Meta-analysis of biomarkers for severe dengue infections
Background: Dengue viral infection is an acute infection that has the potential to have severe complications as its major sequela. Currently, there is no routine laboratory biomarker with which to predict the severity of dengue infection or monitor the effectiveness of standard management. Hence, th...
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my.upm.eprints.623952020-01-10T04:57:33Z http://psasir.upm.edu.my/id/eprint/62395/ Meta-analysis of biomarkers for severe dengue infections Soo, Kuan Meng Khalid, Bahariah Ching, Siew Mooi Tham, Chau Ling Basir, Rusliza Chee, Hui Yee Background: Dengue viral infection is an acute infection that has the potential to have severe complications as its major sequela. Currently, there is no routine laboratory biomarker with which to predict the severity of dengue infection or monitor the effectiveness of standard management. Hence, this meta-analysis compared biomarker levels between dengue fever (DF) and severe dengue infections (SDI) to identify potential biomarkers for SDI. Methods: Data concerning levels of cytokines, chemokines, and other potential biomarkers of DF, dengue hemorrhagic fever, dengue shock syndrome, and severe dengue were obtained for patients of all ages and populations using the Scopus, PubMed, and Ovid search engines. The keywords “(IL1* or IL-1*) AND (dengue*)” were used and the same process was repeated for other potential biomarkers, according to Medical Subject Headings terms suggested by PubMed and Ovid. Meta-analysis of the mean difference in plasma or serum level of biomarkers between DF and SDI patients was performed, separated by different periods of time (days) since fever onset. Subgroup analyses comparing biomarker levels of healthy plasma and sera controls, biomarker levels of primary and secondary infection samples were also performed, as well as analyses of different levels of severity and biomarker levels upon infection by different dengue serotypes. Results: Fifty-six studies of 53 biomarkers from 3,739 dengue cases (2,021 DF and 1,728 SDI) were included in this meta-analysis. Results showed that RANTES, IL-7, IL-8, IL-10, IL-18, TGF-b, and VEGFR2 levels were significantly different between DF and SDI. IL-8, IL-10, and IL-18 levels increased during SDI (95% CI, 18.1–253.2 pg/mL, 3–13 studies, n = 177–1,909, I2 = 98.86%–99.75%). In contrast, RANTES, IL-7, TGF-b, and VEGFR2 showed a decrease in levels during SDI (95% CI, −3238.7 to −3.2 pg/mL, 1–3 studies, n = 95–418, I2 = 97.59%–99.99%). Levels of these biomarkers were also found to correlate with the severity of the dengue infection, in comparison to healthy controls. Furthermore, the results showed that IL-7, IL-8, IL-10, TGF-b, and VEGFR2 display peak differences between DF and SDI during or before the critical phase (day 4–5) of SDI. Discussion: This meta-analysis suggests that IL-7, IL-8, IL-10, TGF-b, and VEGFR2 may be used as potential early laboratory biomarkers in the diagnosis of SDI. This can be used to predict the severity of dengue infection and to monitor the effectiveness of treatment. Nevertheless, methodological and reporting limitations must be overcome in future research to minimize variables that affect the results and to confirm the findings. PeerJ 2017 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/62395/1/Meta-analysis%20of%20biomarkers%20for%20severe.pdf Soo, Kuan Meng and Khalid, Bahariah and Ching, Siew Mooi and Tham, Chau Ling and Basir, Rusliza and Chee, Hui Yee (2017) Meta-analysis of biomarkers for severe dengue infections. PeerJ, 2017 (9). pp. 1-25. ISSN 2167-8359 https://peerj.com/articles/3589/ 10.7717/peerj.3589 |
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Background: Dengue viral infection is an acute infection that has the potential to have severe complications as its major sequela. Currently, there is no routine laboratory biomarker with which to predict the severity of dengue infection or monitor the effectiveness of standard management. Hence, this meta-analysis compared biomarker levels between dengue fever (DF) and severe dengue infections (SDI) to identify potential biomarkers for SDI.
Methods: Data concerning levels of cytokines, chemokines, and other potential biomarkers of DF, dengue hemorrhagic fever, dengue shock syndrome, and severe dengue were obtained for patients of all ages and populations using the Scopus, PubMed, and Ovid search engines. The keywords “(IL1* or IL-1*) AND (dengue*)” were used and the same process was repeated for other potential biomarkers, according to Medical Subject Headings terms suggested by PubMed and Ovid. Meta-analysis of the mean difference in plasma or serum level of biomarkers between DF and SDI patients was performed, separated by different periods of time (days) since fever onset. Subgroup analyses comparing biomarker levels of healthy plasma and sera controls, biomarker levels of primary and secondary infection samples were also performed, as well as analyses of different levels of severity and biomarker levels upon infection by different dengue serotypes. Results: Fifty-six studies of 53 biomarkers from 3,739 dengue cases (2,021 DF and 1,728 SDI) were included in this meta-analysis. Results showed that RANTES, IL-7, IL-8, IL-10, IL-18, TGF-b, and VEGFR2 levels were significantly different between DF and SDI. IL-8, IL-10, and IL-18 levels increased during SDI (95% CI, 18.1–253.2 pg/mL, 3–13 studies, n = 177–1,909, I2 = 98.86%–99.75%). In contrast, RANTES, IL-7, TGF-b, and VEGFR2 showed a decrease in levels during SDI (95% CI, −3238.7 to −3.2 pg/mL, 1–3 studies, n = 95–418, I2 = 97.59%–99.99%). Levels of these biomarkers were also found to correlate with the severity of the dengue infection, in comparison to healthy controls. Furthermore, the results showed that IL-7, IL-8, IL-10, TGF-b, and VEGFR2 display peak differences between DF and SDI during or before the critical phase (day 4–5) of SDI. Discussion: This meta-analysis suggests that IL-7, IL-8, IL-10, TGF-b, and VEGFR2 may be used as potential early laboratory biomarkers in the diagnosis of SDI. This can be used to predict the severity of dengue infection and to monitor the effectiveness of treatment. Nevertheless, methodological and reporting limitations must be overcome in future research to minimize variables that affect the results and to confirm the findings. |
format |
Article |
author |
Soo, Kuan Meng Khalid, Bahariah Ching, Siew Mooi Tham, Chau Ling Basir, Rusliza Chee, Hui Yee |
spellingShingle |
Soo, Kuan Meng Khalid, Bahariah Ching, Siew Mooi Tham, Chau Ling Basir, Rusliza Chee, Hui Yee Meta-analysis of biomarkers for severe dengue infections |
author_facet |
Soo, Kuan Meng Khalid, Bahariah Ching, Siew Mooi Tham, Chau Ling Basir, Rusliza Chee, Hui Yee |
author_sort |
Soo, Kuan Meng |
title |
Meta-analysis of biomarkers for severe dengue infections |
title_short |
Meta-analysis of biomarkers for severe dengue infections |
title_full |
Meta-analysis of biomarkers for severe dengue infections |
title_fullStr |
Meta-analysis of biomarkers for severe dengue infections |
title_full_unstemmed |
Meta-analysis of biomarkers for severe dengue infections |
title_sort |
meta-analysis of biomarkers for severe dengue infections |
publisher |
PeerJ |
publishDate |
2017 |
url |
http://psasir.upm.edu.my/id/eprint/62395/1/Meta-analysis%20of%20biomarkers%20for%20severe.pdf http://psasir.upm.edu.my/id/eprint/62395/ https://peerj.com/articles/3589/ |
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