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Serum aminoacyl-tRNA synthetase-interacting multifunctional protein-1 (AIMP1), a novel disease activity predictive biomarker of systemic lupus erythematosus

1, 2, 3, 4, 5, 6, 7, 8

  1. Division of Rheumatology, Department of Internal Medicine, Yonsei University College of Medicine, Seoul, South Korea.
  2. College of Pharmacy, Ajou University, Suwon, Gyunggido, South Korea.
  3. Department of Laboratory Medicine, Yonsei University College of Medicine, Seoul, South Korea.
  4. Division of Rheumatology, Department of Internal Medicine, Yonsei University College of Medicine, Seoul, South Korea.
  5. Division of Rheumatology, Department of Internal Medicine, Yonsei University College of Medicine, Seoul, South Korea.
  6. Division of Rheumatology, Department of Internal Medicine, Yonsei University College of Medicine, Seoul, South Korea.
  7. Division of Rheumatology, Department of Internal Medicine, Yonsei University College of Medicine, Seoul, South Korea. sangwonlee@yuhs.ac
  8. College of Pharmacy, Ajou University, Suwon, Gyunggido, South Korea. sgpark@ajou.ac.kr

CER10668 Submission on line
2018 Vol.36, N°4 - PI 0533, PF 0539
Full Papers

Rheumatology Article

 

Abstract

OBJECTIVES:
Secreted aminoacyl-tRNA synthetase-interacting multifunctional protein-1 (AIMP1) has been reported to have pro-inflammatory properties. The aim of this study was to evaluate the clinical significance of serum AIMP1 in patients with systemic lupus erythematosus (SLE).
METHODS:
Serum levels of AIMP1 were measured in 160 patients with SLE using a human AIMP1 ELISA kit. Eighty patients were classified as active SLE (SLEDAI-2K ≥ 5), and 80 patients were classified as stable SLE. Correlation between serum AIMP1, SLE disease activity index-2000 (SLEDAI-2K), and laboratory variables related to disease activity or inflammatory burdens were assessed using Pearson’s correlation analysis. The optimal cut-off value for serum AIMP1 to predict active SLE was estimated by using a receiver operator characteristic curve, and logistic regression analysis was used to compare the odds ratios (ORs) of laboratory variables in predicting active SLE.
RESULTS:
The median serum AIMP1 was higher in patients with active SLE than those with stable SLE (8.0 vs. 6.5 ng/ml, p<0.001). Serum AIMP1 demonstrated correlation with SLEDAI-2K and laboratory variables related to disease activity or inflammatory burdens. The optimal cut-off AIMP1 to predict active SLE was 10.09. Multivariate logistic regression analysis including conventional laboratory variables demonstrated that serum AIMP1 ≥10.09 ng/ml (OR 3.919, 95% confidence interval 1.223−12.564, p=0.022) was useful in predicting active SLE.
CONCLUSIONS:
Serum levels of AIMP1 were associated with disease activity of SLE and could predict active SLE based on SLEDAI-2K.

PMID: 29352840 [PubMed]

Received: 06/07/2017 - Accepted : 17/10/2017 - In Press: 15/01/2018 - Published: 19/07/2018