The Personal Genome Project

Molecular Systems Biology (Impact Factor: 10.87). 02/2005; 1(1):2005.0030. DOI: 10.1038/msb4100040
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Available from: George Church, Mar 20, 2015
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    • "The decreasing cost and turn-around time of next generation sequencing (NGS) is accelerating the availability of clinical personal genomes and exomes (Church, 2005; Altshuler et al., 2010). However, data on the predictive clinical utility of whole genome sequencing (WGS) or whole exome sequencing (WES) are minimal, particularly among unselected patients. "
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    ABSTRACT: Whole exome sequencing (WES) is increasingly being used for diagnosis without adequate information on predictive characteristics of reportable variants typically found on any given individual and correlation with clinical phenotype. In this study, we performed WES on 89 deceased individuals (mean age at death 74 years, range 28-93) from the Mayo Clinic Biobank. Significant clinical diagnoses were abstracted from electronic medical record via chart review. Variants [Single Nucleotide Variant (SNV) and insertion/deletion] were filtered based on quality (accuracy >99%, read-depth >20, alternate-allele read-depth >5, minor-allele-frequency <0.1) and available HGMD/OMIM phenotype information. Variants were defined as Tier-1 (nonsense, splice or frame-shifting) and Tier-2 (missense, predicted-damaging) and evaluated in 56 ACMG-reportable genes, 57 cancer-predisposition genes, along with examining overall genotype-phenotype correlations. Following variant filtering, 7046 total variants were identified (~79/person, 644 Tier-1, 6402 Tier-2), 161 among 56 ACMG-reportable genes (~1.8/person, 13 Tier-1, 148 Tier-2), and 115 among 57 cancer-predisposition genes (~1.3/person, 3 Tier-1, 112 Tier-2). The number of variants across 57 cancer-predisposition genes did not differentiate individuals with/without invasive cancer history (P > 0.19). Evaluating genotype-phenotype correlations across the exome, 202(3%) of 7046 filtered variants had some evidence for phenotypic correlation in medical records, while 3710(53%) variants had no phenotypic correlation. The phenotype associated with the remaining 44% could not be assessed from a typical medical record review. These data highlight significant continued challenges in the ability to extract medically meaningful predictive results from WES.
    Frontiers in Genetics 08/2015; 6:244. DOI:10.3389/fgene.2015.00244
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    • "Apart from this, genotype information at sample level for a large number of individuals who participated in various genotype to phenotype association studies are available as part of the dbGAP (Mailman et al. 2007), though many of the datasets are not freely available but are secured under specific license restrictions. The personal genome project (PGP) (Church 2005) is a recent initiative spearheaded to create a publicly available repository of personal genomes for volunteers who would reveal their identity and genome to the public. It has been argued that such an approach with systematic collection of phenotypic correlates would be a valuable tool for research. "
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    ABSTRACT: Advances in technology have enabled understanding genetic makeup of individuals at a clinical timescale and affordable cost. This has brought about new challenges in the ability to decipher the information content of the genome and be able to act on relevant evidence especially in an environment where the information and evidence is dynamic. The availability of genomic sequences of identifiable individuals in public domain could have far-reaching advantages and open up interesting opportunities, not only to the individual, but also towards understanding the genomic biology. Nevertheless, a framework of social acceptance and regulatory oversight might add to the widespread acceptability of such an approach.The recent years have seen phenomenal developments in the scale, throughput and consequential unprecedented reduction in the cost of genome sequencing. This change has largely been brought about by an entire gamut of technologies which have enabled miniaturization, large-scale paralle ...
    Journal of Genetics 12/2014; 93(3):917-20. DOI:10.1007/s12041-014-0451-3 · 1.09 Impact Factor
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    • "A third approach (not at all mutually exclusive with the first two), articulated by Harvard geneticist George Church [8] and instantiated by his Personal Genome Project [9], is to throw up one's hands and simply make one's genotypes and phenotypes public. This response involves saying to patients and research participants in the starkest possible terms, “Secrets, especially genetic ones, are hard to keep. "
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    ABSTRACT: “One can't be of an enquiring and experimental nature, and still be very sensible.” - Charles Fort [1] As the costs of personal genetic testing “self-quantification” fall, publicly accessible databases housing people's genotypic and phenotypic information are gradually increasing in number and scope. The latest entrant is openSNP, which allows participants to upload their personal genetic/genomic and self-reported phenotypic data. I believe the emergence of such open repositories of human biological data is a natural reflection of inquisitive and digitally literate people's desires to make genomic and phenotypic information more easily available to a community beyond the research establishment. Such unfettered databases hold the promise of contributing mightily to science, science education and medicine. That said, in an age of increasingly widespread governmental and corporate surveillance, we would do well to be mindful that genomic DNA is uniquely identifying. Participants in open biological databases are engaged in a real-time experiment whose outcome is unknown.
    PLoS ONE 03/2014; 9(3):e92060. DOI:10.1371/journal.pone.0092060 · 3.23 Impact Factor
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