G-Quadruplexes Formation in the PAI-1 Gene Modulates Sepsis-Induced Coagulopathy and Mortality Risk

Abstract

Background

Early detection of sepsis-induced coagulopathy (SIC) is of great clinical significance, as its closely correlates with disease progression in patients with sepsis. In the present study, we focused on mining the major coagulation factors that participate in the development and progression of SIC, and exploring the potential regulatory networks of these core factors.

Method

Meta-analysis was performed to explore the association between SIC and mortality. eQTLs significantly associate with sepsis-related 28-day mortality and pQTLs were analyzed, to mine the significant sites or genes. Mendelian randomization (MR) was then applied to evaluate the role of coagulation factors in SIC and to explore their genetic regulation via DNA sequence analysis. Moreover, QGRS Mapper combined with ThT fluorescence assays were used to detect G-quadruplexes (G4s) structures within coagulation factor genes.

Results

Sepsis patients with SIC exhibited higher sequential organ failure assessment (SOFA) scores and increased 28-day mortality compared to those without SIC. MR and clinical analyses demonstrated that PAI-1 serves as a major contributor to higher sepsis incidence and 28-day mortality. Notably, the PAI-1 rs1799762 genetic polymorphism alters this biological effect. Mechanistically, G4-forming capacity negatively correlates with PAI-1 expression. In particular, the 5G/5G genotype was associated with a higher G4-forming propensity in the PAI-1 gene, which in turn weakened gene transcription and lowered PAI-1 expression relative to other genotypes.

Conclusion

G4s formation in the PAI-1 gene modulates circulating PAI-1 levels and may serve as a novel prognostic marker and therapeutic target for sepsis severity assessment, particularly in patients with SIC.

Introduction

Sepsis represents a life-threatening organ dysfunction caused by a dysregulated host response to infection. Beyond the initial local inflammation triggered by pathogens, its pathophysiology is hallmarked by systemic inflammatory responses, profound immune imbalances, and severe metabolic disturbances, making it a common and frequently fatal condition in intensive care units (ICUs). ¹ Nowadays, it is becoming a major cause of death in ICU admitted patients globally. ² In China, this crucial illness is associated with an increased 90-day mortality rate from 2.78% to 51.94%. ³ Sepsis is associated with a thrombotic tendency; microvascular thrombosis may progress to disseminated intravascular coagulation (DIC) and organ failure, leading to high mortality rate if not promptly managed. Sepsis patients develop SIC usually has a high mortality rate. ⁴ Early monitoring of SIC could serve as a valuable indicator for timely sepsis diagnosis and prognostic enhancement.

Coagulation abnormalities of SIC manifest throughout the entire pathological course of sepsis serves as a pivotal contributor to both disease initiation and clinical outcomes in sepsis. ⁵ While anticoagulation therapy and judicious antibiotic use have demonstrated efficacy in reducing mortality and improving clinical outcomes in sepsis, existing assessment tools remain limited in their ability to predict both the incidence and mortality risk of SIC during early disease stages. ⁶

Clinical and preclinical studies have shown that sepsis is associated with endothelial injury by pathogens that exposes tissue factor, triggering coagulation and reducing anticoagulant and fibrinolytic activity. Cytokines also reduce the activity of anticoagulant protein S and increase plasminogen activator (PAI)-1 levels, further reducing anticoagulant and fibrinolytic activity. ⁷ Therefore, elucidating the interplay between sepsis-induced mediators and their downstream effects on coagulation factors represents a critical approach for both severity assessment and prognostic prediction in SIC.

Traditionally, PAI-1 regulates clot dissolution and participates in inflammatory modulation during infection. PAI-1 expression levels, influenced by the rs1799762 (4G/5G) polymorphism in the promoter region, are associated with poor outcomes in septic patients. ⁸ The 4G allele is associated with increased PAI-1 transcription compared to the 5G allele.

