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Assessing the social meaning, value and implications of research in genomics
  1. Blanca Lumbreras1,
  2. Miquel Porta2,
  3. Ildefonso Hernández-Aguado1
  1. 1Department of Public Health, Universidad Miguel Hernández, Alicante, Spain
  2. 2Institut Municipal d’Investigació Mèdica, Barcelona, Spain
  1. Correspondence to:
 Blanca Lumbreras
 Public Health Department, History of Science and Gynecology, Miguel Hernández University, Elche, Alicante, Spain; blumbreras{at}umh.es

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Genomic discoveries need to be translated to clinical and public health practice

Many health professionals and citizens believe that science is on the cusp of generating a major revolution in medicine as a result of advances in genomics, proteomics and other “-omics” disciplines. However, it has long been clear that other approaches, such as those typical of epidemiology, are essential to fulfil the promise of genomics for clinical and public health practice,1 and should be part of the research agenda. The main objective is the translation of genomic discoveries to clinical and public health practice. However, moving too rapidly to the clinics with immature technologies could jeopardise the promising future of this research, as Ioannidis remarks in the Research Agenda section in this issue.2

As knowledge of the human genome has progressed,3 health professionals and the general population have been pledged dramatic improvements in health.4 Unfortunately, although such discoveries are occurring at a fast pace, the impact that they will have on public health is unclear; there is ample evidence that many research results have been “lost in translation”.5 There has also been some disappointment and impatience that diagnostic tests derived from the human genome have not been applied immediately to clinical diagnosis. However, Ioannidis and Ransohoff, among others,6–8 have already stressed the need to obtain more robust information regarding several methodological concerns before applying these novel insights to clinical and public health practice. The principles of valid study design and sample size, for instance, must not be forgotten in any drive to generate novel data.9 As Ioannidis describes, genetic association studies of complex phenotypes have typically failed to discover susceptibility loci or to replicate other …

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