Introduction
Individualized risk prediction is a major goal of clinical genetics. For prediction of breast cancer risk, family history is an important factor, women with a first-degree relative having twofold increased risk [
1], while women from families with multiple breast/ovarian cancers or cancers diagnosed at younger age experience a much higher risk of developing the disease [
2]. Rare mutations in high- and moderate-risk genes including
BRCA1,
BRCA2,
TP53, PTEN,
PALB2, and
CHEK2 explain about 20 % of the familial relative risk for breast cancer [
3]. A polygenic component comprising many variants of small effect contributes to the risk of developing the disease in the general population and may also modify the risk in cancer families [
3‐
5].
Over the last few years, genome-wide association studies (GWAS) have been successful in identifying some of the common low-penetrance variants predisposing to breast cancer [
6‐
8]. To date, more than seventy variants have been identified, which together explain about 14 % of the familial risk of breast cancer [
5,
6]. Individually, the effect sizes associated with these common variants are small. However, their combined effect, summarized as a polygenic risk score (PRS), is more substantial [
5]. In a recent population-based case–control study, eight percent of women at the high end of the PRS distribution were found to fall into a group of intermediate life-time risk (17–30 %) according to the UK NICE guidelines [
9]. In recent studies, the PRS has been tested in combination with other risk prediction methods, such as BOADICEA and BRCAPRO [
10], mammographic density (BI-RADS) [
11], and a combination of family history and established risk factors (BCRAT and IBIS) [
10].
The contribution of the PRS to disease risk for individuals with family history of breast cancer and within breast cancer families has not been studied extensively. Here, we investigate the association between a 75-variant PRS and disease status in individuals with and without family history in a large Finnish case–control study and 52 Finnish breast cancer families, which have an extensive pedigree information available and which have been well characterized in terms of their genetic and pathological characteristics. We use a family history score based on the BOADICEA risk prediction algorithm to evaluate whether the PRS predicts disease status among women sharing similar family history, and discuss clinical utility of the PRS for risk prediction in familial breast cancer.
Discussion
In this paper, we have investigated the potential of the PRS to improve risk stratification in the setting of familial breast cancer. The PRS we constructed used information from 75 variants, almost all breast cancer susceptibility variants known to date. We tested for association of this PRS with breast cancer risk among different groups according to their family history of breast cancer. The PRS was on average higher in patients with family history of breast cancer in a first-degree relative than in sporadic cases in the case–control dataset (Table
1). We neither saw a difference in the PRS between the “large” and “small” families, nor an increasing trend with the number of affected first-degree relatives within the family dataset. Epidemiological studies have reported life-time risk for women with two affected first-degree relatives to be higher than for women with only one affected relative (21.1 vs. 13.3 %) [
1]. This difference was not reflected in a change in PRS, although power for this comparison was limited in our dataset (Table
1, Supplementary Fig. 1). The PRS was significantly associated with increased risk of breast cancer within the breast cancer families, when comparing affected to healthy women. Furthermore, the PRS was higher among the healthy women of the breast cancer families compared with healthy controls from the population (Table
1, Supplementary Fig. 1), supporting the notion that common genetic risk variants cluster in breast cancer families.
Our 52 breast cancer families comprised 427 genotyped and ~4000 nongenotyped individuals. The proportion of affected women in the breast cancer families ranged between 6 and 67 % per family (median 22 %) (Supplementary Table 2). Two-thirds of the healthy women of the dataset were first-degree relatives of the breast cancer cases, and the remainder second- or third-degree relatives. The BOADICEA risk prediction algorithm is able to capture complex family structure, including information on more distant relatives as well as information on ages of diagnosis or interview, and is more informative than simpler measures of family history. We therefore calculated a ‘BOADICEA score’ as an estimate of the mean polygenotype for each individual, given their family history. The correlation between our BOADICEA score and the PRS in affected women from the 52 breast cancer families was 0.15, consistent with the relatively small fraction of the heritability explained by these variants. As expected, the correlation among the healthy women was lower (Pearson’s
r = 0.0099). These estimates are somewhat higher than that reported recently between PRS and BOADICEA risk prediction output (0.01 [−0.05–0.07]) by an Australian study [
10]. This could be explained partly by the different study designs, as the Australian study included a large number of sporadic cases, and any pedigree data were collected by interview, whereas we collected family data systematically from population and cancer registries. Furthermore, they included in the correlation both breast cancer cases and healthy controls, which may have masked an existing correlation in cases.