Recent advances in nucleic acid structural biology have revealed that G-quadruplexes (G4s)- non-canonical secondary structures formed in guanine-rich DNA or RNA sequences-play crucial roles in regulating gene expression, replication, and genomic stability. ⁹ However, whether G4 structures form in the PAI-1 gene and whether they play a role in regulating PAI-1 expression during sepsis - particularly in the context of SIC is unclear. To address this issue, the following study was performed, firstly establish the SIC-mortality relationship using clinical data and meta-analysis. Subsequently, Mendelian randomization (MR) analysis was employed to investigate the key coagulation factors involved in SIC, and the findings were further validated using serum samples from sepsis patients. Lastly, the PAI-1 polymorphism was analyzed by genotyping in 20 SIC patients, and PAI-1 expression level was analyzed in the PAI-1 polymorphism groups. This study combined clinical data, meta-analysis and MR analysis to explore how G4 structures and rs1799762 polymorphism of PAI-1 regulate prognosis in septic patients with SIC.

Materials and Methods

Clinic samples from sepsis patients

We obtained data and serum samples from 196 patients with sepsis (including 29 with available serum samples) at Nanjing First Hospital, China, between January 2022 and December 2024. All adult patients diagnosed with sepsis according to the Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3) were consecutively enrolled. ¹⁰ Exclusion criteria were as follows: history of bone marrow transplantation or splenectomy, ongoing chemotherapy, and end-stage cancer. Sepsis-induced coagulopathy (SIC) was diagnosed based on the criteria proposed by the subcommittee of the International Society on Thrombosis and Haemostasis (ISTH). ¹¹ The study was conducted in accordance with the institutional guidelines of Nanjing First Hospital Affiliated to Nanjing Medical University and was approved by its Institutional Review Board (approval number: KY20220516-02).

Meta-analysis

Studies published between January 2016 and December 2025 were identified through an electronic search of PubMed, Embase and Web of Science using the following keywords: sepsis, sepsis-induced coagulation, SIC, and 28-day death or mortality. We additionally manually screened the reference lists of the retrieved publications to identify further eligible studies. Studies were selected for analysis if they met the following criteria ¹ : original epidemiological studies investigating the association between SIC and prognosis in patients with sepsis ² ; each study included both SIC and non-SIC patient groups ³ ; availability of hazard ratios (HRs) with 95% confidence intervals (CIs) or P values for hospital mortality ⁴ ; studies included more than five patients. Studies were excluded based on the following criteria ¹ : duplicate publications, reviews, letters, unpublished data, or comments ² ; studies published in languages other than English ³ ; lack of key information required for further analysis. The primary analysis examined the difference in the risk of 28-day hospital mortality between SIC and non-SIC patients, expressed as odds ratios (ORs) with corresponding 95% CIs. Two independent investigators (ZN and HP) evaluated and extracted data from each eligible study based on the predefined inclusion and exclusion criteria. The corresponding author was contacted to clarify missing or ambiguous data. Additional statistical analyses, including heterogeneity assessment, sensitivity analysis, and evaluation of potential publication bias, were performed to enhance the robustness of the results. All statistical analyses were conducted using the “meta” package in R software.

MR analysis

eQTLs of genes associated with sepsis (ieu-b-4980) were first obtained from the publicly available genome-wide association study (GWAS) dataset IEU OpenGWAS. This GWAS was performed on 486,484 European individuals, including 11,643 sepsis patients and 474,841 controls, and identified 12,243,539 SNPs. Furthermore, eQTLs of genes associated with sepsis-related 28-day mortality (ieu-b-5086) were included to verify the causal effect of key coagulation factors on the prognosis of patients with sepsis. This dataset comprised 486,484 European individuals, including 1,896 sepsis patients and 484,588 controls, with 12,243,487 SNPs. In addition, based on previous studies, protein quantitative trait loci (pQTL) data for 4,907 plasma proteins derived from 35,559 Icelandic individuals were applied.^12,13 All SNPs met the threshold for genome-wide statistical significance (p < 5 × 10^-8). All statistical analyses were performed using the “TwoSampleMR” package in R software (Version 4.2.1). A p-value < 0.05 was considered statistically significant. Several methods, including MR Egger, weighted median, simple mode, weighted mode, and inverse variance weighted (IVW), were applied to evaluate the causal effects of serum proteins. Consistent with previous studies, the Wald ratio was used as the primary estimation method to assess causal relationships between exposures and outcomes. Effect sizes were expressed as odds ratios (ORs) with corresponding 95% confidence intervals (CIs). Additionally, the Wald ratio method was employed as a supplementary approach in MR analyses when only a single instrumental variable (IV) was available. The F-statistic was calculated to assess the strength of IVs and to detect potential weak instrument bias. Heterogeneity among individual SNPs was evaluated using Cochran’s Q test. When the Q p-value was < 0.05, a random-effects IVW model was applied for correction. The MR-Egger intercept method was used to assess the potential presence of horizontal pleiotropy.

