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Abstract

Background

This study aimed to investigate the causal relationship between complement system overactivation and coagulopathy in sepsis using a two-sample Mendelian Randomization (MR) approach.

Methods

We conducted genome-wide association studies (GWAS) using UK Biobank data to identify genetic variants associated with high complement levels in sepsis patients (exposure) and with coagulopathy (outcome). Single nucleotide polymorphisms (SNPs) robustly associated with the exposure were used as instrumental variables in a bidirectional MR analysis to assess causality. The primary analysis utilized the inverse variance weighted (IVW) method, supplemented by extensive sensitivity analyses to test for pleiotropy. Multivariable MR (MVMR) was performed to adjust for the potential confounding effects of C-reactive protein (CRP), a key inflammatory marker.

Results

The GWAS identified distinct and shared genetic loci for high-complement sepsis and coagulopathy, including in key complement (CFH, C3) and coagulation (F5) genes. The primary MR analysis revealed a significant positive causal effect of genetically predicted high C3 levels on the risk of developing coagulopathy (β = 0.62, P = .0008). This finding was robust across all sensitivity analyses, with no evidence of significant horizontal pleiotropy. Conversely, the reverse MR analysis showed no causal effect of coagulopathy on complement activation, establishing a unidirectional relationship. The MVMR analysis demonstrated that the causal effect of C3 on coagulopathy remained significant after adjusting for CRP, suggesting that complement can drive coagulopathy through pathways partially independent of systemic inflammation.

Conclusion

This study provides strong genetic evidence that complement system overactivation is a unidirectional, causal driver of coagulopathy in sepsis.

Keywords

sepsis coagulopathy complement mendelian randomization study

Introduction

Sepsis is a life-threatening disease characterized by dysregulated host immune response to infection, often accompanied by multiple organ dysfunction.^1,2 Previous studies suggest that over half of sepsis patients develop coagulopathy, termed sepsis-associated coagulopathy (SAC),³ which is associated with significantly higher mortality rates.⁴ Although some clinical research suggests that SAC can manifest early in the course of infection and its severity correlates positively with disease progression,^5,6 its underlying pathogenesis remains incompletely understood.

The complement system, a crucial component of innate immunity, plays a pivotal role in modulating inflammatory responses and coagulation activation.⁷ Recent research suggests that crosstalk and mutual activation occur between the complement and coagulation systems during the progression of sepsis.⁸ Activation of the classical and lectin complement pathways leads to the cleavage of C3, generating pro-inflammatory anaphylatoxins such as C3a, C4a, and C5a.⁹ These fragments induce the expression of tissue factor and the production of antifibrinolytic proteins, thereby amplifying the procoagulant state. Concurrently, the formation of the C5b-9 membrane attack complex further activates the coagulation cascade, which can culminate in disseminated intravascular coagulation (DIC).⁷

Animal studies, including those in baboon models, have demonstrated that the administration of complement inhibitors can downregulate tissue factor and plasminogen activator inhibitor-1 (PAI-1), ameliorate abnormalities in coagulation markers (eg, fibrinogen, fibrin degradation products, and activated partial thromboplastin time [APTT]), and preserve endothelial anticoagulant function.¹⁰ These findings suggest that complement activation may be a key upstream driver of SAC. However, most evidence is derived from animal models. Obtaining conclusive clinical evidence in humans is challenging due to the insidious onset, rapid progression, and numerous confounding factors inherent in infectious diseases.

Traditional observational studies cannot definitively establish a causal link between complement system activation and SAC due to susceptibility to confounding bias and reverse causation. Therefore, a robust method is needed to investigate this relationship at the genetic level. Mendelian Randomization (MR) is an instrumental variable approach that leverages genetic variants as proxies for an exposure. By translating causal inference into an analysis of genotype-phenotype associations, MR can effectively mitigate the limitations of confounding and reverse causation. The UK Biobank (UKBB) is the world's largest biomedical cohort, containing phenotypic, genome-wide sequencing, and multi-omics data for nearly 500,000 European individuals, making it an invaluable resource for genome-wide association studies (GWAS) and causal inference research.

This study aims to leverage the UKBB resource to conduct a GWAS for complement activation in sepsis patients and a separate GWAS for coagulopathy. By identifying single nucleotide polymorphisms (SNPs) significantly associated with these phenotypes, we will employ a two-sample MR framework to explore the causal relationship between elevated complement levels in sepsis and the development of coagulopathy.

