Impact of the PPARGC1A Gly482Ser polymorphism on left ventricular structural and functional abnormalities in patients with hypertension

Association of the TNF-α-308G>A gene polymorphism with left ventricular geometry and functional abnormalities in obstructive sleep apnea subjects

OBJECTIVE

Tumor necrosis factor-α (TNF-α) can induce left ventricular remodeling. In this study, we investigated whether the TNF-α-308G>A polymorphism is associated with left ventricular geometry (LVG) and left ventricular functional abnormalities in obstructive sleep apnea (OSA) subjects.

METHODS

Two hundred and seventy-eight subjects were enrolled. Echocardiography and genetic data were assessed in all patients. Geometric patterns of the left ventricle were determined from the relative wall thickness and left ventricular mass index (LVMI). Genetic analysis for the TNF-α-308G>A SNP rs1800629 was identified by Sanger sequencing. The correlations of the TNF-α-308G>A polymorphism with LVG and left ventricular function were analyzed by difference analysis and logistic regression.

RESULTS

The chi-square test showed that there were differences in genotype distributions among the four groups (p = 0.033), such that the frequency of GA+AA genotypes was significantly higher in the concentric hypertrophy group than in the normal geometry group (p < 0.05). Independent sample T tests showed that the GA+AA genotypes had higher IVST, LVPWT, LVMI, E/e' values, and lower e' values than those of the GG genotype (p < 0.05). Logistic regression analysis showed that the TNF-α-308G>A polymorphism was independently correlated with eccentric hypertrophy (OR = 2.456, p = 0.047) and concentric hypertrophy (OR = 2.456, p = 0.047).

CONCLUSION

In OSA patients, the TNF-α-308G>A polymorphism was linked to LVG and abnormal left ventricular diastolic function, suggesting that the TNF-α-308G>A polymorphism may have an important influence on LVG alterations.

Circulating Biomarkers of Fibrosis Formation in Patients with Arrhythmogenic Cardiomyopathy

Arrhythmogenic cardiomyopathy (ACM) is a progressive inheritable disease which is characterized by a gradual fibro-(fatty) replacement of the myocardium. Visualization of diffuse and patchy fibrosis patterns is challenging using clinically applied cardiac imaging modalities (e.g., late gadolinium enhancement, LGE). During collagen synthesis and breakdown, carboxy–peptides are released into the bloodstream, specifically procollagen type-I carboxy-terminal propeptides (PICP) and collagen type-I carboxy-terminal telopeptides (ICTP). We collected the serum and EDTA blood samples and clinical data of 45 ACM patients (age 50.11 ± 15.53 years, 44% female), divided into 35 diagnosed ACM patients with a 2010 ARVC Task Force Criteria score (TFC) ≥ 4, and 10 preclinical variant carriers with a TFC < 4. PICP levels were measured using an enzyme-linked immune sorbent assay and ICTP levels with a radio immunoassay. Increased PICP/ICTP ratios suggest a higher collagen deposition. We found significantly higher PICP and PICP/ICTP levels in diagnosed patients compared to preclinical variant carriers (p < 0.036 and p < 0.027). A moderate negative correlation existed between right ventricular ejection fractions (RVEF) and the PICP/ICTP ratio (r = −0.46, p = 0.06). In addition, significant correlations with left ventricular function (LVEF r = −0.53, p = 0.03 and end-systolic volume r = 0.63, p = 0.02) were found. These findings indicate impaired contractile performance due to pro-fibrotic remodeling. Follow-up studies including a larger number of patients should be performed to substantiate our findings and the validity of those levels as potential promising biomarkers in ACM.

Transcriptomic studies revealed pathophysiological impact of COVID-19 to predominant health conditions

Despite the association of prevalent health conditions with coronavirus disease 2019 (COVID-19) severity, the disease-modifying biomolecules and their pathogenetic mechanisms remain unclear. This study aimed to understand the influences of COVID-19 on different comorbidities and vice versa through network-based gene expression analyses. Using the shared dysregulated genes, we identified key genetic determinants and signaling pathways that may involve in their shared pathogenesis. The COVID-19 showed significant upregulation of 93 genes and downregulation of 15 genes. Interestingly, it shares 28, 17, 6 and 7 genes with diabetes mellitus (DM), lung cancer (LC), myocardial infarction and hypertension, respectively. Importantly, COVID-19 shared three upregulated genes (i.e. MX2, IRF7 and ADAM8) with DM and LC. Conversely, downregulation of two genes (i.e. PPARGC1A and METTL7A) was found in COVID-19 and LC. Besides, most of the shared pathways were related to inflammatory responses. Furthermore, we identified six potential biomarkers and several important regulatory factors, e.g. transcription factors and microRNAs, while notable drug candidates included captopril, rilonacept and canakinumab. Moreover, prognostic analysis suggests concomitant COVID-19 may result in poor outcome of LC patients. This study provides the molecular basis and routes of the COVID-19 progression due to comorbidities. We believe these findings might be useful to further understand the intricate association of these diseases as well as for the therapeutic development.

Linking Metabolic Disease With the PGC-1α Gly482Ser Polymorphism

Peroxisome proliferator-activated receptor γ coactivator 1-α (PGC-1α) is a highly conserved transcriptional coactivator enriched in metabolically active tissues including liver, adipose, pancreas, and muscle. It plays a role in regulating whole body energy metabolism and its deregulation has been implicated in type 2 diabetes (T2D). A single nucleotide variant of the PPARGC1A gene (rs8192678) is associated with T2D susceptibility, relative risk of obesity and insulin resistance, and lower indices of β cell function. This common polymorphism is within a highly conserved region of the bioactive protein and leads to a single amino acid substitution (glycine 482 to serine). Its prevalence and effects on metabolic parameters appear to vary depending on factors including ethnicity and sex, suggesting important interactions between genetics and cultural/environmental factors and associated disease risk. Interestingly, carriers of the serine allele respond better to some T2D interventions, illustrating the importance of understanding functional impacts of genetic variance on PGC-1α when targeting this pathway for personalized medicine. This review summarizes a growing body of literature surrounding possible links between the PGC-1α Gly482Ser single nucleotide polymorphism and diabetes, with focus on key clinical findings, affected metabolic systems, potential molecular mechanisms, and the influence of geographical or ethnic background on associated risk.