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Yozgat I, Cakır U, Serdar MA, Sahin S, Sezerman OU, Nemutlu E, Baykal AT, Serteser M. Longitudinal non-targeted metabolomic profiling of urine samples for monitoring of kidney transplantation patients. Ren Fail 2024; 46:2300736. [PMID: 38213228 PMCID: PMC10791079 DOI: 10.1080/0886022x.2023.2300736] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Accepted: 12/26/2023] [Indexed: 01/13/2024] Open
Abstract
The assessment of kidney function within the first year following transplantation is crucial for predicting long-term graft survival. This study aimed to develop a robust and accurate model using metabolite profiles to predict early long-term outcomes in patient groups at the highest risk of early graft loss. A group of 61 kidney transplant recipients underwent thorough monitoring during a one-year follow-up period, which included a one-week hospital stay and follow-up assessments at three and six months. Based on their 12-month follow-up serum creatinine levels: Group 2 had levels exceeding 1.5 mg/dl, while Group 1 had levels below 1.5 mg/dl. Metabolites were detected by mass spectrometer and first pre-processed. Univariate and multivariate statistical analyses were employed to identify significant differences between the two groups. Nineteen metabolites were found to differ significantly in the 1st week, and seventeen metabolites in the 3rd month (adjusted p-value < 0.05, quality control (QC) < 30, a fold change (FC) > 1.1 or a FC < 0.91, Variable Influence on Projection (VIP) > 1). However, no significant differences were observed in the 6th month. These distinctive metabolites mainly belonged to lipid, fatty acid, and amino acid categories. Ten models were constructed using a backward conditional approach, with the best performance seen in model 5 for Group 2 at the 1st-week mark (AUC 0.900) and model 3 at the 3rd-month mark (AUC 0.924). In conclusion, the models developed in the early stages may offer potential benefits in the management of kidney transplant patients.
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Affiliation(s)
- Ihsan Yozgat
- Department of Medical Biotechnology, Institute of Health Sciences, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey
| | - Ulkem Cakır
- Department of Nephrology, Acibadem University School of Medicine, Istanbul, Turkey
| | | | - Sevgi Sahin
- Department of Nephrology, Acibadem University School of Medicine, Istanbul, Turkey
| | - Osman Ugur Sezerman
- Department of Biostatistics and Medical Informatics, Faculty of Medicine, Acibadem University, Istanbul, Turkey
| | - Emirhan Nemutlu
- Faculty of Pharmacy, Department of Analytical Chemistry, Hacettepe University, Ankara, Türkiye
| | - Ahmet Tarik Baykal
- Department of Medical Biochemistry, Faculty of Medicine, Acibadem University, Istanbul, Turkey
| | - Mustafa Serteser
- Department of Medical Biochemistry, Faculty of Medicine, Acibadem University, Istanbul, Turkey
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2
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Xiang G, Yang L, Qin J, Wang S, Zhang Y, Yang S. Revealing the potential bioactive components and mechanism of Qianhua Gout Capsules in the treatment of gouty arthritis through network pharmacology, molecular docking and pharmacodynamic study strategies. Heliyon 2024; 10:e30983. [PMID: 38770346 PMCID: PMC11103544 DOI: 10.1016/j.heliyon.2024.e30983] [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: 01/08/2024] [Revised: 05/08/2024] [Accepted: 05/08/2024] [Indexed: 05/22/2024] Open
Abstract
Recent clinical studies have confirmed the effectiveness of Qianhua Gout Capsules (QGC) in the treatment of gouty arthritis (GA). However, the specific regulatory targets and mechanisms of action of QGC are still unclear. To address this gap, we utilized network pharmacology, molecular docking, and pharmacodynamic approaches to investigate the bioactive components and associated mechanisms of QGC in the treatment of GA. By employing UPLC-Q Exactive-MS, we identified the compounds present in QGC, with active ingredients defined as those with oral bioavailability ≥30 % and drug similarity ≥0.18. Subsequently, the targets of these active compounds were determined using the TCMSP database, while GA-related targets were identified from DisGeNET, GeneCards, TTD, OMIM, and DrugBank databases. Further analysis including PPI analysis, GO analysis, and KEGG pathway enrichment was conducted on the targets. Validation of the predicted results was performed using a GA rat model, evaluating pathological changes, inflammatory markers, and pathway protein expression. Our results revealed a total of 130 components, 44 active components, 16 potential shared targets, GO-enriched terms, and 47 signaling pathways related to disease targets. Key active ingredients included quercetin, kaempferol, β-sitosterol, luteolin, and wogonin. The PPI analysis highlighted five targets (PPARG, IL-6, MMP-9, IL-1β, CXCL-8) with the highest connectivity, predominantly enriched in the IL-17 signaling pathway. Molecular docking experiments demonstrated strong binding of CXCL8, IL-1β, IL-6, MMP9, and PPARG targets with the top five active compounds. Furthermore, animal experiments confirmed the efficacy of QGC in treating GA in rats, showing reductions in TNF-α, IL-6, and MDA levels, and increases in SOD levels in serum. In synovial tissues, QGC treatment upregulated CXCL8 and PPARG expression, while downregulating IL-1β, MMP9, and IL-6 expression. In conclusion, this study applied a network pharmacology approach to uncover the composition of QGC, predict its pharmacological interactions, and demonstrate its in vivo efficacy, providing insights into the anti-GA mechanisms of QGC. These findings pave the way for future investigations into the therapeutic mechanisms underlying QGC's effectiveness in the treatment of GA.
