Implication of myddosome complex genetic variants in outcome severity of COVID-19 patients
Bibliographic record
Abstract
BACKGROUND/PURPOSE(S): During a viral infection, the immune response is mediated by the toll-like receptors and myeloid differentiation Factor 88 (MyD88) that play an important role sensing infections such as SARS-CoV-2 which has claimed the lives of more than 6.8 million people around the world. METHODS: We carried out a cross-sectional with a population of 618 SARS-CoV-2-positive unvaccinated subjects and further classified based on severity: 22% were mild, 34% were severe, 26% were critical, and 18% were deceased. Toll Like Receptor 7 (TLR7) single-nucleotide polymorphisms (rs3853839, rs179008, rs179009, and rs2302267) and MyD88 (rs7744) were genotyped using TaqMan OpenArray. The association of polymorphisms with disease outcomes was performed by logistic regression analysis adjusted by covariates. RESULTS: A significant association of rs3853839 and rs7744 of the TLR7 and MyD88 genes, respectively, was found with COVID-19 severity. The G/G genotype of the rs3853839 TLR7 was associated with the critical outcome showing an Odd Ratio = 1.98 (95% IC = 1.04-3.77). The results highlighted an association of the G allele of MyD88 gene with severe, critical and deceased outcomes. Furthermore, in the dominant model (AG + GG vs. AA), we observed an Odd Ratio = 1.70 (95% CI = 1.02-2.86) with severe, Odd Ratio = 1.82 (95% CI = 1.04-3.21) with critical, and Odd Ratio = 2.44 (95% CI = 1.21-4.9) with deceased outcomes. CONCLUSION: To our knowledge this work represents an innovative report that highlights the significant association of TLR7 and MyD88 gene polymorphisms with COVID-19 outcomes and the possible implication of the MyD88 variant with D-dimer and IFN-α concentrations.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".