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Zoccali C, Mallamaci F, Lightstone L, Jha V, Pollock C, Tuttle K, Kotanko P, Wiecek A, Anders HJ, Remuzzi G, Kalantar-Zadeh K, Levin A, Vanholder R. A new era in the science and care of kidney diseases. Nat Rev Nephrol 2024; 20:460-472. [PMID: 38575770 DOI: 10.1038/s41581-024-00828-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/06/2024] [Indexed: 04/06/2024]
Abstract
Notable progress in basic, translational and clinical nephrology research has been made over the past five decades. Nonetheless, many challenges remain, including obstacles to the early detection of kidney disease, disparities in access to care and variability in responses to existing and emerging therapies. Innovations in drug development, research technologies, tissue engineering and regenerative medicine have the potential to improve patient outcomes. Exciting prospects include the availability of new drugs to slow or halt the progression of chronic kidney disease, the development of bioartificial kidneys that mimic healthy kidney functions, and tissue engineering techniques that could enable transplantable kidneys to be created from the cells of the recipient, removing the risk of rejection. Cell and gene therapies have the potential to be applied for kidney tissue regeneration and repair. In addition, about 30% of kidney disease cases are monogenic and could potentially be treated using these genetic medicine approaches. Systemic diseases that involve the kidney, such as diabetes mellitus and hypertension, might also be amenable to these treatments. Continued investment, communication, collaboration and translation of innovations are crucial to realize their full potential. In addition, increasing sophistication in exploring large datasets, implementation science, and qualitative methodologies will improve the ability to deliver transformational kidney health strategies.
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Affiliation(s)
- Carmine Zoccali
- Kidney Research Institute, New York City, NY, USA.
- Institute of Molecular Biology and Genetics (Biogem), Ariano Irpino, Italy.
- Associazione Ipertensione Nefrologia Trapianto Kidney (IPNET), c/o Nefrologia, Grande Ospedale Metropolitano, Reggio Calabria, Italy.
| | - Francesca Mallamaci
- Nephrology, Dialysis and Transplantation Unit Azienda Ospedaliera "Bianchi-Melacrino-Morelli", Reggio Calabria, Italy
- CNR-IFC, Institute of Clinical Physiology, Research Unit of Clinical Epidemiology and Physiopathology of Kidney Diseases and Hypertension of Reggio Calabria, Reggio Calabria, Italy
| | - Liz Lightstone
- Department of Immunology and Inflammation, Imperial College London, London, UK
- Imperial College Healthcare NHS Trust, Hammersmith Hospital, London, UK
| | - Vivek Jha
- George Institute for Global Health, UNSW, New Delhi, India
- School of Public Health, Imperial College, London, UK
- Prasanna School of Public Health, Manipal Academy of Medical Education, Manipal, India
| | - Carol Pollock
- Kolling Institute, Royal North Shore Hospital University of Sydney, Sydney, NSW, Australia
| | - Katherine Tuttle
- Providence Medical Research Center, Providence Inland Northwest, Spokane, Washington, USA
- Department of Medicine, University of Washington, Seattle, Spokane, Washington, USA
- Kidney Research Institute, Institute of Translational Health Sciences, University of Washington, Seattle, Washington, USA
| | - Peter Kotanko
- Kidney Research Institute, New York, NY, USA
- Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Andrzej Wiecek
- Department of Nephrology, Transplantation and Internal Medicine, Medical University of Silesia, 40-027, Katowice, Poland
| | - Hans Joachim Anders
- Division of Nephrology, Department of Medicine IV, Hospital of the Ludwig Maximilians University Munich, Munich, Germany
| | - Giuseppe Remuzzi
- Istituto di Ricerche Farmacologiche Mario Negri IRCSS, Bergamo, Italy
| | - Kamyar Kalantar-Zadeh
- Harold Simmons Center for Kidney Disease Research and Epidemiology, California, USA
- Division of Nephrology and Hypertension, University of California Irvine, School of Medicine, Orange, Irvine, USA
- Veterans Affairs Healthcare System, Division of Nephrology, Long Beach, California, USA
| | - Adeera Levin
- University of British Columbia, Vancouver General Hospital, Division of Nephrology, Vancouver, British Columbia, Canada
- British Columbia, Provincial Kidney Agency, Vancouver, British Columbia, Canada
| | - Raymond Vanholder
- European Kidney Health Alliance, Brussels, Belgium
- Nephrology Section, Department of Internal Medicine and Paediatrics, University Hospital Ghent, Ghent, Belgium
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Roccatello D, Lan HY, Sciascia S, Sethi S, Fornoni A, Glassock R. From inflammation to renal fibrosis: A one-way road in autoimmunity? Autoimmun Rev 2024; 23:103466. [PMID: 37848157 DOI: 10.1016/j.autrev.2023.103466] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Accepted: 10/13/2023] [Indexed: 10/19/2023]
Abstract
Renal fibrosis is now recognized as a main determinant of renal pathology to include chronic kidney disease. Deposition of pathological matrix in the walls of glomerular capillaries, the interstitial space, and around arterioles predicts and contributes to the functional demise of the nephron and its surrounding vasculature. The recent identification of the major cell populations of fibroblast precursors in the kidney interstitium such as pericytes and tissue-resident mesenchymal stem cells, or bone-marrow-derived macrophages, and in the glomerulus such as podocytes, parietal epithelial and mesangial cells, has enabled the study of the fibrogenic process thought the lens of involved immunological pathways. Besides, a growing body of evidence is supporting the role of the lymphatic system in modulating the immunological response potentially leading to inflammation and ultimately renal damage. These notions have moved our understanding of renal fibrosis to be recognized as a clinical entity and new main player in autoimmunity, impacting directly the management of patients.
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Affiliation(s)
- Dario Roccatello
- University Center of Excellence on Nephrologic, Rheumatologic and Rare Diseases (ERK-net, ERN-Reconnect and RITA-ERN Member) with Nephrology and Dialysis Unit and Center of Immuno-Rheumatology and Rare Diseases (CMID), Coordinating Center of the Interregional Network for Rare Diseases of Piedmont and Aosta Valley (North-West Italy), San Giovanni Bosco Hub Hospital, ASL Città di Torino and Department of Clinical and Biological Sciences of the University of Turin, Turin, Italy.
| | - Hui-Yao Lan
- Department of Medicine & Therapeutics, and Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, China; Guangdong-Hong Kong Joint Laboratory on Immunological and Genetic Kidney Diseases,Guangdong Academy of Medical Sciences, Guangdong Provincial People's Hospital, Guangzhou, China
| | - Savino Sciascia
- University Center of Excellence on Nephrologic, Rheumatologic and Rare Diseases (ERK-net, ERN-Reconnect and RITA-ERN Member) with Nephrology and Dialysis Unit and Center of Immuno-Rheumatology and Rare Diseases (CMID), Coordinating Center of the Interregional Network for Rare Diseases of Piedmont and Aosta Valley (North-West Italy), San Giovanni Bosco Hub Hospital, ASL Città di Torino and Department of Clinical and Biological Sciences of the University of Turin, Turin, Italy
| | - Sanjeev Sethi
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - Alessia Fornoni
- Peggy and Harold Katz Family Drug Discovery Center, Katz Family Division of Nephrology and Hypertension, Department of Medicine, Miller School of Medicine, University of Miami, Miami, USA
| | - Richard Glassock
- Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
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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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Govender MA, Stoychev SH, Brandenburg JT, Ramsay M, Fabian J, Govender IS. Proteomic insights into the pathophysiology of hypertension-associated albuminuria: Pilot study in a South African cohort. Clin Proteomics 2024; 21:15. [PMID: 38402394 PMCID: PMC10893729 DOI: 10.1186/s12014-024-09458-9] [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: 10/30/2023] [Accepted: 02/06/2024] [Indexed: 02/26/2024] Open
Abstract
BACKGROUND Hypertension is an important public health priority with a high prevalence in Africa. It is also an independent risk factor for kidney outcomes. We aimed to identify potential proteins and pathways involved in hypertension-associated albuminuria by assessing urinary proteomic profiles in black South African participants with combined hypertension and albuminuria compared to those who have neither condition. METHODS The study included 24 South African cases with both hypertension and albuminuria and 49 control participants who had neither condition. Protein was extracted from urine samples and analysed using ultra-high-performance liquid chromatography coupled with mass spectrometry. Data were generated using data-independent acquisition (DIA) and processed using Spectronaut™ 15. Statistical and functional data annotation were performed on Perseus and Cytoscape to identify and annotate differentially abundant proteins. Machine learning was applied to the dataset using the OmicLearn platform. RESULTS Overall, a mean of 1,225 and 915 proteins were quantified in the control and case groups, respectively. Three hundred and thirty-two differentially abundant proteins were constructed into a network. Pathways associated with these differentially abundant proteins included the immune system (q-value [false discovery rate] = 1.4 × 10- 45), innate immune system (q = 1.1 × 10- 32), extracellular matrix (ECM) organisation (q = 0.03) and activation of matrix metalloproteinases (q = 0.04). Proteins with high disease scores (76-100% confidence) for both hypertension and chronic kidney disease included angiotensinogen (AGT), albumin (ALB), apolipoprotein L1 (APOL1), and uromodulin (UMOD). A machine learning approach was able to identify a set of 20 proteins, differentiating between cases and controls. CONCLUSIONS The urinary proteomic data combined with the machine learning approach was able to classify disease status and identify proteins and pathways associated with hypertension-associated albuminuria.
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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.
| | - Stoyan H Stoychev
- Council for Scientific and Industrial Research, NextGen Health, Pretoria, South Africa
- ReSyn Biosciences, Edenvale, South Africa
| | - Jean-Tristan Brandenburg
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- Strengthening Oncology Services, 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
| | - June Fabian
- Wits Donald Gordon Medical Centre, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- Medical Research Council/Wits University Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Ireshyn S Govender
- Council for Scientific and Industrial Research, NextGen Health, Pretoria, South Africa.
- ReSyn Biosciences, Edenvale, South Africa.
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Peters B, Beige J, Siwy J, Rudnicki M, Wendt R, Ortiz A, Sanz AB, Mischak H, Reich HN, Nasic S, Mahmood D, Persson A, Fernström A, Weiner M, Stegmayr B. Dynamics of urine proteomics biomarker and disease progression in patients with IgA nephropathy. Nephrol Dial Transplant 2023; 38:2826-2834. [PMID: 37349951 PMCID: PMC10689155 DOI: 10.1093/ndt/gfad125] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Indexed: 06/24/2023] Open
Abstract
BACKGROUND Immunoglobulin A nephropathy (IgAN) frequently leads to kidney failure. The urinary proteomics-based classifier IgAN237 may predict disease progression at the time of kidney biopsy. We studied whether IgAN237 also predicts progression later in the course of IgAN. METHODS Urine from patients with biopsy-proven IgAN was analyzed using capillary electrophoresis-mass spectrometry at baseline (IgAN237-1, n = 103) and at follow-up (IgAN237-2, n = 89). Patients were categorized as "non-progressors" (IgAN237 ≤0.38) and "progressors" (IgAN237 >0.38). Estimated glomerular filtration rate (eGFR) and urinary albumin-creatinine ratio slopes were calculated. RESULTS Median age at biopsy was 44 years, interval between biopsy and IgAN237-1 was 65 months and interval between IgAN237-1 and IgAN237-2 was 258 days (interquartile range 71-531). IgAN237-1 and IgAN237-2 values did not differ significantly and were correlated (rho = 0.44, P < .001). Twenty-eight percent and 26% of patients were progressors based on IgAN237-1 and IgAN237-2, respectively. IgAN237 inversely correlated with chronic eGFR slopes (rho = -0.278, P = .02 for score-1; rho = -0.409, P = .002 for score-2) and with ±180 days eGFR slopes (rho = -0.31, P = .009 and rho = -0.439, P = .001, respectively). The ±180 days eGFR slopes were worse for progressors than for non-progressors (median -5.98 versus -1.22 mL/min/1.73 m2 per year for IgAN237-1, P < .001; -3.02 vs 1.08 mL/min/1.73 m2 per year for IgAN237-2, P = .0047). In multiple regression analysis baseline progressor/non-progressor according to IgAN237 was an independent predictor of eGFR180days-slope (P = .001). CONCLUSION The urinary IgAN237 classifier represents a risk stratification tool in IgAN also later in the course of the dynamic disease. It may guide patient management in an individualized manner.
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Affiliation(s)
- Björn Peters
- Department of Molecular and Clinical Medicine, Institute of Medicine, the Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden
- Department of Nephrology, Skaraborg Hospital, Skövde, Sweden
| | - Joachim Beige
- Kuratorium for Dialysis and Transplantation, Neu Isenburg/Leipzig, Germany
- Division of Nephrology, Rheumatology and Endocrinology, Martin-Luther University Halle-Wittenberg, Halle/Saale., Germany
| | | | - Michael Rudnicki
- Department of Internal Medicine IV – Nephrology and Hypertension, Medical University Innsbruck, Innsbruck, Austria
| | - Ralph Wendt
- Division of Nephrology and KfH Renal Unit, Hospital St Georg, Leipzig, Germany
| | - Alberto Ortiz
- Instituto de Investigación Sanitaria Fundación Jiménez Díaz (IIS-FJD UAM), Madrid, Spain
| | - Ana Belen Sanz
- Instituto de Investigación Sanitaria Fundación Jiménez Díaz (IIS-FJD UAM), Madrid, Spain
| | | | - Heather N Reich
- Department of Medicine, University of Toronto and Division of Nephrology, University Health Network, Toronto, Ontario, Canada
- Gabor Zellerman Chair in Nephrology Research, University of Toronto, Toronto, Ontario, Canada
| | - Salmir Nasic
- Department of Molecular and Clinical Medicine, Institute of Medicine, the Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden
- Research and Development Centre at Skaraborg Hospital, Skövde, Sweden
| | - Dana Mahmood
- Department of Public Health and Clinical Medicine, Unit Östersund, Umeå University, Umea, Sweden
| | - Anders Persson
- Department of Public Health and Clinical Medicine, Unit Sundsvall, Umeå University, Umea, Sweden
| | - Anders Fernström
- Department of Nephrology and Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden
| | - Maria Weiner
- Department of Nephrology and Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden
| | - Bernd Stegmayr
- Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
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Li L, Wu J, Lyon CJ, Jiang L, Hu TY. Clinical Peptidomics: Advances in Instrumentation, Analyses, and Applications. BME FRONTIERS 2023; 4:0019. [PMID: 37849662 PMCID: PMC10521655 DOI: 10.34133/bmef.0019] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2023] [Accepted: 04/19/2023] [Indexed: 10/19/2023] Open
Abstract
Extensive effort has been devoted to the discovery, development, and validation of biomarkers for early disease diagnosis and prognosis as well as rapid evaluation of the response to therapeutic interventions. Genomic and transcriptomic profiling are well-established means to identify disease-associated biomarkers. However, analysis of disease-associated peptidomes can also identify novel peptide biomarkers or signatures that provide sensitive and specific diagnostic and prognostic information for specific malignant, chronic, and infectious diseases. Growing evidence also suggests that peptidomic changes in liquid biopsies may more effectively detect changes in disease pathophysiology than other molecular methods. Knowledge gained from peptide-based diagnostic, therapeutic, and imaging approaches has led to promising new theranostic applications that can increase their bioavailability in target tissues at reduced doses to decrease side effects and improve treatment responses. However, despite major advances, multiple factors can still affect the utility of peptidomic data. This review summarizes several remaining challenges that affect peptide biomarker discovery and their use as diagnostics, with a focus on technological advances that can improve the detection, identification, and monitoring of peptide biomarkers for personalized medicine.
