, underscore the complexity of diabetes in patients, suggesting avenues for precision phenotyping of risk, response to intervention, and potentially novel therapies. In addition, the influence of external factors and inputs (eg, activity, diet, medical therapies) on each domain of molecular characterization has gained prominence toward better understanding their role in prevention. Here, the authors provide a broad overview of the role of several of these molecular domains in human translational investigation in diabetes.
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Affiliation(s)
- Matthew Nayor
- Division of Cardiology, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA. https://twitter.com/MattNayor
| | - Svati H Shah
- Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, North Carolina, USA; Division of Cardiology, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA. https://twitter.com/SvatiShah
| | - Venkatesh Murthy
- Division of Cardiovascular Medicine, Department of Medicine, University of Michigan, Ann Arbor, Michigan, USA; Frankel Cardiovascular Center, University of Michigan, Ann Arbor, Michigan, USA. https://twitter.com/venkmurthy
| | - Ravi V Shah
- Division of Cardiology, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA.
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127
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Haslam DE, Liang L, Wang DD, Kelly RS, Wittenbecher C, Pérez CM, Martínez M, Lee CH, Clish CB, Wong DTW, Parnell LD, Lai CQ, Ordovás JM, Manson JE, Hu FB, Stampfer MJ, Tucker KL, Joshipura KJ, Bhupathiraju SN. Associations of network-derived metabolite clusters with prevalent type 2 diabetes among adults of Puerto Rican descent. BMJ Open Diabetes Res Care 2021; 9:e002298. [PMID: 34413117 PMCID: PMC8378385 DOI: 10.1136/bmjdrc-2021-002298] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Accepted: 07/25/2021] [Indexed: 01/14/2023] Open
Abstract
INTRODUCTION We investigated whether network analysis revealed clusters of coregulated metabolites associated with prevalent type 2 diabetes (T2D) among Puerto Rican adults. RESEARCH DESIGN AND METHODS We used liquid chromatography-mass spectrometry to measure fasting plasma metabolites (>600) among participants aged 40-75 years in the Boston Puerto Rican Health Study (BPRHS; discovery) and San Juan Overweight Adult Longitudinal Study (SOALS; replication), with (n=357; n=77) and without (n=322; n=934) T2D, respectively. Among BPRHS participants, we used unsupervised partial correlation network-based methods to identify and calculate metabolite cluster scores. Logistic regression was used to assess cross-sectional associations between metabolite clusters and prevalent T2D at the baseline blood draw in the BPRHS, and significant associations were replicated in SOALS. Inverse-variance weighted random-effect meta-analysis was used to combine cohort-specific estimates. RESULTS Six metabolite clusters were significantly associated with prevalent T2D in the BPRHS and replicated in SOALS (false discovery rate (FDR) <0.05). In a meta-analysis of the two cohorts, the OR and 95% CI (per 1 SD increase in cluster score) for prevalent T2D were as follows for clusters characterized primarily by glucose transport (0.21 (0.16 to 0.30); FDR <0.0001), sphingolipids (0.40 (0.29 to 0.53); FDR <0.0001), acyl cholines (0.35 (0.22 to 0.56); FDR <0.0001), sugar metabolism (2.28 (1.68 to 3.09); FDR <0.0001), branched-chain and aromatic amino acids (2.22 (1.60 to 3.08); FDR <0.0001), and fatty acid biosynthesis (1.54 (1.29 to 1.85); FDR <0.0001). Three additional clusters characterized by amino acid metabolism, cell membrane components, and aromatic amino acid metabolism displayed significant associations with prevalent T2D in the BPRHS, but these associations were not replicated in SOALS. CONCLUSIONS Among Puerto Rican adults, we identified several known and novel metabolite clusters that associated with prevalent T2D.
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Affiliation(s)
- Danielle E Haslam
- Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
- Nutrition, Harvard T H Chan School of Public Health, Boston, Massachusetts, USA
| | - Liming Liang
- Biostatistics, Harvard T H Chan School of Public Health, Boston, Massachusetts, USA
- Epidemiology, Harvard T H Chan School of Public Health, Boston, Massachusetts, USA
| | - Dong D Wang
- Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
- Nutrition, Harvard T H Chan School of Public Health, Boston, Massachusetts, USA
| | - Rachel S Kelly
- Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | | | - Cynthia M Pérez
- Department of Biostatistics and Epidemiology, Graduate School of Public Health, University of Puerto Rico Medical Sciences Campus, San Juan, Puerto Rico
| | - Marijulie Martínez
- Center for Clinical Research and Health Promotion, University of Puerto Rico Medical Sciences Campus, San Juan, Puerto Rico
| | - Chih-Hao Lee
- Molecular Metabolism, Harvard T H Chan School of Public Health, Boston, Massachusetts, USA
| | - Clary B Clish
- Metabolomics Platform, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | - David T W Wong
- Center for Oral/Head and Neck Oncology Research, School of Dentistry, University of California Los Angeles, Los Angeles, California, USA
| | - Laurence D Parnell
- Agricultural Research Service, Jean Mayer US Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, Massachusetts, USA
| | - Chao-Qiang Lai
- Agricultural Research Service, Jean Mayer US Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, Massachusetts, USA
| | - José M Ordovás
- IMDEA-Food Institute, CEI UAM+CSIC, Madrid, Spain
- Nutrition and Genomics, Jean Mayer US Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, Massachusetts, USA
| | - JoAnn E Manson
- Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
- Epidemiology, Harvard T H Chan School of Public Health, Boston, Massachusetts, USA
- Division of Preventive Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Frank B Hu
- Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
- Nutrition, Harvard T H Chan School of Public Health, Boston, Massachusetts, USA
- Epidemiology, Harvard T H Chan School of Public Health, Boston, Massachusetts, USA
| | - Meir J Stampfer
- Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
- Nutrition, Harvard T H Chan School of Public Health, Boston, Massachusetts, USA
- Epidemiology, Harvard T H Chan School of Public Health, Boston, Massachusetts, USA
| | - Katherine L Tucker
- Department of Biomedical and Nutritional Sciences and Center for Population Health, University of Massachusetts Lowell, Lowell, Massachusetts, USA
| | - Kaumudi J Joshipura
- Epidemiology, Harvard T H Chan School of Public Health, Boston, Massachusetts, USA
- Center for Clinical Research and Health Promotion, University of Puerto Rico Medical Sciences Campus, San Juan, Puerto Rico
| | - Shilpa N Bhupathiraju
- Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
- Nutrition, Harvard T H Chan School of Public Health, Boston, Massachusetts, USA
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128
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Chen Y, Wang N, Dong X, Zhu J, Chen Y, Jiang Q, Fu C. Associations between serum amino acids and incident type 2 diabetes in Chinese rural adults. Nutr Metab Cardiovasc Dis 2021; 31:2416-2425. [PMID: 34158241 DOI: 10.1016/j.numecd.2021.05.004] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/15/2020] [Revised: 04/23/2021] [Accepted: 05/06/2021] [Indexed: 10/21/2022]
Abstract
BACKGROUND AND AIMS Some amino acids (AAs) may be associated with type 2 diabetes (T2DM). This study aimed to determine the associations of individual AAs with the development of T2DM in rural Chinese adults. METHODS AND RESULTS A cohort study of 1199 individuals aged 18 years or older was conducted from 2006 to 2008 in a rural community of Deqing, China, a repeated survey was done in 2015 and data linkage with the electronic health records system was performed each year for identifying new T2DM cases. A high-performance liquid chromatography approach was used to measure the baseline serum concentrations of 15 AAs. Cox proportional hazards models were used to examine the associations between AAs and the risk of incident T2DM. A total of 98 new T2DM cases were identified during the follow-up of 12 years on average. Among 15 AAs, proline was associated with an increased risk of incident T2DM after adjusted for age, sex, body mass index, fasting plasma glucose, family history of T2DM, smoking status, alcohol use, and history of hypertension, the adjusted hazard ratio for 1-standard deviation increment was 1.20 (95% confidence interval: 1.00, 1.43). The association tended to be more marked in subjects younger than 60 years and overweight/obese subjects. Among participants without hypertension, proline and phenylalanine were associated with an increased risk of incident T2DM, while aspartic acid was associated with a decreased risk. CONCLUSION Serum proline was associated with the risk of incident T2DM in rural Chinese adults and might be a potential predictor.
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Affiliation(s)
- Yun Chen
- School of Public Health, Key Laboratory of Public Health Safety, NHC Key Laboratory of Health Technology Assessment, Fudan University, Shanghai, 200032, China
| | - Na Wang
- School of Public Health, Key Laboratory of Public Health Safety, NHC Key Laboratory of Health Technology Assessment, Fudan University, Shanghai, 200032, China
| | - Xiaolian Dong
- Deqing County Center for Disease Control and Prevention, Deqing, 313299, China
| | - Jianfu Zhu
- Deqing County Center for Disease Control and Prevention, Deqing, 313299, China
| | - Yue Chen
- School of Epidemiology and Public Health, Faculty of Medicine, University of Ottawa, Ottawa, Ontario, K1G 5Z3, Canada
| | - Qingwu Jiang
- School of Public Health, Key Laboratory of Public Health Safety, NHC Key Laboratory of Health Technology Assessment, Fudan University, Shanghai, 200032, China
| | - Chaowei Fu
- School of Public Health, Key Laboratory of Public Health Safety, NHC Key Laboratory of Health Technology Assessment, Fudan University, Shanghai, 200032, China.
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129
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Alqudah A, Wedyan M, Qnais E, Jawarneh H, McClements L. Plasma Amino Acids Metabolomics' Important in Glucose Management in Type 2 Diabetes. Front Pharmacol 2021; 12:695418. [PMID: 34335259 PMCID: PMC8320811 DOI: 10.3389/fphar.2021.695418] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Accepted: 06/30/2021] [Indexed: 12/24/2022] Open
Abstract
The perturbation in plasma free amino acid metabolome has been observed previously in diabetes mellitus, and is associated with insulin resistance as well as the onset of cardiovascular disease in this population. In this study, we investigated, for the first time, changes in the amino acid profile in a group of people with and without type 2 diabetes (T2D) with normal BMI, from Jordan, who were only managed on metformin. Twenty one amino acids were evaluated in plasma samples from 124 people with T2D and 67 healthy controls, matched for age, gender and BMI, using amino acids analyser. Total amino acids, essential amino acids, non-essential amino acids and semi-essential amino acids were similar in T2D compared to healthy controls. Plasma concentrations of four essential amino acids were increased in the presence of T2D (Leucine, p < 0.01, Lysine, p < 0.001, Phenylalanine, p < 0.01, Tryptophan, p < 0.05). On the other hand, in relation to non-essential amino acids, Alanine and Serine were reduced in T2D (p < 0.01, p < 0.001, respectively), whereas Aspartate and Glutamate were increased in T2D compared to healthy controls (p < 0.001, p < 0.01, respectively). A semi-essential amino acid, Cystine, was also increased in T2D compared to healthy controls (p < 0.01). Citrulline, a metabolic indicator amino acid, demonstrated lower plasma concentration in T2D compared to healthy controls (p < 0.01). These amino acids were also correlated with fasting blood glucose and HbA1c (p < 0.05). Glutamate, glycine and arginine were correlated with the duration of metformin treatment (p < 0.05). No amino acid was correlated with lipid profiles. Disturbances in the metabolism of these amino acids are closely implicated in the pathogenesis of T2D and associated cardiovascular disease. Therefore, these perturbed amino acids could be explored as therapeutic targets to improve T2D management and prevent associated cardiovascular complications.