Methods

GWAS: Genetic data from the UKBB were processed following standard procedures. Post-imputation quality control (QC) was performed, which included: 1) Sample QC: exclusion of samples with >10% missing genotype data, close relatives, ethnic outliers, and sex discordance; 2) SNP QC: exclusion of SNPs with >10% missingness, deviation from Hardy-Weinberg equilibrium (HWE, p < 1 × 10⁻⁶), and a minor allele frequency (MAF) < 0.01. Subsequently, linkage disequilibrium (LD) clumping was performed with an r² threshold of 0.1 to ensure the independence of SNPs for downstream GWAS analysis.

Phenotype Definition

Sepsis with High Complement: Following established criteria.^2,11 patients with both an infection and evidence of organ dysfunction were identified as having sepsis. The case group for this phenotype consisted of sepsis patients with elevated levels of complement components C3, C4, and C5. The control group comprised individuals with no history of infection, organ dysfunction, coagulopathy, or elevated complement levels.

Coagulopathy: Cases were defined as patients with a diagnosis of coagulopathy based on International Classification of Diseases, 10th Revision (ICD-10) codes (including D65., D68.8, D68.9, D69.5, and D69.6). Controls were individuals without a history of infection, organ dysfunction, or coagulopathy.

Genotype-Phenotype Association Analysis

Principal component analysis (PCA) was performed to control for population stratification, with the leading principal components included as covariates in the association model along with age and sex. A logistic regression model assuming an additive genetic effect was used to test the association of each SNP with the target phenotypes. All association analyses were conducted on a Linux platform using PLINK and R.

The study design and reporting followed the STROBE-MR guidelines.¹² The MR analysis pipeline involved the following steps:

Instrumental Variable Selection and Data Integration

SNPs significantly associated with exposure (eg, complement protein levels or coagulation indices, P < 5 × 10⁻⁸) and independent (r² < 0.01, window 10,000 kb) were selected as instrumental variables (IVs). Exposure and outcome SNP effect estimates were harmonized and assembled into the MR input dataset.

Main Effect Estimation and Sensitivity Analyses

The primary analysis was conducted using the inverse variance weighted (IVW) method. To assess the robustness of the findings and test for potential horizontal pleiotropy, several sensitivity analyses were performed, including MR-Egger regression, the weighted median method, simple mode, and MR-PRESSO (Pleiotropy RESidual Sum and Outlier) test. A leave-one-out analysis was also conducted to evaluate the influence of individual SNPs on the overall causal estimate.

Power and Robustness Assessment

Cochran's Q test was used to assess heterogeneity among the IVs. The intercept from the MR-Egger regression was examined to detect directional horizontal pleiotropy (a non-zero intercept with P < .05 would be indicative of pleiotropy). The strength of the IVs was assessed by calculating the F-statistic. A P-value < .05 was considered indicative of a statistically significant causal effect. All MR analyses were performed in R (version 4.4.2) using the TwoSampleMR package. Results were visualized using forest plots, scatterplots, funnel plots, and single-SNP effect plots.

Multivariable Mendelian Randomization

A multivariable MR (MVMR) was used as a regression-based approach, which consisted of 2 stages. First, the genetic association coefficients (β coefficients) linking the exposure to the outcome are regressed against the β coefficients representing the genetic association between a third variable and the outcome. This initial step helps to account for any shared genetic influences. Subsequently, the residuals derived from this first regression, which essentially capture the portion of the exposure-outcome association not explained by the third variable—are then regressed on the β coefficients for the exposure itself. MVMR analysis was performed adjusting C3 levels for CRP levels.

Results

GWAS of High-Complement Sepsis and Coagulopathy

For the GWAS of high-complement sepsis, a total of 1326 cases and 3368 controls were included. The mean relative C3 expression in the case group was 0.89 ± 0.21, compared to 0.01 ± 0.34 in the control group (Supplemental Table 1). The correlation analysis revealed distinct and specific associations between key inflammatory mediators, platelet factors, and components of the complement system (Figure 1). A correlation analysis revealed that the levels of C3, C5, and CFHR5 were positively correlated with the coagulopathy-related biomarkers PECAM1, P-selectin, and CD36. The pro-inflammatory cytokines IL-6 and IL-18 were not only strongly correlated with each other, but also exhibited a significant positive correlation (p < .05) with components of the terminal complement pathway, specifically C6, C6b, and C8b. In contrast, their associations with upstream complement proteins (eg, C3, C3b, CFD) were positive but markedly weaker. A different pattern emerged for Platelet Factor 4 (PF4). PF4 showed only weak correlations with the terminal pathway components (C6, C8b) but demonstrated a robust positive correlation with the complement regulatory proteins, Complement Factor I (CFI) and Complement Factor H-related protein 4 (CFHR4).

