SARS–CoV-2 Receptor ACE2 Gene Is Associated with Hypertension and Severity of COVID 19: Interaction with Sex, Obesity, and Smoking
Bibliographic record
Abstract
BACKGROUND: Angiotensin-converting enzyme 2 (ACE2) has been identified as the entry receptor for coronaviruses into human cells, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that causes coronavirus disease 2019 (COVID-19). Since hypertension (HT) is a leading comorbidity in non-survivors of COVID-19, we tested for association between ACE2 gene and HT in interaction with specific pre-existing conditions known to be associated with COVID-19 severity. METHODS: Genetic analysis of ACE2 gene was conducted in French-Canadian (FC) and British populations. RESULTS: In FC individuals, the T allele of the single nucleotide polymorphism rs2074192 of ACE2 gene was a risk factor for HT in adult obese males [odds ratio (OR) = 1.39, 95% confidence interval (CI) 1.06-1.83)] and even more so in obese males who smoked (OR = 1.67, CI: 1.24-2.55), but not in lean males, non-smoker males or females. The T allele was significantly associated with severity of HT and with earlier penetrance of HT in obese smoking males. Significant interaction between the T allele and obesity was present in both sexes. The association of ACE2 (rs233575) genotype with blood pressure was also seen in adolescents but the interaction with obesity was present only in females. Several variants in ACE2 gene were found to be associated with HT in obese, smoking males in British individuals of the UK Biobank. In addition, we observed more severe outcomes to COVID-19 in association with ACE2 risk alleles in obese, smoking males. CONCLUSIONS: This is the first report that ACE2 variants are associated with earlier penetrance and more severe HT and with more severe outcomes of COVID-19 in obese smoking males.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".