Association between interleukin-6-174G/C gene polymorphism and asthma severity: exploring the role of total serum IgE, blood eosinophils, and FeNO as markers of type 2 inflammation
Bibliographic record
Abstract
BACKGROUND: While a connection has been established between serum interleukin-6 (IL-6) levels and the IL-6 gene (- 174G/C) polymorphism in allergic diseases such as asthma, its specific association with severe asthma remains unexplored. This study examined the relationship between the IL-6 (- 174G/C) gene polymorphism and mild and severe asthma, focusing on its influence on type 2 inflammation. METHODS: Our study comprised 98 patients with mild asthma and 116 with severe asthma. Additionally, we recruited 121 healthy participants to serve as controls for comparative analyses. The IL-6 gene (- 174G/C) polymorphism was assessed utilizing the polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method. RESULTS: In our study, the risk of mild asthma exhibited a significant fourfold increase in individuals with the GG genotype pattern compared to healthy controls, yielding an odds ratio (OR) of 4.4 (p < 0.001). Conversely, we found no significant correlation between the IL-6 - 174G/C gene polymorphism and severe asthma when compared to the healthy control group. However, a noteworthy pattern emerged when we compared subgroups of mild and severe asthma. The risk of severe asthma increased fivefold in individuals with the GC polymorphism pattern, with an OR of 4.99 (p < 0.001), while the likelihood of mild asthma showed a similar fourfold increase with the GG polymorphism pattern, OR = 4.4 (p < 0.001). Consequently, we observed a significantly higher frequency of the C allele in patients with severe asthma, whereas the G allele was more prevalent in individuals with mild asthma (p = 0.05). Additionally, the correlation between markers of type 2 inflammation and the dominant model of the IL-6 gene -174G/C polymorphism (CC + CG vs GG) revealed a significant increase in total serum immunoglobulin E (IgE), Blood Eosinophil Counts (BEC), and Fractional Exhaled Nitric Oxide (FeNO) levels in asthmatic patients with the CC + CG gene pattern compared to those with GG, with p-values of 0.04, 0.03, and 0.04, respectively. Furthermore, after adjusting for other risk factors, the likelihood of developing severe asthma increased from fourfold to eightfold, with an OR of 8.12 (p = 0.01) with (CC + CG) gene pattern. Other predictors for severe asthma included older age and childhood-onset disease (OR = 1.13 and 19.19, p < 0.001). Allergic rhinitis (AR) and nasal polyps (NP) also demonstrated a substantial association with an increased risk of severe asthma, with odds ratios of 5 and 32.29 (p = 0.01 and < 0.001), respectively. Additionally, elevated Body Mass Index (BMI), BEC, and FeNO were linked to severe asthma, with ORs of 1.11, 1.00, and 1.04, respectively (p = 0.04, 0.05, and 0.001). CONCLUSION: This study illuminated the intricate relationship between the IL-6 gene polymorphism, type 2 inflammation markers, and diverse risk factors in shaping asthma severity. As a significant association between the GG polymorphism of the IL-6 gene (- 174G/C) and mild asthma was found, while possessing at least one C allele, whether in a homozygous (CC) or heterozygous (CG) combination, independently predicts the likelihood of severe asthma.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".