HLA-D and PLA2R1 risk alleles associate with recurrent primary membranous nephropathy in kidney transplant recipients

Berchtold, Lena; Letouzé, Éric; Alexander, Mariam P.; Canaud, Guillaume; Logt, Anne-Els van de; Hamilton, Patrick; Mousson, Christiane; Vuiblet, Vincent; Moyer, Ann M.; Guibert, Sylvain; Mrázová, Petra; Lévi, Charlène; Dubois, Valérie; Cruzado, Josep M.; Torres, Armando; Gandhi, Manish J.; Yousfi, Nadhir; Tesař, Vladimı́r; Viklický, Ondřej; Hourmant, Maryvonne; Moulin, Anne‐Marie; Rieu, Philippe; Choukroun, Gabriel; Legendre, Christophe; Wetzels, Jack F.M.; Brenchley, Paul; Castán, José Aurelio Ballarín; Dębiec, Hanna; Ronco, Pierre

doi:10.1016/j.kint.2020.08.007

Cited by 28 publications

(25 citation statements)

References 30 publications

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“…35 Finally, HLA-A2 and HLA-DR12 may not be mechanistically involved in recurrent MN but represent haplotypes associated with recurrent MN via linkage disequilibrium. 36 HLA-DR12 is in linkage disequilibrium with HLA-DQA1*0501, which is not consistent with a study by Berchtold et al 10 that identified 2 donor noncoding HLA-D SNPs associated with recurrent MN, none of which were in linkage disequilibrium with MN risk alleles such as HLA-DQA1*0501. Although Berchtold et al 10 performed molecular HLA typing and validated their results in a replication cohort, their analysis did not include class I HLA loci.…”

Section: Discussioncontrasting

confidence: 65%

“…Variables were chosen by supervised feature selection using penalized regression and ensemble tree machine learning techniques, which addressed the issues of overfitting and multiple testing associated with stepwise feature selection in our highdimensional dataset. 27,28 Although multiple studies have identified risk factors for recurrent MN after kidney transplantation such as detectable pretransplant anti-PLA2R autoantibody, steroid-free immunosuppression, and recipient HLA-A3 and donor risk HLA-D and PLA2R1 alleles, 3,6,9,10,29 prediction models to identify patients at high risk of recurrent MN (or other forms of glomerulonephritis) using routine pretransplant clinical data have not been comprehensively evaluated. These predictive approaches may inform clinicians on patients requiring closer monitoring of proteinuria, anti-PLA2R antibody titer, and/or protocol allograft biopsies to detect recurrent MN posttransplantation.…”

Section: Continued Next Pagementioning

confidence: 99%

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Predictive Models for Recurrent Membranous Nephropathy After Kidney Transplantation

Chung

Blazek

Teixeira‐Pinto

et al. 2022

Transplantation Direct

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Background. Recurrent membranous nephropathy (MN) posttransplantation affects 35% to 50% of kidney transplant recipients (KTRs) and accounts for 50% allograft loss 5 y after diagnosis. Predictive factors for recurrent MN may include HLA-D risk alleles, but other factors have not been explored with certainty. Methods. The Australian and New Zealand Dialysis and Transplant registry was used to develop 3 prediction models for recurrent MN (Group Least Absolute Shrinkage and Selection Operator [LASSO], penalized Cox regression, and random forest), which were tuned using tenfold cross-validation in a derivation cohort with complete HLA data. KTRs with MN but incomplete HLA data formed the validation cohort. Model performance was evaluated using area under the receiver operating characteristic curve (AUC-ROC). Results. One hundred ninety-nine KTRs with MN were included, and 25 (13%) had recurrent MN (median follow-up 5.9 y). The AUC-ROCs for Group LASSO, penalized Cox regression, and random forest models were 0.85 (95% confidence interval, 0.76-0.94), 0.91 (0.85-0.96), and 0.62 (0.57-0.69), respectively, in the derivation cohort, with moderate agreement in selected variables between the models (55%-70%). In their validation cohorts, the AUC-ROCs for Group LASSO and penalized Cox regression were 0.60 (0.49-0.70) and 0.73 (0.59-0.86), respectively. Variables of importance chosen by all models included recipient HLA-A2, donor HLA-DR12, donor-recipient HLA-B65, and HLA-DR12 match. Conclusions. A penalized Cox regression performed reasonably for predicting recurrent MN and was superior to Group LASSO and random forest models. These models highlighted the importance of donor-recipient HLA characteristics to recurrent MN, although validation in larger datasets is required.

