1
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Chen Z, Satake E, Pezzolesi MG, Md Dom ZI, Stucki D, Kobayashi H, Syreeni A, Johnson AT, Wu X, Dahlström EH, King JB, Groop PH, Rich SS, Sandholm N, Krolewski AS, Natarajan R. Integrated analysis of blood DNA methylation, genetic variants, circulating proteins, microRNAs, and kidney failure in type 1 diabetes. Sci Transl Med 2024; 16:eadj3385. [PMID: 38776390 DOI: 10.1126/scitranslmed.adj3385] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Accepted: 04/30/2024] [Indexed: 05/25/2024]
Abstract
Variation in DNA methylation (DNAmet) in white blood cells and other cells/tissues has been implicated in the etiology of progressive diabetic kidney disease (DKD). However, the specific mechanisms linking DNAmet variation in blood cells with risk of kidney failure (KF) and utility of measuring blood cell DNAmet in personalized medicine are not clear. We measured blood cell DNAmet in 277 individuals with type 1 diabetes and DKD using Illumina EPIC arrays; 51% of the cohort developed KF during 7 to 20 years of follow-up. Our epigenome-wide analysis identified DNAmet at 17 CpGs (5'-cytosine-phosphate-guanine-3' loci) associated with risk of KF independent of major clinical risk factors. DNAmet at these KF-associated CpGs remained stable over a median period of 4.7 years. Furthermore, DNAmet variations at seven KF-associated CpGs were strongly associated with multiple genetic variants at seven genomic regions, suggesting a strong genetic influence on DNAmet. The effects of DNAmet variations at the KF-associated CpGs on risk of KF were partially mediated by multiple KF-associated circulating proteins and KF-associated circulating miRNAs. A prediction model for risk of KF was developed by adding blood cell DNAmet at eight selected KF-associated CpGs to the clinical model. This updated model significantly improved prediction performance (c-statistic = 0.93) versus the clinical model (c-statistic = 0.85) at P = 6.62 × 10-14. In conclusion, our multiomics study provides insights into mechanisms through which variation of DNAmet may affect KF development and shows that blood cell DNAmet at certain CpGs can improve risk prediction for KF in T1D.
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Affiliation(s)
- Zhuo Chen
- Department of Diabetes Complications and Metabolism, Arthur Riggs Diabetes and Metabolism Research Institute and Beckman Research Institute of City of Hope, Duarte, CA 91010, USA
| | - Eiichiro Satake
- Section on Genetics and Epidemiology, Research Division, Joslin Diabetes Center, Boston, MA 02215, USA
- Department of Medicine, Harvard Medical School, Boston, MA 02215, USA
| | - Marcus G Pezzolesi
- Department of Internal Medicine, Division of Nephrology and Hypertension, University of Utah School of Medicine, Salt Lake City, UT 84132, USA
| | - Zaipul I Md Dom
- Section on Genetics and Epidemiology, Research Division, Joslin Diabetes Center, Boston, MA 02215, USA
- Department of Medicine, Harvard Medical School, Boston, MA 02215, USA
| | - Devorah Stucki
- Department of Internal Medicine, Division of Nephrology and Hypertension, University of Utah School of Medicine, Salt Lake City, UT 84132, USA
| | - Hiroki Kobayashi
- Section on Genetics and Epidemiology, Research Division, Joslin Diabetes Center, Boston, MA 02215, USA
- Department of Medicine, Harvard Medical School, Boston, MA 02215, USA
- Division of Nephrology, Hypertension, and Endocrinology, Nihon University School of Medicine, Tokyo, Japan
| | - Anna Syreeni
- Folkhälsan Research Center, Helsinki, 00290, Finland
- Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, 00290, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, 00290, Finland
| | - Adam T Johnson
- Department of Internal Medicine, Division of Nephrology and Hypertension, University of Utah School of Medicine, Salt Lake City, UT 84132, USA
| | - Xiwei Wu
- Department of Computational and Quantitative Medicine, Beckman Research Institute of City of Hope, Duarte, CA 91010, USA
- Integrative Genomics Core, Beckman Research Institute of City of Hope, Duarte, CA 91010, USA
| | - Emma H Dahlström
- Folkhälsan Research Center, Helsinki, 00290, Finland
- Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, 00290, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, 00290, Finland
| | - Jaxon B King
- Department of Internal Medicine, Division of Nephrology and Hypertension, University of Utah School of Medicine, Salt Lake City, UT 84132, USA
| | - Per-Henrik Groop
- Folkhälsan Research Center, Helsinki, 00290, Finland
- Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, 00290, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, 00290, Finland
- Department of Diabetes, Central Clinical School, Monash University, Melbourne, VIC, 3004, Australia
| | - Stephen S Rich
- Center for Public Health Genomics and Department of Public Health Sciences, University of Virginia, Charlottesville, VA 22908, USA
| | - Niina Sandholm
- Folkhälsan Research Center, Helsinki, 00290, Finland
- Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, 00290, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, 00290, Finland
| | - Andrzej S Krolewski
- Section on Genetics and Epidemiology, Research Division, Joslin Diabetes Center, Boston, MA 02215, USA
- Department of Medicine, Harvard Medical School, Boston, MA 02215, USA
| | - Rama Natarajan
- Department of Diabetes Complications and Metabolism, Arthur Riggs Diabetes and Metabolism Research Institute and Beckman Research Institute of City of Hope, Duarte, CA 91010, USA
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2
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Limonte CP, Gao X, Bebu I, Seegmiller JC, Lorenzi GM, Perkins BA, Karger AB, Arends VL, Paterson A, Molitch ME, de Boer IH. Longitudinal Trajectories of Biomarkers of Kidney Tubular Function in Type 1 Diabetes. Kidney Int Rep 2024; 9:1406-1418. [PMID: 38707816 PMCID: PMC11068962 DOI: 10.1016/j.ekir.2023.11.030] [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: 09/06/2023] [Accepted: 11/06/2023] [Indexed: 05/07/2024] Open
Abstract
