Prognostic gene expression signature for high-grade serous ovarian cancer.

BACKGROUND: Median overall survival (OS) for women with high-grade serous ovarian cancer (HGSOC) is ∼4 years, yet survival varies widely between patients. There are no well-established, gene expression signatures associated with prognosis. The aim of this study was to develop a robust prognostic signature for OS in patients with HGSOC. PATIENTS AND METHODS: Expression of 513 genes, selected from a meta-analysis of 1455 tumours and other candidates, was measured using NanoString technology from formalin-fixed paraffin-embedded tumour tissue collected from 3769 women with HGSOC from multiple studies. Elastic net regularization for survival analysis was applied to develop a prognostic model for 5-year OS, trained on 2702 tumours from 15 studies and evaluated on an independent set of 1067 tumours from six studies. RESULTS: Expression levels of 276 genes were associated with OS (false discovery rate < 0.05) in covariate-adjusted single-gene analyses. The top five genes were TAP1, ZFHX4, CXCL9, FBN1 and PTGER3 (P < 0.001). The best performing prognostic signature included 101 genes enriched in pathways with treatment implications. Each gain of one standard deviation in the gene expression score conferred a greater than twofold increase in risk of death [hazard ratio (HR) 2.35, 95% confidence interval (CI) 2.02-2.71; P < 0.001]. Median survival [HR (95% CI)] by gene expression score quintile was 9.5 (8.3 to -), 5.4 (4.6-7.0), 3.8 (3.3-4.6), 3.2 (2.9-3.7) and 2.3 (2.1-2.6) years. CONCLUSION: The OTTA-SPOT (Ovarian Tumor Tissue Analysis consortium - Stratified Prognosis of Ovarian Tumours) gene expression signature may improve risk stratification in clinical trials by identifying patients who are least likely to achieve 5-year survival. The identified novel genes associated with the outcome may also yield opportunities for the development of targeted therapeutic approaches.

Obesity and survival among women with ovarian cancer: results from the Ovarian Cancer Association Consortium.

BACKGROUND: Observational studies have reported a modest association between obesity and risk of ovarian cancer; however, whether it is also associated with survival and whether this association varies for the different histologic subtypes are not clear. We undertook an international collaborative analysis to assess the association between body mass index (BMI), assessed shortly before diagnosis, progression-free survival (PFS), ovarian cancer-specific survival and overall survival (OS) among women with invasive ovarian cancer. METHODS: We used original data from 21 studies, which included 12 390 women with ovarian carcinoma. We combined study-specific adjusted hazard ratios (HRs) using random-effects models to estimate pooled HRs (pHR). We further explored associations by histologic subtype. RESULTS: Overall, 6715 (54%) deaths occurred during follow-up. A significant OS disadvantage was observed for women who were obese (BMI: 30-34.9, pHR: 1.10 (95% confidence intervals (CIs): 0.99-1.23); BMI: ⩾35, pHR: 1.12 (95% CI: 1.01-1.25)). Results were similar for PFS and ovarian cancer-specific survival. In analyses stratified by histologic subtype, associations were strongest for women with low-grade serous (pHR: 1.12 per 5 kg m(-2)) and endometrioid subtypes (pHR: 1.08 per 5 kg m(-2)), and more modest for the high-grade serous (pHR: 1.04 per 5 kg m(-2)) subtype, but only the association with high-grade serous cancers was significant. CONCLUSIONS: Higher BMI is associated with adverse survival among the majority of women with ovarian cancer.

Clinical characteristics of ovarian cancer classified by BRCA1, BRCA2, and RAD51C status.

