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Sharma V, Khokhar M, Panigrahi P, Gadwal A, Setia P, Purohit P. Advancements, Challenges, and clinical implications of integration of metabolomics technologies in diabetic nephropathy. Clin Chim Acta 2024; 561:119842. [PMID: 38969086 DOI: 10.1016/j.cca.2024.119842] [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: 03/30/2024] [Revised: 06/25/2024] [Accepted: 06/29/2024] [Indexed: 07/07/2024]
Abstract
BACKGROUND Diabetic nephropathy (DN), a severe complication of diabetes, involves a range of renal abnormalities driven by metabolic derangements. Metabolomics, revealing dynamic metabolic shifts in diseases like DN and offering insights into personalized treatment strategies, emerges as a promising tool for improved diagnostics and therapies. METHODS We conducted an extensive literature review to examine how metabolomics contributes to the study of DN and the challenges associated with its implementation in clinical practice. We identified and assessed relevant studies that utilized metabolomics methods, including nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS) to assess their efficacy in diagnosing DN. RESULTS Metabolomics unveils key pathways in DN progression, highlighting glucose metabolism, dyslipidemia, and mitochondrial dysfunction. Biomarkers like glycated albumin and free fatty acids offer insights into DN nuances, guiding potential treatments. Metabolomics detects small-molecule metabolites, revealing disease-specific patterns for personalized care. CONCLUSION Metabolomics offers valuable insights into the molecular mechanisms underlying DN progression and holds promise for personalized medicine approaches. Further research in this field is warranted to elucidate additional metabolic pathways and identify novel biomarkers for early detection and targeted therapeutic interventions in DN.
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Affiliation(s)
- V Sharma
- Department of Biochemistry, All India Institute of Medical Sciences, Jodhpur, Rajasthan 342005, India
| | - M Khokhar
- Department of Biochemistry, All India Institute of Medical Sciences, Jodhpur, Rajasthan 342005, India
| | - P Panigrahi
- Department of Biochemistry, All India Institute of Medical Sciences, Jodhpur, Rajasthan 342005, India
| | - A Gadwal
- Department of Biochemistry, All India Institute of Medical Sciences, Jodhpur, Rajasthan 342005, India
| | - P Setia
- Department of Forensic Medicine and Toxicology, All India Institute of Medical Sciences, Jodhpur, Rajasthan 342005, India
| | - P Purohit
- Department of Biochemistry, All India Institute of Medical Sciences, Jodhpur, Rajasthan 342005, India.
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Ali MM, Parveen S, Williams V, Dons R, Uwaifo GI. Cardiometabolic comorbidities and complications of obesity and chronic kidney disease (CKD). J Clin Transl Endocrinol 2024; 36:100341. [PMID: 38616864 PMCID: PMC11015524 DOI: 10.1016/j.jcte.2024.100341] [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: 02/08/2024] [Revised: 03/28/2024] [Accepted: 03/29/2024] [Indexed: 04/16/2024] Open
Abstract
Obesity and chronic kidney disease are two ongoing progressive clinical pandemics of major public health and clinical care significance. Because of their growing prevalence, chronic indolent course and consequent complications both these conditions place significant burden on the health care delivery system especially in developed countries like the United States. Beyond the chance coexistence of both of these conditions in the same patient based on high prevalence it is now apparent that obesity is associated with and likely has a direct causal role in the onset, progression and severity of chronic kidney disease. The causes and underlying pathophysiology of this are myriad, complicated and multi-faceted. In this review, continuing the theme of this special edition of the journal on " The Cross roads between Endocrinology and Nephrology" we review the epidemiology of obesity related chronic kidney disease (ORCKD), and its various underlying causes and pathophysiology. In addition, we delve into the consequent comorbidities and complications associated with ORCKD with particular emphasis on the cardio metabolic consequences and then review the current body of evidence for available strategies for chronic kidney disease modulation in ORCKD as well as the potential unique role of weight reduction and management strategies in its improvement and risk reduction.
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Affiliation(s)
- Mariam M. Ali
- Southern Illinois School of Medicine, Department of Medicine, Section of Endocrinology, Diabetes and Metabolism, 751 North Rutledge Street, Moy Building, Suite 1700, Springfield, Il 62702, United States
| | - Sanober Parveen
- Southern Illinois School of Medicine, Department of Medicine, Section of Endocrinology, Diabetes and Metabolism, 751 North Rutledge Street, Moy Building, Suite 1700, Springfield, Il 62702, United States
| | - Vanessa Williams
- Southern Illinois School of Medicine, Department of Medicine, Section of Endocrinology, Diabetes and Metabolism, 751 North Rutledge Street, Moy Building, Suite 1700, Springfield, Il 62702, United States
| | - Robert Dons
- Southern Illinois School of Medicine, Department of Medicine, Section of Endocrinology, Diabetes and Metabolism, 751 North Rutledge Street, Moy Building, Suite 1700, Springfield, Il 62702, United States
| | - Gabriel I. Uwaifo
- Section of Endocrinology, Dept of Medicine, SIU School of Medicine, 751 N Rutledge St, Moy Building, Suite 1700, Room #1813, Springfield, Il 62702, United States
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Pandey S. Metabolomics Characterization of Disease Markers in Diabetes and Its Associated Pathologies. Metab Syndr Relat Disord 2024. [PMID: 38778629 DOI: 10.1089/met.2024.0038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/25/2024] Open
Abstract
With the change in lifestyle of people, there has been a considerable increase in diabetes, which brings with it certain follow-up pathological conditions, which lead to a substantial medical burden. Identifying biomarkers that aid in screening, diagnosis, and prognosis of diabetes and its associated pathologies would help better patient management and facilitate a personalized treatment approach for prevention and treatment. With the advancement in techniques and technologies, metabolomics has emerged as an omics approach capable of large-scale high throughput data analysis and identifying and quantifying metabolites that provide an insight into the underlying mechanism of the disease and its progression. Diabetes and metabolomics keywords were searched in correspondence with the assigned keywords, including kidney, cardiovascular diseases and critical illness from PubMed and Scopus, from its inception to Dec 2023. The relevant studies from this search were extracted and included in the study. This review is focused on the biomarkers identified in diabetes, diabetic kidney disease, diabetes-related development of CVD, and its role in critical illness.
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Affiliation(s)
- Swarnima Pandey
- School of Pharmacy, Department of Pharmaceutical Sciences, University of Maryland, Baltimore, Maryland, USA
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Calice-Silva V, Bensenor IM, Titan SM, Cavalcante MRN, Lotufo PA. Association between branched-chain amino acids and renal function in the ELSA-Brasil study. Clin Nutr 2024; 43:1051-1056. [PMID: 38555679 DOI: 10.1016/j.clnu.2024.02.008] [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: 07/27/2023] [Revised: 01/26/2024] [Accepted: 02/09/2024] [Indexed: 04/02/2024]
Abstract
BACKGROUND & AIMS Epidemiologic studies show high circulating Branched-chain amino acids (BCAA) are associated with excess body weight, impaired fasting glucose, insulin resistance, high blood pressure, and dyslipidemia. There is scarce data on the association between renal function and circulating levels of BCAA. Therefore, we aim to study this association in a sample of the Brazilian Longitudinal Study of Adults (ELSA-Brasil) METHODS: We analyzed participants who had at the baseline BCAA: valine, isoleucine, and leucine measured through nuclear magnetic resonance. The outcomes evaluated were estimated glomerular function (eGFR - CKD-EPI without race) and 12h-albumin-creatinine ratio (ACR). In addition, we built unadjusted and adjusted multivariable linear regression models to investigate the association between the BCAA (total and individual) and eGFR and ACR. RESULTS We studied 4912 participants (age 51.7(±9.0) years, 53.4% women, 59.5% White (59.5%), 32.7% hypertension, and 18.2% diabetes). The mean BCAA level was 429.15 ± 87.15. The mean eGFR was 84.95 ± 15 ml/min/1.73 m2, and the median ACR was 6.5 (1.8-4920) mg/g. Descriptive analyses comparing eGFR stratified <60 ml/min/1.73 m2 and ACR≥30 mg/g demonstrate that BCAA levels are higher in patients with eGFR<60 and ACR ≥30. Regarding eGFR, an inverse association was detected with BCAA levels when adjusted for demographic variables, and it is not maintained after adjustments for other confounders. Also, a positive association was found for ACR≥30 mg/g, and BCAA levels, and this association is not confirmed after adjustments. CONCLUSIONS BCAA levels were inversely associated with eGFR and positively associated with ACR. Further studies are necessary to allow the comprehension of those associations.
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Affiliation(s)
- Viviane Calice-Silva
- Pro-rim Foundation, Joinville, Brazil; School of Medicine, UNIVILLE, Joinville, Brazil; Center for Clinical and Epidemiologic Research, Hospital Universitario, University of São Paulo, Sao Paulo, Brazil.
| | - Isabela M Bensenor
- Center for Clinical and Epidemiologic Research, Hospital Universitario, University of São Paulo, Sao Paulo, Brazil
| | - Silvia M Titan
- Center for Clinical and Epidemiologic Research, Hospital Universitario, University of São Paulo, Sao Paulo, Brazil
| | | | - Paulo A Lotufo
- Center for Clinical and Epidemiologic Research, Hospital Universitario, University of São Paulo, Sao Paulo, Brazil
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Rotbain Curovic V, Sørland BA, Hansen TW, Jain SY, Sulek K, Mattila IM, Frimodt-Moller M, Trost K, Legido-Quigley C, Theilade S, Tofte N, Winther SA, Hansen CS, Rossing P, Ahluwalia TS. Circulating metabolomic markers in association with overall burden of microvascular complications in type 1 diabetes. BMJ Open Diabetes Res Care 2024; 12:e003973. [PMID: 38604732 PMCID: PMC11015221 DOI: 10.1136/bmjdrc-2023-003973] [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: 12/12/2023] [Accepted: 03/16/2024] [Indexed: 04/13/2024] Open
Abstract
INTRODUCTION Diabetic retinopathy (DR), diabetic kidney disease (DKD) and distal symmetric polyneuropathy (DSPN) share common pathophysiology and pose an additive risk of early mortality. RESEARCH DESIGN AND METHODS In adults with type 1 diabetes, 49 metabolites previously associated with either DR or DKD were assessed in relation to presence of DSPN. Metabolites overlapping in significance with presence of all three complications were assessed in relation to microvascular burden severity (additive number of complications-ie, presence of DKD±DR±DSPN) using linear regression models. Subsequently, the same metabolites were assessed with progression to endpoints: soft microvascular events (progression in albuminuria grade, ≥30% estimated glomerular filtration rate (eGFR) decline, or any progression in DR grade), hard microvascular events (progression to proliferative DR, chronic kidney failure, or ≥40% eGFR decline), and hard microvascular or macrovascular events (hard microvascular events, cardiovascular events (myocardial infarction, stroke, or arterial interventions), or cardiovascular mortality), using Cox models. All models were adjusted for sex, baseline age, diabetes duration, systolic blood pressure, HbA1c, body mass index, total cholesterol, smoking, and statin treatment. RESULTS The full cohort investigated consisted of 487 participants. Mean (SD) follow-up was 4.8 (2.9, 5.7) years. Baseline biothesiometry was available in 202 participants, comprising the cross-sectional cohort. Eight metabolites were significantly associated with presence of DR, DKD, and DSPN, and six with additive microvascular burden severity. In the full cohort longitudinal analysis, higher levels of 3,4-dihydroxybutanoic acid (DHBA), 2,4-DHBA, ribonic acid, glycine, and ribitol were associated with development of events in both crude and adjusted models. Adding 3,4-DHBA, ribonic acid, and glycine to a traditional risk factor model improved the discrimination of hard microvascular events. CONCLUSIONS While prospective studies directly assessing the predictive ability of these markers are needed, our results strengthen the role of clinical metabolomics in relation to risk assessment of diabetic complications in chronic type 1 diabetes.
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Affiliation(s)
| | | | | | | | | | | | | | - Kajetan Trost
- Steno Diabetes Center Copenhagen, Herlev, Denmark
- Department of Clinical Medicine, University of Copenhagen, København, Denmark
| | | | - Simone Theilade
- Steno Diabetes Center Copenhagen, Herlev, Denmark
- Department of Clinical Medicine, University of Copenhagen, København, Denmark
| | - Nete Tofte
- Steno Diabetes Center Copenhagen, Herlev, Denmark
| | | | | | - Peter Rossing
- Steno Diabetes Center Copenhagen, Herlev, Denmark
- Department of Clinical Medicine, University of Copenhagen, København, Denmark
| | - Tarunveer S Ahluwalia
- Steno Diabetes Center Copenhagen, Herlev, Denmark
- University of Copenhagen Bioinformatics Centre, København, Denmark
- Department of Science and Environment, Roskilde University, Roskilde, Denmark
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Das S, Devi Rajeswari V, Venkatraman G, Elumalai R, Dhanasekaran S, Ramanathan G. Current updates on metabolites and its interlinked pathways as biomarkers for diabetic kidney disease: A systematic review. Transl Res 2024; 265:71-87. [PMID: 37952771 DOI: 10.1016/j.trsl.2023.11.002] [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: 09/04/2023] [Revised: 11/09/2023] [Accepted: 11/09/2023] [Indexed: 11/14/2023]
Abstract
Diabetic kidney disease (DKD) is a major microvascular complication of diabetes mellitus (DM) that poses a serious risk as it can lead to end-stage renal disease (ESRD). DKD is linked to changes in the diversity, composition, and functionality of the microbiota present in the gastrointestinal tract. The interplay between the gut microbiota and the host organism is primarily facilitated by metabolites generated by microbial metabolic processes from both dietary substrates and endogenous host compounds. The production of numerous metabolites by the gut microbiota is a crucial factor in the pathogenesis of DKD. However, a comprehensive understanding of the precise mechanisms by which gut microbiota and its metabolites contribute to the onset and progression of DKD remains incomplete. This review will provide a summary of the current scenario of metabolites in DKD and the impact of these metabolites on DKD progression. We will discuss in detail the primary and gut-derived metabolites in DKD, and the mechanisms of the metabolites involved in DKD progression. Further, we will address the importance of metabolomics in helping identify potential DKD markers. Furthermore, the possible therapeutic interventions and research gaps will be highlighted.
