GABAenergetic-ICNS axis targeting medicine and application thereof in preparation of medicine for autonomic disorder and dilated cardiomyopathy

Abstract

The invention provides a drug targeting a GABA energy-ICNS axis and application of the drug in preparation of drugs for autonomic nervous disorder and dilated cardiomyopathy, and belongs to the field of medicine. The drug for targeting the GABA energy-ICNS axis comprises a preparation for inhibiting GABRB1 up-regulation and / or a preparation for inhibiting GABRB1 hyperglycosylation. The study determines that GABRB1 is a core driving factor for nerve-cardiac-metabolic dysfunction in DCM. The up-regulation of the transcriptional level and the destruction of the glycolytic pathway aggravate the pathological process, and the targeted knock-down carried out for the gene rescues the heart phenotype. The N-glycosylation enhancement of the GABRB1 further highlights the post-translational regulation disorder, and provides a new treatment direction for recovering the nervous autonomic nerves and metabolic homeostasis in the DCM.

Description

Technical Field

[0001] The present invention relates to the field of medicine, and in particular to a drug targeting the GABAergic-ICNS axis and application thereof in preparing drugs for autonomic nervous system disorders and dilated cardiomyopathy. Background Art

[0002] The brain-heart axis, a complex network of interacting neural, mechanical, and biochemical pathways, plays a key role in maintaining cardiovascular homeostasis. Within these pathways, neural components mediated by the autonomic nervous system (ANS) and central autonomic network (CAN) are crucial for regulating cardiac function, including contractility, rhythm, and vascular tone. Dysregulation of autonomic signaling has been associated with a variety of cardiovascular diseases, including dysautonomia and dilated cardiomyopathy (DCM), characterized by impaired ventricular dilation and systolic function. Emerging evidence suggests that neuro-cardiac imbalance, particularly in inhibitory neuromodulatory systems, may be involved in the pathogenesis of DCM.

[0003] The GABAergic system is the main inhibitory neurotransmitter network in the central and peripheral nervous systems and is essential for regulating autonomic nerve outflow. Gamma-aminobutyric acid (GABA) is a classic inhibitory neurotransmitter. [1] In vivo, GABA is generated by the decarboxylation of glutamate catalyzed by glutamate decarboxylase (GAD). GABA can exert its effects by binding to its ionotropic receptor, gamma-aminobutyric acid type A receptor (GABAAR), or its metabotropic receptor, gamma-aminobutyric acid type B receptor (GABABR). [2,3] Extracellular GABA can be rapidly taken up by the GABA transporter (gamma-aminobutyric acid transporter, GAT), and ultimately degraded by the GABA transaminase (gamma-aminobutyric acid transaminase, GABA-T). GABA, its receptors, and metabolism-related proteins are collectively referred to as the GABA signaling system. [4These receptors are crucial for finely regulating neuronal excitability and maintaining sympathetic-vagal balance. Recent studies have highlighted that perturbations in GABAergic signaling may disrupt autonomic regulation. [5] , leading to excessive sympathetic activation or insufficient parasympathetic tone—both hallmark features of DCM progression.

[0004] Therefore, the development of new drugs for autonomic nervous system disorders and dilated cardiomyopathy has become an urgent need. Summary of the Invention

[0005] The present invention is made to solve the above problems, and aims to provide a drug targeting the GABAergic-ICNS axis and its use in the preparation of drugs for autonomic nervous system disorders and dilated cardiomyopathy.

[0006] The present invention provides a drug targeting the GABAergic-ICNS axis, which has the following characteristics: a preparation for inhibiting upregulation of GABRB1 and / or a preparation for inhibiting hyperglycosylation of GABRB1.

[0007] The drug targeting the GABAergic-ICNS axis provided by the present invention may also have the following characteristics: wherein, the preparation that inhibits the upregulation of GABRB1 includes a pharmacological preparation that regulates GABA-A receptor activity and / or a recombinant adeno-associated virus serotype 9 carrying GABRB1 of the cardiac troponin T promoter.

[0008] The drug targeting the GABAergic-ICNS axis provided by the present invention may also have the following feature: the agent for inhibiting the hyperglycosylation of GABRB1 includes an α-mannosidase inhibitor.

[0009] The drug targeting the GABAergic-ICNS axis provided by the present invention may also have the following characteristics: wherein the α-mannosidase inhibitor includes Kifunensine.

[0010] The present invention also provides the use of the above-mentioned drug targeting the GABAergic-ICNS axis in the preparation of drugs for autonomic nervous system disorders and dilated cardiomyopathy.

[0011] In the use of the drug targeting the GABAergic-ICNS axis provided by the present invention in the preparation of drugs for autonomic nervous system disorders and dilated cardiomyopathy, the drug may also have the following characteristics: the pharmacological preparation that regulates the activity of the GABA-A receptor can restore the autonomic nervous system balance; the injection of the recombinant adeno-associated virus serotype 9 carrying the GABRB1 of the cardiac troponin T promoter can alleviate ventricular dilation and systolic dysfunction; the neuromodulation strategy can synergize with the GABAergic intervention to enhance the parasympathetic nerve tone and inhibit the excessive activation of the sympathetic nerve.

[0012] Functions and effects of the invention

[0013] According to the present invention, a drug targeting the GABAergic-ICNS axis and its use in the preparation of a drug for autonomic dysfunction and dilated cardiomyopathy (DCM) revealed the presence of a GABAergic nervous system in left ventricular myocardial tissue through comprehensive multi-omics analysis, including single-cell RNA sequencing, ATAC-seq, and spatial transcriptomics. Furthermore, GABRB1 expression was upregulated in cardiomyocytes of DCM hearts, and its chromatin accessibility profile was enriched for transcription factors that regulate GABRB1. Cell-cell interaction analysis highlighted communication between cardiomyocytes and neurons, further suggesting the existence of a neuro-cardiac regulatory axis. Tissue staining experiments confirmed elevated GABRB1 protein levels in DCM tissues. GABRB1 expression was significantly increased in both in vitro and in vivo DOX-induced DCM models. Therapeutic intervention in DCM mice by tail vein injection of a recombinant adeno-associated virus serotype 9 (AAV9-cTNT-shRNA-GABRB1) carrying the cardiac troponin T promoter reduced ventricular dilation and systolic dysfunction, thereby rescuing the DCM phenotype. Mechanistically, dysregulation of the glycolytic pathway is associated with GABRB1-mediated disease progression, and enhanced N-glycosylation of GABRB1 in DCM suggests that its post-translational modification is involved in the pathophysiology of DCM. These findings position GABRB1 as a core mediator of neuro-cardiac crosstalk and metabolic reprogramming in the pathogenesis of DCM.

[0014] This study identifies GABRB1 as a core driver of neuro-cardio-metabolic dysfunction in DCM. Transcriptional upregulation and glycolytic pathway disruption exacerbate pathological progression, while targeted knockdown rescues the cardiac phenotype. Enhanced N-glycosylation of GABRB1 further highlights post-translational dysregulation and suggests a novel therapeutic approach to restore neuro-autonomic and metabolic homeostasis in DCM. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 This is a diagram showing the comprehensive analysis results of the composition of adult heart cells in an embodiment of the present invention;

[0016] Figure 2 is a result diagram showing whether the sample in the embodiment of the present invention meets the strict quality control standards;

[0017] Figure 3 is a diagram showing the results of an intercellular communication analysis in an embodiment of the present invention;

[0018] Figure 4 This is a diagram of ATAC-seq analysis results in an embodiment of the present invention;

[0019] Figure 51 is a diagram showing the distribution of three transcription factors in an embodiment of the present invention;

[0020] Figure 6 This is a sample difference accessible area result diagram in an embodiment of the present invention;

[0021] Figure 7 is a diagram showing the results of myocardial cell population analysis in an embodiment of the present invention;

[0022] Figure 8 is a graph showing the results of spatial transcriptome analysis of myocardium in an embodiment of the present invention;

[0023] Figure 9 2. This is a graph showing the results of a test for the presence of the neurotransmitter GABA in left ventricular tissue according to an embodiment of the present invention;

[0024] Figure 10 This is a graph showing the results of immunofluorescence evaluation of cell purity in an embodiment of the present invention;

[0025] Figure 11 Flow cytometry, immunofluorescence, and enzyme activity results are shown in the examples of the present invention;

[0026] Figure 12 1. This is a diagram of mouse ultrasound and staining results in an embodiment of the present invention;

[0027] Figure 13 is a graph showing the expression results of GABRB1 after transfection with AAV9-cTNT-shRNA-GABRB1 in an embodiment of the present invention;

[0028] Figure 14 This is a diagram of the ultrasound and staining results of mice after transfection with AAV9-cTNT-shRNA-GABRB1 in an embodiment of the present invention;

[0029] Figure 15 This is a diagram showing the interaction between the transcription factor protein sequence and the GABRB1 promoter region in an embodiment of the present invention;

[0030] Figure 16 This is a diagram showing the results of glycoproteomics research in an embodiment of the present invention;

[0031] Figure 17 1 is a diagram of the ultrasonic cardiology and staining results of mice after kifunensine treatment in an embodiment of the present invention. DETAILED DESCRIPTION

[0032] In order to make the technical means, creative features, objectives and effects achieved by the present invention easier to understand, the following examples, combined with the accompanying drawings, specifically illustrate a drug targeting the GABAergic-ICNS axis of the present invention and its use in the preparation of drugs for autonomic nervous system disorders and dilated cardiomyopathy.