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Affiliation(s)
- Gelin Xiang
- National Traditional Chinese Medicine Clinical Research Base and Drug Research Center of the Affiliated Traditional Chinese Medicine Hospital of Southwest Medical University, Luzhou, China
- State Key Laboratory of Southwestern Chinese Medicine Resources, School of Ethnic Medicine of Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Luyin Yang
- National Traditional Chinese Medicine Clinical Research Base and Drug Research Center of the Affiliated Traditional Chinese Medicine Hospital of Southwest Medical University, Luzhou, China
- Institute of Integrated Chinese and Western Medicine, Southwest Medical University, Luzhou, China
| | - Jing Qin
- State Key Laboratory of Southwestern Chinese Medicine Resources, School of Ethnic Medicine of Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Shaohui Wang
- State Key Laboratory of Southwestern Chinese Medicine Resources, School of Ethnic Medicine of Chengdu University of Traditional Chinese Medicine, Chengdu, China
- Meishan Hospital of Chengdu University of Traditional Chinese Medicine, Meishan, China
| | - Yi Zhang
- State Key Laboratory of Southwestern Chinese Medicine Resources, School of Ethnic Medicine of Chengdu University of Traditional Chinese Medicine, Chengdu, China
- Meishan Hospital of Chengdu University of Traditional Chinese Medicine, Meishan, China
| | - Sijin Yang
- National Traditional Chinese Medicine Clinical Research Base and Drug Research Center of the Affiliated Traditional Chinese Medicine Hospital of Southwest Medical University, Luzhou, China
- Institute of Integrated Chinese and Western Medicine, Southwest Medical University, Luzhou, China
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Gao Z, Zhou W, Lv X, Wang X. Metabolomics as a Critical Tool for Studying Clinical Surgery. Crit Rev Anal Chem 2023; 54:2245-2258. [PMID: 36592066 DOI: 10.1080/10408347.2022.2162810] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
Metabolomics enables the analysis of metabolites within an organism, which offers the closest direct measurement of the physiological activity of the organism, and has advanced efforts to characterize metabolic states, identify biomarkers, and investigate metabolic pathways. A high degree of innovation in analytical techniques has promoted the application of metabolomics, especially in the study of clinical surgery. Metabolomics can be employed as a clinical testing method to maximize therapeutic outcomes, and has been applied in rapid diagnosis of diseases, timely postoperative monitoring, prognostic assessment, and personalized medicine. This review focuses on the use of mass spectrometry and nuclear magnetic resonance-based metabolomics in clinical surgery, including identifying metabolic changes before and after surgery, finding disease-associated biomarkers, and exploring the potential of personalized therapy. Challenges and opportunities of metabolomics in organ transplantation are also discussed, with a particular emphasis on metabolomics in donor organ evaluation and protection, prognostic outcome prediction, as well as postoperative adverse reaction monitoring. In the end, current limitations of metabolomics in clinical surgery and future research directions are presented.
