BREAKING NEWS! Washington University Discover 1,449 Human Host Plasma Proteins Altered By SARS-CoV-2 Infection! Database Useful for Long COVID!

COVID-19 Research: Researchers from Washington University School of Medicine, St Louis, Missouri-USA have in a new study utilizing detailed proteomics discovered that over 1,449 Human Host proteins including critical genes, enzymes and cellular proteases necessary for various cellular functions are altered (damaged, dysregulated or suppressed) by SARS-CoV-2 infections!


 
Identification of proteins dysregulated by COVID-19 infection is critically important for better understanding of its pathophysiology, building prognostic models, and identifying new targets.
 
The study team conducted plasma proteomic profiling of 4,301 human host proteins in two separate and independent datasets and tested for the association for three COVID-19 outcomes (infection, ventilation, and death).
 
The study findings shocking discovered 1,449 proteins consistently in datasets associated in both with any of these three outcomes.
 
The COVID-19 Research team subsequently created highly accurate models that distinctively predict infection, ventilation, and death. These proteins were enriched in specific biological processes including cytokine signaling, Alzheimer’s disease, and coronary artery disease.
 
Mendelian randomization and gene network analyses identified eight causal proteins and 141 highly connected hub proteins including 35 with known drug targets.
 
The study findings provide distinctive prognostic biomarkers for two severe COVID-19 outcomes, reveal their relationship to Alzheimer’s disease and coronary artery disease, and identify potential therapeutic targets for COVID-19 outcomes. 
 
The discovery of these 1,449 huma host proteins that are affected by SARS-CoV-2 infections were published in the peer reviewed journal: iScience.
https://www.cell.com/iscience/fulltext/S2589-0042(23)00485-6
 
The complete database of these 1,449 human host proteins affected by SARS-CoV-2 infections at a new open access site created by the researchers from Washington University School of Medicine.
https://covid.proteomics.wustl.edu/
 
This database can be of great help to researchers conducting research on Post COVID issues and Long COVID and also on research of diseases that can emerge after COVID-19 infections including neurodegenerative diseases such as Alzheimer’s or even about the various cancers that are likely to emerge after SARS-CoV-2 infections.
 
This shocking revelation beats Thailand Medical News earlier findings that about 487 genes, proteases and cellular pathways were affected by the SARS-CoV-2 virus!
 
The findings also indicate that the only approach to dealing with Post COVId and Long COVID health and medica issues would be through a personalized medicine approach and it also sends out an urgent message to the biotech and medica innovations sectors that there is a urgent need for the development of rapid and easier to use and cheap diagnostic platforms that can accommodate as many parameters and biomarkers as possible to aid in this personalized medicine approach to Long COVID.
 
The key findings of the study were:
 
-1,449 plasma proteins are altered by COVID-19 infection, ventilation or death
 
-there were distinct prognostic models for ventilation and death after COVID-19 infection
 
-some of the altered proteins were linked to Alzheimer’s and coronary artery disease pathways
 
-eight proteins were found to potentially causal for COVID-19 infection
 
This is the first study to have conducted deep plasma proteomic profiling on COVID-19 patients to identify biological processes related to the infection and to develop models predicting severe outcomes like ventilation and death.
 
The researchers analyzed data from two large, independent cohorts, using a three-stage study design (discovery, replication, and meta-analysis) and stringent multiple test correction. They identified 1,449 proteins that were dysregulated due to COVID-19 infection, with 841 proteins associated with infection, 833 with ventilation, and 253 with death.
 
The study found that around 20% of proteins were differentially abundant between two cohorts, which seems high. However, stringent criteria were applied, and only proteins passing multiple test corrections in two datasets and the Bonferroni correction in meta-analyses were presented. The high number of proteins may be due to over 90% of the COVID-19 patients in the study having severe infections and being hospitalized, causing significant blood proteome changes compared to healthy controls. Fewer proteins were associated with death due to a smaller number of subjects dying.
 
This study however only tested only 78 immunologic proteins and lacked extensive evaluation of classification performance.
 
In the study, the researchers developed three prediction models for COVID-19 outcomes: infection, ventilation, and death. The first model identifies individuals with COVID-19 infections and predicts their need for ventilation or risk of death with high accuracy (AUC>0.97). Ten proteins were identified with similar predictive power as 64 previously known markers. However, this model doesn't differentiate between ventilation and death. Therefore, two more models were created to specifically predict ventilation and death. Both of these models showed high accuracy, with the death-specific model having an AUC of 0.95. By considering all three models, the most likely outcome for an individual can be determined. These models can help allocate medical resources to high-risk COVID-19 patients.
 
