Article

Xu Z, Taylor JA. SNPinfo: integrating GWAS and candidate gene information into functional SNP selection for genetic association studies. Nucleic Acids Res 37: W600-W605

Epidemiology Branch, National Institute of Environmental Health Sciences, Research Triangle Park, NC 27709, USA.
Nucleic Acids Research (Impact Factor: 9.11). 06/2009; 37(Web Server issue):W600-5. DOI: 10.1093/nar/gkp290
Source: PubMed

ABSTRACT

We have developed a set of web-based SNP selection tools (freely available at http://www.niehs.nih.gov/snpinfo) where investigators can specify genes or linkage regions and select SNPs based on GWAS results, linkage disequilibrium (LD), and predicted functional characteristics of both coding and non-coding SNPs. The algorithm uses GWAS SNP P-value data and finds all SNPs in high LD with GWAS SNPs, so that selection is from a much larger set of SNPs than the GWAS itself. The program can also identify and choose tag SNPs for SNPs not in high LD with any GWAS SNP. We incorporate functional predictions of protein structure, gene regulation, splicing and miRNA binding, and consider whether the alternative alleles of a SNP are likely to have differential effects on function. Users can assign weights for different functional categories of SNPs to further tailor SNP selection. The program accounts for LD structure of different populations so that a GWAS study from one ethnic group can be used to choose SNPs for one or more other ethnic groups. Finally, we provide an example using prostate cancer and demonstrate that this algorithm can select a small panel of SNPs that include many of the recently validated prostate cancer SNPs.

Download full-text

Full-text

Available from: Zongli Xu, Jun 25, 2015
  • Source
    • "For instance , Michel et al. (2010) analyzed 566 SNPs from 14 candidate genes that are believed to be associated with asthma. Xu and Taylor (2009) developed tools to recommend SNPs based on information on gene expression studies , regulatory pathways and functional regions that appear to be linked to the disease. In their example, 1361 SNPs were recommended for a genetic association study on prostate cancer. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Although genome-wide association studies (GWAS) have proven powerful for comprehending the genetic architecture of complex traits, they are challenged by a high dimension of single-nucleotide polymorphisms (SNPs) as predictors, the presence of complex environmental factors, and longitudinal or functional natures of many complex traits or diseases. To address these challenges, we propose a high-dimensional varying-coefficient model for incorporating functional aspects of phenotypic traits into GWAS to formulate a so-called functional GWAS or fGWAS. The Bayesian group lasso and the associated MCMC algorithms are developed to identify significant SNPs and estimate how they affect longitudinal traits through time-varying genetic actions. The model is generalized to analyze the genetic control of complex traits using subject-specific sparse longitudinal data. The statistical properties of the new model are investigated through simulation studies. We use the new model to analyze a real GWAS data set from the Framingham Heart Study, leading to the identification of several significant SNPs associated with age-specific changes of body mass index. The fGWAS model, equipped with the Bayesian group lasso, will provide a useful tool for genetic and developmental analysis of complex traits or diseases.
    Full-text · Article · Sep 2015 · The Annals of Applied Statistics
  • Source
    • "SNPs examined in this study were selected on the basis of the literature data and in silico analysis performed using SNPinfo Web Server (Xu and Taylor, 2009) (please see Supplementary Table 2). This analysis encompassed the gene-transcribed sequences and 3000 bp upstream and 3000 bp downstream regions. "
    [Show abstract] [Hide abstract]
    ABSTRACT: CD28/CTLA-4-CD80/CD86 molecules play an important role in the regulation of T cells activation. Defects in proteins involved in this pathway may lead to the development of autoimmune diseases in which T cells are involved. In this case-control study (336 multiple sclerosis (MS) patients and 322 controls) we investigated the possible association of eleven polymorphisms in CD28, CTLA-4, CD80 and CD86 genes with susceptibility to MS and/or its progression. We also took into account HLA-DRB1* 15:01 status. Moreover, this study aimed to determine the possible gene-gene interactions between examined SNPs associated with the susceptibility to MS and its outcome. Our investigation revealed that in HLA-DRB1* 15:01 negative individuals, G allele in rs231775A > G of CTLA-4 gene was associated with higher risk of multiple sclerosis. Additionally, the association of rs2715267T > G of CD86 gene with MS susceptibility was detected. In details, carriers of G allele at this polymorphic site possessed higher risk of MS in comparison to TT homozygotes. On the other hand, the lower risk of MS was observed in individuals carrying A allele at the rs1599795T > A polymorphic site of CD80. Furthermore, the analysis revealed an interaction between three polymorphisms: rs3116496T > C (CD28), rs6641T > G (CD80) and rs17281995G > C (CD86), associated with the age of MS onset.
    Full-text · Article · Sep 2015 · Journal of Neuroimmunology
  • Source
    • "-511 C Multivessel disease in coronary artery disease [22] -511 T and TT Myocardial infarction and ischemic stroke [17] a SNP ID in database dbSNP. promoter or intronic enhancer regions, and alternative splicing regulation by disrupting exonic splicing enhancers or silencers [28] [29]. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Silent myocardial ischemia (SMI) is a multifactorial and polygenic disorder that results from an excessive inflammatory response. Considering the prominent role of IL-1β, IL-1F10 and IL-1RN as regulators of the inflammatory process and vascular physiology, the aim of the present study was to analyze whether IL-1β, IL-1F10 and IL-1RN single nucleotide polymorphisms (SNPs) are associated with SMI. One polymorphism was associated with risk of SMI. Under co-dominant, recessive and additive models, the IL-1β -511 T>C polymorphism was associated with increased risk of SMI when compared to healthy controls (OR = 4.68, 95%CI = 2.21-9.92, pCCo-dom = 0.0048; OR = 3.97, 95%CI = 1.97-7.99, pCRec = 0.0024; OR = 2.02, 95%CI = 1.41-2.90, pCAdd = 0.0024, respectively). All models were adjusted for gender, age and smoking. Linkage disequilibrium analysis showed four haplotypes (CTCC, CCTC, CCCT and CTCC) with increased frequency in SMI patients when compared to healthy controls (OR = 2.53, 95%CI = 1.47-4.36, pC = 0.0009, OR = 2.34, 95%CI = 1.15-4.74, pC= 0.02, OR = 2.44, 95%CI = 1.14-5.18, pC = 0.02, OR = 5.11, 95%CI = 1.37-19.05, pC= 0.01, respectively). In summary, our data suggest that the IL-1β-511 T>C polymorphism play an important role in the development of SMI in diabetic patients. In addition, in our study was possible to distinguish one protective and four risk haplotypes for development of SMI. Copyright © 2015. Published by Elsevier B.V.
    Full-text · Article · Aug 2015 · Immunology letters
Show more