Plasma Metabolomic and Lipidomic Signatures for Osteoporosis Diagnosis

JiaLong Wang's dataset contains plasma metabolomic and lipidomic profiles from a discovery cohort of 75 osteoporosis patients and 140 healthy controls, with validation in an independent cohort of 20 patients and 42 controls. Ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) was used for non-targeted analysis, and random forest modeling was applied to identify differential metabolites. The data supports the development and validation of a diagnostic model for osteoporosis.

Use Cases

• Developing diagnostic models for osteoporosis based on plasma metabolite profiles.
• Identifying potential metabolic biomarkers for bone density loss using multivariate statistical analysis.
• Validating metabolomic signatures for disease classification in an independent clinical cohort.
• Comparing lipidomic patterns between healthy individuals and osteoporosis patients.

Strengths

• Includes data from a discovery cohort of 215 total participants (75 patients, 140 controls).
• Features an independent validation cohort of 62 participants (20 patients, 42 controls).
• Data is openly available under a CC-BY-4.0 license.

Limitations

• Column names and a detailed data dictionary are not provided, limiting interpretability.
• The dataset size is given as 53445360 bytes, but the exact row count and structure are unknown.
• Geographic origin and specific demographic details of the cohorts are not specified.

Provenance

Source

JiaLong Wang

Collection Method

Ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) analysis of plasma samples.

Freshness

Last updated on 2026-03-19.