Document Detail

A public resource facilitating clinical use of genomes.
MedLine Citation:
PMID:  22797899     Owner:  NLM     Status:  MEDLINE    
Rapid advances in DNA sequencing promise to enable new diagnostics and individualized therapies. Achieving personalized medicine, however, will require extensive research on highly reidentifiable, integrated datasets of genomic and health information. To assist with this, participants in the Personal Genome Project choose to forgo privacy via our institutional review board- approved "open consent" process. The contribution of public data and samples facilitates both scientific discovery and standardization of methods. We present our findings after enrollment of more than 1,800 participants, including whole-genome sequencing of 10 pilot participant genomes (the PGP-10). We introduce the Genome-Environment-Trait Evidence (GET-Evidence) system. This tool automatically processes genomes and prioritizes both published and novel variants for interpretation. In the process of reviewing the presumed healthy PGP-10 genomes, we find numerous literature references implying serious disease. Although it is sometimes impossible to rule out a late-onset effect, stringent evidence requirements can address the high rate of incidental findings. To that end we develop a peer production system for recording and organizing variant evaluations according to standard evidence guidelines, creating a public forum for reaching consensus on interpretation of clinically relevant variants. Genome analysis becomes a two-step process: using a prioritized list to record variant evaluations, then automatically sorting reviewed variants using these annotations. Genome data, health and trait information, participant samples, and variant interpretations are all shared in the public domain-we invite others to review our results using our participant samples and contribute to our interpretations. We offer our public resource and methods to further personalized medical research.
Madeleine P Ball; Joseph V Thakuria; Alexander Wait Zaranek; Tom Clegg; Abraham M Rosenbaum; Xiaodi Wu; Misha Angrist; Jong Bhak; Jason Bobe; Matthew J Callow; Carlos Cano; Michael F Chou; Wendy K Chung; Shawn M Douglas; Preston W Estep; Athurva Gore; Peter Hulick; Alberto Labarga; Je-Hyuk Lee; Jeantine E Lunshof; Byung Chul Kim; Jong-Il Kim; Zhe Li; Michael F Murray; Geoffrey B Nilsen; Brock A Peters; Anugraha M Raman; Hugh Y Rienhoff; Kimberly Robasky; Matthew T Wheeler; Ward Vandewege; Daniel B Vorhaus; Joyce L Yang; Luhan Yang; John Aach; Euan A Ashley; Radoje Drmanac; Seong-Jin Kim; Jin Billy Li; Leonid Peshkin; Christine E Seidman; Jeong-Sun Seo; Kun Zhang; Heidi L Rehm; George M Church
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Publication Detail:
Type:  Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't     Date:  2012-07-13
Journal Detail:
Title:  Proceedings of the National Academy of Sciences of the United States of America     Volume:  109     ISSN:  1091-6490     ISO Abbreviation:  Proc. Natl. Acad. Sci. U.S.A.     Publication Date:  2012 Jul 
Date Detail:
Created Date:  2012-07-25     Completed Date:  2012-10-12     Revised Date:  2013-07-12    
Medline Journal Info:
Nlm Unique ID:  7505876     Medline TA:  Proc Natl Acad Sci U S A     Country:  United States    
Other Details:
Languages:  eng     Pagination:  11920-7     Citation Subset:  IM    
Department of Genetics, Harvard Medical School, Boston, MA 02115, USA.
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MeSH Terms
Cell Line
Data Collection
Databases, Genetic*
Genetic Variation*
Genome, Human / genetics*
Individualized Medicine / methods*,  trends
Sequence Analysis, DNA
Grant Support
Comment In:
Nat Rev Genet. 2012 Sep;13(9):599   [PMID:  22825475 ]

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine

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