Analytical relationship between family history and genetic and environmental risks, with application to female breast cancer

It is well established in genetic epidemiology that family history is an important indicator of familial aggregation of disease in a family. A strong genetic risk factor or an environmental risk factor with high familial correlation can result in a strong family history. In this paper, family history refers to the number of first-degree relatives affected with the disease. Cui and Hopper (Journal of Epidemiology and Biostatistics 2001; 6: 331-342) proposed an analytical relationship between family history and relevant genetic parameters. In this paper we expand the relationship to both genetic and environmental risk factors. We established a closed-form formula for family history as a function of genetic and environmental parameters which include genetic and environmental relative risks, genotype frequency, prevalence and familial correlation of the environmental risk factor. The relationship is illustrated by an example of female breast cancer in Australia. For genetic and environmental relative risks less than 10, most of the female breast cancer cases occur between the age of 40 and 60 years. A higher genetic or environmental relative risk will move the peak of the distribution to a younger age. A more common disease allele or more prevalent environmental risk factor will move the peak to an older age. For a proband with breast cancer, it is most likely (with probability ge80%) that none of her first-degree relatives is affected with the disease. To enable the probability of having a positive family history to reach 50%, the environmental relative risks must be extremely as high as 100, the familial correlation as high as 0.8 and the prevalence as low as 0.1. For genetic risk alone, even the relative risk is as high as 100, the probability of having a positive family history can only reach about 30%. This suggests that the environmental risk factor seems to play a more important role in determining a strong family history than the genetic risk factor.

Regressive logistic and proportional hazards disease models for within-family analyses of measured genotypes, with application to a CYP17 polymorphism and breast cancer

Various statistical methods have been proposed to evaluate associations between measured genetic variants and disease, including some using family designs. For breast cancer and rare variants, we applied a modified segregation analysis method that uses the population cancer incidence and population-based case families in which a mutation is known to be segregating. Here we extend the method to a common polymorphism, and use a regressive logistic approach to model familial aggregation by conditioning each individual on their mother's breast cancer history. We considered three models: 1) class A regressive logistic model; 2) age-of-onset regressive logistic model; and 3) proportional hazards familial model. Maximum likelihood estimates were calculated using the software MENDEL. We applied these methods to data from the Australian Breast Cancer Family Study on the CYP17 5UTR TC MspA1 polymorphism measured for 1,447 case probands, 787 controls, and 213 relatives of case probands found to have the CC genotype. Breast cancer data for first- and second-degree relatives of case probands were used. The three methods gave consistent estimates. The best-fitting model involved a recessive inheritance, with homozygotes being at an increased risk of 47% (95% CI, 28-68%). The cumulative risk of the disease up to age 70 years was estimated to be 10% or 22% for a CYP17 homozygote whose mother was unaffected or affected, respectively. This analytical approach is well-suited to the data that arise from population-based case-control-family studies, in which cases, controls and relatives are studied, and genotype is measured for some but not all subjects.

Genome - wide association study identifies novel breast cancer susceptibility loci

Breast cancer exhibits familial aggregation, consistent with variation in genetic susceptibility to the disease. Known susceptibility genes account for less than 25% of the familial risk of breast cancer, and the residual genetic variance is likely to be due to variants conferring more moderate risks. To identify further susceptibility alleles, we conducted a two-stage genome-wide association study in 4,398 breast cancer cases and 4,316 controls, followed by a third stage in which 30 single nucleotide polymorphisms (SNPs) were tested for confirmation in 21,860 cases and 22,578 controls from 22 studies. We used 227,876 SNPs that were estimated to correlate with 77% of known common SNPs in Europeans at r² > 0.5. SNPs in five novel independent loci exhibited strong and consistent evidence of association with breast cancer (P < 10^-7). Four of these contain plausible causative genes (FGFR2, TNRC9, MAP3K1 and LSP1). At the second stage, 1,792 SNPs were significant at the P < 0.05 level compared with an estimated 1,343 that would be expected by chance, indicating that many additional common susceptibility alleles may be identifiable by this approach.

Risk of prostate cancer associated with a family history in an era of rapid increase in prostate cancer diagnosis (Australia)

OBJECTIVE: We conducted a case-control study of prostate cancer and familial risk of the disease in Australia between 1994 and 1998, a period during which the incidence of prostate cancer increased dramatically with widespread use of prostate-specific antigen (PSA) testing. METHODS: 1475 cases and 1405 controls were asked about prostate cancer in their first-degree relatives. Odds ratios (OR) were calculated using logistic regression. RESULTS: Cases were more likely to report a family history of prostate cancer than controls (OR 3.0; 95% confidence interval (CI) 2.3-3.9) and cases reporting an affected relative were younger (58.8 versus 60.9 years, p < 0.0001). The OR for an affected first-degree relative increased with increasing number of affected relatives and decreased with increasing age of the case. The OR for more than one affected first-degree relative was 6.9 (95% CI 2.7-18). The OR for an affected brother was 3.9 (95% CI 2.5-6.1) and for an affected father was 2.9 (95% CI 2.1-3.9) but these were not significantly different (p = 0.2). When analyses were repeated including only diagnoses made in relatives prior to 1992, the risks were generally similar except that the OR for an affected brother decreased to 3.1 (95% CI 1.2-3.9). When only relatives' diagnoses made after 1991 were included results were again similar to those for all relatives, although the effect for brothers was greater and the attenuation with age at diagnosis dissipated. CONCLUSIONS: The recent introduction of PSA testing that has resulted in a greater prevalence of apparent prostate cancer, does not appear to have substantially altered familial risks of disease, although effects associated with brothers may be inflated.