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.

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.

A common VLDLR polymorphism interacts with APOE genotype in the prediction of carotid artery disease risk.

The genetic factors associated with carotid artery disease (CAAD) are not fully known. Because of its role in lipid metabolism, we hypothesized that common genetic variation in the very low density lipoprotein receptor (VLDLR) gene is associated with severe CAAD (>80% stenosis), body mass index (BMI), and lipid traits in humans. VLDLR was resequenced for variation discovery in 92 subjects, and single nucleotide polymorphisms (tagSNPs) were chosen for genotyping in a larger cohort (n = 1,027). Of the 17 tagSNPs genotyped, one tagSNP (SNP 1226; rs1454626) located in the 5' flanking region of VLDLR was associated with CAAD, BMI, and LDL-associated apolipoprotein B (apoB). We also identified receptor-ligand genetic interactions between VLDLR 1226 and APOE genotype for predicting CAAD case status. These findings may further our understanding of VLDLR function, its ligand APOE, and ultimately the pathogenesis of CAAD in the general population.

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.

Genome scan for quantitative trait loci influencing HDL levels: evidence for multilocus inheritance in familial combined hyperlipidemia.

Several genome scans in search of high-density lipoprotein (HDL) quantitative trait loci (QTLs) have been performed. However, to date the actual identification of genes implicated in the regulation of common forms of HDL abnormalities remains unsuccessful. This may be due, in part, to the oligogenic and multivariate nature of HDL regulation, and potentially, pleiotropy affecting HDL and other lipid-related traits. Using a Bayesian Markov Chain Monte Carlo (MCMC) approach, we recently provided evidence of linkage of HDL level variation to the APOA1-C3-A4-A5 gene complex, in familial combined hyperlipidemia pedigrees, with an estimated number of two to three large QTLs remaining to be identified. We also presented results consistent with pleiotropy affecting HDL and triglycerides at the APOA1-C3-A4-A5 gene complex. Here we use the same MCMC analytic strategy, which allows for oligogenic trait models, as well as simultaneous incorporation of covariates, in the context of multipoint analysis. We now present results from a genome scan in search for the additional HDL QTLs in these pedigrees. We provide evidence of linkage for additional HDL QTLs on chromosomes 3p14 and 13q32, with results on chromosome 3 further supported by maximum parametric and variance component LOD scores of 3.0 and 2.6, respectively. Weaker evidence of linkage was also obtained for 7q32, 12q12, 14q31-32 and 16q23-24.

The role of parametric linkage methods in complex trait analyses using microsatellites.

Many investigators of complexly inherited familial traits bypass classical segregation analysis to perform model-free genome-wide linkage scans. Because model-based or parametric linkage analysis may be the most powerful means to localize genes when a model can be approximated, model-free statistics may result in a loss of power to detect linkage. We performed limited segregation analyses on the electrophysiological measurements that have been collected for the Collaborative Study on the Genetics of Alcoholism. The resulting models are used in whole-genome scans. Four genomic regions provided a model-based LOD > 2 and only 3 of these were detected (p < 0.05) by a model-free approach. We conclude that parametric methods, using even over-simplified models of complex phenotypes, may complement nonparametric methods and decrease false positives.

Bias of allele-sharing linkage statistics in the presence of intermarker linkage disequilibrium.

Current genome-wide linkage-mapping single-nucleotide polymorphism (SNP) panels with densities of 0.3 cM are likely to have increased intermarker linkage disequilibrium (LD) compared to 5-cM microsatellite panels. The resulting difference in haplotype frequencies versus that predicted may affect multipoint linkage analysis with ungenotyped founders; a common haplotype may be assumed to be rare, leading to inflation of identical-by-descent (IBD) allele-sharing estimates and evidence for linkage. Using data simulated for the Genetic Analysis Workshop 14, we assessed bias in allele-sharing measures and nonparametric linkage (NPL all) and Kong and Cox LOD (KC-LOD) scores in a targeted analysis of regions with and without LD and with and without genes. Using over 100 replicates, we found that if founders were not genotyped, multipoint IBD estimates and delta parameters were modestly inflated and NPL all and KC-LOD scores were biased upwards in the region with LD and no gene; rather than centering on the null, the mean NPL all and KC-LOD scores were 0.51 +/- 0.91 and 0.19 +/- 0.38, respectively. Reduction of LD by dropping markers reduced this upward bias. These trends were not seen in the non-LD region with no gene. In regions with genes (with and without LD), a slight loss in power with dropping markers was suggested. These results indicate that LD should be considered in dense scans; removal of markers in LD may reduce false-positive results although information may also be lost. Methods to address LD in a high-throughput manner are needed for efficient, robust genomic scans with dense SNPs.

