Metalloproteinases as Biomarkers and Sociomarkers in Human Health and Disease

Author:

Costa Davide12ORCID,Scalise Enrica12,Ielapi Nicola3ORCID,Bracale Umberto Marcello4ORCID,Andreucci Michele5ORCID,Serra Raffaele12ORCID

Affiliation:

1. Department of Medical and Surgical Sciences, Magna Graecia University of Catanzaro, 88100 Catanzaro, Italy

2. Interuniversity Center of Phlebolymphology (CIFL), Magna Graecia University of Catanzaro, 88100 Catanzaro, Italy

3. Department of Public Health and Infectious Disease, “Sapienza” University of Rome, 00185 Rome, Italy

4. Department of Public Health, University Federico II of Naples, 80131 Naples, Italy

5. Department of Health Sciences, Magna Graecia University of Catanzaro, 88100 Catanzaro, Italy

Abstract

Metalloproteinases (MPs) are zinc-dependent enzymes with proteolytic activity and a variety of functions in the pathophysiology of human diseases. The main objectives of this review are to analyze a specific family of MPs, the matrix metalloproteinases (MMPs), in the most common chronic and complex diseases that affect patients’ social lives and to better understand the nature of the associations between MMPs and the psychosocial environment. In accordance with the PRISMA extension for a scoping review, an examination was carried out. A collection of 24 studies was analyzed, focusing on the molecular mechanisms of MMP and their connection to the manifestation of social aspects in human disease. The complexity of the relationship between MMP and social problems is presented via an interdisciplinary approach based on complexity paradigm as a new approach for conceptualizing knowledge in health research. Finally, two implications emerge from the study: first, the psychosocial states of individuals have a profound impact on their overall health and disease conditions, which implies the importance of adopting a holistic perspective on human well-being, encompassing both physical and psychosocial aspects. Second, the use of MPs as biomarkers may provide physicians with valuable tools for a better understanding of disease when used in conjunction with “sociomarkers” to develop mathematical predictive models.

Publisher

MDPI AG

Subject

Molecular Biology,Biochemistry

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