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Causal relationship between Baff-R expression and normal pressure hydrocephalus: insights from Mendelian randomization analysis

BMC Neurology volume 25, Article number: 98 (2025) Cite this article

Abstract

Objectives

Previous studies have suggested a possible link between normal pressure hydrocephalus (NPH) and immune factors, but the causal relationship between NPH and Baff-R expression on immune cells remains enigmatic. This study used a Mendelian randomization (MR) method to elucidate this association.

Methods

The study used data from the Finngen genome-wide association study (GWAS) and included a large European cohort of 767 patients with NPH and 375,610 controls. Baff-R genetic results in 3,757 individuals of European ancestry had 22 Baff-R-related traits. Different MR techniques were used, and efficacy was assessed using heterogeneity and sensitivity analyses.

Results and conclusion

Among the 22 traits, 8 Baff-R-related traits were causally related to NPH. The genetic prediction indicates that Baff-R, particularly in the area of BAFF − R on unswitched memory B cell, BAFF − R on IgD + CD38 − B cell, BAFF − R on CD24 + CD27 + B cell, BAFF − R on IgD − CD38 − B cell, BAFF − R on IgD + CD38dim B cell, BAFF − R on IgD + CD24 + B cell, BAFF − R on IgD + CD38 − naive B cell, BAFF − R on memory B cell may decrease risks on the development of NPH. These findings may help us to understand the immune mechanisms associated with NPH and help to develop future biomarkers related to the disease.

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Introduction

Normal pressure hydrocephalus (NPH), characterized by ventricular enlargement and normal cerebrospinal fluid (CSF) pressure, presents with the clinical triad of gait disturbance, incontinence, and cognitive decline [1]. Depending on whether there is a clear cause, NPH can be divided into secondary normal pressure hydrocephalus (SNPH) and idiopathic normal pressure hydrocephalus (INPH) [2]. Given the significant economic burden NPH imposes on patients and society, a comprehensive understanding of its pathogenesis is clinically crucial [3]. However, the underlying cause of NPH remains unclear for many patients [4]. In recent years, people have paid more and more attention to the relationship between immune inflammation and NPH.

B-cell activating factor (BAFF), a tumor necrosis factor(TNF) family member [5], is up-regulated in response to genetic alterations and viral infections, strongly associated with autoimmunity, and appears involved in neuroinflammatory processes [6]. BAFF-R, one of three known receptors for BAFF [7], binds specifically to BAFF, controlling B cell survival [8]. Abnormal BAFF-R expression can be observed in neurological diseases such as multiple sclerosis and Alzheimer’s disease [9, 10]. In addition, these neurological disorders often co-occur with NPH, prompting investigation of the link between BAFF-R and its pathogenesis. The pathophysiology of NPH involves arachnoid fibrosis, pathological angiogenesis, and neuroinflammation [11, 12]. Although immune-inflammatory molecules like TGF-β, TNF-α, IL-1β, and IL-6 are closely associated with these mechanisms, the relationship between BAFF-R and NPH remains unclear.

Traditional observational studies are prone to biases arising from confounding variables and reverse causality, which can undermine their overall credibility. In contrast, Mendelian randomization (MR), which leverages data from genome-wide association studies (GWAS), has become a powerful method for exploring causal relationships. This study employs MR to investigate the genetic variants of BAFF-R on immune cells as instrumental variables (IVs), with the goal of determining the causal link between BAFF-R expression on immune cells and the development of NPH.

Material and method

In this study, a MR approach was employed to analyze the cause-and-effect relationship. The exposure variables consisted of BAFF-R expression on immune cells, while the IVs were single nucleotide polymorphisms (SNPs) strongly associated with BAFF-R on immune cells. The primary outcome of interest was NPH. To ensure the robustness of the results, heterogeneity and sensitivity analyses were conducted.

Data sources

The exposures and outcomes were obtained from publicly available databases, and secondary analyses were conducted. Therefore, ethical approval was not required for this study, which focused on European populations for both the exposure and outcome samples.

