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Iman MN, Haslam DE, Liang L, Guo K, Joshipura K, Pérez CM, Clish C, Tucker KL, Manson JE, Bhupathiraju SN, Fukusaki E, Lasky-Su J, Putri SP. Multidisciplinary approach combining food metabolomics and epidemiology identifies meglutol as an important bioactive metabolite in tempe, an Indonesian fermented food. Food Chem 2024; 446:138744. [PMID: 38432131 PMCID: PMC11247955 DOI: 10.1016/j.foodchem.2024.138744] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Revised: 02/09/2024] [Accepted: 02/10/2024] [Indexed: 03/05/2024]
Abstract
This study introduces a multidisciplinary approach to investigate bioactive food metabolites often overlooked due to their low concentrations. We integrated an in-house food metabolite library (n = 494), a human metabolite library (n = 891) from epidemiological studies, and metabolite pharmacological databases to screen for food metabolites with potential bioactivity. We identified six potential metabolites, including meglutol (3-hydroxy-3-methylglutarate), an understudied low-density lipoprotein (LDL)-lowering compound. We further focused on meglutol as a case study to showcase the range of characterizations achievable with this approach. Green pea tempe was identified to contain the highest meglutol concentration (21.8 ± 4.6 mg/100 g). Furthermore, we identified a significant cross-sectional association between plasma meglutol (per 1-standard deviation) and lower LDL cholesterol in two Hispanic adult cohorts (n = 1,628) (β [standard error]: -5.5 (1.6) mg/dl, P = 0.0005). These findings highlight how multidisciplinary metabolomics can serve as a systematic tool for discovering and enhancing bioactive metabolites in food, such as meglutol, with potential applications in personalized dietary approaches for disease prevention.
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Affiliation(s)
- Marvin N Iman
- Department of Biotechnology, Graduate School of Engineering, Osaka University, Japan
| | - Danielle E Haslam
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA; Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Liming Liang
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Kai Guo
- Center for Clinical Research and Health Promotion, Graduate School of Public Health, University of Puerto Rico Medical Sciences Campus, Puerto Rico, USA
| | - Kaumudi Joshipura
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Center for Clinical Research and Health Promotion, Graduate School of Public Health, University of Puerto Rico Medical Sciences Campus, Puerto Rico, USA
| | - Cynthia M Pérez
- Department of Biostatistics and Epidemiology, Graduate School of Public Health, University of Puerto Rico Medical Sciences Campus, Puerto Rico, USA
| | - Clary Clish
- Broad Institute of Massachusetts Institute of Technology and Harvard, USA
| | - Katherine L Tucker
- Department of Biomedical and Nutritional Sciences, University of Massachusetts Lowell, USA
| | - JoAnn E Manson
- Division of Preventive Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Shilpa N Bhupathiraju
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA; Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Eiichiro Fukusaki
- Department of Biotechnology, Graduate School of Engineering, Osaka University, Japan; Industrial Biotechnology Initiative Division, Institute for Open and Transdisciplinary Research Initiatives, Osaka University, Japan; Osaka University-Shimadzu Omics Innovation Research Laboratories, Osaka University, Japan
| | - Jessica Lasky-Su
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Sastia P Putri
- Department of Biotechnology, Graduate School of Engineering, Osaka University, Japan; Osaka University-Shimadzu Omics Innovation Research Laboratories, Osaka University, Japan.
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Fang Y, Wu H, Liang X, Li T, Jia R, Dong Y, Zheng Y, Wang Q, Li L. Efficacy and safety assessment of traditional Chinese patent medicine for dyslipidemia: a systematic review of randomized clinical trials with meta-analysis and trial sequential analysis. Cardiovasc Diagn Ther 2024; 14:419-446. [PMID: 38975001 PMCID: PMC11223937 DOI: 10.21037/cdt-24-146] [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: 04/01/2024] [Accepted: 06/21/2024] [Indexed: 07/09/2024]
Abstract
Background The overall prevalence of dyslipidemia continues to increase, which poses a significant risk for coronary artery disease. Some patients with dyslipidemia do not respond to or benefit from conventional lipid-lowering therapy, which warrants the need for alternative and complementary therapies. Chinese patent medicine (CPM) has shown great potential in the treatment of dyslipidemia, but its clinical value needs to be further explored. This study aims to systematically evaluate the efficacy and safety of CPM in treating dyslipidemia. Methods This study was registered in INPLASY as INPLASY202330090. The randomized controlled trials included in this study were published in January 2013 to March 2023 and retrieved from the Web of Science, PubMed, Embase, Cochrane Library, SinoMed, China National Knowledge Internet, WanFang, and VIP. The bias risk in the study was independently evaluated by two reviewers using the Cochrane Randomized Trial Bias Risk Tool (RoB 2) Review Manager 5.4 software was used for the overall effect analysis and subgroup analysis of four blood lipids, and the trial sequential analysis (TSA) was conducted to check the results. Results A total of 69 studies were included, involving 6,993 participants. The methodological quality was in the middle level. Meta-analysis showed that CPM markedly improved the levels of total cholesterol (TC) [mean difference (MD) =-0.54 mmol/L; 95% confidence interval (CI): -0.71 to -0.37; P<0.001], triglyceride (TG) (MD =-0.43 mmol/L; 95% CI: -0.53 to -0.33; P<0.001), low-density lipoprotein cholesterol (LDL-C) (MD =-0.40 mmol/L; 95% CI: -0.50 to -0.30; P<0.001) and increased levels of high-density lipoprotein cholesterol (HDL-C) (MD =0.23 mmol/L; 95% CI: 0.18 to 0.27; P<0.001), in patients with dyslipidemia. Though CPM did not differ significantly from statins when used alone, it could improve lipid profile better in all cases when used in combination with statins and with drugs used for comorbidities or co-morbidities. Subgroup analysis found that the efficacy of pill formulations was superior to other formulations, and CPM showed better lipid-lowering response in the context of comorbidity. The TSA confirmed the robustness of the analysis of the LDL-C level. No significant difference was observed in the incidence of adverse events between the treatment group and the control group [risk ratio (RR) =0.89; 95% CI: 0.69-1.16; P=0.40]. Conclusions CPM can yield superior therapeutic effects in ameliorating dyslipidemia without exacerbating adverse effects as an alternative and complementary therapy. In addition, the therapeutic effect can be improved by emphasizing pill formulation and strengthening the standardization of syndromes.
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Affiliation(s)
- Yini Fang
- Basic Medical College, Zhejiang Chinese Medical University, Hangzhou, China
- National Institute of Traditional Chinese Medicine Constitution and Preventive Medicine, Beijing University of Chinese Medicine, Beijing, China
| | - Haoran Wu
- National Institute of Traditional Chinese Medicine Constitution and Preventive Medicine, Beijing University of Chinese Medicine, Beijing, China
| | - Xue Liang
- National Institute of Traditional Chinese Medicine Constitution and Preventive Medicine, Beijing University of Chinese Medicine, Beijing, China
| | - Tianxing Li
- National Institute of Traditional Chinese Medicine Constitution and Preventive Medicine, Beijing University of Chinese Medicine, Beijing, China
- Institute of Basic Theory for Chinese Medicine, China Academy of Chinese Medical Sciences, Beijing, China
| | - Ruiting Jia
- Basic Medical College, Zhejiang Chinese Medical University, Hangzhou, China
| | - Yang Dong
- National Administration of Traditional Chinese Medicine Monitoring and Statistics Research Center, Beijing, China
| | - Yanfei Zheng
- National Institute of Traditional Chinese Medicine Constitution and Preventive Medicine, Beijing University of Chinese Medicine, Beijing, China
| | - Qi Wang
- Basic Medical College, Zhejiang Chinese Medical University, Hangzhou, China
- National Institute of Traditional Chinese Medicine Constitution and Preventive Medicine, Beijing University of Chinese Medicine, Beijing, China
| | - Lingru Li
- National Institute of Traditional Chinese Medicine Constitution and Preventive Medicine, Beijing University of Chinese Medicine, Beijing, China
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Xu B, Wu Q, La R, Lu L, Abdu FA, Yin G, Zhang W, Ding W, Ling Y, He Z, Che W. Is systemic inflammation a missing link between cardiometabolic index with mortality? Evidence from a large population-based study. Cardiovasc Diabetol 2024; 23:212. [PMID: 38902748 PMCID: PMC11191290 DOI: 10.1186/s12933-024-02251-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/29/2024] [Accepted: 04/26/2024] [Indexed: 06/22/2024] Open
Abstract
BACKGROUND This study sought to elucidate the associations of cardiometabolic index (CMI), as a metabolism-related index, with all-cause and cardiovascular mortality among the older population. Utilizing data from the National Health and Nutrition Examination Survey (NHANES), we further explored the potential mediating effect of inflammation within these associations. METHODS A cohort of 3029 participants aged over 65 years old, spanning six NHANES cycles from 2005 to 2016, was enrolled and assessed. The primary endpoints of the study included all-cause mortality and cardiovascular mortality utilizing data from National Center for Health Statistics (NCHS). Cox regression model and subgroup analysis were conducted to assess the associations of CMI with all-cause and cardiovascular mortality. The mediating effect of inflammation-related indicators including leukocyte, neutrophil, lymphocyte, systemic immune-inflammation index (SII), neutrophil to lymphocyte ratio (NLR) were evaluated to investigate the potential mechanism of the associations between CMI and mortality through mediation package in R 4.2.2. RESULTS The mean CMI among the enrolled participants was 0.74±0.66, with an average age of 73.28±5.50 years. After an average follow-up period of 89.20 months, there were 1,015 instances of all-cause deaths and 348 cardiovascular deaths documented. In the multivariable-adjusted model, CMI was positively related to all-cause mortality (Hazard Ratio (HR)=1.11, 95% CI=1.01-1.21). Mediation analysis indicated that leukocytes and neutrophils mediated 6.6% and 13.9% of the association of CMI with all-cause mortality. CONCLUSION Elevated CMI is positively associated with all-cause mortality in the older adults. The association appeared to be partially mediated through inflammatory pathways, indicating that CMI may serve as a valuable indicator for poor prognosis among the older population.
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Affiliation(s)
- Bin Xu
- Department of Cardiology, Shanghai Tenth People's Hospital, Tongji University School of Medicine, 301 Yanchang Road, Shanghai, 200072, China
- Department of Cardiology, Zhongshan-Xuhui Hospital, Shanghai Xuhui Central Hospital, Fudan University, Shanghai, China
| | - Qian Wu
- Department of Orthopedic Surgery, Orthopedic Institute, The First Affiliated Hospital of Soochow University, 188 Shizijie Road, Suzhou, 215006, Jiangsu, China.
- Research Institute of Clinical Medicine, Jeonbuk National University Medical School, Jeonju, Republic of Korea.
| | - Rui La
- Department of Orthopedic Surgery, Orthopedic Institute, The First Affiliated Hospital of Soochow University, 188 Shizijie Road, Suzhou, 215006, Jiangsu, China
| | - Lingchen Lu
- Department of Pediatric Surgery and Rehabilitation, Kunshan Maternity and Children's Health Care Hospital, Kunshan, Jiangsu, China
| | - Fuad A Abdu
- Department of Cardiology, Shanghai Tenth People's Hospital, Tongji University School of Medicine, 301 Yanchang Road, Shanghai, 200072, China
| | - Guoqing Yin
- Department of Cardiology, Shanghai Tenth People's Hospital, Tongji University School of Medicine, 301 Yanchang Road, Shanghai, 200072, China
| | - Wen Zhang
- Department of Cardiology, Shanghai Tenth People's Hospital, Tongji University School of Medicine, 301 Yanchang Road, Shanghai, 200072, China
| | - Wenquan Ding
- Department of Orthopedic Surgery, Orthopedic Institute, The First Affiliated Hospital of Soochow University, 188 Shizijie Road, Suzhou, 215006, Jiangsu, China
| | - Yicheng Ling
- Department of Orthopedic Surgery, Orthopedic Institute, The First Affiliated Hospital of Soochow University, 188 Shizijie Road, Suzhou, 215006, Jiangsu, China
| | - Zhiyuan He
- Department of Orthopedic Surgery, Orthopedic Institute, The First Affiliated Hospital of Soochow University, 188 Shizijie Road, Suzhou, 215006, Jiangsu, China
| | - Wenliang Che
- Department of Cardiology, Shanghai Tenth People's Hospital, Tongji University School of Medicine, 301 Yanchang Road, Shanghai, 200072, China.
