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

In a recent study posted to the medRxiv* preprint server, researchers assessed the impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and severity on coronary and Alzheimer’s disease pathways.

Study: Plasma proteomics of SARS-CoV-2 infection and severity reveals impact on Alzheimer and coronary disease pathways. Image Credit: Nhemz/Shutterstock


Several studies show that SARS-CoV-2 infections can directly affect brain function. Coronavirus disease 2019 (COVID-19) has been found to induce long-term effects on the central nervous system, leading to various neurological symptoms, including altered smell and taste , memory decline, and Alzheimer’s disease-like dementia. This indicates the impact of SARS-CoV-2 infection on neurocognitive impairment and brain injury in patients.

About the study

In the present study, researchers examined the potential biomarkers to assess the proteomic profiles related to COVID-19 infection and associated mortality.

The team detected the plasma protein related to COVID-19 outcomes and developed prediction models to identify dysregulated pathways after infection. This was achieved by the generation of high-throughput proteomic data obtained from 332 SARS-CoV-2-infected individuals and 150 control persons from Washington University (WU) and Barnes-Jewish Hospital (BJH) in St Louis (STL). The control cohort was matched as per age, gender, and race. Plasma samples were obtained during admission to BJH.

The team utilized proteomics data available for 297 COVID-19 cases and 76 control persons from the Massachusetts General Hospital (MGH). Furthermore, differential abundance analysis was conducted to detect proteins associated with COVID-19 infection, ventilation, and related death. A three -stage design was performed (1) The discovery stage identified proteins related to the three COVID-19 outcomes of infection, ventilation, and death in the WU-STL group, (2) the replication stage identified proteins associated with COVID-19 outcomes in the MGH group, and (3) the meta-analyses detected among the rest of the proteins, those that passed the Bonferroni threshold.

Furthermore, prediction models were created for infection, ventilation, and deaths reported after the blood samples were collected. These prediction models were developed using proteins associated with all three outcomes, along with ventilation as well as death-specific models according to proteins that were particular to these phenotypes. The team further used pathway enrichment analyses to detect biological pathways that were disturbed due to outcomes of SARS-CoV-2 infections. Causal co-expression networks were utilized to detect proteins related to COVID-19 that were potentially a part of pathological processes affected by infections.


The study results showed that among the 3236 proteins detected in the discovery cohort, 1,558 were upregulated and 1,678 were downregulated. While 906 proteins were detected in the replication cohort and were regulated in the same direction, 841 proteins were detected after Bonferroni correction and included 363 upregulated and 478 downregulated proteins. Furthermore, among the 332 COVID-19 infected individuals, 82 required ventilation 6.8 ± 7.7 days after hospitalization and 84 during the replication stage.

A total of 63 individuals succumbed to COVID-19 from the discovery group and 41 from the replication group. The team detected 2101 proteins related to death in the discovery cohort, among which 297 proteins were replicated. The team also found 64 proteins related to the COVID-1 outcomes of infection, ventilation, and death. Among these, 59 proteins showed consistent upregulation in all COVID-19 patients, including angiopoietin-related protein 4 (ANGL4), bone morphogenetic protein 10 (BMP10), macrophage colony-stimulating factor 1 (CSF-1), leukocyte-specific transcript 1 protein (LST1), interleukin-1 receptor antagonist protein (IL-1Ra), transforming growth factor beta-1 (TGFB1), protein kinase C zeta type (PKC-Z), and vimentin.

The team also detected 64 proteins that could be potentially utilized to predict COVID-19-infected individuals as well as the persons who will require ventilation. Furthermore, the team found a COVID-19-specific pathway that included genes down-regulated by SARS- CoV-2 infection that was found to be enriched for the three COVID-19 outcomes of infection, ventilation, and mortality. Several other pathways that showed enrichment for immunologic signatures included adaptive, innate, B cell response from the influenza vaccine or cytokine signaling in the immune system. Also, enriched pathways not related to the immune response against viral infection, including Alzheimer’s disease and coronary artery disease pathways, were detected.

Several proteins which were related to COVID-19 outcomes were also part of the pathways associated with Alzheimer’s disease, including branched-chain-amino-acid aminotransferase, mitochondrial (BCAT2), ephrin type-A receptor 5 (EPHA5), glial fibrillary acidic protein (GFAP), neurogranin (NEUG), neurofilament light polypeptide (NFL), microtubule-associated protein tau (MAPT), and transmembrane protein 106B (TMEM106B).

Furthermore, the team found substantially high levels of troponin in COVID-19 patients and those requiring ventilation. High concentrations of the ANGL4 were also detected in COVID-19 infection, ventilation, and death. FURIN, which is associated with coronary artery disease, was also found at increased levels in infection and ventilation outcomes.


Overall, the study findings showed that deep proteomics profiling of COVID-19-infected individuals accurately identified dysregulated proteins due to severe COVID-19 outcomes. The researchers believe that the present study could develop the role of proteomic studies in understanding COVID-19.

*Important notice

medRxiv publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be regarded as conclusive, guide clinical practice/health-related behavior, or treated as established information.


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