DNA samples from 120,000 people are to be analysed in a 30 million follow up to last year's Wellcome Trust Case Control Consortium (WTCCC), the largest ever study of the genetics behind common diseases. The seven-fold increase in the number of samples to be analysed will allow researchers to look at a 25 diseases as well as studying the genetics of learning in children and individuals' responses to statins.
Funded by the Wellcome Trust, this new series of genome-wide association studies will be one of the most ambitious initiatives ever undertaken, bringing together leading research groups from at least 60 institutions internationally (including over 20 from the UK). Over the next two years, working in collaboration with the WTCCC or independently, the research teams are expected to analyse as many as 120 billion pieces of genetic data in the search for the genes underlying diseases such as multiple sclerosis, schizophrenia and asthma.
Researchers will examine between 500,000 and 1 million variants (SNPs) per sample as well as a comprehensive set of copy number variants (CNVs). Both SNPs and CNVs are responsible of the individual variation in our genomes.
"We have now entered a new era of large-scale genetics unthinkable even a few years ago," says Professor Peter Donnelly from the University of Oxford, who will chair the consortium. "Breakthroughs in our understanding of the human genome and rapid advances in sequencing technology mean that we are able to do very powerful analysis much faster and on a vastly bigger scale than ever before."
When the results of the WTCCC were announced in 2007, it was seen as a major breakthrough for medical science and was selected as one of the scientific highlights of the year by a number of the most prestigious scientific journals, including Nature and The Lancet. It identified a number of new genes and regions of the human genome which increase peoples susceptibility to or protect them fr
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| Contact: Craig Brierley c.brierley@wellcome.ac.uk 44-207-611-7329 Wellcome Trust Source:Eurekalert |
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