Dataset Information

Prediction of breast cancer risk based on profiling with common genetic variants.

ABSTRACT:

Background

Data for multiple common susceptibility alleles for breast cancer may be combined to identify women at different levels of breast cancer risk. Such stratification could guide preventive and screening strategies. However, empirical evidence for genetic risk stratification is lacking.

Methods

We investigated the value of using 77 breast cancer-associated single nucleotide polymorphisms (SNPs) for risk stratification, in a study of 33 673 breast cancer cases and 33 381 control women of European origin. We tested all possible pair-wise multiplicative interactions and constructed a 77-SNP polygenic risk score (PRS) for breast cancer overall and by estrogen receptor (ER) status. Absolute risks of breast cancer by PRS were derived from relative risk estimates and UK incidence and mortality rates.

Results

There was no strong evidence for departure from a multiplicative model for any SNP pair. Women in the highest 1% of the PRS had a three-fold increased risk of developing breast cancer compared with women in the middle quintile (odds ratio [OR] = 3.36, 95% confidence interval [CI] = 2.95 to 3.83). The ORs for ER-positive and ER-negative disease were 3.73 (95% CI = 3.24 to 4.30) and 2.80 (95% CI = 2.26 to 3.46), respectively. Lifetime risk of breast cancer for women in the lowest and highest quintiles of the PRS were 5.2% and 16.6% for a woman without family history, and 8.6% and 24.4% for a woman with a first-degree family history of breast cancer.

Conclusions

The PRS stratifies breast cancer risk in women both with and without a family history of breast cancer. The observed level of risk discrimination could inform targeted screening and prevention strategies. Further discrimination may be achievable through combining the PRS with lifestyle/environmental factors, although these were not considered in this report.

SUBMITTER: Mavaddat N

PROVIDER: S-EPMC4754625 | biostudies-literature | 2015 May

REPOSITORIES: biostudies-literature

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Publications

Prediction of breast cancer risk based on profiling with common genetic variants.

