A pooling‐based genomewide association study identifies genetic variants associated with <i>Staphylococcus aureus</i> colonization in chronic rhinosinusitis patients
Bibliographic record
Abstract
BACKGROUND: Staphylococcus aureus (S. aureus) has been implicated in the pathogenesis of chronic rhinosinusitis (CRS). However, host factors contributing to susceptibility to S. aureus colonization in CRS remain unknown. We wish to investigate, using a pooled genomewide association study (pGWAS), single-nucleotide polymorphisms (SNPs) associated with S. aureus carriage in CRS patients. METHODS: An existing population of 408 CRS patients and 190 controls was prospectively recruited for genetic association studies. All CRS patients had an endoscopic swab culture as part of phenotyping. A pGWAS compared DNA pools from patients with and without S. aureus colonization using the Illumina HumanHap 1M BeadChip, which interrogates 1 million SNPs. Top-ranked SNPs associated with S. aureus colonization were selected according to biallelic differences and silhouette rank, and confirmed by individual genotyping using the Sequenom platform. PLINK software was used for genetic association tests. Ingenuity pathway analysis was used to identify canonical and signaling pathways enriched for genes neighboring associated SNPs, as well as identification of the underlying biological mechanisms. RESULTS: Thirty-nine top priority SNPs were selected for individual genotyping. Out of 39 SNPs, 23 were associated (p < 0.05) with S. aureus colonization in CRS patients. These SNPs are located within or near 21 genes reported to be implicated in several diseases, endocytic internalization, and bacterial recognition. CONCLUSION: These results suggest novel host genetic factors influencing susceptibility to S. aureus colonization in CRS. Identifying implicated mechanisms may offer new insights into pathogenesis of CRS.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".