Molecular Analysis of Factor VIII and Factor IX Genes in Hemophilia Patients: Identification of Novel Mutations and Molecular Dynamics Studies
Bibliographic record
Abstract
BACKGROUND: Hemophilias A and B are X-linked bleeding disorders caused by mutations in the factor VIII and factor IX genes, respectively. Our objective was to identify the spectrum of mutations of the factor VIII and factor IX genes in Saudi Arabian population and determine the genotype and phenotype correlations by molecular dynamics (MD) simulation. METHODS: For genotyping, blood samples from Saudi Arabian patients were collected, and the genomic DNA was amplified, and then sequenced by Sanger method. For molecular simulations, we have used softwares such as CHARMM (Chemistry at Harvard Macromolecular Mechanics; http://www.charmm-gui.org) and GROMACS. In addition, the secondary structure was determined based on the solvent accessibility for the confirmation of the protein stability at the site of mutation. RESULTS: Six mutations (three novel and three known) were identified in factor VIII gene, and six mutations (one novel and five known) were identified in factor IX gene. The factor VIII novel mutations identified were c.99G>T, p. (W33C) in exon 1, c.2138 DelA, p. (N713Tfs*9) in eon14, also a novel mutation at splicing acceptor site of exon 23 c.6430 - 1G>A. In factor IX, we found a novel mutation c.855G>C, p. (E285D) in exon 8. These novel mutations were not reported in any factor VIII or factor IX databases previously. The deleterious effects of these novel mutations were confirmed by PolyPhen2 and SIFT programs. CONCLUSION: The protein functional and structural studies and the models built in this work would be appropriate for predicting the effects of deleterious amino acid substitutions causing these genetic disorders. These findings are useful for genetic counseling in the case of consanguineous marriages which is more common in the Saudi Arabia.
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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 | 0.000 |
| 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) | 0.001 | 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".