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Affiliation(s)
- Zhenye Gao
- School of Pharmacy, Shanghai Jiao Tong University, Shanghai, P. R. China
| | - Wenxiu Zhou
- School of Pharmacy, Shanghai Jiao Tong University, Shanghai, P. R. China
| | - Xiaoyuan Lv
- School of Pharmacy, Shanghai Jiao Tong University, Shanghai, P. R. China
| | - Xin Wang
- School of Pharmacy, Shanghai Jiao Tong University, Shanghai, P. R. China
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Lim JH, Chung BH, Lee SH, Jung HY, Choi JY, Cho JH, Park SH, Kim YL, Kim CD. Omics-based biomarkers for diagnosis and prediction of kidney allograft rejection. Korean J Intern Med 2022; 37:520-533. [PMID: 35417937 PMCID: PMC9082440 DOI: 10.3904/kjim.2021.518] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/27/2021] [Accepted: 01/11/2022] [Indexed: 11/27/2022] Open
Abstract
Kidney transplantation is the preferred treatment for patients with end-stage kidney disease, because it prolongs survival and improves quality of life. Allograft biopsy is the gold standard for diagnosing allograft rejection. However, it is invasive and reactive, and continuous monitoring is unrealistic. Various biomarkers for diagnosing allograft rejection have been developed over the last two decades based on omics technologies to overcome these limitations. Omics technologies are based on a holistic view of the molecules that constitute an individual. They include genomics, transcriptomics, proteomics, and metabolomics. The omics approach has dramatically accelerated biomarker discovery and enhanced our understanding of multifactorial biological processes in the field of transplantation. However, clinical application of omics-based biomarkers is limited by several issues. First, no large-scale prospective randomized controlled trial has been conducted to compare omics-based biomarkers with traditional biomarkers for rejection. Second, given the variety and complexity of injuries that a kidney allograft may experience, it is likely that no single omics approach will suffice to predict rejection or outcome. Therefore, integrated methods using multiomics technologies are needed. Herein, we introduce omics technologies and review the latest literature on omics biomarkers predictive of allograft rejection in kidney transplant recipients.
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Affiliation(s)
- Jeong-Hoon Lim
- Department of Internal Medicine, Kyungpook National University Hospital, School of Medicine, Kyungpook National University, Daegu,
Korea
| | - Byung Ha Chung
- Department of Internal Medicine, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul,
Korea
| | - Sang-Ho Lee
- Department of Internal Medicine, College of Medicine, Kyung Hee University, Seoul,
Korea
| | - Hee-Yeon Jung
- Department of Internal Medicine, Kyungpook National University Hospital, School of Medicine, Kyungpook National University, Daegu,
Korea
| | - Ji-Young Choi
- Department of Internal Medicine, Kyungpook National University Hospital, School of Medicine, Kyungpook National University, Daegu,
Korea
| | - Jang-Hee Cho
- Department of Internal Medicine, Kyungpook National University Hospital, School of Medicine, Kyungpook National University, Daegu,
Korea
| | - Sun-Hee Park
- Department of Internal Medicine, Kyungpook National University Hospital, School of Medicine, Kyungpook National University, Daegu,
Korea
| | - Yong-Lim Kim
- Department of Internal Medicine, Kyungpook National University Hospital, School of Medicine, Kyungpook National University, Daegu,
Korea
| | - Chan-Duck Kim
- Department of Internal Medicine, Kyungpook National University Hospital, School of Medicine, Kyungpook National University, Daegu,
Korea
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Colas L, Royer AL, Massias J, Raux A, Chesneau M, Kerleau C, Guerif P, Giral M, Guitton Y, Brouard S. Urinary metabolomic profiling from spontaneous tolerant kidney transplanted recipients shows enrichment in tryptophan-derived metabolites. EBioMedicine 2022; 77:103844. [PMID: 35241402 PMCID: PMC9034456 DOI: 10.1016/j.ebiom.2022.103844] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Revised: 01/13/2022] [Accepted: 01/13/2022] [Indexed: 12/27/2022] Open
Abstract
Background Operational tolerance is the holy grail in solid organ transplantation. Previous reports showed that the urinary compartment of operationally tolerant recipients harbor a specific and unique profile. We hypothesized that spontaneous tolerant kidney transplanted recipients (KTR) would have a specific urinary metabolomic profile associated to operational tolerance. Methods We performed metabolomic profiling on urine samples from healthy volunteers, stable KTR under standard and minimal immunosuppression and spontaneous tolerant KTR using liquid chromatography in tandem with mass spectrometry. Supervised and unsupervised multivariate computational analyses were used to highlight urinary metabolomic profile and metabolite identification thanks to workflow4metabolomic platform. Findings The urinary metabolome was composed of approximately 2700 metabolites. Raw unsupervised clustering allowed us to separate healthy volunteers and tolerant KTR from others. We confirmed by two methods a specific urinary metabolomic signature in tolerant KTR mainly driven by kynurenic acid independent of immunosuppressive drugs, serum creatinine and gender. Interpretation Kynurenic acid and tryptamine enrichment allowed the identification of putative pathways and metabolites associated with operational tolerance like IDO, GRP35 and AhR and indole alkaloids. Funding This study was supported by the ANR, IRSRPL and CHU de Nantes.
