Genome-wide linkage and association analysis of cardiometabolic phenotypes in Hispanic Americans.

Linkage studies of complex genetic diseases have been largely replaced by genome-wide association studies, due in part to limited success in complex trait discovery. However, recent interest in rare and low-frequency variants motivates re-examination of family-based methods. In this study, we investigated the performance of two-point linkage analysis for over 1.6 million single-nucleotide polymorphisms (SNPs) combined with single variant association analysis to identify high impact variants, which are both strongly linked and associated with cardiometabolic traits in up to 1414 Hispanics from the Insulin Resistance Atherosclerosis Family Study (IRASFS). Evaluation of all 50 phenotypes yielded 83 557 000 LOD (logarithm of the odds) scores, with 9214 LOD scores ⩾3.0, 845 ⩾4.0 and 89 ⩾5.0, with a maximal LOD score of 6.49 (rs12956744 in the LAMA1 gene for tumor necrosis factor-α (TNFα) receptor 2). Twenty-seven variants were associated with P<0.005 as well as having an LOD score >4, including variants in the NFIB gene under a linkage peak with TNFα receptor 2 levels on chromosome 9. Linkage regions of interest included a broad peak (31 Mb) on chromosome 1q with acute insulin response (max LOD=5.37). This region was previously documented with type 2 diabetes in family-based studies, providing support for the validity of these results. Overall, we have demonstrated the utility of two-point linkage and association in comprehensive genome-wide array-based SNP genotypes.

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.

Association of prostate cancer risk with SNPs in regions containing androgen receptor binding sites captured by ChIP-On-chip analyses.

BACKGROUND: Genome-wide association studies (GWAS) have identified approximately three dozen single nucleotide polymorphisms (SNPs) consistently associated with prostate cancer (PCa) risk. Despite the reproducibility of these associations, the molecular mechanism for most of these SNPs has not been well elaborated as most lie within non-coding regions of the genome. Androgens play a key role in prostate carcinogenesis. Recently, using ChIP-on-chip technology, 22,447 androgen receptor (AR) binding sites have been mapped throughout the genome, greatly expanding the genomic regions potentially involved in androgen-mediated activity. METHODOLOGY/PRINCIPAL FINDINGS: To test the hypothesis that sequence variants in AR binding sites are associated with PCa risk, we performed a systematic evaluation among two existing PCa GWAS cohorts; the Johns Hopkins Hospital and the Cancer Genetic Markers of Susceptibility (CGEMS) study population. We demonstrate that regions containing AR binding sites are significantly enriched for PCa risk-associated SNPs, that is, more than expected by chance alone. In addition, compared with the entire genome, these newly observed risk-associated SNPs in these regions are significantly more likely to overlap with established PCa risk-associated SNPs from previous GWAS. These results are consistent with our previous finding from a bioinformatics analysis that one-third of the 33 known PCa risk-associated SNPs discovered by GWAS are located in regions of the genome containing AR binding sites. CONCLUSIONS/SIGNIFICANCE: The results to date provide novel statistical evidence suggesting an androgen-mediated mechanism by which some PCa associated SNPs act to influence PCa risk. However, these results are hypothesis generating and ultimately warrant testing through in-depth molecular analyses.

Genome-wide linkage analysis of 1,233 prostate cancer pedigrees from the International Consortium for Prostate Cancer Genetics using novel sumLINK and sumLOD analyses.

BACKGROUND: Prostate cancer (PC) is generally believed to have a strong inherited component, but the search for susceptibility genes has been hindered by the effects of genetic heterogeneity. The recently developed sumLINK and sumLOD statistics are powerful tools for linkage analysis in the presence of heterogeneity. METHODS: We performed a secondary analysis of 1,233 PC pedigrees from the International Consortium for Prostate Cancer Genetics (ICPCG) using two novel statistics, the sumLINK and sumLOD. For both statistics, dominant and recessive genetic models were considered. False discovery rate (FDR) analysis was conducted to assess the effects of multiple testing. RESULTS: Our analysis identified significant linkage evidence at chromosome 22q12, confirming previous findings by the initial conventional analyses of the same ICPCG data. Twelve other regions were identified with genome-wide suggestive evidence for linkage. Seven regions (1q23, 5q11, 5q35, 6p21, 8q12, 11q13, 20p11-q11) are near loci previously identified in the initial ICPCG pooled data analysis or the subset of aggressive PC pedigrees. Three other regions (1p12, 8p23, 19q13) confirm loci reported by others, and two (2p24, 6q27) are novel susceptibility loci. FDR testing indicates that over 70% of these results are likely true positive findings. Statistical recombinant mapping narrowed regions to an average of 9 cM. CONCLUSIONS: Our results represent genomic regions with the greatest consistency of positive linkage evidence across a very large collection of high-risk PC pedigrees using new statistical tests that deal powerfully with heterogeneity. These regions are excellent candidates for further study to identify PC predisposition genes.