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Etemadi A, Hassanzadehkiabi F, Mirabolghasemi M, Ahmadi M, Dehghanbanadaki H, Hosseinkhani S, Bandarian F, Najjar N, Dilmaghani-Marand A, Panahi N, Negahdari B, Mazloomi M, Karimi-jafari MH, Razi F, Larijani B. Plasma acylcarnitines and amino acids in dyslipidemia: An integrated metabolomics and machine learning approach. J Diabetes Metab Disord 2024; 23:1057-1069. [PMID: 38932808 PMCID: PMC11196250 DOI: 10.1007/s40200-024-01384-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Accepted: 12/29/2023] [Indexed: 06/28/2024]
Abstract
Purpose The Discovery of underlying intermediates associated with the development of dyslipidemia results in a better understanding of pathophysiology of dyslipidemia and their modification will be a promising preventive and therapeutic strategy for the management of dyslipidemia. Methods The entire dataset was selected from the Surveillance of Risk Factors of Noncommunicable Diseases (NCDs) in 30 provinces of Iran (STEPs 2016 Country report in Iran) that included 1200 subjects and was stratified into four binary classes with normal and abnormal cases based on their levels of triglyceride (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), and non-HDL-C.Plasma concentrations of 20 amino acids and 30 acylcarnitines in each class of dyslipidemia were evaluated using Tandem mass spectrometry. Then, these attributes, along with baseline characteristics data, were used to check whether machine learning (ML) algorithms could classify cases and controls. Results Our ML framework accurately predicts TG binary classes. Among the models tested, the SVM model stood out, performing slightly better with an AUC of 0.81 and a standard deviation of test accuracy at 0.04. Consequently, it was chosen as the optimal model for TG classification. Moreover, the findings showed that alanine, phenylalanine, methionine, C3, C14:2, and C16 had great power in differentiating patients with high TG from normal TG controls. Conclusions: The comprehensive output of this work, along with sex-specific attributes, will improve our understanding of the underlying intermediates involved in dyslipidemia. Supplementary Information The online version contains supplementary material available at 10.1007/s40200-024-01384-9.
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Affiliation(s)
- Ali Etemadi
- Metabolomics and Genomics Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
- Department of Medical Biotechnology, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences (TUMS), Tehran, Iran
| | - Farima Hassanzadehkiabi
- Department of Medical Biotechnology, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences (TUMS), Tehran, Iran
| | - Maryam Mirabolghasemi
- Department of Bioinformatics, Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran
| | - Mehdi Ahmadi
- Department of Medical Biotechnology, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences (TUMS), Tehran, Iran
| | - Hojat Dehghanbanadaki
- Diabetes Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Shaghayegh Hosseinkhani
- Metabolic Disorders Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Fatemeh Bandarian
- Metabolomics and Genomics Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Niloufar Najjar
- Metabolic Disorders Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Arezou Dilmaghani-Marand
- Non-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Nekoo Panahi
- Metabolic Disorders Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Babak Negahdari
- Department of Medical Biotechnology, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences (TUMS), Tehran, Iran
| | - Mohammadali Mazloomi
- Department of Medical Biotechnology, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences (TUMS), Tehran, Iran
| | | | - Farideh Razi
- Metabolomics and Genomics Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Bagher Larijani
- Endocrinology and Metabolism Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
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Zheng C, Liu Y, Xu C, Zeng S, Wang Q, Guo Y, Li J, Li S, Dong M, Luo X, Wu Q. Association between obesity and the prevalence of dyslipidemia in middle-aged and older people: an observational study. Sci Rep 2024; 14:11974. [PMID: 38796639 PMCID: PMC11127928 DOI: 10.1038/s41598-024-62892-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2024] [Accepted: 05/22/2024] [Indexed: 05/28/2024] Open
Abstract
This study aimed to explore the link between various forms of obesity, including body mass index (BMI) and waist circumference (WC), and the risk of dyslipidemia among Chinese residents. We selected the study population through a multi-stage random sampling method from permanent residents aged 35 and older in Ganzhou. Obesity was categorized as non-obesity, general obesity, central obesity, or compound obesity according to established diagnostic criteria. We employed a logistic regression model to assess the relationship between different types of obesity and the risk of dyslipidemia. Additionally, we used the restricted cubic spline model to analyze the association between BMI, WC, and the risk of dyslipidemia. The study included 2030 residents aged 35 or older from Ganzhou, China. The prevalence of dyslipidemia was found to be 39.31%, with an age-standardized prevalence of 36.51%. The highest prevalence of dyslipidemia, 58.79%, was observed among those with compound obesity. After adjusting for confounding factors, we found that the risk of dyslipidemia in those with central and compound obesity was respectively 2.00 (95% CI 1.62-2.46) and 2.86 (95% CI 2.03-4.03) times higher than in the non-obese population. Moreover, the analysis using the restricted cubic spline model indicated a nearly linear association between BMI, WC, and the risk of dyslipidemia. The findings emphasize the significant prevalence of both dyslipidemia and obesity among adults aged 35 and above in Ganzhou, China. Notably, individuals with compound obesity are at a substantially increased risk of dyslipidemia. Therefore, it is crucial to prioritize the use of BMI and WC as screening and preventive measures for related health conditions.
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Affiliation(s)
- Chuanlei Zheng
- School of Public Health and Health Management, Gannan Medical University, Ganzhou, 341000, China
| | - Yanhong Liu
- School of Public Health and Health Management, Gannan Medical University, Ganzhou, 341000, China
| | - Cong Xu
- School of Public Health and Health Management, Gannan Medical University, Ganzhou, 341000, China
| | - Shaobo Zeng
- School of Public Health and Health Management, Gannan Medical University, Ganzhou, 341000, China
| | - Qi Wang
- School of Public Health and Health Management, Gannan Medical University, Ganzhou, 341000, China
| | - Yixing Guo
- School of Public Health and Health Management, Gannan Medical University, Ganzhou, 341000, China
| | - Jian Li
- School of Basic Medicine, Gannan Medical University, Ganzhou, 341000, China
| | - Sisi Li
- School of Public Health and Health Management, Gannan Medical University, Ganzhou, 341000, China
| | - Minghua Dong
- School of Public Health and Health Management, Gannan Medical University, Ganzhou, 341000, China
| | - Xiaoting Luo
- Division of Academic Affairs, Gannan Medical University, Ganzhou, 341000, China
| | - Qingfeng Wu
- School of Public Health and Health Management, Gannan Medical University, Ganzhou, 341000, China.
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Bagheri M, Bombin A, Shi M, Murthy VL, Shah R, Mosley JD, Ferguson JF. Genotype-based "virtual" metabolomics in a clinical biobank identifies novel metabolite-disease associations. Front Genet 2024; 15:1392622. [PMID: 38812968 PMCID: PMC11133605 DOI: 10.3389/fgene.2024.1392622] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2024] [Accepted: 05/03/2024] [Indexed: 05/31/2024] Open
Abstract
Introduction: Circulating metabolites act as biomarkers of dysregulated metabolism and may inform disease pathophysiology. A portion of the inter-individual variability in circulating metabolites is influenced by common genetic variation. We evaluated whether a genetics-based "virtual" metabolomics approach can identify novel metabolite-disease associations. Methods: We examined the association between polygenic scores for 724 metabolites with 1,247 clinical phenotypes in the BioVU DNA biobank, comprising 57,735 European ancestry and 15,754 African ancestry participants. We applied Mendelian randomization (MR) to probe significant relationships and validated significant MR associations using independent GWAS of candidate phenotypes. Results and Discussion: We found significant associations between 336 metabolites and 168 phenotypes in European ancestry and 107 metabolites and 56 phenotypes in African ancestry. Of these metabolite-disease pairs, MR analyses confirmed associations between 73 metabolites and 53 phenotypes in European ancestry. Of 22 metabolitephenotype pairs evaluated for replication in independent GWAS, 16 were significant (false discovery rate p < 0.05). These included associations between bilirubin and X-21796 with cholelithiasis, phosphatidylcholine (16:0/22:5n3,18:1/20:4) and arachidonate with inflammatory bowel disease and Crohn's disease, and campesterol with coronary artery disease and myocardial infarction. These associations may represent biomarkers or potentially targetable mediators of disease risk.
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Affiliation(s)
- Minoo Bagheri
- Division of Cardiovascular Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, United States
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Andrei Bombin
- Division of Cardiovascular Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Mingjian Shi
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Venkatesh L Murthy
- Division of Cardiovascular Medicine, University of Michigan, Ann Arbor, MI, United States
| | - Ravi Shah
- Division of Cardiovascular Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Jonathan D Mosley
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, United States
- Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Jane F Ferguson
- Division of Cardiovascular Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, United States
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Yang C, Ma Y, Yao M, Jiang Q, Xue J. Causal relationships between blood metabolites and diabetic retinopathy: a two-sample Mendelian randomization study. Front Endocrinol (Lausanne) 2024; 15:1383035. [PMID: 38752182 PMCID: PMC11094203 DOI: 10.3389/fendo.2024.1383035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/06/2024] [Accepted: 04/05/2024] [Indexed: 05/18/2024] Open
Abstract
Background Diabetic retinopathy (DR) is a microvascular complication of diabetes, severely affecting patients' vision and even leading to blindness. The development of DR is influenced by metabolic disturbance and genetic factors, including gene polymorphisms. The research aimed to uncover the causal relationships between blood metabolites and DR. Methods The two-sample mendelian randomization (MR) analysis was employed to estimate the causality of blood metabolites on DR. The genetic variables for exposure were obtained from the genome-wide association study (GWAS) dataset of 486 blood metabolites, while the genetic predictors for outcomes including all-stage DR (All DR), non-proliferative DR (NPDR) and proliferative DR (PDR) were derived from the FinnGen database. The primary analysis employed inverse variance weighted (IVW) method, and supplementary analyses were performed using MR-Egger, weighted median (WM), simple mode and weighted mode methods. Additionally, MR-Egger intercept test, Cochran's Q test, and leave-one-out analysis were also conducted to guarantee the accuracy and robustness of the results. Subsequently, we replicated the MR analysis using three additional datasets from the FinnGen database and conducted a meta-analysis to determine blood metabolites associated with DR. Finally, reverse MR analysis and metabolic pathway analysis were performed. Results The study identified 13 blood metabolites associated with All DR, 9 blood metabolites associated with NPDR and 12 blood metabolites associated with PDR. In summary, a total of 21 blood metabolites were identified as having potential causal relationships with DR. Additionally, we identified 4 metabolic pathways that are related to DR. Conclusion The research revealed a number of blood metabolites and metabolic pathways that are causally associated with DR, which holds significant importance for screening and prevention of DR. However, it is noteworthy that these causal relationships should be validated in larger cohorts and experiments.
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Affiliation(s)
- Chongchao Yang
- The Affiliated Eye Hospital, Nanjing Medical University, Nanjing, Jiangsu, China
- The Fourth School of Clinical Medicine, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Yan Ma
- The Affiliated Eye Hospital, Nanjing Medical University, Nanjing, Jiangsu, China
- The Fourth School of Clinical Medicine, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Mudi Yao
- Department of Ophthalmology, The First People's Hospital, Shanghai, China
| | - Qin Jiang
- The Affiliated Eye Hospital, Nanjing Medical University, Nanjing, Jiangsu, China
- The Fourth School of Clinical Medicine, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Jinsong Xue
- The Affiliated Eye Hospital, Nanjing Medical University, Nanjing, Jiangsu, China
- The Fourth School of Clinical Medicine, Nanjing Medical University, Nanjing, Jiangsu, China
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8
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Savytska M, Kyriienko D, Zaychenko G, Ostapchenko D, Falalyeyeva T, Kobyliak N. Probiotic co-supplementation with absorbent smectite for pancreatic beta-cell function in type 2 diabetes: a secondary-data analysis of a randomized double-blind controlled trials. Front Endocrinol (Lausanne) 2024; 15:1276642. [PMID: 38405158 PMCID: PMC10890794 DOI: 10.3389/fendo.2024.1276642] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/12/2023] [Accepted: 01/18/2024] [Indexed: 02/27/2024] Open
Abstract
Introduction There is growing evidence from animal and clinical studies suggesting probiotics can positively affect type 2 diabetes (T2D). In a previous randomized clinical study, we found that administering a live multistrain probiotic and absorbent smectite once a day for eight weeks to patients with T2D could reduce chronic systemic inflammatory state, insulin resistance, waist circumference and improve the glycemic profile. However, there is a lack of evidence supporting the efficacy of probiotic co-supplementation with absorbent smectite on pancreatic β-cell function in T2D. Aim This secondary analysis aimed to assess the effectiveness of an alive multistrain probiotic co-supplementation with absorbent smectite vs placebo on β-cell function in T2D patients. Material and methods We performed a secondary analysis on a previously published randomized controlled trial (NCT04293731, NCT03614039) involving 46 patients with T2D. The main inclusion criteria were the presence of β-cell dysfunction (%B<60%) and insulin therapy alone or combined with oral anti-diabetic drugs. The primary outcome was assessing β-cell function as change C-peptide and %B. Results We observed only a tendency for improving β-cell function (44.22 ± 12.80 vs 55.69 ± 25.75; р=0.094). The effectiveness of the therapy probiotic-smectite group was confirmed by fasting glycemia decreased by 14% (p=0.019), HbA1c - 5% (p=0.007), HOMA-2 - 17% (p=0.003) and increase of insulin sensitivity by 23% (p=0.005). Analysis of the cytokine profile showed that statistical differences after treatment were in the concentration of both pro-inflammatory cytokines: IL-1β (22.83 ± 9.04 vs 19.03 ± 5.57; p=0.045) and TNF-α (31.25 ± 11.32 vs 26.23 ± 10.13; p=0.041). Conclusion Adding a live multistrain probiotic and absorbent smectite supplement slightly improved β-cell function and reduced glycemic-related parameters in patients with T2D. This suggests that adjusting the gut microbiota could be a promising treatment for diabetes and warrants further investigation through more extensive studies.
