Biomarkers in the Pathogenesis, Diagnosis, and Treatment of Systemic Sclerosis.
Maheswari MuruganandamAngie Ariza-HutchinsonRosemina A PatelWilmer L SibbittPublished in: Journal of inflammation research (2023)
Systemic sclerosis (SSc) is a complex autoimmune disease characterized by vascular damage, vasoinstability, and decreased perfusion with ischemia, inflammation, and exuberant fibrosis of the skin and internal organs. Biomarkers are analytic indicators of the biological and disease processes within an individual that can be accurately and reproducibly measured. The field of biomarkers in SSc is complex as recent studies have implicated at least 240 pathways and dysregulated proteins in SSc pathogenesis. Anti-nuclear antibodies (ANA) are classical biomarkers with well-described clinical classifications and are present in more than 90% of SSc patients and include anti-centromere, anti-Th/To, anti-RNA polymerase III, and anti-topoisomerase I antibodies. Transforming growth factor-β (TGF-β) is central to the fibrotic process of SSc and is intimately intertwined with other biomarkers. Tyrosine kinases, interferon-1 signaling, IL-6 signaling, endogenous thrombin, peroxisome proliferator-activated receptors (PPARs), lysophosphatidic acid receptors, and amino acid metabolites are new biomarkers with the potential for developing new therapeutic agents. Other biomarkers implicated in SSc-ILD include signal transducer and activator of transcription 4 (STAT4), CD226 (DNAX accessory molecule 1), interferon regulatory factor 5 (IRF5), interleukin-1 receptor-associated kinase-1 (IRAK1), connective tissue growth factor (CTGF), pyrin domain containing 1 (NLRP1), T-cell surface glycoprotein zeta chain (CD3ζ) or CD247, the NLR family, SP-D (surfactant protein), KL-6, leucine-rich α2-glycoprotein-1 (LRG1), CCL19, genetic factors including DRB1 alleles, the interleukins (IL-1, IL-4, IL-6, IL-8, IL-10 IL-13, IL-16, IL-17, IL-18, IL-22, IL-32, and IL-35), the chemokines CCL (2,3,5,13,20,21,23), CXC (8,9,10,11,16), CX3CL1 (fractalkine), and GDF15. Adiponectin (an indicator of PPAR activation) and maresin 1 are reduced in SSc patients. A new trend has been the use of biomarker panels with combined complex multifactor analysis, machine learning, and artificial intelligence to determine disease activity and response to therapy. The present review is an update of the various biomarker molecules, pathways, and receptors involved in the pathology of SSc.
Keyphrases
- systemic sclerosis
- machine learning
- artificial intelligence
- transforming growth factor
- interstitial lung disease
- growth factor
- dendritic cells
- end stage renal disease
- multiple sclerosis
- ejection fraction
- systemic lupus erythematosus
- stem cells
- prognostic factors
- epithelial mesenchymal transition
- gene expression
- magnetic resonance
- chronic kidney disease
- type diabetes
- insulin resistance
- small molecule
- transcription factor
- climate change
- dna methylation
- juvenile idiopathic arthritis
- cell proliferation
- adipose tissue
- ms ms
- skeletal muscle
- immune response
- fatty acid
- deep learning
- rheumatoid arthritis patients
- soft tissue
- nuclear factor
- human health
- inflammatory response