Pitfall of genome-wide association studies: Sources of inconsistency in genotypes and their effects

Huixiao Hong, Lei Xu, Zhenqiang Su, Jie Liu, Weigong Ge, Jie Shen, Hong Fang, Roger Perkins, Leming Shi, Weida Tong

Bioinformatics Graduate Program, University of Arkansas at Little Rock/University of Arkansas for Medical Sciences, Little Rock, AR 72079, USA.
Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR 72079, USA.
ICF International at National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR 72079, USA.
School of Materials Science and Engineering, Chang’an University, Xi’an, China.

DOI: 10.4236/jbise.2012.510069                

Abstract

Personalized medicine will improve heath outcomes and patient satisfaction. However, implementing personalized medicine based on individuals’ biological information is far from simple, requiring genetic biomarkers that are mainly developed and used by the pharmaceutical companies for selecting those patients who benefit more, or have less risk of adverse drug reactions, from a particular drug. Genome-wide Association Studies (GWAS) aim to identify genetic variants across the human genome that might be utilized as genetic biomarkers for diagnosis and prognosis. During the last several years, high-density genotyping SNP arrays have facilitated GWAS that successfully identified common genetic variants associated with a variety of phenotypes. However, each of the identified genetic variants only explains a very small fraction of the underlying genetic contribution to the studied phenotypic trait. The replication studies demonstrated that only a small portion of associated loci in the initial GWAS can be replicated, even within the same populations. Given the complexity of GWAS, multiple sources of Type I (false positive) and Type II (false negative) errors exist. The inconsistency in genotypes that caused either by the genotypeing experiment or by genotype calling process is a major source of the false GWAS findings. Accurate and reproducible genotypes are paramount as inconsistency in genotypes can lead to an inflation of false associations. This article will review the sources of inconsistency in genotypes and discuss its effect in GWAS findings.

Keywords

Genotype; Association; Reproducibility; Inconsistency; Batch Effect; Genotyping Platform

Conflicts of Interest

The authors declare no conflicts of interest.

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