Assessment of CYP2C9, CYP2C19, and CYP2D6 Polymorphisms in Allergic Patients with Chemical Sensitivity
Bibliographic record
Abstract
BACKGROUND: Self-reported chemical sensitivity (SCS) is characterized by adverse effects due to exposure to low levels of chemical substances. The clinical manifestations of SCS are similar to the allergy, and a high percentage of individuals with both diseases have been found. Various genes, especially genes of importance to the metabolism of xenobiotic compounds, have been associated with SCS. OBJECTIVES: The purpose of this study was to investigate whether allergic individuals with chemical sensitivity differed from allergic patients without chemical sensitivity with regard to the distribution of genotype and phenotype of CYP2C9, CYP2C19, and CYP2D6 polymorphisms. METHODS: A total of 180 patients were enrolled for this study. A questionnaire was employed to collect information on individual chemical sensitivity, while the Skin prick test and the PATCH test were used to verify the presence of an allergic condition against inhalants or contact allergens, respectively. For the evaluation of the CYP2C9, CYP2C19, and CYP2D6 polymorphisms, we used a strategy based on the amplification of the entire gene coupled to direct genomic DNA sequencing analysis. RESULTS: Overall, a total of 15 different CYP2C9, CYP2C19, and CYP2D6 haplotypes were identified in our population. If the 5 CYP2C9 and the 2 CYP2C19 identified alleles correspond to the previously described ones, 4 of the 8 CYP2D6 haplotypes, detected in the study group, present new SNPs combinations. These new suballeles were categorized as CYP2D6*2M Sa-lento Variant 1, CYP2D6*35B Salento Variant 2, CYP2D6*41 Salento Variant 3, and CYP2D6*4P Salento Variant 4 due to the presence of the key SNPs 2,850 C>T, 31G>A, 2,988 G>A, and 1,846 G>A, respectively. When the allergic individuals are divided into 2 groups according to their SCS score, we observed that the distribution of the CYP2D6 phenotypes was significantly different between the 2 groups. CONCLUSIONS: Our idea is that the application of the questionnaire that we have adopted has enabled us to diagnose a degree of chemical sensitivity, which results as comorbid of the allergic disease and in which a condition of poor or intermediate metabolizes for the detrimental CYP2D6 alleles, could represent a discriminant between the chemical sensitivity and the health state.
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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) | 0.001 | 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) | 0.002 | 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".