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. 2024 Jul 22;46(2):2381593. doi: 10.1080/0886022X.2024.2381593

Causal role of immune cells in IgA nephropathy: a mendelian randomization study

Jinlian Shu a,b, Yating Ge a,b, Yonggui Wu a,c,✉
PMCID: PMC11268262  PMID: 39039855

Abstract

Background

Previous observational studies have shown that immune cells play an important role in IgA nephropathy. However, the specific causal relationship between the two is inconsistent.

Methods

We used a two-sample mendelian randomization(MR) analysis to investigate the causal association between 731 immune cell signatures and IgA nephropathy in this study. Based on published GWAS data, immune cells were characterized by four immune types absolute cell (AC) counts, median fluorescence intensity (MFI), morphological parameters (MP), relative cell (RC) counts. Meanwhile, heterogeneity test, horizontal pleiotropy and sensitivity test were used to evaluate the robustness and reliability of the results.

Results

An important causal association was achieved for 14 RC traits/IgA nephropathy, 3 AC traits/IgA nephropathy, 10 MFI traits/IgA nephropathy, and 1 MP trait/IgA nephropathy. However, after false discovery rate (FDR) correction, only one immunophenotype was found to be protective against IgA nephropathy. The OR of herpesvirus entry mediator (HVEM) on terminally differentiated CD4+ T cell (maturation stages of T-cell panel) on IgA nephropathy risk was estimated to be 0.727 (95%CI: 0.624-0.847, p = 4.20e − 05, PFDR = 0.023) according to inverse variance weighting (IVW) method, and the weighted-median method yielded similar results (OR = 0.743, 95% CI: 0.596-0.927, p = 0.008). Although not statistically significant, the association was consistent with MR-Egger, simple mode and weighted mode.

Conclusions

Our study further confirmed that immune cells play a complex and important role in the pathogenesis of IgA nephropathy, providing evidence for clinical research.

Keywords: IgA nephropathy, immune cells, mendelian randomization analysis, causal inference

Introduction

IgA nephropathy is not only the most common glomerular disease in China, but also the most prevalent primary glomerular disease worldwide [1]. Studies have shown that 30%–40% of IgA nephropathy patients reached the endpoint of end stage renal disease within 20 years of diagnosis [2]. Willey CJ et al. [3] reported an estimated annual incidence of IgA nephropathy of 0.76 per 100,000 and a point prevalence of 2.53 per 10,000 in patients of all ages across 10 European countries. At present, the core of the initial treatment of IgA nephropathy is still comprehensive supportive therapy, including blood pressure management, lifestyle modification, use of the maximum tolerated dose of angiotensin converting enzyme inhibitors or angiotensin receptor blocker, assessment of cardiovascular risk, and sodium-dependent glucose transporters 2 inhibitors [4,5]. But there are still some patients who are at high risk for disease progression and may need immunosuppressive therapy. Recent studies have found that in addition to glucocorticoids [6,7], immunosuppressants also included the inhibition of immune complex activation of complement activity, inhibition of B cell activating factor (BAFF)/a proliferation-inducing ligand(APRIL) signaling, depletion of plasma cells and B cells [8]. However, immunosuppressive therapy may carry the risk of treatment-related toxicities such as infections, and the long-term benefits of immunosuppressants need to be further evaluated [9]. Therefore, timely diagnosis and early treatment may help control progression and improve prognosis for IgA nephropathy patients.