We evaluated homologous recombination deficient (HRD) phenotypes in epithelial ovarian cancer (EOC) considering BRCA1, BRCA2, and RAD51C in a large well-annotated patient set. We evaluated EOC patients for germline deleterious mutations (n = 899), somatic mutations (n = 279) and epigenetic alterations (n = 482) in these genes using NGS and genome-wide methylation arrays. Deleterious germline mutations were identified in 32 (3.6%) patients for BRCA1, in 28 (3.1%) for BRCA2 and in 26 (2.9%) for RAD51C. Ten somatically sequenced patients had deleterious alterations, six (2.1%) in BRCA1 and four (1.4%) in BRCA2. Fifty two patients (10.8%) had methylated BRCA1 or RAD51C. HRD patients with germline or somatic alterations in any gene were more likely to be high grade serous, have an earlier diagnosis age and have ovarian and/or breast cancer family history. The HRD phenotype was most common in high grade serous EOC. Identification of EOC patients with an HRD phenotype may help tailor specific therapies.

Variation in genes required for normal mitosis and risk of breast cancer.

The down-regulation of genes involved in normal cell division can cause aberrant mitoses and increased cell death. Surviving cells exhibit aneuploidy and/or polyploidy. Since mitotic disruption has been linked with tumor development and progression, alterations in the expression or activity of these mitotic regulators may contribute to breast tumor formation. We evaluated associations between common inherited variation in these genes and breast cancer risk. Two hundred and five tagging and candidate functional single nucleotide polymorphisms in 30 genes required for normal cell division were genotyped in 798 breast cancer cases and 843 controls from the Mayo Clinic breast cancer study. Two variants in EIF3A (rs10787899 and rs3824830; P < 0.01) and four variants in SART1 (rs660118, rs679581, rs754532, and rs735942; P(trend) < or = 0.02) were significantly associated with an altered risk of breast cancer along with single variants in RRM2, PSCD3, C11orf51, CDC16, SNW1, MFAP1, and CDC2 (P < 0.05). Variation in both SART1 (P = 0.009) and EIF3A (P = 0.02) was also significant at the gene level. Analyses suggested that SART1 SNPs rs660118 and rs679581 accounted for the majority of the association of that gene with breast cancer. The observed associations between breast cancer risk and genetic variation in the SART1 and EIF3A genes that are required for maintenance of normal mitosis suggest a direct role for these genes in the development of breast cancer.

Cell cycle genes and ovarian cancer susceptibility: a tagSNP analysis.

BACKGROUND: Dysregulation of the cell cycle is a hallmark of many cancers including ovarian cancer, a leading cause of gynaecologic cancer mortality worldwide. METHODS: We examined single nucleotide polymorphisms (SNPs) (n=288) from 39 cell cycle regulation genes, including cyclins, cyclin-dependent kinases (CDKs) and CDK inhibitors, in a two-stage study. White, non-Hispanic cases (n=829) and ovarian cancer-free controls (n=941) were genotyped using an Illumina assay. RESULTS: Eleven variants in nine genes (ABL1, CCNB2, CDKN1A, CCND3, E2F2, CDK2, E2F3, CDC2, and CDK7) were associated with risk of ovarian cancer in at least one genetic model. Seven SNPs were then assessed in four additional studies with 1689 cases and 3398 controls. Association between risk of ovarian cancer and ABL1 rs2855192 found in the original population [odds ratio, OR(BB vs AA) 2.81 (1.29-6.09), P=0.01] was also observed in a replication population, and the association remained suggestive in the combined analysis [OR(BB vs AA) 1.59 (1.08-2.34), P=0.02]. No other SNP associations remained suggestive in the replication populations. CONCLUSION: ABL1 has been implicated in multiple processes including cell division, cell adhesion and cellular stress response. These results suggest that characterization of the function of genetic variation in this gene in other ovarian cancer populations is warranted.

Validating genetic risk associations for ovarian cancer through the international Ovarian Cancer Association Consortium.

