IgA腎症

BACKGROUND: Sparsentan has demonstrated significant antiproteinuric effects in randomized trials of IgA nephropathy (IgAN). However, real-world evidence remains scarce and is largely limited to short-term follow-up. Data on the durability of the antiproteinuric response in routine clinical practice are still lacking. METHODS: This multicenter retrospective study included patients with biopsy-proven IgAN treated with sparsentan in routine clinical practice across Spanish centers. Patients were eligible if they initiated sparsentan outside a clinical trial and had at least 3 months of follow-up. The primary outcome was the proportion of patients achieving a >50% reduction in proteinuria at 3 months (responders). Secondary outcomes included changes in proteinuria and kidney function at 6 and 12 months, as well as safety. RESULTS: A total of 41 patients were included. The median age was 42 years, with a median baseline estimated glomerular filtration rate (eGFR) of 44 ml/min/1.73 m2 and 95% receiving concomitant sodium-glucose cotransporter-2 (SGLT2) inhibitors. Median baseline proteinuria was 1163 mg/24 h. At 3 months, proteinuria decreased to 772 mg/24 h (median reduction 44.1%), with 51% of patients achieving a >50% reduction. Among patients with extended follow-up, the antiproteinuric effect was sustained at 6 months (median reduction 46.9%) and persisted at 12 months (median reduction 38.9%), despite increased variability. Notably, kidney function remained stable throughout follow-up, despite a moderately reduced baseline eGFR. No clinically relevant hyperkalemia or severe adverse events were observed. CONCLUSIONS: In this multicenter real-world Spanish cohort, sparsentan was associated with a sustained reduction in proteinuria in patients with biopsy-proven IgAN, maintained up to 12 months, along with preserved kidney function even in those with moderately reduced baseline eGFR, and a favorable safety profile. These findings support the effectiveness of sparsentan on top of contemporary standard of care and provide early evidence of sustained benefit in routine clinical practice.

Background/Objectives: IgA nephropathy (IgAN) is a highly heterogeneous glomerular disease with variable clinical presentation and response to therapy. Standard histopathology provides a static assessment and may not fully reflect dynamic podocyte injury. The objective of this case series was to characterize distinct clinical phenotypes of IgAN and explore the relationship between urinary protein composition assessed by the urine albumin-to-protein ratio (uAPR) and ultrastructural glomerular injury. Methods: We retrospectively analyzed three patients with distinct clinical phenotypes of biopsy-proven IgA nephropathy to examine the relationship between urinary protein composition (uAPR), ultrastructural findings, treatment response, and clinical outcomes. Results: Case 1 demonstrated a podocytopathic phenotype resembling minimal change disease (MCD) with steroid sensitivity. Case 2 showed progression to focal segmental glomerulosclerosis (FSGS) despite stable renal function. Case 3 revealed persistent predominantly non-albumin proteinuria (uAPR 0.07-0.13) preceding biopsy-proven IgAN and resistance to multiple immunosuppressive regimens. Conclusions: Differences in uAPR were observed alongside distinct clinicopathological and ultrastructural phenotypes of IgA nephropathy. These observations suggest that urinary protein composition may provide complementary information on disease phenotype; however, its relationship with specific mechanisms of glomerular injury requires prospective validation.

