scholarly journals Genetic assessments of breast cancer risk that do not account for polygenic background are incomplete and lead to incorrect preventative strategies

2021 ◽  
Author(s):  
George B Busby ◽  
Paul Craig ◽  
Nesrine Yousfi ◽  
Saurabh Hebbalker ◽  
Paolo Di Domenico ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Genetic Risk ◽  
Disease Risk ◽  
Population Level ◽  
Polygenic Risk ◽  
Cancer Susceptibility Genes ◽  
Pathogenic Mutations ◽  
Genome Wide

Breast cancer is the most common cancer among women and is a leading cause of cancer mortality worldwide. There is a significant genetic component to breast cancer risk which is the result of both rare pathogenic mutations and common genome-wide variation. However, the penetrance of pathogenic mutations varies widely and their frequency is low, both at a population level and amongst breast cancer cases. Polygenic risk scores, which aggregate the effect of hundreds to millions of common genome-wide variants offer a way to further understand the contribution of genetics to disease risk. Here we analyse genome-wide data from 221,479 women and 90,307 high coverage exomes to understand how rare and common variation affect lifetime breast cancer risk. We show that PRS strongly modulates the penetrance of mutations in 8 breast cancer susceptibility genes. For example, lifetime risk in BRCA1 carriers with low polygenic risk is almost one third that of carriers with high PRS (26% v 69% in the bottom and top PRS deciles, respectively). Adding family history of breast cancer provides additional stratification on the potential outcome of disease in carriers of rare mutations. PRS also identifies a significant fraction of the population at equivalent risk to carriers of moderate impact pathogenic variants and who are an order of magnitude more common at a population level. These results have important implications for breast cancer risk mitigation strategies, indicating that the genetic risk of breast cancer is determined by both monogenic mutation and polygenic background, and that assessments of genetic risk for breast cancer risk that do not consider the polygenic background are imprecise and unreliable.

scholarly journals Potential of polygenic risk scores for improving population estimates of women’s breast cancer genetic risks

2021 ◽  
Author(s):  
Michael Wolfson ◽  
Steve Gribble ◽  
Nora Pashayan ◽  
Douglas F. Easton ◽  
Antonis C. Antoniou ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Family History ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Risk Stratification ◽  
Breast Cancer Incidence ◽  
Population Level ◽  
Risk Scores ◽  
Polygenic Risk ◽  
Risk Algorithm

Abstract Purpose Breast cancer risk has conventionally been assessed using family history (FH) and rare high/moderate penetrance pathogenic variants (PVs), notably in BRCA1/2, and more recently PALB2, CHEK2, and ATM. In addition to these PVs, it is now possible to use increasingly predictive polygenic risk scores (PRS) as well. The comparative population-level predictive capability of these three different indicators of genetic risk for risk stratification is, however, unknown. Methods The Canadian heritable breast cancer risk distribution was estimated using a novel genetic mixing model (GMM). A realistically representative sample of women was synthesized based on empirically observed demographic patterns for appropriately correlated family history, inheritance of rare PVs, PRS, and residual risk from an unknown polygenotype. Risk assessment was simulated using the BOADICEA risk algorithm for 10-year absolute breast cancer incidence, and compared to heritable risks as if the overall polygene, including its measured PRS component, and PV risks were fully known. Results Generally, the PRS was most predictive for identifying women at high risk, while family history was the weakest. Only the PRS identified any women at low risk of breast cancer. Conclusion PRS information would be the most important advance in enabling effective risk stratification for population-wide breast cancer screening.

scholarly journals Pro-inflammatory cytokine polymorphisms and interactions with dietary alcohol and estrogen, risk factors for invasive breast cancer using a post genome-wide analysis for gene–gene and gene–lifestyle interaction

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Su Yon Jung ◽  
Jeanette C. Papp ◽  
Eric M. Sobel ◽  
Matteo Pellegrini ◽  
Herbert Yu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Visceral Obesity ◽  
Cumulative Exposure ◽  
Environment Interaction ◽  
Dependent Manner ◽  
Nucleotide Polymorphisms ◽  
Genome Wide ◽  
Reduction Methods

