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Hu X, Chen S, Ye S, Chen W, Zhou Y. New insights into the role of immunity and inflammation in diabetic kidney disease in the omics era. Front Immunol 2024; 15:1342837. [PMID: 38487541 PMCID: PMC10937589 DOI: 10.3389/fimmu.2024.1342837] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2023] [Accepted: 02/19/2024] [Indexed: 03/17/2024] Open
Abstract
Diabetic kidney disease (DKD) is becoming the leading cause of chronic kidney disease, especially in the industrialized world. Despite mounting evidence has demonstrated that immunity and inflammation are highly involved in the pathogenesis and progression of DKD, the underlying mechanisms remain incompletely understood. Substantial molecules, signaling pathways, and cell types participate in DKD inflammation, by integrating into a complex regulatory network. Most of the studies have focused on individual components, without presenting their importance in the global or system-based processes, which largely hinders clinical translation. Besides, conventional technologies failed to monitor the different behaviors of resident renal cells and immune cells, making it difficult to understand their contributions to inflammation in DKD. Recently, the advancement of omics technologies including genomics, epigenomics, transcriptomics, proteomics, and metabolomics has revolutionized biomedical research, which allows an unbiased global analysis of changes in DNA, RNA, proteins, and metabolites in disease settings, even at single-cell and spatial resolutions. They help us to identify critical regulators of inflammation processes and provide an overview of cell heterogeneity in DKD. This review aims to summarize the application of multiple omics in the field of DKD and emphasize the latest evidence on the interplay of inflammation and DKD revealed by these technologies, which will provide new insights into the role of inflammation in the pathogenesis of DKD and lead to the development of novel therapeutic approaches and diagnostic biomarkers.
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Affiliation(s)
- Xinrong Hu
- Department of Nephrology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
- Key Laboratory of Nephrology, National Health Commission and Guangdong Province, Guangzhou, China
| | - Sixiu Chen
- Department of Nephrology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
- Key Laboratory of Nephrology, National Health Commission and Guangdong Province, Guangzhou, China
| | - Siyang Ye
- Department of Nephrology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
- Key Laboratory of Nephrology, National Health Commission and Guangdong Province, Guangzhou, China
| | - Wei Chen
- Department of Nephrology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
- Key Laboratory of Nephrology, National Health Commission and Guangdong Province, Guangzhou, China
| | - Yi Zhou
- Department of Nephrology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
- Key Laboratory of Nephrology, National Health Commission and Guangdong Province, Guangzhou, China
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Joshi N, Garapati K, Ghose V, Kandasamy RK, Pandey A. Recent progress in mass spectrometry-based urinary proteomics. Clin Proteomics 2024; 21:14. [PMID: 38389064 PMCID: PMC10885485 DOI: 10.1186/s12014-024-09462-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2024] [Accepted: 02/12/2024] [Indexed: 02/24/2024] Open
Abstract
Serum or plasma is frequently utilized in biomedical research; however, its application is impeded by the requirement for invasive sample collection. The non-invasive nature of urine collection makes it an attractive alternative for disease characterization and biomarker discovery. Mass spectrometry-based protein profiling of urine has led to the discovery of several disease-associated biomarkers. Proteomic analysis of urine has not only been applied to disorders of the kidney and urinary bladder but also to conditions affecting distant organs because proteins excreted in the urine originate from multiple organs. This review provides a progress update on urinary proteomics carried out over the past decade. Studies summarized in this review have expanded the catalog of proteins detected in the urine in a variety of clinical conditions. The wide range of applications of urine analysis-from characterizing diseases to discovering predictive, diagnostic and prognostic markers-continues to drive investigations of the urinary proteome.
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Affiliation(s)
- Neha Joshi
- Manipal Academy of Higher Education (MAHE), Manipal, 576104, India
- Institute of Bioinformatics, International Technology Park, Bangalore, 560066, India
- Department of Laboratory Medicine and Pathology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA
| | - Kishore Garapati
- Manipal Academy of Higher Education (MAHE), Manipal, 576104, India
- Institute of Bioinformatics, International Technology Park, Bangalore, 560066, India
- Department of Laboratory Medicine and Pathology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA
| | - Vivek Ghose
- Manipal Academy of Higher Education (MAHE), Manipal, 576104, India
- Institute of Bioinformatics, International Technology Park, Bangalore, 560066, India
| | - Richard K Kandasamy
- Department of Laboratory Medicine and Pathology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, 55905, USA
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN, 55905, USA
| | - Akhilesh Pandey
- Institute of Bioinformatics, International Technology Park, Bangalore, 560066, India.
- Department of Laboratory Medicine and Pathology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, 55905, USA.
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN, 55905, USA.
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Catanese L, Siwy J, Wendt R, Amann K, Beige J, Hendry B, Mischak H, Mullen W, Paterson I, Schiffer M, Wolf M, Rupprecht H. Differentiating primary and secondary FSGS using non-invasive urine biomarkers. Clin Kidney J 2024; 17:sfad296. [PMID: 38313685 PMCID: PMC10833144 DOI: 10.1093/ckj/sfad296] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Indexed: 02/06/2024] Open
Abstract
Background Focal segmental glomerulosclerosis (FSGS) is divided into genetic, primary (p), uncertain cause, and secondary (s) forms. The subclasses differ in management and prognosis with differentiation often being challenging. We aimed to identify specific urine proteins/peptides discriminating between clinical and biopsy-proven pFSGS and sFSGS. Methods Sixty-three urine samples were collected in two different centers (19 pFSGS and 44 sFSGS) prior to biopsy. Samples were analysed using capillary electrophoresis-coupled mass spectrometry. For biomarker definition, datasets of age-/sex-matched normal controls (NC, n = 98) and patients with other chronic kidney diseases (CKDs, n = 100) were extracted from the urinary proteome database. Independent specificity assessment was performed in additional data of NC (n = 110) and CKD (n = 170). Results Proteomics data from patients with pFSGS were first compared to NC (n = 98). This resulted in 1179 biomarker (P < 0.05) candidates. Then, the pFSGS group was compared to sFSGS, and in a third step, pFSGS data were compared to data from different CKD etiologies (n = 100). Finally, 93 biomarkers were identified and combined in a classifier, pFSGS93. Total cross-validation of this classifier resulted in an area under the receiving operating curve of 0.95. The specificity investigated in an independent set of NC and CKD of other etiologies was 99.1% for NC and 94.7% for CKD, respectively. The defined biomarkers are largely fragments of different collagens (49%). Conclusion A urine peptide-based classifier that selectively detects pFSGS could be developed. Specificity of 95%-99% could be assessed in independent samples. Sensitivity must be confirmed in independent cohorts before routine clinical application.
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Affiliation(s)
- Lorenzo Catanese
- Department of Nephrology, Angiology and Rheumatology, Klinikum Bayreuth GmbH, Bayreuth, Germany
- Kuratorium for Dialysis and Transplantation (KfH) Bayreuth, Bayreuth, Germany
- Medizincampus Oberfranken, Friedrich-Alexander-University Erlangen-Nürnberg, Erlangen, Germany
| | | | - Ralph Wendt
- Division of Nephrology, St. Georg Hospital Leipzig, Leipzig, Germany
| | - Kerstin Amann
- Department of Nephropathology, Institute of Pathology, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany
| | - Joachim Beige
- Kuratorium for Dialysis and Transplantation (KfH) Renal Unit, Leipzig, Germany
- Department of Internal Medicine II, Martin-Luther-University Halle/Wittenberg, Halle/Saale, Germany
| | | | | | - William Mullen
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | | | - Mario Schiffer
- Department of Nephrology and Hypertension, University Hospital Erlangen, Friedrich-Alexander University (FAU) Erlangen-Nürnberg, Erlangen, Germany
- Research Center on Rare Kidney Diseases (RECORD), University Hospital Erlangen, Erlangen, Germany
| | | | - Harald Rupprecht
- Department of Nephrology, Angiology and Rheumatology, Klinikum Bayreuth GmbH, Bayreuth, Germany
- Kuratorium for Dialysis and Transplantation (KfH) Bayreuth, Bayreuth, Germany
- Medizincampus Oberfranken, Friedrich-Alexander-University Erlangen-Nürnberg, Erlangen, Germany
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de Souza Barcelos NE, Limeres ML, Peixoto-Dias AF, Vieira MAR, Peruchetti DB. Kidney Disease and Proteomics: A Recent Overview of a Useful Tool for Improving Early Diagnosis. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2024; 1443:173-186. [PMID: 38409421 DOI: 10.1007/978-3-031-50624-6_9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/28/2024]
Abstract
Kidney disease is a critical and potentially life-threatening degenerative condition that poses a significant global public health challenge due to its elevated rates of morbidity and mortality. It manifests primarily in two distinct clinical forms: acute kidney injury (AKI) and chronic kidney disease (CKD). The development of these conditions hinges on a multitude of factors, including the etiological agents and the presence of coexisting medical conditions. Despite disparities in their underlying pathogenic mechanisms, both AKI and CKD can progress to end-stage kidney disease (ESKD). This advanced stage is characterized by organ failure and its associated complications, greatly increasing the risk of mortality. There is an urgent need to delve into the pathogenic mechanisms underlying these diseases and to identify novel biomarkers that can facilitate earlier diagnosis. Such early detection is crucial for enhancing the efficacy of therapy and impeding disease progression. In this context, proteomic approaches have emerged as invaluable tools for uncovering potential new markers of different pathological conditions, including kidney diseases. In this chapter, we overview the recent discoveries achieved through diverse proteomic techniques aimed at identifying novel molecules that may play a pivotal role in kidney diseases such as diabetic kidney disease (DKD), IgA nephropathy (IgAN), CKD of unknown origin (CKDu), autosomal dominant polycystic kidney disease (ADPKD), lupus nephritis (LN), hypertensive nephropathy (HN), and COVID-19-associated acute kidney injury (COVID-AKI).
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Affiliation(s)
- Nicolly Emanuelle de Souza Barcelos
- Department of Physiology and Biophysics, Institute of Biological Sciences, Federal University of Minas Gerais (UFMG), Belo Horizonte, MG, Brazil
| | - Maria Laura Limeres
- Department of Physiology and Biophysics, Institute of Biological Sciences, Federal University of Minas Gerais (UFMG), Belo Horizonte, MG, Brazil
| | - Ana Flavia Peixoto-Dias
- Department of Physiology and Biophysics, Institute of Biological Sciences, Federal University of Minas Gerais (UFMG), Belo Horizonte, MG, Brazil
| | - Maria Aparecida Ribeiro Vieira
- Department of Physiology and Biophysics, Institute of Biological Sciences, Federal University of Minas Gerais (UFMG), Belo Horizonte, MG, Brazil
| | - Diogo B Peruchetti
- Department of Physiology and Biophysics, Institute of Biological Sciences, Federal University of Minas Gerais (UFMG), Belo Horizonte, MG, Brazil.
- INCT-Nanobiofar, Belo Horizonte, MG, Brazil.
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Catanese L, Siwy J, Mischak H, Wendt R, Beige J, Rupprecht H. Recent Advances in Urinary Peptide and Proteomic Biomarkers in Chronic Kidney Disease: A Systematic Review. Int J Mol Sci 2023; 24:ijms24119156. [PMID: 37298105 DOI: 10.3390/ijms24119156] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Revised: 05/19/2023] [Accepted: 05/22/2023] [Indexed: 06/12/2023] Open
Abstract
Biomarker development, improvement, and clinical implementation in the context of kidney disease have been a central focus of biomedical research for decades. To this point, only serum creatinine and urinary albumin excretion are well-accepted biomarkers in kidney disease. With their known blind spot in the early stages of kidney impairment and their diagnostic limitations, there is a need for better and more specific biomarkers. With the rise in large-scale analyses of the thousands of peptides in serum or urine samples using mass spectrometry techniques, hopes for biomarker development are high. Advances in proteomic research have led to the discovery of an increasing amount of potential proteomic biomarkers and the identification of candidate biomarkers for clinical implementation in the context of kidney disease management. In this review that strictly follows the PRISMA guidelines, we focus on urinary peptide and especially peptidomic biomarkers emerging from recent research and underline the role of those with the highest potential for clinical implementation. The Web of Science database (all databases) was searched on 17 October 2022, using the search terms "marker *" OR biomarker * AND "renal disease" OR "kidney disease" AND "proteome *" OR "peptid *" AND "urin *". English, full-text, original articles on humans published within the last 5 years were included, which had been cited at least five times per year. Studies based on animal models, renal transplant studies, metabolite studies, studies on miRNA, and studies on exosomal vesicles were excluded, focusing on urinary peptide biomarkers. The described search led to the identification of 3668 articles and the application of inclusion and exclusion criteria, as well as abstract and consecutive full-text analyses of three independent authors to reach a final number of 62 studies for this manuscript. The 62 manuscripts encompassed eight established single peptide biomarkers and several proteomic classifiers, including CKD273 and IgAN237. This review provides a summary of the recent evidence on single peptide urinary biomarkers in CKD, while emphasizing the increasing role of proteomic biomarker research with new research on established and new proteomic biomarkers. Lessons learned from the last 5 years in this review might encourage future studies, hopefully resulting in the routine clinical applicability of new biomarkers.
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Affiliation(s)
- Lorenzo Catanese
- Department of Nephrology, Angiology and Rheumatology, Klinikum Bayreuth GmbH, 95447 Bayreuth, Germany
- Kuratorium for Dialysis and Transplantation (KfH), 95445 Bayreuth, Germany
- Medizincampus Oberfranken, Friedrich-Alexander-University Erlangen-Nürnberg, 91054 Erlangen, Germany
| | - Justyna Siwy
- Mosaiques Diagnostics GmbH, 30659 Hannover, Germany
| | | | - Ralph Wendt
- Department of Nephrology, St. Georg Hospital Leipzig, 04129 Leipzig, Germany
| | - Joachim Beige
- Department of Nephrology, St. Georg Hospital Leipzig, 04129 Leipzig, Germany
- Department of Internal Medicine II, Martin-Luther-University Halle/Wittenberg, 06108 Halle/Saale, Germany
- Kuratorium for Dialysis and Transplantation (KfH), 04129 Leipzig, Germany
| | - Harald Rupprecht
- Department of Nephrology, Angiology and Rheumatology, Klinikum Bayreuth GmbH, 95447 Bayreuth, Germany
- Kuratorium for Dialysis and Transplantation (KfH), 95445 Bayreuth, Germany
- Medizincampus Oberfranken, Friedrich-Alexander-University Erlangen-Nürnberg, 91054 Erlangen, Germany
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Jiang X, Liu X, Qu X, Zhu P, Wo F, Xu X, Jin J, He Q, Wu J. Integration of metabolomics and peptidomics reveals distinct molecular landscape of human diabetic kidney disease. Theranostics 2023; 13:3188-3203. [PMID: 37351171 PMCID: PMC10283058 DOI: 10.7150/thno.80435] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Accepted: 04/17/2023] [Indexed: 06/24/2023] Open
Abstract
Diabetic kidney disease (DKD) is the most common microvascular complication of diabetes, and there is an urgent need to discover reliable biomarkers for early diagnosis. Here, we established an effective urine multi-omics platform and integrated metabolomics and peptidomics to investigate the biological changes during DKD pathogenesis. Methods: Totally 766 volunteers (221 HC, 198 T2DM, 175 early DKD, 125 overt DKD, and 47 grey-zone T2DM patients with abnormal urinary mALB concentration) were included in this study. Non-targeted metabolic fingerprints of urine samples were acquired on matrix-free LDI-MS platform by the tip-contact extraction method using fluorinated ethylene propylene coated silicon nanowires chips (FEP@SiNWs), while peptide profiles hidden in urine samples were uncovered by MALDI-TOF MS after capturing urine peptides by porous silicon microparticles. Results: After multivariate analysis, ten metabolites and six peptides were verified to be stepwise regulated in different DKD stages. The altered metabolic pathways and biological processes associated with the DKD pathogenesis were concentrated in amino acid metabolism and cellular protein metabolic process, which were supported by renal transcriptomics. Interestingly, multi-omics significantly increased the diagnostic accuracy for both early DKD diagnosis and DKD status discrimination. Combined with machine learning, a stepwise prediction model was constructed and 89.9% of HC, 75.5% of T2DM, 69.6% of early DKD and 75.7% of overt DKD subjects in the external validation cohort were correctly classified. In addition, 87.5% of grey-zone patients were successfully distinguished from T2DM patients. Conclusion: This multi-omics platform displayed a satisfactory ability to explore molecular information and provided a new insight for establishing effective DKD management.
