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Biomarker studies
TNF-α and plasma albumin as biomarkers of disease activity in systemic lupus erythematosus
  1. Helena Idborg1,
  2. Susanna Eketjäll2,3,
  3. Susanne Pettersson4,5,
  4. Johanna T Gustafsson1,
  5. Agneta Zickert1,
  6. Marika Kvarnström1,
  7. Vilija Oke1,
  8. Per-Johan Jakobsson1,
  9. Iva Gunnarsson1 and
  10. Elisabet Svenungsson1
  1. 1 Rheumatology Unit, Department of Medicine Solna, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden
  2. 2 Cardiovascular and Metabolic Diseases, Innovative Medicines and Early Development Biotech Unit, AstraZeneca, Integrated Cardio Metabolic Centre (ICMC), Karolinska Institutet, Huddinge, Sweden
  3. 3 Science for Life Laboratory, Department of Clinical Neuroscience, Karolinska Institutet, Solna, Sweden
  4. 4 Theme Inflammation and Infection, Karolinska University Hospital, Stockholm, Sweden
  5. 5 Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
  1. Correspondence to Professor Elisabet Svenungsson; Elisabet.Svenungsson{at}ki.se

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.

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

This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/

https://doi.org/10.1136/lupus-2018-000260

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    Footnotes

    • HI and SE contributed equally.

    • Contributors HI: study design, data analysis and manuscript writing. SE: cytokine measurements, manuscript writing. SP: PtGDA data collection and analysis, manuscript writing. JTG: clinical data, manuscript writing/approval. AZ: clinical data, manuscript writing/approval. MK: clinical data, manuscript writing/approval. VO: clinical data, manuscript writing/approval. P-JJ: study design, manuscript writing/approval. IG: SLE cohort responsible, manuscript writing. ES: study design, SLE cohort responsible, data analysis, manuscript writing.

    • Funding This study was supported by the AstraZeneca-Karolinska Institutet Joint Research Program in Translational Science, Swedish Research Council, Stockholm County Council (ALF), Swedish Heart-Lung foundation, King Gustaf Vs 80th Birthday Fund, Swedish Rheumatism Association, Swedish Society of Medicine, The Åke Wiberg Foundation, Karolinska Institutet’s Foundations and The Foundation in memory of Clas Groschinsky.

    • Competing interests SE is an employee of AstraZeneca.

    • Patient consent Obtained.

    • Ethics approval The Local Ethics Committee of the Karolinska University Hospital/Karolinska Institutet in Stockholm approved the study.

    • Provenance and peer review Not commissioned; externally peer reviewed.

    • Data sharing statement There are no additional unpublished data available.