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Robertson H, Kim HJ, Li J, Robertson N, Robertson P, Jimenez-Vera E, Ameen F, Tran A, Trinh K, O'Connell PJ, Yang JYH, Rogers NM, Patrick E. Decoding the hallmarks of allograft dysfunction with a comprehensive pan-organ transcriptomic atlas. Nat Med 2024:10.1038/s41591-024-03030-6. [PMID: 38890530 DOI: 10.1038/s41591-024-03030-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Accepted: 04/29/2024] [Indexed: 06/20/2024]
Abstract
The pathogenesis of allograft (dys)function has been increasingly studied using 'omics'-based technologies, but the focus on individual organs has created knowledge gaps that neither unify nor distinguish pathological mechanisms across allografts. Here we present a comprehensive study of human pan-organ allograft dysfunction, analyzing 150 datasets with more than 12,000 samples across four commonly transplanted solid organs (heart, lung, liver and kidney, n = 1,160, 1,241, 1,216 and 8,853 samples, respectively) that we leveraged to explore transcriptomic differences among allograft dysfunction (delayed graft function, acute rejection and fibrosis), tolerance and stable graft function. We identified genes that correlated robustly with allograft dysfunction across heart, lung, liver and kidney transplantation. Furthermore, we developed a transfer learning omics prediction framework that, by borrowing information across organs, demonstrated superior classifications compared to models trained on single organs. These findings were validated using a single-center prospective kidney transplant cohort study (a collective 329 samples across two timepoints), providing insights supporting the potential clinical utility of our approach. Our study establishes the capacity for machine learning models to learn across organs and presents a transcriptomic transplant resource that can be employed to develop pan-organ biomarkers of allograft dysfunction.
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Affiliation(s)
- Harry Robertson
- School of Mathematics and Statistics, The University of Sydney, Camperdown, New South Wales, Australia
- Sydney Precision Data Science Centre, The University of Sydney, Camperdown, New South Wales, Australia
- Centre for Transplant and Renal Research, Westmead Institute for Medical Research, Westmead, New South Wales, Australia
- Charles Perkins Centre, The University of Sydney, Camperdown, New South Wales, Australia
| | - Hani Jieun Kim
- Sydney Precision Data Science Centre, The University of Sydney, Camperdown, New South Wales, Australia
- Computational Systems Biology Group, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, New South Wales, Australia
- Kinghorn Cancer Centre and Cancer Research Theme, Garvan Institute of Medical Research, Darlinghurst, New South Wales, Australia
- St. Vincent's Clinical School, Faculty of Medicine, University of New South Wales, Sydney, New South Wales, Australia
| | - Jennifer Li
- Centre for Transplant and Renal Research, Westmead Institute for Medical Research, Westmead, New South Wales, Australia
- Department of Renal and Transplantation Medicine, Westmead Hospital, Westmead, New South Wales, Australia
| | - Nicholas Robertson
- School of Mathematics and Statistics, The University of Sydney, Camperdown, New South Wales, Australia
- Sydney Precision Data Science Centre, The University of Sydney, Camperdown, New South Wales, Australia
- Charles Perkins Centre, The University of Sydney, Camperdown, New South Wales, Australia
- Laboratory of Data Discovery for Health Limited (D24H), Science Park, Hong Kong SAR, China
| | - Paul Robertson
- Department of Renal and Transplantation Medicine, Westmead Hospital, Westmead, New South Wales, Australia
| | - Elvira Jimenez-Vera
- Centre for Transplant and Renal Research, Westmead Institute for Medical Research, Westmead, New South Wales, Australia
| | - Farhan Ameen
- School of Mathematics and Statistics, The University of Sydney, Camperdown, New South Wales, Australia
- Sydney Precision Data Science Centre, The University of Sydney, Camperdown, New South Wales, Australia
- Charles Perkins Centre, The University of Sydney, Camperdown, New South Wales, Australia
| | - Andy Tran
- School of Mathematics and Statistics, The University of Sydney, Camperdown, New South Wales, Australia
- Sydney Precision Data Science Centre, The University of Sydney, Camperdown, New South Wales, Australia
- Charles Perkins Centre, The University of Sydney, Camperdown, New South Wales, Australia
| | - Katie Trinh
- Centre for Transplant and Renal Research, Westmead Institute for Medical Research, Westmead, New South Wales, Australia
| | - Philip J O'Connell
- Centre for Transplant and Renal Research, Westmead Institute for Medical Research, Westmead, New South Wales, Australia
- Department of Renal and Transplantation Medicine, Westmead Hospital, Westmead, New South Wales, Australia
- Faculty of Medicine and Health, University of Sydney, Camperdown, New South Wales, Australia
| | - Jean Y H Yang
- School of Mathematics and Statistics, The University of Sydney, Camperdown, New South Wales, Australia
- Sydney Precision Data Science Centre, The University of Sydney, Camperdown, New South Wales, Australia
- Charles Perkins Centre, The University of Sydney, Camperdown, New South Wales, Australia
- Laboratory of Data Discovery for Health Limited (D24H), Science Park, Hong Kong SAR, China
| | - Natasha M Rogers
- Centre for Transplant and Renal Research, Westmead Institute for Medical Research, Westmead, New South Wales, Australia
- Department of Renal and Transplantation Medicine, Westmead Hospital, Westmead, New South Wales, Australia
- Faculty of Medicine and Health, University of Sydney, Camperdown, New South Wales, Australia
| | - Ellis Patrick
- School of Mathematics and Statistics, The University of Sydney, Camperdown, New South Wales, Australia.
