A comparative study on the clinicopathological features and short-term prognosis of IgA-dominant infection-related glomerulonephritis and IgA nephropathy

Abstract

Background

IgA-dominant infection-related glomerulonephritis (IgA-IRGN) and primary IgA nephropathy (IgAN) share similar clinicopathological features, making differentiation challenging despite distinct therapeutic strategies. This study compares the clinicopathological characteristics and short-term prognoses of the two conditions to identify diagnostic differentiators.

Methods

This retrospective study included patients diagnosed with IgA-IRGN (n = 30) and IgAN (n = 120). We comparatively analyzed their clinical and pathological features, as well as the short-term prognostic differences. Univariate and multivariable logistic regression analyses were conducted to evaluate independent associations. Different pathological scoring systems were utilized to assess their diagnostic value. Short-term prognosis was evaluated at a 6-month follow-up, based on changes in the estimated glomerular filtration rate (eGFR) and the remission rate of proteinuria.

Results

Compared to IgAN, IgA-IRGN patients had higher mean arterial pressure, incidences of edema, acute kidney injury (AKI), and hypertension. Serum albumin, eGFR, and complement C3 were lower, while 24-hour proteinuria, neutrophil-to-albumin ratio (NAR), and neutrophil-to-C3 ratio (NC3r) were higher. Pathologically, IgA-IRGN showed diffuse endocapillary hypercellularity (100% vs. 2.5%) and universal subepithelial “hump-like” deposits (100% vs. 0.89%). Multivariable analysis revealed hypocomplementemia C3, AKI, and serum albumin could serve as non-invasive differentiating indicators. After incorporating pathological factors, hypocomplementemia C3, the Lupus Nephritis Activity Index (AI) score, and diffuse foot process effacement emerged as independent differentiating factors. IgA-IRGN patients demonstrated better short-term renal function recovery and higher proteinuria remission rate (P < 0.05).

Conclusions

Significant clinicopathological differences exist between IgA-IRGN and IgAN. Hypocomplementemia C3, AKI, low serum albumin, diffuse foot process effacement, and the AI score were independent indicators for differentiation. IgA-IRGN patients experience better short-term renal recovery and proteinuria remission than IgAN patients.

Supplementary Information

The online version contains supplementary material available at https://doi.org/10.1186/s12882-026-05208-1.

Introduction

Infectious diseases remain a major global public health concern with persistently high morbidity and mortality rates [1]. In adults, especially middle-aged and elderly males, the incidence of infection-related glomerulonephritis has been gradually increasing in recent years [2]. Endocapillary hypercellularity is the most common pathological manifestation. When immunopathological examination reveals a predominance of IgA deposition in glomeruli, the condition is defined as IgA-dominant infection-related glomerulonephritis (IgA-IRGN) [3, 4], which must be differentiated from primary IgA nephropathy (IgAN).

As the most common primary glomerulonephritis worldwide, IgAN is a major cause of chronic kidney disease and end-stage renal disease. The highest incidence was reported in East Asia, especially in China [5–7]. It is often preceded by a history of infection and is immunopathologically characterized by predominant IgA deposition in the glomerular mesangium on immunofluorescence. Its light microscopy manifestations are heterogeneous, typically presenting as mesangium-predominant proliferative lesions, with or without endocapillary hypercellularity [8].

Accurate differentiation between IgA-IRGN and IgAN is often hindered by several factors: occult infections in some patients, overlapping clinical and pathological features of the two diseases, and delayed pathological diagnosis in certain cases. Current diagnostic criteria fail to provide a clear distinction between them, yet their treatment regimens and prognostic outcomes differ significantly [9–11]. This study conducted a single-center retrospective analysis, aiming to identify reliable non-invasive clinical indicators and combined pathological predictors for the differential diagnosis of IgA-IRGN and IgAN, and to compare short-term renal outcomes to guide clinical management.

Materials and methods

Patients

Patients diagnosed with either IgA-IRGN or primary IgAN by renal biopsy at Peking University People’s Hospital between January 1, 2017, and June 1, 2025, were retrospectively enrolled.

IgA-IRGN was diagnosed in accordance with the criteria proposed by Nasr et al. [3], which require predominant IgA deposition on immunofluorescence (IF) and the fulfillment of at least three of the following five criteria: (1) clinical or laboratory evidence of infection prior to or concurrent with the onset of nephritis; (2) decreased serum complement levels; (3) histological findings of endocapillary proliferative and exudative glomerulonephritis; (4) codominant glomerular C3 staining on IF; (5) presence of hump-shaped subepithelial deposits on electron microscopy (EM).

Primary IgAN was diagnosed based on the predominant or co-dominant deposition of IgA on IF, with secondary IgAN excluded, such as Henoch-Schönlein purpura, lupus nephritis, alcoholic cirrhosis, and so on.