The search for genetic variants associated with ovarian cancer risk has focused on pathways including sex steroid hormones, DNA repair, and cell cycle control. The Ovarian Cancer Association Consortium (OCAC) identified 10 single-nucleotide polymorphisms (SNPs) in genes in these pathways, which had been genotyped by Consortium members and a pooled analysis of these data was conducted. Three of the 10 SNPs showed evidence of an association with ovarian cancer at P< or =0.10 in a log-additive model: rs2740574 in CYP3A4 (P=0.011), rs1805386 in LIG4 (P=0.007), and rs3218536 in XRCC2 (P=0.095). Additional genotyping in other OCAC studies was undertaken and only the variant in CYP3A4, rs2740574, continued to show an association in the replication data among homozygous carriers: OR(homozygous(hom))=2.50 (95% CI 0.54-11.57, P=0.24) with 1406 cases and 2827 controls. Overall, in the combined data the odds ratio was 2.81 among carriers of two copies of the minor allele (95% CI 1.20-6.56, P=0.017, p(het) across studies=0.42) with 1969 cases and 3491 controls. There was no association among heterozygous carriers. CYP3A4 encodes a key enzyme in oestrogen metabolism and our finding between rs2740574 and risk of ovarian cancer suggests that this pathway may be involved in ovarian carcinogenesis. Additional follow-up is warranted.

Progesterone receptor variation and risk of ovarian cancer is limited to the invasive endometrioid subtype: results from the Ovarian Cancer Association Consortium pooled analysis.

There is evidence that progesterone plays a role in the aetiology of invasive epithelial ovarian cancer. Therefore, genes involved in pathways that regulate progesterone may be candidates for susceptibility to this disease. Previous studies have suggested that genetic variants in the progesterone receptor gene (PGR) may be associated with ovarian cancer risk, although results have been inconsistent. We have established an international consortium to pool resources and data from many ovarian cancer case-control studies in an effort to identify variants that influence risk. In this study, three PGR single nucleotide polymorphisms (SNPs), for which previous data have suggested they affect ovarian cancer risk, were examined. These were +331 C/T (rs10895068), PROGINS (rs1042838), and a 3' variant (rs608995). A total of 4788 ovarian cancer cases and 7614 controls from 12 case-control studies were included in this analysis. Unconditional logistic regression was used to model the association between each SNP and ovarian cancer risk and two-sided P-values are reported. Overall, risk of ovarian cancer was not associated with any of the three variants studied. However, in histopathological subtype analyses, we found a statistically significant association between risk of endometrioid ovarian cancer and the PROGINS allele (n=651, OR=1.17, 95% CI=1.01-1.36, P=0.036). We also observed borderline evidence of an association between risk of endometrioid ovarian cancer and the +331C/T variant (n=725 cases; OR=0.80, 95% CI 0.62-1.04, P=0.100). These data suggest that while these three variants in the PGR are not associated with ovarian cancer overall, the PROGINS variant may play a modest role in risk of endometrioid ovarian cancer.

Polymorphic variation in hOGG1 and risk of cancer: a review of the functional and epidemiologic literature.

The gene encoding human 8-oxoguanine glycosylase 1 (hOGG1) is involved in DNA base excision repair. The encoded DNA glycosylase excises 7,8-dihydro-8-oxoguanine (8-OHdG), a highly mutagenic base produced in DNA as a result of exposure to reactive oxygen species (ROS). Polymorphisms in this gene may alter glycosylase function and an individual's ability to repair damaged DNA, possibly resulting in genetic instability that can foster carcinogenesis. In order to elucidate the possible impact of polymorphisms in hOGG1, we performed a literature review of both functional and epidemiologic studies that assessed the effects of these polymorphisms on repair function, levels of oxidative DNA damage, or associations with cancer risk. Fourteen functional studies and 19 epidemiologic studies of breast, colon, esophageal, head and neck, lung, nasopharyngeal, orolaryngeal, prostate, squamous cell carcinoma of the head and neck (SCCHN), and stomach cancers were identified. Although the larger functional studies suggest reduced repair function with variant alleles in hOGG1, the evidence is generally inconclusive. There is some epidemiologic evidence that risk for esophageal, lung, nasopharyngeal, orolaryngeal, and prostate is related to hOGG1 genotype, whereas risk of breast cancer does not appear related. In studies that explored potential interactions with environmental factors, cancer risk for hOGG1 genotypes differed depending on exposure, especially for colon cancer. In summary, there is limited evidence that polymorphisms in hOGG1 affect repair function and carcinogenesis. Larger, well-designed functional and epidemiologic studies are needed to clarify these relationships, especially with respect to interactions with other DNA repair enzymes and interactions with environmental factors that increase carcinogenic load.

