Prevalence of methylenetetrahydrofolate reductase gene polymorphisms (C677T, and A1298C) among Saudi children receiving dental treatment
Bibliographic record
Abstract
BACKGROUND: Methylenetetrahydrofolate reductase, the encoded by the MTHFR gene, plays a crucial role in converting the amino acid homocysteine to methionine. Two polymorphisms of the MTHFR gene, C677T and A1298C, reportedly reduce enzyme activity, resulting in hyperhomocysteinemia. Patients with C677T and A1298C polymorphisms may be at higher risk for developing abnormal hyperhomocysteinemia, which has been linked to catastrophic neurological including fatal outcomes. OBJECTIVE: Determine the prevalence of the MTHFR gene variants C677T and A1298C among pediatric dental patients treated at King Abdulaziz University Hospital. DESIGN: Cross-sectional. SETTING: Clinics of pediatric dentistry department. SUBJECTS AND METHODS: Healthy Saudi children 6–12 years old with no known allergies were screened for eligibility between May and December 2019. A single investigator collected saliva samples. The MTHFR C677T and A1298C polymorphisms were analyzed using polymerase chain reaction and restriction fragment length polymorphism. MAIN OUTCOME MEASURE: The prevalence of MTHFR gene variants (C677T and A1298C) among the subjects. SAMPLE SIZE: 138. RESULTS: MTHFR C677T polymorphism was present in 36.2% of the sample and 90.0% of children carrying this allele were heterozygotes. MTHFR A1298C polymorphism was present in 91.3% of the sample and 77.0% of the children carrying this allele were heterozygotes. No linkage disequilibrium between MTHFR C677T and MTHFR A1298C was observed within this sample. CONCLUSIONS: Our study found a high frequency of the MTHFR A1298C genotype, which was substantially more abundant than expected based on a Hardy-Weinberg distribution. Therefore, caution is advised in using N 2 O in Saudi children as the increased prevalence of this MTHFR allele may increase the incidence of serious adverse effects among these children. LIMITATIONS: Further studies are recommended with a larger sample size from randomly selected hospitals from different regions of Saudi Arabia. CONFLICT OF INTEREST: None.
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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) | 0.000 | 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) | 0.002 | 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".