We obtained GWAS data for BAFF-R on immune cells from the ieu open GWAS project website (https://gwas.mrcieu.ac.uk/datasets) to explore the potential effects of BAFF-R on immune cells in NPH [13]. And GWAS data for NPH was obtained at the Finngen GWAS summary statistics website (https://r9.finngen.fi/). A group of 3,757 Europeans were tested for the genetic variation in BAFF-R on immune cells [14]. All data used in the analysis were collected by flow cytometry, and 22 BAFF-R-related features were collected from this cohort. All 22 traits were median fluorescence intensity (MFI). The expression levels of the BAFF-R protein in different cell subgroups are indirectly reflected in the MFI group. Increasing the number of cells expressing BAFF-R or the level of BAFF-R expression in specific cell subsets can enhance the intensity of BAFF-R fluorescence, even when the total cell count remains consistent. Supplementary Table S1 presents the GWAS IDs, names, and trait type information for BAFF-R-related traits. Furthermore, genetic data about NPH was acquired from the Finngen initiative for a substantial European sample set comprising 767 cases and 375,610 controls [15].

Selection of IVs

To function successfully as IVs, SNPs must fulfill three essential assumptions. Firstly, it is crucial to establish a strong correlation between SNPs and the exposure of interest. Additionally, it is necessary to set a minimum threshold of ≥ 10 for the strength of IVs as determined by F-values to mitigate potential bias in estimates of causal effects. Any value below this threshold may pose a significant risk of introducing bias [16]. Afterward, the principle of exclusiveness requires that IVs are not directly associated with the outcome. Their impact ought to be moderated only by exposure, guaranteeing the absence of genetic pleiotropy. Finally, independence: Independence means that IVs are not subject to confounders that influence both exposure and outcome [17]. MR simulates the random distribution process in the population by utilizing the random segregation and recombination of genetic variation during gamete formation. Notably, the integrity of the MR analysis is enhanced as the technique is usually not related to external environmental confounders [18,19,20].

The following parameters were implemented to ensure the authenticity and reliability of the causal relationship between BAFF-R on immune cells and NPH. First, we meticulously selected significant SNPs from the GWAS database of BAFF-R-associated traits. The power was set to F ≥ 10 (Supplementary Table S1), corresponding to the association significance level for “IVs” which is widely regarded as a robust screening threshold for IVs. Additionally, we applied a screening threshold of P < 5 × 10⁻⁶ to ensure an adequate number of SNPs. Second, the coefficient of linkage disequilibrium (LD) was set at r² = 0.001, with a maximum LD region span of 10,000 kb. Third, SNPs associated with BAFF-R were extracted from the NPH GWAS database. Finally, the data from the two relevant datasets were combined, and SNPs with palindromic structures were excluded.

Statistical analyses

R software version R-4.3.1 conducted a statistical analysis of all data. All estimates were considered significant at the level of ≤ 0.05. This study utilized multiple methodologies to deduce the potential causal impacts of BAFF-R-related traits on NPH. The employed methods comprise the MR-Egger, Inverse Variance Weighted (IVW), Simple Mode, Weighted Mode, and Wald Ratio approaches. For instances where three or more SNPs were present, the MR-Egger and IVW methods were utilized. SNP heterogeneity was assessed using Cochran’s Q test, deemed significant with a P-value of < 0.05. If no pleiotropy and heterogeneity were present, preference was granted to the outcomes obtained from the IVW method. To prevent errors caused by multiple hypothesis testing, we used the False Discovery Rate (FDR) method created by Benjamini and Hochberg to regulate the p-value and manage the total error rate. In the MR analysis, we used the odds ratio (OR) to determine the link between outcome and exposure. If OR = 1, it indicates that the exposure has no impact on the outcome. If OR > 1, it implies that the exposure is linked to an increased likelihood of the outcome. On the other hand, if OR < 1, the exposure is associated with a decreased outcome probability.

The MR-Egger regression analysis was used to assess potential horizontal pleiotropy effects associated with the included SNPs. A significant deviation from zero in the intercept term of the MR-Egger method would suggest the presence of horizontal pleiotropy. Additionally, we performed sensitivity analysis using the Leave-one-out sensitivity test, where the results were reanalyzed by systematically excluding individual SNPs. The goal was to determine whether the exclusion of any single SNP caused a significant change in the findings. The reliability of the MR results was considered validated if the exclusion of any SNP did not notably affect the overall outcomes.

Furthermore, the selected SNPs underwent a thorough cross-validation procedure utilizing the website: http://www.phenoscanner.medschl.cam.ac.uk/ can to identify additional characteristics that could potentially impact the study outcomes. Any SNPs that showed correlations with these traits were subsequently removed, successfully reducing the likelihood of confounding factors influencing the results.

