TY - JOUR
T1 - New proteomic signatures to distinguish between zika and dengue infections
AU - Allgoewer, Kristina
AU - Maity, Shuvadeep
AU - Zhao, Alice
AU - Lashua, Lauren
AU - Ramgopal, Moti
AU - Balkaran, Beni N.
AU - Liu, Liyun
AU - Purushwani, Savita
AU - Arévalo, Maria T.
AU - Ross, Ted M.
AU - Choi, Hyungwon
AU - Ghedin, Elodie
AU - Vogel, Christine
N1 - Publisher Copyright:
© 2021 THE AUTHORS. Published by Elsevier Inc on behalf of American Society for Biochemistry and Molecular Biology. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
PY - 2021
Y1 - 2021
N2 - Distinguishing between Zika and dengue virus infections is critical for accurate treatment, but we still lack detailed understanding of their impact on their host. To identify new protein signatures of the two infections, we used next-generation proteomics to profile 122 serum samples from 62 Zika and dengue patients. We quantified >500 proteins and identified 13 proteins that were significantly differentially expressed (adjusted p-value < 0.05). These proteins typically function in infection and wound healing, with several also linked to pregnancy and brain function. We successfully validated expression differences with Carbonic Anhydrase 2 in both the original and an independent sample set. Three of the differentially expressed proteins, i.e., Fibrinogen Alpha, Platelet Factor 4 Variant 1, and Pro-Platelet Basic Protein, predicted Zika virus infection at a ~70% true-positive and 6% false-positive rate. Further, we showed that intraindividual temporal changes in protein signatures can disambiguate diagnoses and serve as indicators for past infections. Taken together, we demonstrate that serum proteomics can provide new resources that serve to distinguish between different viral infections.
AB - Distinguishing between Zika and dengue virus infections is critical for accurate treatment, but we still lack detailed understanding of their impact on their host. To identify new protein signatures of the two infections, we used next-generation proteomics to profile 122 serum samples from 62 Zika and dengue patients. We quantified >500 proteins and identified 13 proteins that were significantly differentially expressed (adjusted p-value < 0.05). These proteins typically function in infection and wound healing, with several also linked to pregnancy and brain function. We successfully validated expression differences with Carbonic Anhydrase 2 in both the original and an independent sample set. Three of the differentially expressed proteins, i.e., Fibrinogen Alpha, Platelet Factor 4 Variant 1, and Pro-Platelet Basic Protein, predicted Zika virus infection at a ~70% true-positive and 6% false-positive rate. Further, we showed that intraindividual temporal changes in protein signatures can disambiguate diagnoses and serve as indicators for past infections. Taken together, we demonstrate that serum proteomics can provide new resources that serve to distinguish between different viral infections.
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U2 - 10.1016/J.MCPRO.2021.100052
DO - 10.1016/J.MCPRO.2021.100052
M3 - Article
C2 - 33582300
AN - SCOPUS:85104414229
SN - 1535-9476
VL - 20
JO - Molecular and Cellular Proteomics
JF - Molecular and Cellular Proteomics
M1 - 100052
ER -