Proteomics profiling in COVID-19 patients identifies dysregulated proteins and pathways

In a recent study posted on medRxiv* Preprint server, researchers evaluated the effects of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and its severity for the coronary and Alzheimer’s disease pathways.

Background

Several studies have shown that SARS-CoV-2 infection can directly affect brain function. Coronavirus disease 2019 (COVID-19) has long-term effects on the central nervous system, causing a variety of neurological symptoms such as changes in odor and taste, poor memory, and dementia such as Alzheimer’s disease. I know. This shows the effect of SARS-CoV-2 infection on neurocognitive dysfunction and brain damage in patients.

About research

In this study, researchers investigated potential biomarkers for assessing proteomic profiles associated with COVID-19 infection and associated mortality.

The team has developed a predictive model to detect plasma proteins associated with COVID-19 results and to identify pathways for post-infection dysregulation. This was achieved by generating high-throughput proteomics data from 332 SARS-CoV-2 infected individuals and 150 controls at Barnes-Jewish Hospital (BJH) in Washington University (WU) and St. Louis (STL). I did. The control cohort was matched by age, gender, and race. Plasma samples were taken during admission to BJH.

The team used proteomics data available for 297 COVID-19 cases and 76 controls at Massachusetts General Hospital (MGH). In addition, differential abundance analysis was performed to detect proteins associated with COVID-19 infection, ventilation, and associated mortality. Three-stage design was performed (1) proteins associated with the three COVID-19 outcomes of WU-STL group infection, ventilation, and death were identified during the discovery stage, and (2) COVID-19 was identified during the replication stage. MGH group results identified proteins associated with, and (3) meta-analysis detected in the remaining proteins (proteins that exceeded the Bonferroni threshold).

In addition, predictive models of infection, ventilation, and mortality reported after blood samples were collected were created. These predictive models were developed using proteins associated with all three outcomes, along with ventilation and death-specific models depending on the proteins specific to these phenotypes. The team also used pathway enrichment analysis to detect biological pathways that were disrupted due to the consequences of SARS-CoV-2 infection. Utilizing the causative co-expression network, we detected a protein associated with COVID-19 that may be part of a pathological process affected by the infection.

result

The study results showed that of the 3236 proteins detected in the discovery cohort, 1,558 were upregulated and 1,678 were downregulated. 906 proteins were detected in the replication cohort and were controlled in the same direction, but 841 proteins were detected after Bonferroni correction, with 363 upregulated proteins and 478 downregulated proteins. Was included. In addition, of the 332 COVID-19-infected individuals, 82 required 6.8 ± 7.7 days after admission and 84 required ventilation during the replication phase.

A total of 63 people died from the discovery group to COVID-19 and 41 from the replication group. The team detected 2101 death-related proteins in the discovery cohort, of which 297 were replicated. The team also discovered 64 proteins associated with COVID-1 outcomes of infection, ventilation, and death. Of these, 59 proteins all include angiopoietin-related protein 4 (ANGL4), bone morphogenesis protein 10 (BMP10), macrophage colony-stimulating factor 1 (CSF-1), and leukocyte-specific transcript 1. Showed consistent upregulation in COVID-19 patients. Protein (LST1), interleukin-1 receptor antagonist protein (IL-1Ra), transforming growth factor beta-1 (TGFB1), protein kinase C zetatype (PKC-Z), and vimentin.

The team also detected 64 proteins that could be used to predict individuals infected with COVID-19 or in need of ventilation. In addition, the team discovered a COVID-19-specific pathway containing genes down-regulated by SARS-CoV-2 infection. It was found to be rich in three COVID-19 results: infection, ventilation, and death. Several other pathways that showed enrichment of immunological features included an adaptive congenital B cell response from the influenza vaccine or cytokine signaling in the immune system. In addition, enriched pathways unrelated to the immune response to viral infections were detected, including pathways for Alzheimer’s disease and coronary artery disease.

Several proteins associated with COVID-19 results are also found in pathways associated with Alzheimer’s disease, such as branched-chain amino acid aminotransferases, mitochondria (BCAT2), ephrin-type A receptor 5 (EPHA5), and glial fibrous acidic proteins. It was a part. (GFAP), neurogranin (NEUG), neurofilament light polypeptide (NFL), microtubule-associated protein tau (MAPT), and transmembrane protein 106B (TMEM106B).

In addition, the team found fairly high levels of troponin in patients with COVID-19 and those in need of ventilation. High concentrations of ANGL4 were also detected in COVID-19 infection, ventilation, and death. FURIN, which is associated with coronary artery disease, was also found to have increased levels of infection and ventilation results.

Conclusion

Overall, study results showed that deep proteomics profiling in individuals infected with COVID-19 accurately identified dysregulated proteins due to severe COVID-19 results. Researchers believe that this study may develop the role of proteomics research in understanding COVID-19.

*Important Notices

medRxiv publishes unpeer-reviewed preliminary scientific reports and should not be considered definitive, guide clinical / health-related behaviors, or be treated as established information.