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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.

Publication ,  Journal Article
Ge, J; Liu, H; Qian, D; Wang, X; Moorman, PG; Luo, S; Hwang, S; Wei, Q
Published in: Int J Cancer
September 1, 2019

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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Published In

Int J Cancer

DOI

EISSN

1097-0215

Publication Date

September 1, 2019

Volume

145

Issue

5

Start / End Page

1270 / 1279

Location

United States

Related Subject Headings

  • White People
  • Polymorphism, Single Nucleotide
  • Oncology & Carcinogenesis
  • Middle Aged
  • Logistic Models
  • Humans
  • Genome-Wide Association Study
  • Genetic Variation
  • Genetic Predisposition to Disease
  • Female
 

Citation

APA
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Ge, J., Liu, H., Qian, D., Wang, X., Moorman, P. G., Luo, S., … Wei, Q. (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. Int J Cancer, 145(5), 1270–1279. https://doi.org/10.1002/ijc.32371
Ge, Jie, Hongliang Liu, Danwen Qian, Xiaomeng Wang, Patricia G. Moorman, Sheng Luo, Shelley Hwang, and Qingyi Wei. “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.Int J Cancer 145, no. 5 (September 1, 2019): 1270–79. https://doi.org/10.1002/ijc.32371.
Ge, Jie, et al. “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.Int J Cancer, vol. 145, no. 5, Sept. 2019, pp. 1270–79. Pubmed, doi:10.1002/ijc.32371.
Ge J, Liu H, Qian D, Wang X, Moorman PG, Luo S, Hwang S, Wei Q. 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. Int J Cancer. 2019 Sep 1;145(5):1270–1279.
Journal cover image

Published In

Int J Cancer

DOI

EISSN

1097-0215

Publication Date

September 1, 2019

Volume

145

Issue

5

Start / End Page

1270 / 1279

Location

United States

Related Subject Headings

  • White People
  • Polymorphism, Single Nucleotide
  • Oncology & Carcinogenesis
  • Middle Aged
  • Logistic Models
  • Humans
  • Genome-Wide Association Study
  • Genetic Variation
  • Genetic Predisposition to Disease
  • Female