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Affiliation(s)
- Xinrong Jiang
- Institution of Analytical Chemistry, Department of Chemistry, Zhejiang University, Hangzhou, 310058, China
| | - Xingyue Liu
- Institution of Analytical Chemistry, Department of Chemistry, Zhejiang University, Hangzhou, 310058, China
| | - Xuetong Qu
- Institution of Analytical Chemistry, Department of Chemistry, Zhejiang University, Hangzhou, 310058, China
| | - Pingya Zhu
- Well-healthcare Technologies Co., Hangzhou, 310051, China
| | - Fangjie Wo
- Well-healthcare Technologies Co., Hangzhou, 310051, China
| | - Xinran Xu
- Institution of Analytical Chemistry, Department of Chemistry, Zhejiang University, Hangzhou, 310058, China
| | - Juan Jin
- Department of Nephrology, The First People's Hospital of Hangzhou Lin'an District, Affiliated Lin'an People's Hospital of Hangzhou Medical College, Hangzhou, 311300, China
| | - Qiang He
- Department of Nephrology, The First Affiliated Hospital of Zhejiang Chinese Medical University, Zhejiang Provincial Hospital of Traditional Chinese Medicine, Hangzhou, 310006, China
| | - Jianmin Wu
- Institution of Analytical Chemistry, Department of Chemistry, Zhejiang University, Hangzhou, 310058, China
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Wu Z, Lohmöller J, Kuhl C, Wehrle K, Jankowski J. Use of Computation Ecosystems to Analyze the Kidney-Heart Crosstalk. Circ Res 2023; 132:1084-1100. [PMID: 37053282 DOI: 10.1161/circresaha.123.321765] [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] [Indexed: 04/15/2023]
Abstract
The identification of mediators for physiologic processes, correlation of molecular processes, or even pathophysiological processes within a single organ such as the kidney or heart has been extensively studied to answer specific research questions using organ-centered approaches in the past 50 years. However, it has become evident that these approaches do not adequately complement each other and display a distorted single-disease progression, lacking holistic multilevel/multidimensional correlations. Holistic approaches have become increasingly significant in understanding and uncovering high dimensional interactions and molecular overlaps between different organ systems in the pathophysiology of multimorbid and systemic diseases like cardiorenal syndrome because of pathological heart-kidney crosstalk. Holistic approaches to unraveling multimorbid diseases are based on the integration, merging, and correlation of extensive, heterogeneous, and multidimensional data from different data sources, both -omics and nonomics databases. These approaches aimed at generating viable and translatable disease models using mathematical, statistical, and computational tools, thereby creating first computational ecosystems. As part of these computational ecosystems, systems medicine solutions focus on the analysis of -omics data in single-organ diseases. However, the data-scientific requirements to address the complexity of multimodality and multimorbidity reach far beyond what is currently available and require multiphased and cross-sectional approaches. These approaches break down complexity into small and comprehensible challenges. Such holistic computational ecosystems encompass data, methods, processes, and interdisciplinary knowledge to manage the complexity of multiorgan crosstalk. Therefore, this review summarizes the current knowledge of kidney-heart crosstalk, along with methods and opportunities that arise from the novel application of computational ecosystems providing a holistic analysis on the example of kidney-heart crosstalk.
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Affiliation(s)
- Zhuojun Wu
- Institute of Molecular Cardiovascular Research (Z.W., J.J.), Rheinisch-Westfälische Technische Hochschule Aachen University, Germany
- Department of Radiology (C.K.), Rheinisch-Westfälische Technische Hochschule Aachen University, Germany
| | - Johannes Lohmöller
- Medical Faculty, and Department of Computer Science, Communication and Distributed Systems (COMSYS) (J.L., K.W.), Rheinisch-Westfälische Technische Hochschule Aachen University, Germany
| | - Christiane Kuhl
- Department of Radiology (C.K.), Rheinisch-Westfälische Technische Hochschule Aachen University, Germany
| | - Klaus Wehrle
- Institute of Molecular Cardiovascular Research (Z.W., J.J.), Rheinisch-Westfälische Technische Hochschule Aachen University, Germany
- Medical Faculty, and Department of Computer Science, Communication and Distributed Systems (COMSYS) (J.L., K.W.), Rheinisch-Westfälische Technische Hochschule Aachen University, Germany
| | - Joachim Jankowski
- Institute of Molecular Cardiovascular Research (Z.W., J.J.), Rheinisch-Westfälische Technische Hochschule Aachen University, Germany
- Department of Pathology, Cardiovascular Research Institute Maastricht (CARIM), University of Maastricht, The Netherlands (J.J.)
- Aachen-Maastricht Institute for Cardiorenal Disease (AMICARE), University Hospital Rheinisch-Westfälische Technische Hochschule Aachen, Germany (J.J.)
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Degenaar A, Jacobs A, Kruger R, Delles C, Mischak H, Mels C. Cardiovascular risk and kidney function profiling using conventional and novel biomarkers in young adults: the African-PREDICT study. BMC Nephrol 2023; 24:96. [PMID: 37055746 PMCID: PMC10103421 DOI: 10.1186/s12882-023-03100-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Accepted: 03/02/2023] [Indexed: 04/15/2023] Open
Abstract
BACKGROUND Low- and middle-income countries experience an increasing burden of chronic kidney disease. Cardiovascular risk factors, including advancing age, may contribute to this phenomenon. We (i) profiled cardiovascular risk factors and different biomarkers of subclinical kidney function and (ii) investigated the relationship between these variables. METHODS We cross-sectionally analysed 956 apparently healthy adults between 20 and 30 years of age. Cardiovascular risk factors such as high adiposity, blood pressure, glucose levels, adverse lipid profiles and lifestyle factors were measured. Various biomarkers were used to assess subclinical kidney function, including estimated glomerular filtration rate (eGFR), urinary albumin, uromodulin and the CKD273 urinary proteomics classifier. These biomarkers were used to divide the total population into quartiles to compare extremes (25th percentiles) on the normal kidney function continuum. The lower 25th percentiles of eGFR and uromodulin and the upper 25th percentiles of urinary albumin and the CKD273 classifier represented the more unfavourable kidney function groups. RESULTS In the lower 25th percentiles of eGFR and uromodulin and the upper 25th percentile of the CKD273 classifier, more adverse cardiovascular profiles were observed. In multi-variable adjusted regression analyses performed in the total group, eGFR associated negatively with HDL-C (β= -0.44; p < 0.001) and GGT (β= -0.24; p < 0.001), while the CKD273 classifier associated positively with age and these same risk factors (age: β = 0.10; p = 0.021, HDL-C: β = 0.23; p < 0.001, GGT: β = 0.14; p = 0.002). CONCLUSION Age, lifestyle and health measures impact kidney health even in the third decade.
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Affiliation(s)
- A Degenaar
- Hypertension in Africa Research Team (HART), North-West University, Potchefstroom, South Africa
| | - A Jacobs
- Hypertension in Africa Research Team (HART), North-West University, Potchefstroom, South Africa
- MRC Research Unit: Hypertension and Cardiovascular Disease, North-West University, Potchefstroom, South Africa
| | - R Kruger
- Hypertension in Africa Research Team (HART), North-West University, Potchefstroom, South Africa
- MRC Research Unit: Hypertension and Cardiovascular Disease, North-West University, Potchefstroom, South Africa
| | - C Delles
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | - H Mischak
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
- Mosaiques Diagnostics GmbH, Hannover, Germany
| | - Cmc Mels
- Hypertension in Africa Research Team (HART), North-West University, Potchefstroom, South Africa.
- MRC Research Unit: Hypertension and Cardiovascular Disease, North-West University, Potchefstroom, South Africa.
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Collagen-Derived Peptides in CKD: A Link to Fibrosis. Toxins (Basel) 2021; 14:toxins14010010. [PMID: 35050988 PMCID: PMC8781252 DOI: 10.3390/toxins14010010] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2021] [Revised: 12/07/2021] [Accepted: 12/17/2021] [Indexed: 02/06/2023] Open
Abstract
Collagen is a major component of the extracellular matrix (ECM) and has an imminent role in fibrosis, in, among others, chronic kidney disease (CKD). Collagen alpha-1(I) (col1a1) is the most abundant collagen type and has previously been underlined for its contribution to the disease phenotype. Here, we examined 5000 urinary peptidomic datasets randomly selected from healthy participants or patients with CKD to identify urinary col1a1 fragments and study their abundance, position in the main protein, as well as their correlation with renal function. We identified 707 col1a1 peptides that differed in their amino acid sequence and/or post-translational modifications (hydroxyprolines). Well-correlated peptides with the same amino acid sequence, but a different number of hydroxyprolines, were combined into a final list of 503 peptides. These 503 col1a1 peptides covered 69% of the full col1a1 sequence. Sixty-three col1a1 peptides were significantly and highly positively associated (rho > +0.3) with the estimated glomerular filtration rate (eGFR), while only six peptides showed a significant and strong, negative association (rho < −0.3). A similar tendency was observed for col1a1 peptides associated with ageing, where the abundance of most col1a1 peptides decreased with increasing age. Collectively the results show a strong association between collagen peptides and loss of kidney function and suggest that fibrosis, potentially also of other organs, may be the main consequence of an attenuation of collagen degradation, and not increased synthesis.
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Govender MA, Brandenburg JT, Fabian J, Ramsay M. The Use of 'Omics for Diagnosing and Predicting Progression of Chronic Kidney Disease: A Scoping Review. Front Genet 2021; 12:682929. [PMID: 34819944 PMCID: PMC8606569 DOI: 10.3389/fgene.2021.682929] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Accepted: 10/18/2021] [Indexed: 12/19/2022] Open
Abstract
Globally, chronic kidney disease (CKD) contributes substantial morbidity and mortality. Recently, various ‘omics platforms have provided insight into the molecular basis of kidney dysfunction. This scoping review is a synthesis of the current literature on the use of different ‘omics platforms to identify biomarkers that could be used to detect early-stage CKD, predict disease progression, and identify pathways leading to CKD. This review includes 123 articles published from January 2007 to May 2021, following a structured selection process. The most common type of ‘omic platform was proteomics, appearing in 55 of the studies and two of these included a metabolomics component. Most studies (n = 91) reported on CKD associated with diabetes mellitus. Thirteen studies that provided information on the biomarkers associated with CKD and explored potential pathways involved in CKD are discussed. The biomarkers that are associated with risk or early detection of CKD are SNPs in the MYH9/APOL1 and UMOD genes, the proteomic CKD273 biomarker panel and metabolite pantothenic acid. Pantothenic acid and the CKD273 biomarker panel were also involved in predicting CKD progression. Retinoic acid pathway genes, UMOD, and pantothenic acid provided insight into potential pathways leading to CKD. The biomarkers were mainly used to detect CKD and predict progression in high-income, European ancestry populations, highlighting the need for representative ‘omics research in other populations with disparate socio-economic strata, including Africans, since disease etiologies may differ across ethnic groups. To assess the transferability of findings, it is essential to do research in diverse populations.
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Affiliation(s)
- Melanie A Govender
- Division of Human Genetics, National Health Laboratory Service and School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.,Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Jean-Tristan Brandenburg
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - June Fabian
- Wits Donald Gordon Medical Centre, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Michèle Ramsay
- Division of Human Genetics, National Health Laboratory Service and School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.,Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
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11
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Karsdal MA, Genovese F, Rasmussen DGK, Bay-Jensen AC, Mortensen JH, Holm Nielsen S, Willumsen N, Jensen C, Manon-Jensen T, Jennings L, Reese-Petersen AL, Henriksen K, Sand JM, Bager C, Leeming DJ. Considerations for understanding protein measurements: Identification of formation, degradation and more pathological relevant epitopes. Clin Biochem 2021; 97:11-24. [PMID: 34453894 DOI: 10.1016/j.clinbiochem.2021.08.007] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2021] [Revised: 08/06/2021] [Accepted: 08/23/2021] [Indexed: 01/01/2023]
Abstract
OBJECTIVES There is a need for precision medicine and an unspoken promise of an optimal approach for identification of the right patients for value-based medicine based on big data. However, there may be a misconception that measurement of proteins is more valuable than measurement of fewer selected biomarkers. In population-based research, variation may be somewhat eliminated by quantity. However, this fascination of numbers may limit the attention to and understanding of the single. This review highlights that protein measurements (with collagens as examples) may mean different things depending on the targeted epitope - formation or degradation of tissues, and even signaling potential of proteins. DESIGN AND METHODS PubMed was searched for collagen, neo-epitope, biomarkers. RESULTS Ample examples of assays with specific epitopes, either pathological such as HbA1c, or domain specific such as pro-peptides, which total protein arrays would not have identified were evident. CONCLUSIONS We suggest that big data may be considered as the funnel of data points, in which most important parameters will be selected. If the technical precision is low or the biological accuracy is limited, and we include suboptimal quality of biomarkers, disguised as big data, we may not be able to fulfill the promise of helping patients searching for the optimal treatment. Alternatively, if the technical precision of the total protein quantification is high, but we miss the functional domains with the most considerable biological meaning, we miss the most important and valuable information of a given protein. This review highlights that measurements of the same protein in different ways may provide completely different meanings. We need to understand the pathological importance of each epitope quantified to maximize protein measurements.
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Affiliation(s)
- M A Karsdal
- Nordic Bioscience, Biomarkers & Research A/S, Herlev, Denmark.
| | - F Genovese
- Nordic Bioscience, Biomarkers & Research A/S, Herlev, Denmark
| | - D G K Rasmussen
- Nordic Bioscience, Biomarkers & Research A/S, Herlev, Denmark
| | - A C Bay-Jensen
- Nordic Bioscience, Biomarkers & Research A/S, Herlev, Denmark
| | - J H Mortensen
- Nordic Bioscience, Biomarkers & Research A/S, Herlev, Denmark
| | - S Holm Nielsen
- Nordic Bioscience, Biomarkers & Research A/S, Herlev, Denmark
| | - N Willumsen
- Nordic Bioscience, Biomarkers & Research A/S, Herlev, Denmark
| | - C Jensen
- Nordic Bioscience, Biomarkers & Research A/S, Herlev, Denmark
| | - T Manon-Jensen
- Nordic Bioscience, Biomarkers & Research A/S, Herlev, Denmark
| | | | | | - K Henriksen
- Nordic Bioscience, Biomarkers & Research A/S, Herlev, Denmark
| | - J M Sand
- Nordic Bioscience, Biomarkers & Research A/S, Herlev, Denmark
| | - C Bager
- Nordic Bioscience, Biomarkers & Research A/S, Herlev, Denmark
| | - D J Leeming
- Nordic Bioscience, Biomarkers & Research A/S, Herlev, Denmark
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12
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Siwy J, Wendt R, Albalat A, He T, Mischak H, Mullen W, Latosinska A, Lübbert C, Kalbitz S, Mebazaa A, Peters B, Stegmayr B, Spasovski G, Wiech T, Staessen JA, Wolf J, Beige J. CD99 and polymeric immunoglobulin receptor peptides deregulation in critical COVID-19: A potential link to molecular pathophysiology? Proteomics 2021; 21:e2100133. [PMID: 34383378 PMCID: PMC8420529 DOI: 10.1002/pmic.202100133] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2021] [Revised: 07/28/2021] [Accepted: 08/09/2021] [Indexed: 11/11/2022]
Abstract
Identification of significant changes in urinary peptides may enable improved understanding of molecular disease mechanisms. We aimed towards identifying urinary peptides associated with critical course of COVID-19 to yield hypotheses on molecular pathophysiological mechanisms in disease development. In this multicentre prospective study urine samples of PCR-confirmed COVID-19 patients were collected in different centres across Europe. The urinary peptidome of 53 patients at WHO stages 6-8 and 66 at WHO stages 1-3 COVID-19 disease was analysed using capillary electrophoresis coupled to mass spectrometry. 593 peptides were identified significantly affected by disease severity. These peptides were compared with changes associated with kidney disease or heart failure. Similarities with kidney disease were observed, indicating comparable molecular mechanisms. In contrast, convincing similarity to heart failure could not be detected. The data for the first time showed deregulation of CD99 and polymeric immunoglobulin receptor peptides and of known peptides associated with kidney disease, including collagen and alpha-1-antitrypsin. Peptidomic findings were in line with the pathophysiology of COVID-19. The clinical corollary is that COVID-19 induces specific inflammation of numerous tissues including endothelial lining. Restoring these changes, especially in CD99, PIGR and alpha-1-antitripsin, may represent a valid and effective therapeutic approach in COVID-19, targeting improvement of endothelial integrity. This article is protected by copyright. All rights reserved.
