The Molecular Basis of Gender Variations in Mortality Rates Associated with the Novel Coronavirus (COVID-19) Outbreak
Bibliographic record
Abstract
Since the outbreak of the novel coronavirus disease (COVID-19) at the end of 2019, the clinical presentation of the disease showed a great heterogeneity with a diverse impact between different subpopulations. Emerging evidence from different parts of the world showed significantly poor outcome among males compared to female patients. A better understanding of the molecular mechanisms behind this difference might be a fundamental step for a more effective and targeted response to the outbreak. For that reason, here we try to investigate the molecular basis of the gender variations in mortality rates related to COVID-19 infection. To achieve this, we used our in-house pipeline to process publicly available lung transcriptomic data from 141 females compared to 286 males. After excluding Y specific genes, our results showed a shortlist of 73 genes that are differentially expressed between the two groups. Our results showed downregulation of a group of genes that are involved in the regulation of hydrolase activity including (AGTR1, CHM, DDX3X, FGFR3, SFRP2, and NLRP2), which is also believed to be essential for lung immune response and antimicrobial activity in the lung tissues in males compared to females. In contrast, our results showed an upregulation of angiotensin II receptor type 1 (AGTR1), a member of the renin-angiotensin system (RAS) that plays a role in angiotensin-converting enzyme 2 (ACE2) activity modulation. Interestingly, recent reports and experimental animal models highlight an important role of this receptor in SARS-Coronavirus lung damage as well as pulmonary edema, suggesting a possible role of its blockers like losartan and olmesartan as potential therapeutic options for COVID-19 infection. Finally, our results also showed a differential expression of different genes that are involved in the immune response including the NLRP2 and PTGDR2, further supporting the notion of the sex-based immunological differences. Taken together, our results provide an initial evidence of the molecular mechanisms that might be involved in the differential outcomes observed between both genders during the COVID-19 outbreak. This might be essential for the discovery of new targets and more precise therapeutic options to treat COVID-19 patients from different clinical and epidemiological characteristics with the aim of improving their outcome.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.110 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".