Introduction: The aim of this study was to evaluate the association of peripheral eosinophil (EOS) count with disease activity and kidney outcomes in lupus nephritis (LN) patients. Methods: A total of 453 hospitalized and biopsy-proven LN patients at our hospital from 2006 to 2013 were enrolled, of which 388 patients had repeated measurements of EOS. Relationships were explored between average EOS and disease activity at baseline, using the systemic lupus erythematosus disease activity (SLEDAI) and activity index (AI) on kidney biopsy. Follow-up data were available through December 2016. The primary outcome measure was a composite of doubling of serum creatinine and end-stage kidney disease after a median follow-up of 51 months. Results: The mean age of the enrolled 388 LN patients was 33.1 ± 10.8 years old, and 335 (86%) were female. The median average peripheral EOS count was 0.033 (0.015–0.057) ×109/L. Mean AI and SLEDAI score were 6.8 ± 2.5 and 14.9 ± 5.4, respectively. Logistic regression models showed that decreased average EOS was independently associated with higher AI (≥6) and higher SLEDAI (≥15) (odds ratio [OR] 0.93, 95% confidence interval [CI] 0.90–0.97; and OR 0.96, 95% CI: 0.93–0.99, respectively). There was a parabolic relationship between average EOS and the primary outcome, with hazard ratio (HR) > 1 for both levels ≤0.033 and >0.16 × 109/L. Conclusion: Lower EOS count was independently associated with severe disease activity and kidney progression in LN.

© 2023 The Author(s). Published by S. Karger AG, Basel

Introduction

Lupus nephritis (LN) is a severe manifestation of system lupus erythematosus (SLE) that is characterized by immune inflammatory lesions in kidney. Approximately 5–20% of LN patients would develop end-stage kidney disease (ESKD) within 10 years of diagnosis [1]. Despite patient survivals and disease prognosis have improved greatly over the last decades, LN remains a crucial determinant of morbidity and mortality in SLE patients [1, 2]. Kidney biopsy plays a fundamental role in evaluation and management of LN [3]. Activity index (AI) scores and chronicity index (CI) scores based on pathological changes have been widely used to semiquantitatively assess the kidney lesions [4, 5]. And the study confirmed that high AI and CI were independent risk factors of ESKD in LN patients [6]. However, as an invasive operation, some patients might not be suitable for biopsy. Therefore, it is necessary to develop noninvasive biomarkers to monitor kidney injury of LN patients. Indeed, some hematological and urinary biomarkers have been explored to evaluate disease activity of SLE and LN patients [7-11].

Previous studies of eosinophils mainly focused on helminth infections [12] and the pathogenic effect on allergic diseases [13, 14]. Nevertheless, growing evidences indicated that eosinophils had a protective impact on antitumor response [15], tissue regeneration [16-18], and inflammation resolution [19, 20]. Also, the helminth products that increased the eosinophils (EOS) were also proved to effectively ameliorate the LN in murine lupus models [21-23]. Moreover, a previous study demonstrated that overexpression of IL-5 could lead to amplification of EOS in peripheral blood and a significant decrease of ds-DNA antibodies, as well as amelioration of kidney injury in SLE-prone (NZB × NZW) F1 mice [24]. IL-5 is the main proliferative factor of EOS and is regarded as a means of exogenously expanding eosinophils in circulation and tissues [25]. Another study found that depletion of EOS significantly increased the serum levels of IgG2a, IgG2b, total IgG, and IgA at 8 weeks of age in pristane-induced lupus models [26]. All these studies indicated that EOS might involve in the disease progress of LN. However, few clinical studies have explored the relationship between EOS and lupus disease activity and clinical outcomes in LN. Thus, we inclined to explore the potential association of EOS with lupus disease activity and kidney activity lesions in hospitalized biopsy-proven LN population.

Materials and MethodsParticipants

In this retrospective cohort study, we enrolled hospitalized LN patients in the First Affiliated Hospital of Sun Yat-Sen University from January 2006 to December 2013. Patients with a history of malignancy or died during the hospitalization were not included. The exclusion criteria were as follows: patients with age <18 years old on admission to hospital, with ESKD, without kidney biopsy at our hospital, and with incomplete data of peripheral EOS counts and kidney pathological evaluation (AI and CI). All the participants were followed up until December 31, 2016. All patients fulfilled the 1997 American College of Rheumatology criteria for SLE [27]. This study was in accord with the Declaration of Helsinki and conducted with the approval of the Institutional Review of the First Affiliated Hospital of Sun Yat-Sen university (No. [2016]2015).

