Polymorphisms in RYBP and AOAH Genes Are Associated with Chronic Rhinosinusitis in a Chinese Population: A Replication Study
Bibliographic record
Abstract
BACKGROUND: The development of CRS is believed to be the result of combined interactions between the genetic background of the affected subject and environmental factors. OBJECTIVES: To replicate and extend our recent findings from genetic association studies in chronic rhinosinusitis (CRS) performed in a Canadian Caucasian population in a Chinese population. METHODS: In a case-control replication study, DNA samples were obtained from CRS with (n = 306; CRSwNP) and without (n = 332; CRSsNP) nasal polyps, and controls (n = 315) in a Chinese population. A total of forty-nine single nucleotide polymorphisms (SNPs) selected from previous identified SNPs associated with CRS in Canadian population, and SNPs from the CHB HapMap dataset were individually genotyped. RESULTS: We identified two SNPs respectively in RYBP (rs4532099, p = 2.15E-06, OR = 2.59) and AOAH (rs4504543, p = 0.0001152, OR = 0.58) significantly associated with whole CRS cohort. Subgroup analysis for the presence of nasal polyps (CRSwNP and CRSsNP) displayed significant association in CRSwNP cohorts regarding to one SNP in RYBP (P = 3.24(E)-006, OR = 2.76). Evidence of association in the CRSsNP groups in terms of 2 SNPs (AOAH_rs4504543 and RYBP_rs4532099) was detected as well. Stratifying analysis by gender demonstrated that none of the selected SNPs were associated with CRSwNP as well as CRSsNP. Meanwhile 3 SNPs (IL1A_rs17561, P = 0.005778; IL1A_rs1800587, P = 0.009561; IRAK4_rs4251513, P = 0.03837) were associated with serum total IgE level. CONCLUSIONS: These genes are biologically plausible, with roles in regulation of transcription (RYBP) and inflammatory response (AOAH). The present data suggests the potential common genetic basis in the development of CRS in Chinese and Caucasian population.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".