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Affiliation(s)
- Lin Li
- Center for Cellular and Molecular Diagnostics, Department of Biochemistry and Molecular Biology, School of Medicine, Tulane University, New Orleans, LA, USA
- Department of Laboratory Medicine and Sichuan Provincial Key Laboratory for Human Disease Gene Study, Sichuan Academy of Medical Sciences and Sichuan Provincial People’s Hospital, Chengdu, China
| | - Jing Wu
- Department of Clinical Laboratory, Third Central Hospital of Tianjin, Tianjin Institute of Hepatobiliary Disease, Tianjin Key Laboratory of Artificial Cell, Artificial Cell Engineering Technology Research Center of Public Health Ministry, Tianjin, China
| | - Christopher J. Lyon
- Center for Cellular and Molecular Diagnostics, Department of Biochemistry and Molecular Biology, School of Medicine, Tulane University, New Orleans, LA, USA
| | - Li Jiang
- Department of Laboratory Medicine and Sichuan Provincial Key Laboratory for Human Disease Gene Study, Sichuan Academy of Medical Sciences and Sichuan Provincial People’s Hospital, Chengdu, China
| | - Tony Y. Hu
- Center for Cellular and Molecular Diagnostics, Department of Biochemistry and Molecular Biology, School of Medicine, Tulane University, New Orleans, LA, USA
- Department of Biomedical Engineering, School of Science and Engineering, Tulane University, New Orleans, LA, USA
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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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Ruilope LM, Ortiz A, Lucia A, Miranda B, Alvarez-Llamas G, Barderas MG, Volpe M, Ruiz-Hurtado G, Pitt B. Prevention of cardiorenal damage: importance of albuminuria. Eur Heart J 2022; 44:1112-1123. [PMID: 36477861 DOI: 10.1093/eurheartj/ehac683] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Revised: 10/20/2022] [Accepted: 11/09/2022] [Indexed: 12/12/2022] Open
Abstract
Abstract
Chronic kidney disease (CKD) is projected to become a leading global cause of death by 2040, and its early detection is critical for effective and timely management. The current definition of CKD identifies only advanced stages, when kidney injury has already destroyed >50% of functioning kidney mass as reflected by an estimated glomerular filtration rate <60 mL/min/1.73 m2 or a urinary albumin/creatinine ratio >six-fold higher than physiological levels (i.e. > 30 mg/g). An elevated urinary albumin-excretion rate is a known early predictor of future cardiovascular events. There is thus a ‘blind spot’ in the detection of CKD, when kidney injury is present but is undetectable by current diagnostic criteria, and no intervention is made before renal and cardiovascular damage occurs. The present review discusses the CKD ‘blind spot’ concept and how it may facilitate a holistic approach to CKD and cardiovascular disease prevention and implement the call for albuminuria screening implicit in current guidelines. Cardiorenal risk associated with albuminuria in the high-normal range, novel genetic and biochemical markers of elevated cardiorenal risk, and the role of heart and kidney protective drugs evaluated in recent clinical trials are also discussed. As albuminuria is a major risk factor for cardiovascular and renal disease, starting from levels not yet considered in the definition of CKD, the implementation of opportunistic or systematic albuminuria screening and therapy, possibly complemented with novel early biomarkers, has the potential to improve cardiorenal outcomes and mitigate the dismal 2040 projections for CKD and related cardiovascular burden.
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Affiliation(s)
- Luis M Ruilope
- Cardiorenal Translational Laboratory, Institute of Research Imas12, Hospital Universitario , 12 de Octubre, Avenida de Córdoba s/n , Spain
- CIBER-CV, Hospital Universitario , Av. de Córdoba s/n, 28041, Madrid , Spain
- Faculty of Sport Sciences, Universidad Europea de Madrid , Tajo, s/n, 28670 Villaviciosa de Odón, Madrid , Spain
| | - Alberto Ortiz
- IIS-Fundación Jiménez Díaz, Universidad Autónoma de Madrid , Av. de los Reyes Católicos, 2, 28040 Madrid , Spain
- RICORS2040, Hospital Universitario Fundación Jiménez Díaz , Madrid , Spain
| | - Alejandro Lucia
- Faculty of Sport Sciences, Universidad Europea de Madrid , Tajo, s/n, 28670 Villaviciosa de Odón, Madrid , Spain
| | - Blanca Miranda
- Fundación Renal Íñigo Álvarez de Toledo , José Abascal, 42, 28003 Madrid , Spain
| | - Gloria Alvarez-Llamas
- IIS-Fundación Jiménez Díaz, Universidad Autónoma de Madrid , Av. de los Reyes Católicos, 2, 28040 Madrid , Spain
- RICORS2040, Hospital Universitario Fundación Jiménez Díaz , Madrid , Spain
| | - Maria G Barderas
- Department of Vascular Physiopathology, Hospital Nacional de Parapléjicos (HNP), SESCAM , FINCA DE, Carr. de la Peraleda, S/N, 45004 Toledo , Spain
| | - Massimo Volpe
- Cardiology, Department of Clinical and Molecular Medicine, Sapienza University of Rome and IRCCS San Raffaele Rome , Sant'Andrea Hospital, Rome , Italy
| | - Gema Ruiz-Hurtado
- Cardiorenal Translational Laboratory, Institute of Research Imas12, Hospital Universitario , 12 de Octubre, Avenida de Córdoba s/n , Spain
- CIBER-CV, Hospital Universitario , Av. de Córdoba s/n, 28041, Madrid , Spain
| | - Bertram Pitt
- Division of Cardiology, University of Michigan School of Medicine , Ann Arbor, MI , USA
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Curovic VR, Eickhoff MK, Rönkkö T, Frimodt-Møller M, Hansen TW, Mischak H, Rossing P, Ahluwalia TS, Persson F. Dapagliflozin Improves the Urinary Proteomic Kidney-Risk Classifier CKD273 in Type 2 Diabetes with Albuminuria: A Randomized Clinical Trial. Diabetes Care 2022; 45:2662-2668. [PMID: 35998283 DOI: 10.2337/dc22-1157] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/13/2022] [Accepted: 07/19/2022] [Indexed: 02/03/2023]
Abstract
OBJECTIVE To evaluate the effect of the sodium-glucose cotransporter 2 inhibitor dapagliflozin on the kidney-risk urinary proteomic classifier (CKD273) in persons with type 2 diabetes (T2D) and albuminuria. RESEARCH DESIGN AND METHODS In a double-blind, randomized, controlled, crossover trial, we assigned participants with T2D and urinary albumin to creatinine ratio (UACR) ≥30 mg/g to receive dapagliflozin or matching placebo added to guideline-recommended treatment (ClinicalTrial.gov identifier NCT02914691). Treatment periods lasted 12 weeks, when crossover to the opposing treatment occurred. The primary outcome was change in CKD273 score. Secondary outcomes included regression from high-risk to low-risk CKD273 pattern using the prespecified cutoff score of 0.154. The primary outcome was assessed using paired t test between end-to-end CKD273 scores after dapagliflozin and placebo treatment. The McNemar test was used to assess regression in risk category. RESULTS A total of 40 participants were randomized and 32 completed the trial with intact proteomic measurements. Twenty-eight (88%) were men, the baseline mean (SD) age was 63.0 (8.3) years, mean (SD) diabetes duration was 15.4 (4.5) years, mean HbA1c was 73 (14) mmol/mol (8.8% [1.3%]), and median (interquartile range) UACR was 154 (94, 329) mg/g. Dapagliflozin significantly lowered CKD273 score compared with placebo (-0.221; 95% CI -0.356, -0.087; P = 0.002). Fourteen participants exhibited a high-risk pattern after dapagliflozin treatment compared with 24 after participants placebo (P = 0.021). CONCLUSIONS Dapagliflozin added to renin-angiotensin system inhibition reduced the urinary proteomic classifier CKD273 in persons with T2D and albuminuria, paving the way for the further investigation of CKD273 as a modifiable kidney risk factor.
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Affiliation(s)
| | | | - Teemu Rönkkö
- Steno Diabetes Center Copenhagen, Herlev, Denmark
| | | | | | | | - Peter Rossing
- Steno Diabetes Center Copenhagen, Herlev, Denmark.,Institute of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
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10
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Copur S, Tanriover C, Yavuz F, Soler MJ, Ortiz A, Covic A, Kanbay M. Novel strategies in nephrology: what to expect from the future? Clin Kidney J 2022; 16:230-244. [PMID: 36755838 PMCID: PMC9900595 DOI: 10.1093/ckj/sfac212] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2022] [Indexed: 11/14/2022] Open
Abstract
Chronic kidney disease (CKD) will become the fifth global case of death by 2040. Its largest impact is on premature mortality but the number of persons with kidney failure requiring renal replacement therapy (RRT) is also increasing dramatically. Current RRT is suboptimal due to the shortage of kidney donors and dismal outcomes associated with both hemodialysis and peritoneal dialysis. Kidney care needs a revolution. In this review, we provide an update on emerging knowledge and technologies that will allow an earlier diagnosis of CKD, addressing the current so-called blind spot (e.g. imaging and biomarkers), and improve renal replacement therapies (wearable artificial kidneys, xenotransplantation, stem cell-derived therapies, bioengineered and bio-artificial kidneys).
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Affiliation(s)
- Sidar Copur
- Department of Medicine, Koc University School of Medicine, Istanbul, Turkey
| | - Cem Tanriover
- Department of Medicine, Koc University School of Medicine, Istanbul, Turkey
| | - Furkan Yavuz
- Department of Medicine, Koc University School of Medicine, Istanbul, Turkey
| | - Maria J Soler
- Department of Nephrology, Vall d’Hebron University Hospital, Universitat Autònoma de Barcelona, Spain,Nephrology and Kidney Transplant Research Group, Vall d'Hebron Research Institute (VHIR), Barcelona, Spain
| | - Alberto Ortiz
- Department of Medicine, Universidad Autonoma de Madrid and IIS-Fundacion Jimenez Diaz, Madrid, Spain
| | - Adrian Covic
- Nephrology Clinic, Dialysis and Renal Transplant Center, ‘C.I. PARHON’ University Hospital, and ‘Grigore T. Popa’ University of Medicine, Iasi, Romania
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11
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Mizdrak M, Kumrić M, Kurir TT, Božić J. Emerging Biomarkers for Early Detection of Chronic Kidney Disease. J Pers Med 2022; 12:jpm12040548. [PMID: 35455664 PMCID: PMC9025702 DOI: 10.3390/jpm12040548] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2022] [Revised: 03/22/2022] [Accepted: 03/28/2022] [Indexed: 12/14/2022] Open
Abstract
Chronic kidney disease (CKD) is a major and serious global health problem that leads to kidney damage as well as multiple systemic diseases. Early diagnosis and treatment are two major measures to prevent further deterioration of kidney function and to delay adverse outcomes. However, the paucity of early, predictive and noninvasive biomarkers has undermined our ability to promptly detect and treat this common clinical condition which affects more than 10% of the population worldwide. Despite all limitations, kidney function is still measured by serum creatinine, cystatin C, and albuminuria, as well as estimating glomerular filtration rate using different equations. This review aims to provide comprehensive insight into diagnostic methods available for early detection of CKD. In the review, we discuss the following topics: (i) markers of glomerular injury; (ii) markers of tubulointerstitial injury; (iii) the role of omics; (iv) the role of microbiota; (v) and finally, the role of microRNA in the early detection of CKD. Despite all novel findings, none of these biomarkers have met the criteria of an ideal early marker. Since the central role in CKD progression is the proximal tubule (PT), most data from the literature have analyzed biomarkers of PT injury, such as KIM-1 (kidney injury molecule-1), NGAL (neutrophil gelatinase-associated lipocalin), and L-FABP (liver fatty acid-binding protein).
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Affiliation(s)
- Maja Mizdrak
- Department of Nephrology and Hemodialysis, University Hospital of Split, 21000 Split, Croatia;
- Department of Pathophysiology, University of Split School of Medicine, 21000 Split, Croatia; (M.K.); (T.T.K.)
| | - Marko Kumrić
- Department of Pathophysiology, University of Split School of Medicine, 21000 Split, Croatia; (M.K.); (T.T.K.)
| | - Tina Tičinović Kurir
- Department of Pathophysiology, University of Split School of Medicine, 21000 Split, Croatia; (M.K.); (T.T.K.)
- Department of Endocrinology, Diabetes and Metabolic Disorders, University Hospital of Split, 21000 Split, Croatia
| | - Joško Božić
- Department of Pathophysiology, University of Split School of Medicine, 21000 Split, Croatia; (M.K.); (T.T.K.)
- Correspondence:
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12
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Abstract
The year 2021 was the last full year of Alberto Ortiz’s editorship at Clinical Kidney Journal (CKJ). On May 2022, Maria José Soler will start her term as the Editor-in-Chief. Over these years, CKJ obtained its first journal impact factor and has consolidated its position among the top journals in the field, consistently ranking among the top 25% (first quartile) journals in Urology and Nephrology. The 2020 journal impact factor rose to 4.45, becoming the top open access journal in Nephrology and the ninth ranked Nephrology journal overall. We now review the recent history of the journal and the most highly cited topics which include the epidemiology of kidney disease, chronic kidney disease topics, such as the assessment and treatment of chronic kidney disease, onconephrology, cardionephrology, glomerular disease, transplantation and coronavirus disease 2019 (COVID-19).