Patients with any of the following criteria were excluded: aged < 12 years; renal biopsy specimens containing less than 8 glomeruli; comorbidity with other primary or secondary kidney diseases; and incomplete clinicopathological data.

Considering the need to observe the clinicopathological differences between the two diseases, patients in the IgAN group were randomly matched in a 1:4 ratio based solely on the number of cases in the IgA-IRGN group, without matching based on specific characteristics.

Clinical and laboratory data

Baseline demographic and clinical data were collected during the first hospitalization for renal biopsy, including gender, age, height, weight, blood pressure (BP), comorbidities, and initial symptoms. Laboratory parameters included complete blood count, serum creatinine (sCr), urea, albumin, triglycerides, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), fasting blood glucose, immunoglobulins, complements, urinalysis, and 24-hour total urine protein (UTP). The estimated glomerular filtration rate (eGFR) was calculated using the CKD-EPI equation. Mean arterial pressure (MAP) was calculated as the diastolic blood pressure plus one-third of the pulse pressure (systolic blood pressure minus diastolic blood pressure). The neutrophil-to-albumin ratio (NAR), neutrophil-to-C3 ratio (NC3r), and body mass index (BMI) were calculated. AKI was identified by an absolute increase in SCr of ≥ 26.5 µmol/L within 48 h or a relative increase of ≥ 50% (1.5-fold) within 7 days before renal biopsy. Urine output criteria were not applied due to the retrospective nature of the study and the unavailability of data. Hypocomplementemia C3 was defined as a serum complement C3 level below 0.9 g/L.

Histopathological evaluation

All renal biopsy specimens were processed for light microscopy (LM), IF, and EM using standard laboratory techniques.

For IF analysis, 5 μm cryosections were stained with polyclonal fluorescein isothiocyanate (FITC)-conjugated antibodies against IgG, IgM, IgA, C3, and C1q (Dako, Denmark), respectively. The deposition intensity for immunoglobulins and complements was graded semi-quantitatively (negative [-], trace [+], 1 + to 4+), and the localization of deposits was recorded in detail. To compare the distribution of κ and λ light chains between the two diseases, immunofluorescence staining after pepsin-induced antigen retrieval was performed on patients’ FFPE tissues. All experimental conditions and exposure times were kept the same. ZEISS ZEN software was used to measure the mean fluorescence intensity of glomeruli, and the κ/λ fluorescence intensity ratio was calculated. Due to limited sample availability, this analysis was performed on all 30 IgA-IRGN patients and a matched subset of 30 IgAN patients (1:1 matched for age and sex).

For LM, kidney biopsy specimens were stained with hematoxylin and eosin (H&E), period acid-Schiff (PAS), Masson’s trichrome, and period acid-silver methenamine (PASM). Since no pathological scoring system has been established for IgA-IRGN, we adopted multiple validated scoring systems for assessment, including the Oxford Classification for IgAN (MEST-C classification) [12], and the NIH Lupus Nephritis Activity Index and Chronicity Index (AI and CI) scores [13]. Pathological scoring was independently performed by two senior renal pathologists who were blinded to the clinical data of the patients, and consensus was reached for discrepant results.

Ultrastructural evaluation was performed using a transmission electron microscope (Thermo Scientific, TECNAI SPIRIT, United States). Key EM findings were recorded, including the location of electron-dense deposits (EDDs), the presence of subepithelial “humps”, the degree of endocapillary proliferation, and the extent of podocyte foot process effacement.

Short-Term outcomes

Short-term renal outcomes were assessed by measuring eGFR and UTP during the 6-month post-treatment follow-up. The change in eGFR (ΔeGFR, calculated as the eGFR value at 6 months minus the baseline eGFR value) was used as the primary indicator to evaluate renal function changes, and the Mann-Whitney U test was used for comparison. Proteinuria remission was defined as a ≥ 30% reduction in UTP compared with the baseline level at the 6-month follow-up, and the Chi-square test was used for comparison.

Statistical methods

The missForest method was employed to impute missing data (when the missing rate < 10%). To maintain the independence of features between groups, data imputation was performed separately for the IgA-IRGN and IgAN groups using the missForest package (version 1.6.1) in R software, with parameters set as ntree = 100 and maxiter = 15. Continuous variables with a normal distribution were expressed as mean ± standard deviation and were compared between groups using the independent samples t-test. Non-normally distributed continuous variables were expressed as median (interquartile range) and compared using the Mann-Whitney U test. Categorical variables were expressed as counts (percentage) and compared using the Chi-square test. A two-sided P < 0.05 was considered statistically significant. First, multivariable logistic regression with forward stepwise selection (entry threshold: P < 0.1; retention criterion: P < 0.05) was performed to identify independent non-invasive factors associated with the differential diagnosis of the two groups. Then, a meaningful pathological scoring system was incorporated, and multivariable logistic regression was conducted again. All statistical analyses were conducted using SPSS 26.0 and R 4.5.1 software.

