Evidence that tirzepatide protects against diabetes-related cardiac damages

Abstract

Background: Glucagon-like peptide-1 receptor agonists (GLP-1RAs) are effective antidiabetic drugs with potential cardiovascular benefits. Despite their well-established role in reducing the risk of major adverse cardiovascular events (MACE), their impact on heart failure (HF) remains unclear. Therefore, our study examined the cardioprotective effects of tirzepatide (TZT), a novel glucose-dependent insulinotropic polypeptide (GIP) and glucagon-like peptide 1 (GLP-1) receptor agonist.

Methods: A three-steps approach was designed: (i) Meta-analysis investigation with the primary objective of assessing major adverse cardiovascular events (MACE) occurrence from major randomized clinical trials.; (ii) TZT effects on a human cardiac AC16 cell line exposed to normal (5 mM) and high (33 mM) glucose concentrations for 7 days. The gene expression and protein levels of primary markers related to cardiac fibrosis, hypertrophy, and calcium modulation were evaluated. (iii) In silico data from bioinformatic analyses for generating an interaction map that delineates the potential mechanism of action of TZT.

Results: Meta-analysis showed a reduced risk for MACE events by TZT therapy (HR was 0.59 (95% CI 0.40-0.79, Heterogeneity: r² = 0.01, I² = 23.45%, H² = 1.31). In the human AC16 cardiac cell line treatment with 100 nM TZT contrasted high glucose (HG) levels increase in the expression of markers associated with fibrosis, hypertrophy, and cell death (p < 0.05 for all investigated markers). Bioinformatics analysis confirmed the interaction between the analyzed markers and the associated pathways found in AC16 cells by which TZT affects apoptosis, fibrosis, and contractility, thus reducing the risk of heart failure.

Conclusion: Our findings indicate that TZT has beneficial effects on cardiac cells by positively modulating cardiomyocyte death, fibrosis, and hypertrophy in the presence of high glucose concentrations. This suggests that TZT may reduce the risk of diabetes-related cardiac damage, highlighting its potential as a therapeutic option for heart failure management clinical trials. Our study strongly supports the rationale behind the clinical trials currently underway, the results of which will be further investigated to gain insights into the cardiovascular safety and efficacy of TZT.

Keywords: AC16 cell line; GIP receptor; GLP-1 receptor.; Heart failure; High glucose; Tirzepatide.

Fig. 1

Meta-analysis of Cardiovascular Safety of Tirzepatide in Randomized Clinical Trials (2020–2023) The forest plot of the meta-analysis was created using Stata software (version 16.0, Stata Corp., College Station, TX)

Fig. 2

Gene expression of GIPR and GLP1R in AC16 cell line. Gene expression analysis showed a disparity in expression levels between GIPR and GLP1R. Gene expression was normalized to the housekeeping gene GAPDH. Data are presented as mean ± SEM of three independent experiments. p < 0.01

Fig. 3

TZT Effects on fibrosis, hypertrophy, and Akt signaling markers mRNA expression and protein levels of A TGF-β, B MMP9, C Collagen, D FBXO32, and E MURF1 exposure to normal glucose (NG), high glucose (HG), or HG with 100 nM TZT after 7 days. Also, F Akt and p-Akt protein levels were shown. β-Actin was used as an internal control in gene expression. The fold increase of mRNA expression compared with NG was calculated using the 2^−ΔΔCt method. Protein expression densitometry analysis was performed using Image J 1.52n software. Data are mean ± SEM of three independent experiments. *p < vs NG; ** p < vs HG

Fig. 4

Effects of TZT on calcium homeostasis markers A SERCA2 mRNA expression, total protein and phospho-T484 protein levels B PLN mRNA expression, total protein and phospho-S16 and -T17 of PLN. C CAMKII mRNA expression, total form of CAMKII and phospho-T287 D mRNA expression and protein levels of PKA exposure to NG, HG, or HG with 100 nM TZT after 7 days. β-Actin was used as internal control for gene expression. The fold increase of mRNA expression compared with NG was calculated using the 2^−ΔΔCt method. Protein expression densitometry analysis was performed using Image J 1.52n software. Data are mean ± SEM of three independent experiments. *p < vs NG; ** p < vs HG

Fig. 5

Protective Effects of TZT on cell proliferation, viability, and toxicity A AC16 cell proliferation analysis performed after cell staining with Ki-67 marker and the histogram represents median of fluorescence (FITC). B Cell viability was assessed using a CCK-8 assay after 7 days of exposure to normal glucose (NG), high glucose (HG), or HG with 100 nM TZT. (C) Cell toxicity assay performed with Lactate dehydrogenase (LDH) activity assay. Data are presented as mean ± SEM of three independent experiments. *p < vs NG; ** p < vs HG

Fig. 6

TZT Effects on apoptosis in AC16 cells exposed to high glucose A Apoptosis was measured using Annexin V-FITC staining followed by a flow cytometer. The histogram represents the median of fluorescence (FITC). mRNA expression and protein levels of pro-apoptotic B BAX, anti-apoptotic C Bcl2 and analysis of D BAX/Bcl2 ratio at the protein level. Also, mRNA expression and protein levels of E Total and cleaved form of caspase-3 exposure to normal glucose (NG), high glucose (HG), or HG with 100 nM TZT were shown. The fold increase of mRNA expression compared with NG was calculated using the 2^−ΔΔCt method. Protein expression densitometry analysis was performed using Image J 1.52n software. Data are mean ± SEM of three independent experiments. *p < vs NG; ** p < vs HG

Fig. 7

Effects of TZT on autophagy markers A Cell autophagy analysis was performed by flow cytometer. The histogram represents median of fluorescence (FITC). mRNA expression and protein levels of the autophagy marker B p62 and C Beclin1 exposure to normal glucose (NG), high glucose (HG), or HG with 100 nM TZT after 7 days. β-Actin was used as internal control for gene expression. The fold increase of mRNA expression compared with NG was calculated using the 2^−ΔΔCt method. Protein expression densitometry analysis was performed using Image J 1.52n software. Data are mean ± SEM of three independent experiments. *p < vs NG; ** p < vs HG

Fig. 8

Building interactive models of experimental systems The key entries genes of this work are labeled in larger bold font with red fill. Direct connections between/among genes are shown in solid lines; indirect interactions are shown as dashed lines (also called “edges”). Connections between genes objective of this work are shown in dark blue; interactions between highlighted genes and not directly mapped in this work are shown in turquoise. Target shapes are indicative of function, and the complete legend has been reported in right part of figure