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He M.,Program in Molecular and Genetic Epidemiology | He M.,Institute of Occupational Medicine | He M.,Huazhong University of Science and Technology | Cornelis M.C.,Program in Molecular and Genetic Epidemiology | And 18 more authors.
Arteriosclerosis, Thrombosis, and Vascular Biology | Year: 2010

Objective: Interleukin-18 (IL-18) is a proinflammatory cytokine involved in the processes of innate and acquired immunities and associated with cardiovascular disease and type 2 diabetes. We sought to identify the common genetic variants associated with IL-18 levels. Methods and results: We performed a 2-stage genome-wide association study among women of European ancestry from the Nurses' Health Study (NHS) and Women's Genome Health Study (WGHS). IL-18 levels were measured by ELISA. In the discovery stage (NHS, n=1523), 7 single-nucleotide polymorphisms (SNPs) at the IL18-BCO2 locus were associated with IL-18 concentrations at the 1×10-5 significance level. The strongest association was found for SNP rs2115763 in the BCO2 gene (P=6.31×10-8). In silico replication in WGHS (435 women) confirmed these findings. The combined analysis of the 2 studies indicated that SNPs rs2115763, rs1834481, and rs7106524 reached a genome-wide significance level (P<5×10-8). Forward selection analysis indicated that SNPs rs2115763 and rs1834481 were independently associated with IL-18 levels (P=0.0002 and 0.0006, respectively). The 2 SNPs together explained 2.9% of variation of plasma IL-18 levels. Conclusion: This study identified several novel variants at the IL18-BCO2 locus associated with IL-18 levels. © 2010 American Heart Association, Inc.

Hutter C.M.,Fred Hutchinson Cancer Research Center | Hutter C.M.,University of Washington | Chang-Claude J.,German Cancer Research Center | Slattery M.L.,University of Utah | And 55 more authors.
Cancer Research | Year: 2012

Genome-wide association studies (GWAS) have identified more than a dozen loci associated with colorectal cancer (CRC) risk. Here, we examined potential effect-modification between single-nucleotide polymorphisms (SNP) at 10 of these loci and probable or established environmental risk factors for CRC in 7,016 CRC cases and 9,723 controls from nine cohort and case - control studies. We used meta-analysis of an efficient empirical-Bayes estimator to detect potential multiplicative interactions between each of the SNPs [rs16892766 at 8q23.3 (EIF3H/UTP23), rs6983267 at 8q24 (MYC), rs10795668 at 10p14 (FLJ3802842), rs3802842 at 11q23 (LOC120376), rs4444235 at 14q22.2 (BMP4), rs4779584 at 15q13 (GREM1), rs9929218 at 16q22.1 (CDH1), rs4939827 at 18q21 (SMAD7), rs10411210 at 19q13.1 (RHPN2), and rs961253 at 20p12.3 (BMP2)] and select major CRC risk factors (sex, body mass index, height, smoking status, aspirin/nonsteroidal antiinflammatory drug use, alcohol use, and dietary intake of calcium, folate, red meat, processed meat, vegetables, fruit, and fiber). The strongest statistical evidence for a gene - environment interaction across studies was for vegetable consumption and rs16892766, located on chromosome 8q23.3, near the EIF3H and UTP23 genes (nominal P interaction = 1.3 × 10 -4; adjusted P = 0.02). The magnitude of the main effect of the SNP increased with increasing levels of vegetable consumption. No other interactions were statistically significant after adjusting for multiple comparisons. Overall, the association of most CRC susceptibility loci identified in initial GWAS seems to be invariant to the other risk factors considered; however, our results suggest potential modification of the rs16892766 effect by vegetable consumption. ©2012 AACR.

Chung C.C.,Laboratory of Translational Genomics | Chung C.C.,U.S. National Institutes of Health | Ciampa J.,U.S. National Institutes of Health | Yeager M.,U.S. National Institutes of Health | And 53 more authors.
Human Molecular Genetics | Year: 2011

Genome-wide association studies have identified prostate cancer susceptibility alleles on chromosome 11q13. As part of the Cancer Genetic Markers of Susceptibility (CGEMS) Initiative, the region flanking the most significant marker, rs10896449, was fine mapped in 10 272 cases and 9123 controls of European origin (10 studies) using 120 common single nucleotide polymorphisms (SNPs) selected by a two-staged tagging strategy using HapMap SNPs. Single-locus analysis identified 18 SNPs below genome-wide significance (P < 10-8) with rs10896449 the most significant (P = 7.94 × 10-19). Multi-locus models that included significant SNPs sequentially identified a second association at rs12793759 [odds ratio (OR) = 1.14, P = 4.76 × 10-5, adjusted P = 0.004] that is independent of rs10896449 and remained significant after adjustment for multiple testing within the region. rs10896438, a proxy of previously reported rs12418451 (r2= 0.96), independent of both rs10896449 and rs12793759 was detected (OR = 1.07, P = 5.92 × 10-3, adjusted P = 0.054). Our observation of a recombination hotspot that separates rs10896438 from rs10896449 and rs12793759, and low linkage disequilibrium (rs10896449-rs12793759, r2= 0.17; r2=10896449-rs10896438, r2= 0.10; rs12793759- rs10896438, r2= 0.12) corroborate our finding of three independent signals. By analysis of tagged SNPs across ~123 kb using next generation sequencing of 63 controls of European origin, 1000 Genome and HapMap data, we observed multiple surrogates for the three independent signals marked by rs10896449 (n = 31), rs10896438 (n = 24) and rs12793759 (n = 8). Our results indicate that a complex architec- ture underlying the common variants contributing to prostate cancer risk at 11q13. We estimate that at least 63 common variants should be considered in future studies designed to investigate the biological basis of the multiple association signals. © The Author 2011. Published by Oxford University Press. All rights reserved.

Lindstrom S.,Program in Molecular and Genetic Epidemiology | Lindstrom S.,Harvard University | Schumacher F.R.,University of Southern California | Cox D.,French Institute of Health and Medical Research | And 42 more authors.
Cancer Epidemiology Biomarkers and Prevention | Year: 2012

Background: One of the goals of personalized medicine is to generate individual risk profiles that could identify individuals in the population that exhibit high risk. The discovery of more than two-dozen independent single-nucleotide polymorphism markers in prostate cancer has raised the possibility for such risk stratification. In this study, we evaluated the discriminative and predictive ability for prostate cancer risk models incorporating 25 common prostate cancer genetic markers, family history of prostate cancer, and age. Methods: We fit a series of risk models and estimated their performance in 7,509 prostate cancer cases and 7,652 controls within the National Cancer Institute Breast and Prostate Cancer Cohort Consortium (BPC3). We also calculated absolute risks based on SEER incidence data. Results: The best risk model (C-statistic = 0.642) included individual genetic markers and family history of prostate cancer. We observed a decreasing trend in discriminative ability with advancing age (P = 0.009), with highest accuracy in men younger than 60 years (C-statistic = 0.679). The absolute ten-year risk for 50-year-old men with a family history ranged from 1.6% (10th percentile of genetic risk) to 6.7% (90th percentile of genetic risk). For men without family history, the risk ranged from 0.8% (10th percentile) to 3.4% (90th percentile). Conclusions: Our results indicate that incorporating genetic information and family history in prostate cancer risk models can be particularly useful for identifying younger men that might benefit from prostate-specific antigen screening. Impact: Although adding genetic risk markers improves model performance, the clinical utility of these genetic risk models is limited. ©2012 AACR.

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