Familial correlations, segregation analysis, and nongenetic correlates of soy isoflavone-metabolizing phenotypes.

Particular intestinal bacteria metabolize the soy isoflavone daidzein to equol and O-desmethylangolensin (O-DMA), metabolites that can be identified in urine. Individuals that harbor bacteria capable of producing equol or O-DMA are known as equol producers (approximately 30%-50% of the population) and O-DMA producers (approximately 80%-90% of the population), respectively. The equol-producer phenotype has been associated with sex hormone-related outcomes in several studies. However, the bacteria responsible for these phenotypes have not yet been identified and factors that influence the manifestation of these phenotypes are not well understood. To evaluate familial clustering of and nongenetic factors associated with these phenotypes, 410 individuals from 112 families participated in phenotyping (3-day soy challenge and Day 4 spot urine collection). In segregation analyses of the equol-producer phenotype, the Mendelian dominant model provided the most parsimonious fit to the data, suggesting that the pattern of inheritance of the equol-producer phenotype is consistent with an autosomal dominant trait. This phenotype was positively associated with education (p trend = 0.01), but not with sex, smoking, or several dietary factors. Results of the segregation analyses of the O-DMA-producer phenotype were inconclusive; no other models provided a more parsimonious fit to the data than the general model. This phenotype was inversely associated with age in a nonlinear model (p = 0.01), positively associated with age- and sex-adjusted height (odds ratio [OR] 10-cm increase = 0.38, 95% confidence interval [CI] = 0.15, 0.95) and body mass index (kg/m(2)) (OR = 0.91, 95% CI = 0.85, 0.96), but not with sex, education, smoking, or several dietary factors. These results suggest the equol-producer phenotype may be under some degree of genetic control and that there are likely other environmental factors not evaluated in the present analysis that contribute to both of these phenotypes. These results provide a foundation for further work to refine our understanding of heritable and environmental determinants of daidzein-metabolizing phenotypes.

Clinical characteristics of prostate cancer in an analysis of linkage to four putative susceptibility loci.

PURPOSE: Hereditary prostate cancer is an etiologically heterogeneous disease with six susceptibility loci mapped to date. We aimed to describe a collection of high-risk prostate cancer families and assess linkage to multiple markers at four loci: HPC1 (1q24-25), PCaP (1q42.2-43), HPCX (Xq27-28), and CAPB (1p36). EXPERIMENTAL DESIGN: Medical record data on 505 affected men in 149 multiply-affected prostate cancer families were reviewed, and correlations of clinical traits within each family were calculated. Logarithm of odds (LOD) score and nonparametric (NPL) linkage analyses were performed; white families were stratified by age of diagnosis, grade and stage of disease, and evidence of linkage to the other loci to increase genetic homogeneity. RESULTS: Age at diagnosis was the most correlated clinical trait within families. A maximum NPL score of 2.61 (P = 0.007) appeared to confirm HPC1 linkage for families that had a prevalence of high-grade or advanced-stage prostate cancer and which were not likely to be linked to PCaP, HPCX, or CAPB. Because the NPL scores improved when families more likely to be linked to the other loci were excluded, HPC1 may act independently of the other loci. The relationship of HPC1 and aggressive disease was strongest in families with median age at diagnosis > or =65 years (NPL, 3.48; P = 0.0008). CONCLUSIONS: The current results suggest that HPC1 linkage may be most common among families with more severe prostate cancer. Stratification by clinical characteristics may be a useful tool in prostate cancer linkage analyses and may increase our understanding of hereditary prostate cancer.