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Affiliation(s)
- Soumik Das
- School of Biosciences and Technology, Vellore Institute of Technology (VIT), Vellore, Tamil Nadu 632014, India
| | - V Devi Rajeswari
- School of Biosciences and Technology, Vellore Institute of Technology (VIT), Vellore, Tamil Nadu 632014, India
| | - Ganesh Venkatraman
- School of Biosciences and Technology, Vellore Institute of Technology (VIT), Vellore, Tamil Nadu 632014, India
| | - Ramprasad Elumalai
- Department of Nephrology, Sri Ramachandra Institute of Higher Education and Research, Porur, Chennai, Tamil Nadu 600116, India
| | - Sivaraman Dhanasekaran
- School of Energy Technology, Pandit Deendayal Energy University, Knowledge Corridor, Raisan Village, PDPU Road, Gandhinagar, Gujarat 382426, India
| | - Gnanasambandan Ramanathan
- School of Biosciences and Technology, Vellore Institute of Technology (VIT), Vellore, Tamil Nadu 632014, India.
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Krasauskaite J, Conway B, Weir C, Huang Z, Price J. Exploration of Metabolomic Markers Associated With Declining Kidney Function in People With Type 2 Diabetes Mellitus. J Endocr Soc 2023; 8:bvad166. [PMID: 38174155 PMCID: PMC10763986 DOI: 10.1210/jendso/bvad166] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/10/2023] [Indexed: 01/05/2024] Open
Abstract
Background Metabolomics, the study of small molecules in biological systems, can provide valuable insights into kidney dysfunction in people with type 2 diabetes mellitus (T2DM), but prospective studies are scarce. We investigated the association between metabolites and kidney function decline in people with T2DM. Methods The Edinburgh Type 2 Diabetes Study, a population-based cohort of 1066 men and women aged 60 to 75 years with T2DM. We measured 149 serum metabolites at baseline and investigated individual associations with baseline estimated glomerular filtration rate (eGFR), incident chronic kidney disease [CKD; eGFR <60 mL/min/(1.73 m)2], and decliner status (5% eGFR decline per year). Results At baseline, mean eGFR was 77.5 mL/min/(1.73 m)2 (n = 1058), and 216 individuals had evidence of CKD. Of those without CKD, 155 developed CKD over a median 7-year follow-up. Eighty-eight metabolites were significantly associated with baseline eGFR (β range -4.08 to 3.92; PFDR < 0.001). Very low density lipoproteins, triglycerides, amino acids (AAs), glycoprotein acetyls, and fatty acids showed inverse associations, while cholesterol and phospholipids in high-density lipoproteins exhibited positive associations. AA isoleucine, apolipoprotein A1, and total cholines were not only associated with baseline kidney measures (PFDR < 0.05) but also showed stable, nominally significant association with incident CKD and decline. Conclusion Our study revealed widespread changes within the metabolomic profile of CKD, particularly in lipoproteins and their lipid compounds. We identified a smaller number of individual metabolites that are specifically associated with kidney function decline. Replication studies are needed to confirm the longitudinal findings and explore if metabolic signals at baseline can predict kidney decline.
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Affiliation(s)
| | - Bryan Conway
- Centre for Cardiovascular Science, The Queen's Medical Research Institute, Edinburgh BioQuarter, University of Edinburgh, EH16 4TJ, Edinburgh, UK
| | - Christopher Weir
- Usher Institute, University of Edinburgh, EH8 9AG, Edinburgh, UK
| | - Zhe Huang
- Usher Institute, University of Edinburgh, EH8 9AG, Edinburgh, UK
| | - Jackie Price
- Usher Institute, University of Edinburgh, EH8 9AG, Edinburgh, UK
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Qian F, Zhao L, Zhang D, Yu M, Zhou W, Jin J. Serum metabolomics detected by LDI-TOF-MS can be used to distinguish between diabetic patients with and without diabetic kidney disease. FEBS Open Bio 2023; 13:1844-1858. [PMID: 37525631 PMCID: PMC10549217 DOI: 10.1002/2211-5463.13683] [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: 04/15/2023] [Revised: 06/21/2023] [Accepted: 07/31/2023] [Indexed: 08/02/2023] Open
Abstract
Diabetic kidney disease (DKD) is an important cause of end-stage renal disease with changes in metabolic characteristics. The objective of this study was to study changes in serum metabolic characteristics in patients with DKD and to examine metabolite panels to distinguish DKD from diabetes with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS). We recruited 40 type II diabetes mellitus (T2DM) patients with or without DKD from a single center for a cross-sectional study. Serum metabolic profiling was performed with MALDI-TOF-MS using a vertical silicon nanowire array. Differential metabolites between DKD and diabetes patients were selected, and their relevance to the clinical parameters of DKD was analyzed. We applied machine learning methods to the differential metabolite panels to distinguish DKD patients from diabetes patients. Twenty-four differential serum metabolites between DKD patients and diabetes patients were identified, which were mainly enriched in butyrate metabolism, TCA cycle, and alanine, aspartate, and glutamate metabolism. Among the metabolites, l-kynurenine was positively correlated with urinary microalbumin, urinary microalbumin/creatinine ratio (UACR), creatinine, and urea nitrogen content. l-Serine, pimelic acid, 5-methylfuran-2-carboxylic acid, 4-methylbenzaldehyde, and dihydrouracil were associated with the estimated glomerular filtration rate (eGFR). The panel of differential metabolites could be used to distinguish between DKD and diabetes patients with an AUC value reaching 0.9899-0.9949. Among the differential metabolites, l-kynurenine was related to the progression of DKD. The differential metabolites exhibited excellent performance at distinguishing between DKD and diabetes. This study provides a novel direction for metabolomics-based clinical detection of DKD.
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Affiliation(s)
- Fengmei Qian
- The Second School of Clinical MedicineZhejiang Chinese Medical UniversityHangzhouChina
| | - Li Zhao
- Department of Nephrology, Urology & Nephrology CenterZhejiang Provincial People's Hospital (Affiliated People's Hospital, Hangzhou Medical College)China
| | - Di Zhang
- Department of Nephrology, Urology & Nephrology CenterZhejiang Provincial People's Hospital (Affiliated People's Hospital, Hangzhou Medical College)China
| | - Mengjie Yu
- Department of Nephrology, Urology & Nephrology CenterZhejiang Provincial People's Hospital (Affiliated People's Hospital, Hangzhou Medical College)China
| | - Wei Zhou
- Department of NephrologyThe First People's Hospital of Hangzhou Lin'an District, Affiliated Lin'an People's Hospital, Hangzhou Medical CollegeChina
| | - Juan Jin
- Department of NephrologyThe First People's Hospital of Hangzhou Lin'an District, Affiliated Lin'an People's Hospital, Hangzhou Medical CollegeChina
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Li C, Gao L, Lv C, Li Z, Fan S, Liu X, Rong X, Huang Y, Liu J. Active role of amino acid metabolism in early diagnosis and treatment of diabetic kidney disease. Front Nutr 2023; 10:1239838. [PMID: 37781128 PMCID: PMC10539689 DOI: 10.3389/fnut.2023.1239838] [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: 06/23/2023] [Accepted: 08/23/2023] [Indexed: 10/03/2023] Open
Abstract
Diabetic Kidney Disease (DKD) is one of the significant microvascular consequences of type 2 diabetes mellitus with a complex etiology and protracted course. In the early stages of DKD, the majority of patients experience an insidious onset and few overt clinical symptoms and indicators, but they are prone to develop end-stage renal disease in the later stage, which is life-threatening. The abnormal amino acid metabolism is tightly associated with the development of DKD, which involves several pathological processes such as oxidative stress, inflammatory response, and immune response and is also closely related to autophagy, mitochondrial dysfunction, and iron death. With a focus on taurine, branched-chain amino acids (BCAAs) and glutamine, we explored the biological effects of various amino acid mechanisms linked to DKD, the impact of amino acid metabolism in the early diagnosis of DKD, and the role of amino acid metabolism in treating DKD, to offer fresh objectives and guidelines for later early detection and DKD therapy.
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Affiliation(s)
- Chenming Li
- Tianjin University of Traditional Chinese Medicine, Tianjin, China
- Clinical Pharmacology Department, Second Affiliated Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Lidong Gao
- College of Traditional Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, China
- Tianjin Key Laboratory of Modern Chinese Medicine Theory of Innovation and Application, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Chunxiao Lv
- Clinical Pharmacology Department, Second Affiliated Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Ziqiang Li
- Clinical Pharmacology Department, Second Affiliated Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Shanshan Fan
- Tianjin University of Traditional Chinese Medicine, Tianjin, China
- Clinical Pharmacology Department, Second Affiliated Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Xinyue Liu
- Tianjin University of Traditional Chinese Medicine, Tianjin, China
- Clinical Pharmacology Department, Second Affiliated Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Xinyi Rong
- Tianjin University of Traditional Chinese Medicine, Tianjin, China
- Clinical Pharmacology Department, Second Affiliated Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Yuhong Huang
- Clinical Pharmacology Department, Second Affiliated Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Jia Liu
- Clinical Pharmacology Department, Second Affiliated Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin, China
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Shi L, Xu J, Green R, Wretlind A, Homann J, Buckley NJ, Tijms BM, Vos SJB, Lill CM, Kate MT, Engelborghs S, Sleegers K, Frisoni GB, Wallin A, Lleó A, Popp J, Martinez-Lage P, Streffer J, Barkhof F, Zetterberg H, Visser PJ, Lovestone S, Bertram L, Nevado-Holgado AJ, Proitsi P, Legido-Quigley C. Multiomics profiling of human plasma and cerebrospinal fluid reveals ATN-derived networks and highlights causal links in Alzheimer's disease. Alzheimers Dement 2023; 19:3350-3364. [PMID: 36790009 DOI: 10.1002/alz.12961] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Revised: 12/07/2022] [Accepted: 12/20/2022] [Indexed: 02/16/2023]
Abstract
INTRODUCTION This study employed an integrative system and causal inference approach to explore molecular signatures in blood and CSF, the amyloid/tau/neurodegeneration [AT(N)] framework, mild cognitive impairment (MCI) conversion to Alzheimer's disease (AD), and genetic risk for AD. METHODS Using the European Medical Information Framework (EMIF)-AD cohort, we measured 696 proteins in cerebrospinal fluid (n = 371), 4001 proteins in plasma (n = 972), 611 metabolites in plasma (n = 696), and genotyped whole-blood (7,778,465 autosomal single nucleotide epolymorphisms, n = 936). We investigated associations: molecular modules to AT(N), module hubs with AD Polygenic Risk scores and APOE4 genotypes, molecular hubs to MCI conversion and probed for causality with AD using Mendelian randomization (MR). RESULTS AT(N) framework associated with protein and lipid hubs. In plasma, Proprotein Convertase Subtilisin/Kexin Type 7 showed evidence for causal associations with AD. AD was causally associated with Reticulocalbin 2 and sphingomyelins, an association driven by the APOE isoform. DISCUSSION This study reveals multi-omics networks associated with AT(N) and causal AD molecular candidates.
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Affiliation(s)
- Liu Shi
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Jin Xu
- Institute of Pharmaceutical Science, King's College London, London, UK
| | - Rebecca Green
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- UK National Institute for Health Research (NIHR) Maudsley Biomedical Research Centre, South London and Maudsley Trust, London, UK
- MRC Unit for Lifelong Health & Ageing at UCL, University College London, London, UK
| | | | - Jan Homann
- Lübeck Interdisciplinary Platform for Genome Analytics, University of Lübeck, Lübeck, Germany
| | - Noel J Buckley
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Betty M Tijms
- Alzheimer Center, VU University Medical Center, Amsterdam, the Netherlands
| | - Stephanie J B Vos
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Alzheimer Centrum Limburg, Maastricht University, Maastricht, the Netherlands
| | - Christina M Lill
- Lübeck Interdisciplinary Platform for Genome Analytics, University of Lübeck, Lübeck, Germany
- Institute of Epidemiology and Social Medicine, University of Muenster, Muenster, Germany
- Ageing Epidemiology Research Unit (AGE), School of Public Health, Imperial College London, London, UK
| | - Mara Ten Kate
- Alzheimer Center, VU University Medical Center, Amsterdam, the Netherlands
| | - Sebastiaan Engelborghs
- Reference Center for Biological Markers of Dementia (BIODEM), Institute Born-Bunge, University of Antwerp, Antwerp, Belgium
- Department of Neurology, UZ Brussel and Center for Neurociences (C4N), Vrije Universiteit Brussel, Brussels, Belgium
| | - Kristel Sleegers
- Complex Genetics Group, VIB Center for Molecular Neurology, VIB, Antwerp, Belgium
- Institute Born-Bunge, Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
| | - Giovanni B Frisoni
- University of Geneva, Geneva, Switzerland
- IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Anders Wallin
- Institute of Neuroscience and Physiology, Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden
| | - Alberto Lleó
- Neurology Department, Centro de Investigación en Red en enfermedades neurodegenerativas (CIBERNED), Hospital Sant Pau, Barcelona, Spain
| | - Julius Popp
- University Hospital of Lausanne, Lausanne, Switzerland
- Department of Geriatric Psychiatry, University Hospital of Psychiatry and University of Zürich, Zürich, Switzerland
| | | | - Johannes Streffer
- AC Immune SA, formerly Janssen R&D, LLC. Beerse, Belgium at the time of study conduct, Lausanne, Switzerland
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherland
- Queen Square Institute of Neurology and Centre for Medical Image Computing, University College London, London, UK
| | - Henrik Zetterberg
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
- UK Dementia Research Institute at UCL, London, UK
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
| | - Pieter Jelle Visser
- Alzheimer Center, VU University Medical Center, Amsterdam, the Netherlands
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Alzheimer Centrum Limburg, Maastricht University, Maastricht, the Netherlands
| | - Simon Lovestone
- Department of Psychiatry, University of Oxford, Oxford, UK
- Janssen Medical (UK), High Wycombe, UK
| | - Lars Bertram
- Lübeck Interdisciplinary Platform for Genome Analytics, University of Lübeck, Lübeck, Germany
- Department of Psychology, University of Oslo, Oslo, Norway
| | | | - Petroula Proitsi
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Cristina Legido-Quigley
- Institute of Pharmaceutical Science, King's College London, London, UK
- Steno Diabetes Center Copenhagen, Gentofte, Denmark
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11
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She R, Al-Sari NH, Mattila IM, Sejling AS, Pedersen J, Legido-Quigley C, Pedersen-Bjergaard U. Decreased branched-chain amino acids and elevated fatty acids during antecedent hypoglycemia in type 1 diabetes. BMJ Open Diabetes Res Care 2023; 11:e003327. [PMID: 37369531 PMCID: PMC10410980 DOI: 10.1136/bmjdrc-2023-003327] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Accepted: 06/08/2023] [Indexed: 06/29/2023] Open
Abstract
INTRODUCTION Hypoglycemia is a major limiting factor in achieving recommended glycemic targets for people with type 1 diabetes. Exposure to recurrent hypoglycemia results in blunted hormonal counter-regulatory and symptomatic responses to hypoglycemia. Limited data on metabolic adaptation to recurrent hypoglycemia are available. This study examined the acute metabolic responses to hypoglycemia and the effect of antecedent hypoglycemia on these responses in type 1 diabetes. RESEARCH DESIGN AND METHODS Twenty-one outpatients with type 1 diabetes with normal or impaired awareness of hypoglycemia participated in a study assessing the response to hypoglycemia on 2 consecutive days by a hyperinsulinemic glucose clamp. Participants underwent a period of normoglycemia and a period of hypoglycemia during the hyperinsulinemic glucose clamp. Plasma samples were taken during normoglycemia and at the beginning and the end of the hypoglycemic period. Metabolomic analysis of the plasma samples was conducted using comprehensive two-dimensional gas chromatography with time-of-flight mass spectrometry. RESULTS In total, 68 metabolites were studied. On day 1, concentrations of the branched-chain amino acids, leucine (p=3.8×10-3) and isoleucine (p=2.2×10-3), decreased during hypoglycemia. On day 2, during hypoglycemia, five amino acids (including leucine and isoleucine) significantly decreased, and two fatty acids (tetradecanoic and oleic acids) significantly increased (p<0.05). Although more metabolites responded to hypoglycemia on day 2, the responses of the single metabolites were not statistically significant between the 2 days. CONCLUSIONS In individuals with type 1 diabetes, one episode of hypoglycemia decreases leucine and isoleucine concentrations. Antecedent hypoglycemia results in the decrement of five amino acids and increases the concentrations of two fatty acids, suggesting an alteration between the two hypoglycemic episodes, which could indicate a possible adaptation. However, more studies are needed to gain a comprehensive understanding of the consequences of these alterations. TRIAL REGISTRATION NUMBER NCT01337362.
