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Association analysis of 9,560 prostate cancer cases from the International Consortium of Prostate Cancer Genetics confirms the role of reported prostate cancer associated SNPs for familial disease.

ABSTRACT: Previous GWAS studies have reported significant associations between various common SNPs and prostate cancer risk using cases unselected for family history. How these variants influence risk in familial prostate cancer is not well studied. Here, we analyzed 25 previously reported SNPs across 14 loci from prior prostate cancer GWAS. The International Consortium for Prostate Cancer Genetics (ICPCG) previously validated some of these using a family-based association method (FBAT). However, this approach suffered reduced power due to the conditional statistics implemented in FBAT. Here, we use a case-control design with an empirical analysis strategy to analyze the ICPCG resource for association between these 25 SNPs and familial prostate cancer risk. Fourteen sites contributed 12,506 samples (9,560 prostate cancer cases, 3,368 with aggressive disease, and 2,946 controls from 2,283 pedigrees). We performed association analysis with Genie software which accounts for relationships. We analyzed all familial prostate cancer cases and the subset of aggressive cases. For the familial prostate cancer phenotype, 20 of the 25 SNPs were at least nominally associated with prostate cancer and 16 remained significant after multiple testing correction (p ? 1E (-3)) occurring on chromosomal bands 6q25, 7p15, 8q24, 10q11, 11q13, 17q12, 17q24, and Xp11. For aggressive disease, 16 of the SNPs had at least nominal evidence and 8 were statistically significant including 2p15. The results indicate that the majority of common, low-risk alleles identified in GWAS studies for all prostate cancer also contribute risk for familial prostate cancer, and that some may contribute risk to aggressive disease.

SUBMITTER: Teerlink CC

PROVIDER: S-EPMC3945961 | biostudies-literature | 2014 Mar

REPOSITORIES: biostudies-literature

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Association analysis of 9,560 prostate cancer cases from the International Consortium of Prostate Cancer Genetics confirms the role of reported prostate cancer associated SNPs for familial disease.

Teerlink Craig C CC Thibodeau Stephen N SN McDonnell Shannon K SK Schaid Daniel J DJ Rinckleb Antje A Maier Christiane C Vogel Walther W Cancel-Tassin Geraldine G Egrot Christophe C Cussenot Olivier O Foulkes William D WD Giles Graham G GG Hopper John L JL Severi Gianluca G Eeles Ros R Easton Douglas D Kote-Jarai Zsofia Z Guy Michelle M Cooney Kathleen A KA Ray Anna M AM Zuhlke Kimberly A KA Lange Ethan M EM Fitzgerald Liesel M LM Stanford Janet L JL Ostrander Elaine A EA Wiley Kathleen E KE Isaacs Sarah D SD Walsh Patrick C PC Isaacs William B WB Wahlfors Tiina T Tammela Teuvo T Schleutker Johanna J Wiklund Fredrik F Grönberg Henrik H Emanuelsson Monica M Carpten John J Bailey-Wilson Joan J Whittemore Alice S AS Oakley-Girvan Ingrid I Hsieh Chih-Lin CL Catalona William J WJ Zheng S Lilly SL Jin Guangfu G Lu Lingyi L Xu Jianfeng J Camp Nicola J NJ Cannon-Albright Lisa A LA

Human genetics 20131026 3

Previous GWAS studies have reported significant associations between various common SNPs and prostate cancer risk using cases unselected for family history. How these variants influence risk in familial prostate cancer is not well studied. Here, we analyzed 25 previously reported SNPs across 14 loci from prior prostate cancer GWAS. The International Consortium for Prostate Cancer Genetics (ICPCG) previously validated some of these using a family-based association method (FBAT). However, this app ...[more]

PMID: 24162621

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Project description: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.