[0033] Example

[0034] 1. Experimental Methods

[0035] 1. Materials and Methods

[0036] This study was conducted in the Department of Cardiovascular Surgery, Changhai Hospital Affiliated to Naval Medical University. Researchers performed heart transplantation on 63 patients with end-stage heart failure between January 2021 and December 2022. Left ventricular samples were collected from 3 patients with DCM during the operation, and 3 donor left ventricular samples were obtained as a control group. The obtained tissue samples were immediately rinsed with sterile saline to eliminate potential contaminants, and histopathological analysis confirmed that the epicardium, ventricular myocytes and endocardial structures were intact. The samples were stored in pre-cooled MACS tissue storage solution (4°C) to facilitate subsequent analysis. This study was approved by the Ethics Committee of Changhai Hospital Affiliated to Naval Medical University (CHEC2024-051) and strictly implemented the principles of the Declaration of Helsinki. Written informed consent was obtained from all participants before sample collection, and no financial compensation was provided.

[0037] 2. Animal Research and Ethics

[0038] Animal experiments followed the Guide for the Care and Use of Laboratory Animals (NIH Bulletin 85-23, revised 1996) and were approved by the Animal Ethics Committee of Changhai Hospital (CHEC2024-397). Male C57BL / 6 mice were purchased from Shanghai Jiesijie Laboratory Animal Co., Ltd. and maintained in an SPF-grade environment at the Changhai Hospital Laboratory Animal Center.

[0039] Viral vector construction and injection: Anesthesia (50 mg / kg) and euthanasia (200 mg / kg) were performed by intraperitoneal injection of sodium pentobarbital. GABRB1 and GFP genes were cloned into vector 2494 (PGMLV-HU6-MCS-CMV-ZsGreen1-PGK-Puro, Shanghai Jiman Biotechnology Co., Ltd.) and packaged into AAV9 viral vectors carrying the cardiac troponin T (cTnT) promoter (control vector: GPAAV-Gallus cTNT-5'miR30-scramble-3'miR30-CW3SL; GABRB1 overexpression vector: GPAAV-Gallus cTNT-5'miR30-M_GABRB1-3'miR30-CW3SL). After anesthesia, the virus suspension (7.5×10 11 vg / ml, 200 μl / animal). Two weeks after the injection, the animals were randomly divided into a control group and a DOX group, and the experiment was performed in a blinded manner.

[0040] Cardiac function assessment: Body weight was recorded at week 5, and M-mode ultrasound was performed on the short-axis section at the level of the parasternal papillary muscle to measure the left ventricular end-diastolic dimension (LVEDD) and end-systolic dimension (LVESD). The following calculations were performed: left ventricular fractional shortening (FS) = (LVEDD-LVESD) / LVEDD × 100%; ejection fraction (EF) = (LVEDD 3 -LVESD 3 ) / LVEDD 3 × 100%. After the test, the animals were euthanized and heart samples and other organ specimens were obtained.

[0041] 3. Histological Staining

[0042] 3.1 HE staining

[0043] 1) Dewaxing and Rehydration: Bake the sections to be stained on a baking sheet at 70°C for approximately 30 minutes to fully evaporate the moisture. Simultaneously, heat a water bath containing glass jars of xylene I and xylene II to 65°C. After sufficient baking, place the slides in a slide rack and dewax them in xylene I and then xylene II for 10 minutes each. Dehydrate the sections by immersing them in a gradient of alcohols: ethanol I, ethanol II, 95% ethanol, 85% ethanol, and 75% ethanol for 3 minutes each. Rinse with PBS. 2) Staining: Use a paper piece approximately the same size as the staining jar to remove any oxides from the surface of the hematoxylin stain. Place the dewaxed and hydrated valve sections in a hematoxylin staining jar for approximately 10 minutes, then rinse with PBS. Place the sections in a dilute hydrochloric acid staining jar for 5 seconds, then rinse with PBS. Place the sections in a lithium carbonate solution to blue the nuclei for 5 seconds, then rinse with PBS. Place the sections in an eosin staining jar for 5 minutes to stain the cytoplasm. Dehydrate the sections in 70% and 90% alcohol for 3 minutes each, then blow dry. 3) Mounting and Microscopic Observation: Apply a drop of neutral resin to the surface of the stained valve sections, seal with a coverslip, and observe under a microscope. Hematoxylin stains the nuclei a bright blue, while eosin stains the cytoplasm in varying shades of pink.

[0044] 3.2 Immunohistochemical staining

[0045] 1) Antigen retrieval: Add 50 μL of 0.25% trypsin to the dewaxed and hydrated valve sections, ensuring that the valve tissue on the sections is completely covered. Then transfer the section box to a 37°C incubator and incubate for 30 minutes. After antigen retrieval, wash three times with PBS for 5 minutes each. 2) Block endogenous peroxidase: Add 50 μL of reagent A (endogenous peroxidase blocker) to each section, incubate at room temperature in the dark for 30 minutes, then shake off reagent A. Rinse with PBS three times for 5 minutes each.) Serum blocking: After rinsing with PBS, add 50 μL of reagent B (non-specific staining blocker) to cover all valve tissue. Block at room temperature in the dark for 30 minutes, then shake off reagent B. Note that PBS is not required for rinsing in this step. 4) Primary antibody incubation: The primary antibody solution is an antibody to the target protein. Prepare the primary antibody solution of the corresponding concentration according to the instructions. Add the primary antibody solution until it covers all valve tissues. Place the slices in a humidified chamber at 4°C in a dark refrigerator overnight. The next day, take out the slices and let them stand at room temperature in the dark for 30 minutes, then shake off the primary antibody solution and rinse with PBS three times, each for 5 minutes. 5) Secondary antibody binding: After rinsing with PBS, add 50 μL of reagent C (biotin-labeled goat anti-mouse / rabbit IgG polymer), incubate at room temperature for 30 minutes, shake off reagent C, and rinse with PBS three times, each for 5 minutes. 6) Biotin labeling: After rinsing with PBS, add 50 μL of reagent D (streptavidin-peroxidase), incubate at room temperature for 30 minutes, shake off reagent D, and rinse with PBS three times, each for 5 minutes. 7) DAB staining: Prepare the DAB colorimetric reagent according to the immunohistochemistry kit instructions in advance. Gently shake off the PBS liquid on the valve slices and add DAB colorimetric solution dropwise until the valve tissue is completely covered. Observe the state of the slices under a microscope, mainly observing whether the tissue appears brown. Avoid prolonged staining time, which may lead to false positive staining results. After observing a positive staining result, immediately wash off the residual DAB dye with PBS. 8) Nuclear staining: Place the DAB-stained slices in a hematoxylin staining jar for 5 minutes, then rinse with PBS buffer for approximately 3 minutes until there is no hematoxylin purple staining on the surface of the slices. 9) After differentiation and blueing, seal the slices and observe under a microscope.