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Affiliation(s)
- Luc Colas
- CHU Nantes, INSERM, Center for Research in Transplantation and Translational Immunology, UMR 1064, ITUN, Centre Hospitalier, Nantes Université, 30 bd Jean Monnet, Nantes F-44000, France.
| | - Anne-Lise Royer
- MELISA Core Facility, Oniris, INRΑE, Nantes F-44307, France; Laboratoire d'Etude des Résidus et Contaminants dans les Aliments (LABERCA), Oniris, INRAE, Nantes F-44307, France.
| | - Justine Massias
- MELISA Core Facility, Oniris, INRΑE, Nantes F-44307, France; Laboratoire d'Etude des Résidus et Contaminants dans les Aliments (LABERCA), Oniris, INRAE, Nantes F-44307, France.
| | - Axel Raux
- MELISA Core Facility, Oniris, INRΑE, Nantes F-44307, France; Laboratoire d'Etude des Résidus et Contaminants dans les Aliments (LABERCA), Oniris, INRAE, Nantes F-44307, France.
| | - Mélanie Chesneau
- CHU Nantes, INSERM, Center for Research in Transplantation and Translational Immunology, UMR 1064, ITUN, Centre Hospitalier, Nantes Université, 30 bd Jean Monnet, Nantes F-44000, France.
| | - Clarisse Kerleau
- CHU Nantes, Service de Néphrologie-Immunologie Clinique, Nantes Université, Nantes, France.
| | - Pierrick Guerif
- CHU Nantes, Service de Néphrologie-Immunologie Clinique, Nantes Université, Nantes, France.
| | - Magali Giral
- CHU Nantes, INSERM, Center for Research in Transplantation and Translational Immunology, UMR 1064, ITUN, Centre Hospitalier, Nantes Université, 30 bd Jean Monnet, Nantes F-44000, France; CHU Nantes, Service de Néphrologie-Immunologie Clinique, Nantes Université, Nantes, France; Centre d'Investigation Clinique en Biothérapie, Centre de Ressources Biologiques (CRB), Nantes, France.
| | - Yann Guitton
- MELISA Core Facility, Oniris, INRΑE, Nantes F-44307, France; Laboratoire d'Etude des Résidus et Contaminants dans les Aliments (LABERCA), Oniris, INRAE, Nantes F-44307, France.
| | - Sophie Brouard
- CHU Nantes, INSERM, Center for Research in Transplantation and Translational Immunology, UMR 1064, ITUN, Centre Hospitalier, Nantes Université, 30 bd Jean Monnet, Nantes F-44000, France; CHU Nantes, Service de Néphrologie-Immunologie Clinique, Nantes Université, Nantes, France; Labex IGO, Nantes, France.
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Lai X, Zheng X, Mathew JM, Gallon L, Leventhal JR, Zhang ZJ. Tackling Chronic Kidney Transplant Rejection: Challenges and Promises. Front Immunol 2021; 12:661643. [PMID: 34093552 PMCID: PMC8173220 DOI: 10.3389/fimmu.2021.661643] [Citation(s) in RCA: 45] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2021] [Accepted: 04/27/2021] [Indexed: 01/09/2023] Open
Abstract
Despite advances in post-transplant management, the long-term survival rate of kidney grafts and patients has not improved as approximately forty percent of transplants fails within ten years after transplantation. Both immunologic and non-immunologic factors contribute to late allograft loss. Chronic kidney transplant rejection (CKTR) is often clinically silent yet progressive allogeneic immune process that leads to cumulative graft injury, deterioration of graft function. Chronic active T cell mediated rejection (TCMR) and chronic active antibody-mediated rejection (ABMR) are classified as two principal subtypes of CKTR. While significant improvements have been made towards a better understanding of cellular and molecular mechanisms and diagnostic classifications of CKTR, lack of early detection, differential diagnosis and effective therapies continue to pose major challenges for long-term management. Recent development of high throughput cellular and molecular biotechnologies has allowed rapid development of new biomarkers associated with chronic renal injury, which not only provide insight into pathogenesis of chronic rejection but also allow for early detection. In parallel, several novel therapeutic strategies have emerged which may hold great promise for improvement of long-term graft and patient survival. With a brief overview of current understanding of pathogenesis, standard diagnosis and challenges in the context of CKTR, this mini-review aims to provide updates and insights into the latest development of promising novel biomarkers for diagnosis and novel therapeutic interventions to prevent and treat CKTR.
