CORTEXA
← Browse
openalexInternational Journal of Molecular Sciences2025-09-03Cited by 3

Musculoskeletal Complications in COVID-19: Exploring the Role of Key Biomarkers

Sagarkumar Patel, Cameron C. Foster, Kamal Patel, Monte Hunter, Carlos M. Isales, Sadanand Fulzele

The COVID-19 pandemic has revealed significant secondary complications affecting musculoskeletal (MSK) health, especially in patients with pre-existing conditions. This review synthesizes data from clinical and experimental studies on key MSK biomarkers, including cartilage oligomeric matrix protein (COMP), hyaluronic acid (HA), osteocalcin, alkaline phosphatase (ALP), procollagen type I N-terminal peptide (PINP), osteopontin (OPN), matrix metalloproteinases (MMP-3 and MMP-9), myostatin, IGF-1, follistatin, and creatine kinase. COVID-19 is associated with decreased COMP and osteocalcin levels, indicating cartilage degradation and impaired bone formation, alongside elevated HA, ALP, PINP, OPN, and MMPs, reflecting increased joint inflammation, bone remodeling, and tissue breakdown. Changes in myostatin, IGF-1, follistatin, and creatine kinase levels have been shown to be linked with COVID-19-related sarcopenia. These biomarker alterations provide insight into the underlying mechanisms of MSK damage in COVID-19 patients and highlight the potential for using these markers in early diagnosis and management of post-COVID musculoskeletal disorders. Further longitudinal research is essential to develop targeted therapies aimed at mitigating long-term MSK complications in affected individuals.

Also available via: Multidisciplinary Digital Publishing Institute

View free PDFSource page

Related papers

crossrefInternational Journal of Molecular Sciences2026-07-05

Machine Learning and Deep Learning Frameworks for Human–Virus Protein–Protein Interaction Prediction: Emerging Architectures, Methods, Benchmarks, and Challenges

Subhadeep Basu, Dipanwita Adhikary, Kuntal Ghosh, Swarup Chattopadhyay, Shramana Deb, Ritwick Mondal, et al.

The outbreak of coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has emerged as one of the most significant global health crises in recent history. Coronaviruses are a diverse group of RNA viruses classified into alpha,…

View free PDFSource page
crossrefInternational Journal of Molecular Sciences2025-05-07Cited by 3

Identification of Hub Genes and Key Pathways Associated with Sepsis Progression Using Weighted Gene Co-Expression Network Analysis and Machine Learning

Qinghui Sun, Hai-Li Zhang, Yichao Wang, Hao Xiu, Yufei Lu, Na He, et al.

Sepsis is a life-threatening condition driven by dysregulated immune responses, resulting in organ dysfunction and high mortality rates. Identifying key genes and pathways involved in sepsis progression is crucial for improving diagnostic and therapeutic strategies. This study an…

View free PDFSource page
openalexInternational Journal of Molecular Sciences2026-07-23

Metainflammation, Mitochondrial Dysfunction, and Organokine Crosstalk: A Central Axis Linking Metabolic Syndrome to Cardiovascular Diseases

Ana Flávia Pontes Sodré, Lucca Gonsales Rodrigues, Kátia P. Sloan, Lance A. Sloan, Masaru Tanaka, Rui Curi, et al.

Metabolic Syndrome (MetS) is a complex and multifactorial condition characterized by insulin resistance, visceral obesity, dyslipidemia, hypertension, and chronic low-grade inflammation, all of which contribute to increased cardiovascular risk. Central to its pathophysiology is m…

View free PDFSource page
crossrefInternational Journal of Molecular Sciences2025-02-27Cited by 5

Therapeutic Mechanisms of Medicine Food Homology Plants in Alzheimer’s Disease: Insights from Network Pharmacology, Machine Learning, and Molecular Docking

Shuran Wen, Ye Han, You Li, Dongling Zhan

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder characterized by a gradual decline in cognitive function. Currently, there are no effective treatments for this condition. Medicine food homology plants have gained increasing attention as potential natural trea…

View free PDFSource page
crossrefInternational Journal of Molecular Sciences2026-05-22

Exploring the Toxicological Relationship Between Diisononyl Cyclohexane-1,2-dicarboxylate and Atherosclerosis Through Network Toxicology, Machine Learning, and Multi-Dimensional Bioinformatics

Jingbo Cao, Ziyao Yang, Qi Zhang, Siwei Zou, Huning Zhang, Anning Yang, et al.

This study integrates multidimensional computational approaches—network toxicology, machine learning, molecular docking, and molecular dynamics simulation—to systematically elucidate the toxic mechanism by which the environmental pollutant diisononyl cyclohexane-1,2-dicarboxylate…

View free PDFSource page
crossrefInternational Journal of Molecular Sciences2025-12-27Cited by 1

Biologically Informed Machine Learning Prioritizes Dietary Supplements That Protect Neural Crest Cells from Ethanol-Induced Epigenetic Dysregulation and Developmental Impairment

Xiaoqing Wang, Miao Bai, Shuoyang Wang, Hongjia Qian, Jie Liu, Wenke Feng, et al.

The impairment of neural crest cells (NCCs) plays a pivotal role in the pathogenesis of fetal alcohol spectrum disorders (FASD). Epigenetic regulators mediate ethanol-induced disruptions in NCC development and represent promising targets for nutritional interventions. Here, we de…

View free PDFSource page