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Affiliation(s)
- Maryana Savytska
- Normal Physiology Department, Danylo Halytsky Lviv National Medical University, Lviv, Ukraine
| | | | - Ganna Zaychenko
- Pharmacology Department, Bogomolets National Medical University, Kyiv, Ukraine
| | - Danylo Ostapchenko
- Educational-Scientific Center “Institute of Biology and Medicine” Taras Shevchenko National University of Kyiv, Kyiv, Ukraine
| | - Tetyana Falalyeyeva
- Educational-Scientific Center “Institute of Biology and Medicine” Taras Shevchenko National University of Kyiv, Kyiv, Ukraine
- Medical Laboratory CSD, Kyiv, Ukraine
| | - Nazarii Kobyliak
- Medical Laboratory CSD, Kyiv, Ukraine
- Endocrinology Department, Bogomolets National Medical University, Kyiv, Ukraine
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9
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Liu Y, Liu JE, He H, Qin M, Lei H, Meng J, Liu C, Chen X, Luo W, Zhong S. Characterizing the metabolic divide: distinctive metabolites differentiating CAD-T2DM from CAD patients. Cardiovasc Diabetol 2024; 23:14. [PMID: 38184583 PMCID: PMC10771670 DOI: 10.1186/s12933-023-02102-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Accepted: 12/25/2023] [Indexed: 01/08/2024] Open
Abstract
OBJECTIVE To delineate the metabolomic differences in plasma samples between patients with coronary artery disease (CAD) and those with concomitant CAD and type 2 diabetes mellitus (T2DM), and to pinpoint distinctive metabolites indicative of T2DM risk. METHOD Plasma samples from CAD and CAD-T2DM patients across three centers underwent comprehensive metabolomic and lipidomic analyses. Multivariate logistic regression was employed to discern the relationship between the identified metabolites and T2DM risk. Characteristic metabolites' metabolic impacts were further probed through hepatocyte cellular experiments. Subsequent transcriptomic analyses elucidated the potential target sites explaining the metabolic actions of these metabolites. RESULTS Metabolomic analysis revealed 192 and 95 significantly altered profiles in the discovery (FDR < 0.05) and validation (P < 0.05) cohorts, respectively, that were associated with T2DM risk in univariate logistic regression. Further multivariate regression analyses identified 22 characteristic metabolites consistently associated with T2DM risk in both cohorts. Notably, pipecolinic acid and L-pipecolic acid, lysine derivatives, exhibited negative association with CAD-T2DM and influenced cellular glucose metabolism in hepatocytes. Transcriptomic insights shed light on potential metabolic action sites of these metabolites. CONCLUSIONS This research underscores the metabolic disparities between CAD and CAD-T2DM patients, spotlighting the protective attributes of pipecolinic acid and L-pipecolic acid. The comprehensive metabolomic and transcriptomic findings provide novel insights into the mechanism research, prophylaxis and treatment of comorbidity of CAD and T2DM.
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Affiliation(s)
- Yingjian Liu
- School of Medicine, South China University of Technology, Guangzhou, 510006, Guangdong, China
- Department of Pharmacy, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, 106 Zhongshan 2nd Road, Guangzhou, 510080, China
- Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080, Guangdong, China
| | - Ju-E Liu
- Department of Pharmacy, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, 106 Zhongshan 2nd Road, Guangzhou, 510080, China
| | - Huafeng He
- School of Medicine, South China University of Technology, Guangzhou, 510006, Guangdong, China
- Department of Pharmacy, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, 106 Zhongshan 2nd Road, Guangzhou, 510080, China
- Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080, Guangdong, China
| | - Min Qin
- School of Medicine, South China University of Technology, Guangzhou, 510006, Guangdong, China
- Department of Pharmacy, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, 106 Zhongshan 2nd Road, Guangzhou, 510080, China
- Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080, Guangdong, China
| | - Heping Lei
- Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080, Guangdong, China
| | - Jinxiu Meng
- Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080, Guangdong, China
| | - Chen Liu
- Department of Cardiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Xiaoping Chen
- Department of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha, China
| | - Wenwei Luo
- Department of Pharmacy, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, 106 Zhongshan 2nd Road, Guangzhou, 510080, China.
| | - Shilong Zhong
- School of Medicine, South China University of Technology, Guangzhou, 510006, Guangdong, China.
- Department of Pharmacy, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, 106 Zhongshan 2nd Road, Guangzhou, 510080, China.
- Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080, Guangdong, China.
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10
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Hasani M, Pilerud ZA, Kami A, Vaezi AA, Sobhani S, Ejtahed HS, Qorbani M. Association between Gut Microbiota Compositions with MicrovascularComplications in Individuals with Diabetes: A Systematic Review. Curr Diabetes Rev 2024; 20:e240124226068. [PMID: 38275035 DOI: 10.2174/0115733998280396231212114345] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/03/2023] [Revised: 11/07/2023] [Accepted: 11/16/2023] [Indexed: 01/27/2024]
Abstract
BACKGROUND Diabetes is one of the chronic and very complex diseases that can lead to microvascular complications. Recent evidence demonstrates that dysbiosis of the microbiota composition might result in low-grade, local, and systemic inflammation, which contributes directly to the development of diabetes mellitus and its microvascular consequences. OBJECTIVE The aim of this systematic review was to investigate the association between diabetes microvascular complications, including retinopathy, neuropathy, nephropathy, and gut microbiota composition. METHODS A systematic search was carried out in PubMed, Scopus, and ISI Web of Science from database inception to March 2023. Screening, data extraction, and quality assessment were performed by two independent authors. The Newcastle-Ottawa Quality Assessment Scale was used for quality assessment. RESULTS About 19 articles were selected from 590 retrieved articles. Among the included studies, nephropathy has been studied more than other complications of diabetes, showing that the composition of the healthy microbiota is changed, and large quantities of uremic solutes that cause kidney injury are produced by gut microbes. Phyla, including Fusobacteria and Proteobacteria, accounted for the majority of the variation in gut microbiota between Type 2 diabetic patients with and without neuropathy. In cases with retinopathy, an increase in pathogenic and proinflammatory bacteria was observed. CONCLUSION Our results revealed that increases in Bacteroidetes, Proteobacteria and Fusobacteria may be associated with the pathogenesis of diabetic nephropathy, neuropathy, and retinopathy. In view of the detrimental role of intestinal dysbiosis in the development of diabetes-related complications, gut microbiota assessment may be used as a biomarker in the future and interventions that modulate the composition of microbiota in individuals with diabetes can be used to prevent and control these complications.
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Affiliation(s)
- Motahareh Hasani
- Department of Nutrition, School of Health, Golestan University of Medical Sciences, Gorgan, Iran
| | - Zahra Asadi Pilerud
- Student Research Committee, Alborz University of Medical Sciences, Karaj, Iran
| | - Atefe Kami
- Golestan University of Medical Sciences, Gorgan, Iran
| | - Amir Abbas Vaezi
- Department of Internal Medicine, School of Medicine, Alborz University of Medical Sciences, Karaj, Iran
| | - Sahar Sobhani
- Noncommunicable Diseases Research Center, Alborz University of Medical Sciences, Karaj, Iran
| | - Hanieh-Sadat Ejtahed
- Obesity and Eating Habits Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
- Endocrinology and Metabolism Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Mostafa Qorbani
- Noncommunicable Diseases Research Center, Alborz University of Medical Sciences, Karaj, Iran
- Chronic Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
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11
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Li W, Lei D, Huang G, Tang N, Lu P, Jiang L, Lv J, Lin Y, Xu F, Qin YJ. Association of glyphosate exposure with multiple adverse outcomes and potential mediators. CHEMOSPHERE 2023; 345:140477. [PMID: 37858770 DOI: 10.1016/j.chemosphere.2023.140477] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/20/2023] [Revised: 10/11/2023] [Accepted: 10/16/2023] [Indexed: 10/21/2023]
Abstract
Glyphosate (GLY) is a widely used herbicide with potential adverse effects on public health. However, the current epidemiological evidence is limited. This study aimed to investigate the potential associations between exposure to GLY and multiple health outcomes. The data on urine GLY concentration and nine health outcomes, including type 2 diabetes mellitus (T2DM), hypertension, cardiovascular disease (CVD), obesity, chronic kidney disease (CKD), hepatic steatosis, cancers, chronic obstructive pulmonary disease (COPD), and neurodegenerative diseases (NGDs), were extracted from NHANES (2013-2016). The associations between GLY exposure and each health outcome were estimated using reverse-scale Cox regression and logistic regression. Furthermore, mediation analysis was conducted to identify potential mediators in the significant associations. The dose-response relationships between GLY exposure with health outcomes and potential mediators were analyzed using restricted cubic spline (RCS) regression. The findings of the study revealed that individuals with higher urinary concentrations of GLY had a higher likelihood of having T2DM, hypertension, CVD and obesity (p < 0.001, p = 0.005, p < 0.001 and p = 0.005, respectively). In the reverse-scale Cox regression, a notable association was solely discerned between exposure to GLY and the risk of T2DM (adjusted HR = 1.22, 95% CI: 1.10, 1.36). Consistent outcomes were also obtained via logistic regression analysis, wherein the adjusted OR and 95% CI for T2DM were determined to be 1.30 (1.12, 1.52). Moreover, the present investigation identified serum high-density lipoprotein cholesterol (HDL) as a mediator in this association, with a mediating effect of 7.14% (p = 0.040). This mediating effect was further substantiated by RCS regression, wherein significant dose-response associations were observed between GLY exposure and an increased risk of T2DM (p = 0.002) and reduced levels of HDL (p = 0.001). Collectively, these findings imply an association between GLY exposure and an increased risk of T2DM in the general adult population.