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Affiliation(s)
- Abdelrahim Alqudah
- Department of Clinical Pharmacy and Pharmacy Practice, Faculty of Pharmaceutical Sciences, The Hashemite University, Zarqa, Jordan
| | - Mohammed Wedyan
- Department of Biology and Biotechnology, Faculty of Science, The Hashemite University, Zarqa, Jordan
| | - Esam Qnais
- Department of Biology and Biotechnology, Faculty of Science, The Hashemite University, Zarqa, Jordan
| | - Hassan Jawarneh
- Department of Biology and Biotechnology, Faculty of Science, The Hashemite University, Zarqa, Jordan
| | - Lana McClements
- School of Life Sciences, Faculty of Science, University of Technology Sydney, Sydney, NSW, Australia
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130
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Gillies NA, Franzke B, Wessner B, Schober-Halper B, Hofmann M, Oesen S, Tosevska A, Strasser EM, Roy NC, Milan AM, Cameron-Smith D, Wagner KH. Nutritional supplementation alters associations between one-carbon metabolites and cardiometabolic risk profiles in older adults: a secondary analysis of the Vienna Active Ageing Study. Eur J Nutr 2021; 61:169-182. [PMID: 34240265 PMCID: PMC8783863 DOI: 10.1007/s00394-021-02607-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2021] [Accepted: 06/02/2021] [Indexed: 11/12/2022]
Abstract
Purpose Cardiovascular diseases and cognitive decline, predominant in ageing populations, share common features of dysregulated one-carbon (1C) and cardiometabolic homeostasis. However, few studies have addressed the impact of multifaceted lifestyle interventions in older adults that combine both nutritional supplementation and resistance training on the co-regulation of 1C metabolites and cardiometabolic markers. Methods 95 institutionalised older adults (83 ± 6 years, 88.4% female) were randomised to receive resistance training with or without nutritional supplementation (Fortifit), or cognitive training (control for socialisation) for 6 months. Fasting plasma 1C metabolite concentrations, analysed by liquid chromatography coupled with mass spectrometry, and cardiometabolic parameters were measured at baseline and the 3- and 6-month follow-ups. Results Regardless of the intervention group, choline was elevated after 3 months, while cysteine and methionine remained elevated after 6 months (mixed model time effects, p < 0.05). Elevated dimethylglycine and lower betaine concentrations were correlated with an unfavourable cardiometabolic profile at baseline (spearman correlations, p < 0.05). However, increasing choline and dimethylglycine concentrations were associated with improvements in lipid metabolism in those receiving supplementation (regression model interaction, p < 0.05). Conclusion Choline metabolites, including choline, betaine and dimethylglycine, were central to the co-regulation of 1C metabolism and cardiometabolic health in older adults. Metabolites that indicate upregulated betaine-dependent homocysteine remethylation were elevated in those with the greatest cardiometabolic risk at baseline, but associated with improvements in lipid parameters following resistance training with nutritional supplementation. The relevance of how 1C metabolite status might be optimised to protect against cardiometabolic dysregulation requires further attention. Supplementary Information The online version contains supplementary material available at 10.1007/s00394-021-02607-y.
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Affiliation(s)
- Nicola A Gillies
- Liggins Institute, University of Auckland, Auckland, New Zealand.,Riddet Institute, Palmerston North, New Zealand
| | - Bernhard Franzke
- Research Platform Active Ageing, University of Vienna, Althanstrasse 14, 1090, Vienna, Austria
| | - Barbara Wessner
- Research Platform Active Ageing, University of Vienna, Althanstrasse 14, 1090, Vienna, Austria.,Department of Sports Medicine, Exercise Physiology and Prevention, University of Vienna, Vienna, Austria
| | - Barbara Schober-Halper
- Research Platform Active Ageing, University of Vienna, Althanstrasse 14, 1090, Vienna, Austria
| | - Marlene Hofmann
- Research Platform Active Ageing, University of Vienna, Althanstrasse 14, 1090, Vienna, Austria
| | - Stefan Oesen
- Research Platform Active Ageing, University of Vienna, Althanstrasse 14, 1090, Vienna, Austria
| | - Anela Tosevska
- Research Platform Active Ageing, University of Vienna, Althanstrasse 14, 1090, Vienna, Austria.,Internal Medicine III, Division of Rheumatology, Medical University of Vienna, Vienna, Austria
| | - Eva-Maria Strasser
- Institute for Physical Medicine and Rehabilitation, Kaiser Franz Josef Hospital - Social Medical Center South, Vienna, Austria
| | - Nicole C Roy
- Liggins Institute, University of Auckland, Auckland, New Zealand.,Riddet Institute, Palmerston North, New Zealand.,Food, Nutrition and Health, AgResearch, Hamilton, New Zealand.,The High-Value Nutrition National Science Challenge, Auckland, New Zealand.,Department of Human Nutrition, University of Otago, Dunedin, New Zealand
| | - Amber M Milan
- Liggins Institute, University of Auckland, Auckland, New Zealand.,Food, Nutrition and Health, AgResearch, Hamilton, New Zealand.,The High-Value Nutrition National Science Challenge, Auckland, New Zealand
| | - David Cameron-Smith
- Liggins Institute, University of Auckland, Auckland, New Zealand.,Riddet Institute, Palmerston North, New Zealand.,Singapore Institute for Clinical Sciences, Agency for Science, Technology, and Research, Singapore, Singapore
| | - Karl-Heinz Wagner
- Research Platform Active Ageing, University of Vienna, Althanstrasse 14, 1090, Vienna, Austria. .,Department of Nutritional Sciences, University of Vienna, Vienna, Austria.
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131
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Lépine G, Fouillet H, Rémond D, Huneau JF, Mariotti F, Polakof S. A Scoping Review: Metabolomics Signatures Associated with Animal and Plant Protein Intake and Their Potential Relation with Cardiometabolic Risk. Adv Nutr 2021; 12:2112-2131. [PMID: 34229350 PMCID: PMC8634484 DOI: 10.1093/advances/nmab073] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2021] [Revised: 04/22/2021] [Accepted: 05/12/2021] [Indexed: 12/11/2022] Open
Abstract
The dietary shift from animal protein (AP) to plant protein (PP) sources is encouraged for both environmental and health reasons. For instance, PPs are associated with lower cardiovascular and diabetes risks compared with APs, although the underlying mechanisms mostly remain unknown. Metabolomics is a valuable tool for globally and mechanistically characterizing the impact of AP and PP intake, given its unique ability to provide integrated signatures and specific biomarkers of metabolic effects through a comprehensive snapshot of metabolic status. This scoping review is aimed at gathering and analyzing the available metabolomics data associated with PP- and AP-rich diets, and discusses the metabolic effects underlying these metabolomics signatures and their potential implication for cardiometabolic health. We selected 24 human studies comparing the urine, plasma, or serum metabolomes associated with diets with contrasted AP and PP intakes. Among the 439 metabolites reported in those studies as able to discriminate AP- and PP-rich diets, 46 were considered to provide a robust level of evidence, according to a scoring system, especially amino acids (AAs) and AA-related products. Branched-chain amino acids, aromatic amino acids (AAAs), glutamate, short-chain acylcarnitines, and trimethylamine-N-oxide, which are known to be related to an increased cardiometabolic risk, were associated with AP-rich diets, whereas glycine (rather related to a reduced risk) was associated with PP-rich diets. Tricarboxylic acid (TCA) cycle intermediates and products from gut microbiota AAA degradation were also often reported, but the direction of their associations differed across studies. Overall, AP- and PP-rich diets result in different metabolomics signatures, with several metabolites being plausible candidates to explain some of their differential associations with cardiometabolic risk. Additional studies specifically focusing on protein type, with rigorous intake control, are needed to better characterize the associated metabolic phenotypes and understand how they could mediate differential AP and PP effects on cardiometabolic risk.
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Affiliation(s)
- Gaïa Lépine
- Université Clermont Auvergne, INRAE, UMR 1019, Unité Nutrition Humaine, Clermont-Ferrand, France,Université Paris-Saclay, AgroParisTech, INRAE, UMR PNCA, Paris, France
| | - Hélène Fouillet
- Université Paris-Saclay, AgroParisTech, INRAE, UMR PNCA, Paris, France
| | - Didier Rémond
- Université Clermont Auvergne, INRAE, UMR 1019, Unité Nutrition Humaine, Clermont-Ferrand, France
| | | | - François Mariotti
- Université Paris-Saclay, AgroParisTech, INRAE, UMR PNCA, Paris, France
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132
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Sriboonvorakul N, Pan-Ngum W, Poovorawan K, Winterberg M, Tarning J, Muangnoicharoen S. Assessment of the amino acid profile in Thai patients with type 2 diabetes mellitus using liquid chromatography-mass spectrometry. Int Health 2021; 13:367-373. [PMID: 33118019 PMCID: PMC8253986 DOI: 10.1093/inthealth/ihaa083] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2020] [Revised: 09/08/2020] [Accepted: 09/30/2020] [Indexed: 12/03/2022] Open
Abstract
Background Type 2 diabetes mellitus (T2DM) is a global health problem. Early identification of those at risk is necessary to prevent its onset through lifestyle and pharmacologic interventions. T2DM is characterized by metabolic abnormalities, including protein metabolism. Evaluation of the amino acid profile might be beneficial for early assessment. Methods Liquid chromatography-mass spectrometry was performed to separate and quantify plasma amino acids from two groups of Thai individuals, patients with T2DM (n=103) and healthy individuals (n=104). Multivariate analysis was applied to compare free amino acid levels between groups. Subgroup analyses of patients with T2DM were performed to assess the association between amino acid profiles and important T2DM clinical characteristics. Results The multivariate analysis showed that glutamic acid was significantly associated with T2DM (OR 1.113, 95% CI 1.006 to 1.231) and results from the subgroup analyses showed that this correlation was significant in all subgroups of patients (p<0.05). Conclusions This finding needs to be confirmed in larger groups of patients with T2DM to explore glutamic acid as a biomarker for early prevention in particular at-risk groups. An in-depth understanding of the involvement of glutamic acid in T2DM could enhance our understanding of the disease and potentially provide novel interventions.