So far, the exact pathogenesis of IgA nephropathy has not been clarified, but the more widely accepted is the ‘four hits’ hypothesis [10]. The first hit is the circulating presence of high levels of galactose-deficient IgA1 (gd-IgA1). Hit 2 is the production of circulating autoantibodies induced by gd-IgA1. Hit 3 is that Gd-IgA1 binds to antibodies to form pathogenic immune complexes. Hit 4 is the deposit of pathogenic immune complexes in the mesangial region of the kidney, which activates the complement pathway and the inflammatory response, leading to kidney damage. In this process, immune cells play an important role in the occurrence and development of IgA nephropathy. Many studies have shown that B cell activation played an important role in the development of IgA nephropathy [11–13]. Mice with overexpression of B lymphocyte activator showed elevated serum IgA levels and IgA deposition in the mesangial region of renal tissue. The expression of B lymphocyte activator-APRIL was increased in the plasma of IgA nephropathy patients, and inhibiting APRIL can reduce the serum IgA level of IgA nephropathy mice, thus significantly reducing the immunodeposition of IgA in the kidney. In addition, studies using single-cell RNA-sequencing technology showed that the number of B2 subgroup cells in peripheral blood of patients with IgA nephropathy increased significantly [14]. The imbalance of T cells can lead to excessive abnormal IgA production by B cells. Naive CD4+ T cell differentiate into T helper cell(Th) 17 cells, then secrete and produce various cytokines IL-17a, IL-17f and IL-22, causing inflammatory cells to further infiltrate the kidney tissue and aggravate the injury of IgA nephropathy [15]. The proportion of Th2, follicular helper T cell(Tfh), Th17, Th22 and γδ T cells in the blood circulation of IgA patients were increased, while the proportion of Th1 and Regulatory T cells (Tregs) were decreased [16]. The changes of T lymphocyte subsets may be related to the different gene sequence and epigenetic composition of IgA nephropathy patients [17]. In addition, multiple studies have shown that innate immnunity and toll-like receptors, monocytes, macrophages, and natural killer(NK) cells were also involved in IgA nephropathy [11,18,19]. These observational studies have shown a strong relationship between immune cell traits and IgA nephropathy. However, due to observational studies, sample size limitations, and relevant confounding factors, these causal association between immune cell traits and IgA nephropathy may not be consistent to date.

Mendelian randomization (MR) is a causal inference method based on genetic variation that explores the causal relationship between exposure and outcome [20]. It can effectively reduce the impact of confounding bias and improve the accuracy of causal inference. Although previous studies have reported some relationship between B cells, T cells, inflammatory cytokines, and complement and IgA nephropathy, some of the findings have been inconsistent [17]. Therefore, this study conducted a two-sample mendelian randomization analysis to evaluate the causal association between immune traits and IgA nephropathy, providing a clue for the mechanism of IgA nephropathy.

Materials and methods

Study design

We performed a two-sample MR analysis to investigate the causal relationship between 731 immune cell traits and IgA nephropathy. Single nucleotide polymorphisms (SNPs) associated with 731 immune cell traits were considered instrumental variables (IVs). In order to obtain valid and reliable results, effective instrumental variables as risk factors must satisfy three core assumptions in MR analysis:(1) genetic variation is strongly associated with exposure factors (correlation hypothesis); (2) genetic variation is not associated with any known or unknown confounding factors (independence hypothesis); (3) genetic variation affects outcomes only through exposure factors and not through any other direct causal pathway (excluding restrictive assumptions). On the basis of the above, we explored the causal relationship between 731 immue cell traits (exposure) and IgA nephropathy (outcome). The detailed flow chart was shown in Figure 1.

Figure 1.

Figure 1.

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The design flow chart for the MR study. MR, Mendelian randomization; GWAS, genome-wide association studies; SNP, single nucleotide polymorphism; IVW, inverse variance weighting; MR-PRESSO, MR pleiotropy residual sum and outlier.

Data sources for IgA nephropathy

The IgA nephropathy genome-wide association studies (GWAS) summary dataset included 592 cases and 376685 controls from the Finnish population. FinnGen is a large genetic research program that aggregates GWAS and PheWAS results for a variety of diseases and aims to explore the relationship between genomic information and health characteristics in the Finnish population. IgA nephropathy was defined according to the international classification of diseases (ICD) diagnostic codes N08.2*D89.80 in this study. This GWAS data can be downloaded from https://r9.finngen.fi/.

