Amylase Alpha 1 Gene (<b><i>AMY1</i></b>) Copy Number Variation and Dental Caries Experience: A Pilot Study among Adults in Lithuania
Bibliographic record
Abstract
INTRODUCTION: Genetic biomarkers have the potential to be used in personalised dentistry for improved prevention and decision-making in caries management. The amylase alpha 1 gene (AMY1) encodes salivary α-amylase and may be one such biomarker. We examined the association between AMY1 copy number variation (CNV) and dental caries experience in adults. MATERIALS AND METHODS: A stratified random sample of 193 participants from the Lithuanian National Oral Health Survey (LNOHS) agreed to provide saliva samples and were included in this analysis (age 35-44 years; participation rate 43%). Information on socio-demographic and behavioural characteristics was taken from the LNHOS, which used the self-administered World Health Organisation (WHO) questionnaire. Data on fluoride levels in drinking water at the recruitment areas was recorded based on information provided by water suppliers. Dental caries experience was recorded at a surface level (smooth-surface and occlusal-surface decayed, missing, filled surfaces [D3MFS] score) by one trained and calibrated examiner using WHO criteria, and subsequently dichotomised for the statistical analyses. DNA extracted from saliva samples was used to investigate AMY1 CNV using the QX200 droplet digital PCR system. Bivariate and multivariable statistical analyses were employed. RESULTS: When compared to participants with an AMY1 copy number (CN) of 2-3, higher odds of smooth-surface D3MFS >14 was observed for participants with a CN of 4-5 (OR 13.3, 95% CI 2.1-86.3), 6-9 (OR 7.0, 95% CI 1.4-34.1), and 10-16 (OR 5.8, 95% CI 1.2-32.2). Female sex was independently associated with a smooth-surface D3MFS >14 (OR 5.7, 95% CI 1.9-17.2). CONCLUSIONS: Our study demonstrated an association between AMY1 CNV and high smooth-surface caries experience. Studies with larger sample sizes are needed to validate this association.
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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 | 0.000 | 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".