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Affiliation(s)
- Rui She
- Department of Endocrinology and Nephrology, Nordsjællands Hospital, Hillerød, Capital Region of Denmark, Denmark
- Department of Clinical Medicine, University of Copenhagen Faculty of Health and Medical Sciences, Kobenhavn, Capital Region of Denmark, Denmark
| | - Naba Hassan Al-Sari
- Clinical Research, Steno Diabetes Center Copenhagen, Herlev, Capital Region of Denmark, Denmark
| | - Ismo Matias Mattila
- Clinical Research, Steno Diabetes Center Copenhagen, Herlev, Capital Region of Denmark, Denmark
| | - Anne-Sophie Sejling
- Boston Global Development, Novo Nordisk, Søborg, Capital Region of Denmark, Denmark
| | - Jens Pedersen
- Department of Internal Medicine, Herlev Hospital, Herlev, Capital Region of Denmark, Denmark
| | - Cristina Legido-Quigley
- Clinical Research, Steno Diabetes Center Copenhagen, Herlev, Capital Region of Denmark, Denmark
- Institute of Pharmaceutical Science, King's College London, London, UK
| | - Ulrik Pedersen-Bjergaard
- Department of Endocrinology and Nephrology, Nordsjællands Hospital, Hillerød, Capital Region of Denmark, Denmark
- Department of Clinical Medicine, University of Copenhagen Faculty of Health and Medical Sciences, Kobenhavn, Capital Region of Denmark, Denmark
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12
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Rotbain Curovic V, Tofte N, Lindhardt M, Adamova K, Bakker SJL, Beige J, Beulens JWJ, Birkenfeld AL, Currie G, Delles C, Dimos I, Francová L, Frimodt-Møller M, Girman P, Göke R, Hansen TW, Havrdova T, Kooy A, Laverman GD, Mischak H, Navis G, Nijpels G, Noutsou M, Ortiz A, Parvanova A, Persson F, Petrie JR, Ruggenenti PL, Rutters F, Rychlík I, Siwy J, Spasovski G, Speeckaert M, Trillini M, Zürbig P, von der Leyen H, Rossing P. Presence of retinopathy and incident kidney and cardiovascular events in type 2 diabetes with normoalbuminuria - A post-hoc analysis of the PRIORITY randomized clinical trial. J Diabetes Complications 2023; 37:108433. [PMID: 36841085 DOI: 10.1016/j.jdiacomp.2023.108433] [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: 12/06/2022] [Revised: 02/06/2023] [Accepted: 02/08/2023] [Indexed: 02/19/2023]
Abstract
AIMS Baseline diabetic retinopathy (DR) and risk of development of microalbuminuria, kidney function decline, and cardiovascular events (CVEs) in type 2 diabetes. METHODS Post-hoc analysis of the PRIORITY study including 1758 persons with type 2 diabetes and normoalbuminuria followed for a median of 2.5 (IQR: 2.0-3.0) years. DR diagnosis included non-proliferative and proliferative abnormalities, macular oedema, or prior laser treatment. Cox models were fitted to investigate baseline DR presence with development of persistent microalbuminuria (urinary albumin-creatinine ratio > 30 mg/g); chronic kidney disease (CKD) G3 (eGFR <60 ml/min/1.73m2); and CVE. Models were adjusted for relevant risk factors. RESULTS At baseline, 304 (17.3 %) had DR. Compared to persons without DR, they were older (mean ± SD: 62.7 ± 7.7 vs 61.4 ± 8.3 years, p = 0.019), had longer diabetes duration (17.9 ± 8.4 vs. 10.6 ± 7.0 years, p < 0.001), and higher HbA1c (62 ± 13 vs. 56 ± 12 mmol/mol, p < 0.001). The adjusted hazard ratios of DR at baseline for development of microalbuminuria (n = 197), CKD (n = 166), and CVE (n = 64) were: 1.50 (95%CI: 1.07, 2.11), 0.87 (95%CI: 0.56, 1.34), and 2.61 (95%CI: 1.44, 4.72), compared to without DR. CONCLUSIONS Presence of DR in normoalbuminuric type 2 diabetes was associated with an increased risk of developing microalbuminuria and CVE, but not with kidney function decline.
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Affiliation(s)
| | - Nete Tofte
- Steno Diabetes Center Copenhagen, Herlev, Denmark
| | - Morten Lindhardt
- Steno Diabetes Center Copenhagen, Herlev, Denmark; Department of Medicine, Copenhagen University Hospital - Holbæk, Holbæk, Denmark; Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Katarina Adamova
- University Clinic of Endocrinology, Diabetes and Metabolic Disorders, Skopje, Macedonia
| | - Stephan J L Bakker
- Division of Nephrology, Department of Internal Medicine, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - Joachim Beige
- Division of Nephrology and KfH Renal Unit, Hospital St Georg, Leipzig, Germany; Martin-Luther University Halle, Wittenberg, Germany
| | - Joline W J Beulens
- Amsterdam UMC, location Vrije Universiteit Amsterdam, Department of Epidemiology and Data Science, Amsterdam, the Netherlands; Amsterdam Cardiovascular Sciences, Amsterdam, the Netherlands; Amsterdam Public Health, Amsterdam, the Netherlands; Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Andreas L Birkenfeld
- Department of Internal Medicine IV, Division of Endocrinology, Diabetology, and Nephrology, University Hospital Tübingen, Tübingen, Germany
| | - Gemma Currie
- School of Cardiovascular and Metabolic Health, University of Glasgow, Glasgow, UK
| | - Christian Delles
- School of Cardiovascular and Metabolic Health, University of Glasgow, Glasgow, UK
| | | | - Lidmila Francová
- Department of Internal Medicine, Charles University, Third Faculty of Medicine, Prague, Czech Republic; Faculty Hospital Královské Vinohrady, Prague, Czech Republic
| | | | - Peter Girman
- Diabetes Center, Institute for Clinical and Experimental Medicine, Prague, Czech Republic
| | - Rüdiger Göke
- Diabetologische Schwerpunktpraxis, Diabetologen Hessen, Marburg, Germany
| | | | - Tereza Havrdova
- Diabetes Center, Institute for Clinical and Experimental Medicine, Prague, Czech Republic
| | - Adriaan Kooy
- Bethesda Diabetes Research Center, Hoogeveen, the Netherlands
| | - Gozewijnw D Laverman
- Department of Internal Medicine/Nephrology, Ziekenhuisgroep Twente Hospital, Almelo, the Netherlands
| | | | - Gerjan Navis
- Division of Nephrology, Department of Internal Medicine, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - Giel Nijpels
- Department General Practice and Elderly Care, Amsterdam, the Netherlands
| | - Marina Noutsou
- Diabetes Center, 2nd Department of Internal Medicine, National and Kapodistrian University of Athens, Medical School, Hippokratio General Hospital, Athens, Greece
| | - Alberto Ortiz
- Instituto de Investigacion Sanitaria de la Fundacion Jiménez Díaz UAM, Madrid, Spain
| | - Aneliya Parvanova
- Department of Renal Medicine, Clinical Research Centre for Rare Diseases "Aldo e Cele Daccò": Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Ranica, Bergamo, Italy
| | | | - John R Petrie
- School of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - Piero L Ruggenenti
- Department of Renal Medicine, Clinical Research Centre for Rare Diseases "Aldo e Cele Daccò": Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Ranica, Bergamo, Italy
| | - Femke Rutters
- Amsterdam UMC, location Vrije Universiteit Amsterdam, Department of Epidemiology and Data Science, Amsterdam, the Netherlands; Amsterdam Public Health, Amsterdam, the Netherlands
| | - Ivan Rychlík
- Department of Internal Medicine, Charles University, Third Faculty of Medicine, Prague, Czech Republic
| | | | - Goce Spasovski
- Department of Nephrology, Cyril and Methodius University in Skopje, Skopje, Macedonia
| | | | - Matias Trillini
- Department of Renal Medicine, Clinical Research Centre for Rare Diseases "Aldo e Cele Daccò": Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Ranica, Bergamo, Italy
| | | | | | - Peter Rossing
- Steno Diabetes Center Copenhagen, Herlev, Denmark; Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
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13
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Reynolds KM, Lin BM, Armstrong ND, Ottosson F, Zhang Y, Williams AS, Yu B, Boerwinkle E, Thygarajan B, Daviglus ML, Muoio D, Qi Q, Kaplan R, Melander O, Lash JP, Cai J, Irvin MR, Newgard CB, Sofer T, Franceschini N. Circulating Metabolites Associated with Albuminuria in a Hispanic/Latino Population. Clin J Am Soc Nephrol 2023; 18:204-212. [PMID: 36517247 PMCID: PMC10103280 DOI: 10.2215/cjn.09070822] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2022] [Revised: 11/22/2022] [Accepted: 12/02/2022] [Indexed: 12/15/2022]
Abstract
BACKGROUND Albuminuria is associated with metabolic abnormalities, but these relationships are not well understood. We studied the association of metabolites with albuminuria in Hispanic/Latino people, a population with high risk for metabolic disease. METHODS We used data from 3736 participants from the Hispanic Community Health Study/Study of Latinos, of which 16% had diabetes and 9% had an increased urine albumin-to-creatinine ratio (UACR). Metabolites were quantified in fasting serum through nontargeted mass spectrometry (MS) analysis using ultra-performance liquid chromatography-MS/MS. Spot UACR was inverse normally transformed and tested for the association with each metabolite or combined, correlated metabolites, in covariate-adjusted models that accounted for the study design. In total, 132 metabolites were available for replication in the Hypertension Genetic Epidemiology Network study ( n =300), and 29 metabolites were available for replication in the Malmö Offspring Study ( n =999). RESULTS Among 640 named metabolites, we identified 148 metabolites significantly associated with UACR, including 18 novel associations that replicated in independent samples. These metabolites showed enrichment for D-glutamine and D-glutamate metabolism and arginine biosynthesis, pathways previously reported for diabetes and insulin resistance. In correlated metabolite analyses, we identified two modules significantly associated with UACR, including a module composed of lipid metabolites related to the biosynthesis of unsaturated fatty acids and alpha linolenic acid and linoleic acid metabolism. CONCLUSIONS Our study identified associations of albuminuria with metabolites involved in glucose dysregulation, and essential fatty acids and precursors of arachidonic acid in Hispanic/Latino population. PODCAST This article contains a podcast at https://dts.podtrac.com/redirect.mp3/www.asn-online.org/media/podcast/CJASN/2023_02_08_CJN09070822.mp3.
