Abstract Background Diabetic cardiomyopathy (DCM) is a complex condition linked to diabetes, characterized by cardiac and vascular dysfunction, frequently concomitant with heart failure with preserved ejection fraction. The extracellular matrix glycoprotein Tenascin-C (TNC) has been found to be upregulated under diabetic conditions. However, the potential contributory role of TNC in the progression of DCM remains largely unclear. This study was designed to elucidate the role of TNC in the pathogenesis of DCM. Methods Diabetes was induced in adult male wild-type (WT) and TNC knockout (TNC-KO) mice, through the administration of streptozotocin (50 mg/kg) for five consecutive days. At 18 weeks cardiac and aortic vascular function was evaluated using echocardiography and wire myography. Myocardium and plasma samples were collected for biochemical, histological, and molecular analyses. Cardiomyocytes and cardiac fibroblasts were used to investigate the impact of diabetes on TNC expression, inflammation, myocardial stiffness and function. Additionally, transcriptomic analysis of cardiac tissue by RNA-sequencing was conducted. Plasma TNC levels were assessed by enzyme-linked immunosorbent assay in cohorts of heart failure patients and type 2 diabetes mellitus. Results TNC-KO diabetic mice showed preserved left ventricular systolic and diastolic function, significantly reduced cardiac fibrosis and mitigated endothelial dysfunction compared to WT diabetic animals. Compared with cardiomyocytes of diabetic WT animals, cardiomyocytes of TNC-KO mice developed less stiffness (Fpassive). Additionally, exposing mouse cardiomyocytes and human cardiac fibroblasts to high glucose stress (30 mM) led to a significant increase in TNC expression. Conversely, recombinant human TNC promoted pro-inflammatory and oxidative stress markers in cardiomyocytes. The role of TNC in fibrosis and DCM was found to involve pathways related to p53 signaling and Serpin1k, Ccn1, Cpt1a, and Slc27a1, as identified by RNA sequencing analysis. Additionally, plasma TNC levels were significantly elevated in patients with heart failure, irrespective of diabetes status, compared to healthy individuals. Conclusions Our findings indicate that in diabetes, TNC contributes to cardiac contractile dysfunction, myocardial fibrosis, oxidative stress, inflammation, and metabolic disturbances in diabetic mouse heart. These results implicate the potential of TNC inhibition as a novel therapeutic approach for treating DCM. Graphical abstract [70]graphic file with name 12933_2025_2780_Figa_HTML.jpg Supplementary Information The online version contains supplementary material available at 10.1186/s12933-025-02780-y. Keywords: Tenascin-C, Diabetic cardiomyopathy, Heart failure pathophysiology, Fibrosis, Inflammation Background Over the past two decades, diabetes has become one of the top ten leading causes of death, with a 70% increase in mortality rates, counting for over six million deaths globally each year [[71]1, [72]2]. The risk of cardiovascular complications is a major concern in diabetes, contributing substantially to both mortality and morbidity among diabetic individuals [[73]3, [74]4]. Diabetic cardiomyopathy (DCM), a form of heart failure (HF), is marked by the progression of left ventricular (LV) systolic and diastolic dysfunction and myocardial fibrosis [[75]5, [76]6]. Clinical trials have indicated that the prevalence of HF among diabetic patients is approximately 22%, with an increasing prevalence over the course of the disease [[77]7, [78]8]. Despite advancements in diabetes treatment, which are beneficial as treatment for HF, such as the use of glucagon-like peptide 1 (GLP-1) receptor agonists and sodium-glucose cotransporter-2 (SGLT2) inhibitors, there remain limited targeted therapeutic options specifically addressing DCM [[79]9, [80]10]. Morphological and structural cardiac remodeling, diastolic dysfunction with reduced cardiac compliance, progressive systolic dysfunction and enlarged LV chamber have been identified in DCM [[81]11–[82]13]. In addition, alteration and accumulation of extracellular matrix (ECM) proteins in the myocardium play a major pathophysiological role in the progression of HF in diabetes [[83]14]. Accordingly, increasing evidence underscore the pathological role of fibrosis in DCM [[84]15, [85]16]. Changes of ECM protein levels, e.g.: Tenascin-C (TNC), have also been linked to poorer prognosis in diabetic patients without HF [[86]17]. Moreover, Gellen et al. demonstrated for the first time that increased serum levels of TNC, an ECM glycoprotein, were independently associated with death and major adverse cardiovascular events among patients with type 2 diabetes mellitus (T2DM) [[87]18]. An increased myocardial TNC expression has been linked to adverse LV remodeling [[88]19, [89]20] and poorer long-term outcomes in dilated cardiomyopathy [[90]21]. TNC is generally expressed during embryonic development, but its expression is largely restricted in healthy adult cardiac tissues [[91]22–[92]24]. However, TNC expression is related to several pathological conditions, such as cancer, chronic inflammation and adverse remodeling processes [[93]25–[94]27]. TNC expression has been associated with fibroblast to myofibroblast transition, cardiac fibrosis and inflammation following myocardial infarction [[95]28, [96]29]. Furthermore, we have demonstrated that TNC knockout (TNC-KO) mice showed a significantly preserved cardiac function and less fibrosis after various models of cardiac pathologies, e.g. myocardial infarction or pressure overload [[97]19, [98]20, [99]30]. More importantly, our recent study provides insight into the diabetic microvascular damage of coronary arterioles and the role of TNC in diabetes [[100]31]. Therefore, this study aimed to investigate the implications of TNC in adverse LV remodeling, fibrosis and cardiomyocyte dysfunction in diabetes. In addition, we performed cardiac RNA-sequencing analysis to identify novel signaling pathways involving TNC in the development of DCM in mice. Methods Animals Adult (8–10 weeks old) male TNC-KO (KO, RBRC00007 A, Experimental Animal Division, Tsukuba, Japan; n = 114) and wild-type mice (WT, A/J, #000646, The Jackson Laboratory, Sacramento, CA, USA; n = 162) were used [[101]21, [102]32–[103]35]. All animals received standard laboratory care and were housed in air-conditioned rooms at 22 °C with a 12/12 h day/night cycle, including free access to water and standard mouse chow. The experimental protocol was approved by the regional Ethics Committee for Laboratory Animal Experiments at the Medical University of Vienna and the Austrian Ministry of Science Research and Economy (BMWFW- 66.009/0014-V/3b/2018). All procedures conform to the guidelines from ARRIVE and Directive 2010/63/EU of the European Parliament on the protection of animals used for scientific purposes. Diabetes mellitus model In both TNC-KO and WT mice, intraperitoneal injections of streptozotocin (STZ, 50 mg/kg) on five consecutive days were administered to induce diabetes as previously described [[104]31]. Blood glucose samples were obtained by tail venopuncture at baseline, weekly until 6 weeks, as well as 8–9, 11–14, and 16–19 weeks after induction with STZ (commercially available whole-blood glucose monitor AccuCheck). Animals exceeding 300 mg/dl blood glucose level were considered hyperglycemic and diabetic [[105]36]. Transthoracic echocardiography Transthoracic echocardiography was conducted using a Vevo 2100 and 3100 Imaging system (FUJIFILM Visualsonics) equipped with a 55‐MHz transducer, following previously established protocols at baseline and 18 weeks after diabetes induction. Mice with diabetes and control non-diabetic animals were anesthetized with 1–1.5% isoflurane inhalation during the echocardiography assessment. Continuous monitoring of ECG and body temperature were ensured via limb electrodes and a rectal probe, respectively. Parasternal long‐axis and short-axis views were acquired for assessment of LV dimension and function as described previously [[106]37]. Ultrasound images were analyzed using Vevo LAB software, with an average of three cardiac cycles per view utilized for each parameter analysis. Assessment of left ventricular hemodynamic function in vivo A group of mice was used to assess invasive LV hemodynamic function in vivo as described previously [[107]37]. Briefly, mice were anesthetized with a mixture of ketamine-xylazine. Upon opening the chest, a microtip pressure catheter (SPR-1000, Millar Instruments, Houston, USA) was inserted trans apical in the LV. Cardiac systolic and end-diastolic pressure (LVSP, LVEDP), heart rate (HR) as well as LV contractility performance (derivative of pressure over time dP/dt) were assessed with Powerlab 8/30 LabChart (v7.3.2; ADInstruments, Dunedin, New Zealand). Isolated cardiomyocyte force measurements Force measurements were performed on single de-membranated cardiomyocytes as previously described [[108]38, [109]39]. Briefly, LV samples were thawed in a relaxing solution (containing in mM: 1.0 free Mg^2+; 100 KCl; 2.0 EGTA; 4.0 Mg-ATP; 10 imidazole; pH 7.0), mechanically disrupted, and incubated for 5 min in relaxing solution supplemented with 0.5% Triton X-100 (all from Sigma-Aldrich). The cell suspension was washed six times in a relaxing solution to remove Triton. Single cardiomyocytes were selected under an inverted microscope and attached with shellac dissolved in ethanol between a force transducer and a high-speed length controller (piezoelectric motor). Sarcomere length (SL) was monitored using a video camera and analysis software provided by the manufacturer. Cardiomyocyte Ca^2+-independent passive force (Fpassive) was measured in relaxing buffer at room temperature within a sarcomere length (SL) range of 1.8–2.4 