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13
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Reproducibility Evaluation of Urinary Peptide Detection Using CE-MS. Molecules 2021; 26:molecules26237260. [PMID: 34885840 PMCID: PMC8658976 DOI: 10.3390/molecules26237260] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2021] [Revised: 11/19/2021] [Accepted: 11/28/2021] [Indexed: 11/29/2022] Open
Abstract
In recent years, capillary electrophoresis coupled to mass spectrometry (CE-MS) has been increasingly applied in clinical research especially in the context of chronic and age-associated diseases, such as chronic kidney disease, heart failure and cancer. Biomarkers identified using this technique are already used for diagnosis, prognosis and monitoring of these complex diseases, as well as patient stratification in clinical trials. CE-MS allows for a comprehensive assessment of small molecular weight proteins and peptides (<20 kDa) through the combination of the high resolution and reproducibility of CE and the distinct sensitivity of MS, in a high-throughput system. In this study we assessed CE-MS analytical performance with regards to its inter- and intra-day reproducibility, variability and efficiency in peptide detection, along with a characterization of the urinary peptidome content. To this end, CE-MS performance was evaluated based on 72 measurements of a standard urine sample (60 for inter- and 12 for intra-day assessment) analyzed during the second quarter of 2021. Analysis was performed per run, per peptide, as well as at the level of biomarker panels. The obtained datasets showed high correlation between the different runs, low variation of the ten highest average individual log2 signal intensities (coefficient of variation, CV < 10%) and very low variation of biomarker panels applied (CV close to 1%). The findings of the study support the analytical performance of CE-MS, underlining its value for clinical application.
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14
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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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15
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Liu S, Gui Y, Wang MS, Zhang L, Xu T, Pan Y, Zhang K, Yu Y, Xiao L, Qiao Y, Bonin C, Hargis G, Huan T, Yu Y, Tao J, Zhang R, Kreutzer DL, Zhou Y, Tian XJ, Wang Y, Fu H, An X, Liu S, Zhou D. Serum integrative omics reveals the landscape of human diabetic kidney disease. Mol Metab 2021; 54:101367. [PMID: 34737094 PMCID: PMC8609166 DOI: 10.1016/j.molmet.2021.101367] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/03/2021] [Revised: 10/16/2021] [Accepted: 10/26/2021] [Indexed: 01/02/2023] Open
Abstract
Objective Diabetic kidney disease (DKD) is the most common microvascular complication of type 2 diabetes mellitus (2-DM). Currently, urine and kidney biopsy specimens are the major clinical resources for DKD diagnosis. Our study proposes to evaluate the diagnostic value of blood in monitoring the onset of DKD and distinguishing its status in the clinic. Methods This study recruited 1,513 participants including healthy adults and patients diagnosed with 2-DM, early-stage DKD (DKD-E), and advanced-stage DKD (DKD-A) from 4 independent medical centers. One discovery and four testing cohorts were established. Sera were collected and subjected to training proteomics and large-scale metabolomics. Results Deep profiling of serum proteomes and metabolomes revealed several insights. First, the training proteomics revealed that the combination of α2-macroglobulin, cathepsin D, and CD324 could serve as a surrogate protein biomarker for monitoring DKD progression. Second, metabolomics demonstrated that galactose metabolism and glycerolipid metabolism are the major disturbed metabolic pathways in DKD, and serum metabolite glycerol-3-galactoside could be used as an independent marker to predict DKD. Third, integrating proteomics and metabolomics increased the diagnostic and predictive stability and accuracy for distinguishing DKD status. Conclusions Serum integrative omics provide stable and accurate biomarkers for early warning and diagnosis of DKD. Our study provides a rich and open-access data resource for optimizing DKD management. Serum proteomics and metabolomics are novel, noninvasive approaches to detect DKD. Integrated serum omics enhances the diagnostic stability and accuracy of DKD diagnoses. Galactose/glycerolipid metabolism is the major disturbed metabolic pathway in DKD. Serum metabolite glycerol-3-galactoside is an independent predictive marker of DKD.
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Affiliation(s)
- Shijia Liu
- Affiliated Hosptial of Nanjing University of Chinese Medicine, Jiangsu Province Hospital of Chinese Medicine, Nanjing, China; IIT Research Institute, Chicago, IL, USA
| | - Yuan Gui
- Division of Nephrology, Department of Medicine, University of Connecticut School of Medicine, Farmington, CT, USA
| | - Mark S Wang
- Division of Nephrology, Department of Medicine, University of Connecticut School of Medicine, Farmington, CT, USA
| | - Lu Zhang
- Affiliated Hosptial of Nanjing University of Chinese Medicine, Jiangsu Province Hospital of Chinese Medicine, Nanjing, China
| | - Tingting Xu
- Affiliated Hosptial of Nanjing University of Chinese Medicine, Jiangsu Province Hospital of Chinese Medicine, Nanjing, China
| | - Yuchen Pan
- Department of Biostatistics, University of Pittsburgh, Pittsburgh, PA, USA; Department of Life Sciences and Institute of Genome Sciences, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Ke Zhang
- Department of Pathology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; Renal Division, The 3rd Xiangya Hospital, Central South University, Changsha, China
| | - Ying Yu
- Department of Pathology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; Renal Division, Tongji Hospital, Tongji University, Shanghai, China
| | - Liangxiang Xiao
- Department of Pathology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; Renal Division, Zhongshan Hospital, Xiamen University, Xiamen, China
| | - Yi Qiao
- Department of Surgery, University of Connecticut School of Medicine, Farmington, CT, USA
| | | | - Geneva Hargis
- University of Connecticut School of Medicine, Farmington, CT, USA
| | - Tao Huan
- Department of Chemistry, University of British Columbia, Vancouver, BC, Canada
| | - Yanbao Yu
- Department of Chemistry & Biochemistry, University of Delaware, Newark, DE, USA
| | - Jianling Tao
- Division of Nephrology, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Rong Zhang
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, USA
| | - Donald L Kreutzer
- Department of Surgery, University of Connecticut School of Medicine, Farmington, CT, USA
| | - Yanjiao Zhou
- University of Connecticut School of Medicine, Farmington, CT, USA
| | - Xiao-Jun Tian
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, USA
| | - Yanlin Wang
- Division of Nephrology, Department of Medicine, University of Connecticut School of Medicine, Farmington, CT, USA
| | - Haiyan Fu
- Department of Pathology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; State Key Laboratory of Organ Failure Research, National Clinical Research Center of Kidney Disease, Division of Nephrology, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Xiaofei An
- Affiliated Hosptial of Nanjing University of Chinese Medicine, Jiangsu Province Hospital of Chinese Medicine, Nanjing, China; Vascular Biology Center, Medical College of Georgia, Augusta University, GA, USA.
| | - Silvia Liu
- Department of Pathology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
| | - Dong Zhou
- Division of Nephrology, Department of Medicine, University of Connecticut School of Medicine, Farmington, CT, USA.
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16
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Kuzyk VO, Somsen GW, Haselberg R. CE-MS for Proteomics and Intact Protein Analysis. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2021; 1336:51-86. [PMID: 34628627 DOI: 10.1007/978-3-030-77252-9_4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
This chapter aims to explore various parameters involved in achieving high-end capillary electrophoresis hyphenated to mass spectrometry (CE-MS) analysis of proteins, peptides, and their posttranslational modifications. The structure of the topics discussed in this book chapter is conveniently mapped on the scheme of the CE-MS system itself, starting from sample preconcentration and injection techniques and finishing with mass analyzer considerations. After going through the technical considerations, a variety of relevant applications for this analytical approach are presented, including posttranslational modifications analysis, clinical biomarker discovery, and its growing use in the biotechnological industry.
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Affiliation(s)
- Valeriia O Kuzyk
- Division of Bioanalytical Chemistry, AIMMS: Amsterdam Institute of Molecular and Life Sciences, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Govert W Somsen
- Division of Bioanalytical Chemistry, AIMMS: Amsterdam Institute of Molecular and Life Sciences, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Rob Haselberg
- Division of Bioanalytical Chemistry, AIMMS: Amsterdam Institute of Molecular and Life Sciences, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
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17
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Helena H, Ivona V, Roman Ř, František F. Current applications of capillary electrophoresis-mass spectrometry for the analysis of biologically important analytes in urine (2017 to mid-2021): A review. J Sep Sci 2021; 45:305-324. [PMID: 34538010 PMCID: PMC9292318 DOI: 10.1002/jssc.202100621] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2021] [Revised: 09/07/2021] [Accepted: 09/10/2021] [Indexed: 12/17/2022]
Abstract
Capillary electrophoresis coupled online with mass detection is a modern tool for analyzing wide ranges of compounds in complex samples, including urine. Capillary electrophoresis with mass spectrometry allows the separation and identification of various analytes spanning from small ions to high molecular weight protein complexes. Similarly to the much more common liquid chromatography‐mass spectrometry techniques, the capillary electrophoresis separation reduces the complexity of the mixture of analytes entering the mass spectrometer resulting in reduced ion suppression and a more straightforward interpretation of the mass spectrometry data. This review summarizes capillary electrophoresis with mass spectrometry studies published between the years 2017 and 2021, aiming at the determination of various compounds excreted in urine. The properties of the urine, including its diagnostical and analytical features and chemical composition, are also discussed including general protocols for the urine sample preparation. The mechanism of the electrophoretic separation and the instrumentation for capillary electrophoresis with mass spectrometry coupling is also included. This review shows the potential of the capillary electrophoresis with mass spectrometry technique for the analyses of different kinds of analytes in a complex biological matrix. The discussed applications are divided into two main groups (capillary electrophoresis with mass spectrometry for the determination of drugs and drugs of abuse in urine and capillary electrophoresis with mass spectrometry for the studies of urinary metabolome).
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Affiliation(s)
- Hrušková Helena
- Institute of Analytical Chemistry, Czech Academy of Sciences, Brno, Czech Republic.,Faculty of Science, Masaryk University, Brno, Czech Republic
| | - Voráčová Ivona
- Institute of Analytical Chemistry, Czech Academy of Sciences, Brno, Czech Republic
| | - Řemínek Roman
- Institute of Analytical Chemistry, Czech Academy of Sciences, Brno, Czech Republic
| | - Foret František
- Institute of Analytical Chemistry, Czech Academy of Sciences, Brno, Czech Republic
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18
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Rotbain Curovic V, Magalhães P, He T, Hansen TW, Mischak H, Rossing P. Urinary peptidome and diabetic retinopathy in the DIRECT-Protect 1 and 2 trials. Diabet Med 2021; 38:e14634. [PMID: 34228837 DOI: 10.1111/dme.14634] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/29/2021] [Accepted: 07/05/2021] [Indexed: 12/12/2022]
Abstract
BACKGROUND Given the association of diabetic retinopathy (DR) and kidney disease, we investigated the urinary peptidome to presence and deterioration of DR in a post hoc analysis of trials investigating the effect of candesartan on progression of DR in type 1 and type 2 diabetes, respectively. METHODS Baseline urinary peptidomic analysis was performed on a random selection of 783 and 792 subjects in two randomized controlled trials, DIRECT-Protect 1 and 2, respectively. End points were two-step (RET2) and three-step (RET3) change in Early Treatment of Diabetic Retinopathy Study protocol (ETDRS) defined level. Peptide levels were correlated to baseline EDTRS level in a discovery set of 2/3 of the participants from DIRECT-Protect 1. The identified peptides were then validated cross-sectionally in the remaining 1/3 from DIRECT-Protect 1. Thereafter, peptides identified in the discovery set were assessed in the entire DIRECT-Protect 1 and 2 cohorts and significant peptides were tested longitudinally. RESULTS Follow-up ranged 4.0-4.7 years. 24 peptides were associated with baseline DR in the discovery set. COL3A1 (seq: NTG~) and COL4A1 (seq: DGA~) were associated with baseline DR in the validation set (Rho: -.223, p < 0.001 and Rho: -.141, p = 0.024). Neither was significantly associated with end points. Assessing the 24 identified peptides in the entire cohorts, several collagen peptides were associated with baseline DR and end points; however, there was no overlap across diabetes types. CONCLUSIONS We identified several urinary peptides (mainly collagen) associated with the presence of DR, however they could not be conclusively associated with worsening of DR.
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Affiliation(s)
| | | | - Tianlin He
- Mosaiques Diagnostics, Hannover, Germany
- Institute for Molecular Cardiovascular Research, University of Aachen, Aachen, Germany
| | | | | | - Peter Rossing
- Steno Diabetes Center Copenhagen, Gentofte, Denmark
- University of Copenhagen, Copenhagen, Denmark
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19
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Catanese L, Siwy J, Mavrogeorgis E, Amann K, Mischak H, Beige J, Rupprecht H. A Novel Urinary Proteomics Classifier for Non-Invasive Evaluation of Interstitial Fibrosis and Tubular Atrophy in Chronic Kidney Disease. Proteomes 2021; 9:32. [PMID: 34287333 PMCID: PMC8293473 DOI: 10.3390/proteomes9030032] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Revised: 07/06/2021] [Accepted: 07/07/2021] [Indexed: 12/25/2022] Open
Abstract
Non-invasive urinary peptide biomarkers are able to detect and predict chronic kidney disease (CKD). Moreover, specific urinary peptides enable discrimination of different CKD etiologies and offer an interesting alternative to invasive kidney biopsy, which cannot always be performed. The aim of this study was to define a urinary peptide classifier using mass spectrometry technology to predict the degree of renal interstitial fibrosis and tubular atrophy (IFTA) in CKD patients. The urinary peptide profiles of 435 patients enrolled in this study were analyzed using capillary electrophoresis coupled with mass spectrometry (CE-MS). Urine samples were collected on the day of the diagnostic kidney biopsy. The proteomics data were divided into a training (n = 200) and a test (n = 235) cohort. The fibrosis group was defined as IFTA ≥ 15% and no fibrosis as IFTA < 10%. Statistical comparison of the mass spectrometry data enabled identification of 29 urinary peptides with differential occurrence in samples with and without fibrosis. Several collagen fragments and peptide fragments of fetuin-A and others were combined into a peptidomic classifier. The classifier separated fibrosis from non-fibrosis patients in an independent test set (n = 186) with area under the curve (AUC) of 0.84 (95% CI: 0.779 to 0.889). A significant correlation of IFTA and FPP_BH29 scores could be observed Rho = 0.5, p < 0.0001. We identified a peptidomic classifier for renal fibrosis containing 29 peptide fragments corresponding to 13 different proteins. Urinary proteomics analysis can serve as a non-invasive tool to evaluate the degree of renal fibrosis, in contrast to kidney biopsy, which allows repeated measurements during the disease course.
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Affiliation(s)
- Lorenzo Catanese
- Department of Nephrology, Angiology and Rheumatology, Klinikum Bayreuth GmbH, 95447 Bayreuth, Germany; (L.C.); (H.R.)
- Kuratorium for Dialysis and Transplantation (KfH) Bayreuth, 95445 Bayreuth, Germany
- Friedrich-Alexander-University Erlangen-Nürnberg, 91054 Erlangen, Germany
| | - Justyna Siwy
- Mosaiques Diagnostics GmbH, 30659 Hannover, Germany; (E.M.); (H.M.)
| | - Emmanouil Mavrogeorgis
- Mosaiques Diagnostics GmbH, 30659 Hannover, Germany; (E.M.); (H.M.)
