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WTCCC Data Suggests Common CNVs Not Key Common Disease Culprits

By a GenomeWeb staff reporter

NEW YORK (GenomeWeb News) – Common copy number variants that can be assessed by current array technology have little influence on common human diseases, according to a paper appearing online in Nature today.

In an effort to find common CNVs linked to eight common diseases, members of the Wellcome Trust Case Control Consortium used an array-based approach to assess common CNVs in about 16,000 affected individuals and 3,000 healthy controls. But, they reported, their search turned up just three genetic loci that were associated with disease and confirmed by follow-up experiments, suggesting common CNVs likely aren't the main cause of these or other common diseases.

"There was a strong view that CNVs would be important for common disease, and that they would explain much of the missing heritability," corresponding author Peter Donnelly, WTCCC chair, director of the Wellcome Trust Centre for Human Genetics, and statistics researcher at the University of Oxford, said in a statement.

"We now believe this is not the case," he wrote. "Our results will be surprising and disappointing for some parts of the community."

For the initial phase of the study, the researchers tested 384 individuals at 156 CNVs using the Agilent CGH, NimbleGen CGH, and Illumina iSelect arrays in order to select a platform for the main portion of the study. Based on this pilot experiment, the team selected the Agilent CGH platform and then designed a custom CNV-typing array in conjunction with researchers from the Genome Structural Variation Consortium.

Using this approach, the researchers evaluated 10,894 CNVs in about 2,000 individuals affected by each of the eight diseases and 3,000 healthy controls.

Samples for the study came from the 1958 British Birth Cohort and the UK Blood Service and were assayed by the UK-based microarray service company Oxford Gene Technology. As a quality control measure, the team also threw in another 270 samples from the HapMap project and 610 duplicate samples.

After tossing out false positive associations and doing quality control steps, the team was left with 3,432 polymorphic CNVs.

In the association testing and follow-up stages of their study, the researchers found just three loci associated with disease: IRGM, which was associated with Crohn's disease, the HLA locus, which was linked to Crohn's disease, rheumatoid arthritis, and type 1 diabetes; and TSPAN8, which was associated with type 2 diabetes. All of these had been identified in prior SNP genotyping studies, they noted.

"It seems unlikely that common CNVs play a major role in the genetic basis of common diseases, either through particular CNVs having a strong effect or through a large number of CNVs each contributing a small effect," co-lead author Matthew Hurles, a human genetics researcher at the Wellcome Trust Sanger Institute, said in a statement. "This is certainly the case for the diseases that we studied, but is likely to be the case for other common diseases, too."

Based on the findings, members of the team are shifting their approach to look for rarer CNVs and SNPs in common diseases. For example, University of Oxford researcher Mark McCarthy is reportedly leading a National Institutes of Health and Wellcome Trust Sanger Institute-funded study to find rare SNPs involved in type 2 diabetes.

More generally, the researchers also urged caution in generating and analyzing array CGH copy number data, noting that several factors can affect the quality and interpretation of the data.

"At least for currently available CNV-typing platforms, we recommend considerable care in interpreting putative CNV associations combined with independent replication on a different experimental platform," they wrote.