Results

Clinical characteristics

A total of 30 patients with IgA-IRGN and 120 patients with IgAN were included in the study. Among the IgA-IRGN patients, 7 met all 5 diagnostic criteria [3], 8 met criteria (1), (3), (4), and (5); 8 met criteria (2), (3), (4), and (5); and 7 met criteria (3), (4), and (5). The median age of the IgA-IRGN group was 38.5 years, and 63.3% were male. The median age of the IgAN group was 35.5 years, and 44.2% were male (Table 1).

Table 1.

Baseline data comparison between IgA-IRGN and IgAN

Variable	IgA-IRGN (n = 30)	IgAN (n = 120)	P value
Demographics
Male, n (%)	19 (63.3%)	53 (44.2%)	0.060
Age, years	38.5 (30.0, 56.5)	35.5 (29.0, 44.0)	0.157
BMI, kg/m2	23.2 (21.3, 25.3)	24.4 (22.3, 26.7)	0.070
MAP, mmHg	102 ± 11.7	96.9 ± 12.3	0.029*
Clinical Manifestations, n (%)
Gross hematuria	6 (20.0%)	30 (25.0%)	0.566
Edema	22 (73.3%)	30 (25.0%)	< 0.01**
AKI	11 (36.7%)	13 (10.8%)	< 0.01**
Comorbidities, n (%)
Hypertension	17 (56.7%)	37 (30.8%)	< 0.01**
Diabetes Mellitus	3 (10.0%)	8 (6.7%)	0.531
Smoking, n (%)	10 (33.3%)	27 (22.5%)	0.218
Laboratory Findings
WBC, ×109/L	6.25 (4.30, 8.00)	6.68 (5.50, 7.30)	0.604
Neutrophils, ×109/L	4.05 (2.70, 5.50)	3.76 (3.10, 4.90)	0.748
Neutrophil percentage, %	64.0 ± 9.70	60.2 ± 9.80	0.058
Hemoglobin, g/L	128 (105, 142)	133 (120, 147)	0.158
Platelets, ×109/L	238 ± 94.0	242 ± 60.2	0.824
Albumin, g/L	30.6 (26.1, 36.0)	38.4 (34.5, 41.7)	< 0.01**
Total Protein, g/L	58.0 (51.2, 66.5)	65.8 (60.5, 70.1)	< 0.01**
Urea, mmol/L	7.10 (5.80, 9.30)	5.10 (4.00, 6.70)	< 0.01**
Uric Acid, µmol/L	412 ± 103	393 ± 105	0.355
Creatinine, µmol/L	127 (77.8, 167)	84.0 (66.0, 99.8)	< 0.01**
eGFR, mL/min/1.73m2	54.1 (37.9, 96.6)	95.6 (65.4, 110)	< 0.01**
Triglycerides, mmol/L	1.24 (0.80, 1.80)	1.47 (1.10, 2.40)	0.038*
TC, mmol/L	4.73 (3.80, 5.70)	5.08 (4.30, 5.80)	0.257
LDL-C, mmol/L	2.91 (2.10, 3.80)	3.09 (2.50, 3.70)	0.256
HDL-C, mmol/L	1.06 (0.90, 1.40)	1.15 (1.00, 1.40)	0.298
IgG, g/L	10.4 (6.4, 12.6)	10.5 (8.5, 12.6)	0.549
IgA, g/L	2.79 ± 1.05	3.04 ± 1.11	0.260
IgM, g/L	0.98 (0.60, 1.40)	1.06 (0.70, 1.40)	0.491
Hypocomplementemia C3	15 (50%)	18 (15%)	< 0.01**
NAR, ×109/g	0.12 (0.08, 0.16)	0.10 (0.08, 0.12)	0.020*
NC3r, ×109/g	4.17 (3.10, 5.50)	3.58 (2.70, 4.30)	0.031*
Urine RBC, /µL	207 (48, 784)	114 (30, 331)	0.108
Urine WBC, /µL	24.8 (3.9, 81.3)	17.5 (7.0, 35.8)	0.172
Total urine protein, g/24 h	2.78 (1.50, 5.40)	1.25 (0.80, 2.60)	< 0.01**