μm. Force values were normalized to myocyte cross-sectional area calculated from the diameter of the cells, assuming a circular shape. Cardiomyocyte Fpassive was then measured within a SL range of 1.8–2.4 μm as described above. Next, the myocyte was adjusted to a SL of 2.2 μm and exposed to 4.5 (maximal activation). Force values were either related to maximum force at pCa 4.5 or normalized to myocyte cross-sectional area calculated from the diameter of the cells, assuming a circular shape. Histologic and immunohistochemical analyses Picro Sirius staining was applied to 4% formalin-fixed paraffin-embedded horizontal 5 µm thick myocardium sections to evaluate the extent of cardiac fibrosis. The microscope images (Olympus VS120, Tokyo, Japan) were captured by digital camera (AVT PIKE F-505C VC 50, Allied Vision Technologies, Stadtroda, Germany). The fibrotic area was estimated on a mid-papillary myocardium slice. Three areas of the left ventricular cross sections, 500 × 500 µm (containing each 640,000 pixels) have been selected and histograms for the green level of the RGB (0–255) values measured using the Image J program. Preliminary evaluation has shown that red colored collagen pixels had green values below 220 green values, while yellow muscle areas were always above that value. The number of pixels were expressed as thousands of ventricular cross section area and pixel frequency plots were constructed for the 165–225 green value ranges. Immunohistochemistry Streptavidin–biotin immunostaining for CD68 of paraffin-embedded tissue sections was performed with antibodies against CD68 (1:100; ED1, ab31630, Abcam, Cambridge, MA, USA) to assess tissue macrophage density as described previously [[110]40]. Primary antibodies were detected with biotinylated secondary antibodies (Vector Laboratories, Burlingame, CA) and peroxidase-conjugated streptavidin (Dako, Glostrup, Denmark), developed with 3,3′-diaminobenzidine (Vector Laboratories), counterstained with hematoxylin, dehydrated and mounted in DPX (Merck, Darmstadt, Germany). Digitized images were generated with a slide scanner (Olympus VS120, Hamburg, Germany) using OLYMPUS-OlyVIA software. CD68+ macrophages were counted, and results were expressed as cells per section. TUNEL staining in heart tissue section Terminal deoxynucleotidyl transferase-mediated dUTP nick end labeling (TUNEL) assay (In situ cell death detection kit, Fluorescein—Roche, Mannheim, Germany) was used to detect the level of apoptosis in heart tissue according to the manufacturer's instructions. Apoptotic nuclei in paraffin-embedded heart tissue sections were labeled with green fluorescein staining, while nuclei in heart tissue were labeled with DAPI. Heart tissue images were viewed by fluorescence microscopy (Slidescanner Olympus VS120, Hamburg, Germany) using OLYMPUS-OlyVIA software. Wire myograph assessment of vascular reactivity Abdominal aortic segments were isolated and subjected to myography as described previously [[111]41, [112]42]. Segments were placed into cold Krebs-buffer (119 mM NaCl, 4.7 mM KCl, 2.5 mM CaCl[2] × 2H[2]O, 1.17 mM MgSO[4] × 7H[2]O, 20 mM NaHCO[3], 1.18 mM KH[2]PO[4], 0.027 mM EDTA, 10.5 mM glucose) and aerated with a mixture of 95% O2 and 5% CO[2], resulting in pH 7.4. Two-millimeter-long aortic rings were mounted onto a multichamber isometric myograph system (Model 620 M, Danish Myo Technology, Aarhus, Denmark), equilibrated at 37 °C and normalized using the ADInstuments Normalization module. Segments were recorded on 8 channels simultaneously by Powerlab data acquisition system, which was evaluated with the LabChart Version 8 evaluation software (ADInstruments, Oxford, UK-Ballagi LTD, Budapest, Hungary). Abdominal aortic segments were stretched gradually to 10 mN tension and allowed to equilibrate for 30 min. Following viability assessment with 124 mM KCl solution, cumulatively increasing concentrations of vasoconstrictor phenylephrine (Phe, 1 nM to 10 µM, Merck KGaA., Darmstadt, Germany) and of endothelium-dependent vasodilator acetylcholine (1 nM-1 µM, with Phe-induced precontraction, Merck KGaA., Darmstadt, Germany) were administered. Contraction responses were normalized to KCl-induced contraction and relaxation responses were calculated as percent changes from Phe-induced precontraction. Human ventricular cardiac fibroblast experiments and western immunoblotting Human ventricular cardiac fibroblasts (NHCF-V, Lonza Bioscience) passage 6 were seeded and expanded in a T75 cm^2 flask in Cardiac Fibroblast Growth Medium-3 (FGM 3) (Gilco, 197,232), supplemented with 10% fetal bovine serum (FBS), insulin, human Fibroblast Growth Factor-basic (hFGF-B), Gentamicin and Amphotericin B (GA-1000), and 1% penicillin/streptomycin (Gibco, 15,140,122, 10,000 U/mL) as described previously [[113]43]. The cells were cultured at 37 °C under 5% CO[2] and a 95% air-humidified atmosphere until they reached 80% confluency. Subsequently, cells were harvested using Trypsin–EDTA 0.25% (Gilco, 25,200,056), and the cell concentration was assessed using trypan blue staining and a hemocytometer. Afterwards, cells were seeded into a 6-well plate at a density of 1 × 10^5 cells/mL. Cultures were washed with 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid (HEPES) buffered saline (Lonza, Basel, Switzerland) when indicated, and split at a confluency level of 70%. Cells were serum starved for 24 h, with subsequent treatment with one of the following:1) Control– treatment with standard cell culture medium or 2) supplement with 30 mM D-(+)-Glucose (G8769, Sigma). The total protein was extracted using Radioimmunoprecipitation Assay (RIPA) buffer (50 mM Tris, pH 8; 150 mM NaCl; 1% NP40; 0.1% SDS; 0.5% sodium deoxycholate; 1% Protease and phosphatase inhibitor) and quantified using the Pierce BCA Protein Assay Kit (23,225, Thermo Scientific). For all the samples, 30 ug of the protein extracts were loaded into 10% sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) gels and transferred to polyvinylidene difluoride (PVDF) membranes. The membranes were analysed using the following primary antibodies: Tenascin C (rabbit, AB19011, MERK, 1:1000) and vinculin clone hVin-1 (mouse, V9131, Sigma, 1:2000). The secondary antibody was Peroxidase-conjugated AffiniPure Goat Anti-Mouse IgG + IgM (H + L) (Jackson Immuno Research, 115–035-044, 1:10,000) and Peroxidase-conjugated AffiniPure Goat Anti-Rabbit IgG (H + L) (Jackson Immuno Research, 111-035-003, 1:10,000). Detection was performed using a ChemiDoc XRS + instrument (BioRad) (chemiluminescence detection), and image quantification was conducted using ImageJ. In addition, NHCF-V cells were cultivated identically as described above. Cells (approximately 40.000) were seeded onto a 24-well plate in 22 mm diameter glass coverslips under sterile conditions. The cells were kept in an incubator (HeraCell 150i) with 37 °C and 5% CO2. 24 h after seeding, three replicates were treated with 30 mM/mL High-Glucose (D-(+)-Glucose solution, Sigma) for 48 h and three replicates were used as control group. After that, we performed the immunocytochemistry for TNC, therefore cells were washed with 1 × Phosphate Buffered Saline (PBS), fixed in 4% paraformaldehyde in PBS (PFA) for 20 min at room temperature (RT), and again washed with PBS. Coverslips were incubated with 100 mM glycine in PBS for 15 min, washed 3 × with PBS for 5 min, and cells were permeabilized in PBS containing 0.1% Triton X-100 for 5 min. For blocking unspecific binding sites, the coverslips were incubated with 4% bovine serum albumin (BSA) in PBS for 1 h at RT. Primary antibody dilutions were prepared in PBS (TNC, 1:100, AB 19011, Merck), and the coverslips were incubated with antibody solution for 1 h at RT. Afterwards, the coverslips were washed 3 × with PBS for 5 min. Fluorescence labelled secondary antibody (Texas Red TI-1000, Vector, 1:200), diluted in PBS, was added and incubated for 1 h at RT under light protection, in the dark. Coverslips were washed 3 × with PBS for 5 min and mounted by placing them onto a small drop of Mowiol with 4′,6-diamidino-2-phenylindole (DAPI) on a glass slide. Samples were dried overnight at RT in the dark and afterwards pictures were captured with Leica Microscope (LSM700). Expression of TNC in diabetic mouse heart In addition, diabetic and non-diabetic mouse hearts (A/J) were collected and TNC expression was assessed by Western immunoblots. Briefly, cell lysates were prepared with Pierce™ RIPA buffer (89,901, Thermo Fisher Scientific, Waltham, CA) according to the manufacturer's protocol and 20 μg/lane were separated by 10% SDS-PAGE prior to electrophoretic transfer to Amersham™ Protan™ Supported 0.2 μm nitrocellulose membrane (GE Healthcare, Buckinghamshire, UK). Blots were probed with antibody to TNC (1:2000, ab108930, Abcam, Cambridge, UK) before incubation with anti-rabbit horseradish peroxidase-conjugated secondary antibody (1:10,000, NA934, GE Healthcare). Alpha-tubulin staining (1:4000, T5168, Sigma-Aldrich, St. Louis, MO) with anti-mouse horseradish peroxidase-conjugated secondary antibody (1:10,000, AP181P, Sigma-Aldrich) was used as a loading control. Proteins were immunodetected by chemiluminescence (ECL™ start Western blotting detection reagent, RPN3245, GE Healthcare), scanned using FUSION-FX7 (Vilber Lourmat, Marne-la-Vallée, France) and quantified using Fusion-CAPT software 16.07 (Vilber Lourmat). Adult mouse cardiomyocyte isolation and cultivation Adult male A/J mice were injected with the mixture of ketamine and xylazine, the chest was quickly opened, the hearts were excised, and cardiomyocytes were isolated as described previously [[114]44]. The heart was transferred to a new dish prefilled with perfusion buffer and injected with 5 ml perfusion buffer through the LV. Then, 20 ml collagenase was injected into the LV, and