Analysis of Xq27-28 linkage in the international consortium for prostate cancer genetics (ICPCG) families.

BACKGROUND: Genetic variants are likely to contribute to a portion of prostate cancer risk. Full elucidation of the genetic etiology of prostate cancer is difficult because of incomplete penetrance and genetic and phenotypic heterogeneity. Current evidence suggests that genetic linkage to prostate cancer has been found on several chromosomes including the X; however, identification of causative genes has been elusive. METHODS: Parametric and non-parametric linkage analyses were performed using 26 microsatellite markers in each of 11 groups of multiple-case prostate cancer families from the International Consortium for Prostate Cancer Genetics (ICPCG). Meta-analyses of the resultant family-specific linkage statistics across the entire 1,323 families and in several predefined subsets were then performed. RESULTS: Meta-analyses of linkage statistics resulted in a maximum parametric heterogeneity lod score (HLOD) of 1.28, and an allele-sharing lod score (LOD) of 2.0 in favor of linkage to Xq27-q28 at 138 cM. In subset analyses, families with average age at onset less than 65 years exhibited a maximum HLOD of 1.8 (at 138 cM) versus a maximum regional HLOD of only 0.32 in families with average age at onset of 65 years or older. Surprisingly, the subset of families with only 2-3 affected men and some evidence of male-to-male transmission of prostate cancer gave the strongest evidence of linkage to the region (HLOD = 3.24, 134 cM). For this subset, the HLOD was slightly increased (HLOD = 3.47 at 134 cM) when families used in the original published report of linkage to Xq27-28 were excluded. CONCLUSIONS: Although there was not strong support for linkage to the Xq27-28 region in the complete set of families, the subset of families with earlier age at onset exhibited more evidence of linkage than families with later onset of disease. A subset of families with 2-3 affected individuals and with some evidence of male to male disease transmission showed stronger linkage signals. Our results suggest that the genetic basis for prostate cancer in our families is much more complex than a single susceptibility locus on the X chromosome, and that future explorations of the Xq27-28 region should focus on the subset of families identified here with the strongest evidence of linkage to this region.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Genome-wide association of familial prostate cancer cases identifies evidence for a rare segregating haplotype at 8q24.21

Previous genome-wide association studies (GWAS) of prostate cancer risk focused on cases unselected for family history and have reported over 100 significant associations. The International Consortium for Prostate Cancer Genetics (ICPCG) has now performed a GWAS of 2511 (unrelated) familial prostate cancer cases and 1382 unaffected controls from 12 member sites. All samples were genotyped on the Illumina 5M+exome single nucleotide polymorphism (SNP) platform. The GWAS identified a significant evidence for association for SNPs in six regions previously associated with prostate cancer in population-based cohorts, including 3q26.2, 6q25.3, 8q24.21, 10q11.23, 11q13.3, and 17q12. Of note, SNP rs138042437 (p = 1.7e−8) at 8q24.21 achieved a large estimated effect size in this cohort (odds ratio = 13.3). 116 previously sampled affected relatives of 62 risk-allele carriers from the GWAS cohort were genotyped for this SNP, identifying 78 additional affected carriers in 62 pedigrees. A test for an excess number of affected carriers among relatives exhibited strong evidence for co-segregation of the variant with disease (p = 8.5e−11). The majority (92 %) of risk-allele carriers at rs138042437 had a consistent estimated haplotype spanning approximately 100 kb of 8q24.21 that contained the minor alleles of three rare SNPs (dosage minor allele frequencies <1.7 %), rs183373024 (PRNCR1), previously associated SNP rs188140481, and rs138042437 (CASC19). Strong evidence for co-segregation of a SNP on the haplotype further characterizes the haplotype as a prostate cancer pre-disposition locus

REVEL: An Ensemble Method for Predicting the Pathogenicity of Rare Missense Variants

