Plasma lipidomic analysis shows a disease progression signature in mdx mice

Molecular profiling of blood plasma-derived extracellular vesicles derived from Duchenne muscular dystrophy patients through integration of FTIR spectroscopy and machine learning reveals disease signatures

PURPOSE

To identify and monitor the FTIR spectral signatures of plasma extracellular vesicles (EVs) from Duchenne Muscular Dystrophy (DMD) patients at different stages with Healthy controls using machine learning models.

MATERIALS AND METHODS

Whole blood samples were collected from the DMD (n = 30) and Healthy controls (n = 12). EVs were extracted by the Total Exosome Isolation (TEI) Method and resuspended in 1XPBS. We characterize the morphology, size, particle count, and surface markers (CD9, Alix, and Flotillin) by HR-TEM, NTA, and Western Blot analysis. The mid-IR spectra were recorded from (4000-400 cm-1) by Bruker ALPHA II FTIR spectrometer model, which was equipped with an attenuated total reflection (ATR) module. Machine learning algorithms like Principal Component Analysis (PCA) and Random Forest (RF) for dimensionality reduction and classifying the two study groups based on the FTIR spectra. The model performance was evaluated by a confusion matrix and the sensitivity, specificity, and Receiver Operating Characteristic Curve (ROC) was calculated respectively.

RESULTS

Alterations in Amide I & II (1700-1470 cm-1) and lipid (3000-2800 cm-1) regions in FTIR spectra of DMD compared with healthy controls. The PCA-RF model classified correctly the two study groups in the range of 4000-400 cm-1 with a sensitivity of 20 %, specificity of 87.50 %, accuracy of 71.43 %, precision of 33.33 %, and 5-fold cross-validation accuracy of 82 %. We analyzed the ten different spectral regions which showed statistically significant at P < 0.01 except the Ester Acyl Chain region.

CONCLUSION

Our proof-of-concept study demonstrated distinct infrared (IR) spectral signatures in plasma EVs derived from DMD. Consistent alterations in protein and lipid configurations were identified using a PCA-RF model, even with a small clinical dataset. This minimally invasive liquid biopsy method, combined with automated analysis, warrants further investigation for its potential in early diagnosis and monitoring of disease progression in DMD patients within clinical settings.

Novel implementation of cardiac magnetic resonance first-pass perfusion imaging for semi-quantitatively evaluating microvascular dysfunction in paediatric patients with Duchenne muscular dystrophy

OBJECTIVES

The current study aimed to assess myocardial microcirculation dysfunction via cardiac magnetic resonance (CMR) first-pass perfusion imaging in children with Duchenne muscular dystrophy (DMD).

METHODS

In total, 67 children with DMD and 15 controls who underwent contrast-enhanced CMR first-pass perfusion imaging were enrolled in this study. CMR first-pass perfusion and late gadolinium enhancement (LGE) sequences were acquired. Further, the global, regional, and coronary artery distribution area perfusion indexes (PI), upslope (%BL), maximum signal intensity (MaxSI), time to maximum signal intensity (TTM), and baseline SI were analysed. The perfusion parameters of the LGE positive (+), LGE negative (-), and control groups were compared. Pearson correlation analysis was performed to assess the association between myocardial microcirculation and conventional cardiac function and LGE parameters.

RESULTS

The LGE+ group had a significantly lower global and apical-ventricular MaxSI than the control group (all P < .05). The left anterior descending arterial (LAD), left circumflex coronary arterial (LCX), and right coronary arterial (RCA) segments of the LGE+ group had a lower upslope and MaxSI than those of the control group (all P < .05). The LAD segments of the LGE- group had a lower MaxSI than those of the control group (41.10 ± 11.08 vs 46.36 ± 13.04; P < .001). The LCX segments of the LGE- group had a lower PI and upslope than those of the control group (11.05 ± 2.84 vs 12.46 ± 2.82; P = .001; 59.31 ± 26.76 vs 68.57 ± 29.99; P = .002). Based on the correlation analysis, the upslope, MaxSI, and TTM were correlated with conventional cardiac function and LGE extent.

CONCLUSIONS

Paediatric patients with DMD may present with microvascular dysfunction. This condition may appear before LGE and may be correlated with coronary artery blood supply and LGE extent.