Introduction Tubular biomarkers may shed insight into progression of kidney tubulointerstitial pathology complementary to traditional measures of glomerular function and damage. Methods We examined trajectories of tubular biomarkers in the Diabetes Control and Complications Trial and the Epidemiology of Diabetes Interventions and Complications Study (DCCT/EDIC Study) of type 1 diabetes (T1D). Biomarkers were measured in a subset of 220 participants across 7 time points over 26 years. Measurements included the following: kidney injury molecule 1 (KIM-1), soluble tumor necrosis factor 1 (sTNFR1) in serum or plasma, epidermal growth factor (EGF), monocyte chemoattractant protein-1 (MCP1) in timed urine, and a composite tubular secretion score. We described biomarker trajectories and examined how these were affected by intensive glucose-lowering therapy and glycemia. Results At baseline, participants had a mean age of 28 years, 45% were women, and 50% were assigned to intensive glucose-lowering therapy. The mean estimated glomerular filtration rate (eGFR) was 125 ml/min per 1.73 m2 and 90% of participants had a urinary albumin excretion rate (AER) <30 mg/24h. Mean changes in biomarkers over time (percent/decade) were: KIM-1: 27.3% (95% confidence interval [CI]: 21.4-33.5), sTNFR1: 16.9% (14.5-19.3), MCP1: 18.4% (8.9-28.8), EGF: -13.5% (-16.7 to -10.1), EGF-MCP1 ratio: -26.9% (-32.2 to -21.3), and tubular secretion score -0.9% (-1.8 to 0.0), versus -12.0% (CI: -12.9 to -11.1) for eGFR and 10.9% (2.5-20.1) for AER. Intensive versus conventional glucose-lowering therapy was associated with slower increase in sTNFR1 (relative difference in change: 0.94 [0.90-0.98]). Higher HbA1c was associated with faster increases in sTNFR1 (relative difference in change: 1.06 per 1% higher HbA1c [1.05-1.08]) and KIM-1 (1.09 [1.05-1.14]). Conclusion Among participants with T1D and normal eGFR at baseline, kidney tubular biomarkers changed significantly over long-term follow-up. Hyperglycemia was associated with larger increases in serum or plasma sTNFR1 and KIM-1, when followed-up longitudinally.
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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
| | - Xiaoyu Gao
- Biostatistics Center, The George Washington University, Rockville, Maryland, USA
| | - Ionut Bebu
- Biostatistics Center, The George Washington University, Rockville, Maryland, USA
| | - Jesse C. Seegmiller
- Department of Laboratory Medicine and Pathology, School of Medicine, University of Minnesota, Minneapolis, Minnesota, USA
| | - Gayle M. Lorenzi
- Department of Medicine, University of California, San Diego, La Jolla, California, USA
| | - Bruce A. Perkins
- Division of Endocrinology, Department of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Amy B. Karger
- Department of Laboratory Medicine and Pathology, School of Medicine, University of Minnesota, Minneapolis, Minnesota, USA
| | - Valerie L. Arends
- Department of Laboratory Medicine and Pathology, School of Medicine, University of Minnesota, Minneapolis, Minnesota, USA
| | - Andrew Paterson
- Program in Genetics and Genome Biology, Hospital for Sick Children, University of Toronto, Toronto, Ontario, Canada
| | - Mark E. Molitch
- Division of Endocrinology, Metabolism, and Molecular Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, 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
| | - DCCT/EDIC Research Group9
- Division of Nephrology, Department of Medicine, University of Washington, Seattle, Washington, USA
- Kidney Research Institute, University of Washington, Seattle, Washington, USA
- Biostatistics Center, The George Washington University, Rockville, Maryland, USA
- Department of Laboratory Medicine and Pathology, School of Medicine, University of Minnesota, Minneapolis, Minnesota, USA
- Department of Medicine, University of California, San Diego, La Jolla, California, USA
- Division of Endocrinology, Department of Medicine, University of Toronto, Toronto, Ontario, Canada
- Program in Genetics and Genome Biology, Hospital for Sick Children, University of Toronto, Toronto, Ontario, Canada
- Division of Endocrinology, Metabolism, and Molecular Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
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3
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Lin JS, Nano J, Petrera A, Hauck SM, Zeller T, Koenig W, Müller CL, Peters A, Thorand B. Proteomic profiling of longitudinal changes in kidney function among middle-aged and older men and women: the KORA S4/F4/FF4 study. BMC Med 2023; 21:245. [PMID: 37407978 DOI: 10.1186/s12916-023-02962-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Accepted: 06/26/2023] [Indexed: 07/07/2023] Open
Abstract
BACKGROUND Due to the asymptomatic nature of the early stages, chronic kidney disease (CKD) is usually diagnosed at late stages and lacks targeted therapy, highlighting the need for new biomarkers to better understand its pathophysiology and to be used for early diagnosis and therapeutic targets. Given the close relationship between CKD and cardiovascular disease (CVD), we investigated the associations of 233 CVD- and inflammation-related plasma proteins with kidney function decline and aimed to assess whether the observed associations are causal. METHODS We included 1140 participants, aged 55-74 years at baseline, from the Cooperative Health Research in the Region of Augsburg (KORA) cohort study, with a median follow-up time of 13.4 years and 2 follow-up visits. We measured 233 plasma proteins using a proximity extension assay at baseline. In the discovery analysis, linear regression models were used to estimate the associations of 233 proteins with the annual rate of change in creatinine-based estimated glomerular filtration rate (eGFRcr). We further investigated the association of eGFRcr-associated proteins with the annual rate of change in cystatin C-based eGFR (eGFRcys) and eGFRcr-based incident CKD. Two-sample Mendelian randomization was used to infer causality. RESULTS In the fully adjusted model, 66 out of 233 proteins were inversely associated with the annual rate of change in eGFRcr, indicating that higher baseline protein levels were associated with faster eGFRcr decline. Among these 66 proteins, 21 proteins were associated with both the annual rate of change in eGFRcys and incident CKD. Mendelian randomization analyses on these 21 proteins suggest a potential causal association of higher tumor necrosis factor receptor superfamily member 11A (TNFRSF11A) level with eGFR decline. CONCLUSIONS We reported 21 proteins associated with kidney function decline and incident CKD and provided preliminary evidence suggesting a potential causal association between TNFRSF11A and kidney function decline. Further Mendelian randomization studies are needed to establish a conclusive causal association.
