Post-Acute COVID-19 Syndrome
Conditions
Keywords
Long COVID, SARS-CoV-2, Post-COVID syndrome, Immune response, Biomarkers, Prospective cohort
Brief summary
The study aims to identify clinical profiles of long-COVID patients and correlate them with immunological and molecular data in order to identify prognostic biomarkers and potential therapeutic targets.
Interventions
OTHERBlood sample collection
A one-time 30 mL blood draw is performed during the inclusion visit for immunological and molecular analysis as part of the HERVCOV research program. No therapeutic intervention is administered, and no samples are stored after analysis.
Sponsors
Hospices Civils de Lyon
Study design
Observational model
COHORT
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
* Documented SARS-CoV-2 infection * Persistent or complex post-COVID symptoms lasting more than 4 weeks or more than 3 months * Patient referred to the EPSILON pathway or to the post-COVID rehabilitation unit * Age ≥ 18 years * Non-institutionalized * Expected survival greater than 6 months
Exclusion criteria
* Refusal to participate or to share data * Uncontrolled comorbidities * Pregnant or breastfeeding women * Persons under legal protection or deprived of liberty * Not affiliated with the French national health insurance system
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Number of participants per clinical cluster at Day 0 (clusters derived from unsupervised multivariate analysis of clinical and paraclinical variables). | At inclusion (Day 0), single time point | At inclusion (Day 0), participants' clinical and paraclinical data will be collected and standardized (z-scores) to derive clinical clusters using unsupervised multivariate methods (principal component analysis for dimensionality reduction if needed, followed by k-means or hierarchical clustering with Euclidean distance). |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Differences in clinical and biological parameters between patient subgroups defined by symptom profile and time since initial infection | At inclusion (Day 0) | atients will be classified into subgroups according to the predominant type and severity of post-COVID symptoms (e.g., fatigue-dominant, cognitive, respiratory) and the interval since acute SARS-CoV-2 infection (\<12 months, ≥12 months). Comparative analyses will assess differences in clinical scores (e.g., fatigue, quality of life), and biological markers (e.g., inflammatory cytokines, immune cell subsets) between groups. |
| Concentration of residual SARS-CoV-2 viral proteins detected in plasma samples at inclusion | At inclusion (Day 0) | Proteomic analyses (e.g., mass spectrometry, immunoassay) will be performed on plasma samples to quantify the presence of SARS-CoV-2 structural or non-structural proteins (e.g., spike, nucleocapsid). |
| Serum biomarker concentrations at Day 0 by clinical cluster | Day 0 | Blood is collected at inclusion (Day 0). Each analyte concentration (pg/mL or ng/mL, as applicable) will be summarized per cluster as mean (SD) or median (IQR) and compared across clusters using ANOVA or Kruskal-Wallis with post-hoc tests as appropriate; effect sizes and 95% CIs will be reported. |
| Association between clinical clusters and serum biomarker panel at Day 0 (standardized mean differences and multivariable models) | Day 0 | Cluster membership will be the exposure; each biomarker (standardized) will be the outcome in linear models adjusted for prespecified covariates (e.g., age, sex, time since first SARS-CoV-2 infection). the investigators will report adjusted differences (β) with 95% CIs and p-values; multiplicity will be handled |
Countries
France
Contacts
CONTACTSébastien Couraud, Pr
Outcome results
None listed