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Affiliation(s)
| | - Ralph Wendt
- Department of Infectious Diseases/Tropical Medicine, Nephrology and Rheumatology, Hospital St. Georg, Leipzig, Germany
| | - Amaya Albalat
- School of Natural Sciences, University of Stirling, Stirling, UK
| | - Tianlin He
- Mosaiques diagnostics GmbH, Hannover, Germany
| | | | - William Mullen
- Institute of Cardiovascular and Medical Science, University of Glasgow, Glasgow, UK
| | | | - Christoph Lübbert
- Department of Infectious Diseases/Tropical Medicine, Nephrology and Rheumatology, Hospital St. Georg, Leipzig, Germany.,Division of Infectious Diseases and Tropical Medicine, Department of Oncology, Gastroenterology, Hepatology, Pneumology and Infectious Diseases, Leipzig University Hospital, Leipzig, Germany.,Interdisciplinary Center for Infectious Diseases, Leipzig University Hospital, Leipzig, Germany
| | - Sven Kalbitz
- Department of Infectious Diseases/Tropical Medicine, Nephrology and Rheumatology, Hospital St. Georg, Leipzig, Germany
| | - Alexandre Mebazaa
- Department of Anesthesiology and Intensive Care, Saint Louis-Lariboisière - Fernand Widal University Hospital, Assistance Publique Hôpitaux de Paris, Paris, France.,Université de Paris, Paris, France.,INSERM UMR-S 942 - MASCOT, Paris, France
| | - Björn Peters
- Department of Nephrology, Skaraborg Hospital, Skövde, Sweden.,Department of Molecular and Clinical Medicine, Institute of Medicine, the Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden
| | - Bernd Stegmayr
- Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
| | - Goce Spasovski
- Department of Nephrology, Medical Faculty, University St.Cyril and Methodius, Umeå, Sweden
| | - Thorsten Wiech
- Nephropathology Section, Institute for Pathology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Jan A Staessen
- Alliance for the Promotion of Preventive Medicine (APPREMED), Mechelen, Belgium.,Biomedical Sciences Group, Faculty of Medicine, University of Leuven, Leuven, Belgium
| | - Johannes Wolf
- Department of Laboratory Medicine, Hospital St. Georg, Leipzig, Germany.,ImmunoDeficiencyCenter Leipzig (IDCL) at Hospital St. Georg Leipzig, Jeffrey Modell Diagnostic and Research Center for Primary Immunodeficiency Diseases, Leipzig, Germany
| | - Joachim Beige
- Department of Infectious Diseases/Tropical Medicine, Nephrology and Rheumatology, Hospital St. Georg, Leipzig, Germany.,Kuratorium for Dialysis and Transplantation (KfH) Renal Unit, Hospital St. Georg, Leipzig, Germany.,Martin-Luther-University Halle/Wittenberg, Halle/Saale, Germany
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13
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García-Foncillas J, Argente J, Bujanda L, Cardona V, Casanova B, Fernández-Montes A, Horcajadas JA, Iñiguez A, Ortiz A, Pablos JL, Pérez Gómez MV. Milestones of Precision Medicine: An Innovative, Multidisciplinary Overview. Mol Diagn Ther 2021; 25:563-576. [PMID: 34331269 DOI: 10.1007/s40291-021-00544-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/04/2021] [Indexed: 12/11/2022]
Abstract
Although the concept of precision medicine, in which healthcare is tailored to the molecular and clinical characteristics of each individual, is not new, its implementation in clinical practice has been heterogenous. In some medical specialties, precision medicine has gone from being just a promise to a reality that achieves better patient outcomes. This is a fact if we consider, for example, the great advances made in the genetic diagnosis and subsequent treatment of countless hereditary diseases, such as cystic fibrosis, which have improved the life expectancy of many of the affected children. In the field of oncology, the development of targeted therapies has prolonged the survival of patients with breast, lung, colorectal, melanoma, and hematological malignancies. In other disciplines, clinical milestones are perhaps less well known, but no less important. The current challenge is to expand and generalize the use of technologies that are central to precision medicine, such as massively parallel sequencing, to improve the management (prevention and treatment) of complex conditions such as cardiovascular, kidney, or autoimmune diseases. This process requires investment in specialized expertise, multidisciplinary collaboration, and the nationwide organization of genetic laboratories for diagnosis of specific diseases.
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Affiliation(s)
- Jesús García-Foncillas
- Department of Oncology, Oncohealth Institute, Fundacion Jimenez Diaz University Hospital, Autonomous University, Madrid, Spain. .,Medical Oncology Department, University Hospital Fundación Jiménez Díaz-Universidad Autonoma de Madrid, Madrid, Spain.
| | - Jesús Argente
- Department of Endocrinology, Instituto de Salud Carlos III, IMDEA Institute, Hospital Infantil Universitario Niño Jesús, Spanish PUBERE Registry, CIBER of Obesity and Nutrition (CIBEROBN), Universidad Autónoma de Madrid, Madrid, Spain.,Department of Pediatrics, Instituto de Salud Carlos III, IMDEA Institute, Hospital Infantil Universitario Niño Jesús, Spanish PUBERE Registry, CIBER of Obesity and Nutrition (CIBEROBN), Universidad Autónoma de Madrid, Madrid, Spain
| | - Luis Bujanda
- Department of Gastroenterology, Hospital Donostia/Instituto Biodonostia, Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBEREHD), Universidad del País Vasco (UPV/EHU), San Sebastian, Spain
| | - Victoria Cardona
- Allergy Section, Department of Internal Medicine, Hospital Vall d'Hebron, Barcelona, Spain.,ARADyAL Research Network, Barcelona, Spain
| | - Bonaventura Casanova
- Neuroimmunology Unit, La Fe University and Polytechnic Hospital, Valencia, Spain.,Department of Medicine, Faculty of Medicine, University of Valencia, Valencia, Spain
| | - Ana Fernández-Montes
- Medical Oncology, Complejo Hospitalario Universitario de Ourense, Ourense, Spain
| | | | - Andrés Iñiguez
- Department of Cardiology, Hospital Álvaro Cunqueiro-Complejo Hospitalario Universitario, Vigo, Spain
| | - Alberto Ortiz
- Department of Nephrology and Hypertension, IIS-Fundación Jiménez Díaz-UAM, Madrid, Spain
| | - José L Pablos
- Grupo de Enfermedades Inflamatorias y Autoinmunes, Instituto de Investigación Hospital 12 de Octubre, Madrid, Spain.,Servicio de Reumatología, Hospital 12 de Octubre, Universidad Complutense de Madrid, Madrid, Spain
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14
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Tye SC, Denig P, Heerspink HJL. Precision medicine approaches for diabetic kidney disease: opportunities and challenges. Nephrol Dial Transplant 2021; 36:3-9. [PMID: 34153985 PMCID: PMC8216727 DOI: 10.1093/ndt/gfab045] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2020] [Indexed: 12/27/2022] Open
Abstract
The prevalence of end-stage kidney disease (ESKD) continuously increases worldwide. The increasing prevalence parallels the growth in the number of people with diabetes, which is the leading cause of ESKD. Early diagnosis of chronic kidney disease (CKD) in patients with diabetes and appropriate intervention is important to delay the progression of kidney function decline and prevent ESKD. Rate of CKD progression and response to treatment varies among patients with diabetes, highlighting the need to tailor individual treatment. In this review, we describe recent advances and areas for future studies with respect to precision medicine in diabetic kidney disease (DKD). DKD is a multi-factorial disease that is subject in part to genetic heritability, but is also influenced by various exogenous mediators, such as environmental or dietary factors. Genetic testing so far has limited utility to facilitate early diagnosis, classify progression or evaluate response to therapy. Various biomarker-based approaches are currently explored to identify patients at high risk of ESKD and to facilitate decision-making for targeted therapy. These studies have led to discovery and validation of a couple of inflammatory proteins such as circulating tumour necrosis factor receptors, which are strong predictors of kidney disease progression. Moreover, risk and drug-response scores based on multiple biomarkers are developed to predict kidney disease progression and long-term drug efficacy. These findings, if implemented in clinical practice, will pave the way to move from a one-size-fits-all to a one-fit-for-everyone approach.
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Affiliation(s)
- Sok Cin Tye
- Department of Clinical Pharmacy and Pharmacology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Petra Denig
- Department of Clinical Pharmacy and Pharmacology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Hiddo J L Heerspink
- Department of Clinical Pharmacy and Pharmacology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
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15
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Tan S, Zeng Y, Kuang S, Li J. Serum Human Epididymis Protein 4 is a Potential Biomarker for Early Chronic Kidney Disease in an Obese Population. Diabetes Metab Syndr Obes 2021; 14:1601-1608. [PMID: 33889001 PMCID: PMC8057804 DOI: 10.2147/dmso.s300940] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/12/2021] [Accepted: 03/10/2021] [Indexed: 11/23/2022] Open
Abstract
BACKGROUND At present, it is difficult to clinically diagnose early chronic kidney disease (CKD). As a novel biomarker of malignancies in the female reproductive tract, the human epididymis protein 4 (HE4) has been reported to be significantly expressed in CKD patients. AIM We sought to assess whether HE4 can be used as a potential biomarker of early-stage CKD. METHODS The association between serum HE4 levels and CKD was analyzed in a retrospective study. A cohort of 506 patients with diabetic nephropathy who were hospitalized at Weihai Central Hospital, China, from January 2016 to November 2019 were included. RESULTS Serum HE4 levels were increased with increasing stage of CKD and significantly elevated in patients with CKD3-5 than CKD1-2 (P<0.001). In multivariate linear regression analyses, HE4 levels were strongly correlated with the estimated glomerular filtration rate (eGFR) in CKD patients (Model 2, P<0.001). HE4 (area under the curve; AUC=0.934) had better diagnostic value than serum creatinine (SCr; AUC=0.770) and blood urea nitrogen (BUN; AUC=0.647) for patients with early-stage CKD (CKD1-2). Additionally, HE4 levels increased with increasing glomerular lesion (GL) and renal interstitial fibrosis (IF)/tubular atrophy (TA) scores in 51 CKD patients (P<0.001). CONCLUSION Serum HE4 levels can be positively associated with the severity of CKD and are a very valuable clinical biomarker for predicting early-stage CKD.
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Affiliation(s)
- Shubo Tan
- Department of Urology, Second Affiliated Hospital of the University of South China, Hengyang City, 421000, People’s Republic of China
| | - Yongmao Zeng
- Department of Urology, Second Affiliated Hospital of the University of South China, Hengyang City, 421000, People’s Republic of China
| | - Shiliang Kuang
- Department of Urology, Second Affiliated Hospital of the University of South China, Hengyang City, 421000, People’s Republic of China
| | - Jianjun Li
- Department of Urology, Second Affiliated Hospital of the University of South China, Hengyang City, 421000, People’s Republic of China
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16
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Chung EY, Ruospo M, Natale P, Bolignano D, Navaneethan SD, Palmer SC, Strippoli GF. Aldosterone antagonists in addition to renin angiotensin system antagonists for preventing the progression of chronic kidney disease. Cochrane Database Syst Rev 2020; 10:CD007004. [PMID: 33107592 PMCID: PMC8094274 DOI: 10.1002/14651858.cd007004.pub4] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
BACKGROUND Treatment with angiotensin-converting enzyme inhibitors (ACEi) and angiotensin receptor blockers (ARB) is used to reduce proteinuria and retard the progression of chronic kidney disease (CKD). However, resolution of proteinuria may be incomplete with these therapies and the addition of an aldosterone antagonist may be added to further prevent progression of CKD. This is an update of a Cochrane review first published in 2009 and updated in 2014. OBJECTIVES To evaluate the effects of aldosterone antagonists (selective (eplerenone), non-selective (spironolactone or canrenone), or non-steroidal mineralocorticoid antagonists (finerenone)) in adults who have CKD with proteinuria (nephrotic and non-nephrotic range) on: patient-centred endpoints including kidney failure (previously know as end-stage kidney disease (ESKD)), major cardiovascular events, and death (any cause); kidney function (proteinuria, estimated glomerular filtration rate (eGFR), and doubling of serum creatinine); blood pressure; and adverse events (including hyperkalaemia, acute kidney injury, and gynaecomastia). SEARCH METHODS We searched the Cochrane Kidney and Transplant Register of Studies up to 13 January 2020 through contact with the Information Specialist using search terms relevant to this review. Studies in the Register are identified through searches of CENTRAL, MEDLINE, and EMBASE, conference proceedings, the International Clinical Trials Register (ICTRP) Search Portal, and ClinicalTrials.gov. SELECTION CRITERIA We included randomised controlled trials (RCTs) and quasi-RCTs that compared aldosterone antagonists in combination with ACEi or ARB (or both) to other anti-hypertensive strategies or placebo in participants with proteinuric CKD. DATA COLLECTION AND ANALYSIS Two authors independently assessed study quality and extracted data. Data were summarised using random effects meta-analysis. We expressed summary treatment estimates as a risk ratio (RR) for dichotomous outcomes and mean difference (MD) for continuous outcomes, or standardised mean difference (SMD) when different scales were used together with their 95% confidence interval (CI). Risk of bias were assessed using the Cochrane tool. Evidence certainty was evaluated using GRADE. MAIN RESULTS Forty-four studies (5745 participants) were included. Risk of bias in the evaluated methodological domains were unclear or high risk in most studies. Adequate random sequence generation was present in 12 studies, allocation concealment in five studies, blinding of participant and investigators in 18 studies, blinding of outcome assessment in 15 studies, and complete outcome reporting in 24 studies. All studies comparing aldosterone antagonists to placebo or standard care were used in addition to an ACEi or ARB (or both). None of the studies were powered to detect differences in patient-level outcomes including kidney failure, major cardiovascular events or death. Aldosterone antagonists had uncertain effects on kidney failure (2 studies, 84 participants: RR 3.00, 95% CI 0.33 to 27.65, I² = 0%; very low certainty evidence), death (3 studies, 421 participants: RR 0.58, 95% CI 0.10 to 3.50, I² = 0%; low certainty evidence), and cardiovascular events (3 studies, 1067 participants: RR 0.95, 95% CI 0.26 to 3.56; I² = 42%; low certainty evidence) compared to placebo or standard care. Aldosterone antagonists may reduce protein excretion (14 studies, 1193 participants: SMD -0.51, 95% CI -0.82 to -0.20, I² = 82%; very low certainty evidence), eGFR (13 studies, 1165 participants, MD -3.00 mL/min/1.73 m², 95% CI -5.51 to -0.49, I² = 0%, low certainty evidence) and systolic blood pressure (14 studies, 911 participants: MD -4.98 mmHg, 95% CI -8.22 to -1.75, I² = 87%; very low certainty evidence) compared to placebo or standard care. Aldosterone antagonists probably increase the risk of hyperkalaemia (17 studies, 3001 participants: RR 2.17, 95% CI 1.47 to 3.22, I² = 0%; moderate certainty evidence), acute kidney injury (5 studies, 1446 participants: RR 2.04, 95% CI 1.05 to 3.97, I² = 0%; moderate certainty evidence), and gynaecomastia (4 studies, 281 participants: RR 5.14, 95% CI 1.14 to 23.23, I² = 0%; moderate certainty evidence) compared to placebo or standard care. Non-selective aldosterone antagonists plus ACEi or ARB had uncertain effects on protein excretion (2 studies, 139 participants: SMD -1.59, 95% CI -3.80 to 0.62, I² = 93%; very low certainty evidence) but may increase serum potassium (2 studies, 121 participants: MD 0.31 mEq/L, 95% CI 0.17 to 0.45, I² = 0%; low certainty evidence) compared to diuretics plus ACEi or ARB. Selective aldosterone antagonists may increase the risk of hyperkalaemia (2 studies, 500 participants: RR 1.62, 95% CI 0.66 to 3.95, I² = 0%; low certainty evidence) compared ACEi or ARB (or both). There were insufficient studies to perform meta-analyses for the comparison between non-selective aldosterone antagonists and calcium channel blockers, selective aldosterone antagonists plus ACEi or ARB (or both) and nitrate plus ACEi or ARB (or both), and non-steroidal mineralocorticoid antagonists and selective aldosterone antagonists. AUTHORS' CONCLUSIONS The effects of aldosterone antagonists when added to ACEi or ARB (or both) on the risks of death, major cardiovascular events, and kidney failure in people with proteinuric CKD are uncertain. Aldosterone antagonists may reduce proteinuria, eGFR, and systolic blood pressure in adults who have mild to moderate CKD but may increase the risk of hyperkalaemia, acute kidney injury and gynaecomastia when added to ACEi and/or ARB.
