RESUMO
This work explores correlations between genetic polymorphisms in apolipoprotein E (ApoE) and atrial fibrillation (AF). We detected polymorphisms in the APOE gene in 64 patients with AF and 49 non-AF volunteers at the Department of Cardiology of Lianyungang Second People's Hospital between July 2017 and July 2019. We found significant differences in age, body mass index, left atrial diameter, and left ventricular ejection fraction between the two groups. Six APOE genotypes were observed: É2/É2; É2/É3; É2/É4; É3/É3; É3/É4; and É4/É4. The É3/É3 genotype was significantly less frequent in the AF group than in the control group, while the É3/É4 and É4/É4 genotypes were significantly more frequent in the AF group than in the control group (p<0.05). ApoE3 penetrance was significantly lower in the AF group than in the control group (p<0.05), while ApoE4 penetrance was significantly higher in the AF group than in the control group (p<0.05). ApoE3 penetrance was significantly lower in the AF group than in the control group (p<0.05). Binary logistic regression analysis showed that age, body mass index, left atrial diameter, left ventricular ejection fraction, and ApoE4 were risk factors for AF. Finally, we found that ApoE polymorphisms impacted the occurrence of AF and that ApoE4 is an AF-sensitive phenotype.
RESUMO
Obesity has been shown as a risk factor to increase the incidence of myocardial infarction (MI). However, obesity has also been linked to the decreased mortality of acute MI with unknown mechanisms. Here, we firstly used large-scale literature data mining to identify obesity downstream targets and MI upstream regulators with polarity, based on which an obesity-MI regulatory network was constructed. Then, a gene set enrichment analysis was conducted to explore the functional profile of the genes involved in the obesity-MI regulatory networks. After that, a mega-analysis using MI RNA expression datasets was conducted to test the expression of obesity-specific genes in MI patients, followed by a shortest-path analysis to explore any potential gene-MI association. Our results suggested that obesity could inhibit 11 MI promoters, including NPPB, NPPA, IRS1, SMAD3, MIR155, ADRB1, AVP, MAPK14, MC3R, ROCK1, and COL3A1, which were mainly involved in blood pressure-related pathways. Our study suggested that obesity could influence MI progression by driving multiple genes associated with blood pressure regulation. Moreover, PTH could be a novel obesity driven gene associated with the pathogenesis of MI, which needs further validation.
RESUMO
Pathogenesis of chronic obstructive pulmonary disease (COPD) is dependent on chronic inflammation and is hypothesized to represent organ-specific senescence phenotype. Identification of senescence-associated gene drivers for the development of COPD is warranted. By employing automated pipeline, we have compiled lists of the genes implicated in COPD (N = 918) and of the genes changing their activity along with cell senescence (N = 262), with a significant (p < 7.06e-60) overlap between these datasets (N = 89). A mega-analysis and a partial mega-analysis were conducted for gene sets linked to senescence but not yet to COPD, in nine independent mRNA expression datasets comprised of tissue samples of COPD cases (N = 171) and controls (N = 256). Mega-analysis of expression has identified CD38 and TNFRSF12A (p < 2.12e-8) as genes not yet explored in a context of senescence-COPD connection. Functional pathway enrichment analysis allowed to generate a model, which explains accelerated aging phenotypes previously observed in COPD patients. Presented results call for investigation of the role of TNFRSF12A/CD38 balance in establishing a vicious cycle of unresolvable tissue remodeling in COPD lungs.
RESUMO
Peroxisome proliferator-activated receptor γ (PPARG) might play a protective role in the development of myocardial infarction (MI) with limited mechanisms identified. Genes associated with both PPARG and MI were extracted from Elsevier Pathway Studio to construct the initial network. The gene expression activity within the network was estimated through a mega-analysis with eight independent expression datasets derived from Gene Expression Omnibus (GEO) to build PPARG and MI connecting pathways. After that, gene set enrichment analysis (GSEA) was conducted to explore the functional profile of the genes involved in the PPARG-driven network. PPARG demonstrated a significantly low expression in MI patients (LFC = -0.52; p < 1.84e - 9). Consequently, PPARG could indicatively be promoting three MI inhibitors (e.g., SOD1, CAV1, and POU5F1) and three MI-downregulated markers (e.g., ALB, ACADM, and ADIPOR2), which were deactivated in MI cases (p < 0.05), and inhibit two MI-upregulated markers (RELA and MYD88), which showed increased expression levels in MI cases (p = 0.0077 and 0.047, respectively). These eight genes were mainly enriched in nutrient- and cell metabolic-related pathways and functionally linked by GSEA and PPCN. Our results suggest that PPARG could protect the heart against both the development and progress of MI through the regulation of nutrient- and metabolic-related pathways.