Note: AKI, acute kidney injury; BMI, body mass index; MAP, mean arterial pressure; WBC, white blood cell; eGFR, estimated glomerular filtration rate; TC, Total Cholesterol; LDL-C, low-density lipoprotein cholesterol; HDL-C, high-density lipoprotein cholesterol; Hypocomplementemia C3, serum complement C3 < 0.9 g/L; NAR, neutrophil-to-albumin ratio; NC3r, neutrophil-to-C3 ratio; RBC, red blood cell. Normal ranges (for reference): WBC 3.5–9.5 × 10⁹/L, Neutrophils 1.8–6.3 × 10⁹/L, Hemoglobin 120–160 g/L (male) or 110–150 g/L (female), Platelets 125–350 × 10⁹/L, Albumin 40–55 g/L, Total Protein 65–85 g/L, Urea 2.6–7.5 mmol/L, Creatinine 44–104 µmol/L (male) or 44–88 µmol/L (female), Triglycerides < 1.7 mmol/L, TC < 6.2 mmol/L, LDL‑C < 3.4 mmol/L, HDL‑C > 1.03 mmol/L, IgG 8.6–17.4 g/L, IgA 1.0–4.2 g/L, IgM 0.5–2.8 g/L, Uric Acid 208–428 µmol/L (male) or 155–357 µmol/L (female). (* P < 0.05, ** P < 0.01)

Compared with the IgAN group, the IgA-IRGN group had a significantly higher mean arterial pressure (MAP), along with significantly higher incidences of hypertension, edema, acute kidney injury (AKI), and hypocomplementemia C3. Serum albumin, total protein, triglycerides, and eGFR were lower in the IgA-IRGN group, while sCr, UTP, NAR, and NC3r were significantly elevated (Fig. 1; Table 1).

Fig. 1.

Distinct Clinical Phenotypes of IgA-IRGN and IgAN. (a). Radar plot comparing clinical manifestations between IgA-IRGN and IgAN. (b). Quantitative comparison of clinical parameters between IgA-IRGN and IgAN. In the figure, sex, age, BMI, and the presence of diabetes mellitus showed no significant differences between the two groups, whereas all other variables were significantly different

In the IgA-IRGN group, pneumonia (26.7%) was the most common predisposing infection, followed by upper respiratory tract infections (13.3%), periodontitis (6.7%), Urinary tract infections (3.3%), and lower limb abscesses (3.3%); the infection site was unidentified in 46.7% of patients. Pathogenetic examinations revealed Legionella in 6.7% of IgA-IRGN patients, COVID-19 in 6.7%, ESBL-producing E. coli in 3.3%, and Staphylococcus in 3.3%, with no clearly identified pathogen in 80% of patients. The interval from infection onset to nephropathy manifestation ranged from 0 to 120 days. In the IgAN group, 15.8% of patients had a history of prodromal infection, predominantly of the upper respiratory tract, and most developed nephropathy within 0 to 3 days after infection. In the IgAN group, routine pathogen testing was not performed in most patients because prodromal infections were typically mild and did not require microbiological investigation; among the few patients who underwent testing, no specific pathogen was identified.

Pathological characteristics

LM findings showed that all IgA-IRGN cases (100%) presented with diffuse endocapillary proliferative glomerulonephritis, a lesion observed in only 2.5% of the IgAN cases. Analysis using MEST-C classification revealed a higher proportion of endocapillary hypercellularity (E) in the IgA-IRGN group, but lower proportion of mesangial hypercellularity (M), segmental glomerulosclerosis (S), and cellular/fibrocellular crescents (C) than those in the IgAN group. Additionally, the AI score was significantly higher in the IgA-IRGN group compared to the IgAN group (Table 2).

Table 2.

Comparison of pathological characteristics between IgA-IRGN and IgAN

Feature	IgA-IRGN (n = 30)	IgAN (n = 120)	P value
Diffuse endocapillary proliferative glomerulonephritis, n (%)	30 (100%)	3 (2.50%)	< 0.01**
Oxford Classification, n (%)
M1	15 (50.0%)	84 (70.0%)	0.039*
E1	30 (100%)	85 (70.8%)	< 0.01**
S1	9 (30.0%)	105 (87.5%)	< 0.01**
T1/2	10 (33.3%)	44 (36.7%)	0.734
C1/2	15 (50.0%)	84 (70.0%)	0.039*
AI score	10.0 (8.0, 12.3)	5.0 (3.0, 7.0)	< 0.01**
CI score	2.0 (2.0, 4.3)	3.0 (2.0, 5.0)	0.127
Immunofluorescence, n (%)
IgA	30 (100%)	120 (100%)	-
IgG	8 (26.7%)	12 (10.0%)	< 0.01**
IgM	26 (86.7%)	97 (80.8%)	0.457
C1q	9 (30.0%)	12 (10.0%)	< 0.01**
C3	30 (100%)	117 (98.0%)	0.382
κ/λ#	0.98 (0.87, 1.26)	0.89 (0.82, 0.97)	0.03*
κ/λ ≥ 1#	15 (50.0%)	4 (13.3%)	< 0.01**
Subepithelial “Hump-like” EDDs, n (%)	30 (100%)	1 (0.89%)	< 0.01**
Diffuse FPEs, n (%)	22 (73.3%)	11 (9.82%)	< 0.01**
Segmental FPEs, n (%)	8 (26.7%)	101 (90.2%)	< 0.01**

