---
title: "Serum Metrnl in Neuromyelitis Optica Spectrum Disorder: Article content unavailable in source"
id: "frontiers-in-immunology-12-characteristics-of-serum-metrnl-levels-in-patients-with-neuromyelitis-optica"
canonical_url: "https://medichelpline.com/clinical-feed/frontiers-in-immunology-12-characteristics-of-serum-metrnl-levels-in-patients-with-neuromyelitis-optica"
content_type: "clinical_feed_article"
specialty: "Neurology"
source_name: "Frontiers in Immunology"
source_url: "https://www.frontiersin.org/articles/10.3389/fimmu.2026.1957990"
published_at: "2026-10-13T00:00:00.000Z"
evidence_level: "Journal Feed"
license: "CC-BY-NC-4.0 / Informational Use"
---
# Serum Metrnl in Neuromyelitis Optica Spectrum Disorder: Article content unavailable in source
## Provenance & Clinical Metadata
- **Canonical URL:** https://medichelpline.com/clinical-feed/frontiers-in-immunology-12-characteristics-of-serum-metrnl-levels-in-patients-with-neuromyelitis-optica
- **Specialty:** [Neurology](https://medichelpline.com/clinical-feed/neurology.md)
- **Primary Source:** Frontiers in Immunology
- **Source URL:** [Original Journal Publication](https://www.frontiersin.org/articles/10.3389/fimmu.2026.1957990)
- **Published At:** 2026-10-13T00:00:00.000Z
- **Evidence Rating:** Journal Feed
## Executive GIST (TL;DR)
- The source page did not include manuscript text, so no patient-level results or numeric outcomes are available to extract. - Investigators and article authors were not listed in the provided content; the source supplied only journal navigation and section listings. - The source did not report study design details (for example: cohort size, inclusion criteria, sampling timeframe, or controls). - No methodology was present: the source lacked information on Metrnl assay type, specimen handling, or timing of sampling relative to disease activity. - Primary endpoints and statistical analyses were not available on the provided page; therefore effect sizes, correlations with inflammatory biomarkers, and p-values cannot be reported. - The source did not document clinical associations between **neuromyelitis optica spectrum disorder** and serum **Metrnl** levels, nor any subgroup or longitudinal data. - Safety, adverse events, or treatment interactions were not provided. - The primary limitation is absence of extractable data; remaining questions include: what were the measured associations, which inflammatory biomarkers were assessed, and what clinical definitions of activity were used? - For readers and clinicians, the next step is to consult the full article on the journal site or contact the corresponding author for the missing experimental details and results.
## Clinical Analysis & Structured Key Points
Frontiers | Characteristics of serum Metrnl levels in patients with neuromyelitis optica spectrum disorder and their associations with disease activity and inflammatory biomarkers ORIGINAL RESEARCH article Front. Immunol. , 13 October 2026 Sec. Inflammation Volume 17 - 2026 | https://doi.org/10.3389/fimmu.2026.1957990 Published in Frontiers in Immunology Inflammation 7 impact factor 11.3 citescore Part of a Research Topic Inflammaging in Non-Communicable Diseases: Mechanisms, Biomarkers, and Translational Perspectives Submission open 7496 views 10 articles Editor & Reviewers Edited by I M Inês Mollet Reviewed by K Q Kun Qian L G Lorna Galleguillos Outline Figures and Tables Figure 1 View in article Figure 2 View in article Figure 3 View in article Figure 4 View in article Figure 5 View in article Table 1 Demographic and clinical characteristics of the study participants. View in article Table 2 Univariable and multivariable logistic regression analyses of factors associated with NMOSD. View in article Table 3 Diagnostic performance of individual biomarkers and the combined model in differentiating patients with NMOSD from healthy controls. View in article Table 4 Longitudinal changes in disability and circulating inflammatory biomarkers before and after high-dose methylprednisolone pulse therapy