Literature DB >> 22830651

Identifying disease mutations in genomic medicine settings: current challenges and how to accelerate progress.

Gholson J Lyon1, Kai Wang2.   

Abstract

The pace of exome and genome sequencing is accelerating, with the identification of many new disease-causing mutations in research settings, and it is likely that whole exome or genome sequencing could have a major impact in the clinical arena in the relatively near future. However, the human genomics community is currently facing several challenges, including phenotyping, sample collection, sequencing strategies, bioinformatics analysis, biological validation of variant function, clinical interpretation and validity of variant data, and delivery of genomic information to various constituents. Here we review these challenges and summarize the bottlenecks for the clinical application of exome and genome sequencing, and we discuss ways for moving the field forward. In particular, we urge the need for clinical-grade sample collection, high-quality sequencing data acquisition, digitalized phenotyping, rigorous generation of variant calls, and comprehensive functional annotation of variants. Additionally, we suggest that a 'networking of science' model that encourages much more collaboration and online sharing of medical history, genomic data and biological knowledge, including among research participants and consumers/patients, will help establish causation and penetrance for disease causal variants and genes. As we enter this new era of genomic medicine, we envision that consumer-driven and consumer-oriented efforts will take center stage, thus allowing insights from the human genome project to translate directly back into individualized medicine.

Entities:  

Year:  2012        PMID: 22830651      PMCID: PMC3580414          DOI: 10.1186/gm359

Source DB:  PubMed          Journal:  Genome Med        ISSN: 1756-994X            Impact factor:   11.117


  133 in total

1.  Accelerated clinical discovery using self-reported patient data collected online and a patient-matching algorithm.

Authors:  Paul Wicks; Timothy E Vaughan; Michael P Massagli; James Heywood
Journal:  Nat Biotechnol       Date:  2011-04-24       Impact factor: 54.908

2.  In search of triallelism in Bardet-Biedl syndrome.

Authors:  Leen Abu-Safieh; Shamsa Al-Anazi; Lama Al-Abdi; Mais Hashem; Hisham Alkuraya; Mushari Alamr; Mugtaba O Sirelkhatim; Zuhair Al-Hassnan; Basim Alkuraya; Jawahir Y Mohamed; Ahmad Al-Salem; May Alrashed; Eissa Faqeih; Ameen Softah; Amal Al-Hashem; Sami Wali; Zuhair Rahbeeni; Moeen Alsayed; Arif O Khan; Lihadh Al-Gazali; Peter E M Taschner; Selwa Al-Hazzaa; Fowzan S Alkuraya
Journal:  Eur J Hum Genet       Date:  2012-02-22       Impact factor: 4.246

3.  Escaping the EHR trap--the future of health IT.

Authors:  Kenneth D Mandl; Isaac S Kohane
Journal:  N Engl J Med       Date:  2012-06-14       Impact factor: 91.245

4.  Using SIFT and PolyPhen to predict loss-of-function and gain-of-function mutations.

Authors:  Sarah E Flanagan; Ann-Marie Patch; Sian Ellard
Journal:  Genet Test Mol Biomarkers       Date:  2010-08

5.  Pitfalls of homozygosity mapping: an extended consanguineous Bardet-Biedl syndrome family with two mutant genes (BBS2, BBS10), three mutations, but no triallelism.

Authors:  Virginie Laurier; Corinne Stoetzel; Jean Muller; Christelle Thibault; Sandra Corbani; Nadine Jalkh; Nabiha Salem; Eliane Chouery; Olivier Poch; Serge Licaire; Jean-Marc Danse; Patricia Amati-Bonneau; Dominique Bonneau; André Mégarbané; Jean-Louis Mandel; Hélène Dollfus
Journal:  Eur J Hum Genet       Date:  2006-07-05       Impact factor: 4.246

6.  Performance of mutation pathogenicity prediction methods on missense variants.

Authors:  Janita Thusberg; Ayodeji Olatubosun; Mauno Vihinen
Journal:  Hum Mutat       Date:  2011-02-22       Impact factor: 4.878

7.  Human Variome Project country nodes: documenting genetic information within a country.

Authors:  George P Patrinos; Timothy D Smith; Heather Howard; Fahd Al-Mulla; Lotfi Chouchane; Andreas Hadjisavvas; Sherifa A Hamed; Xi-Tao Li; Makia Marafie; Rajkumar S Ramesar; Feliciano J Ramos; Thomy de Ravel; Mona O El-Ruby; Tilak Ram Shrestha; María-Jesús Sobrido; Ghazi Tadmouri; Martina Witsch-Baumgartner; Bin Alwi Zilfalil; Arleen D Auerbach; Kevin Carpenter; Garry R Cutting; Vu Chi Dung; Wayne Grody; Julia Hasler; Lynn Jorde; Jim Kaput; Milan Macek; Yoichi Matsubara; Carmancita Padilla; Helen Robinson; Augusto Rojas-Martinez; Graham R Taylor; Mauno Vihinen; Tom Weber; John Burn; Ming Qi; Richard G H Cotton; David Rimoin
Journal:  Hum Mutat       Date:  2012-07-18       Impact factor: 4.878

Review 8.  Exome sequencing: the sweet spot before whole genomes.

