Assessment of patient clinical descriptions and pathogenic variants from gene panel sequences in the CAGI‐5 intellectual disability challenge. Issue 9 (3rd July 2019)

• Record Type: Journal Article
• Authors: Carraro, Marco; Monzon, Alexander Miguel; Chiricosta, Luigi; Reggiani, Francesco; Aspromonte, Maria Cristina; Bellini, Mariagrazia; Pagel, Kymberleigh; Jiang, Yuxiang; Radivojac, Predrag; Kundu, Kunal; Pal, Lipika R.; Yin, Yizhou; Limongelli, Ivan; Andreoletti, Gaia; Moult, John; Wilson, Stephen J.; Katsonis, Panagiotis; Lichtarge, Olivier; Chen, Jingqi; Wang, Yaqiong; Hu, Zhiqiang; Brenner, Steven E.; Ferrari, Carlo; Murgia, Alessandra; Tosatto, Silvio C.E.; Leonardi, Emanuela
• Editors: Moult, John; Brenner, Steven E.
• Other Names: Karchin Rachel guestEditor.; Pal Lipika R. specialEditor.
• Is Part Of: Human mutation. Volume 40:Issue 9(2019)
• Page Start: 1330
• Page End: 1345
• Publication Date: 2019-07-03
• Subjects: community challenge -- critical assessment -- genetic testing -- phenotype prediction -- variant interpretation; Human chromosome abnormalities -- Periodicals; Mutation (Biology) -- Periodicals; 616.04205
• DOI: 10.1002/humu.23823
• Languages: English
• ISSNs: 1059-7794

Abstract

Abstract: The Critical Assessment of Genome Interpretation‐5 intellectual disability challenge asked to use computational methods to predict patient clinical phenotypes and the causal variant(s) based on an analysis of their gene panel sequence data. Sequence data for 74 genes associated with intellectual disability (ID) and/or autism spectrum disorders (ASD) from a cohort of 150 patients with a range of neurodevelopmental manifestations (i.e. ID, autism, epilepsy, microcephaly, macrocephaly, hypotonia, ataxia) have been made available for this challenge. For each patient, predictors had to report the causative variants and which of the seven phenotypes were present. Since neurodevelopmental disorders are characterized by strong comorbidity, tested individuals often present more than one pathological condition. Considering the overall clinical manifestation of each patient, the correct phenotype has been predicted by at least one group for 93 individuals (62%). ID and ASD were the best predicted among the seven phenotypic traits. Also, causative or potentially pathogenic variants were predicted correctly by at least one group. However, the prediction of the correct causative variant seems to be insufficient to predict the correct phenotype. In some cases, the correct prediction has been supported by rare or common variants in genes different from the causative one.