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Affiliation(s)
- Jie-Sheng Lin
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Ingolstädter Landstraße 1, 85764, Neuherberg, Germany
- Institute for Medical Information Processing, Biometry, and Epidemiology (IBE), Faculty of Medicine, LMU Munich, Pettenkofer School of Public Health, Munich, Germany
| | - Jana Nano
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Ingolstädter Landstraße 1, 85764, Neuherberg, Germany
- Chair of Epidemiology, Institute for Medical Information Processing, Biometry, and Epidemiology (IBE), Ludwig-Maximilians-Universität München, Munich, Germany
| | - Agnese Petrera
- Metabolomics and Proteomics Core, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
| | - Stefanie M Hauck
- Metabolomics and Proteomics Core, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
| | - Tanja Zeller
- University Center of Cardiovascular Science, University Heart and Vascular Center, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- German Center for Cardiovascular Research (DZHK), Partner Site Hamburg, Hamburg, Germany
| | - Wolfgang Koenig
- Deutsches Herzzentrum München, Technische Universität München, Munich, Germany
- German Center for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
- Institute of Epidemiology and Medical Biometry, University of Ulm, Ulm, Germany
| | - Christian L Müller
- Institute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
- Helmholtz AI, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
- Department of Statistics, Ludwig-Maximilians-Universität München, Munich, Germany
- Center for Computational Mathematics, Flatiron Institute, New York, USA
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Ingolstädter Landstraße 1, 85764, Neuherberg, Germany
- Chair of Epidemiology, Institute for Medical Information Processing, Biometry, and Epidemiology (IBE), Ludwig-Maximilians-Universität München, Munich, Germany
- German Center for Diabetes Research (DZD), Partner München-Neuherberg, Neuherberg, Germany
| | - Barbara Thorand
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Ingolstädter Landstraße 1, 85764, Neuherberg, Germany.
- German Center for Diabetes Research (DZD), Partner München-Neuherberg, Neuherberg, Germany.
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4
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Grobe N, Scheiber J, Zhang H, Garbe C, Wang X. Omics and Artificial Intelligence in Kidney Diseases. ADVANCES IN KIDNEY DISEASE AND HEALTH 2023; 30:47-52. [PMID: 36723282 DOI: 10.1053/j.akdh.2022.11.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/06/2022] [Revised: 10/28/2022] [Accepted: 11/16/2022] [Indexed: 01/20/2023]
Abstract
Omics applications in nephrology may have relevance in the future to improve clinical care of kidney disease patients. In a short term, patients will benefit from specific measurement and computational analyses around biomarkers identified at various omics-levels. In mid term and long term, these approaches will need to be integrated into a holistic representation of the kidney and all its influencing factors for individualized patient care. Research demonstrates robust data to justify the application of omics for better understanding, risk stratification, and individualized treatment of kidney disease patients. Despite these advances in the research setting, there is still a lack of evidence showing the combination of omics technologies with artificial intelligence and its application in clinical diagnostics and care of patients with kidney disease.
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Affiliation(s)
| | | | | | - Christian Garbe
- Frankfurter Innovationszentrum Biotechnologie, Frankfurt am Main, Germany
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5
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Lousa I, Reis F, Santos-Silva A, Belo L. The Signaling Pathway of TNF Receptors: Linking Animal Models of Renal Disease to Human CKD. Int J Mol Sci 2022; 23:ijms23063284. [PMID: 35328704 PMCID: PMC8950598 DOI: 10.3390/ijms23063284] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Revised: 03/15/2022] [Accepted: 03/16/2022] [Indexed: 11/25/2022] Open
Abstract
Chronic kidney disease (CKD) has been recognized as a global public health problem. Despite the current advances in medicine, CKD-associated morbidity and mortality remain unacceptably high. Several studies have highlighted the contribution of inflammation and inflammatory mediators to the development and/or progression of CKD, such as tumor necrosis factor (TNF)-related biomarkers. The inflammation pathway driven by TNF-α, through TNF receptors 1 (TNFR1) and 2 (TNFR2), involves important mediators in the pathogenesis of CKD. Circulating levels of TNFRs were associated with changes in other biomarkers of kidney function and injury, and were described as predictors of disease progression, cardiovascular morbidity, and mortality in several cohorts of patients. Experimental studies describe the possible downstream signaling pathways induced upon TNFR activation and the resulting biological responses. This review will focus on the available data on TNFR1 and TNFR2, and illustrates their contributions to the pathophysiology of kidney diseases, their cellular and molecular roles, as well as their potential as CKD biomarkers. The emerging evidence shows that TNF receptors could act as biomarkers of renal damage and as mediators of the disease. Furthermore, it has been suggested that these biomarkers could significantly improve the discrimination of clinical CKD prognostic models.
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Affiliation(s)
- Irina Lousa
- Associate Laboratory i4HB-Institute for Health and Bioeconomy, Faculty of Pharmacy, University of Porto, 4050-313 Porto, Portugal; (I.L.); (A.S.-S.)
- UCIBIO—Applied Molecular Biosciences Unit, Laboratory of Biochemistry, Department of Biological Sciences, Faculty of Pharmacy, University of Porto, 4050-313 Porto, Portugal
| | - Flávio Reis
- Institute of Pharmacology & Experimental Therapeutics & Coimbra Institute for Clinical and Biomedical Research (iCBR), Faculty of Medicine, University of Coimbra, 3000-548 Coimbra, Portugal;
- Center for Innovative Biomedicine and Biotechnology (CIBB), University of Coimbra, 3004-504 Coimbra, Portugal
- Clinical Academic Center of Coimbra (CACC), 3000-075 Coimbra, Portugal
| | - Alice Santos-Silva
- Associate Laboratory i4HB-Institute for Health and Bioeconomy, Faculty of Pharmacy, University of Porto, 4050-313 Porto, Portugal; (I.L.); (A.S.-S.)