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Affiliation(s)
| | - Daizai Lei
- Department of Ophthalmology, The People's Hospital of Guangxi Zhuang Autonomous Region & Institute of Ophthalmic Diseases, Guangxi Academy of Medical Sciences & Guangxi Key Laboratory of Eye Health & Guangxi Health Commission Key Laboratory of Ophthalmology and Related Systemic Diseases Artificial Intelligence Screening Technology, Nanning, 530021, China
| | - Guangyi Huang
- Department of Ophthalmology, The People's Hospital of Guangxi Zhuang Autonomous Region & Institute of Ophthalmic Diseases, Guangxi Academy of Medical Sciences & Guangxi Key Laboratory of Eye Health & Guangxi Health Commission Key Laboratory of Ophthalmology and Related Systemic Diseases Artificial Intelligence Screening Technology, Nanning, 530021, China
| | - Ningning Tang
- Department of Ophthalmology, The People's Hospital of Guangxi Zhuang Autonomous Region & Institute of Ophthalmic Diseases, Guangxi Academy of Medical Sciences & Guangxi Key Laboratory of Eye Health & Guangxi Health Commission Key Laboratory of Ophthalmology and Related Systemic Diseases Artificial Intelligence Screening Technology, Nanning, 530021, China
| | - Peng Lu
- Department of Ophthalmology, The People's Hospital of Guangxi Zhuang Autonomous Region & Institute of Ophthalmic Diseases, Guangxi Academy of Medical Sciences & Guangxi Key Laboratory of Eye Health & Guangxi Health Commission Key Laboratory of Ophthalmology and Related Systemic Diseases Artificial Intelligence Screening Technology, Nanning, 530021, China
| | - Li Jiang
- Department of Ophthalmology, The People's Hospital of Guangxi Zhuang Autonomous Region & Institute of Ophthalmic Diseases, Guangxi Academy of Medical Sciences & Guangxi Key Laboratory of Eye Health & Guangxi Health Commission Key Laboratory of Ophthalmology and Related Systemic Diseases Artificial Intelligence Screening Technology, Nanning, 530021, China
| | - Jian Lv
- Department of Ophthalmology, The People's Hospital of Guangxi Zhuang Autonomous Region & Institute of Ophthalmic Diseases, Guangxi Academy of Medical Sciences & Guangxi Key Laboratory of Eye Health & Guangxi Health Commission Key Laboratory of Ophthalmology and Related Systemic Diseases Artificial Intelligence Screening Technology, Nanning, 530021, China
| | - Yunru Lin
- Department of Ophthalmology, The People's Hospital of Guangxi Zhuang Autonomous Region & Institute of Ophthalmic Diseases, Guangxi Academy of Medical Sciences & Guangxi Key Laboratory of Eye Health & Guangxi Health Commission Key Laboratory of Ophthalmology and Related Systemic Diseases Artificial Intelligence Screening Technology, Nanning, 530021, China
| | - Fan Xu
- Department of Ophthalmology, The People's Hospital of Guangxi Zhuang Autonomous Region & Institute of Ophthalmic Diseases, Guangxi Academy of Medical Sciences & Guangxi Key Laboratory of Eye Health & Guangxi Health Commission Key Laboratory of Ophthalmology and Related Systemic Diseases Artificial Intelligence Screening Technology, Nanning, 530021, China.
| | - Yuan-Jun Qin
- Department of Ophthalmology, The People's Hospital of Guangxi Zhuang Autonomous Region & Institute of Ophthalmic Diseases, Guangxi Academy of Medical Sciences & Guangxi Key Laboratory of Eye Health & Guangxi Health Commission Key Laboratory of Ophthalmology and Related Systemic Diseases Artificial Intelligence Screening Technology, Nanning, 530021, China; Department of Ophthalmology, Renmin Hospital of Wuhan University, China.
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12
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Lu Q, Li Y, Ye D, Yu X, Huang W, Zang S, Jiang G. Longitudinal metabolomics integrated with machine learning identifies novel biomarkers of gestational diabetes mellitus. Free Radic Biol Med 2023; 209:9-17. [PMID: 37806596 DOI: 10.1016/j.freeradbiomed.2023.10.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Revised: 09/27/2023] [Accepted: 10/05/2023] [Indexed: 10/10/2023]
Abstract
BACKGROUND Evidence from longitudinal studies is crucial to enhance our understanding of the role of metabolites in the progression of gestational diabetes mellitus (GDM). Herein, a longitudinal untargeted metabolomic study was conducted to reveal the metabolomic profiles and biomarkers associated with the progression of GDM, and characterize the changing patterns of metabolites. METHODS We collected serum samples at three trimesters from 30 patients with GDM and 30 healthy Chinese pregnant women with pre-pregnancy BMI, age, and parity matched, and untargeted metabolomic analysis was performed, followed by machine learning approaches that integrated bootstrap and LASSO. Cluster analysis was conducted to elucidate the patterns of metabolite changes. Pathway analyses were conducted to gain insights into the underlying pathways involved. RESULTS A total of 32 metabolites, mainly belonging to amino acid and its derivatives, were significantly associated with GDM across three trimesters, and were clustered into three distinct patterns. Metabolites belonging to phosphatidylcholines, lysophosphatidylcholines, lysophosphatidic acids, and lysophosphatidylethanolamines were consistently upregulated, and 2,3-Dihydroxypropyl dihydrogen phosphate was downregulated in GDM group. Amino acid-related, glycerophospholipid, and vitamin B6 metabolism were enriched in multiple trimesters. The levels of allantoic acid, which was positively correlated with blood glucose, was consistently higher in GDM patients and exhibited good discriminatory ability for GDM in the early and mid-pregnancy. CONCLUSION We identified and characterized distinct patterns of metabolites associated with GDM throughout pregnancy, and found that allantoic acid was a potential biomarker for early diagnosis of GDM.
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Affiliation(s)
- Qiuhan Lu
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China; School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Yue Li
- Department of Endocrinology, Shanghai Fifth People's Hospital, Fudan University, Shanghai, China
| | - Dewei Ye
- Key Laboratory of Metabolic Phenotyping in Model Animals, Guangdong Pharmaceutical University, Guangzhou, Guangdong, China
| | - Xiangtian Yu
- Clinical Research Center, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Wenyu Huang
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China; School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Shufei Zang
- Department of Endocrinology, Shanghai Fifth People's Hospital, Fudan University, Shanghai, China.
| | - Guozhi Jiang
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China; School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, Guangdong, China.
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13
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Bagheri M, Bombin A, Shi M, Murthy VL, Shah R, Mosley JD, Ferguson JF. Genotype-based "virtual" metabolomics in a clinical biobank identifies novel metabolite-disease associations. RESEARCH SQUARE 2023:rs.3.rs-3222588. [PMID: 37790512 PMCID: PMC10543429 DOI: 10.21203/rs.3.rs-3222588/v2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/11/2024]
Abstract
Circulating metabolites act as biomarkers of dysregulated metabolism, and may inform disease pathophysiology. A portion of the inter-individual variability in circulating metabolites is influenced by common genetic variation. We evaluated whether a genetics-based "virtual" metabolomics approach can identify novel metabolite-disease associations. We examined the association between polygenic scores for 726 metabolites (derived from OMICSPRED) with 1,247 clinical phenotypes in 57,735 European ancestry and 15,754 African ancestry participants from the BioVU DNA Biobank. We probed significant relationships through Mendelian randomization (MR) using genetic instruments constructed from the METSIM Study, and validated significant MR associations using independent GWAS of candidate phenotypes. We found significant associations between 336 metabolites and 168 phenotypes in European ancestry and 107 metabolites and 56 phenotypes among African ancestry. Of these metabolite-disease pairs, MR analyses confirmed associations between 73 metabolites and 53 phenotypes in European ancestry. Of 22 metabolite-phenotype pairs evaluated for replication in independent GWAS, 16 were significant (false discovery rate p<0.05). Validated findings included the metabolites bilirubin and X-21796 with cholelithiasis, phosphatidylcholine(16:0/22:5n3,18:1/20:4) and arachidonate(20:4n6) with inflammatory bowel disease and Crohn's disease, and campesterol with coronary artery disease and myocardial infarction. These associations may represent biomarkers or potentially targetable mediators of disease risk.
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Affiliation(s)
| | | | | | | | - Ravi Shah
- Vanderbilt University Medical Center
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14
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Bagheri M, Bombin A, Shi M, Murthy VL, Shah R, Mosley JD, Ferguson JF. Genotype-based "virtual" metabolomics in a clinical biobank identifies novel metabolite-disease associations. RESEARCH SQUARE 2023:rs.3.rs-3222588. [PMID: 37790512 PMCID: PMC10543429 DOI: 10.21203/rs.3.rs-3222588/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/05/2023]
Abstract
Circulating metabolites act as biomarkers of dysregulated metabolism, and may inform disease pathophysiology. A portion of the inter-individual variability in circulating metabolites is influenced by common genetic variation. We evaluated whether a genetics-based "virtual" metabolomics approach can identify novel metabolite-disease associations. We examined the association between polygenic scores for 726 metabolites (derived from OMICSPRED) with 1,247 clinical phenotypes in 57,735 European ancestry and 15,754 African ancestry participants from the BioVU DNA Biobank. We probed significant relationships through Mendelian randomization (MR) using genetic instruments constructed from the METSIM Study, and validated significant MR associations using independent GWAS of candidate phenotypes. We found significant associations between 336 metabolites and 168 phenotypes in European ancestry and 107 metabolites and 56 phenotypes among African ancestry. Of these metabolite-disease pairs, MR analyses confirmed associations between 73 metabolites and 53 phenotypes in European ancestry. Of 22 metabolite-phenotype pairs evaluated for replication in independent GWAS, 16 were significant (false discovery rate p<0.05). Validated findings included the metabolites bilirubin and X-21796 with cholelithiasis, phosphatidylcholine(16:0/22:5n3,18:1/20:4) and arachidonate(20:4n6) with inflammatory bowel disease and Crohn's disease, and campesterol with coronary artery disease and myocardial infarction. These associations may represent biomarkers or potentially targetable mediators of disease risk.
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Affiliation(s)
| | | | | | | | - Ravi Shah
- Vanderbilt University Medical Center
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15
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Wu Y, Wei Q, Li H, Yang H, Wu Y, Yu Y, Chen Q, He B, Chen F. Association of remnant cholesterol with hypertension, type 2 diabetes, and their coexistence: the mediating role of inflammation-related indicators. Lipids Health Dis 2023; 22:158. [PMID: 37752554 PMCID: PMC10521406 DOI: 10.1186/s12944-023-01915-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Accepted: 09/03/2023] [Indexed: 09/28/2023] Open
Abstract
PURPOSE Cholesterol metabolism is a risk factor for cardiovascular disease, and recent studies have shown that cholesterol metabolism poses a residual risk of cardiovascular disease even when conventional lipid risk factors are in the optimal range. The association between remnant cholesterol (RC) and cardiovascular disease has been demonstrated; however, its association with hypertension, type 2 diabetes mellitus (T2DM), and the concomitance of the two diseases requires further study. This study aimed to evaluate the association of RC with hypertension, T2DM, and both in a large sample of the U.S. population, and to further explore the potential mechanisms involved. METHODS This cross-sectional study used data from the 2005-2018 cycles of the National Health and Nutrition Examination Survey (N = 17,749). Univariable and multivariable logistic regression analyses were performed to explore the relationships of RC with hypertension, T2DM, and both comorbidities. A restricted cubic spline regression model was used to reveal the dose effect. Mediation analyses were performed to explore the potential mediating roles of inflammation-related indicators in these associations. RESULTS Of the 17,749 participants included (mean [SD] age: 41.57 [0.23] years; women: 8983 (50.6%), men: 8766 (49.4%)), the prevalence of hypertension, T2DM, and their co-occurrence was 32.6%, 16.1%, and 11.0%, respectively. Higher RC concentrations were associated with an increased risk of hypertension, T2DM, and their co-occurrence (adjusted odds ratios for per unit increase in RC were 1.068, 2.259, and 2.362, and 95% confidence intervals were 1.063-1.073, 1.797-2.838, and 1.834-3.041, respectively), with a linear dose-response relationship. Even when conventional lipids were present at normal levels, positive associations were observed. Inflammation-related indicators (leukocytes, lymphocytes, monocytes, and neutrophils) partially mediated these associations. Among these, leukocytes had the greatest mediating effect (10.8%, 14.5%, and 14.0%, respectively). CONCLUSION The results of this study provide evidence that RC is associated with the risk of hypertension, T2DM, and their co-occurrence, possibly mediated by an inflammatory response.
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Affiliation(s)
- Yuxuan Wu
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, China
| | - Qinfei Wei
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, China
| | - Husheng Li
- Department of Preventive Medicine, School of Public Health, Fujian Medical University, Fuzhou, China
| | - Han Yang
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, China
| | - Yuying Wu
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, China
| | - Yiming Yu
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, China
| | - Qiansi Chen
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, China
| | - Baochang He
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, China
| | - Fa Chen
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, China.
- Clinical Research Unit, The Second Affiliated Hospital, Fujian Medical University, Quanzhou, China.
