Dataset Information

Breast Cancer Risk Genes - Association Analysis in More than 113,000 Women.

ABSTRACT:

Background

Genetic testing for breast cancer susceptibility is widely used, but for many genes, evidence of an association with breast cancer is weak, underlying risk estimates are imprecise, and reliable subtype-specific risk estimates are lacking.

Methods

We used a panel of 34 putative susceptibility genes to perform sequencing on samples from 60,466 women with breast cancer and 53,461 controls. In separate analyses for protein-truncating variants and rare missense variants in these genes, we estimated odds ratios for breast cancer overall and tumor subtypes. We evaluated missense-variant associations according to domain and classification of pathogenicity.

Results

Protein-truncating variants in 5 genes (ATM, BRCA1, BRCA2, CHEK2, and PALB2) were associated with a risk of breast cancer overall with a P value of less than 0.0001. Protein-truncating variants in 4 other genes (BARD1, RAD51C, RAD51D, and TP53) were associated with a risk of breast cancer overall with a P value of less than 0.05 and a Bayesian false-discovery probability of less than 0.05. For protein-truncating variants in 19 of the remaining 25 genes, the upper limit of the 95% confidence interval of the odds ratio for breast cancer overall was less than 2.0. For protein-truncating variants in ATM and CHEK2, odds ratios were higher for estrogen receptor (ER)-positive disease than for ER-negative disease; for protein-truncating variants in BARD1, BRCA1, BRCA2, PALB2, RAD51C, and RAD51D, odds ratios were higher for ER-negative disease than for ER-positive disease. Rare missense variants (in aggregate) in ATM, CHEK2, and TP53 were associated with a risk of breast cancer overall with a P value of less than 0.001. For BRCA1, BRCA2, and TP53, missense variants (in aggregate) that would be classified as pathogenic according to standard criteria were associated with a risk of breast cancer overall, with the risk being similar to that of protein-truncating variants.

Conclusions

The results of this study define the genes that are most clinically useful for inclusion on panels for the prediction of breast cancer risk, as well as provide estimates of the risks associated with protein-truncating variants, to guide genetic counseling. (Funded by European Union Horizon 2020 programs and others.).

SUBMITTER: Breast Cancer Association Consortium

PROVIDER: S-EPMC7611105 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature

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Publications

Breast Cancer Risk Genes - Association Analysis in More than 113,000 Women.

Dorling Leila L Carvalho Sara S Allen Jamie J González-Neira Anna A Luccarini Craig C Wahlström Cecilia C Pooley Karen A KA Parsons Michael T MT Fortuno Cristina C Wang Qin Q Bolla Manjeet K MK Dennis Joe J Keeman Renske R Alonso M Rosario MR Álvarez Nuria N Herraez Belen B Fernandez Victoria V Núñez-Torres Rocio R Osorio Ana A Valcich Jeanette J Li Minerva M Törngren Therese T Harrington Patricia A PA Baynes Caroline C Conroy Don M DM Decker Brennan B Fachal Laura L Mavaddat Nasim N Ahearn Thomas T Aittomäki Kristiina K Antonenkova Natalia N NN Arnold Norbert N Arveux Patrick P Ausems Margreet G E M MGEM Auvinen Päivi P Becher Heiko H Beckmann Matthias W MW Behrens Sabine S Bermisheva Marina M Białkowska Katarzyna K Blomqvist Carl C Bogdanova Natalia V NV Bogdanova-Markov Nadja N Bojesen Stig E SE Bonanni Bernardo B Børresen-Dale Anne-Lise AL Brauch Hiltrud H Bremer Michael M Briceno Ignacio I Brüning Thomas T Burwinkel Barbara B Cameron David A DA Camp Nicola J NJ Campbell Archie A Carracedo Angel A Castelao Jose E JE Cessna Melissa H MH Chanock Stephen J SJ Christiansen Hans H Collée J Margriet JM Cordina-Duverger Emilie E Cornelissen Sten S Czene Kamila K Dörk Thilo T Ekici Arif B AB Engel Christoph C Eriksson Mikael M Fasching Peter A PA Figueroa Jonine J Flyger Henrik H Försti Asta A Gabrielson Marike M Gago-Dominguez Manuela M Georgoulias Vassilios V Gil Fabian F Giles Graham G GG Glendon Gord G Garcia Encarna B Gómez EBG Alnæs Grethe I Grenaker GIG Guénel Pascal P Hadjisavvas Andreas A Haeberle Lothar L Hahnen Eric E Hall Per P Hamann Ute U Harkness Elaine F EF Hartikainen Jaana M JM Hartman Mikael M He Wei W Heemskerk-Gerritsen Bernadette A M BAM Hillemanns Peter P Hogervorst Frans B L FBL Hollestelle Antoinette A Ho Weang Kee WK Hooning Maartje J MJ Howell Anthony A Humphreys Keith K Idris Faiza F Jakubowska Anna A Jung Audrey A Kapoor Pooja Middha PM Kerin Michael J MJ Khusnutdinova Elza E Kim Sung-Won SW Ko Yon-Dschun YD Kosma Veli-Matti VM Kristensen Vessela N VN Kyriacou Kyriacos K Lakeman Inge M M IMM Lee Jong Won JW Lee Min Hyuk MH Li Jingmei J Lindblom Annika A Lo Wing-Yee WY Loizidou Maria A MA Lophatananon Artitaya A Lubiński Jan J MacInnis Robert J RJ Madsen Michael J MJ Mannermaa Arto A Manoochehri Mehdi M Manoukian Siranoush S Margolin Sara S Martinez Maria Elena ME Maurer Tabea T Mavroudis Dimitrios D McLean Catriona C Meindl Alfons A Mensenkamp Arjen R AR Michailidou Kyriaki K Miller Nicola N Mohd Taib Nur Aishah NA Muir Kenneth K Mulligan Anna Marie AM Nevanlinna Heli H Newman William G WG Nordestgaard Børge G BG Ng Pei-Sze PS Oosterwijk Jan C JC Park Sue K SK Park-Simon Tjoung-Won TW Perez Jose I A JIA Peterlongo Paolo P Porteous David J DJ Prajzendanc Karolina K Prokofyeva Darya D Radice Paolo P Rashid Muhammad U MU Rhenius Valerie V Rookus Matti A MA Rüdiger Thomas T Saloustros Emmanouil E Sawyer Elinor J EJ Schmutzler Rita K RK Schneeweiss Andreas A Schürmann Peter P Shah Mitul M Sohn Christof C Southey Melissa C MC Surowy Harald H Suvanto Maija M Thanasitthichai Somchai S Tomlinson Ian I Torres Diana D Truong Thérèse T Tzardi Maria M Valova Yana Y van Asperen Christi J CJ Van Dam Rob M RM van den Ouweland Ans M W AMW van der Kolk Lizet E LE van Veen Elke M EM Wendt Camilla C Williams Justin A JA Yang Xiaohong R XR Yoon Sook-Yee SY Zamora M Pilar MP Evans D Gareth DG de la Hoya Miguel M Simard Jacques J Antoniou Antonis C AC Borg Åke Å Andrulis Irene L IL Chang-Claude Jenny J García-Closas Montserrat M Chenevix-Trench Georgia G Milne Roger L RL Pharoah Paul D P PDP Schmidt Marjanka K MK Spurdle Amanda B AB Vreeswijk Maaike P G MPG Benitez Javier J Dunning Alison M AM Kvist Anders A Teo Soo H SH Devilee Peter P Easton Douglas F DF