[0046] 3.3Masson staining

[0047] 1) Bake paraffin sections at 70°C for 20 minutes. 2) Immerse in xylene I and xylene II for 10 minutes each, until completely deparaffinized. 3) Immerse sections in anhydrous ethanol, 95% ethanol, 80% ethanol, and 70% ethanol, sequentially for 3 minutes each, and finally immerse in deionized water for 3 minutes to completely hydrate. 4) Apply Weigert's iron hematoxylin stain dropwise to cover the sections for 5 minutes. 5) Remove excess stain with distilled water, add acidic ethanol differentiation solution dropwise for 10 seconds, and rinse with distilled water for 30 seconds. 6) Apply Masson's bluing solution for 3 minutes, and rinse with distilled water for 30 seconds. 7) Stain with Lichunhong Fuchsin solution for 5 minutes. 8) Pour off excess liquid, add phosphomolybdic acid solution dropwise for 1 minute, and rinse with weak acid working solution for 30 seconds. 9) Pour off excess liquid, add aniline blue stain dropwise for 1 minute, and rinse with weak acid working solution for 30 seconds. 10) Rapidly dehydrate with 95% ethanol for a few seconds, then dehydrate twice with anhydrous ethanol for a few seconds each time. 11) Clear the slides twice with xylene for 1 minute each time. 12) Add a drop of neutral resin to seal the slides and observe the staining results under a microscope.

[0048] 3.4 Sirius red staining

[0049] 1) Place paraffin sections on a slide oven at 70°C for 20 minutes. 2) Soak sections in xylene I and xylene II for 10 minutes each, until dewax is complete. 3) Soak sections in anhydrous ethanol, 95% ethanol, 80% ethanol, and 70% ethanol, sequentially for 3 minutes each, followed by a 3-minute soak in deionized water to complete hydration. 4) Soak sections in 0.2% phosphomolybdic acid solution for 2 minutes, then add 0.1% picric acid picrosirius red stain dropwise to the sections and stain for 8 minutes. 5) After aspirating the picrosirius red stain, soak sections in dilute hydrochloric acid for 10 seconds. 6) Soak sections in 70% ethanol, 95% ethanol, anhydrous ethanol, and xylene, sequentially for 2 minutes each, to complete the gradient dehydration process. 7) After aspirating excess solution, mount the sections with neutral resin and observe the staining under a microscope.

[0050] 4. Enzyme-linked immunosorbent assay (ELISA)

[0051] 1) Collect blood samples from each group into anticoagulant tubes and centrifuge at 3000 rpm for 10 minutes. Pipette the plasma into a clean EP tube. Be careful not to disturb the sediment. 2) Dilute the standard sample with standard diluent to prepare a concentration gradient: 15 ng / ml, 10 ng / ml, 5 ng / ml, 2.5 ng / ml, and 1.25 ng / ml. Set up two replicate wells for each gradient, with a final volume of 50 μl per well. 3) Add 40 μl of sample diluent to each well of the ELISA plate, followed by 10 μl of sample. Also set up a blank control well. 4) Cover the plate with a sealing film and incubate on a shaker at 37°C for 30 minutes. 5) Dilute the concentrated wash solution to the working concentration with distilled water. 6) Remove the sealing film and carefully aspirate the liquid from the plate. Invert the plate to dry. Then, top up the plate with wash solution, let it sit for 30 seconds, and then aspirate. Repeat this step five times. Finally, pat the plate dry. 7) Add enzyme-labeled antibody to the bottom of the enzyme-labeled wells, 50 μl per well, and leave blank wells untouched. 8) Cover the plate with sealing film again and incubate on a shaker at 37°C for 30 minutes. 9) Wash again with washing solution 5 times. 10) Add color developer to each well, gently shake to mix, and then incubate in a dark environment at 38°C for 15 minutes. 11) Add 50 μL of stop solution to each well to stop the reaction. When the stop solution is added, the liquid turns from blue to yellow. 12) Measure the absorbance of each well using a photometer at a wavelength of 450 nm. 13) Fit a standard regression curve based on the concentration and absorbance of the standard. Substitute the absorbance value of the sample into the standard regression curve to calculate the concentration of the sample. Finally, multiply the sample concentration by 5 to obtain the final protein concentration in the sample.

[0052] 5. Isolation, Culture, and Treatment of Neonatal Rat Cardiomyocytes (NRCMs)

[0053] 1) After decapitation within 3 days of birth, the baby mice were sterilized with 75% ethanol. 2) The left side of the sternum was opened, and the skin and ribs were quickly cut longitudinally. The heart was squeezed out, and after removing the blood vessels and blood, it was placed in a cell culture dish containing PBS. 3) Using microtweezers, the heart was cut into 1mm pieces. 3Square size. 4) After adding an excess of 0.2% type II collagenase for 15 minutes of digestion, transfer the upper liquid to a new centrifuge tube and add the same volume of DMEM complete culture medium containing 10% FBS to stop the digestion process. 5) Repeat the above digestion step 4) until the myocardial tissue is completely digested. 6) Centrifuge the collected cell suspension at 1200rpm for 5 minutes. 7) After removing the supernatant, the cell pellet is the cardiomyocytes and fibroblasts, and the cell pellet is resuspended in complete culture medium. 8) Use a cell sieve to filter the obtained cell fluid and inoculate it into a cell culture dish. After standing in a 5% CO2 cell incubator for 90 minutes, gently aspirate the culture medium, which contains the required cardiomyocytes, and the cells attached to the bottom of the cell culture dish are fibroblasts. 9) Inoculate the cardiomyocyte suspension into a new cell culture dish, change the medium after 3 days, and proceed to the next experiment.

[0054] 6. Flow Cytometry

[0055] Flow cytometry was used to examine changes in GABRB1 expression in mouse primary cardiomyocytes following DOX treatment. After rinsing cells three times with PBS, they were trypsinized and fixed with 80% methanol for 5 minutes. To obtain a single-cell suspension, cells were filtered through a 70 μm cell strainer to remove cell clumps and treated with permeabilization buffer (containing 0.1% Triton X-100) for 15 minutes. Subsequently, the obtained cells were incubated with FSC-A-labeled anti-cardiac troponin T antibody (Santa Cruz Biotechnology, sc-166408) and FITC-labeled anti-GABRB1 antibody (Miltenyi, ab314676) for 30 minutes at room temperature in the dark. Finally, the stained cells were analyzed using a CytoFLEXTM flow cytometer (Beckman Coulter), and the data were analyzed using FlowJO software (TreeStar, USA).

[0056] 7. Single-cell RNA and single-cell ATAC sequencing analysis

[0057] 7.1 Collection Process

[0058] Multi-omics analysis of cardiac tissue was performed using single-cell RNA sequencing and single-cell ATAC sequencing data. The removed myocardial tissue was washed three times with cold Dulbecco's phosphate-buffered saline (PBS) (Gibco) to prepare a single-cell suspension. The finely minced tissue was mixed with digestion buffer (Dulbecco's modified Eagle's medium (DMEM) (1.5 mL), trypsin (0.5 mL), 0.9 U tissue protease (0.5 mL), and 2 mg / mL collagenase I and II (1 mL each)) preheated to 37°C and gently shaken on a 37°C metal heater for 15 minutes. Subsequently, a sample (10 μL) was transferred to a hemocytometer for observation. The suspension was filtered through a 70 μm mesh filter. The filter was washed with 5 mL of DMEM. The cells were concentrated by centrifugation (500g, 4°C, 5 minutes). After discarding the supernatant, the cell pellet was mixed with lysis buffer (10 mM Tris-HCl, 10 mM NaCl, 3 mM MgCl2, and 0.1% Nonidet TM The samples were mixed by pipetting, vortexed, and incubated on ice for 10 min before centrifugation. The nuclei were then resuspended in 50–100 μL of DMEM containing 10% PBS. The nuclear density was adjusted to 700–1200 nuclei / μL before loading the nuclei onto the 10x Genomics Chromium system. Gel bead emulsions were prepared for reverse transcription and barcoding. Complementary DNA was recovered and libraries were constructed using the ChromiumNext GEM Single Cell Multi-Omics ATAC+ Gene Expression Kit (10x Genomics, Pleasanton, CA, USA). Finally, the libraries were sequenced using the Illumina NovaSeq platform.