Supplemental Data Supplemental Data include one figure and five tables and can be found with this article online at http://dx.doi.org/10.1016/j.ajhg.2016.08.016. Supplemental Data Document S1. Figure S1 and Tables S1–S5 Download Document S2. Article plus Supplemental Data Download Web Resources ClinVar, https://www.ncbi.nlm.nih.gov/clinvar/ dbNSFP, https://sites.google.com/site/jpopgen/dbNSFP Human Gene Mutation Database, http://www.hgmd.cf.ac.uk/ REVEL, https://sites.google.com/site/revelgenomics/ SwissVar, http://swissvar.expasy.org/ The vast majority of coding variants are rare, and assessment of the contribution of rare variants to complex traits is hampered by low statistical power and limited functional data. Improved methods for predicting the pathogenicity of rare coding variants are needed to facilitate the discovery of disease variants from exome sequencing studies. We developed REVEL (rare exome variant ensemble learner), an ensemble method for predicting the pathogenicity of missense variants on the basis of individual tools: MutPred, FATHMM, VEST, PolyPhen, SIFT, PROVEAN, MutationAssessor, MutationTaster, LRT, GERP, SiPhy, phyloP, and phastCons. REVEL was trained with recently discovered pathogenic and rare neutral missense variants, excluding those previously used to train its constituent tools. When applied to two independent test sets, REVEL had the best overall performance (p < 10−12) as compared to any individual tool and seven ensemble methods: MetaSVM, MetaLR, KGGSeq, Condel, CADD, DANN, and Eigen. Importantly, REVEL also had the best performance for distinguishing pathogenic from rare neutral variants with allele frequencies <0.5%. The area under the receiver operating characteristic curve (AUC) for REVEL was 0.046–0.182 higher in an independent test set of 935 recent SwissVar disease variants and 123,935 putatively neutral exome sequencing variants and 0.027–0.143 higher in an independent test set of 1,953 pathogenic and 2,406 benign variants recently reported in ClinVar than the AUCs for other ensemble methods. We provide pre-computed REVEL scores for all possible human missense variants to facilitate the identification of pathogenic variants in the sea of rare variants discovered as sequencing studies expand in scale

A multi-stage genome-wide association study of bladder cancer identifies multiple susceptibility loci.

We conducted a multi-stage, genome-wide association study of bladder cancer with a primary scan of 591,637 SNPs in 3,532 affected individuals (cases) and 5,120 controls of European descent from five studies followed by a replication strategy, which included 8,382 cases and 48,275 controls from 16 studies. In a combined analysis, we identified three new regions associated with bladder cancer on chromosomes 22q13.1, 19q12 and 2q37.1: rs1014971, (P = 8 × 10⁻¹²) maps to a non-genic region of chromosome 22q13.1, rs8102137 (P = 2 × 10⁻¹¹) on 19q12 maps to CCNE1 and rs11892031 (P = 1 × 10⁻⁷) maps to the UGT1A cluster on 2q37.1. We confirmed four previously identified genome-wide associations on chromosomes 3q28, 4p16.3, 8q24.21 and 8q24.3, validated previous candidate associations for the GSTM1 deletion (P = 4 × 10⁻¹¹) and a tag SNP for NAT2 acetylation status (P = 4 × 10⁻¹¹), and found interactions with smoking in both regions. Our findings on common variants associated with bladder cancer risk should provide new insights into the mechanisms of carcinogenesis

Post hoc Analysis for Detecting Individual Rare Variant Risk Associations Using Probit Regression Bayesian Variable Selection Methods in Case-Control Sequencing Studies.

Rare variants (RVs) have been shown to be significant contributors to complex disease risk. By definition, these variants have very low minor allele frequencies and traditional single-marker methods for statistical analysis are underpowered for typical sequencing study sample sizes. Multimarker burden-type approaches attempt to identify aggregation of RVs across case-control status by analyzing relatively small partitions of the genome, such as genes. However, it is generally the case that the aggregative measure would be a mixture of causal and neutral variants, and these omnibus tests do not directly provide any indication of which RVs may be driving a given association. Recently, Bayesian variable selection approaches have been proposed to identify RV associations from a large set of RVs under consideration. Although these approaches have been shown to be powerful at detecting associations at the RV level, there are often computational limitations on the total quantity of RVs under consideration and compromises are necessary for large-scale application. Here, we propose a computationally efficient alternative formulation of this method using a probit regression approach specifically capable of simultaneously analyzing hundreds to thousands of RVs. We evaluate our approach to detect causal variation on simulated data and examine sensitivity and specificity in instances of high RV dimensionality as well as apply it to pathway-level RV analysis results from a prostate cancer (PC) risk case-control sequencing study. Finally, we discuss potential extensions and future directions of this work

Genome-wide interaction study of smoking and bladder cancer risk

Bladder cancer is a complex disease with known environmental and genetic risk factors. We performed a genome-wide interaction study (GWAS) of smoking and bladder cancer risk based on primary scan data from 3002 cases and 4411 controls from the National Cancer Institute Bladder Cancer GWAS. Alternative methods were used to evaluate both additive and multiplicative interactions between individual single nucleotide polymorphisms (SNPs) and smoking exposure. SNPs with interaction P values < 5 x 10(-) (5) were evaluated further in an independent dataset of 2422 bladder cancer cases and 5751 controls. We identified 10 SNPs that showed association in a consistent manner with the initial dataset and in the combined dataset, providing evidence of interaction with tobacco use. Further, two of these novel SNPs showed strong evidence of association with bladder cancer in tobacco use subgroups that approached genome-wide significance. Specifically, rs1711973 (FOXF2) on 6p25.3 was a susceptibility SNP for never smokers [combined odds ratio (OR) = 1.34, 95% confidence interval (CI) = 1.20-1.50, P value = 5.18 x 10(-) (7)]; and rs12216499 (RSPH3-TAGAP-EZR) on 6q25.3 was a susceptibility SNP for ever smokers (combined OR = 0.75, 95% CI = 0.67-0.84, P value = 6.35 x 10(-) (7)). In our analysis of smoking and bladder cancer, the tests for multiplicative interaction seemed to more commonly identify susceptibility loci with associations in never smokers, whereas the additive interaction analysis identified more loci with associations among smokers-including the known smoking and NAT2 acetylation interaction. Our findings provide additional evidence of gene-environment interactions for tobacco and bladder cancer