AbstractMolecular and genetic immune-related pathways connected to breast cancer and lifestyles in postmenopausal women are not fully characterized. In this study, we explored the role of pro-inflammatory cytokines such as C-reactive protein (CRP) and interleukin-6 (IL-6) in those pathways at the genome-wide level. With single-nucleotide polymorphisms (SNPs) in the biomarkers and lifestyles together, we further constructed risk profiles to improve predictability for breast cancer. Our earlier genome-wide association gene-environment interaction study used large cohort data from the Women’s Health Initiative Database for Genotypes and Phenotypes Study and identified 88 SNPs associated with CRP and IL-6. For this study, we added an additional 68 SNPs from previous GWA studies, and together with 48 selected lifestyles, evaluated for the association with breast cancer risk via a 2-stage multimodal random survival forest and generalized multifactor dimensionality reduction methods. Overall and in obesity strata (by body mass index, waist, waist-to-hip ratio, exercise, and dietary fat intake), we identified the most predictive genetic and lifestyle variables. Two SNPs (SALL1 rs10521222 and HLA-DQA1 rs9271608) and lifestyles, including alcohol intake, lifetime cumulative exposure to estrogen, and overall and visceral obesity, are the most common and strongest predictive markers for breast cancer across the analyses. The risk profile that combined those variables presented their synergistic effect on the increased breast cancer risk in a gene–lifestyle dose-dependent manner. Our study may contribute to improved predictability for breast cancer and suggest potential interventions for the women with the risk genotypes and lifestyles to reduce their breast cancer risk.

scholarly journals Analysis of Italian BRCA1/2 Pathogenic Variants Identifies a Private Spectrum in the Population from the Bergamo Province in Northern Italy

Cancers ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 532
Author(s):  
Gisella Figlioli ◽  
Arcangela De Nicolo ◽  
Irene Catucci ◽  
Siranoush Manoukian ◽  
Bernard Peissel ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Disease Risk ◽  
Northern Italy ◽  
Genetic Isolate ◽  
National Population ◽  
Pathogenic Variants ◽  
High Breast Cancer Risk

Germline pathogenic variants (PVs) in the BRCA1 or BRCA2 genes cause high breast cancer risk. Recurrent or founder PVs have been described worldwide including some in the Bergamo province in Northern Italy. The aim of this study was to compare the BRCA1/2 PV spectra of the Bergamo and of the general Italian populations. We retrospectively identified at five Italian centers 1019 BRCA1/2 PVs carrier individuals affected with breast cancer and representative of the heterogeneous national population. Each individual was assigned to the Bergamo or non-Bergamo cohort based on self-reported birthplace. Our data indicate that the Bergamo BRCA1/2 PV spectrum shows less heterogeneity with fewer different variants and an average higher frequency compared to that of the rest of Italy. Consistently, four PVs explained about 60% of all carriers. The majority of the Bergamo PVs originated locally with only two PVs clearly imported. The Bergamo BRCA1/2 PV spectrum appears to be private. Hence, the Bergamo population would be ideal to study the disease risk associated with local PVs in breast cancer and other disease-causing genes. Finally, our data suggest that the Bergamo population is a genetic isolate and further analyses are warranted to prove this notion.

scholarly journals Discovery of breast cancer risk genes and establishment of a prediction model based on estrogen metabolism regulation

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Feng Zhao ◽  
Zhixiang Hao ◽  
Yanan Zhong ◽  
Yinxue Xu ◽  
Meng Guo ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Healthy Subjects ◽  
Metabolic Enzyme ◽  
Estrogen Metabolism ◽  
Polygenic Risk Score ◽  
Risk Genes ◽  
Polygenic Risk ◽  
Enzyme Gene

Abstract Background Multiple common variants identified by genome-wide association studies have shown limited evidence of the risk of breast cancer in Chinese individuals. In this study, we aimed to uncover the relationship between estrogen levels and the genetic polymorphism of estrogen metabolism-related enzymes in breast cancer (BC) and establish a risk prediction model composed of estrogen-metabolizing enzyme genes and GWAS-identified breast cancer-related genes based on a polygenic risk score. Methods Unrelated BC patients and healthy subjects were recruited for analysis of estrogen levels and single nucleotide polymorphisms (SNPs) in genes encoding estrogen metabolism-related enzymes. The polygenic risk score (PRS) was used to explore the combined effect of multiple genes, which was calculated using a Bayesian approach. An independent sample t-test was used to evaluate the differences between PRS scores of BC and healthy subjects. The discriminatory accuracy of the models was compared using the area under the receiver operating characteristic (ROC) curve. Results The estrogen homeostasis profile was disturbed in BC patients, with parent estrogens (E1, E2) and carcinogenic catechol estrogens (2/4-OHE1, 2-OHE2, 4-OHE2) significantly accumulating in the serum of BC patients. We then established a PRS model to evaluate the role of SNPs in multiple genes. PRS model 1 (M1) was established from SNPs in 6 GWAS-identified high risk genes. On the basis of M1, we added SNPs from 7 estrogen metabolism enzyme genes to establish PRS model 2 (M2). The independent sample t-test results showed that there was no difference between BC and healthy subjects in M1 (P = 0.17); however, there was a significant difference between BC and healthy subjects in M2 (P = 4.9*10− 5). The ROC curve results showed that the accuracy of M2 (AUC = 62.18%) in breast cancer risk identification was better than that of M1 (AUC = 54.56%). Conclusion Estrogen and related metabolic enzyme gene polymorphisms are closely related to BC. The model constructed by adding estrogen metabolic enzyme gene SNPs has a good predictive ability for breast cancer risk, and the accuracy is greatly improved compared with that of the PRS model that only includes GWAS-identified gene SNPs.

