Search bioRxiv⌕ Search

bioRxiv · 10.1101/2025.02.20.638615

The preclinical cardiac phenotype of the DE50-MD dog model of Duchenne muscular dystrophy.

Abstract

Cardiomyopathy is the leading cause of death in the X-linked disorder, Duchenne Muscular Dystrophy (DMD) yet optimal management strategies remain undetermined. Advances in the search for novel DMD treatments, particularly at cell and molecular levels, rely heavily on the use of translational animal models. It is crucial that these models faithfully recapitulate the human clinical phenotype to best expedite the development of promising treatments. We sought comprehensively to describe the cardiac phenotype of DE50-MD dogs, a novel dystrophin-deficient model that harbours a mutation within the principal DMD mutational hotspot. Cardiac magnetic resonance imaging and echocardiographic studies were performed at approximately 12-week intervals in male, 3- to 18-month-old DE50-MD (n=17) and age-matched littermates, wild type (WT, n=14) dogs. Late gadolinium enhancement (LGE) imaging was performed in a subpopulation of DE50-MD (n=10) and WT (n=11) dogs aged 9 to 18 months. The DE50-MD dogs had smaller left ventricular (LV) mass and LV dimensions than WT dogs. While global ventricular systolic function was preserved, DE50-MD dogs showed early differences in strain and strain rate parameters. Only DE50-MD dogs demonstrated LGE (3/8 dogs studied at 18 months); the subepicardial to transmural, mid-to-basal LV LGE distribution resembling that of DMD patients and of other dystrophic dog models. Histopathological assessment confirmed that LGE corresponded to fibrofatty myocardial scarring, as described in DMD patients and other canine models of dystrophin-deficient cardiomyopathy. The DE50-MD early preclinical cardiac phenotype shares key features of DMD cardiomyopathy prior to onset of global LV systolic dysfunction. Their disproportionately low LV volume to mass supports possible combined physiological hypotrophy and tonic contraction in affected animals.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Sargent, J., Fuentes, V. L., Terry, R., Riddell, D. O., Harron, R. C., Wells, D. J., Piercy, R. J.. 2025-02-23. The preclinical cardiac phenotype of the DE50-MD dog model of Duchenne muscular dystrophy.. https://doi.org/10.1101/2025.02.20.638615

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Evaluating the Transferability of Pathology Foundation Models Across Cancer-related H&E Neurodegeneration-related Immunohistochemical Classification Tasks

Foundation models (FMs) have rapidly become dominant in artificial intelligence and are increasingly being adopted in computational pathology. Numerous pathology-specific FMs have been developed and evaluated for a variety of downstream tasks, most commonly using frozen image embeddings with linear probes. While a pathology FM, at least implicitly suggests broad reusability across tasks, the transferability of these models to neurodegenerative disease-related tasks remains largely unexplored. In this study, we evaluated fourteen frozen feature extractors, including general-vision and pathology FMs, across four pathology image classification datasets spanning two specialized neurodegenerative disease immuno-histochemistry (IHC) tasks (Tau neurofibrillary tangle (NFT) and amyloid-{beta} plaque classification) and two cancer-related hematoxylin and eosin (H&E) tasks (the breast tissue BACH dataset and the multi-tissue TIL dataset). The cancer-related H&E datasets represent tasks more closely aligned with the predominant pretraining domain of many current pathology FMs, whereas the neurodegenerative IHC datasets represent a more specialized domain with limited representation in existing FM pretraining cohorts. Frozen embedding linear probes were compared against a conventional supervised ResNet-50 convolutional neural network (CNN) trained directly on image tiles using identical train, validation, and test splits. Across both neurodegenerative IHC datasets, the supervised CNN substantially outperformed all frozen FM linear probes. In contrast, pathology FMs achieved performance comparable to, and in some cases exceeding, the supervised CNN across the two cancer-related H&E datasets, with UNI2-h achieving the highest performance on BACH and several pathology FMs performing on par with the CNN on the larger TIL dataset. Furthermore, a supervised CNN trained using only 1% of the Tau NFT training data (1,938 tiles) still exceeded the performance of the best frozen FM linear probe trained on the complete dataset. Together, these results suggest the transferability of frozen pathology FMs may depend strongly on how well the downstream task is represented by their pretraining domain. These findings demonstrate frozen pathology FMs transfer effectively to the cancer-related H&E tasks evaluated here but may be less effective for specialized neurodegenerative IHC tasks less well represented in current FM pretraining cohorts. Expanding pathology FM pretraining datasets to include a broader range of disease domains and staining modalities may therefore improve transferability to specialized pathology applications. Our findings also highlight the continued importance of conventional supervised learning and motivate future work investigating nonlinear probes and end-to-end FM fine-tuning.

