Research article

No evidence for association of inherited variation in genes involved in mitosis and percent mammographic density

Celine M Vachon^1*, Jingmei Li^3,4, Christopher G Scott¹, Per Hall³, Kamila Czene³, Xianshu Wang², Jianjun Liu⁴, Zachary S Fredericksen¹, David N Rider¹, Fang-Fang Wu¹, Janet E Olson¹, Julie M Cunningham², Kristen N Stevens¹, Thomas A Sellers⁵, Shane V Pankratz¹ and Fergus J Couch²

• * Corresponding author: Celine M Vachon vachon.celine@mayo.edu

Author Affiliations

¹ Department of Health Sciences Research, Mayo Clinic College of Medicine, Rochester, MN 55905, USA

² Department of Laboratory Medicine and Pathology, Mayo Clinic College of Medicine, Rochester, MN 55905, USA

³ Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Box 281, Stockholm 17177, Sweden

⁴ Human Genetics, Genome Institute of Singapore, Singapore 138672

⁵ Department of Epidemiology and Genetics, Moffitt Cancer Center, Tampa, FL 33612, USA

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Breast Cancer Research 2012, 14:R7 doi:10.1186/bcr3088

Published: 7 January 2012

Abstract

Introduction

Increased mammographic breast density is one of the strongest risk factors for breast cancer. While two-thirds of the variation in mammographic density appears to be genetically influenced, few variants have been identified. We examined the association of inherited variation in genes from pathways that mediate cell division with percent mammographic density (PMD) adjusted for age, body mass index (BMI) and postmenopausal hormones, in two studies of healthy postmenopausal women.

Methods

We investigated 2,058 single nucleotide polymorphisms (SNPs) in 378 genes involved in regulation of mitosis for associations with adjusted PMD among 484 unaffected postmenopausal controls (without breast cancer) from the Mayo Clinic Breast Cancer Study (MCBCS) and replicated the findings in postmenopausal controls (n = 726) from the Singapore and Sweden Breast Cancer Study (SASBAC) study. PMD was assessed in both studies by a computer-thresholding method (Cumulus) and linear regression approaches were used to assess the association of SNPs and PMD, adjusted for age, BMI and postmenopausal hormones. A P-value threshold of 4.2 × 10^-5 based on a Bonferroni correction of effective number of independent tests was used for statistical significance. Further, a pathway-level analysis was conducted of all 378 genes using the self-contained gene-set analysis method GLOSSI.

Results

A variant in PRPF4, rs10733604, was significantly associated with adjusted PMD in the MCBCS (P = 2.7 × 10^-7), otherwise, no single SNP was associated with PMD. Additionally, the pathway analysis provided no evidence of enrichment in the number of associations observed between SNPs in the mitotic genes and PMD (P = 0.60). We evaluated rs10733604 (PRPF4), and 73 other SNPs at P < 0.05 from 51 genes in the SASBAC study. There was no evidence of an association of rs10733604 (PRPF4) with adjusted PMD in SASBAC (P = 0.23). There were, however, consistent associations (P < 0.05) of variants at the putative locus, LOC375190, Aurora B kinase (AURKB), and Mini-chromosome maintenance complex component 3 (MCM3) with adjusted PMD, although these were not statistically significant.

Conclusions

Our findings do not support a role of inherited variation in genes involved in regulation of cell division and adjusted percent mammographic density in postmenopausal women.