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Metabolomics in rheumatology

The omic with the Potential to provide a holistic view of patients and their disease.

Metabolomics studies have been reported for virtually all of the main rheumatologic diseases, although notably none yet for SSc [5]. Our own group has Demonstrated the use of urinary metabolic fingerprint analysis to predict responses to anti-TNF [6], and we have suggested that metabolites resulting from TNF-driven cachexia are among the useful predictive biomarkers. Serum metabolic profiling can differentiate four types of human arthritis [7], and we have shown the predictive value of the serum metabolite profile in early synovitis patients, with differences between those with self-limiting disease and those who went on to develop persistent RA [8]. The value of combining omics approaches has been demonstrated in a study using proteomics and metabolomics to show alterations in both vitamin D3 metabolites and proteins in patients with AS [9]. The combination of genetic and metabolomic data [10] has shown the potential to identify genotype-influenced metabotypes in a number of chronic diseases.



This post first appeared on Martin Fitzpatrick – Python Coder, Postgraduate, please read the originial post: here

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Metabolomics in rheumatology

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