Results

Selection of IVs

After strict quality control, we finally found SNPs that were consistent with 22 BAFF-R-related traits and NPH GWAS. The SNP’s ID, P-value, β-value, effect allele (EA), other alleles and standard error (SE) were comprehensively merged for later analysis and presented in Supplementary Table S1. Finally, we found that only 8 BAFF-R-related traits showed significant correlation with NPH (Supplementary Figure S1).

Exploration of the causation of Baff-R on immune cells on NPH

As demonstrated in Table 1, a significant correlation suggests that eight traits related to BAFF-R are closely connected to the vulnerability of NPH, acting as protective measures against its onset. All 8 BAFF-R-related trait types were MFI and B cell panels. MFI indicates the degree to which BAFF-R is expressed within a specific cellular subset of B cells. After adjusting for FDR (P-FDR < 0.20), protective effects of eight traits related to BAFF-R were detected on NPH: BAFF − R on unswitched memory B cell, BAFF − R on IgD + CD38 − B cell, BAFF − R on CD24 + CD27 + B cell, BAFF − R on IgD − CD38 − B cell, BAFF − R on IgD + CD38dim B cell, BAFF − R on IgD + CD24 + B cell, BAFF − R on IgD + CD38 − naive B cell, BAFF − R on memory B cell (Figs. 1 and 2). In addition, the robustness of the negative correlation results between the eight traits associated with BAFF-R and NPH was ensured by MR-Egger intercept and MR-PRESSO overall tests (Table 2). The scatter plots, funnel plots and leave-one-out plots (Figs. 3 and 4, Supplementary Figure S2) also indicated the stability of the results.

Table 1 The MR analysis results of BAFF-R related traits on NPH
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Table 2 The sensitivity analysis results of BAFF-R related traits on NPH
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Fig. 1
figure 1

The forest plot of the causation of Baff-R on immune cells on NPH

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Fig. 2
figure 2

The volcano plot of the causation of Baff-R on immune cells on NPH

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Fig. 3
figure 3

The scatter plot of the causation of Baff-R on immune cells on NPH. (A) scatter plots for BAFF − R on unswitched memory B cell on NPH. (B) scatter plots for BAFF − R on IgD + CD38 − B cell on NPH. (C) scatter plots for BAFF − R on CD24 + CD27 + B cell on NPH. (D) scatter plots for BAFF − R on IgD − CD38 − B cell on NPH. (E) scatter plots for BAFF − R on IgD + CD38dim B cell on NPH. (F) scatter plots for BAFF − R on IgD + CD24 + B cell on NPH. (G) scatter plots for BAFF − R on IgD + CD38 − naive B cell on NPH. (H) scatter plots for BAFF − R on memory B cell on NPH

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Fig. 4
figure 4

The funnel plots for Baff-R on immune cells on NPH. (A) funnel plots for BAFF − R on unswitched memory B cell on NPH. (B) funnel plots for BAFF − R on IgD + CD38 − B cell on NPH. (C) funnel plots for BAFF − R on CD24 + CD27 + B cell on NPH. (D) funnel plots for BAFF − R on IgD − CD38 − B cell on NPH. (E) funnel plots for BAFF − R on IgD + CD38dim B cell on NPH. (F) funnel plots for BAFF − R on IgD + CD24 + B cell on NPH. (G) funnel plots for BAFF − R on IgD + CD38 − naive B cell on NPH. (H) funnel plots for BAFF − R on memory B cell on NPH

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Exploration of the causation of NPH on Baff-R on immune cells

We conducted a reverse MR to examine if NPH causally affects Baff-R on immune cells. Nevertheless, we found no causative link between NPH and Baff-R on immune cells. Therefore, this is an indication that there is no reverse causal association between NPH and Baff-R on immune cells (Table 3).

Table 3 Exploration of the causation of NPH on Baff-R on immune cells
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Discussion

Using comprehensive publicly available genetic data, we explored causal associations between 22 Baff-R-related immune cell traits and NPH. The causal association between Baff-R-related immunophenotypes and NPH was investigated for the first time. The study determined that NPH had no causal effects on Baff-R-related immunophenotypes, and eight Baff-R-related immunophenotypes showed a potential causal effect on NPH (FDR < 0.20) [21].

