Reference Citation Analysis: Find an Article, Find a Category, Find a Journal, Find a Scholar

For: Omori K, Katakami N, Arakawa S, Yamamoto Y, Ninomiya H, Takahara M, Matsuoka TA, Tsugawa H, Furuno M, Bamba T, Fukusaki E, Shimomura I. Identification of Plasma Inositol and Indoxyl Sulfate as Novel Biomarker Candidates for Atherosclerosis in Patients with Type 2 Diabetes. -Findings from Metabolome Analysis Using GC/MS. J Atheroscler Thromb 2020;27:1053-1067. [PMID: 31983701 PMCID: PMC7585911 DOI: 10.5551/jat.52506] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2019] [Accepted: 12/08/2019] [Indexed: 12/29/2022] Open

For:	Omori K, Katakami N, Arakawa S, Yamamoto Y, Ninomiya H, Takahara M, Matsuoka TA, Tsugawa H, Furuno M, Bamba T, Fukusaki E, Shimomura I. Identification of Plasma Inositol and Indoxyl Sulfate as Novel Biomarker Candidates for Atherosclerosis in Patients with Type 2 Diabetes. -Findings from Metabolome Analysis Using GC/MS. J Atheroscler Thromb 2020;27:1053-1067. [PMID: 31983701 PMCID: PMC7585911 DOI: 10.5551/jat.52506] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2019] [Accepted: 12/08/2019] [Indexed: 12/29/2022] Open

Number

Cited by Other Article(s)

Mueller JW, Thomas P, Dalgaard LT, da Silva Xavier G. Sulfation pathways in the maintenance of functional beta-cell mass and implications for diabetes. Essays Biochem 2024;68:509-522. [PMID: 39290144 PMCID: PMC11625869 DOI: 10.1042/ebc20240034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2024] [Revised: 08/21/2024] [Accepted: 09/02/2024] [Indexed: 09/19/2024]

Shafiee S, Dastmalchi S, Gharekhani A, Shayanfar A. Analysis of indoxyl sulfate in biological fluids with emphasis on sample preparation techniques: A comprehensive analytical review. Heliyon 2024;10:e35032. [PMID: 39157307 PMCID: PMC11328088 DOI: 10.1016/j.heliyon.2024.e35032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Revised: 07/16/2024] [Accepted: 07/22/2024] [Indexed: 08/20/2024] Open

Peñalver R, Pérez-Álvarez MD, Arroyo-Manzanares N, Campillo N, Viñas P. Determination of extractable pollutants from microplastics to vegetables: Accumulation and incorporation into the food chain. CHEMOSPHERE 2023;341:140141. [PMID: 37696477 DOI: 10.1016/j.chemosphere.2023.140141] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/20/2022] [Revised: 02/13/2023] [Accepted: 09/09/2023] [Indexed: 09/13/2023]

Liu C, Ge P, Zeng C, Yu X, Zhai Y, Liu W, He Q, Li J, Liu X, Wang J, Ye X, Zhang Q, Wang R, Zhang Y, Zhao J, Zhang D. Correlation of Serum N-Acetylneuraminic Acid with the Risk of Moyamoya Disease. Brain Sci 2023;13:913. [PMID: 37371391 PMCID: PMC10296217 DOI: 10.3390/brainsci13060913] [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: 04/23/2023] [Revised: 05/28/2023] [Accepted: 06/02/2023] [Indexed: 06/29/2023] Open

Affiliation(s)