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Affiliation(s)
- Natthida Sriboonvorakul
- Department of Clinical Tropical Medicine, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand
| | - Wirichada Pan-Ngum
- Department of Tropical Hygiene, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand
| | - Kittiyod Poovorawan
- Department of Clinical Tropical Medicine, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand
| | - Markus Winterberg
- Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand.,Centre for Tropical Medicine, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, United Kingdom
| | - Joel Tarning
- Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand.,Centre for Tropical Medicine, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, United Kingdom
| | - Sant Muangnoicharoen
- Department of Clinical Tropical Medicine, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand
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133
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Huang T, Balasubramanian R, Yao Y, Clis CB, Shadyab AH, Liu B, Tworoger SS, Rexrode KM, Manson JE, Kubzansky LD, Hankinson SE. Associations of depression status with plasma levels of candidate lipid and amino acid metabolites: a meta-analysis of individual data from three independent samples of US postmenopausal women. Mol Psychiatry 2021; 26:3315-3327. [PMID: 32859999 PMCID: PMC7914294 DOI: 10.1038/s41380-020-00870-9] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/04/2019] [Revised: 08/04/2020] [Accepted: 08/14/2020] [Indexed: 01/05/2023]
Abstract
Recent animal and small clinical studies have suggested depression is related to altered lipid and amino acid profiles. However, this has not been examined in a population-based sample, particularly in women. We identified multiple metabolites associated with depression as potential candidates from prior studies. Cross-sectional data from three independent samples of postmenopausal women were analyzed, including women from the Women's Health Initiative-Observational Study (WHI-OS, n = 926), the WHI-Hormone Trials (WHI-HT; n = 1,325), and the Nurses' Health Study II Mind-Body Study (NHSII-MBS; n = 218). Positive depression status was defined as having any of the following: elevated depressive symptoms, antidepressant use, or depression history. Plasma metabolites were measured using liquid chromatography-tandem mass spectrometry (21 phosphatidylcholines (PCs), 7 lysophosphatidylethanolamines, 5 ceramides, 3 branched chain amino acids, and 9 neurotransmitters). Associations between depression status and metabolites were evaluated using multivariable linear regression; results were pooled by random-effects meta-analysis with multiple testing adjustment using the false discovery rate (FDR). Prevalence rates of positive depression status were 24.4% (WHI-OS), 25.7% (WHI-HT), and 44.7% (NHSII-MBS). After multivariable adjustment, positive depression status was associated with higher levels of glutamate and PC 36 : 1/38 : 3, and lower levels of tryptophan and GABA-to-glutamate and GABA-to-glutamine ratio (FDR-p < 0.05). Positive associations with LPE 18 : 0/18 : 1 and inverse associations with valine and serotonin were also observed, although these associations did not survive FDR adjustment. Associations of positive depression status with several candidate metabolites including PC 36 : 1/38 : 3 and amino acids involved in neurotransmission suggest potential depression-related metabolic alterations in postmenopausal women, with possible implications for later chronic disease.
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Affiliation(s)
- Tianyi Huang
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, and Harvard Medical School, Boston, MA, USA.
| | - Raji Balasubramanian
- Department of Biostatistics and Epidemiology, University of Massachusetts Amherst, Amherst, MA
| | - Yubing Yao
- Department of Biostatistics and Epidemiology, University of Massachusetts Amherst, Amherst, MA
| | | | - Aladdin H. Shadyab
- Department of Family Medicine and Public Health, University of California San Diego School of Medicine, La Jolla, CA
| | - Buyun Liu
- Department of Epidemiology, College of Public Health, University of Iowa, Iowa City, IA
| | - Shelley S. Tworoger
- Department of Cancer Epidemiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL,Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA
| | - Kathryn M. Rexrode
- Division of Women’s Health, Department of Medicine, Brigham and Women’s Hospital, Boston, MA,Division of Preventive Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - JoAnn E. Manson
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA,Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA,Division of Preventive Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Laura D. Kubzansky
- Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, MA
| | - Susan E. Hankinson
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA,Department of Biostatistics and Epidemiology, University of Massachusetts Amherst, Amherst, MA
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Comte B, Monnerie S, Brandolini-Bunlon M, Canlet C, Castelli F, Chu-Van E, Colsch B, Fenaille F, Joly C, Jourdan F, Lenuzza N, Lyan B, Martin JF, Migné C, Morais JA, Pétéra M, Poupin N, Vinson F, Thevenot E, Junot C, Gaudreau P, Pujos-Guillot E. Multiplatform metabolomics for an integrative exploration of metabolic syndrome in older men. EBioMedicine 2021; 69:103440. [PMID: 34161887 PMCID: PMC8237302 DOI: 10.1016/j.ebiom.2021.103440] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2021] [Revised: 05/20/2021] [Accepted: 06/01/2021] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND Metabolic syndrome (MetS), a cluster of factors associated with risks of developing cardiovascular diseases, is a public health concern because of its growing prevalence. Considering the combination of concomitant components, their development and severity, MetS phenotypes are largely heterogeneous, inducing disparity in diagnosis. METHODS A case/control study was designed within the NuAge longitudinal cohort on aging. From a 3-year follow-up of 123 stable individuals, we present a deep phenotyping approach based on a multiplatform metabolomics and lipidomics untargeted strategy to better characterize metabolic perturbations in MetS and define a comprehensive MetS signature stable over time in older men. FINDINGS We characterize significant changes associated with MetS, involving modulations of 476 metabolites and lipids, and representing 16% of the detected serum metabolome/lipidome. These results revealed a systemic alteration of metabolism, involving various metabolic pathways (urea cycle, amino-acid, sphingo- and glycerophospholipid, and sugar metabolisms…) not only intrinsically interrelated, but also reflecting environmental factors (nutrition, microbiota, physical activity…). INTERPRETATION These findings allowed identifying a comprehensive MetS signature, reduced to 26 metabolites for future translation into clinical applications for better diagnosing MetS. FUNDING The NuAge Study was supported by a research grant from the Canadian Institutes of Health Research (CIHR; MOP-62842). The actual NuAge Database and Biobank, containing data and biologic samples of 1,753 NuAge participants (from the initial 1,793 participants), are supported by the Fonds de recherche du Québec (FRQ; 2020-VICO-279753), the Quebec Network for Research on Aging, a thematic network funded by the Fonds de Recherche du Québec - Santé (FRQS) and by the Merck-Frost Chair funded by La Fondation de l'Université de Sherbrooke. All metabolomics and lipidomics analyses were funded and performed within the metaboHUB French infrastructure (ANR-INBS-0010). All authors had full access to the full data in the study and accept responsibility to submit for publication.
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Affiliation(s)
- Blandine Comte
- Université Clermont Auvergne, INRAE, UNH, Plateforme d'Exploration du Métabolisme, MetaboHUB Clermont, Clermont-Ferrand, France
| | - Stéphanie Monnerie
- Université Clermont Auvergne, INRAE, UNH, Plateforme d'Exploration du Métabolisme, MetaboHUB Clermont, Clermont-Ferrand, France
| | - Marion Brandolini-Bunlon
- Université Clermont Auvergne, INRAE, UNH, Plateforme d'Exploration du Métabolisme, MetaboHUB Clermont, Clermont-Ferrand, France
| | - Cécile Canlet
- Toxalim (Research Center in Food Toxicology), Université de Toulouse, INRAE, ENVT, INP-Purpan, UPS, MetaboHUB, Toulouse 31300, France
| | - Florence Castelli
- Université Paris-Saclay, CEA, INRAE, Département Médicaments et Technologies pour la Santé (DMTS), MetaboHUB, F-91191 Gif sur Yvette, France
| | - Emeline Chu-Van
- Université Paris-Saclay, CEA, INRAE, Département Médicaments et Technologies pour la Santé (DMTS), MetaboHUB, F-91191 Gif sur Yvette, France
| | - Benoit Colsch
- Université Paris-Saclay, CEA, INRAE, Département Médicaments et Technologies pour la Santé (DMTS), MetaboHUB, F-91191 Gif sur Yvette, France
| | - François Fenaille
- Université Paris-Saclay, CEA, INRAE, Département Médicaments et Technologies pour la Santé (DMTS), MetaboHUB, F-91191 Gif sur Yvette, France
| | - Charlotte Joly
- Université Clermont Auvergne, INRAE, UNH, Plateforme d'Exploration du Métabolisme, MetaboHUB Clermont, Clermont-Ferrand, France
| | - Fabien Jourdan
- Toxalim (Research Center in Food Toxicology), Université de Toulouse, INRAE, ENVT, INP-Purpan, UPS, MetaboHUB, Toulouse 31300, France
| | - Natacha Lenuzza
- Université Paris-Saclay, CEA, INRAE, Département Médicaments et Technologies pour la Santé (DMTS), MetaboHUB, F-91191 Gif sur Yvette, France
| | - Bernard Lyan
- Université Clermont Auvergne, INRAE, UNH, Plateforme d'Exploration du Métabolisme, MetaboHUB Clermont, Clermont-Ferrand, France
| | - Jean-François Martin
- Toxalim (Research Center in Food Toxicology), Université de Toulouse, INRAE, ENVT, INP-Purpan, UPS, MetaboHUB, Toulouse 31300, France
| | - Carole Migné
- Université Clermont Auvergne, INRAE, UNH, Plateforme d'Exploration du Métabolisme, MetaboHUB Clermont, Clermont-Ferrand, France
| | - José A Morais
- Division de Gériatrie, McGill University, Center de recherche du Center universitaire de santé McGill, Montreal, Canada
| | - Mélanie Pétéra
- Université Clermont Auvergne, INRAE, UNH, Plateforme d'Exploration du Métabolisme, MetaboHUB Clermont, Clermont-Ferrand, France
| | - Nathalie Poupin
- Toxalim (Research Center in Food Toxicology), Université de Toulouse, INRAE, ENVT, INP-Purpan, UPS, MetaboHUB, Toulouse 31300, France
| | - Florence Vinson
- Toxalim (Research Center in Food Toxicology), Université de Toulouse, INRAE, ENVT, INP-Purpan, UPS, MetaboHUB, Toulouse 31300, France
| | - Etienne Thevenot
- Université Paris-Saclay, CEA, INRAE, Département Médicaments et Technologies pour la Santé (DMTS), MetaboHUB, F-91191 Gif sur Yvette, France
| | - Christophe Junot
- Université Paris-Saclay, CEA, INRAE, Département Médicaments et Technologies pour la Santé (DMTS), MetaboHUB, F-91191 Gif sur Yvette, France
| | - Pierrette Gaudreau
- Center de Recherche du Center hospitalier de l'Université de Montréal, Montreal, Canada; Département de médecine, Université de Montréal, Montreal, Canada
| | - Estelle Pujos-Guillot
- Université Clermont Auvergne, INRAE, UNH, Plateforme d'Exploration du Métabolisme, MetaboHUB Clermont, Clermont-Ferrand, France.
