Phenotypic analysis of 11,125 trio exomes in neurodevelopmental disorders DOI Creative Commons
Shiva Ganesan, Sarah M. Ruggiero, Shridhar Parthasarathy

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2025, Volume and Issue: unknown

Published: March 12, 2025

Genomic sequencing is widely used to identify causative genetic changes in neurodevelopmental disorders, such as autism, intellectual disability, and epilepsy. Most disorders also present with diverse clinical features, delineating the interaction between phenotypic features a key prerequisite for developing personalized therapies. However, assessing at scale that parallels genomic remains challenging. Here, we standardize information across 11,125 patient-parent trios exome data using biomedical ontologies, analyzing 674,767 terms. We find individuals de novo variants 69 out of 261 genes exhibit statistically significant similarities distinct fingerprints. observe relatedness follows gradient, spanning from highly similar dissimilar phenotypes, intra-gene suggesting clinically subgroups seven genes. For most etiologies, only small subset phenotypically carried same gene, highlighting heterogeneous complex landscape disorders. Our study provides large-scale overview dynamic relationship genotypes phenotypes underscoring how inherent complexity these conditions can be deciphered through approaches integrate data.

Language: Английский

Phenotypic analysis of 11,125 trio exomes in neurodevelopmental disorders DOI Creative Commons
Shiva Ganesan, Sarah M. Ruggiero, Shridhar Parthasarathy

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2025, Volume and Issue: unknown

Published: March 12, 2025

Genomic sequencing is widely used to identify causative genetic changes in neurodevelopmental disorders, such as autism, intellectual disability, and epilepsy. Most disorders also present with diverse clinical features, delineating the interaction between phenotypic features a key prerequisite for developing personalized therapies. However, assessing at scale that parallels genomic remains challenging. Here, we standardize information across 11,125 patient-parent trios exome data using biomedical ontologies, analyzing 674,767 terms. We find individuals de novo variants 69 out of 261 genes exhibit statistically significant similarities distinct fingerprints. observe relatedness follows gradient, spanning from highly similar dissimilar phenotypes, intra-gene suggesting clinically subgroups seven genes. For most etiologies, only small subset phenotypically carried same gene, highlighting heterogeneous complex landscape disorders. Our study provides large-scale overview dynamic relationship genotypes phenotypes underscoring how inherent complexity these conditions can be deciphered through approaches integrate data.

Language: Английский

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