the LV was dissected with tweezers until only the smallest possible tissue pieces remained. The suspension was transferred to a 50 ml Falcon tube, along with a 5 ml stop buffer. The suspension was transferred to a new 50 ml tube through a 100 µm strainer to remove undigested tissue debris. The filter was washed with a 5 ml stop buffer. The suspension was equally divided between two 15 ml Falcon tubes, and the cells were allowed to settle and form a pellet for 20 min by gravity. This allows most myocytes to settle, while other cells and debris remain in the suspension. The supernatant was removed, and the pellet was resuspended in a 4 ml perfusion buffer. The cells were let to settle by gravity for 10 min, and the supernatant was removed again. This was repeated three times with increasing concentrations of culture medium to gradually re-introduce calcium to the cells. The calcium concentrations were 0.34, 0.68 and 1.02 mmol/l. The final myocyte pellet was resuspended in 2 ml RT medium and analyzed with a hemocytometer. The cells were plated in a 24-well plate with 1 ml medium and 50 000 cells per well. The plate was placed in the incubator, and cells were treated in one of following conditions; 1) M199 culture medium with normal or high glucose (30 mM) supplement for 24 h. The cells were used to isolate total RNA and then perform RT-qPCR. Cardiomyoblast culture and analysis of DNA methylation by methylation-specific PCR H9c2 cardiomyoblasts (ATCC ® CRL-1446™, Virginia, USA) were cultured using M199 complete media (M199 media supplemented with 10% fetal bovine serum, 1% Penicillin and Streptomycin, and 1% L-glutamine (Thermo Fisher Scientific, Massachusetts, USA)) as previously described [[115]19]. Cells were incubated with (1) Control M199 media or (2) M199 with the supplementation of 30 mM glucose for 24 h. Genomic DNA (gDNA) from H9c2 cells was obtained using the DNeasy® Blood and Tissue Kit according to the manufacturer’s instructions (Qiagen, Hilden, Germany). 1 µg of gDNA was denaturated and unmethylated cytosines converted to uracil in the denatured samples (Cells-to-CpG™ Bisulfite Conversion Kit, Thermofisher Scientific). CpG methylation was quantified by methylation-specific real-time PCR using 100 ng of bisulfite-converted genomic DNA as the template and methylation-specific primers for CpG in the human TNC promoter. The methylation level of TNC promoter was calculated by using the methylation index, as previously reported [[116]45]. Cellular apoptotic assay H9c2 cells at passage 9–12 were maintained in DMEM medium (Gibco, 11,995,065) supplemented with 4,5 g/L D-Glucose, L-Glutamine, Pyruvate, 10% FBS (Gibco, A5256701), and 1% penicillin/streptomycin (Gibco, 15,140,122, 10,000 U/mL) at 37 °C under 5% CO2 and a 95% air-humidified atmosphere. At confluency, the cells were seeded into a 24-well plate at a density of 50 × 103 cells/mL. Twenty four hours following the seeding, the cells were exposed to human Tenascin-C purified protein (MERK, CC065, 5 µg/mL) or D-(+)-Glucose (Sigma, [117]G87769, 30 mM). In the control condition, the cells were kept in standard cell culture medium. Twenty-four hours after the beginning of the treatment, the apoptosis was detected and quantified using the In situ Cell Death Detection kit (Roche, 11,684,795,910) following the manufacture instructions. For imaging was used the confocal microscopy Zeiss LSM 700. Reverse transcription and quantitative polymerase chain reaction (PCR) Total RNA was extracted from CFB and isolated mouse cardiomyocytes using the RNeasy Mini Kit (Qiagen, Hilden, Germany) and quantified by nanodrop spectrophotometer as described previously [[118]43]. cDNA was prepared using QuantiTect re-verse transcription kit (Qiagen, Hilden, Germany). Samples were analyzed in duplicate in a volume of 20 μL per well. The initial denaturation step of 15 min at 95 °C was followed by 45 cycles of 15 s 95 °C, 30 s 50 °C, and 30 s 72 °C, using Rotor-Gene Q (Qi-agen, Hilden, Germany) and Rotor-Gene Q series software for Ct value analysis. Relative gene expression was calculated by the 2 − ΔΔCt method. The list of primers is depicted in Supplemental Table 1. RNA sequencing and data analysis Sequencing library preparation Total RNA was extracted from LV tissue samples using a standard protocol. Sequencing libraries were prepared at the Core Facility Genomics, Medical University of Vienna, utilizing the QuantSeq 3' mRNA-Seq Library Prep Kit FWD for Illumina (Lexogen, Vienna, Austria) according to the manufacturer's instructions. The number of PCR amplification cycles was determined by quantitative PCR (qPCR) optimization, resulting in 16 cycles to ensure optimal library complexity. Library quality was assessed using the Bioanalyzer 2100 system (Agilent Technologies, Santa Clara, CA, USA) with the High Sensitivity DNA Kit to verify insert size distribution. Quantification of libraries was performed using the Qubit dsDNA HS Assay Kit (Invitrogen, Carlsbad, CA, USA). Libraries were pooled equimolarly and sequenced on an Illumina NextSeq 500 platform in single-end 75 bp mode, generating an average of 5.3 million reads per sample. Raw sequencing data were processed using the Illumina bcl2fastq Conversion Software (v2.19.1.403) to generate FASTQ files. RNA sequencing data analysis This is detailed in the Supplemental Methods. Patient population and assessment of TNC in human subjects Plasma levels of TNC in patients with HF with or without diabetes were compared to healthy control subjects in the MetAnEnd study [[119]46]. We included adult patients (aged 19–82 years) with reduced LV ejection fraction (LVEF 10–40%) for the heart failure with reduced ejection fraction (HFrEF) group. The levels of TNC were measured using human TNC Enzyme-Linked Immunosorbent Assay (ELISA) kit (Abcam, ab213831) according to the manufacturer’s instructions. Human ethics The MetAnEnd study was conducted according to the International Conference on Harmonization and Good Clinical Practice guidelines and the Declaration of Helsinki. It was approved by the ethical review board at Karolinksa Institutet (Stockholm, Sweden). Written informed consent was obtained from all participants prior to study participation. Statistical analysis Statistical analyses were performed using R (v4.1.0), Python (v3.8), IBM SPSS Statistics for Windows (v27.0; IBM Corp., Armonk, NY, USA), and GraphPad Prism (v10.2.0). Categorical variables were reported as frequency (percentage), and continuous variables were expressed as mean ± standard deviation (SD). For comparisons of echocardiographic data and other continuous variables, paired Student's t-test or Wilcoxon matched-pairs signed rank test was used, depending on data distribution. One-way ANOVA followed by the Bonferroni post-hoc test or General Linear Model was used when comparing diabetic and non-diabetic animals in WT and TNC-KO groups. The Šídák's multiple comparisons test was applied to adjust p-values for multiple comparisons. For gene expression analyses, one-way ANOVA followed by Tukey's post-hoc test was used where appropriate. A p-value less than 0.05 was considered statistically significant, and all analyses were computed two-tailed. Results TNC deficiency does not affect blood glucose levels Mice developed diabetes mellitus upon treatment with STZ as indicated by a blood glucose level of ≥ 300 mg/dl compared to non-treated controls. Blood glucose levels showed no difference between the diabetic groups (Supplemental Fig. 1). Notably, the body weight was smaller in the TNC-KO diabetic group in comparison to WT diabetic animals (Supplemental Fig. 2), similar to our previous work on this diabetic model [[120]31]. Cardiac expression of TNC was elevated in diabetic mice in comparison to the non-diabetic groups (Supplemental Fig. 3). Cardiovascular function and morphology in TNC deficiency Preserved left ventricular systolic and diastolic function in TNC deficiency Cardiac 2D echocardiography analysis at baseline (prior to STZ injections) showed no differences between the groups (Supplemental Table 2). Cardiac systolic and diastolic function were impaired in WT diabetic mice in comparison to the non-diabetic WT group, confirming that STZ-induced diabetes leads to DCM (Fig. [121]1B-C); (mean LVEF 62.2 ± 6.8% in the non-diabetic vs. 47.3 ± 7.5% in the diabetic group; p = 0.0009). As shown in Fig. [122]1B, TNC deficiency was accompanied by preserved LV function in diabetic animals 18 weeks after induction with STZ (mean LVEF 58.9 ± 5.9% in the non-diabetic vs. 59.6 ± 10.5% in the diabetic group; Fig. [123]1B). In addition, the diastolic dysfunction (Fig. [124]1C), characterized by marked increases in E/A ratio was also significantly alleviated in the TNC-KO diabetic group in comparison to WT diabetic mice (mean E/A ratio 2.5 ± 1.0 in diabetic WT group vs. 1.5 ± 0.6 in diabetic TNC-KO animals; p = 0.0040; Fig. [125]1C). Fig. 1. [126]Fig. 1 [127]Fig. 1 [128]Open in a new tab Echocardiographic parameters 18 weeks after diabetes induction. A Representative images of transthoracic echocardiography with LVEF measurement in the longitudinal axis. B and C Preserved systolic and diastolic function in TNC-KO diabetic animals compared to wild-type mice with diabetes (LVEF and E/A ratio; mean ± SD, n = 8–17/group). D and E Left ventricular diameters: LVEDD and LVESD; mean ± SD, n = 8–17/group. F and G Invasive hemodynamic measurements. LVSP and LVEDP changes (mean ± SD, n = 5–7/group). H and I Contractility in TNC deficient diabetic mice compared to WT animals as illustrated by LVSP, dP/d[tmax] and dP/dt[min] (F, H, I; mean ± SD, n = 5–7/group). DM, diabetes mellitus; dP/dt, derivative of pressure over time; LV, left ventricle; LVEDD, left ventricular end-diastolic diameter; LVEDP, left ventricular enddiastolic pressure; LVEF, left ventricular ejection