The three widely accepted pathophysiological mechanisms of NPH are arachnoid fibrosis [22, 23], pathological angiogenesis [24, 25], and neuroinflammation [11, 26]. Baff is strongly associated with fibrosis, angiogenesis, and neuroinflammation. In our study, BAFF-R was negatively correlated with NPH. Therefore, we hypothesize that BAFF and its receptor BAFF-R may be involved in all three primary mechanisms of NPH.

The involvement of BAFF in fibrosis, demonstrated in previous studies including liver fibrosis [27, 28], multiple sclerosis [29], and interstitial fibrosis [30], contradicts our finding where the level of BAFF-R expressed on immune cells was inversely correlated with the occurrence of NPH. Subarachnoid fibrosis is a crucial mechanism in forming NPH and may be related to the production of inflammatory factors in chronic inflammatory response. In NPH subarachnoid fibrosis, TGF-β emerges as a critical molecule. Previous studies have shown that the BAFF binding to BAFF-R decreases TGF-β levels [31]. Therefore, we hypothesize that BAFF specifically binds to BAFF-R, activating B cells, promoting Treg cell apoptosis, reducing TGF-β, inhibiting the TGF-β pathway, and thus inhibiting subarachnoid fibrosis.

The tumor necrosis factor (TNF) family is vital in the process of angiogenesis [32, 33]. BAFF, also a member of the TNF family, binds explicitly to BAFF-R, increasing TNF-α levels, activating the NF-kb pathway, elevating angiogenic factors, and promoting angiogenesis [34]. Additionally, BAFF specifically binding to BAFF-R activates B cells to produce various cytokines, such as IFN-γ [35, 36]. IFN-γ acts to inhibit angiogenesis [37, 38]. Furthermore, BAFF binding specifically to BAFF-R modulates B and T cells, reducing TGF-β levels [31]. TGF-β negatively correlates with VEGFA expression through TGF-β signaling and can inhibit angiogenesis [39, 40]. The combined effect of these mechanisms may confirm our conclusion that BAFF-R levels are inversely related to NPH.

Neuroinflammation is one of the essential mechanisms in the pathogenesis of NPH, mainly involving glial cell activation [41], the secretion of inflammatory cytokines [42], and alterations to the blood-brain barrier [43]. When BAFF binds to BAFF-R, it can also promote neuronal survival through the JAK-STAT signaling pathway activated by IFN-γ and IL-10 [44, 45]. This aligns precisely with the results of our study.

This research conducted a two-sample MR analysis of the largest published NPH GWAS cohort results. Conclusions are drawn based on genetic instrumental variables using various MR analysis methods. Nevertheless, our research has limitations. Firstly, the small sample size of the current NPH may lead to some false positives in our results. Secondly, additional stratified analysis of the population cannot be performed due to insufficient individual information. Thirdly, because the study used a European database and did not apply to other ethnic groups, the generalizability of our findings is limited. Fourthly, we used a less stringent threshold to evaluate the results. This may increase false-positive results but allows a more comprehensive evaluation of the robust correlation between BAFF-R-related immunophenotypes and NPH. Finally, although we have adopted a variety of methods to detect and adjust horizontal pleiotropy, we still need to pay attention to that certain tool variables may be affected by pleiotropy. Therefore, the stability of the result may still need to be further verified.

Conclusions

In conclusion, our comprehensive bidirectional MR analysis has shown the causal relationships between numerous BAFF-R-related immunophenotypes and NPH. This has highlighted the intricate interaction patterns between these immunophenotypes and NPH, emphasizing their complexity. Moreover, our study has minimized the effect of inescapable confounding variables, reverse causation and other factors. This discovery could pave the way for researchers to investigate the biological mechanisms of NPH further, potentially resulting in earlier interventions and treatment. Our findings augment the existing immunological evidence, offering essential insights into the prevention of NPH.

Data availability

Data is provided within the manuscript or supplementary information files.

References

  1. Siraj S. An overview of normal pressure hydrocephalus and its importance: how much do we really know? J Am Med Dir Assoc. 2011;12(1):19–21.

    Article  PubMed  Google Scholar 

  2. Huang W, Fang X, Li S, Mao R, Ye C, Liu W, et al. Shunt surgery efficacy is correlated with baseline cerebrum perfusion in idiopathic normal pressure hydrocephalus: A 3D pulsed Arterial-Spin labeling study. Front Aging Neurosci. 2022;14:797803.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Del Bigio MR. Epidemiology and direct economic impact of hydrocephalus: a community based study. Can J Neurol Sci. 1998;25(2):123–6.

