Sepsis Multiomic Analysis & Risk sTratification in China

Sepsis is a life-threatening organ dysfunction caused by a dysregulated host response to infection and is listed by the World Health Organization as one of the top 10 causes of death worldwide. According to the Global Burden of Disease Study (GBD 2017), there are approximately 48.9 million cases of sepsis globally each year, resulting in about 11 million deaths, with a case fatality rate as high as 20%-40%. In China, the incidence of sepsis is approximately 240 cases per 100,000 population, and the sepsis-related mortality rate in ICU patients reaches 35.5%, significantly higher than that in developed countries. Although international guidelines (such as the Surviving Sepsis Campaign) emphasize the "golden 6 hours" early intervention concept, clinical practice still faces two core problems: delayed diagnosis and insufficient biomarker efficacy. The current diagnostic criteria (Sepsis-3) rely on the SOFA score and evidence of infection, but the SOFA score depends on laboratory indicators (such as platelets and bilirubin), which are difficult to obtain quickly in emergency settings. Commonly used clinical biomarkers such as procalcitonin (PCT) and C-reactive protein (CRP) have significant limitations: although PCT has certain specificity for bacterial infections, its sensitivity is low (approximately 60%-70%) in local infections (such as abscesses) or infections caused by atypical pathogens (such as viruses and fungi); as an acute-phase reactant, CRP elevation lags behind the inflammatory response (6-12 hours after infection) and is interfered with by non-infectious factors such as surgery and trauma; lactate reflects tissue hypoperfusion, but its elevation mostly indicates that the patient has entered the stage of septic shock, missing the window for early intervention.

Studies have shown that each 1-hour delay in the diagnosis of sepsis increases patient mortality by 7.6%. Therefore, the development of highly sensitive and specific early diagnostic tools is a key breakthrough to improve prognosis.

Although microbial culture is the gold standard for sepsis diagnosis, it takes too long and may delay the diagnosis of sepsis. In addition, microbial culture tests may be negative in approximately 30-50% of sepsis patients. Current research indicates that in the intensive care process of sepsis patients, clinical electronic medical record data are increasingly being used to construct multivariate clinical early warning models. Mining these data may accelerate clinical monitoring of sepsis and provide new ideas for the early identification of post-traumatic sepsis.

Peripheral blood mRNA expression levels can directly reflect the host's gene regulatory response to infection and theoretically show detectable systemic changes within hours after infection, having higher early diagnostic potential than protein biomarkers. With the maturity of RNA sequencing technology and the significant reduction in costs, biomarker screening based on whole transcriptome data has become an important strategy for discovering novel sepsis diagnostic biomarkers. However, existing transcriptome studies are mostly based on small-scale cohorts with limited sample sizes and mainly focus on European and American populations, lacking large-sample prospective studies that systematically screen and validate mRNA diagnostic biomarkers in Chinese ICU populations. In addition to diagnostic dilemmas, sepsis patients show significant differences in response to standardized treatment regimens, suggesting the existence of internal molecular subtypes with different biological characteristics. Transcriptomic studies have confirmed the molecular basis of this heterogeneity: Scicluna et al. identified four genomic intrinsic subtypes (MARS classification) in a European multicenter cohort, with significant differences in immune characteristics and 28-day mortality among subtypes; Seymour et al. described two robust clinical phenotypes (α-type and β-type), with β-type characterized by immunosuppression and multiple organ injury. These studies have laid the theoretical foundation for the precise stratification of sepsis, but their samples are all from European and American populations, and there are systematic differences in genetic background, pathogen spectrum, and medical practice compared with Chinese patients, limiting the direct extrapolation applicability of the classification results. Currently, there are no large-sample transcriptome-based stratification studies of sepsis in Chinese ICU populations. Therefore, we propose Substudy 1: Screening of early diagnostic molecular biomarkers and molecular stratification biomarkers for sepsis based on Bulk RNA-seq transcriptome sequencing.

Reverse transcription loop-mediated isothermal amplification (RT-LAMP) has the characteristics of high sensitivity, high specificity, and fast detection speed, and has been widely used in clinical testing. In our previous work, we developed relevant detection methods. Therefore, we propose Substudy 2: Validate the diagnostic efficacy of RT-LAMP as an early rapid bedside diagnostic tool for ICU sepsis.

In addition, we previously used data-independent acquisition (DIA) proteomics and untargeted metabolomics.to screen a panel of plasma biomarkers with diagnostic potential for sepsis; the specific candidate identities are maintained confidentially and will be disclosed with the primary results. Some candidate biomarkers have been validated in our prior cohort studies. Urine has the same diagnostic value. Therefore, we propose Substudy 3: Validate the diagnostic efficacy of plasma protein/metabolic biomarkers as early diagnostic biomarkers for ICU sepsis. Substudy 4: Validate the diagnostic efficacy of urine protein/metabolic biomarkers as early diagnostic biomarkers for ICU sepsis.

This study intends to rely on the ICU of Yuebei People's Hospital to prospectively enroll 1400 subjects (1000 sepsis cases, 400 non-sepsis controls) and establish the largest comprehensive biobank for sepsis research in Chinese ICUs to date. Bulk RNA-seq, RT-LAMP, parallel reaction monitoring (PRM) proteomics, metabolomics, and ELISA-based immunological detection techniques will be used to detect and analyze whole blood, plasma, or urine samples from enrolled patients.