The phenotype‐driven computational analysis yields clinical diagnosis for patients with atypical manifestations of known intellectual disability syndromes

Abstract

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, and conclusions 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).

Keywords

• AP4M1
• dysmorphology
• EP300
• HPO
• intellectual disability patients
• KMT2A