Green Tea Polyphenols Reduce Body Weight in Rats by Modulating Obesity-Related Genes

Beneficial effects of green tea polyphenols (GTP) against obesity have been reported, however, the mechanism of this protection is not clear. Therefore, the objective of this study was to identify GTP-targeted genes in obesity using the high-fat-diet-induced obese rat model. A total of three groups (n = 12/group) of Sprague Dawley (SD) female rats were tested, including the control group (rats fed with low-fat diet), the HF group (rats fed with high-fat diet), and the HF+GTP group (rats fed with high-fat diet and GTP in drinking water). The HF group increased body weight as compared to the control group. Supplementation of GTP in the drinking water in the HF+GTP group reduced body weight as compared to the HF group. RNA from liver samples was extracted for gene expression analysis. A total of eighty-four genes related to obesity were analyzed using PCR array. Compared to the rats in the control group, the rats in the HF group had the expression levels of 12 genes with significant changes, including 3 orexigenic genes (Agrp, Ghrl, and Nr3c1); 7 anorectic genes (Apoa4, Cntf, Ghr, IL-1β, Ins1, Lepr, and Sort); and 2 genes that relate to energy expenditure (Adcyap1r1 and Adrb1). Intriguingly, the HF+GTP group restored the expression levels of these genes in the high-fat-induced obese rats. The protein expression levels of IL-1β and IL-6 in the serum samples from the control, HF, and HF+GTP groups confirmed the results of gene expression. Furthermore, the protein expression levels of superoxide dismutase-1 (SOD1) and catechol-O-methyltransferase (COMT) also showed GTP-regulated protective changes in this obese rat model. Collectively, this study revealed the beneficial effects of GTP on body weight via regulating obesity-related genes, anti-inflammation, anti-oxidant capacity, and estrogen-related actions in high-fat-induced obese rats

The impact of immunoglobulin G N-glycosylation level on COVID-19 outcome: evidence from a Mendelian randomization study

BackgroundThe coronavirus disease 2019 (COVID-19) pandemic has exerted a profound influence on humans. Increasing evidence shows that immune response is crucial in influencing the risk of infection and disease severity. Observational studies suggest an association between COVID‐19 and immunoglobulin G (IgG) N-glycosylation traits, but the causal relevance of these traits in COVID-19 susceptibility and severity remains controversial.MethodsWe conducted a two-sample Mendelian randomization (MR) analysis to explore the causal association between 77 IgG N-glycosylation traits and COVID-19 susceptibility, hospitalization, and severity using summary-level data from genome-wide association studies (GWAS) and applying multiple methods including inverse-variance weighting (IVW), MR Egger, and weighted median. We also used Cochran’s Q statistic and leave-one-out analysis to detect heterogeneity across each single nucleotide polymorphism (SNP). Additionally, we used the MR-Egger intercept test, MR-PRESSO global test, and PhenoScanner tool to detect and remove SNPs with horizontal pleiotropy and to ensure the reliability of our results.ResultsWe found significant causal associations between genetically predicted IgG N-glycosylation traits and COVID-19 susceptibility, hospitalization, and severity. Specifically, we observed reduced risk of COVID-19 with the genetically predicted increased IgG N-glycan trait IGP45 (OR = 0.95, 95% CI = 0.92–0.98; FDR = 0.019). IGP22 and IGP30 were associated with a higher risk of COVID-19 hospitalization and severity. Two (IGP2 and IGP77) and five (IGP10, IGP14, IGP34, IGP36, and IGP50) IgG N-glycosylation traits were causally associated with a decreased risk of COVID-19 hospitalization and severity, respectively. Sensitivity analyses did not identify any horizontal pleiotropy.ConclusionsOur study provides evidence that genetically elevated IgG N-glycosylation traits may have a causal effect on diverse COVID-19 outcomes. Our findings have potential implications for developing targeted interventions to improve COVID-19 outcomes by modulating IgG N-glycosylation levels

Chemotherapeutic Sensitization of Leptomycin B Resistant Lung Cancer Cells by Pretreatment with Doxorubicin

