Identification of 31 loci for mammographic density phenotypes and their associations with breast cancer risk

Weiva Sieh,Joseph H Rothstein,Robert J Klein,Lori C Sakoda,Russell Mcbride ,Neil Risch,Rebecca E Graff,Alice S Whittemore,Luana Acton,Rhea Liang ,Douglas F Easton,Stacey Alexeeff ,Martin J Yaffe,Ninah Achacoso,Valerie Mcguire,Jafi A Lipson,Eric Jorgenson,Daniel L Rubin,Catherine Schaefer,Laurel A Habel

doi:10.1038/s41467-020-18883-x

Abstract

Mammographic density (MD) phenotypes are strongly associated with breast cancer risk and highly heritable. In this GWAS meta-analysis of 24,192 women, we identify 31 MD loci at P < 5 × 10−8, tripling the number known to 46. Seventeen identified MD loci also are associated with breast cancer risk in an independent meta-analysis (P < 0.05). Mendelian randomization analyses show that genetic estimates of dense area (DA), nondense area (NDA), and percent density (PD) are all significantly associated with breast cancer risk (P < 0.05). Pathway analyses reveal distinct biological processes involving DA, NDA and PD loci. These findings provide additional insights into the genetic basis of MD phenotypes and their associations with breast cancer risk.

Highlights

Mammographic density (MD) phenotypes are strongly associated with breast cancer risk and highly heritable
Mendelian randomization analyses show that genetic estimates of dense area (DA), nondense area (NDA), and percent density (PD) are all significantly associated with breast cancer risk
This genome-wide association study (GWAS) meta-analysis comprised a total of 24,192 non-Hispanic white women with MD phenotypes measured centrally using Cumulus software[16]

Summary

Introduction

Mammographic density (MD) phenotypes are strongly associated with breast cancer risk and highly heritable. Pathway analyses reveal distinct biological processes involving DA, NDA and PD loci These findings provide additional insights into the genetic basis of MD phenotypes and their associations with breast cancer risk. In this genome-wide association study (GWAS) meta-analysis of 24,192 women screened with full-field digital mammography (FFDM), we identify 31 MD loci, of which 17 are associated with breast cancer in an independent study of over 200,000 breast cancer cases and controls[15] These findings triple the total number of independent genome-wide significant MD loci mapped to 46, enabling the first genetic pathway analyses and Mendelian randomization analyses to evaluate the causal nature of the association of MD phenotypes with breast cancer risk. These findings provide additional insights into the genetic basis of MD phenotypes and their relationship with breast cancer risk

Methods

Results

Conclusion