    Article  PubMed  Google Scholar 

  4. Skalický P, Mládek A, Vlasák A, De Lacy P, Beneš V, Bradáč O. Normal pressure hydrocephalus-an overview of pathophysiological mechanisms and diagnostic procedures. Neurosurg Rev. 2020;43(6):1451–64.

    Article  PubMed  Google Scholar 

  5. Thompson JS, Bixler SA, Qian F, Vora K, Scott ML, Cachero TG, et al. BAFF-R, a newly identified TNF receptor that specifically interacts with BAFF. Science. 2001;293(5537):2108–11.

    Article  PubMed  CAS  Google Scholar 

  6. Möckel T, Basta F, Weinmann-Menke J, Schwarting A. B cell activating factor (BAFF): structure, functions, autoimmunity and clinical implications in systemic lupus erythematosus (SLE). Autoimmun Rev. 2021;20(2):102736.

    Article  PubMed  Google Scholar 

  7. Rodig SJ, Shahsafaei A, Li B, Mackay CR, Dorfman DM. BAFF-R, the major B cell-activating factor receptor, is expressed on most mature B cells and B-cell lymphoproliferative disorders. Hum Pathol. 2005;36(10):1113–9.

    Article  PubMed  CAS  Google Scholar 

  8. Moon EY, Yi KY, Lee S. An increase in B cell apoptosis by interfering BAFF-BAFF-R interaction with small synthetic molecules. Int Immunopharmacol. 2011;11(10):1523–33.

    Article  PubMed  CAS  Google Scholar 

  9. Leffler J, Trend S, Ward NC, Grau GE, Hawke S, Byrne SN, et al. Circulating memory B cells in early multiple sclerosis exhibit increased IgA(+) cells, globally decreased BAFF-R expression and an EBV-Related IgM(+) cell signature. Front Immunol. 2022;13:812317.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  10. Matthews AL, Koo CZ, Szyroka J, Harrison N, Kanhere A, Tomlinson MG. Regulation of leukocytes by TspanC8 tetraspanins and the molecular Scissor ADAM10. Front Immunol. 2018;9:1451.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Bräutigam K, Vakis A, Tsitsipanis C. Pathogenesis of idiopathic normal pressure hydrocephalus: A review of knowledge. J Clin Neurosci. 2019;61:10–3.

    Article  PubMed  Google Scholar 

  12. Ma L, Wang W, Zhao Y, Liu M, Ye W, Li X. Application of LRG mechanism in normal pressure hydrocephalus. Heliyon. 2024;10(1):e23940.

    Article  PubMed  CAS  Google Scholar 

  13. Orrù V, Steri M, Sidore C, Marongiu M, Serra V, Olla S, et al. Complex genetic signatures in immune cells underlie autoimmunity and inform therapy. Nat Genet. 2020;52(10):1036–45.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Sidore C, Busonero F, Maschio A, Porcu E, Naitza S, Zoledziewska M, et al. Genome sequencing elucidates Sardinian genetic architecture and augments association analyses for lipid and blood inflammatory markers. Nat Genet. 2015;47(11):1272–81.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  15. Kurki MI, Karjalainen J, Palta P, Sipilä TP, Kristiansson K, Donner KM, et al. Author correction: FinnGen provides genetic insights from a well-phenotyped isolated population. Nature. 2023;615(7952):E19.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  16. Burgess S, Thompson SG. Avoiding bias from weak instruments in Mendelian randomization studies. Int J Epidemiol. 2011;40(3):755–64.

    Article  PubMed  Google Scholar 

  17. Hartwig FP, Borges MC, Horta BL, Bowden J, Davey Smith G. Inflammatory biomarkers and risk of schizophrenia: A 2-Sample Mendelian randomization study. JAMA Psychiatry. 2017;74(12):1226–33.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Birney E. Mendelian randomization. Cold Spring Harb Perspect Med. 2022;12(4).