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Affiliation(s)
- Xingqiang Lai
- Comprehensive Transplant Center, Northwestern University Feinberg School of Medicine, Chicago, IL, United States
- Department of Surgery, Northwestern University Feinberg School of Medicine, Chicago, IL, United States
- Organ Transplant Center, the Second Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Xin Zheng
- Department of Urology, Beijing Youan Hospital, Capital Medical University, Beijing, China
| | - James M. Mathew
- Comprehensive Transplant Center, Northwestern University Feinberg School of Medicine, Chicago, IL, United States
- Department of Surgery, Northwestern University Feinberg School of Medicine, Chicago, IL, United States
| | - Lorenzo Gallon
- Comprehensive Transplant Center, Northwestern University Feinberg School of Medicine, Chicago, IL, United States
- Department of Medicine, Nephrology, Northwestern University Feinberg School of Medicine, Chicago, IL, United States
| | - Joseph R. Leventhal
- Comprehensive Transplant Center, Northwestern University Feinberg School of Medicine, Chicago, IL, United States
- Department of Surgery, Northwestern University Feinberg School of Medicine, Chicago, IL, United States
| | - Zheng Jenny Zhang
- Comprehensive Transplant Center, Northwestern University Feinberg School of Medicine, Chicago, IL, United States
- Department of Surgery, Northwestern University Feinberg School of Medicine, Chicago, IL, United States
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Kalantari S, Chashmniam S, Nafar M, Samavat S, Rezaie D, Dalili N. A Noninvasive Urine Metabolome Panel as Potential Biomarkers for Diagnosis of T Cell-Mediated Renal Transplant Rejection. OMICS-A JOURNAL OF INTEGRATIVE BIOLOGY 2021; 24:140-147. [PMID: 32176594 DOI: 10.1089/omi.2019.0158] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Acute T cell-mediated rejection (TCMR) is a major complication after renal transplantation. TCMR diagnosis is very challenging and currently depends on invasive renal biopsy and nonspecific markers such as serum creatinine. A noninvasive metabolomics panel could allow early diagnosis and improved accuracy and specificity. We report, in this study, on urine metabolome changes in renal transplant recipients diagnosed with TCMR, with a view to future metabolomics-based diagnostics in transplant medicine. We performed urine metabolomic analyses in three study groups: (1) 7 kidney transplant recipients with acute TCMR, (2) 15 kidney transplant recipients without rejection but with impaired kidney function, and (3) 6 kidney transplant recipients with stable renal function, using 1H-nuclear magnetic resonance. Multivariate modeling of metabolites suggested a diagnostic panel where the diagnostic accuracy of each metabolite was calculated by receiver operating characteristic curve analysis. The impaired metabolic pathways associated with TCMR were identified by pathway analysis. In all, a panel of nine differential metabolites encompassing nicotinamide adenine dinucleotide, 1-methylnicotinamide, cholesterol sulfate, gamma-aminobutyric acid (GABA), nicotinic acid, nicotinamide adenine dinucleotide phosphate, proline, spermidine, and alpha-hydroxyhippuric acid were identified as novel potential metabolite biomarkers of TCMR. Proline, spermidine, and GABA had the highest area under the curve (>0.7) and were overrepresented in the TCMR group. Nicotinate and nicotinamide metabolism was the most important pathway in TCMR. These findings call for clinical validation in larger study samples and suggest that urinary metabolomics warrants future consideration as a noninvasive research tool for TCMR diagnostic innovation.
