Association of CASP8 D302H polymorphism with reduced risk of aggressive prostate carcinoma.

BACKGROUND: Because of the dramatically different clinical course of aggressive and indolent prostate carcinoma (PCa), markers that distinguish between these phenotypes are of critical importance. Apoptosis is an important protective mechanism for unrestrained cellular growth and metastasis. Therefore, dysfunction in this pathway is a key step in cancer progression. As such, genetic variants in apoptosis genes are potential markers of aggressive PCa. Recent work in breast carcinoma has implicated the histidine variant of CASP8 D302H (rs1045485) as a protective risk allele. METHODS: We tested the hypothesis that the H variant was protective for aggressive PCa in a pooled analysis of 796 aggressive cases and 2,060 controls. RESULTS: The H allele was associated with a reduced risk of aggressive PCa (OR(per allele) = 0.67, 95% CI: 0.54-0.83, P(trend) = 0.0003). The results were similar for European-Americans (OR(per allele) = 0.68; 95% CI: 0.54-0.86) and African-Americans (OR(per allele) = 0.61; 95% CI: 0.34-1.10). We further determined from the full series of 1,160 cases and 1,166 controls in the Prostate, Lung, Colorectal, Ovarian (PLCO) population that the protective effect of the H allele tended to be limited to high-grade and advanced PCa (all cases OR(per allele) = 0.94; 95% CI: 0.79-1.11; localized, low-grade disease OR(per allele) = 0.98; 95% CI: 0.79-1.23; and aggressive disease OR(per allele) = 0.73; 95% CI: 0.50-1.07). CONCLUSION: These results suggest that histidine variant of CASP8 D302H is a protective allele for aggressive PCa with potential utility for identification of patients at differential risk for this clinically significant phenotype.

A common polymorphism in the upstream promoter region of the hepatocyte nuclear factor-4 alpha gene on chromosome 20q is associated with type 2 diabetes and appears to contribute to the evidence for linkage in an ashkenazi jewish population.

Variants in hepatocyte nuclear factor-4 alpha (HNF4 alpha), a transcription factor that influences the expression of glucose metabolic genes, have been correlated with maturity-onset diabetes of the young, a monogenic form of diabetes. Previously, in a genome scan of Ashkenazi Jewish type 2 diabetic families, we observed linkage to the chromosome 20q region encompassing HNF4 alpha. Here, haplotype-tag single nucleotide polymorphisms (htSNPs) were identified across a 78-kb region around HNF4 alpha and evaluated in an association analysis of Ashkenazi Jewish type 2 diabetic (n = 275) and control (n = 342) subjects. We found that two of nine htSNPs were associated with type 2 diabetes: a 3' intronic SNP, rs3818247 (29.2% case subjects vs. 21.7% control subjects; P = 0.0028, odds ratio [OR] 1.49) and a 5' htSNP located approximately 3.9 kb upstream of P2, rs1884614 (26.9% case subjects vs. 20.3% control subjects; P = 0.0078, OR 1.45). Testing of additional SNPs 5' of rs1884614 revealed a >10-kb haplotype block that was associated with type 2 diabetes. Conditioning on the probands' rs1884614 genotype suggested that the chromosomal region identified by the htSNP accounted for the linkage signal on chromosome 20q in families in which the proband carried at least one risk allele. Notably, the associations and the partitioned linkage profiles near P2 were independently observed in a Finnish sample, suggesting the presence of potential regulatory element(s) that may contribute to the risk for type 2 diabetes.

Microsatellites versus single-nucleotide polymorphisms in linkage analysis for quantitative and qualitative measures.