Project description:A previous linkage study provided evidence for a prostate cancer-susceptibility locus at 1q24-25. Subsequent reports in additional collections of families have yielded conflicting results. In addition, evidence for locus heterogeneity has been provided by the identification of other putative hereditary prostate cancer loci on Xq27-28, 1q42-43, and 1p36. The present study describes a combined analysis for six markers in the 1q24-25 region in 772 families affected by hereditary prostate cancer and ascertained by the members of the International Consortium for Prostate Cancer Genetics (ICPCG) from North America, Australia, Finland, Norway, Sweden, and the United Kingdom. Overall, there was some evidence for linkage, with a peak parametric multipoint LOD score assuming heterogeneity (HLOD) of 1.40 (P=.01) at D1S212. The estimated proportion of families (alpha) linked to the locus was.06 (1-LOD support interval.01-.12). This evidence was not observed by a nonparametric approach, presumably because of the extensive heterogeneity. Further parametric analysis revealed a significant effect of the presence of male-to-male disease transmission within the families. In the subset of 491 such families, the peak HLOD was 2.56 (P=.0006) and alpha =.11 (1-LOD support interval.04-.19), compared with HLODs of 0 in the remaining 281 families. Within the families with male-to-male disease transmission, alpha increased with the early mean age at diagnosis (<65 years, alpha =.19, with 1-LOD support interval.06-.34) and the number of affected family members (five or more family members, alpha =.15, with 1-LOD support interval.04-.28). The highest value of alpha was observed for the 48 families that met all three criteria (peak HLOD = 2.25, P=.001, alpha=.29, with 1-LOD support interval.08-.53). These results support the finding of a prostate cancer-susceptibility gene linked to 1q24-25, albeit in a defined subset of prostate cancer families. Although HPC1 accounts for only a small proportion of all families affected by hereditary prostate cancer, it appears to play a more prominent role in the subset of families with several members affected at an early age and with male-to-male disease transmission.

Project description:Although human leukocyte antigen (HLA) DQ and DR loci appear to confer the strongest genetic risk for type 1 diabetes, more detailed information is required for other loci within the HLA region to understand causality and stratify additional risk factors. The Type 1 Diabetes Genetics Consortium (T1DGC) study design included high-resolution genotyping of HLA-A, B, C, DRB1, DQ, and DP loci in all affected sibling pair and trio families, and cases and controls, recruited from four networks worldwide, for analysis with clinical phenotypes and immunological markers.In this article, we present the operational strategy of training, classification, reporting, and quality control of HLA genotyping in four laboratories on three continents over nearly 5 years.Methods to standardize HLA genotyping at eight loci included: central training and initial certification testing; the use of uniform reagents, protocols, instrumentation, and software versions; an automated data transfer; and the use of standardized nomenclature and allele databases. We implemented a rigorous and consistent quality control process, reinforced by repeated workshops, yearly meetings, and telephone conferences.A total of 15,246 samples have been HLA genotyped at eight loci to four-digit resolution; an additional 6797 samples have been HLA genotyped at two loci. The genotyping repeat rate decreased significantly over time, with an estimated unresolved Mendelian inconsistency rate of 0.21%. Annual quality control exercises tested 2192 genotypes (4384 alleles) and achieved 99.82% intra-laboratory and 99.68% inter-laboratory concordances.The chosen genotyping platform was unable to distinguish many allele combinations, which would require further multiple stepwise testing to resolve. For these combinations, a standard allele assignment was agreed upon, allowing further analysis if required.High-resolution HLA genotyping can be performed in multiple laboratories using standard equipment, reagents, protocols, software, and communication to produce consistent and reproducible data with minimal systematic error. Many of the strategies used in this study are generally applicable to other large multi-center studies.

Dataset Information

Association analysis of 9,560 prostate cancer cases from the International Consortium of Prostate Cancer Genetics confirms the role of reported prostate cancer associated SNPs for familial disease.

Publications

Association analysis of 9,560 prostate cancer cases from the International Consortium of Prostate Cancer Genetics confirms the role of reported prostate cancer associated SNPs for familial disease.

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