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American Journal of Epidemiology - current issue

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Towards Reducing Disparities in Disparities Research
Rowland Hogue, C. J.
Discovery Properties of Genome-wide Association Signals From Cumulatively Combined Data Sets
Pereira, T. V., Patsopoulos, N. A., Salanti, G., Ioannidis, J. P. A. Genetic effects for common variants affecting complex disease risk are subtle. Single genome-wide association (GWA) studies are typically underpowered to detect these effects, and combination of several GWA data sets is needed to enhance discovery. The authors investigated the properties of the discovery process in simulated cumulative meta-analyses of GWA study-derived signals allowing for potential genetic model misspecification and between-study heterogeneity. Variants with null effects on average (but also between-data set heterogeneity) could yield false-positive associations with seemingly homogeneous effects. Random effects had higher than appropriate false-positive rates when there were few data sets. The log-additive model had the lowest false-positive rate. Under heterogeneity, random-effects meta-analyses of 2–10 data sets averaging 1,000 cases/1,000 controls each did not increase power, or the meta-analysis was even less powerful than a single study (power desert). Upward bias in effect estimates and underestimation of between-study heterogeneity were common. Fixed-effects calculations avoided power deserts and maximized discovery of association signals at the expense of much higher false-positive rates. Therefore, random- and fixed-effects models are preferable for different purposes (fixed effects for initial screenings, random effects for generalizability applications). These results may have broader implications for the design and interpretation of large-scale multiteam collaborative studies discovering common gene variants.

American Journal of Epidemiology - recent issues

Table of contents

Subscriptions

Editorial Board

Cover

Towards Reducing Disparities in Disparities Research
Rowland Hogue, C. J.
Discovery Properties of Genome-wide Association Signals From Cumulatively Combined Data Sets
Pereira, T. V., Patsopoulos, N. A., Salanti, G., Ioannidis, J. P. A. Genetic effects for common variants affecting complex disease risk are subtle. Single genome-wide association (GWA) studies are typically underpowered to detect these effects, and combination of several GWA data sets is needed to enhance discovery. The authors investigated the properties of the discovery process in simulated cumulative meta-analyses of GWA study-derived signals allowing for potential genetic model misspecification and between-study heterogeneity. Variants with null effects on average (but also between-data set heterogeneity) could yield false-positive associations with seemingly homogeneous effects. Random effects had higher than appropriate false-positive rates when there were few data sets. The log-additive model had the lowest false-positive rate. Under heterogeneity, random-effects meta-analyses of 2–10 data sets averaging 1,000 cases/1,000 controls each did not increase power, or the meta-analysis was even less powerful than a single study (power desert). Upward bias in effect estimates and underestimation of between-study heterogeneity were common. Fixed-effects calculations avoided power deserts and maximized discovery of association signals at the expense of much higher false-positive rates. Therefore, random- and fixed-effects models are preferable for different purposes (fixed effects for initial screenings, random effects for generalizability applications). These results may have broader implications for the design and interpretation of large-scale multiteam collaborative studies discovering common gene variants.

Epidemiology and Infection - Current Issue

Volume 137 Issue 12
Tue, 01 Dec 2009 00:00:00 -0000
Epidemiology and Infection, Volume 137 Issue 12 Increased frequency in 2007 - now 8 issues per year! Epidemiology and Infection publishes original reports and reviews on all aspects of infection in humans and animals. Particular emphasis is given to the epidemiology, prevention and control of infectious diseases. The field covered is broad and includes the zoonoses, tropical infections, food hygiene, vaccine studies, statistics and the clinical, social and public-health aspects of infectious disease. Papers covering microbiology and immunology which have an epidemiological relevance are part of this broad field. Papers come from medical and veterinary scientists worldwide. It has become the key periodical in which to find the latest reports on recently discovered infections and new technology. For those concerned with policy and planning for the control of infections, the papers on mathematical modelling of epidemics caused by historical, current and emergent infections, will be of particular value. To celebrate 100 years of the journal, a series of important papers has been selected and each, together with a modern commentary on the paper by an expert, will be published on-line. This journal has now moved over to electronic submission, using the Scholar One system. Click here to go to the submission website. Guidance on how to upload your manuscript is available on the site by clicking "User Tutorials". Online manuscript submission (now) available, please go to http://mc.manuscriptcentral.com/cup/hyg
HYG volume 137 issue 12 Cover and Front matter
Miscellaneous Epidemiology and Infection, Volume 137 Issue 12 , pp f1-f2Abstract

Latest Issue of International Journal of Medical Microbiology

Editorial - ETOX turned twenty
Sebo P.
Pathogenomics of mobile genetic elements of toxigenic bacteria
Hacker J.Hochhut B.Middendorf B.Schneider G.Buchrieser C.Gottschalk G.Dobrindt U.

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