Chenglong Liu Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, 119 South Fourth Ring West Road, Fengtai District, Beijing 100070, China; (C.L.); (P.G.); (C.Z.); (X.Y.); (Y.Z.); (W.L.); (Q.H.); (J.L.); (X.L.); (J.W.); (X.Y.); (Q.Z.); (R.W.); (Y.Z.) China National Clinical Research Center for Neurological Diseases, Beijing 100070, China Center of Stroke, Beijing Institute for Brain Disorders, Beijing 100070, China Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, Beijing 100070, China Beijing Translational Engineering Center for 3D Printer in Clinical Neuroscience, Beijing 100070, China
Peicong Ge Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, 119 South Fourth Ring West Road, Fengtai District, Beijing 100070, China; (C.L.); (P.G.); (C.Z.); (X.Y.); (Y.Z.); (W.L.); (Q.H.); (J.L.); (X.L.); (J.W.); (X.Y.); (Q.Z.); (R.W.); (Y.Z.) China National Clinical Research Center for Neurological Diseases, Beijing 100070, China Center of Stroke, Beijing Institute for Brain Disorders, Beijing 100070, China Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, Beijing 100070, China Beijing Translational Engineering Center for 3D Printer in Clinical Neuroscience, Beijing 100070, China
Chaofan Zeng Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, 119 South Fourth Ring West Road, Fengtai District, Beijing 100070, China; (C.L.); (P.G.); (C.Z.); (X.Y.); (Y.Z.); (W.L.); (Q.H.); (J.L.); (X.L.); (J.W.); (X.Y.); (Q.Z.); (R.W.); (Y.Z.) China National Clinical Research Center for Neurological Diseases, Beijing 100070, China Center of Stroke, Beijing Institute for Brain Disorders, Beijing 100070, China Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, Beijing 100070, China Beijing Translational Engineering Center for 3D Printer in Clinical Neuroscience, Beijing 100070, China
Xiaofan Yu Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, 119 South Fourth Ring West Road, Fengtai District, Beijing 100070, China; (C.L.); (P.G.); (C.Z.); (X.Y.); (Y.Z.); (W.L.); (Q.H.); (J.L.); (X.L.); (J.W.); (X.Y.); (Q.Z.); (R.W.); (Y.Z.) China National Clinical Research Center for Neurological Diseases, Beijing 100070, China Center of Stroke, Beijing Institute for Brain Disorders, Beijing 100070, China Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, Beijing 100070, China Beijing Translational Engineering Center for 3D Printer in Clinical Neuroscience, Beijing 100070, China
Yuanren Zhai Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, 119 South Fourth Ring West Road, Fengtai District, Beijing 100070, China; (C.L.); (P.G.); (C.Z.); (X.Y.); (Y.Z.); (W.L.); (Q.H.); (J.L.); (X.L.); (J.W.); (X.Y.); (Q.Z.); (R.W.); (Y.Z.) China National Clinical Research Center for Neurological Diseases, Beijing 100070, China Center of Stroke, Beijing Institute for Brain Disorders, Beijing 100070, China Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, Beijing 100070, China Beijing Translational Engineering Center for 3D Printer in Clinical Neuroscience, Beijing 100070, China
Wei Liu Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, 119 South Fourth Ring West Road, Fengtai District, Beijing 100070, China; (C.L.); (P.G.); (C.Z.); (X.Y.); (Y.Z.); (W.L.); (Q.H.); (J.L.); (X.L.); (J.W.); (X.Y.); (Q.Z.); (R.W.); (Y.Z.) China National Clinical Research Center for Neurological Diseases, Beijing 100070, China Center of Stroke, Beijing Institute for Brain Disorders, Beijing 100070, China Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, Beijing 100070, China Beijing Translational Engineering Center for 3D Printer in Clinical Neuroscience, Beijing 100070, China
Qiheng He Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, 119 South Fourth Ring West Road, Fengtai District, Beijing 100070, China; (C.L.); (P.G.); (C.Z.); (X.Y.); (Y.Z.); (W.L.); (Q.H.); (J.L.); (X.L.); (J.W.); (X.Y.); (Q.Z.); (R.W.); (Y.Z.) China National Clinical Research Center for Neurological Diseases, Beijing 100070, China Center of Stroke, Beijing Institute for Brain Disorders, Beijing 100070, China Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, Beijing 100070, China Beijing Translational Engineering Center for 3D Printer in Clinical Neuroscience, Beijing 100070, China
Junsheng Li Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, 119 South Fourth Ring West Road, Fengtai District, Beijing 100070, China; (C.L.); (P.G.); (C.Z.); (X.Y.); (Y.Z.); (W.L.); (Q.H.); (J.L.); (X.L.); (J.W.); (X.Y.); (Q.Z.); (R.W.); (Y.Z.) China National Clinical Research Center for Neurological Diseases, Beijing 100070, China Center of Stroke, Beijing Institute for Brain Disorders, Beijing 100070, China Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, Beijing 100070, China Beijing Translational Engineering Center for 3D Printer in Clinical Neuroscience, Beijing 100070, China