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Affiliation(s)
- Kaylia M. Reynolds
- Department of Biostatistics, University of North Carolina, Chapel Hill, North Carolina
| | - Bridget M. Lin
- Department of Biostatistics, University of North Carolina, Chapel Hill, North Carolina
| | - Nicole D. Armstrong
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, Alabama
| | - Filip Ottosson
- Department of Clinical Sciences, Lund University, Malmö, Sweden
- Section for Clinical Mass Spectrometry, Danish Center for Neonatal Screening, Department of Congenital Disorders, Statens Serum Institut, Copenhagen, Denmark
| | - Ying Zhang
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, Massachusetts
| | | | - Bing Yu
- Human Genetics Center, University of Texas Health Science Center at Houston, Houston, Texas
| | - Eric Boerwinkle
- Human Genetics Center, University of Texas Health Science Center at Houston, Houston, Texas
| | - Bharat Thygarajan
- Division of Molecular Pathology and Genomics, University of Minnesota, Minneapolis, Minnesota
| | - Martha L. Daviglus
- Institute for Minority Health Research, University of Illinois at Chicago College of Medicine, Chicago, Illinois
| | - Deborah Muoio
- Duke University Medical Center, Durham, North Carolina
| | - Qibin Qi
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, New York
| | - Robert Kaplan
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, New York
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington
| | - Olle Melander
- Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - James P. Lash
- Division of Nephrology, Department of Medicine, University of Illinois, Chicago, Illinois
| | - Jianwen Cai
- Department of Biostatistics, University of North Carolina, Chapel Hill, North Carolina
| | - Marguerite R. Irvin
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, Alabama
| | | | - Tamar Sofer
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, Massachusetts
- Departments of Medicine and Biostatistics, Harvard University, Boston, Massachusetts
| | - Nora Franceschini
- Department of Epidemiology, University of North Carolina, Chapel Hill, North Carolina
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14
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The Growing Challenge of Chronic Kidney Disease: An Overview of Current Knowledge. Int J Nephrol 2023; 2023:9609266. [PMID: 36908289 PMCID: PMC9995188 DOI: 10.1155/2023/9609266] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2022] [Revised: 02/02/2023] [Accepted: 02/17/2023] [Indexed: 03/05/2023] Open
Abstract
Chronic kidney disease (CKD) is becoming one of the world's most prevalent noncommunicable chronic diseases. The World Health Organization projects CKD to become the 5th most common chronic disease in 2040. Causes of CKD are multifactorial and diverse, but early-stage symptoms are often few and silent. Progression rates are highly variable, but patients encounter both an increased risk for end-stage kidney disease (ESKD) as well as increased cardiovascular risk. End-stage kidney disease incidence is generally low, but every single case carries a significant burden of illness and healthcare costs, making prevention by early intervention both desirable and worthwhile. This review focuses on the prevalence, diagnosis, and causes of CKD. In addition, we discuss the developments in the general treatment of CKD, with particular attention to what can be initiated in general practice. With the addition of recent landmark findings and the expansion of the indication for using sodium-glucose cotransporter 2 inhibitors, there are now new effective treatments to add to standard therapy. This will also be relevant for primary care physicians as many patients with CKD have their family physician as their primary health care professional handling kidney function preservation. In the future, more precise and less invasive diagnostic methods may not only improve the determination of the underlying cause of CKD but may also carry information regarding which treatment to use (i.e. personalized medicine). This could lead to a reduced number of preventive treatments per individual, while at the same time improving the prognosis. This review summarizes ongoing efforts in this area.
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15
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Abstract
The prevalence of obesity has increased dramatically during the past decades, which has been a major health problem. Since 1975, the number of people with obesity worldwide has nearly tripled. An increasing number of studies find obesity as a driver of chronic kidney disease (CKD) progression, and the mechanisms are complex and include hemodynamic changes, inflammation, oxidative stress, and activation of the renin-angiotensin-aldosterone system (RAAS). Obesity-related kidney disease is characterized by glomerulomegaly, which is often accompanied by localized and segmental glomerulosclerosis lesions. In these patients, the early symptoms are atypical, with microproteinuria being the main clinical manifestation and nephrotic syndrome being rare. Weight loss and RAAS blockers have a protective effect on obesity-related CKD, but even so, a significant proportion of patients eventually progress to end-stage renal disease despite treatment. Thus, it is critical to comprehend the mechanisms underlying obesity-related CKD to create new tactics for slowing or stopping disease progression. In this review, we summarize current knowledge on the mechanisms of obesity-related kidney disease, its pathological changes, and future perspectives on its treatment.
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Affiliation(s)
- Zongmiao Jiang
- Department of Endocrinology and Metabolism, The First Hospital of Jilin University, Changchun, China
| | - Yao Wang
- Department of Orthopedics, The Second Hospital Jilin University, Changchun, China
| | - Xue Zhao
- Department of Endocrinology and Metabolism, The First Hospital of Jilin University, Changchun, China
| | - Haiying Cui
- Department of Endocrinology and Metabolism, The First Hospital of Jilin University, Changchun, China
| | - Mingyue Han
- Department of Endocrinology and Metabolism, The First Hospital of Jilin University, Changchun, China
| | - Xinhua Ren
- Department of Endocrinology and Metabolism, The First Hospital of Jilin University, Changchun, China
| | - Xiaokun Gang
- Department of Endocrinology and Metabolism, The First Hospital of Jilin University, Changchun, China
| | - Guixia Wang
- Department of Endocrinology and Metabolism, The First Hospital of Jilin University, Changchun, China
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16
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Vigers T, Vinovskis C, Li LP, Prasad P, Heerspink H, D'Alessandro A, Reisz JA, Piani F, Cherney DZ, van Raalte DH, Nadeau KJ, Pavkov ME, Nelson RG, Pyle L, Bjornstad P. Plasma levels of carboxylic acids are markers of early kidney dysfunction in young people with type 1 diabetes. Pediatr Nephrol 2023; 38:193-202. [PMID: 35507146 PMCID: PMC10182875 DOI: 10.1007/s00467-022-05531-3] [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: 11/23/2021] [Revised: 02/25/2022] [Accepted: 03/07/2022] [Indexed: 01/10/2023]
Abstract
BACKGROUND We compared plasma metabolites of amino acid oxidation and the tricarboxylic acid (TCA) cycle in youth with and without type 1 diabetes mellitus (T1DM) and related the metabolites to glomerular filtration rate (GFR), renal plasma flow (RPF), and albuminuria. Metabolites associated with impaired kidney function may warrant future study as potential biomarkers or even future interventions to improve kidney bioenergetics. METHODS Metabolomic profiling of fasting plasma samples using a targeted panel of 644 metabolites and an untargeted panel of 19,777 metabolites was performed in 50 youth with T1DM ≤ 10 years and 20 controls. GFR and RPF were ascertained by iohexol and p-aminohippurate clearance, and albuminuria calculated as urine albumin to creatinine ratio. Sparse partial least squares discriminant analysis and moderated t tests were used to identify metabolites associated with GFR and RPF. RESULTS Adolescents with and without T1DM were similar in age (16.1 ± 3.0 vs. 16.1 ± 2.9 years) and BMI (23.4 ± 5.1 vs. 22.7 ± 3.7 kg/m2), but those with T1DM had higher GFR (189 ± 40 vs. 136 ± 22 ml/min) and RPF (820 ± 125 vs. 615 ± 65 ml/min). Metabolites of amino acid oxidation and the TCA cycle were significantly lower in adolescents with T1DM vs. controls, and the measured metabolites were able to discriminate diabetes status with an AUC of 0.82 (95% CI: 0.71, 0.93) and error rate of 0.21. Lower glycine (r:-0.33, q = 0.01), histidine (r:-0.45, q < 0.001), methionine (r: -0.29, q = 0.02), phenylalanine (r: -0.29, q = 0.01), serine (r: -0.42, q < 0.001), threonine (r: -0.28, q = 0.02), citrate (r: -0.35, q = 0.003), fumarate (r: -0.24, q = 0.04), and malate (r: -0.29, q = 0.02) correlated with higher GFR. Lower glycine (r: -0.28, q = 0.04), phenylalanine (r:-0.3, q = 0.03), fumarate (r: -0.29, q = 0.04), and malate (r: -0.5, q < 0.001) correlated with higher RPF. Lower histidine (r: -0.28, q = 0.02) was correlated with higher mean ACR. CONCLUSIONS In conclusion, adolescents with relatively short T1DM duration exhibited lower plasma levels of carboxylic acids that associated with hyperfiltration and hyperperfusion. TRIAL REGISTRATION ClinicalTrials.gov NCT03618420 and NCT03584217 A higher resolution version of the Graphical abstract is available as Supplementary information.
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Affiliation(s)
- Timothy Vigers
- Department of Pediatrics, Section of Endocrinology, University of Colorado School of Medicine, Aurora, CO, USA.
- Department of Biostatistics and Informatics, Colorado School of Public Health, 13123 E 16th Ave, A036-B265, Aurora, CO, 80045, USA.
| | - Carissa Vinovskis
- Department of Pediatrics, Section of Endocrinology, University of Colorado School of Medicine, Aurora, CO, USA
| | - Lu-Ping Li
- Department of Radiology, NorthShore University HealthSystem, Evanston, IL, USA
| | - Pottumarthi Prasad
- Department of Radiology, NorthShore University HealthSystem, Evanston, IL, USA
| | - Hiddo Heerspink
- Department Clinical Pharmacy and Pharmacology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Angelo D'Alessandro
- Department of Biochemistry and Molecular Genetics, University of Colorado School of Medicine, Aurora, CO, USA
| | - Julie A Reisz
- Department of Biochemistry and Molecular Genetics, University of Colorado School of Medicine, Aurora, CO, USA
| | - Federica Piani
- Department of Pediatrics, Section of Endocrinology, University of Colorado School of Medicine, Aurora, CO, USA
| | - David Z Cherney
- Department of Medicine, Division of Nephrology, University of Toronto School of Medicine, Toronto, Ontario, Canada
| | - Daniel H van Raalte
- Diabetes Center, Department of Internal Medicine, Amsterdam University Medical Centers, location VUmc, Amsterdam, the Netherlands
| | - Kristen J Nadeau
- Department of Pediatrics, Section of Endocrinology, University of Colorado School of Medicine, Aurora, CO, USA
| | - Meda E Pavkov
- Division of Diabetes Translation, Center for Disease Control and Prevention, Atlanta, GA, USA
| | - Robert G Nelson
- Chronic Kidney Disease Section, Phoenix Epidemiology and Clinical Research Branch, NIDDK, Phoenix, AZ, USA
| | - Laura Pyle
- Department of Pediatrics, Section of Endocrinology, University of Colorado School of Medicine, Aurora, CO, USA
- Department of Biostatistics and Informatics, Colorado School of Public Health, 13123 E 16th Ave, A036-B265, Aurora, CO, 80045, USA
| | - Petter Bjornstad
- Department of Pediatrics, Section of Endocrinology, University of Colorado School of Medicine, Aurora, CO, USA
- Department of Medicine, Division of Nephrology, University of Colorado School of Medicine, Aurora, CO, USA
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17
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Ferreira-Divino LF, Suvitaival T, Rotbain Curovic V, Tofte N, Trošt K, Mattila IM, Theilade S, Winther SA, Hansen TW, Frimodt-Møller M, Legido-Quigley C, Rossing P. Circulating metabolites and molecular lipid species are associated with future cardiovascular morbidity and mortality in type 1 diabetes. Cardiovasc Diabetol 2022; 21:135. [PMID: 35850688 PMCID: PMC9295441 DOI: 10.1186/s12933-022-01568-8] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Accepted: 07/05/2022] [Indexed: 11/10/2022] Open
Abstract
Background Cardiovascular disease remains the leading cause of mortality in individuals with diabetes and improved understanding of its pathophysiology is needed. We investigated the association of a large panel of metabolites and molecular lipid species with future cardiovascular events in type 1 diabetes. Methods The study included 669 individuals with type 1 diabetes. Non-targeted serum metabolomics and lipidomics analyses were performed using mass spectrometry. Data on cardiovascular events (cardiovascular mortality, coronary artery disease, stroke, and peripheral arterial interventions) were obtained from Danish Health registries and analyzed by Cox hazards models. Metabolites and molecular lipid species were analyzed in univariate models adjusted for false discovery rate (FDR). Metabolites and molecular lipid species fulfilling a pFDR < 0.05 were subsequently analyzed in adjusted models including age, sex, hemoglobin A1c, mean arterial pressure, smoking, body mass index, low-density lipoprotein cholesterol, estimated glomerular filtration rate, urinary albumin excretion rate and previous cardiovascular disease. Analyses of molecular lipid species were further adjusted for triglycerides and statin use. Results Of the included participants, 55% were male and mean age was 55 ± 13 years. Higher 4-hydroxyphenylacetic acid (HR 1.35, CI [1.01–1.80], p = 0.04) and lower threonine (HR 0.81, CI [0.67–0.98] p = 0.03) were associated with development of cardiovascular events (n = 95). In lipidomics analysis, higher levels of three different species, diacyl-phosphatidylcholines (PC)(36:2) (HR 0.82, CI [0.70–0.98], p = 0.02), alkyl-acyl-phosphatidylcholines (PC-O)(34:2) (HR 0.76, CI [0.59–0.98], p = 0.03) and (PC-O)(34:3) (HR 0.75, CI [0.58–0.97], p = 0.03), correlated with lower risk of cardiovascular events, whereas higher sphingomyelin (SM)(34:1) (HR 1.32, CI [1.04–1.68], p = 0.02), was associated with an increased risk. Conclusions Circulating metabolites and molecular lipid species were associated with future cardiovascular events in type 1 diabetes. While the causal effect of these biomolecules on the cardiovascular system remains unknown, our findings support that omics-based technologies, although still in an early phase, may have the potential to unravel new pathways and biomarkers in the field of cardiovascular disease in type 1 diabetes. Supplementary Information The online version contains supplementary material available at 10.1186/s12933-022-01568-8.
