Pathway Analysis for Genome-Wide Association Study of Basal Cell Carcinoma of the Skin

Recently, a pathway-based approach has been developed to evaluate the cumulative contribution of the functionally related genes for genome-wide association studies (GWASs), which may help utilize GWAS data to a greater extent.In this study, we applied this approach for the GWAS of basal cell carcinoma (BCC) of the skin. We first conducted the BCC GWAS among 1,797 BCC cases and 5,197 controls in Caucasians with 740,760 genotyped SNPs. 115,688 SNPs were grouped into gene transcripts within 20 kb in distance and then into 174 Kyoto Encyclopedia of Genes and Genomes pathways, 205 BioCarta pathways, as well as two positive control gene sets (pigmentation gene set and BCC risk gene set). The association of each pathway with BCC risk was evaluated using the weighted Kolmogorov-Smirnov test. One thousand permutations were conducted to assess the significance.Both of the positive control gene sets reached pathway p-values<0.05. Four other pathways were also significantly associated with BCC risk: the heparan sulfate biosynthesis pathway (p  =  0.007, false discovery rate, FDR  =  0.35), the mCalpain pathway (p  =  0.002, FDR  =  0.12), the Rho cell motility signaling pathway (p  =  0.011, FDR  =  0.30), and the nitric oxide pathway (p  =  0.022, FDR  =  0.42).We identified four pathways associated with BCC risk, which may offer new insights into the etiology of BCC upon further validation, and this approach may help identify potential biological pathways that might be missed by the standard GWAS approach

Genome Wide Association Study to predict severe asthma exacerbations in children using random forests classifiers

<p>Abstract</p> <p>Background</p> <p>Personalized health-care promises tailored health-care solutions to individual patients based on their genetic background and/or environmental exposure history. To date, disease prediction has been based on a few environmental factors and/or single nucleotide polymorphisms (SNPs), while complex diseases are usually affected by many genetic and environmental factors with each factor contributing a small portion to the outcome. We hypothesized that the use of random forests classifiers to select SNPs would result in an improved predictive model of asthma exacerbations. We tested this hypothesis in a population of childhood asthmatics.</p> <p>Methods</p> <p>In this study, using emergency room visits or hospitalizations as the definition of a severe asthma exacerbation, we first identified a list of top Genome Wide Association Study (GWAS) SNPs ranked by Random Forests (RF) importance score for the CAMP (Childhood Asthma Management Program) population of 127 exacerbation cases and 290 non-exacerbation controls. We predict severe asthma exacerbations using the top 10 to 320 SNPs together with age, sex, pre-bronchodilator FEV1 percentage predicted, and treatment group.</p> <p>Results</p> <p>Testing in an independent set of the CAMP population shows that severe asthma exacerbations can be predicted with an Area Under the Curve (AUC) = 0.66 with 160-320 SNPs in comparison to an AUC score of 0.57 with 10 SNPs. Using the clinical traits alone yielded AUC score of 0.54, suggesting the phenotype is affected by genetic as well as environmental factors.</p> <p>Conclusions</p> <p>Our study shows that a random forests algorithm can effectively extract and use the information contained in a small number of samples. Random forests, and other machine learning tools, can be used with GWAS studies to integrate large numbers of predictors simultaneously.</p

Genome-wide association study identifies nidogen 1 (NID1) as a susceptibility locus to cutaneous nevi and melanoma risk

We conducted a genome-wide association study on the number of melanocytic nevi reported by 9136 individuals of European ancestry, with follow-up replication in 3581 individuals. We identified the nidogen 1 (NID1) gene on 1q42 associated with nevus count (two linked single nucleotide polymorphisms with r2 > 0.9: rs3768080 A allele associated with reduced count, P = 6.5 × 10−8; and rs10754833 T allele associated with reduced count, P = 1.5 × 10−7). We further determined that the rs10754833 [T] was associated with a decreased melanoma risk in 2368 melanoma cases and 7432 controls [for CT genotype: odds ratio (OR) = 0.86, 95% confidence interval (CI) = 0.75–0.99, P = 0.04; for TT genotype: OR = 0.84, 95% CI = 0.71–0.98, P = 0.03]. Expression level of the NID1 locus was 2-fold higher for the rs10754833 T allele carriers than that with the CC genotype (P = 0.017) in the 87 HapMap CEU cell lines. The NID1 gene is a biologically plausible locus for nevogenesis and melanoma development, with decreased expression levels of NID1 in benign nevi (P = 3.5 × 10−6) and in primary melanoma (P = 4.6 × 10−4) compared with the normal skin