BACKGROUND: Genetic maps based on single-nucleotide polymorphisms (SNP) are increasingly being used as an alternative to microsatellite maps. This study compares linkage results for both types of maps for a neurophysiology phenotype and for an alcohol dependence phenotype. Our analysis used two SNP maps on the Illumina and Affymetrix platforms. We also considered the effect of high linkage disequilibrium (LD) in regions near the linkage peaks by analysing a "sparse" SNP map obtained by dropping some markers in high LD with other markers in those regions. RESULTS: The neurophysiology phenotype at the main linkage peak near 130 MB gave LOD scores of 2.76, 2.53, 3.22, and 2.68 for the microsatellite, Affymetrix, Illumina, and Illumina-sparse maps, respectively. The alcohol dependence phenotype at the main linkage peak near 101 MB gave LOD scores of 3.09, 3.69, 4.08, and 4.11 for the microsatellite, Affymetrix, Illumina, and Illumina-sparse maps, respectively. CONCLUSION: The linkage results were stronger overall for SNPs than for microsatellites for both phenotypes. However, LOD scores may be artificially elevated in regions of high LD. Our analysis indicates that appropriately thinning a SNP map in regions of high LD should give more accurate LOD scores. These results suggest that SNPs can be an efficient substitute for microsatellites for linkage analysis of both quantitative and qualitative phenotypes.

An analysis of identical single-nucleotide polymorphisms genotyped by two different platforms.

The overlap of 94 single-nucleotide polymorphisms (SNP) among the 4,720 and 11,120 SNPs contained in the linkage panels of Illumina and Affymetrix, respectively, allows an assessment of the discrepancy rate produced by these two platforms. Although the no-call rate for the Affymetrix platform is approximately 8.6 times greater than for the Illumina platform, when both platforms make a genotypic call, the agreement is an impressive 99.85%. To determine if disputed genotypes can be resolved without sequencing, we studied recombination in the region of the discrepancy for the most discrepant SNP rs958883 (typed by Illumina) and tsc02060848 (typed by Affymetrix). We find that the number of inferred recombinants is substantially higher for the Affymetrix genotypes compared to the Illumina genotypes. We illustrate this with pedigree 10043, in which 3 of 7 versus 0 of 7 offspring must be double recombinants using the genotypes from the Affymetrix and the Illumina platforms, respectively. Of the 36 SNPs with one or more discrepancies, we identified a subset that appears to cluster in families. Some of this clustering may be due to the presence of a second segregating SNP that obliterates a XbaI site (the restriction enzyme used in the Affymetrix platform), resulting in a fragment too long (>1,000 bp) to be amplified.

Multipoint identity-by-descent computations for single-point polymorphism and microsatellite maps.

We used the LOKI software to generate multipoint identity-by-descent matrices for a microsatellite map (with 31 markers) and two single-nucleotide polymorphism (SNP) maps to examine information content across chromosome 7 in the Collaborative Study on the Genetics of Alcoholism dataset. Despite the lower information provided by a single SNP, SNP maps overall had higher and more uniform information content across the chromosome. The Affymetrix map (578 SNPs) and the Illumina map (271 SNPs) provided almost identical information. However, increased information has a computational cost: SNP maps require 100 times as many iterations as microsatellites to produce stable estimates.

The efficacy of short tandem repeat polymorphisms versus single-nucleotide polymorphisms for resolving population structure.

Accurately resolving population structure in a sample is important for both linkage and association studies. In this study we investigated the power of single-nucleotide polymorphisms (SNPs) in detecting population structure in a sample of 286 unrelated individuals. We varied the number of SNPs to determine how many are required to approach the degree of resolution obtained with the Collaborative Study on the Genetics of Alcoholism (COGA) short tandem repeat polymorphisms (STRPs). In addition, we selected SNPs with varying minor allele frequencies (MAFs) to determine whether low or high frequency SNPs are more efficient in resolving population structure. We conclude that a set of at least 100 evenly spaced SNPs with MAFs of 40-50% is required to resolve population structure in this dataset. If SNPs with lower MAFs are used, then more than 250 SNPs may be required to obtain reliable results.

Detecting population stratification using related individuals.

Although identification of cryptic population stratification is necessary for case/control association analyses, it is also vital for linkage analyses and family-based association tests when founder genotypes are missing. However, including related individuals in an analysis such as EIGENSTRAT can result in bias; using only founders or one individual per pedigree results in loss of data and inaccurate estimates of stratification. We examine a generalization of principal-component analyses to allow for the inclusion of related individuals by down-weighting the significance of individual comparisons.

A search for non-chromosome 6 susceptibility loci contributing to rheumatoid arthritis.