  19. Bowden J, Holmes MV. Meta-analysis and Mendelian randomization: A review. Res Synth Methods. 2019;10(4):486–96.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Davey Smith G, Hemani G. Mendelian randomization: genetic anchors for causal inference in epidemiological studies. Hum Mol Genet. 2014;23(R1):R89–98.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  21. Wang C, Zhu D, Zhang D, Zuo X, Yao L, Liu T, et al. Causal role of immune cells in schizophrenia: Mendelian randomization (MR) study. BMC Psychiatry. 2023;23(1):590.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Motohashi O, Suzuki M, Shida N, Umezawa K, Ohtoh T, Sakurai Y, et al. Subarachnoid haemorrhage induced proliferation of leptomeningeal cells and deposition of extracellular matrices in the arachnoid granulations and subarachnoid space. Immunhistochemical study. Acta Neurochir (Wien). 1995;136(1–2):88–91.

    Article  PubMed  CAS  Google Scholar 

  23. Bech RA, Juhler M, Waldemar G, Klinken L, Gjerris F. Frontal brain and leptomeningeal biopsy specimens correlated with cerebrospinal fluid outflow resistance and B-wave activity in patients suspected of normal-pressure hydrocephalus. Neurosurgery. 1997;40(3):497–502.

    PubMed  CAS  Google Scholar 

  24. Koto A, Rosenberg G, Zingesser LH, Horoupian D, Katzman R. Syndrome of normal pressure hydrocephalus: possible relation to hypertensive and arteriosclerotic vasculopathy. J Neurol Neurosurg Psychiatry. 1977;40(1):73–9.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  25. Casati M, Arosio B, Gussago C, Ferri E, Magni L, Assolari L, et al. Down-regulation of adenosine A1 and A2A receptors in peripheral cells from idiopathic normal-pressure hydrocephalus patients. J Neurol Sci. 2016;361:196–9.

    Article  PubMed  CAS  Google Scholar 

  26. Yang F, Yang L, Fang X, Deng Y, Mao R, Yan A, et al. Increased cerebrospinal fluid levels of soluble triggering receptor expressed on myeloid cells 2 and Chitinase-3-Like protein 1 in idiopathic Normal-Pressure hydrocephalus. J Alzheimers Dis. 2023;93(4):1341–54.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  27. Kanemitsu-Okada K, Abe M, Nakamura Y, Miyake T, Watanabe T, Yoshida O et al. Role of B Cell-Activating factor in fibrosis progression in a murine model of Non-Alcoholic steatohepatitis. Int J Mol Sci. 2023;24(3).

  28. Dong P, Mei C, Yang Y, Zhou Y, Xu Y, Song L et al. Blocking BAFF alleviates hepatic fibrosis in Schistosoma japonicum-Infected mice. Pathogens. 2023;12(6).

  29. Krumbholz M, Faber H, Steinmeyer F, Hoffmann LA, Kümpfel T, Pellkofer H, et al. Interferon-beta increases BAFF levels in multiple sclerosis: implications for B cell autoimmunity. Brain. 2008;131(Pt 6):1455–63.

    Article  PubMed  CAS  Google Scholar 

  30. Hamada T, Samukawa T, Kumamoto T, Hatanaka K, Tsukuya G, Yamamoto M, et al. Serum B cell-activating factor (BAFF) level in connective tissue disease associated interstitial lung disease. BMC Pulm Med. 2015;15:110.

    Article  PubMed  PubMed Central  Google Scholar 

  31. Zhang B, Hu M, Zhang P, Cao H, Wang Y, Wang Z, et al. BAFF promotes regulatory T-cell apoptosis and blocks cytokine production by activating B cells in primary biliary cirrhosis. Braz J Med Biol Res. 2013;46(5):433–9.

    Article  PubMed  PubMed Central  Google Scholar 

  32. Naldini A, Carraro F. Role of inflammatory mediators in angiogenesis. Curr Drug Targets Inflamm Allergy. 2005;4(1):3–8.

    Article  PubMed  CAS  Google Scholar 

  33. Waters JP, Pober JS, Bradley JR. Tumour necrosis factor and cancer. J Pathol. 2013;230(3):241–8.

    Article  PubMed  CAS  Google Scholar 

  34. Jin F, Zheng X, Yang Y, Yao G, Ye L, Doeppner TR, et al. Impairment of hypoxia-induced angiogenesis by LDL involves a HIF-centered signaling network linking inflammatory TNFα and angiogenic VEGF. Aging. 2019;11(2):328–49.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  35. Scapini P, Hu Y, Chu CL, Migone TS, Defranco AL, Cassatella MA, et al. Myeloid cells, BAFF, and IFN-gamma Establish an inflammatory loop that exacerbates autoimmunity in Lyn-deficient mice. J Exp Med. 2010;207(8):1757–73.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  36. Lolansen SD, Rostgaard N, Oernbo EK, Juhler M, Simonsen AH, MacAulay N. Inflammatory markers in cerebrospinal fluid from patients with hydrocephalus: A systematic literature review. Dis Markers. 2021;2021:8834822.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Hayakawa Y, Takeda K, Yagita H, Smyth MJ, Van Kaer L, Okumura K, et al. IFN-gamma-mediated Inhibition of tumor angiogenesis by natural killer T-cell ligand, alpha-galactosylceramide. Blood. 2002;100(5):1728–33.