Xingju Liu Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, 119 South Fourth Ring West Road, Fengtai District, Beijing 100070, China; (C.L.); (P.G.); (C.Z.); (X.Y.); (Y.Z.); (W.L.); (Q.H.); (J.L.); (X.L.); (J.W.); (X.Y.); (Q.Z.); (R.W.); (Y.Z.) China National Clinical Research Center for Neurological Diseases, Beijing 100070, China Center of Stroke, Beijing Institute for Brain Disorders, Beijing 100070, China Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, Beijing 100070, China Beijing Translational Engineering Center for 3D Printer in Clinical Neuroscience, Beijing 100070, China
Jia Wang Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, 119 South Fourth Ring West Road, Fengtai District, Beijing 100070, China; (C.L.); (P.G.); (C.Z.); (X.Y.); (Y.Z.); (W.L.); (Q.H.); (J.L.); (X.L.); (J.W.); (X.Y.); (Q.Z.); (R.W.); (Y.Z.) China National Clinical Research Center for Neurological Diseases, Beijing 100070, China Center of Stroke, Beijing Institute for Brain Disorders, Beijing 100070, China Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, Beijing 100070, China Beijing Translational Engineering Center for 3D Printer in Clinical Neuroscience, Beijing 100070, China
Xun Ye Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, 119 South Fourth Ring West Road, Fengtai District, Beijing 100070, China; (C.L.); (P.G.); (C.Z.); (X.Y.); (Y.Z.); (W.L.); (Q.H.); (J.L.); (X.L.); (J.W.); (X.Y.); (Q.Z.); (R.W.); (Y.Z.) China National Clinical Research Center for Neurological Diseases, Beijing 100070, China Center of Stroke, Beijing Institute for Brain Disorders, Beijing 100070, China Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, Beijing 100070, China Beijing Translational Engineering Center for 3D Printer in Clinical Neuroscience, Beijing 100070, China
Qian Zhang Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, 119 South Fourth Ring West Road, Fengtai District, Beijing 100070, China; (C.L.); (P.G.); (C.Z.); (X.Y.); (Y.Z.); (W.L.); (Q.H.); (J.L.); (X.L.); (J.W.); (X.Y.); (Q.Z.); (R.W.); (Y.Z.) China National Clinical Research Center for Neurological Diseases, Beijing 100070, China Center of Stroke, Beijing Institute for Brain Disorders, Beijing 100070, China Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, Beijing 100070, China Beijing Translational Engineering Center for 3D Printer in Clinical Neuroscience, Beijing 100070, China
Rong Wang Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, 119 South Fourth Ring West Road, Fengtai District, Beijing 100070, China; (C.L.); (P.G.); (C.Z.); (X.Y.); (Y.Z.); (W.L.); (Q.H.); (J.L.); (X.L.); (J.W.); (X.Y.); (Q.Z.); (R.W.); (Y.Z.) China National Clinical Research Center for Neurological Diseases, Beijing 100070, China Center of Stroke, Beijing Institute for Brain Disorders, Beijing 100070, China Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, Beijing 100070, China Beijing Translational Engineering Center for 3D Printer in Clinical Neuroscience, Beijing 100070, China
Yan Zhang Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, 119 South Fourth Ring West Road, Fengtai District, Beijing 100070, China; (C.L.); (P.G.); (C.Z.); (X.Y.); (Y.Z.); (W.L.); (Q.H.); (J.L.); (X.L.); (J.W.); (X.Y.); (Q.Z.); (R.W.); (Y.Z.) China National Clinical Research Center for Neurological Diseases, Beijing 100070, China Center of Stroke, Beijing Institute for Brain Disorders, Beijing 100070, China Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, Beijing 100070, China Beijing Translational Engineering Center for 3D Printer in Clinical Neuroscience, Beijing 100070, China
Jizong Zhao Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, 119 South Fourth Ring West Road, Fengtai District, Beijing 100070, China; (C.L.); (P.G.); (C.Z.); (X.Y.); (Y.Z.); (W.L.); (Q.H.); (J.L.); (X.L.); (J.W.); (X.Y.); (Q.Z.); (R.W.); (Y.Z.) China National Clinical Research Center for Neurological Diseases, Beijing 100070, China Center of Stroke, Beijing Institute for Brain Disorders, Beijing 100070, China Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, Beijing 100070, China Beijing Translational Engineering Center for 3D Printer in Clinical Neuroscience, Beijing 100070, China
Dong Zhang Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, 119 South Fourth Ring West Road, Fengtai District, Beijing 100070, China; (C.L.); (P.G.); (C.Z.); (X.Y.); (Y.Z.); (W.L.); (Q.H.); (J.L.); (X.L.); (J.W.); (X.Y.); (Q.Z.); (R.W.); (Y.Z.) China National Clinical Research Center for Neurological Diseases, Beijing 100070, China Center of Stroke, Beijing Institute for Brain Disorders, Beijing 100070, China Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, Beijing 100070, China Beijing Translational Engineering Center for 3D Printer in Clinical Neuroscience, Beijing 100070, China Department of Neurosurgery, Beijing Hospital, Beijing 100730, China