Note: M1, E1, S1, T1/2, and C1/2, the Oxford Classification for IgAN. AI/CI score, the NIH Lupus Nephritis Activity/Chronicity Index scores. EDDs: electron-dense deposits. FPE: Foot Process Effacement. Electronic microscopy analysis was performed in 30 IgA-IRGN patients and 112 IgAN patients due to complete glomerulosclerosis in partial specimens. #, For κ/λ analysis, data are from 30 IgA-IRGN patients and 30 age-/sex-matched IgAN patients. (* P < 0.05, ** P < 0.01)

IF findings revealed that the positive rates of IgG and C1q were significantly higher in the IgA-IRGN group than in the IgAN group. The intensity of IgA deposition was weaker in the IgA-IRGN group (2.5 vs. 3.0, P < 0.01), while the deposition intensities of IgG [0.0 (0.0, 1.3) vs. 0.0 (0.0, 0.0), P = 0.011] and C1q [0.0 (0.0, 2.0) vs. 0.0 (0.0, 0.0), P < 0.01] were significantly higher. Isolated mesangial IgA deposition was observed in 30% of IgA-IRGN patients and 85% of IgAN patients, which was statistically significant (P < 0.01). Quantitative analysis of immunofluorescence intensity for κ and λ light chains showed that the κ/λ ratio in the IgA‑IRGN group was higher than that in the IgAN group, and the proportion of cases with λ light chain predominance was much lower than that in the IgAN group.

Due to complete glomerulosclerosis in the specimens for EM analysis, a total of 30 IgA-IRGN cases and 112 IgAN cases were ultimately included for EM evaluation. Diffuse podocyte foot process effacement was observed in 73.3% of IgA-IRGN patients, compared with only 9.82% in the IgAN group; in contrast, segmental foot process effacement was present in 90.18% of IgAN patients and only 26.7% of IgA-IRGN patients (P < 0.01). (Table 2).

Given that the AI score differed significantly between the two groups, the receiver operating characteristic (ROC) curve of the AI score was plotted. The area under the curve was 0.875 (95% confidence interval: 0.809–0.941) (Fig. 2). According to the Youden index, the optimal cutoff value was 7.5. At a cutoff > 7.5, the sensitivity for diagnosing IgA-IRGN was 83.3% and the specificity was 82.5%.

Fig. 2.

ROC curve of the AI score for discrimination

Given the difficulty in distinguishing IgA-IRGN presenting as AKI from IgAN, a subgroup analysis was performed on patients with AKI. Although both groups presented with AKI, the IgA-IRGN group (n = 11) showed higher levels of MAP, NAR, and NC3r than the IgAN group (n = 13) (Supplementary Table 1). According to the MEST-C classification, the proportion of the E score was higher in the IgA-IRGN group than in the IgAN group, while the proportions of the S, T, and C scores were lower. Moreover, the CI score was significantly lower in the IgA-IRGN group than in the IgAN group (Supplementary Table 2).

Multivariable logistic regression

Variables including AKI, male gender, MAP, BMI, albumin, urea, sCr, eGFR, hypocomplementemia C3, NAR, NC3r, and UTP were incorporated into the multivariable logistic regression analysis. The results identified hypocomplementemia C3, AKI, and low serum albumin as stable independent predictive factors for IgA-IRGN (Table 3).The regression equation was: logit(P) = 1.47 + 1.33 × (hypocomplementemia) + 1.62 × (AKI) – 0.10 × (albumin).

Table 3.

Logistic regression results of clinical diagnostic factors

Variable	Univariate OR (95% CI)	P value	Multivariable Adjusted OR (95% CI)	P value
Hypocomplementemia C3	5.67 [2.37, 13.6]	< 0.01**	3.78 [1.40, 10.2]	< 0.01**
AKI	4.77 [1.85, 12.3]	< 0.01**	5.07 [1.74, 14.8]	< 0.01**
Albumin	0.88 [0.83, 0.93]	< 0.01**	0.90 [0.84, 0.96]	< 0.01**

Note: AKI, acute kidney injury; Hypocomplementemia C3, serum complement C3 < 0.9 g/L. (* P < 0.05, ** P < 0.01)

Given the significant intergroup differences observed for certain pathological parameters, we further performed multivariable logistic regression (forward selection) incorporating the activity index (AI) score, Oxford M score, immunofluorescence intensity of IgG, C1q, and C3, subepithelial humps on electron microscopy, and pattern of foot process effacement (diffuse/segmental), along with acute kidney injury (AKI), albumin, and hypocomplementemia C3. The results showed that hypocomplementemia C3, the AI score, and diffuse foot process effacement were stable independent predictors. The regression equation was: logit(P) = -6.554 + 3.83 × (hypocomplementemia C3) + 3.01 × (elevated AI score) + 4.55 × (diffuse foot process effacement) (Table 4).