- Institute for Molecular Cardiovascular Research (IMCAR), RWTH Aachen University Hospital, 52074 Aachen, Germany
| | - Kerstin Amann
- Department of Nephropathology, Institute of Pathology, University of Erlangen-Nürnberg, 91054 Erlangen, Germany;
| | - Harald Mischak
- Mosaiques Diagnostics GmbH, 30659 Hannover, Germany; (E.M.); (H.M.)
| | - Joachim Beige
- Department of Infectious Diseases/Tropical Medicine, Nephrology/KfH Renal Unit and Rheumatology, St. Georg Hospital Leipzig, 04129 Leipzig, Germany;
- Kuratorium for Dialysis and Transplantation (KfH) Renal Unit, Hospital St. Georg, 04129 Leipzig, Germany
- Department of Internal Medicine II, Martin-Luther-University Halle/Wittenberg, 06108 Halle/Saale, Germany
| | - Harald Rupprecht
- Department of Nephrology, Angiology and Rheumatology, Klinikum Bayreuth GmbH, 95447 Bayreuth, Germany; (L.C.); (H.R.)
- Kuratorium for Dialysis and Transplantation (KfH) Bayreuth, 95445 Bayreuth, Germany
- Friedrich-Alexander-University Erlangen-Nürnberg, 91054 Erlangen, Germany
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20
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Trindade F, Barros AS, Silva J, Vlahou A, Falcão-Pires I, Guedes S, Vitorino C, Ferreira R, Leite-Moreira A, Amado F, Vitorino R. Mining the Biomarker Potential of the Urine Peptidome: From Amino Acids Properties to Proteases. Int J Mol Sci 2021; 22:5940. [PMID: 34073067 PMCID: PMC8197949 DOI: 10.3390/ijms22115940] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Revised: 05/27/2021] [Accepted: 05/28/2021] [Indexed: 12/11/2022] Open
Abstract
Native biofluid peptides offer important information about diseases, holding promise as biomarkers. Particularly, the non-invasive nature of urine sampling, and its high peptide concentration, make urine peptidomics a useful strategy to study the pathogenesis of renal conditions. Moreover, the high number of detectable peptides as well as their specificity set the ground for the expansion of urine peptidomics to the identification of surrogate biomarkers for extra-renal diseases. Peptidomics further allows the prediction of proteases (degradomics), frequently dysregulated in disease, providing a complimentary source of information on disease pathogenesis and biomarkers. Then, what does urine peptidomics tell us so far? In this paper, we appraise the value of urine peptidomics in biomarker research through a comprehensive analysis of all datasets available to date. We have mined > 50 papers, addressing > 30 different conditions, comprising > 4700 unique peptides. Bioinformatic tools were used to reanalyze peptide profiles aiming at identifying disease fingerprints, to uncover hidden disease-specific peptides physicochemical properties and to predict the most active proteases associated with their generation. The molecular patterns found in this study may be further validated in the future as disease biomarker not only for kidney diseases but also for extra-renal conditions, as a step forward towards the implementation of a paradigm of predictive, preventive and personalized (3P) medicine.
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Affiliation(s)
- Fábio Trindade
- UnIC—Cardiovascular Research and Development Centre, Department of Surgery and Physiology, Faculty of Medicine, University of Porto, 4200-319 Porto, Portugal; (A.S.B.); (I.F.-P.); (A.L.-M.)
| | - António S. Barros
- UnIC—Cardiovascular Research and Development Centre, Department of Surgery and Physiology, Faculty of Medicine, University of Porto, 4200-319 Porto, Portugal; (A.S.B.); (I.F.-P.); (A.L.-M.)
| | - Jéssica Silva
- iBiMED—Department of Medical Sciences, Institute of Biomedicine, University of Aveiro, 3810-193 Aveiro, Portugal;
| | - Antonia Vlahou
- Biotechnology Division, Biomedical Research Foundation of the Academy of Athens, 115 27 Athens, Greece;
| | - Inês Falcão-Pires
- UnIC—Cardiovascular Research and Development Centre, Department of Surgery and Physiology, Faculty of Medicine, University of Porto, 4200-319 Porto, Portugal; (A.S.B.); (I.F.-P.); (A.L.-M.)
| | - Sofia Guedes
- LAQV-REQUIMTE, Departamento de Química, Universidade de Aveiro, 3810-193 Aveiro, Portugal; (S.G.); (R.F.); (F.A.)
| | - Carla Vitorino
- Faculty of Pharmacy, University of Coimbra, 3000-548 Coimbra, Portugal;
- Coimbra Chemistry Centre, Department of Chemistry, University of Coimbra, 3004-535 Coimbra, Portugal
- Center for Neurosciences and Cell Biology (CNC), University of Coimbra, 3004-504 Coimbra, Portugal
| | - Rita Ferreira
- LAQV-REQUIMTE, Departamento de Química, Universidade de Aveiro, 3810-193 Aveiro, Portugal; (S.G.); (R.F.); (F.A.)
| | - Adelino Leite-Moreira
- UnIC—Cardiovascular Research and Development Centre, Department of Surgery and Physiology, Faculty of Medicine, University of Porto, 4200-319 Porto, Portugal; (A.S.B.); (I.F.-P.); (A.L.-M.)
| | - Francisco Amado
- LAQV-REQUIMTE, Departamento de Química, Universidade de Aveiro, 3810-193 Aveiro, Portugal; (S.G.); (R.F.); (F.A.)
| | - Rui Vitorino
- UnIC—Cardiovascular Research and Development Centre, Department of Surgery and Physiology, Faculty of Medicine, University of Porto, 4200-319 Porto, Portugal; (A.S.B.); (I.F.-P.); (A.L.-M.)
- iBiMED—Department of Medical Sciences, Institute of Biomedicine, University of Aveiro, 3810-193 Aveiro, Portugal;
- LAQV-REQUIMTE, Departamento de Química, Universidade de Aveiro, 3810-193 Aveiro, Portugal; (S.G.); (R.F.); (F.A.)
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21
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Tailliar M, Schanstra JP, Dierckx T, Breuil B, Hanouna G, Charles N, Bascands JL, Dussol B, Vazi A, Chiche L, Siwy J, Faguer S, Daniel L, Daugas E, Jourde-Chiche N. Urinary Peptides as Potential Non-Invasive Biomarkers for Lupus Nephritis: Results of the Peptidu-LUP Study. J Clin Med 2021; 10:jcm10081690. [PMID: 33920017 PMCID: PMC8071029 DOI: 10.3390/jcm10081690] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2021] [Revised: 04/08/2021] [Accepted: 04/09/2021] [Indexed: 12/16/2022] Open
Abstract
Background: Lupus nephritis (LN) is a severe manifestation of Systemic Lupus Erythematosus (SLE). The therapeutic strategy relies on kidney biopsy (KB) results. We tested whether urinary peptidome analysis could non-invasively differentiate active from non-active LN. Design: Urinary samples were collected from 93 patients (55 with active LN and 38 with non-active LN), forming a discovery (n = 42) and an independent validation (n = 51) cohort. Clinical characteristics were collected at inclusion and prospectively for 24 months. The urinary peptidome was analyzed by capillary-electrophoresis coupled to mass-spectrometry, comparing active LN to non-active LN, and assessing chronic lesions and response to therapy. The value of previously validated prognostic (CKD273) and differential diagnostic (LN172) signatures was evaluated. Results: Urinary peptides could not discriminate between active and non-active LN or predict early response to therapy. Tubulo-interstitial fibrosis was correlated to the CKD273. The LN172 score identified 92.5% of samples as LN. Few patients developed new-onset CKD. Conclusions: We validated the CKD273 and LN172 classifiers but did not identify a robust signature that could predict active LN and replace KB. The value of urinary peptidome to predict long-term CKD, or renal flares in SLE, remains to be evaluated.
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Affiliation(s)
- Maxence Tailliar
- AP-HM, Centre de Néphrologie et Transplantation Rénale, Hôpital de la Conception, 13005 Marseille, France; (M.T.); (B.D.)
| | - Joost P. Schanstra
- Institut National de la Santé et de la Recherche Médicale (INSERM), U1297, Institut of Metabolic and Cardiovascular Disease (I2MC), 31432 Toulouse, France; (J.P.S.); (B.B.); (S.F.)
- Université Toulouse III Paul-Sabatier, 31062 Toulouse, France
| | - Tim Dierckx
- Laboratory of Clinical and Epidemiological Virology, Department of Microbiology and Immunology, Rega Institute for Medical Research, KU Leuven, 3000 Leuven, Belgium;
| | - Benjamin Breuil
- Institut National de la Santé et de la Recherche Médicale (INSERM), U1297, Institut of Metabolic and Cardiovascular Disease (I2MC), 31432 Toulouse, France; (J.P.S.); (B.B.); (S.F.)
- Université Toulouse III Paul-Sabatier, 31062 Toulouse, France
| | - Guillaume Hanouna
- AP-HP, Service de Néphrologie, Hôpital Bichat, DMU VICTOIRE, 75018 Paris, France; (G.H.); (E.D.)
| | - Nicolas Charles
- Centre de Recherche sur l’Inflammation, Université de Paris, INSERM UMRS1149, CNRS ERL8252, Labex INFLAMEX, DHU FIRE, 75890 Paris, France;
| | - Jean-Loup Bascands
- Institut National de la Santé et de la Recherche Médicale (INSERM), U1188-Université de La Réunion, 97490 Saint-Denis, France;
| | - Bertrand Dussol
- AP-HM, Centre de Néphrologie et Transplantation Rénale, Hôpital de la Conception, 13005 Marseille, France; (M.T.); (B.D.)
- Centre d’Investigation Clinique, CHU Conception, AP-HM, 13005 Marseille, France;
| | - Alain Vazi
- Centre d’Investigation Clinique, CHU Conception, AP-HM, 13005 Marseille, France;
| | - Laurent Chiche
- Médecine Interne, Hôpital Européen, 13003 Marseille, France;
| | - Justyna Siwy
- Mosaiques Diagnostics GmbH, 30659 Hannover, Germany;
| | - Stanislas Faguer
- Institut National de la Santé et de la Recherche Médicale (INSERM), U1297, Institut of Metabolic and Cardiovascular Disease (I2MC), 31432 Toulouse, France; (J.P.S.); (B.B.); (S.F.)
- Université Toulouse III Paul-Sabatier, 31062 Toulouse, France
- CHU de Toulouse, Service de Néphrologie, 31300 Toulouse, France
| | - Laurent Daniel
- AP-HM, Laboratoire d’Ananatomie Pathologique, Hôpital de la Timone, 13005 Marseille, France;
- Center for CardioVascular and Nutrition Research (C2VN), Aix-Marseille University, INSERM, INRAE, 13005 Marseille, France
| | - Eric Daugas
- AP-HP, Service de Néphrologie, Hôpital Bichat, DMU VICTOIRE, 75018 Paris, France; (G.H.); (E.D.)
- Centre de Recherche sur l’Inflammation, Université de Paris, INSERM UMRS1149, CNRS ERL8252, Labex INFLAMEX, DHU FIRE, 75890 Paris, France;
| | - Noémie Jourde-Chiche
- AP-HM, Centre de Néphrologie et Transplantation Rénale, Hôpital de la Conception, 13005 Marseille, France; (M.T.); (B.D.)
- Center for CardioVascular and Nutrition Research (C2VN), Aix-Marseille University, INSERM, INRAE, 13005 Marseille, France
- Correspondence:
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22
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Urinary Growth Differentiation Factor-15 (GDF15) levels as a biomarker of adverse outcomes and biopsy findings in chronic kidney disease. J Nephrol 2021; 34:1819-1832. [PMID: 33847920 DOI: 10.1007/s40620-021-01020-2] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2020] [Accepted: 03/03/2021] [Indexed: 12/20/2022]
Abstract
BACKGROUND Growth Differentiation Factor-15 (GDF15) is a member of the TGF-β superfamily. Increased serum GDF15 has been associated with increased risk of chronic kidney disease (CKD) progression. However, no prior studies have addressed the significance of urinary GDF15 in adult CKD. METHODS We measured serum and urinary GDF15 in a prospective cohort of 84 patients who underwent kidney biopsy and assessed their association with outcomes (survival, kidney replacement therapy) during a follow-up of 29 ± 17 months. RESULTS There was a statistically significant correlation between serum and urine GDF15 values. However, while serum GDF15 values increased with decreasing glomerular filtration rate, urinary GDF15 did not. Immunohistochemistry located kidney GDF15 expression mainly in tubular cells, and kidney GDF15 staining correlated with urinary GDF15 values. Urine GDF15 was significantly higher in patients with a histologic diagnosis of diabetic nephropathy than in diabetic patients without diabetic nephropathy. This was not the case for serum GDF15. Both serum and urine GDF15 were negatively associated with patient survival in multivariate models. However, when both urine and serum GDF15 were present in the model, lower urine GDF15 predicted patient survival [B coefficient (SEM) - 0.395 (0.182) p 0.03], and higher urine GDF15 predicted a composite of mortality or kidney replacement therapy [0.191 (0.06) p 0.002], while serum GDF15 was not predictive. Decision tree analysis yielded similar results. The area under the curve (AUC) of the receiver operating curve (ROC) for urine GDF15 as a predictor of mortality was 0.95 (95% CI 0.89-1.00, p < 0.001). CONCLUSIONS In conclusion, urinary GDF15 is associated with kidney histology patterns, mortality and the need for renal replacement therapy (RRT) in CKD patients who underwent a kidney biopsy.
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23
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Mavrogeorgis E, Mischak H, Beige J, Latosinska A, Siwy J. Understanding glomerular diseases through proteomics. Expert Rev Proteomics 2021; 18:137-157. [PMID: 33779448 DOI: 10.1080/14789450.2021.1908893] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
INTRODUCTION Chronic kidney disease is avery common and complex chronic disease. Uncovering the pathological patterns of CKD on the molecular level of bio-fluids and tissue appears to be both vital and promising for a more favorable outcome. We reviewed recently discovered proteomics biomarkers for CKD to provide new insight into disease pathology. AREAS COVERED We review the application of proteome analysis in the context of CKD with various etiologies within the last 5 years. Proteins and peptides associated with CKD as derived from multiple sources (urine, blood and tissue) are reported along with their various biological pathways. EXPERT OPINION A systematic and theoretical comprehension of the CKD pathology is essential for its successful management. The underlying complexity of the disease further requires specific conditions for reliable and interpretable results. In this context, clinical proteomics has resulted in first encouraging findings in CKD. A more complete understanding of the biological pathways related to the disease, based on the scope of a holistic proteomic approach, could improve substantially the management of CKD, especially when in conjunction with the current trend of personalized medicine.
