| Literature DB >> 27597864 |
Hernán Gonzalo Villagarcía1, Vanesa Sabugo1, María Cecilia Castro1, Guillermo Schinella2, Daniel Castrogiovanni3, Eduardo Spinedi1, María Laura Massa1, Flavio Francini1.
Abstract
We investigated the impact of chronic hypercorticosteronemia (due to neonatal monosodium L-glutamate, MSG, and treatment) on liver oxidative stress (OS), inflammation, and carbohydrate/lipid metabolism in adult male rats. We evaluated the peripheral concentrations of several metabolic and OS markers and insulin resistance indexes. In liver we assessed (a) OS (GSH and protein carbonyl groups) and inflammatory (IL-1b, TNFa, and PAI-1) biomarkers and (b) carbohydrate and lipid metabolisms. MSG rats displayed degenerated optic nerves, hypophagia, low body and liver weights, and enlarged adipose tissue mass; higher peripheral levels of glucose, triglycerides, insulin, uric acid, leptin, corticosterone, transaminases and TBARS, and peripheral and liver insulin resistance; elevated liver OS, inflammation markers, and glucokinase (mRNA/activity) and fructokinase (mRNA). Additionally, MSG liver phosphofructokinase-2, glucose-6-phosphatase (mRNA and activity) and glucose-6-phosphate dehydrogenase, Chrebp, Srebp1c, fatty acid synthase, and glycerol-3-phosphate (mRNAs) were increased. In conclusion adult MSG rats developed an insulin-resistant state and increased OS and serious hepatic dysfunction characterized by inflammation and metabolic signs suggesting increased lipogenesis. These features, shared by both metabolic and Cushing's syndrome human phenotypes, support that a chronic glucocorticoid-rich endogenous environment mainly impacts on hepatic glucose cycle, displacing local metabolism to lipogenesis. Whether correcting the glucocorticoid-rich environment ameliorates such dysfunctions requires further investigation.Entities:
Year: 2016 PMID: 27597864 PMCID: PMC4997070 DOI: 10.1155/2016/7838290
Source DB: PubMed Journal: Int J Endocrinol ISSN: 1687-8337 Impact factor: 3.257
Rat specific primers used for real-time PCR analyses.
| GBAN | bp | ||
|---|---|---|---|
|
| F, 5′-AGAGGGAAATCGTGCGTGAC-3′ | NM_031144 | 138 |
| R, 5′-CGATAGTGATGACCTGACCGT-3′ | |||
|
| F, 5′-CAGATGCGGGACATGTTTGA-3′ | NM_133552.1 | 205 |
| R, 5′-AATAAAGGTCGGATGAGGATGCT-3′ | |||
|
| F, 5′-GTCTGCAGCTACCCACCCGTG-3′ | NM_017332.1 | 214 |
| R, 5′-CTTCTCCAGGGTGGGGACCAG-3′ | |||
|
| F, 5′-ACGGATCGCAGGTGCCTAT-3′ | NM_031855.3 | 68 |
| R, 5′-AGCACAGTGCAGGAGTTGGA-3′ | |||
|
| F, 5′-GTGTACAAGCTGCACCCGA-3′ | NM_012565.1 | 156 |
| R, 5′-CAGCATGCAAGCCTTCTTG-3′ | |||
|
| F, 5′-GACGAAGCCTTCCGAAGGA-3′ | AF_021348 | 68 |
| R, 5′-GACTTGCTGGCGGTGAAGAG-3′ | |||
|
| F, 5′-GATCGCTGACCTCAGGAACGC-3′ | NM_013098.2 | 198 |
| R, 5′-AGAGGCACGGAGCTGTTGCTG-3′ | |||
|
| F, 5′-TTCCGGGATGGCCTTCTAC-3′ | NM_017006.2 | 81 |
| R, 5′-TTTGCGGATGTCATCCACTGT-3′ | |||
|
| F, 5′-ACAAGGAGAGACAAGCAACGAC-3′ | NM_031512.2 | 140 |
| R, 5′-TCTTCTTTGGGTATTGTTTGGG-3′ | |||
|
| F, 5′-CCACGGTGAAGCAGGTGGACT-3′ | NM_012620.1 | 195 |
| R, 5′-TGCTGGCCTCTAAGAAGGGG-3′ | |||
|
| F, 5′-TGCCCCAGGAAGTGAGGAAG-3′ | NM_198780.3 | 177 |
| R, 5′-GGTCAGTGAGAGCCAGCCAAC-3′ | |||
|
| F, 5′-CGATCTATCTACCTATGCCGCCAT-3′ | NM_012621.4 | 256 |
| R, 5′-ACACCCGCATCAATCTCATTCA-3′ | |||
|
| F, 5′-TTTCTTCGTGGATGGGGACT-3′ | XM_213329.5 | 208 |
| R, 5′-CTGTAGATATCCAAGAGCATC-3′ | |||
|
| F, 5′- GGCATGGATCTCAAAGACAACC-3′ | NM_012675.3 | 130 |
| R, 5′- CAAATCGGCTGACGGTGTG-3′ |
F: forward primer; R: reverse primer; GBAN: GenBank accession number; amplicon length, in bp.
