The DOI matches its Crossref record; 64 of the 64 references it cites were found in a registry or an index.
Comorbid diabetes results in immune dysregulation and enhanced disease severity following MERS-CoV infection
Open accessAbstract
Middle East respiratory syndrome coronavirus (MERS-CoV) emerged in 2012 in Saudi Arabia and has caused over 2400 cases and more than 800 deaths. Epidemiological studies identified diabetes as the primary comorbidity associated with severe or lethal MERS-CoV infection. Understanding how diabetes affects MERS is important because of the global burden of diabetes and pandemic potential of MERS-CoV. We used a model in which mice were made susceptible to MERS-CoV by expressing human DPP4, and type 2 diabetes was induced by administering a high-fat diet. Upon infection with MERS-CoV, diabetic mice had a prolonged phase of severe disease and delayed recovery that was independent of virus titers. Histological analysis revealed that diabetic mice had delayed inflammation, which was then prolonged through 21 days after infection. Diabetic mice had fewer inflammatory monocyte/macrophages and CD4+ T cells, which correlated with lower levels of Ccl2 and Cxcl10 expression. Diabetic mice also had lower levels of Tnfa, Il6, Il12b, and Arg1 expression and higher levels of Il17a expression. These data suggest that the increased disease severity observed in individuals with MERS and comorbid type 2 diabetes is likely due to a dysregulated immune response, which results in more severe and prolonged lung pathology.
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Cites
International Diabetes Federation 2017
Carracher, A. M., Marathe, P. H., & Close, K. L. (2018) · Journal of Diabetes · doi:10.1111/1753-0407.12644 · Cited by 13,418
Assiri, A., Al-Tawfiq, J. A., Al-Rabeeah, A. A., Al-Rabiah, F. A., Al-Hajjar, S., Al-Barrak, A., Flemban, H., Al-Nassir, W. N., Balkhy, H. H., Al-Hakeem, R. F., et al. (2013) · The Lancet Infectious Diseases · doi:10.1016/s1473-3099(13)70204-4 · Cited by 1,435
The use of animal models in diabetes research
King, A. J. (2012) · British Journal of Pharmacology · doi:10.1111/j.1476-5381.2012.01911.x · Cited by 1,303
Sex differences in human adipose tissues – the biology of pear shape
Karastergiou, K., Smith, S. R., Greenberg, A. S., & Fried, S. K. (2012) · Biology of Sex Differences · doi:10.1186/2042-6410-3-13 · Cited by 1,109
Evidence for Camel-to-Human Transmission of MERS Coronavirus
Azhar, E. I., El-Kafrawy, S. A., Farraj, S. A., Hassan, A. M., Al-Saeed, M. S., Hashem, A. M., & Madani, T. A. (2014) · New England Journal of Medicine · doi:10.1056/nejmoa1401505 · Cited by 905
Molecular basis of binding between novel human coronavirus MERS-CoV and its receptor CD26
Lu, G., Hu, Y., Wang, Q., Qi, J., Gao, F., Li, Y., Zhang, Y., Zhang, W., Yuan, Y., Bao, J., et al. (2013) · Nature · doi:10.1038/nature12328 · Cited by 739
Middle East respiratory syndrome coronavirus in dromedary camels: an outbreak investigation
Haagmans, B. L., Al Dhahiry, S. H. S., Reusken, C. B. E. M., Raj, V. S., Galiano, M., Myers, R., Godeke, G.-J., Jonges, M., Farag, E., Diab, A., et al. (2014) · The Lancet Infectious Diseases · doi:10.1016/s1473-3099(13)70690-x · Cited by 671
MERS-CoV infection in humans is associated with a pro-inflammatory Th1 and Th17 cytokine profile
Mahallawi, W. H., Khabour, O. F., Zhang, Q., Makhdoum, H. M., & Suliman, B. A. (2018) · Cytokine · doi:10.1016/j.cyto.2018.01.025 · Cited by 558
Rapid generation of a mouse model for Middle East respiratory syndrome
Zhao, J., Li, K., Wohlford-Lenane, C., Agnihothram, S. S., Fett, C., Zhao, J., Gale, M. J., Baric, R. S., Enjuanes, L., Gallagher, T., et al. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1323279111 · Cited by 452
Hui, D. S., Azhar, E. I., Kim, Y.-J., Memish, Z. A., Oh, M.-D., & Zumla, A. (2018) · The Lancet Infectious Diseases · doi:10.1016/s1473-3099(18)30127-0 · Cited by 448
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Zhu, L., She, Z.-G., Cheng, X., Qin, J.-J., Zhang, X.-J., Cai, J., Lei, F., Wang, H., Xie, J., Wang, W., et al. (2020) · Cell Metabolism · doi:10.1016/j.cmet.2020.04.021 · Cited by 1,602
Why does COVID-19 disproportionately affect older people?
Mueller, A. L., McNamara, M. S., & Sinclair, D. A. (2020) · Aging · doi:10.18632/aging.103344 · Cited by 1,128
Diabetes in COVID-19: Prevalence, pathophysiology, prognosis and practical considerations
Singh, A. K., Gupta, R., Ghosh, A., & Misra, A. (2020) · Diabetes & Metabolic Syndrome: Clinical Research & Reviews · doi:10.1016/j.dsx.2020.04.004 · Cited by 893
COVID-19 pandemic, coronaviruses, and diabetes mellitus
Muniyappa, R., & Gubbi, S. (2020) · American Journal of Physiology-Endocrinology and Metabolism · doi:10.1152/ajpendo.00124.2020 · Cited by 869
Metadata
- Authors
- Kulcsar, K. A., Coleman, C. M., Beck, S. E., & Frieman, M. B.
- Venue
- JCI Insight
- Published
- 2019-10-17
- Volume
- 4
- Issue
- 20
- ISSN
- 2379-3708 (ISSN-L)
- OpenAlex
- W2974984390
- Cited by
- 373
- References
- 64
- FWCI
- 52.34
- Type
- journal article
- Language
- en
- Open access
- gold
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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