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Affiliation(s)
| | - H Mischak
- Mosaiques Diagnostics GmbH, Hannover, Germany.,Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | - J Beige
- Division of Nephrology and KfH Renal Unit, Hospital St. Georg, Leipzig, Germany.,Department of Internal Medicine 2 (Nephrology, Rheumatology, Endocrinology), Martin-Luther-University Halle, Wittenberg, Germany
| | | | - J Siwy
- Mosaiques Diagnostics GmbH, Hannover, Germany
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24
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Obert LA, Elmore SA, Ennulat D, Frazier KS. A Review of Specific Biomarkers of Chronic Renal Injury and Their Potential Application in Nonclinical Safety Assessment Studies. Toxicol Pathol 2021; 49:996-1023. [PMID: 33576319 DOI: 10.1177/0192623320985045] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
A host of novel renal biomarkers have been developed over the past few decades which have enhanced monitoring of renal disease and drug-induced kidney injury in both preclinical studies and in humans. Since chronic kidney disease (CKD) and acute kidney injury (AKI) share similar underlying mechanisms and the tubulointerstitial compartment has a functional role in the progression of CKD, urinary biomarkers of AKI may provide predictive information in chronic renal disease. Numerous studies have explored whether the recent AKI biomarkers could improve upon the standard clinical biomarkers, estimated glomerular filtration rate (eGFR), and urinary albumin to creatinine ratio, for predicting outcomes in CKD patients. This review is an introduction to alternative assays that can be utilized in chronic (>3 months duration) nonclinical safety studies to provide information on renal dysfunction and to demonstrate specific situations where these assays could be utilized in nonclinical drug development. Novel biomarkers such as symmetrical dimethyl arginine, dickkopf homolog 3, and cystatin C predict chronic renal injury in animals, act as surrogates for GFR, and may predict changes in GFR in patients over time, ultimately providing a bridge from preclinical to clinical renal monitoring.
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Affiliation(s)
- Leslie A Obert
- 549350GlaxoSmithKline (GSK), Nonclinical Safety, Collegeville, PA, USA
| | - Susan A Elmore
- Cellular and Molecular Pathology Branch, National Toxicology Program (NTP), 6857National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA
| | - Daniela Ennulat
- 549350GlaxoSmithKline (GSK), Nonclinical Safety, Collegeville, PA, USA
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25
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Abstract
Interstitial fibrosis with tubule atrophy (IF/TA) is the response to virtually any sustained kidney injury and correlates inversely with kidney function and allograft survival. IF/TA is driven by various pathways that include hypoxia, renin-angiotensin-aldosterone system, transforming growth factor (TGF)-β signaling, cellular rejection, inflammation and others. In this review we will focus on key pathways in the progress of renal fibrosis, diagnosis and therapy of allograft fibrosis. This review discusses the role and origin of myofibroblasts as matrix producing cells and therapeutic targets in renal fibrosis with a particular focus on renal allografts. We summarize current trends to use multi-omic approaches to identify new biomarkers for IF/TA detection and to predict allograft survival. Furthermore, we review current imaging strategies that might help to identify and follow-up IF/TA complementary or as alternative to invasive biopsies. We further discuss current clinical trials and therapeutic strategies to treat kidney fibrosis.Supplemental Visual Abstract; http://links.lww.com/TP/C141.
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26
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Zhang W, Ramautar R. CE-MS for metabolomics: Developments and applications in the period 2018-2020. Electrophoresis 2021; 42:381-401. [PMID: 32906195 PMCID: PMC7891659 DOI: 10.1002/elps.202000203] [Citation(s) in RCA: 53] [Impact Index Per Article: 17.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2020] [Revised: 08/30/2020] [Accepted: 09/01/2020] [Indexed: 02/06/2023]
Abstract
Capillary electrophoresis-mass spectrometry (CE-MS) is now a mature analytical technique in metabolomics, notably for the efficient profiling of polar and charged metabolites. Over the past few years, (further) progress has been made in the design of improved interfacing techniques for coupling CE to MS; also, in the development of CE-MS approaches for profiling metabolites in volume-restricted samples, and in strategies that further enhance the metabolic coverage. In this article, which is a follow-up of a previous review article covering the years 2016-2018 (Electrophoresis 2019, 40, 165-179), the main (technological) developments in CE-MS methods and strategies for metabolomics are discussed covering the literature from July 2018 to June 2020. Representative examples highlight the utility of CE-MS in the fields of biomedical, clinical, microbial, plant and food metabolomics. A complete overview of recent CE-MS-based metabolomics studies is given in a table, which provides information on sample type and pretreatment, capillary coatings, and MS detection mode. Finally, some general conclusions and perspectives are given.
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Affiliation(s)
- Wei Zhang
- Biomedical Microscale Analytics, Leiden Academic Centre for Drug ResearchLeiden UniversityLeidenThe Netherlands
| | - Rawi Ramautar
- Biomedical Microscale Analytics, Leiden Academic Centre for Drug ResearchLeiden UniversityLeidenThe Netherlands
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27
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Latosinska A, Siwy J, Faguer S, Beige J, Mischak H, Schanstra JP. Value of Urine Peptides in Assessing Kidney and Cardiovascular Disease. Proteomics Clin Appl 2021; 15:e2000027. [PMID: 32710812 DOI: 10.1002/prca.202000027] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2020] [Revised: 05/18/2020] [Indexed: 12/14/2022]
Abstract
Urinary peptides gained significant attention as potential biomarkers especially in the context of kidney and cardiovascular disease. In this manuscript the recent literature since 2015 on urinary peptide investigation in human kidney and cardiovascular disease is reviewed. The technology most commonly used in this context is capillary electrophoresis coupled mass spectrometry, in part owed to the large database available and the well-defined dataspace. Several studies based on over 1000 subjects are reported in the recent past, especially examining CKD273, a classifier for assessment of chronic kidney disease based on 273 urine peptides. Interestingly, the most abundant urinary peptides are generally collagen fragments, which may have gone undetected for some time as they are typically modified via proline hydroxylation. The data available suggest that urinary peptides specifically depict inflammation and fibrosis, and may serve as a non-invasive tool to assess fibrosis, which appears to be a key driver in kidney and cardiovascular disease. The recent successful completion of the first urinary peptide guided intervention trial, PRIORITY, is expected to further spur clinical application of urinary peptidomics, aiming especially at early detection of chronic diseases, prediction of progression, and prognosis of drug response.
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Affiliation(s)
| | - Justyna Siwy
- Mosaiques Diagnostics GmbH, Rotenburger Straße 20, 30659, Hannover, Germany
| | - Stanislas Faguer
- Département de Néphrologie et Transplantation d'organes, Centre de référence des maladies rénales rares, Centre Hospitalier Universitaire de Toulouse, 1, Avenue Jean Poulhes, Toulouse, 31059, France
- Institut National de la Santé et de la Recherche Médicale (INSERM), U1048, Institut of Cardiovascular and Metabolic Disease, 1 Avenue Jean Poulhès, BP 84225, Toulouse Cedex 4, 31432, France
- Université Toulouse III Paul-Sabatier, Route de Narbonne, Toulouse, 31330, France
| | - Joachim Beige
- Department of Nephrology and Kuratorium for Dialysis and Transplantation Renal Unit, Hospital St Georg, Delitzscher Str. 141, 04129, Leipzig, Germany
- Department of Nephrology, Martin-Luther-University Halle/Wittenberg, Universitätsplatz 10, 06108, Halle (Saale), Germany
| | - Harald Mischak
- Mosaiques Diagnostics GmbH, Rotenburger Straße 20, 30659, Hannover, Germany
| | - Joost P Schanstra
- Institut National de la Santé et de la Recherche Médicale (INSERM), U1048, Institut of Cardiovascular and Metabolic Disease, 1 Avenue Jean Poulhès, BP 84225, Toulouse Cedex 4, 31432, France
- Université Toulouse III Paul-Sabatier, Route de Narbonne, Toulouse, 31330, France
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28
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Lousa I, Reis F, Beirão I, Alves R, Belo L, Santos-Silva A. New Potential Biomarkers for Chronic Kidney Disease Management-A Review of the Literature. Int J Mol Sci 2020; 22:E43. [PMID: 33375198 PMCID: PMC7793089 DOI: 10.3390/ijms22010043] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Revised: 12/14/2020] [Accepted: 12/21/2020] [Indexed: 02/07/2023] Open
Abstract
The prevalence of chronic kidney disease (CKD) is increasing worldwide, and the mortality rate continues to be unacceptably high. The biomarkers currently used in clinical practice are considered relevant when there is already significant renal impairment compromising the early use of potentially successful therapeutic interventions. More sensitive and specific biomarkers to detect CKD earlier on and improve patients' prognoses are an important unmet medical need. The aim of this review is to summarize the recent literature on new promising early CKD biomarkers of renal function, tubular lesions, endothelial dysfunction and inflammation, and on the auspicious findings from metabolomic studies in this field. Most of the studied biomarkers require further validation in large studies and in a broad range of populations in order to be implemented into routine CKD management. A panel of biomarkers, including earlier biomarkers of renal damage, seems to be a reasonable approach to be applied in clinical practice to allow earlier diagnosis and better disease characterization based on the underlying etiologic process.
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Affiliation(s)
- Irina Lousa
- UCIBIO\REQUIMTE, Laboratory of Biochemistry, Department of Biological Sciences, Faculty of Pharmacy, University of Porto, 4050-313 Porto, Portugal; (I.L.); (L.B.)
| | - Flávio Reis
- Institute of Pharmacology & Experimental Therapeutics, & Coimbra Institute for Clinical and Biomedical Research (iCBR), Faculty of Medicine, University of Coimbra, 3000-548 Coimbra, Portugal;
- Center for Innovative Biomedicine and Biotechnology (CIBB), University of Coimbra, 3004-504 Coimbra, Portugal
- Clinical Academic Center of Coimbra (CACC), 3000-075 Coimbra, Portugal
| | - Idalina Beirão
- Universitary Hospital Centre of Porto (CHUP), 4099-001 Porto, Portugal;
- Institute of Biomedical Sciences Abel Salazar (ICBAS), University of Porto, 4050-313 Porto, Portugal
| | - Rui Alves
- Nephrology Department, Coimbra University Hospital Center, 3004-561 Coimbra, Portugal;
- University Clinic of Nephrology, Faculty of Medicine, University of Coimbra, 3000-075 Coimbra, Portugal
| | - Luís Belo
- UCIBIO\REQUIMTE, Laboratory of Biochemistry, Department of Biological Sciences, Faculty of Pharmacy, University of Porto, 4050-313 Porto, Portugal; (I.L.); (L.B.)
| | - Alice Santos-Silva
- UCIBIO\REQUIMTE, Laboratory of Biochemistry, Department of Biological Sciences, Faculty of Pharmacy, University of Porto, 4050-313 Porto, Portugal; (I.L.); (L.B.)
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29
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Eddy S, Mariani LH, Kretzler M. Integrated multi-omics approaches to improve classification of chronic kidney disease. Nat Rev Nephrol 2020; 16:657-668. [PMID: 32424281 DOI: 10.1038/s41581-020-0286-5] [Citation(s) in RCA: 82] [Impact Index Per Article: 20.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/07/2020] [Indexed: 12/11/2022]
Abstract
Chronic kidney diseases (CKDs) are currently classified according to their clinical features, associated comorbidities and pattern of injury on biopsy. Even within a given classification, considerable variation exists in disease presentation, progression and response to therapy, highlighting heterogeneity in the underlying biological mechanisms. As a result, patients and clinicians experience uncertainty when considering optimal treatment approaches and risk projection. Technological advances now enable large-scale datasets, including DNA and RNA sequence data, proteomics and metabolomics data, to be captured from individuals and groups of patients along the genotype-phenotype continuum of CKD. The ability to combine these high-dimensional datasets, in which the number of variables exceeds the number of clinical outcome observations, using computational approaches such as machine learning, provides an opportunity to re-classify patients into molecularly defined subgroups that better reflect underlying disease mechanisms. Patients with CKD are uniquely poised to benefit from these integrative, multi-omics approaches since the kidney biopsy, blood and urine samples used to generate these different types of molecular data are frequently obtained during routine clinical care. The ultimate goal of developing an integrated molecular classification is to improve diagnostic classification, risk stratification and assignment of molecular, disease-specific therapies to improve the care of patients with CKD.
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Affiliation(s)
- Sean Eddy
- Division of Nephrology, Department of Internal Medicine, Michigan Medicine, Ann Arbor, MI, USA
| | - Laura H Mariani
- Division of Nephrology, Department of Internal Medicine, Michigan Medicine, Ann Arbor, MI, USA
| | - Matthias Kretzler
- Division of Nephrology, Department of Internal Medicine, Michigan Medicine, Ann Arbor, MI, USA.
- Department of Computational Medicine and Bioinformatics, Michigan Medicine, Ann Arbor, MI, USA.
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30
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Ortiz A. Ckj consolidation among Q1 Urology and Nephrology journals. Clin Kidney J 2020; 13:723-727. [PMID: 33123351 PMCID: PMC7577766 DOI: 10.1093/ckj/sfaa197] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2020] [Accepted: 09/02/2020] [Indexed: 12/21/2022] Open
Abstract
The Clinical Kidney Journal (ckj) impact factor from Clarivate’s Web of Science for 2019 was 3.388. This consolidates ckj among journals in the top 25% (first quartile, Q1) in the Urology and Nephrology field according to the journal impact factor. The manuscripts contributing the most to the impact factor focused on chronic kidney disease (CKD) epidemiology and evaluation, CKD complications and their management, cost-efficiency of renal replacement therapy, pathogenesis of CKD, familial kidney disease and the environment–genetics interface, onconephrology, technology, SGLT2 inhibitors and outcome prediction. We provide here an overview of the hottest and most impactful topics for 2017–19.
