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. 2017 Mar;5(6):e13187.
doi: 10.14814/phy2.13187.

Effects of insulin and the glucagon-like peptide 1 receptor agonist liraglutide on the kidney proteome in db/db mice

Leena Liljedahl  1 , Jenny Norlin  2 , James N McGuire  2 , Peter James  3
Affiliations

Effects of insulin and the glucagon-like peptide 1 receptor agonist liraglutide on the kidney proteome in db/db mice

Leena Liljedahl et al. Physiol Rep. 2017 Mar.

Abstract

Diabetes mellitus (DM) is a worldwide disease that affects 9% of the adult world population and type 2 DM accounts for 90% of those. A common consequence of DM is kidney complications, which could lead to kidney failure VSports手机版. We studied the potential effects of treatment with insulin and the glucagon-like peptide 1 receptor (GLP-1R) agonist liraglutide on the diabetic kidney proteome through the use of the db/db mouse model system and mass spectrometry (MS). Multivariate analyses revealed distinct effects of insulin and liraglutide on the db/db kidney proteome, which was seen on the protein levels of, for example, pterin-4 α-carbinolamine dehydratase/dimerization cofactor of hepatocyte nuclear factor-1α (PCBD1), neural precursor cell expressed developmentally down-regulated-8 (NEDD8), transcription elongation factor-B polypeptide-1 (ELOC) and hepcidin (HEPC). Furthermore, the separation of the insulin, liraglutide and vehicle db/db mouse groups in multivariate analyses was not mainly related to the albumin excretion rate (AER) or the level of glycated hemoglobin A1c (HbA1c%) in the mice. In summary, we show that insulin and liraglutide give rise to separate protein profiles in the db/db mouse kidney. .

Keywords: GLP‐1R agonist liraglutide; OPLS‐DA; insulin; kidney proteome V体育安卓版. .

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Figure 1
Figure 1
Mouse parameters HbA1c(%) and albumin excretion rate (AER). (A) The level of HbA1c(%) was significantly higher in the three db/db groups than in the healthy control group at all time points. At the terminal time point there was no significant difference within the three groups of db/db mice. The significance level at 12.5 weeks is indicated with asterisks in Panel (A). (B) After 12 weeks of dosing there was significant difference in the AER between the healthy control and db/db vehicle group (P = 0.013) and the healthy control and db/db insulin group (P = 0.041), indicated by an asterisk in the figure. Total n = 20, n = 5 in each group. One‐way ANOVA with Tukey post hoc test was performed, P < 0.05 was considered significant. *P < 0.05, **P < 0.01, ***P < 0.001. Data are presented as mean ± SEM.
Figure 2
Figure 2
Multivariate data analyses of the shotgun data. The abundances of the 1390 proteins identified in the shotgun MS analysis were used as variables in the multivariate analyses. (A) Component 1 and 3 are shown in the PCA of the four mouse groups included in this study. The healthy control group was clearly separated from the three db/db mouse groups. Insulin and liraglutide had separate effects on the protein abundances in the db/db mouse model, although the three db/db mouse groups were not completely separated. Statistical parameters for the PCA were R2X(cum) = 0.615, Q2(cum) = 0.366 with three components (obtained from SIMCA). (B) Supervised OPLS analysis of the four mouse groups is shown where the db/db groups are separated from each other. Statistical parameters for the model are R2X(cum) = 0.794, R2Y(cum) = 0.957, Q2(cum) = 0.716 and 3+3+0 latent structures (obtained from SIMCA). (C) The level of HbA1c(%), BG, KW/BW and AER after 12 weeks of dosing were included, respectively, and together as Y‐variables in the OPLS analysis of the four mouse groups. In C HbA1c(%) is shown as an example of an included mouse parameter, illustrating that when including these y‐variables, the three db/db mouse groups were not well separated from each other. SIMCA statistical parameters for the model were R2X(cum) = 0.364, R2Y(cum) = 0.737 Q2(cum) = 0.639 and 1+1+0 latent structures.
Figure 3
Figure 3
Quantitative confirmation of shotgun data with SRM. Both graphs show meprin‐α subunit‐β (MEP1B). Panel (A) shows shotgun MS and panel (B) targeted SRM MS. One‐way ANOVA and Tukey post hoc test was applied, P < 0.05 was considered significant. Mean and 95% confidence intervals are indicated in the figure.
Figure 4
Figure 4
The effect of liraglutide or insulin on protein abundances. For the proteins illustrated in panel (A–D), it could be seen that insulin and liraglutide had both similar and opposite effects on the protein abundances. (A–D) show targeted SRM MS data with relative normalized abundances. One‐way ANOVA and Tukey post hoc test was applied to all groups and proteins, in graphs mean with 95% confidence interval are indicated. P < 0.05 was considered significant.
Figure 5
Figure 5
Shotgun data with insulin and/or liraglutide effects on protein abundances. Panel (A–F) show distinct effects of insulin and liraglutide on the protein abundance levels in the db/db mouse model. One‐way ANOVA and Tukey post hoc test was applied, P < 0.05 was considered significant. In graphs mean with 95% confidence interval are indicated. In PCBD1, NEDD8 and ELOC trends toward differential protein abundances (P < 0.1) are shown.
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