Tests of coagulation markers

Venous blood samples were collected within 2 hours of admission to the ICU and centrifuged at 3,000 rpm for 10 minutes. Coagulation and fibrinolytic parameters were analyzed immediately after centrifugation. Tissue plasminogen activator-inhibitor complex (t-PAIC) was measured using a Sysmex HISCL-5000 chemiluminescence immunoassay analyzer, while prothrombin time (PT) was analyzed using a Sysmex CS5100 coagulation analyzer. All reagents and calibrators were original supporting products and were reconstituted strictly in accordance with the manufacturer’s instructions.

Reverse transcription and real-time RT-PCR

Whole blood samples from 29 patients with sepsis were collected at Nanjing First Hospital Affiliated to Nanjing Medical University between November 2022 and August 2025. Total RNA was extracted using a Total RNA Kit (Omega, USA) according to the manufacturer’s protocol. Reverse transcription was then performed as follows: 1 µg of RNA and 4 µl of buffer containing random hexamers and reverse transcriptase (RT; Takara, Japan) were incubated for 15 minutes at 37°C, followed by 5 seconds at 85°C, and then stored at 4°C in a final volume of 20 µl. Real-time PCR amplification was carried out using a QuantiTect SYBR Green PCR Kit (Qiagen) with 2 µl of cDNA and 500 nM primers. Relative quantification of gene expression changes was recorded after normalization to 18S expression, which was calculated using the 2^-ΔΔCT method (User Manual 2, ABI 7500 System). The primer sequences are provided in Supplemental Table 1.

Extraction of DNA and genotyping

Genomic DNA was extracted from peripheral blood cells and immediately used for PCR amplification. The primer sequences were as follows: forward primer, 5′-CCA​CCC​CAC​CCA​GCA​CAC​CTC​CAA​CCT​CAG​C-3'; reverse primer, 5′-CCC​AGC​CCA​ACA​GCC​ACA​GGG​CAT​GCA​GCC​A-3'. The predicted amplicon size was 284 bp. PCR products were separated on a 2.5% agarose gel, stained with ethidium bromide, and visualized under UV transillumination. Subsequently, the PCR products were purified and genotyped by Sanger sequencing. Finally, the sequences were aligned and analyzed using Angiotool Software.

Thioflavin (ThT) fluorescence measurement

PAI-1 DNA molecules (5 µM) were first incubated at 95 °C for 10 minutes and immediately cooled in an ice bath for 15 minutes. Subsequently, 20 µM Thioflavin T (ThT) was added, and the DNA molecules were incubated at 37 °C for 90 minutes. A solution containing 20 µM ThT in DEPC-treated water was used as a negative control (NC). Fluorescence intensity at 485 nm was measured to compare the ThT fluorescence enhancement effect of different G-rich DNA sequences.

Statistical Analysis

Continuous data were tested for normality. Normally distributed data were expressed as mean ± standard deviation (x̄ ± s) and compared using Student's t-test. Categorical data were expressed as numbers (%), and intergroup differences were assessed using the χ² test. Correlation analyses were performed using Pearson’s and Spearman’s tests. Survival rates between groups were evaluated using the Kaplan-Meier method and the log-rank test. Differences were considered statistically significant at p < 0.05.

