The switch from proteasome to immunoproteasome is increased in circulating cells of patients with fast progressive immunoglobulin A nephropathy and associated with defective CD46 expression

The proteasome to immunoproteasome (iPS) switch consists of b1, b2 and b5 subunit replacement by low molecular weight protein 2 (LMP2), LMP7 and multicatalytic endopeptidase-like complex-1 (MECL1) subunits, resulting in a more efficient peptide preparation for major histocompatibility complex 1 (MHC-I) presentation. It is activated by toll-like receptor (TLR) agonists and interferons and may also be influenced by genetic variation. In a previous study we found an iPS upregulation in peripheral cells of patients with immunoglobulin A nephropathy (IgAN). We aimed to investigate in 157 IgAN patients enrolled through the multinational Validation Study of the Oxford Classification of IgAN (VALIGA) study the relationships between iPS switch and estimated glomerular filtration rate (eGFR) modifications from renal biopsy to sampling. Patients had a previous long follow-up (6.4 years in median) that allowed an accurate calculation of their slope of renal function decline. We also evaluated the effects of the PSMB8/PSMB9 locus (rs9357155) associated with IgAN in genome-wide association studies and the expression of messenger RNAs (mRNAs) encoding for TLRs and CD46, a C3 convertase inhibitor, acting also on T-regulatory cell promotion, found to have reduced expression in progressive IgAN. We detected an upregulation of LMP7/b5 and LMP2/b1 switches. We observed no genetic effect of rs9357155. TLR4 and TLR2 mRNAs were found to be significantly associated with iPS switches, particularly TLR4 and LMP7/b5 (P< 0.0001). The LMP7/b5 switch was significantly associated with the rate of eGFR loss (P= 0.026), but not with eGFR at biopsy. Fast progressors (defined as the loss of eGFR >75th centile, i.e. 1.91 mL/min/1.73 m2/year) were characterized by significantly elevated LMP7/b5 mRNA (P= 0.04) and low CD46 mRNA expression (P< 0.01). A multivariate logistic regression model, categorizing patients by different levels of kidney disease progression, showed a high prediction value for the combination of high LMP7/b5 and low CD46 expression

Defective gene expression of the membrane complement inhibitor CD46 in patients with progressive immunoglobulin A nephropathy

Background: Complement is thought to play a role in immunoglobulin A nephropathy (IgAN), though the activating mechanisms are unknown. This study focused on the gene expression of CD46 and CD55, two key molecules for regulating C3 convertase activity of lectin and alternative complement pathways at a cellular level. Methods: The transcriptional expression in peripheral white blood cells (WBCs) of CD46 and CD55 was investigated in 157 patients enrolled by the Validation of the Oxford Classification of IgAN group, looking for correlations with clinical and pathology features and estimated glomerular filtration rate (eGFR) modifications from renal biopsy to sampling. Patients had a previous median follow-up of 6.4 (interquartile range 2.8-10.7) years and were divided into progressors and non-progressors according to the median value of their velocity of loss of renal function per year (-0.41 mL/min/1.73 m2/year). Results: CD46 and CD55 messenger RNA (mRNA) expression in WBCs was not correlated with eGFR values or proteinuria at sampling. CD46 mRNA was significantly correlated with eGFR decline rate as a continuous outcome variable (P = 0.014). A significant difference was found in CD46 gene expression between progressors and non-progressors (P = 0.013). CD46 and CD55 mRNA levels were significantly correlated (P < 0.01), although no difference between progressors and non-progressors was found for CD55 mRNA values. The prediction of progression was increased when CD46 and CD55 mRNA expressions were added to clinical data at renal biopsy (eGFR, proteinuria and mean arterial blood pressure) and Oxford MEST-C (mesangial hypercellularity, endocapillary hypercellularity, segmental glomerulosclerosis, tubular atrophy/interstitial fibrosis, presence of any crescents) score. Conclusions: Patients with progressive IgAN showed lower expression of mRNA encoding for the complement inhibitory protein CD46, which may implicate a defective regulation of C3 convertase with uncontrolled complement activation

Is there long-term value of pathology scoring immmunoglobulin A nephropathy? A validation study of the Oxford Classification for IgA Nephropathy (VALIGA) update

Background. It is unknown whether renal pathology lesions in immunoglobulin A nephropathy (IgAN) correlate with renal outcomes over decades of follow-up.Methods. In 1130 patients of the original Validation Study of the Oxford Classification for IgA Nephropathy (VALIGA) cohort, we studied the relationship between the MEST score (mesangial hypercellularity, M; endocapillary hypercellularity, E; segmental glomerulosclerosis, S; tubular atrophy/interstitial fibrosis, T), crescents (C) and other histological lesions with both a combined renal endpoint [50% estimated glomerular filtration rate (eGFR) loss or kidney failure] and the rate of eGFR decline over a follow-up period extending to 35 years [median 7 years (interquartile range 4.1-10.8)].Results. In this extended analysis, MI, S1 and T1-T2 lesions as well as the whole MEST score were independently related with the combined endpoint (P < 0.01), and there was no effect modification by age for these associations, suggesting that they may be valid in children and in adults as well. Only T lesions were associated with the rate of eGFR loss in the whole cohort, whereas C showed this association only in patients not treated with immunosuppression. In separate prognostic analyses, the whole set of pathology lesions provided a gain in discrimination power over the clinical variables alone, which was similar at 5 years (+2.0%) and for the whole follow-up (+1.8%). A similar benefit was observed for risk reclassification analyses (+2.7% and +2.4%).Conclusion. Long-term follow-up analyses of the VALIGA cohort showed that the independent relationship between kidney biopsy findings and the risk of progression towards kidney failure in IgAN remains unchanged across all age groups and decades after the renal biopsy