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Affiliation(s)
- Edmund Ym Chung
- Department of Medicine, Royal North Shore Hospital, Sydney, Australia
| | - Marinella Ruospo
- Sydney School of Public Health, The University of Sydney, Sydney, Australia
- Department of Emergency and Organ Transplantation, University of Bari, Bari, Italy
| | - Patrizia Natale
- Sydney School of Public Health, The University of Sydney, Sydney, Australia
- Department of Emergency and Organ Transplantation, University of Bari, Bari, Italy
| | - Davide Bolignano
- Institute of Clinical Physiology, CNR - Italian National Council of Research, Reggio Calabria, Italy
| | | | - Suetonia C Palmer
- Department of Medicine, University of Otago Christchurch, Christchurch, New Zealand
| | - Giovanni Fm Strippoli
- Sydney School of Public Health, The University of Sydney, Sydney, Australia
- Department of Emergency and Organ Transplantation, University of Bari, Bari, Italy
- Cochrane Kidney and Transplant, Centre for Kidney Research, The Children's Hospital at Westmead, Westmead, Australia
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17
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Insights into predicting diabetic nephropathy using urinary biomarkers. BIOCHIMICA ET BIOPHYSICA ACTA-PROTEINS AND PROTEOMICS 2020; 1868:140475. [DOI: 10.1016/j.bbapap.2020.140475] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/29/2020] [Revised: 05/27/2020] [Accepted: 06/14/2020] [Indexed: 12/20/2022]
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18
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Beige J, Drube J, von der Leyen H, Pape L, Rupprecht H. Früherkennung mittels Urinproteomanalyse. Internist (Berl) 2020; 61:1094-1105. [DOI: 10.1007/s00108-020-00863-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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19
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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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20
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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, Havrdova T, Heerspink HJL, 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. Early detection of diabetic kidney disease by urinary proteomics and subsequent intervention with spironolactone to delay progression (PRIORITY): a prospective observational study and embedded randomised placebo-controlled trial. Lancet Diabetes Endocrinol 2020; 8:301-312. [PMID: 32135136 DOI: 10.1016/s2213-8587(20)30026-7] [Citation(s) in RCA: 128] [Impact Index Per Article: 32.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/13/2019] [Revised: 01/07/2020] [Accepted: 01/16/2020] [Indexed: 01/08/2023]
Abstract
BACKGROUND Microalbuminuria is an early sign of kidney disease in people with diabetes and indicates increased risk of cardiovascular disease. We tested whether a urinary proteomic risk classifier (CKD273) score was associated with development of microalbuminuria and whether progression to microalbuminuria could be prevented with the mineralocorticoid receptor antagonist spironolactone. METHODS In this multicentre, prospective, observational study with embedded randomised controlled trial (PRIORITY), we recruited people with type 2 diabetes, normal urinary albumin excretion, and preserved renal function from 15 specialist centres in ten European countries. All participants (observational cohort) were tested with the CKD273 classifier and classified as high risk (CKD273 classifier score >0·154) or low risk (≤0·154). Participants who were classified as high risk were entered into a randomised controlled trial and randomly assigned (1:1), by use of an interactive web-response system, to receive spironolactone 25 mg once daily or matched placebo (trial cohort). The primary endpoint was development of confirmed microalbuminuria in all individuals with available data (observational cohort). Secondary endpoints included reduction in incidence of microalbuminuria with spironolactone (trial cohort, intention-to-treat population) and association between CKD273 risk score and measures of impaired renal function based on estimated glomerular filtration rate (eGFR; observational cohort). Adverse events (particularly gynaecomastia and hyperkalaemia) and serious adverse events were recorded for the intention-to-treat population (trial cohort). This study is registered with the EU Clinical Trials Register (EudraCT 20120-004523-4) and ClinicalTrials.gov (NCT02040441) and is completed. FINDINGS Between March 25, 2014, and Sept 30, 2018, we enrolled and followed-up 1775 participants (observational cohort), 1559 (88%) of 1775 participants had a low-risk urinary proteomic pattern and 216 (12%) had a high-risk pattern, of whom 209 were included in the trial cohort and assigned to spironolactone (n=102) or placebo (n=107). The overall median follow-up time was 2·51 years (IQR 2·0-3·0). Progression to microalbuminuria was seen in 61 (28%) of 216 high-risk participants and 139 (9%) of 1559 low-risk participants (hazard ratio [HR] 2·48, 95% CI 1·80-3·42; p<0·0001, after adjustment for baseline variables of age, sex, HbA1c, systolic blood pressure, retinopathy, urine albumin-to-creatinine ratio [UACR], and eGFR). Development of impaired renal function (eGFR <60 mL/min per 1·73 m2) was seen in 48 (26%) of 184 high-risk participants and 119 (8%) of 1423 low-risk participants (HR 3·50; 95% CI 2·50-4·90, after adjustment for baseline variables). A 30% decrease in eGFR from baseline (post-hoc endpoint) was seen in 42 (19%) of 216 high-risk participants and 62 (4%) of 1559 low-risk participants (HR 5·15, 95% CI 3·41-7·76; p<0·0001, after adjustment for basline eGFR and UACR). In the intention-to-treat trial cohort, development of microalbuminuria was seen in 35 (33%) of 107 in the placebo group and 26 (25%) of 102 in the spironolactone group (HR 0·81, 95% CI 0·49-1·34; p=0·41). In the safety analysis (intention-to-treat trial cohort), events of plasma potassium concentrations of more than 5·5 mmol/L were seen in 13 (13%) of 102 participants in the spironolactone group and four (4%) of 107 participants in the placebo group, and gynaecomastia was seen in three (3%) participants in the spironolactone group and none in the placebo group. One patient died in the placebo group due to a cardiac event (considered possibly related to study drug) and one patient died in the spironolactone group due to cancer, deemed unrelated to study drug. INTERPRETATION In people with type 2 diabetes and normoalbuminuria, a high-risk score from the urinary proteomic classifier CKD273 was associated with an increased risk of progression to microalbuminuria over a median of 2·5 years, independent of clinical characteristics. However, spironolactone did not prevent progression to microalbuminuria in high-risk patients. FUNDING European Union Seventh Framework Programme.
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Affiliation(s)
- Nete Tofte
- Steno Diabetes Center Copenhagen, Gentofte, 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, 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 Public Health Research Institute, VU University Medical Center, Amsterdam, Netherlands; Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, Netherlands
| | - Andreas L Birkenfeld
- Department of Internal Medicine IV, Division of Endocrinology, Diabetology, and Nephrology, University Hospital Tübingen, Tübingen, Germany; Institute for Diabetes Research and Metabolic Diseases, Helmholtz Center Munich at Eberhard Karls University of Tübingen, Tübingen, Germany; German Center for Diabetes Research, Neuherberg, Germany
| | - Gemma Currie
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | - Christian Delles
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | | | - Lidmila Francová
- 1st Department, Charles University, Third Faculty of Medicine, 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
| | - Hiddo J L Heerspink
- Department of Clinical Pharmacy and Pharmacology, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Adriaan Kooy
- Bethesda Diabetes Research Center, Hoogeveen, Netherlands; Diabetes Vascular Research Foundation (DVRF), Hoogeveen, Netherlands; University Medical Center Groningen, Groningen, Netherlands
| | - Gozewijn D Laverman
- Department of Internal Medicine/Nephrology, Ziekenhuisgroep Twente Hospital, Almelo, Netherlands
| | | | - Gerjan Navis
- Division of Nephrology, Department of Internal Medicine, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Giel Nijpels
- Department General Practice and Elderly Care, Amsterdam, Netherlands
| | - Marina Noutsou
- Diabetes Center, 2nd Department of Internal Medicine, Medical School, National and Kapodistrian University of Athens, 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 CeleDaccò": Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Ranica, Bergamo, Italy
| | | | - John R Petrie
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | - Piero L Ruggenenti
- Department of Renal Medicine, Clinical Research Centre for Rare Diseases "Aldo e CeleDaccò": Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Ranica, Bergamo, Italy
| | - Femke Rutters
- Amsterdam Public Health Research Institute, VU University Medical Center, Amsterdam, Netherlands
| | - Ivan Rychlík
- 1st Department, Charles University, Third Faculty of Medicine, Prague, Czech Republic; Faculty Hospital Královské Vinohrady, Prague, Czech Republic
| | | | - Goce Spasovski
- Department of Nephrology, Cyril and Methodius University in Skopje, Skopje, North Macedonia
| | | | - Matias Trillini
- Department of Renal Medicine, Clinical Research Centre for Rare Diseases "Aldo e CeleDaccò": Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Ranica, Bergamo, Italy
| | | | | | - Peter Rossing
- Steno Diabetes Center Copenhagen, Gentofte, Denmark; University of Copenhagen, Copenhagen, Denmark.
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Rasmussen DGK, Boesby L, Nielsen SH, Tepel M, Birot S, Karsdal MA, Kamper AL, Genovese F. Collagen turnover profiles in chronic kidney disease. Sci Rep 2019; 9:16062. [PMID: 31690732 PMCID: PMC6831687 DOI: 10.1038/s41598-019-51905-3] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2018] [Accepted: 10/08/2019] [Indexed: 12/13/2022] Open
Abstract
Renal fibrosis is a hallmark of chronic kidney disease (CKD) caused by an imbalance between formation and degradation of extracellular matrix proteins. We investigated the collagen turnover profile of 81 non-dialysis CKD stage 2-5 patients by measuring peptides reflecting formation and degradation of collagen type (COL) I, III, IV, and VI. Based on the collagen turnover profile, we identified four clusters of patients. Cluster 1 contained one patient with prostate cancer, who had a distinct collagen turnover. The other clusters generally had severe (Cluster 2), moderate (Cluster 4), or mild CKD (Cluster 3). Cluster 4 patients were characterized by higher levels of COL III, COL IV, and COL VI (all p < 0.001) degradation fragments in plasma, while patients in Clusters 2 and 4 had higher levels of COL VI formation (p < 0.05). COL IV fragments in plasma were lower in Cluster 2 (p < 0.01). Urinary COL III fragments decreased from Cluster 3 to 4, and from Cluster 4 to 2 (both p < 0.001). We show that patients with similar kidney function have a different collagen remodeling profile, suggesting that different phenotypes exist with different disease activity and potentially disease progression. Biomarkers of collagen remodeling could provide additional information to traditional markers of renal function.
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Affiliation(s)
- Daniel Guldager Kring Rasmussen
- Nordic Bioscience, Herlev, Denmark.
- Department of Cardiovascular and Renal Research, Institute of Molecular Medicine, University of Southern Denmark, Odense, Denmark.
| | - Lene Boesby
- Department of Medicine, University Hospital Roskilde, Roskilde, Denmark
- Department of Nephrology, Herlev Hospital, Herlev, Denmark
| | - Signe Holm Nielsen
- Nordic Bioscience, Herlev, Denmark
- Department of Biotechnology and Biomedicine, Technical University of Denmark, Kgs, Lyngby, Denmark
| | - Martin Tepel
- Department of Cardiovascular and Renal Research, Institute of Molecular Medicine, University of Southern Denmark, Odense, Denmark
- Department of Nephrology, Odense University Hospital, Odense, Denmark
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22
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Schena FP, Serino G, Sallustio F, Falchi M, Cox SN. Omics studies for comprehensive understanding of immunoglobulin A nephropathy: state-of-the-art and future directions. Nephrol Dial Transplant 2019; 33:2101-2112. [PMID: 29905852 DOI: 10.1093/ndt/gfy130] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2018] [Accepted: 04/17/2018] [Indexed: 12/11/2022] Open
Abstract
Immunoglobulin A nephropathy (IgAN) is the most common worldwide primary glomerulonephritis with a strong autoimmune component. The disease shows variability in both clinical phenotypes and endpoints and can be potentially subdivided into more homogeneous subtypes through the identification of specific molecular biomarkers. This review focuses on the role of omics in driving the identification of potential molecular subtypes of the disease through the integration of multilevel data from genomics, transcriptomics, epigenomics, proteomics and metabolomics. First, the identification of molecular biomarkers, including mapping of the full spectrum of common and rare IgAN risk alleles, could permit a more precise stratification of IgAN patients. Second, the analysis of transcriptomic patterns and their modulation by epigenetic factors like microRNAs has the potential to increase our understanding in the pathogenic mechanisms of the disease. Third, the specificity of urinary proteomic and metabolomic signatures and the understanding of their functional relevance may contribute to the development of new non-invasive biomarkers for a better molecular characterization of the renal damage and its follow-up. All these approaches can give information for targeted therapeutic decisions and will support novel clinical decision making. In conclusion, we offer a framework of omic studies and outline barriers and potential solutions that should be used for improving the diagnosis and treatment of the disease. The ongoing decade is exploiting novel high-throughput molecular technologies and computational analyses for improving the diagnosis (precision nephrology) and treatment (personalized therapy) of the IgAN subtypes.
