scholarly journals A Role for Common Genomic Variants in the Assessment of Familial Breast Cancer

2012 ◽  
Vol 30 (35) ◽  
pp. 4330-4336 ◽  
Author(s):  
Sarah Sawyer ◽  
Gillian Mitchell ◽  
Joanne McKinley ◽  
Georgia Chenevix-Trench ◽  
Jonathan Beesley ◽  
...  
Keyword(s):  
Breast Cancer ◽  
High Risk ◽  
Familial Breast Cancer ◽  
Brca2 Mutation ◽  
Mutation Screening ◽  
Polygenic Risk Score ◽  
Genome Wide Association Studies ◽  
Polygenic Risk ◽  
Genomic Variants ◽  
Risk Distribution

Purpose Genome-wide association studies have identified common genomic variants associated with increased susceptibility to breast cancer. In the general population, the risk associated with these known variants seems insufficient to inform clinical management. Their contribution to the development of familial breast cancer is less clear. Patients and Methods We studied 1,143 women with breast cancer who had completed BRCA1 and BRCA2 mutation screening as a result of a high risk for hereditary breast cancer. Genotyping of 22 breast cancer–associated genomic variants was performed. A polygenic risk score (PRS), calculated as the sum of the log odds ratios for each allele, was compared with the same metric in 892 controls from the Australian Ovarian Cancer Study. The clinical features associated with the high and low ends of the polygenic risk distribution were compared. Results Women affected by familial breast cancer had a highly significant excess of risk alleles compared with controls (P = 1.0 × 10−16). Polygenic risk (measured by the PRS) was greater in women who tested negative for a BRCA1 or BRCA2 mutation compared with mutation carriers (P = 2.3 × 10−6). Non-BRCA1/2 women in the top quartile of the polygenic risk distribution were more likely to have had early-onset breast cancer (< 30 years of age, odds ratio [OR]= 3.37, P = .03) and had a higher rate of second breast cancer (OR 1.96, P = .02) compared with women with low polygenic risk. Conclusion Genetic testing for common risk variants in women undergoing assessment for familial breast cancer may identify a distinct group of high-risk women in whom the role of risk-reducing interventions should be explored.

Risk of Breast Cancer Among Carriers of Pathogenic Variants in Breast Cancer Predisposition Genes Varies by Polygenic Risk Score

2021 ◽  
pp. JCO.20.01992
Author(s):  
Chi Gao ◽  
Eric C. Polley ◽  
Steven N. Hart ◽  
Hongyan Huang ◽  
Chunling Hu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
General Population ◽  
Association Studies ◽  
Polygenic Risk Score ◽  
Genome Wide Association Studies ◽  
Polygenic Risk ◽  
First Degree Relatives ◽  
Pathogenic Variants ◽  
Predisposition Genes ◽  
Brca1 Brca2

PURPOSE This study assessed the joint association of pathogenic variants (PVs) in breast cancer (BC) predisposition genes and polygenic risk scores (PRS) with BC in the general population. METHODS A total of 26,798 non-Hispanic white BC cases and 26,127 controls from predominately population-based studies in the Cancer Risk Estimates Related to Susceptibility consortium were evaluated for PVs in BRCA1, BRCA2, ATM, CHEK2, PALB2, BARD1, BRIP1, CDH1, and NF1. PRS based on 105 common variants were created using effect estimates from BC genome-wide association studies; the performance of an overall BC PRS and estrogen receptor–specific PRS were evaluated. The odds of BC based on the PVs and PRS were estimated using penalized logistic regression. The results were combined with age-specific incidence rates to estimate 5-year and lifetime absolute risks of BC across percentiles of PRS by PV status and first-degree family history of BC. RESULTS The estimated lifetime risks of BC among general-population noncarriers, based on 10th and 90th percentiles of PRS, were 9.1%-23.9% and 6.7%-18.2% for women with or without first-degree relatives with BC, respectively. Taking PRS into account, more than 95% of BRCA1, BRCA2, and PALB2 carriers had > 20% lifetime risks of BC, whereas, respectively, 52.5% and 69.7% of ATM and CHEK2 carriers without first-degree relatives with BC, and 78.8% and 89.9% of those with a first-degree relative with BC had > 20% risk. CONCLUSION PRS facilitates personalization of BC risk among carriers of PVs in predisposition genes. Incorporating PRS into BC risk estimation may help identify > 30% of CHEK2 and nearly half of ATM carriers below the 20% lifetime risk threshold, suggesting the addition of PRS may prevent overscreening and enable more personalized risk management approaches.

Polygenic risk score for breast cancer in high-risk women.