- UCIBIO—Applied Molecular Biosciences Unit, Laboratory of Biochemistry, Department of Biological Sciences, Faculty of Pharmacy, University of Porto, 4050-313 Porto, Portugal
| | - Luís Belo
- Associate Laboratory i4HB-Institute for Health and Bioeconomy, Faculty of Pharmacy, University of Porto, 4050-313 Porto, Portugal; (I.L.); (A.S.-S.)
- UCIBIO—Applied Molecular Biosciences Unit, Laboratory of Biochemistry, Department of Biological Sciences, Faculty of Pharmacy, University of Porto, 4050-313 Porto, Portugal
- Correspondence:
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6
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Perkins BA, Bebu I, Gao X, Karger AB, Hirsch IB, Karanchi H, Molitch ME, Zinman B, Lachin JM, de Boer IH. Early Trajectory of Estimated Glomerular Filtration Rate and Long-term Advanced Kidney and Cardiovascular Complications in Type 1 Diabetes. Diabetes Care 2022; 45:585-593. [PMID: 35015817 PMCID: PMC8918200 DOI: 10.2337/dc21-1883] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/06/2021] [Accepted: 11/21/2021] [Indexed: 02/03/2023]
Abstract
OBJECTIVE Rapid loss of estimated glomerular filtration rate (eGFR) within its normal range has been proposed as a strong predictor of future kidney disease. We investigated this association of eGFR slope early in the course of type 1 diabetes with long-term incidence of kidney and cardiovascular complications. RESEARCH DESIGN AND METHODS The annual percentage change in eGFR (slope) was calculated during the Diabetes Control and Complications Trial (DCCT) for each of 1,441 participants over a mean of 6.5 years and dichotomized by the presence or absence of early rapid eGFR loss (slope ≤-3% per year) as the exposure of interest. Outcomes were incident reduced eGFR (eGFR <60 mL/min/1.73 m2), composite cardiovascular events, or major adverse cardiovascular events (MACE) during the subsequent 24 years post-DCCT closeout follow-up. RESULTS At DCCT closeout (the baseline for this analysis), diabetes duration was 12 ± 4.8 years, most participants (85.9%) had normoalbuminuria, mean eGFR was 117.0 ± 13.4 mL/min/1.73 m2, and 149 (10.4%) had experienced early rapid eGFR loss over the preceding trial phase. Over the 24-year subsequent follow-up, there were 187 reduced eGFR (6.3 per 1,000 person-years) and 113 MACE (3.6 per 1,000 person-years) events. Early rapid eGFR loss was associated with risk of reduced eGFR (hazard ratio [HR] 1.81, 95% CI 1.18-2.79, P = 0.0064), but not after adjustment for baseline eGFR level (HR 0.94, 95% CI 0.53-1.66, P = 0.84). There was no association with composite cardiovascular events or MACE. CONCLUSIONS In people with type 1 diabetes primarily with normal eGFR and normoalbuminuria, the preceding slope of eGFR confers no additional association with kidney or cardiovascular outcomes beyond knowledge of an individual's current level.
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Affiliation(s)
- Bruce A Perkins
- Department of Endocrinology and Metabolism, University of Toronto, Toronto, Ontario, Canada
| | - Ionut Bebu
- The Biostatistics Center, Milken Institute School of Public Health, The George Washington University, Washington, DC
| | - Xiaoyu Gao
- The George Washington University, Washington, DC
| | - Amy B Karger
- University of Minnesota Twin Cities, Twin Cities, MN
| | - Irl B Hirsch
- Division of Metabolism, Endocrinology, and Nutrition, Department of Medicine, University of Washington, Seattle, WA
| | - Harsha Karanchi
- Department of Medicine, Medical University of South Carolina, Charleston, SC
| | - Mark E Molitch
- Endocrinology, Metabolism and Molecular Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Bernard Zinman
- Departments of Endocrinology and Metabolism, Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada
| | - John M Lachin
- The Biostatistics Center, Milken Institute School of Public Health, The George Washington University, Washington, DC
| | - Ian H de Boer
- Division of Metabolism, Endocrinology, and Nutrition, Department of Medicine, University of Washington, Seattle, WA
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7
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Afshinnia F, Rajendiran TM, He C, Byun J, Montemayor D, Darshi M, Tumova J, Kim J, Limonte CP, Miller RG, Costacou T, Orchard TJ, Ahluwalia TS, Rossing P, Snell-Bergeon JK, de Boer IH, Natarajan L, Michailidis G, Sharma K, Pennathur S. Circulating Free Fatty Acid and Phospholipid Signature Predicts Early Rapid Kidney Function Decline in Patients With Type 1 Diabetes. Diabetes Care 2021; 44:2098-2106. [PMID: 34244329 PMCID: PMC8740931 DOI: 10.2337/dc21-0737] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/04/2021] [Accepted: 05/27/2021] [Indexed: 02/03/2023]
Abstract
OBJECTIVES Patients with type 1 diabetes (T1D) exhibit modest lipid abnormalities as measured by traditional metrics. This study aimed to identify lipidomic predictors of rapid decline of kidney function in T1D. RESEARCH DESIGN AND METHODS In a case-control study, 817 patients with T1D from three large cohorts were randomly split into training and validation subsets. Case was defined as >3 mL/min/1.73 m2 per year decline in estimated glomerular filtration rate (eGFR), while control was defined as <1 mL/min/1.73 m2 per year decline over a minimum 4-year follow-up. Lipids were quantified in baseline serum samples using a targeted mass spectrometry lipidomic platform. RESULTS At individual lipids, free fatty acid (FFA)20:2 was directly and phosphatidylcholine (PC)16:0/22:6 was inversely and independently associated with rapid eGFR decline. When examined by lipid class, rapid eGFR decline was characterized by higher abundance of unsaturated FFAs, phosphatidylethanolamine (PE)-Ps, and PCs with an unsaturated acyl chain at the sn1 carbon, and by lower abundance of saturated FFAs, longer triacylglycerols, and PCs, PEs, PE-Ps, and PE-Os with an unsaturated acyl chain at the sn1 carbon at eGFR ≥90 mL/min/1.73 m2. A multilipid panel consisting of unsaturated FFAs and saturated PE-Ps predicted rapid eGFR decline better than individual lipids (C-statistic, 0.71) and improved the C-statistic of the clinical model from 0.816 to 0.841 (P = 0.039). Observations were confirmed in the validation subset. CONCLUSIONS Distinct from previously reported predictors of GFR decline in type 2 diabetes, these findings suggest differential incorporation of FFAs at the sn1 carbon of the phospholipids' glycerol backbone as an independent predictor of rapid GFR decline in T1D.