scholarly journals The development of rs7107217 genotyping method and initial study of the association of this gene with the breast cancer risk in Vietnamese women

2019 ◽  
Vol 2 (5) ◽  
pp. 40-49
Author(s):  
Thanh Thi Ngoc Nguyen ◽  
Giau Thi Ngoc Mai ◽  
Hue Thi Nguyen
Keyword(s):  
Breast Cancer ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Cancer Susceptibility ◽  
Regulation Of Gene Expression ◽  
High Sensitivity ◽  
Nucleotide Polymorphisms ◽  
Coding Region ◽  
Cancer Susceptibility Genes ◽  
And Control

Breast cancer is the most common cancer for women around the world. The presence of single nucleotide polymorphisms (SNP) on or near the coding region of breast cancer susceptibility genes can affect the regulation of gene expression, which may increase or decrease the risk of breast cancer. BARX2 was showed to stimulate the expression of ERS1, which involved in the development of breast cancer. SNP rs7107217 on 152kb downstream of the BARX2 could affect the level of protein BARX2 and had been proved to associate with the breast cancer risk in populations similar to Vietnamese, including Chinese and Korean. In this study, rs7107217 was genotyped and initially detemined the association with the breast cancer risk in Vietnamese. Real-time PCR HRM was optimized and used to genotype rs7107217 in 117 breast cancer cases and 105 healthy controls. Thereafter, the correlation of this SNP with the risk of breast cancer was initially determined by analyzing the differences in allelic and genotypic frequencies between cases and control groups. The results showed the optimal rs7107217 genotyping condition was successfully developed with the high sensitivity, specificity, and consistency. SNP rs7107217 had high polymorphism with the frequency of minor allele C of 29.9% and 35.3% in case and control, respectively. SNP rs7107217 had been found no association with the breast cancer risk (C vs A: P = 0.23, OR (95% CI) = 0.79 (0.53 – 1.17)). However with the low reliability of the analysis (11.71%) and the high potential related to the formation of breast cancer, the association between rs7107217 and breast cancer risk in Vietnamese population should be further conducted on a larger sample size to get higher accuracy.

scholarly journals Circulating carotenoids and breast cancer among high-risk individuals

2020 ◽  
Author(s):  
Cheng Peng ◽  
Chi Gao ◽  
Donghao Lu ◽  
Bernard A Rosner ◽  
Oana Zeleznik ◽  
...  
Keyword(s):  
Breast Cancer ◽  
High Risk ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Genetic Risk ◽  
Case Control Study ◽  
Case Control ◽  
Polygenic Risk Score ◽  
Nested Case Control ◽  
Control Study

ABSTRACT Background Carotenoids represent 1 of few modifiable factors to reduce breast cancer risk. Elucidation of interactions between circulating carotenoids and genetic predispositions or mammographic density (MD) may help inform more effective primary preventive strategies in high-risk populations. Objectives We tested whether women at high risk for breast cancer due to genetic predispositions or high MD would experience meaningful and greater risk reduction from higher circulating levels of carotenoids in a nested case-control study in the Nurses’ Health Studies (NHS and NHSII). Methods This study included 1919 cases and 1695 controls in a nested case-control study in the NHS and NHSII. We assessed both multiplicative and additive interactions. RR reductions and 95% CIs were calculated using unconditional logistic regressions, adjusting for matching factors and breast cancer risk factors. Absolute risk reductions (ARR) were calculated based on Surveillance, Epidemiology, and End Results incidence rates. Results We showed that compared with women at low genetic risk or low MD, those with higher genetic risk scores or high MD had greater ARRs for breast cancer as circulating carotenoid levels increase (additive P-interaction = 0.05). Among women with a high polygenic risk score, those in the highest quartile of circulating carotenoids had a significant ARR (28.6%; 95% CI, 14.8–42.1%) compared to those in the lowest quartile of carotenoids. For women with a high percentage MD (≥50%), circulating carotenoids were associated with a 37.1% ARR (95% CI, 21.7–52.1%) when comparing the highest to the lowest quartiles of circulating carotenoids. Conclusions The inverse associations between circulating carotenoids and breast cancer risk appeared to be more pronounced in high-risk women, as defined by germline genetic makeup or MD.

Abstract 4720: Genome-wide copy number variation and breast cancer risk: Preliminary report

2010 ◽  
Author(s):  
Kyoung-Mu Lee ◽  
Miey Park ◽  
Sang-Hoon Moon ◽  
Hyung-Chol Kim ◽  
Ji-Young Lee ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Copy Number Variation ◽  
Copy Number ◽  
Preliminary Report ◽  
Genome Wide ◽  
Number Variation
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