Mavaddat Nasim N Pharoah Paul D P PD Michailidou Kyriaki K Tyrer Jonathan J Brook Mark N MN Bolla Manjeet K MK Wang Qin Q Dennis Joe J Dunning Alison M AM Shah Mitul M Luben Robert R Brown Judith J Bojesen Stig E SE Nordestgaard Børge G BG Nielsen Sune F SF Flyger Henrik H Czene Kamila K Darabi Hatef H Eriksson Mikael M Peto Julian J Dos-Santos-Silva Isabel I Dudbridge Frank F Johnson Nichola N Schmidt Marjanka K MK Broeks Annegien A Verhoef Senno S Rutgers Emiel J EJ Swerdlow Anthony A Ashworth Alan A Orr Nick N Schoemaker Minouk J MJ Figueroa Jonine J Chanock Stephen J SJ Brinton Louise L Lissowska Jolanta J Couch Fergus J FJ Olson Janet E JE Vachon Celine C Pankratz Vernon S VS Lambrechts Diether D Wildiers Hans H Van Ongeval Chantal C van Limbergen Erik E Kristensen Vessela V Grenaker Alnæs Grethe G Nord Silje S Borresen-Dale Anne-Lise AL Nevanlinna Heli H Muranen Taru A TA Aittomäki Kristiina K Blomqvist Carl C Chang-Claude Jenny J Rudolph Anja A Seibold Petra P Flesch-Janys Dieter D Fasching Peter A PA Haeberle Lothar L Ekici Arif B AB Beckmann Matthias W MW Burwinkel Barbara B Marme Frederik F Schneeweiss Andreas A Sohn Christof C Trentham-Dietz Amy A Newcomb Polly P Titus Linda L Egan Kathleen M KM Hunter David J DJ Lindstrom Sara S Tamimi Rulla M RM Kraft Peter P Rahman Nazneen N Turnbull Clare C Renwick Anthony A Seal Sheila S Li Jingmei J Liu Jianjun J Humphreys Keith K Benitez Javier J Pilar Zamora M M Arias Perez Jose Ignacio JI Menéndez Primitiva P Jakubowska Anna A Lubinski Jan J Jaworska-Bieniek Katarzyna K Durda Katarzyna K Bogdanova Natalia V NV Antonenkova Natalia N NN Dörk Thilo T Anton-Culver Hoda H Neuhausen Susan L SL Ziogas Argyrios A Bernstein Leslie L Devilee Peter P Tollenaar Robert A E M RA Seynaeve Caroline C van Asperen Christi J CJ Cox Angela A Cross Simon S SS Reed Malcolm W R MW Khusnutdinova Elza E Bermisheva Marina M Prokofyeva Darya D Takhirova Zalina Z Meindl Alfons A Schmutzler Rita K RK Sutter Christian C Yang Rongxi R Schürmann Peter P Bremer Michael M Christiansen Hans H Park-Simon Tjoung-Won TW Hillemanns Peter P Guénel Pascal P Truong Thérèse T Menegaux Florence F Sanchez Marie M Radice Paolo P Peterlongo Paolo P Manoukian Siranoush S Pensotti Valeria V Hopper John L JL Tsimiklis Helen H Apicella Carmel C Southey Melissa C MC Brauch Hiltrud H Brüning Thomas T Ko Yon-Dschun YD Sigurdson Alice J AJ Doody Michele M MM Hamann Ute U Torres Diana D Ulmer Hans-Ulrich HU Försti Asta A Sawyer Elinor J EJ Tomlinson Ian I Kerin Michael J MJ Miller Nicola N Andrulis Irene L IL Knight Julia A JA Glendon Gord G Marie Mulligan Anna A Chenevix-Trench Georgia G Balleine Rosemary R Giles Graham G GG Milne Roger L RL McLean Catriona C Lindblom Annika A Margolin Sara S Haiman Christopher A CA Henderson Brian E BE Schumacher Fredrick F Le Marchand Loic L Eilber Ursula U Wang-Gohrke Shan S Hooning Maartje J MJ Hollestelle Antoinette A van den Ouweland Ans M W AM Koppert Linetta B LB Carpenter Jane J Clarke Christine C Scott Rodney R Mannermaa Arto A Kataja Vesa V Kosma Veli-Matti VM Hartikainen Jaana M JM Brenner Hermann H Arndt Volker V Stegmaier Christa C Karina Dieffenbach Aida A Winqvist Robert R Pylkäs Katri K Jukkola-Vuorinen Arja A Grip Mervi M Offit Kenneth K Vijai Joseph J Robson Mark M Rau-Murthy Rohini R Dwek Miriam M Swann Ruth R Annie Perkins Katherine K Goldberg Mark S MS Labrèche France F Dumont Martine M Eccles Diana M DM Tapper William J WJ Rafiq Sajjad S John Esther M EM Whittemore Alice S AS Slager Susan S Yannoukakos Drakoulis D Toland Amanda E AE Yao Song S Zheng Wei W Halverson Sandra L SL González-Neira Anna A Pita Guillermo G Rosario Alonso M M Álvarez Nuria N Herrero Daniel D Tessier Daniel C DC Vincent Daniel D Bacot Francois F Luccarini Craig C Baynes Caroline C Ahmed Shahana S Maranian Mel M Healey Catherine S CS Simard Jacques J Hall Per P Easton Douglas F DF Garcia-Closas Montserrat M

Journal of the National Cancer Institute 20150408 5

<h4>Background</h4>Data for multiple common susceptibility alleles for breast cancer may be combined to identify women at different levels of breast cancer risk. Such stratification could guide preventive and screening strategies. However, empirical evidence for genetic risk stratification is lacking.<h4>Methods</h4>We investigated the value of using 77 breast cancer-associated single nucleotide polymorphisms (SNPs) for risk stratification, in a study of 33 673 breast cancer cases and 33 381 con ...[more]