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Affiliation(s)
- Francesco Paolo Schena
- Division of Nephrology, Dialysis, and Transplantation, Department of Emergency and Organ Transplantation, University of Bari, Bari, Italy.,Schena Foundation, Valenzano, Bari, Italy
| | - Grazia Serino
- National Institute of Gastroenterology 'S. de Bellis', Research Hospital, Castellana Grotte, Bari, Italy
| | - Fabio Sallustio
- Division of Nephrology, Dialysis, and Transplantation, Department of Emergency and Organ Transplantation, University of Bari, Bari, Italy
| | - Mario Falchi
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Sharon N Cox
- Division of Nephrology, Dialysis, and Transplantation, Department of Emergency and Organ Transplantation, University of Bari, Bari, Italy.,Schena Foundation, Valenzano, Bari, Italy
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23
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Lindhardt M, Persson F, Oxlund C, Jacobsen IA, Zürbig P, Mischak H, Rossing P, Heerspink HJL. Predicting albuminuria response to spironolactone treatment with urinary proteomics in patients with type 2 diabetes and hypertension. Nephrol Dial Transplant 2019; 33:296-303. [PMID: 28064163 DOI: 10.1093/ndt/gfw406] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2016] [Accepted: 10/24/2016] [Indexed: 01/07/2023] Open
Abstract
Background The mineralocorticoid receptor antagonist spironolactone significantly reduces albuminuria in patients with diabetes. Prior studies have shown large between-patient variability in albuminuria treatment response. We previously developed and validated a urinary proteomic classifier that predicts onset and progression of chronic kidney disease. Here, we tested whether the proteomic classifier based on 273 urinary peptides (CKD273) predicts albuminuria response to spironolactone treatment. Methods We performed a post hoc analysis in a double-blind randomized clinical trial with allocation to either spironolactone 12.5-50 mg/day (n = 57) or placebo (n = 54) for 16 weeks. Patients were diagnosed with type 2 diabetes and resistant hypertension. Treatment was an adjunct to renin-angiotensin system inhibition. Primary endpoint was the percentage change in urine albumin to creatinine ratio (UACR). Capillary electrophoresis mass spectrometry was used to quantify urinary peptides at baseline. The previously validated combination of 273 known urinary peptides was used as proteomic classifier. Results Spironolactone reduced UACR relative to placebo by 50%, although with a large between-patient variability in UACR response (5th to 95th percentile, 7 to 312%). An interaction was detected between CKD273 and treatment assignment (β = -1.09, P = 0.026). Higher values of CKD273 at baseline were associated with a larger reduction in UACR in the spironolactone group (β = -0.70, P = 0.049), but not in the placebo group (β = 0.39, P = 0.25). Stratified in tertiles of baseline CKD273, reduction in UACR was greater in the highest tertile, 63% (95% confidence interval: 35-79%), as compared with the two other tertiles combined, 16% (-17 to 40%) (P = 0.011). Conclusions A urinary proteomics classifier can be used to identify individuals with type 2 diabetes who are more likely to show an albuminuria-lowering response to spironolactone treatment. These results suggest that urinary proteomics may be a valuable tool to tailor therapy, but confirmation in a larger clinical trial is required.
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Affiliation(s)
| | | | - Christina Oxlund
- University of Southern Denmark, Research Unit for Cardiovascular and renal protection, Odense, Denmark
| | - Ib A Jacobsen
- University of Southern Denmark, Research Unit for Cardiovascular and renal protection, Odense, Denmark
| | | | | | - Peter Rossing
- Faculty of Heath, University of Aarhus, Aarhus, Denmark.,The Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
| | - Hiddo J L Heerspink
- Department of Clinical Pharmacy and Pharmacology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
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Abstract
Proteome analysis has been applied in multiple studies in the context of chronic kidney disease, aiming at improving our knowledge on the molecular pathophysiology of the disease. The approach is generally based on the hypothesis that proteins are key in maintaining kidney function, and disease is a clinical consequence of a significant change of the protein level. Knowledge on critical proteins and their alteration in disease should in turn enable identification of ideal biomarkers that could guide patient management. In addition, all drugs currently employed target proteins. Hence, proteome analysis also promises to enable identifying the best suited therapeutic target, and, in combination with biomarkers, could be used as the rationale basis for personalized intervention. To assess the current status of proteome analysis in the context of CKD, we present the results of a systematic review, of up-to-date scientific research, and give an outlook on the developments that can be expected in near future. Based on the current literature, proteome analysis has already seen implementation in the management of CKD patients, and it is expected that this approach, also supported by the positive results generated to date, will see advanced high-throughput application.
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25
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Kontostathi G, Makridakis M, Zoidakis J, Vlahou A. Applications of multiple reaction monitoring targeted proteomics assays in human plasma. Expert Rev Mol Diagn 2019; 19:499-515. [PMID: 31057016 DOI: 10.1080/14737159.2019.1615448] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Introduction: Multiple (or selected) reaction monitoring-mass spectrometry (MRM/SRM) is a targeted proteomic method that can be used for relative and absolute quantification. Multiple reports exist supporting the potential of the approach in proteomic biomarker validation. Areas covered: To get an overview of the applications of MRM in protein quantification in plasma, a search in MedLine/PubMed was performed using the keywords: 'MRM/SRM plasma proteomic/proteomics/proteome'. The retrieved studies were further filtered to focus on disease biomarkers and the main results are summarized. Expert opinion: MRM is increasingly employed for the quantification of both well-established but also newly discovered putative biomarkers and occasionally their post-translationally modified forms in plasma. Fractionation is regularly required for the detection of low abundance proteins. Standardized procedures to facilitate assay establishment and marker quantification have been proposed and, in few cases, implemented. Nevertheless, in most cases, absolute quantification is not performed. To advance, multiple technical issues including the regular use of standard labeled peptides and appropriate quality controls to monitor assay performance should be considered. Additionally, clinical aspects involving careful study design to address biomarker clinical use should also be considered.
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Affiliation(s)
- Georgia Kontostathi
- a Biotechnology Division , Biomedical Research Foundation, Academy of Athens (BRFAA) , Athens , Greece
| | - Manousos Makridakis
- a Biotechnology Division , Biomedical Research Foundation, Academy of Athens (BRFAA) , Athens , Greece
| | - Jerome Zoidakis
- a Biotechnology Division , Biomedical Research Foundation, Academy of Athens (BRFAA) , Athens , Greece
| | - Antonia Vlahou
- a Biotechnology Division , Biomedical Research Foundation, Academy of Athens (BRFAA) , Athens , Greece
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Latosinska A, Siwy J, Mischak H, Frantzi M. Peptidomics and proteomics based on CE‐MS as a robust tool in clinical application: The past, the present, and the future. Electrophoresis 2019; 40:2294-2308. [DOI: 10.1002/elps.201900091] [Citation(s) in RCA: 38] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2019] [Revised: 04/16/2019] [Accepted: 04/16/2019] [Indexed: 12/23/2022]
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Cañadas-Garre M, Anderson K, McGoldrick J, Maxwell AP, McKnight AJ. Proteomic and metabolomic approaches in the search for biomarkers in chronic kidney disease. J Proteomics 2019; 193:93-122. [PMID: 30292816 DOI: 10.1016/j.jprot.2018.09.020] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2018] [Revised: 09/20/2018] [Accepted: 09/30/2018] [Indexed: 12/15/2022]
Abstract
Chronic kidney disease (CKD) is an aging-related disorder that represents a major global public health burden. Current biochemical biomarkers, such as serum creatinine and urinary albumin, have important limitations when used to identify the earliest indication of CKD or in tracking the progression to more advanced CKD. These issues underline the importance of finding and testing new molecular biomarkers that are capable of successfully meeting this clinical need. The measurement of changes in nature and/or levels of proteins and metabolites in biological samples from patients provide insights into pathophysiological processes. Proteomic and metabolomic techniques provide opportunities to record dynamic chemical signatures in patients over time. This review article presents an overview of the recent developments in the fields of metabolomics and proteomics in relation to CKD. Among the many different proteomic biomarkers proposed, there is particular interest in the CKD273 classifier, a urinary proteome biomarker reported to predict CKD progression and with implementation potential. Other individual non-invasive peptidomic biomarkers that are potentially relevant for CKD detection include type 1 collagen, uromodulin and mucin-1. Despite the limited sample sizes and variability of the metabolomics studies, some metabolites such as trimethylamine N-oxide, kynurenine and citrulline stand out as potential biomarkers in CKD.
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Affiliation(s)
- M Cañadas-Garre
- Epidemiology and Public Health Research Group, Centre for Public Health, Queen's University of Belfast, Regional Genetics Centre, Level A, Tower Block, Belfast City Hospital, Lisburn Road, Belfast BT9 7AB, United Kingdom; Regional Nephrology Unit, Belfast City Hospital, Belfast, United Kingdom.
| | - K Anderson
- Epidemiology and Public Health Research Group, Centre for Public Health, Queen's University of Belfast, Regional Genetics Centre, Level A, Tower Block, Belfast City Hospital, Lisburn Road, Belfast BT9 7AB, United Kingdom; Regional Nephrology Unit, Belfast City Hospital, Belfast, United Kingdom.
| | - J McGoldrick
- Epidemiology and Public Health Research Group, Centre for Public Health, Queen's University of Belfast, Regional Genetics Centre, Level A, Tower Block, Belfast City Hospital, Lisburn Road, Belfast BT9 7AB, United Kingdom; Regional Nephrology Unit, Belfast City Hospital, Belfast, United Kingdom.
| | - A P Maxwell
- Epidemiology and Public Health Research Group, Centre for Public Health, Queen's University of Belfast, Regional Genetics Centre, Level A, Tower Block, Belfast City Hospital, Lisburn Road, Belfast BT9 7AB, United Kingdom; Regional Nephrology Unit, Belfast City Hospital, Belfast, United Kingdom.
| | - A J McKnight
- Epidemiology and Public Health Research Group, Centre for Public Health, Queen's University of Belfast, Regional Genetics Centre, Level A, Tower Block, Belfast City Hospital, Lisburn Road, Belfast BT9 7AB, United Kingdom; Regional Nephrology Unit, Belfast City Hospital, Belfast, United Kingdom.
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Abstract
BACKGROUND This study aimed to analyze the scientific outputs of diabetic kidney disease (DKD) research and explore its hotspots and frontiers from 2000 to 2017, using bibliometric methods. METHODS Articles in DKD research between 2000 and 2017 were retrieved from the Web of Science Core Collection (WoSCC). We used the VOSviewer 1.6.8 and CiteSpace 5.2 to analyze publication years, journals, countries, institutions, authors, references, and keywords. Keywords with citation bursts were used to analyze the research hotspots and emerging trends. RESULTS We identified 27,577 publications in DKD research from 2000 to 2017. The annual publication number increased with time. Nephrology Dialysis Transplantation published the highest number of articles. The United States was the most influential country with most publications and collaborations with other countries. Harvard University was the leading institute. Parving had the most cited publications. Keywords analysis indicated that the renin-angiotensin system inhibition used to be the most prevalent research topic, while recent research hotspots were podocyte, inflammation, and biomarker. The biomarkers for DKD screening, diagnosis, and prognosis could be a research frontier. CONCLUSIONS The number of DKD related publications rapidly increased over the past 2 decades. Our study revealed the structure, hotspots, and evolution trends of DKD research. Further studies and more collaborations are needed.
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Affiliation(s)
- Lu-Xi Zou
- School of Management, Zhejiang University, Hangzhou, Zhejiang
| | - Ling Sun
- Department of Nephrology, Xuzhou Central Hospital, Medical College of Southeast University, Xuzhou, Jiangsu, China
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Siwy J, Klein T, Rosler M, von Eynatten M. Urinary Proteomics as a Tool to Identify Kidney Responders to Dipeptidyl Peptidase-4 Inhibition: A Hypothesis-Generating Analysis from the MARLINA-T2D Trial. Proteomics Clin Appl 2019; 13:e1800144. [PMID: 30632692 DOI: 10.1002/prca.201800144] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2018] [Revised: 12/27/2018] [Indexed: 01/13/2023]
Abstract
PURPOSE Chronic kidney disease (CKD) is a serious complication of hyperglycemia and treatment options to slow its progression are scarce. Dipeptidyl peptidase-4 (DPP-4) inhibitors are common glucose-lowering drugs in type 2 diabetes (T2D). Among these, linagliptin has been suggested to exert kidney protective effects. It is investigated whether an effect of linagliptin on kidney function could be unmasked by characterizing the urinary proteome profile (UPP) in albuminuric T2D individuals. EXPERIMENTAL DESIGN Participants of the MARLINA-T2D trial (NCT01792518) are randomized 1:1 to receive either linagliptin 5 mg or placebo for 24 weeks. A previously developed proteome-based classifier, CKD273, is assessed. RESULTS Results confirm a significant correlation between CKD273 and clinical kidney parameters as well as with eGFR decline. Patient stratification using CKD273 at baseline, show a trend toward attenuation of renal function loss in high CKD-risk patients treated with linagliptin. Moreover, characterized are linagliptin affected peptides of which the majority contained a DPP-4 target sequence. CONCLUSIONS AND CLINICAL RELEVANCE CKD273 is a promising tool for identifying patients at high risk for CKD progression and may unmask a potential of linagliptin to slow progressive kidney function loss in high CKD-risk patients. UPP characterization reveals a significant impact of linagliptin on urinary peptides.
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Affiliation(s)
- Justyna Siwy
- mosaiques-diagnostics GmbH, Rotenburger Str. 20, 30659, Hannover, Germany
| | - Thomas Klein
- Boehringer Ingelheim Pharma GmbH & Co. KG, Birkendorfer Str. 65, 88397, Biberach an der Riß, Germany
| | - Marcel Rosler
- Boehringer Ingelheim Pharma GmbH & Co. KG, Birkendorfer Str. 65, 88397, Biberach an der Riß, Germany
| | - Maximilian von Eynatten
- Boehringer Ingelheim International GmbH. KG, Binger Str. 173, 55216, Ingelheim am Rhein, Germany
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Colombo M, Looker HC, Farran B, Hess S, Groop L, Palmer CNA, Brosnan MJ, Dalton RN, Wong M, Turner C, Ahlqvist E, Dunger D, Agakov F, Durrington P, Livingstone S, Betteridge J, McKeigue PM, Colhoun HM. Serum kidney injury molecule 1 and β 2-microglobulin perform as well as larger biomarker panels for prediction of rapid decline in renal function in type 2 diabetes. Diabetologia 2019; 62:156-168. [PMID: 30288572 PMCID: PMC6290680 DOI: 10.1007/s00125-018-4741-9] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/08/2018] [Accepted: 09/04/2018] [Indexed: 12/24/2022]
Abstract
AIMS/HYPOTHESIS As part of the Surrogate Markers for Micro- and Macrovascular Hard Endpoints for Innovative Diabetes Tools (SUMMIT) programme we previously reported that large panels of biomarkers derived from three analytical platforms maximised prediction of progression of renal decline in type 2 diabetes. Here, we hypothesised that smaller (n ≤ 5), platform-specific combinations of biomarkers selected from these larger panels might achieve similar prediction performance when tested in three additional type 2 diabetes cohorts. METHODS We used 657 serum samples, held under differing storage conditions, from the Scania Diabetes Registry (SDR) and Genetics of Diabetes Audit and Research Tayside (GoDARTS), and a further 183 nested case-control sample set from the Collaborative Atorvastatin in Diabetes Study (CARDS). We analysed 42 biomarkers measured on the SDR and GoDARTS samples by a variety of methods including standard ELISA, multiplexed ELISA (Luminex) and mass spectrometry. The subset of 21 Luminex biomarkers was also measured on the CARDS samples. We used the event definition of loss of >20% of baseline eGFR during follow-up from a baseline eGFR of 30-75 ml min-1 [1.73 m]-2. A total of 403 individuals experienced an event during a median follow-up of 7 years. We used discrete-time logistic regression models with tenfold cross-validation to assess association of biomarker panels with loss of kidney function. RESULTS Twelve biomarkers showed significant association with eGFR decline adjusted for covariates in one or more of the sample sets when evaluated singly. Kidney injury molecule 1 (KIM-1) and β2-microglobulin (B2M) showed the most consistent effects, with standardised odds ratios for progression of at least 1.4 (p < 0.0003) in all cohorts. A combination of B2M and KIM-1 added to clinical covariates, including baseline eGFR and albuminuria, modestly improved prediction, increasing the area under the curve in the SDR, Go-DARTS and CARDS by 0.079, 0.073 and 0.239, respectively. Neither the inclusion of additional Luminex biomarkers on top of B2M and KIM-1 nor a sparse mass spectrometry panel, nor the larger multiplatform panels previously identified, consistently improved prediction further across all validation sets. CONCLUSIONS/INTERPRETATION Serum KIM-1 and B2M independently improve prediction of renal decline from an eGFR of 30-75 ml min-1 [1.73 m]-2 in type 2 diabetes beyond clinical factors and prior eGFR and are robust to varying sample storage conditions. Larger panels of biomarkers did not improve prediction beyond these two biomarkers.