Assessment of Kidney Histopathology and Clinical Data

Kidney biopsy samples were evaluated by light microscopy, immunofluorescence, and electron microscopy. Kidney pathology was evaluated by three experienced pathologists based on the 2003 International Society of Nephrology/Renal Pathology Society (ISN/RPS) classification system [28]. The AI and CI proposed by Austin et al. [4] were used to assess semiquantitatively the morphological changes in kidney biopsy specimens. There are total scores of 24 in AI scores and 12 in the CI scores. AI scores comprise the following items: endocapillary hypercellularity (scores 0–3), glomerular leukocyte infiltration (scores 0–3), subendothelial hyaline deposits (scores 0–3), fibrinoid necrosis/karyorrhexis (scores [0–3] ×2), cellular crescents (score [0–3] ×2), and interstitial inflammation (scores 0–3). AI scores are applied to measure the severity of active immunoinflammatory lesions to kidney parenchyma. CI scores comprise the following items: glomerular sclerosis (scores 0–3), fibrous crescents (scores 0–3), tubular atrophy (scores 0–3), and interstitial fibrosis (scores 0–3). CI scores represent the chronic irreversible tissue damage of LN. Immune complexes (IgA, IgM, IgG, C1q, and C3) deposited in kidney glomerulus were graded from 1 to 6 according to the intensity of fluorescence.

SLE disease activity index (SLEDAI) was used to evaluate the global lupus disease activity and was assessed in the early admission period [29, 30]. There were 24 items that covering nine organ systems in the scoring system, with each descriptor scoring range from 1 to 8 and a total score of 105. Estimated glomerular filtration rate was assessed by the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation [31].

Peripheral blood cell counts, serum biochemical indexes, ANA, and dsDNA were tested in the laboratory of our hospital. The results of each examination of peripheral EOS during the hospitalization were collected. The data of serum creatinine (Scr), blood urea nitrogen (BUN), ANA, dsDNA, C-reactive protein, and erythrocyte sedimentation rate detected for the first time during the hospitalization were collected. Peripheral cell counts and hemoglobin were measured by blood cell counters (Sysmex XE-2100, Sysmex Co., Kobe, Japan). Scr, BUN, albumin, erythrocyte sedimentation rate, C-reactive protein, dsDNA, ANA, systolic blood pressure (SBP), and diastolic blood pressure (DBP) were all detected with standardized methods. The use of glucocorticoid (GC) included oral administration of prednisolone acetate or methylprednisolone (Medrol), and high-dose pulsed methylprednisolone (≥250 mg per day). The use of immunosuppressant (ISA) included mycophenolate mofetil (MMF), cyclophosphamide, Cyclosporin A, and methotrexate. Urine protein was measured with a 24-h urine collection.

Outcomes

The primary outcome was a composite of doubling of Scr and ESKD. The secondary outcome was kidney AI and SLEDAI. ESKD was defined as patients receiving maintenance dialysis or kidney transplantation.

Statistical Analysis

Correlations of peripheral eosinophil counts with AI or SLEDAI were conducted with the Spearman test. Multilinear regression models and multivariate logistic regression models were performed to explore the independent association of peripheral eosinophil counts with lupus disease activity and kidney activity lesions. Age, gender, neutrophil counts, albumin, and 24 h-proteinuria were included for adjustments. The stepwise selection method was conducted to remove nonsignificant variables with a p value <0.10 in multilinear regression models. Also, covariates that might result in multicollinearity were not incorporated in the models. Time-dependent receiver-operating characteristic curve for renal survival was performed to determine the cut point for stratification. Restricted cubic spline (RCS) was performed to evaluate the nonlinear association of average EOS with renal survival.

Variables with normal distribution are presented as mean ± standard deviation and compared with t test. Nonparametric variables are presented as median with interquartile range and compared with Mann-Whitney U test. The change of eosinophils before and after administration of GC or MMF was compared with Wilcoxon signed rank test or Friedman test as appropriate. Categorical variables are presented as frequency with percentage and compared with the χ2 test or Fisher’s exact test. All the analyses were conducted by IBM SPSS Statistics 25.0 software (SPSS, Chicago, IL, USA) and R version 4.1.1 (R Foundation for Statistical Computing, Vienna, Austria). A two-side p value <0.05 was considered to be significant.