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Affiliation(s)
- Farsad Afshinnia
- Department of Internal Medicine-Nephrology, University of Michigan, Ann Arbor, MI
| | - Thekkelnaycke M Rajendiran
- Michigan Regional Comprehensive Metabolomics Resource Core, University of Michigan, Ann Arbor, MI.,Department of Pathology, University of Michigan, Ann Arbor, MI
| | - Chenchen He
- Department of Internal Medicine-Nephrology, University of Michigan, Ann Arbor, MI
| | - Jaeman Byun
- Department of Internal Medicine-Nephrology, University of Michigan, Ann Arbor, MI
| | - Daniel Montemayor
- Division of Nephrology, University of Texas Health Science Center San Antonio, San Antonio, TX.,Center for Renal Precision Medicine, Division of Nephrology, Department of Medicine, University of Texas Health Science Center San Antonio, San Antonio, TX
| | - Manjula Darshi
- Division of Nephrology, University of Texas Health Science Center San Antonio, San Antonio, TX.,Center for Renal Precision Medicine, Division of Nephrology, Department of Medicine, University of Texas Health Science Center San Antonio, San Antonio, TX
| | - Jana Tumova
- Division of Nephrology, University of Texas Health Science Center San Antonio, San Antonio, TX.,Center for Renal Precision Medicine, Division of Nephrology, Department of Medicine, University of Texas Health Science Center San Antonio, San Antonio, TX
| | - Jiwan Kim
- Division of Nephrology, University of Texas Health Science Center San Antonio, San Antonio, TX.,Center for Renal Precision Medicine, Division of Nephrology, Department of Medicine, University of Texas Health Science Center San Antonio, San Antonio, TX
| | - Christine P Limonte
- Division of Nephrology, Department of Medicine, University of Washington, Seattle, WA.,Kidney Research Institute, University of Washington, Seattle, WA
| | - Rachel G Miller
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA
| | - Tina Costacou
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA
| | - Trevor J Orchard
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA
| | - Tarunveer S Ahluwalia
- Steno Diabetes Center Copenhagen, Copenhagen, Denmark.,Department of Biology, The Bioinformatics Center, University of Copenhagen, Copenhagen, Denmark
| | - Peter Rossing
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark.,Barbara Davis Center for Diabetes, University of Colorado Anschutz Medical Campus, Aurora, CO
| | - Janet K Snell-Bergeon
- Barbara Davis Center for Diabetes, University of Colorado Anschutz Medical Campus, Aurora, CO
| | - Ian H de Boer
- Division of Nephrology, Department of Medicine, University of Washington, Seattle, WA.,Kidney Research Institute, University of Washington, Seattle, WA.,Puget Sound Veterans Affairs Healthcare System, Seattle, WA
| | - Loki Natarajan
- Division of Biostatistics and Bioinformatics, Herbert Wertheim School of Public Health and Human Longevity Science and Moores Cancer Center, University of California San Diego, La Jolla, CA
| | - George Michailidis
- Department of Statistics and the Informatics Institute, University of Florida, Gainesville, FL
| | - Kumar Sharma
- Division of Nephrology, University of Texas Health Science Center San Antonio, San Antonio, TX .,Center for Renal Precision Medicine, Division of Nephrology, Department of Medicine, University of Texas Health Science Center San Antonio, San Antonio, TX
| | - Subramaniam Pennathur
- Department of Internal Medicine-Nephrology, University of Michigan, Ann Arbor, MI .,Michigan Regional Comprehensive Metabolomics Resource Core, University of Michigan, Ann Arbor, MI.,Department of Molecular and Integrative Physiology, University of Michigan, Ann Arbor, MI
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8
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Satake E, Saulnier PJ, Kobayashi H, Gupta MK, Looker HC, Wilson JM, Md Dom ZI, Ihara K, O’Neil K, Krolewski B, Pipino C, Pavkov ME, Nair V, Bitzer M, Niewczas MA, Kretzler M, Mauer M, Doria A, Najafian B, Kulkarni RN, Duffin KL, Pezzolesi MG, Kahn CR, Nelson RG, Krolewski AS. Comprehensive Search for Novel Circulating miRNAs and Axon Guidance Pathway Proteins Associated with Risk of ESKD in Diabetes. J Am Soc Nephrol 2021; 32:2331-2351. [PMID: 34140396 PMCID: PMC8729832 DOI: 10.1681/asn.2021010105] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2021] [Accepted: 04/23/2021] [Indexed: 02/04/2023] Open
Abstract
BACKGROUND Mechanisms underlying the pro gression of diabetic kidney disease to ESKD are not fully understood. METHODS We performed global microRNA (miRNA) analysis on plasma from two cohorts consisting of 375 individuals with type 1 and type 2 diabetes with late diabetic kidney disease, and targeted proteomics analysis on plasma from four cohorts consisting of 746 individuals with late and early diabetic kidney disease. We examined structural lesions in kidney biopsy specimens from the 105 individuals with early diabetic kidney disease. Human umbilical vein endothelial cells were used to assess the effects of miRNA mimics or inhibitors on regulation of candidate proteins. RESULTS In the late diabetic kidney disease cohorts, we identified 17 circulating miRNAs, represented by four exemplars (miR-1287-5p, miR-197-5p, miR-339-5p, and miR-328-3p), that were strongly associated with 10-year risk of ESKD. These miRNAs targeted proteins in the axon guidance pathway. Circulating levels of six of these proteins-most notably, EFNA4 and EPHA2-were strongly associated with 10-year risk of ESKD in all cohorts. Furthermore, circulating levels of these proteins correlated with severity of structural lesions in kidney biopsy specimens. In contrast, expression levels of genes encoding these proteins had no apparent effects on the lesions. In in vitro experiments, mimics of miR-1287-5p and miR-197-5p and inhibitors of miR-339-5p and miR-328-3p upregulated concentrations of EPHA2 in either cell lysate, supernatant, or both. CONCLUSIONS This study reveals novel mechanisms involved in progression to ESKD and points to the importance of systemic factors in the development of diabetic kidney disease. Some circulating miRNAs and axon guidance pathway proteins represent potential targets for new therapies to prevent and treat this condition.