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Hübel C, Herle M, Santos Ferreira DL, Abdulkadir M, Bryant-Waugh R, Loos RJF, Bulik CM, Lawlor DA, Micali N. Childhood overeating is associated with adverse cardiometabolic and inflammatory profiles in adolescence. Sci Rep 2021; 11:12478. [PMID: 34127697 PMCID: PMC8203659 DOI: 10.1038/s41598-021-90644-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2020] [Accepted: 05/07/2021] [Indexed: 12/15/2022] Open
Abstract
Childhood eating behaviour contributes to the rise of obesity and related noncommunicable disease worldwide. However, we lack a deep understanding of biochemical alterations that can arise from aberrant eating behaviour. In this study, we prospectively associate longitudinal trajectories of childhood overeating, undereating, and fussy eating with metabolic markers at age 16 years to explore adolescent metabolic alterations related to specific eating patterns in the first 10 years of life. Data are from the Avon Longitudinal Study of Parents and Children (n = 3104). We measure 158 metabolic markers with a high-throughput (1H) NMR metabolomics platform. Increasing childhood overeating is prospectively associated with an adverse cardiometabolic profile (i.e., hyperlipidemia, hypercholesterolemia, hyperlipoproteinemia) in adolescence; whereas undereating and fussy eating are associated with lower concentrations of the amino acids glutamine and valine, suggesting a potential lack of micronutrients. Here, we show associations between early behavioural indicators of eating and metabolic markers.
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Affiliation(s)
- Christopher Hübel
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- UK National Institute for Health Research (NIHR) Biomedical Research Centre for Mental Health, South London and Maudsley Hospital, London, UK
- National Centre for Register-Based Research, Department of Economics and Business Economics, Aarhus University, Aarhus, Denmark
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Moritz Herle
- Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Diana L Santos Ferreira
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Mohamed Abdulkadir
- Department of Pediatrics Gynaecology and Obstetrics, Faculty of Medicine, University of Geneva, Geneva, Switzerland
- Department of Psychiatry, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Rachel Bryant-Waugh
- Maudsley Centre for Child and Adolescent Eating Disorders, Michael Rutter Centre for Children and Young People, Maudsley Hospital, London, UK
| | - Ruth J F Loos
- Icahn School of Medicine At Mount Sinai, New York, NY, USA
| | - Cynthia M Bulik
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Department of Psychiatry, University of North Carolina At Chapel Hill, Chapel Hill, NC, USA
- Department of Nutrition, University of North Carolina At Chapel Hill, Chapel Hill, NC, USA
| | - Deborah A Lawlor
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Bristol National Institute of Health Research Biomedical Research Centre, Bristol, UK
| | - Nadia Micali
- Department of Pediatrics Gynaecology and Obstetrics, Faculty of Medicine, University of Geneva, Geneva, Switzerland.
- Department of Psychiatry, Faculty of Medicine, University of Geneva, Geneva, Switzerland.
- Great Ormond Street Institute of Child Health, University College London, London, UK.
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Bardanzellu F, Puddu M, Peroni DG, Fanos V. The clinical impact of maternal weight on offspring health: lights and shadows in breast milk metabolome. Expert Rev Proteomics 2021; 18:571-606. [PMID: 34107825 DOI: 10.1080/14789450.2021.1940143] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Abstract
INTRODUCTION Pre-pregnancy overweight and obesity, depending on maternal nutrition and metabolic state, can influence fetal, neonatal and long-term offspring health, regarding cardio-metabolic, respiratory, immunological and cognitive outcomes. Thus, maternal weight can act, through mechanisms that are not full understood, on the physiology and metabolism of some fetal organs and tissues, to adapt themselves to the intrauterine environment and nutritional reserves. These effects could occur by modulating gene expression, neonatal microbiome, and through breastfeeding. AREAS COVERED In this paper, we investigated the potential effects of metabolites found altered in breast milk (BM) of overweight/obese mothers, through an extensive review of metabolomics studies, and the potential short- and long-term clinical effects in the offspring, especially regarding overweight, glucose homeostasis, insulin resistance, oxidative stress, infections, immune processes, and neurodevelopment. EXPERT OPINION Metabolomics seems the ideal tool to investigate BM variation depending on maternal or fetal/neonatal factors. In particular, BM metabolome alterations according to maternal conditions were recently pointed out in cases of gestational diabetes, preeclampsia, intrauterine growth restriction and maternal overweight/obesity. In our opinion, even if BM is the food of choice in neonatal nutrition, the deepest comprehension of its composition in overweight/obese mothers could allow targeted supplementation, to improve offspring health and metabolic homeostasis.
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Affiliation(s)
- Flaminia Bardanzellu
- Neonatal Intensive Care Unit, Department of Surgical Sciences, AOU and University of Cagliari. SS 554 km 4,500, 09042 Monserrato. Italy
| | - Melania Puddu
- Neonatal Intensive Care Unit, Department of Surgical Sciences, AOU and University of Cagliari. SS 554 km 4,500, 09042 Monserrato. Italy
| | - Diego Giampietro Peroni
- Clinical and Experimental Medicine Department, section of Pediatrics, University of Pisa, Italy. Via Roma, 55, 56126 Pisa PI, Italy
| | - Vassilios Fanos
- Neonatal Intensive Care Unit, Department of Surgical Sciences, AOU and University of Cagliari. SS 554 km 4,500, 09042 Monserrato. Italy
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Zheng J, Xiao H, Duan Y, Song B, Zheng C, Guo Q, Li F, Li T. Roles of amino acid derivatives in the regulation of obesity. Food Funct 2021; 12:6214-6225. [PMID: 34105579 DOI: 10.1039/d1fo00780g] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Obesity is an issue of great concern to people all over the world. It is accompanied by serious complications, leading to reduced quality of life and higher morbidity and mortality. Over the past few years, there has been an explosion in knowledge about the roles of potential therapeutic agents in obesity management. Among them, amino acid (AA) derivatives, such as taurine, glutathione (GSH), betaine, α-ketoglutarate (AKG), β-aminoisobutyric acid (BAIBA), and β-hydroxy-β-methylbutyrate (HMB), have recently gained popularity due to their beneficial effects on the promotion of weight loss and improvement in the lipid profile. The mechanisms of action of these derivatives mainly include inhibiting adipogenesis, increasing lipolysis, promoting brown/beige adipose tissue (BAT) development, and improving glucose metabolism. Therefore, this review summarizes these AA derivatives and the possible mechanisms responsible for their anti-obesity effects. Based on the current findings, these AA derivatives could be potential therapeutic agents for obesity and its related metabolic diseases.
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Affiliation(s)
- Jie Zheng
- CAS Key Laboratory of Agro-ecological Processes in Subtropical Region, Hunan Provincial Key Laboratory of Animal Nutritional Physiology and Metabolic Process, National Engineering Laboratory for Pollution Control and Waste Utilization in Livestock and Poultry Production, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha 410125, China.
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Matteo G, Hoyeck MP, Blair HL, Zebarth J, Rick KRC, Williams A, Gagné R, Buick JK, Yauk CL, Bruin JE. Prolonged Low-Dose Dioxin Exposure Impairs Metabolic Adaptability to High-Fat Diet Feeding in Female but Not Male Mice. Endocrinology 2021; 162:bqab050. [PMID: 33693622 PMCID: PMC8101695 DOI: 10.1210/endocr/bqab050] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/05/2020] [Indexed: 12/17/2022]
Abstract
CONTEXT Human studies consistently show an association between exposure to persistent organic pollutants, including 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD, aka "dioxin"), and increased diabetes risk. We previously showed that a single high-dose TCDD exposure (20 µg/kg) decreased plasma insulin levels in male and female mice in vivo, but effects on glucose homeostasis were sex-dependent. OBJECTIVE The current study assessed whether prolonged exposure to a physiologically relevant low-dose of TCDD impacts glucose homeostasis and/or the islet phenotype in a sex-dependent manner in chow-fed or high-fat diet (HFD)-fed mice. METHODS Male and female mice were exposed to 20 ng/kg/d TCDD 2×/week for 12 weeks and simultaneously fed standard chow or a 45% HFD. Glucose homeostasis was assessed by glucose and insulin tolerance tests, and glucose-induced plasma insulin levels were measured in vivo. Histological analysis was performed on pancreas from male and female mice, and islets were isolated from females for TempO-Seq transcriptomic analysis. RESULTS Low-dose TCDD exposure did not lead to adverse metabolic consequences in chow-fed male or female mice, or in HFD-fed males. However, TCDD accelerated the onset of HFD-induced hyperglycemia and impaired glucose-induced plasma insulin levels in females. TCDD caused a modest increase in islet area in males but reduced the percent beta cell area within islets in females. TempO-Seq analysis suggested abnormal changes to endocrine and metabolic pathways in female TCDDHFD islets. CONCLUSION Our data suggest that prolonged low-dose TCDD exposure has minimal effects on glucose homeostasis and islet morphology in chow-fed male and female mice but promotes maladaptive metabolic responses in HFD-fed females.
