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Regression models for linkage heterogeneity applied to familial prostate cancer.

ABSTRACT: Linkage heterogeneity frequently occurs for complex genetic diseases, and statistical methods must account for it to avoid severe loss in power to discover susceptibility genes. A common method to allow for only a fraction of linked pedigrees is to fit a mixture likelihood and then to test for linkage homogeneity, given linkage (admixture test), or to test for linkage while allowing for heterogeneity, using the heterogeneity LOD (HLOD) score. Furthermore, features of the families, such as mean age at diagnosis, may help to discriminate families that demonstrate linkage from those that do not. Pedigree features are often used to create homogeneous subsets, and LOD or HLOD scores are then computed within the subsets. However, this practice introduces several problems, including reduced power (which results from multiple testing and small sample sizes within subsets) and difficulty in interpretation of results. To address some of these limitations, we present a regression-based extension of the mixture likelihood for which pedigree features are used as covariates that determine the probability that a family is the linked type. Some advantages of this approach are that multiple covariates can be used (including quantitative covariates), covariates can be adjusted for each other, and interactions among covariates can be assessed. This new regression method is applied to linkage data for familial prostate cancer and provides new insights into the understanding of prostate cancer linkage heterogeneity.

SUBMITTER: Schaid DJ

PROVIDER: S-EPMC1226099 | biostudies-literature | 2001 May

REPOSITORIES: biostudies-literature

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Regression models for linkage heterogeneity applied to familial prostate cancer.

Schaid D J DJ McDonnell S K SK Thibodeau S N SN

American journal of human genetics 20010413 5

Linkage heterogeneity frequently occurs for complex genetic diseases, and statistical methods must account for it to avoid severe loss in power to discover susceptibility genes. A common method to allow for only a fraction of linked pedigrees is to fit a mixture likelihood and then to test for linkage homogeneity, given linkage (admixture test), or to test for linkage while allowing for heterogeneity, using the heterogeneity LOD (HLOD) score. Furthermore, features of the families, such as mean a ...[more]

PMID: 11309684

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Project description:To investigate the relationship between HPC2/ELAC2 and prostate cancer risk, we performed the following analyses: (1) a linkage study of six markers in and around the HPC2/ELAC2 gene at 17p11 in 159 pedigrees with hereditary prostate cancer (HPC); (2) a mutation-screening analysis of all coding exons of the gene in 93 probands with HPC; (3) family-based and population-based association study of common HPC2/ELAC2 missense variants in 159 probands with HPC, 249 patients with sporadic prostate cancer, and 222 unaffected male control subjects. No evidence for linkage was found in the total sample, nor in any subset of pedigrees based on characteristics that included age at onset, number of affected members, male-to-male disease transmission, or race. Furthermore, only the two previously reported missense changes (Ser217Leu and Ala541Thr) were identified by mutational analysis of all HPC2/ELAC exons in 93 probands with HPC. In association analyses, family-based tests did not reveal excess transmission of the Leu217 and/or Thr541 alleles to affected offspring, and population-based tests failed to reveal any statistically significant difference in the allele frequencies of the two polymorphisms between patients with prostate cancer and control subjects. The results of this study lead us to reject the three alternative hypotheses of (1) a highly penetrant, major prostate cancer-susceptibility gene at 17p11, (2) the allelic variants Leu217 or Thr541 of HPC2/ELAC2 as high-penetrance mutations, and (3) the variants Leu217 or Thr541 as low-penetrance, risk-modifying alleles. However, we did observe a trend of higher Leu217 homozygous carrier rates in patients than in control subjects. Considering the impact of genetic heterogeneity, phenocopies, and incomplete penetrance on the linkage and association studies of prostate cancer and on the power to detect linkage and association in our study sample, our results cannot rule out the possibility of a highly penetrant prostate cancer gene at this locus that only segregates in a small number of pedigrees. Nor can we rule out a prostate cancer-modifier gene that confers a lower-than-reported risk. Additional larger studies are needed to more fully evaluate the role of this gene in prostate cancer risk.

Project description:BackgroundCommercial gene expression assays are guiding clinical decision making in patients with prostate cancer, particularly when considering active surveillance. Given heterogeneity and multifocality of primary prostate cancer, such assays should ideally be robust to the coexistence of unsampled higher grade disease elsewhere in the prostate in order to have clinical utility. Herein, we comprehensively evaluated transcriptomic profiles of primary multifocal prostate cancer to assess robustness to clinically relevant multifocality.MethodsWe designed a comprehensive, multiplexed targeted RNA-sequencing assay capable of assessing multiple transcriptional classes and deriving commercially available prognostic signatures, including the Myriad Prolaris Cell Cycle Progression score, the Oncotype DX Genomic Prostate Score, and the GenomeDX Decipher Genomic Classifier. We applied this assay to a retrospective, multi-institutional cohort of 156 prostate cancer samples. Derived commercial biomarker scores for 120 informative primary prostate cancer samples from 44 cases were determined and compared.ResultsDerived expression scores were positively correlated with tumor grade (rS = 0.53-0.73; all P < 0.001), both within the same case and across the entire cohort. In cases of extreme grade-discordant multifocality (co-occurrence of grade group 1 [GG1] and ?GG4 foci], gene expression scores were significantly lower in low- (GG1) versus high-grade (?GG4) foci (all P < 0.001). No significant differences in expression scores, however, were observed between GG1 foci from prostates with and without coexisting higher grade cancer (all P > 0.05).ConclusionsMultifocal, low-grade and high-grade prostate cancer foci exhibit distinct prognostic expression signatures. These findings demonstrate that prognostic RNA expression assays performed on low-grade prostate cancer biopsy tissue may not provide meaningful information on the presence of coexisting unsampled aggressive disease.FundingProstate Cancer Foundation, National Institutes of Health (U01 CA214170, R01 CA183857, University of Michigan Prostate Specialized Program of Research Excellence [S.P.O.R.E.] P50 CA186786-05, Weill Cornell Medicine S.P.O.R.E. P50 CA211024-01A1), Men of Michigan Prostate Cancer Research Fund, University of Michigan Comprehensive Cancer Center core grant (2-P30-CA-046592-24), A. Alfred Taubman Biomedical Research Institute, and Department of Defense.

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Regression models for linkage heterogeneity applied to familial prostate cancer.

Publications

Regression models for linkage heterogeneity applied to familial prostate cancer.

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