The development of novel targeted therapies has become an important research focus for lung cancer treatment. Our previous study has shown leptomycin B (LMB) significantly inhibited proliferation of lung cancer cells; however, p53 wild type lung cancer cells were resistant to LMB. Therefore, the objective of this study was to develop and evaluate a novel therapeutic strategy to sensitize LMB-resistant lung cancer cells by combining LMB and doxorubicin (DOX). Among the different treatment regimens, pretreatment with DOX (pre-DOX) and subsequent treatment with LMB to A549 cells significantly decreased the 50% inhibitory concentration (IC50) as compared to that of LMB alone (4.4 nM vs. 10.6 nM, P<0.05). Analysis of cell cycle and apoptosis by flow cytometry further confirmed the cytotoxic data. To investigate molecular mechanisms for this drug combination effects, p53 pathways were analyzed by Western blot, and nuclear proteome was evaluated by two dimensional-difference gel electrophoresis (2D-DIGE) and mass spectrometry. In comparison with control groups, the levels of p53, phospho-p53 (ser15), and p21 proteins were significantly increased while phospho-p53 (Thr55) and survivin were significantly decreased after treatments of pre-DOX and LMB (P<0.05). The 2D-DIGE/MS analysis identified that sequestosome 1 (SQSTM1/p62) had a significant increase in pre-DOX and LMB-treated cells (P<0.05). In conclusion, our results suggest that drug-resistant lung cancer cells with p53 wild type could be sensitized to cell death by scheduled combination treatment of DOX and LMB through activating and restoring p53 as well as potentially other signaling pathway(s) involving sequestosome 1

Hsa_circ_0010220 regulates miR-198/Syntaxin 6 axis to promote osteosarcoma progression

Background: Circular RNAs (circRNAs) are a class of endogenous RNAs that are involved in osteosarcoma progression. Hsa_circ_0010220 (circ_0010220) is a circRNA generated by gene Rho Guanine Nucleotide Exchange Factor 10 Like (ARHGEF10L) and is upregulated in osteosarcoma, but its functional role in osteosarcoma is limited studied. This study aimed to illustrate the regulatory mechanism underlying circ_0010220 in osteosarcoma. Methods: 51 paired tumor and normal tissues were obtained from osteosarcoma patients. circ_0010220, microRNA (miR)-198 and Syntaxin 6 (STX6) abundances were examined by quantitative reverse transcription polymerase chain reaction and western blot. Cell proliferation, cell cycle, apoptosis, migration and invasion were analyzed via Cell Counting Kits-8 (CCK-8), colony formation, flow cytometry and transwell analyses. Target relationship was verified via dual-luciferase reporter analysis, RNA immunoprecipitation and pull-down. The in vivo function was analyzed using a xenograft model. Results: Circ_0010220 was elevated in osteosarcoma tissues and cells, and was related to the lower survival rate of osteosarcoma patients. Circ_0010220 knockdown inhibited cell proliferation, migration and invasion, but induced cell cycle arrest and apoptosis in vitro. Besides, circ_0010220 silence curbed the growth of xenograft osteosarcoma tumors in vivo. Mechanistic research revealed that miR-198 is a target of circ_0010220, and directly targets STX6. Moreover, circ_0010220 upregulated the expression of STX6 by sponging miR-198 to regulate cell proliferation, migration, invasion, cell cycle, and apoptosis. Conclusion: Circ_0010220 contributes to osteosarcoma progression through mediating miR-198/STX6 axis, which might be a novel therapeutic target for osteosarcoma therapy

The changes of obesity-related genes among the control, HF, and HF+GTP groups.

<p>(A) Representative PCR array gene tables of undetected genes and detected genes. (B) The heat map demonstrating fold regulation expression data between the HF group and the control group. Genes with significant differences between two groups are shown in the histogram. (C) The heat map demonstrating fold regulation expression data between the HF+GTP group and the HF group. Genes with significant differences between two groups are shown in the histogram. (D) The heat map demonstrating fold regulation expression data between the HF+GTP group and the control group. Genes with significant differences between two groups are shown in the histogram.</p

Rat obesity PCR Array.

<p>(A) Functional gene grouping in 3 colors: orexigenic genes in red, anorectic genes in yellow, and genes involved in energy expenditure in green. (B) The C_T value of quality control used rat genomic DNA.</p

Western blot analyses of protein expression in the control, HF, and HF+GTP groups.

<p>(A) Effects of HF and HF+GTP treatment on the protein expression of SOD1. (B) Effects of HF and HF+GTP treatment on the protein expression of COMT. Blots were also probed for α-tubulin to confirm equal protein loading. The relative protein intensities of SOD1 and COMT were compared with the intensity of α-tubulin. The intensity of each band was quantified using Quantity One software. Data are means±SE, n = 3. The experiments were conducted in triplicate. * P<0.05 between the control and HF groups; ** P<0.01 between the control and HF groups; ## P<0.01 between HF and HF+GTP; ∧∧P<0.01 between the control and HF+GTP groups.</p

Proinflammatory cytokines changes among the control, HF, and HF+GTP groups.

<p>Results are expressed as mean±SE. # P<0.05 between the HF and HF+GTP groups.</p