Causal Associations of Cardiovascular Proteins and Diabetic Nephropathy Revealed by Mediation and Phenome-Wide Mendelian Randomization
Article information
Abstract
Cardiovascular factors play a critical role in the progression of diabetic nephropathy (DN). This study utilized Mendelian randomization analysis to explore the causal relationships among cardiovascular proteins, risk factors, and DN. Using cis-protein quantitative trait loci (cis-pQTL) data for 90 cardiovascular proteins, we identified C-X3-C motif chemokine ligand 1 (CX3CL1) and colony-stimulating factor-1 (CSF-1) as potential therapeutic targets for DN. CX3CL1 was found to increase DN risk through mechanisms involving body mass index, fasting insulin, and hypertension. Conversely, CSF-1 appeared to protect against DN by reducing the number of monocytes expressing high levels of human leukocyte antigen. Additionally, targeting CX3CL1 could lower the risk of DN as well as other conditions, including acute renal injury, pituitary disorders, and necrotizing vasculopathies. These results highlight CX3CL1 and CSF-1 as promising novel therapeutic targets for DN.
INTRODUCTION
Diabetic nephropathy (DN) is a common microvascular complication of diabetes mellitus and a leading cause of chronic kidney disease [1]. Identifying and addressing the cardiovascular influences on DN are critical for its prevention and treatment [2]. Proteins, as products of gene expression, play pivotal roles in various biological processes and represent primary sources of therapeutic targets [3]. Mendelian randomization (MR) leverages single-nucleotide polymorphisms (SNPs) to explore causal relationships between exposures and outcomes from the perspective of genetic variation. This approach mitigates biases inherent in cellular and animal experiments and reduces the influence of confounding factors [4-6]. In this study, we utilized genome-wide association study (GWAS) data from European populations and applied drug-target, mediation, and phenome-wide MR (Phe-MR) to investigate the etiology of DN. Our objectives were to: (1) identify causal relationships between 90 cardiovascular proteins and DN; (2) comprehensively assess mediation effects and explore potential pathophysiological mechanisms involving 14 cardiovascular risk factors, eight cardiovascular diseases, and 731 immunophenotypes; and (3) extensively evaluate the impact of druggable proteins on diseases across different systems.
METHODS
This MR study was conducted in three stages. In the first stage, we used two-sample drug-target MR to evaluate the causal effects of 90 cardiovascular proteins on DN. The cis-protein quantitative trait loci (cis-pQTL) data for these proteins were obtained from cohort studies on heart failure by Stenemo et al. [7] and Ferreira et al. [8]. The selection criteria for pQTLs as instrumental variables were as follows: (1) P<5×10−8; (2) removal of linkage disequilibrium (kb=10,000 and r2=0.1); and (3) location within 200 kbp upstream or downstream of the cognate protein-encoding transcription start and stop sites [9]. The GWAS data for DN, comprising 4,111 cases and 308,539 controls, were sourced from the FinnGen database (https://www.finngen.fi/en) [10]. MR analysis was performed using six methods: MR Egger, weighted median, inverse variance weighted, simple mode, weighted mode, and Wald ratio. Causal relationships between cardiovascular proteins and DN were determined based on inverse variance weighted (for SNPs >1) or Wald ratio (for SNP=1) results after Bonferroni correction. In the second stage, we conducted mediation MR, incorporating 14 cardiovascular risk factors, eight cardiovascular diseases, and 731 immunophenotypes to identify pathways through which cardiovascular proteins influence DN. In the third stage, we performed Phe-MR analysis to investigate the effects of druggable proteins on diseases across various systems. Sensitivity analyses were conducted to assess the robustness of the MR results. All data analyses were performed using R version 4.2.3 (R Foundation for Statistical Computing, Vienna, Austria). As all summary-level GWAS data were publicly available, this study was exempt from ethical review (Supplemental Table S1).
RESULTS
Of the 90 cardiovascular proteins, 69 were included in the drug-target MR analysis. After Bonferroni correction, the results revealed significant genetic associations of C-X3-C motif chemokine ligand 1 (CX3CL1) (odds ratio [OR], 1.34; 95% confidence interval [CI], 1.17 to 1.54; adjusted P=0.003) and colony-stimulating factor-1 (CSF-1) (OR, 0.74; 95% CI, 0.63 to 0.88; adjusted P=0.026) with DN (Fig. 1A). CX3CL1 was identified as a risk factor for DN, while CSF-1 was identified as a protective factor. No anomalies were detected in heterogeneity, horizontal pleiotropy, or Steiger directionality tests. The effects of CX3CL1 and CSF-1 on DN were further validated externally (Fig. 1B).

Drug-target and mediation Mendelian randomization (MR) results for the relationship between cardiovascular proteins and diabetic nephropathy (DN). (A) Volcano plot of MR results for cardiovascular proteins and DN. P value: nominal P value; β: causal effect of cardiovascular proteins on DN; Protection: proteins with adjusted P<0.05 and β<0 after the Bonferroni statistical tests; Risk: proteins with adjusted P<0.05 and β>0; Not significant: proteins with adjusted P>0.05. (B) External validation results for cardiovascular proteins and DN. (C) Forest plot of MR results for cardiovascular mediators with colony-stimulating factor-1 (CSF-1) and C-X3-C motif chemokine ligand 1 (CX3CL1), and mediators with DN. (D) Hip circumference, body mass index, hypertension, and fasting insulin mediate the pathogenic risk of CX3CL1 on DN. β0: effect of CX3CL1 on DN; β1: effect of CX3CL1 on mediators; β2: effect of mediators on DN; Mediation effect proportion calculated as β1×β2/β0. OR, odds ratio; CI, confidence interval; LDL, low-density lipoprotein; HDL, high-density lipoprotein; HbA1c, glycated hemoglobin.