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Affiliation(s)
- Alberto Ortiz
- IIS-Fundación Jiménez Diaz, Department of Medicine, School of Medicine, Universidad Autónoma de Madrid, Madrid, Spain.,Red de Investigación Renal (REDINREN), Instituto Carlos III-FEDER, Madrid, Spain
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Drouin N, van Mever M, Zhang W, Tobolkina E, Ferre S, Servais AC, Gou MJ, Nyssen L, Fillet M, Lageveen-Kammeijer GS, Nouta J, Chetwynd AJ, Lynch I, Thorn JA, Meixner J, Lößner C, Taverna M, Liu S, Tran NT, Francois Y, Lechner A, Nehmé R, Al Hamoui Dit Banni G, Nasreddine R, Colas C, Lindner HH, Faserl K, Neusüß C, Nelke M, Lämmerer S, Perrin C, Bich-Muracciole C, Barbas C, Gonzálvez Á, Guttman A, Szigeti M, Britz-McKibbin P, Kroezen Z, Shanmuganathan M, Nemes P, Portero EP, Hankemeier T, Codesido S, González-Ruiz V, Rudaz S, Ramautar R. Capillary Electrophoresis-Mass Spectrometry at Trial by Metabo-Ring: Effective Electrophoretic Mobility for Reproducible and Robust Compound Annotation. Anal Chem 2020; 92:14103-14112. [PMID: 32961048 PMCID: PMC7581015 DOI: 10.1021/acs.analchem.0c03129] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2020] [Accepted: 09/22/2020] [Indexed: 12/15/2022]
Abstract
Capillary zone electrophoresis-mass spectrometry (CE-MS) is a mature analytical tool for the efficient profiling of (highly) polar and ionizable compounds. However, the use of CE-MS in comparison to other separation techniques remains underrepresented in metabolomics, as this analytical approach is still perceived as technically challenging and less reproducible, notably for migration time. The latter is key for a reliable comparison of metabolic profiles and for unknown biomarker identification that is complementary to high resolution MS/MS. In this work, we present the results of a Metabo-ring trial involving 16 CE-MS platforms among 13 different laboratories spanning two continents. The goal was to assess the reproducibility and identification capability of CE-MS by employing effective electrophoretic mobility (μeff) as the key parameter in comparison to the relative migration time (RMT) approach. For this purpose, a representative cationic metabolite mixture in water, pretreated human plasma, and urine samples spiked with the same metabolite mixture were used and distributed for analysis by all laboratories. The μeff was determined for all metabolites spiked into each sample. The background electrolyte (BGE) was prepared and employed by each participating lab following the same protocol. All other parameters (capillary, interface, injection volume, voltage ramp, temperature, capillary conditioning, and rinsing procedure, etc.) were left to the discretion of the contributing laboratories. The results revealed that the reproducibility of the μeff for 20 out of the 21 model compounds was below 3.1% vs 10.9% for RMT, regardless of the huge heterogeneity in experimental conditions and platforms across the 13 laboratories. Overall, this Metabo-ring trial demonstrated that CE-MS is a viable and reproducible approach for metabolomics.
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Affiliation(s)
- Nicolas Drouin
- Division
of Systems Biomedicine and Pharmacology, Leiden Academic Centre for
Drug Research, Leiden University, 2311 G Leiden, The Netherlands
| | - Marlien van Mever
- Division
of Systems Biomedicine and Pharmacology, Leiden Academic Centre for
Drug Research, Leiden University, 2311 G Leiden, The Netherlands
| | - Wei Zhang
- Division
of Systems Biomedicine and Pharmacology, Leiden Academic Centre for
Drug Research, Leiden University, 2311 G Leiden, The Netherlands
| | - Elena Tobolkina
- School
of Pharmaceutical Sciences, University of
Geneva, Rue Michel Servet 1, 1211 4 Geneva, Switzerland
- Institute
of Pharmaceutical Sciences of Western Switzerland, University of Geneva, Rue Michel Servet 1, 1211 4 Geneva, Switzerland
| | - Sabrina Ferre
- School
of Pharmaceutical Sciences, University of
Geneva, Rue Michel Servet 1, 1211 4 Geneva, Switzerland
- Institute
of Pharmaceutical Sciences of Western Switzerland, University of Geneva, Rue Michel Servet 1, 1211 4 Geneva, Switzerland
| | - Anne-Catherine Servais
- Laboratory
for the Analysis of Medicines, Center for Interdisciplinary Research
on Medicines (CIRM), University of Liège, Avenue Hippocrate 15, B-4000 Liège, Belgium
| | - Marie-Jia Gou
- Laboratory
for the Analysis of Medicines, Center for Interdisciplinary Research
on Medicines (CIRM), University of Liège, Avenue Hippocrate 15, B-4000 Liège, Belgium
| | - Laurent Nyssen
- Laboratory
for the Analysis of Medicines, Center for Interdisciplinary Research
on Medicines (CIRM), University of Liège, Avenue Hippocrate 15, B-4000 Liège, Belgium
- Department
of Clinical Chemistry, Center for Interdisciplinary Research on Medicines
(CIRM), University of Liège, Avenue Hippocrate 15, B-4000 Liège, Belgium
| | - Marianne Fillet
- Laboratory
for the Analysis of Medicines, Center for Interdisciplinary Research
on Medicines (CIRM), University of Liège, Avenue Hippocrate 15, B-4000 Liège, Belgium
| | | | - Jan Nouta
- Leiden University
Medical Center, Center for Proteomics
and Metabolomics, 2300 RC Leiden, The Netherlands
| | - Andrew J. Chetwynd
- School
of Geography Earth and Environmental Sciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, U.K.
| | - Iseult Lynch
- School
of Geography Earth and Environmental Sciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, U.K.
| | - James A. Thorn
- AB
Sciex UK Ltd, Phoenix House, Lakeside Drive, Warrington, Cheshire WA1 1RX, U.K.
| | - Jens Meixner
- Agilent
Technologies R&D and Marketing GmbH & Co. KG, Hewlett-Packard-Straße 8, 76337 Waldbronn, Germany
| | | | - Myriam Taverna
- Université Paris-Saclay, CNRS, Institut Galien Paris-Saclay, 92296 Châtenay-Malabry, France
- Institut Universitaire de France, 1 Rue Descartes, 75231 CEDEX 05 Paris, France
| | - Sylvie Liu
- Université Paris-Saclay, CNRS, Institut Galien Paris-Saclay, 92296 Châtenay-Malabry, France
| | - N. Thuy Tran
- Université Paris-Saclay, CNRS, Institut Galien Paris-Saclay, 92296 Châtenay-Malabry, France
| | - Yannis Francois
- Laboratoire
de Spectromètrie de Masse des Interactions et des Systémes
(LSMIS) UMR 7140 (Unistra-CNRS), Université
de Strasbourg, 4 Rue Blaise Pascal, 67081 CEDEX Strasbourg, France
| | - Antony Lechner
- Laboratoire
de Spectromètrie de Masse des Interactions et des Systémes
(LSMIS) UMR 7140 (Unistra-CNRS), Université
de Strasbourg, 4 Rue Blaise Pascal, 67081 CEDEX Strasbourg, France
| | - Reine Nehmé
- Institut
de Chimie Organique et Analytique (ICOA), CNRS FR 2708 - UMR 7311, Université d’Orléans, 45067 Orléans, France
| | - Ghassan Al Hamoui Dit Banni
- Institut
de Chimie Organique et Analytique (ICOA), CNRS FR 2708 - UMR 7311, Université d’Orléans, 45067 Orléans, France
| | - Rouba Nasreddine
- Institut
de Chimie Organique et Analytique (ICOA), CNRS FR 2708 - UMR 7311, Université d’Orléans, 45067 Orléans, France
| | - Cyril Colas
- Institut
de Chimie Organique et Analytique (ICOA), CNRS FR 2708 - UMR 7311, Université d’Orléans, 45067 Orléans, France
- Centre de Biophysique Moléculaire,
CNRS-Université
d’Orléans, UPR 4311, 45071 CEDEX 2 Orléans, France
| | - Herbert H. Lindner
- Institute
of Clinical Biochemistry, Innsbruck Medical
University, Innrain 80-82, A-6020 Innsbruck, Austria
| | - Klaus Faserl
- Institute
of Clinical Biochemistry, Innsbruck Medical
University, Innrain 80-82, A-6020 Innsbruck, Austria
| | - Christian Neusüß
- Faculty
of Chemistry, Aalen University, Beethovenstraße 1, 73430 Aalen, Germany
| | - Manuel Nelke
- Faculty
of Chemistry, Aalen University, Beethovenstraße 1, 73430 Aalen, Germany
| | - Stefan Lämmerer
- Faculty
of Chemistry, Aalen University, Beethovenstraße 1, 73430 Aalen, Germany
| | - Catherine Perrin
- Institut
des Biomolécules Max Mousseron (IBMM), UMR 5247-CNRS-UM-ENSCM, Université de Montpellier, 34093 CEDEX 5 Montpellier, France
| | - Claudia Bich-Muracciole
- Institut
des Biomolécules Max Mousseron (IBMM), UMR 5247-CNRS-UM-ENSCM, Université de Montpellier, 34093 CEDEX 5 Montpellier, France
| | - Coral Barbas
- Centre
for Metabolomics and Bioanalysis (CEMBIO), Department of Chemistry
and Biochemistry, Facultad de Farmacia, Universidad San Pablo-CEU, CEU Universities, Urbanización
Montepríncipe, Boadilladel
Monte 28660, Madrid, Spain
| | - Ángeles
López Gonzálvez
- Centre
for Metabolomics and Bioanalysis (CEMBIO), Department of Chemistry
and Biochemistry, Facultad de Farmacia, Universidad San Pablo-CEU, CEU Universities, Urbanización
Montepríncipe, Boadilladel
Monte 28660, Madrid, Spain
| | - Andras Guttman
- Horváth
Csaba Memorial Laboratory of Bioseparation Sciences, Research Center
for Molecular Medicine, Faculty of Medicine, Doctoral School of Molecular
Medicine, University of Debrecen, 98 Nagyerdei Road, H-4032 Debrecen, Hungary
- Translation
Glycomics Group, Research Institute of Biomolecular and Chemical Engineering, University of Pannonia, 10 Egyetem Street, Veszprem H-8200, Hungary
- Sciex, 250 South Kraemer Boulevard, Brea, California 92821, United States
| | - Marton Szigeti
- Horváth
Csaba Memorial Laboratory of Bioseparation Sciences, Research Center
for Molecular Medicine, Faculty of Medicine, Doctoral School of Molecular
Medicine, University of Debrecen, 98 Nagyerdei Road, H-4032 Debrecen, Hungary
- Translation
Glycomics Group, Research Institute of Biomolecular and Chemical Engineering, University of Pannonia, 10 Egyetem Street, Veszprem H-8200, Hungary
| | - Philip Britz-McKibbin
- Department
of Chemistry and Chemical Biology, McMaster
University, 1280 Main St. W., Hamilton, Ontario L8S 4M1, Canada
| | - Zachary Kroezen
- Department
of Chemistry and Chemical Biology, McMaster
University, 1280 Main St. W., Hamilton, Ontario L8S 4M1, Canada
| | - Meera Shanmuganathan
- Department
of Chemistry and Chemical Biology, McMaster
University, 1280 Main St. W., Hamilton, Ontario L8S 4M1, Canada
| | - Peter Nemes
- Department
of Chemistry & Biochemistry, University
of Maryland, College
Park, Maryland 20742, United States
| | - Erika P. Portero
- Department
of Chemistry & Biochemistry, University
of Maryland, College
Park, Maryland 20742, United States
| | - Thomas Hankemeier
- Division
of Systems Biomedicine and Pharmacology, Leiden Academic Centre for
Drug Research, Leiden University, 2311 G Leiden, The Netherlands
| | - Santiago Codesido
- School
of Pharmaceutical Sciences, University of
Geneva, Rue Michel Servet 1, 1211 4 Geneva, Switzerland
- Institute
of Pharmaceutical Sciences of Western Switzerland, University of Geneva, Rue Michel Servet 1, 1211 4 Geneva, Switzerland
| | - Víctor González-Ruiz
- School
of Pharmaceutical Sciences, University of
Geneva, Rue Michel Servet 1, 1211 4 Geneva, Switzerland
- Institute
of Pharmaceutical Sciences of Western Switzerland, University of Geneva, Rue Michel Servet 1, 1211 4 Geneva, Switzerland
- Swiss Centre for Applied Human Toxicology
(SCAHT), Missionsstrasse
64, 4055 Bâle, Switzerland
| | - Serge Rudaz
- School
of Pharmaceutical Sciences, University of
Geneva, Rue Michel Servet 1, 1211 4 Geneva, Switzerland
- Institute
of Pharmaceutical Sciences of Western Switzerland, University of Geneva, Rue Michel Servet 1, 1211 4 Geneva, Switzerland
- Swiss Centre for Applied Human Toxicology
(SCAHT), Missionsstrasse
64, 4055 Bâle, Switzerland
| | - Rawi Ramautar
- Division
of Systems Biomedicine and Pharmacology, Leiden Academic Centre for
Drug Research, Leiden University, 2311 G Leiden, The Netherlands
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32
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Duan S, Chen J, Wu L, Nie G, Sun L, Zhang C, Huang Z, Xing C, Zhang B, Yuan Y. Assessment of urinary NGAL for differential diagnosis and progression of diabetic kidney disease. J Diabetes Complications 2020; 34:107665. [PMID: 32653382 DOI: 10.1016/j.jdiacomp.2020.107665] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/04/2020] [Revised: 06/03/2020] [Accepted: 06/21/2020] [Indexed: 12/22/2022]
Abstract
OBJECTIVE Chronic kidney disease (CKD) related to diabetes has become more common than glomerulonephritis in recent years. Given the inefficient and difficult identification of diabetic kidney disease (DKD) from non-diabetic kidney disease (NDKD) as well as a result of emerging evidence supporting a role for tubular involvement in DKD, we aimed to investigate the utility of urinary neutrophil gelatinase-associated lipocalin (uNGAL) in the differential diagnosis and predictive value of DKD from NDKD. METHODS Data for 100 type 2 diabetic patients with CKD at our center from June 2016 to August 2019 were reviewed. All the patients were categorized into 2 groups by the renal biopsy results: DKD and NDKD. Urinary NGAL levels were normalized by urinary creatinine and calculated as uNGAL/creatinine ratios (uNCR). The independent factors of the occurrence of DKD and the diagnostic implications of uNCR were explored by logistic regression and receiver-operating characteristic (ROC) curve analysis. In addition, we analyzed the relationship between uNCR and proteinuria in patients with DKD by Pearson test and linear regression. Kaplan-Meier survival analysis was performed to assess the prospective association of uNCR with the renal outcome. RESULTS Significantly higher levels of uNCR were observed in patients with DKD when compared to those with NDKD (28.65 ng/mg vs 27.47 ng/mg, p< .001). uNCR was identified as an independent risk factor for the occurrence of DKD in diabetic patients with CKD (odds ratio [OR] = 1.020; 95%CI = [1.001-1.399], p = .042). The optimal cutoff value of uNCR for predicting DKD was 60.685 ng/mg with high specificity (90.5%) but relatively low sensitivity (55.7%). In Pearson test, uNCR was positively correlated with proteinuria, serum creatine, blood urea nitrogen, duration of diabetes, interstitial inflammation score and global sclerosis, whereas it was inversely correlated with eGFR, hemoglobin, serum albumin and 25-hydroxy vitamin D. Furthermore, in a fully adjusted model including eGFR, serum albumin and total cholesterol, the group with uNCR>60.685 ng/mg was associated with 7.595 times higher likelihood of nephrotic-range proteinuria compared to the group with uNCR≤60.685 ng/mg. In the Kaplan-Meier survival analysis, the event-free survival probability in patients with uNCR>60.685 ng/mg was significantly lower than those with uNCR≤60.685 ng/mg (p = .048). CONCLUSIONS uNCR might serve as a potential tool for identifying cases in which there was a high clinical suspicion of DKD and that in whom confirmatory biopsy could be considered, and the best predictive cutoff value of normalized uNCR for DKD diagnosis was 60.685 ng/mg. Type 2 diabetic patients with increased level of uNCR had higher risk to nephrotic-range proteinuria and worse renal outcome.
