Rapid Discrimination of Malaria- and Dengue-Infected Patients Sera Using Raman Spectroscopy

Malaria and dengue have overlapping clinical symptoms and are prevalent in the same geographic region (tropical and subtropical), hence precise diagnosis is challenging. The high mortality rate associated with both malaria and dengue could be attributed to “false”, “delayed”, or “missed” diagnosis....

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Veröffentlicht in:Analytical chemistry (Washington) 2019-06, Vol.91 (11), p.7054-7062
Hauptverfasser: Patel, Sandip K, Rajora, Nishant, Kumar, Saurabh, Sahu, Aditi, Kochar, Sanjay K, Krishna, C. Murali, Srivastava, Sanjeeva
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Sprache:eng
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Zusammenfassung:Malaria and dengue have overlapping clinical symptoms and are prevalent in the same geographic region (tropical and subtropical), hence precise diagnosis is challenging. The high mortality rate associated with both malaria and dengue could be attributed to “false”, “delayed”, or “missed” diagnosis. The present study thus aims to stratify malaria and dengue using Raman spectroscopy (RS). In total, 130 human sera were analyzed for model development and double-blinded testing. Principal components linear discriminant analysis (PC-LDA) of acquired RS-spectra could classify malaria and dengue with a minor overlap of 16.7%. Receiver operating characteristic (ROC) analysis of test samples showed sensitivity/specificity of 0.9529 for malaria vs healthy controls (HC) and 0.9584 for dengue vs HC. The Raman findings were complemented by mass spectroscopy (MS)-based metabolite analysis of 8 individuals, each from malaria, dengue, and HC. Several of the metabolites, including amino acids, cell-free DNA, creatinine, and bilirubin, assigned for the predominant RS-bands were also identified by MS and showed similar trends. Our data clearly indicates that RS-based serum analysis using a microprobe has immense potential for early, accurate, and automated detection and discrimination of malaria and dengue, and in the future, it could be extrapolated in field-settings combined with hand-held RS. Further, this approach might be extended to diagnose other closely related infections with similar clinical manifestations.
ISSN:0003-2700
1520-6882
DOI:10.1021/acs.analchem.8b05907