[0059] 7.2 Single-cell data processing and annotation

[0060] Clean reads were aligned to the UCSC human GRCh38 reference genome using Cell Ranger (version 4.0.0). Quality control and data integration were performed using Seurat (version 4.3.0.1) and R (version 4.2.0), respectively. Data from cells with <300 or >8000 genes, total counts >50,000, or a mitochondrial gene fraction >10% were excluded. Data normalization and variable feature selection were performed using the "NormalizeData" and "FindVariableFeatures" functions, respectively, and data scaling was performed using "ScaleData." Dimensionality reduction was achieved using principal component analysis, followed by Harmony-based integration. Visualization was performed using uniform manifold approximation and projection techniques, and clustering was performed using the "FindClusters" function at a resolution of 0.6. Cell type annotation was performed using SingleR and validated against canonical marker gene expression. ATAC-seq libraries were constructed and sequenced. Peak identification and chromatin accessibility analysis were performed using ArchR (version 1.0.2). ATAC-seq and scRNA-seq data were integrated through ArchR to match cell type annotations and identify cell type-specific open chromatin regions.

[0061] 7.3 Spatial transcriptome

[0062] Selected samples were analyzed using spatial transcriptomics to visualize gene expression patterns within the tissue context. Slides were prepared according to the manufacturer's protocol and sequenced on the 10xVisium platform. Cell type identification and spatial distribution map construction were performed using CellTrek software.

[0063] Spatial transcriptome analysis was performed on cardiac tissue sections from patients with diabetic comorbidity (DCM) and controls. RNA integrity and spatial context were maintained during sample processing. Data processing and cell name standardization were performed using CellTrek in the R language. Spatial data were then integrated with scRNA-seq data for cell type annotation. A training model was established using "CellTrek::traint" to align highly variable genes with scRNA-seq-annotated cell types. Spatial localization was predicted using "DimPlot" and the optimized "CellTrek::celltrek" function for visualization and cellular localization. Differential gene expression was visually verified using the "VlnPlot" function. Cellular interactions and signaling pathway analysis were performed using "CellTrek::scoloc," and spatial interaction significance was assessed using the Kolmogorov-Smirnov test. Predicted cell type distributions and colocalization patterns were visualized and overlaid onto tissue images using "CellTrek::celltrek_vis." Minimum spanning trees (MSTs) of the interaction graphs and associated metadata were used to analyze the connectivity and distribution of cell types within the spatial arrangement.

[0064] 7.4 Cell Communication Analysis

[0065] CellChat was used to analyze intercellular signaling pathways based on scRNA-seq and scATAC-seq datasets. Neurons and cardiomyocytes were classified based on GABBR1 expression, and network analysis was used to identify changes in signaling pathways and interactions between neurons and cardiomyocytes.

[0066] For cell communication analysis, the CellChatR package was used to quantify and interpret the complex signaling networks across different cell types in cardiac tissue samples. Independent samples from two controls (Control_1 and Control_2) and two patients with diabetic comorbidity (DCM) (DCM_2 and DCM_3) were selected to detect specific and shared signaling patterns. The scRNA-seq dataset was subsetted by patient identifier and cell type, specifying 'RNA' as the analysis type for communication probability calculation, and generating a CellChat object for each sample. This study utilized the comprehensive database "CellChatDB.human," which contains detailed information on known ligand-receptor interactions. After database assignment, the subset data was filtered to focus on relevant cells and interactions.

[0067] Communication probability calculations were used to determine the likelihood of cell-cell interactions, followed by pathway-level analysis. Communication signals were filtered based on a minimum number of cells, and networks were aggregated to analyze the overall signaling landscape. Communication networks were visualized using the "netVisual_circle" function to reveal the number and strength of interactions within a sample. Data from all samples were integrated using "mergeCellChat" to compare interaction patterns and identify sample-specific and shared signaling pathways.

[0068] Perform differential analysis of ligand-receptor pairs across different conditions to identify signaling changes associated with DCM. The "netMappingDEG" function maps differentially expressed genes to the cellular communication network. Subsequent subsetting isolates upregulated interactions in DCM from downregulated interactions in controls, extracting a subset of interaction-related genes for further analysis. "netVisual_bubble" generates a signaling change comparison plot, highlighting upregulated signals in DCM relative to controls. Finally, "netVisual_aggregate" is used to highlight the distribution of signaling activity across cell types for specific targeted pathways (e.g., 'NRG').

[0069] 8. Transcriptome Sequencing Analysis

[0070] Total RNA was isolated from mouse heart tissue using TRIzol reagent and the RNeasy mini kit (QIAGEN). RNA purity and integrity were assessed using a 2100 Bioanalyzer. RNA-seq libraries were constructed using the NEBNext Ultra II Directional RNA Library Preparation Kit (New England Biolabs, MA, USA) and sequenced using an Illumina HiSeq 2500 System for single-end 60-bp sequencing. Library preparation and sequencing were performed by the CNIC Genomics Center.

[0071] FastQ sequencing files were processed and analyzed using the RaNA-seq online tool. An 18-fold corrected t-test was performed using the Limma package to identify differentially expressed genes between groups, and Benjamini-Hochberg correction was applied (P < 0.1). For Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway gene set enrichment analysis, only significant enrichment results with a Benjamini-Hochberg-corrected P value < 0.01 were considered. For heatmap generation, core gene sets were extracted from the selected enriched pathways, annotated with corresponding TPM values, and converted to raw Z scores. Heatmaps were then generated using GraphPad Prism 9.0.

[0072] 9. Glycosylation

[0073] 9.1 Protein enzymatic hydrolysis

[0074] The protein concentration of the supernatant was determined by BCA protein assay, and then 1 mg of protein for each condition was transferred to a new Eppendorf tube and the final volume was adjusted to 200 μL with 8 M urea. 20 μL of 0.5 M TCEP was added, and the sample was incubated at 37°C for 1 hour, followed by the addition of 40 μL of 1 M iodoacetamide and a further incubation of 40 min at room temperature in the dark. Subsequently, five volumes of -20°C pre-cooled acetonitrile were added and the protein was precipitated at -20°C overnight. The precipitate was washed twice with 1 mL of pre-cooled 90% acetonitrile aqueous solution and then redissolved in 1 mL of 100 mM TEAB. Sequence-grade modified trypsin (Promega) was added at a ratio of 1:50 (enzyme: protein, weight: weight) and the protein was digested at 37°C overnight. The peptide mixture was desalted with a C18 ZipTip and lysed using a Pierce TM Quantification was performed using a quantitative colorimetric peptide assay kit (23275) and subsequently lyophilized by SpeedVac.

[0075] 9.2 Glycopeptide Enrichment

[0076] Lyophilized peptides were reconstituted in 80% acetonitrile / 1% TFA and loaded onto an iHouse ZIC-HILIC microcolumn containing 30 mg of HILIC particles (packed with C8 membrane). The flow-through was collected and repeated four times. After washing the column with 80% acetonitrile / 1% TFA, the enriched glycopeptides were eluted sequentially with 0.1% TFA, 25 mM NH₄HCO₃, and 50% acetonitrile. The eluate was dried by vacuum centrifugation.

[0077] 9.3 Nano-liquid chromatography-tandem mass spectrometry

[0078] The peptides were redissolved in 10 μL of solvent A (solvent A: 0.1% formic acid in water) and analyzed by nanospray liquid chromatography-mass spectrometry (LC-MS / MS) using an Orbitrap Fusion Lumos Tribrid (Thermo Scientific, MA, USA) coupled to an EASY-nano-LC 1200 system (Thermo Scientific, MA, USA) without a trapping column. A 3 μL peptide sample was loaded onto a C18 spray tip 15 cm × 75 μm inner diameter column (Acclaim PepMap) and separated at a flow rate of 300 nL / min using an 180 min gradient elution.

[0079] The mass spectrometer was operated in data-dependent acquisition mode and automatically switched between mass spectrometry (MS) and secondary mass spectrometry (MS / MS) modes. The following parameters were used: 1) Mass spectrometry: scan range (mass-to-charge ratio) = 350–2000; resolution = 120,000; automatic gain control (AGC) target = 500,000; maximum injection time = 50 ms; charge states included = 2–6; number of dynamic exclusions, n = 1; dynamic exclusion duration = 15 s; one high-energy collisional dissociation-mass spectrometry (HCD-MS / MS) analysis was performed for each selected precursor ion; 2) HCD-MS / MS: isolation window = 4; detector type = Orbitrap; resolution = 15,000; AGC target = 500,000; maximum injection time = 250 ms; collision energy = 30%; step collision mode was on, with an energy difference of ±10% (calculated as 10% of the absolute value in Orbitrap Fusion).

[0080] 9.4 Database Search

[0081] The original files were processed using Byonic software. The enzyme digestion method was trypsin / P (a maximum of two missed cut sites were allowed).