Evidence for two independent prostate cancer risk-associated loci in the HNF1B gene at 17q12.

We carried out a fine-mapping study in the HNF1B gene at 17q12 in two study populations and identified a second locus associated with prostate cancer risk, approximately 26 kb centromeric to the first known locus (rs4430796); these loci are separated by a recombination hot spot. We confirmed the association with a SNP in the second locus (rs11649743) in five additional populations, with P = 1.7 x 10(-9) for an allelic test of the seven studies combined. The association at each SNP remained significant after adjustment for the other SNP.

Two genome-wide association studies of aggressive prostate cancer implicate putative prostate tumor suppressor gene DAB2IP.

BACKGROUND: The consistent finding of a genetic susceptibility to prostate cancer suggests that there are germline sequence variants predisposing individuals to this disease. These variants could be useful in screening and treatment. METHODS: We performed an exploratory genome-wide association scan in 498 men with aggressive prostate cancer and 494 control subjects selected from a population-based case-control study in Sweden. We combined the results of this scan with those for aggressive prostate cancer from the publicly available Cancer Genetic Markers of Susceptibility (CGEMS) Study. Single-nucleotide polymorphisms (SNPs) that showed statistically significant associations with the risk of aggressive prostate cancer based on two-sided allele tests were tested for their association with aggressive prostate cancer in two independent study populations composed of individuals of European or African American descent using one-sided tests and the genetic model (dominant or additive) associated with the lowest value in the exploratory study. RESULTS: Among the approximately 60,000 SNPs that were common to our study and CGEMS, we identified seven that had a similar (positive or negative) and statistically significant (P<.01) association with the risk of aggressive prostate cancer in both studies. Analysis of the distribution of these SNPs among 1032 prostate cancer patients and 571 control subjects of European descent indicated that one, rs1571801, located in the DAB2IP gene, which encodes a novel Ras GTPase-activating protein and putative prostate tumor suppressor, was associated with aggressive prostate cancer (one-sided P value = .004). The association was also statistically significant in an African American study population that included 210 prostate cancer patients and 346 control subjects (one-sided P value = .02). CONCLUSION: A genetic variant in DAB2IP may be associated with the risk of aggressive prostate cancer and should be evaluated further.

Multiple genomic alterations on 21q22 predict various TMPRSS2/ERG fusion transcripts in human prostate cancers.

A number of TMPRSS2/ERG fusion transcripts have been reported since the discovery that recurrent genomic rearrangements result in the fusion of TMPRSS2 and ETS family member genes. In this article we present evidence demonstrating that multiple genomic alterations contribute to the formation of various TMPRSS2/ERG transcripts. Using allele-specific analysis of the data generated from the GeneChip 500K SNP array we observed both hemizygous and homozygous deletions occurring at different locations between and within TMPRSS2 and ERG in prostate cancers. The 500K SNP array enabled us to fine map the start and end of each deletion to specific introns of these two genes, and to predict a variety of fusion transcripts, including a new form which was confirmed by sequence analysis of the fusion transcripts in various tumors. We also inferred that translocation is an additional mechanism of fusion for these two genes in some tumors, based on largely diploid genomic DNA between TMPRSS and ERG, and different fusion transcripts produced in these tumors. Using a bioinformatics approach, we then uncovered the consensus sequences in the regions harboring the breakpoints of the deletions. These consensus sequences were homologous to the human Alu-Sq and Alu-Sp subfamily consensus sequences, with more than 80% homology. The presence/absence of Alu family consensus sequence in the introns of TMPRSS2 and ERG correlates with the presence/absence of fusion transcripts of theses two genes, indicating that these consensus sequences may contribute to genomic deletions and the fusion of TMPRSS2 and ERG in prostate cancer.

Compelling evidence for a prostate cancer gene at 22q12.3 by the International Consortium for Prostate Cancer Genetics.