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Affiliation(s)
- Geronimo Matteo
- Department of Biology & Institute of Biochemistry, Carleton University, Ottawa, Ontario, K1S 5B6, Canada
| | - Myriam P Hoyeck
- Department of Biology & Institute of Biochemistry, Carleton University, Ottawa, Ontario, K1S 5B6, Canada
| | - Hannah L Blair
- Department of Biology & Institute of Biochemistry, Carleton University, Ottawa, Ontario, K1S 5B6, Canada
| | - Julia Zebarth
- Department of Biology & Institute of Biochemistry, Carleton University, Ottawa, Ontario, K1S 5B6, Canada
| | - Kayleigh R C Rick
- Department of Biology & Institute of Biochemistry, Carleton University, Ottawa, Ontario, K1S 5B6, Canada
| | - Andrew Williams
- Environmental Health Science and Research Bureau, Health Canada, Ottawa, Ontario K1A 0K9, Canada
| | - Rémi Gagné
- Environmental Health Science and Research Bureau, Health Canada, Ottawa, Ontario K1A 0K9, Canada
| | - Julie K Buick
- Environmental Health Science and Research Bureau, Health Canada, Ottawa, Ontario K1A 0K9, Canada
| | - Carole L Yauk
- Environmental Health Science and Research Bureau, Health Canada, Ottawa, Ontario K1A 0K9, Canada
- Department of Biology, University of Ottawa, Ontario, KIN 6N5, Canada
| | - Jennifer E Bruin
- Department of Biology & Institute of Biochemistry, Carleton University, Ottawa, Ontario, K1S 5B6, Canada
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Jie Z, Liang S, Ding Q, Li F, Tang S, Wang D, Lin Y, Chen P, Cai K, Qiu X, Li Q, Liao Y, Zhou D, Lian H, Zuo Y, Chen X, Rao W, Ren Y, Wang Y, Zi J, Wang R, Zhou H, Lu H, Wang X, Zhang W, Zhang T, Xiao L, Zong Y, Liu W, Yang H, Wang J, Hou Y, Liu X, Kristiansen K, Zhong H, Jia H, Xu X. A transomic cohort as a reference point for promoting a healthy human gut microbiome. MEDICINE IN MICROECOLOGY 2021. [DOI: 10.1016/j.medmic.2021.100039] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
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Morais T, Seabra AL, Patrício BG, Guimarães M, Nora M, Oliveira PF, Alves MG, Monteiro MP. Visceral Adipose Tissue Displays Unique Metabolomic Fingerprints in Obesity, Pre-Diabetes and Type 2 Diabetes. Int J Mol Sci 2021; 22:5695. [PMID: 34071774 PMCID: PMC8199212 DOI: 10.3390/ijms22115695] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2021] [Revised: 05/24/2021] [Accepted: 05/24/2021] [Indexed: 11/16/2022] Open
Abstract
Visceral adipose tissue (VAT) metabolic profiling harbors the potential to disentangle molecular changes underlying obesity-related dysglycemia. In this study, the VAT exometabolome of subjects with obesity and different glycemic statuses are analyzed. The subjects (n = 19) are divided into groups according to body mass index and glycemic status: subjects with obesity and euglycemia (Ob+NGT, n = 5), subjects with obesity and pre-diabetes (Ob+Pre-T2D, n = 5), subjects with obesity and type 2 diabetes under metformin treatment (Ob+T2D, n = 5) and subjects without obesity and with euglycemia (Non-Ob, n = 4), used as controls. VATs are incubated in culture media and extracellular metabolite content is determined by proton nuclear magnetic resonance (1H-NMR). Glucose consumption is not different between the groups. Pyruvate and pyroglutamate consumption are significantly lower in all groups of subjects with obesity compared to Non-Ob, and significantly lower in Ob+Pre-T2D as compared to Ob+NGT. In contrast, isoleucine consumption is significantly higher in all groups of subjects with obesity, particularly in Ob+Pre-T2D, compared to Non-Ob. Acetate production is also significantly lower in Ob+Pre-T2D compared to Non-Ob. In sum, the VAT metabolic fingerprint is associated with pre-diabetes and characterized by higher isoleucine consumption, accompanied by lower acetate production and pyruvate and pyroglutamate consumption. We propose that glucose metabolism follows different fates within the VAT, depending on the individuals' health status.
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Affiliation(s)
- Tiago Morais
- Endocrine and Metabolic Research, Unit for Multidisciplinary Research in Biomedicine (UMIB), University of Porto, 4050-313 Porto, Portugal; (T.M.); (A.L.S.); (B.G.P.); (M.G.); (M.N.); (M.G.A.)
- Laboratory for Integrative and Translational Research in Population Health (ITR), University of Porto, 4050-313 Porto, Portugal
- Department of Anatomy, Institute of Biomedical Sciences Abel Salazar (ICBAS), University of Porto, 4050-313 Porto, Portugal
| | - Alexandre L. Seabra
- Endocrine and Metabolic Research, Unit for Multidisciplinary Research in Biomedicine (UMIB), University of Porto, 4050-313 Porto, Portugal; (T.M.); (A.L.S.); (B.G.P.); (M.G.); (M.N.); (M.G.A.)
- Laboratory for Integrative and Translational Research in Population Health (ITR), University of Porto, 4050-313 Porto, Portugal
- Department of Anatomy, Institute of Biomedical Sciences Abel Salazar (ICBAS), University of Porto, 4050-313 Porto, Portugal
| | - Bárbara G. Patrício
- Endocrine and Metabolic Research, Unit for Multidisciplinary Research in Biomedicine (UMIB), University of Porto, 4050-313 Porto, Portugal; (T.M.); (A.L.S.); (B.G.P.); (M.G.); (M.N.); (M.G.A.)
- Laboratory for Integrative and Translational Research in Population Health (ITR), University of Porto, 4050-313 Porto, Portugal
- Department of Anatomy, Institute of Biomedical Sciences Abel Salazar (ICBAS), University of Porto, 4050-313 Porto, Portugal
| | - Marta Guimarães
- Endocrine and Metabolic Research, Unit for Multidisciplinary Research in Biomedicine (UMIB), University of Porto, 4050-313 Porto, Portugal; (T.M.); (A.L.S.); (B.G.P.); (M.G.); (M.N.); (M.G.A.)
- Laboratory for Integrative and Translational Research in Population Health (ITR), University of Porto, 4050-313 Porto, Portugal
- Department of Anatomy, Institute of Biomedical Sciences Abel Salazar (ICBAS), University of Porto, 4050-313 Porto, Portugal
- Department of General Surgery, Centro Hospitalar de Entre o Douro e Vouga, 4520-220 Santa Maria da Feira, Portugal
| | - Mário Nora
- Endocrine and Metabolic Research, Unit for Multidisciplinary Research in Biomedicine (UMIB), University of Porto, 4050-313 Porto, Portugal; (T.M.); (A.L.S.); (B.G.P.); (M.G.); (M.N.); (M.G.A.)
- Laboratory for Integrative and Translational Research in Population Health (ITR), University of Porto, 4050-313 Porto, Portugal
- Department of General Surgery, Centro Hospitalar de Entre o Douro e Vouga, 4520-220 Santa Maria da Feira, Portugal
| | - Pedro F. Oliveira
- QOPNA & LAQV, Department of Chemistry, University of Aveiro, 3810-193 Aveiro, Portugal;
| | - Marco G. Alves
- Endocrine and Metabolic Research, Unit for Multidisciplinary Research in Biomedicine (UMIB), University of Porto, 4050-313 Porto, Portugal; (T.M.); (A.L.S.); (B.G.P.); (M.G.); (M.N.); (M.G.A.)
- Laboratory for Integrative and Translational Research in Population Health (ITR), University of Porto, 4050-313 Porto, Portugal
- Department of Anatomy, Institute of Biomedical Sciences Abel Salazar (ICBAS), University of Porto, 4050-313 Porto, Portugal
| | - Mariana P. Monteiro
- Endocrine and Metabolic Research, Unit for Multidisciplinary Research in Biomedicine (UMIB), University of Porto, 4050-313 Porto, Portugal; (T.M.); (A.L.S.); (B.G.P.); (M.G.); (M.N.); (M.G.A.)
- Laboratory for Integrative and Translational Research in Population Health (ITR), University of Porto, 4050-313 Porto, Portugal
- Department of Anatomy, Institute of Biomedical Sciences Abel Salazar (ICBAS), University of Porto, 4050-313 Porto, Portugal
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Alesi S, Ghelani D, Rassie K, Mousa A. Metabolomic Biomarkers in Gestational Diabetes Mellitus: A Review of the Evidence. Int J Mol Sci 2021; 22:ijms22115512. [PMID: 34073737 PMCID: PMC8197243 DOI: 10.3390/ijms22115512] [Citation(s) in RCA: 36] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2021] [Revised: 05/20/2021] [Accepted: 05/20/2021] [Indexed: 12/14/2022] Open
Abstract
Gestational diabetes mellitus (GDM) is the fastest growing type of diabetes, affecting between 2 to 38% of pregnancies worldwide, varying considerably depending on diagnostic criteria used and sample population studied. Adverse obstetric outcomes include an increased risk of macrosomia, and higher rates of stillbirth, instrumental delivery, and birth trauma. Metabolomics, which is a platform used to analyse and characterise a large number of metabolites, is increasingly used to explore the pathophysiology of cardiometabolic conditions such as GDM. This review aims to summarise metabolomics studies in GDM (from inception to January 2021) in order to highlight prospective biomarkers for diagnosis, and to better understand the dysfunctional metabolic pathways underlying the condition. We found that the most commonly deranged pathways in GDM include amino acids (glutathione, alanine, valine, and serine), carbohydrates (2-hydroxybutyrate and 1,5-anhydroglucitol), and lipids (phosphatidylcholines and lysophosphatidylcholines). We also highlight the possibility of using certain metabolites as predictive markers for developing GDM, with the use of highly stratified modelling techniques. Limitations for metabolomic research are evaluated, and future directions for the field are suggested to aid in the integration of these findings into clinical practice.
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Affiliation(s)
- Simon Alesi
- Monash Centre for Health Research and Implementation (MCHRI), School of Public Health and Preventive Medicine, Monash University, Melbourne 3168, Australia; (S.A.); (D.G.); (K.R.)
| | - Drishti Ghelani
- Monash Centre for Health Research and Implementation (MCHRI), School of Public Health and Preventive Medicine, Monash University, Melbourne 3168, Australia; (S.A.); (D.G.); (K.R.)
| | - Kate Rassie
- Monash Centre for Health Research and Implementation (MCHRI), School of Public Health and Preventive Medicine, Monash University, Melbourne 3168, Australia; (S.A.); (D.G.); (K.R.)
- Department of Diabetes, Monash Health, Melbourne 3168, Australia
| | - Aya Mousa
- Monash Centre for Health Research and Implementation (MCHRI), School of Public Health and Preventive Medicine, Monash University, Melbourne 3168, Australia; (S.A.); (D.G.); (K.R.)
