A novel method to test associations between a weighted combination of phenotypes and genetic variants

Many complex diseases like diabetes, hypertension, metabolic syndrome, et cetera, are measured by multiple correlated phenotypes. However, most genome-wide association studies (GWAS) focus on one phenotype of interest or study multiple phenotypes separately for identifying genetic variants associate...

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Published inPloS one Vol. 13; no. 1; p. e0190788
Main Authors Zhu, Huanhuan, Zhang, Shuanglin, Sha, Qiuying
Format Journal Article
LanguageEnglish
Published United States Public Library of Science 12.01.2018
Public Library of Science (PLoS)
Subjects
Biology and Life Sciences
Breast cancer
Diabetes
Diabetes mellitus
Disease
Genetic Variation
Genetics
Genome-wide association studies
Genome-Wide Association Study
Genomes
Genotype & phenotype
Humans
Hypertension
Metabolic syndrome X
Methods
Models, Genetic
Performance evaluation
Phenotype
Physical Sciences
Population
Power
Research and Analysis Methods
Research methodology
Risk factors
Simulation
Single nucleotide polymorphisms
Studies
Survival analysis
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Summary:Many complex diseases like diabetes, hypertension, metabolic syndrome, et cetera, are measured by multiple correlated phenotypes. However, most genome-wide association studies (GWAS) focus on one phenotype of interest or study multiple phenotypes separately for identifying genetic variants associated with complex diseases. Analyzing one phenotype or the related phenotypes separately may lose power due to ignoring the information obtained by combining phenotypes, such as the correlation between phenotypes. In order to increase statistical power to detect genetic variants associated with complex diseases, we develop a novel method to test a weighted combination of multiple phenotypes (WCmulP). We perform extensive simulation studies as well as real data (COPDGene) analysis to evaluate the performance of the proposed method. Our simulation results show that WCmulP has correct type I error rates and is either the most powerful test or comparable to the most powerful test among the methods we compared. WCmulP also has an outstanding performance for identifying single-nucleotide polymorphisms (SNPs) associated with COPD-related phenotypes.
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Competing Interests: The authors have declared that no competing interests exist.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0190788