---
title: "Small extracellular vesicle proteome shows persistent inflammatory and coagulopathic signatures in"
id: "frontiers-in-immunology-1-small-extracellular-vesicles-proteome-reveals-persistent-inflammatory-and"
canonical_url: "https://medichelpline.com/clinical-feed/frontiers-in-immunology-1-small-extracellular-vesicles-proteome-reveals-persistent-inflammatory-and"
content_type: "clinical_feed_article"
specialty: "Infectious Disease"
source_name: "Frontiers in Immunology"
source_url: "https://www.frontiersin.org/articles/10.3389/fimmu.2026.1805159"
published_at: "2026-07-20T00:00:00.000Z"
evidence_level: "Journal Feed"
license: "CC-BY-NC-4.0 / Informational Use"
---
# Small extracellular vesicle proteome shows persistent inflammatory and coagulopathic signatures in
## Provenance & Clinical Metadata
- **Canonical URL:** https://medichelpline.com/clinical-feed/frontiers-in-immunology-1-small-extracellular-vesicles-proteome-reveals-persistent-inflammatory-and
- **Specialty:** [Infectious Disease](https://medichelpline.com/clinical-feed/infectious-disease.md)
- **Primary Source:** Frontiers in Immunology
- **Source URL:** [Original Journal Publication](https://www.frontiersin.org/articles/10.3389/fimmu.2026.1805159)
- **Published At:** 2026-07-20T00:00:00.000Z
- **Evidence Rating:** Journal Feed
## Executive GIST (TL;DR)
- Study compared the **protein cargo of plasma-derived small extracellular vesicles (SEVs)** from individuals with post-acute sequelae of SARS-CoV-2 (PASC, n=20 overall; n=13 for proteomics) versus PASC-negative controls (n=11 overall; n=10 for proteomics) using size-exclusion chromatography and the Olink Explore HT platform. - PASC-positive participants commonly reported fatigue, shortness of breath, brain fog, sleep disturbances, musculoskeletal or chest pain, and rash; symptom ascertainment used REDCap surveys and clinical records. - SEV particle size distribution and concentration did not differ significantly between PASC-positive and PASC-negative groups; canonical EV markers (CD9, CD63, CD81, Integrin β1, Alix, TSG101) were detected by Western blot. - Proteomic profiling identified substantial SEV protein dysregulation in PASC: 269 proteins significantly altered overall, with 84 upregulated and 21 downregulated proteins showing >2-fold change in PASC in the abstract summary. - Dysregulated SEV proteins mapped to pathways involving **coagulation**, **inflammation**, apoptosis, fibrosis, extracellular matrix remodeling, mitochondrial dynamics, and immune activation according to enrichment analyses (GO, KEGG, IPA, Reactome). - Specific proteins persistently elevated in PASC SEVs included FN1, HCF-H, HGF, and IL-17RA; HGF and IL-17RA showed larger differences in SEVs than in matched plasma and were significantly altered in SEVs but not plasma. - Six clusters of differential SEV protein expression were identified by heatmap analysis, with one cluster predominantly downregulated and five clusters predominantly upregulated in PASC. - Statistical analysis used limma for differential expression and Wilcoxon Rank Sum tests for symptom associations; pathway enrichment used Enrichr, IPA, STRING and Cytoscape. - The authors conclude SEV proteomic alterations highlight inflammatory, thrombotic, and neurobiological dysregulation in long COVID and support the potential of SEVs as biomarker sources and mechanistic mediators. - Several methodological details reported: SEVs isolated from 0.5 ml platelet-free EDTA plasma via qEV size-exclusion columns, pooled fractions 7–10, concentrated to 500 µl; NTA performed with NanoSight (five 60-second videos); Olink assays reported as NPX (log2).
