Ivan P. Gorlov

Genome-wide association scan of tag SNPs identifies a susceptibility locus for lung cancer at 15q25.1

To identify risk variants for lung cancer, we conducted a multistage genome-wide association study. In the discovery phase, we analyzed 315,450 tagging SNPs in 1,154 current and former (ever) smoking cases of European ancestry and 1,137 frequency-matched, ever-smoking controls from Houston, Texas. For replication, we evaluated the ten SNPs most significantly associated with lung cancer in an additional 711 cases and 632 controls from Texas and 2,013 cases and 3,062 controls from the UK. Two SNPs, rs1051730 and rs8034191, mapping to a region of strong linkage disequilibrium within 15q25.1 containing PSMA4 and the nicotinic acetylcholine receptor subunit genes CHRNA3 and CHRNA5, were significantly associated with risk in both replication sets. Combined analysis yielded odds ratios of 1.32 (P < 1 × 10−17) for both SNPs. Haplotype analysis was consistent with there being a single risk variant in this region. We conclude that variation in a region of 15q25.1 containing nicotinic acetylcholine receptors genes contributes to lung cancer risk.

Shifting Paradigm of Association Studies: Value of Rare Single-Nucleotide Polymorphisms

Currently, single-nucleotide polymorphisms (SNPs) with minor allele frequency (MAF) of >5% are preferentially used in case-control association studies of common human diseases. Recent technological developments enable inexpensive and accurate genotyping of a large number of SNPs in thousands of cases and controls, which can provide adequate statistical power to analyze SNPs with MAF <5%. Our purpose was to determine whether evaluating rare SNPs in case-control association studies could help identify causal SNPs for common diseases. We suggest that slightly deleterious SNPs (sdSNPs) subjected to weak purifying selection are major players in genetic control of susceptibility to common diseases. We compared the distribution of MAFs of synonymous SNPs with that of nonsynonymous SNPs (1) predicted to be benign, (2) predicted to be possibly damaging, and (3) predicted to be probably damaging by PolyPhen. Our sources of data were the International HapMap Project, ENCODE, and the SeattleSNPs project. We found that the MAF distribution of possibly and probably damaging SNPs was shifted toward rare SNPs compared with the MAF distribution of benign and synonymous SNPs that are not likely to be functional. We also found an inverse relationship between MAF and the proportion of nsSNPs predicted to be protein disturbing. On the basis of this relationship, we estimated the joint probability that a SNP is functional and would be detected as significant in a case-control study. Our analysis suggests that including rare SNPs in genotyping platforms will advance identification of causal SNPs in case-control association studies, particularly as sample sizes increase.

Variants at IRF5-TNPO3, 17q12-21 and MMEL1 are associated with primary biliary cirrhosis

We genotyped individuals with primary biliary cirrhosis and unaffected controls for suggestive risk loci (genome-wide association P < 1 × 10−4) identified in a previous genome-wide association study. Combined analysis of the genome-wide association and replication datasets identified IRF5-TNPO3 (combined P = 8.66 × 10−13), 17q12-21 (combined P = 3.50 × 10−13) and MMEL1 (combined P = 3.15 × 10−8) as new primary biliary cirrhosis susceptibility loci. Fine-mapping studies showed that a single variant accounts for the IRF5-TNPO3 association. As these loci are implicated in other autoimmune conditions, these findings confirm genetic overlap among such diseases.

Evolutionary evidence of the effect of rare variants on disease etiology

Gorlov IP, Gorlova OY, Frazier ML, Spitz MR, Amos CI. Evolutionary evidence of the effect of rare variants on disease etiology.

Nicotinic Acetylcholine Receptor Region on Chromosome 15q25 and Lung Cancer Risk Among African Americans: A Case–Control Study

