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Meta-analysis

BA Babatunde Adedokun
ZD Zhaohui Du
GG Guimin Gao
TA Thomas U. Ahearn
KL Kathryn L. Lunetta
GZ Gary Zirpoli
JF Jonine Figueroa
EJ Esther M. John
LB Leslie Bernstein
WZ Wei Zheng
JH Jennifer J. Hu
RZ Regina G. Ziegler
SN Sarah Nyante
EB Elisa V. Bandera
SI Sue A. Ingles
MP Michael F. Press
SD Sandra L. Deming-Halverson
JR Jorge L. Rodriguez-Gil
SY Song Yao
TO Temidayo O. Ogundiran
OO Oladosu Ojengbede
WB William Blot
MT Melissa A. Troester
KN Katherine L. Nathanson
AH Anselm Hennis
BN Barbara Nemesure
SA Stefan Ambs
PF Peter N. Fiorica
LS Lara E. Sucheston-Campbell
JB Jeannette T. Bensen
LK Lawrence H. Kushi
GT Gabriela Torres-Mejia
DH Donglei Hu
LF Laura Fejerman
MB Manjeet K. Bolla
JD Joe Dennis
AD Alison M. Dunning
DE Douglas F. Easton
KM Kyriaki Michailidou
PP Paul D. P. Pharoah
QW Qin Wang
DS Dale P. Sandler
JT Jack A. Taylor
KO Katie M. O’Brien
CK Cari M. Kitahara
AF Adeyinka G. Falusi
CB Chinedum Babalola
JY Joel Yarney
BA Baffour Awuah
BA Beatrice Addai-Wiafe
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Regression coefficient estimates from the five contributing African ancestry studies were combined in a fixed effects meta-analysis using METAL54. Variants associated with breast cancer at P < 0.05 from the African ancestry meta-analysis were then combined in another fixed effects meta-analysis with the coefficients from the BCAC European ancestry data. Heterogeneity in both meta-analyses was assessed using the I2 statistic. SNPs that were significant genome-wide (P < 5 × 10−8) in the cross-ancestry meta-analysis, and >500 kb away from the 180 loci known to be associated with breast cancer risk were identified5,6. Conditional analysis below confirmed the identified loci. All analyses were done separately for ER-positive, ER-negative, and overall breast cancer risk.

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