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Affiliation(s)
- Eiichiro Satake
- Research Division, Joslin Diabetes Center, Boston, Massachusetts,Department of Medicine, Harvard Medical School, Boston, Massachusetts
| | - Pierre-Jean Saulnier
- Chronic Kidney Disease Section, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, Arizona,Poitiers University Hospital, University of Poitiers, Institut National de la Santé et de la Recherche Médicale (INSERM), Clinical Investigation Center CIC1402, Poitiers, France
| | - Hiroki Kobayashi
- Research Division, Joslin Diabetes Center, Boston, Massachusetts,Department of Medicine, Harvard Medical School, Boston, Massachusetts
| | - Manoj K. Gupta
- Research Division, Joslin Diabetes Center, Boston, Massachusetts,Department of Medicine, Harvard Medical School, Boston, Massachusetts
| | - Helen C. Looker
- Chronic Kidney Disease Section, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, Arizona
| | - Jonathan M. Wilson
- Diabetes and Complication Department, Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, Indiana
| | - Zaipul I. Md Dom
- Research Division, Joslin Diabetes Center, Boston, Massachusetts,Department of Medicine, Harvard Medical School, Boston, Massachusetts
| | - Katsuhito Ihara
- Research Division, Joslin Diabetes Center, Boston, Massachusetts,Department of Medicine, Harvard Medical School, Boston, Massachusetts
| | - Kristina O’Neil
- Research Division, Joslin Diabetes Center, Boston, Massachusetts,Department of Medicine, Harvard Medical School, Boston, Massachusetts
| | - Bozena Krolewski
- Research Division, Joslin Diabetes Center, Boston, Massachusetts,Department of Medicine, Harvard Medical School, Boston, Massachusetts
| | - Caterina Pipino
- Research Division, Joslin Diabetes Center, Boston, Massachusetts,Department of Medicine, Harvard Medical School, Boston, Massachusetts,Department of Medical, Oral and Biotechnological Sciences, Center for Advanced Studies and Technology (CAST), University G. d’Annunzio, Chieti, Italy
| | - Meda E. Pavkov
- Division of Diabetes Translation, Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Viji Nair
- Nephrology/Internal Medicine and Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan
| | - Markus Bitzer
- Nephrology/Internal Medicine and Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan
| | - Monika A. Niewczas
- Research Division, Joslin Diabetes Center, Boston, Massachusetts,Department of Medicine, Harvard Medical School, Boston, Massachusetts
| | - Matthias Kretzler
- Nephrology/Internal Medicine and Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan
| | - Michael Mauer
- Department of Pediatrics and Medicine, University of Minnesota, Minneapolis, Minnesota
| | - Alessandro Doria
- Research Division, Joslin Diabetes Center, Boston, Massachusetts,Department of Medicine, Harvard Medical School, Boston, Massachusetts
| | - Behzad Najafian
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, Washington
| | - Rohit N. Kulkarni
- Research Division, Joslin Diabetes Center, Boston, Massachusetts,Department of Medicine, Harvard Medical School, Boston, Massachusetts
| | - Kevin L. Duffin
- Diabetes and Complication Department, Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, Indiana
| | - Marcus G. Pezzolesi
- Research Division, Joslin Diabetes Center, Boston, Massachusetts,Department of Medicine, Harvard Medical School, Boston, Massachusetts,Division of Nephrology and Hypertension, University of Utah, Salt Lake City, Utah
| | - C. Ronald Kahn
- Research Division, Joslin Diabetes Center, Boston, Massachusetts,Department of Medicine, Harvard Medical School, Boston, Massachusetts
| | - Robert G. Nelson
- Chronic Kidney Disease Section, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, Arizona
| | - Andrzej S. Krolewski
- Research Division, Joslin Diabetes Center, Boston, Massachusetts,Department of Medicine, Harvard Medical School, Boston, Massachusetts
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9
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Di Bonito P, Mozzillo E, Rosanio FM, Maltoni G, Piona CA, Franceschi R, Ripoli C, Ricciardi MR, Tornese G, Arnaldi C, Iovane B, Iafusco D, Zanfardino A, Suprani T, Savastio S, Cherubini V, Tiberi V, Piccinno E, Schiaffini R, Delvecchio M, Casertano A, Maffeis C, Franzese A. Albuminuric and non-albuminuric reduced eGFR phenotypes in youth with type 1 diabetes: Factors associated with cardiometabolic risk. Nutr Metab Cardiovasc Dis 2021; 31:2033-2041. [PMID: 34083127 DOI: 10.1016/j.numecd.2021.03.019] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/02/2021] [Revised: 03/21/2021] [Accepted: 03/23/2021] [Indexed: 01/11/2023]
Abstract
BACKGROUND AND AIM Albuminuria and reduced eGFR are hallmarks of Diabetic Kidney Disease in adults. Our aim was to analyze factors associated with albuminuric and non-albuminuric mildly reduced eGFR phenotypes in youths with type 1 diabetes. METHODS AND RESULTS This multicenter cross-sectional study included 1549 youths (age 5-17 years) with type 1 diabetes enrolled at 14 Italian Pediatric Diabetes Centers. Albuminuria, creatinine, glycosylated hemoglobin (HbA1c), lipids, blood pressure (BP), neutrophils (N) and lymphocytes (L) count were analyzed. Uric acid (UA) was available in 848 individuals. Estimated GFR (eGFR) was calculated using bedside Schwartz's equation. The sample was divided in three phenotypes: 1) normoalbuminuria and eGFR ≥90 mL/min/1.73 m2 (reference category, n = 1204), 2) albuminuric and normal GFR phenotype (n = 106), 3) non-albuminuric mildly reduced GFR (MRGFR) phenotype (eGFR 60-89 mL/min/1.73 m2, n = 239). Albuminuric and non-albuminuric reduced eGFR phenotypes were significantly associated with autoimmune thyroiditis (P =0.028 and P=0.044, respectively). Albuminuric phenotype showed high risk of high HbA1c (P=0.029), high BP (P < 0.001), and low HDL-C (P =0.045) vs reference category. Non-albuminuric MRGFR phenotype showed high risk of high BP (P < 0.0001), low HDL-C (P =0.042), high Triglycerides/HDL-C ratio (P =0.019), and high UA (P < 0.0001) vs reference category. CONCLUSION Non albuminuric MRGFR phenotype is more prevalent than albuminuric phenotype and shows a worst cardiometabolic risk (CMR) profile). Both phenotypes are associated with autoimmune thyroiditis. Our data suggest to evaluate both albuminuria and eGFR earlier in type 1 diabetes to timely identify young people with altered CMR profile.
