Interpreting gene-association studies

Abstract

Human gene mapping has made a crucial contribution to the positional cloning approach, which has identified the molecular basis of numerous inherited diseases. This research depended on the development of markers and experimental technologies (e.g. RFLPs and microsatellites), genomic resources (e.g. linkage maps) and statistical methods to efficiently and reliably analyse the data. De facto, standards to judge the quality of mapping experiments arose organically with invaluable input from the Human Gene Mapping workshops. Nowadays, the gene mapping community is absorbed with the daunting task of localizing susceptibility genes for common, complex diseases, research which is increasingly dependent on the medium of gene-association studies. Consequently, genotyping techniques are being devised to carry out this work on an unprecedented scale, valuable genomic resources such as dbSNP and HapMap are in their final editions and statistical geneticists are facing the challenge of how to make reliable inferences from the mass of accumulating data. Human Molecular Genetics should play a leading role in this ground-breaking area of research by publishing work of the highest quality which will have a lasting and productive impact on the field. As always, the journal depends on authors and reviewers to ensure that the design, implementation and analysis of these experiments is truly state-of-the-art. However, we are attentive to the widely held concern that an unacceptable proportion of positive reports of gene-association are unreliable, which if unchecked will erode confidence in this powerful experimental approach. The most exciting results which could expose novel molecular mechanisms for complex diseases are inevitably accompanied by some risk of false positive reports. It is appropriate to manage this risk quantitatively, to keep it in balance with the benefits and resist the temptation to be overly stringent and suffocate this promising research area. Well-designed, substantive studies can make important contributions with or without thrilling headline results. With these issues in mind, the following two notes provide guidance for authors and reviewers when reporting the design, execution and analysis of gene-association studies. The emphasison meticulous experimental design and statistical analysiswillmaximizetheimpactofthestudies.Theguidelines are not intended to be a prescriptive checklist or to stifle methodological innovation. However, they do demonstrate the resolve that rigorous standards will be applied to this emerging field by providing a framework upon which future submissions will be assessed.