fulltext.study @t Gmail

Using propensity score adjustment method in genetic association studies

Paper ID Volume ID Publish Year Pages File Format Full-Text
14908 1361 2016 11 PDF Available
Title
Using propensity score adjustment method in genetic association studies
Abstract

•Propensity score adjustment method (PSAM) is proposed as a tool for dimension reduction to improve the power for single locus studies through an estimated propensity score (PS).•PS is used to adjust for the effect of SNPs that influence the marginal association of a candidate marker.•PS adjusts for influence from these SNPs while regressing disease status on the target-genetic locus.•These SNPs might be in linkage disequilibrium (LD) and/or epistatic with the target-SNP and have a joint interactive influence on the disease under study.•PSAM was able to identify significant SNPs from the GAW16 NARAC dataset by reducing the original trend-test p-values which were further found to be associated with immunity and inflammation.

BackgroundThe statistical tests for single locus disease association are mostly under-powered. If a disease associated causal single nucleotide polymorphism (SNP) operates essentially through a complex mechanism that involves multiple SNPs or possible environmental factors, its effect might be missed if the causal SNP is studied in isolation without accounting for these unknown genetic influences. In this study, we attempt to address the issue of reduced power that is inherent in single point association studies by accounting for genetic influences that negatively impact the detection of causal variant in single point association analysis. In our method we use propensity score (PS) to adjust for the effect of SNPs that influence the marginal association of a candidate marker. These SNPs might be in linkage disequilibrium (LD) and/or epistatic with the target-SNP and have a joint interactive influence on the disease under study. We therefore propose a propensity score adjustment method (PSAM) as a tool for dimension reduction to improve the power for single locus studies through an estimated PS to adjust for influence from these SNPs while regressing disease status on the target-genetic locus. The degree of freedom of such a test is therefore always restricted to 1.ResultsWe assess PSAM under the null hypothesis of no disease association to affirm that it correctly controls for the type-I-error rate (<0.05). PSAM displays reasonable power (>70%) and shows an average of 15% improvement in power as compared with commonly-used logistic regression method and PLINK under most simulated scenarios. Using the open-access multifactor dimensionality reduction dataset, PSAM displays improved significance for all disease loci. Through a whole genome study, PSAM was able to identify 21 SNPs from the GAW16 NARAC dataset by reducing their original trend-test p-values from within 0.001 and 0.05 to p-values less than 0.0009, and among which 6 SNPs were further found to be associated with immunity and inflammation.ConclusionsPSAM improves the significance of single-locus association of causal SNPs which have had marginal single point association by adjusting for influence from other SNPs in a dataset. This would explain part of the missing heritability without increasing the complexity of the model due to huge multiple testing scenarios. The newly reported SNPs from GAW16 data would provide evidences for further research to elucidate the etiology of rheumatoid arthritis. PSAM is proposed as an exploratory tool that would be complementary to other existing methods. A downloadable user friendly program, PSAM, written in SAS, is available for public use.

Graphical abstractThe proposed propensity score adjustment method (PSAM) is a tool to improve power for single locus association studies through an estimated propensity-score (PS) by adjusting for SNPs that might be in linkage disequilibrium (LD) and/or epistatic with the target-SNP while regressing disease status on target SNP. The degree of freedom is always restricted to 1.Figure optionsDownload full-size imageDownload as PowerPoint slide

Keywords
PS, propensity Score; PSAM, propensity score adjustment method; ULRM, univariate logistic regression method; S-MLRM, stepwise-multivariate logistic regressioin method; GWAS, Genome Wide Association studies; GAW, genetic analysis workshop; NARAC, North Ame
First Page Preview
Using propensity score adjustment method in genetic association studies
Get Full-Text Now
Don't Miss Today's Special Offer
Price was $35.95
You save - $31
Price after discount Only $4.95
100% Money Back Guarantee
Full-text PDF Download
Online Support
Any Questions? feel free to contact us
Publisher
Database: Elsevier - ScienceDirect
Journal: Computational Biology and Chemistry - Volume 62, June 2016, Pages 1–11
Authors
, , , , , ,
Subjects
Physical Sciences and Engineering Chemical Engineering Bioengineering
Get Full-Text Now
Don't Miss Today's Special Offer
Price was $35.95
You save - $31
Price after discount Only $4.95
100% Money Back Guarantee
Full-text PDF Download
Online Support
Any Questions? feel free to contact us