Genome-wide association studies of white persons with lung cancer have identified a region of extensive linkage disequilibrium on chromosome 15q25.1 that appears to be associated with both risk for lung cancer and smoking dependence. Because studying African American persons, who exhibit lower levels of linkage disequilibrium in this region, may identify additional loci that are associated with lung cancer, we genotyped 34 single-nucleotide polymorphisms (SNPs) in this region (including LOC123688, PSMA4, CHRNA5, CHRNA3, and CHRNB4 genes) in 467 African American patients with lung cancer and 388 frequency-matched African American control subjects. Associations of SNPs in LOC123688 (rs10519203; odds ratio [OR] = 1.60, 95% confidence interval [CI] = 1.25 to 2.05, P = .00016), CHRNA5 (rs2036527; OR = 1.67, 95% CI = 1.26 to 2.21, P = .00031), and CHRNA3 (rs1051730; OR = 1.81, 95% CI = 1.26 to 2.59, P = .00137) genes with lung cancer risk reached Bonferroni-corrected levels of statistical significance (all statistical tests were two-sided). Joint logistic regression analysis showed that rs684513 (OR = 0.47, 95% CI = 0.31 to 0.71, P = .0003) in CHRNA5 and rs8034191 (OR = 1.76, 95% CI = 1.23 to 2.52, P = .002) in LOC123688 were also associated with risk. The functional A variant of rs1696698 in CHRNA5 had the strongest association with lung cancer (OR = 1.98, 95% CI = 1.25 to 3.11, P = .003). These SNPs were primarily associated with increased risk for lung adenocarcinoma histology and were only weakly associated with smoking phenotypes. Thus, among African American persons, multiple loci in the region of chromosome 15q25.1 appear to be strongly associated with lung cancer risk.

Novel genetic variants in the chromosome 5p15.33 region associate with lung cancer risk

Chromosome 5p15.33 has been identified by genome-wide association studies as one of the regions that associate with lung cancer risk. A few single-nucleotide polymorphisms (SNPs) in the telomerase reverse transcriptase (TERT) and cleft lip and palate transmembrane 1-like (CLPTM1L) genes located in this region have shown consistent associations. We performed dense genotyping of SNPs in this region to refine the previously reported association signals for lung cancer risk. Two hundred and fifteen SNPs were genotyped on an Illumina iSelect panel, in a hospital-based case-control study of 1681 lung cancer cases and 1235 unaffected controls. Association was tested using unconditional logistic regression, while adjusting for age, sex and pack-years smoked. Furthermore, since many of the SNPs were in linkage disequilibrium (LD), haplotype blocks were constructed, from which tagging SNPs at an r(2) threshold of ≥0.95 were included in a stepwise forward selection logistic regression model. Of the 215 SNPs, 69 were significant at P < 0.05 in univariate analysis; of these, 35 SNPs meeting the r(2) threshold were included in the multiple logistic regression model. Two SNPs, rs370348 (odds ratio = 0.76, P = 1.6 × 10(-6)) and rs4975538 (odds ratio = 1.18, P = 0.005), significantly associated with risk in the overall sample. Among ever smokers, rs4975615 (odds ratio = 0.75, P = 1.2 × 10(-4)) and rs4975538 (odds ratio = 1.26, P = 0.002) were significant, whereas among never-smokers, rs451360 (odds ratio = 0.62, P = 7.6 × 10(-5)) was significant. We refined the consistent association signal in this region, allowing for the considerable LD between SNPs and identified four novel SNPs that were independently and significantly associated with lung cancer risk. Results of these analyses strongly suggest effects on risk from several loci in the TERT/CLPTM1L region.

Cryptorchidism in mice with an androgen receptor ablation in gubernaculum testis

Androgens play a critical role in the development of the male reproductive system, including the positioning of the gonads. It is not clear, however, which developmental processes are influenced by androgens and what are the target tissues and cells mediating androgen signaling during testicular descent. Using a Cre-loxP approach, we have produced male mice (GU-ARKO) with conditional inactivation of the androgen receptor (Ar) gene in the gubernacular ligament connecting the epididymis to the caudal abdominal wall. The GU-ARKO males had normal testosterone levels but developed cryptorchidism with the testes located in a suprascrotal position. Although initially subfertile, the GU-ARKO males became sterile with age. We have shown that during development, the mutant gubernaculum failed to undergo eversion, a process giving rise to the processus vaginalis, a peritoneal outpouching inside the scrotum. As a result, the cremasteric sac did not form properly, and the testes remained in the low abdominal position. Abnormal development of the cremaster muscles in the GU-ARKO males suggested the participation of androgens in myogenic differentiation; however, males with conditional AR inactivation in the striated or smooth muscle cells had a normal testicular descent. Gene expression analysis showed that AR deficiency in GU-ARKO males led to the misexpression of genes involved in muscle differentiation, cell signaling, and extracellular space remodeling. We therefore conclude that AR signaling in gubernacular cells is required for gubernaculum eversion and outgrowth. The GU-ARKO mice provide a valuable model of isolated cryptorchidism, one of the most common birth defects in newborn boys.

