Frontiers in Immunology (Jan 2024)

Systemic inflammation response index is a useful indicator in distinguishing MOGAD from AQP4-IgG-positive NMOSD

  • Lei Wang,
  • Ruihong Xia,
  • Xiangliang Li,
  • Jingli Shan,
  • Shengjun Wang

DOI
https://doi.org/10.3389/fimmu.2023.1293100
Journal volume & issue
Vol. 14

Abstract

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ObjectiveTo identify reliable immune-inflammation indicators for distinguishing myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) from anti–aquaporin-4 immunoglobulin G (AQP4-IgG)-positive neuromyelitis optica spectrum disorders (NMOSD). To assess these indicators’ predictive significance in MOGAD recurrence.MethodsThis study included 25 MOGAD patients, 60 AQP4-IgG-positive NMOSD patients, and 60 healthy controls (HCs). Age and gender were matched among these three groups. Participant clinical and imaging findings, expanded disability status scale (EDSS) scores, cerebrospinal fluid (CSF) information, and blood cell counts were documented. Subsequently, immune-inflammation indicators were calculated and compared among the MOGAD, AQP4-IgG-positive NMOSD, and HC groups. Furthermore, we employed ROC curve analysis to assess the predictive performance of each indicator and binary logistic regression analysis to assess potential risk factors.ResultsIn MOGAD patients, systemic inflammation response index (SIRI), CSF white cell count (WCC), and CSF immunoglobulin A (IgA) levels were significantly higher than in AQP4-IgG-positive NMOSD patients (p = 0.038, p = 0.039, p = 0.021, respectively). The ROC curves showed that SIRI had a sensitivity of 0.68 and a specificity of 0.7 for distinguishing MOGAD from AQP4-IgG-positive NMOSD, with an AUC of 0.692 (95% CI: 0.567-0.818, p = 0.0054). Additionally, compared to HCs, both MOGAD and AQP4-IgG-positive NMOSD patients had higher neutrophils, neutrophil-to-lymphocyte ratio (NLR), SIRI, and systemic immune-inflammation index (SII). Eight (32%) of the 25 MOGAD patients had recurrence within 12 months. We found that the monocyte-to-lymphocyte ratio (MLR, AUC = 0.805, 95% CI = 0.616–0.994, cut-off value = 0.200, sensitivity = 0.750, specificity = 0.882) was an effective predictor of MOGAD recurrence. Binary logistic regression analysis showed that MLR below 0.200 at first admission was the only risk factor for recurrence (p = 0.005, odds ratio =22.5, 95% CI: 2.552–198.376).ConclusionElevated SIRI aids in distinguishing MOGAD from AQP4-IgG-positive NMOSD; lower MLR levels may be linked to the risk of MOGAD recurrence.

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