BACKGROUND: The burden of chronic kidney disease (CKD) continues to grow, affecting over 850 million individuals globally. Current methods to precisely and definitively classify CKD still rely on renal biopsy, a procedure with a 5.1% rate of major complications, and further cost and access complications in low-resource settings. The retina, containing the only accessible microvasculature for direct and non-invasive visualization, shares deep developmental and structural features with, and biologically plausible pathogenic overlap with, the kidney (see Sect. 3 for the distinction between established and hypothesized components of this relationship). Oculomics, an emerging discipline that incorporates AI to analyze retinal images to identify systemic disease, has shown promising results for binary CKD screening, with AUC scores of 0.83-0.93; this is distinct from, and should not be conflated with, the prediction of specific renal pathological categories discussed below. A 2025 study introducing the Kidney Intelligent Diagnosis System (KIDS) was among the first to demonstrate that specific renal pathological categories-IgA nephropathy, idiopathic membranous nephropathy, arterionephrosclerosis, diabetic nephropathy, and a combined idiopathic minimal change disease/focal segmental glomerulosclerosis category-could be predicted from retinal images using five separate binary prediction tasks, reporting AUC values of 0.790-0.932 (internal and, for a subset, external validation; hybrid image-plus-clinical-data models performed at the higher end of this range). This is best regarded as an early proof-of-concept for a non-invasive risk-stratification tool, conceptually described in this review as a 'virtual renal biopsy'-a metaphor for a proposed research framework, not a claim of diagnostic equivalence with tissue histopathology (Meng et al.'s DeepDKD model had earlier used retinal images to distinguish biopsy-defined diabetic from non-diabetic kidney disease, so KIDS is best described as an early multi-category model rather than the first retinal-AI study in this space). AIM: This narrative review aims to consolidate various biological, technological, and clinical components of AI-driven retinal phenotyping and outline the path toward non-invasive prediction of kidney pathological categories. This includes the aspects of continuous progression from binary screening of CKD towards predicting specific histopathologies while considering the current state of explainability of AI, the performance metrics beyond AUC that are required for clinical deployment, and offering a detailed clinical research roadmap. METHODS: Narrative synthesis was utilized to integrate data on CKD and deep learning, retinal vascular research, research on retinal-renal connections, AI explainability, and the KIDS model. A structured search of PubMed/MEDLINE, Embase, Scopus, and Google Scholar was performed for English-language, peer-reviewed original studies, systematic reviews, and clinical guidelines relevant to retinal-renal biology, oculomics, and AI-based renal pathology prediction; representative search terms, eligibility criteria, and the handling of preprints are detailed in Sect. 2. The data were organized by biological plausibility, evolution of modeling, integration of imaging technologies, metrics required for clinical validation, and research in translational barriers. CONCLUSIONS: The combination of the biological plausibility of a retinal signature of renal injury, the advances in oculomics, AI, and early multi-category models such as KIDS lays a preliminary foundation for research toward non-invasive prediction of kidney pathological categories. In order to advance this research agenda, numerous multidisciplinary clinical studies are required along with the integration of different imaging technologies, rigorous reporting of calibration and clinically relevant performance metrics, and the creation of ethical and regulatory frameworks. The 'virtual renal biopsy' concept will not replace histopathology and is not yet supported by evidence sufficient for clinical deployment; if the underlying research agenda is executed rigorously, it may in time provide an adjunctive, non-invasive risk-stratification tool for the hundreds of millions of patients who do not have access to renal histopathological diagnosis.

BACKGROUND: Pathological renal injuries after liver transplantation are multifactorial, yet the clinicopathological characteristics of glomerulonephritis presenting as nephrotic syndrome remain unclear. This study aimed to investigate its clinicopathological features, treatment, and outcomes. METHODS: We retrospectively identified 12 patients with NS who underwent kidney biopsy after liver transplantation and investigated their clinicopathological findings, treatment, and clinical course. RESULTS: At the time of biopsy, the mean time after liver transplantation was 3.4 years, and mean age was 58.9 years. Mean estimated glomerular filtration rate (eGFR) and urinary protein-to-creatinine ratio (UP/UCr) were 40.1 ± 15.6 mL/min/1.73 m2 and 6.74 ± 3.01 g/gCr, respectively. The pathological diagnoses were: IgA nephropathy (IgA-N) in 5 patients (42%), membranoproliferative glomerulonephritis (MPGN) in 2 patients, diabetic nephropathy in 2 patients, thrombotic microangiopathy in 1 patient, pauci-immune crescentic glomerulonephritis (CrGN) in 1 patient, and membranous nephropathy in 1 patient. All patients were treated with induction or dose escalation of angiotensin II receptor blockers, and patients with IgA-N or CrGN received steroid pulse therapy; In patients with IgA-N, mean UP/UCr significantly decreased from 9.01 ± 3.32 g/gCr to 1.45 ± 1.40 g/gCr after 2 years. During the 5.8-year follow-up period, 8 patients (67%) achieved incomplete remission (< 3.5 g/gCr), but 3 patients (one each with IgA-N, MPGN and CrGN) progressed to end-stage kidney disease. CONCLUSIONS: The pathological findings of NS after liver transplantation in this selected cohort are heterogeneous, therefore kidney biopsy might be valuable for evaluating the condition and guiding the selection of appropriate therapeutic strategies.