Previously, an analysis of 14 extended, high-risk Utah pedigrees localized in the chromosome 22q linkage region to 3.2 Mb at 22q12.3-13.1 (flanked on each side by three recombinants) contained 31 annotated genes. In this large, multi-centered, collaborative study, we performed statistical recombinant mapping in 54 pedigrees selected to be informative for recombinant mapping from nine member groups of the International Consortium for Prostate Cancer Genetics (ICPCG). These 54 pedigrees included the 14 extended pedigrees from Utah and 40 pedigrees from eight other ICPCG member groups. The additional 40 pedigrees were selected from a total pool of 1213 such that each pedigree was required to contain both at least four prostate cancer (PRCA) cases and exhibit evidence for linkage to the chromosome 22q region. The recombinant events in these 40 independent pedigrees confirmed the previously proposed region. Further, when all 54 pedigrees were considered, the three-recombinant consensus region was narrowed down by more than a megabase to 2.2 Mb at chromosome 22q12.3 flanked by D22S281 and D22S683. This narrower region eliminated 20 annotated genes from that previously proposed, leaving only 11 genes. This region at 22q12.3 is the most consistently identified and smallest linkage region for PRCA. This collaborative study by the ICPCG illustrates the value of consortium efforts and the continued utility of linkage analysis using informative pedigrees to localize genes for complex diseases.

Integration of somatic deletion analysis of prostate cancers and germline linkage analysis of prostate cancer families reveals two small consensus regions for prostate cancer genes at 8p.

The evidence for tumor suppressor genes at 8p is well supported by many somatic deletion studies and genetic linkage studies. However, it remains a challenge to pinpoint the tumor suppressor genes at 8p primarily because the implicated regions are broad. In this study, we attempted to narrow down the implicated regions by incorporating evidence from both somatic and germline studies. Using high-resolution Affymetrix arrays, we identified two small common deleted regions among 55 prostate tumors at 8p23.1 (9.8-11.5 Mb) and 8p21.3 (20.6-23.7 Mb). Interestingly, our fine mapping linkage analysis at 8p among 206 hereditary prostate cancer families also provided evidence for linkage at these two regions at 8p23.1 (5.8-11.2 Mb) and at 8p21.3 (19.6-23.9 Mb). More importantly, by combining the results from the somatic deletion analysis and genetic linkage analysis, we were able to further narrow the regions to approximately 1.4 Mb at 8p23.1 and approximately 3.1 Mb at 8p21.3. These smaller consensus regions may facilitate a more effective search for prostate cancer genes at 8p.

Germline copy number polymorphisms involving larger than 100 kb are uncommon in normal subjects.

BACKGROUND: Recent studies using ROMA and Array-CGH suggest that germline copy number polymorphisms (CNPs) involving >100 kb are common in humans. METHODS: In this study, we used the Affymetrix GeneChip 100K single nucleotide polymorphisms (SNP) mapping panel to further examine the type and frequency of germline CNPs in the genome. By utilizing the allele intensity data generated while genotyping approximately 116,000 SNPs among 23 subjects from 4 families, we were able to detect multiple CNPs. RESULTS: However, in contrast to several previous studies, we found that CNPs >100 kb are rare in the genome but CNPs involving 100s-1,000s of base pairs are more common. CONCLUSIONS: We have demonstrated the utility of this approach, which has an important advantage over other methods because it is able to simultaneously assess both CNPs and SNPs, and therefore has great potential in genetic association studies of common diseases.

Comprehensive assessment of DNA copy number alterations in human prostate cancers using Affymetrix 100K SNP mapping array.

Although multiple recurrent chromosomal alterations have been identified in prostate cancer cells, the specific genes driving the apparent selection of these changes remain largely unknown. In part, this uncertainty is due to the limited resolution of the techniques used to detect these alterations. In this study, we applied a high-resolution genome-wide method, Affymetrix 100K SNP mapping array, to screen for somatic DNA copy number (CN) alterations among 22 pairs of samples from primary prostate cancers and matched nonmalignant tissues. We detected 355 recurrent deletions and 223 recurrent gains, many of which were novel. As expected, the sizes of novel alterations tend to be smaller. Importantly, among tumors with increasing grade, Gleason sum 6, 7, and 8, we found a significant trend of larger number of alterations in the tumors with higher grade. Overall, gains are significantly more likely to occur within genes (74%) than are deletions (49%). However, when we looked at the most frequent CN alterations, defined as those in > or =4 subjects, we observed that both gains (85%) and deletions (57%) occur preferentially within genes. An example of a novel, recurrent alteration observed in this study was a deletion between the ERG and TMPRSS2 genes on chromosome 21, presumably related to the recently identified fusion transcripts from these two genes. Results from this study provide a basis for a systematic and comprehensive cataloging of CN alterations associated with grades of prostate cancer, and the subsequent identification of specific genes that associated with initiation and progression of the disease. This article contains supplementary material available via the Internet at http://www.interscience.wiley.com/jpages/1045-2257/suppmat

A comprehensive association study for genes in inflammation pathway provides support for their roles in prostate cancer risk in the CAPS study.

