| Literature DB >> 31144778 |
Marco Carraro1, Alexander Miguel Monzon1, Luigi Chiricosta1, Francesco Reggiani1,2, Maria Cristina Aspromonte3, Mariagrazia Bellini3,4, Kymberleigh Pagel5, Yuxiang Jiang5, Predrag Radivojac5, Kunal Kundu6,7, Lipika R Pal6, Yizhou Yin6,7, Ivan Limongelli8, Gaia Andreoletti6,9, John Moult6,9, Stephen J Wilson10, Panagiotis Katsonis10, Olivier Lichtarge10, Jingqi Chen11, Yaqiong Wang11, Zhiqiang Hu11, Steven E Brenner11, Carlo Ferrari2, Alessandra Murgia3,4, Silvio C E Tosatto1,12, Emanuela Leonardi3,4.
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.Entities:
Keywords: community challenge; critical assessment; genetic testing; phenotype prediction; variant interpretation
Mesh:
Year: 2019 PMID: 31144778 PMCID: PMC7341177 DOI: 10.1002/humu.23823
Source DB: PubMed Journal: Hum Mutat ISSN: 1059-7794 Impact factor: 4.878