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Section: Discussioncontrasting

confidence: 65%

Section: Continued Next Pagementioning

confidence: 99%

Predictive Models for Recurrent Membranous Nephropathy After Kidney Transplantation

Chung

Blazek

Teixeira‐Pinto

et al. 2022

Transplantation Direct

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“…Also, genetic factors have been associated to MN risk of recurrence. For example, the presence of SNP mutations on HLA-D and PLA2R loci confer more risk of recurrence when presented by the donor ( 67 ). Most recipients with recurrent MN are under CNI treatment, an effective therapy in native kidneys.…”

Section: The Harmsmentioning

confidence: 99%

Chronic Kidney Allograft Disease: New Concepts and Opportunities

et al. 2021

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Chronic kidney disease (CKD) is increasing in most countries and kidney transplantation is the best option for those patients requiring renal replacement therapy. Therefore, there is a significant number of patients living with a functioning kidney allograft. However, progressive kidney allograft functional deterioration remains unchanged despite of major advances in the field. After the first post-transplant year, it has been estimated that this chronic allograft damage may cause a 5% graft loss per year. Most studies focused on mechanisms of kidney graft damage, especially on ischemia-reperfusion injury, alloimmunity, nephrotoxicity, infection and disease recurrence. Thus, therapeutic interventions focus on those modifiable factors associated with chronic kidney allograft disease (CKaD). There are strategies to reduce ischemia-reperfusion injury, to improve the immunologic risk stratification and monitoring, to reduce calcineurin-inhibitor exposure and to identify recurrence of primary renal disease early. On the other hand, control of risk factors for chronic disease progression are particularly relevant as kidney transplantation is inherently associated with renal mass reduction. However, despite progress in pathophysiology and interventions, clinical advances in terms of long-term kidney allograft survival have been subtle. New approaches are needed and probably a holistic view can help. Chronic kidney allograft deterioration is probably the consequence of damage from various etiologies but can be attenuated by kidney repair mechanisms. Thus, besides immunological and other mechanisms of damage, the intrinsic repair kidney graft capacity should be considered to generate new hypothesis and potential therapeutic targets. In this review, the critical risk factors that define CKaD will be discussed but also how the renal mechanisms of regeneration could contribute to a change chronic kidney allograft disease paradigm.

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“…Based on these, we suggested that the two genes might have a synergistic protective effect through PPARα regulation in the fatty acid metabolism pathway in IF/TA group, and the combined analysis of them might improve the diagnostic specificity. Moreover, FCGR2B, HLA-DQA2, and LTF are involved in tumor or organ transplantation [33][34][35]. It is reported that HLA-DQA2 is a HLA class II molecule expressed in the surface of antigen-presenting cells and involved in the recognition of peptide antigens by CD41 T cells [36].…”

Section: Discussionmentioning

confidence: 99%

The Potential Diagnostic Value of Immune-Related Genes in Interstitial Fibrosis and Tubular Atrophy after Kidney Transplantation

Yang

Shi

Chen

et al. 2022

Journal of Immunology Research

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Background. Inflammation within areas of interstitial fibrosis and tubular atrophy (IF/TA) is associated with kidney allograft failure. The aim of this study was to reveal new diagnostic markers of IF/TA based on bioinformatics analysis. Methods. Raw data of IF/TA samples after kidney transplantation and control samples after kidney transplantation were extracted from the Gene Expression Omnibus (GEO) database (GSE76882 and GSE120495 datasets), and genes that were differentially expressed between the two groups (DEGs) were screened. Gene Set Enrichment Analysis (GSEA), ESTIMATE and single sample GSEA (ssGSEA), least absolute shrinkage and selection operator (LASSO) regression analysis, and competing endogenous RNA (ceRNA) network were used to analyze the data. Results. The results of GSEA revealed that multiple immune-related pathways were enriched in the IF/TA group, and subsequent immune landscape analysis also showed that the IF/TA group had higher immune and stromal scores and up to 15 types of immune cells occupied them, such as B cells, cytotoxic cells, and T cells. LASSO regression analysis selected 6 (including ANGPTL3, APOH, LTF, FCGR2B, HLA-DQA2, and EGF) out of 14 DE-IRGs as diagnostic genes to construct a diagnostic model. Then, receiver operating characteristic (ROC) curve analysis showed the powerful diagnostic value of the model, and the area under the curve (AUC) of a single diagnostic gene was greater than 0.75. The results of ingenuity pathway analysis (IPA) also indicated that DEGs were involved in the immune system and kidney disease-related pathways. Finally, we found multiple miRNAs that could regulate diagnostic genes from the ceRNA network. Conclusion. This study identified 6 IF/TA-related genes, which might be used as a new diagnosis model in the clinical practice.

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HLA-D and PLA2R1 risk alleles associate with recurrent primary membranous nephropathy in kidney transplant recipients

Cited by 28 publications

References 30 publications

Predictive Models for Recurrent Membranous Nephropathy After Kidney Transplantation

Predictive Models for Recurrent Membranous Nephropathy After Kidney Transplantation

Chronic Kidney Allograft Disease: New Concepts and Opportunities

The Potential Diagnostic Value of Immune-Related Genes in Interstitial Fibrosis and Tubular Atrophy after Kidney Transplantation

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