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Affiliation(s)
| | - Tommi Suvitaival
- Steno Diabetes Center Copenhagen, Borgmester Ib Juuls Vej 83, 2730, Herlev, Denmark
| | | | - Nete Tofte
- Steno Diabetes Center Copenhagen, Borgmester Ib Juuls Vej 83, 2730, Herlev, Denmark
| | - Kajetan Trošt
- Steno Diabetes Center Copenhagen, Borgmester Ib Juuls Vej 83, 2730, Herlev, Denmark.,University of Copenhagen, Copenhagen, Denmark
| | - Ismo M Mattila
- Steno Diabetes Center Copenhagen, Borgmester Ib Juuls Vej 83, 2730, Herlev, Denmark
| | - Simone Theilade
- Steno Diabetes Center Copenhagen, Borgmester Ib Juuls Vej 83, 2730, Herlev, Denmark.,University of Copenhagen, Copenhagen, Denmark.,The Department of Medicine, Herlev-Gentofte Hospital, Copenhagen, Denmark
| | - Signe A Winther
- Steno Diabetes Center Copenhagen, Borgmester Ib Juuls Vej 83, 2730, Herlev, Denmark
| | - Tine W Hansen
- Steno Diabetes Center Copenhagen, Borgmester Ib Juuls Vej 83, 2730, Herlev, Denmark
| | - Marie Frimodt-Møller
- Steno Diabetes Center Copenhagen, Borgmester Ib Juuls Vej 83, 2730, Herlev, Denmark
| | | | - Peter Rossing
- Steno Diabetes Center Copenhagen, Borgmester Ib Juuls Vej 83, 2730, Herlev, Denmark.,University of Copenhagen, Copenhagen, Denmark
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Trans- and Multigenerational Maternal Social Isolation Stress Programs the Blood Plasma Metabolome in the F3 Generation. Metabolites 2022; 12:metabo12070572. [PMID: 35888696 PMCID: PMC9320469 DOI: 10.3390/metabo12070572] [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: 05/03/2022] [Revised: 06/12/2022] [Accepted: 06/15/2022] [Indexed: 11/21/2022] Open
Abstract
Metabolic risk factors are among the most common causes of noncommunicable diseases, and stress critically contributes to metabolic risk. In particular, social isolation during pregnancy may represent a salient stressor that affects offspring metabolic health, with potentially adverse consequences for future generations. Here, we used proton nuclear magnetic resonance (1H NMR) spectroscopy to analyze the blood plasma metabolomes of the third filial (F3) generation of rats born to lineages that experienced either transgenerational or multigenerational maternal social isolation stress. We show that maternal social isolation induces distinct and robust metabolic profiles in the blood plasma of adult F3 offspring, which are characterized by critical switches in energy metabolism, such as upregulated formate and creatine phosphate metabolisms and downregulated glucose metabolism. Both trans- and multigenerational stress altered plasma metabolomic profiles in adult offspring when compared to controls. Social isolation stress increasingly affected pathways involved in energy metabolism and protein biosynthesis, particularly in branched-chain amino acid synthesis, the tricarboxylic acid cycle (lactate, citrate), muscle performance (alanine, creatine phosphate), and immunoregulation (serine, threonine). Levels of creatine phosphate, leucine, and isoleucine were associated with changes in anxiety-like behaviours in open field exploration. The findings reveal the metabolic underpinnings of epigenetically heritable diseases and suggest that even remote maternal social stress may become a risk factor for metabolic diseases, such as diabetes, and adverse mental health outcomes. Metabolomic signatures of transgenerational stress may aid in the risk prediction and early diagnosis of non-communicable diseases in precision medicine approaches.
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Al-Sari N, Kutuzova S, Suvitaival T, Henriksen P, Pociot F, Rossing P, McCloskey D, Legido-Quigley C. Precision diagnostic approach to predict 5-year risk for microvascular complications in type 1 diabetes. EBioMedicine 2022; 80:104032. [PMID: 35533498 PMCID: PMC9092516 DOI: 10.1016/j.ebiom.2022.104032] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Revised: 04/11/2022] [Accepted: 04/12/2022] [Indexed: 12/03/2022] Open
Abstract
Background Individuals with long standing diabetes duration can experience damage to small microvascular blood vessels leading to diabetes complications (DCs) and increased mortality. Precision diagnostic tailors a diagnosis to an individual by using biomedical information. Blood small molecule profiling coupled with machine learning (ML) can facilitate the goals of precision diagnostics, including earlier diagnosis and individualized risk scoring. Methods Using data in a cohort of 537 adults with type 1 diabetes (T1D) we predicted five-year progression to DCs. Prediction models were computed first with clinical risk factors at baseline and then with clinical risk factors and blood-derived molecular data at baseline. Progression of diabetic kidney disease and diabetic retinopathy were predicted in two complication-specific models. Findings The model predicts the progression to diabetic kidney disease with accuracy: 0.96 ± 0.25 and 0.96 ± 0.06 area under curve, AUC, with clinical measurements and with small molecule predictors respectively and highlighted main predictors to be albuminuria, glomerular filtration rate, retinopathy status at baseline, sugar derivatives and ketones. For diabetic retinopathy, AUC 0.75 ± 0.14 and 0.79 ± 0.16 with clinical measurements and with small molecule predictors respectively and highlighted key predictors, albuminuria, glomerular filtration rate and retinopathy status at baseline. Individual risk scores were built to visualize results. Interpretation With further validation ML tools could facilitate the implementation of precision diagnosis in the clinic. It is envisaged that patients could be screened for complications, before these occur, thus preserving healthy life-years for persons with diabetes. Funding This study has been financially supported by Novo Nordisk Foundation grant NNF14OC0013659.
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Artemether Alleviates Diabetic Kidney Disease by Modulating Amino Acid Metabolism. BIOMED RESEARCH INTERNATIONAL 2022; 2022:7339611. [PMID: 35601149 PMCID: PMC9117059 DOI: 10.1155/2022/7339611] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Accepted: 04/08/2022] [Indexed: 11/17/2022]
Abstract
Diabetes is a worldwide metabolic disease with rapid growing incidence, characterized by hyperglycemia. Diabetic kidney disease (DKD), the leading cause of chronic kidney disease (CKD), has a high morbidity according to the constantly increasing diabetic patients and always develops irreversible deterioration of renal function. Though different in pathogenesis, clinical manifestations, and therapies, both type 1 diabetes mellitus (T1DM) and type 2 diabetes mellitus (T2DM) can evolve into DKD. Since amino acids are both biomarkers and causal agents, rarely report has been made about its metabolism which lies in T1DM- and T2DM-related kidney disease. This study was designed to investigate artemether in adjusting renal amino acid metabolism in T1DM and T2DM mice. Artemether was applied as treatment in streptozotocin (STZ) induced T1DM mice and db/db T2DM mice, respectively. Artemether-treated mice showed lower FBG and HbA1c and reduced urinary albumin excretion, as well as urinary NAG. Both types of diabetic mice showed enlarged kidneys, as confirmed by increased kidney weight and the ratio of kidney weight to body weight. Artemether normalized kidney size and thus attenuated renal hypertrophy. Kidney tissue UPLC-MS analysis showed that branched-chain amino acids (BCAAs) and citrulline were upregulated in diabetic mice without treatment and downregulated after being treated with artemether. Expressions of glutamine, glutamic acid, aspartic acid, ornithine, glycine, histidine, phenylalanine and threonine were decreased in both types of diabetic mice whereas they increased after artemether treatment. The study demonstrates the initial evidence that artemether exerted renal protection in DKD by modulating amino acid metabolism.
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Clos-Garcia M, Ahluwalia TS, Winther SA, Henriksen P, Ali M, Fan Y, Stankevic E, Lyu L, Vogt JK, Hansen T, Legido-Quigley C, Rossing P, Pedersen O. Multiomics signatures of type 1 diabetes with and without albuminuria. Front Endocrinol (Lausanne) 2022; 13:1015557. [PMID: 36531462 PMCID: PMC9755599 DOI: 10.3389/fendo.2022.1015557] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Accepted: 11/11/2022] [Indexed: 12/05/2022] Open
Abstract
AIMS/HYPOTHESIS To identify novel pathophysiological signatures of longstanding type 1 diabetes (T1D) with and without albuminuria we investigated the gut microbiome and blood metabolome in individuals with T1D and healthy controls (HC). We also mapped the functional underpinnings of the microbiome in relation to its metabolic role. METHODS One hundred and sixty-one individuals with T1D and 50 HC were recruited at the Steno Diabetes Center Copenhagen, Denmark. T1D cases were stratified based on levels of albuminuria into normoalbuminuria, moderate and severely increased albuminuria. Shotgun sequencing of bacterial and viral microbiome in stool samples and circulating metabolites and lipids profiling using mass spectroscopy in plasma of all participants were performed. Functional mapping of microbiome into Gut Metabolic Modules (GMMs) was done using EggNog and KEGG databases. Multiomics integration was performed using MOFA tool. RESULTS Measures of the gut bacterial beta diversity differed significantly between T1D and HC, either with moderately or severely increased albuminuria. Taxonomic analyses of the bacterial microbiota identified 51 species that differed in absolute abundance between T1D and HC (17 higher, 34 lower). Stratified on levels of albuminuria, 10 species were differentially abundant for the moderately increased albuminuria group, 63 for the severely increased albuminuria group while 25 were common and differentially abundant both for moderately and severely increased albuminuria groups, when compared to HC. Functional characterization of the bacteriome identified 23 differentially enriched GMMs between T1D and HC, mostly involved in sugar and amino acid metabolism. No differences in relation to albuminuria stratification was observed. Twenty-five phages were differentially abundant between T1D and HC groups. Six of these varied with albuminuria status. Plasma metabolomics indicated differences in the steroidogenesis and sugar metabolism and circulating sphingolipids in T1D individuals. We identified association between sphingolipid levels and Bacteroides sp. abundances. MOFA revealed reduced interactions between gut microbiome and plasma metabolome profiles albeit polar metabolite, lipids and bacteriome compositions contributed to the variance in albuminuria levels among T1D individuals. CONCLUSIONS Individuals with T1D and progressive kidney disease stratified on levels of albuminuria show distinct signatures in their gut microbiome and blood metabolome.
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Affiliation(s)
- Marc Clos-Garcia
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- LEITAT Technological Center, Terrassa, Spain
| | - Tarunveer S. Ahluwalia
- Complications Research, Steno Diabetes Center Copenhagen, Herlev, Denmark
- The Bioinformatics Center, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Signe A. Winther
- Complications Research, Steno Diabetes Center Copenhagen, Herlev, Denmark
| | - Peter Henriksen
- Complications Research, Steno Diabetes Center Copenhagen, Herlev, Denmark
| | - Mina Ali
- Complications Research, Steno Diabetes Center Copenhagen, Herlev, Denmark
| | - Yong Fan
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Evelina Stankevic
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Liwei Lyu
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Josef K. Vogt
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Clinical Microbiomics, Copenhagen, Denmark
| | - Torben Hansen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | | | - Peter Rossing
- Complications Research, Steno Diabetes Center Copenhagen, Herlev, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Oluf Pedersen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Center for Clinical Metabolic Research, Gentofte University Hospital, Copenhagen, Denmark
- *Correspondence: Oluf Pedersen,
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22
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Konstantinou C, Gaengler S, Oikonomou S, Delplancke T, Charisiadis P, Makris KC. Use of metabolomics in refining the effect of an organic food intervention on biomarkers of exposure to pesticides and biomarkers of oxidative damage in primary school children in Cyprus: A cluster-randomized cross-over trial. ENVIRONMENT INTERNATIONAL 2022; 158:107008. [PMID: 34991267 DOI: 10.1016/j.envint.2021.107008] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/04/2021] [Revised: 11/02/2021] [Accepted: 11/24/2021] [Indexed: 05/22/2023]
Abstract
BACKGROUND Exposure to pesticides has been associated with oxidative stress in animals and humans. Previously, we showed that an organic food intervention reduced pesticide exposure and oxidative damage (OD) biomarkers over time; however associated metabolic changes are not fully understood yet. OBJECTIVES We assessed perturbations of the urine metabolome in response to an organic food intervention for children and its association with pesticides biomarkers [3-phenoxybenzoic acid (3-PBA) and 6-chloronicotinic acid (6-CN)]. We also evaluated the molecular signatures of metabolites associated with biomarkers of OD (8-iso-PGF2a and 8-OHdG) and related biological pathways. METHODS We used data from the ORGANIKO LIFE + trial (NCT02998203), a cluster-randomized cross-over trial conducted among primary school children in Cyprus. Participants (n = 149) were asked to follow an organic food intervention for 40 days and their usual food habits for another 40 days, providing up to six first morning urine samples (>850 samples in total). Untargeted GC-MS metabolomics analysis was performed. Metabolites with RSD ≤ 20% and D-ratio ≤ 50% were retained for analysis. Associations were examined using mixed-effect regression models and corrected for false-discovery rate of 0.05. Pathway analysis followed. RESULTS Following strict quality checks, 156 features remained out of a total of 610. D-glucose was associated with the organic food intervention (β = -0.23, 95% CI: -0.37,-0.10), aminomalonic acid showed a time-dependent increase during the intervention period (βint = 0.012; 95% CI:0.002, 0.022) and was associated with the two OD biomarkers (β = -0.27, 95% CI:-0.34,-0.20 for 8-iso-PGF2a and β = 0.19, 95% CI:0.11,0.28 for 8-OHdG) and uric acid with 8-OHdG (β = 0.19, 95% CI:0.11,0.26). Metabolites were involved in pathways such as the starch and sucrose metabolism and pentose and glucuronate interconversions. DISCUSSION This is the first metabolomics study providing evidence of differential expression of metabolites by an organic food intervention, corroborating the reduction in biomarkers of OD. Further mechanistic evidence is warranted to better understand the biological plausibility of an organic food treatment on children's health outcomes.
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Affiliation(s)
- Corina Konstantinou
- Cyprus International Institute for Environmental and Public Health, Cyprus University of Technology, Cyprus
| | - Stephanie Gaengler
- Cyprus International Institute for Environmental and Public Health, Cyprus University of Technology, Cyprus
| | - Stavros Oikonomou
- Cyprus International Institute for Environmental and Public Health, Cyprus University of Technology, Cyprus
| | - Thibaut Delplancke
- Cyprus International Institute for Environmental and Public Health, Cyprus University of Technology, Cyprus
| | - Pantelis Charisiadis
- Cyprus International Institute for Environmental and Public Health, Cyprus University of Technology, Cyprus
| | - Konstantinos C Makris
- Cyprus International Institute for Environmental and Public Health, Cyprus University of Technology, Cyprus.
