A road map for efficient and reliable human genome epidemiology

  title={A road map for efficient and reliable human genome epidemiology},
  author={John P. A. Ioannidis and Marta Gwinn and Julian Little and Julian P. T. Higgins and Jonine L. Bernstein and Paolo Boffetta and Melissa Bondy and Molly S. Bray and Paul E. Brenchley and Patricia A. Buffler and Juan Pablo Casas and Anand P Chokkalingam and John Danesh and George Davey Smith and Siobhan M. Dolan and Ross Duncan and Nelleke A. Gruis and Patricia Hartge and Mia Hashibe and David J. Hunter and Marjo-Riitta Jarvelin and Beatrice Malmer and Demetrius M. Maraganore and Julia A Newton-Bishop and Thomas R O'Brien and Gloria M. Petersen and Elio Riboli and Georgia Salanti and Daniela Seminara and Liam Smeeth and Emanuela Taioli and Nicholas John Timpson and Andr{\'e} G. Uitterlinden and Paolo Vineis and Nicholas J. Wareham and Deborah M Winn and Ron L. Zimmern and Muin J. Khoury},
  journal={Nature Genetics},
Networks of investigators have begun sharing best practices, tools and methods for analysis of associations between genetic variation and common diseases. A Network of Investigator Networks has been set up to drive the process, sponsored by the Human Genome Epidemiology Network. A workshop is planned to develop consensus guidelines for reporting results of genetic association studies. Published literature databases will be integrated, and unpublished data, including 'negative' studies, will be… 
A navigator for human genome epidemiology
The HuGE Navigator allows users to navigate and search the database in an integrated manner by using the six applications discussed below, which have developed data and text mining algorithms to create a knowledge base for exploring genetic associations, candidate gene selection and investigator networks.
Development and application of Human Genome Epidemiology
In this review, the development of Human Genome Epidemiology, research content, the construction and structure of relevant network, research standards, as well as the existing results and problems are briefly outlined.
Genome-Wide Association Studies, Field Synopses, and the Development of the Knowledge Base on Genetic Variation and Human Diseases
Current experience and challenges on integrating evidence from genome-wide association studies and candidate gene studies, and a vision of collaboration that builds reliable cumulative evidence for genetic associations with common complex diseases and a transparent, distributed, authoritative knowledge base on genetic variation and human health are summarized.
Into the post-HapMap era.
Assessment of cumulative evidence on genetic associations: interim guidelines.
A proposed semi-quantitative index assigns three levels for the amount of evidence, extent of replication, and protection from bias, and also generates a composite assessment of 'strong', 'moderate' or 'weak' epidemiological credibility.
Combining molecular and genetic data from different sources.
This chapter will discuss ways of combining evidence from different sources using meta-analysis methods, including systematic reviews and meta-analyses in human genome epidemiology, which comprise the bulk of the available evidence in molecular epidemiology where these methods have been applied to date.
Genetic epidemiology with a Capital E, ten years after
An online informatics tool, the HuGE Navigator, is used to describe the growth in the field in the past decade and extends Duncan Thomas' capital E to include “Evaluation” as the tools of epidemiology are increasingly used to assess how genome‐based information can be applied in medicine and public health.
Genome scanning by composite likelihood.
This preliminary analysis leads to five inferences: permutation of cases and controls provides a test of association free of autocorrelation; two hypotheses give similar estimates, but one is consistently more accurate; the minimal data for successful meta-analysis are inferred; and power is robust for all genomic factors except minor-allele frequency.
Quantifying realistic sample size requirements for human genome epidemiology
A string of recent successes indicates that if sample sizes are large enough, it is possible to identify and replicate genetic associations with common complex diseases, but it is still unclear what ‘ large enough ’ really means.


A network of investigator networks in human genome epidemiology.
The authors propose the creation of a network of networks that include groups of investigators collecting data for human genome epidemiology research, and aims to register these networks, teams, and investigators.
Commentary: meta-analysis of individual participants' data in genetic epidemiology.
The authors summarize their experience in the conduct of meta-analysis of individual participants' data with time-to-event analyses in the field of genetic epidemiology and find the MIPD method is a useful tool to help clarify the role of candidate genes in complex human diseases.
Guidelines for association studies in Human Molecular Genetics.
The present guidelines aim at helping authors and reviewers to make sure that the published paper is self-contained in terms of providing all the details needed for readers to be able to interpret the results.
The human genome project is complete. How do we develop a handle for the pump?
An overview of the experience gained in integrating evidence in the Human Genome Epidemiology (HuGE) reviews is provided and changes that may encourage more investigators to contribute reviews and to respond to changes in the character of the evidence are suggested.
Genetic variation and cancer: improving the environment for publication of association studies.
The completion of a working draft of the human genome and the rapidly expanding knowledge base that has accompanied it are having a major impact on our understanding of the role of genes in human
Local Literature Bias in Genetic Epidemiology: An Empirical Evaluation of the Chinese Literature
Evidence is provided for the interplay of selective reporting and language biases in human genome epidemiology that point to the need for a global, transparent, comprehensive outlook in molecular population genetics and epidemiologic studies in general.
Proposed guidelines for papers describing DNA polymorphism-disease associations
Guidelines are proposed that are intended to promote the publication of scientifically meaningful disease association studies through the introduction of sensible methodological standards.
Minimum information about a microarray experiment (MIAME)—toward standards for microarray data
The ultimate goal of this work is to establish a standard for recording and reporting microarray-based gene expression data, which will in turn facilitate the establishment of databases and public repositories and enable the development of data analysis tools.
Publication Environment and Broad Investigation of the Genome
  • S. Wacholder
  • Biology
    Cancer Epidemiology Biomarkers & Prevention
  • 2005
The days when most studies report results on a single gene, or even several genes, are almost over, and CEBP editors need to decide how to handle reports from broad investigations of the vast number of genes.
Cancer Epidemiol Biomarkers Prev
  • Psychology
  • 2004
We would like to introduce a new section in Cancer, Epidemiology, Biomarkers and Prevention (CEBP) called “Looking farther afield . . . .” This editorial feature will involve summarizing one or more