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Affiliation(s)
- Marco Colombo
- Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | - Helen C Looker
- Population Health Sciences, University of Dundee, Dundee, UK
| | - Bassam Farran
- MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road South, Edinburgh, EH4 2XU, UK
| | - Sibylle Hess
- Sanofi-Aventis Deutschland GmbH, Frankfurt, Germany
| | - Leif Groop
- Lund University Diabetes Centre, Lund University, Malmö, Sweden
| | - Colin N A Palmer
- Ninewells Hospital and Medical School, University of Dundee, Dundee, UK
| | | | - R Neil Dalton
- Evelina London Children's Hospital, Guy's & St Thomas NHS Foundation Trust, London, UK
| | - Max Wong
- Evelina London Children's Hospital, Guy's & St Thomas NHS Foundation Trust, London, UK
| | - Charles Turner
- Evelina London Children's Hospital, Guy's & St Thomas NHS Foundation Trust, London, UK
| | - Emma Ahlqvist
- Lund University Diabetes Centre, Lund University, Malmö, Sweden
| | - David Dunger
- Department of Paediatrics, Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | | | - Paul Durrington
- Division of Cardiovascular Sciences, University of Manchester, Manchester, UK
| | | | - John Betteridge
- Department of Endocrinology and Diabetes, University College London Hospitals, London, UK
| | - Paul M McKeigue
- Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | - Helen M Colhoun
- MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road South, Edinburgh, EH4 2XU, UK.
- NHS Fife, Fife, UK.
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Perico L, Perico N, Benigni A. The incessant search for renal biomarkers: is it really justified? Curr Opin Nephrol Hypertens 2018; 28:195-202. [PMID: 30531471 DOI: 10.1097/mnh.0000000000000481] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
PURPOSE OF REVIEW This review summarizes the most recent and relevant findings in the search for novel biomarkers for the most common renal diseases. RECENT FINDINGS Unprecedented, fast-paced technical advances in biomedical research have offered an opportunity to identify novel and more specific renal biomarkers in several clinical settings. However, despite the huge efforts made, the molecules identified so far have generally failed to provide relevant information beyond what has already been generated by established biomarkers, such as serum creatinine and proteinuria, whereas the complexity and costs of these technology platforms hamper their widespread implementation. SUMMARY No novel renal biomarkers have added clear-cut additional value in clinical decision-making. The only exception is anti-phospholipase A2 receptor antibodies, which have been implemented successfully as a diagnostic and prognostic biomarker of membranous nephropathy. This achievement, along with the large number of ongoing collaborative projects worldwide, should lead the renal community to be quite confident regarding the successful qualification of novel and effective diagnostic, prognostic and therapeutic response biomarkers for kidney diseases, hopefully in the next few years.
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Affiliation(s)
- Luca Perico
- Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Bergamo, Italy
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32
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Novel Urinary Biomarkers For Improved Prediction Of Progressive Egfr Loss In Early Chronic Kidney Disease Stages And In High Risk Individuals Without Chronic Kidney Disease. Sci Rep 2018; 8:15940. [PMID: 30374033 PMCID: PMC6206033 DOI: 10.1038/s41598-018-34386-8] [Citation(s) in RCA: 42] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2018] [Accepted: 10/15/2018] [Indexed: 12/22/2022] Open
Abstract
Chronic kidney disease is associated with increased risk of CKD progression and death. Therapeutic approaches to limit progression are limited. Developing tools for the early identification of those individuals most likely to progress will allow enriching clinical trials in high risk early CKD patients. The CKD273 classifier is a panel of 273 urinary peptides that enables early detection of CKD and prognosis of progression. We have generated urine capillary electrophoresis-mass spectrometry-based peptidomics CKD273 subclassifiers specific for CKD stages to allow the early identification of patients at high risk of CKD progression. In the validation cohort, the CKD273 subclassifiers outperformed albuminuria and CKD273 classifier for predicting rapid loss of eGFR in individuals with baseline eGFR > 60 ml/min/1.73 m2. In individuals with eGFR > 60 ml/min/1.73 m2 and albuminuria <30 mg/day, the CKD273 subclassifiers predicted rapid eGFR loss with AUC ranging from 0.797 (0.743-0.844) to 0.736 (0.689-0.780). The association between CKD273 subclassifiers and rapid progression remained significant after adjustment for age, sex, albuminuria, DM, baseline eGFR, and systolic blood pressure. Urinary peptidomics CKD273 subclassifiers outperformed albuminuria and CKD273 classifier for predicting the risk of rapid CKD progression in individuals with eGFR > 60 ml/min/1.73 m2. These CKD273 subclassifiers represented the earliest evidence of rapidly progressive CKD in non-albuminuric individuals with preserved renal function.
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33
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Tofte N, Lindhardt M, Adamova K, Beige J, Beulens JWJ, Birkenfeld AL, Currie G, Delles C, Dimos I, Francová L, Frimodt-Møller M, Girman P, Göke R, Havrdova T, Kooy A, Mischak H, Navis G, Nijpels G, Noutsou M, Ortiz A, Parvanova A, Persson F, Ruggenenti PL, Rutters F, Rychlík I, Spasovski G, Speeckaert M, Trillini M, von der Leyen H, Rossing P. Characteristics of high- and low-risk individuals in the PRIORITY study: urinary proteomics and mineralocorticoid receptor antagonism for prevention of diabetic nephropathy in Type 2 diabetes. Diabet Med 2018; 35:1375-1382. [PMID: 29781558 DOI: 10.1111/dme.13669] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 05/10/2018] [Indexed: 12/13/2022]
Abstract
AIM To compare clinical baseline data in individuals with Type 2 diabetes and normoalbuminuria, who are at high or low risk of diabetic kidney disease based on the urinary proteomics classifier CKD273. METHODS We conducted a prospective, randomized, double-blind, placebo-controlled international multicentre clinical trial and observational study in participants with Type 2 diabetes and normoalbuminuria, stratified into high- or low-risk groups based on CKD273 score. Clinical baseline data for the whole cohort and stratified by risk groups are reported. The associations between CKD273 and traditional risk factors for diabetic kidney disease were evaluated using univariate and logistic regression analysis. RESULTS A total of 1777 participants from 15 centres were included, with 12.3% of these having a high-risk proteomic pattern. Participants in the high-risk group (n=218), were more likely to be men, were older, had longer diabetes duration, a lower estimated GFR and a higher urinary albumin:creatinine ratio than those in the low-risk group (n=1559, P<0.02). Numerical differences were small and univariate regression analyses showed weak associations (R2 < 0.04) of CKD273 with each baseline variable. In a logistic regression model including clinical variables known to be associated with diabetic kidney disease, estimated GFR, gender, log urinary albumin:creatinine ratio and use of renin-angiotensin system-blocking agents remained significant determinants of the CKD273 high-risk group: area under the curve 0.72 (95% CI 0.68-0.75; P<0.01). CONCLUSIONS In this population of individuals with Type 2 diabetes and normoalbuminuria, traditional diabetic kidney disease risk factors differed slightly between participants at high risk and those at low risk of diabetic kidney disease, based on CKD273. These data suggest that CKD273 may provide additional prognostic information over and above the variables routinely available in the clinic. Testing the added value will be subject to our ongoing study. (European Union Clinical Trials Register: EudraCT 2012-000452-34 and Clinicaltrials.gov: NCT02040441).
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Affiliation(s)
- N Tofte
- Steno Diabetes Centre Copenhagen, Gentofte, Denmark
| | - M Lindhardt
- Steno Diabetes Centre Copenhagen, Gentofte, Denmark
| | - K Adamova
- University Clinic of Endocrinology, Diabetes and Metabolic Disorders, Skopje, Macedonia
| | - J Beige
- Klinikum St. Georg, Nephrology and KfH Renal Unit, Leipzig, Martin-Luther University Halle, Wittenberg, Germany
| | - J W J Beulens
- Amsterdam Public Health Research Institute, VU University Medical Centre, Amsterdam, The Netherlands
- Julius Centre for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - A L Birkenfeld
- Clinical Study Centre Metabolic Vascular Medicine, GWT TU-Dresden GmbH, Dresden, Germany
- Paul Langerhans Institute Dresden of the Helmholtz Centre Munich at University Hospital, and Faculty of Medicine, TU Dresden, Dresden, Germany
- German Centre for Diabetes Research (DZD e.V.), Neuherberg, Germany
| | - G Currie
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | - C Delles
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | - I Dimos
- Diabetespraxis, Leipzig, Germany
| | - L Francová
- 1st Department, Charles University, Third Faculty of Medicine, Prague, Czech Republic
| | | | - P Girman
- Diabetes Centre, Institute for Clinical and Experimental Medicine, Prague, Czech Republic
| | - R Göke
- Diabetologische Schwerpunktpraxis, Diabetologen Hessen, Marburg, Germany
| | - T Havrdova
- Diabetes Centre, Institute for Clinical and Experimental Medicine, Prague, Czech Republic
| | - A Kooy
- Bethesda Diabetes Research Centre, Hoogeveen and University Medical Centre Groningen, Netherlands
| | - H Mischak
- Mosaiques Diagnostics, Hannover, Germany
| | - G Navis
- Division of Nephrology, Department of Internal Medicine, University Medical Centre Groningen, Groningen, Netherlands
| | - G Nijpels
- Department General Practice and Elderly Care, Amsterdam Public Health VU University Medical Centre, Amsterdam, The Netherlands
| | - M Noutsou
- Diabetes Centre and 2nd Department of Internal Medicine, National and Kapodistrian University of Athens, Hippokratio General Hospital, Athens, Greece
| | - A Ortiz
- Instituto de Investigacion Sanitaria de la Fundacion Jiménez Díaz UAM, Madrid, Spain
| | - A Parvanova
- Istituto di Richerche Farmacologiche Mario Negri, Bergamo, Italy
| | - F Persson
- Steno Diabetes Centre Copenhagen, Gentofte, Denmark
| | - P L Ruggenenti
- Istituto di Richerche Farmacologiche Mario Negri, Bergamo, Italy
| | - F Rutters
- Amsterdam Public Health Research Institute, VU University Medical Centre, Amsterdam, The Netherlands
| | - I Rychlík
- 1st Department, Charles University, Third Faculty of Medicine, Prague, Czech Republic
- Faculty Hospital Královské Vinohrady, Prague, Czech Republic
| | - G Spasovski
- Department of Nephrology, Cyril and Methodius University in Skopje, Skopje, Macedonia
| | - M Speeckaert
- Ghent University Hospital, Department of Nephrology, Ghent, Belgium
| | - M Trillini
- Istituto di Richerche Farmacologiche Mario Negri, Bergamo, Italy
| | | | - P Rossing
- Steno Diabetes Centre Copenhagen, Gentofte, Denmark
- University of Copenhagen, Copenhagen, Denmark
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Wallbach M, Zürbig P, Dihazi H, Müller GA, Wachter R, Beige J, Koziolek MJ, Mischak H. Kidney protective effects of baroreflex activation therapy in patients with resistant hypertension. J Clin Hypertens (Greenwich) 2018; 20:1519-1526. [PMID: 30203514 DOI: 10.1111/jch.13365] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2018] [Revised: 06/27/2018] [Accepted: 07/13/2018] [Indexed: 02/06/2023]
Abstract
Baroreflex activation therapy (BAT) is approved for the treatment of resistant hypertension. In addition to blood pressure (BP) reduction, pilot studies suggested several organoprotective effects of BAT. Thirty-two patients with resistant hypertension were prospectively treated with BAT. Besides office BP and 24-hour ambulatory BP (ABP) measurements, detection of a urinary proteome-based classifier (CKD273), which has been shown to predict chronic kidney disease (CKD) progression, was carried out at baseline and after 6 months of BAT. Office BP significantly decreased from 170 ± 25/90 ± 18 to 149 ± 29/82 ± 18 mm Hg. Analysis of CKD273 score and eGFR with CKD-EPI equation at baseline revealed strong correlation (r = 0.568, P < 0.001). After 6 months of BAT, there was no significant change in CKD273 score (-0.061 [95% CI: -0.262 to 0.140], P = 0.601). However, by stratification of the data regarding ABP response, there was a statistically significant (P = 0.0113) reduction in the CKD273 score from a mean of 0.161 [95% CI: -0.093 to 0.414] to -0.346 [95% CI: -0.632 to -0.060] after BAT in patients with systolic ABP decrease of ≥5 mm Hg. These data emphasized potential nephroprotective effects of BAT in patients with sufficient BP response.
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Affiliation(s)
- Manuel Wallbach
- Department of Nephrology & Rheumatology, University Medical Center Göttingen, Göttingen, Germany
| | | | - Hassan Dihazi
- Department of Nephrology & Rheumatology, University Medical Center Göttingen, Göttingen, Germany
| | - Gerhard A Müller
- Department of Nephrology & Rheumatology, University Medical Center Göttingen, Göttingen, Germany
| | - Rolf Wachter
- Department of Cardiology & Pneumology, University Medical Center Göttingen, Göttingen, Germany.,Clinic and Policlinic for Cardiology, University Hospital Leipzig, Leipzig, Germany
| | - Joachim Beige
- Department of Nephrology/KfH Renal Unit, Hospital Sankt Georg, Leipzig, Germany.,Martin-Luther-University Halle/Wittenberg, Halle, Germany
| | - Michael J Koziolek
- Department of Nephrology & Rheumatology, University Medical Center Göttingen, Göttingen, Germany
| | - Harald Mischak
- Mosaiques Diagnostics GmbH, Hannover, Germany.,BHF Glasgow Cardiovascular Research Centre, University of Glasgow, Glasgow, UK
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35
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Frantzi M, Latosinska A, Kontostathi G, Mischak H. Clinical Proteomics: Closing the Gap from Discovery to Implementation. Proteomics 2018; 18:e1700463. [PMID: 29785737 DOI: 10.1002/pmic.201700463] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2018] [Revised: 05/10/2018] [Indexed: 12/15/2022]
Abstract
Clinical proteomics, the application of proteome analysis to serve a clinical purpose, represents a major field in the area of proteome research. Over 1000 manuscripts on this topic are published each year, with numbers continuously increasing. However, the anticipated outcome, the transformation of the reported findings into improvements in patient management, is not immediately evident. In this article, the value and validity of selected clinical proteomics findings are investigated, and it is assessed how far implementation has progressed. A main conclusion from this assessment is that to achieve implementation, well-powered clinical studies are required in the appropriate population, addressing a specific clinical need and with a clear context-of-use. Efforts toward implementation, to be feasible, must be supported by the key players in science: publishers and funders. The authors propose a change on objectives, from additional discovery studies toward studies aiming at validation of the plethora of potential biomarkers that have been described, to demonstrate practical value of clinical proteomics. All elements required, potential biomarkers, technologies, and bio-banked samples are available (based on today's literature), hence a change in focus from discovery toward validation and application is not only urgently necessary, but also possible based on resources available today.