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Yousri NA, Albagha OME, Hunt SC. Integrated epigenome, whole genome sequence and metabolome analyses identify novel multi-omics pathways in type 2 diabetes: a Middle Eastern study. BMC Med 2023; 21:347. [PMID: 37679740 PMCID: PMC10485955 DOI: 10.1186/s12916-023-03027-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Accepted: 08/09/2023] [Indexed: 09/09/2023] Open
Abstract
BACKGROUND T2D is of high prevalence in the middle east and thus studying its mechanisms is of a significant importance. Using 1026 Qatar BioBank samples, epigenetics, whole genome sequencing and metabolomics were combined to further elucidate the biological mechanisms of T2D in a population with a high prevalence of T2D. METHODS An epigenome-wide association study (EWAS) with T2D was performed using the Infinium 850K EPIC array, followed by whole genome-wide sequencing SNP-CpG association analysis (> 5.5 million SNPs) and a methylome-metabolome (CpG-metabolite) analysis of the identified T2D sites. RESULTS A total of 66 T2D-CpG associations were identified, including 63 novel sites in pathways of fructose and mannose metabolism, insulin signaling, galactose, starch and sucrose metabolism, and carbohydrate absorption and digestion. Whole genome SNP associations with the 66 CpGs resulted in 688 significant CpG-SNP associations comprising 22 unique CpGs (33% of the 66 CPGs) and included 181 novel pairs or pairs in novel loci. Fourteen of the loci overlapped published GWAS loci for diabetes related traits and were used to identify causal associations of HK1 and PFKFB2 with HbA1c. Methylome-metabolome analysis identified 66 significant CpG-metabolite pairs among which 61 pairs were novel. Using the identified methylome-metabolome associations, methylation QTLs, and metabolic networks, a multi-omics network was constructed which suggested a number of metabolic mechanisms underlying T2D methylated genes. 1-palmitoyl-2-oleoyl-GPE (16:0/18:1) - a triglyceride-associated metabolite, shared a common network with 13 methylated CpGs, including TXNIP, PFKFB2, OCIAD1, and BLCAP. Mannonate - a food component/plant shared a common network with 6 methylated genes, including TXNIP, BLCAP, THBS4 and PEF1, pointing to a common possible cause of methylation in those genes. A subnetwork with alanine, glutamine, urea cycle (citrulline, arginine), and 1-carboxyethylvaline linked to PFKFB2 and TXNIP revealed associations with kidney function, hypertension and triglyceride metabolism. The pathway containing STYXL1-POR was associated with a sphingosine-ceramides subnetwork associated with HDL-C and LDL-C and point to steroid perturbations in T2D. CONCLUSIONS This study revealed several novel methylated genes in T2D, with their genomic variants and associated metabolic pathways with several implications for future clinical use of multi-omics associations in disease and for studying therapeutic targets.
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Affiliation(s)
- Noha A Yousri
- Genetic Medicine, Weill Cornell Medicine-Qatar, Doha, Qatar.
- College of Health and Life Sciences, Hamad Bin Khalifa University, Doha, Qatar.
- Computer and Systems Engineering, Alexandria University, Alexandria, Egypt.
| | - Omar M E Albagha
- College of Health and Life Sciences, Hamad Bin Khalifa University, Doha, Qatar
| | - Steven C Hunt
- Genetic Medicine, Weill Cornell Medicine-Qatar, Doha, Qatar
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17
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Naja K, Anwardeen N, Al-Hariri M, Al Thani AA, Elrayess MA. Pharmacometabolomic Approach to Investigate the Response to Metformin in Patients with Type 2 Diabetes: A Cross-Sectional Study. Biomedicines 2023; 11:2164. [PMID: 37626661 PMCID: PMC10452592 DOI: 10.3390/biomedicines11082164] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Revised: 07/14/2023] [Accepted: 07/30/2023] [Indexed: 08/27/2023] Open
Abstract
Metformin constitutes the foundation therapy in type 2 diabetes (T2D). Despite its multiple beneficial effects and widespread use, there is considerable inter-individual variability in response to metformin. Our objective is to identify metabolic signatures associated with poor and good responses to metformin, which may improve our ability to predict outcomes for metformin treatment. In this cross-sectional study, clinical and metabolic data for 119 patients with type 2 diabetes taking metformin were collected from the Qatar Biobank. Patients were empirically dichotomized according to their HbA1C levels into good and poor responders. Differences in the level of metabolites between these two groups were compared using orthogonal partial least square discriminate analysis (OPLS-DA) and linear models. Good responders showed increased levels of sphingomyelins, acylcholines, and glutathione metabolites. On the other hand, poor responders showed increased levels of metabolites resulting from glucose metabolism and gut microbiota metabolites. The results of this study have the potential to increase our knowledge of patient response variability to metformin and carry significant implications for enabling personalized medicine.
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Affiliation(s)
- Khaled Naja
- Biomedical Research Center, Qatar University, Doha P.O. Box 2713, Qatar; (K.N.); (N.A.); (A.A.A.T.)
| | - Najeha Anwardeen
- Biomedical Research Center, Qatar University, Doha P.O. Box 2713, Qatar; (K.N.); (N.A.); (A.A.A.T.)
| | | | - Asmaa A. Al Thani
- Biomedical Research Center, Qatar University, Doha P.O. Box 2713, Qatar; (K.N.); (N.A.); (A.A.A.T.)
- QU Health, Qatar University, Doha P.O. Box 2713, Qatar;
| | - Mohamed A. Elrayess
- Biomedical Research Center, Qatar University, Doha P.O. Box 2713, Qatar; (K.N.); (N.A.); (A.A.A.T.)
- QU Health, Qatar University, Doha P.O. Box 2713, Qatar;
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18
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Vieira JPP, Ottosson F, Jujic A, Denisov V, Magnusson M, Melander O, Duarte JMN. Metabolite Profiling in a Diet-Induced Obesity Mouse Model and Individuals with Diabetes: A Combined Mass Spectrometry and Proton Nuclear Magnetic Resonance Spectroscopy Study. Metabolites 2023; 13:874. [PMID: 37512581 PMCID: PMC10385288 DOI: 10.3390/metabo13070874] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Revised: 07/19/2023] [Accepted: 07/20/2023] [Indexed: 07/30/2023] Open
Abstract
Mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy techniques have been used extensively for metabolite profiling. Although combining these two analytical modalities has the potential of enhancing metabolite coverage, such studies are sparse. In this study we test the hypothesis that combining the metabolic information obtained using liquid chromatography (LC) MS and 1H NMR spectroscopy improves the discrimination of metabolic disease development. We induced metabolic syndrome in male mice using a high-fat diet (HFD) exposure and performed LC-MS and NMR spectroscopy on plasma samples collected after 1 and 8 weeks of dietary intervention. In an orthogonal projection to latent structures (OPLS) analysis, we observed that combining MS and NMR was stronger than each analytical method alone at determining effects of both HFD feeding and time-on-diet. We then tested our metabolomics approach on plasma from 56 individuals from the Malmö Diet and Cancer Study (MDCS) cohort. All metabolic pathways impacted by HFD feeding in mice were confirmed to be affected by diabetes in the MDCS cohort, and most prominent HFD-induced metabolite concentration changes in mice were also associated with metabolic syndrome parameters in humans. The main drivers of metabolic disease discrimination emanating from the present study included plasma levels of xanthine, hippurate, 2-hydroxyisovalerate, S-adenosylhomocysteine and dimethylguanidino valeric acid. In conclusion, our combined NMR-MS approach provided a snapshot of metabolic imbalances in humans and a mouse model, which was improved over employment of each analytical method alone.
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Affiliation(s)
- João P P Vieira
- Department of Experimental Medical Science, Faculty of Medicine, Lund University, 22184 Lund, Sweden
- Wallenberg Centre for Molecular Medicine, Lund University, 22100 Lund, Sweden
| | - Filip Ottosson
- Department of Clinical Sciences-Malmö, Faculty of Medicine, Lund University, 20502 Malmö, Sweden
| | - Amra Jujic
- Wallenberg Centre for Molecular Medicine, Lund University, 22100 Lund, Sweden
- Department of Clinical Sciences-Malmö, Faculty of Medicine, Lund University, 20502 Malmö, Sweden
- Department of Cardiology, Skåne University Hospital, 21428 Malmö, Sweden
| | - Vladimir Denisov
- Biomedical Engineering Division, Department of Clinical Sciences-Lund, Faculty of Medicine, Lund University, 22100 Lund, Sweden
| | - Martin Magnusson
- Wallenberg Centre for Molecular Medicine, Lund University, 22100 Lund, Sweden
- Department of Clinical Sciences-Malmö, Faculty of Medicine, Lund University, 20502 Malmö, Sweden
- Department of Cardiology, Skåne University Hospital, 21428 Malmö, Sweden
- Hypertension in Africa Research Team, North-West University, Potchefstroom 2520, South Africa
| | - Olle Melander
- Department of Clinical Sciences-Malmö, Faculty of Medicine, Lund University, 20502 Malmö, Sweden
| | - João M N Duarte
- Department of Experimental Medical Science, Faculty of Medicine, Lund University, 22184 Lund, Sweden
- Wallenberg Centre for Molecular Medicine, Lund University, 22100 Lund, Sweden
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19
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Zheng R, Michaëlsson K, Fall T, Elmståhl S, Lind L. The metabolomic profiling of total fat and fat distribution in a multi-cohort study of women and men. Sci Rep 2023; 13:11129. [PMID: 37429905 DOI: 10.1038/s41598-023-38318-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Accepted: 07/06/2023] [Indexed: 07/12/2023] Open
Abstract
Currently studies aiming for the comprehensive metabolomics profiling of measured total fat (%) as well as fat distribution in both sexes are lacking. In this work, bioimpedance analysis was applied to measure total fat (%) and fat distribution (trunk to leg ratio). Liquid chromatography-mass spectrometry-based untargeted metabolomics was employed to profile the metabolic signatures of total fat (%) and fat distribution in 3447 participants from three Swedish cohorts (EpiHealth, POEM and PIVUS) using a discovery-replication cross-sectional study design. Total fat (%) and fat distribution were associated with 387 and 120 metabolites in the replication cohort, respectively. Enriched metabolic pathways for both total fat (%) and fat distribution included protein synthesis, branched-chain amino acids biosynthesis and metabolism, glycerophospholipid metabolism and sphingolipid metabolism. Four metabolites were mainly related to fat distribution: glutarylcarnitine (C5-DC), 6-bromotryptophan, 1-stearoyl-2-oleoyl-GPI (18:0/18:1) and pseudouridine. Five metabolites showed different associations with fat distribution in men and women: quinolinate, (12Z)-9,10-dihydroxyoctadec-12-enoate (9,10-DiHOME), two sphingomyelins and metabolonic lactone sulfate. To conclude, total fat (%) and fat distribution were associated with a large number of metabolites, but only a few were exclusively associated with fat distribution and of those metabolites some were associated with sex*fat distribution. Whether these metabolites mediate the undesirable effects of obesity on health outcomes remains to be further investigated.
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Affiliation(s)
- Rui Zheng
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden.
| | - Karl Michaëlsson
- Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
| | - Tove Fall
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Sölve Elmståhl
- Division of Geriatric Medicine, Department of Clinical Sciences in Malmö, Lund University, Malmö, Sweden
| | - Lars Lind
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
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20
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Wu ZP, Wei W, Cheng Y, Chen JY, Liu Y, Liu S, Hu MD, Zhao H, Li XF, Chen X. Altered adolescents obesity metabolism is associated with hypertension: a UPLC-MS-based untargeted metabolomics study. Front Endocrinol (Lausanne) 2023; 14:1172290. [PMID: 37229452 PMCID: PMC10203610 DOI: 10.3389/fendo.2023.1172290] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Accepted: 04/19/2023] [Indexed: 05/27/2023] Open
Abstract
Objective This study aimed to explore the relationship between the plasma metabolites of adolescent obesity and hypertension and whether metabolite alterations had a mediating effort between adolescent obesity and hypertension. Methods We applied untargeted ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) to detect the plasma metabolomic profiles of 105 adolescents. All participants were selected randomly based on a previous cross-sectional study. An orthogonal partial least squares- discriminant analysis (OPLS-DA), followed by univariate statistics and enrichment analysis, was used to identify differential metabolites. Using logistic regression for variable selection, an obesity-related metabolite score (OMS, OMS=∑k=1nβnmetabolite n) was constructed from the metabolites identified, and hypertension risk was estimated. Results In our study, based on P< 0.05, variable importance in projection (VIP) > 1.0, and impact value > 0.1, we identified a total of 12 differential metabolites. Significantly altered metabolic pathways were the sphingolipid metabolism, purine metabolism, pyrimidine metabolism, phospholipid metabolism, steroid hormone biosynthesis, tryptophan, tyrosine, and phenylalanine biosynthesis. The logistic regression selection resulted in a four-metabolite score (thymidine, sphingomyelin (SM) d40:1, 4-hydroxyestradiol, and L-lysinamide), which was positively associated with hypertension risk (odds ratio: 7.79; 95% confidence interval: 2.13, 28.47; for the quintile 4 compared with quartile 1 of OMS) after multivariable adjustment. Conclusions The OMS constructed from four differential metabolites was used to predict the risk of hypertension in adolescents. These findings could provide sensitive biomarkers for the early recognition of hypertension in adolescents with obesity.