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Hansen CS, Suvitaival T, Theilade S, Mattila I, Lajer M, Trošt K, Ahonen L, Hansen TW, Legido-Quigley C, Rossing P, Ahluwalia TS. Cardiovascular Autonomic Neuropathy in Type 1 Diabetes Is Associated With Disturbances in TCA, Lipid, and Glucose Metabolism. Front Endocrinol (Lausanne) 2022; 13:831793. [PMID: 35498422 PMCID: PMC9046722 DOI: 10.3389/fendo.2022.831793] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Accepted: 03/11/2022] [Indexed: 11/17/2022] Open
Abstract
INTRODUCTION Diabetic cardiovascular autonomic neuropathy (CAN) is associated with increased mortality and morbidity. To explore metabolic mechanisms associated with CAN we investigated associations between serum metabolites and CAN in persons with type 1 diabetes (T1D). MATERIALS AND METHODS Cardiovascular reflex tests (CARTs) (heart rate response to: deep breathing; lying-to-standing test; and the Valsalva maneuver) were used to diagnose CAN in 302 persons with T1D. More than one pathological CARTs defined the CAN diagnosis. Serum metabolomics and lipidomic profiles were analyzed with two complementary non-targeted mass-spectrometry methods. Cross-sectional associations between metabolites and CAN were assessed by linear regression models adjusted for relevant confounders. RESULTS Participants were median (IQR) aged 55(49, 63) years, 48% males with diabetes duration 39(32, 47) years, HbA1c 63(55,69) mmol/mol and 34% had CAN. A total of 75 metabolites and 106 lipids were analyzed. In crude models, the CAN diagnosis was associated with higher levels of hydroxy fatty acids (2,4- and 3,4-dihydroxybutanoic acids, 4-deoxytetronic acid), creatinine, sugar derivates (ribitol, ribonic acid, myo-inositol), citric acid, glycerol, phenols, phosphatidylcholines and lower levels of free fatty acids and the amino acid methionine (p<0.05). Upon adjustment, positive associations with the CAN diagnoses were retained for hydroxy fatty acids, tricarboxylic acid (TCA) cycle-based sugar derivates, citric acid, and phenols (P<0.05). CONCLUSION Metabolic pathways, including the TCA cycle, hydroxy fatty acids, phosphatidylcholines and sugar derivatives are associated with the CAN diagnosis in T1D. These pathway may be part of the pathogeneses leading to CAN and may be modifiable risk factors for the complication.
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Affiliation(s)
- Christian S. Hansen
- Complications Research, Steno Diabetes Center Copenhagen, Herlev, Denmark
- *Correspondence: Christian S. Hansen,
| | - Tommi Suvitaival
- Complications Research, Steno Diabetes Center Copenhagen, Herlev, Denmark
| | - Simone Theilade
- Complications Research, Steno Diabetes Center Copenhagen, Herlev, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
- The Department of Medicine, Herlev-Gentofte Hospital, Copenhagen, Denmark
| | - Ismo Mattila
- Complications Research, Steno Diabetes Center Copenhagen, Herlev, Denmark
| | - Maria Lajer
- Complications Research, Steno Diabetes Center Copenhagen, Herlev, Denmark
| | - Kajetan Trošt
- Complications Research, Steno Diabetes Center Copenhagen, Herlev, Denmark
| | - Linda Ahonen
- Complications Research, Steno Diabetes Center Copenhagen, Herlev, Denmark
| | - Tine W. Hansen
- Complications Research, Steno Diabetes Center Copenhagen, Herlev, Denmark
| | | | - Peter Rossing
- Complications Research, Steno Diabetes Center Copenhagen, Herlev, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Tarunveer S. Ahluwalia
- Complications Research, Steno Diabetes Center Copenhagen, Herlev, Denmark
- The Bioinformatics Center, Department of Biology, University of Copenhagen, Copenhagen, Denmark
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Huang G, Li M, Li Y, Mao Y. OUP accepted manuscript. Lab Med 2022; 53:545-551. [PMID: 35748329 DOI: 10.1093/labmed/lmac041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Affiliation(s)
- Guoqing Huang
- Department of Endocrinology, The Affiliated Hospital of Medical School, Ningbo University, Ningbo, China
- School of Medicine, Ningbo University, Ningbo, China
| | - Mingcai Li
- School of Medicine, Ningbo University, Ningbo, China
| | - Yan Li
- Department of Endocrinology, The Affiliated Hospital of Medical School, Ningbo University, Ningbo, China
- School of Medicine, Ningbo University, Ningbo, China
| | - Yushan Mao
- Department of Endocrinology, The Affiliated Hospital of Medical School, Ningbo University, Ningbo, China
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25
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Lu Y, Zhou C, Yan R, Lian J, Cai H, Yu J, Chen D, Su X, Qian J, Yang Y, Li L. Dynamic metabolic profiles for HBeAg seroconversion in chronic hepatitis B (CHB) patients by gas chromatography-mass spectrometry (GC-MS). J Pharm Biomed Anal 2021; 206:114349. [PMID: 34597840 DOI: 10.1016/j.jpba.2021.114349] [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: 03/11/2021] [Revised: 08/27/2021] [Accepted: 08/27/2021] [Indexed: 11/19/2022]
Abstract
Chronic hepatitis B (CHB) remains a major public health problem globally. HBeAg seroconversion is a vital hallmark for the improvement of CHB. The plasma metabolic profile has not been clear in CHB patients and searching metabolic candidates to represent HBeAg seroconversion is also difficult currently. In this study, CHB patients were recruited, followed and divided into the HBeAg-positive (HBeAg-pos.) group (n = 29) and the HBeAg-negative (HBeAg-neg.) group (n = 29) based on HBeAg seroconversion or not. The plasma metabolic profiles were measured by gas chromatography-mass spectrometry (GC-MS) at 0 week (0w), 24 weeks (24w) and 48 weeks (48w) after administration. The acquired data was analyzed using orthogonal partial least squares discriminate analysis (OPLS-DA) and the differential metabolites were further assessed by self and group comparison. No differences of age, gender and serological characteristics were observed between two groups at 0w and 48w separately. The OPLS-DA score plots depending on administration time displayed robust metabolic differences no matter HBeAg turned to be negative or not. According to VIP> 1.0, a total of 15 differential metabolites were same in the two groups, 7 differential metabolites (glycolic acid, D-talose, L-proline, L-(-)-arabitol, ethyl-alpha-D-glucopyranoside, L-leucine and dihydroxybutanoic acid) were derived from one group alone and considered as metabolic candidates. At 0w versus (vs.) 24w, only 3 of 7 candidates (L-proline, L-(-)-arabitol, dihydroxybutanoic acid) showed nonuniform in the two groups, while at 0w vs. 48w, all of them varied inconsistently. Conclusively the dynamic metabolic profiles assayed by GC-MS were different between CHB patients with and without HBeAg seroconversion. The 7 metabolic candidates probably had the ability to reflect the CHB progression for HBeAg seroconversion and 3 of them showed strong relationship with HbeAg seroconversion early.
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Affiliation(s)
- Yingfeng Lu
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Chiyan Zhou
- Department of Prenatal Diagnosis, The Affiliated Women and Children Hospital, Jiaxing University School of Medicine, Jiaxing, China
| | - Ren Yan
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Jiangshan Lian
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Huan Cai
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Jiong Yu
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Deyin Chen
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Xiaoling Su
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Jiajie Qian
- Department of Gastrointestinal Surgery, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Yida Yang
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
| | - Lanjuan Li
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
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Jin Q, Ma RCW. Metabolomics in Diabetes and Diabetic Complications: Insights from Epidemiological Studies. Cells 2021; 10:cells10112832. [PMID: 34831057 PMCID: PMC8616415 DOI: 10.3390/cells10112832] [Citation(s) in RCA: 66] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2021] [Revised: 10/11/2021] [Accepted: 10/13/2021] [Indexed: 12/18/2022] Open
Abstract
The increasing prevalence of diabetes and its complications, such as cardiovascular and kidney disease, remains a huge burden globally. Identification of biomarkers for the screening, diagnosis, and prognosis of diabetes and its complications and better understanding of the molecular pathways involved in the development and progression of diabetes can facilitate individualized prevention and treatment. With the advancement of analytical techniques, metabolomics can identify and quantify multiple biomarkers simultaneously in a high-throughput manner. Providing information on underlying metabolic pathways, metabolomics can further identify mechanisms of diabetes and its progression. The application of metabolomics in epidemiological studies have identified novel biomarkers for type 2 diabetes (T2D) and its complications, such as branched-chain amino acids, metabolites of phenylalanine, metabolites involved in energy metabolism, and lipid metabolism. Metabolomics have also been applied to explore the potential pathways modulated by medications. Investigating diabetes using a systems biology approach by integrating metabolomics with other omics data, such as genetics, transcriptomics, proteomics, and clinical data can present a comprehensive metabolic network and facilitate causal inference. In this regard, metabolomics can deepen the molecular understanding, help identify potential therapeutic targets, and improve the prevention and management of T2D and its complications. The current review focused on metabolomic biomarkers for kidney and cardiovascular disease in T2D identified from epidemiological studies, and will also provide a brief overview on metabolomic investigations for T2D.
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Affiliation(s)
- Qiao Jin
- Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China;
| | - Ronald Ching Wan Ma
- Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China;
- Laboratory for Molecular Epidemiology in Diabetes, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong, China
- Chinese University of Hong Kong-Shanghai Jiao Tong University Joint Research Centre in Diabetes Genomics and Precision Medicine, The Chinese University of Hong Kong, Hong Kong, China
- Correspondence: ; Fax: +852-26373852
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Jing Z, Liu L, Shi Y, Du Q, Zhang D, Zuo L, Du S, Sun Z, Zhang X. Association of Coronary Artery Disease and Metabolic Syndrome: Usefulness of Serum Metabolomics Approach. Front Endocrinol (Lausanne) 2021; 12:692893. [PMID: 34630321 PMCID: PMC8498335 DOI: 10.3389/fendo.2021.692893] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/09/2021] [Accepted: 08/25/2021] [Indexed: 01/04/2023] Open
Abstract
Introduction Individuals with metabolic syndrome (MetS) are at increasing risk of coronary artery disease (CAD). We investigated the common metabolic perturbations of CAD and MetS via serum metabolomics to provide insight into potential associations. Methods Non-targeted serum metabolomics analyses were performed using ultra high-performance liquid chromatography coupled with Q Exactive hybrid quadrupole-orbitrap high-resolution accurate mass spectrometry (UHPLC-Q-Orbitrap HRMS) in samples from 492 participants (272 CAD vs. 121 healthy controls (HCs) as cohort 1, 55 MetS vs. 44 HCs as cohort 2). Cross-sectional data were obtained when the participants were recruited from the First Affiliated Hospital of Zhengzhou University. Multivariate statistics and Student's t test were applied to obtain the significant metabolites [with variable importance in the projection (VIP) values >1.0 and p values <0.05] for CAD and MetS. Logistic regression was performed to investigate the association of identified metabolites with clinical cardiac risk factors, and the association of significant metabolic perturbations between CAD and MetS was visualized by Cytoscape software 3.6.1. Finally, the receiver operating characteristic (ROC) analysis was evaluated for the risk prediction values of common changed metabolites. Results Thirty metabolites were identified for CAD, mainly including amino acids, lipid, fatty acids, pseudouridine, niacinamide; 26 metabolites were identified for MetS, mainly including amino acids, lipid, fatty acids, steroid hormone, and paraxanthine. The logistic regression results showed that all of the 30 metabolites for CAD, and 15 metabolites for MetS remained significant after adjustments of clinical risk factors. In the common metabolic signature association analysis between CAD and MetS, 11 serum metabolites were significant and common to CAD and MetS outcomes. Out of this, nine followed similar trends while two had differing directionalities. The nine common metabolites exhibiting same change trend improved risk prediction for CAD (86.4%) and MetS (90.9%) using the ROC analysis. Conclusion Serum metabolomics analysis might provide a new insight into the potential mechanisms underlying the common metabolic perturbations of CAD and MetS.
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Affiliation(s)
- Ziwei Jing
- Department of Pharmacy, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Liwei Liu
- Department of Pharmacy, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yingying Shi
- Department of Pharmacy, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Qiuzheng Du
- Department of Pharmacy, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Dingding Zhang
- Department of Vasculocardiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Lihua Zuo
- Department of Pharmacy, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Shuzhang Du
- Department of Pharmacy, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Zhi Sun
- Department of Pharmacy, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Xiaojian Zhang
- Department of Pharmacy, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
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Barutta F, Bellini S, Canepa S, Durazzo M, Gruden G. Novel biomarkers of diabetic kidney disease: current status and potential clinical application. Acta Diabetol 2021; 58:819-830. [PMID: 33528734 DOI: 10.1007/s00592-020-01656-9] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/18/2020] [Accepted: 12/09/2020] [Indexed: 12/12/2022]
Abstract
Diabetic kidney disease (DKD) is a leading cause of end-stage renal disease (ESRD). Although both albuminuria and glomerular filtration rate (GFR) are well-established diagnostic/prognostic biomarkers of DKD, they have important limitations. There is, thus, increasing quest to find novel biomarkers to identify the disease in an early stage and to improve risk stratification. In this review, we will outline the major pitfalls of currently available markers, describe promising novel biomarkers, and discuss their potential clinical relevance. In particular, we will focus on the importance of recent advancements in multi-omic technologies in the discovery of new DKD biomarkers. In addition, we will provide an update on new emerging approaches to explore renal function and structure, using functional tests and imaging.
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Affiliation(s)
- Federica Barutta
- Department of Medical Sciences, University of Turin, Turin, Italy.
| | - Stefania Bellini
- Department of Medical Sciences, University of Turin, Turin, Italy
| | - Silvia Canepa
- Department of Medical Sciences, University of Turin, Turin, Italy
| | - Marilena Durazzo
- Department of Medical Sciences, University of Turin, Turin, Italy
| | - Gabriella Gruden
- Department of Medical Sciences, University of Turin, Turin, Italy
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29
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Moon S, Tsay JJ, Lampert H, Md Dom ZI, Kostic AD, Smiles A, Niewczas MA. Circulating short and medium chain fatty acids are associated with normoalbuminuria in type 1 diabetes of long duration. Sci Rep 2021; 11:8592. [PMID: 33883567 PMCID: PMC8060327 DOI: 10.1038/s41598-021-87585-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2020] [Accepted: 03/30/2021] [Indexed: 11/08/2022] Open
Abstract
A substantial number of subjects with Type 1 Diabetes (T1D) of long duration never develop albuminuria or renal function impairment, yet the underlying protective mechanisms remain unknown. Therefore, our study included 308 Joslin Kidney Study subjects who had T1D of long duration (median: 24 years), maintained normal renal function and had either normoalbuminuria or a broad range of albuminuria within the 2 years preceding the metabolomic determinations. Serum samples were subjected to global metabolomic profiling. 352 metabolites were detected in at least 80% of the study population. In the logistic analyses adjusted for multiple testing (Bonferroni corrected α = 0.000028), we identified 38 metabolites associated with persistent normoalbuminuria independently from clinical covariates. Protective metabolites were enriched in Medium Chain Fatty Acids (MCFAs) and in Short Chain Fatty Acids (SCFAs) and particularly involved odd-numbered and dicarboxylate Fatty Acids. One quartile change of nonanoate, the top protective MCFA, was associated with high odds of having persistent normoalbuminuria (OR (95% CI) 0.14 (0.09, 0.23); p < 10-12). Multivariable Random Forest analysis concordantly indicated to MCFAs as effective classifiers. Associations of the relevant Fatty Acids with albuminuria seemed to parallel associations with tubular biomarkers. Our findings suggest that MCFAs and SCFAs contribute to the metabolic processes underlying protection against albuminuria development in T1D that are independent from mechanisms associated with changes in renal function.