fraction; LVESD, left ventricular endsystolic diameter; LVSP, left ventricular systolic pressure; STZ, streptozotocin; TNC-KO, Tenascin-C knock-out; WT, wild-type; ****p < 0.0001; ***p < 0.001; **p < 0.01; *p < 0.05; ns not significant Significant enlargement of LV diameter was observed in both diabetic groups, as indicated by increased LVEDD (mean LVEDD 1.175 ± 0.175 mm in WT non-diabetic vs. 1.738 ± 0.318 mm in WT diabetic group; p = 0.0001 and 1.26 ± 0.189 mm in TNC-KO non-diabetic vs. 1.653 ± 0.3 mm in TNC-KO diabetic group; p = 0.0028) and LVESD (mean LVESD 0.8 ± 0.169 mm in WT non-diabetic vs. 1.314 ± 0.241 mm in WT diabetic animals; p < 0.0001 and 0.88 ± 0.14 in TNC-KO non-diabetic vs. 1.141 ± 0.224 mm in TNC-KO diabetic group; p = 0.0112) (Fig. [129]1D-E). While LVESD showed a trend toward reduction in TNC-KO diabetic mice compared to WT diabetic mice (p = 0.0975), LVEDD remained unchanged between these groups. Given that LVEDD is a primary indicator of LV dilation, these findings suggest that the structural remodeling of the LV was not significantly different between diabetic TNC-KO and WT mice. However, the trend toward less extension of LVESD in TNC-KO diabetic mice may reflect better-preserved systolic function, aligning with the observed differences in LVEF. To further characterize the cardiac function, a group of mice were used to measure invasive cardiac hemodynamics as previously described [[130]37]. Diabetic mice showed significantly lower LVSP (mean LVSP 91 ± 5 mmHg in WT non-diabetic vs. 77 ± 5 mmHg in WT diabetic animals; p = 0.0005 and 92 ± 6 in TNC-KO non-diabetic vs. 83 ± 4 mmHg in TNC-KO diabetic group; p = 0.0119), and an increased LVEDP (mean LVEDP 2.4 ± 0.5 mmHg in WT non-diabetic vs. 5.5 ± 1.04 mmHg in WT diabetic animals; p < 0.0001 and 2.6 ± 0.4 mmHg in TNC-KO non-diabetic vs. 3.99 ± 0.7 mmHg in TNC-KO diabetic group; p = 0.0091) compared to the non-diabetic groups (Fig. [131]1F-G). Notably, TNC-KO diabetic mice exhibited a significantly lower LVEDP aligning with the echocardiography results (p = 0.0045). Myocardial contractility measured by peak dP/dt, showed a significant decline in diabetic WT mice compared to WT non-diabetic controls (peak dP/dt 6571 ± 753 in WT non-diabetic vs. 5260 ± 765 in WT diabetic animals; p = 0.0042). However, no statistically significant difference was observed between TNC-KO diabetic and TNC-KO non-diabetic groups (6067 ± 321 vs. 5683 ± 424 in TNC-KO diabetic group p = 0.692). Similarly, dP/dt[min] (dp/dt[min] -5848 ± 967 in WT non-diabetic vs. − 3881 ± 1137 in WT diabetic animals; p = 0.0017 and − 5552 ± 297 in TNC-KO non-diabetic vs. − 4922 ± 559 in TNC-KO diabetic group; p = 0.5337) followed the same trend. Given the relatively small sample size (n = 5–7), conclusions regarding the protective effect of TNC deficiency on contractility should be interpreted with caution, as the observed variation between individual animals may influence the results. These data are illustrated in F[132]ig. [133]1H-I. HR did not differ between groups (data not shown). Myofilament Ca^2+-dependent active and passive force production To further investigate the potential adverse role of TNC in the progression of cardiac dysfunction in diabetes, we assessed cardiomyocyte contractile filament Ca^2+-dependent active and passive force production in skinned cardiomyocyte preparation. The maximal force (Fmax) results show that diabetes induces a decline in active force production in skinned cardiomyocyte preparation. WT diabetic mice showed lower values, but no significant difference was observed between the two diabetic groups (Fig. [134]2D). In addition, cardiomyocyte stiffness (Fpassive) of diabetic and non-diabetic cardiomyocytes was measured at different sarcomere lengths. W t diabetic mice exhibited increased cardiomyocyte stiffness, as indicated by a higher Fpassive at equivalent sarcomere lengths compared to non-diabetic groups. However, in TNC-KO diabetic mice the Fpassive was lower (Fig. [135]2A). Fig. 2. [136]Fig. 2 [137]Open in a new tab Cardiomyocyte passive force. Elevated Fpassive was characteristic to all diabetic animals (A–C). Cardiomyocytes of diabetic TNC-KO mice showed less increase in Fpassive compared to wild-type animals (A). There was no significant change in Factive between the groups (D). TNC-KO Tenascin-C knock-out (Data shown as mean ± SD; n = 7–12/group.) Cardiac fibrosis Cardiac fibrosis is a hallmark of DCM, and our recent studies showed the maladaptive role of TNC in cardiac fibrosis [[138]30]. Figure [139]3 shows representative images of collagen deposition (Picrosirius red staining) in the cardiac tissue (Fig. [140]3A) summarizing the results of the differences between the four groups (Fig. [141]3B). These findings demonstrate that collagen staining is more pronounced in WT diabetic mice, whereas knocking out the TNC gene provided marked protection against cardiac fibrosis in diabetes (Fig. [142]3B). Fig. 3. [143]Fig. 3 [144]Open in a new tab Fibrosis in wild-type and Tenascin-C deficient non-diabetic and diabetic animals. Wild-type (WT) and Tenascin-C knockout (TNC-KO) mice, diabetic vs. non-diabetic. Picro-Sirius staining of ventricular tissue. Scanned, Bitmap pictures. Representative pictures of the left ventricular anterior wall. Picro-Sirius staining for collagen. Increased fibrosis is visible as purple staining in between cardiomyocyte fibers in WT diabetic mice (upper right). Less fibrosis was found in TNC-KO diabetic animals (bottom right) (A). Quantitative analysis of collagen content. Histogram for number of pixels with different green densities (ImageJ) **WT diabetic versus WT non-diabetic p < 0.01; +  + WT diabetic versus TNC-KO diabetic p < 0.01; + WT diabetic versus TNC-KO diabetic p < 0.05 (B). TNC-KO Tenascin-C knockout; WT wild-type (Data shown as mean ± SEM, n = 7/group, pixels with green densities ≤ 210 can be considered containing collagen) Preserved vascular endothelial function in diabetic TNC-KO animals In addition to phenylephrine (Phe)-induced vasoconstriction, acetylcholine (ACh)-induced vasorelaxation, an indicative parameter of endothelium-dependent vasodilation was assessed in isolated abdominal aortic segments from non-diabetic and diabetic mice 18 weeks after STZ injection. Phe-induced vasoconstriction was similar in all groups (Fig. [145]4A). In Phe-preconstricted aortic rings, the relaxation in response to ACh was significantly blunted in WT diabetic mice in comparison to WT non-diabetic mice (Fig. [146]4B), indicating an impaired endothelial-dependent vasorelaxation. In contrast, TNC-KO diabetic mice showed a significantly preserved endothelial function, suggesting deleterious effects of TNC on vascular endothelial function in diabetes (Fig. [147]4B). Fig. 4. [148]Fig. 4 [149]Open in a new tab Dose–response curves obtained from wire myograph measurements. Treatment of the vessels with phenylephrine induced similar contraction of the vessel walls in all animals (A). Acetylcholine (ACh) induced relaxation was impaired in the diabetic groups. TNC-KO animals showed restored relaxation compared to the WT mice (B). Endothelium-dependent relaxation to ACh significantly decreased in the diabetic WT group compared to non-diabetic WT animals (*p < 0.05). This attenuated relaxation was significantly restored in the aortas of diabetic TNC-KO mice. Statistics: two-way ANOVA. Data displayed as mean ± SD; n = 20–50 segments/group. Ach, acetylcholine; Phe, phenylephrine; TNC-KO, Tenascin-C knock-out; WT, wild-type Lack of TNC protects against increased angiotensin-converting enzyme activity in lung and kidney tissue samples as well as plasma malondialdehyde upregulation in mice (Data shown in Supplementary Paragraph and Fig. [150]4). The impact of TNC and diabetes on apoptosis and inflammation The effect of TNC deficiency on diabetes-induced apoptosis was assessed using TUNEL staining. No TUNEL-positive cells were observed in WT non-diabetic and TNC-KO non-diabetic tissue. In contrast, the WT diabetic group exhibited positively stained cells, particularly in regions showing signs of remodeling. However, the number of TUNEL-positive cells was notably reduced in the diabetic TNC KO group (Fig. [151]5A), suggesting that TNC deficiency mitigates diabetes-induced apoptosis in cardiac tissue. Next, we investigated whether TNC directly affects apoptosis in H9c2 cells. As shown in Fig. [152]5D-H, exposure to high glucose increased apoptosis signaling. However, quantitative analysis of TUNEL staining revealed no significant difference in apoptosis between the recombinant human TNC-treated group and the control group. Fig. 5. [153]Fig. 5 [154]Open in a new tab Apoptosis and CD68+ expression. A Representative images of terminal deoxynucleotidyl transferase-mediated dUTP nick-end labelling (TUNEL) staining for apoptotic cells in the left ventricular wall of wild-type (WT) and Tenascin-C knockout (TNC-KO) mice, diabetic vs. non-diabetic. TUNEL staining was performed to assess the extent and distribution of apoptotic cells in the cardiac tissue. Green dots represent apoptotic cells resulting from the mixture of TUNEL-stained and DAPI-counterstained nuclei. Blue dots represent non-apoptotic cells stained with DAPI only. No evidence of apoptosis was found in WT non-diabetic and TNC-KO non-diabetic heart tissue, whereas apoptotic cells were frequently found in areas thought to represent remodeling, visible as green staining in WT diabetic mice. Fewer TUNEL-positive cells were found in TNC-KO diabetic heart tissue compared to diabetic WT animals. Scale bar = 100 µm (200× magnification). B Immunoperoxidase staining for CD68. Representative images of myocardial tissue from WT and TNC-KO mice, diabetic vs. non-diabetic, showing CD68+ macrophages in the myocardium (magnification× 200, scale bar: 50 μm). (C) No