- Correspondence:
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Kovalik JP, Zhao X, Gao F, Leng S, Chow V, Chew H, Teo LLY, Tan RS, Ewe SH, Tan HC, Wee HN, Lee LS, Ching J, Keng BMH, Koh WP, Zhong L, Koh AS. Amino acid differences between diabetic older adults and non-diabetic older adults and their associations with cardiovascular function. J Mol Cell Cardiol 2021; 158:63-71. [PMID: 34033835 DOI: 10.1016/j.yjmcc.2021.05.009] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/24/2021] [Revised: 04/26/2021] [Accepted: 05/18/2021] [Indexed: 01/06/2023]
Abstract
BACKGROUND Ageing and insulin resistant states such as diabetes mellitus frequently coexist and increase the risk of cardiovascular disease development among older adults. Here we investigate metabolic differences in amino acid profiles between ageing and diabetes mellitus, and their associations with cardiovascular function. METHODS In a group of community older adults we performed echocardiography, cardiac magnetic resonance imaging as well as cross sectional and longitudinal metabolomics profiling based on current and archived sera obtained fifteen years prior to examination. RESULTS We studied a total of 515 participants (women 50%, n = 255) with a mean age 73 (SD = 4.3) years. Diabetics had higher alanine (562 vs 448, p < 0.0001), higher glutamate (107 vs 95, p = 0.016), higher proline (264 vs 231, p = 0.008) and lower arginine (107 vs 117, p = 0.043), lower citrulline (30 vs 38, p = 0.006) levels (μM) compared to non-diabetics. Over time, changes in amino acid profiles differentiated diabetic older adults from non-diabetic older adults, with greater accumulation of alanine (p = 0.002), proline (p = 0.008) and (non-significant) trend towards greater accumulation of glycine (p = 0.057) among the older diabetics compared to the older non-diabetics. However, independent of diabetes status, amino acids were associated with cardiovascular functions in ageing, [archived valine (p = 0.011), leucine (p = 0.011), archived isoleucine (p = 0.0006), archived serine (p = 0.008), archived glycine (p = 0.006) methionine (p = 0.003)] which were associated with impairments in E/A ratio. CONCLUSION Markers of branched chain amino acids and one ‑carbon metabolism pathways were associated with changes in cardiovascular function in older adults regardless of diabetes status. However, nitrogen handling pathways were specifically altered among older adults with diabetes. These findings broaden our understanding into specific amino acid pathways that may be altered between diabetic and non-diabetic older adults, and their relevance to cardiovascular function in ageing. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT02791139.
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Affiliation(s)
- Jean-Paul Kovalik
- Duke-NUS Medical School, Singapore; Singapore General Hospital, Singapore
| | | | - Fei Gao
- National Heart Centre Singapore, Singapore; Duke-NUS Medical School, Singapore
| | | | | | | | - Louis L Y Teo
- National Heart Centre Singapore, Singapore; Duke-NUS Medical School, Singapore
| | - Ru San Tan
- National Heart Centre Singapore, Singapore; Duke-NUS Medical School, Singapore
| | - See Hooi Ewe
- National Heart Centre Singapore, Singapore; Duke-NUS Medical School, Singapore
| | - Hong Chang Tan
- Duke-NUS Medical School, Singapore; Singapore General Hospital, Singapore
| | | | | | - Jianhong Ching
- Duke-NUS Medical School, Singapore; KK Research Centre, KK Women's and Children's Hospital, Singapore
| | | | - Woon-Puay Koh
- Healthy Longevity Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Liang Zhong
- National Heart Centre Singapore, Singapore; Duke-NUS Medical School, Singapore
| | - Angela S Koh
- National Heart Centre Singapore, Singapore; Duke-NUS Medical School, Singapore.
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143
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White PJ, McGarrah RW, Herman MA, Bain JR, Shah SH, Newgard CB. Insulin action, type 2 diabetes, and branched-chain amino acids: A two-way street. Mol Metab 2021; 52:101261. [PMID: 34044180 PMCID: PMC8513145 DOI: 10.1016/j.molmet.2021.101261] [Citation(s) in RCA: 124] [Impact Index Per Article: 41.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/05/2021] [Revised: 05/17/2021] [Accepted: 05/19/2021] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND A strong association of obesity and insulin resistance with increased circulating levels of branched-chain and aromatic amino acids and decreased glycine levels has been recognized in human subjects for decades. SCOPE OF REVIEW More recently, human metabolomics and genetic studies have confirmed and expanded upon these observations, accompanied by a surge in preclinical studies that have identified mechanisms involved in the perturbation of amino acid homeostasis- how these events are connected to dysregulated glucose and lipid metabolism, and how elevations in branched-chain amino acids (BCAA) may participate in the development of insulin resistance, type 2 diabetes (T2D), and other cardiometabolic diseases and conditions. MAJOR CONCLUSIONS In human cohorts, BCAA and related metabolites are now well established as among the strongest biomarkers of obesity, insulin resistance, T2D, and cardiovascular diseases. Lowering of BCAA and branched-chain ketoacid (BCKA) levels by feeding BCAA-restricted diet or by the activation of the rate-limiting enzyme in BCAA catabolism, branched-chain ketoacid dehydrogenase (BCKDH), in rodent models of obesity have clear salutary effects on glucose and lipid homeostasis, but BCAA restriction has more modest effects in short-term studies in human T2D subjects. Feeding of rats with diets enriched in sucrose or fructose result in the induction of the ChREBP transcription factor in the liver to increase expression of the BCKDH kinase (BDK) and suppress the expression of its phosphatase (PPM1K) resulting in the inactivation of BCKDH and activation of the key lipogenic enzyme ATP-citrate lyase (ACLY). These and other emergent links between BCAA, glucose, and lipid metabolism motivate ongoing studies of possible causal actions of BCAA and related metabolites in the development of cardiometabolic diseases.
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Affiliation(s)
- Phillip J White
- Sarah W. Stedman Nutrition and Metabolism Center, Duke University Medical Center, Durham, NC, 27701, USA; Duke Molecular Physiology Institute, Duke University Medical Center, Durham, NC, 27701, USA; Department of Pharmacology & Cancer Biology, Duke University Medical Center, Durham, NC, 27701, USA; Department of Medicine, Divisions of Endocrinology & Metabolism and Cardiology, Duke University Medical Center, Durham, NC, 27701, USA
| | - Robert W McGarrah
- Sarah W. Stedman Nutrition and Metabolism Center, Duke University Medical Center, Durham, NC, 27701, USA; Duke Molecular Physiology Institute, Duke University Medical Center, Durham, NC, 27701, USA; Department of Medicine, Divisions of Endocrinology & Metabolism and Cardiology, Duke University Medical Center, Durham, NC, 27701, USA
| | - Mark A Herman
- Sarah W. Stedman Nutrition and Metabolism Center, Duke University Medical Center, Durham, NC, 27701, USA; Duke Molecular Physiology Institute, Duke University Medical Center, Durham, NC, 27701, USA; Department of Pharmacology & Cancer Biology, Duke University Medical Center, Durham, NC, 27701, USA; Department of Medicine, Divisions of Endocrinology & Metabolism and Cardiology, Duke University Medical Center, Durham, NC, 27701, USA
| | - James R Bain
- Sarah W. Stedman Nutrition and Metabolism Center, Duke University Medical Center, Durham, NC, 27701, USA; Duke Molecular Physiology Institute, Duke University Medical Center, Durham, NC, 27701, USA; Department of Medicine, Divisions of Endocrinology & Metabolism and Cardiology, Duke University Medical Center, Durham, NC, 27701, USA
| | - Svati H Shah
- Sarah W. Stedman Nutrition and Metabolism Center, Duke University Medical Center, Durham, NC, 27701, USA; Duke Molecular Physiology Institute, Duke University Medical Center, Durham, NC, 27701, USA; Department of Medicine, Divisions of Endocrinology & Metabolism and Cardiology, Duke University Medical Center, Durham, NC, 27701, USA
| | - Christopher B Newgard
- Sarah W. Stedman Nutrition and Metabolism Center, Duke University Medical Center, Durham, NC, 27701, USA; Duke Molecular Physiology Institute, Duke University Medical Center, Durham, NC, 27701, USA; Department of Pharmacology & Cancer Biology, Duke University Medical Center, Durham, NC, 27701, USA; Department of Medicine, Divisions of Endocrinology & Metabolism and Cardiology, Duke University Medical Center, Durham, NC, 27701, USA.
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144
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Zhong W, Deng Q, Deng X, Zhong Z, Hou J. Plasma Metabolomics of Acute Coronary Syndrome Patients Based on Untargeted Liquid Chromatography-Mass Spectrometry. Front Cardiovasc Med 2021; 8:616081. [PMID: 34095243 PMCID: PMC8172787 DOI: 10.3389/fcvm.2021.616081] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2020] [Accepted: 03/18/2021] [Indexed: 11/13/2022] Open
Abstract
Background: Acute coronary syndrome (ACS) is the main cause of death and morbidity worldwide. The present study aims to investigate the altered metabolites in plasma from patients with ACS and sought to identify metabolic biomarkers for ACS. Methods: The plasma metabolomics profiles of 284 ACS patients and 130 controls were carried out based on an untargeted liquid chromatography coupled with tandem mass spectrometry (LC-MS) approach. Multivariate statistical methods, pathway enrichment analysis, and univariate receiver operating characteristic (ROC) curve analysis were performed. Results: A total of 328 and 194 features were determined in positive and negative electrospray ionization mode in the LC-MS analysis, respectively. Twenty-eight metabolites were found to be differentially expressed, in ACS patients relative to controls (p < 0.05). Pathway analysis revealed that these metabolites are mainly involved in synthesis and degradation of ketone bodies, phenylalanine metabolism, and arginine and proline metabolism. Furthermore, a diagnostic model was constructed based on the metabolites identified and the areas under the curve (AUC) for 5-oxo-D-proline, creatinine, phosphatidylethanolamine lyso 16:0, and LPC (20:4) range from 0.764 to 0.844. The higher AUC value of 0.905 was obtained for the combined detection of phosphatidylethanolamine lyso 16:0 and LPC (20:4). Conclusions: Differential metabolic profiles may be useful for the effective diagnosis of ACS and may provide additional insight into the molecular mechanisms underlying ACS.
