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. 2026 Jul 7;21(7):e0352017. doi: 10.1371/journal.pone.0352017

Evaluation of plasma neurofilament light chain and glial fibrillary acidic protein in myasthenia gravis: A controlled cohort study

Arta Grosmane-Bataraga 1,2,¤,#, Evita Saluvēra 3,¤,#, Marija Roddate 2, Vladimirs Krutovs 2, Kaj Blennow 4,5, Henrik Zetterberg 4,5,6,7,8,9,10, Maksims Zolovs 11,12,¤, Nataļja Kurjāne 13,14,¤, Viktorija Ķēniņa 13,15,*,¤
Editor: Karlo Toljan16
PMCID: PMC13340798  PMID: 42412876

Abstract

Aims

To evaluate plasma neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP) as candidate biomarkers in myasthenia gravis (MG).

Methods

Ninety MG patients and 40 healthy controls were recruited. Disease severity was assessed by the Myasthenia Gravis Foundation of America (MGFA) classification, Myasthenia Gravis Composite (MGC) score, and Myasthenia Gravis Activities of Daily Living (MG-ADL) scale. Plasma NfL and GFAP were quantified using Single Molecule Array (Simoa) assays.

Results

NfL and GFAP plasma concentration did not differ between MG and controls (p > 0.05). Neither biomarker correlated with MG-ADL or MGC, and no differences were observed across MGFA classes (p > 0.05). Biomarker levels were unrelated to myasthenic crisis history or treatment exposure.

Conclusion

Plasma NfL and GFAP, although informative in other neuroimmunological and neurodegenerative conditions, do not distinguish MG from healthy controls and show no association with disease severity. This study adds to the emerging literature on NfL in MG and represents one of the larger controlled analyses incorporating both NfL and GFAP biomarkers in this disease. The findings argue against adopting NfL or GFAP for MG monitoring and highlight the need for MG-specific biomarker strategies.

Introduction

Biomarkers play a pivotal role in neuroimmunology by providing objective measures of disease activity, prognosis, and treatment response. In conditions such as multiple sclerosis and neuromyelitis optica spectrum disorders, fluid biomarkers including neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP) have gained increasing attention as tools for monitoring neuroaxonal injury and astrocytic activation. In contrast, the biomarker landscape in myasthenia gravis (MG) remains poorly defined.

MG is a chronic autoimmune disorder targeting the neuromuscular junction, clinically characterised by fluctuating muscle weakness and fatigability [1]. The disease is mediated by pathogenic autoantibodies, most commonly against the acetylcholine receptor (AChR), muscle-specific kinase (MuSK), or lipoprotein receptor-related protein 4 (LRP4). Although antibody testing is invaluable for diagnosis, antibody titers do not consistently correlate with disease severity or prognosis [2]. Thus, there is an unmet need for reliable biomarkers that can predict disease generalization, monitor disease activity, and serve as outcome measures in clinical trials [3].

Recent studies have explored circulating microRNAs and serum protein signatures as potential MG biomarkers, but none have yet translated into clinical practice [4,5]. Neurofilaments (Nfs) are structural proteins that constitute a part of the axonal cytoskeleton. Nfs comprise the following subunits: α-internexin and neurofilament heavy, median and light (NfL) proteins [6]. Low levels of NfL proteins are continuously released from axons and tend to rise with age [7]. As a response to axonal damage in the central nervous system (CNS), the release of NfL sharply increases due to inflammation, neurodegeneration, trauma, and vascular injury [8]. Elevated NfL levels are well established in neurodegenerative and demyelinating CNS diseases, and more recently, in peripheral neuropathies. Similarly, some studies have detected higher plasma NfL levels in patient groups than in healthy controls outside the CNS, including in Charcot-Marie-Tooth disease and MG; however, correlations with disease severity have rarely been observed [9,10]. This biomarker profile is particularly well characterised in amyotrophic lateral sclerosis (ALS), another disorder affecting the motor unit. Serum NfL levels identify over 80% of patients with ALS and predict survival, outperforming both GFAP and pTau181. In contrast, GFAP did not show a significant pre-diagnostic association with incident ALS, remaining flat in the years preceding clinical onset, suggesting a more limited role in this condition. Given that ALS and MG both target the neuromuscular system, these findings provide a relevant framework for evaluating NfL and GFAP as candidate biomarkers in MG [11,12]. Preliminary reports in MG have suggested modest elevations, but findings have been inconsistent, and their clinical relevance remains uncertain.

