Literature DB >> 31144778

Assessment of patient clinical descriptions and pathogenic variants from gene panel sequences in the CAGI-5 intellectual disability challenge.

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.
© 2019 Wiley Periodicals, Inc.

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


  39 in total

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Authors:  Elena Nabieva; Kam Jim; Amit Agarwal; Bernard Chazelle; Mona Singh
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2.  XLID-causing mutations and associated genes challenged in light of data from large-scale human exome sequencing.

Authors:  Amélie Piton; Claire Redin; Jean-Louis Mandel
Journal:  Am J Hum Genet       Date:  2013-07-18       Impact factor: 11.025

3.  REVEL: An Ensemble Method for Predicting the Pathogenicity of Rare Missense Variants.

Authors:  Nilah M Ioannidis; Joseph H Rothstein; Vikas Pejaver; Sumit Middha; Shannon K McDonnell; Saurabh Baheti; Anthony Musolf; Qing Li; Emily Holzinger; Danielle Karyadi; Lisa A Cannon-Albright; Craig C Teerlink; Janet L Stanford; William B Isaacs; Jianfeng Xu; Kathleen A Cooney; Ethan M Lange; Johanna Schleutker; John D Carpten; Isaac J Powell; Olivier Cussenot; Geraldine Cancel-Tassin; Graham G Giles; Robert J MacInnis; Christiane Maier; Chih-Lin Hsieh; Fredrik Wiklund; William J Catalona; William D Foulkes; Diptasri Mandal; Rosalind A Eeles; Zsofia Kote-Jarai; Carlos D Bustamante; Daniel J Schaid; Trevor Hastie; Elaine A Ostrander; Joan E Bailey-Wilson; Predrag Radivojac; Stephen N Thibodeau; Alice S Whittemore; Weiva Sieh
Journal:  Am J Hum Genet       Date:  2016-09-22       Impact factor: 11.025

4.  Characterization of intellectual disability and autism comorbidity through gene panel sequencing.

Authors:  Maria C Aspromonte; Mariagrazia Bellini; Alessandra Gasparini; Marco Carraro; Elisa Bettella; Roberta Polli; Federica Cesca; Stefania Bigoni; Stefania Boni; Ombretta Carlet; Susanna Negrin; Isabella Mammi; Donatella Milani; Angela Peron; Stefano Sartori; Irene Toldo; Fiorenza Soli; Licia Turolla; Franco Stanzial; Francesco Benedicenti; Cristina Marino-Buslje; Silvio C E Tosatto; Alessandra Murgia; Emanuela Leonardi
Journal:  Hum Mutat       Date:  2019-08-02       Impact factor: 4.878

Review 5.  Epilepsy and intellectual disability.

Authors:  C Bowley; M Kerr
Journal:  J Intellect Disabil Res       Date:  2000-10

6.  ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data.

Authors:  Kai Wang; Mingyao Li; Hakon Hakonarson
Journal:  Nucleic Acids Res       Date:  2010-07-03       Impact factor: 16.971

7.  Human Gene Mutation Database (HGMD): 2003 update.

Authors:  Peter D Stenson; Edward V Ball; Matthew Mort; Andrew D Phillips; Jacqueline A Shiel; Nick S T Thomas; Shaun Abeysinghe; Michael Krawczak; David N Cooper
Journal:  Hum Mutat       Date:  2003-06       Impact factor: 4.878

8.  An integrated approach to inferring gene-disease associations in humans.

Authors:  Predrag Radivojac; Kang Peng; Wyatt T Clark; Brandon J Peters; Amrita Mohan; Sean M Boyle; Sean D Mooney
Journal:  Proteins       Date:  2008-08-15

9.  RNA splicing. The human splicing code reveals new insights into the genetic determinants of disease.

Authors:  Hui Y Xiong; Babak Alipanahi; Leo J Lee; Hannes Bretschneider; Daniele Merico; Ryan K C Yuen; Yimin Hua; Serge Gueroussov; Hamed S Najafabadi; Timothy R Hughes; Quaid Morris; Yoseph Barash; Adrian R Krainer; Nebojsa Jojic; Stephen W Scherer; Benjamin J Blencowe; Brendan J Frey
Journal:  Science       Date:  2014-12-18       Impact factor: 47.728

10.  ClinVar: public archive of relationships among sequence variation and human phenotype.

Authors:  Melissa J Landrum; Jennifer M Lee; George R Riley; Wonhee Jang; Wendy S Rubinstein; Deanna M Church; Donna R Maglott
Journal:  Nucleic Acids Res       Date:  2013-11-14       Impact factor: 16.971

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  3 in total

1.  Novel loss-of-function variants in TRIO are associated with neurodevelopmental disorder: case report.

Authors:  Laura Schultz-Rogers; Karthik Muthusamy; Filippo Pinto E Vairo; Eric W Klee; Brendan Lanpher
Journal:  BMC Med Genet       Date:  2020-11-10       Impact factor: 2.103

Review 2.  Genome interpretation using in silico predictors of variant impact.

Authors:  Panagiotis Katsonis; Kevin Wilhelm; Amanda Williams; Olivier Lichtarge
Journal:  Hum Genet       Date:  2022-04-30       Impact factor: 5.881

3.  Case Report: Identification of a novel CASK missense variant in a Chinese family with MICPCH.

Authors:  Runfeng Zhang; Peng Jia; Yanyi Yao; Feng Zhu
Journal:  Front Genet       Date:  2022-08-25       Impact factor: 4.772

  3 in total

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