Objective:Ectopic calcification is an important contributor to chronic diseases, such as osteoarthritis. Currently, no effective therapies exist to counteract calcification. We developed peptides derived from the calcium binding domain of human Alpha-2-HS-Glycoprotein (AHSG/Fetuin A) to counteract calcification.
Methods:A library of seven 30 amino acid (AA) long peptides, spanning the 118 AA Cystatin 1 domain of AHSG, were synthesized and evaluated in an in vitro calcium phosphate precipitation assay. The best performing peptide was modified (cyclic, retro-inverso and combinations thereof) and evaluated in cellular calcification models and the rat Medial Collateral Ligament Transection + Medial Meniscal Tear (MCLT + MMT) osteoarthritis model.
Results:A cyclic peptide spanning AA 1-30 of mature AHSG showed clear inhibition of calcium phosphate precipitation in the nM-pM range that far exceeded the biological activity of the linear peptide variant or bovine Fetuin. Biochemical and electron microscopy analyses of calcium phosphate particles revealed a similar, but distinct, mode of action in comparison with bFetuin. A cyclic-inverso variant of the AHSG 1-30 peptide inhibited calcification of human articular chondrocytes, vascular smooth muscle cells and during osteogenic differentiation of bone marrow derived stromal cells. Lastly, we evaluated the effect of intra-articular injection of the cyclic-inverso AHSG 1-30 peptide in a rat osteoarthritis model. A significant improvement was found in histopathological osteoarthritis score and animal mobility. Serum levels of IFNγ were found to be lower in AHSG 1-30 peptide treated animals.
Conclusions:The cyclic-inverso AHSG 1-30 peptide directly inhibits the calcification process and holds the potential for future application in osteoarthritis.
Keywords:Calcification; Fetuin A; Osteoarthritis; Peptide.
Development of a cyclic-inverso AHSG/Fetuin A-based peptide for inhibition of calcification in osteoarthritis
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基因水平:PCR Array、RT-PCR、PCR、单细胞测序
蛋白水平:MSD、Luminex、CBA、Elispot、Antibody Array、ELISA、Sengenics
细胞水平:细胞染色、细胞分选、细胞培养、细胞功能
组织水平:空间多组学、多重荧光免疫组化、免疫组化、免疫荧光
数据分析:流式数据分析、组化数据分析、多因子数据分析
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