Textbook of Personalized Medicine - Second Edition [2015]

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Personal Genome Project


Achieving personalized medicine will require extensive research on highly re-
identifi able, integrated datasets of genomic and health information. A Personal
Genome Project (PGP) was launched as a sequel of the Human Genome project and
volunteers were recruited to make their own genomic and phenomic data available.
Participants in the PGP choose to forgo privacy via institutional review board-
approved “open consent” process. These resources were planned to include full
(46-chromosome) genome sequences, digital medical records and other medical
information that would become a part of personal health profi le. It also includes
comprehensive data about RNA and protein, body and facial measurements and
imaging such as MRI. Human cell lines representing each subject are deposited in a
repository at the National Institute of Genome Medical Sciences. Details of PGP
can be found at the following web site: http://arep.med.harvard.edu/PGP/.
The fi ndings after enrollment of more than 1,800 participants, including WGS of
10 pilot participant genomes (the PGP-10), have been published (Ball et al. 2012 ).
The Genome-Environment-Trait Evidence (GET-Evidence) system, which automat-
ically processes genomes and prioritizes both published and novel variants for inter-
pretation, was introduced. In the process of reviewing the presumed healthy PGP-10
genomes, the authors found numerous literature references implying serious dis-
ease. Although it is sometimes impossible to rule out a late-onset effect, stringent
evidence requirements can address the high rate of incidental fi ndings. To that end
the team developed 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 analy-
sis 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. There is an open invitation to others to review the
results using participant samples and contribute to interpretations. This public
resource and methods are offered to further personalized medical research. In the
ongoing project, the organizers hope to enroll 100,000 participants.


Biochips and Microarrays


Biochip is a broad term indicating the use of microchip technology in molecular
biology and can be defi ned as arrays of selected biomolecules immobilized on a
surface. This technology has been described in more detail elsewhere (Jain 2015a ).
DNA microarray is a rapid method of sequencing and analyzing genes. An array is
an orderly arrangement of samples. The sample spot sizes in microarray are usually
<200 μm in diameter. It is comprised of DNA probes formatted on a biochip plus the
instruments needed to handle samples (automated robotics), read the reporter mol-
ecules (scanners) and analyze the data (bioinformatic tools).


2 Molecular Diagnostics in Personalized Medicine
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