Study of KIAA0319, DYXIC1 and DCDC2 Gene Polymorphisms in Children with Dyslexia in Indian Population
Bibliographic record
Abstract
Background:Dyslexia is a typical learning disability that does not affect intelligence but causes problems with reading, writing, and spelling. It is influenced by certain genes, due to which several researchers have attempted to identify the susceptible gene. Dyslexia is incurable and diagnosis is difficult because it always overlaps with other learning disabilities. Hence, timely assessment and intervention consequently give the best results. Therefore, our aim was to find the relation between dyslexia and single nucleotide polymorphisms (SNPs) in several candidate genes like DYX1C1, KIAA0319, and DCDC2 in Indian population. Methods:In the present study, 103 individuals with dyslexia and 100 controls in the age group between 6 to 15 years were taken. Thirteen SNPs in the KIAA gene, seven SNPs of DCDC2, and three SNPs of the DYX1C1 gene were analysed by the Mass Array technique. Results:The association of dyslexia with SNPs rs3756821, rs6935076, rs4576240 of the KIAA gene was found significant. A significant association was found with rs600753 of the DYX1C1 gene and dyslexia and we could not find any association of the DCDC2 gene with dyslexia. Conclusions:Prerequisite genetic analysis is necessary for the diagnosis of dyslexia as it is a crucial educational barrier. Treatment is known to be most effective if dyslexia is identified in the early stages for effective intervention for children before they experience prolonged reading failure. Further, it helps in prenatal diagnosis for early intervention.
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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 | 0.001 | 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 | 0.001 |
| 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".