METHODS: All case-control studies published in different languages such as English, Japanese, Korean, Spanish, Chinese, Hungarian, Ukrainian, or Russian were identified from databases. The pooled odds ratios (ORs) and 95% confidence intervals (CIs) were calculated via fixed- and random-effect models. Sensitivity analysis, heterogeneity test, Hardy Weinberg Equilibrium, and Egger's regression analyses were performed in this study.
RESULTS: A total of 490 case-control studies with 138,592 cases and 159,314 controls were included in this meta-analysis. Pooled ORs from all the genetic models indicated that MTHFR 677TT and 1298CC, eNOS +894TT and VNTR, PDE4D SNP 83, ACE DD, AGT 235TT, PON1 192RR, and ApoE ε4 polymorphisms were increasing the risks of ischemic stroke. Nevertheless, PDE4D SNP 87 and eNOS -786T>C polymorphisms are not associated with ischemic stroke risks.
CONCLUSIONS: Hence, the evidence from this meta-analysis concluded that MTHFR (677C>T and 1298A>C), eNOS (+894G>T and VNTR), PDE4D SNP 83, ACE I/D, AGT 235M>T, PON1 192Q>R, and ApoE ε2ε3ε4 polymorphisms predispose individuals to ischemic stroke.
AIM: To investigate the endothelial activation, inflammation, monocyte-endothelial cell binding and oxidative stress effects of four FD varieties.
METHODS: Human coronary artery endothelial cells (HCAEC) were incubated with different concentrations of aqueous ethanolic extracts of FD var. trengganuensis (FDT), var. kunstleri (FDK), var. deltoidea (FDD) and var. intermedia (FDI), together with LPS. Protein and gene expression of vascular cell adhesion molecule-1 (VCAM-1), intercellular cell adhesion molecule-1 (ICAM-1), endothelial-leukocyte adhesion molecule-1 (E-selectin), interleukin-6 (IL-6), Nuclear factor-κB (NF-κB) p50 and p65 and endothelial nitric oxide synthase (eNOS) were measured using ELISA and QuantiGene plex, respectively. Adhesion of monocyte to HCAEC and formation of reactive oxygen species (ROS) were detected by Rose Bengal staining and 2'-7'-dichlorofluorescein diacetate (DCFH-DA) assay.
RESULTS: FDK exhibited the highest inhibition of biomarkers in relation to endothelial activation and inflammation, second in reducing monocyte binding (17.3%) compared to other varieties. FDK (25.6%) was also the most potent at decreasing ROS production.
CONCLUSION: FD has anti-atherogenic effects, possibly mediated by NF-κB and eNOS pathways; with FDK being the most potent variety. It is potentially beneficial in mitigating atherogenesis.
METHODS: A case-control study was conducted involving 600 people with type 2 diabetes (300 chronic kidney disease cases, 300 controls) who participated in The Malaysian Cohort project. Retrospective subanalysis was performed on the chronic kidney disease cases to assess chronic kidney disease progression from the recruitment phase. We genotyped 32 single nucleotide polymorphisms using mass spectrometry. The probability of chronic kidney disease and predicted rate of newly detected chronic kidney disease progression were estimated from the significant gene-environment interaction analyses.
RESULTS: Four single nucleotide polymorphisms (eNOS rs2070744, PPARGC1A rs8192678, KCNQ1 rs2237895 and KCNQ1 rs2283228) and five environmental factors (age, sex, smoking, waist circumference and HDL) were significantly associated with chronic kidney disease. Gene-environment interaction analyses revealed significant probabilities of chronic kidney disease for sex (PPARGC1A rs8192678), smoking (eNOS rs2070744, PPARGC1A rs8192678 and KCNQ1 rs2237895), waist circumference (eNOS rs2070744, PPARGC1A rs8192678, KCNQ1 rs2237895 and KCNQ1 rs2283228) and HDL (eNOS rs2070744 and PPARGC1A rs8192678). Subanalysis indicated that the rate of newly detected chronic kidney disease progression was 133 cases per 1000 person-years (95% CI: 115, 153), with a mean follow-up period of 4.78 (SD 0.73) years. There was a significant predicted rate of newly detected chronic kidney disease progression in gene-environment interactions between KCNQ1 rs2283228 and two environmental factors (sex and BMI).
CONCLUSIONS: Our findings suggest that the gene-environment interactions of eNOS rs2070744, PPARGC1A rs8192678, KCNQ1 rs2237895 and KCNQ1 rs2283228 with specific environmental factors could modify the probability for chronic kidney disease.