in 30 patients with NMOSD. View in article ORIGINAL RESEARCH article Front. Immunol. , 13 October 2026 Sec. Inflammation Volume 17 - 2026 | https://doi.org/10.3389/fimmu.2026.1957990 Characteristics of serum Metrnl levels in patients with neuromyelitis optica spectrum disorder and their associations with disease activity and inflammatory biomarkers L L Li-Min Li 1 Y S Yingzhe Shao 1 H C Hao Cai 2 L Y Li Yang 1 * 1. Department of Neurology, Tianjin Neurological Institute, Tianjin Medical University General Hospital, Tianjin, China 2. Department of Neurology, Tianjin Huanhu Hospital, Tianjin, China Article metrics View details Abstract Background: Neuromyelitis optica spectrum disorder (NMOSD) is a severe autoimmune inflammatory disease for which reliable biomarkers of disease activity are lacking. Meteorin-like protein (Metrnl) has not been investigated in NMOSD; this study assessed its clinical significance in NMOSD patients. Methods: Serum Metrnl, interleukin (IL)-6, and IL-17A levels were quantified by enzyme-linked immunosorbent assay in 50 patients with NMOSD and 30 age- and sex-matched healthy controls (HCs) and correlated with clinical and laboratory data. Metrnl levels were also remeasured in 30 patients before and after high-dose methylprednisolone therapy, together with derived inflammatory indices. Benjamini–Hochberg false-discovery-rate (FDR) correction was applied within prespecified test families, with a sensitivity power analysis. Metrnl alone and a combined multimarker logistic regression model were evaluated by receiver operating characteristic (ROC) analysis, DeLong tests, bootstrap validation, calibration, and decision curve analysis. Results: Serum Metrnl levels were higher in NMOSD patients than in HCs and were greater in those with mild disability than in those with moderate-to-severe disability (both p < 0.001); the increase in patients with gadolinium-enhancing lesions was nominal ( p = 0.034, q = 0.068). After FDR correction, serum Metrnl levels correlated negatively with IL-6, IL-17A, neutrophil-to-lymphocyte ratio (NLR), systemic immune-inflammation index (SII), and Expanded Disability Status Scale (EDSS) score (all q < 0.05), but not with high-sensitivity C-reactive protein (hs-CRP). Metrnl alone distinguished NMOSD patients from HCs (area under the curve [AUC] 0.752), whereas a combined model of Metrnl, IL-6, IL-17A, and hs-CRP performed markedly better (AUC 0.933; DeLong p < 0.001), increasing specificity from 53.3% to 80.0% at 100% sensitivity. After methylprednisolone therapy, Metrnl, IL-6, and IL-17A levels decreased ( p < 0.001) along with clinical improvement, whereas NLR, platelet-to-lymphocyte ratio, and SII remained unchanged; the decrease in Metrnl levels (median −25.5%) was the largest and was uncorrelated with changes in other biomarkers. Conclusions: Serum Metrnl levels were elevated in patients with NMOSD, inversely related to disease severity and inflammatory biomarkers, and decreased after immunotherapy, supporting it as a dynamic biomarker of disease activity and a component of a multimarker diagnostic panel. The cross-sectional design precludes causal inference, and exploratory subgroup findings require external validation. 1 Introduction Neuromyelitis optica spectrum disorder (NMOSD) is a severe autoimmune-mediated inflammatory disorder of the central nervous system (CNS), which predominantly affects the optic nerves and spinal cord ( 1 ). The precise underlying pathogenic mechanisms remain incompletely understood. Current evidence indicates that NMOSD is primarily driven by pathogenic autoantibodies against aquaporin-4 (AQP4)—a water channel protein densely expressed on astrocytic endfeet—together with AQP4-specific T helper 17 (Th17) cells ( 2 , 3 ). Disease initiation occurs in peripheral immune compartments (including lymph nodes and bone marrow), where autoreactive lymphocytes undergo activation and differentiation. These primed cells subsequently breach the blood–brain barrier (BBB) and infiltrate the CNS parenchyma, thus amplifying