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Affiliation(s)
- Procolo Di Bonito
- Department of Internal Medicine, "S. Maria Delle Grazie", Pozzuoli Hospital, Naples, Italy
| | - Enza Mozzillo
- Department of Translational Medical Science, Section of Pediatrics, Regional Center of Pediatric Diabetes, Federico II University of Naples, Naples, Italy.
| | - Francesco M Rosanio
- Department of Translational Medical Science, Section of Pediatrics, Regional Center of Pediatric Diabetes, Federico II University of Naples, Naples, Italy
| | - Giulio Maltoni
- Department of Woman, Child and Urological Diseases, S. Orsola-Malpighi University Hospital, Bologna, Italy
| | - Claudia A Piona
- Pediatric Diabetes and Metabolic Disorders Unit, University of Verona, Verona, Italy
| | | | - Carlo Ripoli
- Pediatric Diabetology Unit, Pediatric and Microcytemia Department, AO Brotzu, Cagliari, Italy
| | - Maria R Ricciardi
- Pediatric Diabetology Unit, Pediatric and Microcytemia Department, AO Brotzu, Cagliari, Italy
| | - Gianluca Tornese
- Institute for Maternal and Child Health IRCCS 'Burlo Garofolo', Trieste, Italy
| | | | - Brunella Iovane
- Regional Diabetes Center, Children Hospital "Pietro Barilla", University Hospital of Parma, Parma, Italy
| | - Dario Iafusco
- Department of Woman, Child and General and Specialized Surgery, University of Campania "Luigi Vanvitelli", Naples, Italy
| | - Angela Zanfardino
- Department of Woman, Child and General and Specialized Surgery, University of Campania "Luigi Vanvitelli", Naples, Italy
| | | | - Silvia Savastio
- SCDU of Pediatrics, University Hospital Maggiore Della Carità, Novara, Italy
| | - Valentino Cherubini
- Regional Center for Diabetes in Children and Adolescents, Department of Woman and Child Health, AOU Salesi Hospital, Ancona, Italy
| | - Valentino Tiberi
- Regional Center for Diabetes in Children and Adolescents, Department of Woman and Child Health, AOU Salesi Hospital, Ancona, Italy
| | - Elvira Piccinno
- Metabolic Diseases, Clinical Genetics and Diabetology Unit, Giovanni XXIII Children's Hospital, Bari, Italy
| | | | - Maurizio Delvecchio
- Metabolic Diseases, Clinical Genetics and Diabetology Unit, Giovanni XXIII Children's Hospital, Bari, Italy
| | - Alberto Casertano
- Department of Translational Medical Science, Section of Pediatrics, Regional Center of Pediatric Diabetes, Federico II University of Naples, Naples, Italy
| | - Claudio Maffeis
- Pediatric Diabetes and Metabolic Disorders Unit, University of Verona, Verona, Italy
| | - Adriana Franzese
- Department of Translational Medical Science, Section of Pediatrics, Regional Center of Pediatric Diabetes, Federico II University of Naples, Naples, Italy
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10
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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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11
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Davanso MR, Crisma AR, Braga TT, Masi LN, do Amaral CL, Leal VNC, de Lima DS, Patente TA, Barbuto JA, Corrêa-Giannella ML, Lauterbach M, Kolbe CC, Latz E, Camara NOS, Pontillo A, Curi R. Macrophage inflammatory state in Type 1 diabetes: triggered by NLRP3/iNOS pathway and attenuated by docosahexaenoic acid. Clin Sci (Lond) 2021; 135:19-34. [PMID: 33399849 DOI: 10.1042/cs20201348] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2020] [Revised: 12/01/2020] [Accepted: 12/02/2020] [Indexed: 12/13/2022]
Abstract
Type 1 diabetes mellitus (T1D) is a chronic autoimmune disease characterized by insulin-producing pancreatic β-cell destruction and hyperglycemia. While monocytes and NOD-like receptor family-pyrin domain containing 3 (NLRP3) are associated with T1D onset and development, the specific receptors and factors involved in NLRP3 inflammasome activation remain unknown. Herein, we evaluated the inflammatory state of resident peritoneal macrophages (PMs) from genetically modified non-obese diabetic (NOD), NLRP3-KO, wild-type (WT) mice and in peripheral blood mononuclear cells (PBMCs) from human T1D patients. We also assessed the effect of docosahexaenoic acid (DHA) on the inflammatory status. Macrophages from STZ-induced T1D mice exhibited increased inflammatory cytokine/chemokine levels, nitric oxide (NO) secretion, NLRP3 and iNOS protein levels, and augmented glycolytic activity compared to control animals. In PMs from NOD and STZ-induced T1D mice, DHA reduced NO production and attenuated the inflammatory state. Furthermore, iNOS and IL-1β protein expression levels and NO production were lower in the PMs from diabetic NLRP3-KO mice than from WT mice. We also observed increased IL-1β secretion in PBMCs from T1D patients and immortalized murine macrophages treated with advanced glycation end products and palmitic acid. The present study demonstrated that the resident PMs are in a proinflammatory state characterized by increased NLRP3/iNOS pathway-mediated NO production, up-regulated proinflammatory cytokine/chemokine receptor expression and altered glycolytic activity. Notably, ex vivo treatment with DHA reverted the diabetes-induced changes and attenuated the macrophage inflammatory state. It is plausible that DHA supplementation could be employed as adjuvant therapy for treating individuals with T1D.