Data sources for immune traits

The summary statistics of SNPs related to 731 immune traits were extracted from the GWAS catalog (accession numbers from GCST0001391 to GCST0002121), which was publicly available [21]. By analyzing peripheral blood from 3,757 Sardinians, the study reported about 22 million genetic variations on 731 immune cell traits. Total immunophenotypes included: absolute cell (AC) counts (n = 118), median fluorescence intensities (MFI) reflecting surface antigen levels (n = 389), morphological parameters (MP) (n = 32) and relative cell (RC) counts (n = 192). Specifically, they contained TBNK, Tregs, T cell maturation stages, dendritic cells(DCs), B cells, monocytes, myeloid cells.

Selection of instrumental variables (IVs)

The significance threshold for each immune traits was set to p-value < 1 × 10−5 in accordance with the recent studies [21,22]. IVs pruning was performed using PLINK software (version v1.90) with linkage disequilibrium (LD) r2 threshold < 0.1 within 500 kb distance, where LD r2 was calculated from 1000 genomes projects [23].

To assess the strength of genetic variables and avoid weak instrumental bias, we calculated the proportion of phenotypic variation explained (PVE) and the F statistic.

If the F statistic is <10, these genetic variables are eliminated. According to the relevant setting criteria above, a total of 7-1786 independent IVs for immunophenotypes were obtained, and these IVs could explain 0.240% (0.004%–3.652%) of the variation in their respective immune traits.

Statistical analysis

Multiple methods were employed to understand whether immune traits have a causal relationship on the risk of IgA nephropathy, namely inverse variance weighting (IVW), MR-Egger, weighted median, simple mode, weighted mode and MR pleiotropy residual sum and outlier (MR-PRESSO). Among them, the IVW method was used as the main MR analyses (≥3SNPs constructed random effects model, <3SNPs constructed fixed effect model). The Cochran’s Q test was applied to assess the heterogeneity of the IVW model, with p < 0.05 indicating heterogeneity. The MR-Egger regression intercept and MR-PRESSO test were used to test pleiotropy. If the regression intercept is not zero and P for intercept <0.05, this indicates the presence of horizontal pleiotropy. The MR-PRESSO test can detect potentially abnormal SNPs, and then the MR analysis can be re-performed after the abnormal values are eliminated. In addition, we performed a leave-one out analysis to assess whether the estimates were driven by a single SNP.

All statistical analyses were performed using R version 4.3.1 and the TwoSampleMR (0.5.4) packages and MRPRESSO (4.0.0). We used the publicly available GWAS summary statistics and therefore did not require ethical approval in this study.

Results

As shown in the Figures 2 and 3, by using IVW MR as the primary method, there were 14 pairs of RC traits/IgA nephropathy, 3 pairs of AC/IgA nephropathy, 10 pairs of MFI/IgA nephropathy, 1 pair of MP/IgA nephropathy that achieved a significant association (p < 0.05). In 14 pairs RC traits/IgA nephropathy, immune traits were classified according to the seven panels, of which 5 were classified as Tregs, 4 belonged to B cells, 3 belonged to monocytes, and 2 from TBNK. In 3 pairs AC traits/IgA nephropathy, 2 immune traits belonged to TBNK, 1 immune trait was classified as monocyte. In 10 pairs MFI/IgA nephropathy, maturation stages of T-cell panel had the most significant associations than other panels. The MP/IgA nephropathy pair belonged to the DC panel. Detailed analysis results of each trait were presented in supplementary Tables 1–3 and Figures 4–7.

Figure 2.

Figure 2.

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The Forest plot of immune cell traits effect on IgA nephropathy. OR, odds ratio; CI, confidence interval; P-val, the p-value of IVW MR analysis.

Figure 3.

Figure 3.

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Volcano plot of immune cell traits effect on IgA nephropathy. The red dots indicate risk factors, the yellow plots represent protective factors and the blue dots represent inconsistent direction.

