Meta-analysis of the association between Apolipoprotein E polymorphism and risks of myocardial infarction.

BACKGROUND: Myocardial infarction (MI) remains the leading cause of death and disability among cardiovascular diseases worldwide. Studies show that elevated low-density lipid protein cholesterol (LDL-C) levels confer the highest absolute risk of MI, and Apolipoprotein E (ApoE) is implicated in regulating levels of triglycerides (TGs), cholesterol, and LDL-C. Our study aimed to evaluate the association between APOE polymorphism and MI, and to provide evidence for the etiology of MI. METHODS: Case-control studies on the association between APOE polymorphisms and the risk of myocardial infarction were included by searching PubMed, Web of Science, and CNKI, and this meta-analysis was written in accordance with PRISMA guideline statement. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated using either random-effects or fixed-effects models by R software. RESULTS: A total of 33 eligible articles involving 13,706 cases and 14,817 controls were finally selected. The pooled analysis based on the total eligible articles showed that the risk of MI was associated with ApoE epsilon 2 and epsilon 4 alleles. The results showed that patients with MI had a low frequency of the ε2 allele (OR 0.74, 95% CI 0.64-0.86) and a high frequency of the ε4 allele (OR 1.24, 95% CI 1.09-1.42). CONCLUSIONS: APOE ε2-involved genotypes may be protective factors for MI; in contrast, ε4-involved genotypes (ε4/ε3 vs. ε3/ε3, and ε4/ε4 vs. ε3/ε3) may be risk factors for MI.

Sociodemographic and behavioral influences on multimorbidity among adult residents of northeastern China.

BACKGROUND: Multimorbidity is defined as two or more chronic health conditions existing in an individual simultaneously. Multimorbidity has been associated with poor conditions, such as higher health care costs and the poor quality of life. Thus, identifying the risk factors of the multimorbidity is required for multimorbidity prevention. METHODS: This study was based on the Comprehensive Demonstration Research Project of Major Chronic Noncommunicable Disease Prevention and Control Technology in Northeast China initiated by China Medical University. The investigation was a cross-sectional study under a multistage stratified cluster random sampling design. Associations between multimorbidity and sociodemographic and behavioral factors in adult residents were investigated using univariate analysis and multivariate logistic regression analysis. RESULTS: A total of 6706 participants were enrolled in this investigation, and the prevalence of multimorbidity was 21.2% among the adult residents of northeastern China. There existed differences of association between age and multimorbidity risks (65-69 years old: OR = 3.53, 95%CI: 2.04-6.12; 70-74 years old: OR = 5.26, 95%CI: 3.02-9.17). Participants who are overweight had significantly high multimorbidity risk (OR = 2.76, 95%CI: 1.50-5.24). Family history of hypertension and family history of diabetes were significantly associated with high multimorbidity risk (family history of hypertension: OR = 2.34, 95%CI: 1.96-2.79; family history of diabetes: OR = 1.77, 95%CI: 1.38-2.26). Compared with the frequency of fatigue (< 1 time/week or 1-2 times/week), that (≥3 times/week) was associated with high multimorbidity risk (OR = 1.39, 95%CI: 1.07-1.81). For fresh fruit consumption, compared with eating fruits regularly, eating rarely had a higher risk of multimorbidity (OR = 2.33, 95%CI: 1.90-2.85). CONCLUSIONS: Sociodemographic indices (age, BMI, family history of hypertension, and family history of diabetes) and behavioral indices (fatigue status and fresh fruit consumption) increase the risks of multimorbidity. This study provides a necessary route to prevent and control multimorbidity in northeast China.

Transcription factor AP-2 gamma/Krüppel-like factor 10 axis is involved in miR-3656-related dysfunction of endothelial cells in hypertension.

BACKGROUND: Dysfunction of endothelial cells links to microvascular rarefaction, reflecting the pathogenesis of hypertension. Our previous studies found that miR-3656 reduces nitric oxide generation and von Willebrand factor (vWF) cleavage, thereby retarding blood flow and potentially increasing blood pressure. In this paper, we investigated mechanism of transcription regulation contributing to miR-3656-damaged endothelial cells in hypertension. METHODS: The effects of miR-3656 on function of endothelial cells were analyzed on the basis of proliferation, migration, tube formation, and apoptosis. The mRNA level and protein level of genes were examined using quantitative real-time polymerase chain reaction (qRT-PCR) and western blot. Dual-luciferase reporter assay was performed to confirm the binding between miR-3656 and 3' untranslated region (UTR) of transcription factor AP-2 gamma ( TFAP2C ). The binding between TFAP2C and the promoter region of Krüppel-like factor 10 ( KLF10 ) was confirmed by chromatin immunoprecipitation-qPCR assay. RESULTS: miR-3656 impaired the cell proliferation, migration, tube formation, and apoptosis of endothelial cells. miR-3656 inhibited the expression of TFAP2C by directly targeting 3'UTR of TFAP2C ; moreover, miR-3656-induced injury of endothelial cells was rescued by TFAP2C overexpression. Furthermore, downregulated TFAP2C decreased KLF10 expression by binding to KLF10 promoter region, and upregulated KLF10 reversed the effects of silencing TFAP2C on endothelial cells. These inhibitory processes led to interference of miR-3656 to KLF10-promoted function of endothelial cells. CONCLUSION: TFAP2C/KLF10 axis is involved in miR-3656-related dysfunction of endothelial cells in hypertension. The 3'UTR of TFAP2C and KLF10 promoter region are the hubs of the TFAP2C/KLF10 axis.

Association between KCNJ11 E23K polymorphism and the risk of type 2 diabetes mellitus: A global meta-analysis.

BACKGROUND: Potassium inwardly rectifying channel, subfamily J member 11(KCNJ11) is considered to be a potential susceptible gene of type 2 diabetes mellitus (T2DM), and the association between KCNJ11 E23K polymorphism and T2DM risk is still controversial worldwide. This meta-analysis was performed to assess the association more accurately between KCNJ11 E23K polymorphism and T2DM risk. METHODS: The up-to-data meta-analysis was conducted based on studies selected from eight databases (PubMed, Web of Science, Medline, Scopus, Embase, CNKI, WanFang, and Vip). Five gene models were included in our study: allele model (K-allele vs. E-allele), heterozygous model (EK vs. EE), homozygous model (KK vs. EE), dominant genetic model (EK + KK vs. EE), and recessive genetic model (EK + EE vs. KK). Association strength was evaluated by odds ratio (OR) and 95% confidence interval (CI), publication bias was evaluated by Begg's funnel plot and Egger's test, sensitivity analysis and trial sequential analysis (TSA) were used to evaluate the stability of the results. RESULTS: According to the inclusion and exclusion criteria, 31 eligible articles were finally selected in our meta-analysis, including 8754 T2DM cases and 7587 controls. We found that allelic model (OR = 1.25, 95%CI: 1.15-1.35, P < 0.01), heterozygous model (OR = 1.31, 95% CI: 1.18-1.44, P < 0.01), homozygous model (OR = 1.48, 95% CI: 1.24-1.76, P < 0.01), and dominant genetic model (OR = 1.35, 95% CI: 1.22-1.50, P < 0.01) were significantly associated with increased risk of T2DM, but recessive genetic model (OR = 0.78, 95% CI: 0.67-0.91, P < 0.01) was considered as a protective factor for T2DM. No significant evidence of publication bias was found. CONCLUSION: Our meta-analysis confirms the association between KCNJ11 E23K polymorphism and the risk of T2DM, highlighting that gene-gene interaction and gene-environment interaction should be investigated in future.