Imperial College London
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Dr. Anna C. Need

Faculty of Medicine, Department of Brain Sciences

Honorary Lecturer
 
 
 
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Contact

 

+44 (0)20 3313 8436a.need Website

 
 
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Location

 

7N2aCommonwealth BuildingHammersmith Campus

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Summary

 

Publications

Citation

BibTex format

@article{Zhu:2015:10.1038/gim.2014.191,
author = {Zhu, X and Petrovski, S and Xie, P and Ruzzo, EK and Lu, Y-F and McSweeney, KM and Ben-Zeev, B and Nissenkorn, A and Anikster, Y and Oz-Levi, D and Dhindsa, RS and Hitomi, Y and Schoch, K and Spillmann, RC and Heimer, G and Marek-Yagel, D and Tzadok, M and Han, Y and Worley, G and Goldstein, J and Jiang, Y-H and Lancet, D and Pras, E and Shashi, V and McHale, D and Need, AC and Goldstein, DB},
doi = {10.1038/gim.2014.191},
journal = {Genetics in Medicine},
pages = {774--781},
title = {Whole-exome sequencing in undiagnosed genetic diseases: interpreting 119 trios},
url = {http://dx.doi.org/10.1038/gim.2014.191},
volume = {17},
year = {2015}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Purpose:Despite the recognized clinical value of exome-based diagnostics, methods for comprehensive genomic interpretation remain immature. Diagnoses are based on known or presumed pathogenic variants in genes already associated with a similar phenotype. Here, we extend this paradigm by evaluating novel bioinformatics approaches to aid identification of new gene–disease associations.Methods:We analyzed 119 trios to identify both diagnostic genotypes in known genes and candidate genotypes in novel genes. We considered qualifying genotypes based on their population frequency and in silico predicted effects we also characterized the patterns of genotypes enriched among this collection of patients.Results:We obtained a genetic diagnosis for 29 (24%) of our patients. We showed that patients carried an excess of damaging de novo mutations in intolerant genes, particularly those shown to be essential in mice (P = 3.4 × 10−8). This enrichment is only partially explained by mutations found in known disease-causing genes.Conclusion:This work indicates that the application of appropriate bioinformatics analyses to clinical sequence data can also help implicate novel disease genes and suggest expanded phenotypes for known disease genes. These analyses further suggest that some cases resolved by whole-exome sequencing will have direct therapeutic implications.
AU  - Zhu,X
AU  - Petrovski,S
AU  - Xie,P
AU  - Ruzzo,EK
AU  - Lu,Y-F
AU  - McSweeney,KM
AU  - Ben-Zeev,B
AU  - Nissenkorn,A
AU  - Anikster,Y
AU  - Oz-Levi,D
AU  - Dhindsa,RS
AU  - Hitomi,Y
AU  - Schoch,K
AU  - Spillmann,RC
AU  - Heimer,G
AU  - Marek-Yagel,D
AU  - Tzadok,M
AU  - Han,Y
AU  - Worley,G
AU  - Goldstein,J
AU  - Jiang,Y-H
AU  - Lancet,D
AU  - Pras,E
AU  - Shashi,V
AU  - McHale,D
AU  - Need,AC
AU  - Goldstein,DB
DO  - 10.1038/gim.2014.191
EP  - 781
PY  - 2015///
SN  - 1530-0366
SP  - 774
TI  - Whole-exome sequencing in undiagnosed genetic diseases: interpreting 119 trios
T2  - Genetics in Medicine
UR  - http://dx.doi.org/10.1038/gim.2014.191
UR  - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000362441900005&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR  - http://hdl.handle.net/10044/1/38939
VL  - 17
ER  -
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