# Diagnostic biomarkers for differentiating AQP4-IgG- negative NMOSD from other nervous system autoimmune disorders: a retrospective study

## TL;DR

This study identifies clinical and lab markers to distinguish AQP4-IgG-negative NMOSD from other autoimmune disorders of the nervous system.

## Contribution

A multi-indicator diagnostic model with high accuracy for differentiating AQP4-IgG-negative NMOSD from other CNS disorders is proposed.

## Key findings

- AQP4-IgG-negative NMOSD shows higher diplopia and brainstem involvement compared to other groups.
- A diagnostic model with twelve predictors achieved an AUC of 0.936 in training and 0.929 in external validation.
- Clinical, imaging, and lab profiles of AQP4-IgG-negative NMOSD differ significantly from other autoimmune disorders.

## Abstract

The clinical manifestations of neuromyelitis optica spectrum disorders (NMOSD) overlap with those of other central nervous system (CNS) disorders, making differential diagnosis based on symptoms alone difficult. This study aimed to identify distinguishing indicators of aquaporin-4 (AQP4) IgG-negative NMOSD and assess their diagnostic value.

We analyzed four groups: 85 patients with AQP4-IgG-negative NMOSD, 192 with AQP4-IgG-positive NMOSD, 547 with other nervous system autoimmune disorders (e.g., multiple sclerosis, Guillain-Barré syndrome, and viral and autoimmune encephalitis), and 269 healthy controls matched for sex, age, and BMI.A diagnostic model was established using clinical, biochemical, and cerebrospinal fluid (CSF) variables. The dataset was divided into training and internal validation cohorts, and model performance was further assessed through external validation using an independently collected dataset obtained during the same study period.

We enrolled 1,093 participants. The AQP4-IgG-negative NMOSD group showed: higher diplopia incidence (35.29% vs. 17.19% in positive NMOSD, 17.18% in controls; P<0.001); lower limb sensory abnormalities (76.47% vs. 89.58%, P = 0.0056) and urinary dysfunction (36.47% vs. 57.29%, P = 0.0017) than positive cases; predominant brainstem involvement (50.59% vs. 31.77% in positive, 28.70% in controls; P<0.001); moderate spinal cord involvement (70.59% vs. 88.02% in positive, 38.57% in controls; P<0.001); and altered thyroxine, apolipoprotein A1, eosinophils, and basophils. After false discovery rate correction (q<0.1), diplopia, brainstem involvement, spinal cord involvement, serum albumin, and CSF albumin remained significant. A combined model incorporating twelve predictors (Ocular symptoms, Gastrointestinal symptoms, Water swallowing and choking difficulties, Cerebral lobes, Centrum semiovale, Brainstem, Cerebral ganglia, Spinal cord, APOA1, Ca, Toxoplasma gondii IgM Antibody, CSF IgG) achieved an AUC of 0.936in the training cohort and 0.929 in external validation.

AQP4-IgG-negative NMOSD shows distinct clinical, imaging, and laboratory profiles compared to other nervous system autoimmune disorders. A multi-indicator diagnostic approach offers higher accuracy than single-marker diagnostics.