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United States Department of Agriculture

Agricultural Research Service

Title: Turning the pump handle: Evolving methods for integrating the evidence on gene-disease association)

Author
item Higgins, Julian
item Little, Julian
item Ionnidis, John
item Bray, Molly
item Manolio, Teri
item Smeeth, Liam
item Sterne, Jonathan
item Anagostelis, Betsy
item Butterworth, Adam
item Danesh, John
item Dezateux, Carol
item Gallacher, John
item Gwinn, Marta
item Lewis, Sarah
item Minelli, Cosetta
item Pharoah, Paul
item Salanti, Georgia
item Sanderson, Simon
item Smith, Lesley
item Taioli, Emanuela
item Thompson, John
item Thompson, Simon
item Walker, Neil
item Zimmern, Ron
item Khoury, Muin

Submitted to: American Journal of Epidemiology
Publication Type: Review Article
Publication Acceptance Date: 8/1/2007
Publication Date: 10/15/2007
Citation: Higgins, J.P., Little, J., Ionnidis, J.P., Bray, M.S., Manolio, T.A., Smeeth, L., Sterne, J.A., Anagostelis, B., Butterworth, A.S., Danesh, J., Dezateux, C., Gallacher, J.E., Gwinn, M., Lewis, S.J., Minelli, C., Pharoah, P.D., Salanti, G., Sanderson, S., Smith, L.A., Taioli, E., Thompson, J.R., Thompson, S.G., Walker, N., Zimmern, R.L., Khoury, M.J. 2007. Turning the pump handle: Evolving methods for integrating the evidence on gene-disease association. American Journal of Epidemiology. 166(8):863-866.

Interpretive Summary:

Technical Abstract: Recent findings from genome-wide association studies have demonstrated their considerable potential for identifying genetic determinants of common diseases of public health significance such as cancer, heart disease, and diabetes, but they have also highlighted the continued importance of targeted genotyping to replicate genome-wide association findings. Approaches to the integration of evidence in human genome epidemiology have evolved rapidly in the last few years. The combination of results from multiple studies, often known as meta-analysis, has a key role both in enhancing power and in characterizing relative risks. As evidence accumulates on genetic variants that confer identifiable effects on disease susceptibility, so does the need to summarize the evidence in digestible and accessible formats. Here, we describe how the Human Genome Epidemiology Network (HuGENet) is keeping abreast of developments in methods for collating and synthesizing the evidence.

Last Modified: 8/24/2016
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