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JOURNAL ARTICLE
RESEARCH SUPPORT, NON-U.S. GOV'T
Impact of Interaction Between PPAR Alpha and PPAR Gamma on Breast Cancer Risk in the Chinese Han Population.
Clinical Breast Cancer 2017 August
BACKGROUND: Several studies have been conducted to investigate the association of the peroxisome proliferator-activated receptor (PPAR) alpha (PPAR A) and PPAR gamma (PPAR G) polymorphism and breast cancer (BC) risk, but the results were inconsistent, and, until now, no study focused on the impact of gene-gene interactions between PPAR A and PPAR G on BC risk; thus, the aim of this study was to investigate the impact of interaction between PPAR A and PPAR G on BC risk in the Chinese Han population.
METHODS: A total of 862 participants with a mean age of 63.0 ± 15.7 years were selected, including 432 patients with BC and 430 controls. A logistic regression model was used to examine the association between single-nucleotide polymorphisms and BC risk. The odds ratios (ORs) and 95% confidence intervals (95% CIs) were calculated. Generalized multifactor dimensionality reduction was employed to analyze the gene-gene interaction.
RESULTS: Logistic regression analysis showed that BC risk was significantly higher in carriers of G allele of rs1800206 polymorphism than those with CC (CG + GG vs. CC) (adjusted OR, 1.50; 95% CI, 1.20-1.93). In addition, we found that BC risk was also significantly higher in carriers of the G allele of the rs1805192 polymorphism than those with the CC genotype (CG + GG vs. CC) (adjusted OR, 1.78; 95% CI, 1.34-2.26). There was a significant gene-gene interaction between rs1805192 and rs1800206. Overall, the 2-locus models had a cross-validation consistency of 10 of 10, and had a testing accuracy of 60.11%. Patients with CG or GG of rs1805192 and CG or GG of rs1800206 genotype have the highest BC risk, compared with patients with CC of rs1805192 and CC of rs1800206 genotype (OR, 2.59; 95% CI, 1.70-3.48, after covariates adjustment for gender, age, age at menarche, number of children, body mass index, and waist circumference).
CONCLUSIONS: The minor allele of rs1800206 and rs1805192 and its interaction were associated with increased BC risk.
METHODS: A total of 862 participants with a mean age of 63.0 ± 15.7 years were selected, including 432 patients with BC and 430 controls. A logistic regression model was used to examine the association between single-nucleotide polymorphisms and BC risk. The odds ratios (ORs) and 95% confidence intervals (95% CIs) were calculated. Generalized multifactor dimensionality reduction was employed to analyze the gene-gene interaction.
RESULTS: Logistic regression analysis showed that BC risk was significantly higher in carriers of G allele of rs1800206 polymorphism than those with CC (CG + GG vs. CC) (adjusted OR, 1.50; 95% CI, 1.20-1.93). In addition, we found that BC risk was also significantly higher in carriers of the G allele of the rs1805192 polymorphism than those with the CC genotype (CG + GG vs. CC) (adjusted OR, 1.78; 95% CI, 1.34-2.26). There was a significant gene-gene interaction between rs1805192 and rs1800206. Overall, the 2-locus models had a cross-validation consistency of 10 of 10, and had a testing accuracy of 60.11%. Patients with CG or GG of rs1805192 and CG or GG of rs1800206 genotype have the highest BC risk, compared with patients with CC of rs1805192 and CC of rs1800206 genotype (OR, 2.59; 95% CI, 1.70-3.48, after covariates adjustment for gender, age, age at menarche, number of children, body mass index, and waist circumference).
CONCLUSIONS: The minor allele of rs1800206 and rs1805192 and its interaction were associated with increased BC risk.
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