## Clinical Analysis & Structured Key Points
About us All journals All articles Submit your research Search Frontiers in Immunology Sections Articles Research Topics Editorial board About journal Published in Frontiers in Immunology Inflammation 7 impact factor 11.3 citescore Part of a Research Topic Coagulation, Inflammation, and Healing: Defining the Intricate Network for Clinical Innovation 41k views 22 articles Editor & Reviewers Edited by B W Baojun Wu Reviewed by E J Edward J Goetzl L M Luzia Maria De-Oliveira-Pinto Outline Abstract Introduction Materials and methods Results Discussion Data availability statement Ethics statement Author contributions Funding Conflict of interest Generative AI statement Publisher’s note References Figures and Tables Figure 1 View in article Figure 2 View in article Figure 3 View in article Figure 4 View in article Figure 5 View in article Figure 6 View in article Table 1 Demographic and clinical characteristics of individuals with and without PASC. View in article ORIGINAL RESEARCH article Front. Immunol., 20 July 2026 Sec. Inflammation Volume 17 - 2026 | https://doi.org/10.3389/fimmu.2026.1805159 Small extracellular vesicles proteome reveals persistent inflammatory and coagulopathic dysregulation in long-COVID S C Sivasankar Chandran 1 L C Ling Chen 1 A K Anil Kumar Ram 1 L S Leslie Spikes 1 P C Prabhakar Chalise 2 N K Navneet K. Dhillon 1* 1. Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Kansas City, KS, United States 2. Department of Biostatistics & Data Science, University of Kansas Medical Center, Kansas City, KS, United States Abstract Background: Post-acute sequelae of SARS-CoV-2 (PASC) or Long-COVID affects millions and remains mechanistically undefined due to its heterogeneous clinical presentation. Identifying robust biological signatures is essential for understanding disease mechanisms and improving diagnosis. Here, we investigated the protein cargo of plasma-derived small extracellular vesicles (SEVs) from PASC-positive and PASC-negative individuals to identify EV-linked biomarkers of Long-COVID. Methods: SEVs were isolated from EDTA plasma of PASC-positive (n=20) and PASC-negative (n=11) individuals using size-exclusion chromatography. SEV protein cargo was profiled across more than 5400 proteins using the Olink Explore HT platform. Results: PASC-positive patients commonly reported fatigue, shortness of breath, brain fog, sleep disruption, and mood changes. Proteomic analysis revealed 269 significantly dysregulated proteins, including 84 upregulated and 21 downregulated, with a fold change >2 in PASC. These differentially altered proteins were enriched in pathways related to coagulation, inflammation, apoptosis, fibrosis, extracellular matrix remodeling, mitochondrial dynamics, and immune activation. PASC-positive SEVs showed persistent increases in FN1, HCF-H, HGF, and IL-17RA, proteins previously dysregulated in acute COVID-19. These markers showed greater differences in SEVs than in matched plasma, particularly HGF and IL-17RA, which were significantly altered in SEVs but not in plasma. Conclusion: Proteomic alterations in SEVs from PASC patients highlight the inflammatory, thrombotic, and neurobiological dysregulation, underscoring the potential of SEVs as biomarkers and mechanistic drivers of long COVID. Introduction Regardless of the severity of the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection, studies indicate that approximately 45% of COVID-19 survivors continue to exhibit post-acute sequelae of SARS-CoV-2 infection (PASC), commonly referred to as long COVID (1). More recently, a 2025 meta-analysis estimated that the global pooled prevalence of long COVID is about 36% among individuals with confirmed COVID-19 (2). The short- and long-term consequences of PASC markedly affect patients’ quality of life, productivity, and overall health care expenditures (3). The clinical presentation of PASC varies widely and therefore represents a significant challenge for both clinical management and public health (4) (5). PASC is characterized by a broad spectrum of symptoms affecting multiple physiological systems, with over 100 distinct manifestations reported. As a multiorgan condition, PASC frequently presents with persistent pulmonary symptoms such as dyspnea, reduced exercise tolerance, hypoxemia, and restrictive ventilatory defects (6). Neuropsychiatric manifestations such