Noninvasive Proteomic Markers for Respiratory Tract Infections in Mechanically Ventilated Patients

Abstract

Introduction: Early and accurate diagnosis of respiratory tract infections (RTI) in critical care settings is essential for appropriate antibiotic treatment and lowering mortality. The current diagnostic methods face critical challenges, including the lack of noninvasive specimens from the site of infection and molecular biomarkers that can predict disease progression and treatment effect. In this study, we addressed these critical challenges by developing a noninvasive method based on the characterization of truncated proteoforms contained in exhaled air collected from mechanically ventilated patients. Methods: Exhaled air samples were collected from twenty-five intubated patients with RTI and twenty-two intubated patients without RTI, determined by clinical data and microbiological testing. Truncated proteoforms were identified using top-down proteomics. Feature selection algorithms were used to identify significant truncated proteoforms associated with RTI. A score system combining the significant truncated proteoforms was constructed and evaluated using multiple logistic regression to predict RTI. Results: The results showed that six truncated proteoforms of lung structure and proteolytic proteins were statistically different between intubated patients with and without RTI. Specifically, the truncated proteoforms of collagen type VI alpha three chain protein, matrix metalloproteinase 9, and putative homeodomain transcription factor 2 were found to be independently associated with RTI. A score system named TrunScore was constructed by combining the three truncated proteoforms, and the diagnostic accuracy was significantly improved compared to individual truncated proteoforms. Conclusions: In this study, we presented a noninvasive method to address the current challenges in diagnosing RTI in critical care settings, by characterizing truncated proteoforms contained in exhaled air from intubated patients. The method provides an accurate prediction for RTI in mechanically ventilated patients and can help diagnose other respiratory tract diseases.

Competing Interest Statement

DC, APD, CRH, ERC, WAB, and MM have competing interests. DC, APD, CRH, and ERC are employed by Zeteo Tech, Inc. WAB is the President and CEO of Zeteo Tech, Inc. MM is the Vice President of Research at Zeteo Tech, Inc. MAM and SC have no competing interests. An unpublished U.S. Provisional Patent Application assigned to Zeteo Tech, Inc was applied based on this research.

Funding Statement

The work presented in this study was supported by the internal research and development fund at Zeteo Tech, Inc.

Author Declarations

I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

Yes

The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

Ethics committee/IRB of The Johns Hopkins University School of Medicine gave ethical approval for this work.

I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.

Yes

I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).

Yes

I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.

Yes

Data Availability

All data produced in the present study are available upon reasonable request to the corresponding author.

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