[0082] Modification types were set as follows: fixed modification was carbamidomethylation of cysteine; variable modifications included methionine oxidation, asparagine / glutamine deamidation, and glycosylation modifications (e.g., N-glycans: N-acetylhexosamine (2) hexose (3-9) fucose (0-2) neuraminic acid (0-2); O-glycans: N-acetylhexosamine (1-3) hexose (1-3) neuraminic acid (0-2)). Mass tolerance parameters were: primary mass spectrometry (10 ppm) and secondary mass spectrometry (20 ppm).

[0083] 10. Statistical Analysis

[0084] Data were analyzed using GraphPad Prism 9 software (GraphPad Software, Inc., California, USA). Unless otherwise stated, all experiments were performed in triplicate. Data are presented as mean ± standard deviation or median ± interquartile range. Data normality was assessed using the Shapiro-Wilk test. For comparisons between two groups, normally distributed data were analyzed with an unpaired two-sided Student's t test, and skewed data were analyzed with the Mann-Whitney test. For comparisons between three or more groups, normally distributed data with homogeneous variance were analyzed with one-way analysis of variance (ANOVA) followed by a Tukey post hoc test; normally distributed data with homogeneous variance and involving multiple factors were analyzed with two-way ANOVA followed by a Bonferroni post hoc test; normally distributed data with unequal variance were analyzed with a one-way ANOVA followed by a Tamhane T2 post hoc test; and skewed data were analyzed with a Kruskal-Wallis test followed by a Dunn post hoc test.

[0085] 2. Experimental results

[0086] 2.1 Comprehensive analysis of adult cardiac cellular composition

[0087] Between January 2021 and December 2022, we performed heart transplantation on 63 patients with end-stage heart failure. After matching the basic clinical information of three healthy heart donors, three patients diagnosed with dilated cardiomyopathy (DCM) after orthotopic heart transplantation were selected as the experimental group. The left ventricular specimens of all six samples were digested under the same conditions to obtain single-cell suspensions for single-cell RNA sequencing (scRNA-seq) analysis ( Figure 1 A, B). One DCM sample (DCM_1) and a control sample (Control_3) did not meet the strict quality control standards set for subsequent analysis ( Figure 2). We collected a total of 55,933 single cells using a platform that enables single-cell visualization, detection, and screening, of which 5,349 cells passed strict quality control and were retained for further analysis. Canonical correlation analysis (CCA) was used to remove potential batch effects or individual differences in sequencing data, and cell classification was performed by shared nearest neighbor (SNN) unsupervised clustering and t-distributed stochastic neighbor embedding (t-SNE). UMAP analysis showed the cell clustering distribution of single-cell transcriptome data of two control samples (Control_1, Control_2) and DCM samples (DCM_2, DCM_3), and divided all cells into 10 categories based on molecular characteristics, including adipocytes, cardiomyocytes, endocardial cells, endothelial cells, fibroblasts, lymphatic cells, macrophages, MKI67+ cells, neurons, and pericytes ( Figure 1 C, D, E). We first performed differential gene expression analysis between the DCM group and the control group in neuronal subpopulations. The annotated differentially expressed genes were as follows Figure 1 F. Notably, the neuronal cells in the DCM group showed global gene expression downregulation, which is consistent with the neuromodulatory dysfunction phenotype observed in dilated cardiomyopathy. However, the gene GABBR1 was significantly upregulated in the disease group ( Figure 1 F, G). To investigate whether GABBR1-expressing neurons play a key role in the pathogenesis of DCM, we subsequently divided neurons into GABBR1-positive and GABBR1-negative subpopulations based on their GABBR1 expression profiles. Intercellular communication analysis focusing on neuron-cardiomyocyte interactions showed that the interaction strength between GABBR1-positive neurons and cardiomyocytes was enhanced compared with the negative subpopulation ( Figure 1 H, Figure 3 These findings suggest that the pathological changes in cardiomyocytes may be related to the regulatory mechanism mediated by GABBR1-positive neural circuits.

[0088] ATAC-seq analysis identifies aberrant gene regulatory regions in dilated cardiomyopathy

[0089] To elucidate the gene regulatory mechanisms in various cell types associated with DCM, ATAC-seq analysis was performed on the same samples. Both the control and DCM groups met the ATAC-seq quality control criteria, but there were systematic differences in the chromatin accessibility profiles between the two groups ( Figure 4 ). Transcription start site (TSS) enrichment score ( Figure 4 A) shows that all samples have values ​​> 2.5, with DCM_3 and Control_2 exceeding the high-quality threshold. Nuclear fragment complexity analysis ( Figure 4B) shows that the log10(nFrags) values ​​range from 3.0 to 5.0. The complexity of DCM is higher than that of the control group, but both meet the baseline quality standard (log10(nFrags)>3.0). Figure 4 CF, K) showed a conservative bimodal pattern in both groups. Figure 4 GJ) shows distribution differences: DCM samples are concentrated in high-quality areas), while the control group is located in low-density areas within an acceptable range. TSS accessibility map ( Figure 4 L) Confirmed the consistent enrichment pattern among the groups (within TSS ± ​​500 bp).

[0090] To maximize the capture of specific regulatory elements, we first defined a set of consistent ATAC-seq peaks for each sample and detected differentially accessible regions between the four samples. The confusionMatrix algorithm was used to generate an inter-cluster confusion matrix for each sample, and the results were visualized in the form of a discriminant heat map. Figure 6 A, Highlights significant differences between normal and DCM samples. Figure 6 B. Use ArchR software to visualize marker genes in the data and draw them based on annotated cell population types. Figure 6 C. Figure 6 C shows a three-dimensional UMAP projection of hierarchical cellular heterogeneity by color coding of sample source (n=4), cluster identity (12 distinct subpopulations), and annotated cell lineage. Computational analysis systematically classified these clusters into five biologically relevant cell populations: cardiomyocytes (n=6597), endothelial cells (n=5085), fibroblasts (n=7381), lymphatic cells (n=3672), and macrophages (n=5895). Figure 6 D shows the detailed statistical results of peak distribution in different genomic regions such as promoters, gene bodies and distal regulatory elements. Figure 6 Heatmaps in E demonstrate cell type-specific peaks, highlighting distinct chromatin accessibility patterns. Figure 6 Motif analysis (F) identified MEF2A, SPIB, and TFAP4 as transcription factors that were differentially expressed between normal and DCM samples. The ridge plot showed that the distribution of these three transcription factors was highly enriched in macrophages, cardiomyocytes, and fibroblasts, respectively ( Figure 5 A). Cardiomyocytes display unique chromatin accessibility peaks overlapping with promoter-proximal regulatory elements, whereas fibroblasts and macrophages exhibit distinct accessibility patterns at distal intergenic regions, suggesting cell-specific transcriptional regulation ( Figure 5 B, C). Figure 6The UMAP plot of G displays ChromVAR deviation scores, highlighting transcription factors and enabling the identification of cell type- and disease state-specific regulatory networks. Figure 6 H revealed the DNA binding pattern of transcription factors through footprint analysis, providing valuable clues for in-depth research on the regulatory mechanisms affecting cardiomyocytes.

[0091] 2.3 Integration of ATAC-seq and single-cell RNA analysis reveals the role of GABRB1-positive cardiomyocytes in dilated cardiomyopathy Role in pathogenesis

[0092] In Results 2.2, we integrated ATAC-seq and single-cell RNA sequencing data to reveal differences in chromatin accessibility in cardiomyocytes during DCM. To analyze cardiomyocyte-related changes during DCM pathogenesis, we further analyzed cardiomyocyte populations.

[0093] like Figure 7 A volcano plot of single-cell analysis highlights differential gene expression in cardiomyocytes, with GABRB1 being particularly notable for its upregulation in DCM, highlighting its potential role in disease pathology. Figure 7 In B and C, we performed GO and KEGG pathway analyses to identify relevant biological processes and pathways. These analyses showed that biological processes and signaling pathways related to myocardial and cardiomyocyte contraction were significantly enriched, such as the “muscle system process” in GO and the “cardiac contraction” in KEGG.