The PRS was significantly associated with breast cancer risk in a logistic regression model adjusted for age and the BOADICEA score (OR: 1.55 [1.26–1.91]). The magnitude of the effect size associated with the PRS was consistent with the estimate made in the unselected series of the case–control dataset (OR: 1.49 [1.38–1.62]) and with the estimate reported in a recent population-based study (OR: 1.55 [1.52–1.58]) [
5], and provides further support for using the PRS in risk prediction. Furthermore, when the model was adjusted for the moderate-penetrance mutations in
CHEK2,
PALB2, and
FANCM, the OR associated with the PRS was very similar (1.59 [1.28–1.98]) supporting a multiplicative mode of interaction between the low- and moderate-penetrance genetic variants. This is been demonstrated explicitly for CHEK2:c.1100delC and the PRS (Muranen et al. in review), but further analyses in larger datasets would be needed to evaluate such interactions for the
FANCM and
PALB2 variants.
A recent study examined the utility of the PRS for risk prediction in breast cancer families in the BCFR [
27]; our results are broadly in agreement with the conclusions of this prospective study. This study used only 24 variants rather than the full complement of 75 (or 77 as in [
5]), so we would have expected to see a larger effect size in our study. However, we were not able to directly compare the effect sizes reported, as the BCFR-study was prospective in design, used Cox regression for modeling, and the effect of the PRS was studied in the context of 10-year BOADICEA risk estimates. In addition, individuals with moderate-penetrance mutations were excluded from their analyses, while these individuals were included in our analyses.
Our results on subtype-specific associations are consistent with previous observations that most common genetic variants are more strongly associated with ER-positive disease, while fewer ER-negative specific variants have been identified. Although pathology information in the familial study was limited, we noted a higher proportion of ER-negative cancers among women with the lowest PRS in this study. Noteworthy, none of these cancers were from carriers of
PALB2 or
FANCM mutations, which have been previously associated with ER-negative disease [
19,
20]. It would be of interest to study the pathology of breast cancers within families and evaluate any correlations in the context of the PRS.
The effect sizes associated with the PRS can be used to derive estimates of the absolute risk of breast cancer according to PRS [
5]. In women with a family history of breast cancer, the baseline absolute risk of developing breast cancer is higher. Our observations indicate that the relative risks associated with the PRS are similar to those in the general population, consistent with a model in which the PRS multiplies the effects of other familial risk factors. Hence, the effect of the PRS on the absolute risk of disease will be much greater than in the general population. For example, if the pedigree-based familial risk for a woman was about 17 % [
9], and her PRS was in the highest 20 centile, the combined risk would be 30.9 %, moving her from intermediate- to high-risk category according to UK NICE guidelines [
9]. By comparison, women with no data on family history would have to be in the top centile of the PRS to have the same absolute risk (~30 %). We did not find support for the protective effect associated with low PRS-values (Fig.
1). This may reflect low power, as few women have very low PRS in the breast cancer families. However, it might be explained by the presence of yet-unidentified moderate/high-risk genetic or shared environmental factors [
28].
Acknowledgments
We thank all the individuals taking part in this study; Drs. Kirsimari Aaltonen, Tuomas Heikkinen, Päivi Heikkilä and Karl von Smitten for their help with the patient samples and data; and research nurse Irja Erkkilä for the assistance in the data collection and management. This work was supported by the Helsinki University Hospital Research Fund, the Finnish Cancer Society, the Nordic Cancer Union, the Academy of Finland [266528] and the Sigrid Juselius Foundation. The work of TAM has been supported by Finnish Cultural Foundation and Orion-Farmos Research Foundation. Genotyping of the iCOGS array, and the Breast Cancer Association Consortium, was supported by Cancer Research UK (C1287/A10118, C1287/A12014, C1287/A10710) and by the European Community's Seventh Framework Programme under grant agreement n° 223175 (HEALTH-F2-2009-223175) (COGS). NM was supported by Cancer Research UK (C1287/ C1287/A16563) and the PERSPECTIVE project, funded from the Government of Canada through Genome Canada and the Canadian Institutes of Health Research. AL was supported by Cancer Research UK.
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