Serum proteome and metabolome uncover novel biomarkers for the assessment of disease activity and diagnosing of systemic lupus erythematosus

Systemic lupus erythematosus (SLE) is an autoimmune disease affecting thousands of people. There are still no effective biomarkers for SLE diagnosis and disease activity assessment. We performed proteomics and metabolomics analyses of serum from 121 SLE patients and 106 healthy individuals, and identified 90 proteins and 76 metabolites significantly changed. Several apolipoproteins and the metabolite arachidonic acid were significantly associated with disease activity. Apolipoprotein A-IV (APOA4), LysoPC(16:0), punicic acid and stearidonic acid were correlated with renal function. Random forest model using the significantly changed molecules identified 3 proteins including ATRN, THBS1 and SERPINC1, and 5 metabolites including cholesterol, palmitoleoylethanolamide, octadecanamide, palmitamide and linoleoylethanolamide, as potential biomarkers for SLE diagnosis. Those biomarkers were further validated in an independent cohort with high accuracy (AUC = 0.862 and 0.898 for protein and metabolite biomarkers respectively). This unbiased screening has led to the discovery of novel molecules for SLE disease activity assessment and SLE classification.

Automated summary

Proteomics and metabolomics analyses of serum from SLE patients and healthy individuals revealed significant changes in 90 proteins and 76 metabolites. Several apolipoproteins and a metabolite were associated with disease activity, while others were correlated with renal function. Using these significantly changed molecules, a random forest model identified potential biomarkers for SLE diagnosis.