statistical difference in numbers of CD68+ macrophages in the myocardium between the groups. The graph shows the number of CD68-positive cells. Data are expressed as mean ± SD; n = 4/group. (D)High glucose and (E)Tenascin C-induced apoptosis in H9C2 cells. Representative fluorescence pictures demonstrate the presence of positive TUNEL and DAPI as well as merged staining in positive control (cells were treated with 500 U/mL DNase I), negative control (cells were with the enzymatic solution without the labeled antibody), control, glucose (30 mM) and rh TNC (5 µg/mL) treatment groups. (G-H) Quantitative analysis of the TUNEL assay. DAPI, 4′,6-diamidino-2-phenylindole; Rh TNC, recombinant human Tenascin-C; TNC-KO, Tenascin-C knockout; TUNEL, terminal deoxynucleotidyl transferase-mediated dUTP nick-end labelling; WT, wildt-type. Data shown as mean ± SD, n = 3–6/ condition; *p < 0.05 To assess macrophage infiltration, immunohistochemistry was performed to detect CD68+ macrophages (Fig. [155]5B-C). A slight increase in macrophage content was observed in diabetic hearts compared to non-diabetic hearts. In contrast, the number of CD68+ macrophages was reduced in the LV myocardial tissue in the TNC-KO diabetic groups. Hyperglycemic environment induces TNC expression in human ventricular cardiac fibroblasts as well as overexpression of TNC and inflammation in cardiomyocytes Next, we assessed whether high glucose stress (30 mM) increases TNC levels in adult human ventricular cardiac fibroblasts. Our data clearly demonstrated that TNC protein expression levels were markedly increased after 30 mM glucose administration (Fig. [156]6A-C), suggesting that hyperglycemia seems to be a crucial factor in the upregulation of TNC in cardiac fibroblasts. Fig. 6. [157]Fig. 6 [158]Open in a new tab Tenascin-C expression and pro-inflammatory cytokines. A and B Representative picture of Western Blot results. Tenascin-C expression in control (top row) and High Glucose treated (bottom row) NHFC cells. Representative photomicrographs of nuclei immunostaining using DAPI (left column), Tenascin-C (TNC) staining (middle column) and the combination of merged staining (right column). The white line represents the scale and corresponds to 20 µm in every image. Control NHFC cells (n = 3) and 48 h high-glucose treated (30 mM) NHFC cells (n = 3). C Western blot results show increased TNC protein expression under 30 mM glucose treatment in human NHFC cells. D Elevated glucose levels influence the DNA methylation of the TNC promoter compared to the control in H9c2 cells (ratio Me/UMe TNC promoter in hyperglycemic environment vs. control 49.35 versus 100, respectively; p = 0.0019). E–G Oxidative stress markers after incubation with rh TNC. NOX4 and TNF-α levels increased significantly upon incubation with rhTNC (p = 0.0435 and p = 0.0180, respectively; E, G). IL-6 levels were also markedly elevated (D). C control; DAPI, 4’,6-diamidino-2-phenylindole; HG, high glucose; H9c2 cells, line of embryonic rat cardiomyocytes; IL-6, interleukin 6; Me/Ume, methylated/unmethylated TNC promoter; NHFC, normal human ventricular cardiac fibroblasts; NOX4, nicotinamide adenine dinucleotide phosphate oxidase 4; rh TNC, recombinant human Tenascin-C; TNF-α, tumor necrosis factor alpha; **p < 0.01; *p < 0.05. Data shown as mean ± SD, n = 3–6/group We then sought to determine the TNC promoter methylation in H9c2 cells exposed to 30 mM glucose environment. An increase in the proportion of unmethylated TNC promoter regions, reflected by a decrease in the Me/UMe ratio compared to the control (Fig. [159]6D) suggests the higher expression of TNC in this condition. Therefore, further analysis was focused on the direct effects of TNC on cardiomyocytes. We observed a significant upregulation in the expression of pro-inflammatory cytokines and increased oxidative stress markers after TNC treatment in isolated mouse cardiomyocytes (Fig. [160]6E-G). Collectively, these data suggest that TNC expression is at least partially triggered by high glucose in cardiac fibroblasts and cardiomyocytes. RNA sequencing analysis Differential gene expression in A/J diabetic versus A/J non-diabetic mice A total of 322 genes were found to be significantly differentially expressed between A/J diabetic and A/J non-diabetic groups based on a FDR-adjusted p-value (q-value) of less than 0.05 (Fig. [161]7B). The volcano plot (Fig. [162]7B) illustrates the distribution of upregulated and downregulated genes, highlighting those with significant expression differences. Fig. 7. [163]Fig. 7 [164]Open in a new tab Differential gene expression, pathway, and transcription factor activity analysis in A/J wild-type diabetic and non-diabetic mice. This figure illustrates the results of RNA sequencing and subsequent analyses comparing A/J diabetic mice to A/J non-diabetic mice. Panel A presents a volcano plot of differential gene expression, where the x-axis represents the log₂ fold change (log2FC), and the y-axis shows the negative logarithm (base 10) of the adjusted p-value (-log10(p-value)). Genes significantly upregulated (q-value < 0.05) are highlighted in red, and significantly downregulated genes are highlighted in blue, with the horizontal dashed line denoting the significance threshold. Panel B shows pathway activity analysis using the PROGENy framework, indicating significant downregulation of the PI3K and estrogen pathways, while upregulation is observed in the JAK-STAT pathway. Other pathways, such as TGF-β and p53, show minimal changes in activity. In panel C, pathway enrichment analysis using Metascape highlights the top enriched biological processes and pathways among the significantly differentially expressed genes, including “Cytoskeleton in muscle cells” (mmu04820), “Sarcomere organization” (GO:0045214), and “RHO GTPase cycle” (R-MMU-9012999), pointing to potential impacts on muscle cell structure and function. Panel D shows transcription factor activity analysis inferred using the decoupler package, where transcription factors such as Stat2, Irf9, Creb1, and Smad4 exhibit increased activity. At the same time Elk3 displays decreased activity, suggesting changes in transcriptional regulation, particularly related to inflammation and cellular stress responses. Panel E presents a hub gene analysis performed using Cytohubba, where highly connected hub genes are shown in red, intermediate hub genes in yellow, and neighboring nodes in blue. Genes such as Myh6, Myh7, Myom2, Lmod2, and Tnnt2 are central within this network, highlighting their involvement in muscle contraction and structure. This network illustrates key molecular interactions that may be influenced by diabetes in A/J mice Pathway activity analysis Using the PROGENy framework, pathway activity analysis was performed to identify key signaling pathways affected in A/J diabetic group compared to A/J non-diabetic group (Fig. [165]7A). The analysis revealed significant upregulation of hypoxia-related pathways, indicating increased cellular stress in the diabetic hearts. Conversely, the PI3K pathway was significantly downregulated, suggesting potential impairments in insulin signaling and metabolic regulation. Enrichment and overrepresentation analysis Metascape overrepresentation analysis was conducted on the significantly differentially expressed genes to identify enriched biological processes and pathways (Fig. [166]7C). The top enriched terms included “Cytoskeleton in muscle cells” (mmu04820), “Sarcomere organization” (GO:0045214), and “RHO GTPase cycle” (R-MMU-9012999). These pathways are critical for maintaining cardiac muscle structure and function, suggesting that diabetes may impact sarcomere organization and cytoskeletal integrity in cardiac muscle cells. Transcription factor activity inference TF activity analysis using the decoupler package identified several TFs with altered activity in A/J diabetic mice compared to A/J non-diabetic controls (Fig. [167]7D). Notably, Elk3 showed decreased activity, which may affect angiogenesis and vascular remodeling processes. In contrast, TFs such as Stat2, Irf9, Creb1, and Smad4 exhibited increased activity, indicating potential changes in inflammatory signaling, interferon responses, and transcriptional regulation related to cellular proliferation and ECM production. Protein–protein interaction network and hub gene identification A protein–protein interaction network was constructed using significantly differentially expressed genes and network analysis identified several hub genes with high connectivity, determined using the Maximal Clique Centrality (MCC) algorithm (Fig. [168]7F). The following top hub genes were identified: Ckm (creatine kinase, muscle), Fabp4 (fatty acid-binding protein 4), Lmod2 (leiomodin 2), Myh6 (myosin heavy chain 6), Myh7 (myosin heavy chain 7), Myl1 (myosin light chain 1), Myom2 (myomesin 2), Ppara (peroxisome proliferator-activated receptor alpha), Tcap (titin-cap), and Tnnt2 (troponin T2). Differential gene expression in TNC-KO diabetic versus A/J diabetic mice Comparative RNA sequencing analysis between TNC-KO diabetic and A/J diabetic groups revealed that 41 genes were significantly differentially expressed based on a q-value of less than 0.05. When considering a p-value threshold of less than 0.05 without adjustment, 1,089 genes exhibited differential expression (Fig. [169]8C). Volcano plots illustrate the gene expression changes for the following comparisons: TNC-KO non-diabetic vs A/J non-diabetic groups (Fig. [170]8A), and TNC-KO diabetic vs A/J diabetic groups (Fig. [171]8B-C). Fig. 8. [172]Fig. 8 [173]Open in a new tab Differential gene expression, pathway, and transcription factor activity analysis in TNC-KO and A/J wild-type diabetic mice. Results of RNA sequencing and subsequent analyses comparing TNC-KO diabetic mice to A/J diabetic