Exome Aggregation Consortium (ExAC), generated the largest catalogue so far of variation in human protein-coding regions: Sequence data of 60,000 people, NOW is a publicly accessible database
August 18, 2016 by 2012pharmaceutical
Reporter: Aviva Lev-Ari, PhD, RN
UPDATED on 8/22/2016
“The ExAC resource gives us incredible insight when evaluating a patient’s genome sequence in the clinic,” said Heidi Rehm, HMS associate professor of pathology at Brigham and Women’s Hospital, medical clinical director of the Broad’s Clinical Research Sequencing Platform and chief laboratory director of the Laboratory for Molecular Medicine at Partners HealthCare Personalized Medicine.
“In our own research, using the ExAC resource has allowed us to apply novel statistical methods to identify several new severe developmental disorders,” said Matthew Hurles, a researcher at the Wellcome Trust Sanger Institute and frequent user of the ExAC database. “Resources such as ExAC exemplify the benefits that can be achieved for families coping with rare genetic diseases, as a result of the mass altruism of many research participants who allow their data to be aggregated and shared.”
SOURCE
http://hms.harvard.edu/news/going-wide-and-deep?utm_source=Silverpop&utm_medium=email&utm_content=s3&utm_campaign=08.22.16.HMS
These variant data already guide diagnoses and treatment
E. V. Minikel et al. Sci. Transl. Med. 8, 322ra9; 2016
Quantifying prion disease penetrance using large population control cohorts
- Eric Vallabh Minikel1,2,3,4,*,
- Sonia M. Vallabh1,3,4,
- Monkol Lek1,2,
- Karol Estrada1,2,
- Kaitlin E. Samocha1,2,3,
- J. Fah Sathirapongsasuti5,
- Cory Y. McLean5,
- Joyce Y. Tung5,
- Linda P. C. Yu5,
- Pierluigi Gambetti6,
- Janis Blevins6,
- Shulin Zhang7,
- Yvonne Cohen6,
- Wei Chen6,
- Masahito Yamada8,
- Tsuyoshi Hamaguchi8,
- Nobuo Sanjo9,
- Hidehiro Mizusawa10,
- Yosikazu Nakamura11,
- Tetsuyuki Kitamoto12,
- Steven J. Collins13,
- Alison Boyd13,
- Robert G. Will14,
- Richard Knight14,
- Claudia Ponto15,
- Inga Zerr15,
- Theo F. J. Kraus16,
- Sabina Eigenbrod16,
- Armin Giese16,
- Miguel Calero17,
- Jesús de Pedro-Cuesta17,
- Stéphane Haïk18,19,
- Jean-Louis Laplanche20,
- Elodie Bouaziz-Amar20,
- Jean-Philippe Brandel18,19,
- Sabina Capellari21,22,
- Piero Parchi21,22,
- Anna Poleggi23,
- Anna Ladogana23,
- Anne H. O’Donnell-Luria1,2,24,
- Konrad J. Karczewski1,2,
- Jamie L. Marshall1,2,
- Michael Boehnke25,
- Markku Laakso26,
- Karen L. Mohlke27,
- Anna Kähler28,
- Kimberly Chambert29,
- Steven McCarroll29,
- Patrick F. Sullivan27,28,
- Christina M. Hultman28,
- Shaun M. Purcell30,
- Pamela Sklar30,
- Sven J. van der Lee31,
- Annemieke Rozemuller32,
- Casper Jansen32,
- Albert Hofman31,
- Robert Kraaij33,
- Jeroen G. J. van Rooij33,
- M. Arfan Ikram31,
- André G. Uitterlinden31,33,
- Cornelia M. van Duijn31,
- Exome Aggregation Consortium (ExAC)†,
- Mark J. Daly1,2 and
- Daniel G. MacArthur1,2,*
+ Author Affiliations
- ↵*Corresponding author. E-mail: eminikel@broadinstitute.org (E.V.M.); macarthur@atgu.mgh.harvard.edu (D.G.M.)
and
R. Walsh et al. Genet. Med. http://dx.doi.org/10.1038/gim.2016.90; 2016).
Reassessment of Mendelian gene pathogenicity using 7,855 cardiomyopathy cases and 60,706 reference samples
- Roddy Walsh BSc, MSc,
- Kate L. Thomson BSc, FRCPath,
- James S. Ware PhD, MRCP,
- Birgit H. Funke PhD, FACMG,
- Jessica Woodley BSc,
- Karen J. McGuire BSc,
- Francesco Mazzarotto BSc, MSc,
- Edward Blair BMSc, MRCP,
- Anneke Seller PhD,
- Jenny C. Taylor PhD,
- Eric V. Minikel MS,
- Exome Aggregation Consortium,
- Daniel G. MacArthur PhD,
- Martin Farrall FRCPath,
- Stuart A. Cook PhD, MRCPath
- & Hugh Watkins MD, PhD
- Genetics in Medicine
- (2016)
- doi:10.1038/gim.2016.90
- Published online
- 17 August 2016
The ExAC project plans to grow over the next year to include 120,000 exome and 20,000 whole-genome sequences. It relies on the willingness of large research consortia to cooperate, and highlights the huge value of sharing, aggregation and harmonization of genomic data. This is also true for patient variants — there is a need for databases that provide greater confidence in variant interpretation, such as the US National Center for Biotechnology Information’s ClinVar database.
SOURCE
Nature536,249(18 August 2016)doi:10.1038/536249a
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