Genetic variants of genes in the NER pathway associated with risk of breast cancer: A large-scale analysis of 14 published GWAS datasets in the DRIVE study.


A recent hypothesis-free pathway-level analysis of genome-wide association study (GWAS) datasets suggested that the overall genetic variation measured by single nucleotide polymorphisms (SNPs) in the nucleotide excision repair (NER) pathway genes was associated with breast cancer (BC) risk, but no detailed SNP information was provided. To substantiate this finding, we performed a larger meta-analysis of 14 previously published GWAS datasets in the Discovery, Biology and Risk of Inherited Variants in Breast Cancer (DRIVE) study with 53,107 subjects of European descent. Using a hypothesis-driven approach, we selected 138 candidate genes from the NER pathway using the "Molecular Signatures Database (MsigDB)" and "PathCards". All SNPs were imputed using IMPUTE2 with the 1000 Genomes Project Phase 3. Logistic regression was used to estimate BC risk, and pooled ORs for each SNP were obtained from the meta-analysis using the false discovery rate for multiple test correction. RegulomeDB, HaploReg, SNPinfo and expression quantitative trait loci (eQTL) analysis were used to assess the SNP functionality. We identified four independent SNPs associated with BC risk, BIVM-ERCC5 rs1323697_C (OR = 1.06, 95% CI = 1.03-1.10), GTF2H4 rs1264308_T (OR = 0.93, 95% CI = 0.89-0.97), COPS2 rs141308737_C deletion (OR = 1.06, 95% CI = 1.03-1.09) and ELL rs1469412_C (OR = 0.93, 95% CI = 0.90-0.96). Their combined genetic score was also associated with BC risk (OR = 1.12, 95% CI = 1.08-1.16, ptrend < 0.0001). The eQTL analysis revealed that BIVM-ERCC5 rs1323697 C and ELL rs1469412 C alleles were correlated with increased mRNA expression levels of their genes in 373 lymphoblastoid cell lines (p = 0.022 and 2.67 × 10-22 , respectively). These SNPs might have roles in the BC etiology, likely through modulating their corresponding gene expression.





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Publication Info

Ge, Jie, Hongliang Liu, Danwen Qian, Xiaomeng Wang, Patricia G Moorman, Sheng Luo, Shelley Hwang, Qingyi Wei, et al. (2019). Genetic variants of genes in the NER pathway associated with risk of breast cancer: A large-scale analysis of 14 published GWAS datasets in the DRIVE study. International journal of cancer, 145(5). pp. 1270–1279. 10.1002/ijc.32371 Retrieved from

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Patricia Gripka Moorman

Professor Emeritus in Family Medicine and Community Health

Dr. Moorman's research focuses on the epidemiology of women's health issues. Her work includes research on ovarian cancer, breast cancer and hysterectomy. Areas of particular interest include disparities in cancer risk factors and outcomes and the effects of hysterectomy on ovarian function.  As part of the Duke Evidence Synthesis group, she has also been involved in systematic reviews and meta-analyses related to ovarian cancer, breast cancer and infertility.


Sheng Luo

Professor of Biostatistics & Bioinformatics

Qingyi Wei

Professor Emeritus in Population Health Sciences

Qingyi Wei, MD, PhD, Professor in the Department of Medicine, is Associate Director for Cancer Control and Population Sciences, Co-leader of CCPS and Co-leader of Epidemiology and Population Genomics (Focus Area 1). He is a professor of Medicine and an internationally recognized epidemiologist focused on the molecular and genetic epidemiology of head and neck cancers, lung cancer, and melanoma. His research focuses on biomarkers and genetic determinants for the DNA repair deficient phenotype and variations in cell death. He is Editor-in-Chief of the open access journal "Cancer Medicine" and Associate Editor-in-Chief of the International Journal of Molecular Epidemiology and Genetics.

Area of Expertise: Epidemiology

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