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Sakanaka A, Katakami N, Furuno M, Nishizawa H, Omori K, Taya N, Ishikawa A, Mayumi S, Inoue M, Tanaka Isomura E, Amano A, Shimomura I, Fukusaki E, Kuboniwa M. Salivary metabolic signatures of carotid atherosclerosis in patients with type 2 diabetes hospitalized for treatment. Front Mol Biosci 2022;9:1074285. [PMID: 36619162 PMCID: PMC9815705 DOI: 10.3389/fmolb.2022.1074285] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Accepted: 11/28/2022] [Indexed: 12/24/2022] Open

Jiang T, Li Y, Li L, Liang T, Du M, Yang L, Yang J, Yang R, Zhao H, Chen M, Ding Y, Zhang J, Wang J, Xie X, Wu Q. Bifidobacterium longum 070103 Fermented Milk Improve Glucose and Lipid Metabolism Disorders by Regulating Gut Microbiota in Mice. Nutrients 2022;14:nu14194050. [PMID: 36235706 PMCID: PMC9573661 DOI: 10.3390/nu14194050] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Revised: 09/21/2022] [Accepted: 09/23/2022] [Indexed: 12/08/2022] Open

Affiliation(s)

Tong Jiang College of Food Science, South China Agricultural University, Guangzhou 510642, China Key Laboratory of Agricultural Microbiomics and Precision Application, Ministry of Agriculture and Rural Affairs, Guangdong Provincial Key Laboratory of Microbial Safety and Health, State Key Laboratory of Applied Microbiology Southern China, Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou 510070, China
Ying Li Key Laboratory of Agricultural Microbiomics and Precision Application, Ministry of Agriculture and Rural Affairs, Guangdong Provincial Key Laboratory of Microbial Safety and Health, State Key Laboratory of Applied Microbiology Southern China, Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou 510070, China
Longyan Li College of Food Science, South China Agricultural University, Guangzhou 510642, China Key Laboratory of Agricultural Microbiomics and Precision Application, Ministry of Agriculture and Rural Affairs, Guangdong Provincial Key Laboratory of Microbial Safety and Health, State Key Laboratory of Applied Microbiology Southern China, Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou 510070, China
Tingting Liang Key Laboratory of Agricultural Microbiomics and Precision Application, Ministry of Agriculture and Rural Affairs, Guangdong Provincial Key Laboratory of Microbial Safety and Health, State Key Laboratory of Applied Microbiology Southern China, Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou 510070, China
Mingzhu Du Key Laboratory of Agricultural Microbiomics and Precision Application, Ministry of Agriculture and Rural Affairs, Guangdong Provincial Key Laboratory of Microbial Safety and Health, State Key Laboratory of Applied Microbiology Southern China, Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou 510070, China
Lingshuang Yang College of Food Science, South China Agricultural University, Guangzhou 510642, China Key Laboratory of Agricultural Microbiomics and Precision Application, Ministry of Agriculture and Rural Affairs, Guangdong Provincial Key Laboratory of Microbial Safety and Health, State Key Laboratory of Applied Microbiology Southern China, Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou 510070, China
Juan Yang Key Laboratory of Agricultural Microbiomics and Precision Application, Ministry of Agriculture and Rural Affairs, Guangdong Provincial Key Laboratory of Microbial Safety and Health, State Key Laboratory of Applied Microbiology Southern China, Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou 510070, China
Runshi Yang Key Laboratory of Agricultural Microbiomics and Precision Application, Ministry of Agriculture and Rural Affairs, Guangdong Provincial Key Laboratory of Microbial Safety and Health, State Key Laboratory of Applied Microbiology Southern China, Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou 510070, China
