9:45 Industrial-Scale Genotyping: Identifying, Validating, and Translating
Association Findings
Dietrich Stephan, Ph.D., Director & Senior Investigator, Neurogenomics, Translational Genomics Institute
Dissecting the genetic variants that subtly predispose to common and complex human disease requires careful study design considerations, a robust high-throughput environment, and evolving analysis paradigms. If done correctly, the results can routinely be expected to result in therapeutic targets with an order of magnitude more precise than historical strategies, as well as probabilistic risk assessment tools.
10:15 Networking Coffee Break
10:45 Genome Scan of 310 African-American Families for Genes Linked to Higher Risk of Diabetes and Cardiovascular Disease
Michael Christman, Ph.D., President and Chief Executive Officer, Coriell Institute for Medical Research
Obesity, hypertension, type 2 diabetes and their complications are more common among African Americans than European Americans. Collectively, these diseases explain over 80% of the health disparity between Americans of African descent and Americans of Western European descent. The Howard University Family Study was developed as a population-based resource of multi-generational African American pedigrees to study the genetic epidemiology of these diseases. We have used the Affymetrix SNP 6.0 arrays combined with a family-based association analysis to identify common genetic factors influencing heritability of these common diseases in African Americans.
11:15 Copy-Number Variation in Control Population Cohorts
Richard F. Wintle, Ph.D., Assistant Director, Center for Applied Genomics, Hospital for Sick Children
Copy-number variation (CNV) is the most prevalent type of variation with respect to total nucleotide content in the human genome. In order to understand the contribution of CNV to both normal human variation and disease susceptibility, it is crucial to understand the range and characteristics of CNV variability in healthy population cohorts. In our group, a variety of approaches, both laboratory-based and analytical, are being applied to various different control cohort populations. Here, we will describe recent work using high-density arrays from the major vendors to ascertain genome-wide copy number. We also describe the development of a novel algorithm for the determination of genomic copy number from these array platforms, and the application of the Database of Genomic Variants con-taining normal variation data to disease studies.
11:45 Structural Genomic Variation in the Human Genome: The Impact of Copy Number Variants (CNVs) in Clinical Diagnoses
Charles Lee, Ph.D., FACMG, Director of Cytogenetics, Harvard Cancer Center, Assistant Professor, Harvard Medical School; Associate Faculty Member, MIT Broad Institute, and Department of Pathology, Brigham and Women’s Hospital
Genomic imbalances were traditionally thought to be rare and disease causing. However, over the past three years we have come to appreciate that structural genomic variation (including copy number variants – CNVs) are widespread and many can be very common among healthy individuals. This has complicated accurate interpretation of data being generated from genome-wide comparative genomic hybridization (CGH) / genotyping platforms being used for clinical diagnoses. Strategies to determine if a particular CNV is pathogenic or benign will be discussed, in the context of our recent studies that define the fine-scale genomic architecture of hundreds of common CNVs.
12:15 pm Close of Morning Session
12:30 Luncheon Technology Workshops
(Sponsorships Available) or Lunch on Your Own
2:00 Chairperson’s Remarks
Constantin
Polychronakos, M.D., F.R.C.P.C., Professor,
Departments of Pediatrics and Human Genetics and
Director, Pediatric Endocrinology, McGill University
Health Center (Children’s Hospital)
2:05 SNP and CNV-Based Genome-Wide Association Studies: Elements for Success
John Raelson, Ph.D., Chief Geneticist, Genizon Biosciences
Genizon Biosciences has successfully conducted SNP-based genome-wide association studies (GWAS) in 8 complex genetic diseases using samples from the Quebec founder population. More recently, copy number variant (CNV) analyses have also been performed. Several critical elements for success that have been identified in the course of these studies and incorporated into Genizon’s analytical
methodology will be discussed.
2:35 Genetics of Human Gene Expression and the Interpretation of Genome-Wide Association Study Results
Andrew Kasarskis, Ph.D., Scientific Director, Genetics, Rosetta Inpharmatics LLC - Merck Research Laboratories
Systematic investigation of the genetics of human gene expression through genome-wide assocation studies coupled with gene expression microarrays has allowed us to characterize the molecular networks of several human tissues in some detail. These networks give a rich description of the relationships between genes in each tissue, the relationships between the expression of genes in those tissues and phe-notpyes measured in these populations, and the extent to which inherited variation modulates these relationships. Comparison with similar networks generated in genetically diverse mouse populations has the potential to improve the translation of results from mouse to human, and the combination of mouse and human networks is a powerful tool to probe the mechanism behind the many statistically robust but poorly understood associations between DNA variation and clinical phenotypes that result from genome-wide association studies.
3:05 Type 1 Diabetes: A Staged Approach to Genome-Wide Association. Where Do We Go from Here?
Constantin Polychronakos, M.D., F.R.C.P.C., Professor, Departments of Pediatrics and Human Genetics and Director, Pediatric Endocrinology, McGill University Health Center (Children’s Hospital)
Two published genome-wide association studies for type 1 diabetes (T1D) have discovered four
robustly replicated susceptibility loci that either reached statistical significance in the first stage (involving 2,000 and 1,000 cases in each of the studies) or were close enough to be fast-tracked to replica-tion. This approach does not have the power to reveal all loci. Therefore, it is not surprising that, added to the known associations the newly discovered loci still do not entirely explain the familial aggrega-tion of T1D. Work is underway to identify the remaining loci through a full second stage, whereby the loci with statistical significance above a certain limit are being tested in additional cohorts. In parallel, fine-mapping of the known loci, especially the newly discovered ones, is likely to increase their known contribution with the discovery of the most highly associated variant. Any residual heritability that cannot be explained by these common variants should be sought in rare variants with large effects, probably through large-scale exon resequencing of genes mapping to linkage peaks.
3:35 Technology Spotlight
Tailored
Solutions for Today's Requirements for Clinical
Genotping
Vera Sturma, Global Business Leader Genotyping,
EPIDAUROS Biotechnologie AG
3:50 Networking Refreshment Break
4:15 New Prostate Cancer Risk Alleles Update
William J. Catalona, M.D., Professor, Urology, Northwestern University
4:45 Panel Discussion
Moderator: TBA
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How much of genotyping information will be useful?
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How useful is the information we are now getting from genotyping studies?
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What were the keys to getting here? Has genotyping reached its zenith? Or is there much more ahead?
5:15 Welcoming Reception in the Exhibit Hall
6:30 Close of Day
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