OsteoDIP

OsteoDIP curates and integrates published human osteoarthritis RNA expression profiles and associated clinical data to support comparative analyses and biomarker discovery.

Key Features:

• Curated Data Collection: OsteoDIP annually searches PubMed for "osteoarthritis gene expression profile" and includes only publications with patient data and reported differentially expressed genes, with scope expanded in 2020 to include non-coding RNAs.
• Integration with GEO Datasets: GEO datasets are integrated using filters such as 'Homo sapiens' and 'Expression profiling by array', resulting in 28 datasets that include clinical data alongside gene expression profiles.
• Extensive Data Coverage: The literature-derived collection comprises 1,204 curated papers with 63 selected for inclusion covering 1,924 human samples, and GEO datasets add data from 1,012 patients.
• Focus on Key Tissues and Joints: Most studies focus on knee osteoarthritis with cartilage as the primary tissue type.

Scientific Applications:

• Biomarker identification: Centralized RNA expression and clinical data enable discovery and cross-study validation of candidate biomarkers for osteoarthritis.
• Disease mechanism analysis: Aggregated differentially expressed genes and non-coding RNAs support investigation of molecular pathways involved in osteoarthritis pathogenesis.
• Therapeutic target discovery: Integrated datasets facilitate identification of gene-level targets and assessment across multiple patient cohorts.
• Personalized medicine analyses: Combined clinical annotations and expression profiles enable cohort stratification and exploratory analyses relevant to patient-specific outcomes.

Methodology:

Data compilation uses annual PubMed literature searches with the query "osteoarthritis gene expression profile", integration of GEO datasets filtered by 'Homo sapiens' and 'Expression profiling by array', and gene annotations sourced from external databases.