Hui Zhao Key Laboratory of Agricultural Microbiomics and Precision Application, Ministry of Agriculture and Rural Affairs, Guangdong Provincial Key Laboratory of Microbial Safety and Health, State Key Laboratory of Applied Microbiology Southern China, Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou 510070, China
Moutong Chen Key Laboratory of Agricultural Microbiomics and Precision Application, Ministry of Agriculture and Rural Affairs, Guangdong Provincial Key Laboratory of Microbial Safety and Health, State Key Laboratory of Applied Microbiology Southern China, Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou 510070, China
Yu Ding Key Laboratory of Agricultural Microbiomics and Precision Application, Ministry of Agriculture and Rural Affairs, Guangdong Provincial Key Laboratory of Microbial Safety and Health, State Key Laboratory of Applied Microbiology Southern China, Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou 510070, China
Jumei Zhang Key Laboratory of Agricultural Microbiomics and Precision Application, Ministry of Agriculture and Rural Affairs, Guangdong Provincial Key Laboratory of Microbial Safety and Health, State Key Laboratory of Applied Microbiology Southern China, Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou 510070, China
Juan Wang College of Food Science, South China Agricultural University, Guangzhou 510642, China Correspondence: (J.W.); (X.X.); (Q.W.)
Xinqiang Xie Key Laboratory of Agricultural Microbiomics and Precision Application, Ministry of Agriculture and Rural Affairs, Guangdong Provincial Key Laboratory of Microbial Safety and Health, State Key Laboratory of Applied Microbiology Southern China, Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou 510070, China Correspondence: (J.W.); (X.X.); (Q.W.)
Qingping Wu Key Laboratory of Agricultural Microbiomics and Precision Application, Ministry of Agriculture and Rural Affairs, Guangdong Provincial Key Laboratory of Microbial Safety and Health, State Key Laboratory of Applied Microbiology Southern China, Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou 510070, China Correspondence: (J.W.); (X.X.); (Q.W.)

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Mechanism of enhanced production of triterpenoids in algal-fungal consortium. Bioprocess Biosyst Eng 2022;45:1625-1633. [PMID: 35963944 DOI: 10.1007/s00449-022-02768-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2022] [Accepted: 07/31/2022] [Indexed: 11/02/2022]

Huang Z, Klaric L, Krasauskaite J, McLachlan S, Strachan MWJ, Wilson JF, Price JF. Serum metabolomic profiles associated with subclinical and clinical cardiovascular phenotypes in people with type 2 diabetes. Cardiovasc Diabetol 2022;21:62. [PMID: 35477395 PMCID: PMC9047374 DOI: 10.1186/s12933-022-01493-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Accepted: 04/05/2022] [Indexed: 02/04/2023] Open

Abstract

BACKGROUND

Atherosclerotic cardiovascular diseases (CVD) is the leading cause of death in diabetes, but the full range of biomarkers reflecting atherosclerotic burden and CVD risk in people with diabetes is unknown. Metabolomics may help identify novel biomarkers potentially involved in development of atherosclerosis. We investigated the serum metabolomic profile of subclinical atherosclerosis, measured using ankle brachial index (ABI), in people with type 2 diabetes, compared with the profile for symptomatic CVD in the same population.

METHODS

The Edinburgh Type 2 Diabetes Study is a cohort of 1,066 individuals with type 2 diabetes. ABI was measured at baseline, years 4 and 10, with cardiovascular events assessed at baseline and during 10 years of follow-up. A panel of 228 metabolites was measured at baseline using nuclear magnetic resonance spectrometry, and their association with both ABI and prevalent CVD was explored using univariate regression models and least absolute shrinkage and selection operator (LASSO). Metabolites associated with baseline ABI were further explored for association with follow-up ABI and incident CVD.