ResultsCharacteristics of the Participants

There were 117 patients with age <18 years old on admission to hospital, 77 patients with ESKD, 294 patients without kidney biopsy in our hospital or underwent kidney biopsy in other hospitals, and 30 patients with incomplete data of EOS or kidney pathological evaluation. Ultimately, a total of 453 LN patients were eligible for analysis in the study. Of which 238 patients had taken GC or ISA within 3 months before the first measurement of EOS while 215 patients didn’t. Eventually, 388 of the patients who had repeated measurements of EOS during hospitalization were enrolled for further analysis (shown in Fig. 1). The mean age of the enrolled patients was 33.1 ± 10.8 years old, and 335 (86.3%) of the patients were female. The median of average peripheral EOS counts was 0.033 (0.015–0.057) ×109/L. The mean SLEDAI score and AI score were 14.9 ± 5.4 and 6.8 ± 2.5, respectively (shown in Table 1). The median time from first measurement of EOS to kidney biopsy was 6 (4–11) days.

Table 1.

Baseline characteristics in LN patients with different levels of eosinophils

Fig. 1.Variability of Peripheral Eosinophil Counts during the Hospitalization

To evaluate the daily fluctuation of peripheral EOS during the hospitalization of LN patients, we calculated the days from the day of admission, and superimposed the available data of peripheral EOS from the 388 enrolled patients based on the distribution. The average value of EOS in the same day was defined as the value of the day. As shown in Figure 2a, the level of EOS counts was generally maintained at a low level below 0.05 × 109/L. Unsurprisingly, the administration of GC significantly further decreased the level of peripheral EOS counts in LN patients. Our results showed that LN patients taking GC or ISA within 3 months of the first measurement of peripheral EOS counts had a lower level of EOS counts than that of patients not taking GC or ISA (0.02 [0.010–0.060] versus 0.05 [0.020–0.100] ×109/L, p < 0.001). However, even without administration of GC or ISA prior to measurement, the level of peripheral EOS counts of LN patients on admission was low, with a median of 0.05 × 109/L (shown in Fig. 2b). Additionally, we analyzed the changes of peripheral EOS before and after treatment with GC or MMF during hospitalization. As shown in Figure 2c, the level of EOS decreased significantly after treatment with GC (0.05 [0.020–0.090] versus 0.02 [0.007–0.050] ×109/L, p < 0.001). The high-dose pulsed methylprednisolone therapy also significantly reduced the EOS levels (0.033 [0.010–0.100] versus 0 [0–0.010] ×109/L, p = 0.002), but this inhibiting effect was neutralized 3 days after the impulse treatment (0.033 [0.010–0.100] versus 0.020 [0.010–0.050] ×109/L, p = 0.630) (shown in Fig. 2d). Treatment with MMF slightly increased the EOS level, but the difference was not significant (0.020 [0.005–0.057] versus 0.033 [0.015–0.054] ×109/L, p = 0.229) (shown in Fig. 2e).

Fig. 2.

The variability of eosinophils during hospitalization (a) and the effect of medication on eosinophils (b–e).

Comparisons of LN Patients with Different Levels of Peripheral Eosinophil Counts

To minimize the variability of EOS, we averaged the repeated measures of EOS during hospitalization and obtained a single mean value of EOS for further analysis. According to the time-dependent receiver-operating characteristic analysis (shown in online suppl. Fig. S1; for all online suppl. material, see www.karger.com/doi/10.1159/000528486), we divided the LN patients into the low average EOS group (<0.034 × 109/L) and high average EOS group (≥0.034 × 109/L). As shown in Table 1, compared to high EOS group, LN patients in the low EOS group had a significantly lower level of peripheral lymphocyte counts (p < 0.001), platelets (p = 0.003), albumin (p = 0.044), and hemoglobin (p = 0.029), whereas higher levels of serum BUN (p = 0.004), dsDNA (p = 0.003), SLEDAI score (p = 0.045), AI score (p = 0.003), kidney IgA (p = 0.004), IgG (p = 0.027), IgM (p = 0.042), C1q (p < 0.001), and C3 (p = 0.004) deposit, and marginally higher percentage of LN classification of III or IV (p = 0.092). The administration of GC and pulsed methylprednisolone was higher in LN patients with lower average EOS.