    PubMed  CAS  Google Scholar 

  38. Sato N, Nariuchi H, Tsuruoka N, Nishihara T, Beitz JG, Calabresi P, et al. Actions of TNF and IFN-gamma on angiogenesis in vitro. J Invest Dermatol. 1990;95(6 Suppl):s85–9.

    Article  Google Scholar 

  39. Geng L, Chaudhuri A, Talmon G, Wisecarver JL, Wang J. TGF-Beta suppresses VEGFA-mediated angiogenesis in colon cancer metastasis. PLoS ONE. 2013;8(3):e59918.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  40. Zhang J, Li C, Zheng Y, Lin Z, Zhang Y, Zhang Z. Inhibition of angiogenesis by arsenic trioxide via TSP-1-TGF-β1-CTGF-VEGF functional module in rheumatoid arthritis. Oncotarget. 2017;8(43):73529–46.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Hasan-Olive MM, Enger R, Hansson HA, Nagelhus EA, Eide PK. Pathological mitochondria in neurons and perivascular astrocytic endfeet of idiopathic normal pressure hydrocephalus patients. Fluids Barriers CNS. 2019;16(1):39.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  42. Braun M, Boström G, Ingelsson M, Kilander L, Löwenmark M, Nyholm D, et al. Levels of inflammatory cytokines MCP-1, CCL4, and PD-L1 in CSF differentiate idiopathic normal pressure hydrocephalus from neurodegenerative diseases. Fluids Barriers CNS. 2023;20(1):72.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  43. Wang Z, Zhang Y, Hu F, Ding J, Wang X. Pathogenesis and pathophysiology of idiopathic normal pressure hydrocephalus. CNS Neurosci Ther. 2020;26(12):1230–40.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  44. Li K, Yu W, Cao R, Zhu Z, Zhao G. Microglia-mediated BAFF-BAFFR ligation promotes neuronal survival in brain ischemia injury. Neuroscience. 2017;363:87–96.

    Article  PubMed  CAS  Google Scholar 

  45. Tada S, Yasui T, Nakatsuji Y, Okuno T, Koda T, Mochizuki H, et al. BAFF controls neural cell survival through BAFF receptor. PLoS ONE. 2013;8(7):e70924.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

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Acknowledgements

Not applicable.

Funding

This work was supported in part by grants from Neurosurgery First-class Discipline Funding Project of the Second Affiliated Hospital of Harbin Medical University.

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  1. The Second Affiliated Hospital of Harbin Medical University, Harbin, 150086, People’s Republic of China

    Wencai Wang, Luyao Ma, Menghao Liu, Yongqiang Zhao, Wei Ye & Xianfeng Li

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  1. Wencai Wang
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Contributions

Conceptualization: Wencai Wang, Luyao Ma, Menghao Liu, Yongqiang Zhao, and Wei Ye; acquisition, analysis, or interpretation of data: Wencai Wang and Luyao Ma; drafting of the manuscript: Wencai Wang; critical revision and editing of the manuscript: Wencai Wang, Luyao Ma, and Xianfeng Li. All authors read and approved the final version of the manuscript.

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Correspondence to Xianfeng Li.

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All data in the manuscript were obtained from public databases, GWAS data for BAFF-R on immune cells from the ieu open GWAS project website (https://gwas.mrcieu.ac.uk/datasets). GWAS data for NPH was obtained at the Finngen GWAS summary statistics website (https://r9.finngen.fi/).

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Wang, W., Ma, L., Liu, M. et al. Causal relationship between Baff-R expression and normal pressure hydrocephalus: insights from Mendelian randomization analysis. BMC Neurol 25, 98 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12883-025-04098-4

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  • DOI: https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12883-025-04098-4

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BMC Neurology

ISSN: 1471-2377

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