A post-GWAS analysis of predicted regulatory variants and tuberculosis susceptibility

Utilizing data from published tuberculosis (TB) genome-wide association studies (GWAS), we use a bioinformatics pipeline to detect all polymorphisms in linkage disequilibrium (LD) with variants previously implicated in TB disease susceptibility. The probability that these variants had a predicted regulatory function was estimated using RegulomeDB and Ensembl's Variant Effect Predictor. Subsequent genotyping of these 133 predicted regulatory polymorphisms was performed in 400 admixed South African TB cases and 366 healthy controls in a population-based case-control association study to fine-map the causal variant. We detected associations between tuberculosis susceptibility and six intronic polymorphisms located in MARCO, IFNGR2, ASHAS2, ACACA, NISCH and TLR10. Our post- GWAS approach demonstrates the feasibility of combining multiple TB GWAS datasets with linkage information to identify regulatory variants associated with this infectious disease.

Description

CITATION: Uren, C., et al. 2017. A post-GWAS analysis of predicted regulatory variants and tuberculosis susceptibility. PLoS ONE, 2(4):1-12, doi:10.1371/journal.pone.0174738.
The original publication is available at http://journals.plos.org/plosone

Keywords

Tuberculosis -- Susceptibility, Tuberculosis -- Genome-wide association study, Tuberculosis -- Variants, Tuberculosis -- Genetic factors

Citation

Uren, C., et al. 2017. A post-GWAS analysis of predicted regulatory variants and tuberculosis susceptibility. PLoS ONE, 2(4):1-12, doi:10.1371/journal.pone.0174738

URI

http://hdl.handle.net/10019.1/101505

Collections

Research Articles (Molecular Biology and Human Genetics)

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