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Affiliation(s)
- Suyan Duan
- Department of Nephrology, the First Affiliated Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing, China
| | - Jiajia Chen
- Department of Nephrology, the First Affiliated Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing, China
| | - Lin Wu
- Department of Nephrology, the First Affiliated Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing, China
| | - Guangyan Nie
- Department of Nephrology, the First Affiliated Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing, China
| | - Lianqin Sun
- Department of Nephrology, the First Affiliated Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing, China
| | - Chengning Zhang
- Department of Nephrology, the First Affiliated Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing, China
| | - Zhimin Huang
- Department of Nephrology, the First Affiliated Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing, China
| | - Changying Xing
- Department of Nephrology, the First Affiliated Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing, China.
| | - Bo Zhang
- Department of Nephrology, the First Affiliated Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing, China.
| | - Yanggang Yuan
- Department of Nephrology, the First Affiliated Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing, China.
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33
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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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34
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Martínez-Castelao A, Soler MJ, Górriz Teruel JL, Navarro-González JF, Fernandez-Fernandez B, de Alvaro Moreno F, Ortiz A. Optimizing the timing of nephrology referral for patients with diabetic kidney disease. Clin Kidney J 2020; 14:5-8. [PMID: 33564400 PMCID: PMC7857795 DOI: 10.1093/ckj/sfaa125] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2020] [Accepted: 06/08/2020] [Indexed: 02/06/2023] Open
Abstract
Age-standardized rates of diabetes mellitus (DM)-related complications, such as acute myocardial infarction, stroke or amputations, have decreased in recent years, but this was not associated with a clear reduction of the incidence of advanced chronic kidney disease (CKD) requiring renal replacement therapy. The early detection of diabetic kidney disease (DKD) is a key to reduce complications, morbidity and mortality. Consensus documents and clinical practice guidelines recommend referral of DM patients to nephrology when the estimated glomerular filtration rate falls below 30 mL/min/1.73 m2 or when albuminuria exceeds 300 mg/g urinary creatinine. Conceptually, it strikes as odd that patients with CKD are referred to the specialist caring for the prevention and treatment of CKD only when >70% of the functioning kidney mass has been lost. The increasing global health burden of CKD, driven in large part by DKD, the suboptimal impact of routine care on DKD outcomes as compared with other DM complications, the realization that successful therapy of CKD requires early diagnosis and intervention, the advances in earlier diagnosis of kidney injury and the recent availability of antidiabetic drugs with a renal mechanism of action and lack of hypoglycaemia risk, which additionally are cardio- and nephroprotective, all point towards a paradigm shift in the care for DM patients in which they should be referred earlier to nephrology as part of a coordinated and integrated care approach.
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Affiliation(s)
- Alberto Martínez-Castelao
- Nephrology department, Bellvitge University Hospital, Barcelona, Spain
- GEENDIAB (Grupo Español de Estudio de la Nefropatía Diabética), Sociedad Española Nefrología (SEN), Santander, Spain
- REDinREN, Instituto Salud Carlos III, Madrid, Spain
- Correspondence to: Alberto Martínez-Castelao; E-mail:
| | - María José Soler
- GEENDIAB (Grupo Español de Estudio de la Nefropatía Diabética), Sociedad Española Nefrología (SEN), Santander, Spain
- REDinREN, Instituto Salud Carlos III, Madrid, Spain
- Nephrology department, Hospital Universitari Vall d’Hebrón, Barcelona, Spain
| | - José Luis Górriz Teruel
- GEENDIAB (Grupo Español de Estudio de la Nefropatía Diabética), Sociedad Española Nefrología (SEN), Santander, Spain
- REDinREN, Instituto Salud Carlos III, Madrid, Spain
- Nephrology department, Hospital Clínico Valencia, INCLIVA, Valencia, Spain
| | - Juan F Navarro-González
- GEENDIAB (Grupo Español de Estudio de la Nefropatía Diabética), Sociedad Española Nefrología (SEN), Santander, Spain
- REDinREN, Instituto Salud Carlos III, Madrid, Spain
- Nephrology department, Unidad Investigación Hospital Nuestra Señora de Candelaria, Tenerife, Spain
| | - Beatriz Fernandez-Fernandez
- REDinREN, Instituto Salud Carlos III, Madrid, Spain
- Nephrology department, IIS-Fundación Jiménez Díaz UAM, Madrid, Spain
| | - Fernando de Alvaro Moreno
- GEENDIAB (Grupo Español de Estudio de la Nefropatía Diabética), Sociedad Española Nefrología (SEN), Santander, Spain
- Nephrology department, Hospitales Madrid, Madrid, Spain
| | - Alberto Ortiz
- GEENDIAB (Grupo Español de Estudio de la Nefropatía Diabética), Sociedad Española Nefrología (SEN), Santander, Spain
- REDinREN, Instituto Salud Carlos III, Madrid, Spain
- Nephrology department, IIS-Fundación Jiménez Díaz UAM, Madrid, Spain
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35
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Ahn HS, Kim JH, Jeong H, Yu J, Yeom J, Song SH, Kim SS, Kim IJ, Kim K. Differential Urinary Proteome Analysis for Predicting Prognosis in Type 2 Diabetes Patients with and without Renal Dysfunction. Int J Mol Sci 2020; 21:ijms21124236. [PMID: 32545899 PMCID: PMC7352871 DOI: 10.3390/ijms21124236] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2020] [Revised: 06/05/2020] [Accepted: 06/12/2020] [Indexed: 12/28/2022] Open
Abstract
Renal dysfunction, a major complication of type 2 diabetes, can be predicted from estimated glomerular filtration rate (eGFR) and protein markers such as albumin concentration. Urinary protein biomarkers may be used to monitor or predict patient status. Urine samples were selected from patients enrolled in the retrospective diabetic kidney disease (DKD) study, including 35 with good and 19 with poor prognosis. After removal of albumin and immunoglobulin, the remaining proteins were reduced, alkylated, digested, and analyzed qualitatively and quantitatively with a nano LC-MS platform. Each protein was identified, and its concentration normalized to that of creatinine. A prognostic model of DKD was formulated based on the adjusted quantities of each protein in the two groups. Of 1296 proteins identified in the 54 urine samples, 66 were differentially abundant in the two groups (area under the curve (AUC): p-value < 0.05), but none showed significantly better performance than albumin. To improve the predictive power by multivariate analysis, five proteins (ACP2, CTSA, GM2A, MUC1, and SPARCL1) were selected as significant by an AUC-based random forest method. The application of two classifiers—support vector machine and random forest—showed that the multivariate model performed better than univariate analysis of mucin-1 (AUC: 0.935 vs. 0.791) and albumin (AUC: 1.0 vs. 0.722). The urinary proteome can reflect kidney function directly and can predict the prognosis of patients with chronic kidney dysfunction. Classification based on five urinary proteins may better predict the prognosis of DKD patients than urinary albumin concentration or eGFR.
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Affiliation(s)
- Hee-Sung Ahn
- Asan Institute for Life Sciences, Asan Medical Center, Seoul 05505, Korea; (H.-S.A.); (J.Y.)
| | - Jong Ho Kim
- Department of Internal Medicine and Biomedical Research Institute, Pusan National University Hospital, Busan 49241, Korea; (J.H.K.); (S.H.S.); (S.S.K.)
| | - Hwangkyo Jeong
- Department of Biomedical Sciences, University of Ulsan College of Medicine, Seoul 05505, Korea;
| | - Jiyoung Yu
- Asan Institute for Life Sciences, Asan Medical Center, Seoul 05505, Korea; (H.-S.A.); (J.Y.)
| | - Jeonghun Yeom
- Convergence Medicine Research Center, Asan Institute for Life Sciences, Seoul 05505, Korea;
| | - Sang Heon Song
- Department of Internal Medicine and Biomedical Research Institute, Pusan National University Hospital, Busan 49241, Korea; (J.H.K.); (S.H.S.); (S.S.K.)
| | - Sang Soo Kim
- Department of Internal Medicine and Biomedical Research Institute, Pusan National University Hospital, Busan 49241, Korea; (J.H.K.); (S.H.S.); (S.S.K.)
| | - In Joo Kim
- Department of Internal Medicine and Biomedical Research Institute, Pusan National University Hospital, Busan 49241, Korea; (J.H.K.); (S.H.S.); (S.S.K.)
- Correspondence: (I.J.K.); (K.K.); Tel.: +82-51-240-7224 (I.J.K.); +82-2-1688-7575 (K.K.)
| | - Kyunggon Kim
- Asan Institute for Life Sciences, Asan Medical Center, Seoul 05505, Korea; (H.-S.A.); (J.Y.)
- Department of Biomedical Sciences, University of Ulsan College of Medicine, Seoul 05505, Korea;
- Clinical Proteomics Core Laboratory, Convergence Medicine Research Center, Asan Medical Center, Seoul 05505, Korea
- Bio-Medical Institute of Technology, Asan Medical Center, Seoul 05505, Korea
- Correspondence: (I.J.K.); (K.K.); Tel.: +82-51-240-7224 (I.J.K.); +82-2-1688-7575 (K.K.)
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36
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He T, Siwy J, Metzger J, Mullen W, Mischak H, Schanstra JP, Zürbig P, Jankowski V. Associations of urinary polymeric immunoglobulin receptor peptides in the context of cardio-renal syndrome. Sci Rep 2020; 10:8291. [PMID: 32427855 PMCID: PMC7237418 DOI: 10.1038/s41598-020-65154-2] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2019] [Accepted: 04/24/2020] [Indexed: 11/09/2022] Open
Abstract
The polymeric immunoglobulin receptor (pIgR) transports immunoglobulins from the basolateral to the apical surface of epithelial cells. PIgR was recently shown to be associated with kidney dysfunction. The immune defense is initiated at the apical surface of epithelial cells where the N-terminal domain of pIgR, termed secretory component (SC), is proteolytically cleaved and released either unbound (free SC) or bound to immunoglobulins. The aim of our study was to evaluate the association of pIgR peptides with the cardio-renal syndrome in a large cohort and to obtain information on how the SC is released. We investigated urinary peptides of 2964 individuals available in the Human Urine Proteome Database generated using capillary electrophoresis coupled to mass spectrometry. The mean amplitude of 23 different pIgR peptides correlated negatively with the estimated glomerular filtration rate (eGFR, rho = −0.309, p < 0.0001). Furthermore, pIgR peptides were significantly increased in cardiovascular disease (coronary artery disease and heart failure) after adjustment for eGFR. We further predicted potential proteases involved in urinary peptide generation using the Proteasix algorithm. Peptide cleavage site analysis suggested that several, and not one, proteases are involved in the generation of the SC. In this large cohort, we could demonstrate that pIgR is associated with the cardio-renal syndrome and provided a more detailed insight on how pIgR can be potentially cleaved to release the SC.
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Affiliation(s)
- Tianlin He
- Mosaiques Diagnostics GmbH, Hannover, Germany.,Institute for Molecular Cardiovascular Research (IMCAR), University Hospital RWTH Aachen, Aachen, Germany
| | | | | | - William Mullen
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | - Harald Mischak
- Mosaiques Diagnostics GmbH, Hannover, Germany.,Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | - Joost P Schanstra
- INSERM U1048, Institute of Cardiovascular and Metabolic Diseases, Toulouse, France. .,Université Toulouse III Paul-Sabatier, Toulouse, France.
| | | | - Vera Jankowski
- Institute for Molecular Cardiovascular Research (IMCAR), University Hospital RWTH Aachen, Aachen, Germany
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37
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Sanchez-Niño MD, Fernandez-Fernandez B, Ortiz A. Klotho, the elusive kidney-derived anti-ageing factor. Clin Kidney J 2020; 13:125-127. [PMID: 32297880 PMCID: PMC7147303 DOI: 10.1093/ckj/sfz125] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2019] [Accepted: 08/09/2019] [Indexed: 12/17/2022] Open
Abstract
Chronic kidney disease (CKD) is one of the fastest growing causes of death worldwide. Only early diagnosis will allow prevention of both CKD progression and the negative impact of CKD on all-cause and cardiovascular mortality. Klotho is a protein produced by the kidneys that has anti-ageing and phosphaturic properties, preventing excess positive phosphate balance. There is evidence that Klotho downregulation is one of the earliest consequences of kidney injury. Thus the development of reliable assays to monitor Klotho levels may allow an early diagnosis of CKD and monitoring the impact of therapies aimed at preserving Klotho expression or at preventing CKD progression. However, the performance of Klotho assays has been suboptimal so far. In this issue of Clinical Kidney Journal, Neyra et al. explore methods to improve the reliability of Klotho assays.
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Affiliation(s)
- Maria Dolores Sanchez-Niño
- IIS-Fundacion Jimenez Diaz, School of Medicine, Universidad Autonoma de Madrid; Fundacion Renal Iñigo Alvarez de Toledo-IRSIN and REDINREN, Madrid, Spain
| | - Beatriz Fernandez-Fernandez
- IIS-Fundacion Jimenez Diaz, School of Medicine, Universidad Autonoma de Madrid; Fundacion Renal Iñigo Alvarez de Toledo-IRSIN and REDINREN, Madrid, Spain
| | - Alberto Ortiz
- IIS-Fundacion Jimenez Diaz, School of Medicine, Universidad Autonoma de Madrid; Fundacion Renal Iñigo Alvarez de Toledo-IRSIN and REDINREN, Madrid, Spain
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Vitko D, Cho PS, Kostel SA, DiMartino SE, Cabour LD, Migliozzi MA, Logvinenko T, Warren PG, Froehlich JW, Lee RS. Characterizing Patients with Recurrent Urinary Tract Infections in Vesicoureteral Reflux: A Pilot Study of the Urinary Proteome. Mol Cell Proteomics 2020; 19:456-466. [PMID: 31896675 PMCID: PMC7050111 DOI: 10.1074/mcp.ra119.001873] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2019] [Revised: 12/25/2019] [Indexed: 01/23/2023] Open
Abstract
Recurrent urinary tract infections (UTIs) pose a significant burden on the health care system. Underlying mechanisms predisposing children to UTIs and associated changes in the urinary proteome are not well understood. We aimed to investigate the urinary proteome of a subset of children who have vesicoureteral reflux (VUR) and recurrent UTIs because of their risk of developing infection-related renal damage. Improving diagnostic modalities to identify UTI risk factors would significantly alter the clinical management of children with VUR. We profiled the urinary proteomes of 22 VUR patients with low grade VUR (1-3 out of 5), a history of recurrent UTIs, and renal scarring, comparing them to those obtained from 22 age-matched controls. Urinary proteins were analyzed by mass spectrometry followed by protein quantitation based on spectral counting. Of the 2,551 proteins identified across both cohorts, 964 were robustly quantified, as defined by meeting criteria with spectral count (SC) ≥2 in at least 7 patients in either VUR or control cohort. Eighty proteins had differential expression between the two cohorts, with 44 proteins significantly up-regulated and 36 downregulated (q <0.075, FC ≥1.2). Urinary proteins involved in inflammation, acute phase response (APR), modulation of extracellular matrix (ECM), and carbohydrate metabolism were altered among the study cohort.