Genetic linkage analysis of prostate cancer families to Xq27-28.

OBJECTIVES: A recent linkage analysis of 360 families at high risk for prostate cancer identified the q27-28 region on chromosome X as the potential location of a gene involved in prostate cancer susceptibility. Here we report on linkage analysis at this putative HPCX locus in an independent set of 186 prostate cancer families participating in the Prostate Cancer Genetic Research Study (PROGRESS). METHODS: DNA samples from these families were genotyped at 8 polymorphic markers spanning 14.3 cM of the HPCX region. RESULTS: Two-point parametric analysis of the total data set resulted in positive lod scores at only two markers, DXS984 and DXS1193, with scores of 0.628 at a recombination fraction (theta) of 0.36 and 0.012 at theta = 0.48, respectively. The stratification of pedigrees according to the assumed mode of transmission increased the evidence of linkage at DXS984 in 81 families with no evidence of male-to-male transmission (lod = 1.062 at theta = 0.28). CONCLUSIONS: Although this analysis did not show statistically significant evidence for the linkage of prostate cancer susceptibility to Xq27-28, the results are consistent with a small percentage of families being linked to this region. The analysis further highlights difficulties in replicating linkage results in an etiologically heterogeneous, complexly inherited disease.

A genomic scan of families with prostate cancer identifies multiple regions of interest.

A 10-cM genomewide scan of 94 families with hereditary prostate cancer, including 432 affected men, was used to identify regions of putative prostate cancer-susceptibility loci. There was an average of 3.6 affected, genotyped men per family, and an overall mean age at diagnosis of 65.4 years. A total of 50 families were classified as early onset (mean age at diagnosis <66 years), and 44 families were classified as later onset (mean age at diagnosis > or =66 years). When the entire data set is considered, regions of interest (LOD score > or =1.5) were identified on chromosomes 10, 12, and 14, with a dominant model of inheritance. Under a recessive model LOD scores > or =1.5 were found on chromosomes 1, 8, 10, and 16. Stratification by age at diagnosis highlighted a putative susceptibility locus on chromosome 11, among the later-onset families, with a LOD score of 3. 02 (recombination fraction 0) at marker ATA34E08. Overall, this genomic scan suggests that there are multiple prostate cancer loci responsible for the hereditary form of this common and complex disease and that stratification by a variety of factors will be required for identification of all relevant genes.

Linkage analysis of 150 high-risk prostate cancer families at 1q24-25.

Confirmation of linkage and estimation of the proportion of families who are linked in large independent datasets is essential to understanding the significance of cancer susceptibility genes. We report here on an analysis of 150 high-risk prostate cancer families (2,176 individuals) for potential linkage to the HPC1 prostate cancer susceptibility locus at 1q24-25. This dataset includes 640 affected men with an average age at prostate cancer diagnosis of 66. 8 years (range, 39-94), representing the largest collection of high-risk families analyzed for linkage in this region to date. Linkage to multiple 1q24-25 markers was strongly rejected for the sample as a whole (lod scores at theta = 0 ranged from -30.83 to -18. 42). Assuming heterogeneity, the estimated proportion of families linked (alpha) at HPC1 in the entire dataset was 2.6%, using multipoint analysis. Because locus heterogeneity may lead to false rejection of linkage, data were stratified based on homogeneous subsets. When restricted to 21 Caucasian families with five or more affected family members and mean age at diagnosis < = 65 years, the lod scores at theta = 0 remained less than -4.0. These results indicate that the overall portion of hereditary prostate cancer families whose disease is due to inherited variation in HPC1 may be less than originally estimated.

