Faculty Collaboration Database

CAGI SickKids challenges: Assessment of phenotype and variant predictions derived from clinical and genomic data of children with undiagnosed diseases. Hum Mutat 2019 Sep;40(9):1373-1391

Date

07/20/2019

Pubmed ID

31322791

Pubmed Central ID

PMC7318886

DOI

10.1002/humu.23874

Scopus ID

2-s2.0-85070509840 (requires institutional sign-in at Scopus site)   7 Citations

Abstract

Whole-genome sequencing (WGS) holds great potential as a diagnostic test. However, the majority of patients currently undergoing WGS lack a molecular diagnosis, largely due to the vast number of undiscovered disease genes and our inability to assess the pathogenicity of most genomic variants. The CAGI SickKids challenges attempted to address this knowledge gap by assessing state-of-the-art methods for clinical phenotype prediction from genomes. CAGI4 and CAGI5 participants were provided with WGS data and clinical descriptions of 25 and 24 undiagnosed patients from the SickKids Genome Clinic Project, respectively. Predictors were asked to identify primary and secondary causal variants. In addition, for CAGI5, groups had to match each genome to one of three disorder categories (neurologic, ophthalmologic, and connective), and separately to each patient. The performance of matching genomes to categories was no better than random but two groups performed significantly better than chance in matching genomes to patients. Two of the ten variants proposed by two groups in CAGI4 were deemed to be diagnostic, and several proposed pathogenic variants in CAGI5 are good candidates for phenotype expansion. We discuss implications for improving in silico assessment of genomic variants and identifying new disease genes.

Author List

Kasak L, Hunter JM, Udani R, Bakolitsa C, Hu Z, Adhikari AN, Babbi G, Casadio R, Gough J, Guerrero RF, Jiang Y, Joseph T, Katsonis P, Kotte S, Kundu K, Lichtarge O, Martelli PL, Mooney SD, Moult J, Pal LR, Poitras J, Radivojac P, Rao A, Sivadasan N, Sunderam U, Saipradeep VG, Yin Y, Zaucha J, Brenner SE, Meyn MS

MESH terms used to index this publication - Major topics in bold

Adolescent
Child
Child, Preschool
Computational Biology
Computer Simulation
Databases, Genetic
Female
Genetic Predisposition to Disease
Genetic Variation
Humans
Male
Phenotype
Whole Genome Sequencing