The DOI matches its Crossref record; 120 of the 120 references it cites were found in a registry or an index.
ACE2/ADAM17/TMPRSS2 Interplay May Be the Main Risk Factor for COVID-19
Open accessAbstract
The Coronavirus Disease 2019 (COVID-19) has already caused hundreds of thousands of deaths worldwide in a few months. Cardiovascular disease, hypertension, diabetes and chronic lung disease have been identified as the main COVID-19 comorbidities. Moreover, despite similar infection rates between men and women, the most severe course of the disease is higher in elderly and co-morbid male patients. Therefore, the occurrence of specific comorbidities associated with renin-angiotensin system (RAS) imbalance mediated by the interaction between angiotensin-converting enzyme 2 (ACE2) and desintegrin and metalloproteinase domain 17 (ADAM17), along with specific genetic factors mainly associated with type II transmembrane serine protease (TMPRSS2) expression, could be decisive for the clinical outcome of COVID-19. Indeed, the exacerbated ADAM17-mediated ACE2, TNF-α, and IL-6R secretion emerges as a possible underlying mechanism for the acute inflammatory immune response and the activation of the coagulation cascade. Therefore, in this review, we focus on the main pathophysiological aspects of ACE2, ADAM17, and TMPRSS2 host proteins in COVID-19. Additionally, we discuss a possible mechanism to explain the deleterious effect of ADAM17 and TMPRSS2 over-activation in the COVID-19 outcome.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China
Huang, C., Wang, Y., Li, X., Ren, L., Zhao, J., Hu, Y., Zhang, L., Fan, G., Xu, J., Gu, X., et al. (2020) · The Lancet · doi:10.1016/s0140-6736(20)30183-5 · Cited by 48,884
Clinical characteristics of coronavirus disease 2019 in China
Guan, W.-J., Ni, Z.-Y., Hu, Y., Liang, W.-H., Ou, C.-Q., He, J.-X., Liu, L., Shan, H., Lei, C.-L., Hui, D. S. C., et al. (2020) · New England Journal of Medicine · doi:10.1056/nejmoa2002032 · Cited by 30,246
A novel coronavirus from patients with pneumonia in China, 2019
Zhu, N., Zhang, D., Wang, W., Li, X., Yang, B., Song, J., Zhao, X., Huang, B., Shi, W., Lu, R., et al. (2020) · New England Journal of Medicine · doi:10.1056/nejmoa2001017 · Cited by 28,244
A pneumonia outbreak associated with a new coronavirus of probable bat origin
Zhou, P., Yang, X.-L., Wang, X.-G., Hu, B., Zhang, L., Zhang, W., Si, H.-R., Zhu, Y., Li, B., Huang, C.-L., et al. (2020) · Nature · doi:10.1038/s41586-020-2012-7 · Cited by 21,969
Hoffmann, M., Kleine-Weber, H., Schroeder, S., Krüger, N., Herrler, T., Erichsen, S., Schiergens, T. S., Herrler, G., Wu, N.-H., Nitsche, A., et al. (2020) · Cell · doi:10.1016/j.cell.2020.02.052 · Cited by 20,286
Yang, X., Yu, Y., Xu, J., Shu, H., Xia, J., Liu, H., Wu, Y., Zhang, L., Yu, Z., Fang, M., et al. (2020) · The Lancet Respiratory Medicine · doi:10.1016/s2213-2600(20)30079-5 · Cited by 10,066
Cryo-EM structure of the 2019-nCoV spike in the prefusion conformation
Wrapp, D., Wang, N., Corbett, K. S., Goldsmith, J. A., Hsieh, C.-L., Abiona, O., Graham, B. S., & McLellan, J. S. (2020) · Science · doi:10.1126/science.abb2507 · Cited by 8,897
Structure, function and antigenicity of the SARS-CoV-2 spike glycoprotein
Walls, A. C., Park, Y.-J., Tortorici, M. A., Wall, A., McGuire, A. T., & Veesler, D. (2020) · doi:10.1101/2020.02.19.956581 · Cited by 8,586
Pathological findings of COVID-19 associated with acute respiratory distress syndrome
Xu, Z., Shi, L., Wang, Y., Zhang, J., Huang, L., Zhang, C., Liu, S., Zhao, P., Liu, H., Zhu, L., et al. (2020) · The Lancet Respiratory Medicine · doi:10.1016/s2213-2600(20)30076-x · Cited by 8,545
A novel coronavirus outbreak of global health concern
Wang, C., Horby, P. W., Hayden, F. G., & Gao, G. F. (2020) · The Lancet · doi:10.1016/s0140-6736(20)30185-9 · Cited by 7,700
Cited by
Chen, H., Peng, J., Wang, T., Wen, J., Chen, S., Huang, Y., & Zhang, Y. (2023) · Biochemical Pharmacology · doi:10.1016/j.bcp.2022.115370 · Cited by 19
Metadata
- Authors
- Zipeto, D., Palmeira, J. D. F., Argañaraz, G. A., & Argañaraz, E. R.
- Venue
- Frontiers in Immunology
- Publisher
- Frontiers Media SA
- Published
- 2020-10-07
- Volume
- 11
- Pages
- 576745-576745
- ISSN
- 1664-3224 (ISSN-L)
- OpenAlex
- W3092005914
- Cited by
- 267
- References
- 120
- FWCI
- 6.04
- Type
- journal article
- Language
- en
- Open access
- gold
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: ACE2/ADAM17/TMPRSS2 Interplay May Be the Main Risk Factor for COVID-19. https://app.cochat.ai/papers/10.3389/fimmu.2020.576745
- The paper
- Zipeto, D., Palmeira, J. D. F., Argañaraz, G. A., & Argañaraz, E. R. (2020). ACE2/ADAM17/TMPRSS2 Interplay May Be the Main Risk Factor for COVID-19. Frontiers in Immunology. https://doi.org/10.3389/fimmu.2020.576745
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.