Targeted analysis of dyslexia-associated regions on chromosomes 6, 12 and 15 in large multigenerational cohorts
Notice bibliographique
Résumé
ABSTRACT Dyslexia is a common specific learning disability with a strong genetic basis that affects word reading and spelling. An increasing list of loci and genes have been implicated, but analyses to-date investigated only limited genomic variation within each locus with no confirmed pathogenic variants. In a collection of >2000 participants in families enrolled at three independent sites, we performed targeted capture and comprehensive sequencing of all exons and some regulatory elements of five candidate dyslexia risk genes ( DNAAF4 , CYP19A1 , DCDC2 , KIAA0319 and GRIN2B ) for which prior evidence of association exists from more than one sample. For each of six dyslexia-related phenotypes we used both individual-single nucleotide polymorphism (SNP) and aggregate testing of multiple SNPs to evaluate evidence for association. We detected no promoter alterations and few potentially deleterious variants in the coding exons, none of which showed evidence of association with any phenotype. All genes except DNAAF4 provided evidence of association, corrected for the number of genes, for multiple non-coding variants with one or more phenotypes. Results for a variant in the downstream region of CYP19A1 and a haplotype in DCDC2 yielded particularly strong statistical significance for association. This haplotype and another in DCDC2 affected performance of real word reading in opposite directions. In KIAA0319 , two missense variants annotated as tolerated/benign associated with poor performance on spelling. Ten non-coding SNPs likely affect transcription factor binding. Findings were similar regardless of whether phenotypes were adjusted for verbal IQ. Our findings from this large-scale sequencing study complement those from genome-wide association studies (GWAS), argue strongly against the causative involvement of large-effect coding variants in these five candidate genes, support an oligogenic etiology, and suggest a role of transcriptional regulation. Author Summary Family studies show that genes play a role in dyslexia and a small number of genomic regions have been implicated to date. However, it has proven difficult to identify the specific genetic variants in those regions that affect reading ability by using indirect measures of association with evenly spaced polymorphisms chosen without regard to likely function. Here, we use recent advances in DNA sequencing to examine more comprehensively the role of genetic variants in five previously nominated candidate dyslexia risk genes on several dyslexia-related traits. Our analysis of more than 2000 participants in families with dyslexia provides strong evidence for a contribution to dyslexia risk for the non-protein coding genetic variant rs9930506 in the CYP19A1 gene on chromosome 15 and excludes the DNAAF4 gene on the same chromosome. We identified other putative causal variants in genes DCDC2 and KIAA0319 on chromosome 6 and GRIN2B on chromosome 12. Further studies of these DNA variants, all of which were non-coding, may point to new biological pathways that affect susceptibility to dyslexia. These findings are important because they implicate regulatory variation in this complex trait that affects ability of individuals to effectively participate in our increasingly informatic world.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».