Authors:  Jamie K Teer; James C Mullikin
Journal:  Hum Mol Genet       Date:  2010-08-12       Impact factor: 6.150

9.  Genomic landscape of a three-generation pedigree segregating affective disorder.

Authors:  Shuzhang Yang; Kai Wang; Brittany Gregory; Wade Berrettini; Li-San Wang; Hakon Hakonarson; Maja Bucan
Journal:  PLoS One       Date:  2009-02-13       Impact factor: 3.240

10.  A genome-wide association study of Hodgkin's lymphoma identifies new susceptibility loci at 2p16.1 (REL), 8q24.21 and 10p14 (GATA3).

Authors:  Victor Enciso-Mora; Peter Broderick; Yussanne Ma; Ruth F Jarrett; Henrik Hjalgrim; Kari Hemminki; Anke van den Berg; Bianca Olver; Amy Lloyd; Sara E Dobbins; Tracy Lightfoot; Flora E van Leeuwen; Asta Försti; Arjan Diepstra; Annegien Broeks; Jayaram Vijayakrishnan; Lesley Shield; Annette Lake; Dorothy Montgomery; Eve Roman; Andreas Engert; Elke Pogge von Strandmann; Katrin S Reiners; Ilja M Nolte; Karin E Smedby; Hans-Olov Adami; Nicola S Russell; Bengt Glimelius; Stephen Hamilton-Dutoit; Marieke de Bruin; Lars P Ryder; Daniel Molin; Karina Meden Sorensen; Ellen T Chang; Malcolm Taylor; Rosie Cooke; Robert Hofstra; Helga Westers; Tom van Wezel; Ronald van Eijk; Alan Ashworth; Klaus Rostgaard; Mads Melbye; Anthony J Swerdlow; Richard S Houlston
Journal:  Nat Genet       Date:  2010-10-31       Impact factor: 38.330

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  37 in total

1.  Genomic variant annotation and prioritization with ANNOVAR and wANNOVAR.

Authors:  Hui Yang; Kai Wang
Journal:  Nat Protoc       Date:  2015-09-17       Impact factor: 13.491

2.  Single-nucleotide evolution quantifies the importance of each site along the structure of mitochondrial carriers.

Authors:  Ciro Leonardo Pierri; Ferdinando Palmieri; Anna De Grassi
Journal:  Cell Mol Life Sci       Date:  2013-06-26       Impact factor: 9.261

Review 3.  Evaluating rare variants in complex disorders using next-generation sequencing.

Authors:  Matthew Ezewudo; Michael E Zwick
Journal:  Curr Psychiatry Rep       Date:  2013-04       Impact factor: 5.285

4.  Phenolyzer: phenotype-based prioritization of candidate genes for human diseases.

Authors:  Hui Yang; Peter N Robinson; Kai Wang
Journal:  Nat Methods       Date:  2015-07-20       Impact factor: 28.547

5.  InterVar: Clinical Interpretation of Genetic Variants by the 2015 ACMG-AMP Guidelines.

Authors:  Quan Li; Kai Wang
Journal:  Am J Hum Genet       Date:  2017-01-26       Impact factor: 11.025

6.  Development of the variant calling algorithm, ADIScan, and its use to estimate discordant sequences between monozygotic twins.

Authors:  Yangrae Cho; Sunho Lee; Jong Hui Hong; Byong Joon Kim; Woon-Young Hong; Jongcheol Jung; Hyang Burm Lee; Joohon Sung; Han-Na Kim; Hyung-Lae Kim; Jongsun Jung
Journal:  Nucleic Acids Res       Date:  2018-09-06       Impact factor: 16.971

7.  Annotate-it: a Swiss-knife approach to annotation, analysis and interpretation of single nucleotide variation in human disease.

Authors:  Alejandro Sifrim; Jeroen Kj Van Houdt; Leon-Charles Tranchevent; Beata Nowakowska; Ryo Sakai; Georgios A Pavlopoulos; Koen Devriendt; Joris R Vermeesch; Yves Moreau; Jan Aerts
Journal:  Genome Med       Date:  2012-09-26       Impact factor: 11.117

Review 8.  Technologies and Computational Analysis Strategies for CRISPR Applications.

Authors:  Kendell Clement; Jonathan Y Hsu; Matthew C Canver; J Keith Joung; Luca Pinello
Journal:  Mol Cell       Date:  2020-07-02       Impact factor: 17.970

Review 9.  The genetics of Autism Spectrum Disorders--a guide for clinicians.

Authors:  Karsten M Heil; Christian P Schaaf
Journal:  Curr Psychiatry Rep       Date:  2013-01       Impact factor: 5.285

10.  MAPPIN: a method for annotating, predicting pathogenicity and mode of inheritance for nonsynonymous variants.

Authors:  Nehal Gosalia; Aris N Economides; Frederick E Dewey; Suganthi Balasubramanian
Journal:  Nucleic Acids Res       Date:  2017-10-13       Impact factor: 16.971

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