pathology↗

Keto-gluconeogenic metabolic axis mirrors renal homeostasis and post-injury response in spatial transcriptomics

Metabolic disturbance is a key feature in acute kidney injury (AKI) and chronic kidney disease (CKD). The kidney highly depends on fatty acid metabolism; how renal cells rewire metabolism upon AKI and CKD transition remained unclear. Here, we combine spatial transcriptomics with biochemical analyses to characterize metabolic changes and intercellular interactions during AKI to CKD transition. Using aristolochic acid model of CKD, we spatio-temporally correlated changes in structure and function with metabolic profile during AKI to CKD transition. Surprisingly, keto-gluconeogenic metabolic axis was highly enriched in healthy kidney and paralleled injury phase transitions. Intercellular interaction analysis associated a subtype of macrophage with the drift to chronicity. Online scRNAseq datasets analysis confirmed altered keto-gluconeogenic metabolic pathways in ischemia-reperfusion injured mouse kidneys and AKI and CKD human kidney biopsies compared to healthy controls. This study identifies a metabolic axis transcriptionally mirroring renal homeostasis and injury responses, and tubulo-interstitial interactions that can be targeted to mitigate AKI to CKD transition.

pathology↗

Identification of Novel Inhibitors of JEV RdRp as Potent Antiviral Drugs: Targeting NS5-NS3 Protein Interaction

Japanese Encephalitis Virus (JEV) belongs to the Flavivirus family, and the RNA dependent RNA polymerase (RdRp) domain located at the C terminus of non structural protein 5 (NS5) regulates de novo viral genome synthesis. The conserved priming loop inserted in the thumb domain of RDRP initiates de novo genome synthesis. Interestingly, the reported replication process initiates with an interaction between NS5 (methyltransferase/RDRP) and NS3 (protease/helicase), and inhibiting this interaction directly correlates with the inhibition of viral replication. The function of the priming loop in the context of the NS5 NS3 interaction is not yet known. In this study, we studied the priming loop function in the NS5 NS3 interaction and viral replication. Using a structure based drug design approach, we screened the Maybridge compound library against the RdRp priming loop and identified 15 candidate compounds based on binding energy. Among them, DSHS00151 showed significant dose dependent inhibition of the NS5 NS3 interaction with an IC50 of 3.5 micromolar in the mammalian two hybrid assay, inhibited viral infectivity with an IC50 of 2.54 micromolar, and reduced viral RNA load with an IC50 of 2.9 micromolar, compared to CD10712. Molecular Dynamics (MD) simulations revealed that DSHS00151 exhibits stronger and more stable binding with the priming loop residues (790 to 812) compared to CD10712. The molecular mechanism suggested by the docking of the NS5 and NS3 proteins showed that the priming loop tends to rotate toward the NS3 protein to stabilize the complex, and compound binding restricts this loop rotation, thus compromising the stability of the NS5 and NS3 complex and affecting viral replication. Overall, our study validated the function of the NS5 priming loop as an allosteric site, and compounds binding to this allosteric site belong to the Non Nucleoside Reverse Transcriptase Inhibitors (NNRTI) class of inhibitors, which disrupt the NS5 and NS3 interaction and could be developed as novel anti JEV therapeutics.

pathology↗