Results

This study aimed to identify key coagulation factors involved in SIC and to explore their regulatory mechanisms through an integrated approach combining meta-analysis, Mendelian randomization, and clinical validation. The primary outcome was 28-day hospital mortality in sepsis patients.

Association between SIC and sepsis prognosis

Our first pooled analyses on the association between SIC and hospital sepsis 28-day mortality included seven studies.^14-20 Under the random-effects model, the hazard ratios (HRs) for SIC patients compared with non-SIC patients was 2.031 (95% CI: 1.630-2.531); Figure 1a). Funnel plot and Egger’s test were subsequently performed to assess publication bias among studies examining the association between SIC and 28-day hospital mortality in sepsis. The funnel plot was symmetric, and Egger’s test suggested no evidence of publication bias (p = 0.548; Figure 1b). In addition, sensitivity analysis indicated that the overall results were not significantly influenced by the sequential removal of any single study (Figure 1c). Consistently, further analysis of 196 sepsis patients followed for four weeks after ICU admission revealed that surviving patients had lower SIC scores than non-survivors (p < 0.001; Figure 1d).

Figure 1.

The affection of SIC in sepsis patients. a: The forest plot of analyses on the association between SIC and sepsis 28-day mortality; b: The funnel plot and Egger’s test of the publication bias in obtained studies; c: The sensitivity analysis of meta-analysis results by removing single study each time; d: The association between SIC score and sepsis prognosis; e: The correlation between SIC and APACHEII or SOFA score

Given that both APACHE II and SOFA scores are widely used for prognostic evaluation in hospitalized septic patients, we further compared these scores between SIC and non-SIC patients. ²¹ First, the association between 28-day hospital mortality and APACHE II/SOFA scores was investigated using meta-analysis. Both APACHE II and SOFA scores showed a positive association with 28-day hospital mortality in septic patients (Supplemental Figure 1). Accordingly, their correlation with SIC was further evaluated. Although no significant difference was observed in APACHE II scores between the two groups (p = 0.458), SIC patients demonstrated significantly higher SOFA scores than non-SIC patients, indicating greater severity of organ dysfunction in the SIC group (p < 0.001; Figure 1e).

Identification of key coagulation factors (MR analysis)

MR analysis was performed to explore the causal effects of 28 common coagulation and fibrinolytic parameters on sepsis progression in hospitalized patients (Supplemental Table 2). As shown in Figure 2a, coagulation factor XI (OR = 0.965, 95% CI: 0.931-0.999, p = 0.045), plasminogen activator inhibitor-1 (PAI-1; OR = 1.157, 95% CI: 1.078-1.242, p < 0.001), and haptoglobin (OR = 1.039, 95% CI: 1.003-1.076, p = 0.034) were associated with an increased risk of sepsis incidence, and notably, the results for PAI-1 obtained using other methods (MR Egger, weighted median, and simple mode) were all consistent with the inverse variance weighted (IVW) results (Figure 2a). Subsequently, the causal effects of coagulation factors on 28-day sepsis-related mortality were analyzed, revealing that coagulation factor XIII (OR = 1.136, 95% CI: 1.017-1.269, p = 0.024), PAI-1 (OR = 1.205, 95% CI: 1.009-1.438, p = 0.039), and thrombin (OR = 0.845, 95% CI: 0.733-0.974, p = 0.020) were associated with an increased risk of 28-day mortality, and again, the results for PAI-1 from MR Egger, weighted median, and simple mode were consistent with the IVW results (Figure 2b). Furthermore, Cochran’s Q test revealed no heterogeneity for PAI-1 with respect to either sepsis incidence or 28-day hospital mortality (p > 0.05; Supplemental Table 3), and the MR-Egger regression method provided no evidence of horizontal pleiotropy (p > 0.05; Supplemental Table 3). Finally, the robustness of these findings was further validated using the leave-one-out method, which supported the association between PAI-1 and both sepsis incidence and 28-day hospital mortality (Supplemental Figure 2).

Figure 2.

