Lack of association between CYP1A1 T6235C polymorphism and coronary artery disease: evidence from a meta-analysis

Gene-gene interaction between PPARG and CYP1A1 gene on coronary artery disease in the Chinese Han Population

AIMS

To observe the influence of the peroxisome proliferator-activator receptor-G (PPAR-G) gene and cytochrome P4501A1 (CYP1A1) single-nucleotide polymorphisms (SNPs), and interactions among several SNPs on coronary artery disease (CAD) risk.

METHODS

A total of 1106 participants (including 583 males and 523 females) including 550 CAD patients and 556 control subjects were recruited in this study, and the mean age for these participants was 55.5 ± 11.8 years old. Logistic regression was used to observe association of SNP within PPARG and CYP1A1 with CAD risk and GMDR model was used to screen the best interaction combinations.

RESULTS

CAD susceptibility was higher in those with homozygous mutant of rs10865710, rs1805192 and rs4646903 than those with wild-type homozygotes, OR (95%CI) were 1.47 (1.15-1.92), 1.69 (1.27-2.09) and 1.72 (1.35-2.32), respectively. We also found a significant two-locus model involving rs1805192 and rs4646903 (p = 0.0107), and the cross-validation consistency of this locus model was 10 of 10, the testing accuracy of this model is 62.17%. Logistic regression shown that CAD risk was the highest in those with rs1805192- Pro/Ala or Ala/Ala and rs4646903- AG+GG genotype, and was lowest in those with rs1805192- Pro/ Pro and rs4646903- AA genotype, OR(95%CI) = 3.56 (1.91-5.42).

CONCLUSIONS

Polymorphism in rs10865710, rs1805192 and rs4646903 and interaction between rs1805192 and rs4646903 were related with increased CAD susceptibility.

Impact of interaction between CYP1A1 genetic polymorphisms and smoking on coronary artery disease in the Han of China

AIMS

To investigate the association of CYP1A1 genotype and additional gene-smoking interaction with coronary artery disease (CAD) risk based on a Chinese case-control study.

METHODS

A total of 1862 participants (1134 men, 728 women) were selected, including 620 CAD patients and 1242 normal controls. Logistic regression was performed to investigate association of CYP1A1 genotype, gene-gene, and gene-smoking interaction with CAD. Generalized multifactor dimensionality reduction (GMDR) was used to screen the best gene-gene and gene-smoking interaction combination, cross-validation consistency, the testing balanced accuracy, and the sign test, to assess if each selected interaction was calculated.

RESULTS

The carriers of homozygous mutant of rs4886605 polymorphism and heterozygous of rs4646903 are associated with increased CAD risk than those with wild-type homozygotes; OR (95% CI) was 1.98 (1.53-2.61) and 1.58 (1.24-1.96), respectively. The carriers of homozygous mutant of rs1048943 polymorphism is associated with decreased CAD risk than those with wild-type homozygotes, OR (95% CI) = 0.75 (0.60-0.93). GMDR model indicated a potential gene-gene interaction between rs4886605 and rs4646903 and a potential gene-smoking interaction between rs4886605 and smoking. Participants with rs4886605-CT or TT and rs4646903-TC or CC genotype have the highest CAD risk, compared to participants with rs4886605-CC and rs4646903-TT genotype; OR (95% CI) was 2.72 (2.03-3.61). In addition, we also found that smokers with rs4886605-CT or TT genotype have the highest CAD risk, compared to nonsmokers with rs4886605-CC genotype; OR (95% CI) was 3.07 (2.23-3.96).

CONCLUSIONS

rs4886605 and rs4646903 are associated with increased CAD risk, but rs1048943 is associated with decreased CAD risk; we also found gene-gene interaction between rs4886605 and rs4646903 and gene-environment interaction between rs4886605 and smoking.

Blood-based multiple-microRNA assay displays a better diagnostic performance than single-microRNA assay in the diagnosis of breast tumor

Accumulating evidence has suggested that concentrations of blood-based circulating micro-ribonucleic acids (microRNAs, miRNAs) in breast tumor patients are significantly higher/lower than that in normal individuals, indicating that circulating miRNAs may serve as novel blood-based biomarkers for breast tumor. However, the results of previous studies on this issue have been inconclusive. Therefore, we perform a meta-analysis to determine whether aberrant miRNA expression can be used as molecular markers in blood for the diagnosis of breast tumor. PubMed and other databases were searched to identify eligible studies. The sensitivity and specificity were used to plot the summary receiver operator characteristic curve and calculate the area under the curve (AUC). Finally, 15 articles with a total of 1,428 breast tumor patients and 952 healthy individuals were involved. The summary estimates revealed that the pooled sensitivity was 76 % with 95 % confidence interval (CI) of 67-83 %; the specificity was 87 % with 95 % CI of 77-93 %; the PLR was 5.9 with 95 % CI of 3.3-10.4; the NLR was 0.28 with 95 % CI of 0.20-0.39; the DOR was 21 with 95 % CI of 10-44; and the AUC was 0.88 with 95 % CI of 0.84-0.90. The most noteworthy is that multiple-miRNA assay displayed a better diagnostic performance than single-miRNA assay. In summary, the results of the present meta-analysis suggested that blood-based miRNAs may serve as novel molecular biomarkers for breast tumor, with a relative high level of accuracy, especially based on multiple-miRNA assay. Further large-scale prospective studies are necessary to validate their potential applicability for breast tumor prognosis, treatment, and surveillance.