COVID-19 biomarkers

COVID-19 biomarkers integrates and harmonizes curated COVID-19 biomarker data with ontology-based annotations and identifier mappings to support analysis of host response and disease mechanisms.

Key Features:

• Integrated Knowledgebase: An integrated repository contains 138 unique COVID-19 biomarkers curated and harmonized from multiple sources.
• Comprehensive Biomarker Entries: Each biomarker entry is annotated with canonical UniProtKB accession, PubChem Compound ID, Cell Ontology ID, Protein Ontology ID, NCI Thesaurus Code, Disease Ontology ID, BEST biomarker category, and specimen type using Uberon Anatomy Ontology.
• Ontology Standards: Use of ontology standards (Cell Ontology, Protein Ontology, NCI Thesaurus, Disease Ontology, Uberon) enhances interoperability and standardized annotation across datasets.
• Biomarker Type Combinations: Cross-validation and manual curation identify 265 unique biomarker type combinations reflecting multiple proposed roles for the same biomarker substances.
• Trend Analysis: Preliminary trends highlight immune-related markers (e.g., SAA, TNF-α, IP-10), coagulopathy markers (e.g., D-dimer, antithrombin, VWF), and overlaps with cancer-associated markers (e.g., ACE2, IL-6, IL-4, IL-2).

Scientific Applications:

• Research into Host Responses: Enables analysis of variability in host responses to SARS-CoV-2 infection driven by immunity, genetics, and comorbidities.
• Clinical Translation: Supports translation of biomarker evidence toward diagnostic and therapeutic strategy development.
• Hypothesis Testing: Facilitates testing of hypotheses on COVID-19 pathogenesis, particularly immune response and coagulation disorder mechanisms.

Methodology:

Data collection and integration methods leverage a data model originally developed for cancer biomarker research, incorporate rapid crowdsourcing of COVID-19 biomarker data, and apply cross-validation for annotation consistency.