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ToolsSaha, Pratyasha, Defernez, Marianne, Le Gall, Gwénaëlle, Pirt, Jeremy, Wachowiak, Ethan, Dainty, Jack, Durrant, Karen, Yates, Max, Kemsley, Kate and MacGregor, Alexander (2025) OA40 Longitudinal metabolomic shifts in RA:insights from 49 NMR spectra show changes at 7 years. Rheumatology, 64 (Supplement_3). ISSN 1462-0324
Full text not available from this repository. (Request a copy)Abstract
Background/Aims: The cause of rheumatoid arthritis (RA) is multifactorial and likely due to complex interactions between environmental and genetic factors, resulting in unique metabolomic signatures. Understanding how metabolomic profiles change throughout the course of RA is key to unravelling its pathophysiology. Whilst previous studies have focussed mainly on cross-sectional or pre-disease metabolomic profiles, longitudinal changes have not been explored. This study aimed to investigate time-dependent metabolic variations in people with RA using NMR-based metabolomics. Methods: Data were derived from the Versus Arthritis-funded DeSignA study (Identifying the Dietary Signatures of Arthritis through Metabolomics), involving seven RA patients from the Norfolk Arthritis Register (NOAR) sampled at seven time points. NOAR is a Norfolk-based long term observational study established in 1989, with well-phenotyped cases of new-onset inflammatory arthritis with longitudinal data up to 20 years. Exploratory analyses were carried out to observe variations over time and between participants. Data were normalised using Probabilistic Quotient Normalisation, and missing values imputed at half the limit of detection. Ordinary and multilevel principal component analysis (PCA) were performed to identify patterns and variations. Results: A total of 49 NMR spectra from seven participants across seven time points were analysed. Metabolite quantification using Chenomx software identified 78 metabolites, with 64 retained after data filtering steps. PCA identified metabolites with both inter-participant and time-dependent variability. Glucose and lactate concentrations remained consistently elevated over time in all participants, indicating stable metabolic activity. Amino acids and organic acids, such as xanthine, methylsuccinate, acetone and creatinine, demonstrated differences between individuals. In contrast, some metabolites exhibited clear time-dependent changes, including pyruvate, succinate, isovalerate, propionate and glutamate; these shifts were more pronounced around the 7-year time point, suggesting that this may be a critical phase in RA pathophysiology and progression. Conclusion: This study demonstrates the potential of NMR-based metabolomics to detect longitudinal metabolic changes in RA patients over time, and that this may be more pronounced 7 years after diagnosis. PCA allowed for the identification of both time-dependent and participant-specific metabolic variations, which may reflect underlying disease mechanisms and potential treatment response. While further research with larger cohorts is needed, the observed trends provide insights into disease progression and potential critical phases for future interventions. These findings provide a foundation for future studies using larger datasets, such as the UK Biobank, to confirm the clinical relevance of these metabolite patterns.
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