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Machine learning-driven blood transcriptome-based discovery of SARS-CoV-2 specific severity biomarkers
Pandikannan Krishnamoorthy1, Athira S Raj1, Himanshu Kumar1,2
1Laboratory of Immunology and Infectious Disease Biology, Department of Biological Sciences, Indian Institute of Science Education and Research (IISER) Bhopal, Bhopal, Madhya Pradesh, India.
Journal of Medical Virology
|January 10, 2023
Summary
A new 7-gene biomarker accurately distinguishes COVID-19 from other respiratory illnesses and predicts disease severity. This discovery offers potential for early diagnosis and reduced mortality from Coronavirus disease 2019 (COVID-19).
Area of Science:
- Biotechnology
- Bioinformatics
- Genomics
Background:
- The Coronavirus disease 2019 (COVID-19) pandemic, driven by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants, remains a global health crisis.
- Differentiating COVID-19 from other respiratory infections is challenging due to overlapping symptoms, necessitating improved diagnostic tools.
- Early identification of biomarkers is crucial for predicting disease severity and mitigating mortality during outbreaks.
Purpose of the Study:
- To develop a novel diagnostic and prognostic tool for COVID-19 using integrated bioinformatics and machine learning.
- To identify a robust gene signature capable of distinguishing SARS-CoV-2 associated acute respiratory illness (ARI) from other ARIs.
- To validate the identified biomarker's ability to differentiate between severe and non-severe COVID-19 cases and assess its prognostic value.
Main Methods:
- Integration of bioinformatics and machine learning algorithms applied to publicly available COVID-19 transcriptome datasets.
- Identification and validation of a 7-gene biomarker panel.
- Analysis of an independent blood transcriptome dataset for longitudinal assessment of COVID-19 patients.
Main Results:
- A robust 7-gene biomarker was identified, capable of discriminating SARS-CoV-2 associated ARI from other ARIs.
- The biomarker successfully differentiated severe COVID-19 patients from non-severe cases.
- Validation in an independent dataset confirmed the biomarker's dysregulation in severe disease, with restoration during recovery, indicating prognostic potential.
Conclusions:
- The identified 7-gene blood biomarker holds significant potential for the early diagnosis of COVID-19.
- This biomarker may aid in predicting disease severity and reducing COVID-19 associated mortality.
- The findings support the use of this biomarker as a candidate diagnostic and prognostic tool in clinical settings.
