Sensor array and gas chromatographic detection of the blood serum volatolomic signature of COVID-19
Yolande Ketchanji Mougang,
Lorena Di Zazzo,
Marilena Minieri,
Rosamaria Capuano,
Alexandro Catini,
Jacopo Maria Legramante,
Roberto Paolesse,
Sergio Bernardini,
Corrado Di Natale
Affiliations
Yolande Ketchanji Mougang
Department of Electronic Engineering, University of Rome Tor Vergata, Via del Politecnico 1, 00133 Rome, Italy
Lorena Di Zazzo
Department of Chemical Science and Technology, University of Rome Tor Vergata, Via della Ricerca Scientifica, 00133 Rome, Italy
Marilena Minieri
Department of Experimental Medicine, University of Rome Tor Vergata, Via Montpellier 1, 00133 Rome, Italy
Rosamaria Capuano
Department of Electronic Engineering, University of Rome Tor Vergata, Via del Politecnico 1, 00133 Rome, Italy
Alexandro Catini
Department of Electronic Engineering, University of Rome Tor Vergata, Via del Politecnico 1, 00133 Rome, Italy
Jacopo Maria Legramante
Department of Medicine's Systems, University of Rome Tor Vergata, Via Montpellier 1, 00133 Rome, Italy
Roberto Paolesse
Department of Chemical Science and Technology, University of Rome Tor Vergata, Via della Ricerca Scientifica, 00133 Rome, Italy
Sergio Bernardini
Department of Experimental Medicine, University of Rome Tor Vergata, Via Montpellier 1, 00133 Rome, Italy; Emerging Technologies Division of International Federation Clinical Chemistry and Laboratory Medicine (IFCC), Milano, Italy
Corrado Di Natale
Department of Electronic Engineering, University of Rome Tor Vergata, Via del Politecnico 1, 00133 Rome, Italy; Corresponding author
Summary: Volatolomics is gaining consideration as a viable approach to diagnose several diseases, and it also shows promising results to discriminate COVID-19 patients via breath analysis. This paper extends the study of the relationship between volatile compounds (VOCs) and COVID-19 to blood serum. Blood samples were collected from subjects recruited at the emergency department of a large public hospital. The VOCs were analyzed with a gas chromatography mass spectrometer (GC/MS). GC/MS data show that in more than 100 different VOCs, the pattern of abundances of 17 compounds identifies COVID-19 from non-COVID with an accuracy of 89% (sensitivity 94% and specificity 83%). GC/MS analysis was complemented by an array of gas sensors whose data achieved an accuracy of 89% (sensitivity 94% and specificity 80%).