Low-density lipoprotein particle size loci in familial combined hyperlipidemia: evidence for multiple loci from a genome scan.

OBJECTIVE: Low-density lipoprotein (LDL) size is associated with vascular disease and with familial combined hyperlipidemia (FCHL). METHODS AND RESULTS: We used logarithm of odds (lod) score and Bayesian Markov chain Monte Carlo (MCMC) linkage analysis methods to perform a 10-cM genome scan of LDL size, measured as peak particle diameter (PPD) and adjusted for age, sex, body mass index, and triglycerides in 4 large families with FCHL (n=185). We identified significant evidence of linkage to a chromosome 9p locus (multipoint lod(max)=3.70; MCMC intensity ratio [IR]=21) in a single family, and across all 4 families to chromosomes 16q23 (lod(max)=3.00; IR=43) near cholesteryl ester transfer protein (CETP) and to 11q22 (lod(max)=3.71; IR=120). Chromosome 14q24-31, a region with previous suggestive LDL PPD linkage evidence, yielded an IR of 71 but an lod(max)=1.79 in the combined families. CONCLUSIONS: These results of significant evidence of linkage to 3 regions (9p, 16q, and 11q) and confirmatory support of previous reported linkage to 14q in large FCHL pedigrees demonstrate that LDL size is a trait influenced by multiple loci and illustrate the complementary use of lod score and MCMC methods in analysis of a complex trait.

Identification of a prostate cancer susceptibility locus on chromosome 7q11-21 in Jewish families.

Results from over a dozen prostate cancer susceptibility genome-wide scans, encompassing some 1,500 hereditary prostate cancer families, indicate that prostate cancer is an extremely heterogeneous disease with multiple loci contributing to overall susceptibility. In an attempt to reduce locus heterogeneity, we performed a genomewide linkage scan for prostate cancer susceptibility genes with 36 Jewish families, which represent a stratification of hereditary prostate cancer families with potentially increased locus homogeneity. The 36 Jewish families represent a combined dataset of 17 Jewish families from the Fred Hutchinson Cancer Research Center-based Prostate Cancer Genetic Research Study dataset and 19 Ashkenazi Jewish families collected at Johns Hopkins University. All available family members, including 94 affected men, were genotyped at markers distributed across the genome with an average interval of <10 centimorgans. Nonparametric multipoint linkage analyses were the primary approach, although parametric analyses were performed as well. Our strongest signal was a significant linkage peak at 7q11-21, with a nonparametric linkage (NPL) score of 3.01 (P = 0.0013). Simulations indicated that this corresponds to a genomewide empirical P = 0.006. All other regions had NPL P values >/=0.02. After genotyping additional markers within the 7q11-21 peak, the NPL score increased to 3.35 (P = 0.0004) at D7S634 with an allele-sharing logarithm of odds of 3.12 (P = 0.00007). These studies highlight the utility of analyzing defined sets of families with a common origin for reducing locus heterogeneity problems associated with studying complex traits.

Summary report: Missing data and pedigree and genotyping errors.

Genetic epidemiology is faced with mapping complex traits to genes with relatively small effects whose phenotypes may be modulated by temporal factors. To do this, detailed and accurate data must be available on families, perhaps collected over time. The Framingham Heart Study data supplied to Genetic Analysis Workshop 13 (GAW13), along with its simulated counterpart, contain longitudinal measurements and genomic scan data on 2,885 individuals in 330 families, and offer an opportunity to examine data quality and completeness issues as they affect analytical conclusions. Six GAW13 contributions applied methods to deal with missing data, both phenotypic and genotypic, at a single time point and longitudinally, and with possible errors in pedigree structure and genotypes. The methods included missing phenotypic data imputation by Markov chain Monte Carlo sampling, propensity scoring, regression, and adjusted mean values, as well as the assessment of transmission-disequilibrium tests when missing marker data may be allele-specific. Pedigree structural errors were found by genome-wide allele-sharing probabilities, while Mendelian consistent genotype errors were evaluated through likelihoods of double-recombination events. Each of the methods reviewed here offered insights into how to better take advantage of large, time-dependent, familial data sets. However, no one of them dealt with the longitudinal and familial aspects simultaneously. Overall, more consideration needs to be given to the effects that missing data and data errors have on our ability to map complex traits efficiently and accurately.

Genomic scan of 254 hereditary prostate cancer families.