[0094] We further divided the cardiomyocyte subpopulations into GABRB1-expressing and GABRB1-non-expressing phenotypes. After computational alignment of single-cell chromatin accessibility (scATAC-seq) and transcriptome (scRNA-seq) datasets using the addGeneIntegrationMatrix algorithm (v2.1.0; ArchR software package), multimodal dimensionality reduction was performed to generate Figure 7 The unified UMAP projection in D was used. The chromatin accessibility landscape was systematically explored by specifying the PeakMatrix mode and performing peak identification using addMarkerFeatures (ArchR v1.0.3). To account for technical variation between cellular compartments, we performed quality-aware differential analysis by incorporating bias correction parameters for TSS enrichment scores and unique nuclear fragment counts. Subsequently, cell-state-specific regulatory elements were visualized as clustered chromatin accessibility heatmaps ( Figure 7 E).

[0095] After confirming that the GABRB1 gene is located within an open chromatin region, we performed comparative transcriptome analysis of differentially expressed genes in GABRB1-positive and -negative cardiomyocyte populations to assess the relative activity of signaling pathways. Notably, pathways related to cell contraction showed more significant differences, with key regulatory factors such as VEGF and NCAM being upregulated in DCM, suggesting that they may play a role in disease pathogenesis ( Figure 7 F). Subsequent comparative analysis of signaling pathway activation revealed that GABRB1-positive cardiomyocytes in the DCM cohort had significantly increased activity in pathways related to cell signaling. These findings suggest that GABRB1-positive cardiomyocytes play a key role in the pathophysiological processes that drive the progression of DCM ( Figure 7 G). Figure 7 H depicts the intercellular interactions between GABRB1-positive cardiomyocyte subpopulations and neighboring cell types. Quantitative analysis showed that bidirectional signaling pathways were significantly enriched, mainly involving neurons and fibroblasts, suggesting that they may coordinate microenvironmental interactions during cardiac remodeling ( Figure 7 H). Figure 7 K shows a heat map of signaling pathways in the intercellular communication network between GABRB1-positive cardiomyocyte subpopulations and neighboring cells in normal and DCM tissues. Functional enrichment analysis showed that GABRB1-positive cells in DCM exhibited a unique pathway activation profile, significantly involving VEGFA-mediated angiogenic signaling and NCAM1-driven neuronal adhesion mechanisms ( Figure 7 I and J), whereas the interactions in GABRB1-negative cells remained associated with baseline homeostatic pathways.

[0096] These findings suggest that GABRB1-positive cardiomyocytes interact with other cell types through multiple signaling pathways, highlighting the critical involvement of GABRB1 in DCM pathology.

[0097] 2.4GABRB1 expression is significantly upregulated in cardiomyocytes of the dilated cardiomyopathy group

[0098] To elucidate the spatial distribution of various cell types within myocardial tissue and analyze their interaction networks, we performed spatial transcriptome sequencing analysis on three samples. This approach enables us to track changes in gene expression at different stages of heart disease, thereby identifying key drivers in the transition from compensatory hypertrophy to pathological cardiac dilatation and revealing the complex intercellular signaling pathways involved in cardiac remodeling. We performed spatial transcriptome analysis on the left ventricular myocardium of one normal and two DCM patients. After dimensionality reduction and clustering, we annotated 10 different cell populations based on marker genes, such as Figure 8AI is shown. To identify intercellular signaling events that may be involved in myocardial cell pathology in the heart, we used NicheNet to detect ligand-receptor signaling events that are enriched in diseased states compared to healthy donors. The corresponding network diagram of the cell population interactions in these specimens is shown in Figure 8 As shown by JL, we focused on the strength of the signals received by cardiomyocytes from neurons. By quantitatively mapping the flux of targeted signals from innervated cardiomyocytes using single-cell ligand-receptor topology analysis, we found that cardiomyocytes interact more strongly with neurons in DCM tissue.

[0099] like Figure 8 As shown in M, N, and O, three-dimensional histochemical imaging and optical clearing were performed on the left ventricular tissue of the dilated cardiomyopathy specimen to depict the spatial topology of the neural network within the myocardial structure. This method revealed a unique sympathetic nerve structure (anti-TH, green) and GABAergic neural network (anti-GABA, red). Histopathological analysis showed that the GABAergic neural network was precisely located within the myocardial parenchyma, confirming the presence of GABAergic nerves in myocardial tissue. At the same time, the GABAergic neural network in normal left ventricular tissue was stained in the same way for comparative analysis, as shown in Figure 2. Figure 8 P, Q, R, and S. The results of three-dimensional optical clearing and staining showed that the distribution of GABAergic neural network in the left ventricular tissue of the control group was relatively sparse.

[0100] Integrated single-cell transcriptomic and chromatin accessibility analyses revealed that GABRB1+ cardiomyocytes are a key pathophysiological determinant of DCM. Spatial transcriptomic analysis revealed enhanced crosstalk between the cardiomyocyte-neuronal microenvironment in the diseased myocardium. Three-dimensional imaging with tissue clearing staining confirmed the structural integration of the GABAergic network within cardiac microarchitecture. These multimodal findings position GABRB1-expressing cardiomyocytes as central regulators of neuro-cardiac axis dysfunction in the pathogenesis of DCM.

[0101] To test this hypothesis, we first confirmed the presence of the neurotransmitter GABA in left ventricular tissue. Enzyme-linked immunosorbent assay (ELISA) was used to detect GABA in left ventricular tissue samples from three normal and three DCM groups. This method allowed us to quantify GABA levels and assess potential differences associated with tissue status. Figure 9 A) The results showed that GABA levels in DCM samples were not statistically different from those in the normal control group. To verify GABRB1 expression and further elucidate the expression site of this receptor in cardiomyocytes, we performed qRT-PCR, Western blotting, and immunohistochemistry (IHC) experiments on myocardial tissue.

[0102] qRT-PCR results showed that the mRNA expression level of GABRB1 in DCM tissues was higher than that in the normal control group ( Figure 9 B). At the same time, Western blot analysis of proteins extracted from left ventricular tissues confirmed that the GABRB1 protein level in DCM tissues was higher than that in the normal control group ( Figure 9 C and D). Immunohistochemistry results also showed that GABRB1 expression was upregulated in the DCM group ( Figure 9 E and F). Notably, cardiac GABRB1 expression was inversely correlated with heart failure severity, as measured by BNP and LVEF levels ( Figure 9 G and H).

[0103] We isolated cardiomyocytes from primary lactating mice and assessed cell purity by immunofluorescence, as Figure 10 All subsequent cell experiments used these primary lactating mouse cardiomyocytes. [6] Neonatal rat ventricular myocytes (NRVMs) were treated with doxorubicin (10 μM) for 24 hours to simulate the DCM phenotype caused by myocardial injury in vivo. Flow cytometric analysis showed that GABRB1+ cardiomyocytes were differentially enriched after exposure to doxorubicin (71.1% vs. control group: 62.1%), as shown in Figure 3. Figure 11 As shown in A and B.

[0104] Immunofluorescence analysis showed that GABRB1 expression was upregulated in adriamycin-treated cardiomyocytes, consistent with human myocardial pathological changes ( Figure 11 C, I). qRT-PCR and WB confirmed that GABRB1 transcription and protein levels were upregulated. Figure 11 As shown in DF.

[0105] Na + / K + β-ATPase is a membrane-bound enzyme system ubiquitously expressed in various tissues that plays a key role in maintaining cellular homeostasis. The enzyme is essential for maintaining the electrochemical gradient, which is crucial for many physiological processes, including ion transport, cell volume regulation, and membrane potential stabilization. 2+ ATPase is another key membrane-bound enzyme that is essential for maintaining intracellular Ca 2+ Na homeostasis is crucial. It plays a fundamental role in regulating cardiac and skeletal muscle contraction, mediating neuronal action potential transmission, and promoting cell secretion and proliferation. Therefore, we evaluated the Na + / K + -ATPase and Ca 2 + -ATPase expression and activity to assess whether cardiomyocytes exhibit phenotypic characteristics of dilated cardiomyopathy ( Figure 11 GH). The results showed that Na+ / K + -ATPase and Ca 2+ -ATPase levels were reduced, confirming the successful establishment of a cell model with a dilated cardiomyopathy phenotype.