We conducted a search for non-chromosome 6 genes that may increase risk for rheumatoid arthritis (RA). Our approach was to retrospectively ascertain three "extreme" subsamples from the North American Rheumatoid Arthritis Consortium. The three subsamples are: 1) RA cases who have two low-risk HLA-DRB1 alleles (N = 18), 2) RA cases who have two high-risk HLA-DRB1 alleles (N = 163), and 3) controls who have two low-risk HLA-DRB1 alleles (N = 652). We hypothesized that since Group 1's RA was likely due to non-HLA related risk factors, and because Group 3, by definition, is unaffected, comparing Group 1 with Group 2 and Group 1 with Group 3 would result in the identification of candidate susceptibility loci located outside of the MHC region. Accordingly, we restricted our search to the 21 non-chromosome 6 autosomes. The case-case comparison of Groups 1 and 2 resulted in the identification of 17 SNPs with allele frequencies that differed at p < 0.0001. The case-control comparison of Groups 1 and 3 identified 23 SNPs that differed in allele frequency at p < 0.0001. Eight of these SNPs (rs10498105, rs2398966, rs7664880, rs7447161, rs2793471, rs2611279, rs7967594, and rs742605) were common to both lists.

Power and false-positive rates for the restricted partition method (RPM) in a large candidate gene data set.

Many phenotypes of public health importance (e.g., diabetes, coronary artery disease, major depression, obesity, and addictions to alcohol and nicotine) involve complex pathways of action. Interactions between genetic variants or between genetic variants and environmental factors likely play important roles in the functioning of these pathways. Unfortunately, complex interacting systems are likely to have important interacting factors that may not readily reveal themselves to univariate analyses. Instead, detecting the role of some of these factors may require analyses that are sensitive to interaction effects.In this study, we evaluate the sensitivity and specificity of the restricted partition method (RPM) to detect signals related to coronary artery disease in the Genetic Analysis Workshop 16 Problem 3 data using the 50,000 k candidate gene single-nucleotide polymorphism set. Power and false-positive rates were evaluated using the first 100 replicate datasets. This included an exploration of the utility of using of all genotyped family members compared with selecting one member per family.

Association between polymorphisms in cell cycle genes and advanced prostate carcinoma.

BACKGROUND: Single nucleotide polymorphisms (SNPs) have been associated with a variety of malignancies including prostate carcinoma (PCa). Since a high percentage of PCa patients have low risk disease, of particular interest is not whether SNPs are associated with localized PCa, but whether they are associated with aggressive, potentially lethal disease. Herein, we explored the role of SNPs in cell cycle genes to determine if they were associated with advanced PCa. METHODS: Nine previously implicated SNPs in six cell cycle genes were evaluated in a European-American cohort of 186 patients with advanced PCa and 222 cancer-free controls. All patients received hormone ablation and had either a PSA>50 ng/ml or documented metastatic disease. Controls were all 75 years of age or older, had a negative DRE and had a PSA<4.0 ng/ml. All genotypes were determined using Pyrosequencing assays. RESULTS: One of nine (CDKN1A c10791t) was statistically different (P<0.05) and an additional two of nine (CCND1 a870g and MDM2 tSNP309g) approached significance (P<0.1). Analysis of genotypes revealed that presence of at least one copy of the t allele of MDM2 tSNP309g was associated with an increased risk of advanced PCa (OR 2.26: 95% CI=1.15-4.46) which was particularly strong in androgen-independent disease (OR 2.28: 95% CI=1.01-5.12) and younger age of diagnosis (OR 2.61: 95% CI=1.05-6.46). CONCLUSION: These results suggest that in a European-American population, SNPs within cell cycle genes are promising markers for aggressive PCa. Larger studies will be needed to confirm these findings.

Linkage, case-control association, and family-based association tests for complex disorders.

We carried out an analysis of the Genetic Analysis Workshop 15 simulated Problem 3 data. We restricted ourselves to the present/absent phenotype. Linkage analysis revealed a very strong signal on chromosome 6. Association analysis revealed additional susceptible loci located on chromosomes 11 and 18. The latter two signals were subsequently verified with linkage analysis - but only after 20 replicates were pooled. Analysis of linkage disequilibrium patterns, in concert with family-based association tests, led us to infer the presence of a second chromosome 6 locus located in the vicinity of single-nucleotide polymorphisms 160-162. These analyses were carried out without knowledge of the model used to generate the simulation.

