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. 2023 Aug 9;25(1):93.
doi: 10.1186/s13058-023-01691-8.

A genome-wide gene-environment interaction study of breast cancer risk for women of European ancestry

Pooja Middha  1 Xiaoliang Wang  2   3 Sabine Behrens  4 Manjeet K Bolla  5 Qin Wang  5 Joe Dennis  5 Kyriaki Michailidou  5   6 Thomas U Ahearn  7 Irene L Andrulis  8   9 Hoda Anton-Culver  10 Volker Arndt  11 Kristan J Aronson  12 Paul L Auer  13 Annelie Augustinsson  14 Thaïs Baert  15 Laura E Beane Freeman  7 Heiko Becher  16 Matthias W Beckmann  17 Javier Benitez  18   19 Stig E Bojesen  20   21   22 Hiltrud Brauch  23   24   25 Hermann Brenner  11   26   27 Angela Brooks-Wilson  28 Daniele Campa  4   29 Federico Canzian  30 Angel Carracedo  31   32 Jose E Castelao  33 Stephen J Chanock  7 Georgia Chenevix-Trench  34 CTS ConsortiumEmilie Cordina-Duverger  35 Fergus J Couch  36 Angela Cox  37 Simon S Cross  38 Kamila Czene  39 Laure Dossus  40 Pierre-Antoine Dugué  41   42 A Heather Eliassen  43   44   45 Mikael Eriksson  39 D Gareth Evans  46   47 Peter A Fasching  17 Jonine D Figueroa  7   48   49 Olivia Fletcher  50 Henrik Flyger  51 Marike Gabrielson  39 Manuela Gago-Dominguez  31 Graham G Giles  41   42   52 Anna González-Neira  53 Felix Grassmann  39   54 Anne Grundy  55 Pascal Guénel  35 Christopher A Haiman  56 Niclas Håkansson  57 Per Hall  39   58 Ute Hamann  59 Susan E Hankinson  43   60 Elaine F Harkness  61   62   63 Bernd Holleczek  64 Reiner Hoppe  23   65 John L Hopper  52 Richard S Houlston  66 Anthony Howell  67 David J Hunter  44   68 Christian Ingvar  69 ABCTB InvestigatorskConFab InvestigatorsKarolin Isaksson  70 Helena Jernström  14 Esther M John  71   72 Michael E Jones  66 Rudolf Kaaks  4 Renske Keeman  73 Cari M Kitahara  74 Yon-Dschun Ko  75 Stella Koutros  7 Allison W Kurian  71   72 James V Lacey  76   77 Diether Lambrechts  78   79 Nicole L Larson  80 Susanna Larsson  57   81 Loic Le Marchand  82 Flavio Lejbkowicz  83 Shuai Li  5   41   52 Martha Linet  74 Jolanta Lissowska  84 Maria Elena Martinez  85 Tabea Maurer  86 Anna Marie Mulligan  87   88 Claire Mulot  89 Rachel A Murphy  90   91 William G Newman  46   47 Sune F Nielsen  20   21 Børge G Nordestgaard  20   21   22 Aaron Norman  80 Katie M O'Brien  92 Janet E Olson  80 Alpa V Patel  93 Ross Prentice  94 Erika Rees-Punia  93 Gad Rennert  83 Valerie Rhenius  95 Kathryn J Ruddy  96 Dale P Sandler  92 Christopher G Scott  97 Mitul Shah  95 Xiao-Ou Shu  98 Ann Smeets  99 Melissa C Southey  41   42   100 Jennifer Stone  52   101 Rulla M Tamimi  44   102 Jack A Taylor  92   103 Lauren R Teras  93 Katarzyna Tomczyk  50 Melissa A Troester  104 Thérèse Truong  35 Celine M Vachon  80 Sophia S Wang  76   77 Clarice R Weinberg  105 Hans Wildiers  15 Walter Willett  43   44   45 Stacey J Winham  106 Alicja Wolk  57   81 Xiaohong R Yang  7 M Pilar Zamora  107 Wei Zheng  98 Argyrios Ziogas  10 Alison M Dunning  95 Paul D P Pharoah  5   95 Montserrat García-Closas  7 Marjanka K Schmidt  73   108 Peter Kraft  44   109 Roger L Milne  41   42   52 Sara Lindström  2   3 Douglas F Easton #  5   95 Jenny Chang-Claude #  4   86
Affiliations

A genome-wide gene-environment interaction study of breast cancer risk for women of European ancestry

Pooja Middha et al. Breast Cancer Res. .

Abstract

Background: Genome-wide studies of gene-environment interactions (G×E) may identify variants associated with disease risk in conjunction with lifestyle/environmental exposures. We conducted a genome-wide G×E analysis of ~ 7.6 million common variants and seven lifestyle/environmental risk factors for breast cancer risk overall and for estrogen receptor positive (ER +) breast cancer.

Methods: Analyses were conducted using 72,285 breast cancer cases and 80,354 controls of European ancestry from the Breast Cancer Association Consortium. Gene-environment interactions were evaluated using standard unconditional logistic regression models and likelihood ratio tests for breast cancer risk overall and for ER + breast cancer. Bayesian False Discovery Probability was employed to assess the noteworthiness of each SNP-risk factor pairs.

Results: Assuming a 1 × 10-5 prior probability of a true association for each SNP-risk factor pairs and a Bayesian False Discovery Probability < 15%, we identified two independent SNP-risk factor pairs: rs80018847(9p13)-LINGO2 and adult height in association with overall breast cancer risk (ORint = 0.94, 95% CI 0.92-0.96), and rs4770552(13q12)-SPATA13 and age at menarche for ER + breast cancer risk (ORint = 0.91, 95% CI 0.88-0.94).

Conclusions: Overall, the contribution of G×E interactions to the heritability of breast cancer is very small. At the population level, multiplicative G×E interactions do not make an important contribution to risk prediction in breast cancer.

Keywords: Breast cancer; European ancestry; Gene-environment interactions; Genetic epidemiology.

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Conflict of interest statement

The authors do not have any conflict of interest.

Figures

Fig. 1
Fig. 1
Manhattan plot of genome-wide interactions of adult height on overall breast cancer risk. The genome-wide significance threshold of P < 5 x 10−8 is indicated by the dashed black line. Genome-wide significant findings are highlighted in blue
Fig. 2
Fig. 2
Manhattan plot of genome-wide interaction of age at menarche for ER + breast cancer risk. The genome-wide significance threshold of P < 5 x 10−8 is indicated by the dashed black line. Genome-wide significant findings are highlighted in blue.

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