Figure 1.

Association Between the Complements and Coagulation Parameters.

The GWAS for high-complement sepsis identified 80 SNPs reaching genome-wide significance (P < 5 × 10⁻⁸) after logistic regression adjusted for age and sex (Manhattan and QQ plots in Figure 3A and Supplemental Figure 2). Notable association peaks were observed in the CFH and F5 regions on chromosome 1 and the C3 region on chromosome 19. Key SNPs included rs1410996 in the CFH gene (p = 2.93 × 10⁻⁷) and rs3753394 at locus 1q31.3 (p = 2.27 × 10⁻⁷).

For the coagulopathy GWAS (Figure 3A), 6190 cases and 390,103 controls were included. This analysis identified 120 genome-wide significant SNPs (Supplemental Figure 2B). Association peaks were located at previously reported loci, including the F5 (Factor V) and SELP (P-selectin) regions on chromosome 1, the PROC (Protein C) and CASP10 regions on chromosome 2, and the FGA (Fibrinogen) region on chromosome 4, confirming the validity of our phenotype definition.

MR Considering High Complement as Exposure

A bidirectional MR analysis was performed to assess the causal relationship between elevated complement in sepsis and coagulopathy. When high-level C3 in sepsis was treated as the exposure, the IVW analysis revealed a significant positive causal effect on coagulopathy (β = 0.62, P = .0008; Figure 2A , Supplemental Table 2). This finding was consistent across sensitivity analyses, including MR-Egger and the weighted median method (Supplemental Figures 2–4). The MR-Egger intercept (p = .12) and the MR-PRESSO test did not detect significant horizontal pleiotropy (Supplemental Table 4). Furthermore, Cochran's Q test showed no evidence of heterogeneity among the IVs (Q = 17.88, p = .11; Supplemental Table 5).

Figure 2.

Forest Plots of the Association of Genetically Determined C3, C4, and C5 Levels in Sepsis Patients with Coagulopathy.

Figure 3.

Manhattan Plots and QQ Plots of Genome-Wide Association with High-Complement in the Sepsis Cohort and Coagulopathy Cohort. P Values Were Generated Using Logistic Regression Adjusted for Age, and Sex.

MR Considering Coagulopathy as Exposure

In the reverse MR analysis, we investigated whether coagulopathy had a causal effect on elevated complement levels in sepsis patients. The primary IVW analysis showed no evidence of a causal relationship (OR = 0.03, 95% CI: −0.00-0.07, p = .215; Supplemental Figure 1). Sensitivity analyses using MR-Egger and the weighted median method yielded directionally consistent results (all OR < 1), although with wider confidence intervals (Supplemental Figures 5–7). No significant pleiotropy was detected by MR-Egger regression or MR-PRESSO (p = .45).

Multivariable Mendelian Randomization

To disentangle the effects of inflammation, an MVMR analysis was conducted to adjust the effect of C3 levels on coagulopathy for the genetic influence of C-reactive protein (CRP) levels. After adjustment, the causal effect of C3 on coagulopathy remained significant (p = .025), although the effect estimate was attenuated. The unadjusted OR was 1.99 (95% CI: 1.74-2.53), compared to an adjusted OR of 1.82 (95% CI: 1.17-2.03). The analysis also revealed a significant indirect effect of CRP on coagulopathy mediated through C3 levels (p < .001).

Discussion

This study is the first to systematically apply Mendelian Randomization to large-scale genomic data to elucidate the causal relationship between complement system overactivation and coagulopathy in sepsis. Our primary finding, robustly supported by genetic evidence, is that complement overactivation is a unidirectional, upstream driver of SAC. This conclusion offers novel insights into the complex pathophysiology of sepsis and identifies promising therapeutic targets.