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Affiliation(s)
- Zhi-Ping Wu
- Department of Epidemiology, School of Public Health, Dalian Medical University, Dalian, China
| | - Wei Wei
- Department of Neurosurgery, Central Hospital of Dalian University of Technology, Dalian, China
| | - Yuan Cheng
- Department of Epidemiology, School of Public Health, Dalian Medical University, Dalian, China
| | - Jing-Yi Chen
- Department of Epidemiology, School of Public Health, Dalian Medical University, Dalian, China
| | - Yang Liu
- Institute of Health Science, China Medical University, Shenyang, China
| | - Shan Liu
- Department of Epidemiology, School of Public Health, Dalian Medical University, Dalian, China
| | - Meng-Die Hu
- Department of Epidemiology, School of Public Health, Dalian Medical University, Dalian, China
| | - Heng Zhao
- Department of Epidemiology, School of Public Health, Dalian Medical University, Dalian, China
| | - Xiao-Feng Li
- Department of Epidemiology, School of Public Health, Dalian Medical University, Dalian, China
| | - Xin Chen
- Department of Epidemiology, School of Public Health, Dalian Medical University, Dalian, China
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21
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Yao X, Zhang J, Zhang X, Jiang T, Zhang Y, Dai F, Hu H, Zhang Q. Age at diagnosis, diabetes duration and the risk of cardiovascular disease in patients with diabetes mellitus: a cross-sectional study. Front Endocrinol (Lausanne) 2023; 14:1131395. [PMID: 37223032 PMCID: PMC10200881 DOI: 10.3389/fendo.2023.1131395] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/25/2022] [Accepted: 04/17/2023] [Indexed: 05/25/2023] Open
Abstract
Background The purpose of the study was to evaluate characteristics and risk of cardiovascular disease (CVD) according to age at diagnosis and disease duration among adults with diabetes mellitus (DM). Methods The association between age at diagnosis, diabetes duration and CVD were examined in 1,765 patients with DM. High risk of estimated ten-year atherosclerotic cardiovascular disease (ASCVD) was performed by the Prediction for ASCVD Risk in China (China-PAR) project. Data were compared with analysis of variance and χ2 test, respectively. Multiple logistic regression was used to determine the risk factors of CVD. Results The mean age at diagnosis (± standard deviation) was 52.91 ± 10.25 years and diabetes duration was 8.06 ± 5.66 years. Subjects were divided into early-onset DM group (≤43 years), late-onset DM group (44 to 59 years), elderly-onset DM group (≥60 years) according to age at diagnosis. Diabetes duration was classified by 5 years. Both early-onset and longest diabetes duration (>15 years) had prominent hyperglycaemia. Diabetes duration was associated with the risk of ischemic stroke (odds ratio (OR), 1.091) and coronary artery disease (OR, 1.080). Early-onset group (OR, 2.323), and late-onset group (OR, 5.199), and hypertension (OR, 2.729) were associated with the risk of ischemic stroke. Late-onset group (OR, 5.001), disease duration (OR, 1.080), and hypertension (OR, 2.015) and hyperlipidemia (OR, 1.527) might increase the risk of coronary artery disease. Aged over 65 (OR, 10.192), central obesity (OR, 1.992), hypertension (OR, 18.816), cardiovascular drugs (OR, 5.184), antihypertensive drugs (OR, 2.780), and participants with disease duration >15 years (OR, 1.976) were associated with the high risk of estimated ten-year ASCVD in participants with DM. Conclusion Age at diagnosis, diabetes duration, hypertension and hyperlipidemia were independent risks of CVD. Longest (>15 years) diabetes duration increased the high risk of ten-year ASCVD prediction among Chinese patients with DM. It's urgent to emphasize the importance of age at diagnosis and diabetes duration to improve primary complication of diabetes.
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Affiliation(s)
| | | | | | | | | | | | - Honglin Hu
- *Correspondence: Honglin Hu, ; Qiu Zhang,
| | - Qiu Zhang
- *Correspondence: Honglin Hu, ; Qiu Zhang,
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22
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Lee H, Gao Y, Kim JK, Shin S, Choi M, Hwang Y, Lee S, Rhyu DY, Kim KT. Synergetic effects of concurrent chronic exposure to a mixture of OCPs and high-fat diets on type 2 diabetes and beneficial effects of caloric restriction in female zebrafish. JOURNAL OF HAZARDOUS MATERIALS 2023; 446:130659. [PMID: 36587596 DOI: 10.1016/j.jhazmat.2022.130659] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/02/2022] [Revised: 12/20/2022] [Accepted: 12/21/2022] [Indexed: 06/17/2023]
Abstract
This study aimed to investigate the relationship among chronic exposure to a low concentration of organochlorine pesticides (OCPs), high-fat diet (HFD)-induced obesity, and caloric restriction in type 2 diabetes (T2D). Thus, female zebrafish were divided into four groups and treated for 12 weeks as follows: (i) negative control, (ii) HFD (obesity) control, (iii) obesity + a mixture of OCPs (OP), and (iv) obesity + a mixture of OCPs + caloric restriction (OPR). We then assessed T2D-related effects via hematological analysis, histopathology, mitochondrial evaluation, and multiomics analyses. The OP group showed a significant increase in glucose levels, whereas the OPR group maintained glucose at nonsignificant levels. Multiomics analyses revealed that the exacerbated metabolic effects in the OP group were associated with molecular alterations in oxidative stress, inflammation, nucleotide metabolism, and glucose/lipid homeostasis. These alterations were histologically verified by the increased numbers of hypertrophic adipocytes and inflammatory cells observed. Caloric restriction activated pathways related to antioxidant response, mitochondrial fatty acid oxidation, and energy metabolism in zebrafish, leading to preserved glucose homeostasis. In conclusion, this study identified molecular mechanisms underlying the synergistic effect of concurrent exposure to a mixture of OCPs and HFD as well as shed light on the beneficial effect of regular caloric restriction in T2D development.
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Affiliation(s)
- Hyojin Lee
- Department of Environmental Engineering, Seoul National University of Science and Technology, Seoul 01811, Republic of Korea
| | - Yan Gao
- BK21 Plus KNU Multi-Omics Based Creative Drug Research Team, College of Pharmacy, Research Institute of Pharmaceutical Sciences, Kyungpook National University, Daegu 41566, Republic of Korea; Department of Core Analytical Service, Wuxi AppTec, Shanghai 200131, China
| | - Jae Kwan Kim
- Korea Basic Science Institute, Seoul 02841, Republic of Korea
| | - Sooim Shin
- Department of Biotechnology and Bioengineering, Chonnam National University, Gwangju 61186, Republic of Korea
| | - Moonsung Choi
- Department of Optometry, Seoul National University of Science and Technology, Seoul 01811, Republic of Korea
| | - Youngja Hwang
- Metabolomics Laboratory, College of Pharmacy, Korea University, Sejong City 30019, Republic of Korea
| | - Sangkyu Lee
- BK21 Plus KNU Multi-Omics Based Creative Drug Research Team, College of Pharmacy, Research Institute of Pharmaceutical Sciences, Kyungpook National University, Daegu 41566, Republic of Korea; Mass Spectrometry Based Convergence Research Institute, Kyungpook National University, Daegu 41566, Republic of Korea
| | - Dong Young Rhyu
- Department of Biomedicine, Health & Life Convergence Sciences, BK21 FOUR, Mokpo National University, Jeonnam 58554, Republic of Korea
| | - Ki-Tae Kim
- Department of Environmental Engineering, Seoul National University of Science and Technology, Seoul 01811, Republic of Korea.
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23
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Dorgan JF, Ryan AS, LeBlanc ES, Van Horn L, Magder LS, Snetselaar LG, Zhang Y, Dallal CM, Jung S, Shepherd JA. A comparison of associations of body mass index and dual-energy x-ray absorptiometry measured percentage fat and total fat with global serum metabolites in young women. Obesity (Silver Spring) 2023; 31:525-536. [PMID: 36642094 PMCID: PMC9937438 DOI: 10.1002/oby.23619] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Revised: 09/21/2022] [Accepted: 09/23/2022] [Indexed: 01/17/2023]
Abstract
OBJECTIVE Body mass index (BMI) does not directly measure adiposity, whereas dual-energy x-ray absorptiometry (DXA) provides valid direct estimates of adiposity. Therefore, this study evaluated usefulness of BMI as a measure of adiposity in serum metabolomics studies. METHODS A cross-sectional analysis was conducted of 202 women aged 25 to 29 years in the Dietary Intervention Study in Children Follow-Up Study. Heights and weights were measured, and body composition was quantified using clinical DXA protocols. Serum metabolomic profiling was performed by liquid chromatography-tandem mass spectrometry. Partial correlations of BMI, percentage fat (%FAT), and total fat (TOTFAT) with log transformed serum metabolites were calculated. RESULTS There was significant overlap in the 93 metabolites that correlated with BMI, %FAT, and/or TOTFAT; 9 differently correlated with BMI and %FAT, whereas 15 differently correlated with BMI and TOTFAT. Even for these metabolites, absolute differences were modest. Metabolite set enrichment analysis identified diacylglycerol and sphingolipid metabolism as overrepresented among metabolites significantly correlated with all three measures of adiposity. CONCLUSIONS BMI can be a good proxy for DXA measured %FAT and TOTFAT in descriptive metabolomic studies of healthy, young White women. Larger studies in more diverse populations are needed to endorse more generalized conclusions.
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Affiliation(s)
- Joanne F Dorgan
- Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Alice S Ryan
- Department of Medicine, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Erin S LeBlanc
- Kaiser Permanente Center for Health Research, Portland, Oregon, USA
| | - Linda Van Horn
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Laurence S Magder
- Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Linda G Snetselaar
- Department of Epidemiology, University of Iowa College of Public Health, Iowa City, Iowa, USA
| | - Yuji Zhang
- Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Cher M Dallal
- Department of Epidemiology and Biostatistics, University of Maryland School of Public Health, College Park, Maryland, USA
| | - Seungyoun Jung
- Department of Nutritional Science & Food Management, Ewha Womans University, Seoul, South Korea
- Graduate Program in System Health Science & Engineering, Ewha Womans University, Seoul, South Korea
| | - John A Shepherd
- Department of Nutritional Sciences, University of Hawaii at Manoa, Honolulu, Hawaii, USA
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24
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Liu Y, Gan L, Zhao B, Yu K, Wang Y, Männistö S, Weinstein SJ, Huang J, Albanes D. Untargeted metabolomic profiling identifies serum metabolites associated with type 2 diabetes in a cross-sectional study of the Alpha-Tocopherol, Beta-Carotene Cancer Prevention (ATBC) Study. Am J Physiol Endocrinol Metab 2023; 324:E167-E175. [PMID: 36516224 PMCID: PMC9925157 DOI: 10.1152/ajpendo.00287.2022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 12/07/2022] [Accepted: 12/10/2022] [Indexed: 12/15/2022]
Abstract
Type 2 diabetes (T2D) is a complex chronic disease with substantial phenotypic heterogeneity affecting millions of individuals. Yet, its relevant metabolites and etiological pathways are not fully understood. The aim of this study is to assess a broad spectrum of metabolites related to T2D in a large population-based cohort. We conducted a metabolomic analysis of 4,281 male participants within the Alpha-Tocopherol, Beta-Carotene Cancer Prevention (ATBC) Study. The serum metabolomic analysis was performed using an LC-MS/GC-MS platform. Associations between 1,413 metabolites and T2D were examined using linear regression, controlling for important baseline risk factors. Standardized β-coefficients and standard errors (SEs) were computed to estimate the difference in metabolite concentrations. We identified 74 metabolites that were significantly associated with T2D based on the Bonferroni-corrected threshold (P < 3.5 × 10-5). The strongest signals associated with T2D were of carbohydrates origin, including glucose, 1,5-anhydroglucitol (1,5-AG), and mannose (β = 0.34, -0.91, and 0.41, respectively; all P < 10-75). We found several chemical class pathways that were significantly associated with T2D, including carbohydrates (P = 1.3 × 10-11), amino acids (P = 2.7 × 10-6), energy (P = 1.5 × 10-4), and xenobiotics (P = 1.2 × 10-3). The strongest subpathway associations were seen for fructose-mannose-galactose metabolism, glycolysis-gluconeogenesis-pyruvate metabolism, fatty acid metabolism (acyl choline), and leucine-isoleucine-valine metabolism (all P < 10-8). Our findings identified various metabolites and candidate chemical class pathways that can be characterized by glycolysis and gluconeogenesis metabolism, fructose-mannose-galactose metabolism, branched-chain amino acids, diacylglycerol, acyl cholines, fatty acid oxidation, and mitochondrial dysfunction.NEW & NOTEWORTHY These metabolomic patterns may provide new additional evidence and potential insights relevant to the molecular basis of insulin resistance and the etiology of T2D.