Impact of family structure on the power of linkage tests using sib-pair methods.

This analysis sought to determine the impact of specific ascertainment criteria based upon nuclear family affectation structures. Specifically, we evaluated the predicted and observed proportion of alleles shared identical by descent conditional on the number of affected and unaffected siblings in a pedigree, and compared sib-pair method linkage results under two ascertainment schemes, random vs. selected ascertainment, for this simulated complex genetic disease. These results suggest that samples differing in the composition of affected and unaffected siblings in the family will differ in their power to detect linkage. An effect of sampling scheme on power to map using affected-sib-pair methods should be considered when a reported linkage is not found in another study population.

Analysis of chromosome 1q42.2-43 in 152 families with high risk of prostate cancer.

One hundred fifty-two families with prostate cancer were analyzed for linkage to markers spanning a 20-cM region of 1q42.2-43, the location of a putative prostate cancer-susceptibility locus (PCAP). No significant evidence for linkage was found, by use of both parametric and nonparametric tests, in our total data set, which included 522 genotyped affected men. Rejection of linkage may reflect locus heterogeneity or the confounding effects of sporadic disease in older-onset cases; therefore, pedigrees were stratified into homogeneous subsets based on mean age at diagnosis of prostate cancer and number of affected men. Analyses of these subsets also detected no significant evidence for linkage, although LOD scores were positive at higher recombination fractions, which is consistent with the presence of a small proportion of families with linkage. The most suggestive evidence of linkage was in families with at least five affected men (nonparametric linkage score of 1.2; P=.1). If heterogeneity is assumed, an estimated 4%-9% of these 152 families may show linkage in this region. We conclude that the putative PCAP locus does not account for a large proportion of these families with prostate cancer, although the linkage of a small subset is compatible with these data.

Evidence for a rare prostate cancer-susceptibility locus at chromosome 1p36.

Combining data from a genomic screen in 70 families with a high risk for prostate cancer (PC) with data from candidate-region mapping in these families and an additional 71 families, we have localized a potential hereditary PC-susceptibility locus to chromosome 1p36. Because an excess of cases of primary brain cancer (BC) have been observed in some studies of families with a high risk for PC, and because loss of heterozygosity at 1p36 is frequently observed in BC, we further evaluated 12 families with both a history of PC and a blood relative with primary BC. The overall LOD score in these 12 families was 3.22 at a recombination fraction (theta) of .06, with marker D1S507. On the basis of an a priori hypothesis, this group was stratified by age at diagnosis of PC. In the younger age group (mean age at diagnosis <66 years), a maximum two-point LOD score of 3.65 at straight theta = .0 was observed, with D1S407. This linkage was rejected in both early- and late-onset families without a history of BC (LOD scores -7.12 and -6.03, respectively, at straight theta = .0). After exclusion of 3 of the 12 families that had better evidence of linkage to previously described PC-susceptibility loci, linkage to the 1p36 region was suggested by a two-point LOD score of 4.74 at straight theta = .0, with marker D1S407. We conclude that a significant proportion of these families with both a high risk for PC and a family member with BC show linkage to the 1p36 region.

Confirmation of prostate cancer susceptibility genes using high-risk families.

Data from many types of studies support the hypothesis that strong familial components are involved in the etiology of prostate cancer. One way to access such genes is through the study of families with multiple affected family members and, in particular, families with individuals affected comparatively early in life. Several prostate cancer susceptibility loci have been described to date. Confirmation of the linkage and estimation of the proportion of families who are linked in large independent datasets is essential to understanding the significance of susceptibility genes. We explore the methodology used to perform such studies and the factors that can limit the ability to confirm linkage results. We report specifically the example of the HPC1 gene on 1q24-25.

Linkage analysis of 49 high-risk families does not support a common familial prostate cancer-susceptibility gene at 1q24-25.