Figure 4.

Figure 4.

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The scatter plots of the causal effect the SNP effect size of relative cell (RC) count and the corresponding effect size estimates of IgA nephropathy. What is shown in the figure is the regression line of inverse variance weighted, MR-egger, weighted median, simple mode and weighted mode. The slope of the straight line indicates the magnitude of causality. The x-axis showed the SNP effect on each relative cell count. The y-axis shows the SNP effect on IgA nephropathy. (A): IgD+ B cell %B cell. (B): IgD + CD24- B cell %B cell. (C): IgD + CD24+ B cell %lymphocyte. (D): Activated CD4 Treg %CD4 Treg. (E): Activated & resting CD4 Treg %CD4+ T cell. (F): Activated & secreting CD4 Treg %CD4+ T cell. (G): transitional B cell %B cell. (H): CD14- CD16+ monocyte %monocyte. (I): CD14+ CD16- monocyte %monocyte. (J): CD16+ monocyte %monocyte. (K): NKT %T cell. (L): NKT %lymphocyte. (M):CD127- CD8+ T cell %T cell. (N): CD28- CD8+ T cell %T cell.

Figure 5.

Figure 5.

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The scatter plots of the effect size for each SNP on median fluorescence intensity (MFI), morphological parameters (MP), absolute cell (AC) counts and IgA nephropathy. The x-axis showed the SNP effect on each immune trait. The y-axis shows the SNP effect on IgA nephropathy. (A): CD25 on B cell. (B): CD3 on Effector Memory CD4+ T cell. (C): CD3 on CD28+ CD4-CD8- T cell. (D): HVEM on Terminally Differentiated CD4+ T cell. (E): CD64 on CD14+ CD16+ monocyte. (F): CD4 on naive CD4+ T cell. (G): CD80 on CD62L + myeloid Dendritic Cell. (H): CD45 on CD33dim HLA DR-. (I): CD8 on Terminally Differentiated CD8+ T cell. (J): HLA DR on CD33- HLA DR+. (K): FSC-A on granulocyte. (L): CD14+ CD16- monocyte Absolute Count. (M): CD4+ T cell Absolute Count. (N): HLA DR + NK Absolute Count.

Figure 6.

Figure 6.

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Leave-one-out analyses for the causal estimates of RC on IgA nephropathy. (A): IgD+ B cell %B cell. (B): IgD + CD24- B cell %B cell. (C): IgD + CD24+ B cell %lymphocyte. (D): Activated CD4 Treg %CD4 Treg. (E): Activated & resting CD4 Treg %CD4+ T cell. (F): Activated & secreting CD4 Treg %CD4+ T cell. (G): transitional B cell %B cell. (H): CD14- CD16+ monocyte %monocyte. (I): CD14+ CD16- monocyte %monocyte. (J): CD16+ monocyte %monocyte. (K): NKT %T cell. (L): NKT %lymphocyte. (M): CD127- CD8+ T cell %T cell. (N): CD28- CD8+ T cell %T cell.

Figure 7.

Figure 7.

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Leave-one-out analyses for the causal estimates of MFI, MP, AC counts on IgA nephropathy. (A): CD25 on B cell. (B): CD3 on Effector Memory CD4+ T cell. (C): CD3 on CD28+ CD4-CD8- T cell. (D): HVEM on Terminally Differentiated CD4+ T cell. (E): CD64 on CD14+ CD16+ monocyte. (F): CD4 on naive CD4+ T cell. (G): CD80 on CD62L + myeloid Dendritic Cell. (H): CD45 on CD33dim HLA DR-. (I): CD8 on Terminally Differentiated CD8+ T cell. (J): HLA DR on CD33- HLA DR+. (K): FSC-A on granulocyte. (L): CD14+ CD16- monocyte Absolute Count. (M): CD4+ T cell Absolute Count. (N): HLA DR + NK Absolute Count.