RESULTS

Mean (standard deviation, SD) ABI at baseline was 0.97 (0.18, N = 1025), and prevalence of CVD was 35.0%. During 10-year follow-up, mean (SD) change in ABI was + 0.006 (0.178, n = 436), and 257 CVD events occurred. Lactate, glycerol, creatinine and glycoprotein acetyls levels were associated with baseline ABI in both univariate regression [βs (95% confidence interval, CI) ranged from - 0.025 (- 0.036, - 0.015) to - 0.023 (- 0.034, - 0.013), all p < 0.0002] and LASSO analysis. The associations remained nominally significant after adjustment for major vascular risk factors. In prospective analyses, lactate was nominally associated with ABI measured at years 4 and 10 after adjustment for baseline ABI. The four ABI-associated metabolites were all positively associated with prevalent CVD [odds ratios (ORs) ranged from 1.29 (1.13, 1.47) to 1.49 (1.29, 1.74), all p < 0.0002], and they were also positively associated with incident CVD [ORs (95% CI) ranged from 1.19 (1.02, 1.39) to 1.35 (1.17, 1.56), all p < 0.05].

CONCLUSIONS

Serum metabolites relating to glycolysis, fluid balance and inflammation were independently associated with both a marker of subclinical atherosclerosis and with symptomatic CVD in people with type 2 diabetes. Additional investigation is warranted to determine their roles as possible etiological and/or predictive biomarkers for atherosclerotic CVD.

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Taya N, Katakami N, Omori K, Arakawa S, Hosoe S, Watanabe H, Takahara M, Miyashita K, Nishizawa H, Matsuoka T, Furuno M, Bamba T, Iida J, Fukusaki E, Shimomura I. Evaluation of change in metabolome caused by comprehensive diabetes treatment: A prospective observational study of diabetes inpatients with gas chromatography/mass spectrometry-based non-target metabolomic analysis. J Diabetes Investig 2021;12:2232-2241. [PMID: 34032389 PMCID: PMC8668060 DOI: 10.1111/jdi.13600] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/09/2020] [Revised: 04/17/2021] [Accepted: 05/20/2021] [Indexed: 11/28/2022] Open

Abstract

AIMS/INTRODUCTION

Diabetes patients develop a variety of metabolic abnormalities in addition to hyperglycemia. However, details regarding change in various metabolites after comprehensive diabetes treatment remain unknown. This study aimed to identify the short-term change in metabolome in inpatients who were subject to comprehensive diabetes treatment, using gas chromatography/mass spectrometry-based non-target metabolomics techniques.

MATERIALS AND METHODS

Participants of the present study were randomly recruited from the patients with type 2 diabetes hospitalized due to problems with glycemic control (n = 31) and volunteers without diabetes (n = 30), both of whom were aged between 20 and 75 years. A metabolomic analysis of fasting plasma samples on the 2nd (pre-treatment) and 16th hospital (post-treatment) day with gas chromatography/mass spectrometry using a multiple reaction monitoring mode was carried out.

RESULTS

A principal component analysis showed that metabolome of fasting plasma was different between individuals with and without diabetes. The metabolome of fasting plasma in diabetes patients after treatment was different from that of pre-treatment, as well as individuals without diabetes. Many amino acids (proline, glycine, serine, threonine, methionine, pyroglutamic acid, glutamine and lysine) were significantly increased by >10% after administering the inpatient diabetes treatment. A hierarchical clustering analysis showed that in the case of patients with markedly decreased monosaccharide levels and increased 1,5-anhydroglucitol, the levels of amino acids increased more significantly.

CONCLUSIONS

After a 2-week comprehensive treatment, the plasma levels of various amino acids increased in conjunction with the reduction in monosaccharide levels in poorly controlled type 2 diabetes patients.