as fatigue, cognitive deficits (brain fog), anxiety, and sleep disturbances are also frequently observed (7, 8). Cardiovascular manifestations, including palpitations, chest discomfort, and myocardial impairments, further contribute to the clinical burden (9, 10). In addition, endocrine (11, 12) renal, gastrointestinal, hepatobiliary, and dermatologic abnormalities, highlight the multisystemic nature of post-acute sequelae of COVID-19 (13). Several interrelated pathogenic mechanisms have been proposed to underlie the development of long COVID, with the most prominent including immune dysregulation, viral persistence, or the continued presence of viral components, autoimmune responses, and endotheliopathy (5). Extracellular vesicles (EVs) released by cells in response to multiple physiological and pathological stimuli, such as infection, stress, and inflammation, play a crucial role in disease pathogenesis (14–18). EVs carry bioactive molecules such as proteins, lipids, and microRNAs that have the ability to modulate inflammation, coagulation, vascular remodeling, and immune responses (19, 20). EV cargo is increasingly recognized as a valuable source of biomarkers for monitoring disease progression with improved detection of subtle molecular alterations. Compared with whole−blood analytes, plasma−derived EV contents may serve as better biomarkers because they are less complex, shielded from degradation, and remain stable for extended periods (21, 22). EVs have already gained considerable importance as informative biomarkers in acute COVID-19, reflecting both viral persistence and host immune responses (23). Emerging evidence indicates that EV profiles differ between mild and severe disease and are closely associated with inflammation and immune dysregulation, supporting their utility in assessing disease severity (14). Our previous proteomic analysis of EVs from patients with acute COVID-19 showed enrichment of proinflammatory, procoagulant, immunoregulatory, and tissue remodeling proteins, clearly distinguishing symptomatic patients from uninfected controls with matched comorbidities (17). Furthermore, EV cargo differed between moderate and critical disease severity. Other studies have similarly highlighted EVs as a promising liquid biopsy platform for integrated diagnosis and monitoring of COVID-19 disease progression (14, 24). In this study, we now investigate the protein cargo in circulating small EVs (SEVs) from PASC positive patients to identify EV-associated biomarkers indicative of Long-COVID and further understand the pathophysiology of PASC. Materials and methods Human samples and data collection Participants classified as having post−acute sequelae of SARS−CoV−2 infection (PASC) (N = 20) were those who reported one or more ongoing symptoms persisting beyond 6-9 months after their initial infection, except one participant infected 66 days prior, and two others infected 85 and 89 days before, respectively. Symptom persistence was identified either through responses to a REDCap survey or documentation of continued symptoms during clinical follow−up. Reported symptoms included fatigue, post−exertional malaise, dyspnea, cough, anosmia or ageusia, fever, myalgias, headaches, chest discomfort, cognitive difficulties (“brain fog”), sleep disturbances, mood changes, rash, and tinnitus. Individuals without PASC were selected from participants in the ACTIV−2 clinical trial who had completed the first 24 weeks of study follow−up. These participants had a confirmed prior SARS−CoV−2 infection (PCR−positive) 6-15 months before assessment and reported no persistent symptoms (N = 11). One PASC negative individual, however, underwent a blood draw at 84 days after acute infection. For validation analyses, plasma samples were also obtained from hospitalized acutely infected patients with a confirmed positivity for COVID-19 PCR (N = 10) and from healthy volunteers whose samples were collected before the COVID−19 pandemic (N = 5). All participants were enrolled through The University of Kansas Health System (TUKHS) COVID-19 Biorepository, and blood samples were collected in accordance with the protocols approved by the Institutional Review Board. Demographic characteristics, comorbidities, body mass index, interval from last positive test to study enrollment, and symptom profiles were obtained from electronic medical records or participant surveys and stored