Given the false positive results, the p-values were corrected using false discovery rate (FDR) in different trait types and panels. After FDR correction, we found only one immunophenotype that was protective against IgA nephropathy. The IVW method showed that the odds ratio of herpesvirus entry mediator(HVEM) on terminally differentiated CD4+ T cell (maturation stages of T-cell panel) on IgA nephropathy risk was estimated to be 0.727 (95%CI: 0.624-0.847, p = 4.20e − 05, PFDR = 0.023), and can be proven in the weighted median (OR = 0.743, 95%CI: 0.596-0.927, p = 0.008). The causal estimates from MR-Egger, simple mode, weighted mode were consistent with IVW method, although the results were non-significant (Figure 5). In addition, heterogeneity was not detected by the heterogeneity and pleiotropy test in the sensitivity analysis, and the possibility of horizontal pleiotropy was excluded by the MR-Egger intercept and MR-PRESSO global test, which indicated the robustness of the causal relationship observed. Scatter plots and a leave-one analysis also suggest the stability of the results (Figure 7).

Discussion

At present, the widely accepted pathogenesis of IgA nephropathy is the ‘four-hit hypothesis’, which is closely related to the immune system, but its role in the progression of IgA nephropathy is still complicated and unclear. To this end, we explored the causal relationship between immune traits and IgA nephropathy according to publicly available GWAS data. Our results showed that among the four immune traits (MFI, RC, AC, and MP), 28 immunophenotypes had significant causal effects on IgA nephropathy, of which 14 immunophenotypes were associated with increased IgA nephropathy risk and 14 were associated with a reduced risk of IgA nephropathy.

After FDR correction, we observed that HVEM on terminally differentiated CD4+ T cell was significantly associated with a reduced risk of IgA nephropathy. HVEM, a member of TNFRSF (tumor necrosis factor receptor superfamily), is a type I transmembrane glycoprotein. HVEM is present in almost all internal organs, with the highest expression in the lungs, kidneys and liver. In addition, HVEM is widely expressed on a variety of immune cells, including dendritic cells, primary T and B cells, NK cells, monocytes, and neutrophils [24,25]. B- and T- lymphocyte attenuator (BTLA) is an important co-suppressor receptor with the ligand HVEM. HVEM’s interaction with BTLA is the earliest known link between Ig structure and the TNFR family. HVEM has other ligands besides BTLA, including CD160, LIGHT(lymphotoxin-like inducible protein that competes with glycoprotein D for herpes virus entry on T cells), lymphotoxin-A, and herpes simplex virus glycoprotein D. HVEM binding to BTLA inhibits T cell and B cell activation, proliferation and cytokine production [26]. HVEM played a dual role in regulating T cells, with HVEM binding to BTLA/CD160 triggering a co-inhibitory signal, while HVEM transmitting a co-stimulatory signal when binding to LIGHT/LT-α. Therefore, HVEM is generally thought to depend on the molecular switching of the ligand to which it is bound [27]. With the deepening of the research, it was found that immune checkpoint not only played an important role in tumor diseases, but also played a central role in autoimmune diseases [28]. In patients with rheumatoid arthritis, it was found that BTLA expression was increased and HVEM expression was decreased in circulating T lymphocytes [29]. Similarly, overexpression of HVEM has been found in skin samples from patients with systemic sclerosis [30]. In inflammatory bowel disease, HVEM has been reported as a risk gene by genome-wide association studies [31]. At present, the study on HVEM in IgA nephropathy has not been reported. We speculate that HVEM expression on regulatory T cells is up-regulated after HVEM is stimulated and combined with BTLA, thus enhancing the inhibitory activity of regulatory T cells. The specific mechanism remains to be further studied and explored.