The immune system operates as an intricate and highly coordinated network, integrating cellular and humoral components to maintain host defense and homeostasis. Within this network, the complement system serves as a pivotal humoral arm that bridges innate immunity, inflammation, and coagulation.¹³ Upon activation, complement components (such as C3 and C5) generate potent anaphylatoxins (C3a, C5a) and opsonins, which recruit and activate neutrophils, macrophages, and endothelial cells.^14,15 These events trigger secondary cascades including tissue factor exposure, platelet activation, and endothelial injury, all of which potentiate thromboinflammatory responses.¹⁶ Therefore, the complement system does not function in isolation but acts in concert with cytokine signaling, leukocyte activation, and the coagulation system to orchestrate the systemic inflammatory milieu characteristic of sepsis.

Our GWAS provides a genetic basis for a “complement-coagulation axis.” In the sepsis cohort characterized by high complement activation, we identified significant genetic signals not only in canonical complement genes (eg, CFH, C3) but also in the key coagulation factor gene F5.^7,17 These findings suggest an overlapping genetic architecture underlying immune–coagulatory crosstalk.⁷ Consistently, our replication of known coagulopathy-related loci (F5, SELP, PROC, FGA) validates the accuracy of our phenotypic definitions.^18,19 Building upon these genetic associations, our bidirectional Mendelian randomization analysis offers strong causal inference: genetically proxied higher levels of complement C3 exhibit a significant positive causal effect on the development of coagulopathy (β = 0.62, p = .0008). Multiple sensitivity analyses support the robustness of this inference, with no evidence of horizontal pleiotropy. Conversely, the reverse MR analysis revealed no causal effect of coagulopathy on complement activation. Taken together, these results delineate a unidirectional yet biologically integrated causal pathway, in which complement overactivation precedes and amplifies coagulation dysfunction through its coordinated interactions with the broader immune network, thereby clarifying a long-debated temporal relationship in sepsis pathophysiology.

These findings align with observational studies. Elevated plasma levels of C3 have been associated with incident venous thromboembolism (VTE),²⁰ and genetic variants in CFHR5 have been linked to VTE risk independent of C3 concentration.¹⁷ Furthermore, a positive correlation between platelet C3a receptor expression and platelet activation has been observed in patients with coronary artery disease, suggesting a role for complement in thrombus formation.²¹ Our own correlational data (Figure 1) further illuminates the specific nature of this crosstalk, revealing differential patterns of association. These findings highlight the intricate and differential crosstalk between inflammation, coagulation, and the complement cascade. The strong positive association between IL-6/IL-18 and the terminal components C6 and C8b suggests that a heightened systemic inflammatory state, driven by these cytokines, may directly promote the assembly of the Membrane Attack Complex (MAC). This link provides evidence for an ‘immuno-thrombotic’ amplification loop, where inflammation fuels terminal complement activation, a key driver of endothelial damage and pro-coagulant states. Conversely, the unique correlation of PF4 with complement regulators (CFI and CFHR4), rather than its lytic effectors, implies a more nuanced modulatory role. This suggests that as platelets activate and release PF4, they may concurrently engage inhibitory complement pathways. This could represent a localized protective mechanism, potentially to limit bystander cell damage at the site of vascular injury and modulate the downstream inflammatory consequences of complement activation. Our study strengthens this body of evidence by establishing a causal link at the genetic level between high C3 expression in sepsis and coagulopathy, using 16 genetic instruments and rigorous sensitivity analyses.

To further dissect this causal pathway, our MVMR analysis indicates that the direct causal effect of C3 on coagulopathy persists after adjusting for the genetic effects of the inflammatory marker CRP. This suggests that the complement system can induce coagulopathy through mechanisms independent of canonical inflammation, such as by directly activating platelets and endothelial cells.¹⁴ Critically, our analysis also showed that the effect of CRP on coagulopathy is significantly mediated by C3 (p < .001 for the indirect effect). This positions the complement system as a pivotal hub linking inflammation and thrombosis, suggesting that systemic inflammatory signals in sepsis may require amplification and transduction via the complement system to trigger catastrophic coagulopathy.