Linkage and association analyses of principal components in expression data.

Performing linkage and association analyses on a large set of correlated data presents an interesting set of problems. In the current setting, we have 3554 expression levels from lymphoblastoid cell lines in 194 individuals from 14 three-generation Utah CEPH (Centre d'Etude du Polymorphisme Humain) pedigrees. We formed multivariate expression phenotypes from six sets of genes. These consisted of a set of genes identified by the data providers as showing common linkage to a region of chromosome 14, as well as five other sets suggested by ontological evidence. Using principal-component analyses, we generated seven quantitative phenotypes for expression levels from these six sets of genes. We performed quantitative genome linkage screens on these traits using the expression traits from the third generation of each pedigree. As expected, the strongest linkage signal was achieved when the trait under analysis was the composite of the expressions of genes previously showing linkage to chromosome 14. In particular, this trait produced a LOD score of 5.2 on chromosome 14. The trait also produced LOD scores over 3.5 on chromosomes 1, 7, 9, and 11; this suggests that these genes may be controlled by additional genetic factors on the genome. Subsequent association analyses on the first two generations of these pedigrees identified two polymorphisms on chromosome 11 as significant after correcting for multiple tests. These results suggest that principal-component analyses are useful for the analysis of pleiotropic loci. Furthermore, we have identified two single-nucleotide polymorphisms that may influence the expression of multiple genes linked to chromosome 14.

Gene x gene and gene x environment interactions for complex disorders.

The restricted partition method (RPM) provides a way to detect qualitative factors (e.g. genotypes, environmental exposures) associated with variation in quantitative or binary phenotypes, even if the contribution is predominantly an interaction displaying little or no signal in univariate analyses. The RPM provides a model (possibly non-linear) of the relationship between the predictor covariates and the phenotype as well as measures of statistical and clinical significance for the model.Blind to the generating model, we used the RPM to screen a data set consisting 1500 unrelated cases and 2000 unrelated controls from Replicate 1 of the Genetic Analysis Workshop 15 Problem 3 data for genetic and environmental factors contributing to rheumatoid arthritis (RA) risk. Both univariate and pair-wise analyses were performed using sex, smoking, parental DRB1 HLA microsatellite alleles, and 9187 single-nucleotide polymorphisms genotypes from across the genome. With this approach we correctly identified three genetic loci contributing directly to RA risk, and one quantitative trait locus for the endophenotype IgM level. We did not mistakenly identify any factors not in the generating model. All the factors we found were detectable with univariate RPM analyses. We failed to identify two genetic loci modifying the risk of RA. After breaking the blind, we examined the true modeling factors in the first 50 data replicates and found that we would not have identified the additional factors as important even had we combined all the data from the first 50 replicates in a single data set.

Tagging SNPs in the kallikrein genes 3 and 2 on 19q13 and their associations with prostate cancer in men of European origin.

Two of the classical kallikrein genes KLK3 and KLK2 on 19q13.4 are plausible candidates in prostate cancer susceptibility. They are expressed almost exclusively in prostate tissue. We have performed a comprehensive analysis of association of variants in these two genes with prostate cancer among men of European descent using a tagging SNP approach. Thirteen SNPs selected from the HapMap database were analyzed in a sample of 596 histologically verified prostate cancer cases and 567 ethnically matched controls. Five SNPs showed significant association at single marker level. Linkage disequilibrium (LD) analysis revealed four LD blocks. We performed a haplotype analysis within each LD block. A major haplotype in block 1 that contains the first two significantly associated SNPs was significantly underrepresented in the prostate cancer cases; a second haplotype in block 3 also showed significant frequency differences between cases and controls. Four of the studied SNPs show positive associations with serum PSA levels. A structure analysis revealed no population stratification in our samples that could have confounded the association results. These findings suggest a plausible role of kallikrein gene variants in the etiology of prostate cancer among men of European ancestry.

Variants in the HEPSIN gene are associated with prostate cancer in men of European origin.

