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Dowling P, Trollet C, Negroni E, Swandulla D, Ohlendieck K. How Can Proteomics Help to Elucidate the Pathophysiological Crosstalk in Muscular Dystrophy and Associated Multi-System Dysfunction? Proteomes 2024; 12:4. [PMID: 38250815 PMCID: PMC10801633 DOI: 10.3390/proteomes12010004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Revised: 01/09/2024] [Accepted: 01/12/2024] [Indexed: 01/23/2024] Open
Abstract
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.
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Affiliation(s)
- Paul Dowling
- Department of Biology, Maynooth University, National University of Ireland, W23 F2H6 Maynooth, Co. Kildare, Ireland;
- Kathleen Lonsdale Institute for Human Health Research, Maynooth University, W23 F2H6 Maynooth, Co. Kildare, Ireland
| | - Capucine Trollet
- Center for Research in Myology U974, Sorbonne Université, INSERM, Myology Institute, 75013 Paris, France; (C.T.); (E.N.)
| | - Elisa Negroni
- Center for Research in Myology U974, Sorbonne Université, INSERM, Myology Institute, 75013 Paris, France; (C.T.); (E.N.)
| | - Dieter Swandulla
- Institute of Physiology, Faculty of Medicine, University of Bonn, D53115 Bonn, Germany;
| | - Kay Ohlendieck
- Department of Biology, Maynooth University, National University of Ireland, W23 F2H6 Maynooth, Co. Kildare, Ireland;
- Kathleen Lonsdale Institute for Human Health Research, Maynooth University, W23 F2H6 Maynooth, Co. Kildare, Ireland
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Murphy S, Zweyer M, Swandulla D, Ohlendieck K. Bioinformatic Analysis of the Subproteomic Profile of Cardiomyopathic Tissue. Methods Mol Biol 2023; 2596:377-395. [PMID: 36378452 DOI: 10.1007/978-1-0716-2831-7_26] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
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.
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Affiliation(s)
- Sandra Murphy
- Charles River Laboratories, Chesterford Research Park, Saffron Walden, UK
| | - Margit Zweyer
- Department of Neonatology and Pediatric Intensive Care, Children's Hospital, University of Bonn, Bonn, Germany
| | | | - Kay Ohlendieck
- Department of Biology, Maynooth University, National University of Ireland, Maynooth, Co. Kildare, Ireland.
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Kim H, Kamm RD, Vunjak-Novakovic G, Wu JC. Progress in multicellular human cardiac organoids for clinical applications. Cell Stem Cell 2022; 29:503-514. [PMID: 35395186 PMCID: PMC9352318 DOI: 10.1016/j.stem.2022.03.012] [Citation(s) in RCA: 42] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
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.
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Affiliation(s)
- Hyeonyu Kim
- Stanford Cardiovascular Institute, Stanford, CA 94305, USA
| | - Roger D Kamm
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Gordana Vunjak-Novakovic
- Department of Biomedical Engineering, Columbia University, New York, NY 10027, USA; Department of Medicine, Columbia University, New York, NY 10032, USA
| | - Joseph C Wu
- Stanford Cardiovascular Institute, Stanford, CA 94305, USA; Department of Medicine, Stanford University, Stanford, CA 94305, USA.
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Cong G, Cui X, Ferrari R, Pipinos II, Casale GP, Chattopadhyay A, Sachdev U. Fibrosis Distinguishes Critical Limb Ischemia Patients from Claudicants in a Transcriptomic and Histologic Analysis. J Clin Med 2020; 9:jcm9123974. [PMID: 33302519 PMCID: PMC7763090 DOI: 10.3390/jcm9123974] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2020] [Revised: 11/24/2020] [Accepted: 11/26/2020] [Indexed: 01/01/2023] Open
Abstract
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.
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Affiliation(s)
- Guangzhi Cong
- Department of Surgery, University of Pittsburgh Medical Centre, Pittsburgh, PA 15217, USA; (G.C.); (X.C.); (R.F.)
- Department of Surgery, University of Nebraska at Medical Center, Omaha, NE 68198, USA
| | - Xiangdong Cui
- Department of Surgery, University of Pittsburgh Medical Centre, Pittsburgh, PA 15217, USA; (G.C.); (X.C.); (R.F.)
| | - Ricardo Ferrari
- Department of Surgery, University of Pittsburgh Medical Centre, Pittsburgh, PA 15217, USA; (G.C.); (X.C.); (R.F.)
| | - Iraklis I. Pipinos
- Department of Surgery and VA Research Service, VA Nebraska-Western Iowa Health Care System, Omaha, NE 68198, USA; (I.I.P.); (G.P.C.)
- Molecular Biology Information Service, Health Sciences Library System University of Pittsburgh, Pittsburgh, PA 15261, USA;
| | - George P. Casale
- Department of Surgery and VA Research Service, VA Nebraska-Western Iowa Health Care System, Omaha, NE 68198, USA; (I.I.P.); (G.P.C.)
| | - Ansuman Chattopadhyay
- Molecular Biology Information Service, Health Sciences Library System University of Pittsburgh, Pittsburgh, PA 15261, USA;
| | - Ulka Sachdev
- Department of Surgery, University of Pittsburgh Medical Centre, Pittsburgh, PA 15217, USA; (G.C.); (X.C.); (R.F.)
- Correspondence:
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Gruson D, Bernardini S, Dabla PK, Gouget B, Stankovic S. Collaborative AI and Laboratory Medicine integration in precision cardiovascular medicine. Clin Chim Acta 2020; 509:67-71. [PMID: 32505771 DOI: 10.1016/j.cca.2020.06.001] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2020] [Revised: 05/30/2020] [Accepted: 06/01/2020] [Indexed: 12/11/2022]
Abstract
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.
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Affiliation(s)
- Damien Gruson
- Department of Clinical Biochemistry, Cliniques Universitaires St-Luc and Université Catholique de Louvain, Brussels, Belgium; Pôle de recherche en Endocrinologie, Diabète et Nutrition, Institut de Recherche Expérimentale et Clinique, Cliniques Universitaires St-Luc and Université Catholique de Louvain, Brussels, Belgium; Emerging Technologies Division-MHBLM Committee, International Federation Clinical Chemistry and Laboratory Medicine (IFCC), Italy.
| | - Sergio Bernardini
- Department of Experimental Medicine, University of Tor Vergata, Rome, Italy; Emerging Technologies Division-MHBLM Committee, International Federation Clinical Chemistry and Laboratory Medicine (IFCC), Italy
| | - Pradeep Kumar Dabla
- Department of Biochemistry, G.B Pant Institute of Postgraduate Medical Education & Research, Associated to Maulana Azad Medical College, New Delhi, India; Emerging Technologies Division-MHBLM Committee, International Federation Clinical Chemistry and Laboratory Medicine (IFCC), Italy
| | - Bernard Gouget
- President-Healthcare Division Committee, Comité Français d'accréditation (Cofrac), 75012 Paris, France; Emerging Technologies Division-MHBLM Committee, International Federation Clinical Chemistry and Laboratory Medicine (IFCC), Italy
| | - Sanja Stankovic
- Center for Medical Biochemistry, Clinical Center of Serbia, Belgrade, Serbia; Emerging Technologies Division-MHBLM Committee, International Federation Clinical Chemistry and Laboratory Medicine (IFCC), Italy
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