Identification of key coagulation factor in SIC regulation. a: MR analysis of 28 coagulation factors causal effect on hospital sepsis incidence; b: MR analysis of 28 coagulation factors causal effect on hospital sepsis 28-day death

Clinical validation of PAI-1 and regulatory mechanism

To further evaluate PAI-1 expression in SIC, we applied the biomarker tissue-type plasminogen activator-plasminogen activator inhibitor-1 complex (t-PAIC), which is composed of tissue-type plasminogen activator (t-PA) and PAI-1, based on previous studies.^22,23 First, two different PAI-1 primers were used to validate the association between PAI-1 and t-PAIC. As shown in Figure 3a, sepsis patients exhibited a significant positive correlation between PAI-1 and t-PAIC expression (P₁ =0.011 and P₂ =0.045). Subsequently, t-PAIC expression data were collected and analyzed from clinical records of 196 sepsis patients. SIC patients were observed to have higher t-PAIC expression than non-SIC patients (p = 0.001; Table 1). Furthermore, the relationship between t-PAIC and sepsis mortality was investigated, revealing that increased t-PAIC expression was found in the non-survivor group compared with the survivor group (p < 0.001; Table 1). Moreover, the Kaplan-Meier survival curve demonstrated that sepsis patients with higher t-PAIC levels had a significantly worse prognosis than those with lower levels (Figure 3b, p < 0.001).

Figure 3.

Evaluation of the relationship between PAI-1 expression and SIC. a: The correlation assessment between PAI-1 and t-PAIC expression; b: The expression of t-PAIC in SIC patients and its affection to sepsis prognosis

Table 1.

The expression of t-PAIC in sepsis patients

​	N	t-PAIC	P value
Disease
SIC	98	20.63±1.94	0.001
Non-SIC	97	13.98±1.65	​
status
Death	69	27.35±2.91	<0.001
Survival	126	11.83±0.90	​

According to previous studies, PAI-1 polymorphism played a crucial role in regulating PAI-1 expression. ⁸ Therefore, the PAI-1 polymorphism (rs1799762) was analyzed by genotyping in 20 SIC patients (Figure 4a). The distribution of the 4G/5G genotypes was as follows: 8 patients (4G/4G), 9 patients (4G/5G), and 3 patients (5G/5G), with a sample size power of 0.4137 based on the reported ratio of the PAI-1 SNP. Notably, sepsis patients with the 4G/4G genotype exhibited significantly higher PAI-1 expression than those with the other genotypes (p = 0.042; Figure 4b). Consistently, an increased risk of SIC was also observed in sepsis patients carrying the 4G/4G genotype, which was further associated with a higher risk of 28-day mortality (p < 0.041; Table 2).

Figure 4.

The exploration of relationship between PAI-1 polymorphism and gene expression in Sepsis. a: The DNA sequence analysis of sepsis patients: all the DNA samples (234bp) were verified by 2% agarose gel electrophoresis before sequencing which were divided into 5G/5G, 4G/5G and 4G/4G groups; b: The PAI-1 expression in sepsis patients with different PAI-1 rs1799762 polymorphism

Table 2.

Analysis of potential factors associated with different PAI-1 polymorphism (rs1799762)

​	SIC			Status
	Yes	No	P value	Alive	Dead	P value
Allele
4G	13	4	​	8	9	​
5G	6	6	0.14	9	3	0.13
Genotype
4G/4G	8	0	​	1	7	​
4G/5G	5	4	​	3	6	​
5G/5G	0	3	0.005	3	0	0.014

G-quadruplexes (G4s) are non-canonical nucleic acid secondary structures that play a crucial role in regulating DNA replication. ²⁴ As shown in Figure 5a, the PAI-1 sequence encompassing rs1799762 contains multiple guanine-rich repeats. Therefore, QGRS Mapper analysis was performed to predict G-quadruplex formation in PAI-1 sequences, revealing that both the PAI-1 5G allele (G-score: 8) and the 4G allele (G-score: 7) sequences have the potential to form G-quadruplexes. Subsequently, PAI-1 5G and 4G allele sequences were separately treated with Thioflavin T (ThT; Figure 5b). Notably, the fluorescence emission of ThT was dramatically enhanced in the PAI-5G group compared with the PAI-4G and negative control (NC) groups (p < 0.001; Figure 5c). Furthermore, the effect of PAI-1 5G allele sequence concentration on ThT fluorescence intensity was examined. A marked concentration-dependent enhancement of fluorescence intensity was observed in the PAI-5G group as the PAI-1 5G allele sequence concentration increased from 2 to 10 µM. In contrast, the fluorescence intensity of the NC group remained unchanged (Figure 5c).