Body weight (BW), daily food intake, wet tissue (visceral adipose tissue, VAT, and liver), and mass and peripheral levels of several biomarkers in control (C) and MSG rats.
| C | MSG | |
|---|---|---|
| Body weight (g) | 404.6 ± 9.1 | 349.3 ± 7.6 |
| Food intake (g/day) | 20.81 ± 1.95 | 15.61 ± 0.87 |
| VAT mass (g) | 4.47 ± 0.88 | 14.18 ± 1.77 |
| Liver weight (g/100 g BW) | 3.19 ± 0.07 | 2.93 ± 0.06 |
| Glycemia (g/L) | 1.06 ± 0.02 | 1.17 ± 0.03 |
| Insulin (ng/mL) | 0.81 ± 0.05 | 1.37 ± 0.19 |
| Leptin (ng/mL) | 1.39 ± 0.37 | 16.49 ± 2.38 |
| Triglycerides (g/L) | 1.06 ± 0.07 | 1.85 ± 0.18 |
| Uric acid (mg/dL) | 1.19 ± 0.09 | 1.82 ± 0.22 |
| Corticosterone ( | 6.19 ± 0.98 | 13.75 ± 1.12 |
| GOT (U/L) | 75.5 ± 3.2 | 96.9 ± 5.8 |
| GPT (U/L) | 9.51 ± 0.69 | 15.49 ± 1.19 |
Values are means ± SEM. P < 0.05 versus C values (n = 12 rats per group).
Peripheral and liver (n = 12 and 6 specimens per group, resp.) oxidative stress markers in control (C) and MSG rats.
| C | MSG | |
|---|---|---|
| Peripheral TBARS (pmol/mg of protein per mL of plasma) | 40.3 ± 3.6 | 85.1 ± 15.2 |
| Liver protein carbonyl groups (nmol/mg of tissue protein) | 4.43 ± 0.15 | 7.81 ± 1.32 |
| Liver GSH (nmol/g tissue) | 2.71 ± 0.03 | 2.05 ± 0.04 |
Values are means ± SEM. P < 0.05 versus C values.
Figure 1Liver mRNA levels of Il1b, Tnfa, and Pai-1 (panels (a), (b), and (c), resp.) in control (white bars) and MSG rats (black bars). Results are means ± SEM (n = 8 rats per group). P < 0.05 versus control values. Statistical analysis was performed by ANOVA, followed by Dunnett's test for multiple comparisons.
Figure 2Hepatic protein content and activity levels of GCK (panels (a) and (b), resp.), mRNA levels and protein content of PFK2 (panels (c) and (d), resp.), and mRNA levels and enzyme activity of G6Pase (panels (e) and (f), resp.) in control (white bars) and MSG-treated rats (black bars). Results are means ± SEM (n = 8 rats per group). P < 0.05 versus control values. Statistical analysis was performed by ANOVA, followed by Dunnett's test for multiple comparisons.
Figure 3Hepatic G6pdh (panel (a)), Chrebp (panel (b)), and Pepck (panel (c)) gene expression in control (white bars) and MSG-treated rats (black bars). Results are means ± SEM (n = 8 rats per group). P < 0.05 versus control values. Statistical analysis was performed by ANOVA, followed by Dunnett's test for multiple comparisons.
Figure 4Liver FK activity (panel (a)), mRNA levels of Srebp1c (panel (b)), Fas (panel (c)), and Gpat (panel (d)) in control (white bars) and MSG rats (black bars). Results are means ± SEM (n = 8 rats per group). P < 0.05 versus control values. Statistical analysis was performed by ANOVA, followed by Dunnett's test for multiple comparisons.