Considering that this study was an exploratory study, we observed that B lymphocytes, T lymphocytes, monocytes, dendritic cell and NK T cells played an important role in IgA nephropathy before FDR correction. A number of previous reports had shown that the number and function of Tregs in IgA nephropathy patients were abnormal [11,15,17,32–34]. Treg was a subgroup of T cells with immunosuppressive function, which played an immunomodulatory role in immune responses triggered by both self and foreign antigens. Lin FJ [15] et al. reported frequencies of CD45RA-FoxP3high activated Treg cells were significantly reduced in IgA nephropathy patients compared to healthy controls, while the frequencies of total FoxP3+CD4+ T cells, CD45RA+FoxP3low resting Treg, CD45RA-FoxP3low non-regulatory T cells did not differ between the two groups. Our results are consistent with these previous reports, showing that activated Treg% CD4 Treg, activated & secreting Treg% CD4+ T increased the risk of IgA nephropathy, while activated & resting Treg% CD4+ T was associated with a reduced risk of IgA nephropathy. This suggested that the renal injury in patients with IgA nephropathy was associated with reduced Tregs numbers and functionally deficient.

The main function of B cells was to participate in the immune response by secreting antibodies, and can act as antigen-presenting cells to mediate T cell activation. A large number of previous studies had confirmed that B cell-mediated immune were involved in the pathogenesis of IgA nephropathy [12,35]. Studies [13] had shown that the CD19 + CD27+ memory B cells in tonsil and peripheral blood of patients with IgA nephropathy were significantly higher than those in healthy control group, and they were significantly correlated with hematuria and urinary protein. It has been reported in the literature that the frequency of circulating unswitched memory B cells and plasma blast cells in patients with IgA nephropathy were increased compared with the healthy control group. Moreover, the frequency of circulating unswitched memory B cells and plasma blast cells correlated positively with 24-h urinary protein concentration, suggesting that B cells played an important role in the occurrence and development of IgA nephropathy [36]. In the early stage of development, immature B cells only express IgM B cell antigen receptor (BCR), and mature B cells co-express IgM and IgD BCR, in which IgD BCR becomes the main antigen receptor. Recent studies had shown that IgD BCR prevent the rapid activation of B cells and the secretion of IgM antibodies [37], and IgD played an important role in CXCR4 function, which was a chemokine receptor necessary for germinal center function and affinity maturation [38]. Furthermore, IgD was involved in shaping the human preimmune naive B cell compartment, and the frequencies of IgM lo/-B cells in mature naive B cell compartmen lacking IgD were decreased [39]. Our results showed that IgD + B cell %B cells was associated with an increased risk of IgA nephropathy. To date, there has been limited research on the role of IgD + B cell in IgA nephropathy. Compared with healthy controls, the proportion of pre-switched B cells(CD19+ CD27+ IgD+) and plasmablasts (CD19+ CD27+ CD38+)in the peripheral circulation in IgA nephropathy patients was significantly reduced, while there was no significant difference between the proportions of naïve B cells(CD19+ CD27-, IgD+) and switched B cells (CD19+ CD27+ IgD-) [40]. This study only reported the changes of pre-switched B cell subsets containing IgD+, but the percentage of IgD + B cell subsets in IgA nephropathy was not reported in the literature. In addition, our results showed that IgD + CD24- B cell %B cell, IgD + CD24+ B cell %lymphocyte, transitional B cell % B cell reduced the risk of IgA nephropathy. These results suggested that the B cell receptor immune repertoire in IgA nephropathy was significantly altered. CD24 expression on human B cells has been widely used as an immunophenotypic marker of early B cells, with the highest expression in transitional B cells, followed by a sharp decline in mature naive B cells. Some studies had shown that the expression of CD24 on B cells was related to energy metabolism during differentiation, reflecting the differences in energy metabolism among different B cell subsets, and its role is different among B cell subsets [41]. Transitional B cells are the key developmental stage between immature B cells in bone marrow and peripheral mature B cells. Transitional B cells not only produce IL-10, but also regulate the proliferation of CD4 +T cells and differentiate into helper T (Th) effector cells [42]. However, Esteve Cols C et al. reported that the percentage of transitional B lymphocytes (CD19+ CD27-CD24highCD38high) in IgA nephropathy patients was lower than that in healthy controls [43]. Surely, transitional B cells contain a variety of other different subsets, and studies have found that the frequencies and function of transitional B cells may change in different autoimmune diseases [44]. Regretfully, the specific pathogenesis of transitional B cells in IgA nephropathy is rarely reported at present, and further studies are needed in the future.