Figure 5.

The identification of G4s in PAI-1 DNA. a: The QGRS Mapper analysis results of PAI-1 5G and 4G allele sequences; b: The diagram of ThT fluorescence measurement process; c: The fluorescence intensity results of ThT added with different PAI-1 DNA sequences

Discussion

In this study, we identified PAI-1 as a key coagulation factor associated with SIC and 28-day mortality in sepsis patients through an integrated approach combining meta-analysis, Mendelian randomization, and clinical validation. We further demonstrated that the PAI-1 rs1799762 polymorphism influences PAI-1 expression, and importantly, the 5G allele exhibits a greater propensity for G-quadruplex formation, which may negatively regulate PAI-1 transcription. These findings provide novel mechanistic insights into the regulation of PAI-1 expression in sepsis and suggest potential prognostic and therapeutic implications for SIC management.

The Significance of PAI-1 and G4 Structural Regulation in SIC Progression

SIC represents a common and critical complication of sepsis which exhibits considerable variability, encompassing a broad spectrum from subtle hemostatic disturbances to the most fulminant form - acute disseminated intravascular coagulation (DIC). ²⁵ Studies had reported that anticoagulation therapy may lead to a significant decrease in mortality risk and improve outcomes among septic patients with coagulopathy. ²⁶ Thus, it is crucial to develop a model that enables early and progressive real-time prediction of SIC. In this study, our meta-analysis of 1,520 sepsis patients and subsequent clinical validation involving 196 sepsis patients demonstrated that SIC is associated with an increased risk of hospital 28-day hospital sepsis mortality, which was frequently accompanied by elevated PAI-1 expression. Further MR and clinical analyses revealed that high PAI-1 expression was inversely correlated with rs1799762 polymorphism of sepsis patients.

Sepsis patients with 5G/5G sequence exhibited enhanced ThT fluorescence, suggesting a greater propensity for G4 formation, therefore leading to lower transcription rates and less PAI-1 expression compared with other sepsis patients(P<0.001). G4s formation in the PAI-1 gene modulates circulating PAI-1 levels may offer a novel prognostic strategy for sepsis, particularly in SIC patients.

Endothelial Biomarkers: Pathological Implication and Clinical Utility in SIC

Sepsis is a dysregulated host response to infection, characterized by complex pathophysiological disturbances. Initially, invading pathogens release endotoxins that damage vascular endothelial cells. ²⁷ Then a series of pathways that control vascular permeability, coagulation, and systemic inflammation are activated by the tissue factors released from the injury, ultimately leading to organ dysfunction. ²⁸ The presence of SIC often manifests early, either at sepsis diagnosis or within the subsequent four days, underscoring the importance of timely coagulation monitoring for severity assessment and prognostic evaluation. ²⁹ Though SIC criteria and its scoring system were constructed in 2017 for SIC assessment, it did not encompass any endothelial markers. ¹¹ Previous studies have demonstrated that integrating endothelial dysfunction markers such as soluble thrombomodulin (sTM), PAI-1, and angiopoietin-2 can improve SIC diagnostic performance. ³⁰ In this study, we identified a positive causal relationship between elevated PAI-1 levels and both sepsis incidence and 28-day mortality, which was further validated in clinical sepsis cohorts. All our findings indicated detection of PAI-1 and its derivative such as t-PAIC could present an effective approach to enhancing the assessment of SIC.