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Affiliation(s)
- Maria Frantzi
- Mosaiques Diagnostics GmbH, Hannover, 30659, Germany
| | | | - Georgia Kontostathi
- Department of Biotechnology, Biomedical Research Foundation Academy of Athens, Athens, 11527, Greece
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36
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Siwy J, Zürbig P, Argiles A, Beige J, Haubitz M, Jankowski J, Julian BA, Linde PG, Marx D, Mischak H, Mullen W, Novak J, Ortiz A, Persson F, Pontillo C, Rossing P, Rupprecht H, Schanstra JP, Vlahou A, Vanholder R. Noninvasive diagnosis of chronic kidney diseases using urinary proteome analysis. Nephrol Dial Transplant 2018; 32:2079-2089. [PMID: 27984204 DOI: 10.1093/ndt/gfw337] [Citation(s) in RCA: 38] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2016] [Accepted: 08/10/2016] [Indexed: 12/11/2022] Open
Abstract
Background In spite of its invasive nature and risks, kidney biopsy is currently required for precise diagnosis of many chronic kidney diseases (CKDs). Here, we explored the hypothesis that analysis of the urinary proteome can discriminate different types of CKD irrespective of the underlying mechanism of disease. Methods We used data from the proteome analyses of 1180 urine samples from patients with different types of CKD, generated by capillary electrophoresis coupled to mass spectrometry. A set of 706 samples served as the discovery cohort, and 474 samples were used for independent validation. For each CKD type, peptide biomarkers were defined using statistical analysis adjusted for multiple testing. Potential biomarkers of statistical significance were combined in support vector machine (SVM)-based classifiers. Results For seven different types of CKD, several potential urinary biomarker peptides (ranging from 116 to 619 peptides) were defined and combined into SVM-based classifiers specific for each CKD. These classifiers were validated in an independent cohort and showed good to excellent accuracy for discrimination of one CKD type from the others (area under the receiver operating characteristic curve ranged from 0.77 to 0.95). Sequence analysis of the biomarkers provided further information that may clarify the underlying pathophysiology. Conclusions Our data indicate that urinary proteome analysis has the potential to identify various types of CKD defined by pathological assessment of renal biopsies and current clinical practice in general. Moreover, these approaches may provide information to model molecular changes per CKD.
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Affiliation(s)
| | | | | | - Joachim Beige
- KfH Renal Unit, Department Nephrology, Leipzig and Martin Luther University, Halle/Wittenberg, Germany
| | - Marion Haubitz
- Department of Nephrology, Klinikum Fulda gAG, Fulda, Germany
| | - Joachim Jankowski
- Institute for Molecular Cardiovascular Research, RWTH Aachen University Hospital, Aachen, Germany.,School for Cardiovascular Diseases (CARIM), University of Maastricht, Maastricht, The Netherlands
| | - Bruce A Julian
- University of Alabama at Birmingham, Birmingham, AL, USA
| | | | - David Marx
- Department of Nephrology and Kidney Transplantation, Hôpitaux Universitaires de Strasbourg, Strasbourg, France
| | - Harald Mischak
- Mosaiques Diagnostics GmbH, Hanover, Germany.,BHF Glasgow Cardiovascular Research Centre, Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | - William Mullen
- BHF Glasgow Cardiovascular Research Centre, Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | - Jan Novak
- University of Alabama at Birmingham, Birmingham, AL, USA
| | - Alberto Ortiz
- School of Medicine, Jimenez Diaz Foundation Institute for Health Research, Autonomous University of Madrid, Madrid, Spain
| | | | - Claudia Pontillo
- Mosaiques Diagnostics GmbH, Hanover, Germany.,Charite-Universitätsmedizin, Berlin, Germany
| | - Peter Rossing
- Steno Diabetes Center, Gentofte, Denmark.,Faculty of Health, University of Aarhus, Aarhus, Denmark.,Faculty of Health, University of Copenhagen, Copenhagen, Denmark
| | | | - Joost P Schanstra
- Institute of Cardiovascular and Metabolic Disease, French Institute of Health and Medical Research U1048, Toulouse, France.,Université Toulouse III Paul-Sabatier, Toulouse, France
| | - Antonia Vlahou
- Division of Biotechnology, Biomedical Research Foundation, Academy of Athens, Athens, Greece
| | - Raymond Vanholder
- Nephrology Section, Department of Internal Medicine, Ghent University Hospital, Ghent, Belgium
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Pontillo C, Jacobs L, Staessen JA, Schanstra JP, Rossing P, Heerspink HJL, Siwy J, Mullen W, Vlahou A, Mischak H, Vanholder R, Zürbig P, Jankowski J. A urinary proteome-based classifier for the early detection of decline in glomerular filtration. Nephrol Dial Transplant 2018; 32:1510-1516. [PMID: 27387473 DOI: 10.1093/ndt/gfw239] [Citation(s) in RCA: 40] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2016] [Accepted: 05/02/2016] [Indexed: 12/13/2022] Open
Abstract
Background Chronic kidney disease (CKD) progression is currently assessed by a decline in estimated glomerular filtration rate (eGFR) and/or an increase in urinary albumin excretion (UAE). However, these markers are considered either to be late-stage markers or to have low sensitivity or specificity. In this study, we investigated the performance of the urinary proteome-based classifier CKD273, compared with UAE, in a number of different narrow ranges of CKD severity, with each range separated by an eGFR of 10 mL/min/1.73 m 2 . Methods A total of 2672 patients with different CKD stages were included in the study. Of these, 394 individuals displayed a decline in eGFR of >5 mL/min/1.73 m 2 /year (progressors) and the remaining individuals were considered non-progressors. For all samples, UAE values and CKD273 classification scores were obtained. To assess UAE values and CKD273 scores at different disease stages, the cohort was divided according to baseline eGFRs of ≥80, 70-79, 60-69, 50-59, 40-49, 30-39 and <29 mL/min/1.73 m 2 . In addition, areas under the curve for CKD273 and UAE were calculated. Results In early stage CKD, the urinary proteome-based classifier performed significantly better than UAE in detecting progressors. In contrast, UAE performed better in patients with late-stage CKD. No significant difference in performance was found between CKD273 and UAE in patients with moderately reduced renal function. Conclusions These results suggest that urinary peptides, as combined in the CKD273 classifier, allow the detection of progressive CKD at early stages, a point where therapeutic intervention is more likely to be effective. However, late-stage disease, where irreversible damage of the kidney is already present, is better detected by UAE.
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Affiliation(s)
- Claudia Pontillo
- Mosaiques Diagnostics, Hanover, Germany.,Charité-Universitatsmedizin, Berlin, Germany
| | - Lotte Jacobs
- Department of Cardiovascular Sciences, University of Leuven, Leuven, Belgium
| | - Jan A Staessen
- Department of Cardiovascular Sciences, University of Leuven, Leuven, Belgium.,R&D VitaK Group, Maastricht University, Maastricht, The Netherlands
| | - Joost P Schanstra
- Institute of Metabolic and Cardiovascular Diseases, Inserm U1048, Toulouse, France.,Université Toulouse III Paul-Sabatier, Toulouse, France
| | - Peter Rossing
- Steno Diabetes Center, Gentofte, Denmark.,University of Aarhus, Aarhus, Denmark.,Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
| | - Hiddo J L Heerspink
- Department of Clinical Pharmacy and Pharmacology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | | | | | - Antonia Vlahou
- Biomedical Research Foundation, Academy of Athens, Athens, Greece
| | - Harald Mischak
- Mosaiques Diagnostics, Hanover, Germany.,University of Glasgow, Glasgow, UK
| | - Ray Vanholder
- Nephrology Section, Department of Internal Medicine, Ghent University Hospital, Ghent, Belgium
| | | | - Joachim Jankowski
- Charité-Universitatsmedizin, Berlin, Germany.,Institute for Molecular Cardiovascular Research, University Hospital RWTH, Aachen, Germany.,Department of Pathology, Cardiovascular Research Institute Maastricht (CARIM), University of Maastricht, Maastricht, The Netherlands
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38
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Lindhardt M, Persson F, Zürbig P, Stalmach A, Mischak H, de Zeeuw D, Lambers Heerspink H, Klein R, Orchard T, Porta M, Fuller J, Bilous R, Chaturvedi N, Parving HH, Rossing P. Urinary proteomics predict onset of microalbuminuria in normoalbuminuric type 2 diabetic patients, a sub-study of the DIRECT-Protect 2 study. Nephrol Dial Transplant 2018; 32:1866-1873. [PMID: 27507891 DOI: 10.1093/ndt/gfw292] [Citation(s) in RCA: 34] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2016] [Accepted: 06/13/2016] [Indexed: 11/12/2022] Open
Abstract
Background Early prevention of diabetic nephropathy is not successful as early interventions have shown conflicting results, partly because of a lack of early and precise indicators of disease development. Urinary proteomics has shown promise in this regard and could identify those at high risk who might benefit from treatment. In this study we investigate its utility in a large type 2 diabetic cohort with normoalbuminuria. Methods We performed a post hoc analysis in the Diabetic Retinopathy Candesartan Trials (DIRECT-Protect 2 study), a multi centric randomized clinical controlled trial. Patients were allocated to candesartan or placebo, with the aim of slowing the progression of retinopathy. The secondary endpoint was development of persistent microalbuminuria (three of four samples). We used a previously defined chronic kidney disease risk score based on proteomic measurement of 273 urinary peptides (CKD273-classifier). A Cox regression model for the progression of albuminuria was developed and evaluated with integrated discrimination improvement (IDI), continuous net reclassification index (cNRI) and receiver operating characteristic curve statistics. Results Seven hundred and thirty-seven patients were analysed and 89 developed persistent microalbuminuria (12%) with a mean follow-up of 4.1 years. At baseline the CKD273-classifier predicted development of microalbuminuria during follow-up, independent of treatment (candesartan/placebo), age, gender, systolic blood pressure, urine albumin excretion rate, estimated glomerular filtration rate, HbA1c and diabetes duration, with hazard ratio 2.5 [95% confidence interval (CI) 1.4-4.3; P = 0.002] and area under the curve 0.79 (95% CI 0.75-0.84; P < 0.0001). The CKD273-classifier improved the risk prediction (relative IDI 14%, P = 0.002; cNRI 0.10, P = 0.043). Conclusions In this cohort of patients with type 2 diabetes and normoalbuminuria from a large intervention study, the CKD273-classifier was an independent predictor of microalbuminuria. This may help identify high-risk normoalbuminuric patients for preventive strategies for diabetic nephropathy.
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Affiliation(s)
| | | | | | | | - Harald Mischak
- Mosaiques Diagnostics GmbH, Hannover, Germany.,University of Glasgow, Glasgow, UK
| | - Dick de Zeeuw
- Department of Clinical Pharmacology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Hiddo Lambers Heerspink
- Department of Clinical Pharmacology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Ronald Klein
- Department of Ophthalmology and Visual Sciences, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Trevor Orchard
- Department of Epidemiology, Medicine & Pediatrics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Massimo Porta
- Department of Medical Sciences, University of Turin, Torino, Italy
| | - John Fuller
- Department of Epidemiology and Public Health, University College London, London, UK
| | - Rudolf Bilous
- Institute of Cellular Medicine, Newcastle University, Newcastle upon Tyne, UK.,South Tees NHS Trust, Middlesbrough, UK
| | - Nish Chaturvedi
- Institute of Cardiovascular Sciences, University College London, London, UK
| | - Hans-Henrik Parving
- Department of Medical Endocrinology, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Peter Rossing
- Steno Diabetes Center, Gentofte, Denmark.,Faculty of Health Science, University of Aarhus, Aarhus, Denmark.,The Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
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39
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Lyu LL, Feng Y, Liu BC. Urinary Biomarkers for Chronic Kidney Disease with a Focus on Gene Transcript. Chin Med J (Engl) 2018; 130:2251-2256. [PMID: 28875962 PMCID: PMC5598339 DOI: 10.4103/0366-6999.213965] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Objective: In the upcoming era of precision medicine, searching for the early, noninvasive biomarkers has been the cornerstone and major challenge in the management of chronic kidney disease (CKD). Urine contains rich biological information which could be the ideal source for noninvasive biomarkers of CKD. This review will discuss the recent advance in urinary biomarker. Data Sources: This review was based on data in articles published in the PubMed databases up to June 20, 2017, with the following keywords: “Chronic kidney disease”, “Biomarker”, and “Urine”. Study Selection: Original articles and important reviews on urinary biomarker were selected for this review. Results: Urinary biomarker studies of CKD mainly focused on urine sediment, supernatant, and urinary extracellular vesicles. The gene transcript (microRNA [miRNA], messenger RNA [mRNA]) biomarkers have been recently shown with diagnostic potential for CKD reflecting kidney function and histological change. However, challenges regarding technique and data analysis need to be resolved before translation to clinic. Conclusions: Different fractions of urine contain rich information for biomarker discovery, among which urine (extracellular vesicles) mRNA, miRNA, might represent promising biomarker for CKD.
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Affiliation(s)
- Lin-Li Lyu
- Department of Nephrology, School of Medicine, Zhongda Hospital, Southeast University, Nanjing, Jiangsu 210009, China
| | - Ye Feng
- Department of Nephrology, School of Medicine, Zhongda Hospital, Southeast University, Nanjing, Jiangsu 210009, China
| | - Bi-Cheng Liu
- Department of Nephrology, School of Medicine, Zhongda Hospital, Southeast University, Nanjing, Jiangsu 210009, China
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40
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Abstract
Diabetic kidney disease (DKD) remains one of the leading causes of reduced lifespan in diabetes. The quest for both prognostic and surrogate endpoint biomarkers for advanced DKD and end-stage renal disease has received major investment and interest in recent years. However, at present no novel biomarkers are in routine use in the clinic or in trials. This review focuses on the current status of prognostic biomarkers. First, we emphasise that albuminuria and eGFR, with other routine clinical data, show at least modest prediction of future renal status if properly used. Indeed, a major limitation of many current biomarker studies is that they do not properly evaluate the marginal increase in prediction on top of these routinely available clinical data. Second, we emphasise that many of the candidate biomarkers for which there are numerous sporadic reports in the literature are tightly correlated with each other. Despite this, few studies have attempted to evaluate a wide range of biomarkers simultaneously to define the most useful among these correlated biomarkers. We also review the potential of high-dimensional panels of lipids, metabolites and proteins to advance the field, and point to some of the analytical and post-analytical challenges of taking initial studies using these and candidate approaches through to actual clinical biomarker use.
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Affiliation(s)
- Helen M Colhoun
- MRC Institute of Genetics & Molecular Medicine, The University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK.
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41
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Abstract
PURPOSE OF REVIEW Current biomarkers for chronic kidney disease (CKD) are limited by lack of sensitivity and inability to prognosticate CKD progression. Significant recent research has better characterized novel biomarker candidates that are associated with CKD progression and cardiovascular mortality in CKD. This review discusses the most significant advances within the past year. RECENT FINDINGS We discuss biomarkers for outcomes in CKD under two categories: emerging (defined as having been validated in an independent cohort), which include serum cystatin C, serum β-trace protein, β2-microglobulin, soluble urokinase-type plasminogen activator receptor, soluble tumor necrosis factor receptors 1/2, urinary monocyte chemotactic protein-1, neutrophil gelatin-associated lipocalin, kidney injury molecule-1, and fibroblast growth factor-23; and novel (which have shown associations in smaller observational studies but have not been validated yet), which include indoxyl sulfate, p-cresyl sulfate, trimethylamine-N-oxide, IL-18, Klotho, markers of endothelial dysfunction, vimentin, and procollagen type III N-terminal propeptide. Further, we also discuss future directions for biomarker research including unbiased -omics approaches. SUMMARY There are a number of promising biomarkers that can better prognosticate outcomes in and progression of CKD. Further research is warranted to examine whether these biomarkers validate independently as well, and if their incorporation improves clinical practice or trial enrollment.