PMID: 25855707

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Project description:A younger age at menarche and an older age at menopause are well established risk factors for breast cancer. Recent genome-wide association studies have identified several novel genetic loci associated with these two traits. However, the association between these loci and breast cancer risk is unknown.In this study, we investigated 19 and 17 newly identified single nucleotide polymorphisms (SNPs) from the ReproGen Consortium that have been associated with age at menarche and age at natural menopause, respectively, and assessed their associations with breast cancer risk in 6 population-based studies among up to 3,683 breast cancer cases and 34,174 controls in white women of European ancestry. In addition, we used these SNPs to calculate genetic risk scores (GRSs) based on their associations with each trait.After adjusting for age and potential population stratification, two age at menarche associated SNPs (rs1079866 and rs7821178) and one age at natural menopause associated SNP (rs2517388) were associated with breast cancer risk (p values, 0.003, 0.009 and 0.023, respectively). The odds ratios for breast cancer corresponding to per-risk-allele were 1.14 (95% CI, 1.05 to 1.24), 1.08 (95% CI, 1.02 to 1.15) and 1.10 (95% CI, 1.01 to 1.20), respectively, and were in the direction predicted by their associations with age at menarche or age at natural menopause. These associations did not appear to be attenuated by further controlling for self-reported age at menarche, age at natural menopause, or known breast cancer susceptibility loci. Although we did not observe a statistically significant association between any GRS for reproductive aging and breast cancer risk, the 4th and 5th highest quintiles of the younger age at menarche GRS had odds ratios of 1.14 (95% CI, 1.01 to 1.28) and 1.13 (95% CI, 1.00 to 1.27), respectively, compared to the lowest quintile.Our study suggests that three genetic variants, independent of their associations with age at menarche or age at natural menopause, were associated with breast cancer risk and may contribute modestly to breast cancer risk prediction; however, the combination of the 19 age at menarche or the 17 age at natural menopause associated SNPs did not appear to be useful for identifying a high risk subgroup for breast cancer.

Project description:Women with unilateral breast cancer (UBC) are at risk of developing a subsequent contralateral breast cancer (CBC). Common variants are associated with breast cancer risk. Whether these influence CBC risk is unknown. Participants were breast cancer cases from the population-based Women's Environmental Cancer and Radiation Epidemiology (WECARE) Study. Sixty-seven established breast cancer risk loci were genotyped directly or by imputation in 1459 case subjects with CBC and 2126 UBC control subjects. An unweighted polygenic risk score (PRS) was created by summing the number of risk alleles for each directly genotyped single nucleotide polymorphism (SNP), or for imputed loci, the imputed dosage. A weighted PRS was calculated similarly, but where each SNP's contribution was weighted by the published per-allele log odds ratio. Unweighted and weighted polygenic risk scores and CBC risk were modeled using conditional logistic regression. Cumulative CBC risk was estimated and benchmarked using Surveillance, Epidemiology, and End Results population incidence rates. Both unweighted and weighted PRS were statistically significantly associated with CBC risk. The adjusted risk ratio of CBC in women in the upper quartile of unweighted PRS compared with the lowest quartile was 1.63 (95% confidence interval [CI] = 1.33 to 2.00). The estimated 10-year cumulative risk for women in the upper quartile of the unweighted PRS was 7.4% (95% CI = 6.0% to 9.1%). For women in the upper quartile of the weighted PRS, the risk ratio for CBC was 1.75 (95% CI = 1.41 to 2.18) compared with women in the lowest quartile. There was no statistically significant heterogeneity by age, treatment (radiation therapy dose, tamoxifen, chemotherapy), estrogen receptor status of the first primary, histology of the first primary, length of at-risk period for CBC, or breast cancer family history. Common genomic variants associated with the development of first primary breast cancer are also associated with the development of CBC; the risk is strongest among those who carry more risk alleles.

Dataset Information

Prediction of breast cancer risk based on profiling with common genetic variants.

Background

Methods

Results

Conclusions

Publications

Prediction of breast cancer risk based on profiling with common genetic variants.

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