Clinical Study of Transcriptome-based Diagnostic Biomarker for Acute Febrile Illness

Transcriptome-based Diagnostic Biomarker for Acute Febrile Illness: a Cross-sectional Observational Study

Acute febrile illness is the main cause of outpatient visits，and bacterial and viral infections remains the most common cause. The diagnosis of infection is still based on symptoms and traditional techniques, resulting in overuse of antibacterial drugs or delay in treatment. The signature of host transcripts has a potential to reveal different modes of host-pathogen interaction and may serve as a biomarker for infection discrimination. Of note, transcriptome-microarray and RNA-seq methods need sophisticated techniques and expertise interpretation, hampering the universal implement of these platforms in low-tier hospitals and under- resourced countries. This study explores transcriptome-based diagnostic biomarker for acute febrile illness , hoping to achieve rapid, accurate and cost-effective distinction between bacterial and viral infection.

Study Overview

• Status: Recruiting
• Conditions: Acute Febrile Illness
• Intervention / Treatment: Other: Infection

Detailed Description

Acute fever is a common medical emergency worldwide, most often caused by bacterial or viral infections. Early and rapid differential diagnosis of infectious diseases is crucial for improving patient outcomes. While pathogen detection remains the gold standard for diagnosing infections, methods like culture are time-consuming and often lack sensitivity. Additionally, the presence of normal colonizing microorganisms, such as bacteria and viruses in the human body, can lead to false positives in pathogen detection. These limitations often compel physicians to rely on empirical antibacterial therapy based on clinical symptoms, inadvertently contributing to antibiotic overuse and the growing problem of bacterial resistance.

Furthermore, the misuse of antibacterial drugs in patients with non-bacterial infections can lead to complications such as secondary infections with Clostridium difficile, liver dysfunction, kidney damage, cytopenia, and alterations in the body's microbiota. Diagnostic markers based on host inflammatory responses offer an alternative approach to infection diagnosis. However, protein biomarkers like procalcitonin, though widely used in clinical settings, are far from ideal for accurately diagnosing bacterial infections, as they are prone to false positives and negatives.

A promising direction is the analysis of host-pathogen interactions at the transcriptome level, particularly the differential gene expression of the host in response to various pathogens. This area of research has gained significant attention recently. Transcriptomic markers derived from patients' peripheral blood have been successfully utilized in diagnosing and studying the pathogenesis of various infectious diseases.

Despite these advances, studies relying on RNA sequencing or transcriptome chip technology require specialized equipment and bioinformatics expertise, making them expensive and challenging to implement in routine clinical practice. Additionally, the results from transcriptome analysis are not easily validated by reverse transcription polymerase chain reaction(RT-PCR), the "gold standard" for RNA quantification. Therefore, to make transcriptome-based diagnostic markers more clinically applicable, there is a need for real-time technologies, such as PCR, to enhance the accuracy of infection diagnosis and reduce the misuse of antibacterial drugs. Currently, research in this area remains limited.

• Study Type: Observational
• Enrollment (Estimated): 900

Contacts and Locations

• Study Contact: Name: Gang Wang, professor; Phone Number: 86-18560082130; Email: wangg1975@hotmail.com

Study Locations

• China
  • Shandong
    • Jinan, Shandong, China, 250012
      • Recruiting
      • Qilu Hospital of Shandong University
      • Contact: Gang Wang

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Child; Adult; Older Adult
• Accepts Healthy Volunteers: Yes

• Sampling Method: Non-Probability Sample

Study Population

Individuals who have an axillary temperature of 38°C or higher, with a fever duration of less than 14 days.

Description

Inclusion Criteria:

• 1. axillary temperature ≥38°C; 2. duration of fever shorter than 14 days; 3. subjects who are fully informed and agree to participate in this study.

Exclusion Criteria:

• 1.having comorbidities that may affect host gene expression, such as advanced malignancy, autoimmune diseases，immunodeficiency, or taking immune suppressors; 2.pregnancy; 3. mixed infection (viral combined with bacterial infection, autoimmune disease combined with bacterial infection); 4.incomplete clinical information; 5. For safety reasons or the interests of patients, clinicians believe that patients should not participate in any situation in this study.

Study Plan

How is the study designed?

Number of groups / cohorts

3

Cohorts and Interventions

Group / Cohort	Intervention / Treatment
Bacterial infection; Individuals with acute fever whose positive bacteria isolated from sterile or non-sterile sites have pathological characteristics.	Other: Infection; Pathogens such as bacteria and viruses invade the human body, grow, and proliferation, triggering an immune response.
Viral infection; Individuals with acute fever whose viral nucleic acid test and/or serological positive compatible with acute syndrome#(e.g. serology, PCR).	Other: Infection; Pathogens such as bacteria and viruses invade the human body, grow, and proliferation, triggering an immune response.
non-infectious group; Individuals with acute fever whose have negative findings in cultures and PCR; negative image modality findings suspected for infection; confirmed or highly likely other diagnosis; improvement without antibiotics.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
AUC for distinguishing bacterial infection from viral infection	The AUC of the transcript biomarkers for distinguishing bacterial infection from viral infection reflects the diagnostic accuracy of the transcript biomarkers.	Through study completion, an average of 2 years

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
AUC for distinguishing infectious disease from noninfectious disease	The AUC of the transcript biomarkers for distinguishing infectious disease from noninfectious disease reflects the diagnostic accuracy of the transcript biomarkers.	Through study completion, an average of 2 years

Collaborators and Investigators

• Sponsor: Qilu Hospital of Shandong University
• Investigators: Study Director: Gang Wang, Qilu Hospital of Shandong University

Study record dates

Study Major Dates

• Study Start (Actual): September 1, 2021
• Primary Completion (Estimated): December 31, 2024
• Study Completion (Estimated): August 30, 2025

Study Registration Dates

• First Submitted: August 11, 2024
• First Submitted That Met QC Criteria: August 11, 2024
• First Posted (Actual): August 14, 2024

Study Record Updates

• Last Update Posted (Actual): August 14, 2024
• Last Update Submitted That Met QC Criteria: August 11, 2024
• Last Verified: November 1, 2023

More Information

Terms related to this study

• Keywords: Bacterial infection; Viral infection; noninfectious disease
• Additional Relevant MeSH Terms: Wounds and Injuries; Body Temperature Changes; Heat Stress Disorders; Hyperthermia; Fever
• Other Study ID Numbers: KYLL-202008-058

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: UNDECIDED
• IPD Plan Description: It may require further evaluation of data privacy and ethical considerations to ensure that participants' privacy is not compromised by data sharing.

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No