It was currently believed that monocytes were the precursor of macrophages, which had obvious deformation movement, phagocytosis, removal of injured and senescent cells and their debris, and it was also involved in immune response [45,46]. Some studies have confirmed that CD16+ monocytes had a high tendency of spontaneous apoptosis and weak resistance to oxidative stress. Compared with CD16+ monocytes, CD16-monocytes have better anti-oxidative stress and can significantly reduce cell death [47,48]. Eljaszewicz A. et al. [49] found that compared with healthy controls, the number of intermediate monocytes (CD14++CD16+) increased significantly in IgA nephropathy patients, but the number of classical (CD14++CD16−) and non-classical monocytes (CD14 + CD16++) did not increase. No significant correlation was found between different monocyte subsets and biochemical parameters of IgA nephropathy. However, Esteve Cols C et al. [43] showed a lower percentage of classical monocytes (CD14 + CD16-) in patients with IgA nephropathy compared to healthy controls, with no significant differences observed in the percentage of intermediate (CD14 + CD16+) or non-classical monocytes (CD14lowCD16++). Sendic et al. [40] reported that compared with healthy control and autosomal dominant polycystic kidney disease patients, IgA nephropathy patients had a higher proportion of non-classical monocytes(CD14+ CD16++). No significant difference was observed in classical monocyte (CD14++, CD16-) or intermediate monocyte(CD14++ CD16+) proportions. In summary, the results of the above studies indicated that the changes of monocyte subsets in IgA nephropathy were not consistent at present, which may be influenced by sample size and population. Our study showed that CD14+ CD16 − monocyte absolute count, CD14+ CD16− monocyte %monocyte reduced the risk of IgA nephropathy, while CD14-CD16+ monocyte% monocyte, CD16+ monocyte%monocyte increased the risk of IgA nephropathy. Therefore, the specific mechanism of monocyte subsets in IgA nephropathy remains to be further studied.

Dendritic cells are lymphoid or myeloid cells that originate in the bone marrow and reside in peripheral and lymphoid tissue. It can be divided into three main DC subgroups: plasma cell-like DC (pDC), myeloid/conventional DC1 (cDC1), and myeloid/conventional DC2 (cDC2) [50]. Mature dendritic cells can express high levels of CD80,CD86 and other helper molecules. Intestinal dendritic cells, on the one hand, can induce B cells to differentiate into IgA-secreting cells by promoting T cell activation, proliferation and differentiation, on the other hand, they can also mediate IgA1 class switch by secreting factors such as BAFF and APRIL [51,52]. During the transport process, IgA-secreting plasma cells enter the circulation and secrete a large amount of gd-IgA1, which in turn induced complement activation and inflammation in the kidney and aggravates the injury of IgA nephropathy. However, the increased expression of CD80 in CD62L + myeloid dendritic appears to increase the risk of IgA nephropathy, but the current literature support is limited, and the detailed mechanism still needs further exploring.