- Sydney Precision Data Science Centre, The University of Sydney, Camperdown, New South Wales, Australia.
- Centre for Transplant and Renal Research, Westmead Institute for Medical Research, Westmead, New South Wales, Australia.
- Charles Perkins Centre, The University of Sydney, Camperdown, New South Wales, Australia.
- Laboratory of Data Discovery for Health Limited (D24H), Science Park, Hong Kong SAR, China.
- Centre for Cancer Research, Westmead Institute for Medical Research, Westmead, New South Wales, Australia.
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Carrillo J, Del Bello A, Sallusto F, Delas A, Colombat M, Mansuy JM, Izopet J, Kamar N, Belliere J. Effect of steroid pulses in severe BK virus allograft nephropathy with extensive interstitial inflammation. Transpl Infect Dis 2024; 26:e14260. [PMID: 38547002 DOI: 10.1111/tid.14260] [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: 08/21/2023] [Revised: 02/09/2024] [Accepted: 02/12/2024] [Indexed: 04/12/2024]
Abstract
INTRODUCTION As there is no specific antiviral treatment currently available for BK polyomavirus associated nephropathy (BKVAN), its management relies on immunosuppression reduction in kidney transplant patients. Data on efficacy of steroid pulses in this indication are lacking. METHODS We performed a retrospective monocenter study on 64 patients diagnosed with biopsy-proven BKVAN. Patients within the "pulse group" (n = 37) received IV methylprednisolone 10 mg/kg 3 days consecutively. In the "low dose" steroid group (n = 27), patients were continued oral prednisone 5 mg daily. RESULTS Mean follow up was 78 months in the steroid pulse group and 56 months in the low dose group (p = 0.15). Mean eGFR values at diagnosis were comparable, as well as other demographic characteristics. Mean BK plasma viral load was higher in "pulse" than in "low dose" steroid group. Pulse group had higher inflammation and tubulitis (p < 0.05). Graft loss reached 57% in the "pulse" group versus 41% in the "low dose" group, p = 0.20. Rejection events were similar. No major adverse event was statistically associated with steroid pulse, including infections, cancer, and de novo diabetes. CONCLUSION No significant differences were found in the evolution of both groups of patients, despite patients receiving "pulse" steroids were identified as the most severe sharing higher BK viral load and more frequent active lesions on histology.
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Affiliation(s)
- Julien Carrillo
- Department of Nephrology and Organ Transplantation, Referral Centre for Rare Kidney Diseases, French Intensive Care Renal Network, University Hospital of Toulouse, Toulouse, France
| | - Arnaud Del Bello
- Department of Nephrology and Organ Transplantation, Referral Centre for Rare Kidney Diseases, French Intensive Care Renal Network, University Hospital of Toulouse, Toulouse, France
| | - Federico Sallusto
- Department of Urology and Kidney Transplantation, CHU Rangueil, Toulouse, France
| | - Audrey Delas
- Department of Pathology, University Hospital of Toulouse, University Cancer Institute of Toulouse, Toulouse, France
| | - Magali Colombat
- Department of Pathology, University Hospital of Toulouse, University Cancer Institute of Toulouse, Toulouse, France
- Université Toulouse III, Toulouse, France
| | - Jean Michel Mansuy
- Laboratory of Virology, Institut fédératif de Biologie, University Hospital of Toulouse, Toulouse, France
| | - Jacques Izopet
- Laboratory of Virology, Institut fédératif de Biologie, University Hospital of Toulouse, Toulouse, France
| | - Nassim Kamar
- Department of Nephrology and Organ Transplantation, Referral Centre for Rare Kidney Diseases, French Intensive Care Renal Network, University Hospital of Toulouse, Toulouse, France
- Université Toulouse III, Toulouse, France
- INSERM UMR1291-CNRS UMR5051, Toulouse, France
| | - Julie Belliere
- Department of Nephrology and Organ Transplantation, Referral Centre for Rare Kidney Diseases, French Intensive Care Renal Network, University Hospital of Toulouse, Toulouse, France
- Université Toulouse III, Toulouse, France
- INSERM U1297, Institute of Metabolic and Cardiovascular Diseases, Toulouse, France
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The Pathological and Clinical Diversity of Acute Vascular Rejection in Kidney Transplantation. Transplantation 2022; 106:1666-1676. [PMID: 35266923 DOI: 10.1097/tp.0000000000004071] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
