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Abstract

Sweat-Based Volatile Organic Compound Identification of SARS-CoV-2 Detection †

by
Sorrawit Songsathitmetha
1,
Isaya Thaveesangsakulthai
2,*,
Kaywalee Chatdarong
3 and
Chadin Kulsing
2
1
Department of Pathology, Faculty of Veterinary Science, Chulalongkorn University, Bangkok 10330, Thailand
2
Department of Chemistry, Faculty of Science, Chulalongkorn University, Bangkok 10330, Thailand
3
Department of Obstetrics Gynaecology and Reproduction, Faculty of Veterinary Science, Chulalongkorn University, Bangkok 10330, Thailand
*
Author to whom correspondence should be addressed.
Presented at the 4th International Electronic Conference on Biosensors, 20–22 May 2024; Available online: https://sciforum.net/event/IECB2024.
Proceedings 2024, 104(1), 38; https://doi.org/10.3390/proceedings2024104038
Published: 28 May 2024
(This article belongs to the Proceedings of The 4th International Electronic Conference on Biosensors)
Due to an outbreak of COVID-19 pandemic in recent years, the emerging variants of SARS-CoV-2 causing diagnostic challenges. The rapid, non-invasive diagnostic is an urgent need to differentiate between infected with asymptomatic or symptomatic individuals and uninfected with COVID-19 to control the silent virus spreading in the community. This research developed alternative method of detecting COVID-19, in these approaches mainly focused on volatile organic compound (VOCs) in armpit sweat samples derived from population in Thailand, during variants occurring between April 2021 to May 2023, including Delta and Omicron BA.1/BA.2. VOCs odor emission produced in response to inflammation and infection from SARS-CoV-2 infection body by Gerstel Multi-purpose sampler, headspace solid-phase microextraction coupled with gas chromatography-mass spectrometry (HS-SPME/GC-MS) technique with the total of 150 collected sweat samples with 75 negative confirmed COVID-19 and 75 positive confirmed COVID-19 cases (asymptomatic/symptomatic) used to identified potential biomarkers for COVID-19 related with peak areas of chromatogram results. The statistical analysis of ROC curves including classification rate indices of sensitivity, specificity and accuracy of the different potential markers for armpit sweat samples in GC-MS allowed potential VOCs biomarkers to discriminate the COVID-19 patients as nonanal and aromatic compounds (up to 92% sensitivity, 97% selectivity, and 96% specificity), respectively, and validated the results by comparison with the RT-PCR gold standard technique.

Author Contributions

Conceptualization, I.T. and K.C.; methodology, I.T. and K.C.; software, S.S.; validation, I.T., K.C. and S.S.; formal analysis, C.K.; investigation, S.S., K.C. and C.K.; resources, S.S., K.C. and C.K.; data curation, I.T.; writing—original draft preparation, I.T. and S.S.; writing—review and editing, I.T. and S.S.; visualization, K.C. and C.K.; supervision, S.S. and K.C.; funding acquisition, K.C. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by Chevron Thailand Exploration and Production, Ltd.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Central Research Ethics Committee (COA-CREC103/2020), and approved by the Institutional Review Board at the Faculty of Medicine, Chulalongkorn University (897/63).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.

Conflicts of Interest

The authors declare that this study received funding from Chevron Thailand Exploration and Production, Ltd. The funder had the following involvement with the study: K9 dogs sniff COVID-19 in Thailand. The authors declare that this study received funding from Chevron Thailand Exploration and Production, Ltd. The funder was not involved in the study design, collection, analysis, interpretation of data, the writing of this article or the decision to submit it for publication.
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Share and Cite

MDPI and ACS Style

Songsathitmetha, S.; Thaveesangsakulthai, I.; Chatdarong, K.; Kulsing, C. Sweat-Based Volatile Organic Compound Identification of SARS-CoV-2 Detection. Proceedings 2024, 104, 38. https://doi.org/10.3390/proceedings2024104038

AMA Style

Songsathitmetha S, Thaveesangsakulthai I, Chatdarong K, Kulsing C. Sweat-Based Volatile Organic Compound Identification of SARS-CoV-2 Detection. Proceedings. 2024; 104(1):38. https://doi.org/10.3390/proceedings2024104038

Chicago/Turabian Style

Songsathitmetha, Sorrawit, Isaya Thaveesangsakulthai, Kaywalee Chatdarong, and Chadin Kulsing. 2024. "Sweat-Based Volatile Organic Compound Identification of SARS-CoV-2 Detection" Proceedings 104, no. 1: 38. https://doi.org/10.3390/proceedings2024104038

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