mice. Panels (A), (B), and (C) display volcano plots of differential gene expression for three comparisons: (A) TNC-KO diabetic (dia) versus A/J non-diabetic (nondia) mice, B TNC-KO diabetic versus A/J diabetic (dia) mice, and (C) TNC-KO non-diabetic versus A/J non-diabetic comparison. In each plot, the x-axis represents the log₂ fold change (log2FC), and the y-axis shows the negative logarithm (base 10) of the adjusted p-value (-log10(p-value)). Genes significantly upregulated are indicated in red, and significantly downregulated genes are shown in blue, with horizontal dashed lines representing the significance. Panel (D) presents a pathway enrichment analysis conducted using Metascape for the TNC-KO diabetic versus A/J diabetic comparison, integrating KEGG and GO terms. The most significant pathways include “generation of precursor metabolites and energy,” “transport of small molecules,” and “energy reserve metabolic process,” indicating disruptions in metabolic pathways and transport mechanisms. Panel (E) shows pathway activity analysis, revealing significant upregulation of the JAK-STAT pathway and downregulation of the p53 pathway in TNC-KO diabetic mice, suggesting alterations in cytokine signaling and cell cycle regulation. Panel (F) illustrates transcription factor (TF) activity inferred from gene expression data, with transcription factors such as Rxra, Smad1, and Foxc2 displaying reduced activity, while Rrra and Nfe2l3 show increased activity in TNC-KO diabetic mice, implicating disrupted metabolic regulation and transcriptional control. Panel (G) depicts a hub gene analysis performed using Cytohubba. Genes are ranked based on their degree of connectivity, with hub genes shown on a continuum from red (highly connected) to yellow (moderately connected). At the same time, neighboring nodes are depicted in blue. Central hub genes, including Ppargc1b, Ndufs, and Sdha, which are involved in metabolic and mitochondrial processes, are highlighted, suggesting critical molecular interactions that may be impacted by TNC deficiency Pathway activity and enrichment analysis in TNC-KO diabetic mice Pathway activity analysis comparing TNC-KO diabetic mice to WT diabetic mice revealed significant alterations in several key terms (Fig. [174]8D) and signaling pathways (Fig. [175]8E). Metabolic terms such as GO:0006091: generation of precursor metabolites and energy and GO:006112: energy reserve metabolic process, showed significant alteration in TNC-KO diabetic mice. The JAK-STAT pathway was notably upregulated in TNC-KO diabetic mice, suggesting enhanced cytokine signaling and immune responses associated with TNC deficiency in diabetes. In contrast, the p53 signaling pathway was significantly downregulated in TNC-KO diabetic mice compared to A/J diabetic controls, indicating potential alterations in cell cycle regulation and apoptosis. Transcription factor activity inference TF activity analysis identified several TFs with altered activity in TNC-KO diabetic mice compared to A/J diabetic mice (Fig. [176]8F). The activity of Rxra (retinoid X receptor alpha) was markedly decreased in TNC-KO diabetic mice. Other TFs showing decreased activity such as Smad1, Smad3, Dlx2, Ppara (peroxisome proliferator-activated receptor alpha), and Foxa3. Conversely, Nfe2l3 (nuclear factor, erythroid 2 like 3) exhibited increased activity in TNC-KO diabetic mice. Protein–protein interaction network A protein–protein interaction network was constructed using the differentially expressed genes identified in the TNC-KO diabetic versus A/J diabetic comparison (Fig. [177]8G). This network provides a visual representation of potential interactions among these genes, illustrating the molecular landscape affected by TNC deficiency in diabetic conditions. Plasma levels of TNC in HF patients Previous studies showed the association of circulating levels of TNC and worse clinical outcome among patients with T2DM. However, no comprehensive results show whether TNC levels are altered among patients with HFrEF and HFrEF with diabetes. Demographic data in individuals with HFrEF with and without diabetes and controls is provided in Table [178]1. HFrEF patients without diabetes (HFrEF nonDM) were significantly younger than the diabetic and the control groups. The HF groups had a significantly higher female quota than the control group. Ischemic and dilated cardiomyopathies were the most common causes of HF. Diabetic patients exhibited significantly higher BMI and fasting blood sugar levels compared to HF subjects without diabetes or control subjects. Both HF groups had lower blood pressure compared to the control group. There was no difference in the pharmacological regimen between the two HFrEF groups. Table 1. Patient demographics HFrEF HFrEF + DM control p-value n = 37 n = 22 n = 21 Age (mean; SD) 56 ± 14 66 ± 8 65 ± 7 0.0022 Female sex (n; %) 29 (78) 18 (82) 9 0.0065 Etiology of heart failure Ischemic (n; %) 10 (27) 17 (77) Dilated (n; %) 19 (51) 5 (23) Hypertrophic (n; %) 1 (2.7) 0 Myocarditis (n; %) 1 (2.7) 0 Unknown (n; %) 6 (16) 0 LVEF % (mean ± SD) 21.3 ± 8.0 23.5 ± 9.0 0.3229 BMI (mean ± SD) 26.1 ± 4.7 29.9 ± 4.5 24.9 ± 3.4 0.0006 BP systolic (mean ± SD) 112 ± 21 113 ± 20 129 ± 12 0.0048 BP diastolic (mean ± SD) 71 ± 10 73 ± 11 80 ± 7 0.0036 NYHA classification I (n; %) 0 0 21 (100) II (n; %) 2 (5.4) 1 (4.5) 0 III (n; %) 33 (89.2) 20 (91) 0 IV (n; %) 2 (5.4) 1 (4.5) 0 Therapy ACEI (n; %) 25 (68) 12 (55) 0 ARB (n; %) 14 (38) 9 (41) 0 Beta blocker (n; %) 36 (97) 22 (100) 0 Mineralocorticoid receptor antagonist (n; %) 25 (68) 16 (73) 0 Loop diuretics (n; %) 32 (86) 17 (77) 0 Statin (n; %) 13 (35) 15 (68) 0 Plasma glucose level (mg/dL ± mean; SD) 99 ± 15 138 ± 24 98 ± 12 .00007 [179]Open in a new tab P-values refer to the comparison of means or medians (as stated in the first column) of all three groups. ACEI, angiotensin-converting enzyme inhibitor; ARB, angiotensin 2 receptor blocker; BMI, body mass index; BP, blood pressure; DM, diabetes mellitus; HFrEF, heart failure with reduced ejection fraction; LVEF, left ventricular ejection fraction; NA, not available; NYHA, New York Heart Association; SD, standard deviation Plasma concentrations of TNC were significantly elevated in HFrEF patients compared to healthy controls, without statistically significant difference between the HFrEF with or without diabetes (Fig. [180]9), suggesting that TNC may be a biomarker for adverse cardiac remodeling and cardiomyopathy in HFrEF. Nonetheless, these findings highlight the need for additional studies to explore TNC expression levels in cardiac tissue during the early stages of diabetes. Further investigation should also focus on elucidating the role of TNC in modulating cardiac cellularity and alterations in the ECM composition associated with diabetes. Fig. 9. Fig. 9 [181]Open in a new tab Plasma levels of Tenascin-C (TNC) in patients. Plasma TNC levels in healthy subjects (n = 21) and patients with HFrEF with (n = 22) or without (n = 37) diabetes. Mean plasma level of TNC (pg/ml; SD) in control, HFrEF and diabetic HFrEF patients: 296.4 (159.7), 1237 (934.4) and 875.9 (682.6) pg/ml, respectively. One-way ANOVA with Bonferroni’s multiple comparison test: control versus HFrEF p < 0.0001, control versus HFrEF + DM p = 0.0402, HFrEF versus HFrEF + DM p = 0.2213. ANOVA, analysis of variance; DM, diabetes mellitus; HFrEF, heart failure with reduced ejection fraction; hTNC, human Tenascin-C. Mean ± SD are shown. **p < 0.01; *p < 0.05 Discussion The primary finding of this study was that in a mouse model of STZ-induced diabetes, TNC deficiency was linked to preserved left ventricular systolic and diastolic function, reduced cardiac fibrosis, mitigated endothelial dysfunction, and decreased cardiac stiffness. In cardiomyocytes, high glucose levels increased TNC expression, while recombinant human TNC stimulated pro-inflammatory and oxidative stress markers. Pathways involving Serpin1k, Ccn1, Cpt1a, and Slc27a1 may implicate TNC in fibrosis and the progression of DCM. Additionally, TNC may influence cardiac fibrosis and fibroblasts through a signaling mechanism regulated by p53. In patients with HFrEF, TNC concentrations were elevated compared to healthy individuals, regardless of diabetes status, suggesting a potential causative role for TNC in the development of DCM and vascular dysfunction. A growing amount of research on TNC is dedicated to elucidate whether TNC contributes to tissue repair or exacerbates pathological processes, amplifying the damage associated with ischemia, pressure or volume overload, or diabetes.