Linkage of a putative prostate cancer-susceptibility locus (HPC1) to chromosome 1q24-25 has recently been reported. Confirmation of this linkage in independent data sets is essential because of the complex nature of this disease. Here we report the results of a linkage analysis using 10 polymorphic markers spanning approximately 37 cM in the region of the putative HPC1 locus in 49 high-risk prostate cancer families. Data were analyzed by use of two parametric models and a nonparametric method. For the parametric LOD-score method, the first model was identical to the original report by Smith and coworkers ("Hopkins"), and the second was based on a segregation analysis previously reported by Carter and coworkers ("Seattle"). In both cases, our results do not confirm the linkage reported for this region. Calculated LOD scores from the two-point analysis for each marker were highly negative at small recombination fractions. Multipoint LOD scores for this linkage group were also highly negative. Additionally, we were unable to demonstrate heterogeneity within the data set, using HOMOG. Although these data do not formally exclude linkage of a prostate cancer-susceptibility locus at HPC1, it is likely that other prostate cancer-susceptibility loci play a more critical role in the families that we studied.

Evidence that the apolipoprotein E-genotype effects on lipid levels can change with age in males: a longitudinal analysis.

We previously reported that change, with age, in plasma levels of total cholesterol (TC) and LDL cholesterol (LDL-C) differed between apolipoprotein E (APOE) genotypes epsilon 3 epsilon 3 and epsilon 3 epsilon 4, in a sample of 77 older, unrelated males. By use of a larger sample from that cohort, followed longitudinally during 1969-87, the change in TC and in LDL-C, between the epsilon 3 epsilon 3 and epsilon 3 epsilon 4 APOE genotypes, over three exams, was reanalyzed. Additionally, the change in triglycerides (TG) and in HDL-cholesterol (HDL-C), between the epsilon 3 epsilon 3 and epsilon 3 epsilon 4 APOE genotypes-as well as the differences between the epsilon 3 epsilon 3 and epsilon 3 epsilon 2 genotypes, for TC, LDL-C, TG, and HDL-C-were contrasted over the three exams. At exam 1 TG was higher in the epsilon 3 epsilon 4 group than in the epsilon 3 epsilon 3 group (mean age 48 years), and at exams 2 and exam 3 (mean ages 58 and 63 years, respectively) it was similar (P = .009 for the exam-by-genotype-interaction effect in the repeated-measures analysis). A similar trend was seen for TC (P = .03), yet previously detected LDL-C effects were not apparent (P = .46). Those with the epsilon 3 epsilon 2 genotype had higher TG and lower LDL-C and TC at each exam than were seen in those with the epsilon 3 epsilon 3 genotype, although the differences in the values were not always statistically significant. Differences in TC, LDL-C, and TG, between the epsilon 3 epsilon 2-genotype and epsilon 3 epsilon 3-genotype groups, did not significantly change over the three exams. HDL-C levels were relatively stable over the exams; however, the exam-by-genotype interaction was significant for the epsilon 3 epsilon 2 genotype versus the epsilon 3 epsilon 3 genotype (P = .02). The epsilon 4 allele effects on TG and TC changed between longitudinal exams and may be age dependent. Changes, with age, in the effect of the epsilon 3 epsilon 4 genotype on lipids may impact the risk of developing atherosclerotic disease.

Segregation and linkage analysis of a quantitative versus a qualitative trait in large pedigrees.

Goals of this analysis were to map loci contributing to variation in the quantitative trait, Q1, using the lod-score method on data set 1, and to explore the difference in power to map genes when considering the discrete vs. quantitative phenotype. Segregation analyses, after covariate adjustment, correctly suggested two contributing loci. The major gene on chromosome 5 was successfully mapped, but the major gene on chromosome 8 was not. Comparison of linkage analyses for the qualitative and quantitative traits confirmed that the quantitative trait is more informative, suggesting that localizing disease genes with a qualitative trait would be more difficult in these pedigrees.