BACKGROUND Vascular rejection (VR) is characterized by arteritis, steroid resistance, and increased graft loss but is poorly described using modern diagnostics. METHODS We screened 3715 consecutive biopsies and retrospectively evaluated clinical and histological phenotypes of VR (n = 100) against rejection without arteritis (v0REJ, n = 540) and normal controls (n = 1108). RESULTS Biopsy sample size affected the likelihood of arterial sampling, VR diagnosis, and final Banff v scores (P < 0.001). Local v and cv scores were greatest in larger arteries (n = 258). VR comprised 15.6% of all rejection episodes, presented earlier (median 1.0 mo, interquartile range, 0.4-8 mo) with higher serum creatinine levels and inferior graft survival, versus v0REJ (P < 0.001). Early VR (≤1 mo) was common (54%) and predicted by sensitization, delayed function, and prior corticosteroid use, with associated acute dysfunction and optimal therapeutic response, independent of Banff v score. Late VR followed under-immunosuppression in 71.4% (noncompliance 38.8%, iatrogenic 32.6%), and was associated with chronic interstitial fibrosis, incomplete renal functional recovery and persistent inflammation using sequential histopathology. The etiology was "pure" antibody-mediated VR (n = 21), mixed VR (n = 36), and "pure" T cell-mediated VR (n = 43). Isolated VR (n = 34, Banff i < 1 without tubulitis) comprised 24 T cell-mediated VR and 10 antibody-mediated VR, presenting with mild renal dysfunction, minimal Banff acute scores, and better graft survival compared with inflamed VR. Interstitial inflammation influenced acute renal dysfunction and early treatment response, whereas chronic tubulointerstitial damage determined long-term graft loss. CONCLUSIONS VR is a heterogenous entity influenced by time-of-onset, pathophysiology, accompanying interstitial inflammation and fibrosis. Adequate histological sampling is essential for its accurate diagnostic classification and treatment.
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Ricaurte Archila L, Denic A, Mullan AF, Narasimhan R, Bogojevic M, Thompson RH, Leibovich BC, Sangaralingham SJ, Smith ML, Alexander MP, Rule AD. A Higher Foci Density of Interstitial Fibrosis and Tubular Atrophy Predicts Progressive CKD after a Radical Nephrectomy for Tumor. J Am Soc Nephrol 2021; 32:2623-2633. [PMID: 34531177 PMCID: PMC8722813 DOI: 10.1681/asn.2021020267] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2021] [Accepted: 05/22/2021] [Indexed: 02/04/2023] Open
Abstract
BACKGROUND Chronic tubulointerstitial injury on kidney biopsy is usually quantified by the percentage of cortex with interstitial fibrosis/tubular atrophy (IF/TA). Whether other patterns of IF/TA or inflammation in the tubulointerstitium have prognostic importance beyond percentage IF/TA is unclear. METHODS We obtained, stained, and digitally scanned full cortical thickness wedge sections of renal parenchyma from patients who underwent a radical nephrectomy for a tumor over 2000-2015, and morphometrically analyzed the tubulointerstitium of the cortex for percentage IF/TA, IF/TA density (foci per mm2 cortex), percentage subcapsular IF/TA, striped IF/TA, percentage inflammation (both within and outside IF/TA regions), and percentage subcapsular inflammation. Patients were followed with visits every 6-12 months. Progressive CKD was defined as dialysis, kidney transplantation, or 40% decline from the postnephrectomy eGFR. Cox models assessed the risk of CKD or noncancer mortality with morphometric measures of tubulointerstitial injury after adjustment for the percentage IF/TA and clinical characteristics. RESULTS Among 936 patients (mean age, 64 years; postnephrectomy baseline eGFR, 48 ml/min per 1.73m2), 117 progressive CKD events and 183 noncancer deaths occurred over a median 6.4 years. Higher IF/TA density predicted both progressive CKD and noncancer mortality after adjustment for percentage IF/TA and predicted progressive CKD after further adjustment for clinical characteristics. Independent of percentage IF/TA, age, and sex, higher IF/TA density correlated with lower eGFR, smaller nonsclerosed glomeruli, more global glomerulosclerosis, and smaller total cortical volume. CONCLUSIONS Higher density of IF/TA foci (a more scattered pattern with more and smaller foci) predicts higher risk of progressive CKD after radical nephrectomy compared with the same percentage of IF/TA but with fewer and larger foci.
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Affiliation(s)
| | - Aleksandar Denic
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota
| | - Aidan F. Mullan
- Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota
| | - Ramya Narasimhan
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota
| | - Marija Bogojevic
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota
| | | | | | | | - Maxwell L. Smith
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota
| | - Mariam P. Alexander
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Scottsdale, Arizona
| | - Andrew D. Rule
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota,Division of Epidemiology, Mayo Clinic, Rochester, Minnesota
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