neuroinflammation through proinflammatory cytokine networks, complement activation, and the recruitment of monocytes and neutrophils ( 4 – 6 ). Histopathologically, NMOSD reflects the coordinated action of multiple immune effector pathways, culminating in primary astrocyte injury, secondary demyelination, oligodendrocyte apoptosis, and axonal damage ( 7 – 9 ). Although the full pathogenic cascade remains incompletely delineated, dysregulated neuroinflammatory responses constitute the core pathological driver of disease progression. Accumulating evidence underscores the pivotal role of cytokine-mediated immune dysregulation in NMOSD pathogenesis, thereby reinforcing the potential utility of cytokines as both prognostic biomarkers and therapeutically actionable targets ( 10 – 12 ). Nevertheless, early intervention in NMOSD remains clinically challenging owing to diagnostic delays and phenotypic heterogeneity; thus, the timely initiation of high-efficacy immunosuppressive therapy is essential to mitigate acute neuroinflammation and prevent irreversible neurological sequelae. Consequently, the discovery and validation of novel molecular biomarkers and mechanistically informed therapeutic targets are imperative for improving long-term neurological outcomes in patients with NMOSD. Meteorin-like protein (Metrnl), which is also known as Meteorin-β, Subfatin, interleukin (IL)-41, and Cometin, is a recently identified multifunctional cytokine involved in the regulation of diverse physiological and pathological processes, including inflammatory and immune responses, energy metabolism, and tissue homeostasis ( 13 ). In both humans and mice, Metrnl is preferentially expressed in skeletal muscle, barrier tissues (e.g., skin epidermis and intestinal mucosa), and M2-polarized macrophages ( 14 ). Subsequent studies have demonstrated that Metrnl is secreted by multiple innate immune cell types, including distinct macrophage subsets, dendritic cells, and select granulocyte populations; however, it is undetectable in lymphoid lineages, specifically CD4 + and CD8 + T cells, B cells, natural killer cells, and natural killer T cells ( 15 ). Metrnl-knockout mice exhibit impaired B-cell development and reduced serum IgG levels, indicating that Metrnl plays a role in maintaining humoral immune homeostasis ( 16 ). Clinically, Metrnl expression is elevated in the synovial tissue and peripheral blood of patients with rheumatoid arthritis (RA) and correlates positively with disease activity ( 17 ); similarly, serum Metrnl levels are significantly increased in patients with myasthenia gravis (MG) and are associated with clinical severity ( 18 ). In vitro and in vivo studies have further demonstrated that Metrnl expression in bone marrow–derived cells is inducible by proinflammatory stimuli and that Metrnl itself can modulate the production of key immunoregulatory cytokines implicated in NMOSD pathogenesis (particularly IL-6 and IL-17A) ( 19 , 20 ). Nevertheless, the functional role and clinical relevance of Metrnl in NMOSD remain incompletely characterized. In this study, serum Metrnl levels were quantified in patients with NMOSD, and their associations with clinical phenotypes and other inflammatory biomarkers were assessed to explore the potential pathophysiological relevance of Metrnl in NMOSD. 2 Materials and methods 2.1 Recruitment of patients and controls A total of 50 patients with NMOSD experiencing an acute attack were consecutively enrolled from the Department of Neurology, Tianjin Medical University General Hospital, between January 2023 and February 2026. Thirty healthy controls (HCs), matched to the NMOSD group for age and sex, were recruited concurrently. All patients met the 2015 International Consensus Diagnostic Criteria for NMOSD ( 21 ). The following exclusion criteria were applied: 1) active infection within 3 months prior to enrollment; 2) coexisting autoimmune disorders or malignancies; 3) pre-existing hyperlipidemia, diabetes mellitus, cerebrovascular disease, coronary heart disease, or cognitive