In mediation MR analyses involving 14 cardiovascular risk factors and eight cardiovascular diseases, CX3CL1 was found to increase DN risk through pathways related to hip circumference, body mass index, hypertension, and fasting insulin, with mediation effects accounting for 6.78%, 5.80%, 2.41%, and 9.08%, respectively (Fig. 1C, D). In analyses involving 731 immunophenotypes, CSF-1 exerted a protective effect on DN by reducing the human leukocyte antigen-DR highly positive monocyte absolute count, with a mediation effect proportion of 36.50% (Fig. 2A).

Volcano plot of the Mendelian randomization (MR) results between immunophenotypes and diabetic nephropathy (A) and phenomewide MR results of C-X3-C motif chemokine ligand 1 (CX3CL1) (B). SSC-A, side scatter area; HLA DR, human leukocyte antigen-DR.
The Phe-MR analysis included nearly 2,800 phenotypes for CX3CL1 and CSF-1. CX3CL1 was identified as a risk factor for necrotizing vasculopathies (OR, 2.10; 95% CI, 1.56 to 2.82; adjusted P=0.003), acute renal failure (OR, 1.58; 95% CI, 1.32 to 1.89; adjusted P=0.001), renal tubulointerstitial disorders (OR, 1.18; 95% CI, 1.10 to 1.26; adjusted P<0.001), glomerular disorders (OR, 1.60; 95% CI, 1.30 to 1.96; adjusted P=0.003), disorders of pituitary gland (OR, 10.18; 95% CI, 4.05 to 25.58; adjusted P=0.002), benign neoplasms of the ovary (OR, 1.42; 95% CI, 1.21 to 1.66; adjusted P=0.034), and focal brain injury (OR, 1.87; 95% CI, 1.44 to 2.43; adjusted P=0.003) after Bonferroni correction (Fig. 2B). Lowering CX3CL1 levels not only reduces DN risk but also confers protective effects against these diseases.
DISCUSSION
Our findings indicate genetic associations between CX3CL1 and CSF-1 with DN, suggesting that these proteins may serve as potential therapeutic targets for DN. CX3CL1, a chemokine, mediates the recruitment and activation of immune cells, particularly monocytes and macrophages, which contribute to inflammation and fibrosis in the kidneys [11,12]. Elevated levels of CX3CL1 in the circulation and renal tissue have been shown to promote glomerular injury and tubulointerstitial fibrosis, both hallmark features of DN [13]. Furthermore, CX3CL1 interacts with various cardiovascular risk factors, including obesity, insulin resistance, and hypertension, which may exacerbate the progression of DN [14].
CSF-1 plays a critical protective role in DN by regulating macrophage polarization and promoting tissue repair. Recent studies suggest that CSF-1 can drive macrophages toward an M2-like, anti-inflammatory phenotype, which supports tissue repair and mitigates the damaging effects of chronic inflammation [15]. In DN, this shift is vital for counteracting maladaptive immune responses that contribute to kidney injury. Additionally, CSF-1 may enhance the resolution of inflammation by inhibiting the production of pro-inflammatory cytokines and facilitating the clearance of apoptotic cells and cellular debris [16]. These protective effects are likely mediated through CSF-1’s ability to stimulate the release of anti-inflammatory factors, such as interleukin-10 and transforming growth factor-beta, which help suppress excessive fibrosis and scarring [17].
In Phe-MR analyses of drug targets, CX3CL1 was identified as a risk factor for necrotizing vasculopathies, acute renal failure, renal tubulointerstitial disorders, and benign ovarian tumors. These findings highlight the broader implications of CX3CL1 inhibition. However, it is important to consider the potential off-target effects of targeting this protein. Previous studies have demonstrated that serum CX3CL1 levels are significantly higher in patients with polyarteritis nodosa compared to healthy controls, with pronounced expression in endothelial cells at the site of skin lesions [18]. In mouse models, inhibiting CX3CL1 has been shown to alleviate acute kidney injury induced by cisplatin and endotoxin [19]. CX3CL1 also regulates the proliferation of epithelial ovarian tumor cells [20]. These findings suggest that CX3CL1 inhibitors may hold therapeutic potential for treating other diseases. Nevertheless, due to the limited clinical experimental evidence, the safety profile of CX3CL1 inhibitors must be carefully evaluated in clinical settings.
This study also has some limitations. First, the results of the MR analysis require robust experimental evidence for further validation. Second, the lack of GWAS data from non-European populations limits the analysis to European cohorts, which may restrict the generalizability of the MR results.
Supplementary Material
Supplemental Table S1.
Data Availability
Notes
CONFLICTS OF INTEREST
No potential conflict of interest relevant to this article was reported.
ACKNOWLEDGMENTS
This study was supported by Chengdu Science and Technology Bureau Grant (grant no. 2019-YF09-00090-SN) and Science and Technology Department of Sichuan Province (grant no. 2024YFFK0388).
AUTHOR CONTRIBUTIONS
Conception or design: L.C., W.T. Acquisition, analysis, or interpretation of data: L.C., Y.Z., M.H., J.D. Drafting the work or revising: L.C., W.T. Final approval of the manuscript: L.C., Y.Z., M.H., J.D., W.T.