The New England journal of medicine 20210120 5

<h4>Background</h4>Genetic testing for breast cancer susceptibility is widely used, but for many genes, evidence of an association with breast cancer is weak, underlying risk estimates are imprecise, and reliable subtype-specific risk estimates are lacking.<h4>Methods</h4>We used a panel of 34 putative susceptibility genes to perform sequencing on samples from 60,466 women with breast cancer and 53,461 controls. In separate analyses for protein-truncating variants and rare missense variants in t ...[more]

PMID: 33471991

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Project description:Previous studies suggest that melatonin may act on cancer growth through a variety of mechanisms, most notably by direct anti-proliferative effects on breast cancer cells and via interactions with the estrogen pathway. Three genes are largely responsible for mediating the downstream effects of melatonin: melatonin receptors 1a and 1b (MTNR1a and MTNR1b), and arylalkylamine N-acetyltransferase (AANAT). It is hypothesized that genetic variation in these genes may lead to altered protein production or function. To address this question, we conducted a comprehensive evaluation of the association between common single nucleotide polymorphisms (SNPs) in the MTNR1a, MTNR1b, and AANAT genes and breast cancer risk among 2,073 cases and 2,083 controls, using a two-stage analysis of genome-wide association data among women of the Shanghai Breast Cancer Study. Results demonstrate two SNPs were consistently associated with breast cancer risk across both study stages. Compared with MTNR1b rs10765576 major allele carriers (GG or GA), a decreased risk of breast cancer was associated with the AA genotype (OR = 0.78, 95% CI = 0.62-0.97, P = 0.0281). Although no overall association was seen in the combined analysis, the effect of MTNR1a rs7665392 was found to vary by menopausal status (P-value for interaction = 0.001). Premenopausal women with the GG genotype were at increased risk for breast cancer compared with major allele carriers (TT or TG) (OR = 1.57, 95% CI = 1.07-2.31, P = 0.020), while postmenopausal women were at decreased risk (OR = 0.58, 95% 0.36-0.95, P = 0.030). No significant breast cancer associations were found for variants in the AANAT gene. These results suggest that common genetic variation in the MTNR1a and 1b genes may contribute to breast cancer susceptibility, and that associations may vary by menopausal status. Given that multiple variants in high linkage disequilibrium with MTNR1b rs76653292 have been associated with altered function or expression of insulin and glucose family members, further research may focus on clarifying this relationship.

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Dataset Information

Breast Cancer Risk Genes - Association Analysis in More than 113,000 Women.

Background

Methods

Results

Conclusions

Publications

Breast Cancer Risk Genes - Association Analysis in More than 113,000 Women.

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