BACKGROUND: Recently identified associations of prostate cancer risk with several genes involved in innate immunity support a role of inflammation in the etiology of prostate cancer. Considering inflammation is regulated by a complex system of gene products, we hypothesize sequence variants in many other genes of this pathway are associated with prostate cancer. METHODS: We evaluated 9,275 SNPs in 1,086 genes of the inflammation pathway using a MegAllele genotyping system among 200 familial cases and 200 unaffected controls selected from a large Swedish case-control population (CAPS). RESULTS: We found that significantly more than the expected numbers of SNPs were significant at a nominal P-value of 0.01, 0.05, and 0.1, providing overall support for our hypothesis. The excess was largest when using a more liberal nominal P-value (0.1); we observed 992 significant SNPs compared with the 854 significant SNPs expected by chance, and this difference was significant based on a permutation test (P = 0.0025). We also began the effort of differentiating true associated SNPs by selecting a small subset of significant SNPs (N = 26) and genotyped these in an independent sample of approximately 1,900 CAPS1 subjects. We were able to confirm 3 of these 26 SNPs. It is expected that many more true associated SNPs will be confirmed among the 992 significant SNPs identified in our pathway screen. CONCLUSIONS: Our study provides the first objective support for an association between prostate cancer and multiple modest-effect genes in inflammatory pathways.

Pooled genome linkage scan of aggressive prostate cancer: results from the International Consortium for Prostate Cancer Genetics.

While it is widely appreciated that prostate cancers vary substantially in their propensity to progress to a life-threatening stage, the molecular events responsible for this progression have not been identified. Understanding these molecular mechanisms could provide important prognostic information relevant to more effective clinical management of this heterogeneous cancer. Hence, through genetic linkage analyses, we examined the hypothesis that the tendency to develop aggressive prostate cancer may have an important genetic component. Starting with 1,233 familial prostate cancer families with genome scan data available from the International Consortium for Prostate Cancer Genetics, we selected those that had at least three members with the phenotype of clinically aggressive prostate cancer, as defined by either high tumor grade and/or stage, resulting in 166 pedigrees (13%). Genome-wide linkage data were then pooled to perform a combined linkage analysis for these families. Linkage signals reaching a suggestive level of significance were found on chromosomes 6p22.3 (LOD = 3.0), 11q14.1-14.3 (LOD = 2.4), and 20p11.21-q11.21 (LOD = 2.5). For chromosome 11, stronger evidence of linkage (LOD = 3.3) was observed among pedigrees with an average at diagnosis of 65 years or younger. Other chromosomes that showed evidence for heterogeneity in linkage across strata were chromosome 7, with the strongest linkage signal among pedigrees without male-to-male disease transmission (7q21.11, LOD = 4.1), and chromosome 21, with the strongest linkage signal among pedigrees that had African American ancestry (21q22.13-22.3; LOD = 3.2). Our findings suggest several regions that may contain genes which, when mutated, predispose men to develop a more aggressive prostate cancer phenotype. This provides a basis for attempts to identify these genes, with potential clinical utility for men with aggressive prostate cancer and their relatives.

Two-locus genome-wide linkage scan for prostate cancer susceptibility genes with an interaction effect.

Prostate cancer represents a significant worldwide public health burden. Epidemiological and genetic epidemiological studies have consistently provided data supporting the existence of inherited prostate cancer susceptibility genes. Segregation analyses of prostate cancer suggest that a multigene model may best explain familial clustering of this disease. Therefore, modeling gene-gene interactions in linkage analysis may improve the power to detect chromosomal regions harboring these disease susceptibility genes. In this study, we systematically screened for prostate cancer linkage by modeling two-locus gene-gene interactions for all possible pairs of loci across the genome in 426 prostate cancer families from Johns Hopkins Hospital, University of Michigan, University of Umeå, and University of Tampere. We found suggestive evidence for an epistatic interaction for six sets of loci (target chromosome-wide/reference marker-specific P< or =0.0001). Evidence for these interactions was found in two independent subsets from within the 426 families. While the validity of these results requires confirmation from independent studies and the identification of the specific genes underlying this linkage evidence, our approach of systematically assessing gene-gene interactions across the entire genome represents a promising alternative approach for gene identification for prostate cancer.

The interaction of four genes in the inflammation pathway significantly predicts prostate cancer risk.