in a secure database. Survey data were collected using REDCap and incorporated the standardized World Health Organization (WHO) Global COVID−19 Clinical Platform Case Report Form for Post−COVID Conditions. Participants completed surveys at enrollment and at 3−month intervals thereafter. Isolation of small EVs from plasma samples EDTA plasma was separated within 4 hours of collection by centrifugation at 2000 × g for 15 minutes at 4 °C, aliquoted immediately, and stored at −80 °C until analysis. Plasma turbidity was monitored; in cases of hemolysis, it was documented, and such samples were excluded from EV isolation. Approximately 500 µl of frozen EDTA plasma (without prior freeze–thaw cycles) was thawed at room temperature and centrifuged at 2500 × g for 15 min at room temperature to obtain platelet-free plasma (PFP). The PFP was subsequently centrifuged at 20,000 × g for 15 min at 4 °C to pellet large extracellular vesicles, which were removed and stored separately. The resulting supernatant was subjected to small EV (SEV) isolation via size-exclusion chromatography (qEV original 35 nm columns; Izon Science, Cambridge, MA) as previously reported (17). Final SEV preparation was reconstituted in the same volume as the starting plasma volume used for isolation of EVs. NanoSight nanoparticle tracking analysis (NTA) was used to identify EV-enriched fractions, and fractions 7–10 were pooled. Pooled SEV fractions were concentrated to a final volume of 500 µl using Amicon Ultra-4 centrifugal filters (10 kDa; Millipore Sigma, USA). Characterization of SEVs To assess the size distribution and concentration of SEVs, NTA was performed in each sample as described previously (17). Samples were diluted 1:100 in phosphate-buffered saline (PBS) and gently vortexed before analysis. The diluted suspensions were then introduced into the sample chamber using a syringe pump. For each sample, five 60-second videos were recorded using NanoSight software (version NTA 3.4) with screen gain set to 4 and camera gain to 10 during acquisition. A detection threshold of 10 and screen gain of 10 were used for data processing. Manual focusing was performed to optimize visualization and maximize SEV detection. Isolated SEVs were lysed using a RIPA lysis buffer for Western Blot analysis of EV markers. Approximately 5 μg of SEV lysates were resolved on a 12% SDS-PAGE gel and subsequently transferred onto an Immobilon-P PVDF membrane. The membranes were incubated overnight at 4 °C with primary antibodies against established EV markers, including the tetraspanins: CD9, CD81, CD63; Integrin β1; and cytosolic proteins: TSG101 and Alix. HRP-conjugated IgG secondary antibodies were used for detection. Signals were developed using the Pierce ECL and SuperSignal West Femto (Thermo Fisher Scientific, USA), and the images were captured with the LI-COR Odyssey Fc imaging system. Olink proximity extension analysis An equal volume of SEV sample from each PASC-positive (n=13) and PASC-negative (n=10) individual was lysed for Olink analysis using a proteomic-grade lysis buffer as described in previous studies (17, 25). Fifty microliters of lysed SEVs was then transferred in a randomized order to a 96-well PCR plate and submitted to the Clinical Genomics Center at the Oklahoma Medical Research Foundation for analysis. SEV protein cargo was profiled using the Olink Explore HT panels. Samples were randomly distributed across the plate, and both assay performance and sample quality were monitored using four internal controls. Protein abundance was reported as normalized protein expression (NPX) values on a log2 scale, where higher NPX values correspond to higher protein expression levels. Samples failing technical quality metrics or exhibiting abnormally high variability were excluded from further analysis. For validation, ELISA kits were obtained from Proteintech (Catalog numbers KE00788; KE00168, KE00900; KE00039) and the experiments were performed as per the manufacturer’s instructions. Statistical analysis Differences in protein expression NPX values between PASC-positive and PASC-negative groups were assessed using linear models for omics data implemented in the limma Bioconductor R package (26). The Wilcoxon Rank Sum test was used to compare protein levels between participants with or without binary clinical symptoms such as shortness of breath, brain fog, and sleep disturbance. The protein