impairment; and 4) use of systemic corticosteroid or immunosuppressant therapy (including azathioprine, cyclophosphamide, or mycophenolate mofetil) within 4 weeks before enrollment, or B-cell–depleting therapy within 6 months before enrollment. Baseline blood samples were collected on the day of admission, before the first dose of high-dose intravenous methylprednisolone, and all patients subsequently received the same acute treatment, namely high-dose intravenous methylprednisolone pulse therapy. This study was conducted in strict accordance with the ethical principles of the Declaration of Helsinki and was approved by the Medical Ethics Committee of Tianjin Medical University General Hospital (Approval No. IRB2022-KY-264). Written informed consent was obtained from all participants before enrollment. 2.2 Clinical and laboratory assessments Systematic demographic and clinical data were collected from all participants. Height and body weight were measured in light clothing without shoes, and body mass index (BMI) was calculated as weight in kilograms divided by the square of height in meters. Laboratory assessments involved measurements of complete blood count parameters, including white blood cell (WBC), neutrophil, lymphocyte, monocyte, and platelet counts, as well as high-sensitivity C-reactive protein (hs-CRP), blood glucose, triglyceride (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C) levels. Derived inflammatory indices were calculated as follows: neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and monocyte-to-lymphocyte ratio (MLR) were defined as the respective absolute counts divided by the absolute lymphocyte count; WBC-to-HDL-C ratio (WHR), neutrophil-to-HDL-C ratio (NHR), and monocyte-to-HDL-C ratio (MHR) were computed by dividing the corresponding cellular counts (WBCs, neutrophils, or monocytes) by the serum HDL-C level; systemic immune-inflammation index (SII) was calculated as the product of platelet and neutrophil counts divided by the lymphocyte count; and systemic inflammation response index (SIRI) was calculated as the product of neutrophil and monocyte counts divided by the lymphocyte count. Neurological disability was independently evaluated by two neurologists using the Expanded Disability Status Scale (EDSS), and the CNS lesion burden was evaluated via magnetic resonance imaging (MRI). Patients were stratified into two groups based on disability severity: the mild disability (EDSS score < 4) and moderate/severe disability (EDSS score ≥ 4) groups ( 22 ). Additionally, patients with NMOSD were categorized according to age at disease onset into early-onset NMOSD (EO-NMOSD; onset age < 50 years) and late-onset NMOSD (LO-NMOSD; onset age ≥ 50 years) groups ( 23 ). An EDSS score of 4.0 was adopted as the cutoff for two reasons. First, it is the point at which the scale changes construct: steps below 4.0 are defined by the functional-system scores of patients who remain fully ambulatory, whereas a score of 4.0 denotes relatively severe disability that begins to limit full daily activity in a patient who remains self-sufficient, is up and about for approximately 12 hours per day, and can walk approximately 500 m without aid or rest. Second, an EDSS score of 4.0 is an established disability milestone in NMOSD, having been used both as an endpoint in natural-history analyses of disability accumulation ( 23 ) and as the threshold separating mild from moderate-to-severe disability in previous biomarker studies of this disease ( 22 ); adopting the same threshold ensures that the present results are directly comparable to those in the literature. 