Ferulic Acid Ameliorates Isoproterenol-Induced Heart Failure by Decreasing Oxidative Stress and Inhibiting Cardiocyte Apoptosis via Activating Nrf2 Signaling Pathway in Rats.

Ferulic acid (FA) has potential therapeutic effects in multiple diseases including cardiovascular diseases. However, the effect and molecular basis of FA in heart failure (HF) has not been thoroughly elucidated. Herein, we investigated the roles and mechanisms of FA in HF in isoproterenol (ISO)-induced HF rat model. Results found that FA ameliorated cardiac dysfunction, alleviated oxidative stress, reduced cell/myocardium injury-related enzyme plasma level, inhibited cardiocyte apoptosis in ISO-induced HF rat models. Moreover, FA reduced the co-localization of Keap1 and nuclear factor-E2-related factor 2 (Nrf2) in heart tissues of ISO-induced HF rats, and FA alleviated the inhibitory effects of ISO on expressions of p-Nrf2, heme oxygenase-1 (HO-1) and reduced nicotinamide adenine dinucleotide phosphate quinone dehydrogenase 1 (NQO1). Additionally, Nrf2 signaling pathway inhibitor ML385 showed adverse effects. FA weakened the effects of ML385 in ISO-induced HF rat models. Collectively, FA ameliorated HF by decreasing oxidative stress and inhibiting cardiocyte apoptosis via activating Nrf2 pathway in ISO-induced HF rats. Our data elucidated the underling molecular mechanism and provided a novel insight into the cardioprotective function of FA, thus suggested the therapeutic potential of FA in HF treatment.

GPNMB contributes to a vicious circle for chronic obstructive pulmonary disease.

Osteoporosis (OP) is significant and debilitating comorbidity of chronic obstructive pulmonary disease (COPD). We hypothesize that genetic variance identified with OP may also play roles in COPD. We have conducted a large-scale relation data analysis to explore the genes implicated with either OP or COPD, or both. Each gene linked to OP but not to COPD was further explored in a mega-analysis and partial mega-analysis of 15 independently collected COPD RNA expression datasets, followed by gene set enrichment analysis (GSEA) and literature-based pathway analysis to explore their functional linked to COPD. A multiple linear regression (MLR) model was built to study the possible influence of sample size, population region, and study date on the gene expression data in COPD. At the first step of the analysis, we have identified 918 genes associated with COPD, 581 with OP, and a significant overlap (P<2.30e-140; 210 overlapped genes). Partial mega-analysis showed that, one OP gene, GPNMB presented significantly increased expression in COPD patients (P-value = 0.0018; log fold change = 0.83). GPNMB was enriched in multiple COPD pathways and plays roles as a gene hub formulating multiple vicious COPD pathways included gene MMP9 and MYC. GPNMB could be a novel gene that plays roles in both COPD and OP. Partial mega-analysis is valuable in identify case-specific genes for COPD.