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. 2024 Feb 26;25(5):2702.
doi: 10.3390/ijms25052702.

Lipidomics Reveals Myocardial Lipid Composition in a Murine Model of Insulin Resistance Induced by a High-Fat Diet

Josefa Girona  1   2 , Oria Soler  1   2 , Sara Samino  2   3 , Alexandra Junza  2   3 , Neus Martínez-Micaelo  1   2 , María García-Altares  2   3 , Pere Ràfols  2   3 , Yaiza Esteban  1   2 , Oscar Yanes  2   3 , Xavier Correig  2   3 , Lluís Masana  1   2 , Ricardo Rodríguez-Calvo  1   2
Affiliations

Lipidomics Reveals Myocardial Lipid Composition in a Murine Model of Insulin Resistance Induced by a High-Fat Diet

Josefa Girona et al. Int J Mol Sci. .

Abstract

Ectopic fat accumulation in non-adipose tissues is closely related to diabetes-related myocardial dysfunction. Nevertheless, the complete picture of the lipid metabolites involved in the metabolic-related myocardial alterations is not fully characterized. The aim of this study was to characterize the specific lipid profile in hearts in an animal model of obesity/insulin resistance induced by a high-fat diet (HFD). The cardiac lipidome profiles were assessed via liquid chromatography-mass spectrometry (LC-MS)/MS-MS and laser desorption/ionization-mass spectrometry (LDI-MS) tissue imaging in hearts from C57BL/6J mice fed with an HFD or standard-diet (STD) for 12 weeks. Targeted lipidome analysis identified a total of 63 lipids (i.e., 48 triacylglycerols (TG), 5 diacylglycerols (DG), 1 sphingomyelin (SM), 3 phosphatidylcholines (PC), 1 DihydroPC, and 5 carnitines) modified in hearts from HFD-fed mice compared to animals fed with STD. Whereas most of the TG were up-regulated in hearts from animals fed with an HFD, most of the carnitines were down-regulated, thereby suggesting a reduction in the mitochondrial β-oxidation. Roughly 30% of the identified metabolites were oxidated, pointing to an increase in lipid peroxidation. Cardiac lipidome was associated with a specific biochemical profile and a specific liver TG pattern. Overall, our study reveals a specific cardiac lipid fingerprint associated with metabolic alterations induced by HFD.

Keywords: cardiac lipotoxicity; lipid peroxidation; myocardial steatosis.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Figure 1
Figure 1
HFD induced myocardial lipid accumulation in C57BL/6J mice. (A) Representative Oil Red O staining in hearts cross sections from mice fed with STD or HFD. Scale bar: 50 μm. (B) Volcano plot of all hits in hearts from STD- and HFD-fed animals. Colored points indicate metabolites that were significantly down- (red) or upregulated (green) in hearts from HFD-fed animals compared to hearts from animals fed with STD. (C) PCA score plots from hearts of STD- and HFD-fed animals.
Figure 2
Figure 2
Family lipid profile in hearts from HFD-fed mice. (A) Pie chart of the lipid class identified in hearts from HFD-mice. (B) Changes in total signal of the different lipid species in hearts from HFD-fed mice compared with mice fed with a STD. TG: triacylglycerols; DG: diacylglycerols; Cer: ceramides; Cer-P ceramide phosphate; GlcCer; glucoceramides; SM: sphingomyelins; PA: phosphatidic acid; PC: phosphatidylcholines; PG: phosphatidylglycerols; PI: phosphatidylinositols; PS: phosphatidylserines. Data are expressed as the mean ± SEM (* p < 0.05, ** p < 0.01, *** p < 0.001 vs. STD-fed mice).
Figure 3
Figure 3
LDI–MS tissue imaging visualization of the metabolite distributions in heart cross sections. A representative tissue image showing the abundance of 10 of the 63 metabolites identified via LC-MS is shown. Green color denotes a higher abundance of a particular metabolite, whereas blue denotes a lower abundance. Average spectra identifying the Mix TG (O-52:8): m/z 855.68, mass error Δ = −39 ppm; Mix TG (O-53:7): m/z 871.72, mass error Δ = 35 ppm; Mix TG (54:4): m/z 905.76, mass error Δ = 17 ppm; Mix TG (54:5): m/z 881.76, mass error Δ = 28 ppm; Mix TG (54:6): m/z 879.74, mass error Δ = 33 ppm; Mix TG (O-54:6):O: m/z 881.76, mass error Δ = 28 ppm; Mix TG (O-55:8): m/z 897.73, mass error Δ = 42 ppm; DG (36:3): m/z 641.51, mass error Δ = 24 ppm; DG (36:4): m/z 617.51, mass error Δ = 22 ppm; PC (40:5): m/z 820.62, mass error Δ = 25 ppm.
Figure 4
Figure 4
OPLS-DA score plots (A) and OPLS-DA-derived VIP values (B) performed with the identified metabolites in hearts from STD and HFD mice. The blue boxes denote lower abundance of a particular metabolite, whereas red boxes denote a higher abundance.
Figure 5
Figure 5
Heatmap showing Spearman’s correlation between the altered myocardial metabolites and the weight and biochemical variables related to glucose and fatty acid metabolism. The color intensity shows the degree of the association, with the positive correlations in green and the negative ones in red.
Figure 6
Figure 6
Heatmap showing Spearman’s correlation between the altered myocardial metabolites and liver TG. The color intensity shows the degree of the association, with the positive correlations in green and the negative ones in red.
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