Table 4.

Logistic regression results of clinical and diagnostic pathological factors

Variable	Multivariable Adjusted OR (95% CI)	P value
Hypocomplementemia C3	46.21 [4.8, 448]	< 0.01**
elevated AI score	20.20 [3.8, 109]	< 0.01**
diffuse foot process effacement	94.22 [9.9, 894]	< 0.01**

Note: elevated AI score, AI score > 7.5; Hypocomplementemia C3, serum complement C3 < 0.9 g/L. (* P < 0.05, ** P < 0.01)

Treatment and prognosis

Non-immunosuppressive therapies (including ACEIs, ARBs, SGLT-2 inhibitors, etc.) were administered to 90% of IgA-IRGN patients and 96% of IgAN patients. In the IgA-IRGN group, 11 patients (36.7%) received anti-infective therapy (Supplementary Table 3), and 9 patients (30%) received immunosuppressive therapy; in the IgAN group, 4 patients (3.3%) received anti-infective therapy (unrelated to their IgAN diagnosis), and 44 patients (36.7%) received immunosuppressive therapy.

A 6-month short-term follow-up was completed by 24 IgA-IRGN patients (6 were lost to follow-up due to being unreachable; their baseline characteristics were similar to those who completed follow-up, data not shown) and 120 IgAN patients. The results showed that the improvement in eGFR was more significant in the IgA-IRGN group than in the IgAN group (+ 3.37 mL/min/1.73 m² vs. -0.61 mL/min/1.73 m², P = 0.036), and the proteinuria remission rate was significantly higher in the IgA-IRGN group (87.5% vs. 60%, P = 0.01). Among IgA-IRGN patients without active infection, there were no significant differences between the group receiving immunosuppressive therapy and the group not receiving immunosuppressive therapy in terms of eGFR improvement (1.01 vs. 4.0, P = 0.655) and proteinuria remission rate (100% vs. 80%, P = 0.151).

Discussion

This single-center retrospective study systematically compared the clinicopathological features and short-term prognosis of IgA-IRGN and IgAN in a Chinese population, further clarifying the significant differences between the two conditions in terms of clinical manifestations, laboratory parameters, pathological changes, and short-term renal outcomes. Furthermore, this study is the first to apply multiple pathological scoring systems (such as the Oxford Classification and the NIH Activity Index) in combination for the evaluation of IgA-IRGN, revealing its pathologically higher activity of inflammatory features and validating the potential value of the AI score in differential diagnosis. In addition, we proposed the diagnostic significance of NAR and NC3r as novel inflammatory biomarkers in IgA-IRGN. Finally, through multivariable regression analysis, we identified hypocomplementemia C3, AKI, and low serum albumin as independent predictors in clinical analysis, and further identified hypocomplementemia C3, high AI score, and diffuse foot process effacement as independent predictors when pathological factors were included, laying the foundation for the further development of a differential diagnostic model. These findings not only enhance the understanding of the pathological mechanisms of IgA-IRGN but also provide important evidence for accurate clinical identification and personalized treatment.

Compared with previous international cohorts [4], the IgA-IRGN patients in our cohort were relatively younger (median age 38.5 years), with respiratory infections being the main predisposing factor, and a lower Staphylococcus detection rate (3.3%). However, the results of this study are highly consistent with findings from other East Asian populations, such as the Japanese cohort reported by Handa et al. [10] and the Chinese cohort reported by Huang et al. [11], suggesting that East Asian populations may have unique epidemiological characteristics: a younger population, fewer cutaneous manifestations of staphylococcal infection, and fewer patients with comorbid diabetes.

To date, no dedicated pathological scoring system has been established for IgA-IRGN. In this study, we adopted the MEST-C Classification for IgAN for pathological assessment. As Friedrich et al. [14] used the NIH AI score and CI score for lupus nephritis to distinguish IgAN from IgAV, and given that IgA‑IRGN, IgAN, and IgAV share similar pathological features, we attempted to use these indices to differentiate IgA-IRGN from IgAN. The results showed that IgA-IRGN was associated with more prominent active pathological lesions, including the E and S lesions, as well as the AI score. The significant difference in the AI score between the two diseases suggests that IgA-IRGN is a state of more severe active inflammation.

IF analysis revealed that both the positivity rate and deposition intensity of C1q were significantly higher in the IgA-IRGN group than in the IgAN group. These findings were inconsistent with some previous studies [4], and implied the different mechanisms of complement activation between the two diseases. Previous research generally holds that complement activation in IgAN mainly bypasses the classical pathway [15], while IgA-IRGN is frequently triggered by bacterial infections (e.g., Staphylococcus), which induce the formation of circulating antigen-antibody complexes that can effectively initiate the classical complement cascade [16].

