TNF-α and plasma albumin as biomarkers of disease activity in systemic lupus erythematosus - PubMed (original) (raw)

TNF-α and plasma albumin as biomarkers of disease activity in systemic lupus erythematosus

Helena Idborg et al. Lupus Sci Med. 2018.

Abstract

Objectives: Composite criteria/indices are presently used to diagnose and monitor patients with systemic lupus erythematosus (SLE). Biomarkers for these purposes would be helpful in clinical practice. We therefore evaluated a large panel of cytokines and basic laboratory tests and investigated their performance as discriminators versus controls and as biomarkers of disease activity (DA).

Methods: We examined 437 patients with SLE, fulfilling American College of Rheumatology-82 criteria, and 322 matched controls. DA was assessed according to both SLE DA Index 2000 (SLEDAI-2K) and SLE Activity Measure (SLAM). British Isles Lupus Activity Group (BILAG) was used to assess renal DA. Additionally, 132 patients self-assessed their Global Disease Activity (PtGDA). Mesoscale Discovery 30-plex cytokine assay and routine blood chemistry was performed on fasting EDTA-plasma.

Results: Of 26 tested biomarkers, we identified TNF-α as the superior discriminator between patients with SLE and controls (median=4.5 pg/mL, IQR=3.1-6.2 vs median=2.3 pg/mL, IQR=2.0-2.8). The strongest correlations to SLEDAI-2K and SLAM were obtained with TNF-α (Spearman rho (ρ)=0.32 and ρ=0.34, respectively), partly driven by the nephritis subgroup, and with p-albumin (ρ=-0.33 and ρ=-0.31, respectively). P-albumin was decreased and TNF-α was increased in patients with kidney involvement (renal BILAG A/B vs C/D/E, p=4×10-16 and p=6×10-9 respectively). IP-10 was increased in patients with joint involvement (SLAM item 24≥2 vs ≤1, p=0.0005) but did not differ when comparing patients with active/inactive kidney involvement. The most powerful correlations to PtGDA was observed with p-albumin (ρ=-0.42), IL-6 (ρ=0.30) and TNF-α (ρ=0.29).

Conclusion: TNF-α and p-albumin both performed well as discriminators between patients with SLE and controls and as proxies for DA according to both rheumatologists' and patients' assessments. In particular, renal DA was well reflected by TNF-α. We propose that the TNF-α and p-albumin merit further investigations as clinically useful biomarkers in SLE. We also observed that the pattern of activated cytokines varies with organ involvement.

Keywords: Eotaxin; IFN-gamma; IL-10; IL-12; IL-15; IL-16; IL-1alpha; IL-23; IL-6; IL-7; IL-8; IP-10; MCP-1; MCP-4; MDC; MIP-1beta; TNF-alpha; VEGF; cytokines; disease activity; p-albumin; systemic lupus erythematosus.

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Conflict of interest statement

Competing interests: SE is an employee of AstraZeneca.

Figures

Figure 3

Figure 3

The relationship of TNF-α to different measures of DA are shown: Log10 TNF-α levels versus quartiles of (A) SLEDAI-2K, (B) SLAM and (C) PtGDA. DA, disease activity; PtGDA, patients’ assessment of Global Disease Activity; SLAM, SLE Activity Measure; SLAQ, Systemic Lupus Activity Questionnaire; SLE, systemic lupus erythematosus; SLEDAI, SLE DA Index.

Figure 1

Figure 1

Cytokines with the lowest p values (Mann Whitney U test) comparing SLE to controls are noted. In addition, the six investigated standard clinical laboratory measurements are shown as squares. P values above the dotted line are significant (p<0.05) after correction for multiple testing (n=26). SLE, systemic lupus erythematosus.

Figure 2

Figure 2

ROC curve analysis of TNF-α was used to assess the discrimination between patients with SLE and controls. The AUC for TNF-α was 0.86 (0.83–0.89). AUC, area under the curve; ROC, receiver operating characteristic; SLE, systemic lupus erythematosus.

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