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Affiliation(s)
- Shiva Kalantari
- Department of Nephrology, Chronic Kidney Disease Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Saeed Chashmniam
- Department of Chemistry, Sharif University of Technology, Tehran, Iran
| | - Mohsen Nafar
- Department of Nephrology, Chronic Kidney Disease Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Shiva Samavat
- Department of Nephrology, Urology-Nephrology Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Danial Rezaie
- Department of Nephrology, Shahid Labbafinejad Medical Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Nooshin Dalili
- Department of Nephrology, Shahid Labbafinejad Medical Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran
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Tryptophan Metabolism via Kynurenine Pathway: Role in Solid Organ Transplantation. Int J Mol Sci 2021; 22:ijms22041921. [PMID: 33671985 PMCID: PMC7919278 DOI: 10.3390/ijms22041921] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2021] [Revised: 02/10/2021] [Accepted: 02/11/2021] [Indexed: 01/01/2023] Open
Abstract
Solid organ transplantation is a gold standard treatment for patients suffering from an end-stage organ disease. Patient and graft survival have vastly improved during the last couple of decades; however, the field of transplantation still encounters several unique challenges, such as a shortage of transplantable organs and increasing pool of extended criteria donor (ECD) organs, which are extremely prone to ischemia-reperfusion injury (IRI), risk of graft rejection and challenges in immune regulation. Moreover, accurate and specific biomarkers, which can timely predict allograft dysfunction and/or rejection, are lacking. The essential amino acid tryptophan and, especially, its metabolites via the kynurenine pathway has been widely studied as a contributor and a therapeutic target in various diseases, such as neuropsychiatric, autoimmune disorders, allergies, infections and malignancies. The tryptophan-kynurenine pathway has also gained interest in solid organ transplantation and a variety of experimental studies investigating its role both in IRI and immune regulation after allograft implantation was first published. In this review, the current evidence regarding the role of tryptophan and its metabolites in solid organ transplantation is presented, giving insights into molecular mechanisms and into therapeutic and diagnostic/prognostic possibilities.
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Urinary Biomarkers for Diagnosis and Prediction of Acute Kidney Allograft Rejection: A Systematic Review. Int J Mol Sci 2020; 21:ijms21186889. [PMID: 32961825 PMCID: PMC7555436 DOI: 10.3390/ijms21186889] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2020] [Revised: 09/16/2020] [Accepted: 09/18/2020] [Indexed: 01/10/2023] Open
Abstract
Noninvasive tools for diagnosis or prediction of acute kidney allograft rejection have been extensively investigated in recent years. Biochemical and molecular analyses of blood and urine provide a liquid biopsy that could offer new possibilities for rejection prevention, monitoring, and therefore, treatment. Nevertheless, these tools are not yet available for routine use in clinical practice. In this systematic review, MEDLINE was searched for articles assessing urinary biomarkers for diagnosis or prediction of kidney allograft acute rejection published in the last five years (from 1 January 2015 to 31 May 2020). This review follows the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines. Articles providing targeted or unbiased urine sample analysis for the diagnosis or prediction of both acute cellular and antibody-mediated kidney allograft rejection were included, analyzed, and graded for methodological quality with a particular focus on study design and diagnostic test accuracy measures. Urinary C-X-C motif chemokine ligands were the most promising and frequently studied biomarkers. The combination of precise diagnostic reference in training sets with accurate validation in real-life cohorts provided the most relevant results and exciting groundwork for future studies.
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10
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Recent Advances on Biomarkers of Early and Late Kidney Graft Dysfunction. Int J Mol Sci 2020; 21:ijms21155404. [PMID: 32751357 PMCID: PMC7432796 DOI: 10.3390/ijms21155404] [Citation(s) in RCA: 39] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2020] [Revised: 07/22/2020] [Accepted: 07/27/2020] [Indexed: 02/06/2023] Open
Abstract
New biomarkers of early and late graft dysfunction are needed in renal transplant to improve management of complications and prolong graft survival. A wide range of potential diagnostic and prognostic biomarkers, measured in different biological fluids (serum, plasma, urine) and in renal tissues, have been proposed for post-transplant delayed graft function (DGF), acute rejection (AR), and chronic allograft dysfunction (CAD). This review investigates old and new potential biomarkers for each of these clinical domains, seeking to underline their limits and strengths. OMICs technology has allowed identifying many candidate biomarkers, providing diagnostic and prognostic information at very early stages of pathological processes, such as AR. Donor-derived cell-free DNA (ddcfDNA) and extracellular vesicles (EVs) are further promising tools. Although most of these biomarkers still need to be validated in multiple independent cohorts and standardized, they are paving the way for substantial advances, such as the possibility of accurately predicting risk of DGF before graft is implanted, of making a “molecular” diagnosis of subclinical rejection even before histological lesions develop, or of dissecting etiology of CAD. Identification of “immunoquiescent” or even tolerant patients to guide minimization of immunosuppressive therapy is another area of active research. The parallel progress in imaging techniques, bioinformatics, and artificial intelligence (AI) is helping to fully exploit the wealth of information provided by biomarkers, leading to improved disease nosology of old entities such as transplant glomerulopathy. Prospective studies are needed to assess whether introduction of these new sets of biomarkers into clinical practice could actually reduce the need for renal biopsy, integrate traditional tools, and ultimately improve graft survival compared to current management.
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11
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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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