NEW YORK – A research team based in Australia and the UK has turned to a statistical method called segregation analysis to dig into breast cancer risk within families that cannot be explained by variation in half a dozen known breast cancer susceptibility genes.
"Our findings are informative for the design of sequencing studies to identify novel breast cancer susceptibility genes and modeling breast cancer genetic susceptibility for disease risk prediction," first and corresponding author Shuai Li, an epidemiology and biostatistics researcher affiliated with the University of Melbourne, the University of Cambridge, Monash University, and the Murdoch Children's Research Institute, and his colleagues wrote.
As they reported in the American Journal of Human Genetics on Thursday, the researchers brought together targeted gene panel sequence data for members of 17,425 multi-generation breast cancer-affected families enrolled through the Australian Breast Cancer Family Registry (ABCFR) or the UK's "Studies of Epidemiology and Risk Factors in Cancer Heredity" (SEARCH) study, modeling breast cancer risk with complex segregation analyses informed by pathogenic variant profiles falling in BRCA1, BRCA2, PALB2, CHEK2, ATM, and TP53.
"We conducted complex segregation analyses and fitted genetic models in which breast cancer incidence depended on the effects of known susceptibility genes and other unidentified major genes and a normally distributed polygenic component," the authors explained.
The team tracked down pathogenic breast cancer susceptibility gene changes in 892 of the 15,032 panel-sequenced breast cancer patients from the affected ABCFR and SEARCH population study families. Together, the risk variants explained an estimated 46 percent of the familial variance for breast cancer for 20- to 29-year-olds within the families considered.
But the familial variance explained by the pathogenic variants diminished as the family members aged, despite a rise in cumulative disease risk, the researchers reported, as did the apparent contributions of recessively inherited variants in yet-to-be-identified genes, which also showed peak contributions to breast cancer heritability in individuals between the ages of 20 and 29.
"[O]ur analysis estimates the proportion of breast cancer familial aggregation that is explained by established susceptibility genes and variants and provides evidence for an additional recessive risk component," the authors explained, "which could explain a substantial proportion of the residual familial aggregation, especially at a younger age."
In contrast, the team found that breast cancer familial variance attributed to common risk variants and common polygenic risk score contributors identified through prior breast cancer genome-wide association studies did not appear to waver with age.
Among the potential limitations of their study, the authors cautioned that breast cancer cases in the analyses were self-reported and primarily from families with European ancestry, while genetic profiling did not include all of the genes and variants implicated in breast cancer. Even so, they suggested, the results so far "have implications for strategies to identify new breast cancer susceptibility genes and improve disease-risk prediction, especially at a young age."