title: Breast cancer-associated high-order SNP-SNP interaction of CXCL12/CXCR4-related genes by an improved multifactor dimensionality reduction (MDR-ER).
abstract: In association studies, the combined effects of single nucleotide polymorphism (SNP)-SNP interactions and the problem of imbalanced data between cases and controls are frequently ignored. In the present study, we used an improved multifactor dimensionality reduction (MDR) approach namely MDR-ER to detect the high order SNP‑SNP interaction in an imbalanced breast cancer data set containing seven SNPs of chemokine CXCL12/CXCR4 pathway genes. Most individual SNPs were not significantly associated with breast cancer. After MDR‑ER analysis, six significant SNP‑SNP interaction models with seven genes (highest cross‑validation consistency, 10; classification error rates, 41.3‑21.0; and prediction error rates, 47.4‑55.3) were identified. CD4 and VEGFA genes were associated in a 2‑loci interaction model (classification error rate, 41.3; prediction error rate, 47.5; odds ratio (OR), 2.069; 95% bootstrap CI, 1.40‑2.90; P=1.71E‑04) and it also appeared in all the best 2‑7‑loci models. When the loci number increased, the classification error rates and P‑values decreased. The powers in 2‑7‑loci in all models were >0.9. The minimum classification error rate of the MDR‑ER‑generated model was shown with the 7‑loci interaction model (classification error rate, 21.0; OR=15.282; 95% bootstrap CI, 9.54‑23.87; P=4.03E‑31). In the epistasis network analysis, the overall effect with breast cancer susceptibility was identified and the SNP order of impact on breast cancer was identified as follows: CD4 = VEGFA > KITLG > CXCL12 > CCR7 = MMP2 > CXCR4. In conclusion, the MDR‑ER can effectively and correctly identify the best SNP‑SNP interaction models in an imbalanced data set for breast cancer cases.
authors.affiliation: Graduate Institute of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung 80708, Taiwan, R.O.C.
authors.forename: Ou-Yang
authors.initials: OY
authors.lastname: Fu
authors.affiliation: Cancer Center, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung 80708, Taiwan, R.O.C.
authors.forename: Hsueh-Wei
authors.initials: HW
authors.lastname: Chang
authors.affiliation: Department of Electronic Engineering, National Kaohsiung University of Applied Sciences, Kaohsiung 80778, Taiwan, R.O.C.
authors.forename: Yu-Da
authors.initials: YD
authors.lastname: Lin
authors.affiliation: Department of Chemical Engineering and Institute of Biotechnology and Chemical Engineering, I‑Shou University, Kaohsiung 84001, Taiwan, R.O.C.
authors.forename: Li-Yeh
authors.initials: LY
authors.lastname: Chuang
authors.affiliation: Cancer Center, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung 80708, Taiwan, R.O.C.
authors.forename: Ming-Feng
authors.initials: MF
authors.lastname: Hou
authors.affiliation: Department of Electronic Engineering, National Kaohsiung University of Applied Sciences, Kaohsiung 80778, Taiwan, R.O.C.
authors.forename: Cheng-Hong
authors.initials: CH
authors.lastname: Yang
mesh_terms: D000465:Algorithms; D001943:Breast Neoplasms / Q000235:genetics*; D054377:Chemokine CXCL12 / Q000235:genetics*; D004843:Epistasis, Genetic / Q000235:genetics; D005260:Female; D020022:Genetic Predisposition to Disease / Q000235:genetics; D006801:Humans; D008957:Models, Genetic; D058011:Multifactor Dimensionality Reduction / Q000379:methods*; D020641:Polymorphism, Single Nucleotide / Q000235:genetics*; D019718:Receptors, CXCR4 / Q000235:genetics*
chemical_list: C515255:CXCL12 protein, human; C527276:CXCR4 protein, human; D054377:Chemokine CXCL12; D019718:Receptors, CXCR4