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 . Our own group has demonstrated the use of urinary metabolic fingerprint analysis to predict responses to anti-TNF , 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 , 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 . 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 . The combination of genetic and metabolomic data  has shown the potential to identify genotype-influenced metabotypes in a number of chronic diseases.
- Pathomx: an interactive workflow-based tool for the analysis of metabolomic data
- Metabolic profiling predicts response to anti-TNFα therapy in patients with rheumatoid arthritis
- Do differentiated macrophages display profoundly different metabolic profiles, reflecting their different functions?
- Metabolomics in the Analysis of Inflammatory Diseases