Assessment of Rare BRCA1 and BRCA2 Variants of Unknown Significance Using Hierarchical Modeling

Department of Epidemiology and Biostatistics, Memorial Sloan-Kettering Cancer Center, New York, NY 10065, USA.
Genetic Epidemiology (Impact Factor: 2.6). 07/2011; 35(5):389-97. DOI: 10.1002/gepi.20587
Source: PubMed


Current evidence suggests that the genetic risk of breast cancer may be caused primarily by rare variants. However, while classification of protein-truncating mutations as deleterious is relatively straightforward, distinguishing as deleterious or neutral the large number of rare missense variants is a difficult on-going task. In this article, we present one approach to this problem, hierarchical statistical modeling of data observed in a case-control study of contralateral breast cancer (CBC) in which all the participants were genotyped for variants in BRCA1 and BRCA2. Hierarchical modeling permits leverage of information from observed correlations of characteristics of groups of variants with case-control status to infer with greater precision the risks of individual rare variants. A total of 181 distinct rare missense variants were identified among the 705 cases with CBC and the 1,398 controls with unilateral breast cancer. The model identified three bioinformatic hierarchical covariates, align-GV, align-GD, and SIFT scores, each of which was modestly associated with risk. Collectively, the 11 variants that were classified as adverse on the basis of all the three bioinformatic predictors demonstrated a stronger risk signal. This group included five of six missense variants that were classified as deleterious at the outset by conventional criteria. The remaining six variants can be considered as plausibly deleterious, and deserving of further investigation (BRCA1 R866C; BRCA2 G1529R, D2665G, W2626C, E2663V, and R3052W). Hierarchical modeling is a strategy that has promise for interpreting the evidence from future association studies that involve sequencing of known or suspected cancer genes.

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    • "The study was then extended to include BRCA1, BRCA2, and CHEK2, which are all involved in homologous recombination repair (HRR), and later still to include a broader set of 38 candidate genes involved in this and other pathways for DSB damage response. We have previously reported on the main effects of ionizing radiation [2] [3], ATM [4] [5] [6], BRCA1/2 [7] [8] [9] [10] [11] [12], CHEK2 [13], and the interactions of radiation with ATM [14] and BRCA1/2 [15] as well as with other treatments and reproductive factors [16] [17], amongst other risk factors. The aim of this paper is to provide a comprehensive modeling strategy for examining the effects of all genes in a pathway and to apply the approach to candidate genes for CBC risk in the WECARE study. "
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    • "We estimated the relative risk conferred by pathogenic PALB2 mutations by comparing the breast cancer incidence in their first degree female relatives with the corresponding incidence in first degree relatives of non-carrier CBC cases using conventional actuarial techniques, and then by transforming the resulting estimate (Saunders and Begg, 2003). We further examined the relative risks of individual rare missense variants (MAF≤1%) using a hierarchical modeling approach developed for this purpose (Capanu, et al., 2011). This model included adjustment for eight common polymorphisms (MAF>1%), the presence of a truncation or splicing mutation, the presence of a rare intronic mutation, the presence of a rare synonymous mutation, as well as childbearing history as possible confounders. "
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