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European Network for Genetic and Genomic Epidemiology

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Genomic epidemiology to identify disease biomarkers

Large-scale genome profiling has the potential to identify diagnostic indicators for common diseases that will help us to understand risk factors, disease progression and why people differ in responses to treatment.

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Advances in genomic technology permit the faster analysis of genetic sequences, thereby enabling the identification of genetic variations that contribute to disease and uncovering the effects of the complex interactions of genes. This offers the potential to study the underlying mechanisms of many diseases and lead to the development of targeted therapeutic interventions. Based on this, the EU-funded ′European network for genetic and genomic epidemiology′ (Engage) effort wished to perform large-scale integrated genetic association analyses in order to identify novel disease-susceptibility variants that would otherwise be undetectable in individual studies. Project partners developed new computational tools to support data sharing and the harmonisation of cohort phenotypes. Meta-analysis of information from cohorts of over 600 000 subjects and 100 000 genome-wide association data identified many hundreds of genetic loci influencing medically-significant traits, ranging from type 2 diabetes and obesity, to smoking behaviour and birth weight. These genetic discoveries were used to define the molecular mechanisms through which they impact disease, but the most challenging task was to track the specific causal alleles. Phenotypic efforts focused on exploring the wider biological consequences of associated variants, and the impact of environmental exposures. Although the full clinical impact of Engage discoveries requires time to be seen, the finding that C reactive protein (CRP) is a useful diagnostic biomarker for diabetes constitutes an important example of this potential. The continuation of these efforts after the Engage project will ensure the future discovery of disease-associated genomic variants and better understanding of biological mechanisms in common complex diseases. Please see:

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