# Creatinine, leucine, and tetrahydrocorticosterone emerge as potential biomarkers for the diagnosis of sarcopenic osteoarthritis in middle-aged and elderly individuals: a cross-sectional exploratory study

## TL;DR

This study identifies creatinine, leucine, and tetrahydrocorticosterone as potential biomarkers for diagnosing sarcopenic osteoarthritis in older adults.

## Contribution

The study introduces novel serum biomarkers for sarcopenic osteoarthritis using untargeted metabolomics.

## Key findings

- Metabolomic analysis revealed distinct profiles for sarcopenic osteoarthritis involving steroid hormone and sphingolipid metabolism.
- Three key biomarkers—creatinine, leucine, and tetrahydrocorticosterone—were identified for sarcopenic osteoarthritis.
- The biomarkers are clinically relevant and easily measurable for phenotyping this condition.

## Abstract

Osteoarthritis is a common degenerative joint disease that is often associated with age-related muscle wasting known as sarcopenia, particularly in the elderly. This comorbid condition, referred to as “sarcopenic osteoarthritis”, may have a distinct metabolic profile; however, specific serum biomarkers for this phenotype remain poorly characterized. Therefore, we conducted an untargeted serum metabolomics study to identify potential biomarkers of osteoarthritis in individuals with sarcopenia.

This cross-sectional study enrolled 82 participants categorized into healthy controls, osteoarthritis, and sarcopenic osteoarthritis groups (n = 30, 30, 22). Fasting serum was analysed by untargeted LC-MS metabolomics. Differential metabolites were identified using multivariate statistics (PCA, PLS-DA; VIP >1) combined with univariate tests (P < 0.05, FDR-adjusted q < 0.05, |log2FC| ≥ 1). Enriched KEGG pathways were determined (P < 0.05).

Metabolomic analyses distinguished sarcopenic osteoarthritis from osteoarthritis alone by significant alterations in steroid hormone biosynthesis and sphingolipid metabolism. We screened a total of 20 substances for use as biomarkers of sarcopenic osteoarthritis and ended up focusing mainly on three of them.

Untargeted serum metabolomics successfully distinguished between healthy controls, osteoarthritis, and sarcopenic osteoarthritis and identified several candidate biomarkers. Creatinine, leucine, and tetrahydrocorticosterone emerged as promising biomarkers for the detection and phenotyping of the distinct sarcopenic osteoarthritis phenotype based on their clinical relevance and ease of measurement.