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NCT Number: NCT07599644

Sepsis Multiomic Analysis & Risk sTratification in China

Sepsis is a life-threatening organ dysfunction caused by a dysregulated host response to infection, and delayed diagnosis remains a major driver of mortality, while traditional biomarkers (PCT, CRP, lactate) have limited early sensitivity and timeliness. This prospective, single-center, observational cohort study at Yuebei People's Hospital will enroll approximately 1400 ICU patients (1000 with sepsis and 400 non-sepsis controls) to build a comprehensive multi-omics biobank and identify early diagnostic and risk-stratification biomarkers for sepsis. Using bulk RNA sequencing, targeted proteomics (PRM), targeted metabolomics, and ELISA validation, the study aims to: (1) screen mRNA diagnostic biomarkers and establish a molecular risk-stratification system; (2) develop and validate an RT-LAMP rapid bedside detection method; and (3) identify and validate plasma and urine protein/metabolite biomarkers and build a combined diagnostic model. The specific candidate biomarker identities are maintained confidentially and will be disclosed with the primary results.

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Key information

Age range

18 year and older

Sex eligibility

All sexes

Study type

Observational

Primary location

Yuebei People's Hospital

Shaoguan, Guangdong, 512026, China

Location status: Recruiting

Location contact

Pingsen Zhao Principal Investigator, Dr.

CONTACT

[email protected]

8613923034950

About this study

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.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

- Sepsis Group:

  • Age ≥ 18 years
  • Meets the Sepsis-3 diagnostic criteria: confirmed or suspected infection with an increase in SOFA score of ≥ 2 points from baseline
  • Develops sepsis within 72 hours of ICU admission
  • Voluntarily signs the informed consent form (or signed by the legal representative)

Inclusion criteria

- Non-Sepsis Group:

  • Age ≥ 18 years
  • Hospitalized in the ICU during the same period, with no clear evidence of infection and not meeting the diagnostic criteria for sepsis
  • Expected ICU treatment time ≥ 24 hours
  • Voluntarily signs the informed consent form (or signed by the legal representative)

Exclusion criteria

  • End-stage chronic organ failure (end-stage renal disease, decompensated liver cirrhosis [Child-Pugh Grade C], or chronic heart failure NYHA Class IV), or malignant tumor
  • Immunocompromised, autoimmune disease, or long-term use of glucocorticoids/immunosuppressants within the past 3 months
  • Pregnant or postpartum patients
  • Other conditions deemed unsuitable by the investigator (e.g., terminal state, refusal to cooperate with sample collection, or inability to cooperate with in-hospital and out-of-hospital follow-up)

Treatment and study plan

Primary outcomes

  1. Diagnostic performance of the mRNA biomarker panel for early sepsis

    Time frame: Within 24 hours of ICU admission (baseline)

    Whole-blood Bulk RNA-seq expression profiling of the sepsis versus non-sepsis groups. Core diagnostic mRNA biomarkers are selected by multi-algorithm cross-validation (WGCNA + LASSO + SVM-RFE). Diagnostic efficacy for early ICU sepsis is assessed against the Sepsis-3 reference classification and reported as AUC, sensitivity, specificity, PPV, and NPV.

  2. Number of sepsis molecular subtypes identified by unsupervised consensus clustering

    Time frame: Baseline (within 24 hours of ICU admission)

    Unsupervised consensus clustering is applied to the sepsis-group whole-blood mRNA expression profiles; the optimal number of subtypes is determined by standard criteria (consensus CDF and delta-area). The reported value is the number of molecular subtypes identified.

    Unit of Measure: subtypes (count)

  3. Diagnostic accuracy (AUC) of the RT-LAMP assay for early sepsis

    Time frame: Within 24 hours of ICU admission (baseline)

    The RT-LAMP assay targeting core sepsis mRNA markers is applied to whole-blood samples. Diagnostic accuracy for distinguishing sepsis from non-sepsis (against the Sepsis-3 reference classification) is summarized by the area under the ROC curve (AUC). Sensitivity, specificity, PPV, and NPV at the optimal cut-off are reported as supporting measures in the Description.

    Unit of Measure: AUC (0-1)

  4. Diagnostic accuracy (AUC) of the combined protein/metabolic biomarker model for sepsis

    Time frame: Within 24 hours of ICU admission (baseline)

    Plasma/urine protein biomarkers (measured by PRM/ELISA) and metabolic biomarkers are combined by multivariable logistic regression into a multi-marker diagnostic model. Diagnostic accuracy for distinguishing sepsis from non-sepsis (against the Sepsis-3 reference classification) is summarized by the area under the ROC curve (AUC). Sensitivity, specificity, PPV, and NPV at the optimal cut-off are reported as supporting measures in the Description.

    Unit of Measure: AUC (0-1)

Secondary outcomes

  1. 28-day all-cause mortality

    Time frame: 28 days from baseline

    ll-cause mortality within 28 days after enrollment, confirmed via the medical record system and telephone follow-up.

    Unit of Measure: participants (percentage)

  2. ICU length of stay

    Time frame: From ICU admission through ICU discharge, up to 28 days

    Duration of the ICU stay for enrolled patients, from ICU admission to ICU discharge.

    Unit of Measure: days

  3. Incidence of new-onset organ dysfunction

    Time frame: Through 28 days from baseline

    Proportion of patients developing new-onset organ dysfunction during the observation period, defined by an increase in the SOFA score in an organ system not already dysfunctional at baseline.

    Unit of Measure: participants (percentage)

  4. Correlation of core biomarker expression with 28-day mortality and SOFA score

    Time frame: 28 days from baseline

    Correlation between the mRNA and protein expression levels of core biomarkers and (a) 28-day all-cause mortality and (b) the Sequential Organ Failure Assessment (SOFA) score. The SOFA score ranges from 0 to 24, with higher scores indicating more severe organ dysfunction (a worse outcome).

  5. Comparative diagnostic performance versus PCT and CRP

    Time frame: Within 24 hours of ICU admission (baseline)

    Comparison of diagnostic efficacy (AUC, compared by DeLong's test) between the novel biomarkers/combined diagnostic model and the traditional indicators PCT and CRP.

  6. Subgroup analysis of biomarker diagnostic performance

    Time frame: Within 24 hours of ICU admission (baseline)

    Diagnostic efficacy (AUC, sensitivity, specificity) of biomarkers across pre-specified subgroups (infection site, pathogen type, organ injury).

  7. Immune-inflammatory pathway characteristics across molecular strata

    Time frame: Baseline (within 24 hours of ICU admission)

    Analysis of immune-inflammatory pathway features (e.g., by GSEA) that differentiate the sepsis molecular strata.

Study contacts

Contact information is provided by the study sponsor or research team.

Principal Investigator

CONTACT

[email protected]

8613923034950

Sponsors and collaborators

Lead sponsor

Yuebei People's Hospital

Other

Registry information

Official study title

Sepsis Multiomic Analysis & Risk sTratification in China (China SMART-1): A Prospective Observational Cohort Study

Acronym: China SMART-1

Important dates

Study start
2026
Primary completion
2027
Study completion
2028
First posted
May 20, 2026
Registry last updated
Jul 10, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

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This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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