In IgA-IRGN, the glomerular κ/λ ratio was higher than that in IgAN, and it lacked the typical λ light chain dominance. At the same time, IgAN showed typical λ light chain predominance, consistent with that reported by Haas et al. [17]. This difference suggests different mechanisms. In IgAN, Gd-IgA1 producing B cells preferentially express λ chains [18]. In IgA-IRGN, acute infection causes nonspecific B cell activation and polyclonal immunoglobulins, leading to no κ/λ bias.

EM findings revealed that diffuse foot process effacement was the main manifestation in IgA-IRGN (73.3%) while segmental effacement was predominant in IgAN (90.2%). Numerous studies indicate a correlation between the extent of foot process effacement and the severity of proteinuria [19]. The disparity in proteinuria between the two groups can be elucidated from the perspective of dysregulated podocyte-endothelial crosstalk. The intense inflammatory microenvironment in IgA-IRGN—characterized by complement activation and neutrophil infiltration—primarily targets glomerular endothelial cells, resulting in prominent endocapillary changes. These injured endothelial cells not only lose their supportive function for podocytes but also actively secrete injurious factors (e.g., endothelin-1 [20]) that disrupt podocyte architecture across the glomerular basement membrane. Furthermore, endothelial dysfunction impairs the proper reception of podocyte-derived VEGF signals [21], leading to an imbalance in the VEGF-α/Angiopoietin-1 axis and subsequently increasing glomerular basement membrane permeability. Consequently, the initial endothelial injury is translated into podocyte damage through this disrupted bidirectional communication, ultimately manifesting as the marked proteinuria observed clinically.

To investigate the non-invasive diagnostic differentiators between the two diseases, we initially included clinical variables in the multivariable logistic regression analysis and identified hypocomplementemia C3, AKI, and low serum albumin as independent predictors of IgA-IRGN. We further incorporated clinical and pathological factors into the analysis and identified hypocomplementemia C3, a high AI score, and diffuse foot process effacement as independent predictors of IgA-IRGN. However, limited by our sample size, we did not construct a formal differential diagnostic model. Future large-scale, prospective cohort studies are required to discover novel biomarkers and develop more precise diagnostic algorithms for the two diseases.

As indicators of inflammation and poor prognosis, NAR has been validated in patients with cancer, infections, and heart failure [22, 23]. Bacterial infections are known to induce the activation of the complement system [24]. Neutrophils and their effector products (e.g., neutrophil extracellular traps, NETs) play a central role in the infectious process [25]. Therefore, we proposed that NC3r may have diagnostic value for IgA-IRGN. This study found that both NAR and NC3r were significantly elevated in the IgA-IRGN group compared with the IgAN group, indicating that complement activation, neutrophil infiltration, and the associated inflammatory cascade play crucial roles in the pathogenesis of IgA-IRGN. This finding warrants further validation in larger cohorts to explore their potential clinical application value in the differential diagnosis of IgA-IRGN and IgAN.

Given the greater difficulty in differentiating IgAN from IgA-IRGN when both present with AKI, we performed a subgroup analysis. The results showed that the IgA-IRGN group had higher levels of MAP, NAR, and NC3r. Pathologically, the CI score was significantly lower in the IgA‑IRGN group than in the IgAN group, further suggesting that although IgAN can present with AKI, it may still harbor underlying chronic lesions. Neutrophil‑related indices may serve as potential differential diagnostic markers, but this requires validation in larger cohorts.

For IgA-IRGN patients without active infection, whether to initiate immunosuppressive therapy remains controversial. A prospective case-control study reported that corticosteroid therapy did not improve 6-month renal outcomes; instead it increased the risk of adverse events [26]. In contrast, a retrospective study suggested that corticosteroids might improve renal prognosis in such patients [27]. Bu et al. also found significant variability in the efficacy of glucocorticoid treatment for IgA-IRGN patients [9]. In our study, subgroup analysis of IgA-IRGN patients showed no significant differences in renal function recovery or proteinuria remission rate between patients who received immunosuppressive therapy and those who did not. This suggested that the short-term efficacy of immunosuppression in IgA-IRGN is not significant. However, it is worth noting that the baseline eGFR of patients receiving immunosuppressive therapy was lower than that of those not receiving such treatment (30.5 mL/min/1.73 m² vs. 66.9 mL/min/1.73 m²). Therefore, the expected prognosis for patients receiving immunosuppressive therapy was inherently poorer than that of the non-immunosuppressive therapy group, a finding that may warrant further evidence for clarification.

