The Activin/Follistatin Axis Is Severely Deregulated in COVID-19 and Independently Associated With In-Hospital Mortality
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Abstract
Background
Activins are members of the transforming growth factor-β superfamily implicated in the pathogenesis of several immunoinflammatory disorders. Based on our previous studies demonstrating that overexpression of activin-A in murine lung causes pathology sharing key features of coronavirus disease 2019 (COVID-19), we hypothesized that activins and their natural inhibitor follistatin might be particularly relevant to COVID-19 pathophysiology.
Methods
Activin-A, activin-B, and follistatin were retrospectively analyzed in 574 serum samples from 263 COVID-19 patients hospitalized in 3 independent centers, and compared with demographic, clinical, and laboratory parameters. Optimal scaling with ridge regression was used to screen variables and establish a prediction model.
Result
The activin/follistatin axis was significantly deregulated during the course of COVID-19, correlated with severity and independently associated with mortality. FACT-CLINYCoD, a scoring system incorporating follistatin, activin-A, activin-B, C-reactive protein, lactate dehydrogenase, intensive care unit admission, neutrophil/lymphocyte ratio, age, comorbidities, and D-dimers, efficiently predicted fatal outcome (area under the curve [AUC], 0.951; 95% confidence interval, .919−.983; P <10−6). Two validation cohorts indicated similar AUC values.
Conclusions
This study demonstrates a link between activin/follistatin axis and COVID-19 mortality and introduces FACT-CLINYCoD, a novel pathophysiology-based tool that allows dynamic prediction of disease outcome, supporting clinical decision making.
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SciScore for 10.1101/2020.09.05.20184655: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement IRB: The study protocol design was approved by the Local Scientific and Ethics Committees and Institutional Review Boards of the University Hospital of Alexandroupolis (Ref. No. 803/23-09-2019 and Ref. No. 87/08-04-2020), AHEPA University Hospital of Thessaloniki (Ref. No. 1789/2020) and ATTIKON University Hospital of Athens (Ref. No. 487/3-9-2020). Randomization An initial cohort of 117 consecutive COVID-19 patients hospitalized at University Hospital, Alexandroupolis and “AHEPA” Hospital, Thessaloniki from March 10, 2020 and had an outcome until July 7, 2020 was endorsed and 314 randomly acquired samples were analyzed (Table 1 and Supplementary Figure 1B). Blind… SciScore for 10.1101/2020.09.05.20184655: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement IRB: The study protocol design was approved by the Local Scientific and Ethics Committees and Institutional Review Boards of the University Hospital of Alexandroupolis (Ref. No. 803/23-09-2019 and Ref. No. 87/08-04-2020), AHEPA University Hospital of Thessaloniki (Ref. No. 1789/2020) and ATTIKON University Hospital of Athens (Ref. No. 487/3-9-2020). Randomization An initial cohort of 117 consecutive COVID-19 patients hospitalized at University Hospital, Alexandroupolis and “AHEPA” Hospital, Thessaloniki from March 10, 2020 and had an outcome until July 7, 2020 was endorsed and 314 randomly acquired samples were analyzed (Table 1 and Supplementary Figure 1B). Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We found bar graphs of continuous data. We recommend replacing bar graphs with more informative graphics, as many different datasets can lead to the same bar graph. The actual data may suggest different conclusions from the summary statistics. For more information, please see Weissgerber et al (2015).
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
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