Correlation between Peripheral Eosinophil Counts and Clinical Parameters

In the correlation analysis, average EOS counts were significantly and negatively correlated with SLEDAI (r = −0.115, p = 0.024) and AI score (r = −0.186, p < 0.001), as shown in online supplementary Table S1. In addition, peripheral eosinophil counts were negatively correlated with BUN (r = −0.173, p = 0.001), ANA (r = −0.126, p = 0.014), dsDNA (r = −0.195, p < 0.001), kidney IgA deposit (r = −0.217, p < 0.001), IgM deposit (r = −0.133, p = 0.009), IgG (−0.121, p = 0.017), C1q deposit (r = −0.255, p < 0.001), and C3 deposit (r = −0.219, p < 0.001), while positively correlated with first-measured EOS (r = 0.814, p < 0.001), age (r = 0.107, p = 0.035), lymphocyte counts (r = 0.303, p < 0.001), leukocytes (r = 0.187, p < 0.001), hemoglobin (r = 0.135, p = 0.008), albumin (r = 0.107, p = 0.034), and platelets (r = 0.220, p < 0.001).

Association of Peripheral Eosinophil Counts with Clinical Outcomes in Lupus Nephritis PatientsDoes Eosinophils Associate with Activity Index?

In the multilinear regression models adjusted for age, gender, neutrophils, albumin, Scr, and proteinuria, peripheral average EOS was independently and negatively linearly associated with AI score (β = −0.143, p = 0.002), as illustrated in online supplementary Table S2. In the multivariate logistic regression model, as described in Table 2, a decrease of peripheral EOS was significantly associated with a higher AI score (≥6) (odds ratio 0.93, 95% confidence interval [CI]: 0.90–0.97, p = 0.001).

Table 2.

Associated factors of higher AI score (≥6) and higher SLEDAI score (≥15) in multivariate logistic regression model

Does Eosinophils Associate with SLEDAI?

After adjusting the variables as mentioned above, we also found that average peripheral EOS was negatively associated with SLEDAI (β = −0.138, p = 0.005) in the multilinear regression analysis (shown in online suppl. Table S2). Multivariate logistic regression analysis showed that each 0.01 × 109/L increase of average EOS was associated with 4% (odds ratio 0.96, 95% CI: 0.93–0.99, p = 0.021) lower risk of higher SLEDAI (≥15) (shown in Table 2).

Does Eosinophils Predict Outcomes of Lupus Nephritis?

During a median follow-up duration of 50.8 (interquartile range: 19.2–77.8) months, 33 patients reached the primary outcomes. And 12 patients died within the follow-up duration. We found a nonlinear relationship (p = 0.015) between average EOS and kidney outcomes by using RCS. As depicted in Figure 3, there was a parabolic relationship between average EOS and kidney outcomes. When average EOS ≤0.033 × 109/L, there was a significantly higher HR (HR >1) for kidney progression. We also observed a higher HR (HR >1) for kidney progression when average EOS >0.16 × 109/L, though the association was insignificant.

Fig. 3.

Restricted cubic spline analysis for the association of average eosinophils and hazard ratio for kidney progression.

Conclusion

In this cohort study, we demonstrated that the peripheral EOS count in SLE patients with kidney involvement was significantly lower and first revealed that decreased peripheral EOS count was an independent factor of higher levels of AI score and SLEDAI score. These results indicated that EOS counts were associated with lupus disease activity and kidney active lesions. Notably, we found that lower average peripheral EOS count (≤0.033 × 109/L) during the hospitalization was associated with a higher risk for kidney progression.

In this study, we found a prominent reduction of the peripheral EOS count in SLE patients with kidney involvement (0.06 ± 0.09 × 109/L), with up to 55.4% of the enrolled LN patients had EOS count lower than 0.05 × 109/L (normal references: 0.05–0.5 × 109/L). GC is widely used to treat hypereosinophilic syndromes in clinical and is acknowledged to decrease EOS levels [32]. Also, a recent study revealed that the effect of GC inducing peripheral EOS reduction was via chemokine receptor CXCR4-dependent migration of EOS to the bone marrow [33]. Our results also certified that GC could reduce the peripheral EOS level. However, even in LN patients without exposure to GC, up to 45% of the patients had EOS levels lower than 0.05 × 109/L. A previous report also showed that the peripheral EOS count (0.06 ± 0.15 × 109/L) in SLE patients without administration of GC was significantly lower than that of healthy controls (0.11 ± 0.08 × 109/L) and other systemic autoimmune rheumatic diseases (0.15 ± 0.37 × 109/L in rheumatoid arthritis, 0.15 ± 0.15 × 109/L in ankylosing spondylitis, etc.) [8]. These results indicated that peripheral EOS in SLE and LN patients tends to decrease intrinsically. What’s more, we showed that peripheral EOS count was negatively correlated with disease activity and kidney AI of LN. However, the potential mechanisms of significantly lower EOS count in SLE patients and LN patients remained obscure. Interleukin (IL)-5 secreted primarily by type II innate lymphocyte (ILC2) was indispensable for development and survival of EOS [34, 35]. Prior studies had confirmed that ILC2 numbers were both significantly decreased in SLE patients [36, 37] and murine lupus model [38]. The substantial increase of interferon-γ in lupus could inhibit ILC2 proliferation and activation [38, 39], thus reduced ILC2 numbers, and subsequently decreased EOS. Additionally, results in our study suggested that peripheral average EOS counts were negatively correlated with serum ANA and dsDNA, as well as glomerular deposit of IgA, IgM, C1q, and C3. These results indicated that EOS counts might correlate with autoantibody production in SLE and LN patients. Indeed, mechanistic study had confirmed that overexpression of IL-5 and EOS resulted in a significantly decrease of anti-DNA antibodies and amelioration of autoimmune disease [24].