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Affiliation(s)
- Salina Moon
- Research Division, Joslin Diabetes Center, One Joslin Place, Boston, MA, 02215, USA
| | - John J Tsay
- Research Division, Joslin Diabetes Center, One Joslin Place, Boston, MA, 02215, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Medicine, Veterans Affairs Boston Healthcare System, Boston, MA, USA
| | - Heather Lampert
- Research Division, Joslin Diabetes Center, One Joslin Place, Boston, MA, 02215, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Department of Family Medicine, Brown University, Providence, RI, USA
| | - Zaipul I Md Dom
- Research Division, Joslin Diabetes Center, One Joslin Place, Boston, MA, 02215, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Aleksandar D Kostic
- Research Division, Joslin Diabetes Center, One Joslin Place, Boston, MA, 02215, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Department of Microbiology, Harvard Medical School, Boston, MA, USA
| | - Adam Smiles
- Research Division, Joslin Diabetes Center, One Joslin Place, Boston, MA, 02215, USA
| | - Monika A Niewczas
- Research Division, Joslin Diabetes Center, One Joslin Place, Boston, MA, 02215, USA.
- Department of Medicine, Harvard Medical School, Boston, MA, USA.
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30
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Huang J, Covic M, Huth C, Rommel M, Adam J, Zukunft S, Prehn C, Wang L, Nano J, Scheerer MF, Neschen S, Kastenmüller G, Gieger C, Laxy M, Schliess F, Adamski J, Suhre K, de Angelis MH, Peters A, Wang-Sattler R. Validation of Candidate Phospholipid Biomarkers of Chronic Kidney Disease in Hyperglycemic Individuals and Their Organ-Specific Exploration in Leptin Receptor-Deficient db/db Mouse. Metabolites 2021; 11:metabo11020089. [PMID: 33546276 PMCID: PMC7913334 DOI: 10.3390/metabo11020089] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Revised: 01/27/2021] [Accepted: 01/29/2021] [Indexed: 12/03/2022] Open
Abstract
Biological exploration of early biomarkers for chronic kidney disease (CKD) in (pre)diabetic individuals is crucial for personalized management of diabetes. Here, we evaluated two candidate biomarkers of incident CKD (sphingomyelin (SM) C18:1 and phosphatidylcholine diacyl (PC aa) C38:0) concerning kidney function in hyperglycemic participants of the Cooperative Health Research in the Region of Augsburg (KORA) cohort, and in two biofluids and six organs of leptin receptor-deficient (db/db) mice and wild type controls. Higher serum concentrations of SM C18:1 and PC aa C38:0 in hyperglycemic individuals were found to be associated with lower estimated glomerular filtration rate (eGFR) and higher odds of CKD. In db/db mice, both metabolites had a significantly lower concentration in urine and adipose tissue, but higher in the lungs. Additionally, db/db mice had significantly higher SM C18:1 levels in plasma and liver, and PC aa C38:0 in adrenal glands. This cross-sectional human study confirms that SM C18:1 and PC aa C38:0 associate with kidney dysfunction in pre(diabetic) individuals, and the animal study suggests a potential implication of liver, lungs, adrenal glands, and visceral fat in their systemic regulation. Our results support further validation of the two phospholipids as early biomarkers of renal disease in patients with (pre)diabetes.
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Affiliation(s)
- Jialing Huang
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, 85764 Neuherberg, Germany; (J.H.); (M.C.); (M.R.); (J.A.); (L.W.); (C.G.)
- Institute of Epidemiology, Helmholtz Zentrum München, 85764 Neuherberg, Germany; (C.H.); (J.N.); (A.P.)
- German Center for Diabetes Research (DZD), 85764 München-Neuherberg, Germany;
| | - Marcela Covic
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, 85764 Neuherberg, Germany; (J.H.); (M.C.); (M.R.); (J.A.); (L.W.); (C.G.)
- Institute of Epidemiology, Helmholtz Zentrum München, 85764 Neuherberg, Germany; (C.H.); (J.N.); (A.P.)
- German Center for Diabetes Research (DZD), 85764 München-Neuherberg, Germany;
| | - Cornelia Huth
- Institute of Epidemiology, Helmholtz Zentrum München, 85764 Neuherberg, Germany; (C.H.); (J.N.); (A.P.)
| | - Martina Rommel
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, 85764 Neuherberg, Germany; (J.H.); (M.C.); (M.R.); (J.A.); (L.W.); (C.G.)
- Institute of Epidemiology, Helmholtz Zentrum München, 85764 Neuherberg, Germany; (C.H.); (J.N.); (A.P.)
| | - Jonathan Adam
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, 85764 Neuherberg, Germany; (J.H.); (M.C.); (M.R.); (J.A.); (L.W.); (C.G.)
- Institute of Epidemiology, Helmholtz Zentrum München, 85764 Neuherberg, Germany; (C.H.); (J.N.); (A.P.)
| | - Sven Zukunft
- Research Unit of Molecular Endocrinology and Metabolism, Helmholtz Zentrum München, 85764 Neuherberg, Germany; (S.Z.); (J.A.)
- Centre for Molecular Medicine, Institute for Vascular Signaling, Goethe University, 60323 Frankfurt am Main, Germany
| | - Cornelia Prehn
- Metabolomics and Proteomics Core Facility, Helmholtz Zentrum München, 85764 Neuherberg, Germany;
| | - Li Wang
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, 85764 Neuherberg, Germany; (J.H.); (M.C.); (M.R.); (J.A.); (L.W.); (C.G.)
- Institute of Epidemiology, Helmholtz Zentrum München, 85764 Neuherberg, Germany; (C.H.); (J.N.); (A.P.)
- Liaocheng People’s Hospital—Department of Scientific Research, Shandong University Postdoctoral Work Station, Liaocheng 252000, China
| | - Jana Nano
- Institute of Epidemiology, Helmholtz Zentrum München, 85764 Neuherberg, Germany; (C.H.); (J.N.); (A.P.)
- German Center for Diabetes Research (DZD), 85764 München-Neuherberg, Germany;
| | - Markus F. Scheerer
- Institute of Experimental Genetics, Helmholtz Zentrum München, 85764 Neuherberg, Germany; (M.F.S.); (S.N.)
- Bayer AG, Medical Affairs & Pharmacovigilance, 13353 Berlin, Germany
| | - Susanne Neschen
- Institute of Experimental Genetics, Helmholtz Zentrum München, 85764 Neuherberg, Germany; (M.F.S.); (S.N.)
- Sanofi Aventis Deutschland GmbH, Industriepark Hoechst, 65929 Frankfurt am Main, Germany
| | - Gabi Kastenmüller
- Institute of Computational Biology, Helmholtz Zentrum München, 85764 Neuherberg, Germany;
| | - Christian Gieger
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, 85764 Neuherberg, Germany; (J.H.); (M.C.); (M.R.); (J.A.); (L.W.); (C.G.)
- Institute of Epidemiology, Helmholtz Zentrum München, 85764 Neuherberg, Germany; (C.H.); (J.N.); (A.P.)
- German Center for Diabetes Research (DZD), 85764 München-Neuherberg, Germany;
| | - Michael Laxy
- Institute of Health Economics and Health Care Management, Helmholtz Zentrum München, 85764 Neuherberg, Germany;
| | | | - Jerzy Adamski
- Research Unit of Molecular Endocrinology and Metabolism, Helmholtz Zentrum München, 85764 Neuherberg, Germany; (S.Z.); (J.A.)
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117597, Singapore
- Chair of Experimental Genetics, Center of Life and Food Sciences Weihenstephan, Technische Universität München, 85353 Freising, Germany
| | - Karsten Suhre
- Department of Physiology and Biophysics, Weill Cornell Medical College in Qatar (WCMC-Q), Education City, Qatar Foundation, Doha P.O. Box 24144, Qatar;
| | - Martin Hrabe de Angelis
- German Center for Diabetes Research (DZD), 85764 München-Neuherberg, Germany;
- Institute of Experimental Genetics, Helmholtz Zentrum München, 85764 Neuherberg, Germany; (M.F.S.); (S.N.)
- Chair of Experimental Genetics, Center of Life and Food Sciences Weihenstephan, Technische Universität München, 85353 Freising, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, 85764 Neuherberg, Germany; (C.H.); (J.N.); (A.P.)
- German Center for Diabetes Research (DZD), 85764 München-Neuherberg, Germany;
| | - Rui Wang-Sattler
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, 85764 Neuherberg, Germany; (J.H.); (M.C.); (M.R.); (J.A.); (L.W.); (C.G.)
- Institute of Epidemiology, Helmholtz Zentrum München, 85764 Neuherberg, Germany; (C.H.); (J.N.); (A.P.)
- German Center for Diabetes Research (DZD), 85764 München-Neuherberg, Germany;
- Correspondence: ; Tel.: +49-89-3187-3978; Fax: + 49-89-3187-2428
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Pandey S, Adnan Siddiqui M, Azim A, Trigun SK, Sinha N. Serum metabolic profiles of septic shock patients based upon co-morbidities and other underlying conditions. Mol Omics 2021; 17:260-276. [PMID: 33399607 DOI: 10.1039/d0mo00177e] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Diagnosis and management of patients with septic shock is still a significant challenge for clinicians with its high mortality amongst hospitalized patients. Septic shock is a heterogeneous condition and is usually accompanied by various underlying disease conditions. Dissecting the specific metabolic changes induced by these underlying disease conditions through metabolomics has shown the potential to improve our understanding of the disease's relevant pathophysiological mechanisms, leading to improved treatment. This study has shown the metabolic alterations caused due to co-morbid conditions like diabetes, hypertension, CAD, and CKD in septic shock. It has also shown the distinct metabolic profiles of septic shock patients with underlying respiratory illnesses and encephalopathy. Metabolic profiling of sera obtained from 50 septic shock patients and 20 healthy controls was performed using high-resolution 1D 1H CPMG and diffusion-edited NMR spectra. Univariate and multivariate statistical analyses were performed to identify the potential molecular biomarkers. Noted dysregulations in amino acids, carbohydrates, and lipid metabolism were observed in septic shock patients. Further stratification within the septic shock patients based on co-morbid conditions and primary diagnosis has shown their role in causing metabolic alterations. Evaluation of these compounds during treatment will help design a personalized treatment protocol for the patients, improving therapeutics.
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Affiliation(s)
- Swarnima Pandey
- Centre of Biomedical Research, SGPGIMS Campus, Raebareli Road, Lucknow, 226014, India.
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32
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Zhang H, Shen Y, Kim IM, Weintraub NL, Tang Y. The Impaired Bioenergetics of Diabetic Cardiac Microvascular Endothelial Cells. Front Endocrinol (Lausanne) 2021; 12:642857. [PMID: 34054724 PMCID: PMC8160466 DOI: 10.3389/fendo.2021.642857] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/16/2020] [Accepted: 04/06/2021] [Indexed: 01/22/2023] Open
Abstract
Diabetes causes hyperglycemia, which can create a stressful environment for cardiac microvascular endothelial cells (CMECs). To investigate the impact of diabetes on the cellular metabolism of CMECs, we assessed glycolysis by quantifying the extracellular acidification rate (ECAR), and mitochondrial oxidative phosphorylation (OXPHOS) by measuring cellular oxygen consumption rate (OCR), in isolated CMECs from wild-type (WT) hearts and diabetic hearts (db/db) using an extracellular flux analyzer. Diabetic CMECs exhibited a higher level of intracellular reactive oxygen species (ROS), and significantly reduced glycolytic reserve and non-glycolytic acidification, as compared to WT CMECs. In addition, OCR assay showed that diabetic CMECs had increased maximal respiration, and significantly reduced non-mitochondrial oxygen consumption and proton leak. Quantitative PCR (qPCR) showed no difference in copy number of mitochondrial DNA (mtDNA) between diabetic and WT CMECs. In addition, gene expression profiling analysis showed an overall decrease in the expression of essential genes related to β-oxidation (Sirt1, Acox1, Acox3, Hadha, and Hadhb), tricarboxylic acid cycle (TCA) (Idh-3a and Ogdh), and electron transport chain (ETC) (Sdhd and Uqcrq) in diabetic CMECs compared to WT CMECs. Western blot confirmed that the protein expression of Hadha, Acox1, and Uqcrq was decreased in diabetic CMECs. Although lectin staining demonstrated no significant difference in capillary density between the hearts of WT mice and db/db mice, diabetic CMECs showed a lower percentage of cell proliferation by Ki67 staining, and a higher percentage of cellular apoptosis by TUNEL staining, compared with WT CMECs. In conclusion, excessive ROS caused by hyperglycemia is associated with impaired glycolysis and mitochondrial function in diabetic CMECs, which in turn may reduce proliferation and promote CMEC apoptosis.
