SBIR-STTR Award

In the process of pre-implantation genetic diagnoses (PGD), a single blastomere is removed from the early stage embryo for analysis. Currently, most PGD techniques focus on detection of chromosomal abnormalities such as aneuploidies and balanced translocations.1 However, in order to understand the inheritance of the majority of disease phenotypes, it will be necessary to measure multiple single nucleotide polymorphisms (SNPs) on the embryonic DNA. Techniques are available in research laboratories today, with estimated availability within two years, to measure SNPs from the DNA of a single cell. However, since only a single copy of the DNA is available from one cell, the SNP measurements will be highly error-prone or noisy. Gene Security Network has developed a proprietary technique, termed Parental Support TM, for cleaning the noisy measurements of embryonic DNA. In essence, the algorithm makes use of genetic data of the mother and the father, together with the knowledge of the mechanism of meiosis and the noisy measurements of the embryonic DNA, in order to reconstruct in-silicon the embryonic DNA at the location of key SNPS with a high degree of confidence. This project extends GSN's recent work in developing a translation engine for the efficient integration of multiple sets of pharamacogenomic data into a standardized ontology. The translation engine is used to create a cartridge for each local source of data. The cartridge translates the genetic, phenotypic and meta-data from the local source into the format of the standardized ontology, where it can be analyzed by expert rules and statistical models for data validation and outcome prediction. This work is being performed in collaboration with the PharmGKB Project at Stanford University. PharmGKB manages an openly-shared Internet repository for clinical trial data with the intent to uncover how individual genetic variation contributes to distinctive reactions to pharmaceuticals. As a member of the NIH Pharmacogenetics Research Network (PGRN), PharmGKB's database includes extensive pharmacokinetic and genomic records from cardiovascular, pulmonary, and cancer research. In aim 1, we will extend GSN's work with PharmGKB by working with pharmGKB to create a standardized, computable ontology for genotyping array data together with a cartridge for integrating Affymetrix genotyping array data into that format. This will enable PharmGKB to efficiently make high-throughput genotyping data publicly available for pharmacogenomic research. The computable genotyping data standard will also establish the foundation for aims 2 and 3 of this project. In aim 2, we will demonstrate the utility of the computable data format by inputting high-throughput genotyping array data from an Affymetrix 500k Gene chip Array into that standard and predicting the susceptibility to key disease phenotypes, based on data aggregated from the public domain. In aim 3, we will refine and implement the Parental Support TM technique for cleaning the embryonic DNA, measured using either PCR-based techniques, or molecular inversion-probe (MIPS) based techniques. Relevance to Healthcare Aim 1 provides a standardized ontology for genotyping array data, and a cartridge for easily submitting genotyping array data into the public domain. Having this data in the public domain will considerably benefit research in understanding gene-disease association and gene functions. In addition, the availability of the genotyping data in standardized computable format will ultimately enhance the ability of doctors to use that information for clinical decisions. Aim 2 will enable the knowledge of gene-disease associations to enhance pre-implantation genetic diagnosis. Aim 3 will refine the Parental Support method to enable genotyping technologies, operating on a single cell, to produce reliable genotyping data in the IVF setting. This reliable genotyping data is absolutely critical for the task of predicting susceptibilities to various disease phenotypes.

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In 2006, across the globe, more than 800,000 in-vitro fertilization (IVF) cycles were run. Of 150,000 cycles run in the US, roughly 10,000 involved pre-implantation genetic diagnosis (PGD). Current PGD techniques are unregulated, expensive and highly unreliable: error rates for screening disease-linked loci or aneuploidy are on the order of 10%; each screening test costs more than $5,000; and a couple is forced to choose between testing aneuploidy, which afflicts roughly 40% of IVF embryos, or screening for disease-linked loci on the single cell. There is a great need for an affordable technology that can reliably determine genetic data from the single cell in order to screen in parallel for aneuploidy, monogenic diseases such as Cystic Fibrosis, and susceptibility to complex disease phenotypes for which the multiple genetic markers are known through whole-genome association (WGA) studies. The process of PGD during IVF involves extracting a single cell from the roughly 8 cells of an early-stage embryo for analysis. Since only a single copy of the DNA is available from one cell, direct measurements of the DNA are highly error-prone, or noisy. Gene Security Network (GSN) has developed a novel technology, termed Parental SupportTM (PS), for determining the embryonic DNA at hundreds of loci together with copy numbers for 23 chromosomes, with error rates below 0.1%, from a single cell. The proprietary technique makes use of genetic data of the mother and the father, together with the knowledge of the mechanism of meiosis and noisy measurements of the embryonic DNA, in order to determine which segments of parent chromosomes contributed to the gametes that fertilized and hence to reconstruct in silico the embryonic DNA with confidence exceeding 99%. Based on the results of our phase I study, GSN has executed letters of intent with the 5 leading IVF centers in the United States to use the GSN diagnostic service. In aim 1 of this proposal, we will demonstrate the ability of the PS technology to reliably reconstruct genetic data using the measured genetic data from isolated single cells from a born child, and parental genetic data. In aim 2 we will demonstrate the ability of the PS technology to detect aneuploidy at all 23 chromosomes, also using isolated single cell genetic data, by means of an innovative single cell model for aneuploidy that does not require direct work on embryos. In Aim 3 we will perform a clinical trial in conjunction with Stanford IVF Center, Boston IVF and Huntington Reproductive Center that applies the techniques from aims 1 and 2 to real blastomeres in the IVF context and compare our predictions with truth measured on the child when born. One goal of the study is to generate data that will be used to obtain approval of this diagnostic technique by the Food and Drug Administration. The PS technology of Gene Security Network will bring the domain of PGD into the realm of reliable diagnostics which can be regulated and used with confidence in clinical decisions. The selection of the embryos to implant is a clinical decision that has direct and absolute impact on outcomes. Narrative and Relevance to Healthcare

Public Health Relevance:
As data associating disease phenotypes with genotype continues to grow, the question arises: how can this knowledge be used to improve the quality of life and health? With this grant, Gene Security Network will thoroughly validate a technology for screening embryos during in-vitro fertilization for a multiplicity of disease linked genes and TM aneuploidy. This technology, termed Parental Support (PS) which is built on the fundamental principles of meiosis and data that has recently become available through the human genome project. Compared to existing technologies, PS enables: i) determination of disease linked loci with roughly two orders of magnitude lower error rates; ii) determination of multiple disease-linked loci in parallel; iii) determination of aneuploidy with roughly two orders of magnitude lower error rates; and iv) determination of aneuploidy across all chromosomes together with multiple disease-linked loci all from a single cell. GSN is developing the enhanced reporting system, statistical methods, and wet-lab infrastructure to offer this service to the leading IVF centers who have signed letters of intent to purchase the service, and then to the worldwide IVF community. Funding for this study will enable us to validate the performance of the diagnostic with known truth models on single cells, and to validate predictions made from a single blastomere by comparing those predictions with genetic data measured when a child is born. Roughly 152,000 and 653,000 IVF cycles were performed in 2006 in the US and internationally. The rate of growth of PGD is roughly 33% annually. Funding for this study will enable us to validate the performance of the diagnostic with known truth models on single cells, and to validate predictions made from a single blastomere by comparing those predictions with genetic data measured when a child is born. GSN's PS technology of will bring the domain of PGD into the realm of reliable diagnostics which can be regulated and used as part of the standard of care during in-vitro fertilization.

Public Health Relevance:
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