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Affiliation(s)

Naohiro Taya Department of Metabolic MedicineOsaka University Graduate School of MedicineOsakaJapan
Naoto Katakami Department of Metabolic MedicineOsaka University Graduate School of MedicineOsakaJapan Department of Metabolism and AtherosclerosisOsaka University Graduate School of MedicineOsakaJapan
Kazuo Omori Department of Metabolic MedicineOsaka University Graduate School of MedicineOsakaJapan
Shoya Arakawa Laboratory of Bioresource EngineeringDepartment of BiotechnologyGraduate School of EngineeringOsaka UniversityOsakaJapan
Shigero Hosoe Department of Metabolic MedicineOsaka University Graduate School of MedicineOsakaJapan
Hirotaka Watanabe Department of Metabolic MedicineOsaka University Graduate School of MedicineOsakaJapan
Mitsuyoshi Takahara Department of Metabolic MedicineOsaka University Graduate School of MedicineOsakaJapan Department of Diabetes Care MedicineGraduate School of MedicineOsaka UniversityOsakaJapan
Kazuyuki Miyashita Department of Metabolic MedicineOsaka University Graduate School of MedicineOsakaJapan
Hitoshi Nishizawa Department of Metabolic MedicineOsaka University Graduate School of MedicineOsakaJapan
Taka‐Aki Matsuoka Department of Metabolic MedicineOsaka University Graduate School of MedicineOsakaJapan
Masahiro Furuno Laboratory of Bioresource EngineeringDepartment of BiotechnologyGraduate School of EngineeringOsaka UniversityOsakaJapan
Takeshi Bamba Division of MetabolomicsResearch Center for Transomics MedicineMedical Institute of BioregulationKyushu UniversityFukuokaJapan
Junko Iida Shimadzu CorporationKyotoJapan Osaka University Shimadzu Omics Innovation Research LaboratoriesGraduate School of EngineeringOsaka UniversityOsakaJapan
Eiichiro Fukusaki Laboratory of Bioresource EngineeringDepartment of BiotechnologyGraduate School of EngineeringOsaka UniversityOsakaJapan
Iichiro Shimomura Department of Metabolic MedicineOsaka University Graduate School of MedicineOsakaJapan

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O'Kell AL, Wasserfall C, Guingab-Cagmat J, Webb-Roberston BJM, Atkinson MA, Garrett TJ. Targeted metabolomic analysis identifies increased serum levels of GABA and branched chain amino acids in canine diabetes. Metabolomics 2021;17:100. [PMID: 34775536 PMCID: PMC8693811 DOI: 10.1007/s11306-021-01850-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/15/2021] [Accepted: 10/29/2021] [Indexed: 12/17/2022]

Abstract

INTRODUCTION

Dogs with naturally occurring diabetes mellitus represent a potential model for human type 1 diabetes, yet significant knowledge voids exist in terms of the pathogenic mechanisms underlying the canine disorder. Untargeted metabolomic studies from a limited number of diabetic dogs identified similarities to humans with the disease.

OBJECTIVE

To expand and validate earlier metabolomic studies, identify metabolites that differ consistently between diabetic and healthy dogs, and address whether certain metabolites might serve as disease biomarkers.

METHODS

Untargeted metabolomic analysis via liquid chromatography-mass spectrometry was performed on serum from diabetic (n = 15) and control (n = 15) dogs. Results were combined with those of our previously published studies using identical methods (12 diabetic and 12 control dogs) to identify metabolites consistently different between the groups in all 54 dogs. Thirty-two candidate biomarkers were quantified using targeted metabolomics. Biomarker concentrations were compared between the groups using multiple linear regression (corrected P < 0.0051 considered significant).

RESULTS

Untargeted metabolomics identified multiple persistent differences in serum metabolites in diabetic dogs compared with previous studies. Targeted metabolomics showed increases in gamma amino butyric acid, valine, leucine, isoleucine, citramalate, and 2-hydroxyisobutyric acid in diabetic versus control dogs while indoxyl sulfate, N-acetyl-L-aspartic acid, kynurenine, anthranilic acid, tyrosine, glutamine, and tauroursodeoxycholic acid were decreased.

CONCLUSION

Several of these findings parallel metabolomic studies in both human diabetes and other animal models of this disease. Given recent studies on the role of GABA and branched chain amino acids in human diabetes, the increase in serum concentrations in canine diabetes warrants further study of these metabolites as potential biomarkers, and to identify similarity in mechanisms underlying this disease in humans and dogs.

