Dissecting complex genetic diseases
Mounting evidence indicates that most complex, prevelant and chronic diseases are caused by genetic, environmental and lifestyle factors. The EU-funded 'Hypergenes' project focused on defining a comprehensive genetic epidemiological model of such complex traits. To achieve this, partners combined high-throughput genotyping with sophisticated statistical–mathematical modelling analyses. Hypertension (EH) and intermediate phenotypes of hypertension-dependent and -associated target organ damages (TODs) served as models. Over 4 000 subjects with EH, TOD or other endophenotypes relevant to hypertension were analysed to produce a list of associated single nucleotide polymorphisms (SNPs). SNPs are small variations in DNA code. The researchers found hundreds of significant associations, which only partially overlapped with results from previous studies. The best 15 000 SNPs were subsequently used to build a custom array that validated the findings in an additional independent sample of 8 000 subjects. The parts of the genome that showed promising results were sequenced to obtain a more detailed understanding of the nucleotide sequences in question. The consortium also directed efforts at the storing of molecular, clinical and environmental data with the development of a biomedical information infrastructure (BII). Software tools for bioclinical data mining and SNP association analysis were also established. These helped to build a risk prediction disease model where each gene is represented by one SNP. The Hypergenes genetic epidemiological model of complex traits is expected to help translate genetic findings into improved diagnostics, early detection, prevention and, eventually, personalised treatment.