[0106] Similarly, we used DOX-induced cardiotoxicity to establish a mouse model with DCM phenotype. [6] (8.0 mg / kg, once a week for 4 weeks), echocardiographic evaluation showed that the DCM group mice showed significant phenotypic changes ( Figure 12 A). Both LVEF and FS of these mice were significantly decreased ( Figure 12 G and H), indicating decreased cardiac output and impaired systolic function. In addition, increased LVEDD and LVESD were observed ( Figure 12 I and J), indicating enlargement of the cardiac chambers. We also assessed cardiac morphology to investigate the effects of DOX on cardiac structural remodeling in mice. We found that DOX exacerbated cardiac dilation and myocardial injury in mice, as reflected by increased heart weight ( Figure 12 KN). In addition, in the DOX-treated group, the left ventricular cross-sectional area increased and fibrosis was aggravated ( Figure 12 BE). Notably, both the transcription and protein levels of GABRB1 were upregulated in the DOX-treated group ( Figure 12 F, O, and P). Immunofluorescence staining further confirmed these findings, showing that GABRB1 expression was higher in left ventricular tissues in the DOX group ( Figure 12 Q).

[0107] 2.5 Cardiac GABRB1 gene knockdown improves cardiac remodeling and dysfunction in dilated cardiomyopathy

[0108] To elucidate the functional role of GABRB1 in the pathogenesis of DCM in vivo, we used a cardiac-specific adeno-associated virus type 9 (AAV9) vector encoding a short hairpin RNA (shRNA) targeting GABRB1 under the control of the cardiac troponin T (cTNT) promoter (AAV9-cTNT-shRNA-GABRB1). This approach allows for myocardial-selective knockdown of GABRB1 expression to investigate its effect on disease progression in a preclinical DCM model. All mice were subsequently housed under DOX-treated conditions for 1 month and underwent echocardiography at week 5. Western blot was used to detect the expression of GABRB1 after transfection with AAV9-cTNT-shRNA-GABRB1 ( Figure 13 B, C).

[0109] Echocardiography showed that the left ventricular ejection fraction (LVEF), fractional shortening (FS), left ventricular end-diastolic dimension (LVEDD), and left ventricular end-systolic dimension (LVESD) of AAV9-shGABRB1 mice were significantly preserved compared with AAV9-Null mice ( Figure 14 A, JM). In addition, the heart weight (HW), heart weight / body weight ratio (HW / BW), lung weight / body weight ratio (LW / BW), and heart weight / tibia length ratio (HW / TL) of AAV9-shGABRB1 mice were lower than those of the AAV9-Null control group ( Figure 14 NQ). In the DOX model, AAV9-shGABRB1 mice also had smaller cardiomyocyte cross-sectional areas ( Figure 14 BC). In addition, Masson staining and Sirius red staining showed that knockdown of GABRB1 alleviated DOX-induced cardiac fibrosis ( Figure 14 DG). Protein expression of ANP, a gene associated with heart failure, was reduced in GABRB1 knockdown mice ( Figure 14 HI, RS). In conclusion, knockdown of GABRB1 effectively inhibited the progression of DOX-induced heart failure and DCM.

[0110] 2.6 GABRB1 affects the progression of dilated cardiomyopathy through the glucose metabolism pathway

[0111] To elucidate the molecular mechanisms underlying GABRB1 upregulation in DCM and its role in regulating disease progression, we first explored the transcriptional regulatory network. Based on the identification of cardiac-enriched transcription factors (MEF2A, MEF2B, MEF2C, NFIC, and NFIX) by ATAC-seq chromatin accessibility analysis, we hypothesized that increased GABRB1 transcriptional activity in cardiomyocytes might be driven by altered expression of these transcription factors.

[0112] Subsequently, we used AlphaFold 3 (v3.2.0) to model the potential ligand-receptor interactions between these transcription factor protein sequences (ligands) and the GABRB1 promoter region (receptor). Structural predictions showed that all five factors have the ability to bind to the GABRB1 promoter ( Figure 15 A).

[0113] Notably, single-cell RNA sequencing of cardiomyocyte subsets revealed no statistically significant differences in the expression levels of these transcription factors between disease states ( Figure 15 B). To functionally validate these observations, we performed quantitative qRT-PCR and Western blot analysis on human left ventricular tissue specimens (n ​​= 3 per group). Transcriptional and translational assessments confirmed that there was no statistically significant difference in the expression levels of these five factors between the DCM group and the control group ( Figure 15 C, D).

[0114] To explore the protective mechanism of GABRB1 reduction in myocardial tissue, we performed RNA-seq on the heart tissues of control and DOX mice treated with AAV9-Null or AAV9-shGABRB1. Principal component analysis (PCA) was performed using the gmodels package in R language to analyze gene expression data, aiming to facilitate the comparison of samples within and between groups, and to evaluate the repeatability of samples within the group and the variability between different groups. Group A was a control specimen injected with normal saline, Group B was a DOX-treated specimen, and Group C was a DOX+AAV9-shGABRB1-treated specimen. Compared with the control group, 2360 upregulated genes and 2326 downregulated genes were identified in the DOX group ( Figure 15 E, F). Meanwhile, compared with AAV9-Null-treated DOX mice, 3424 genes were upregulated and 1742 genes were downregulated in AAV9-shGABRB1-treated DOX mice ( Figure 15 G, H). Venn diagram showing that 2037 genes were downregulated in DOX hearts from RNA-seq data but upregulated after AAV9-shGABRB1 intervention ( Figure 15 I).

[0115] Subsequently, we performed a systematic KEGG signaling pathway enrichment analysis on the screened differentially expressed gene sets and identified 13 significantly enriched pathways ( Figure 15 The analysis clearly highlighted several key pathways: the neuroactive ligand-receptor interaction pathway was the most significantly enriched pathway for differentially expressed genes, a finding that aligns remarkably with the well-established GABAergic signaling mechanism. The significant enrichment of the calcium signaling pathway was expected, as it is closely associated with remodeling processes such as cardiomyocyte hypertrophy, apoptosis, and impaired excitation-contraction coupling in various cardiomyopathies, including DCM.

[0116] Particularly noteworthy was the enrichment of the glycosaminoglycan degradation pathway. This discovery exceeded our initial expectations and provided a key, unexpected clue. Glycosaminoglycans are core components of the extracellular matrix (e.g., chondroitin sulfate and heparin sulfate). They covalently link with core proteins to form proteoglycans, forming a complex extracellular network that not only provides structural support but also serves as a crucial reservoir of signaling molecules and a signal transduction platform, profoundly influencing processes such as cell adhesion, migration, proliferation, and growth factor signaling.

[0117] This transcriptomic evidence for activation of the glycosaminoglycan degradation pathway suggests that the glycosylation landscape of the extracellular matrix may undergo profound and pathological remodeling in DCM. We speculate that abnormal glycosaminoglycan degradation may not only directly impair the structural integrity of myocardial tissue but also exacerbate myocardial dysfunction and ventricular remodeling by releasing or altering bioactive molecules stored in the matrix (such as growth factors and cytokines) and disrupting intercellular communication that relies on intact glycosaminoglycan chains.

[0118] Therefore, to directly test this hypothesis and gain insights into the true state of glycosylation modifications in DCM, we performed targeted glycosylation sequencing analysis.

[0119] 2.7 Complete glycoproteomic study of dilated cardiomyopathy and normal hearts reveals glycoprotein landscape

[0120] We performed systematic quantitative N-glycosylation sequencing analysis of left ventricular myocardial tissue from patients with DCM and normal donors and identified a disease-associated post-translational modification signature that correlated with a functional severity index.

[0121] We identified a total of 5,642 unique N-glycopeptides corresponding to 4,134 unique N-glycoforms with 222 different N-glycan compositions at 1,590 unique N-glycosylation sites on 774 unique N-glycoproteins ( Figure 16 A, B).

[0122] Next, we assessed disease-associated abundance changes of individual glycoforms by differential glycoform abundance analysis ( Figure 16 C, D, E), and 214 glycoforms were identified. Compared with the control hearts, the glycoform levels of DCM were significantly changed, including increased abundance of 173 glycoforms in 106 glycoproteins and decreased abundance of 41 glycoforms in 36 glycoproteins. Quantitative glycoform analysis showed that the abundance of two specific N-linked glycans was different in DCM tissues ( Figure 16 F), confirming the pathway-level dysregulation observed in the glycosylation-related protein network.

[0123] We found that both hyperglycosylated and hypoglycosylated datasets contained glycoforms and glycoproteins with altered oligomannosylation, fucosylation, and / or sialylation ( Figure 16 GABRB1 protein shows hyperglycosylation of oligomannose moieties in dilated cardiomyopathy ( Figure 16 H).