2.3 Serum Metrnl, inflammatory cytokines, and AQP4-IgG detection Venous blood samples were drawn from all participants in the early morning following an overnight fast of at least 8 hours. In a subset of 30 patients with NMOSD, paired serum samples were obtained before and after high-dose intravenous methylprednisolone therapy. Serum was isolated via centrifugation at 1000 × g for 10 min at 4 °C, immediately aliquoted into sterile polypropylene tubes, and stored at −80 °C until analysis. Serum levels of Metrnl, IL-6, and IL-17A were quantified using commercially available, analytically validated ELISA kits (Wuhan Fine Biotech Co., Ltd.), strictly according to the manufacturer’s instructions. All the assays were performed in duplicate under double-blind conditions. Serum AQP4-IgG status in patients with NMOSD was determined by using a live cell–based assay. 2.4 Statistical analysis Statistical analyses were conducted using IBM SPSS Statistics version 26.0, GraphPad Prism version 8.0, and R version 4.4.1. The Shapiro–Wilk test was used to evaluate the normality of continuous variables. Categorical variables were summarized as frequencies and percentages and compared using the chi-square test or Fisher’s exact test, as appropriate. Continuous variables were presented as the mean ± standard deviation (SD) for normally distributed data and were analyzed by Student’s t -test; for nonnormally distributed data, medians with interquartile ranges (IQRs) were reported, and group comparisons were performed using the Mann–Whitney U test. Paired pre- and post-treatment measurements were compared using the paired t -test or the Wilcoxon signed-rank test according to the distribution of the within-patient differences, and standardized effect sizes (Cohen’s d for independent samples, d z for paired samples) were reported. Treatment-associated changes were additionally expressed as the median percentage change from baseline, and the relationships between the changes in serum Metrnl levels and the concurrent changes in IL-6, IL-17A, NLR, PLR, and SII were assessed by Spearman’s rank correlation coefficient of the paired differences. Multivariable logistic regression was used to identify factors that were independently associated with NMOSD, and odds ratios (ORs) with 95% confidence intervals (CIs) were calculated per 1-SD increment for continuous variables. To limit overfitting, no more than four predictors were retained. The predicted probability derived from the final model was used as the combined diagnostic index. Receiver operating characteristic (ROC) curve analysis was performed to assess the diagnostic performance of serum Metrnl in differentiating patients with NMOSD from HCs. Differences between the AUCs were assessed by the DeLong test. The incremental value of Metrnl over the remaining biomarkers was further evaluated by the likelihood-ratio test, the integrated discrimination improvement (IDI), and the continuous net reclassification improvement (NRI), with 95% CIs derived from 2000 bootstrap resamples. The combined model was internally validated by bootstrapping (1000 resamples) to obtain an optimism-corrected AUC and by repeated fivefold cross-validation (200 repetitions). Calibration was assessed by the Hosmer–Lemeshow goodness-of-fit test, the Brier score and a bootstrap bias-corrected calibration curve, and clinical utility was examined by decision curve analysis. Logistic regression modeling, model validation, decision curve analysis and nomogram construction were performed in R. Correlations between serum Metrnl levels and clinical or laboratory parameters were evaluated using Spearman’s rank correlation coefficient for nonnormally distributed variables and Pearson’s correlation coefficient for normally distributed variables. Because multiple clinical and laboratory parameters were examined, all p values were additionally corrected for multiplicity using the Benjamini–Hochberg false-discovery-rate (FDR) procedure ( 24 ) within four prespecified families of tests: (i) the 25 NMOSD-versus-HC comparisons summarized in Table 1 , (ii) the four comparisons of serum Metrnl across clinical subgroups of NMOSD, (iii) the 15 correlations between serum Metrnl and clinical or laboratory parameters, and (iv) the seven paired pre- versus post-treatment comparisons. Both unadjusted p values and FDR-adjusted q values were reported, and findings were described as significant only when q < 0.05. No a priori sample-size