Functional Characteristics and Prognostic Potential of PAI-1/t-PAIC in Sepsis

PAI-1, a member of the serine protease inhibitor (SERPIN) family, was initially identified as a key regulator of the fibrinolytic system. ³¹ Beyond its role in fibrinolysis, PAI-1 has been implicated in modulating inflammatory and immune responses during infection. ³² The active form of PAI-1 exhibits remarkable instability, with a half-life of less than 10 minutes before transitioning to its inactive latent conformation. In circulation, PAI-1 primarily exists in complex with tPA. During sepsis progression, injured vascular endothelial cells persistently release both t-PA and PAI-1, which subsequently form the t-PA/PAI-1 complex (t-PAIC). ³³ Previous investigations have demonstrated parallel expression patterns between total PAI-1 and t-PAIC levels. ³⁴ Consequently, elevated circulating t-PAIC serves as a sensitive biomarker reflecting both fibrinolytic system dysregulation and vascular endothelial injury, thereby facilitating sepsis severity assessment. ³⁵ Earlier studies have established t-PAIC as a reliable predictor of septic shock in ICU patients, with elevated levels also documented in pediatric SIC cases.^36,37 Consistent with these findings, our study revealed a strong positive correlation between PAI-1 and t-PAIC expression in sepsis patients (p<0.05). Moreover, high t-PAIC levels were significantly associated with increased hospital 28-day mortality risk (p<0.05), further underscoring its prognostic value.

Regulatory Mechanism of PAI-1 Expression via G4 Structure and rs1799762 Variant

G4s are increasingly recognized as fundamental structural features of the genome, implicated in a broad spectrum of key biological processes. Experimental evidence has shown that G4 structures bind Thioflavin T (ThT) with high affinity, resulting in a marked enhancement of ThT fluorescence. ³⁸ In the present study, a significant increase in ThT fluorescence emission was observed upon the addition of ThT to PAI-1 5G allele sequences, whereas no such change was detected with PAI-1 4G allele sequences or DEPC-treated water. G4s formation is thought to interfere with critical nucleic acid transactions, including replication, transcription, and translation. Specifically, G4 structures can impede replication fork progression, leading to fork collapse and subsequent double-strand breaks, thereby contributing to genomic instability. ³⁹ Due to their unusual thermodynamic stability, G4s could serve as physical barriers to DNA/RNA unwinding, thereby impeding replication, transcription, and translation and compromising genome integrity. Previous studies had showed that the G4s formed in the NHE III1 region of the c-Myc promoter played an important role in c-Myc transcription suppression. ⁴⁰ In this study, PAI-1 with 5G/5G showed a significant lower gene expression than PAI with 4G/5G or 4G/4G which might due to the G4s formation in PAI-1 5G allele sequence.

Conclusions

This study demonstrates that septic patients with SIC are associated with a higher risk of 28-day hospital mortality, particularly those exhibiting elevated levels of PAI-1. PAI-1 was identified as a key coagulation factor in SIC, and its expression was correlated with the PAI-1 polymorphism (rs1799762) in patients with sepsis. Notably, individuals carrying the 5G/5G genotype displayed enhanced G4-forming propensity in DNA, which contributed to reduced transcriptional activity and consequently lower PAI-1 expression compared to patients with other genotypes. The formation of G4s within the PAI-1 gene may represent a novel mechanism modulating circulating PAI-1 levels, offering a potential prognostic strategy for sepsis, particularly in patients complicated with SIC.

We acknowledge that ThT fluorescence enhancement, while widely used as a reliable indicator of G4 formation, does not provide definitive information on the specific topology of the G4 structures. Future studies employing circular dichroism (CD) spectroscopy or nuclear magnetic resonance (NMR) are warranted to characterize the precise conformational features of the G4s formed in the PAI-1 promoter region.

ORCID iD

Tianyi Gao https://orcid.org/0000-0003-2155-7839

Ethical considerations

The study was conducted in accordance with the institutional guidelines of Nanjing First Hospital Affiliated to Nanjing Medical University and was approved by its Institutional Review Board (approval number: KY20220516-02).

Data Availability Statement

All data generated or analyzed during this study are included in this published article. The DNA sequence results were submitted in supplementary files.*