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Affiliation(s)
- Haitao Zhang
- Vascular Biology Center, Medical College of Georgia, Augusta University, Augusta, GA, United States
| | - Yan Shen
- Vascular Biology Center, Medical College of Georgia, Augusta University, Augusta, GA, United States
| | - Il-man Kim
- Anatomy, Cell Biology & Physiology, School of Medicine, Indiana University, Indianapolis, IN, United States
| | - Neal L. Weintraub
- Vascular Biology Center, Medical College of Georgia, Augusta University, Augusta, GA, United States
| | - Yaoliang Tang
- Vascular Biology Center, Medical College of Georgia, Augusta University, Augusta, GA, United States
- *Correspondence: Yaoliang Tang,
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Pollo BJ, Teixeira CA, Belinato JR, Furlan MF, Cunha ICDM, Vaz CR, Volpato GV, Augusto F. Chemometrics, Comprehensive Two-Dimensional gas chromatography and “omics” sciences: Basic tools and recent applications. Trends Analyt Chem 2021. [DOI: 10.1016/j.trac.2020.116111] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
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Limonte CP, Valo E, Montemayor D, Afshinnia F, Ahluwalia TS, Costacou T, Darshi M, Forsblom C, Hoofnagle AN, Groop PH, Miller RG, Orchard TJ, Pennathur S, Rossing P, Sandholm N, Snell-Bergeon JK, Ye H, Zhang J, Natarajan L, de Boer IH, Sharma K. A Targeted Multiomics Approach to Identify Biomarkers Associated with Rapid eGFR Decline in Type 1 Diabetes. Am J Nephrol 2020; 51:839-848. [PMID: 33053547 PMCID: PMC7606554 DOI: 10.1159/000510830] [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] [Subscribe] [Scholar Register] [Received: 06/19/2020] [Accepted: 08/11/2020] [Indexed: 01/19/2023]
Abstract
BACKGROUND Individuals with type 1 diabetes (T1D) demonstrate varied trajectories of estimated glomerular filtration rate (eGFR) decline. The molecular pathways underlying rapid eGFR decline in T1D are poorly understood, and individual-level risk of rapid eGFR decline is difficult to predict. METHODS We designed a case-control study with multiple exposure measurements nested within 4 well-characterized T1D cohorts (FinnDiane, Steno, EDC, and CACTI) to identify biomarkers associated with rapid eGFR decline. Here, we report the rationale for and design of these studies as well as results of models testing associations of clinical characteristics with rapid eGFR decline in the study population, upon which "omics" studies will be built. Cases (n = 535) and controls (n = 895) were defined as having an annual eGFR decline of ≥3 and <1 mL/min/1.73 m2, respectively. Associations of demographic and clinical variables with rapid eGFR decline were tested using logistic regression, and prediction was evaluated using area under the curve (AUC) statistics. Targeted metabolomics, lipidomics, and proteomics are being performed using high-resolution mass-spectrometry techniques. RESULTS At baseline, the mean age was 43 years, diabetes duration was 27 years, eGFR was 94 mL/min/1.73 m2, and 62% of participants were normoalbuminuric. Over 7.6-year median follow-up, the mean annual change in eGFR in cases and controls was -5.7 and 0.6 mL/min/1.73 m2, respectively. Younger age, longer diabetes duration, and higher baseline HbA1c, urine albumin-creatinine ratio, and eGFR were significantly associated with rapid eGFR decline. The cross-validated AUC for the predictive model incorporating these variables plus sex and mean arterial blood pressure was 0.74 (95% CI: 0.68-0.79; p < 0.001). CONCLUSION Known risk factors provide moderate discrimination of rapid eGFR decline. Identification of blood and urine biomarkers associated with rapid eGFR decline in T1D using targeted omics strategies may provide insight into disease mechanisms and improve upon clinical predictive models using traditional risk factors.
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Affiliation(s)
- Christine P Limonte
- Division of Nephrology, Department of Medicine, University of Washington, Seattle, Washington, USA,
- Kidney Research Institute, University of Washington, Seattle, Washington, USA,
| | - Erkka Valo
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland
- Abdominal Center, Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Daniel Montemayor
- Division of Nephrology, UT Health Science Center San Antonio, San Antonio, Texas, USA
- Center for Renal Precision Medicine, Division of Nephrology, Department of Medicine, University of Texas Health San Antonio, San Antonio, Texas, USA
| | - Farsad Afshinnia
- Department of Internal Medicine-Nephrology, University of Michigan, Ann Arbor, Michigan, USA
| | - Tarunveer S Ahluwalia
- Steno Diabetes Center Copenhagen, Copenhagen, Denmark
- The Bioinformatics Centre, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Tina Costacou
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Manjula Darshi
- Division of Nephrology, UT Health Science Center San Antonio, San Antonio, Texas, USA
- Center for Renal Precision Medicine, Division of Nephrology, Department of Medicine, University of Texas Health San Antonio, San Antonio, Texas, USA
| | - Carol Forsblom
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland
- Abdominal Center, Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Andrew N Hoofnagle
- Division of Nephrology, Department of Medicine, University of Washington, Seattle, Washington, USA
- Department of Laboratory Medicine, University of Washington, Seattle, Washington, USA
| | - Per-Henrik Groop
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland
- Abdominal Center, Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Rachel G Miller
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Trevor J Orchard
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Subramaniam Pennathur
- Departments of Medicine-Nephrology and Molecular and Integrative Physiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Peter Rossing
- Steno Diabetes Center Copenhagen, Copenhagen, Denmark
- Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Niina Sandholm
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland
- Abdominal Center, Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Janet K Snell-Bergeon
- Barbara Davis Center for Diabetes, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
| | - Hongping Ye
- Division of Nephrology, UT Health Science Center San Antonio, San Antonio, Texas, USA
- Center for Renal Precision Medicine, Division of Nephrology, Department of Medicine, University of Texas Health San Antonio, San Antonio, Texas, USA
| | - Jing Zhang
- Division of Biostatistics and Bioinformatics, Department of Family Medicine and Public Health and UC San Diego Moores Comprehensive Cancer Center, La Jolla, California, USA
| | - Loki Natarajan
- Division of Biostatistics and Bioinformatics, Department of Family Medicine and Public Health and UC San Diego Moores Comprehensive Cancer Center, La Jolla, California, USA
| | - Ian H de Boer
- Division of Nephrology, Department of Medicine, University of Washington, Seattle, Washington, USA
- Kidney Research Institute, University of Washington, Seattle, Washington, USA
- Puget Sound VA Healthcare System, Seattle, Washington, USA
| | - Kumar Sharma
- Division of Nephrology, UT Health Science Center San Antonio, San Antonio, Texas, USA
- Center for Renal Precision Medicine, Division of Nephrology, Department of Medicine, University of Texas Health San Antonio, San Antonio, Texas, USA
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Curovic VR, Suvitaival T, Mattila I, Ahonen L, Trošt K, Theilade S, Hansen TW, Legido-Quigley C, Rossing P. Circulating Metabolites and Lipids Are Associated to Diabetic Retinopathy in Individuals With Type 1 Diabetes. Diabetes 2020; 69:2217-2226. [PMID: 32737117 PMCID: PMC7506826 DOI: 10.2337/db20-0104] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/27/2020] [Accepted: 07/29/2020] [Indexed: 12/17/2022]
Abstract
Omics-based methods may provide new markers associated to diabetic retinopathy (DR). We investigated a wide omics panel of metabolites and lipids related to DR in type 1 diabetes. Metabolomic analyses were performed using two-dimensional gas chromatography with time-of-flight mass spectrometry and lipidomic analyses using an ultra-high-performance liquid chromatography quadruple time-of-flight mass spectrometry method in 648 individuals with type 1 diabetes. Subjects were subdivided into no DR, mild nonproliferative DR (NPDR), moderate NPDR, proliferative DR, and proliferative DR with fibrosis. End points were any progression of DR, onset of DR, and progression from mild to severe DR tracked from standard ambulatory care and investigated using Cox models. The cohort consisted of 648 participants aged a mean of 54.4 ± 12.8 years, 55.5% were men, and follow-up was 5.1-5.5 years. Cross-sectionally, 2,4-dihydroxybutyric acid (DHBA), 3,4-DHBA, ribonic acid, ribitol, and the triglycerides 50:1 and 50:2 significantly correlated (P < 0.042) to DR stage. Longitudinally, higher 3,4-DHBA was a risk marker for progression of DR (n = 133) after adjustment (P = 0.033). We demonstrated multiple metabolites being positively correlated to a higher grade of DR in type 1 diabetes and several triglycerides being negatively correlated. Furthermore, higher 3,4-DHBA was an independent risk marker for progression of DR; however, confirmation is required.
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Affiliation(s)
| | | | - Ismo Mattila
- Steno Diabetes Center Copenhagen, Gentofte, Denmark
| | - Linda Ahonen
- Steno Diabetes Center Copenhagen, Gentofte, Denmark
| | | | | | | | - Cristina Legido-Quigley
- Steno Diabetes Center Copenhagen, Gentofte, Denmark
- Institute of Pharmaceutical Science, Faculty of Life Sciences & Medicine, King's College London, London, U.K
| | - Peter Rossing
- Steno Diabetes Center Copenhagen, Gentofte, Denmark
- University of Copenhagen, Copenhagen, Denmark
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Tofte N, Vogelzangs N, Mook-Kanamori D, Brahimaj A, Nano J, Ahmadizar F, van Dijk KW, Frimodt-Møller M, Arts I, Beulens JWJ, Rutters F, van der Heijden AA, Kavousi M, Stehouwer CDA, Nijpels G, van Greevenbroek MMJ, van der Kallen CJH, Rossing P, Ahluwalia TS, 't Hart LM. Plasma Metabolomics Identifies Markers of Impaired Renal Function: A Meta-analysis of 3089 Persons with Type 2 Diabetes. J Clin Endocrinol Metab 2020; 105:5818360. [PMID: 32271379 DOI: 10.1210/clinem/dgaa173] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/27/2019] [Accepted: 04/08/2020] [Indexed: 01/10/2023]
Abstract
CONTEXT There is a need for novel biomarkers and better understanding of the pathophysiology of diabetic kidney disease. OBJECTIVE To investigate associations between plasma metabolites and kidney function in people with type 2 diabetes (T2D). DESIGN 3089 samples from individuals with T2D, collected between 1999 and 2015, from 5 independent Dutch cohort studies were included. Up to 7 years follow-up was available in 1100 individuals from 2 of the cohorts. MAIN OUTCOME MEASURES Plasma metabolites (n = 149) were measured by nuclear magnetic resonance spectroscopy. Associations between metabolites and estimated glomerular filtration rate (eGFR), urinary albumin-to-creatinine ratio (UACR), and eGFR slopes were investigated in each study followed by random effect meta-analysis. Adjustments included traditional cardiovascular risk factors and correction for multiple testing. RESULTS In total, 125 metabolites were significantly associated (PFDR = 1.5×10-32 - 0.046; β = -11.98-2.17) with eGFR. Inverse associations with eGFR were demonstrated for branched-chain and aromatic amino acids (AAAs), glycoprotein acetyls, triglycerides (TGs), lipids in very low-density lipoproteins (VLDL) subclasses, and fatty acids (PFDR < 0.03). We observed positive associations with cholesterol and phospholipids in high-density lipoproteins (HDL) and apolipoprotein A1 (PFDR < 0.05). Albeit some metabolites were associated with UACR levels (P < 0.05), significance was lost after correction for multiple testing. Tyrosine and HDL-related metabolites were positively associated with eGFR slopes before adjustment for multiple testing (PTyr = 0.003; PHDLrelated < 0.05), but not after. CONCLUSIONS This study identified metabolites associated with impaired kidney function in T2D, implying involvement of lipid and amino acid metabolism in the pathogenesis. Whether these processes precede or are consequences of renal impairment needs further investigation.
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Affiliation(s)
- Nete Tofte
- Steno Diabetes Center, Copenhagen, Denmark
| | - Nicole Vogelzangs
- Department of Epidemiology & Maastricht Centre for Systems Biology (MaCSBio), Maastricht University, Maastricht, the Netherlands
- Cardiovascular Research Institute Maastricht (CARIM), Maastricht University, Maastricht, the Netherlands
| | - Dennis Mook-Kanamori
- Departments of Clinical Epidemiology and Public Health and Primary Care, Leiden University Medical Center, Leiden, the Netherlands
| | - Adela Brahimaj
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
- Department of General Practice, Erasmus Medical Center, Rotterdam, the Netherlands
| | - Jana Nano
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
- Institute of Epidemiology, Helmholtz Zentrum, Munich, Germany
- German Center for Diabetes Research, Munich, Germany
| | - Fariba Ahmadizar
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Ko Willems van Dijk
- Departments of Human Genetics and Internal Medicine/Endocrinology, Leiden University Medical Center, Leiden, the Netherlands
| | | | - Ilja Arts
- Department of Epidemiology & Maastricht Centre for Systems Biology (MaCSBio), Maastricht University, Maastricht, the Netherlands
- Cardiovascular Research Institute Maastricht (CARIM), Maastricht University, Maastricht, the Netherlands
| | - Joline W J Beulens
- Department of Epidemiology and Biostatistics, Amsterdam University Medical Center, Amsterdam, the Netherlands
| | - Femke Rutters
- Department of Epidemiology and Biostatistics, Amsterdam University Medical Center, Amsterdam, the Netherlands
| | - Amber A van der Heijden
- Department of General Practice and Elderly Care Medicine, Amsterdam University Medical Center, Amsterdam, the Netherlands
| | - Maryam Kavousi
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Coen D A Stehouwer
- Cardiovascular Research Institute Maastricht (CARIM), Maastricht University, Maastricht, the Netherlands
- Department of Internal Medicine, Maastricht University Medical Center, Maastricht, the Netherlands
| | - Giel Nijpels
- Department of General Practice and Elderly Care Medicine, Amsterdam University Medical Center, Amsterdam, the Netherlands
| | - Marleen M J van Greevenbroek
- Cardiovascular Research Institute Maastricht (CARIM), Maastricht University, Maastricht, the Netherlands
- Department of Internal Medicine, Maastricht University Medical Center, Maastricht, the Netherlands
| | - Carla J H van der Kallen
- Cardiovascular Research Institute Maastricht (CARIM), Maastricht University, Maastricht, the Netherlands
- Department of Internal Medicine, Maastricht University Medical Center, Maastricht, the Netherlands
| | - Peter Rossing
- Steno Diabetes Center, Copenhagen, Denmark
- University of Copenhagen, Copenhagen, Denmark
| | | | - Leen M 't Hart
- Department of Epidemiology and Biostatistics, Amsterdam University Medical Center, Amsterdam, the Netherlands
- Department of Cell and Chemical Biology & Department of Biomedical Data Sciences, Section Molecular Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
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Omics research in diabetic kidney disease: new biomarker dimensions and new understandings? J Nephrol 2020; 33:931-948. [DOI: 10.1007/s40620-020-00759-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2020] [Accepted: 05/23/2020] [Indexed: 12/14/2022]
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