ABSTRACT
Identification of the plasma proteomic changes of Coronavirus disease 2019 (COVID-19) is essential to understanding the pathophysiology of the disease and developing predictive models and novel therapeutics. We performed plasma deep proteomic profiling from 332 COVID-19 patients and 150 controls and pursued replication in an independent cohort (297 cases and 76 controls) to find potential biomarkers and causal proteins for three COVID-19 outcomes (infection, ventilation, and death). We identified and replicated 1,449 proteins associated with any of the three outcomes (841 for infection, 833 for ventilation, and 253 for death) that can be query on a web portal (https://covid.proteomics.wustl.edu/). Using those proteins and machine learning approached we created and validated specific prediction models for ventilation (AUC>0.91), death (AUC>0.95) and either outcome (AUC>0.80). These proteins were also enriched in specific biological processes, including immune and cytokine signaling (FDR [≤] 3.72x10-14), Alzheimers disease (FDR [≤] 5.46x10-10) and coronary artery disease (FDR [≤] 4.64x10-2). Mendelian randomization using pQTL as instrumental variants nominated BCAT2 and GOLM1 as a causal proteins for COVID-19. Causal gene network analyses identified 141 highly connected key proteins, of which 35 have known drug targets with FDA-approved compounds. Our findings provide distinctive prognostic biomarkers for two severe COVID-19 outcomes (ventilation and death), reveal their relationship to Alzheimers disease and coronary artery disease, and identify potential therapeutic targets for COVID-19 outcomes.
ABSTRACT
Tissue fibrosis, characterized by excessive accumulation of aberrant extracellular matrix (ECM) produced by myofibroblasts, is a growing cause of mortality worldwide. Understanding the factors that induce myofibroblastic differentiation is paramount to prevent or reverse the fibrogenic process. Integrin-mediated interaction between the ECM and cytoskeleton promotes myofibroblast differentiation. In the present study, we explored the significance of integrin alpha 11 (ITGA11), the integrin alpha subunit that selectively binds to type I collagen during tissue fibrosis in the liver, lungs and kidneys. We showed that ITGA11 was co-localized with α-smooth muscle actin-positive myofibroblasts and was correlatively induced with increasing fibrogenesis in mouse models and human fibrotic organs. Furthermore, transcriptome and protein expression analysis revealed that ITGA11 knockdown in hepatic stellate cells (liver-specific myofibroblasts) markedly reduced transforming growth factor β-induced differentiation and fibrotic parameters. Moreover, ITGA11 knockdown dramatically altered the myofibroblast phenotype, as indicated by the loss of protrusions, attenuated adhesion and migration, and impaired contractility of collagen I matrices. Furthermore, we demonstrated that ITGA11 was regulated by the hedgehog signaling pathway, and inhibition of the hedgehog pathway reduced ITGA11 expression and fibrotic parameters in human hepatic stellate cells in vitro, in liver fibrosis mouse model in vivo and in human liver slices ex vivo. Therefore, we speculated that ITGA11 might be involved in fibrogenic signaling and might act downstream of the hedgehog signaling pathway. These findings highlight the significance of the ITGA11 receptor as a highly promising therapeutic target in organ fibrosis.