Yano N [53] reported that HLA-DR-positive NK cells were significantly increased in IgA nephropathy patients, and HLA-DR-positive NK cells had greater ability to produce IFN-γ than HLA-DR-negative NK cells, thus exacerbating kidney injury [54]. Previous studies have shown that the decline in the number and function of NK cells was closely related to the disease progression of IgA nephropathy [55,56]. Recently Zeng H [13] further confirmed through single-cell RNA-sequencing that total NK (CD56 + CD3 ±) and NK-1 and NK-2 (CD56 + CD3-) cell numbers were significantly reduced in IgA nephropathy. The number of cells in the NK subpopulation were significantly negatively correlated with clinical parameters of IgA nephropathy, including levels of urine protein creatinine ratio (UPCR), gd-IgA1, and IgA, suggesting that NK cells in IgA nephropathy were depleted and decreased and correlated with disease presentation. Our results were consistent with these findings. Chronic viral infection can up-regulate HLA-C expression and inhibit cytotoxic function of NK cells. HLA-C expression levels were generally upregulated in IgA nephropathy patients, suggesting that NK cell activation and cytotoxic functions were strongly inhibited. The specific mechanism by which the decrease of NK cells aggravates the risk of IgA nephropathy remains to be further studied and explored.

To our knowledge, this is the first study to investigate the causal relationship between immune traits and IgA nephropathy using MR analysis. Although various methods were used to rule out horizontal pleiotropy and other confounding effects to ensure that these results are robust, there are some limitations to this study. Firstly, in order to include more genetic variants as instrumental variables for sensitivity analysis and pleiotropy analysis, the SNPs used in this study did not reach the traditional GWAS significance threshold (p < 5×10-8). In addition, the biological role of the selected SNPs is still unknown. Just as the leave one out results showed potential outliers in some SNPs, for this reason we used FDR correction to limit the possibility of false positives. Secondly, the sample size of the IgA nephropathy GWAS data was not large, especially the number of IgA nephropathy cases was significantly less than that of the control group, and the numbers of cases and the control numbers were seriously mismatched. Therefore, the current results should be interpreted with caution and further analysis based on larger GWAS studies is needed in the future. Thirdly, the incidence of IgA nephropathy is geographically different [57]. Studies have reported that the incidence of IgA nephropathy was higher in Asia, and the risk of progression was 36% higher than that of the European population. However, the GWAS data used in our study was based on the European population, so the conclusions of this study cannot be extended to other ethnic groups and were not universal. In addition, our findings only reported a causal relationship between immune traits and IgA nephropathy, but the underlying specific mechanisms need to be further studied.

Conclusions

In short, based on the GWAS data of immune traits and IgA nephropathy, we used MR analysis to explore the genetic relationship and potential causal association between the two, and the results showed that there was a causal relationship between HVEM on terminally differentiated CD4+ T cell and IgA nephropathy, highlighting the important role of the immune system in the mechanism of IgA nephropathy. This provides a useful clue for exploring the early prevention and treatment of IgA nephropathy.

Supplementary Material

supplement table 3.xlsx
IRNF_A_2381593_SM4114.xlsx (656.6KB, xlsx)
supplement table 2.csv
IRNF_A_2381593_SM4113.csv (959.6KB, csv)
supplement table 1.xls
IRNF_A_2381593_SM4112.xls (58KB, xls)

Acknowledgements

We thank all GWAS participants and investigators for make the summary statistics data publicly available.

Funding Statement

The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

Disclosure statement

The authors report there are no competing interests to declare.

Ethics

The study is a mendelian randomization study based on GWAS to analyze and explore exposure factors and outcome factors, and does not require ethical review and approval according to local legislation and institutional requirements.

Data availability statement

Summary statistics can be downloaded from the appropriate website (see Materials and methods for details). Further inquiries and requests can be directed to the corresponding author.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

supplement table 3.xlsx
IRNF_A_2381593_SM4114.xlsx (656.6KB, xlsx)
supplement table 2.csv
IRNF_A_2381593_SM4113.csv (959.6KB, csv)
supplement table 1.xls
IRNF_A_2381593_SM4112.xls (58KB, xls)

Data Availability Statement

Summary statistics can be downloaded from the appropriate website (see Materials and methods for details). Further inquiries and requests can be directed to the corresponding author.

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