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Affiliation(s)
- Yuzhao Liu
- Department of Endocrinology, Affiliated Hospital of Qingdao University, Qingdao, China
| | - Lu Gan
- National Clinical Research Center for Metabolic Diseases, Metabolic Syndrome Research Center, Key Laboratory of Diabetes Immunology, Ministry of Education, and Department of Metabolism and Endocrinology, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Bin Zhao
- National Clinical Research Center for Metabolic Diseases, Metabolic Syndrome Research Center, Key Laboratory of Diabetes Immunology, Ministry of Education, and Department of Metabolism and Endocrinology, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Kai Yu
- Division of Cancer Epidemiology and Genetics, Department of Health and Human Services, National Cancer Institute, NIH, Bethesda, Maryland
| | - Yangang Wang
- Department of Endocrinology, Affiliated Hospital of Qingdao University, Qingdao, China
| | - Satu Männistö
- Department of Public Health Solutions, National Institute for Health and Welfare, Helsinki, Finland
| | - Stephanie J Weinstein
- Division of Cancer Epidemiology and Genetics, Department of Health and Human Services, National Cancer Institute, NIH, Bethesda, Maryland
| | - Jiaqi Huang
- National Clinical Research Center for Metabolic Diseases, Metabolic Syndrome Research Center, Key Laboratory of Diabetes Immunology, Ministry of Education, and Department of Metabolism and Endocrinology, The Second Xiangya Hospital of Central South University, Changsha, China
- Xiangya School of Public Health, Central South University, Changsha, China
| | - Demetrius Albanes
- Division of Cancer Epidemiology and Genetics, Department of Health and Human Services, National Cancer Institute, NIH, Bethesda, Maryland
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25
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Zhou Y, Zeng Y, Pan Z, Jin Y, Li Q, Pang J, Wang X, Chen Y, Yang Y, Ling W. A Randomized Trial on Resveratrol Supplement Affecting Lipid Profile and Other Metabolic Markers in Subjects with Dyslipidemia. Nutrients 2023; 15:nu15030492. [PMID: 36771199 PMCID: PMC9921501 DOI: 10.3390/nu15030492] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2022] [Revised: 01/13/2023] [Accepted: 01/14/2023] [Indexed: 01/19/2023] Open
Abstract
Resveratrol is a polyphenol with a well-established beneficial effect on dyslipidemia and hyperuricemia in preclinical experiments. Nonetheless, its efficacy and dose-response relationship in clinical trials remains unclear. This study examined whether resveratrol supplement improves the serum lipid profile and other metabolic markers in a dose-response manner in individuals with dyslipidemia. A total of 168 subjects were randomly assigned to placebo (n = 43) and resveratrol treatment groups of 100 mg/d (n = 41), 300 mg/d (n = 43), and 600 mg/d (n = 41). Anthropometric and biochemical parameters were analyzed at baseline and 4 and 8 weeks. Resveratrol supplementation for 8 weeks did not significantly change the lipid profile compared with the placebo. However, a significant decrease of serum uric acid was observed at 8 weeks in 300 mg/d (-23.60 ± 61.53 μmol/L, p < 0.05) and 600 mg/d resveratrol groups (-24.37 ± 64.24 μmol/L, p < 0.01) compared to placebo (8.19 ± 44.60 μmol/L). Furthermore, xanthine oxidase (XO) activity decreased significantly in the 600 mg/d resveratrol group (-0.09 ± 0.29 U/mL, p < 0.05) compared with placebo (0.03 ± 0.20 U/mL) after 8 weeks. The reduction of uric acid and XO activity exhibited a dose-response relationship (p for trend, <0.05). Furthermore, a marked correlation was found between the changes in uric acid and XO activity in the resveratrol groups (r = 0.254, p < 0.01). Resveratrol (10 μmol/L) treatment to HepG2 cells significantly reduced the uric acid levels and intracellular XO activity. Nevertheless, we failed to detect significant differences in glucose, insulin, or oxidative stress biomarkers between the resveratrol groups and placebo. In conclusion, resveratrol supplementation for 8 weeks had no significant effect on lipid profile but decreased uric acid in a dose-response manner, possibly due to XO inhibition in subjects with dyslipidemia. The trial was registered on ClinicalTrials.gov (NCT04886297).
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Affiliation(s)
- Yuqing Zhou
- Department of Nutrition, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
- Guangdong Provincial Key Laboratory of Food, Nutrition and Health, Guangzhou 510080, China
| | - Yupeng Zeng
- Department of Nutrition, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
- Guangdong Provincial Key Laboratory of Food, Nutrition and Health, Guangzhou 510080, China
| | - Zhijun Pan
- Department of Nutrition, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
- Guangdong Provincial Key Laboratory of Food, Nutrition and Health, Guangzhou 510080, China
| | - Yufeng Jin
- Department of Nutrition, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
- Guangdong Provincial Key Laboratory of Food, Nutrition and Health, Guangzhou 510080, China
| | - Qing Li
- Department of Nutrition, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
- Guangdong Provincial Key Laboratory of Food, Nutrition and Health, Guangzhou 510080, China
| | - Juan Pang
- Department of Nutrition, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
- Guangdong Provincial Key Laboratory of Food, Nutrition and Health, Guangzhou 510080, China
| | - Xin Wang
- Department of Nutrition, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
- Guangdong Provincial Key Laboratory of Food, Nutrition and Health, Guangzhou 510080, China
| | - Yu Chen
- Department of Nutrition, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
- Guangdong Provincial Key Laboratory of Food, Nutrition and Health, Guangzhou 510080, China
| | - Yan Yang
- Guangdong Provincial Key Laboratory of Food, Nutrition and Health, Guangzhou 510080, China
- Guangdong Engineering Technology Center of Nutrition Transformation, Guangzhou 510080, China
- Department of Nutrition, School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen 518107, China
- Correspondence: (Y.Y.); (W.L.)
| | - Wenhua Ling
- Department of Nutrition, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
- Guangdong Provincial Key Laboratory of Food, Nutrition and Health, Guangzhou 510080, China
- Guangdong Engineering Technology Center of Nutrition Transformation, Guangzhou 510080, China
- Correspondence: (Y.Y.); (W.L.)
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26
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Hasken JM, de Vries MM, Marais AS, May PA, Parry CDH, Seedat S, Mooney SM, Smith SM. Untargeted Metabolome Analysis of Alcohol-Exposed Pregnancies Reveals Metabolite Differences That Are Associated with Infant Birth Outcomes. Nutrients 2022; 14:nu14245367. [PMID: 36558526 PMCID: PMC9786146 DOI: 10.3390/nu14245367] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Revised: 12/06/2022] [Accepted: 12/14/2022] [Indexed: 12/23/2022] Open
Abstract
Prenatal alcohol exposure can produce offspring growth deficits and is a leading cause of neurodevelopmental disability. We used untargeted metabolomics to generate mechanistic insight into how alcohol impairs fetal development. In the Western Cape Province of South Africa, 52 women between gestational weeks 5-36 (mean 18.5 ± 6.5) were recruited, and they provided a finger-prick fasting bloodspot that underwent mass spectrometry. Metabolomic data were analyzed using partial least squares-discriminant analyses (PLS-DA) to identify metabolites that correlated with alcohol exposure and infant birth outcomes. Women who consumed alcohol in the past seven days were distinguished by a metabolite profile that included reduced sphingomyelins, cholesterol, and pregnenolones, and elevated fatty acids, acyl and amino acyl carnitines, and androsterones. Using PLS-DA, 25 of the top 30 metabolites differentiating maternal groups were reduced by alcohol with medium-chain free fatty acids and oxidized sugar derivatives having the greatest influence. A separate ortho-PLS-DA analysis identified a common set of 13 metabolites that were associated with infant length, weight, and head circumference. These included monoacylglycerols, glycerol-3-phosphate, and unidentified metabolites, and most of their associations were negative, implying they represent processes having adverse consequences for fetal development.
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Affiliation(s)
- Julie M. Hasken
- Nutrition Research Institute, University of North Carolina at Chapel Hill, Kannapolis, NC 28081, USA
- Correspondence: ; Tel.: +1-(704)-250-5002
| | - Marlene M. de Vries
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Tygerberg 7602, South Africa
| | - Anna-Susan Marais
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Tygerberg 7602, South Africa
| | - Philip A. May
- Nutrition Research Institute, University of North Carolina at Chapel Hill, Kannapolis, NC 28081, USA
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Tygerberg 7602, South Africa
- Department of Nutrition, University of North Carolina at Chapel Hill, Kannapolis, NC 28081, USA
- Center on Alcohol, Substance Abuse, and Addictions, University of New Mexico, Albuquerque, NM 87131, USA
| | - Charles D. H. Parry
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Tygerberg 7602, South Africa
- Alcohol, Tobacco, and Other Drug Research Unit, South African Medical Research Council, Cape Town 7760, South Africa
| | - Soraya Seedat
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Tygerberg 7602, South Africa
| | - Sandra M. Mooney
- Nutrition Research Institute, University of North Carolina at Chapel Hill, Kannapolis, NC 28081, USA
- Department of Nutrition, University of North Carolina at Chapel Hill, Kannapolis, NC 28081, USA
| | - Susan M. Smith
- Nutrition Research Institute, University of North Carolina at Chapel Hill, Kannapolis, NC 28081, USA
- Department of Nutrition, University of North Carolina at Chapel Hill, Kannapolis, NC 28081, USA
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Amino Acids Metabolism in Retinopathy: From Clinical and Basic Research Perspective. Metabolites 2022; 12:metabo12121244. [PMID: 36557282 PMCID: PMC9781488 DOI: 10.3390/metabo12121244] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Revised: 11/22/2022] [Accepted: 12/06/2022] [Indexed: 12/14/2022] Open
Abstract
Retinopathy, including age-related macular degeneration (AMD), diabetic retinopathy (DR), and retinopathy of prematurity (ROP), are the leading cause of blindness among seniors, working-age populations, and children. However, the pathophysiology of retinopathy remains unclear. Accumulating studies demonstrate that amino acid metabolism is associated with retinopathy. This study discusses the characterization of amino acids in DR, AMD, and ROP by metabolomics from clinical and basic research perspectives. The features of amino acids in retinopathy were summarized using a comparative approach based on existing high-throughput metabolomics studies from PubMed. Besides taking up a large proportion, amino acids appear in both human and animal, intraocular and peripheral samples. Among them, some metabolites differ significantly in all three types of retinopathy, including glutamine, glutamate, alanine, and others. Studies on the mechanisms behind retinal cell death caused by glutamate accumulation are on the verge of making some progress. To develop potential therapeutics, it is imperative to understand amino acid-induced retinal functional alterations and the underlying mechanisms. This review delineates the significance of amino acid metabolism in retinopathy and provides possible direction to discover therapeutic targets for retinopathy.
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Jian Q, Wu Y, Zhang F. Metabolomics in Diabetic Retinopathy: From Potential Biomarkers to Molecular Basis of Oxidative Stress. Cells 2022; 11:cells11193005. [PMID: 36230967 PMCID: PMC9563658 DOI: 10.3390/cells11193005] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2022] [Accepted: 09/22/2022] [Indexed: 11/18/2022] Open
Abstract
Diabetic retinopathy (DR), the leading cause of blindness in working-age adults, is one of the most common complications of diabetes mellitus (DM) featured by metabolic disorders. With the global prevalence of diabetes, the incidence of DR is expected to increase. Prompt detection and the targeting of anti-oxidative stress intervention could effectively reduce visual impairment caused by DR. However, the diagnosis and treatment of DR is often delayed due to the absence of obvious signs of retina imaging. Research progress supports that metabolomics is a powerful tool to discover potential diagnostic biomarkers and therapeutic targets for the causes of oxidative stress through profiling metabolites in diseases, which provides great opportunities for DR with metabolic heterogeneity. Thus, this review summarizes the latest advances in metabolomics in DR, as well as potential diagnostic biomarkers, and predicts molecular targets through the integration of genome-wide association studies (GWAS) with metabolomics. Metabolomics provides potential biomarkers, molecular targets and therapeutic strategies for controlling the progress of DR, especially the interventions at early stages and precise treatments based on individual patient variations.
