lunes, 10 de septiembre de 2012

A public resource facilitating clinical use of genomes

A public resource facilitating clinical use of genomes

A public resource facilitating clinical use of genomes

  1. George M. Churcha,2

+ Author Affiliations

  1. aDepartment of Genetics, Harvard Medical School, Boston, MA 02115;

  2. bDivision of Medical Genetics, Massachusetts General Hospital, Boston, MA 02114;

  3. cClinical Future Inc., Cambridge, MA 02142;

  4. dIon Torrent by Life Technologies, Guilford, CT 06437;

  5. eDepartment of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO 63110;

  6. fDuke University Institute for Genome Sciences and Policy, Durham, NC 27708-0141;

  7. gTheragen BiO Institute, TheragenEtex Inc., Suwon, 443-270, Korea;

  8. hGenomics Department, Personal Genomics Institute, Suwon 443-766, Korea;

  9., Boston, MA 02215;

  10. jComplete Genomics, Inc., Mountain View, CA 94043;

  11. kDepartment of Computer Science and A.I., University of Granada, 18071 Granada, Spain;

  12. lDepartments of Pediatrics and Medicine, Columbia University, New York, NY 10032;

  13. mTeloMe, Inc., Waltham, MA 02451;

  14. nDepartment of Bioengineering, University of California at San Diego, La Jolla, CA 92093;

  15. oDivision of Genetics, NorthShore University HealthSystem, Evanston, IL 60201;

  16. pFaculty of Earth and Life Sciences, Department of Molecular Cell Physiology, VU University Amsterdam, 1081 HV Amsterdam, The Netherlands;

  17. qFaculty of Health, Medicine and Life Sciences, Maastricht University, 6200 MD Maastricht, The Netherlands;

  18. rGenomic Medicine Institute, Medical Research Center, College of Medicine, Seoul National University, Seoul, Korea;

  19. sPsoma Therapeutics Inc., Gasan-dong, Kumchun-gu, Seoul 153-781, Korea;

  20. tDivision of Genetics, Brigham and Women’s Hospital, Boston, MA 02115;

  21., San Carlos, California 94070;

  22. vBioinformatics Program, Boston University, Boston, MA 02215;

  23. wStanford Center for Inherited Cardiovascular Disease, Stanford University School of Medicine, Stanford, CA 94305;

  24. xRobinson Bradshaw & Hinson, P.A., Chapel Hill, NC 27517;

  25. yPersonalis, Inc., Palo Alto, CA 94301;

  26. zCha Cancer Institute, Cha University of Medicine and Science, Seoul 135-081, Korea;

  27. aaDepartment of Genetics, Stanford University, Stanford, CA 94305;

  28. bbDepartment of Systems Biology, Harvard Medical School, Boston, MA 02115;

  29. ccDepartment of Genetics, Harvard Medical School and Howard Hughes Medical Institute, Boston, MA 02115;

  30. ddMacrogen, Seoul, Korea; and

  31. eeDepartment of Pathology, Harvard Medical School, Boston, MA 02115

  1. Edited by C. Thomas Caskey, Baylor College of Medicine, Houston, TX, and approved June 11, 2012 (received for review February 1, 2012)


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.


  • Author contributions: M.P.B., J.V.T., A.W.Z., M.A., J. Bobe, M.F.C., S.M.D., P.W.E., J.E.L., D.B.V., H.L.R., and G.M.C. designed research; M.P.B., J.V.T., A.W.Z., T.C., A. M. Rosenbaum, X.W., W.K.C., P.W.E., A. M. Raman, K.R., C.E.S., and H.L.R. performed research; M.P.B., J.V.T., A.W.Z., T.C., A. M. Rosenbaum, X.W., J. Bhak, C.C., A.G., A.L., J.-H.L., B.C.K., Z.L., A. M. Raman, W.V., J.L.Y., L.Y., S.-J.K., J.B.L., L.P., and K.Z. contributed new reagents/analytic tools; M.P.B., J.V.T., A.W.Z., T.C., A. M. Rosenbaum, X.W., M.J.C., P.H., J.-I.K., M.F.M., G.B.N., B.A.P., H.Y.R., K.R., M.T.W., W.V., J.A., E.A.A., R.D., and J.-S.S. analyzed data; and M.P.B., J.V.T., A.W.Z., and G.M.C. wrote the paper.

  • Conflict of interest statement: G.M.C. has advisory roles in and research sponsorships from several companies involved in genome sequencing technology and personal genomics (

  • This article is a PNAS Direct Submission.

  • This article is part of the special series of Inaugural Articles by members of the National Academy of Sciences elected in 2011.

  • See Profile on page 11893.

  • Data deposition: The sequences reported in this paper are made available through the Personal Genome Project (

  • This article contains supporting information online at

Freely available online through the PNAS open access option.

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