Candidate pathways and genes for prostate cancer: a meta-analysis of gene expression data

BackgoundThe genetic mechanisms of prostate tumorigenesis remain poorly understood, but with the advent of gene expression array capabilities, we can now produce a large amount of data that can be used to explore the molecular and genetic mechanisms of prostate tumorigenesis.MethodsWe conducted a meta-analysis of gene expression data from 18 gene array datasets targeting transition from normal to localized prostate cancer and from localized to metastatic prostate cancer. We functionally annotated the top 500 differentially expressed genes and identified several candidate pathways associated with prostate tumorigeneses.ResultsWe found the top differentially expressed genes to be clustered in pathways involving integrin-based cell adhesion: integrin signaling, the actin cytoskeleton, cell death, and cell motility pathways. We also found integrins themselves to be downregulated in the transition from normal prostate tissue to primary localized prostate cancer. Based on the results of this study, we developed a collagen hypothesis of prostate tumorigenesis. According to this hypothesis, the initiating event in prostate tumorigenesis is the age-related decrease in the expression of collagen genes and other genes encoding integrin ligands. This concomitant depletion of integrin ligands leads to the accumulation of ligandless integrin and activation of integrin-associated cell death. To escape integrin-associated death, cells suppress the expression of integrins, which in turn alters the actin cytoskeleton, elevates cell motility and proliferation, and disorganizes prostate histology, contributing to the histologic progression of prostate cancer and its increased metastasizing potential.ConclusionThe results of this study suggest that prostate tumor progression is associated with the suppression of integrin-based cell adhesion. Suppression of integrin expression driven by integrin-mediated cell death leads to increased cell proliferation and motility and increased tumor malignancy.

GWAS Meets Microarray: Are the Results of Genome-Wide Association Studies and Gene-Expression Profiling Consistent? Prostate Cancer as an Example

Background Genome-wide association studies (GWASs) and global profiling of gene expression (microarrays) are two major technological breakthroughs that allow hypothesis-free identification of candidate genes associated with tumorigenesis. It is not obvious whether there is a consistency between the candidate genes identified by GWAS (GWAS genes) and those identified by profiling gene expression (microarray genes). Methodology/Principal Findings We used the Cancer Genetic Markers Susceptibility database to retrieve single nucleotide polymorphisms from candidate genes for prostate cancer. In addition, we conducted a large meta-analysis of gene expression data in normal prostate and prostate tumor tissue. We identified 13,905 genes that were interrogated by both GWASs and microarrays. On the basis of P values from GWASs, we selected 1,649 most significantly associated genes for functional annotation by the Database for Annotation, Visualization and Integrated Discovery. We also conducted functional annotation analysis using same number of the top genes identified in the meta-analysis of the gene expression data. We found that genes involved in cell adhesion were overrepresented among both the GWAS and microarray genes. Conclusions/Significance We conclude that the results of these analyses suggest that combining GWAS and microarray data would be a more effective approach than analyzing individual datasets and can help to refine the identification of candidate genes and functions associated with tumor development.

Prioritizing genes associated with prostate cancer development

BackgroundThe genetic control of prostate cancer development is poorly understood. Large numbers of gene-expression datasets on different aspects of prostate tumorigenesis are available. We used these data to identify and prioritize candidate genes associated with the development of prostate cancer and bone metastases. Our working hypothesis was that combining meta-analyses on different but overlapping steps of prostate tumorigenesis will improve identification of genes associated with prostate cancer development.MethodsA Z score-based meta-analysis of gene-expression data was used to identify candidate genes associated with prostate cancer development. To put together different datasets, we conducted a meta-analysis on 3 levels that follow the natural history of prostate cancer development. For experimental verification of candidates, we used in silico validation as well as in-house gene-expression data.ResultsGenes with experimental evidence of an association with prostate cancer development were overrepresented among our top candidates. The meta-analysis also identified a considerable number of novel candidate genes with no published evidence of a role in prostate cancer development. Functional annotation identified cytoskeleton, cell adhesion, extracellular matrix, and cell motility as the top functions associated with prostate cancer development. We identified 10 genes--CDC2, CCNA2, IGF1, EGR1, SRF, CTGF, CCL2, CAV1, SMAD4, and AURKA--that form hubs of the interaction network and therefore are likely to be primary drivers of prostate cancer development.ConclusionsBy using this large 3-level meta-analysis of the gene-expression data to identify candidate genes associated with prostate cancer development, we have generated a list of candidate genes that may be a useful resource for researchers studying the molecular mechanisms underlying prostate cancer development.