calculation was performed because the cohort comprised all consecutively eligible patients who were recruited during the study period; a sensitivity power analysis was therefore conducted to define the effect sizes detectable with 80% power at a two-sided α of 0.05, and FDR correction and power analyses were carried out in R. To determine whether BMI confounded the relationship between serum Metrnl and disability, a multivariable linear regression model was fitted with serum Metrnl as the dependent variable and EDSS score, BMI, age, and sex as independent variables, and partial correlation coefficients between serum Metrnl and EDSS score were calculated before and after adjustment for BMI. A two-tailed p value < 0.05 was considered statistically significant. Table 1 Variables NMOSD (n = 50) HC (n = 30) p q Sex, F/M 42/8 27/3 0.451 0.773 Age, y 52.68 ± 15.32 53.57 ± 15.37 0.803 0.958 BMI (kg/m²) 23.13 ± 3.04 23.48 ± 2.72 0.609 0.902 Disease duration, median (IQR), months 11.5 (6.0–21.0) – – – EDSS scores 4.35 ± 2.02 – – – Number of relapses, median (IQR) 1 (1–2) – – – Annualized relapse rate, median (IQR) 1.37 (0.82–2.40) – – – Type of attack, n (%) 50 (100%) – Optic neuritis 16 (32%) – – – Myelitis 39 (78%) – – – Area postrema syndrome 3 (6%) – – – Other types 6 (12%) – – – Laboratory test results – TG (mmol/L) 1.11 ± 0.33 1.22 ± 0.35 0.186 0.343 TC (mmol/L) 4.15 ± 0.83 4.24 ± 0.74 0.613 0.920 LDL-C (mmol/L) 2.53 ± 0.58 2.30 ± 0.63 0.105 0.210 HDL-C (mmol/L) 1.17 ± 0.28 1.17 ± 0.33 0.963 0.963 FBG (mmol/L) 5.14 ± 0.62 5.24 ± 0.69 0.503 0.805 WBC, median (IQR), (10 9 /L) 6.68 (5.68–8.93) 6.64 (5.47–8.57) 0.735 0.958 NEU, median (IQR), (10 9 /L) 5.37 (3.33–7.07) 3.83 (3.13–5.03) 0.020 0.059 LYM, median (IQR), (10 9 /L) 1.63 (1.36–2.25) 1.66 (1.34–2.15) 0.921 0.961 MON, median (IQR), (10 9 /L) 0.44 (0.33–0.61) 0.44 (0.35–0.65) 0.878 0.958 PLT, median (IQR), (10 9 /L) 280.00 (238.50–330.50) 232.00 (160.00–294.25) 0.002 0.008 NLR, median (IQR) 3.05 (1.71–4.64) 2.06 (1.50–2.93) 0.022 0.059 MLR, median (IQR) 0.25 (0.20–0.40) 0.25 (0.20–0.35) 0.854 0.958 PLR, median (IQR) 172.27 (121.51–210.09) 131.07 (96.15–162.91) 0.009 0.031 SII, median (IQR) 792.75 (591.87–1355.76) 487.11 (346.39–674.49) <0.001 0.002 SIRI, median (IQR) 1.48 (0.82–2.80) 0.99 (0.69–1.63) 0.097 0.210 WHR, median (IQR)
## Related Clinical Research

- [Sex Differences in Mortality After Traumatic Brain Injury: Systematic Review, Meta-analysis, and E](https://medichelpline.com/clinical-feed/medrxiv-5-evidence-synthesis-on-sex-differences-in-mortality-after-traumatic-brain-injury.md)
- [Current immunosuppressive treatment and self-reported lifetime stroke history in US adults](https://medichelpline.com/clinical-feed/plos-one-4-current-immunosuppressive-treatment-and-self-reported-lifetime-stroke-history.md)
- [Autoimmune Disease Rates in the 10 Years Before Myasthenia Gravis Diagnosis: Nationwide Korean Coh](https://medichelpline.com/clinical-feed/pubmed-42555884.md) (DOI: 10.1212/WNL.0000000000218377)
- [Bupropion Hydrochloride for Improving Recovery in Acute Ischaemic Stroke: BASE Trial Protocol](https://medichelpline.com/clinical-feed/bmj-open-4-protocol-for-base-a-multicentre-double-blind-randomised-controlled-trial-of.md)
- [Moderate-to-severe chronic spontaneous urticaria linked to higher risk of rheumatoid arthritis and](https://medichelpline.com/clinical-feed/plos-one-9-moderate-to-severe-chronic-spontaneous-urticaria-is-associated-with-increased.md)

## Navigation
- [← Back to Neurology Feed](https://medichelpline.com/clinical-feed/neurology.md)
- [← All Clinical Specialties](https://medichelpline.com/clinical-feed.md)
## Medical & Regulatory Disclaimer

> [!CAUTION]
> MedicHelpline content is structured for research, educational, and professional discovery purposes. It does not constitute individual medical advice, clinical diagnosis, or treatment recommendations.
> Always verify dosing, contraindications, and regulatory alerts against official product labeling and primary regulatory sources before clinical decision-making.