Reply to Jakovac: Sex differences in COVID-19 course and outcome: progesterone should not be neglected
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Abstract
Letter to the EditorReply to Jakovac: Sex differences in COVID-19 course and outcome: progesterone should not be neglectedLuciane H. Gargaglioni and Danuzia A. MarquesLuciane H. GargaglioniDepartment of Animal Morphology and Physiology, FCAVJ-UNESP-São Paulo State University, Jaboticabal, Brazil and Danuzia A. MarquesDepartment of Pediatrics, Centre de recherche de l'Institut Universitaire de Cardiologie et de Pneumologie de Québec, Université Laval, Québec, CanadaPublished Online:23 Oct 2020https://doi.org/10.1152/japplphysiol.00835.2020MoreFiguresReferencesRelatedInformationSectionsGRANTSDISCLOSURESAUTHOR CONTRIBUTIONSAUTHOR NOTESPDF (69 KB)Download PDF ToolsExport citationAdd to favoritesGet permissionsTrack citations ShareShare onFacebookXLinkedInWeChat to the editor: The Letter to the Editor entitled "Sex differences in COVID-19 course and outcome: progesterone should not be neglected" (4a) in response to our study (2) included a proposition of the benefits of progesterone use for COVID-19 course and outcome. In fact, one recent review also suggested the use of sex hormones, such as estradiol and progesterone, in the fight against COVID-19 (5). Additionally, there is one ongoing study registered at ClinicalTrials.gov (NCT04365127—Progesterone for the Treatment of COVID-19 in Hospitalized Men) in which volunteer men who are hospitalized with COVID-19 and meet the eligibility criteria will receive 100 mg of progesterone administered subcutaneously twice daily for 5 days, in addition to institutional standard of care. The organism's first antiviral responses against pathogens are made by the activation inflammatory pathways of the immune system; in this scenario, estradiol can be important, as it has immunostimulatory roles (6) and can help the organism to respond to the viral infection. However, an exaggerated immune response, known as a "cytokine storm," can lead to increased severity of the disease and progesterone and testosterone might be used in this case, as both are immunosuppressive and counteract the pathways affected by estradiol (6). As widely reported by many studies, scientific reports and by the media, the highest mortality in patients with COVID-19 is observed in older and immunocompromised individuals. Age increases the levels of proinflammatory cytokines and decreases the expression of immune memory/effector cells which could lead to increased susceptibility to infections and worsening of the disease (3). This remodeling of the immune system and decline in immune efficacy with age could drive a decreased response to vaccines (3) and can be a challenge in the control of COVID-19. Age is accompanied by a decline in sex hormones in both sexes, which could be related to the remodeling of the immune system (3). Therefore, sex hormone replacement could be important in the context of COVID-19 and cytokine release (as we discussed in our study), as sex hormones modulate the immune system and can help with the balance of inflammatory and anti-inflammatory cytokines (6). Nevertheless, sex hormone therapies can also bring risks, as they can change many homeostatic parameters, depending on type of hormone (different synthetic variations or bioidentical), the dose used, the via (oral, transdermal, etc.), and the period of use, since many studies already shown high risk for vascular problems related hormonal replacement therapy. In this regard, one French study of 271 postmenopausal women who had previously presented venous thrombotic event (VTE) episode showed that oral hormone treatment users had 4-fold-increased odds of a VTE, whereas transdermal hormone users had no increased risk (1). Therefore, it is important to highlight that synthetic progestins present differing degrees of androgenic and thromboembolic properties that should be considered when prescribing individualized treatments (4). In conclusion, the use of sex hormone therapies can have benefits, but can also lead to adverse effects. Interactions in individuals with comorbidities must be carefully evaluated so that their risks do not outweigh the benefits.GRANTS This work was supported by MCTI Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq): Luciane H. Gargaglioni 407490/2018-3 and by São Paulo Research Foundation (FAPESP): Luciane H. Gargaglioni 2019/09469-8.DISCLOSURES No conflicts of interest, financial or otherwise, are declared by the authors.AUTHOR CONTRIBUTIONS L.H.G. and D.A.M. drafted manuscript; L.H.G. and D.A.M. edited and revised manuscript; L.H.G. and D.A.M. approved final version of manuscript.AUTHOR NOTESCorrespondence: L. H. Gargaglioni (luciane.gargaglioni@unesp.br); D. A. Marques (danuzia.am@gmail.com). Download PDF Previous Back to Top Next FiguresReferencesRelatedInformationREFERENCES1. Canonico M, Oger E, Plu-Bureau G, Conard J, Meyer G, Lévesque H, Trillot N, Barrellier MT, Wahl D, Emmerich J, Scarabin PY; Estrogen and Thromboembolism Risk (ESTHER) Study Group. Hormone therapy and venous thromboembolism among postmenopausal women: impact of the route of estrogen administration and progestogens: the ESTHER study. Circulation 115: 840–845, 2007. doi:10.1161/CIRCULATIONAHA.106.642280. Crossref | PubMed | Web of Science | Google Scholar2. Gargaglioni LH, Marques DA. Let's talk about sex in the context of COVID-19. J Appl Physiol (1985) 128: 1533–1538, 2020. doi:10.1152/japplphysiol.00335.2020. Link | Web of Science | Google Scholar3. Giefing-Kröll C, Berger P, Lepperdinger G, Grubeck-Loebenstein B. How sex and age affect immune responses, susceptibility to infections, and response to vaccination. Aging Cell 14: 309–321, 2015. doi:10.1111/acel.12326. Crossref | PubMed | Web of Science | Google Scholar4. Giordano Imbroll M, Gruppetta M. A current perspective into young female sex hormone replacement: a review. Expert Rev Endocrinol Metab. In press. doi:10.1080/17446651.2020.1816820. Crossref | PubMed | Web of Science | Google Scholar4a. Jakovac H. Sex differences in COVID-19 course and outcome: progesterone should not be neglected. J Appl Physiol (1985). doi:10.1152/japplphysiol.00740.2020.Link | Web of Science | Google Scholar5. Mauvais-Jarvis F, Klein SL, Levin ER. Estradiol, progesterone, immunomodulation, and COVID-19 outcomes. Endocrinology 161: bqaa127, 2020. doi:10.1210/endocr/bqaa127. Crossref | PubMed | Web of Science | Google Scholar6. Moulton VR. Sex hormones in acquired immunity and autoimmune disease. Front Immunol 9: 2279, 2018. doi:10.3389/fimmu.2018.02279. Crossref | PubMed | Web of Science | Google Scholar CollectionsAPS Cross-Journal CollectionsCoronavirus-Related Papers Related ArticlesSex differences in COVID-19 course and outcome: progesterone should not be neglected 23 Oct 2020Journal of Applied Physiology More from this issue > Volume 129Issue 5November 2020Pages 1009-1010 Copyright & PermissionsCopyright © 2020 the American Physiological Societyhttps://doi.org/10.1152/japplphysiol.00835.2020PubMed33096967History Received 30 September 2020 Accepted 1 October 2020 Published online 23 October 2020 Published in print 1 November 2020 KeywordsCOVID-19estradiolfemalemaleprogesterone Metrics publications0supporting0mentioning0contrasting0Smart Citations0000Citing PublicationsSupportingMentioningContrastingView CitationsSee how this article has been cited at scite.aiscite shows how a scientific paper has been cited by providing the context of the citation, a classification describing whether it supports, mentions, or contrasts the cited claim, and a label indicating in which section the citation was made. 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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.047 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.026 | 0.032 |
| Insufficient payload (model declined to judge) | 0.005 | 0.005 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".