Hereditary prostate cancer (HPC) is a genetically heterogeneous disease, complicating efforts to map and clone susceptibility loci. We have used stratification of a large dataset of 254 HPC families in an effort to improve power to detect HPC loci and to understand what types of family features may improve locus identification. The strongest result is that of a dominant locus at 6p22.3 (heterogeneity LOD (HLOD) = 2.51), the evidence for which is increased by consideration of the age of PC onset (HLOD = 3.43 in 214 families with median age-of-onset 56-72 years) and co-occurrence of primary brain cancer (HLOD = 2.34 in 21 families) in the families. Additional regions for which we observe modest evidence for linkage include chromosome 7q and 17p. Only weak evidence of several previously implicated HPC regions is detected. These analyses support the existence of multiple HPC loci, whose presence may be best identified by analyses of large, including pooled, datasets which consider locus heterogeneity.

An examination of the genotyping error detection function of SIMWALK2.

This investigation was undertaken to assess the sensitivity and specificity of the genotyping error detection function of the computer program SIMWALK2. We chose to examine chromosome 22, which had 7 microsatellite markers, from a single simulated replicate (330 pedigrees with a pattern of missing genotype data similar to the Framingham families). We created genotype errors at five overall frequencies (0.0, 0.025, 0.050, 0.075, and 0.100) and applied SIMWALK2 to each of these five data sets, respectively assuming that the total error rate (specified in the program), was at each of these same five levels. In this data set, up to an assumed error rate of 10%, only 50% of the Mendelian-consistent mistypings were found under any level of true errors. And since as many as 70% of the errors detected were false-positives, blanking suspect genotypes (at any error probability) will result in a reduction of statistical power due to the concomitant blanking of correctly typed alleles. This work supports the conclusion that allowing for genotyping errors within likelihood calculations during statistical analysis may be preferable to choosing an arbitrary cut-off.

Multiple genome-wide analyses of smoking behavior in the Framingham Heart Study.

BACKGROUND: Cigarette smoking behavior may have a genetic basis. We assessed evidence for quantitative trait loci (QTLs) affecting the maximum number of cigarettes smoked per day, a trait meant to quantify this behavior, using data collected over 40 years as part of the Framingham Heart Study's original and offspring cohorts. RESULTS: Heritability was estimated to be approximately 21% using variance components (VC) methods (SOLAR), while oligogenic linkage and segregation analysis based on Bayesian Markov chain Monte Carlo (MCMC) methods (LOKI) estimated a mean of two large QTLs contributing approximately 28% and 20%, respectively, to the trait's variance. Genome-wide parametric (FASTLINK) and VC linkage analyses (SOLAR) revealed several LOD scores greater than 1.0, with peak LOD scores using both methods on chromosomes 2, 17, and 20; multi-point MCMC methods followed up on these chromosomes. The most robust linkage results were for a QTL between 65 and 84 cM on chromosome 20 with signals from multiple sex- and age-adjusted analyses including two-point LOD scores of 1.30 (parametric) and 1.07 (heritability = 0.17, VC) at 70.51 cM, a multi-point LOD score of 1.50 (heritability = 0.20, VC) at 84 cM, and an intensity ratio of 12.0 (MCMC) at 65 cM. CONCLUSION: Familial aggregation of the maximum number of cigarettes smoked per day was consistent with a genetic component to this behavior, and oligogenic segregation analyses using MCMC suggested two important QTLs. Linkage signals on chromosome 20 between 65 and 84 cM were seen using multiple analytical methods. No linkage result, however, met genome-wide statistical significance criteria, and the true relationship between these regions and smoking behavior remains unclear.

Evaluation of linkage of breast cancer to the putative BRCA3 locus on chromosome 13q21 in 128 multiple case families from the Breast Cancer Linkage Consortium.

The known susceptibility genes for breast cancer, including BRCA1 and BRCA2, only account for a minority of the familial aggregation of the disease. A recent study of 77 multiple case breast cancer families from Scandinavia found evidence of linkage between the disease and polymorphic markers on chromosome 13q21. We have evaluated the contribution of this candidate "BRCA3" locus to breast cancer susceptibility in 128 high-risk breast cancer families of Western European ancestry with no identified BRCA1 or BRCA2 mutations. No evidence of linkage was found. The estimated proportion (alpha) of families linked to a susceptibility locus at D13S1308, the location estimated by Kainu et al. [(2000) Proc. Natl. Acad. Sci. USA 97, 9603-9608], was 0 (upper 95% confidence limit 0.13). Adjustment for possible bias due to selection of families on the basis of linkage evidence at BRCA2 did not materially alter this result (alpha = 0, upper 95% confidence limit 0.18). The proportion of linked families reported by Kainu et al. (0.65) is excluded with a high degree of confidence in our dataset [heterogeneity logarithm of odds (HLOD) at alpha = 0.65 was -11.0]. We conclude that, if a susceptibility gene does exist at this locus, it can only account for a small proportion of non-BRCA1/2 families with multiple cases of early-onset breast cancer.