Long COVID Neuroinflammation Biomarkers and Drug Screening

A clinical study analyzes neuropeptide and cytokine expression in 90 long COVID patients with neuropsychological sequelae. Experimental data shows upregulation of IL-6, IL-10, and Substance P, and computational screening identifies aprepitant and N-acetyl-L-tryptophan as potential NK1R antagonists.

Use Cases

• Correlate patient-reported symptom severity (fatigue, headache, anxiety, depression) with measured IL-6, IL-10, and Substance P expression levels.
• Analyze biomarker expression (IL-6, IL-10, SP) differences between symptomatic and asymptomatic long COVID patient groups.
• Evaluate computational drug screening results, including binding affinity scores (e.g., -9.3 kcal/mol for aprepitant) and molecular dynamics stability metrics (RMSD, RMSF, Rg).
• Assess demographic distributions (age, gender) and symptom persistence duration (19-44 weeks) across patient cohorts.

Strengths

• Includes experimental biomarker data (IL-6, IL-10, SP) from 90 patients with detailed demographic breakdown (60% male, 40% female).
• Provides computational drug screening results with specific quantitative metrics like binding affinity and RMSD values.
• Covers multiple neuropsychological sequelae with reported prevalence percentages (e.g., 48% fatigue, 28% anxiety).

Limitations

• Very small dataset (379.8 KB DOCX file) containing a study summary, not a raw, analyzable tabular dataset.
• No structured data rows or columns are provided; analysis requires extracting information from textual descriptions and figures.
• Patient sample size of 90 limits statistical power for subgroup analyses.

Provenance

Source

figshare, author Muhammad Abdullah

Collection Method

Clinical screening and blood sample analysis (ELISA, RT-qPCR) on long COVID patients, followed by computational virtual screening of nine drugs.

Time Range

Study period not specified; data reflects a cross-sectional analysis.

Freshness

2026-03-26

Geography

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