To date, no clinical studies had explored the predictive value of peripheral EOS counts on kidney outcomes in LN patients. Interestingly, our study found that lower average peripheral EOS count (≤0.033 × 109/L) had a higher risk for worse kidney outcomes. Our results indicated that peripheral EOS counts might be monitored as a promising index to predict kidney progression. The possible mechanisms for lower EOS count associated with more severe lupus disease activity and kidney progression were puzzling. Recently, studies confirmed that EOS-derived IL-4, mEar1, and IL-13 could facilitate inflammation resolution and constrain necrosis and fibrosis of injury tissues [16, 17]. In the MRL/lpr lupus model, IL-33-mediated expansion of ILC2 exerted protection on LN and was accompanied with increased EOS [38]. And another study demonstrated that the protective role of ILC2 expansion on progressive glomerulosclerosis was relied on amplification of EOS [40]. These results implied that EOS might also play a critical role in restraining inflammation and acute damage of kidney parenchyma in LN. However, these studies are still insufficient to demonstrate a direct role of eosinophils in lupus. More clinical and basic researches are warranted to prove these speculations.

The strength of our study was the relatively large population of hospitalized and biopsy-proven LN patients and sufficient pathological data on kidney biopsy, as well as a relative long-term follow-up duration, and this was the first study to explore the association of EOS count with disease activity and kidney outcomes in LN patients. However, there were also limitations in this study. As a single-center study with mostly patients in Southern China, the conclusions may not be suitable for other populations. Additionally, we only collected the baseline EOS during the hospitalization and lacked follow-up data of EOS. As described above, EOS level might fluctuate due to administration of GC during hospitalization; thus, the short-term or single EOS measure may lead to some bias on the results. Considering this, we applied the average value of multiple EOS measures for analysis, in order to minimize the potential bias due to the different timing of single EOS measure. In the further study, we would like to collect the follow-up data of EOS and explore the long-term variability of EOS and its impact on clinical outcomes in LN patients.

In conclusion, we first demonstrated that decreased peripheral EOS counts in biopsy-proven hospitalized LN patients were independently associated with severe lupus disease activity and kidney progression. Peripheral EOS count might be a useful index for monitoring lupus disease activity and kidney activity lesions. However, further clinical and mechanistic researches are warranted to clarify the potential effect of EOS in LN.

Statement of Ethics

This study was in accord with the Declaration of Helsinki and conducted with the approval of the Institutional Review of the First Affiliated Hospital of Sun Yat-Sen university (No. [2016]2015). All hospitalized patients signed a written informed consent when they collected blood samples, agreeing that their test results would be used for noncommercial scientific research.

Conflict of Interest Statement

The authors declare that they have no conflict of interest.

Funding Sources

This work was supported by the National Natural Science Foundation of China (Grant No. 82274277, 82074170, and 81774069), Guangdong Provincial Key Laboratory of Nephrology (Grant No. 2020B1212060028), and NHC Key Laboratory of Clinical Nephrology (Sun Yat-Sen University).

Author Contributions

Yang X proposed the concept of the study. Ruihua Liu and Hongjian Ye analyzed and interpreted the data. Ruihua Liu made the draft of the article and revised it under the supervision of Professor Xiao Yang. Yuan Peng and Xi Xia collected the data. Wei Chen, Fengxian Huang, and Zhijian Li provided intellectual content of critical importance to the work described. All authors approved the final version of the manuscript.

Data Availability Statement

All data generated or analyzed during this study are included in this article and its supplementary material files. Further enquiries can be directed to the corresponding author.

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