Genomic and Structural Investigation of Mutations in Biotinidase (BTD) Gene Deficiency in Greater Middle Eastern Cohort: Insights from Molecular Dynamics Study
Bibliographic record
Abstract
Background: Biotinidase deficiency (BD) is a common autosomal recessive metabolic disorder in Qatar and the Arab world. It is treatable if detected early, making it essential to understand the genetic variants involved. This study aimed to investigate the carrier frequency of BD-related variants in a healthy Qatari population, reflecting the genetic landscape of the broader Middle Eastern region; classify them using bioinformatics tools; and compare findings with global datasets. Methods: Whole-genome sequencing data from 14,669 participants in the Qatar Genome Program (QGP), a multiethnic cohort including Qatari nationals and long-term residents (≥15 years), were analyzed to identify BTD variants. A total of 723, including 653 single-nucleotide polymorphisms (SNPs) and 70 structural variants (SVs) in BTD associated with BD, were screened against the Qatari cohort and compared with international data. In silico tools were used to assess variant pathogenicity, conservation, and protein stability. Molecular dynamics (MD) simulations were performed to evaluate structural and functional changes in the BTD. Results: A total of 80 SNPs and 3 SVs were identified, among which 21 variants (19 SNPs and 2 SVs) were classified as pathogenic or likely pathogenic, according to ClinVar. The carrier frequency of BTD-related variants in Qatar was 1:20, primarily driven by rs13078881 (D444H). Molecular dynamics (MD) simulations revealed significant conformational changes with H323R, D444H, and P497S, which demonstrated increased flexibility (higher RMSD/RMSF and PCA trace values). Additionally, R209C and D444H showed reduced compactness (higher Rg) and distinct energy minima, suggesting altered conformational states. Conclusions: This study demonstrates a high carrier frequency of pathogenic BTD variants in the Qatari population, underscoring the need to integrate these SNPs and SVs into the national genomic neonatal screening program (gNBS) for enhanced early detection and treatment strategies. The mild structural deviations observed in the D444H mutant through MD simulations may explain its association with milder clinical phenotypes of BTD, offering valuable insights for personalized therapeutic approaches.
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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) | 0.000 | 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) | 0.000 | 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".