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Affiliation(s)
- Dijana Vitko
- Department of Urology, Boston Children's Hospital, Boston, Massachusetts
| | - Patricia S Cho
- Department of Urology, Boston Children's Hospital, Boston, Massachusetts; Department of Urology, University of Massachusetts Medical School, Worcester, Massachusetts
| | - Stephen A Kostel
- Department of Urology, Boston Children's Hospital, Boston, Massachusetts
| | | | - Lily D Cabour
- Department of Urology, Boston Children's Hospital, Boston, Massachusetts
| | | | - Tanya Logvinenko
- Department of Urology, Boston Children's Hospital, Boston, Massachusetts
| | - Peter G Warren
- Department of Urology, Boston Children's Hospital, Boston, Massachusetts
| | - John W Froehlich
- Department of Urology, Boston Children's Hospital, Boston, Massachusetts
| | - Richard S Lee
- Department of Urology, Boston Children's Hospital, Boston, Massachusetts.
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Sirolli V, Pieroni L, Di Liberato L, Urbani A, Bonomini M. Urinary Peptidomic Biomarkers in Kidney Diseases. Int J Mol Sci 2019; 21:E96. [PMID: 31877774 PMCID: PMC6982248 DOI: 10.3390/ijms21010096] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2019] [Revised: 12/16/2019] [Accepted: 12/19/2019] [Indexed: 12/20/2022] Open
Abstract
In order to effectively develop personalized medicine for kidney diseases we urgently need to develop highly accurate biomarkers for use in the clinic, since current biomarkers of kidney damage (changes in serum creatinine and/or urine albumin excretion) apply to a later stage of disease, lack accuracy, and are not connected with molecular pathophysiology. Analysis of urine peptide content (urinary peptidomics) has emerged as one of the most attractive areas in disease biomarker discovery. Urinary peptidome analysis allows the detection of short and long-term physiological or pathological changes occurring within the kidney. Urinary peptidomics has been applied extensively for several years now in renal patients, and may greatly improve kidney disease management by supporting earlier and more accurate detection, prognostic assessment, and prediction of response to treatment. It also promises better understanding of kidney disease pathophysiology, and has been proposed as a "liquid biopsy" to discriminate various types of renal disorders. Furthermore, proteins being the major drug targets, peptidome analysis may allow one to evaluate the effects of therapies at the protein signaling pathway level. We here review the most recent findings on urinary peptidomics in the setting of the most common kidney diseases.
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Affiliation(s)
- Vittorio Sirolli
- Nephrology and Dialysis Unit, Department of Medicine, G. d’Annunzio University, Chieti-Pescara, SS.Annunziata Hospital, Via dei Vestini, 66013 Chieti, Italy; (V.S.); (L.D.L.)
| | - Luisa Pieroni
- Proteomics and Metabonomics Unit, IRCCS Fondazione Santa Lucia, 00179 Rome, Italy;
| | - Lorenzo Di Liberato
- Nephrology and Dialysis Unit, Department of Medicine, G. d’Annunzio University, Chieti-Pescara, SS.Annunziata Hospital, Via dei Vestini, 66013 Chieti, Italy; (V.S.); (L.D.L.)
| | - Andrea Urbani
- Institute of Biochemistry and Clinical Biochemistry, Università Cattolica del Sacro Cuore, 00168 Rome, Italy
- Department of Laboratory Diagnostic and Infectious Diseases, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, 00168 Rome, Italy
| | - Mario Bonomini
- Nephrology and Dialysis Unit, Department of Medicine, G. d’Annunzio University, Chieti-Pescara, SS.Annunziata Hospital, Via dei Vestini, 66013 Chieti, Italy; (V.S.); (L.D.L.)
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Kira S, Mitsui T, Miyamoto T, Ihara T, Nakagomi H, Hashimoto Y, Takamatsu H, Tanahashi M, Takeda M, Tsuchiya S, Sawada N, Takeda M. Urinary metabolites identified using metabolomic analysis as potential biomarkers of nocturia in elderly men. World J Urol 2019; 38:2563-2569. [DOI: 10.1007/s00345-019-03042-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2019] [Accepted: 11/25/2019] [Indexed: 12/31/2022] Open
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Gagnebin Y, Pezzatti J, Lescuyer P, Boccard J, Ponte B, Rudaz S. Combining the advantages of multilevel and orthogonal partial least squares data analysis for longitudinal metabolomics: Application to kidney transplantation. Anal Chim Acta 2019; 1099:26-38. [PMID: 31986274 DOI: 10.1016/j.aca.2019.11.050] [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] [Received: 03/22/2019] [Revised: 11/15/2019] [Accepted: 11/21/2019] [Indexed: 11/29/2022]
Abstract
Kidney transplantation is one of the renal replacement options in patients suffering from end-stage renal disease (ESRD). After a transplant, patient follow-up is essential and is mostly based on immunosuppressive drug levels control, creatinine measurement and kidney biopsy in case of a rejection suspicion. The extensive analysis of metabolite levels offered by metabolomics might improve patient monitoring, help in the surveillance of the restoration of a "normal" renal function and possibly also predict rejection. The longitudinal follow-up of those patients with repeated measurements is useful to understand changes and decide whether an intervention is necessary. The time modality, therefore, constitutes a specific dimension in the data structure, requiring dedicated consideration for proper statistical analysis. The handling of specific data structures in metabolomics has received strong interest in recent years. In this work, we demonstrated the recently developed ANOVA multiblock OPLS (AMOPLS) to efficiently analyse longitudinal metabolomic data by considering the intrinsic experimental design. Indeed, AMOPLS combines the advantages of multilevel approaches and OPLS by separating between and within individual variations using dedicated predictive components, while removing most uncorrelated variations in the orthogonal component(s), thus facilitating interpretation. This modelling approach was applied to a clinical cohort study aiming to evaluate the impact of kidney transplantation over time on the plasma metabolic profile of graft patients and donor volunteers. A dataset of 266 plasma metabolites was identified using an LC-MS multiplatform analytical setup. Two separate AMOPLS models were computed: one for the recipient group and one for the donor group. The results highlighted the benefits of transplantation for recipients and the relatively low impacts on blood metabolites of donor volunteers.
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Affiliation(s)
- Yoric Gagnebin
- Institute of Pharmaceutical Sciences of Western Switzerland, University of Geneva, Geneva, Switzerland
| | - Julian Pezzatti
- Institute of Pharmaceutical Sciences of Western Switzerland, University of Geneva, Geneva, Switzerland
| | - Pierre Lescuyer
- Department of Genetic and Laboratory Medicine, Geneva University Hospitals (HUG), Geneva, Switzerland
| | - Julien Boccard
- Institute of Pharmaceutical Sciences of Western Switzerland, University of Geneva, Geneva, Switzerland
| | - Belen Ponte
- Service of Nephrology, Geneva University Hospitals (HUG), Geneva, Switzerland
| | - Serge Rudaz
- Institute of Pharmaceutical Sciences of Western Switzerland, University of Geneva, Geneva, Switzerland.
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Kašička V. Recent developments in capillary and microchip electroseparations of peptides (2017–mid 2019). Electrophoresis 2019; 41:10-35. [DOI: 10.1002/elps.201900269] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2019] [Revised: 10/08/2019] [Accepted: 10/19/2019] [Indexed: 12/14/2022]
Affiliation(s)
- Václav Kašička
- Institute of Organic Chemistry and BiochemistryCzech Academy of Sciences Prague 6 Czechia
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Dubin RF, Rhee EP. Proteomics and Metabolomics in Kidney Disease, including Insights into Etiology, Treatment, and Prevention. Clin J Am Soc Nephrol 2019; 15:404-411. [PMID: 31636087 PMCID: PMC7057308 DOI: 10.2215/cjn.07420619] [Citation(s) in RCA: 86] [Impact Index Per Article: 17.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
In this review of the application of proteomics and metabolomics to kidney disease research, we review key concepts, highlight illustrative examples, and outline future directions. The proteome and metabolome reflect the influence of environmental exposures in addition to genetic coding. Circulating levels of proteins and metabolites are dynamic and modifiable, and thus amenable to therapeutic targeting. Design and analytic considerations in proteomics and metabolomics studies should be tailored to the investigator's goals. For the identification of clinical biomarkers, adjustment for all potential confounding variables, particularly GFR, and strict significance thresholds are warranted. However, this approach has the potential to obscure biologic signals and can be overly conservative given the high degree of intercorrelation within the proteome and metabolome. Mass spectrometry, often coupled to up-front chromatographic separation techniques, is a major workhorse in both proteomics and metabolomics. High-throughput antibody- and aptamer-based proteomic platforms have emerged as additional, powerful approaches to assay the proteome. As the breadth of coverage for these methodologies continues to expand, machine learning tools and pathway analyses can help select the molecules of greatest interest and categorize them in distinct biologic themes. Studies to date have already made a substantial effect, for example elucidating target antigens in membranous nephropathy, identifying a signature of urinary peptides that adds prognostic information to urinary albumin in CKD, implicating circulating inflammatory proteins as potential mediators of diabetic nephropathy, demonstrating the key role of the microbiome in the uremic milieu, and highlighting kidney bioenergetics as a modifiable factor in AKI. Additional studies are required to replicate and expand on these findings in independent cohorts. Further, more work is needed to understand the longitudinal trajectory of select protein and metabolite markers, perform transomics analyses within merged datasets, and incorporate more kidney tissue-based investigation.
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Affiliation(s)
- Ruth F Dubin
- Division of Nephrology, San Francisco Veterans Affairs Medical Center, University of California, San Francisco, California; and
| | - Eugene P Rhee
- Nephrology Division and Endocrine Unit, Massachusetts General Hospital, Boston, Massachusetts
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Siwy J, Mischak H, Zürbig P. Proteomics and personalized medicine: a focus on kidney disease. Expert Rev Proteomics 2019; 16:773-782. [DOI: 10.1080/14789450.2019.1659138] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Affiliation(s)
- Justyna Siwy
- R & D, Mosaiques Diagnostics GmbH, Hannover, Germany
| | - Harald Mischak
- R & D, Mosaiques Diagnostics GmbH, Hannover, Germany
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | - Petra Zürbig
- R & D, Mosaiques Diagnostics GmbH, Hannover, Germany
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Zürbig P, Siwy J, Mischak H. Emerging urine-based proteomic biomarkers as valuable tools in the management of chronic kidney disease. Expert Rev Mol Diagn 2019; 19:853-856. [DOI: 10.1080/14737159.2019.1657406] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Affiliation(s)
| | | | - Harald Mischak
- Mosaiques Diagnostics GmbH, Hannover, Germany
- Institute of Cardiovascular and Medical Sciences University of Glasgow, Glasgow, UK
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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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Unbiased data analytic strategies to improve biomarker discovery in precision medicine. Drug Discov Today 2019; 24:1735-1748. [PMID: 31158511 DOI: 10.1016/j.drudis.2019.05.018] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2019] [Revised: 04/23/2019] [Accepted: 05/28/2019] [Indexed: 12/25/2022]
Abstract
Omics technologies promised improved biomarker discovery for precision medicine. The foremost problem of discovered biomarkers is irreproducibility between patient cohorts. From a data analytics perspective, the main reason for these failures is bias in statistical approaches and overfitting resulting from batch effects and confounding factors. The keys to reproducible biomarker discovery are: proper study design, unbiased data preprocessing and quality control analyses, and a knowledgeable application of statistics and machine learning algorithms. In this review, we discuss study design and analysis considerations and suggest standards from an expert point-of-view to promote unbiased decision-making in biomarker discovery in precision medicine.
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Thornton Snider J, Sullivan J, van Eijndhoven E, Hansen MK, Bellosillo N, Neslusan C, O’Brien E, Riley R, Seabury S, Kasiske BL. Lifetime benefits of early detection and treatment of diabetic kidney disease. PLoS One 2019; 14:e0217487. [PMID: 31150444 PMCID: PMC6544227 DOI: 10.1371/journal.pone.0217487] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2018] [Accepted: 05/13/2019] [Indexed: 01/02/2023] Open
Abstract
OBJECTIVES Diabetic kidney disease (DKD) is a frequent complication of diabetes with potentially devastating consequences that may be prevented or delayed. This study aimed to estimate the health and economic benefit of earlier diagnosis and treatment of DKD. METHODS Life expectancy and medical spending for people with diabetes were modeled using The Health Economics Medical Innovation Simulation (THEMIS). THEMIS uses data from the Health and Retirement Study to model cohorts of individuals over age 50 to project population-level lifetime health and economic outcomes. DKD status was imputed based on diagnoses and laboratory values in the National Health and Nutrition Examination Survey. We simulated the implementation of a new biomarker identifying people with diabetes at an elevated risk of DKD and DKD patients at risk of rapid progression. RESULTS Compared to baseline, the prevalence of DKD declined 5.1% with a novel prognostic biomarker test, while the prevalence of diabetes with stage 5 chronic kidney disease declined 3.0%. Consequently, people with diabetes gained 0.2 years in life expectancy, while per-capita annual medical spending fell by 0.3%. The estimated cost was $12,796 per life-year gained and $25,842 per quality-adjusted life-year. CONCLUSIONS A biomarker test that allows earlier treatment reduces DKD prevalence and slows DKD progression, thereby increasing life expectancy among people with diabetes while raising healthcare spending by less than one percent.
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Affiliation(s)
| | - Jeffrey Sullivan
- Precision Health Economics, Los Angeles, CA, United States of America
| | | | - Michael K. Hansen
- Janssen Research and Development, Spring House, PA, United States of America
| | | | - Cheryl Neslusan
- Janssen Global Services, Raritan, NJ, United States of America
| | - Ellen O’Brien
- Janssen Global Services, Raritan, NJ, United States of America
| | - Ralph Riley
- Janssen Global Services, Raritan, NJ, United States of America
| | - Seth Seabury
- Precision Health Economics, Los Angeles, CA, United States of America
| | - Bertram L. Kasiske
- Hennepin County Medical Center, Minneapolis, MN, United States of America
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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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50
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