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Affiliation(s)
- Wei Zhong
- Center for Cardiovascular Diseases, Meizhou People's Hospital (Huangtang Hospital), Meizhou Hospital Affiliated to Sun Yat-sen University, Meizhou, China.,Guangdong Provincial Engineering and Technology Research Center for Molecular Diagnostics of Cardiovascular Diseases, Meizhou, China.,Guangdong Provincial Key Laboratory of Precision Medicine and Clinical Translational Research of Hakka Population, Meizhou, China
| | - Qiaoting Deng
- Guangdong Provincial Engineering and Technology Research Center for Molecular Diagnostics of Cardiovascular Diseases, Meizhou, China.,Guangdong Provincial Key Laboratory of Precision Medicine and Clinical Translational Research of Hakka Population, Meizhou, China.,Research Experimental Center, Meizhou People's Hospital (Huangtang Hospital), Meizhou Hospital Affiliated to Sun Yat-sen University, Meizhou, China
| | - Xunwei Deng
- Guangdong Provincial Engineering and Technology Research Center for Molecular Diagnostics of Cardiovascular Diseases, Meizhou, China.,Guangdong Provincial Key Laboratory of Precision Medicine and Clinical Translational Research of Hakka Population, Meizhou, China.,Research Experimental Center, Meizhou People's Hospital (Huangtang Hospital), Meizhou Hospital Affiliated to Sun Yat-sen University, Meizhou, China
| | - Zhixiong Zhong
- Center for Cardiovascular Diseases, Meizhou People's Hospital (Huangtang Hospital), Meizhou Hospital Affiliated to Sun Yat-sen University, Meizhou, China.,Guangdong Provincial Engineering and Technology Research Center for Molecular Diagnostics of Cardiovascular Diseases, Meizhou, China.,Guangdong Provincial Key Laboratory of Precision Medicine and Clinical Translational Research of Hakka Population, Meizhou, China
| | - Jingyuan Hou
- Guangdong Provincial Engineering and Technology Research Center for Molecular Diagnostics of Cardiovascular Diseases, Meizhou, China.,Guangdong Provincial Key Laboratory of Precision Medicine and Clinical Translational Research of Hakka Population, Meizhou, China.,Research Experimental Center, Meizhou People's Hospital (Huangtang Hospital), Meizhou Hospital Affiliated to Sun Yat-sen University, Meizhou, China
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145
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Circulating Metabolites Associated with Body Fat and Lean Mass in Adults with Overweight/Obesity. Metabolites 2021; 11:metabo11050317. [PMID: 34068443 PMCID: PMC8153621 DOI: 10.3390/metabo11050317] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2021] [Revised: 05/05/2021] [Accepted: 05/12/2021] [Indexed: 12/26/2022] Open
Abstract
The interplay between fat mass and lean mass within human metabolism is not completely understood. We aimed to identify specific circulating metabolomic profiles associated with these body composition compartments. Cross-sectional analyses were conducted over 236 adults with overweight/obesity from the Satiety Innovation (SATIN) study. Body composition was assessed by dual-energy X-ray absorptiometry. A targeted multiplatform metabolite profiling approach was applied. Associations between 168 circulating metabolites and the body composition measures were assessed using elastic net regression analyses. The accuracy of the multimetabolite weighted models was evaluated using a 10-fold cross-validation approach and the Pearson's correlation coefficients between metabolomic profiles and body compartments were estimated. Two different profiles including 86 and 65 metabolites were selected for % body fat and lean mass. These metabolites mainly consisted of lipids (sphingomyelins, phosphatidylcholines, lysophosphatidylcholines), acylcarnitines, and amino acids. Several metabolites overlapped between these body composition measures but none of them towards the same direction. The Pearson correlation coefficients between the metabolomic profiles and % body fat or lean mass were 0.80 and 0.79, respectively. Our findings suggest alterations in lipid metabolism, fatty acid oxidation, and protein degradation with increased adiposity and decreased lean body mass. These findings could help us to better understand the interplay between body composition compartments with human metabolic processes.
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146
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Ishibashi Y, Harada S, Takeuchi A, Iida M, Kurihara A, Kato S, Kuwabara K, Hirata A, Shibuki T, Okamura T, Sugiyama D, Sato A, Amano K, Hirayama A, Sugimoto M, Soga T, Tomita M, Takebayashi T. Reliability of urinary charged metabolite concentrations in a large-scale cohort study using capillary electrophoresis-mass spectrometry. Sci Rep 2021; 11:7407. [PMID: 33795760 PMCID: PMC8016858 DOI: 10.1038/s41598-021-86600-9] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2020] [Accepted: 03/17/2021] [Indexed: 12/19/2022] Open
Abstract
Currently, large-scale cohort studies for metabolome analysis have been launched globally. However, only a few studies have evaluated the reliability of urinary metabolome analysis. This study aimed to establish the reliability of urinary metabolomic profiling in cohort studies. In the Tsuruoka Metabolomics Cohort Study, 123 charged metabolites were identified and routinely quantified using capillary electrophoresis-mass spectrometry (CE-MS). We evaluated approximately 750 quality control (QC) samples and 6,720 participants’ spot urine samples. We calculated inter- and intra-batch coefficients of variation in the QC and participant samples and technical intraclass correlation coefficients (ICC). A correlation of metabolite concentrations between spot and 24-h urine samples obtained from 32 sub-cohort participants was also evaluated. The coefficient of variation (CV) was less than 20% for 87 metabolites (70.7%) and 20–30% for 19 metabolites (15.4%) in the QC samples. There was less than 20% inter-batch CV for 106 metabolites (86.2%). Most urinary metabolites would have reliability for measurement. The 96 metabolites (78.0%) was above 0.75 for the estimated ICC, and those might be useful for epidemiological analysis. Among individuals, the Pearson correlation coefficient of 24-h and spot urine was more than 70% for 59 of the 99 metabolites. These results show that the profiling of charged metabolites using CE-MS in morning spot human urine is suitable for epidemiological metabolomics studies.
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Affiliation(s)
- Yoshiki Ishibashi
- Department of Preventive Medicine and Public Health, Keio University School of Medicine, 35 Shinanomachi, Shinjuku, Tokyo, Japan
| | - Sei Harada
- Department of Preventive Medicine and Public Health, Keio University School of Medicine, 35 Shinanomachi, Shinjuku, Tokyo, Japan.,Institute for Advanced Biosciences, Keio University, Tsuruoka, Yamagata, Japan
| | - Ayano Takeuchi
- Department of Preventive Medicine and Public Health, Keio University School of Medicine, 35 Shinanomachi, Shinjuku, Tokyo, Japan
| | - Miho Iida
- Department of Preventive Medicine and Public Health, Keio University School of Medicine, 35 Shinanomachi, Shinjuku, Tokyo, Japan
| | - Ayako Kurihara
- Department of Preventive Medicine and Public Health, Keio University School of Medicine, 35 Shinanomachi, Shinjuku, Tokyo, Japan
| | - Suzuka Kato
- Department of Preventive Medicine and Public Health, Keio University School of Medicine, 35 Shinanomachi, Shinjuku, Tokyo, Japan
| | - Kazuyo Kuwabara
- Department of Preventive Medicine and Public Health, Keio University School of Medicine, 35 Shinanomachi, Shinjuku, Tokyo, Japan
| | - Aya Hirata
- Department of Preventive Medicine and Public Health, Keio University School of Medicine, 35 Shinanomachi, Shinjuku, Tokyo, Japan
| | - Takuma Shibuki
- Department of Preventive Medicine and Public Health, Keio University School of Medicine, 35 Shinanomachi, Shinjuku, Tokyo, Japan
| | - Tomonori Okamura
- Department of Preventive Medicine and Public Health, Keio University School of Medicine, 35 Shinanomachi, Shinjuku, Tokyo, Japan
| | - Daisuke Sugiyama
- Department of Preventive Medicine and Public Health, Keio University School of Medicine, 35 Shinanomachi, Shinjuku, Tokyo, Japan.,Faculty of Nursing And Medical Care, Keio University, Fujisawa, Kanagawa, Japan
| | - Asako Sato
- Institute for Advanced Biosciences, Keio University, Tsuruoka, Yamagata, Japan
| | - Kaori Amano
- Institute for Advanced Biosciences, Keio University, Tsuruoka, Yamagata, Japan
| | - Akiyoshi Hirayama
- Institute for Advanced Biosciences, Keio University, Tsuruoka, Yamagata, Japan
| | - Masahiro Sugimoto
- Institute for Advanced Biosciences, Keio University, Tsuruoka, Yamagata, Japan
| | - Tomoyoshi Soga
- Institute for Advanced Biosciences, Keio University, Tsuruoka, Yamagata, Japan.,Faculty of Environment and Information Studies, Keio University, Fujisawa, Kanagawa, Japan
| | - Masaru Tomita
- Institute for Advanced Biosciences, Keio University, Tsuruoka, Yamagata, Japan.,Faculty of Environment and Information Studies, Keio University, Fujisawa, Kanagawa, Japan
| | - Toru Takebayashi
- Department of Preventive Medicine and Public Health, Keio University School of Medicine, 35 Shinanomachi, Shinjuku, Tokyo, Japan. .,Institute for Advanced Biosciences, Keio University, Tsuruoka, Yamagata, Japan.
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147
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Dietary glutamic acid and aspartic acid as biomarkers for predicting diabetic retinopathy. Sci Rep 2021; 11:7244. [PMID: 33790305 PMCID: PMC8012375 DOI: 10.1038/s41598-021-83165-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2020] [Accepted: 01/20/2021] [Indexed: 11/25/2022] Open
Abstract
The screening rate of diabetic retinopathy (DR) is low despite the importance of early diagnosis. We investigated the predictive value of dietary glutamic acid and aspartic acid for diagnosis of DR using the Korea National Diabetes Program cohort study. The 2067 patients with type 2 diabetes without DR were included. The baseline intakes of energy, glutamic acid and aspartic acid were assessed using a 3-day food records. The risk of DR incidence based on intake of glutamic acid and aspartic acid was analyzed. The DR group was older, and had higher HbA1c, longer DM duration, lower education level and income than non-DR group (all p < 0.05). The intake of total energy, glutamic acid and aspartic acid were lower in DR group than non-DR group (p = 0.010, p = 0.025 and p = 0.042, respectively). There was no difference in the risk of developing DR according to the intake of glutamic acid and ascorbic acid. But, aspartic acid intake had a negative correlation with PDR. Hence, the intake of glutamic acid and aspartic acid did not affect in DR incidence. However, lower aspartic acid intake affected the PDR incidence.
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148
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Duan W, Zi T, Zhao Y, Shan R, Wu H, Sun H, Tian Z, Wang J, Liu L, Zhang Y, Li Y, Sun C. Extent reflecting overall dietary amino acids composition adherence to the human requirement amino acids pattern is associated with the development of type 2 diabetes. Aging (Albany NY) 2021; 13:10141-10157. [PMID: 33819181 PMCID: PMC8064212 DOI: 10.18632/aging.202777] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2020] [Accepted: 12/19/2020] [Indexed: 12/12/2022]
Abstract
This study aimed to elucidate whether dietary amino acids (AAs) composition is associated with type 2 diabetes mellitus (T2DM) and to investigate how serum AAs profiles mediated this association. Two prospective cohorts of 1750 and 4024 adults were enrolled. Dietary AAs compositions index (AACI) was developed to reflect the overall quality of dietary AAs composition. Multivariate linear regression and logistic regression models were used to examine associations of AACI and T2DM. The AACI was associated with the incidence of T2DM with the relative risk and 95%CI from the bottom to the top tertiles being 1.00, 1.49 (0.88-2.51) and 2.27 (1.20-4.28), and 1.00, 1.58 (1.13-2.19) and 2.33 (1.56-3.47) in the two cohorts, respectively. The AACI was positively associated with serum valine, isoleucine, glutamic acid and phenylalanine, and it was negatively associated with serum glycine and histidine in both cohorts (P<0.01). Valine, glutamic acid and histidine consistently and partially mediated the association between the AACI and T2DM in the two cohorts, with total mediation effects of 33.4% and 54.6%, respectively. Dietary AAs composition was associated with the incidence of T2DM, meanwhile, the relationship was mediated by some degree of serum AAs. Future dietary strategies should focus on the improvement of the overall quality of dietary AAs compositions.