Is there long-term value of pathology scoring in immunoglobulin A nephropathy? A validation study of the Oxford Classification for IgA Nephropathy (VALIGA) update

Background: It is unknown whether renal pathology lesions in immunoglobulin A nephropathy (IgAN) correlate with renal outcomes over decades of follow-up. Methods: In 1130 patients of the original Validation Study of the Oxford Classification for IgA Nephropathy (VALIGA) cohort, we studied the relationship between the MEST score (mesangial hypercellularity, M; endocapillary hypercellularity, E; segmental glomerulosclerosis, S; tubular atrophy/interstitial fibrosis, T), crescents (C) and other histological lesions with both a combined renal endpoint [50% estimated glomerular filtration rate (eGFR) loss or kidney failure] and the rate of eGFR decline over a follow-up period extending to 35 years [median 7 years (interquartile range 4.1-10.8)]. Results: In this extended analysis, M1, S1 and T1-T2 lesions as well as the whole MEST score were independently related with the combined endpoint (P &lt; 0.01), and there was no effect modification by age for these associations, suggesting that they may be valid in children and in adults as well. Only T lesions were associated with the rate of eGFR loss in the whole cohort, whereas C showed this association only in patients not treated with immunosuppression. In separate prognostic analyses, the whole set of pathology lesions provided a gain in discrimination power over the clinical variables alone, which was similar at 5 years (+2.0%) and for the whole follow-up (+1.8%). A similar benefit was observed for risk reclassification analyses (+2.7% and +2.4%). Conclusion: Long-term follow-up analyses of the VALIGA cohort showed that the independent relationship between kidney biopsy findings and the risk of progression towards kidney failure in IgAN remains unchanged across all age groups and decades after the renal biopsy

Development and testing of an artificial intelligence tool for predicting end-stage kidney disease in patients with immunoglobulin A nephropathy

We have developed an artificial neural network prediction model for end-stage kidney disease (ESKD) in patients with primary immunoglobulin A nephropathy (IgAN) using a retrospective cohort of 948 patients with IgAN. Our tool is based on a two-step procedure of a classifier model that predicts ESKD, and a regression model that predicts development of ESKD over time. The classifier model showed a performance value of 0.82 (area under the receiver operating characteristic curve) in patients with a follow-up of five years, which improved to 0.89 at the ten-year follow-up. Both models had a higher recall rate, which indicated the practicality of the tool. The regression model showed a mean absolute error of 1.78 years and a root mean square error of 2.15 years. Testing in an independent cohort of 167patients with IgAN found successful results for 91% of the patients. Comparison of our system with other mathematical models showed the highest discriminant Harrell C index at five- and ten-years follow-up (81% and 86%, respectively), paralleling the lowest Akaike information criterion values (355.01 and 269.56, respectively). Moreover, our system was the best calibrated model indicating that the predicted and observed outcome probabilities did not significantly differ. Finally, the dynamic discrimination indexes of our artificial neural network, expressed as the weighted average of time-dependent areas under the curve calculated at one and two years, were 0.80 and 0.79, respectively. Similar results were observed over a 25-year follow-up period. Thus, our tool identified individuals who were at a high risk of developing ESKD due to IgAN and predicted the time-to-event endpoint. Accurate prediction is an important step toward introduction of a therapeutic strategy for improving clinical outcomes

Development and testing of an artificial intelligence tool for predicting end-stage kidney disease in patients with immunoglobulin A nephropathy

We have developed an artificial neural network prediction model for end-stage kidney disease (ESKD) in patients with primary immunoglobulin A nephropathy (IgAN) using a retrospective cohort of 948 patients with IgAN. Our tool is based on a two-step procedure of a classifier model that predicts ESKD, and a regression model that predicts development of ESKD over time. The classifier model showed a performance value of 0.82 (area under the receiver operating characteristic curve) in patients with a follow-up of five years, which improved to 0.89 at the ten-year follow-up. Both models had a higher recall rate, which indicated the practicality of the tool. The regression model showed a mean absolute error of 1.78 years and a root mean square error of 2.15 years. Testing in an independent cohort of 167patients with IgAN found successful results for 91% of the patients. Comparison of our system with other mathematical models showed the highest discriminant Harrell C index at five- and ten-years follow-up (81% and 86%, respectively), paralleling the lowest Akaike information criterion values (355.01 and 269.56, respectively). Moreover, our system was the best calibrated model indicating that the predicted and observed outcome probabilities did not significantly differ. Finally, the dynamic discrimination indexes of our artificial neural network, expressed as the weighted average of time-dependent areas under the curve calculated at one and two years, were 0.80 and 0.79, respectively. Similar results were observed over a 25-year follow-up period. Thus, our tool identified individuals who were at a high risk of developing ESKD due to IgAN and predicted the time-to-event endpoint. Accurate prediction is an important step toward introduction of a therapeutic strategy for improving clinical outcomes