Genetic variants associated with breast cancer risk for Ashkenazi Jewish women with strong family histories but no identifiable BRCA1/2 mutation

Rinella, Erica S.; Shao, Yongzhao; Yackowski, Lauren; Pramanik, Sreemanta; Oratz, Ruth; Schnabel, Freya; Guha, Saurav; LeDuc, Charles A.; Campbell, Christopher; Klugman, Susan; Terry, Mary Beth; Senie, Ruby T.; Andrulis, Irene L.; Daly, Mary B.; John, Esther M.; Roses, Daniel F.; Chung, Wendy K.; Ostrer, Harry

doi:10.1007/s00439-013-1269-4

Cited by 20 publications

(20 citation statements)

References 46 publications

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“…Interpreting these multiple risks constitutes another challenge to panel testing. Integrating SNP-associated risks has been based on additive models and has shown moderate discriminatory accuracy (Lalloo and Evans 2012;Rinella et al 2013). However the formalism for combining higher penetrance genetic risk variants to yield a composite risk score for multigenic diseases has not yet been developed (Ng et al, 2009;Swan et al 2010).…”

Section: Risk Estimatesmentioning

confidence: 99%

Cancer Risk Assessment Using Genetic Panel Testing: Considerations for Clinical Application

Hiraki

Rinella

Schnabel

et al. 2014

Journal of Genetic Counseling

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With the completion of the Human Genome Project and the development of high throughput technologies, such as next-generation sequencing, the use of multiplex genetic testing, in which multiple genes are sequenced simultaneously to test for one or more conditions, is growing rapidly. Reflecting underlying heterogeneity where a broad range of genes confer risks for one or more cancers, the development of genetic cancer panels to assess these risks represents just one example of how multiplex testing is being applied clinically. There are a number of issues and challenges to consider when conducting genetic testing for cancer risk assessment, and these issues become exceedingly more complex when moving from the traditional single-gene approach to panel testing. Here, we address the practical considerations for clinical use of panel testing for breast, ovarian, and colon cancers, including the benefits, limitations and challenges, genetic counseling issues, and management guidelines.

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Section: Risk Estimatesmentioning

confidence: 99%

Cancer Risk Assessment Using Genetic Panel Testing: Considerations for Clinical Application

Hiraki

Rinella

Schnabel

et al. 2014

Journal of Genetic Counseling

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“…Our FGFR2 SNP, rs2981579, was first identified by Thomas et al [31] and independently replicated in two other GWAS [23, 32]. Other GWAS found stronger associations with other SNPs in the same gene [1, 7, 8, 10, 12, 15, 19, 22, 26]. Ahsan et al [1], for example, reported genome-wide significant p-values for 4 FGFR2 SNPs and young-onset breast cancer, with the smallest p-value seen for rs2981579.…”

Section: Methodsmentioning

confidence: 51%

Previous GWAS hits in relation to young-onset breast cancer

Shi

O’Brien

Sandler

et al. 2016

Breast Cancer Res Treat

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Purpose Genome-wide association studies (GWAS) have identified dozens of single nucleotide polymorphisms (SNPs) associated with breast cancer. Few studies focused on young-onset breast cancer, which exhibits etiologic and tumor-type differences from older-onset disease. Possible confounding by prenatal effects of the maternal genome has also not been considered. Methods Using a family-based design for breast cancer before age 50, we assessed the relationship between breast cancer and 77 GWAS-identified breast cancer risk SNPs. We estimated relative risks (RR) for inherited and maternally-mediated genetic effects. We also used published RR estimates to calculate genetic risk scores and model joint effects. Results Seventeen of the candidate SNPs were nominally associated with young-onset breast cancer in our 1,296 non-Hispanic white affected families (uncorrected p-value<0.05). Top-ranked SNPs included rs3803662-A (TOX3, RR=1.39; p=7.0×10−6), rs12662670-G (ESR1, RR=1.56; p=5.7×10−4), rs2981579-A (FGFR2, RR=1.24; p=0.002), and rs999737-G (RAD51B, RR=1.37; p=0.003). No maternally-mediated effects were found. A risk score based on all 77 SNPs indicated that their overall relationship to young-onset breast cancer risk was more than additive (additive-fit p=2.2×10−7) and consistent with a multiplicative joint effect (multiplicative-fit p=0.27). With the multiplicative formulation, the case sister’s genetic risk score exceeded that of her unaffected sister in 59% of families. Conclusions The results of this family-based study indicate that no effects of previously-identified risk SNPs were explained by prenatal effects of maternal variants. Many of the known breast cancer risk variants were associated with young-onset breast cancer, with evidence that TOX3, ESR1, FGFR2, and RAD51B are important for young-onset disease.

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“…87 articles were excluded because they clearly did not meet the criteria or overlapping references (Figure S1). Finally, a total of 26 eligible association studies were included involving 101,529 breast cancer cases and 167,363 controls [12], [20]–[44]. Of the cases, 80% were White, 12% were East Asian, 7% were African descent, and 1% were of other ethnic origins.…”

Section: Resultsmentioning

confidence: 99%

Assessing Interactions between Common Genetic Variant on 2q35 and Hormone Receptor Status with Breast Cancer Risk: Evidence Based on 26 Studies

et al. 2013

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Genome-wide association studies have identified 2q35-rs13387042 as a new breast cancer (BC) susceptibility locus in populations of European descent. Since then, the relationship between 2q35-rs13387042 and breast cancer has been reported in various ethnic groups; however, these studies have yielded inconsistent results. To investigate this inconsistency, we performed a meta-analysis of 26 studies involving a total of 101,529 cases and 167,363 controls for 2q35-rs13387042 polymorphism to evaluate its effect on genetic susceptibility for breast cancer. An overall random effects odds ratio of 1.14 (95% CI: 1.11–1.16, P<10−5) was found for rs13387042-A variant. Significant results were also observed using dominant (OR = 1.14, 95% CI: 1.12–1.17, P<10−5), recessive (OR = 1.17, 95% CI: 1.13–1.21, P<10−5) and co-dominant genetic model (heterozygous: OR = 1.15, 95% CI: 1.12–1.19, P<10−5; homozygous: OR = 1.20, 95% CI: 1.15–1.24, P<10−5). There was strong evidence of heterogeneity, which largely disappeared after stratification by ethnicity. Significant associations were found in East Asians, and White populations when stratified by ethnicity; while no significant associations were observed in Africans and other ethnic populations. An association was observed for both ER-positive (OR = 1.17, 95% 1.15–1.19; P<10−5) and ER-negative disease (OR = 1.08, 95% CI: 1.04–1.13; P<10−4) and both progesterone receptor (PR)-positive (OR = 1.18, 95% CI: 1.15–1.21; P<10−5) and PR-negative disease (OR = 1.10, 95% CI: 1.05–1.15; P<10−4). In conclusion, this meta-analysis demonstrated that the A allele of 2q35-rs13387042 is a risk factor associated with increased breast cancer susceptibility.

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Genetic variants associated with breast cancer risk for Ashkenazi Jewish women with strong family histories but no identifiable BRCA1/2 mutation

Cited by 20 publications

References 46 publications

Cancer Risk Assessment Using Genetic Panel Testing: Considerations for Clinical Application

Cancer Risk Assessment Using Genetic Panel Testing: Considerations for Clinical Application

Previous GWAS hits in relation to young-onset breast cancer

Assessing Interactions between Common Genetic Variant on 2q35 and Hormone Receptor Status with Breast Cancer Risk: Evidence Based on 26 Studies

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