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Thorax 2005;60:357-359 doi:10.1136/thx.2005.040790
  • Editorial

Genetic association studies in Thorax

  1. I P Hall,
  2. J D Blakey
  1. Division of Therapeutics and Molecular Medicine, Queen’s Medical Centre, University Hospital, Nottingham, UK
  1. Correspondence to:
    Professor I P Hall
    Division of Therapeutics and Molecular Medicine, D Floor, South Block, Queen’s Medical Centre, University Hospital, Nottingham NG7 2UH, UK; ian.hallnottingham.ac.uk

    A guide to assessing the validity of genetic association studies in respiratory disease

    Increasing knowledge regarding the extent of genetic variation in the human genome has led to an explosion of interest in performing genetic association studies in complex diseases. Well designed studies have the potential to provide functionally relevant data on the pathophysiology of disease initiation and severity.1 Unfortunately, this field has acquired a bad reputation over recent years because of problems with poor design and variable replication of findings.2,3 Because such studies are relatively easy to undertake when one has access to a population of patients with disease, the number of such studies has increased markedly: Thorax now receives, on average, eight each month. As there are a number of common flaws present in many of these studies, we felt it would be helpful to publish some broad guidance on the subject. While Thorax will always be keen to receive high quality manuscripts dealing with genetic studies in respiratory disease, in the future it is unlikely that submitted manuscripts will be sent out for further review if they do not conform to the guidance contained within this editorial.

    STUDY POPULATION SIZE

    The majority of submitted genetic association studies use a case-control design, so this is the focus of this editorial. The limiting factor in recruitment is usually the number of cases available to study. There are some advantages in increasing the number of controls (that is, having more than one matched control for each case): in practice 2:1 matching of controls to cases often provides the most efficient design for relatively common diseases. For any given genetic association study an initial power calculation should be undertaken to determine the power of the study to detect effects. For most of the genetic factors contributing to common complex diseases, published …

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