Search our Database of Scientific Publications and Authors

I’m looking for a

    Details and Download Full Text PDF:
    Integrative pathway analysis of genome-wide association studies and gene expression data in prostate cancer.

    • Authors:
    • Peilin Jia
      Vanderbilt University School of Medicine
      Nashville | United States
      Yang Liu
      Chinese PLA General Hospital
      Zhongming Zhao
      Vanderbilt University School of Medicine
      United States
    BMC Syst Biol 2012 17;6 Suppl 3:S13. Epub 2012 Dec 17.
    Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, TN, USA.
    Background: Pathway analysis of large-scale omics data assists us with the examination of the cumulative effects of multiple functionally related genes, which are difficult to detect using the traditional single gene/marker analysis. So far, most of the genomic studies have been conducted in a single domain, e.g., by genome-wide association studies (GWAS) or microarray gene expression investigation. A combined analysis of disease susceptibility genes across multiple platforms at the pathway level is an urgent need because it can reveal more reliable and more biologically important information.

    Results: We performed an integrative pathway analysis of a GWAS dataset and a microarray gene expression dataset in prostate cancer. We obtained a comprehensive pathway annotation set from knowledge-based public resources, including KEGG pathways and the prostate cancer candidate gene set, and gene sets specifically defined based on cross-platform information. By leveraging on this pathway collection, we first searched for significant pathways in the GWAS dataset using four methods, which represent two broad groups of pathway analysis approaches. The significant pathways identified by each method varied greatly, but the results were more consistent within each method group than between groups. Next, we conducted a gene set enrichment analysis of the microarray gene expression data and found 13 pathways with cross-platform evidence, including "Fc gamma R-mediated phagocytosis" (P GWAS = 0.003, P expr < 0.001, and P combined = 6.18 × 10(-8)), "regulation of actin cytoskeleton" (P GWAS = 0.003, P expr = 0.009, and P combined = 3.34 × 10(-4)), and "Jak-STAT signaling pathway" (P GWAS = 0.001, P expr = 0.084, and P combined = 8.79 × 10(-4)).

    Conclusions: Our results provide evidence at both the genetic variation and expression levels that several key pathways might have been involved in the pathological development of prostate cancer. Our framework that employs gene expression data to facilitate pathway analysis of GWAS data is not only feasible but also much needed in studying complex disease.
    PDF Download - Full Text Link
    ( Please be advised that this article is hosted on an external website not affiliated with
    Source Status ListingPossible

    Similar Publications

    Gene, pathway and network frameworks to identify epistatic interactions of single nucleotide polymorphisms derived from GWAS data.
    BMC Syst Biol 2012 17;6 Suppl 3:S15. Epub 2012 Dec 17.
    Center for Proteomics and Bioinformatics, Case Western Reserve University, Cleveland, OH, USA.
    Background: Interactions among genomic loci (also known as epistasis) have been suggested as one of the potential sources of missing heritability in single locus analysis of genome-wide association studies (GWAS). The computational burden of searching for interactions is compounded by the extremely low threshold for identifying significant p-values due to multiple hypothesis testing corrections. Utilizing prior biological knowledge to restrict the set of candidate SNP pairs to be tested can alleviate this problem, but systematic studies that investigate the relative merits of integrating different biological frameworks and GWAS data have not been conducted. Read More
    Genome-wide genetic analyses highlight mitogen-activated protein kinase (MAPK) signaling in the pathogenesis of endometriosis.
    Hum Reprod 2017 04;32(4):780-793
    Endometriosis CaRe Centre, Nuffield Department of Obstetrics and Gynaecology, University of Oxford, Women's Centre, John Radcliffe Hospital, Oxford, UK.
    Study Question: Do genome-wide association study (GWAS) data for endometriosis provide insight into novel biological pathways associated with its pathogenesis?

    Summary Answer: GWAS analysis uncovered multiple pathways that are statistically enriched for genetic association signals, analysis of Stage A disease highlighted a novel variant in MAP3K4, while top pathways significantly associated with all endometriosis and Stage A disease included several mitogen-activated protein kinase (MAPK)-related pathways.

    What Is Known Already: Endometriosis is a complex disease with an estimated heritability of 50%. To date, GWAS revealed 10 genomic regions associated with endometriosis, explaining <4% of heritability, while half of the heritability is estimated to be due to common risk variants. Read More
    Detecting discordance enrichment among a series of two-sample genome-wide expression data sets.
    BMC Genomics 2017 01 25;18(Suppl 1):1050. Epub 2017 Jan 25.
    Department of Medicine, Division of Genomic Medicine, The George Washington University Medical Center, Washington, 20037, D.C., USA.
    Background: With the current microarray and RNA-seq technologies, two-sample genome-wide expression data have been widely collected in biological and medical studies. The related differential expression analysis and gene set enrichment analysis have been frequently conducted. Integrative analysis can be conducted when multiple data sets are available. Read More
    Association between Prostinogen (KLK15) genetic variants and prostate cancer risk and aggressiveness in Australia and a meta-analysis of GWAS data.
    PLoS One 2011 23;6(11):e26527. Epub 2011 Nov 23.
    Australian Prostate Cancer Research Centre-Queensland and Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Queensland, Australia.
    Background: Kallikrein 15 (KLK15)/Prostinogen is a plausible candidate for prostate cancer susceptibility. Elevated KLK15 expression has been reported in prostate cancer and it has been described as an unfavorable prognostic marker for the disease.

    Objectives: We performed a comprehensive analysis of association of variants in the KLK15 gene with prostate cancer risk and aggressiveness by genotyping tagSNPs, as well as putative functional SNPs identified by extensive bioinformatics analysis. Read More