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International Team Using Exome Sequencing for Association Study of Metabolic Disorders

By Andrea Anderson

WASHINGTON (GenomeWeb News) – Members of the LuCAMP Consortium are analyzing sequence data on thousands of Danish exomes as part of a two-stage association study intended to root out relatively low frequency common variants associated with metabolic disorders such as type 2 diabetes, hypertension, and obesity.

During a presentation to reporters here yesterday at the American Society of Human Genetics annual meeting, Yingrui Li, director of Beijing Genomics Institute's bioinformatics center, and Oluf Pedersen, Hagedorn Research Institute researcher and LuCAMP Centre Director, described the project and its progress so far.

Although numerous SNPs have been associated with type 2 diabetes and obesity, Li noted, these variants still explain a relatively small percentage of the human variation that exists for these traits.

The LuCAMP team, which includes researchers from Hagedorn Research Institute, BGI, the University of Aarhus, and the University of Copenhagen, is using a combination of exome sequencing and genotyping to try to uncover metabolic disorder-related variants with a minor allele to frequency of between one and five percent.

To do this, they first set out to sequence the exomes of 1,000 Danish individuals with type 2 diabetes, as well as 1,000 glucose-tolerant control individuals from the same population, to around 10 times coverage using Roche NimbleGen exon capture arrays and Illumina sequencing.

The team reported on results from the first 200 control individuals' exomes in a paper appearing online in Nature Genetics last month. Data from those individuals pointed to a previously unappreciated excess of non-synonymous — and potentially deleterious — variants amongst the lower frequency variants in the human genome.

From the broader exome sequencing phase of the study, the researchers have identified the top 1,000 highest-ranked candidate SNPs.

These SNPs are being incorporated with about 19,000 other SNPs on an Illumina array that's being used to genotype 17,000 more individuals from the same population — including about 5,000 individuals with type 2 diabetes, 5,000 obese individuals, and 7,000 controls.

The researchers are currently analyzing data from the study using several approaches intended to tease apart information on both genes and pathways that may contribute to metabolic disease, Pedersen explained, and may eventually do additional replication studies in independent populations.

By narrowing in on lower frequency variants, particularly those with a minor allele frequency of around one percent that are not covered by arrays used in past genome-wide association studies, Pedersen added, the researchers hope to get a "new window" on type 2 diabetes, obesity, and related conditions.

Those involved in the study also touted its potential for helping to turn up variants that can be applied to the next generation of genome-wide association studies.

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