[[182]18–[183]20, [184]30, [185]43, [186]47–[187]51]. Simultaneously, investigations on TNC in the context of diabetes aim to discern whether increased TNC levels trigger signaling pathways leading to diabetes or if diabetic conditions enhance the upregulation of TNC [[188]52]. We therefore investigated the potential rationale for the pathophysiological involvement of TNC in the progression of cardiovascular dysfunction associated with diabetes. TNC deficiency does not inherently shield against diabetes per se; we could show however, that it does impart a safeguard against cardiac complications commonly correlated with diabetes. TNC, an ECM glycoprotein, is recognized for its involvement in tissue remodeling and repair processes [[189]25]. While animals lacking TNC still exhibit susceptibility to diabetes, their cardiac tissues appear less prone to the adverse structural and functional alterations associated with DCM. This observation underscores the intricate interplay between ECM remodeling and the pathophysiology of diabetes-induced cardiovascular complications [[190]15], with our data suggesting that TNC plays a key role in mediating the deleterious effects of diabetes. TNC deficiency ameliorates cardiac dysfunction in diabetes Similarly to HF of other etiologies without diabetes [[191]20, [192]30, [193]53], we found preserved systolic and diastolic LV function in TNC-KO diabetic mice compared to WT diabetic animals. Furthermore, TNC deficiency in diabetes resulted in less endothelial dysfunction and myocardial fibrosis compared to the WT diabetic group. Notably, WT diabetic mice displayed increased cardiomyocyte stiffness, evidenced by higher passive force (Fpassive) at equivalent sarcomere lengths. This increased Fpassive along with cardiac fibrosis and cardiomyocyte stiffness, contributes to the diastolic dysfunction observed in vivo. Considering that 18 weeks after diabetes induction both diastolic and systolic LV function were impaired, our data support the theory of DCM as a complex, progressive condition, where diastolic and systolic dysfunction exist simultaneously and aggravate each other as described previously [[194]10]. This observation aligns with the understanding that LV dilation is a hallmark of diabetes and contributes to poorer clinical outcomes in diabetic patients. Previously, we demonstrated that LV dilatation was markedly alleviated in TNC-KO mice following myocardial infarction, partially through mechanisms involving ACE and MMPs activation [[195]20]. In addition, we provide evidence that recombinant human TNC (rhTNC) significantly upregulates ACE expression in human ventricular cardiac fibroblasts [[196]43]. This upregulation may be linked to cardiac fibrosis, myocardial stiffness, and LV dilation. However, in our current study, TNC-KO diabetic mice did not exhibit a significant reduction in LVEDD compared to WT mice. Meanwhile, the trend toward less LVESD expansion in TNC-KO diabetic mice may indicate improved and preserved systolic function, consistent with the observed differences in LVEF. Cellular source of TNC Elevated levels of TNC were linked to diabetes in different patient cohorts [[197]17, [198]18, [199]31] and circulating TNC is independently associated with worse clinical prognosis in T2DM [[200]18], after acute myocardial infarction [[201]54] as well as in dilated cardiomyopathy [[202]55]. Moreover, enhanced TNC expressions were demonstrated in retinal ECs in diabetes with or without manifest retinopathy [[203]56, [204]57]. In our cohort, elevated TNC plasma levels were measured in HFrEF patients with but also without T2DM. As for the cellular source of TNC, we found evidence of upregulated TNC-expression in cardiac fibroblasts under high glucose underlying the detrimental role of hyperglycemia-induced TNC overexpression. Moreover, hyperglycemia induced the stimulation of TNC promoter activity in H9c2 cardiomyoblasts. This finding implies that high glucose conditions can induce epigenetic changes in cardiomyocytes, thereby contributing to the regulation of TNC expression and presumably exerting a role in cardiac remodeling and disease processes. Interestingly, a recent study has demonstrated that TNC overexpression in mouse hearts did not cause distinct histological and functional abnormalities in the absence of a pathological stimulus [[205]58]. In contrast, cardiac expression of pro-inflammatory cytokines and chemokines was substantially elevated, accompanied by increased mortality observed during the acute post-MI phase in mice with heart-specific overexpression of TNC. This suggests that pathological stimuli, such as an ischemic insult and diabetic conditions, may play a significant role in driving TNC overexpression. In addition to cardiac fibrosis, oxidative stress plays a major role in myocardial stiffness and apoptosis in DCM. The adverse effects of TNC on cardiomyocytes were shown in a number of studies via a signaling mechanism involving cardiac fibrosis [[206]25, [207]28]. In our study, rhTNC treatment markedly increased the expression of oxidative and pro-inflammatory molecules such as IL-6, NOX-4, and TNF-α in isolated adult mouse cardiomyocytes. Interestingly, our in vitro study shows that high glucose enhances apoptosis signaling in H9c2 cells, whereas recombinant human TNC, as previously reported, does not have a significant effect on apoptosis [[208]19].The elevated plasma MDA levels observed in diabetic animals provide further evidence of oxidative stress. The observation that TNC-KO diabetic animals exhibit a reduced amount of MDA suggests that TNC plays a distinct role in oxidative stress signaling in diabetic hearts, thereby enhancing fibrosis and vascular dysfunction. Oxidative stress can cause structural and functional alterations in CMs, such as increased fibrosis, disrupted ECM remodeling, and impaired contractile function [[209]59]. This contributes to an increase in myocardial stiffness, which is often reflected in stiffness-force measurements. Our results indicate that diabetes induces a reduction in active force production in cardiomyocytes, evidenced by a decline in maximal force (Fmax) in skinned cardiomyocyte preparations. This reduced contractility reflects a known consequence of diabetes on cardiomyocyte function, where hyperglycemia, oxidative stress, and other metabolic alterations disrupt calcium handling and myofilament function, leading to impaired contractility. Notably, while both WT and TNC-KO diabetic mice exhibited reduced Fmax compared to non-diabetic controls, no significant difference was detected between the diabetic groups. The absence of a significant difference in maximal active force (Fmax) between these groups may appear unexpected, considering the preserved cardiac function in TNC-KO diabetic mice. However, cardiac performance is influenced by multiple compensatory mechanisms. Although reduced cardiomyocyte active force indicates impaired contractility, LVEF does not directly correspond to intrinsic cellular function. Adaptive processes such as increased preload, hypertrophic remodeling, changes in myocardial stiffness, and enhanced sympathetic activation can help maintain LVEF despite decreased active force. Therefore, the preserved LVEF in TNC-KO diabetic mice likely reflects these compensatory adaptations, allowing overall cardiac function to remain stable despite localized impairments. However, the observed decrease in Fpassive in TNC-KO mice suggests that the absence of TNC alleviates maladaptive stiffening. This reduction may contribute to improved diastolic function, offering potential therapeutic benefits. Targeting TNC could potentially mitigate diastolic dysfunction and reduce myocardial stiffness. Endothelial dysfunction is a hallmark of diabetes, significantly contributing to cardiovascular complications and is thought to be a key driver of diastolic dysfunction and HFpEF [[210]60–[211]62]. Chronic hyperglycemia in diabetes induces persistent oxidative stress and inflammatory responses, damaging endothelial cells, which play an essential role in maintaining vascular tone and integrity. Elevated ACE activity in diabetes exacerbates these effects by promoting vasoconstriction, inflammation, and oxidative stress, further compromising endothelial function [[212]63]. Additionally, angiotensin II stimulates the production of pro-fibrotic cytokines like transforming growth factor-beta (TGF-β), contributing to fibrosis. This fibrotic response is particularly detrimental in DCM, where cardiac and vascular fibrosis contribute to tissue stiffening, reduced ventricular compliance, and impaired cardiac performance, worsening patient outcomes. Interestingly, findings from TNC-KO diabetic mice, which showed a significant reduction in ACE activity in kidney and lung tissues, suggest that the absence of TNC may confer protective benefits. This reduction in ACE activity could mitigate fibrotic progression and organ damage, and delay the deterioration associated with DCM. The pro-fibrotic effect of TNC in diabetes Fibrosis occurs in various diabetic tissues, especially in those with lack of regenerative capacity, such as the myocardium [[213]64]. Several studies have associated hyperglycemia-induced fibrosis with pro-inflammatory cytokines [[214]16], which in turn promote macrophage activation toward an inflammatory phenotype. TNC has been shown to play a crucial role in several fibrotic conditions, including end-stage renal diseases [[215]65], post-infarction adverse cardiac remodeling [[216]48], ischemia–reperfusion injury [[217]66], dilated cardiomyopathy [[218]21, [219]53], diabetic retinopathy [[220]57], pressure overload [[221]30] and pulmonary hypertension [[222]67]. Our study stated that TNC deficiency is protective in terms of cardiac fibrosis in diabetes. Consequently, LV compliance and vascular function were preserved in TNC-KO diabetic mice. Fibroblast activation and fibroblast to myofibroblast conversion has been reported to be responsible for cardiac fibrosis in diabetes [[223]16]. In line with these findings, we demonstrated that rhTNC similar to TGF-ß caused smooth muscle actin (SMA) and collagen type 1 (Col 1) upregulation in ventricular human cardiac fibroblasts [[224]43]. Nonetheless, the increased secretion of TGF-ß appears to be a consistent response to high levels of glucose, resulting in increased ECM production, proliferation and myofibroblast transition. Additionally, we demonstrated for the first time that human cardiac fibroblasts express elevated levels of TNC under high glucose conditions. Conversely, we may speculate that TGF-ß overexpression stimulates TNC re-expression and subsequently aggravates progressive fibrosis and cardiac dysfunction [[225]68]. Persistent hyperglycemia drives the accumulation and infiltration of pro-inflammatory macrophages in the heart [[226]69], leading to increased cytokine secretion, including TGF-β, which can trigger or worsen cardiac damage. This cascade contributes to adverse remodeling, myocardial fibrosis, and the activation of toll-like