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Persistence of SARS-CoV-2 S1 Protein in CD16+ Monocytes in Post-Acute Sequelae of COVID-19 (PASC)

Hyperlink:     Link to Study

Date:               09 January 2022

Authors:        

Patterson, B.K; Francisco, E.B; Yogendra, R; Long, E; Pise, A; Rodrigues, H;  Hall, E; Herrera, M; Parikh, P; Guevara-Coto, J; Triche, T.J.

 This study investigates how lingering viral components may drive the persistent symptoms of Long COVID (PASC). Researchers evaluated immune markers in 144 individuals across mild, moderate, and severe COVID-19, as well as PASC cases. A key finding is that the S1 protein—a component of SARS-CoV-2—can remain in CD16+ monocytes for up to 15 months post-infection, even when the virus itself is undetectable.

Two notable findings underscore potential mechanisms of Long COVID:

1. Elevated Non-Classical Monocytes: PASC patients exhibited significantly higher levels of these CD16+ cells than healthy controls.

2. Residual Viral Fragments: These monocytes contained the S1 protein but lacked full viral RNA, suggesting inflammation arises from fragments rather than active replication.

Advanced analytical methods confirmed that this residual protein can trigger immunological and inflammatory pathways, possibly explaining chronic symptoms such as fatigue, cognitive issues, and ongoing inflammation.

 Hyperlink:     Link to Study

Hyperlink:     Link to Study

Authors:         Patterson, B.K; Yogendra, R; Guevara-Coto, J; Mora-Rodriguez, R.A; Osgood, E; Bream, J; Parikh, P; Kreimer, M; Jeffers, D; Rutland, C; Kaplan, G

Date:               14 May 2024

This case series explores the potential of maraviroc and pravastatin as treatments for Long COVID, a condition characterized by persistent symptoms such as fatigue, brain fog, and breathing difficulties. The study included 18 participants with confirmed SARS-CoV-2 infection and symptoms lasting over three months, assessing the effects of these drugs on inflammation and immune regulation.

1.     Targeted therapeutic approach: Maraviroc, a CCR5 receptor blocker, and pravastatin, an anti-inflammatory statin, were used to modulate immune and vascular inflammation associated with Long COVID.

2.     Clinical improvements observed: Over 6 to 12 weeks, patients showed significant symptom relief across validated scales, including the Fatigue Severity Scale and COMPASS-31 autonomic dysfunction questionnaire, with reductions in inflammatory markers like VEGF and sCD40L.

These promising findings highlight a potential therapeutic strategy for PASC, providing a strong rationale for larger, randomized controlled trials to confirm efficacy and offer relief to affected individuals worldwide.

Hyperlink:     Link to Study

Hyperlink:     Link to Study

Authors:         Patterson, B.K; Guevara-Coto, J; Yogendra, R; Francisco, E.B; Long, E; Pise, A; Rodrigues, H; Parikh, P; Mora, J; Mora-Rodríguez, R.A.

Date:               27 June 2021

This research aimed to identify immune markers that predict COVID-19 severity and the risk of Long COVID (PASC) using advanced machine learning techniques. Blood samples from 224 individuals, including healthy controls, mild-to-moderate COVID-19 cases, severe cases, and Long COVID patients, were analyzed to uncover distinct immune profiles.

1.     Key immune markers identified: Severe and PASC patients showed elevated inflammatory markers, including CCL5 (RANTES), IL-6, and VEGF, while PASC patients exhibited reduced regulatory T cells and CD4/CD8 T cells expressing PD-1, suggesting persistent immune dysregulation.

2.     Machine learning for risk prediction: Models such as random forest classifiers effectively differentiated patient groups with high accuracy, predicting disease severity and identifying individuals at risk of developing PASC.

3.     Quantitative immune scoring for treatment guidance: The study introduced the Long Hauler Index (LHI), defined as LHI = (IL-2 + IFN-γ) / CCL4, highlighting cytokines' role in immune dysregulation and offering a potential biomarker for monitoring Long COVID.

By combining machine learning and immune profiling, this research advances precision medicine for COVID-19, providing tools to predict outcomes and guide treatment strategies.

Hyperlink:     Link to Study

Hyperlink:     Link to Study

Authors:         Patterson, B.K; Guevara-Coto, J; Mora, J; Francisco, E.B; Yogendra, R; Mora-Rodríguez, R.A; Beaty, C; Lemaster, G; Kaplan DO, G; Katz, A; Bellanti, J.A.

Date:               26 August 2024

This study addresses the diagnostic challenges of Long COVID (LC) and Chronic Lyme Disease (CLD), two conditions with overlapping symptoms like fatigue, brain fog, and post-exertional malaise. Researchers analyzed cytokine profiles from 347 individuals, including LC patients, CLD patients, and healthy controls, using machine learning to create a diagnostic tool that distinguishes between LC and CLD with high accuracy.

1. Machine learning for precision diagnosis: The study employed tree-based machine learning models, including gradient-boosting machines (GBMs), which achieved 97% sensitivity and 90% specificity in differentiating LC from CLD in blinded tests.

2. Cytokine-based Lyme Index: Researchers developed a Lyme Index with two features derived from cytokine profiles to further confirm CLD diagnoses:

   1. Feature 1: (TNF-α + IL-4) / (IFN-γ + IL-2)

   2. Feature 2: (TNF-α × IL-4) / (IFN-γ + IL-2 + CCL3)

These features were selected for their immunological relevance to CLD and LC, enhancing diagnostic precision by distinguishing between the two conditions and reducing errors from overlapping symptoms. The study underscores the distinct immune pathways involved, highlighting the importance of precision diagnostics for tailored treatment. By leveraging immune biomarkers and machine learning, the Lyme Index represents a significant advancement in diagnosing chronic inflammatory diseases.

Hyperlink:     Link to Study