2018 ◽  
Vol 36 (15_suppl) ◽  
pp. 1508-1508 ◽  
Author(s):  
Mary Helen Black ◽  
Shuwei Li ◽  
Holly LaDuca ◽  
Jefferey Chen ◽  
Robert Hoiness ◽  
...  
Keyword(s):  
Breast Cancer ◽  
High Risk ◽  
Risk Score ◽  
Polygenic Risk Score ◽  
Polygenic Risk ◽  
High Risk Women

CHEK2*1100delC Genotyping for Clinical Assessment of Breast Cancer Risk: Meta-Analyses of 26,000 Patient Cases and 27,000 Controls

2008 ◽  
Vol 26 (4) ◽  
pp. 542-548 ◽  
Author(s):  
Maren Weischer ◽  
Stig Egil Bojesen ◽  
Christina Ellervik ◽  
Anne Tybjærg-Hansen ◽  
Børge Grønne Nordestgaard
Keyword(s):  
Breast Cancer ◽  
Early Onset ◽  
Familial Breast Cancer ◽  
Brca2 Mutation ◽  
Mutation Screening ◽  
Cumulative Risk ◽  
Brca1 And Brca2 ◽  
Chek2 1100Delc ◽  
Increased Risk ◽  
Meta Analyses

Purpose CHEK2*1100delC heterozygosity may be associated with an increased risk of breast cancer; however, it is unclear whether the evidence is sufficient to recommend genotyping in clinical practice. Patients and Methods We identified studies on CHEK2*1100delC heterozygosity and the risk of unselected, early-onset, and familial breast cancer through comprehensive, computer-based searches of PubMed, EMBASE, and Web of Science. Aggregated risk estimates were compared with previous estimates for BRCA1 and BRCA2 mutation heterozygotes. Results By using fixed-effect models for CHEK2*1100delC heterozygotes versus noncarriers, we found aggregated odds ratios of 2.7 (95% CI, 2.1 to 3.4) for unselected breast cancer, 2.6 (95% CI, 1.3 to 5.5) for early-onset breast cancer, and 4.8 (95% CI, 3.3 to 7.2) for familial breast cancer. For familial breast cancer, this corresponds to a cumulative risk of breast cancer at age 70 years in CHEK2*1100delC heterozygotes of 37% (95% CI, 26% to 56%), which compares with similar previous estimates of 57% (95% CI, 47% to 66%) for BRCA1 mutation heterozygotes and 49% (95% CI, 40% to 57%) for BRCA2 mutation heterozygotes. Conclusion These meta-analyses emphasize that CHEK2*1100delC is an important breast cancer–predisposing gene, which increases the risk three- to five-fold. Because the cumulative risk of breast cancer at age 70 years among familial patient cases for CHEK2*1100delC heterozygotes is almost as high as that for BRCA1 and BRCA2 mutation heterozygotes, genotyping for CHEK2*1100delC should be considered together with BRCA1 and BRCA2 mutation screening in women with a family history of breast cancer.

scholarly journals Polygenic risk for aggressive behaviour from late childhood through early adulthood

2021 ◽  
Author(s):  
Tina Kretschmer ◽  
Isabelle Ouellet-Morin ◽  
Charlotte Vrijen ◽  
Ilja Maria Nolte ◽  
Catharina A. Hartman
Keyword(s):  
High Risk ◽  
Risk Score ◽  
Genetic Information ◽  
Aggressive Behaviour ◽  
Population Sample ◽  
Genome Wide Association ◽  
Polygenic Risk Score ◽  
Genome Wide Association Studies ◽  
Polygenic Risk ◽  
Genome Wide

Twin studies suggest a substantial role for genes in explaining individual differences in aggressive behaviour across development. It is unclear, however, how directly measured genetic risk is associated with aggressive behaviour at different moments across adolescence and how genes might distinguish developmental trajectories of aggressive behaviour. Here, a polygenic risk score derived from the EAGLE-Consortium genome-wide association study of aggressive behaviour in children was tested as predictor of latent growth classes derived from those measures in an adolescent population (n = 2229, of which n = 1259 with genetic information) and a high-risk sample (n = 543, of which n = 339 with genetic information). In the population sample, the polygenic risk score explained variation in parent-reported aggressive behaviour at all ages and distinguished between stable low aggressive behaviour and moderate and high-decreasing trajectories based on parent-report. In contrast, the polygenic risk score was not associated with self- and teacher-reported aggressive behaviour, and no associations were found in the high-risk sample. This pattern of results suggests that methodological choices made in genome-wide association studies impact the predictive power of polygenic risk scores, not just with respect to power but likely also in terms of generalizability and specificity.

scholarly journals Women’s Responses and Understanding of Polygenic Breast Cancer Risk Information

2019 ◽  
Author(s):  
Tatiane Yanes
Keyword(s):  
Breast Cancer ◽  
High Risk ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Risk Information ◽  
Risk Level ◽  
Cancer Information ◽  
Polygenic Risk Score ◽  
Clinical Implementation ◽  
Polygenic Risk

