Title

Authors

Affiliation

¹Dept of Bioclinical Informatics, Tohoku Medical Megabank Organization, Tohoku University; ²Medical IT Center, School of Medicine, Tohoku University; ³Dept. of Bioinformatics, Medical Research Institute, Tokyo Medical and Dental University

Email

ogishima@sysmedbio.org; *Corresponding author

Article Type

Prediction model

Date

Received March 17, 2015; Accepted March 21, 2015; Published March 31, 2015

Genome-wide association studies (GWAS) and linkage analysis has identified many single nucleotide polymorphisms (SNPs) related to disease. There are many unknown SNPs whose minor allele frequencies (MAFs) as low as 0.005 having intermediate effects with odds ratio between 1.5~3.0. Low frequency variants having intermediate effects on disease pathogenesis are believed to have complex interactions with environmental factors called gene-environment interactions (GxE). Hence, we describe a model using 3D Manhattan plot called GxE landscape plot to visualize the association of p-values for gene-environment interactions (GxE). We used the Gene-Environment iNteraction Simulator 2 (GENS2) program to simulate interactions between two genetic loci and one environmental factor in this exercise. The dataset used for training contains disease status, gender, 20 environmental exposures and 100 genotypes for 170 subjects, and p-values were calculated by Cochran-Mantel-Haenszel chi-squared test on known data. Subsequently, we created a 3D GxE landscape plot of negative logarithm of the association of p-values for all the possible combinations of genetic and environmental factors with their hierarchical clustering. Thus, the GxE landscape plot is a valuable model to predict association of p-values for GxE and similarity among genotypes and environments in the context of disease pathogenesis.

Abbreviation

GxE: Gene-environment interactions; GWAS: Genome-wide association study; MAFs: Minor allele frequencies; SNPs: Single nucleotide polymorphisms; EWAS: Environment-wide association study; FDR: False discovery rate; JPT+CHB: HapMap population of Japanese in Tokyo, Japan + Han Chinese in Beijing, China.

Citation

Nagaie et al. Bioinformation 11(3): 161-164 (2015)
 

Edited by

P Kangueane

ISSN

0973-2063

Publisher

Biomedical Informatics

License

This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.