It is widely hypothesized that the interactions of multiple genes influence individual risk to prostate cancer. However, current efforts at identifying prostate cancer risk genes primarily rely on single-gene approaches. In an attempt to fill this gap, we carried out a study to explore the joint effect of multiple genes in the inflammation pathway on prostate cancer risk. We studied 20 genes in the Toll-like receptor signaling pathway as well as several cytokines. For each of these genes, we selected and genotyped haplotype-tagging single nucleotide polymorphisms (SNP) among 1,383 cases and 780 controls from the CAPS (CAncer Prostate in Sweden) study population. A total of 57 SNPs were included in the final analysis. A data mining method, multifactor dimensionality reduction, was used to explore the interaction effects of SNPs on prostate cancer risk. Interaction effects were assessed for all possible n SNP combinations, where n = 2, 3, or 4. For each n SNP combination, the model providing lowest prediction error among 100 cross-validations was chosen. The statistical significance levels of the best models in each n SNP combination were determined using permutation tests. A four-SNP interaction (one SNP each from IL-10, IL-1RN, TIRAP, and TLR5) had the lowest prediction error (43.28%, P = 0.019). Our ability to analyze a large number of SNPs in a large sample size is one of the first efforts in exploring the effect of high-order gene-gene interactions on prostate cancer risk, and this is an important contribution to this new and quickly evolving field.

A combined genomewide linkage scan of 1,233 families for prostate cancer-susceptibility genes conducted by the international consortium for prostate cancer genetics.

Evidence of the existence of major prostate cancer (PC)-susceptibility genes has been provided by multiple segregation analyses. Although genomewide screens have been performed in over a dozen independent studies, few chromosomal regions have been consistently identified as regions of interest. One of the major difficulties is genetic heterogeneity, possibly due to multiple, incompletely penetrant PC-susceptibility genes. In this study, we explored two approaches to overcome this difficulty, in an analysis of a large number of families with PC in the International Consortium for Prostate Cancer Genetics (ICPCG). One approach was to combine linkage data from a total of 1,233 families to increase the statistical power for detecting linkage. Using parametric (dominant and recessive) and nonparametric analyses, we identified five regions with "suggestive" linkage (LOD score >1.86): 5q12, 8p21, 15q11, 17q21, and 22q12. The second approach was to focus on subsets of families that are more likely to segregate highly penetrant mutations, including families with large numbers of affected individuals or early age at diagnosis. Stronger evidence of linkage in several regions was identified, including a "significant" linkage at 22q12, with a LOD score of 3.57, and five suggestive linkages (1q25, 8q13, 13q14, 16p13, and 17q21) in 269 families with at least five affected members. In addition, four additional suggestive linkages (3p24, 5q35, 11q22, and Xq12) were found in 606 families with mean age at diagnosis of < or = 65 years. Although it is difficult to determine the true statistical significance of these findings, a conservative interpretation of these results would be that if major PC-susceptibility genes do exist, they are most likely located in the regions generating suggestive or significant linkage signals in this large study.

Interaction effect of PTEN and CDKN1B chromosomal regions on prostate cancer linkage.

The tumor suppressor functions of PTEN and CDKN1B have been extensively characterized. Recent data from mouse models suggest that, for some organs, the combined action of both PTEN and CDKN1B has a stronger tumor suppressor function than each alone; for the prostate, heterozygous knockout of both genes leads to 100% penetrance for prostate cancer. To assess whether such an interaction contributes to an increased risk of prostate cancer in humans, we performed a series of epistatic PTEN and CDKN1B interaction analyses in a collection of 188 high-risk hereditary prostate cancer families. Two different analytical approaches were performed; a nonparametric linkage (NPL) regression analysis that simultaneously models allele sharing at these two regions in all families, and an ordered subset analysis (OSA) that assesses linkage evidence at a target region in a subset of families based on the magnitude of allele sharing at the reference region. The strongest evidence of interaction effect was observed at 10q23-24 and 12p11-13 from both the NPL regression analysis (P = 0.0002) in all families and the OSA analyses in subsets of families. A LOD-delta of 3.15 (P = 0.01) was observed at 10q23-24 among 54 families with the highest NPL scores at 12p11-13, and a LOD-delta of 2.63 (P = 0.02) was observed at 12p11-13 among 34 families with the highest NPL scores at 10q23-24. The evidence for the interaction was stronger when using additional fine-mapping markers in the PTEN (10q23) and CDKN1B (12p13) regions. Our data are consistent with epistatic interactions between the PTEN and CDKN1B genes affecting risk for prostate cancer and demonstrate the utility of modeling epistatic effects in linkage analysis to detect susceptibility genes of complex diseases.