ADVANCES IN KNOWLEDGE

First-pass perfusion parameters may reveal the status of myocardial microcirculation and reflect the degree of myocardial injury at an earlier time in DMD patients. Perfusion parameters should be analysed not only via global or base, middle, and apical segments but also according to coronary artery distribution area, which may detect myocardial microvascular dysfunction at an earlier stage, in DMD patients with LGE-.

How Can Proteomics Help to Elucidate the Pathophysiological Crosstalk in Muscular Dystrophy and Associated Multi-System Dysfunction?

This perspective article is concerned with the question of how proteomics, which is a core technique of systems biology that is deeply embedded in the multi-omics field of modern bioresearch, can help us better understand the molecular pathogenesis of complex diseases. As an illustrative example of a monogenetic disorder that primarily affects the neuromuscular system but is characterized by a plethora of multi-system pathophysiological alterations, the muscle-wasting disease Duchenne muscular dystrophy was examined. Recent achievements in the field of dystrophinopathy research are described with special reference to the proteome-wide complexity of neuromuscular changes and body-wide alterations/adaptations. Based on a description of the current applications of top-down versus bottom-up proteomic approaches and their technical challenges, future systems biological approaches are outlined. The envisaged holistic and integromic bioanalysis would encompass the integration of diverse omics-type studies including inter- and intra-proteomics as the core disciplines for systematic protein evaluations, with sophisticated biomolecular analyses, including physiology, molecular biology, biochemistry and histochemistry. Integrated proteomic findings promise to be instrumental in improving our detailed knowledge of pathogenic mechanisms and multi-system dysfunction, widening the available biomarker signature of dystrophinopathy for improved diagnostic/prognostic procedures, and advancing the identification of novel therapeutic targets to treat Duchenne muscular dystrophy.

The Interaction of Duchenne Muscular Dystrophy and Insulin Resistance

Duchenne muscular dystrophy (DMD), caused by deficiency of functional dystrophin protein, is a fatal, progressive muscle disease that frequently includes metabolic dysregulation. Herein, we explore the physiologic consequences of dystrophin deficiency within the context of obesity and insulin resistance. We hypothesized that dystrophin deficiency increases the frequency of insulin resistance, and insulin resistance potentiates muscle pathology caused by dystrophin deficiency.

A fat- and sucrose-enriched diet causes metabolic alterations in mdx mice

Duchenne muscular dystrophy (DMD), a progressive muscle disease caused by the absence of functional dystrophin protein, is associated with multiple cellular, physiological, and metabolic dysfunctions. As an added complication to the primary insult, obesity/insulin resistance (O/IR) is frequently reported in patients with DMD; however, how IR impacts disease severity is unknown. We hypothesized a high-fat, high-sucrose diet (HFHSD) would induce O/IR, exacerbate disease severity, and cause metabolic alterations in dystrophic mice. To test this hypothesis, we treated 7-wk-old mdx (disease model) and C57 mice with a control diet (CD) or an HFHSD for 15 wk. The HFHSD induced insulin resistance, glucose intolerance, and hyperglycemia in C57 and mdx mice. Of note, mdx mice on CD were also insulin resistant. In addition, visceral adipose tissue weights were increased with HFHSD in C57 and mdx mice though differed by genotype. Serum creatine kinase activity and histopathological analyses using Masson's trichrome staining in the diaphragm indicated muscle damage was driven by dystrophin deficiency but was not augmented by diet. In addition, markers of inflammatory signaling, mitochondrial abundance, and autophagy were impacted by disease but not diet. Despite this, in addition to disease signatures in CD-fed mice, metabolomic and lipidomic analyses demonstrated a HFHSD caused some common changes in C57 and mdx mice and some unique signatures of O/IR within the context of dystrophin deficiency. In total, these data revealed that in mdx mice, 15 wk of HFHSD did not overtly exacerbate muscle injury but further impaired the metabolic status of dystrophic muscle.

