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Finding Diagnostically Useful Patterns in Quantitative Phenotypic Data.

Published version
Peer-reviewed

Type

Article

Change log

Authors

Aitken, Stuart 
Firth, Helen V 
McRae, Jeremy 
Halachev, Mihail 
Kini, Usha 

Abstract

Trio-based whole-exome sequence (WES) data have established confident genetic diagnoses in ∼40% of previously undiagnosed individuals recruited to the Deciphering Developmental Disorders (DDD) study. Here we aim to use the breadth of phenotypic information recorded in DDD to augment diagnosis and disease variant discovery in probands. Median Euclidean distances (mEuD) were employed as a simple measure of similarity of quantitative phenotypic data within sets of ≥10 individuals with plausibly causative de novo mutations (DNM) in 28 different developmental disorder genes. 13/28 (46.4%) showed significant similarity for growth or developmental milestone metrics, 10/28 (35.7%) showed similarity in HPO term usage, and 12/28 (43%) showed no phenotypic similarity. Pairwise comparisons of individuals with high-impact inherited variants to the 32 individuals with causative DNM in ANKRD11 using only growth z-scores highlighted 5 likely causative inherited variants and two unrecognized DNM resulting in an 18% diagnostic uplift for this gene. Using an independent approach, naive Bayes classification of growth and developmental data produced reasonably discriminative models for the 24 DNM genes with sufficiently complete data. An unsupervised naive Bayes classification of 6,993 probands with WES data and sufficient phenotypic information defined 23 in silico syndromes (ISSs) and was used to test a "phenotype first" approach to the discovery of causative genotypes using WES variants strictly filtered on allele frequency, mutation consequence, and evidence of constraint in humans. This highlighted heterozygous de novo nonsynonymous variants in SPTBN2 as causative in three DDD probands.

Description

Keywords

developmental disease, genotype, naive Bayes, phenotype, tSNE, Bayes Theorem, Child, Developmental Disabilities, Dwarfism, Exome, Female, Gene Frequency, Genetic Predisposition to Disease, Heterozygote, Humans, Male, Mutation, Phenotype, Repressor Proteins, Spectrin, Exome Sequencing

Journal Title

Am J Hum Genet

Conference Name

Journal ISSN

0002-9297
1537-6605

Volume Title

105

Publisher

Elsevier BV
Sponsorship
Wellcome Trust (091310/Z/10/Z)