Development and validation of the high-quality ‘rapid method for swab’ to genotype the HTTLPR serotonin transporter (SLC6A4) promoter polymorphism
Bibliographic record
Abstract
BACKGROUND: The importance of genetic variation to the etiology of neuropsychiatric disorders is well established and is currently being examined for diagnosis and treatment. The most popular method of obtaining material for genotype analysis, high-yielding DNA extraction from blood, has several limitations, including invasiveness, need for skilled individuals to collect material, and requirement for cold storage. Saliva sampling is noninvasive and trained personnel are less necessary, but it still requires a relatively high level of subject compliance. Buccal mucosa cells sampling is almost completely noninvasive, reducing compliance issues significantly. Samples collected have been shown to produce usable DNA after shipment through conventional mail. The DNA produced by rapid elution of these swabs in chaotropic buffers is, however, of limited quality and low purity. OBJECTIVE: Our aim was to develop a rapid, economical, and environmentally safe method for extraction of high-quality genomic DNA, which can be used to determine clinically important genotypes from trace quantity samples and which has sufficient yield for multiple assays. METHODS: We developed a method of extracting high-quality genomic DNA from buccal swab, which we termed the 'rapid method for swab' (RMS). We compared RMS with two established procedures, specifically the original rapid method and the commercially available Buccal Amp method. We assessed the generated genomic DNAs by their (i) quality, (ii) quantity, (iii) restriction enzyme digestibility, and (iv) PCR-based genotyping in addition to time, cost, and environmental impact of the procedures. MAIN RESULTS: DNA generated by RMS was of higher purity than that by Buccal Amp. RMS is nonenzymatic and does not use strong chaotropic salts or extreme pH. We also showed the suitability of RMS-DNA for LA/LG genotyping as generated by PCR using 7-deaza-dGTP. CONCLUSION: The RMS procedure is novel, efficient, safe, and yields sufficient material for multiple genotyping analyses. The RMS produces DNA of high quality from a single human buccal swab. RMS is a noninvasive technique and particularly suitable for children and older individuals and in field collection settings.
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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 | 0.010 | 0.013 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".