This study focuses on identifying proteins associated with COVID-19 outcomes to understand dysfunctional biological processes and potential causal proteins. The identified proteins are enriched for genes downregulated by SARS-CoV-2 infection, demonstrating that the methodology captures relevant biological processes. Several immune system pathways, including adaptive, innate, and cytokine, were identified, involving proteins such as IL-1Ra, IL-21sR, IFN-a/b R1, IFNA5, TGFB1, and CSF-1. The FDA-approved drug Anakinra has shown improved survival and ventilation-free survival for acute respiratory distress syndrome patients with COVID-19. Additionally, TGFB1 suppresses IFN response, and high CSF-1 levels have been reported in COVID-19 patients, suggesting potential therapeutic targets.
 
The study findings identified several pathways that help understand long-term effects of COVID-19 infection, such as brain-fog/dementia and cardiovascular problems. The analysis supports the central nervous system's involvement in COVID-19 and found proteins linked to Alzheimer's disease (AD) pathogenesis, like APP, TMEM106B, and others. Recent studies suggest a mechanistic overlap between AD and COVID-19. AD and neurodegenerative biomarkers are altered in COVID-19 patients, potentially affecting diagnosis.
 
COVID-19 cases may also increase the risk for coronary artery disease (CAD) due to myocardial injury from viral infection. The study found significantly enriched CAD-related pathways and heart-specific genes, such as Troponin T, ANGL4, FURIN, and ATP1B1. The damage to the brain and heart may cause post-acute COVID-19 syndrome (PACS), which includes symptoms like tiredness, dyspnea, chest pain, brain fog, and headache. The identified dysregulated proteins could be used as a prognostic tool for identifying high-risk CAD and Long COVID cases.
 
Using Mendelian randomization (MR), the researchers identified three proteins (BCAT2, GOLM1, and NUCB1) as causal risk factors and five proteins (IR, PLA2R, ACE, EPHA4, and Fucosyltransferase 3) as causal protective factors for COVID-19 infection. Among these, GOLM1 and ACE were already known as causal risk factors, while the other seven proteins were discovered as causal biomarkers for the first time.
 
The study findings reveal that several proteins are associated with COVID-19-related observations or organ dysfunction. BCAT2 is a key plasma biomarker for COVID-19, while ACE plays a role in the rapid progression of the disease due to dysregulated ACE/ACE2 balance. FUT3 genotypes can offer protection against severe COVID-19 cases, and Eph receptors may contribute to neurodegenerative disease development in relation to COVID-19. IR interacts with SARS-CoV-2, PLA2R is linked to membranous nephropathy, and NUCB1 is implicated in Alzheimer's disease pathogenesis. Targeting these proteins may help reduce COVID-19 infection risks and related dysfunctions.
 
The study used a Bayesian approach to identify key proteins in the network as potential therapeutic targets for COVID-19. A total of 141 key proteins were found, with 35 having known drug targets. Fostamatinib, a tyrosine kinase inhibitor, was found to target 5 hub proteins and has shown promise in clinical trials for treating COVID-19-related acute respiratory distress syndrome. Tetracyclines, a class of antibiotics, target PRIO and MK12 and may have potential to reduce COVID-19 severity through multiple pathways, including RNA replication inhibition or downregulation of the NF-κB pathway. Further research is needed to confirm the impact of these targets and FDA compounds on COVID-19 outcomes.
 
The study also found that obesity and diabetes can lead to a dysregulated immune response, causing more severe lung issues. Obesity, as indicated by a high BMI, has been shown to increase severe COVID-19 outcomes by 1.8 times. The study didn't collect obesity and BMI data, so it couldn't consider them as factors. Some proteins identified in COVID-19 patients may be related to BMI, as previous research has found correlations between BMI and certain proteins. The study identified a number of proteins with higher levels in COVID-19 cases, patients needing ventilation, and those who died. However, since these proteins are also linked to BMI, it's possible that the identified proteins may be related to BMI rather than COVID-19 outcomes.
 
In conclusion, the study teamconducted an in-depth proteomics study on COVID-19 patients, identifying proteins linked to severe outcomes. They developed an interactive web portal for scientists to access the data and created prediction models for ventilation and death. Additionally, they found connections between Alzheimer's Disease, coronary artery disease, and COVID-19, as well as seven new potential druggable targets. These findings demonstrate the potential of proteomic studies to enhance the understanding of COVID-19 biology and disease progression.
 
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