The phenotype-driven computational analysis yields clinical diagnosis for patients with atypical manifestations of known intellectual disability syndromes.
Mol Genet Genomic Med
; 8(9): e1263, 2020 09.
Article
em En
| MEDLINE
| ID: mdl-32337850
ABSTRACT
BACKGROUND:
Due to extensive clinical and genetic heterogeneity of intellectual disability (ID) syndromes, the process of diagnosis is very challenging even for expert clinicians. Despite recent advancements in molecular diagnostics methodologies, a significant fraction of ID patients remains without a clinical diagnosis. METHODS, RESULTS, ANDCONCLUSIONS:
Here, in a prospective study on a cohort of 21 families (trios) with a child presenting with ID of unknown etiology, we executed phenotype-driven bioinformatic analysis method, PhenIX, utilizing targeted next-generation sequencing (NGS) data and Human Phenotype Ontology (HPO)-encoded phenotype data. This approach resulted in clinical diagnosis for eight individuals presenting with atypical manifestations of Rubinstein-Taybi syndrome 2 (MIM 613684), Spastic Paraplegia 50 (MIM 612936), Wiedemann-Steiner syndrome (MIM 605130), Cornelia de Lange syndrome 2 (MIM 300590), Cerebral creatine deficiency syndrome 1 (MIM 300352), Glass Syndrome (MIM 612313), Mental retardation, autosomal dominant 31 (MIM 616158), and Bosch-Boonstra-Schaaf optic atrophy syndrome (MIM 615722).Palavras-chave
Texto completo:
1
Bases de dados:
MEDLINE
Assunto principal:
Fenótipo
/
Deficiências do Desenvolvimento
/
Testes Genéticos
/
Diagnóstico por Computador
/
Deficiência Intelectual
Tipo de estudo:
Diagnostic_studies
/
Observational_studies
/
Prognostic_studies
/
Risk_factors_studies
Limite:
Adolescent
/
Child
/
Child, preschool
/
Female
/
Humans
/
Male
Idioma:
En
Revista:
Mol Genet Genomic Med
Ano de publicação:
2020
Tipo de documento:
Article
País de afiliação:
Polônia