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42
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Urinary proteomics using capillary electrophoresis coupled to mass spectrometry for diagnosis and prognosis in kidney diseases. Curr Opin Nephrol Hypertens 2018; 25:494-501. [PMID: 27584928 DOI: 10.1097/mnh.0000000000000278] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
Abstract
PURPOSE OF REVIEW Urine is the most useful of body fluids for biomarker research. Therefore, we have focused on urinary proteomics, using capillary electrophoresis coupled to mass spectrometry, to investigate kidney diseases in recent years. RECENT FINDINGS Several urinary proteomics studies for the detection of various kidney diseases have indicated the potential of this approach aimed at diagnostic and prognostic assessment. Urinary protein biomarkers such as collagen fragments, serum albumin, α-1-antitrypsin, and uromodulin can help to explain the processes involved during disease progression. SUMMARY Urinary proteomics has been used in several studies in order to identify and validate biomarkers associated with different kidney diseases. These biomarkers, with improved sensitivity and specificity when compared with the current gold standards, provide a significant alternative for diagnosis and prognosis, as well as improving clinical decision-making.
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43
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The Patterns, Risk Factors, and Prediction of Progression in Chronic Kidney Disease: A Narrative Review. Semin Nephrol 2018; 36:273-82. [PMID: 27475658 DOI: 10.1016/j.semnephrol.2016.05.004] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Chronic kidney disease (CKD) is a global public health problem that is associated with excess morbidity, mortality, and health resource utilization. The progression of CKD is defined by a decrease in glomerular filtration rate and leads to a variety of metabolic abnormalities including acidosis, hypertension, anemia, and mineral bone disorder. Lower glomerular filtration rate also bears a strong relationship with an increased risk of cardiovascular events, end-stage renal disease, and death. Patterns of CKD progression include linear and nonlinear trajectories, but kidney function can remain stable for years in some individuals. Addressing modifiable risk factors for the progression of CKD is needed to attenuate its associated morbidity and mortality. Developing effective risk prediction models for CKD progression is critical to identify patients who are more likely to benefit from interventions and more intensive monitoring. Accurate risk-prediction algorithms permit systems to best align health care resources with risk to maximize their effects and efficiency while guiding overall decision making.
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44
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Chen L, Su W, Chen H, Chen DQ, Wang M, Guo Y, Zhao YY. Proteomics for Biomarker Identification and Clinical Application in Kidney Disease. Adv Clin Chem 2018; 85:91-113. [PMID: 29655463 DOI: 10.1016/bs.acc.2018.02.005] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Treatment effectiveness for kidney disease is limited by lack of accuracy, sensitivity, specificity of diagnostic, prognostic, and therapeutic biomarkers. The gold standard test renal biopsy along with serum creatinine and proteinuria is often necessary to establish a diagnosis, particularly in glomerular disease. Proteomics has become a powerful tool for novel biomarker discovery in kidney disease. Novel proteomics offer earlier and more accurate diagnosis of renal pathology than possible with traditional biomarkers such as serum creatinine and urine protein. In addition, proteomic biomarkers could also be useful to choose the most suitable therapeutic targets. This review focuses on the current status of proteomic biomarkers from animal models (5/6 nephrectomy, unilateral ureteral obstruction, and diabetic nephropathy) and human studies (chronic kidney disease, glomerular diseases, transplantation, dialysis, acute and drug-induced kidney injury) to assess relevant findings and clinical usefulness. Current issues and problems related to the discovery, validation, and clinical application of proteomic biomarkers are discussed. We also describe several proteomic strategies highlighting technologic advancements, specimen selection, data processing and analysis. This review might provide help in future proteomic studies to improve the diagnosis and management of kidney disease.
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Affiliation(s)
- Lin Chen
- Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education, School of Life Science, Northwest University, Xi'an, China
| | - Wei Su
- Baoji Central Hospital, Baoji, China
| | - Hua Chen
- Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education, School of Life Science, Northwest University, Xi'an, China
| | - Dan-Qian Chen
- Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education, School of Life Science, Northwest University, Xi'an, China
| | - Ming Wang
- Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education, School of Life Science, Northwest University, Xi'an, China
| | - Yan Guo
- University of New Mexico, Comprehensive Cancer Center, Albuquerque, NM, United States
| | - Ying-Yong Zhao
- Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education, School of Life Science, Northwest University, Xi'an, China.
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45
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Krochmal M, Schanstra JP, Mischak H. Urinary peptidomics in kidney disease and drug research. Expert Opin Drug Discov 2017; 13:259-268. [DOI: 10.1080/17460441.2018.1418320] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Affiliation(s)
- Magdalena Krochmal
- Department of Biotechnology, Biomedical Research Foundation Academy of Athens, Athens, Greece
- Mosaiques Diagnostics GmbH, Hannover, Germany
| | - Joost P Schanstra
- Institut of Cardiovascular and Metabolic Disease, Institut National de la Santé et de la Recherche Médicale (INSERM), U1048, Toulouse, France
- Université Toulouse III Paul-Sabatier, Toulouse, France
| | - Harald Mischak
- Mosaiques Diagnostics GmbH, Hannover, Germany
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
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46
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Magalhães P, Pejchinovski M, Markoska K, Banasik M, Klinger M, Švec-Billá D, Rychlík I, Rroji M, Restivo A, Capasso G, Bob F, Schiller A, Ortiz A, Perez-Gomez MV, Cannata P, Sanchez-Niño MD, Naumovic R, Brkovic V, Polenakovic M, Mullen W, Vlahou A, Zürbig P, Pape L, Ferrario F, Denis C, Spasovski G, Mischak H, Schanstra JP. Association of kidney fibrosis with urinary peptides: a path towards non-invasive liquid biopsies? Sci Rep 2017; 7:16915. [PMID: 29208969 PMCID: PMC5717105 DOI: 10.1038/s41598-017-17083-w] [Citation(s) in RCA: 60] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2017] [Accepted: 11/20/2017] [Indexed: 12/16/2022] Open
Abstract
Chronic kidney disease (CKD) is a prevalent cause of morbidity and mortality worldwide. A hallmark of CKD progression is renal fibrosis characterized by excessive accumulation of extracellular matrix (ECM) proteins. In this study, we aimed to investigate the correlation of the urinary proteome classifier CKD273 and individual urinary peptides with the degree of fibrosis. In total, 42 kidney biopsies and urine samples were examined. The percentage of fibrosis per total tissue area was assessed in Masson trichrome stained kidney tissues. The urinary proteome was analysed by capillary electrophoresis coupled to mass spectrometry. CKD273 displayed a significant and positive correlation with the degree of fibrosis (Rho = 0.430, P = 0.0044), while the routinely used parameters (glomerular filtration rate, urine albumin-to-creatinine ratio and urine protein-to-creatinine ratio) did not (Rho = -0.222; -0.137; -0.070 and P = 0.16; 0.39; 0.66, respectively). We identified seven fibrosis-associated peptides displaying a significant and negative correlation with the degree of fibrosis. All peptides were collagen fragments, suggesting that these may be causally related to the observed accumulation of ECM in the kidneys. CKD273 and specific peptides are significantly associated with kidney fibrosis; such an association could not be detected by other biomarkers for CKD. These non-invasive fibrosis-related biomarkers can potentially be implemented in future trials.
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Affiliation(s)
- Pedro Magalhães
- Mosaiques Diagnostics GmbH, Hannover, Germany
- Department of Pediatric Nephrology, Hannover Medical School, Hannover, Germany
| | | | - Katerina Markoska
- Department of Nephrology, Medical Faculty, University of Skopje, Skopje, Macedonia
| | - Miroslaw Banasik
- Department of Nephrology and Transplantation Medicine, Wroclaw Medical University, Wroclaw, Poland
| | - Marian Klinger
- Department of Nephrology and Transplantation Medicine, Wroclaw Medical University, Wroclaw, Poland
| | - Dominika Švec-Billá
- 1st Department of Medicine, Third Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Ivan Rychlík
- 1st Department of Medicine, Third Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Merita Rroji
- Department of Nephrology, University Hospital Center "Mother Teresa", Tirana, Albania
| | - Arianna Restivo
- Department of Nephrology, University of Campania "Luigi Vanvitelli", Naples, Italy
| | | | - Flaviu Bob
- Department of Nephrology, 'Victor Babes' University of Medicine and Pharmacy, County Emergency Hospital, Timisoara, Romania
| | - Adalbert Schiller
- Department of Nephrology, 'Victor Babes' University of Medicine and Pharmacy, County Emergency Hospital, Timisoara, Romania
| | | | | | | | | | - Radomir Naumovic
- Clinic of Nephrology, Clinical Center of Serbia, Belgrade, Serbia
- School of Medicine, University of Belgrade, Belgrade, Serbia
| | - Voin Brkovic
- Clinic of Nephrology, Clinical Center of Serbia, Belgrade, Serbia
- School of Medicine, University of Belgrade, Belgrade, Serbia
| | | | - William Mullen
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | - Antonia Vlahou
- Biotechnology Division, Biomedical Research Foundation, Academy of Athens, Athens, Greece
| | | | - Lars Pape
- Department of Pediatric Nephrology, Hannover Medical School, Hannover, Germany
| | | | - Colette Denis
- Institut National de la Santé et de la Recherche Médicale (INSERM), Institute of Cardiovascular and Metabolic Disease, Toulouse, France
- Université Toulouse III Paul-Sabatier, Toulouse, France
| | - Goce Spasovski
- Department of Nephrology, Medical Faculty, University of Skopje, Skopje, Macedonia
| | - Harald Mischak
- Mosaiques Diagnostics GmbH, Hannover, Germany
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | - Joost P Schanstra
- Institut National de la Santé et de la Recherche Médicale (INSERM), Institute of Cardiovascular and Metabolic Disease, Toulouse, France.
- Université Toulouse III Paul-Sabatier, Toulouse, France.
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47
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Harpole M, Davis J, Espina V. Current state of the art for enhancing urine biomarker discovery. Expert Rev Proteomics 2017; 13:609-26. [PMID: 27232439 DOI: 10.1080/14789450.2016.1190651] [Citation(s) in RCA: 85] [Impact Index Per Article: 12.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
INTRODUCTION Urine is a highly desirable biospecimen for biomarker analysis because it can be collected recurrently by non-invasive techniques, in relatively large volumes. Urine contains cellular elements, biochemicals, and proteins derived from glomerular filtration of plasma, renal tubule excretion, and urogenital tract secretions that reflect, at a given time point, an individual's metabolic and pathophysiologic state. AREAS COVERED High-resolution mass spectrometry, coupled with state of the art fractionation systems are revealing the plethora of diagnostic/prognostic proteomic information existing within urinary exosomes, glycoproteins, and proteins. Affinity capture pre-processing techniques such as combinatorial peptide ligand libraries and biomarker harvesting hydrogel nanoparticles are enabling measurement/identification of previously undetectable urinary proteins. Expert commentary: Future challenges in the urinary proteomics field include a) defining either single or multiple, universally applicable data normalization methods for comparing results within and between individual patients/data sets, and b) defining expected urinary protein levels in healthy individuals.
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Affiliation(s)
- Michael Harpole
- a Center for Applied Proteomics and Molecular Medicine , George Mason University , Manassas , VA , USA
| | - Justin Davis
- b Department of Chemistry/Biochemistry , George Mason University , Manassas , VA , USA
| | - Virginia Espina
- a Center for Applied Proteomics and Molecular Medicine , George Mason University , Manassas , VA , USA
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48
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Markoska K, Pejchinovski M, Pontillo C, Zürbig P, Jacobs L, Smith A, Masin-Spasovska J, Stojceva-Taneva O, Polenakovic M, Magni F, Mischak H, Spasovski G. Urinary peptide biomarker panel associated with an improvement in estimated glomerular filtration rate in chronic kidney disease patients. Nephrol Dial Transplant 2017; 33:751-759. [DOI: 10.1093/ndt/gfx263] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2017] [Accepted: 07/09/2017] [Indexed: 01/21/2023] Open
Affiliation(s)
| | | | - Claudia Pontillo
- Department of Clinical Proteomics, Mosaiques Diagnostics, Hanover, Germany
| | - Petra Zürbig
- Department of Clinical Proteomics, Mosaiques Diagnostics, Hanover, Germany
| | - Lotte Jacobs
- Department of Cardiovascular Sciences, University of Leuven, Leuven, Belgium
| | - Andrew Smith
- Unit of Proteomics, Department of Medicine and Surgery, University of Milano-Bicocca, Monza, Italy
| | | | | | | | - Fulvio Magni
- Unit of Proteomics, Department of Medicine and Surgery, University of Milano-Bicocca, Monza, Italy
| | - Harald Mischak
- Department of Clinical Proteomics, Mosaiques Diagnostics, Hanover, Germany
| | - Goce Spasovski
- Department of Nephrology, Medical Faculty, University of Skopje, Skopje, Macedonia
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49
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Critselis E, Vlahou A, Stel VS, Morton RL. Cost-effectiveness of screening type 2 diabetes patients for chronic kidney disease progression with the CKD273 urinary peptide classifier as compared to urinary albumin excretion. Nephrol Dial Transplant 2017; 33:441-449. [DOI: 10.1093/ndt/gfx068] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2016] [Accepted: 03/16/2017] [Indexed: 12/23/2022] Open
Affiliation(s)
- Elena Critselis
- Proteomics Laboratory, Center for Basic Research, Biomedical Research Foundation of the Academy of Athens, Athens, Greece
| | - Antonia Vlahou
- Proteomics Laboratory, Center for Basic Research, Biomedical Research Foundation of the Academy of Athens, Athens, Greece
| | - Vianda S Stel
- ERA-EDTA Registry, Department of Medical Informatics, Academic Medical Center, University of Amsterdam, Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Rachael L Morton
- National Health and Medical Research Council Clinical Trials Centre, University of Sydney, Sydney, Australia
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50
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Pontillo C, Mischak H. Urinary peptide-based classifier CKD273: towards clinical application in chronic kidney disease. Clin Kidney J 2017; 10:192-201. [PMID: 28694965 PMCID: PMC5499684 DOI: 10.1093/ckj/sfx002] [Citation(s) in RCA: 60] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2016] [Indexed: 12/22/2022] Open
Abstract
Capillary electrophoresis coupled with mass spectrometry (CE-MS) has been used as a platform for discovery and validation of urinary peptides associated with chronic kidney disease (CKD). CKD affects ∼ 10% of the population, with high associated costs for treatments. A urinary proteome-based classifier (CKD273) has been discovered and validated in cross-sectional and longitudinal studies to assess and predict the progression of CKD. It has been implemented in studies employing cohorts of > 1000 patients. CKD273 is commercially available as an in vitro diagnostic test for early detection of CKD and is currently being used for patient stratification in a multicentre randomized clinical trial (PRIORITY). The validity of the CKD273 classifier has recently been evaluated applying the Oxford Evidence-Based Medicine and Southampton Oxford Retrieval Team guidelines and a letter of support for CKD273 was issued by the US Food and Drug Administration. In this article we review the current evidence published on CKD273 and the challenges associated with implementation. Definition of a possible surrogate early endpoint combined with CKD273 as a biomarker for patient stratification currently appears as the most promising strategy to enable the development of effective drugs to be used at an early time point when intervention can still be effective.
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Affiliation(s)
| | - Harald Mischak
- Mosaiques Diagnostics, Hannover, Germany.,Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
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