It is estimated that polygenic factors can explain up to 18% of familial breast cancer. Clinical implementation of polygenic testing has begun, with several commercial laboratories now testing. Despite commercial implementation, there is little research investigating how women respond and understand polygenic risk information. This study aimed to explore women’s experience receiving their personalized polygenic risk score (PRS) and compare responses of women at different levels of polygenic risk. Eligible participants were affected and unaffected women from families clinically assessed to be at high risk for breast cancer who had received their personalized PRS as part of the Variants in Practice Psychosocial Study (ViPPs). In-depth semi-structured interviews were conducted with 21 women (mean age 53.4 years) up to four weeks after receiving their PRS. Interviews were transcribed verbatim and analyzed using thematic analysis. Eleven women received a PRS that was in the top quartile of PRS distribution and 10 in the lowest quartile. Women’s lived experience with breast cancer informed how they responded to their PRS, constructed and made sense of breast cancer risk following receipt of their PRS, and integrated this new information into their breast cancer risk management. Regardless of polygenic risk level, all participants demonstrated broad knowledge of concepts related to polygenic information and were able to accurately describe the implications of their PRS. Receiving PRS did not appear to negatively impact women’s reported distress levels. Our findings suggest polygenic breast cancer information is well received and understood by women at high-risk for breast cancer.

scholarly journals Addition of a 161-SNP polygenic risk score to family history-based risk prediction: impact on clinical management in non-BRCA1/2 breast cancer families

2019 ◽  
Vol 56 (9) ◽  
pp. 581-589 ◽  
Author(s):  
Inge M M Lakeman ◽  
Florentine S Hilbers ◽  
Mar Rodríguez-Girondo ◽  
Andrew Lee ◽  
Maaike P G Vreeswijk ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Family History ◽  
High Risk ◽  
Risk Prediction ◽  
Clinical Management ◽  
Polygenic Risk Score ◽  
Polygenic Risk ◽  
High Risk Breast Cancer ◽  
High Risk Breast ◽  
Risk Breast Cancer

BackgroundThe currently known breast cancer-associated single nucleotide polymorphisms (SNPs) are presently not used to guide clinical management. We explored whether a genetic test that incorporates a SNP-based polygenic risk score (PRS) is clinically meaningful in non-BRCA1/2 high-risk breast cancer families.Methods101 non-BRCA1/2 high-risk breast cancer families were included; 323 cases and 262 unaffected female relatives were genotyped. The 161-SNP PRS was calculated and standardised to 327 population controls (sPRS). Association analysis was performed using a Cox-type random effect regression model adjusted by family history. Updated individualised breast cancer lifetime risk scores were derived by combining the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm breast cancer lifetime risk with the effect of the sPRS.ResultsThe mean sPRS for cases and their unaffected relatives was 0.70 (SD=0.9) and 0.53 (SD=0.9), respectively. A significant association was found between sPRS and breast cancer, HR=1.16, 95% CI 1.03 to 1.28, p=0.026. Addition of the sPRS to risk prediction based on family history alone changed screening recommendations in 11.5%, 14.7% and 19.8 % of the women according to breast screening guidelines from the USA (National Comprehensive Cancer Network), UK (National Institute for Health and Care Excellence and the Netherlands (Netherlands Comprehensive Cancer Organisation), respectively.ConclusionOur results support the application of the PRS in risk prediction and clinical management of women from genetically unexplained breast cancer families.

scholarly journals Precision Breast Cancer Screening with a Polygenic Risk Score

2020 ◽  
Author(s):  
Tonis Tasa ◽  
Mikk Puustusmaa ◽  
Neeme Tonisson ◽  
Berit Kolk ◽  
Peeter Padrik
Keyword(s):  
Breast Cancer ◽  
Cancer Screening ◽  
Secondary Prevention ◽  
Breast Cancer Screening ◽  
Risk Score ◽  
Polygenic Risk Score ◽  
Genome Wide Association Studies ◽  
Primary And Secondary Prevention ◽  
Polygenic Risk ◽  
Incident Cases

Breast cancer (BC) is the leading cause of cancer deaths in women in the world. Genome-wide association studies have identified numerous genetic variants (SNPs) independently associated with BC. The effects of such SNPs can be combined into a single polygenic risk score (PRS). Stratification of women according to PRS could be introduced to primary and secondary prevention. Our aim was to revalidate a PRS model and to develop a pipeline for individualizing breast cancer screening. Previously published PRS models for predicting the risk of breast cancer were collected from the literature. Models were validated on the Estonian Biobank (EGC) dataset consisting of 32,548 quality-controlled genotypes with 315 prevalent and 365 incident BC cases and on 249,062 samples in the UK Biobank dataset consisting of 8637 prevalent and 6825 incident cases. The best performing model was selected based on the AUC in prevalent data and independently validated in both incident datasets. Using Estonian BC background information, we performed absolute risk simulations and developed individual risk-based recommendations for prevention. The best-performing PRS included 2803 SNPs. The C-index of the Cox regression model associating BC status with PRS was 0.656 (SE = 0.05) with a hazard ratio of 1.66 (95% confidence interval 1.5 - 1.84) on the incident EGC dataset. The PRS is able to stratify individuals with more than a 3-fold risk increase. The observed 10-year risks of individuals in the 99th percentile exceeded the 1st percentile more than 10-fold. PRS is a powerful predictor of breast cancer risk. Currently, PRS scores are not implemented in routine BC screening. We have developed PRS-based recommendations for personalized primary and secondary prevention and our approach is easily adaptable to other nationalities by using population-specific background data of other genetically similar populations.

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