A key fatty acid synthesis enzyme, acetyl-CoA carboxylase alpha (ACC-alpha), has been shown to be highly expressed in human breast cancer and other tumor types and also to specifically interact with the protein coded by one of two major breast cancer susceptibility genes BRCA1. We used a comprehensive haplotype analysis to examine the contribution of the ACC-alpha common genetic variation (allele frequency >5%) to breast cancer in a case-control study (1,588 cases/2,600 controls) nested within the European Prospective Investigation into Cancer and Nutrition. We identified 21 haplotype-tagging polymorphisms efficiently capturing common variation within 325 kb of ACC-alpha and surrounding sequences using genotype data from the HapMap project and our resequencing data. We found an effect on overall risk of breast cancer in homozygous carriers of one common haplotype [odds ratio (OR), 1.74; 95% confidence interval (95% CI), 1.03-2.94]. When the data were subdivided by menopausal status, we found statistical evidence of heterogeneity for two other common haplotypes (P value for heterogeneity = 0.016 and 0.045). In premenopausal women, the carriers of these haplotypes, compared with noncarriers, had an altered risk of breast cancer (OR, 0.70; 95% CI, 0.53-0.92 and OR, 1.35; 95% CI, 1.04-1.76). These findings were not significant after adjustment for multiple testing and therefore should be considered as preliminary and evaluated in larger independent studies. However, they suggest a possible role of the ACC-alpha common sequence variants in susceptibility to breast cancer and encourage studies of other genes involved in fatty acid synthesis.

Original publication

DOI

10.1158/1055-9965.EPI-06-0617

Type

Journal article

Journal

Cancer Epidemiol Biomarkers Prev

Publication Date

03/2007

Volume

16

Pages

409 - 415

Keywords

Acetyl-CoA Carboxylase, Adult, Aged, Alleles, Breast Neoplasms, Case-Control Studies, Chi-Square Distribution, Europe, Female, Gene Frequency, Genetic Predisposition to Disease, Genetic Variation, Genotype, Haplotypes, Humans, Logistic Models, Middle Aged, Risk Factors