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NDT Advance Access originally published online on July 4, 2006
Nephrology Dialysis Transplantation 2006 21(10):2775-2779; doi:10.1093/ndt/gfl334
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© The Author [2006]. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

DNA polymorphisms and renal disease: a critical appraisal of studies presented at the annual ERA/EDTA and ASN conferences in 2004 and 2005

Adrian Mondry1,2,*,, Marie Loh1,*, Kevin Ben Laurence1 and Nelson Low1

1Bioinformatics Institute, Agency for Science, Technology and Research, Singapore and 2Department of Surgery, Yong Loo Lin School of Medicine, National University of Singapore, Singapore

Correspondence and offprint requests to: Assoc. Prof. Dr Adrian Mondry, The Bioinformatics Institute, 30 Biopolis Street, #07-01 Matrix Building, Singapore 138671. Email: mondry{at}hotmail.com

Countless studies try to associate single DNA polymorphisms with disease, while there is growing evidence that many of these studies are of flawed design. Based on the Journal of the American Society of Nephrology (JASN) requirements for gene-disease association study quality, the abstracts presented at the two major international nephrology conferences in 2004 and 2005 organized by the European Renal Association/European Dialysis and Transplantation Association (ERA/EDTA) and American Society of Nephrology (ASN) are analysed to show how this problem affects nephrology. Over time, average sample numbers have increased, as have the numbers of abstracts compliant with the JASN requirements. This indicates a potential beneficial effect of the published stricter guidelines on study quality. Alternative options include pre-registration of studies in dedicated databases, secondary assessment of association studies through meta-analysis and participation in network approaches, such as the Human Genome Epidemiology Network (HuGE Net) and the Renal Genome Network.

Keywords: gene association studies; renal disease; renal genome network; sample size; the human genome epidemiology network

* The authors wish it to be known that, in their opinion, the first two authors contributed equally to this work.


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