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MESH Headings
- Adult
- Animals
- Anti-Inflammatory Agents/pharmacology
- Cells, Cultured
- Cytokines/metabolism
- Diabetes Mellitus, Experimental/chemically induced
- Diabetes Mellitus, Experimental/drug therapy
- Diabetes Mellitus, Experimental/enzymology
- Diabetes Mellitus, Experimental/immunology
- Diabetes Mellitus, Type 1/chemically induced
- Diabetes Mellitus, Type 1/drug therapy
- Diabetes Mellitus, Type 1/enzymology
- Diabetes Mellitus, Type 1/immunology
- Docosahexaenoic Acids/pharmacology
- Female
- Humans
- Inflammation/chemically induced
- Inflammation/drug therapy
- Inflammation/enzymology
- Inflammation/immunology
- Inflammation Mediators/metabolism
- Macrophage Activation/drug effects
- Macrophages, Peritoneal/drug effects
- Macrophages, Peritoneal/enzymology
- Macrophages, Peritoneal/immunology
- Male
- Mice, Inbred C57BL
- Mice, Inbred NOD
- Mice, Knockout
- Middle Aged
- NLR Family, Pyrin Domain-Containing 3 Protein/genetics
- NLR Family, Pyrin Domain-Containing 3 Protein/metabolism
- Nitric Oxide Synthase Type II/metabolism
- Pregnancy
- Signal Transduction
- Streptozocin
- Mice
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Affiliation(s)
- Mariana Rodrigues Davanso
- Department of Physiology and Biophysics, Institute of Biomedical Sciences, University of Sao Paulo, Sao Paulo, Sao Paulo, Brazil
- Laboratory of Immunogenetics, Department of Immunology, Institute of Biomedical Sciences, University of Sao Paulo, Sao Paulo, Sao Paulo, Brazil
- Institute of Innate Immunity, University Hospital, University of Bonn, Bonn, Germany
| | - Amanda Rabello Crisma
- Department of Physiology and Biophysics, Institute of Biomedical Sciences, University of Sao Paulo, Sao Paulo, Sao Paulo, Brazil
- Laboratory of Physiology and Cell Signalling, Department of Clinical Analyses, Federal University of Paraná, Curitiba, Paraná, Brazil
| | - Tárcio Teodoro Braga
- Institute of Innate Immunity, University Hospital, University of Bonn, Bonn, Germany
- Department of Basic Pathology, Federal University of Parana, Curitiba, Parana, Brazil
| | - Laureane Nunes Masi
- Department of Physiology and Biophysics, Institute of Biomedical Sciences, University of Sao Paulo, Sao Paulo, Sao Paulo, Brazil
- Interdisciplinary Post-graduate Program in Health Sciences, Cruzeiro of Sul University, Sao Paulo, Sao Paulo, Brazil
| | - Cátia Lira do Amaral
- Campus of Exact Sciences and Technology, State University of Goias, Anapolis, Goias, Brazil
| | - Vinícius Nunes Cordeiro Leal
- Laboratory of Immunogenetics, Department of Immunology, Institute of Biomedical Sciences, University of Sao Paulo, Sao Paulo, Sao Paulo, Brazil
| | - Dhêmerson Souza de Lima
- Laboratory of Immunogenetics, Department of Immunology, Institute of Biomedical Sciences, University of Sao Paulo, Sao Paulo, Sao Paulo, Brazil
| | - Thiago Andrade Patente
- Laboratory of Tumour Immunology, Department of Immunology, Institute of Biomedical Sciences, University of Sao Paulo, Sao Paulo, Sao Paulo, Brazil
| | - José Alexandre Barbuto
- Laboratory of Tumour Immunology, Department of Immunology, Institute of Biomedical Sciences, University of Sao Paulo, Sao Paulo, Sao Paulo, Brazil
| | - Maria L Corrêa-Giannella
- Laboratory of Carbohydrates and Radioimmunoassay, Faculty of Medicine, University of Sao Paulo, Sao Paulo, Sao Paulo, Brazil
- Post-graduation Program of Medicine, UNINOVE, Sao Paulo, Brazil
| | - Mario Lauterbach
- Institute of Innate Immunity, University Hospital, University of Bonn, Bonn, Germany
| | - Carl Christian Kolbe
- Institute of Innate Immunity, University Hospital, University of Bonn, Bonn, Germany
| | - Eicke Latz
- Institute of Innate Immunity, University Hospital, University of Bonn, Bonn, Germany
| | - Niels Olsen Saraiva Camara
- Laboratory of Immunology of Transplantation, Department of Immunology, Institute of Biomedical Sciences, University of Sao Paulo, Sao Paulo, Sao Paulo, Brazil
| | - Alessandra Pontillo
- Laboratory of Immunogenetics, Department of Immunology, Institute of Biomedical Sciences, University of Sao Paulo, Sao Paulo, Sao Paulo, Brazil
| | - Rui Curi
- Department of Physiology and Biophysics, Institute of Biomedical Sciences, University of Sao Paulo, Sao Paulo, Sao Paulo, Brazil
- Interdisciplinary Post-graduate Program in Health Sciences, Cruzeiro of Sul University, Sao Paulo, Sao Paulo, Brazil
- Butantan Institute, Sao Paulo, Sao Paulo, Brazil
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