Multiomic characterization of disease progression in mice lacking dystrophin

Duchenne muscular dystrophy (DMD) is caused by genetic mutations leading to lack of dystrophin in skeletal muscle. A better understanding of how objective biomarkers for DMD vary across subjects and over time is needed to model disease progression and response to therapy more effectively, both in pre-clinical and clinical research. We present an in-depth characterization of disease progression in 3 murine models of DMD by multiomic analysis of longitudinal trajectories between 6 and 30 weeks of age. Integration of RNA-seq, mass spectrometry-based metabolomic and lipidomic data obtained in muscle and blood samples by Multi-Omics Factor Analysis (MOFA) led to the identification of 8 latent factors that explained 78.8% of the variance in the multiomic dataset. Latent factors could discriminate dystrophic and healthy mice, as well as different time-points. MOFA enabled to connect the gene expression signature in dystrophic muscles, characterized by pro-fibrotic and energy metabolism alterations, to inflammation and lipid signatures in blood. Our results show that omic observations in blood can be directly related to skeletal muscle pathology in dystrophic muscle.

Lipidomics-Paving the Road towards Better Insight and Precision Medicine in Rare Metabolic Diseases

Even though the application of Next-Generation Sequencing (NGS) has significantly facilitated the identification of disease-associated mutations, the diagnostic rate of rare diseases is still below 50%. This causes a diagnostic odyssey and prevents specific treatment, as well as genetic counseling for further family planning. Increasing the diagnostic rate and reducing the time to diagnosis in children with unclear disease are crucial for a better patient outcome and improvement of quality of life. In many cases, NGS reveals variants of unknown significance (VUS) that need further investigations. The delineation of novel (lipid) biomarkers is not only crucial to prove the pathogenicity of VUS, but provides surrogate parameters for the monitoring of disease progression and therapeutic interventions. Lipids are essential organic compounds in living organisms, serving as building blocks for cellular membranes, energy storage and signaling molecules. Among other disorders, an imbalance in lipid homeostasis can lead to chronic inflammation, vascular dysfunction and neurodegenerative diseases. Therefore, analyzing lipids in biological samples provides great insight into the underlying functional role of lipids in healthy and disease statuses. The method of choice for lipid analysis and/or huge assemblies of lipids (=lipidome) is mass spectrometry due to its high sensitivity and specificity. Due to the inherent chemical complexity of the lipidome and the consequent challenges associated with analyzing it, progress in the field of lipidomics has lagged behind other omics disciplines. However, compared to the previous decade, the output of publications on lipidomics has increased more than 17-fold within the last decade and has, therefore, become one of the fastest-growing research fields. Combining multiple omics approaches will provide a unique and efficient tool for determining pathogenicity of VUS at the functional level, and thereby identifying rare, as well as novel, genetic disorders by molecular techniques and biochemical analyses.

Breathing in Duchenne muscular dystrophy: Translation to therapy

Duchenne muscular dystrophy (DMD) is an X-linked neuromuscular disease caused by a deficiency in dystrophin - a structural protein which stabilizes muscle during contraction. Dystrophin deficiency adversely affects the respiratory system leading to sleep-disordered breathing, hypoventilation, and weakness of the expiratory and inspiratory musculature, which culminate in severe respiratory dysfunction. Muscle degeneration associated respiratory impairment in neuromuscular disease is a result of disruptions at multiple sites of the respiratory control network, including sensory and motor pathways. As a result of this pathology, respiratory failure is a leading cause of premature death in DMD patients. Currently available treatments for DMD respiratory insufficiency attenuate respiratory symptoms without completely reversing the underlying pathophysiology. This underscores the need to develop curative therapies to improve quality of life and longevity of DMD patients. This review summarises research findings on the pathophysiology of respiratory insufficiencies in DMD disease in humans and animal models, the clinical interventions available to ameliorate symptoms, and gene-based therapeutic strategies uncovered by preclinical animal studies. Abstract figure legend: Summary of the therapeutic strategies for respiratory insufficiency in DMD (Duchenne muscular dystrophy). Treatment options currently in clinical use only attenuate respiratory symptoms without reversing the underlying pathology of DMD-associated respiratory insufficiencies. Ongoing preclinical and clinical research is aimed at developing curative therapies that both improve quality of life and longevity of DMD patients. AAV - adeno-associated virus, PPMO - Peptide-conjugated phosphorodiamidate morpholino oligomer This article is protected by copyright. All rights reserved.