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Genome-wide SNP association: identification of susceptibility alleles for osteoarthritis
Kenneth Abel1, Rikard Reneland, Stefan Kammerer
1SEQUENOM, Inc., 3595 John Hopkins Court, San Diego, CA, USA 92121.
Abstract:
The successful identification of genes involved in common human disorders is dependent upon availability of informative sample sets, validated marker panels, a high-throughput scoring technology, and a strategy for combining these resources. We have developed a universal platform based on mass spectrometry (MassARRAY) for analyzing nucleic acids with high precision and accuracy. To fuel this technology we have generated more than 100,000 validated assays for single nucleotide polymorphisms (SNPs) covering virtually all known and predicted human genes, and a large DNA sample bank from more than 50,000 consented diseased (case) and healthy (control) individuals. Taking advantage of MassARRAY's capability for quantitative analysis of nucleic acids, allele frequencies are estimated in sample pools containing large numbers of individual DNAs. Comparing frequencies between case and control pools as a first-pass filtering step is a tremendous advantage in throughput and cost over individual genotyping. We have employed this approach in numerous genome-wide association studies to identify genes implicated in common complex diseases, including osteoarthritis (OA). Access to additional patient samples through collaborations allows us to conduct replication studies that validate true disease genes. These discoveries will expand our understanding of genetic disease predisposition, and our capabilities for early diagnosis and improved therapeutic approaches.
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