There is considerable evidence that genetic factors are involved in prostate cancer susceptibility. We have studied the association of 11 single nucleotide polymorphisms (SNPs) in the HEPSIN gene (HPN) with prostate cancer in men of European ancestry. HPN is a likely candidate in prostate cancer susceptibility, as it encodes a transmembrane cell surface serum protease, which is overexpressed in prostate cancer; HPN is also located on 19q11-q13.2, where linkage is found with prostate cancer susceptibility. In this case-control association study (590 men with histologically verified prostate cancer and 576 unrelated controls, all of European descent), we find significant allele frequency differences between cases and controls at five SNPs that are located contiguously within the gene. A major 11-locus haplotype is significantly associated, which provides further support that HPN is a potentially important candidate gene involved in prostate cancer susceptibility. Association of one of the SNPs with Gleason score is also suggestive of a plausible role of HPN in tumor aggressiveness.

Genomewide linkage scan of 409 European-ancestry and African American families with schizophrenia: suggestive evidence of linkage at 8p23.3-p21.2 and 11p13.1-q14.1 in the combined sample.

We report the clinical characteristics of a schizophrenia sample of 409 pedigrees--263 of European ancestry (EA) and 146 of African American ancestry (AA)--together with the results of a genome scan (with a simple tandem repeat polymorphism interval of 9 cM) and follow-up fine mapping. A family was required to have a proband with schizophrenia (SZ) and one or more siblings of the proband with SZ or schizoaffective disorder. Linkage analyses included 403 independent full-sibling affected sibling pairs (ASPs) (279 EA and 124 AA) and 100 all-possible half-sibling ASPs (15 EA and 85 AA). Nonparametric multipoint linkage analysis of all families detected two regions with suggestive evidence of linkage at 8p23.3-q12 and 11p11.2-q22.3 (empirical Z likelihood-ratio score [Z(lr)] threshold >/=2.65) and, in exploratory analyses, two other regions at 4p16.1-p15.32 in AA families and at 5p14.3-q11.2 in EA families. The most significant linkage peak was in chromosome 8p; its signal was mainly driven by the EA families. Z(lr) scores >2.0 in 8p were observed from 30.7 cM to 61.7 cM (Center for Inherited Disease Research map locations). The maximum evidence in the full sample was a multipoint Z(lr) of 3.25 (equivalent Kong-Cox LOD of 2.30) near D8S1771 (at 52 cM); there appeared to be two peaks, both telomeric to neuregulin 1 (NRG1). There is a paracentric inversion common in EA individuals within this region, the effect of which on the linkage evidence remains unknown in this and in other previously analyzed samples. Fine mapping of 8p did not significantly alter the significance or length of the peak. We also performed fine mapping of 4p16.3-p15.2, 5p15.2-q13.3, 10p15.3-p14, 10q25.3-q26.3, and 11p13-q23.3. The highest increase in Z(lr) scores was observed for 5p14.1-q12.1, where the maximum Z(lr) increased from 2.77 initially to 3.80 after fine mapping in the EA families.

Analysis of candidate genes for prostate cancer.

Considerable evidence demonstrates that genetic factors are important in the development and aggressiveness of prostate cancer. To identify genetic variants that predispose to prostate cancer we tested candidate SNPs from genomic regions that show linkage to prostate cancer susceptibility and/or aggressiveness, as well as genes that show a significant difference in mRNA expression level between tumor and normal tissue. Cases had histologically verified prostate cancer. Controls were at least 65 years old, never registered a PSA above 2.5 ng/ml, always had digital rectal examinations that were not suspicious for cancer, and have no known family history of prostate cancer. Thirty-nine coding SNPs and nine non-coding SNPs were tested in up to 590 cases and 556 controls resulting in over 40,000 SNP genotypes. Significant differences in allele frequencies between cases and controls were observed for ID3 (inhibitor of DNA binding), p = 0.05, HPN (hepsin), p = 0.009, BCAS1 (breast carcinoma amplified sequence 1), p = 0.007, CAV2 (caveolin 2), p = 0.007, EMP3 (epithelial membrane protein 3), p < 0.0001, and MLH1 (mutL homolog 1), p < 0.0001. SNPs in three of these genes (BCAS1, EMP3 and MLH1) remained significant in an age-matched subsample.