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Su J, Zhao Q, Zhao A, Jia W, Zhu W, Lu J, Ma X. Serum metabolic signatures of subclinical atherosclerosis in patients with type 2 diabetes mellitus: a preliminary study. Acta Diabetol 2021;58:1217-1224. [PMID: 33871690 DOI: 10.1007/s00592-021-01717-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/01/2021] [Accepted: 04/05/2021] [Indexed: 12/14/2022]

Arakawa S, Furuno M, Fukusaki E. Minimization of adverse effects of blank matrices from various apparatuses in the downsizing of gas chromatography-mass spectrometry-based metabolomics. J Biosci Bioeng 2021;132:102-107. [PMID: 33879405 DOI: 10.1016/j.jbiosc.2021.03.005] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2020] [Revised: 02/23/2021] [Accepted: 03/10/2021] [Indexed: 10/21/2022]

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Matsumoto T, Kojima M, Takayanagi K, Taguchi K, Kobayashi T. Role of S-Equol, Indoxyl Sulfate, and Trimethylamine N-Oxide on Vascular Function. Am J Hypertens 2020;33:793-803. [PMID: 32300778 PMCID: PMC7481967 DOI: 10.1093/ajh/hpaa053] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2020] [Revised: 02/21/2020] [Accepted: 03/20/2020] [Indexed: 12/15/2022] Open

Li MN, Qian SH, Yao ZY, Ming SP, Shi XJ, Kang PF, Zhang NR, Wang XJ, Gao DS, Gao Q, Zhang H, Wang HJ. Correlation of serum N-Acetylneuraminic acid with the risk and prognosis of acute coronary syndrome: a prospective cohort study. BMC Cardiovasc Disord 2020;20:404. [PMID: 32912159 PMCID: PMC7488474 DOI: 10.1186/s12872-020-01690-z] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2020] [Accepted: 08/27/2020] [Indexed: 12/22/2022] Open

Katakami N, Omori K, Taya N, Arakawa S, Takahara M, Matsuoka TA, Tsugawa H, Furuno M, Bamba T, Fukusaki E, Shimomura I. Plasma metabolites associated with arterial stiffness in patients with type 2 diabetes. Cardiovasc Diabetol 2020;19:75. [PMID: 32527273 PMCID: PMC7291560 DOI: 10.1186/s12933-020-01057-w] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/13/2020] [Accepted: 06/08/2020] [Indexed: 12/16/2022] Open

Abstract

BACKGROUND

Although an increased arterial stiffness has been associated with traditional coronary risk factors, the risk factors and pathology of arterial stiffness remain unclear. In this study, we aimed to identify the plasma metabolites associated with arterial stiffness in patients with type 2 diabetes mellitus.

METHODS

We used the metabolomic data of 209 patients with type 2 diabetes as the first dataset for screening. To form the second dataset for validation, we enlisted an additional 31 individuals with type 2 diabetes. The non-targeted metabolome analysis of fasting plasma samples using gas chromatography coupled with mass spectrometry and the measurement of brachial-ankle pulse wave velocity (baPWV) were performed.

RESULTS

A total of 65 annotated metabolites were detected. In the screening dataset, there were statistically significant associations between the baPWV and plasma levels of indoxyl sulfate (r = 0.226, p = 0.001), mannitol (r = 0.178, p = 0.010), mesoerythritol (r = 0.234, p = 0.001), and pyroglutamic acid (r = 0.182, p = 0.008). Multivariate regression analyses revealed that the plasma levels of mesoerythritol were significantly (β = 0.163, p = 0.025) and that of indoxyl sulfate were marginally (β = 0.124, p = 0.076) associated with baPWV, even after adjusting for traditional coronary risk factors. In the independent validation dataset, there was a statistically significant association between the baPWV and plasma levels of indoxyl sulfate (r = 0.430, p = 0.016). However, significant associations between the baPWV and plasma levels of the other three metabolites were not confirmed.

CONCLUSIONS/INTERPRETATION

The plasma levels of indoxyl sulfate were associated with arterial stiffness in Japanese patients with type 2 diabetes. Although the plasma levels of mannitol, mesoerythritol, and pyroglutamic acid were also associated with arterial stiffness, further investigation is needed to verify the results.

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