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Studying disease associations

Jonathan B Weitzman

Genome Biology 2001, 2:spotlight-20011023-03  doi:10.1186/gb-spotlight-20011023-03

The electronic version of this article is the complete one and can be found online at:


Published:23 October 2001

© 2001 BioMed Central Ltd

Research news

In the Advanced Online Publication of Nature Genetics, John Ioannidis and colleagues at the University of Ioannina School of Medicine, Ioannina, Greece, describe a study to determine the reliability of disease association and genetic linkage reports (DOI:10.1038/ng749). They assembled data from published reports of 36 different disease associations, ranging from schizophrenia to hypertension. They used meta-analysis to explore the diversity and discrepancies between different studies. In 39% of cases they found statistically relevant heterogeneity between studies. The first published reports (often appearing in high impact-factor journals) tended to give more impressive disease association, which became less prominent in subsequent reports. In some cases the accumulation of additional data led to increased statistical significance of the genetic association. Ioannidis et al. conclude that meta-analysis is useful for the cautious evaluation of genetic association studies and human genome epidemiology.

References

  1. [http://genetics.nature.com] webcite

    Nature Genetics

  2. [http://www.uoi.gr] webcite

    University of Ioannina

  3. Summing up evidence: one answer is not always enough

    PubMed Abstract | Publisher Full Text OpenURL

  4. Human genome epidemiologic reviews: the beginning of something HuGE

    PubMed Abstract OpenURL