receptor 4 (TLR-4), a known endogenous receptor for TNC [[227]70]. Notably, our findings revealed a reduced presence of CD68+ macrophages in the diabetic TNC-KO heart compared to WT diabetic mice. Bioinformatics analysis of cardiac gene expression in mouse heart tissue It was shown previously that even cardiac dysfunction induced by prediabetes, a precursor state of T2DM, could be characterized by transcriptomic changes in the heart [[228]71]. Therefore, we conducted a comprehensive transcriptomic analysis of RNA sequencing data to further elucidate the molecular mechanisms underlying the protective effects of TNC deficiency in DCM. First, by comparing WT diabetic and WT non-diabetic mice, we identified 322 significantly differentially expressed genes based on a stringent q-value threshold. Pathway activity analysis showed significant upregulation of hypoxia-associated pathways in the hearts of diabetic A/J mice. Increased cellular stress and potential hypoxic conditions adversely affect cardiac metabolism and impair myocardial contractility [[229]72]. In contrast, the PI3K pathway was significantly downregulated in WT diabetic mice compared to non-diabetic animals. Given the PI3K pathway's crucial roles in insulin signaling, cell survival, and metabolic regulation, its suppression aligns with the metabolic dysfunctions characteristic for diabetes [[230]73]. This could hamper cardiomyocyte contractile function and contribute to increased stiffness, aligning with our observations in skinned cardiomyocytes [[231]74]. Transcription factor activity analysis revealed decreased activity of Elk3 in WT diabetic mice, which partially explains vascular dysfunction [[232]75]. Increased activity of Stat2, Irf9, Creb1, and Smad4 was also observed in diabetic hearts and these changes were linked to inflammation, fibrosis and adverse remodeling [[233]76]. Finally, Hub gene analysis identified several key genes with high connectivity within the protein–protein interaction network, including Myh6, Myh7, Ppara, and Tnnt2. These genes are integral to cardiac contractility and energy metabolism in diabetes [[234]77]. In TNC-KO diabetic mice, transcriptomic analysis revealed significant alterations compared to WT diabetic mice, despite similar levels of hyperglycemia. One of the most important findings was the p53 signaling pathway downregulation in the TNC-KO diabetic groups versus WT diabetic groups. More recent studies demonstrated that p53 plays a maladaptive role in cardiac fibrosis and cardiomyopathy in various models of diabetes [[235]78, [236]79]. Diabetes-induced cardiac apoptosis typically occurs early (within 7–21 days) in mice through a mitochondria-dependent pathway. Interestingly, despite persistently elevated p53 expression in the diabetic group at 3 and 6 months post-diabetes onset, the rate of cardiomyocyte apoptosis was significantly lower, as indicated by cleaved caspase-3 levels and TUNEL assay results [[237]80]. Our bioinformatics analysis at 18 weeks post-STZ injection revealed reduced p53 signaling in the TNC-KO diabetic group, suggesting a potential role for TNC in modulating cardiomyocyte apoptosis. To investigate this, we performed a TUNEL assay on cardiac tissue slices, which revealed relatively low apoptosis levels in H9c2 cells but a more pronounced effect in remodeled cardiac tissue. However, when assessing TUNEL-positive staining in H9c2 cardiomyocytes, TNC treatment did not significantly increase apoptosis, indicating that TNC may influence p53 signaling primarily in other cell types, such as cardiac fibroblasts. Notably, p53 is known to regulate fibroblast proliferation and fibrosis in pressure-overload-induced hypertrophy. In p53 KO mice, early disease progression is characterized by excessive cardiac fibroblast proliferation, followed by cell-cycle arrest and extensive ECM remodeling over time [[238]81]. In our study, bioinformatics analysis revealed increased p53 signaling in WT diabetic mice compared to WT non-diabetic controls. Given previous findings, we hypothesize that at this stage of diabetes (18 weeks post-STZ), heightened p53 signaling may be linked to the upregulation of ECM proteins secreted by fibroblasts rather than fibroblast proliferation, contributing to myocardial stiffness and contractile dysfunction. In contrast, TNC-KO diabetic mice exhibited significantly lower p53 signaling than WT diabetic mice. These findings suggest that TNC may have a maladaptive role in the progression of diabetic cardiomyopathy and fibrosis. However, further studies are necessary to determine whether p53 signaling alterations in activated fibroblasts influence disease progression and whether TNC modulates cardiac fibroblast phenotypes in diabetes. In addition, transcription factor activity analysis in TNC-KO diabetic heart showed decreased activity of Rxra, Smad1, Smad3, Dlx2, Ppara, and Foxo3. These transcription factors are associated with lipid metabolism, energy homeostasis, and ECM remodeling [[239]82]. Importantly, Ccn2 encodes connective tissue growth factor (CTGF), and its expression was significantly downregulated in the hearts of TNC-KO diabetic mice compared to WT diabetic mice. Ccn2 is a key pro-fibrotic molecule disrupted in various forms of cardiomyopathy [[240]83] and it was a strong activator of ECM proteins, including TNC in cardiomyocytes [[241]84]. The significant downregulation of Ccn2 in TNC-KO diabetic hearts aligns with the observed reduction in cardiac fibrosis. In diabetes, increased cardiac fatty acid oxidation contributes to contractile dysfunction by suppressing glucose oxidation and reducing cardiac efficiency. The upregulation of Cpt1a and Slc27a1, regulated by Ppara, plays a key role in this metabolic shift, promoting cardiomyocyte apoptosis and impairing myocardial contractility. Notably, Cpt1a and Slc27a1 were downregulated in TNC-KO diabetic hearts, correlating with improved myocardial efficiency and attenuated contractile dysfunction. Finally, to complete our understanding of the translational and clinical relevance of our findings, circulating levels of TNC were assessed in patients. Importantly, TNC levels were elevated in HFrEF patients independent of the presence of diabetes. Our findings are consistent with previous studies which have demonstrated a correlation between elevated circulating TNC levels and worse clinical outcomes in various etiologies of HF [[242]85, [243]86]. However, whether TNC shows different expression patterns in cardiac tissue among ischemic, dilated, and DCM is still largely unknown. Indeed, in a recent intriguing study, Yokokawa et al. demonstrated the cardiac overexpression of TNC in HF and diabetes [[244]21]. In our patient cohorts, we did not have access to collect endocardial biopsy in order to assess the expression of TNC in the myocardium. However, we may anticipate a higher expression of TNC in diabetes, since we found an upregulation of TNC in diabetic mouse hearts. Collectively, elevated plasma TNC levels may be a potential biomarker for cardiac fibrosis and cardiomyopathy, but further research is needed to understand its prognostic value for all-cause mortality and major adverse cardiovascular events in DCM. Limitations The most important limitations in terms of translatability to humans include that our type 1 diabetes mellitus (T1DM) model was induced by repeated STZ injections, which could potentially influence all findings and limit drawing conclusions on the effects of hyperglycemia with respect to T2DM. The pathomechanism of cardiomyopathy observed in a T1DM animal model may not resemble and match those playing a role in T2DM disease. Next, our study included solely male animals, whereas sex plays an extremely important role in cardiovascular outcome. Additional limitation of this study is the use of bulk RNA-seq on whole heart tissue, which may obscure cell type–specific transcriptional changes. Future application of single-cell or single-nucleus RNA-sequencing approaches could offer deeper insights into the cellular and molecular heterogeneity underlying the observed effect. Bioinformatics analysis demonstrated the significance of TNC in cardiac metabolism, apoptosis and fibrosis. However, we did not analyze the changes of the above-mentioned transcriptional factors, metabolite and lipids in the myocardium. These are beyond the scope of our investigations. One key limitation of our study is that transcriptomic analysis was performed at a single time point, 18 weeks after STZ injection. It cannot be ruled out that different time points might yield distinct results, which is important to emphasize. Future studies should consider temporal changes in gene expression to provide a more comprehensive understanding of disease progression. Nevertheless, additional studies are required to further elucidate our findings. Conclusion In this study, we present the first evidence of TNC’s role in causing DCM and vascular dysfunction in a mouse model of STZ-induced diabetes. Mechanistically, TNC may contribute to adverse LV remodeling and vascular dysfunction through interconnected pathways, including myocardial fibrosis, inflammation, and metabolic dysfunction. Thus, targeting TNC may provide a new therapeutic approach to prevent and alleviate DCM development, potentially enhancing cardiac function and improving patient outcomes. Supplementary Information [245]12933_2025_2780_MOESM1_ESM.pdf^ (652.9KB, pdf) Supplemental Material 1. Table 1 List of primers. Table 2– Baseline echocardiographic measurements. Figure 1– Blood sugar measurements. Figure 2– Body weight results after diabetes induction. Figure 3– Cardiac expression of TNC. Figure 4– ACE activity in lung and kidney tissue, MDA levels [246]12933_2025_2780_MOESM2_ESM.pdf^ (295.8KB, pdf) Supplemental Material 2. Supplemental Methods Acknowledgements