Effects of Source of DNA on Genotyping Success Rates and Allele Percentages in the Preschoolers with Attention-Deficit/Hyperactivity Disorder Treatment Study (PATS)
Bibliographic record
Abstract
OBJECTIVE: In children diagnosed with attention-deficit/hyperactivity disorder (ADHD) and their parents, who were participants of the Preschool ADHD Treatment Study (PATS), we assessed the effect of source of DNA (from buccal or blood cells) on the genotyping success rate and allele percentages for the five polymorphisms in three candidate genes (DAT1, DRD4, and SNAP 25) investigated in the PATS pharmacogenetic study of response to stimulant medication. METHOD: At baseline assessment, 241 individuals (113 probands and 128 parents) consented to participate; 144 individuals (52 probands and 92 parents) provided blood samples from venipuncture, and 97 individuals (61 probands and 36 parents) provided buccal samples from cheek swab as specimens for isolation of DNA. Three types of polymorphisms-variable number of tandem repeat (VNTR) polymorphism, tandem duplication polymorphism (TDP), and single nucleotide polymorphism (SNP)-were evaluated, including the DRD4 gene 48-bp VNTR in exon III, the DAT1 gene 40-bp VNTR in 3'-untranslated region, the DRD4 gene TDP 120-bp duplication in the promoter region, the SNAP-25 gene TC-1069 SNP, and the SNAP-25 gene TG-1065 SNP. Standard procedures were used to genotype individuals for each of these five polymorphisms. RESULTS: Using the methods available in 2004, the genotyping success rate was on the average much greater for DNA from blood cells than buccal cells (e.g., 91% vs. 54% in probands). For some polymorphisms (DRD4-VNTR, DRD4-TDP, and SNAP25-TC SNP), allele proportion also varied by blood versus buccal source of DNA (e.g., 26.5% vs. 18.6% for the 7-repeat allele of the DRD4 gene). CONCLUSIONS: The much lower success rate for genotyping based on DNA from buccal than blood cells is likely due to the quality of DNA derived from these two sources. The observed source differences in allele proportion may be due to self-selection related to choice of how specimens were collected (from cheek swab or venipuncture), or to a selective detection of some alleles based on differences in DNA quality.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".