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Assessment of patient clinical descriptions and pathogenic variants from gene panel sequences in the CAGI‐5 intellectual disability challenge
Author(s) -
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
Publication year - 2019
Publication title -
human mutation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.981
H-Index - 162
eISSN - 1098-1004
pISSN - 1059-7794
DOI - 10.1002/humu.23823
Subject(s) - university hospital , library science , medicine , family medicine , computer science
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.