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Affiliation(s)
- Qizhi Jian
- National Clinical Research Center for Eye Diseases, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200080, China
- Shanghai Key Laboratory of Ocular Fundus Diseases, Shanghai 200080, China
- Shanghai Engineering Center for Visual Science and Photomedicine, Shanghai 200080, China
- Shanghai Engineering Center for Precise Diagnosis and Treatment of Eye Diseases, Shanghai 200080, China
| | - Yingjie Wu
- Institute for Genome Engineered Animal Models of Human Diseases, National Center of Genetically Engineered Animal Models for International Research, Liaoning Provence Key Laboratory of Genome Engineered Animal Models, Dalian Medical University, Dalian 116000, China
- Shandong Provincial Hospital, School of Laboratory Animal & Shandong Laboratory Animal Center, Science and Technology Innovation Center, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan 250021, China
- Department of Molecular Pathobiology, New York University College of Dentistry, New York, NY 10010, USA
- Correspondence: (Y.W.); (F.Z.)
| | - Fang Zhang
- National Clinical Research Center for Eye Diseases, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200080, China
- Shanghai Key Laboratory of Ocular Fundus Diseases, Shanghai 200080, China
- Shanghai Engineering Center for Visual Science and Photomedicine, Shanghai 200080, China
- Shanghai Engineering Center for Precise Diagnosis and Treatment of Eye Diseases, Shanghai 200080, China
- Correspondence: (Y.W.); (F.Z.)
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Weinisch P, Fiamoncini J, Schranner D, Raffler J, Skurk T, Rist MJ, Römisch-Margl W, Prehn C, Adamski J, Hauner H, Daniel H, Suhre K, Kastenmüller G. Dynamic patterns of postprandial metabolic responses to three dietary challenges. Front Nutr 2022; 9:933526. [PMID: 36211489 PMCID: PMC9540193 DOI: 10.3389/fnut.2022.933526] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2022] [Accepted: 08/01/2022] [Indexed: 11/13/2022] Open
Abstract
Food intake triggers extensive changes in the blood metabolome. The kinetics of these changes depend on meal composition and on intrinsic, health-related characteristics of each individual, making the assessment of changes in the postprandial metabolome an opportunity to assess someone's metabolic status. To enable the usage of dietary challenges as diagnostic tools, profound knowledge about changes that occur in the postprandial period in healthy individuals is needed. In this study, we characterize the time-resolved changes in plasma levels of 634 metabolites in response to an oral glucose tolerance test (OGTT), an oral lipid tolerance test (OLTT), and a mixed meal (SLD) in healthy young males (n = 15). Metabolite levels for samples taken at different time points (20 per individual) during the challenges were available from targeted (132 metabolites) and non-targeted (502 metabolites) metabolomics. Almost half of the profiled metabolites (n = 308) showed a significant change in at least one challenge, thereof 111 metabolites responded exclusively to one particular challenge. Examples include azelate, which is linked to ω-oxidation and increased only in OLTT, and a fibrinogen cleavage peptide that has been linked to a higher risk of cardiovascular events in diabetes patients and increased only in OGTT, making its postprandial dynamics a potential target for risk management. A pool of 89 metabolites changed their plasma levels during all three challenges and represents the core postprandial response to food intake regardless of macronutrient composition. We used fuzzy c-means clustering to group these metabolites into eight clusters based on commonalities of their dynamic response patterns, with each cluster following one of four primary response patterns: (i) “decrease-increase” (valley-like) with fatty acids and acylcarnitines indicating the suppression of lipolysis, (ii) “increase-decrease” (mountain-like) including a cluster of conjugated bile acids and the glucose/insulin cluster, (iii) “steady decrease” with metabolites reflecting a carryover from meals prior to the study, and (iv) “mixed” decreasing after the glucose challenge and increasing otherwise. Despite the small number of subjects, the diversity of the challenges and the wealth of metabolomic data make this study an important step toward the characterization of postprandial responses and the identification of markers of metabolic processes regulated by food intake.
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Affiliation(s)
- Patrick Weinisch
- Institute of Computational Biology, Helmholtz Zentrum München, Neuherberg, Germany
| | - Jarlei Fiamoncini
- Food Research Center – FoRC, Department of Food Science and Experimental Nutrition, School of Pharmaceutical Sciences, University of São Paulo, São Paulo, Brazil
| | - Daniela Schranner
- Institute of Computational Biology, Helmholtz Zentrum München, Neuherberg, Germany
| | - Johannes Raffler
- Institute of Computational Biology, Helmholtz Zentrum München, Neuherberg, Germany
- Digital Medicine, University Hospital of Augsburg, Augsburg, Germany
| | - Thomas Skurk
- Core Facility Human Studies, ZIEL Institute for Food and Health, Technical University of Munich, Freising, Germany
- Else Kröner Fresenius Center for Nutritional Medicine, School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Manuela J. Rist
- Department of Physiology and Biochemistry of Nutrition, Max Rubner-Institut, Karlsruhe, Germany
| | - Werner Römisch-Margl
- Institute of Computational Biology, Helmholtz Zentrum München, Neuherberg, Germany
| | - Cornelia Prehn
- Metabolomics and Proteomics Core, Helmholtz Zentrum München, Neuherberg, Germany
| | - Jerzy Adamski
- Institute of Experimental Genetics, Helmholtz Zentrum München, Neuherberg, Germany
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Institute of Biochemistry, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Hans Hauner
- Else Kröner Fresenius Center for Nutritional Medicine, School of Life Sciences, Technical University of Munich, Freising, Germany
- Institute for Nutritional Medicine, School of Medicine, Technical University of Munich, Munich, Germany
| | - Hannelore Daniel
- Department of Food and Nutrition, Technical University of Munich, Freising, Germany
| | - Karsten Suhre
- Department of Biophysics and Physiology, Weill Cornell Medicine—Qatar, Doha, Qatar
| | - Gabi Kastenmüller
- Institute of Computational Biology, Helmholtz Zentrum München, Neuherberg, Germany
- *Correspondence: Gabi Kastenmüller
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30
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Lv Q, Li Z, Sui A, Yang X, Han Y, Yao R. The role and mechanisms of gut microbiota in diabetic nephropathy, diabetic retinopathy and cardiovascular diseases. Front Microbiol 2022; 13:977187. [PMID: 36060752 PMCID: PMC9433831 DOI: 10.3389/fmicb.2022.977187] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Accepted: 07/28/2022] [Indexed: 11/26/2022] Open
Abstract
Type 2 diabetes mellitus (T2DM) and T2DM-related complications [such as retinopathy, nephropathy, and cardiovascular diseases (CVDs)] are the most prevalent metabolic diseases. Intriguingly, overwhelming findings have shown a strong association of the gut microbiome with the etiology of these diseases, including the role of aberrant gut bacterial metabolites, increased intestinal permeability, and pathogenic immune function affecting host metabolism. Thus, deciphering the specific microbiota, metabolites, and the related mechanisms to T2DM-related complications by combined analyses of metagenomics and metabolomics data can lead to an innovative strategy for the treatment of these diseases. Accordingly, this review highlights the advanced knowledge about the characteristics of the gut microbiota in T2DM-related complications and how it can be associated with the pathogenesis of these diseases. Also, recent studies providing a new perspective on microbiota-targeted therapies are included.
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31
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Novel Plasma Metabolomic Markers Associated with Diabetes Progression in Older Puerto Ricans. Metabolites 2022; 12:metabo12060513. [PMID: 35736445 PMCID: PMC9227184 DOI: 10.3390/metabo12060513] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2022] [Accepted: 05/25/2022] [Indexed: 11/30/2022] Open
Abstract
We assessed longitudinal associations between plasma metabolites, their network-derived clusters, and type 2 diabetes (T2D) progression in Puerto Rican adults, a high-risk Hispanic subgroup with established health disparities. We used data from 1221 participants free of T2D and aged 40–75 years at baseline in the Boston Puerto Rican Health and San Juan Overweight Adult Longitudinal Studies. We used multivariable Poisson regression models to examine associations between baseline concentrations of metabolites and incident T2D and prediabetes. Cohort-specific estimates were combined using inverse-variance weighted fixed-effects meta-analyses. A cluster of 13 metabolites of branched chain amino acids (BCAA), and aromatic amino acid metabolism (pooled IRR = 1.87, 95% CI: 1.28; 2.73), and a cell membrane component metabolite cluster (pooled IRR = 1.54, 95% CI: 1.04; 2.27) were associated with a higher risk of incident T2D. When the metabolites were tested individually, in combined analysis, 5 metabolites involved in BCAA metabolism were associated with incident T2D. These findings highlight potential prognostic biomarkers to identify Puerto Rican adults who may be at high risk for diabetes. Future studies should examine whether diet and lifestyle can modify the associations between these metabolites and progression to T2D.
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32
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Lind L, Salihovic S, Sundström J, Elmståhl S, Hammar U, Dekkers K, Ärnlöv J, Smith JG, Engström G, Fall T. Metabolic Profiling of Obesity With and Without the Metabolic Syndrome: A Multisample Evaluation. J Clin Endocrinol Metab 2022; 107:1337-1345. [PMID: 34984454 DOI: 10.1210/clinem/dgab922] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/21/2021] [Indexed: 12/31/2022]
Abstract
CONTEXT There is a dispute whether obesity without major metabolic derangements may represent a benign condition or not. OBJECTIVE We aimed to compare the plasma metabolome in obese subjects without metabolic syndrome (MetS) with normal-weight subjects without MetS and with obese subjects with MetS. METHODS This was a cross-sectional study at 2 academic centers in Sweden. Individuals from 3 population-based samples (EpiHealth, n = 2342, SCAPIS-Uppsala, n = 4985, and SCAPIS-Malmö, n = 3978) were divided into groups according to their body mass index (BMI) and presence/absence of MetS (National Cholesterol Education Program [NCEP]/consensus criteria). In total, 791 annotated endogenous metabolites were measured by ultra-performance liquid chromatography-tandem mass spectrometry. RESULTS We observed major differences in metabolite profiles (427 metabolites) between obese (BMI ≥ 30 kg/m2) and normal-weight (BMI < 25 kg/m2) subjects without MetS after adjustment for major lifestyle factors. Pathway enrichment analysis highlighted branch-chained and aromatic amino acid synthesis/metabolism, aminoacyl-tRNA biosynthesis, and sphingolipid metabolism. The same pathways, and similar metabolites, were also highlighted when obese subjects with and without MetS were compared despite adjustment for BMI and waist circumference, or when the metabolites were related to BMI and number of MetS components in a continuous fashion. Similar metabolites and pathways were also related to insulin sensitivity (Matsuda index) in a separate study (POEM, n = 501). CONCLUSION Our data suggest a graded derangement of the circulating metabolite profile from lean to obese to MetS, in particular for metabolites involved in amino acid synthesis/metabolism and sphingolipid metabolism. Insulin resistance is a plausible mediator of this gradual metabolic deterioration.
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Affiliation(s)
- Lars Lind
- Department of Medical Sciences, Uppsala University, Sweden
| | - Samira Salihovic
- Inflammatory Response and Infection Susceptibility Centre, School of Medical Sciences, Örebro University, Örebro, Sweden
| | | | - Sölve Elmståhl
- Department of Clinical Sciences, Division of Geriatric Medicine, Lund University, Malmö University Hospital, Malmö, Sweden
| | - Ulf Hammar
- Department of Medical Sciences, Uppsala University, Sweden
| | - Koen Dekkers
- Department of Medical Sciences, Uppsala University, Sweden
| | - Johan Ärnlöv
- Division of Family Medicine and Primary Care, Department of Neurobiology, Care Science and Society, Karolinska Institutet, Huddinge, Sweden
- School of Health and Social Studies, Dalarna University, Falun, Sweden
| | - J Gustav Smith
- Department of Cardiology, Clinical Sciences, Lund University and Skåne University Hospital , Lund, Sweden
- The Wallenberg Laboratory/Department of Molecular and Clinical Medicine, Institute of Medicine, Gothenburg University and the Department of Cardiology, Sahlgrenska University Hospital, Gothenburg, Sweden
- Wallenberg Center for Molecular Medicine and Lund University Diabetes Center, Lund University, Lund, Sweden
| | - Gunnar Engström
- Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Tove Fall
- Department of Medical Sciences, Uppsala University, Sweden
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