Multiomic approaches to delineate the pathogenesis of cardiac disease

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.

Bioinformatic Analysis of the Subproteomic Profile of Cardiomyopathic Tissue

Following large-scale protein separation by two-dimensional gel electrophoresis or liquid chromatography, mass spectrometry-based proteomics can be used for the swift identification and characterization of cardiac proteins and their various proteoforms. Comparative cardiac proteomics has been widely applied for the systematic analysis of heart disease and the establishment of novel diagnostic protein biomarkers. The X-linked neuromuscular disorder Duchenne muscular dystrophy is a multisystemic disease that is characterized by late-onset cardiomyopathy. This chapter outlines the bioinformatic analysis of the subproteomic profile of cardiac tissue from wild-type versus the dystrophic mdx-4cv mouse model of dystrophinopathy.

Progress in multicellular human cardiac organoids for clinical applications

Advances in self-organizing cardiac organoids to recapitulate human cardiogenesis have provided a powerful tool for unveiling human cardiac development, studying cardiovascular diseases, testing drugs, and transplantation. Here, we highlight the recent remarkable progress on multicellular cardiac organoids and review the current status for their practical applications. We then introduce key readouts and tools for assessing cardiac organoids for clinical applications, address major challenges, and provide suggestions for each assessment method. Lastly, we discuss the current limitations of cardiac organoids as miniature models of the human heart and suggest a direction for moving forward toward building the mini-heart from cardiac organoids.

Fibrosis Distinguishes Critical Limb Ischemia Patients from Claudicants in a Transcriptomic and Histologic Analysis

Most patients with critical limb ischemia (CLI) from peripheral arterial disease (PAD) do not have antecedent intermittent claudication (IC). We hypothesized that transcriptomic analysis would identify CLI-specific pathways, particularly in regards to fibrosis. Derivation cohort data from muscle biopsies in PAD and non-PAD (controls) was obtained from the Gene Expression Omnibus (GSE120642). Transcriptomic analysis indicated CLI patients (N = 16) had a unique gene expression profile, when compared with non-PAD controls (N = 15) and IC (N = 20). Ninety-eight genes differed between controls and IC, 2489 genes differed between CLI and controls, and 2783 genes differed between CLI and IC patients. Pathway enrichment analysis showed that pathways associated with TGFβ, collagen deposition, and VEGF signaling were enriched in CLI but not IC. Receiver operating curve (ROC) analysis of nine fibrosis core gene expression revealed the areas under the ROC (AUC) were all >0.75 for CLI. Furthermore, the fibrosis area (AUC = 0.81) and % fibrosis (AUC = 0.87) in validation cohort validated the fibrosis discrimination CLI from IC and control (all n = 12). In conclusion, transcriptomic analysis identified fibrosis pathways, including those involving TGFβ, as a novel gene expression feature for CLI but not IC. Fibrosis is an important characteristic of CLI, which we confirmed histologically, and may be a target for novel therapies in PAD.

Collaborative AI and Laboratory Medicine integration in precision cardiovascular medicine

Artificial Intelligence (AI) is a broad term that combines computation with sophisticated mathematical models and in turn allows the development of complex algorithms which are capable to simulate human intelligence such as problem solving and learning. It is devised to promote a significant paradigm shift in the most diverse areas of medical knowledge. On the other hand, Cardiology is a vast field dealing with diseases relating to the heart, the circulatory system, and includes coronary heart disease, cerebrovascular disease, rheumatic heart disease and other conditions. AI has emerged as a promising tool in cardiovascular medicine which is aimed in augmenting the effectiveness of the cardiologist and to extend better quality to patients. It has the ability to support decision‑making and improve diagnostic and prognostic performance. Attempt has also been made to explore novel genotypes and phenotypes in existing cardiovascular diseases, improve the quality of patient care, to enablecost-effectiveness with reducereadmissionand mortality rates. Our review addresses the integration of AI and laboratory medicine as an accelerator of personalization care associated with the precision and the need of value creation services in cardiovascular medicine.