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Full-Text Articles in Medicine and Health Sciences
A Pooled Analysis Of Smoking And Colorectal Cancer: Timing Of Exposure And Interactions With Environmental Factors
Shuo Jiao
Background:Considerable evidence suggests that cigarette smoking is associated with a higher risk of colorectal cancer. What is unclear, however, is the impact of quitting smoking on risk attenuation and whether other risk factors for colorectal cancer modify this association. Methods:We performed a pooled analysis of 8 studies, including 6,796 colorectal cancer cases and 7,770 controls to evaluate the association between cigarette smoking history and colorectal cancer risk, and to investigate potential effect modification by other risk factors. Results:Current smokers (OR=1.26, 95% CI=1.11-1.43) and former smokers (OR=1.18, 95% CI=1.09-1.27), relative to never smokers, showed higher risks of colorectal cancer. Former smokers …
Characterization Of Gene–Environment Interactions For Colorectal Cancer Susceptibility Loci
Characterization Of Gene–Environment Interactions For Colorectal Cancer Susceptibility Loci
Shuo Jiao
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 …
Powerful Cocktail Methods For Detecting Genome-Wide Gene-Environment Interaction, Li Hsu, Shuo Jiao, James Y. Dai, Carolyn M. Hutter, Ulrike Peters, Charles Kooperberg
Powerful Cocktail Methods For Detecting Genome-Wide Gene-Environment Interaction, Li Hsu, Shuo Jiao, James Y. Dai, Carolyn M. Hutter, Ulrike Peters, Charles Kooperberg
Shuo Jiao
Identifying gene and environment interaction (G × E) can provide insights into biological networks of complex diseases, identify novel genes that act synergistically with environmental factors, and inform risk prediction. However, despite the fact that hundreds of novel disease-associated loci have been identified from genome-wide association studies (GWAS), few G×Es have been discovered. One reason is thatmost studies are underpowered for detecting these interactions. Several new methods have been proposed to improve power for G × E analysis, but performance varies with scenario. In this article, we present a module-based approach to integrating various methods that exploits each method’s most …
A Systematic Mapping Approach Of 16q12.2/Fto And Bmi In More Than 20,000 African Americans Narrows In On The Underlying Functional Variation: Results From The Population Architecture Using Genomics And Epidemiology (Page) Study
Shuo Jiao
Genetic variants in intron 1 of the fat mass– and obesity-associated (FTO) gene have been consistently associated with body mass index (BMI) in Europeans. However, follow-up studies in African Americans (AA) have shown no support for some of the most consistently BMI–associated FTO index single nucleotide polymorphisms (SNPs). This is most likely explained by different race-specific linkage disequilibrium (LD) patterns and lower correlation overall in AA, which provides the opportunity to fine-map this region and narrow in on the functional variant. To comprehensively explore the 16q12.2/FTO locus and to search for second independent signals in the broader region, we fine-mapped …
Genome-Wide Search For Gene-Gene Interactions In Colorectal Cancer
Genome-Wide Search For Gene-Gene Interactions In Colorectal Cancer
Shuo Jiao
Genome-wide association studies (GWAS) have successfully identified a number of single-nucleotide polymorphisms (SNPs) associated with colorectal cancer (CRC) risk. However, these susceptibility loci known today explain only a small fraction of the genetic risk. Gene-gene interaction (GxG) is considered to be one source of the missing heritability. To address this, we performed a genome-wide search for pair-wise GxG associated with CRC risk using 8,380 cases and 10,558 controls in the discovery phase and 2,527 cases and 2,658 controls in the replication phase. We developed a simple, but powerful method for testing interaction, which we term the Average Risk Due to …