Chromosomes 4 and 8 implicated in a genome wide SNP linkage scan of 762 prostate cancer families collected by the ICPCG

BACKGROUND In spite of intensive efforts, understanding of the genetic aspects of familial prostate cancer (PC) remains largely incomplete. In a previous microsatellite‐based linkage scan of 1,233 PC families, we identified suggestive evidence for linkage (i.e., LOD ≥ 1.86) at 5q12, 15q11, 17q21, 22q12, and two loci on 8p, with additional regions implicated in subsets of families defined by age at diagnosis, disease aggressiveness, or number of affected members. METHODS In an attempt to replicate these findings and increase linkage resolution, we used the Illumina 6000 SNP linkage panel to perform a genome‐wide linkage scan of an independent set of 762 multiplex PC families, collected by 11 International Consortium for Prostate Cancer Genetics (ICPCG) groups. RESULTS Of the regions identified previously, modest evidence of replication was observed only on the short arm of chromosome 8, where HLOD scores of 1.63 and 3.60 were observed in the complete set of families and families with young average age at diagnosis, respectively. The most significant linkage signals found in the complete set of families were observed across a broad, 37 cM interval on 4q13–25, with LOD scores ranging from 2.02 to 2.62, increasing to 4.50 in families with older average age at diagnosis. In families with multiple cases presenting with more aggressive disease, LOD scores over 3.0 were observed at 8q24 in the vicinity of previously identified common PC risk variants, as well as MYC , an important gene in PC biology. CONCLUSIONS These results will be useful in prioritizing future susceptibility gene discovery efforts in this common cancer. Prostate 72:410–426, 2012. © 2011 Wiley Periodicals, Inc.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/90245/1/21443_ftp.pd

Genome-wide association study identifies multiple risk loci for renal cell carcinoma

Previous genome-wide association studies (GWAS) have identified six risk loci for renal cell carcinoma (RCC). We conducted a meta-analysis of two new scans of 5,198 cases and 7,331 controls together with four existing scans, totalling 10,784 cases and 20,406 controls of European ancestry. Twenty-four loci were tested in an additional 3,182 cases and 6,301 controls. We confirm the six known RCC risk loci and identify seven new loci at 1p32.3 (rs4381241, P=3.1 × 10−10), 3p22.1 (rs67311347, P=2.5 × 10−8), 3q26.2 (rs10936602, P=8.8 × 10−9), 8p21.3 (rs2241261, P=5.8 × 10−9), 10q24.33-q25.1 (rs11813268, P=3.9 × 10−8), 11q22.3 (rs74911261, P=2.1 × 10−10) and 14q24.2 (rs4903064, P=2.2 × 10−24). Expression quantitative trait analyses suggest plausible candidate genes at these regions that may contribute to RCC susceptibility

Identification of Novel Susceptibility Loci and Genes for Prostate Cancer Risk: A Transcriptome-Wide Association Study in over 140,000 European Descendants

Genome-wide association study–identified prostate cancer risk variants explain only a relatively small fraction of its familial relative risk, and the genes responsible for many of these identified associations remain unknown. To discover novel prostate cancer genetic loci and possible causal genes at previously identified risk loci, we performed a transcriptome-wide association study in 79,194 cases and 61,112 controls of European ancestry. Using data from the Genotype-Tissue Expression Project, we established genetic models to predict gene expression across the transcriptome for both prostate models and cross-tissue models and evaluated model performance using two independent datasets. We identified significant associations for 137 genes at P < 2.61 × 10−6, a Bonferroni-corrected threshold, including nine genes that remained significant at P < 2.61 × 10−6 after adjusting for all known prostate cancer risk variants in nearby regions. Of the 128 remaining associated genes, 94 have not yet been reported as potential target genes at known loci. We silenced 14 genes and many showed a consistent effect on viability and colony-forming efficiency in three cell lines. Our study provides substantial new information to advance our understanding of prostate cancer genetics and biology. SIGNIFICANCE: This study identifies novel prostate cancer genetic loci and possible causal genes, advancing our understanding of the molecular mechanisms that drive prostate cancer