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Affiliation(s)
- Wei Duan
- National Key Discipline, Department of Nutrition and Food Hygiene, School of Public Health, Harbin Medical University, Harbin, China
| | - Tianqi Zi
- National Key Discipline, Department of Nutrition and Food Hygiene, School of Public Health, Harbin Medical University, Harbin, China
| | - Yanhe Zhao
- National Key Discipline, Department of Nutrition and Food Hygiene, School of Public Health, Harbin Medical University, Harbin, China
| | - Ruiqi Shan
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
| | - Huanyu Wu
- National Key Discipline, Department of Nutrition and Food Hygiene, School of Public Health, Harbin Medical University, Harbin, China
| | - Hu Sun
- National Key Discipline, Department of Nutrition and Food Hygiene, School of Public Health, Harbin Medical University, Harbin, China
| | - Zhen Tian
- National Key Discipline, Department of Nutrition and Food Hygiene, School of Public Health, Harbin Medical University, Harbin, China
| | - Jiemei Wang
- National Key Discipline, Department of Nutrition and Food Hygiene, School of Public Health, Harbin Medical University, Harbin, China
| | - Liyan Liu
- National Key Discipline, Department of Nutrition and Food Hygiene, School of Public Health, Harbin Medical University, Harbin, China
| | - Yuntao Zhang
- National Key Discipline, Department of Nutrition and Food Hygiene, School of Public Health, Harbin Medical University, Harbin, China
| | - Ying Li
- National Key Discipline, Department of Nutrition and Food Hygiene, School of Public Health, Harbin Medical University, Harbin, China
| | - Changhao Sun
- National Key Discipline, Department of Nutrition and Food Hygiene, School of Public Health, Harbin Medical University, Harbin, China
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149
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Porcu E, Gilardi F, Darrous L, Yengo L, Bararpour N, Gasser M, Marques-Vidal P, Froguel P, Waeber G, Thomas A, Kutalik Z. Triangulating evidence from longitudinal and Mendelian randomization studies of metabolomic biomarkers for type 2 diabetes. Sci Rep 2021; 11:6197. [PMID: 33737653 PMCID: PMC7973501 DOI: 10.1038/s41598-021-85684-7] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2020] [Accepted: 03/03/2021] [Indexed: 02/08/2023] Open
Abstract
The number of people affected by Type 2 diabetes mellitus (T2DM) is close to half a billion and is on a sharp rise, representing a major and growing public health burden. Given its mild initial symptoms, T2DM is often diagnosed several years after its onset, leaving half of diabetic individuals undiagnosed. While several classical clinical and genetic biomarkers have been identified, improving early diagnosis by exploring other kinds of omics data remains crucial. In this study, we have combined longitudinal data from two population-based cohorts CoLaus and DESIR (comprising in total 493 incident cases vs. 1360 controls) to identify new or confirm previously implicated metabolomic biomarkers predicting T2DM incidence more than 5 years ahead of clinical diagnosis. Our longitudinal data have shown robust evidence for valine, leucine, carnitine and glutamic acid being predictive of future conversion to T2DM. We confirmed the causality of such association for leucine by 2-sample Mendelian randomisation (MR) based on independent data. Our MR approach further identified new metabolites potentially playing a causal role on T2D, including betaine, lysine and mannose. Interestingly, for valine and leucine a strong reverse causal effect was detected, indicating that the genetic predisposition to T2DM may trigger early changes of these metabolites, which appear well-before any clinical symptoms. In addition, our study revealed a reverse causal effect of metabolites such as glutamic acid and alanine. Collectively, these findings indicate that molecular traits linked to the genetic basis of T2DM may be particularly promising early biomarkers.
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Affiliation(s)
- Eleonora Porcu
- grid.9851.50000 0001 2165 4204Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland ,grid.419765.80000 0001 2223 3006Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Federica Gilardi
- grid.150338.c0000 0001 0721 9812Unit of Forensic Toxicology and Chemistry, CURML, Lausanne University Hospital and Geneva University Hospitals, Geneva, Switzerland ,grid.9851.50000 0001 2165 4204Faculty Unit of Toxicology, CURML, Faculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland
| | - Liza Darrous
- grid.419765.80000 0001 2223 3006Swiss Institute of Bioinformatics, Lausanne, Switzerland ,grid.9851.50000 0001 2165 4204Center for Primary Care and Public Health, University of Lausanne, Lausanne, Switzerland
| | - Loic Yengo
- grid.1003.20000 0000 9320 7537Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia
| | - Nasim Bararpour
- grid.150338.c0000 0001 0721 9812Unit of Forensic Toxicology and Chemistry, CURML, Lausanne University Hospital and Geneva University Hospitals, Geneva, Switzerland ,grid.9851.50000 0001 2165 4204Faculty Unit of Toxicology, CURML, Faculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland
| | - Marie Gasser
- grid.150338.c0000 0001 0721 9812Unit of Forensic Toxicology and Chemistry, CURML, Lausanne University Hospital and Geneva University Hospitals, Geneva, Switzerland ,grid.9851.50000 0001 2165 4204Faculty Unit of Toxicology, CURML, Faculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland
| | - Pedro Marques-Vidal
- grid.8515.90000 0001 0423 4662Department of Medicine, Internal Medicine, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Philippe Froguel
- grid.410463.40000 0004 0471 8845Inserm UMR1283, CNRS UMR8199, European Genomic Institute for Diabetes (EGID), Université de Lille, Institut Pasteur de Lille, Lille University Hospital, Lille, France ,grid.7445.20000 0001 2113 8111Department of Metabolism, Imperial College London, London, UK
| | - Gerard Waeber
- grid.8515.90000 0001 0423 4662Department of Medicine, Internal Medicine, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Aurelien Thomas
- grid.150338.c0000 0001 0721 9812Unit of Forensic Toxicology and Chemistry, CURML, Lausanne University Hospital and Geneva University Hospitals, Geneva, Switzerland ,grid.9851.50000 0001 2165 4204Faculty Unit of Toxicology, CURML, Faculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland
| | - Zoltán Kutalik
- grid.419765.80000 0001 2223 3006Swiss Institute of Bioinformatics, Lausanne, Switzerland ,grid.9851.50000 0001 2165 4204Center for Primary Care and Public Health, University of Lausanne, Lausanne, Switzerland
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150
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Ngo D, Benson MD, Long JZ, Chen ZZ, Wang R, Nath AK, Keyes MJ, Shen D, Sinha S, Kuhn E, Morningstar JE, Shi X, Peterson BD, Chan C, Katz DH, Tahir UA, Farrell LA, Melander O, Mosley JD, Carr SA, Vasan RS, Larson MG, Smith JG, Wang TJ, Yang Q, Gerszten RE. Proteomic profiling reveals biomarkers and pathways in type 2 diabetes risk. JCI Insight 2021; 6:144392. [PMID: 33591955 PMCID: PMC8021115 DOI: 10.1172/jci.insight.144392] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2020] [Accepted: 01/28/2021] [Indexed: 01/14/2023] Open
Abstract
Recent advances in proteomic technologies have made high-throughput profiling of low-abundance proteins in large epidemiological cohorts increasingly feasible. We investigated whether aptamer-based proteomic profiling could identify biomarkers associated with future development of type 2 diabetes (T2DM) beyond known risk factors. We identified dozens of markers with highly significant associations with future T2DM across 2 large longitudinal cohorts (n = 2839) followed for up to 16 years. We leveraged proteomic, metabolomic, genetic, and clinical data from humans to nominate 1 specific candidate to test for potential causal relationships in model systems. Our studies identified functional effects of aminoacylase 1 (ACY1), a top protein association with future T2DM risk, on amino acid metabolism and insulin homeostasis in vitro and in vivo. Furthermore, a loss-of-function variant associated with circulating levels of the biomarker WAP, Kazal, immunoglobulin, Kunitz, and NTR domain-containing protein 2 (WFIKKN2) was, in turn, associated with fasting glucose, hemoglobin A1c, and HOMA-IR measurements in humans. In addition to identifying potentially novel disease markers and pathways in T2DM, we provide publicly available data to be leveraged for insights about gene function and disease pathogenesis in the context of human metabolism.
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Affiliation(s)
- Debby Ngo
- Cardiovascular Institute
- Division of Pulmonary, Critical Care and Sleep Medicine, and
| | - Mark D. Benson
- Cardiovascular Institute
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center (BIDMC), Boston, Massachusetts, USA
| | - Jonathan Z. Long
- Department of Pathology, Stanford University, Stanford, California, USA
| | - Zsu-Zsu Chen
- Cardiovascular Institute
- Division of Endocrinology, Diabetes and Metabolism, BIDMC, Boston, Massachusetts, USA
| | - Ruiqi Wang
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, USA
| | | | | | | | | | - Eric Kuhn
- Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA
| | | | | | | | | | - Daniel H. Katz
- Cardiovascular Institute
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center (BIDMC), Boston, Massachusetts, USA
| | - Usman A. Tahir
- Cardiovascular Institute
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center (BIDMC), Boston, Massachusetts, USA
| | | | - Olle Melander
- Department of Cardiology, Clinical Sciences, Lund University and Skåne University Hospital, Lund, Sweden
| | - Jonathan D. Mosley
- Departments of Medicine and Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Steven A. Carr
- Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA
| | - Ramachandran S. Vasan
- Department of Medicine, Divisions of Preventive Medicine and Cardiology, Boston University School of Medicine, Boston, Massachusetts, USA
- The National Heart, Lung, and Blood Institute’s Framingham Heart Study, Framingham, Massachusetts, USA
| | - Martin G. Larson
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, USA
- The National Heart, Lung, and Blood Institute’s Framingham Heart Study, Framingham, Massachusetts, USA
| | - J. Gustav Smith
- Department of Cardiology, Clinical Sciences, Lund University and Skåne University Hospital, Lund, Sweden
- Wallenberg Center for Molecular Medicine and Diabetes Center, Lund University, Lund, Sweden
- Department of Cardiology and Wallenberg Laboratory, Gothenburg University and Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Thomas J. Wang
- Department of Medicine, University of Texas, Southwestern Medical Center, Dallas, Texas, USA
| | - Qiong Yang
- Division of Endocrinology, Diabetes and Metabolism, BIDMC, Boston, Massachusetts, USA
| | - Robert E. Gerszten
- Cardiovascular Institute
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center (BIDMC), Boston, Massachusetts, USA
- Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA
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