The interplay between the complement and protein C systems is a plausible mechanistic link. Protein C, encoded by PROC, is central to regulating coagulation and inflammation.²² Endothelial protein C, activated by the thrombomodulin (TM)-thrombin complex, proteolytically inactivates factors Va and VIIa, slowing coagulation. The TM-thrombin complex also activates TAFI, which inactivates complement fragments C3a and C5a, suppressing innate immunity. The lectin-like domain of TM has documented anti-inflammatory effects during PC activation.²³ This domain can also neutralize complement activation; mice lacking this domain show C3 deposition in joints and kidneys,²⁴ which can be suppressed by supplemental TM.²⁵ Thus, the complement–protein C link may be a therapeutic target for SAC.²⁶ Similarly, the identification of F5 as a shared genetic locus is consistent with its role in thrombin generation and the pathogenesis of thrombotic disorders.^27,28

In summary, our study confirms a unidirectional causal link from complement activation to coagulopathy in sepsis and positions the complement system as a core upstream driver of inflammation-induced thrombosis. These findings have significant clinical translational potential, suggesting that targeting the complement system (eg, C3 or C5 inhibitors) may represent a more fundamental, ‘upstream’ therapeutic strategy than anti-inflammatory or anticoagulant therapies alone.

Limitation

This study has several limitations. First, our analyses were based on GWAS summary statistics from individuals of European ancestry, and the generalizability of our findings to other populations requires further validation. Second, sepsis is an inherently heterogeneous syndrome involving diverse infectious pathogens, host immune responses, and clinical trajectories. In the present analysis, sepsis cases were identified based on explicit ICD-10 diagnostic codes without further stratification by underlying conditions or disease stages. Third, coagulation examinations, complement and inflammatory biomarkers in the UK Biobank were not measured longitudinally during hospitalization, which limited our ability to capture their dynamic changes and the temporal progression toward coagulopathy. These constraints are inherent to the current dataset and warrant validation in future studies with serial measurements and more refined clinical phenotyping. Fourth, there was a lack of sample overlap between the GWAS for the exposure (sepsis with high C3) and the outcome (coagulopathy), which can affect the power of a two-sample MR study. Finally, as with all MR studies, we cannot definitively exclude the possibility of residual horizontal pleiotropy, where genetic instruments influence the outcome through pathways independent of the exposure. Although we employed multiple sensitivity analyses to mitigate this risk, no single test can completely rule it out. Finally, sepsis is a clinically heterogeneous syndrome, and while our phenotype definitions were rigorously constructed, they may not capture all clinical subtypes. Future research should prioritize validating these findings in prospective clinical cohorts and randomized controlled trials of complement inhibitors.

Conclusion

This Mendelian Randomization study provides robust genetic evidence that elevated complement expression in sepsis is a causal driver of coagulopathy. The demonstration of this positive, unidirectional causal relationship highlights the complement system as a critical upstream target for therapeutic intervention aimed at mitigating coagulopathy and improving outcomes for patients with sepsis.

Key Points

This study provides strong genetic evidence that complement system overactivation is a causal driver of coagulopathy in sepsis. These findings position the complement cascade as a critical upstream hub linking inflammation and thrombosis in a harmonized pattern, highlighting it as a promising therapeutic target to prevent or treat sepsis-associated coagulopathy and improve patient outcomes.

Supplemental Material

sj-docx-1-cat-10.1177_10760296251396143 - Supplemental material for Complement Overactivation as a Causal Driver of Sepsis-Associated Coagulopathy: A Mendelian Randomization Study from the UK Biobank

Supplemental material, sj-docx-1-cat-10.1177_10760296251396143 for Complement Overactivation as a Causal Driver of Sepsis-Associated Coagulopathy: A Mendelian Randomization Study from the UK Biobank by Rong Liufu, Mao-Mao Cao, Yan Chen, Yang-Yan-Qiu Wang, Yao Wu, Wei Jiang, Jin-Min Peng, Bin Du and Li Weng in Clinical and Applied Thrombosis/Hemostasis

Footnotes

ORCID iD

Rong Liufu

Ethical Considerations

This retrospective study was approved by the Ethics Committee of Peking Union Medical College Hospital (NO.I-23PJ2189).

Author Contribution Statement

Rong Liufu designed research. Rong Liufu performed research and drafted the manuscript. Mao-Mao Cao, Yan Chen, Yang-Yan-Qiu Wang, and Yao Wu contributed vital new reagents or analytical tools. Wei Jiang, Chun-Yao Wang, and Jin-Min Peng analyzed data. Rong Liufu, Li Weng, and Bin Du, M.D. revised the paper.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was supported by National Key R&D Program of China (No.2022YFC2304601), Noncommunicable Chronic Diseases-National Science and Technology Major Project (2023ZD0506505), CAMS Innovation Fund for Medical Sciences (CIFMS) from Chinese Academy of Medical Sciences (2021-I2M-1-062).

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Availability of Data and Materials

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

Supplemental Material

Supplemental material for this article is available online.

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Supplementary Material

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