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Proteomic analysis of Post-COVID Condition: Insights from supernatant and pellet blood fractions

ABSTRACT: Post-COVID condition (PCC), or long COVID, continues to significantly impact a considerable number of COVID-19 survivors, affecting their quality of life long after the initial infection. In a novel approach utilizing Sequential Window Acquisition of All Theoretical Mass Spectra (SWATH-MS) technology, a comprehensive proteomic analysis was conducted that included both plasma and the typically discarded residual blood fraction, known as the pellet. This study examined protein expression profiles in 65 individuals diagnosed with PCC, compared to 9 healthy controls, revealing distinct proteomic signatures that correlate with the severity of clinical symptoms. A significant outcome of this research is the development of a proteomic severity scale that aligns closely with clinical assessments, providing a new method for categorizing the severity of PCC. This scale is particularly valuable for enhancing patient management strategies and guiding therapeutic interventions. By analyzing both the plasma and pellet blood fractions, the study highlights the importance of considering all blood components in PCC research, which could lead to novel insights into the disease mechanisms. The findings indicate substantial immunological and metabolic disruptions that extend beyond the acute phase of COVID-19, suggesting that PCC may involve more complex systemic changes than previously understood. The identification of key biomarkers and pathways differentiating mild from severe PCC underscores the potential of proteomic profiling to reveal the underlying pathophysiology of long COVID and to pinpoint potential therapeutic targets, advancing the overall understanding of the condition's long-term impacts.

INSTRUMENT(S):

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Blood

DISEASE(S): Long Covid

SUBMITTER: Susana Bravo

LAB HEAD: Susana Bravo

PROVIDER: PXD051740 | Pride | 2026-02-16

REPOSITORIES: Pride

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Project description:Postural orthostatic tachycardia syndrome (POTS) is a chronic neurological disorder of the autonomic nervous system (ANS) that is characterized by an excessive increase in heart rate upon orthostatic challenge. The symptoms of POTS are often debilitating, and it primarily affects young females. Even prior to coronavirus disease 2019 (COVID-19) pandemic, POTS was prevalent, affecting an estimated 0.5% to 1% of the entire population in the United States (US). Since the COVID-19 pandemic, the incidence of POTS has acutely risen, adding roughly 6-7 million POTS patients in the US alone. Despite its importance, there is currently no reliable serum biomarker for POTS. One of the major hurdles in identifying biomarkers of POTS is the heterogenous nature of the clinical syndrome. To address this challenge, we focused our analysis on patients from the recent increase in cases of post-COVID-19 onset POTS (PC-POTS). We hypothesized that PC-POTS represents a relatively homogeneous subgroup of POTS, likely triggered by the same pathogen, and presents with symptoms that are more pronounced compared to those in healthy controls. We identified 752 proteins from 18 serum proteome samples composed of 9 PC-POTS patients and 9 health control (HC) individuals, and 31 proteins showed a significant protein abundance difference in PC-POTS. Notably, the majority of the elevated proteins are associated with either actin filaments or immune functions/inflammation. The Weighted Gene Co-Expression Network Analysis (WGCNA) revealed that the module 7 (M7) most highly correlated with the diagnosis also exhibited strong correlations with various sample traits such as the Orthostatic Intolerance Score, Gastrointestinal Score, Pupillomotor Score, and the COMPASS-31 score. The proteins MTPN, TAGLN2, ADP-ribosylation factor 1, PDLIM1, PPIA, CNN2, LGALSL, TXN, TLN1, TUBA4A, IL4, TREML1, GP1BA, and GP6 were identified as common proteins overlapping in various sample traits. Cell-type enrichment analysis revealed that M7 is highly associated with immune and neuronal cells. The main pathways identified in this module include the integrin signaling pathway, blood coagulation, and glycolysis. This suggests that these proteins could potentially serve as biomarkers for PC-POTS. This study utilizes mass spectrometry-based proteomic analysis to identify serum biomarkers that differentiate patients with PC-POTS from HC individuals, thus establishing a foundation for further research and validation.

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Proteomic analysis of Post-COVID Condition: Insights from supernatant and pellet blood fractions

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