[0124] We then performed Gene Ontology (GO) enrichment analysis on the hyperglycosylated and hypoglycosylated datasets to elucidate the cellular functions and processes affected by dysregulated N-glycan modifications in DCM ( Figure 16I). The results showed that plasma membrane and extracellular proteins were significantly enriched, involving synaptic membrane adhesion, postsynaptic density membrane function and glutamate receptor activity, including homotypic cell adhesion, synaptic assembly, regulation of nervous system development, and neurotransmitter receptor activity involved in postsynaptic membrane potential regulation. In addition to GO enrichment analysis, we also performed KEGG pathway enrichment analysis to further delineate the biological pathways affected by N-glycosylation dysregulation in DCM ( Figure 16 J). KEGG results showed that pathways such as extracellular matrix-receptor interaction, cell adhesion molecules, glutamatergic synapses, and dilated cardiomyopathy were significantly enriched, which is consistent with our GO findings. Notably, the emergence of pathways such as nicotine addiction and axon guidance suggests a possible association between synaptic signaling disorders and disease progression. Cytoskeletal pathways in muscle cells were also enriched, highlighting the structural and functional damage of cardiomyocytes. Comprehensive GO and KEGG analysis showed that abnormal N-glycosylation is widely involved in disrupting synaptic signaling, extracellular matrix integrity, and cardiomyocyte structure, all of which may contribute to the pathogenesis of DCM. In addition, we also identified glycosylation changes in the GABRB1 glycoprotein ( Figure 16 J), specifically, oligomannose hyperglycosylation was observed at the glycosylation site P18505-105 of GABRB1 (Table 24).

[0125] To further explore the molecular pathways associated with GABRB1 in DCM, we analyzed its related KEGG pathways ( Figure 16 K). The GABAergic synaptic pathway was significantly enriched, with 136 genes identified in experimental validation and 92 genes annotated in the database, highlighting its central role in synaptic signaling regulation. Notably, the nicotine addiction pathway was also significantly involved, with 390 and 153 genes involved in the database and experimental datasets, respectively. These findings are consistent with our previous observations of glutamatergic synaptic dysregulation, suggesting a broader imbalance in excitatory-inhibitory neurotransmitter systems in DCM. In addition, the high gene counts (such as 136 experimental hits for GABAergic synapses) and rigorous cross-validation between database annotations and experimental data reinforce the reliability of these pathways in disease pathology. The interaction between GABAergic signaling and nicotine addiction pathways may further indicate a role for neuro-cardiac crosstalk in the progression of DCM, linking synaptic dysfunction to cardiomyocyte structural remodeling.

[0126] To further characterize the GABRB1 protein in DCM, we performed liquid chromatography-mass spectrometry (LC-MS) analysis to assess its expression and potential post-translational modifications ( Figure 16L). The LC-MS spectrum of GABRB1 revealed prominent peptide peaks with high signal intensities (up to 1.000e+06), indicating high protein abundance. Key fragment ions, including b2, y2, y3, and b3, were identified within the m / z 100–450 range, confirming the sequence-specific detection of GABRB1-derived peptides. The presence of these fragments, particularly y3 and b3, was consistent with the theoretical fragmentation pattern, supporting the accurate identification and structural integrity of GABRB1 in the DCM sample.

[0127] Combining these results with our previous GO and KEGG analyses, we propose that GABRB1 contributes to DCM pathogenesis through dysregulated synaptic signaling, a process that may be exacerbated by its interaction with glycosylated extracellular matrix components or neurotransmitter receptors.

[0128] 2.8 Inhibition of GABRB1 hyperglycosylation partially improves the phenotype of dilated cardiomyopathy

[0129] After glycosylation analysis confirmed that hyperglycosylation of GABRB1 plays a key role in regulating the neuro-cardiac network in the pathogenesis of DCM, we administered kifunensine (an α-mannosidase inhibitor) to partially inhibit glycosylation in animal models to determine whether reduced glycosylation levels could reverse DCM-related disease phenotypes.

[0130] First, consistent with the previous article, we used the cardiac-specific AAV9 vector to construct the AdGABRB1 virus that can specifically express GABRB1 in cardiomyocytes. Subsequently, under the same DOX modeling conditions, mice were intraperitoneally injected with 0.9% saline and kifunensine, respectively. Both groups of mice were injected with the control virus AAV9-Null and the overexpression virus AAV9-AdGABRB1 through the tail vein. Western blotting was used to detect the expression of GABRB1 after transfection with AAV9-cTNT-AdGABRB1 ( Figure 13 D, E).

[0131] In the 0.9% saline group, overexpression of GABRB1 alone exacerbated the DCM phenotype. Meanwhile, echocardiographic analysis of the AdGABRB1 group showed that kifunensine-treated mice had significantly improved LVEF, FS, LVEDD, and LVESD compared with saline-treated mice ( Figure 17 A, JM). In addition, compared with the saline control group, HW, HW / BW, LW / BW, and HW / TL were decreased in the kifunensine-treated group ( Figure 17 NQ). In the DOX model, the cross-sectional area of ​​cardiomyocytes in mice treated with kifunensine was smaller ( Figure 17BC). In addition, Masson trichrome staining and Sirius red staining showed that partial inhibition of glycosylation could alleviate cardiac fibrosis induced by GABRB1 overexpression ( Figure 17 Furthermore, mice with reduced glycosylation showed reduced expression of the ANP protein, which is associated with heart failure ( Figure 17 HI, RS). In summary, partial inhibition of glycosylation can attenuate the progression of DOX-induced and GABRB1-driven heart failure and DCM.

[0132] The above experimental results indicate that targeting the GABAergic-ICNS axis provides a new therapeutic approach. Pharmacological agents that modulate GABA-A receptor activity (such as benzodiazepines) Analogs (such as vasopressin analogs) can restore autonomic balance, while gene therapy approaches (such as GABRB1 knockdown) can directly alleviate excessive cardiomyocyte inhibition. Neuromodulatory strategies (such as vagus nerve stimulation (VNS)) can synergize with GABAergic interventions to enhance parasympathetic tone and inhibit sympathetic overactivation.

[0133] References

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[0137] [4]WALLS AB, EYJOLFSSON EM, SMELAND OB, et al. Knockout of GAD65 has major impact on synaptic GABA synthesized from astrocyte-derived glutamine [J]. Journal of Cerebral Blood Flow and Metabolism: Official Journal of the International Society of Cerebral Blood Flow and Metabolism, 2011, 31(2): 494-503.

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[0139] [6] ZENG C, DUAN F, HU J, et al. NLRP3 inflammasome-mediated pyroptosis contributes to the pathogenesis of non-ischemic dilated cardiomyopathy [J]. Redox Biology, 2020, 34: 101523. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions are only for illustrative purposes. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the invention claimed. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. A drug targeting the GABAergic-ICNS axis, characterized in that: include: An agent that inhibits upregulation of GABRB1 and / or an agent that inhibits hyperglycosylation of GABRB1.

2. The drug targeting the GABAergic-ICNS axis according to claim 1, characterized in that: in, The agents for inhibiting the upregulation of GABRB1 include pharmacological agents that regulate the activity of GABA-A receptors and / or recombinant adeno-associated virus serotype 9 carrying GABRB1 of cardiac troponin T promoter.

3. The drug targeting the GABAergic-ICNS axis according to claim 1, characterized in that: in, The preparation for inhibiting GABRB1 hyperglycosylation includes an α-mannosidase inhibitor.

4. The drug targeting the GABAergic-ICNS axis according to claim 3, characterized in that: in, The α-mannosidase inhibitors include Kifunensine.

5. Use of the drug targeting the GABAergic-ICNS axis according to any one of claims 1 to 4 in the preparation of drugs for autonomic nervous system disorders and dilated cardiomyopathy.

6. Use of the drug targeting the GABAergic-ICNS axis according to claim 5 in the preparation of drugs for autonomic nervous system disorders and dilated cardiomyopathy, characterized in that: in, Pharmacological agents that modulate GABA-A receptor activity can restore autonomic balance; Injection of recombinant adeno-associated virus serotype 9 carrying GABRB1 from the cardiac troponin T promoter can alleviate ventricular dilation and systolic dysfunction; Neuromodulatory strategies may work synergistically with GABAergic interventions to enhance parasympathetic tone and inhibit sympathetic overactivation.

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