Yong Zhou1, Xi Zhang1, Rui Chen2, Su Han3, Yishu Liu1, Xuefeng Liu1, Ming Gao1, Chundong Yang1, Daifeng Lu1, Beibei Sun3, Hao Chen3. 1. Department of Orthopaedic Surgery, The Fourth Affiliated Hospital of Harbin Medical University, Harbin, People's Republic of China. 2. Department of Orthopaedic Surgery, The Fourth Affiliated Hospital of Harbin Medical University, Harbin, People's Republic of China. chen0082@126.com. 3. Department of Parasitology, Harbin Medical University, Harbin, People's Republic of China.
Abstract
BACKGROUND: Ankylosing spondylitis (AS) is a common chronic inflammatory arthritis, causing lasting back pain with progressive loss of spinal mobility. However, the exact pathogenesis of AS remains unclear. We aim to use the metabolomics analysis to characterize the metabolic profile of AS, in order to better understand the pathogenesis of AS and monitor disease activity and progression. METHODS: The ultra-high performance liquid chromatography-triple quadrupole mass spectrometry (UPLC-TQ-MS) was used for investigating the serum amino acid metabolomic profiling of 30 AS patients, in comparison with 32 rheumatoid arthritis (RA) patients and 30 healthy controls, combined with multivariate statistical analysis. Metabolite association analysis with disease activity was performed using generalized linear regression. The metabolic pathway analysis for the important metabolites was performed using MetPA and the metabolic network was constructed. RESULTS: A total of 29 amino acids and biogenic amines were detected in all participants by UPLC-TQ-MS. It showed significant amino acid differences between the AS/RA patients and control subjects. Additionally, 4-hydroxy-L-proline, alanine, γ-aminobutyric acid, glutamine, and taurine were identified as candidate markers shared by AS/RA groups. Specifically, lysine, proline, serine, and alanine were found correlated with disease activity of AS. Furthermore, the most significant metabolic pathway identified were alanine, aspartate, and glutamate metabolism, arginine and proline metabolism, aminoacyl tRNA biosynthesis and glycine, serine, and threonine metabolism. CONCLUSIONS: These preliminary results demonstrate that UPLC-TQ-MS analysis method is a powerful tool to identify metabolite profiles of AS. Research in identified disease activity-associated metabolites and biological pathways may provide assistance for clinical diagnosis and pathological mechanism of AS. Key Points • There are perturbations of serum amino acid metabolism in AS, compared with RA and healthy controls, determined by UPLC-TQ-MS. • Metabolomics pathway is used to analysis for the differential metabolites of AS. • The altered serum amino acid could monitor disease activity of AS.
BACKGROUND:Ankylosing spondylitis (AS) is a common chronic inflammatory arthritis, causing lasting back pain with progressive loss of spinal mobility. However, the exact pathogenesis of AS remains unclear. We aim to use the metabolomics analysis to characterize the metabolic profile of AS, in order to better understand the pathogenesis of AS and monitor disease activity and progression. METHODS: The ultra-high performance liquid chromatography-triple quadrupole mass spectrometry (UPLC-TQ-MS) was used for investigating the serum amino acid metabolomic profiling of 30 AS patients, in comparison with 32 rheumatoid arthritis (RA) patients and 30 healthy controls, combined with multivariate statistical analysis. Metabolite association analysis with disease activity was performed using generalized linear regression. The metabolic pathway analysis for the important metabolites was performed using MetPA and the metabolic network was constructed. RESULTS: A total of 29 amino acids and biogenic amines were detected in all participants by UPLC-TQ-MS. It showed significant amino acid differences between the AS/RApatients and control subjects. Additionally, 4-hydroxy-L-proline, alanine, γ-aminobutyric acid, glutamine, and taurine were identified as candidate markers shared by AS/RA groups. Specifically, lysine, proline, serine, and alanine were found correlated with disease activity of AS. Furthermore, the most significant metabolic pathway identified were alanine, aspartate, and glutamate metabolism, arginine and proline metabolism, aminoacyl tRNA biosynthesis and glycine, serine, and threonine metabolism. CONCLUSIONS: These preliminary results demonstrate that UPLC-TQ-MS analysis method is a powerful tool to identify metabolite profiles of AS. Research in identified disease activity-associated metabolites and biological pathways may provide assistance for clinical diagnosis and pathological mechanism of AS. Key Points • There are perturbations of serum amino acid metabolism in AS, compared with RA and healthy controls, determined by UPLC-TQ-MS. • Metabolomics pathway is used to analysis for the differential metabolites of AS. • The altered serum amino acid could monitor disease activity of AS.
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