level changes were visualized using heatmaps, and the differential expression analyses were summarized with volcano plots. All protein expression analyses were performed using R software version 4.5.0. For the SEV concentration measurement, Student’s t-test analysis was carried out using GraphPad Prism 9. A p-value 0.9999 Days of Hospitalization (if applicable) 4-29 2-35 0.8 COVID-19 Vaccinated 9 (69.23%) 6 (60.00%) 0.685 Boosted 6 (46.15%) 4 (57.14%) 0.6802 Co-morbidities Diabetes 2 (15.38%) 2 (25.00%) >0.9999 Hypertension 4 (30.77%) 2 (25.00%) 0.66 Congestive Heart Failure 1 (7.69%) 1 (12.50%) >0.9999 Coronary Artery Disease 0 (0.00%) 3 (37.50%) 0.0678 Kidney Disease 1 (7.69%) 1 (12.50%) >0.9999 Pulmonary Disease 5 (38.46%) 1 (12.50%) 0.179 Depressive Disorder 4 (30.77%) 1 (12.50%) 0.3394 Anxiety 3 (23.08%) 0 (0.00%) 0.2292 GERD 4 (30.77%) 1 (12.50%) 0.3394 Smoking Status 1 (7.7%) 0 (0.00%) >0.9999 Hyperlipidemia, Hypercholesterolemia, or Dyslipidemia 3(23.08%) 1 (12.50%) 0.6036 Migraines 3 (23.08%) 0 (0.00%) 0.2292 PASC symptoms Fatigue 10 (76.92%) NA Post-exertional malaise 3 (23.08%) NA Shortness of Breath 9 (69.23%) NA Coughing 2 (15.38%) NA Loss of taste or smell 4 (30.77%) NA Fever 1 (7.69%) NA Body aches, headaches, chest pain, stomach pain 6 (46.15%) NA Brain Fog 6 (46.15%) NA Sleep Disturbances 5 (38.46%) NA Mood Changes 2 (15.38%) NA Rash 5 (38.46%) NA Demographic and clinical characteristics of individuals with and without PASC. 1 n (%); Median (IQR). Plasma-derived SEV characterization reveals no differences in particle number or size between PASC-positive and PASC-negative individuals SEVs isolated by size exclusion chromatography from PASC-positive and PASC-negative plasma samples were evaluated for particle concentration and size distribution. Particle size distributions were comparable between the groups, with the majority of SEVs falling within the 50-200 nm range, as illustrated in Figure 1A. Total SEV concentration, normalized per milliliter of plasma or per microgram of EV protein, also showed no significant differences between the groups (Figures 1B, C). Western blotting confirmed the presence of canonical EV markers, including tetraspanins, CD9, CD81, and CD63, as well as Integrin β1, Alix, and TSG101 (Figure 1D). Figure 1 Characterization of plasma-derived small extracellular vesicles (SEVs) from PASC-positive (n = 13) and PASC-negative (n = 10) patients. SEVs were isolated from 0.5 ml of platelet-free EDTA plasma. (A) A representative line diagram of EV size distribution and (B) Nanoparticle tracking analysis (NTA) of total SEV counts expressed as particles per ml of the final EV suspension; and (C) SEV counts per ug of EV protein in each group using NanoSight nanoparticle tracking analyzer. (D) Representative western blot images showing EV-specific markers in the EV lysate from PASC samples. SEV protein cargo exhibits significant alterations in PASC-positive individuals Proteomic profiling using the Olink Explore HT platform identified substantial differences in SEV-associated proteins between PASC-positive (n = 13) and PASC-negative (n = 10) groups. Heatmaps illustrate differential protein expression patterns between groups (Figure 2A), with pronounced alterations in the proteins related to prothrombotic activity, apoptosis, cell proliferation, complement activation, and inflammatory signaling. The heatmap highlights differential SEV protein expression between groups. Overall, six distinct clusters of protein expression patterns were identified. Notably, one cluster on the top showed a consistent downregulation of proteins in the PASC-positive group, while the remaining five clusters exhibited predominant upregulation of SEV protein cargo in PASC-positive individuals. Figure 2 Proximity extension analysis (PEA) of circulating SEVs in PASC patients. EDTA plasma samples from PASC-positive (n = 13) and PASC-negative (n = 10) individuals were analyzed to compare SEV-associated protein cargo using Olink’s multiplex PEA technology. (A) A heatmap with hierarchical clustering displays significantly altered EV proteins between the two groups (P<0.05). (B) Volcano plots illustrate pairwise post hoc comparisons of SEV protein cargo, with −log10 (P value) plotted against the mean difference. Differentially altered proteins with P < 0.05 are highlighted in red. Positive and ne
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