Previous studies have shown that the long-term prognosis for IgA-IRGN patients is generally worse than that for IgAN patients [10, 11]. Research also indicate that the change of eGFR within 6 months and a ≥ 30% reduction in UTP are important indicators of long-term renal outcomes of glomerulonephritis patients [28, 29]. In our study, patients with IgA-IRGN showed a better short-term renal function recovery and higher proteinuria remission rate than those with IgAN. We hypothesize that this is due to the acute injury in IgA-IRGN which allows for rapid repair of the filtration barrier once the infection subsides, leading to quick improvements in proteinuria and renal function. In contrast, chronic injury in IgAN results in slow repair of the glomerular structure and persistent proteinuria, thus showing a slight decline in short-term renal function.

It should be noted that IgA-IRGN patients in our cohort were younger and had fewer comorbidities, which may be important confounding factors affecting their short-term prognosis. Whether the long-term prognosis will ultimately surpass that of IgAN patients requires further observation and investigation through long-term follow-up studies with larger sample sizes.

This study has several limitations that should be acknowledged. First, it is a single-center retrospective study with a relatively small sample size of IgA-IRGN patients. Second, due to the occult nature of some infections, the diagnosis of most IgA-IRGN patients in this study relied heavily on pathological criteria (diffuse endocapillary hypercellularity on LM, co-deposition of IgA and C3 on IF, and hump-like EDDs on EM), which may introduce certain selection bias. Additionally, due to limited biopsy material and serum samples, we were unable to perform Gd‑IgA1 or KM55 staining, although these biomarkers would be valuable for differential diagnosis; we have initiated pilot experiments for future investigation. Future prospective, large-sample, multicenter studies are necessary to further verify the conclusions of this study and explore more reliable diagnostic and prognostic indicators for IgA-IRGN.

Conclusions

According to our study, IgA-IRGN and IgAN exhibit both similarities and significant differences in their clinicopathological characteristics. Hypocomplementemia C3, AKI, low serum albumin, diffuse foot process effacement, and the AI score may have predictive value for the differential diagnosis of the two diseases. IgA-IRGN patients achieve a more favorable short-term prognosis, which may be related to the acute pathological injury characteristics of IgA-IRGN. Future prospective studies with large sample sizes and long-term follow-up are needed to further clarify the long-term prognostic differences between the two diseases and explore novel inflammatory biomarkers and their clinical value in IgA-IRGN.

Supplementary Information

Below is the link to the electronic supplementary material.

Abbreviations

ACE

Angiotensin-converting enzyme inhibitor

AI

Activity index (NIH lupus nephritis activity index)

AKI

Acute kidney injury

ARB

Angiotensin II receptor blocker

BMI

Body mass index

CI

Chronicity index

CKD-EPI

Chronic Kidney Disease Epidemiology Collaboration

EDD

Electron-dense deposit

eGFR

Estimated glomerular filtration rate

EM

Electron microscopy

FITC

Fluorescein isothiocyanate

FPE

Foot process effacement

H&E

Hematoxylin and eosin

HDL-C

High-density lipoprotein cholesterol

IF

Immunofluorescence

Ig

Immunoglobulin

IgA-IRGN

IgA-dominant infection-related glomerulonephritis

IgAN

IgA nephropathy

LDL-C

Low-density lipoprotein cholesterol

LM

Light microscopy

MAP

Mean arterial pressure

MEST-C

Mesangial hypercellularity, endocapillary hypercellularity, segmental glomerulosclerosis, tubular atrophy/interstitial fibrosis, crescents (Oxford Classification)

NAR

Neutrophil-to-albumin ratio

NC3r

Neutrophil-to-C3 ratio

NET

Neutrophil extracellular trap

PAS

Periodic acid-Schiff

PASM

Periodic acid-silver methenamine

ROC

Receiver operating characteristic

sCr

Serum creatinine

SGLT-2

Sodium-glucose cotransporter 2

UTP

Urine total protein

VEGF

Vascular endothelial growth factor

Author contributions

Conceptualization, J.Z. and Y.Y.; methodology, Y.Y. and L.Z.; software, J.Z. and Y.W.; validation, B.D.; formal analysis, D.Y. and M.C.; investigation, J.Z. and D.Y.; data curation, C.S. and X.L.; writing—original draft preparation, all authors; writing—review and editing, Y.Y. and L.Z.; visualization, J.Z., Y.W. and Y.Y; supervision, L.Z.; project administration, L.Z. funding acquisition, Y.Y. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Natural Science Foundation of China (81000296) and Peking University People’s Hospital Scientific Research Development Funds (RDL2022-08).

Data availability

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Declarations

Ethics approval and consent to participate

This retrospective study complied with the guidelines of the Declaration of Helsinki and was approved by the Medical Ethics Committee of Peking University People’s Hospital, Beijing, China. Since this study involved retrospective review of existing data, approval from the Institutional Review Board was obtained and administrative permissions were not required. There was no specific informed consent from patients. The Institutional Review Board of Peking University People’s Hospital specifically waived the need for consent for these studies.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.