Glial fibrillary acidic protein is a major component of the intermediate filament of the astrocyte cytoskeleton, and increased GFAP levels are thought to relate to reactive astrocytosis [13]. GFAP is expressed in both the CNS and peripheral nervous system (PNS) in non-myelinating immature Schwann cells and satellite cells of the dorsal root ganglia [14]. However, it is also likely that CNS and PNS GFAP are not identical since a GFAP monoclonal antibody has been found that selectively recognises GFAP in astrocytes but not in PNS cells [15]. Studies have shown that GFAP is also expressed in immature Schwann cells during the development and repair of Schwann cells after nerve injury [16]. However, to date, GFAP has not been systematically studied in MG.

The present study, therefore, aimed (1) to measure plasma concentrations of NfL and GFAP in patients with MG compared to healthy controls, and (2) to assess their potential associations with clinical severity, thereby evaluating their utility as candidate biomarkers for hypothesised diagnostic, prognostic and monitoring relevance in MG.

Methods

Participants

Patients were recruited between 1st of January and December 20th, 2023, during outpatient visits or hospital stays in a single centre setting. Inclusion criteria were: age ≥ 18 years, a confirmed diagnosis of MG, and provision of written informed consent. MG diagnosis was confirmed by a board-certified neurologist based on clinical presentation, serological antibody testing, and neurophysiological studies. Exclusion criteria included concomitant neurodegenerative disease, polyneuropathy, or malignancy.

The control group consisted of 40 healthy individuals without autoimmune disease or other relevant comorbidities.

Clinical evaluation

Certified neurologists assessed the patients. Each patient’s demographic data, clinical information, and antibody status were collected during the visits.

Disease severity was assessed by the Myasthenia Gravis Foundation of America (MGFA) classification and MGFA post-intervention status (MGFA-PIS) classification [17], as well as by the Myasthenia Gravis Composite (MGC) score [18] and Myasthenia Gravis Activities of Daily Living (MG-ADL) scale [19].

Blood sampling and measurement of plasma NfL and GFAP concentrations

Certified nursing staff acquired the patients’ blood samples during the visit or hospital stay. Blood sampling and subsequent storage procedures adhered to standard operating protocols. Blood samples were collected in tubes containing EDTA and processed within an hour after collection.

Samples were centrifuged at 20 °C and 3500 rpm for 10 minutes. The plasma was then carefully removed and stored at −20 °C. While maintaining the temperature, all samples were sent to plasma NfL and GFAP analysis. Plasma NfL and GFAP concentrations were measured using commercially available Single molecule array (Simoa) assays (Quanterix, Billerica, MA). All measurements were performed in one round of experiments using one batch of reagents by board-certified laboratory technicians blinded to the clinical data. Intra-assay coefficients of variation were below 10%.

Statistical analysis

The primary objective was to determine whether plasma NfL and GFAP concentrations differ between MG patients and controls, and whether they associate with disease severity. Two prespecified hypotheses were tested: (i) plasma NfL and GFAP levels are elevated in MG compared with controls after adjusting for age and sex, and (ii) higher candidate marker concentrations are associated with greater disease severity (MGFA class, MGC score, MG-ADL). Secondary analyses evaluated associations with history of myasthenic crisis, exposure to rescue therapies [intravenous immunoglobulin (IVIg), plasma exchange (PEX)] at any time during the disease course, and current maintenance treatment regimens at the time of the blood sampling. The analyses were designed to evaluate associations between biomarker concentrations and treatment exposure categories/current immunosuppressive regimens rather than dose-dependent treatment effects. Therefore, medication dosing was not incorporated into the statistical models.

Continuous variables were summarized as mean (SD) or median (IQR), and categorical variables as frequencies (%). Between-group comparisons were performed using the Kruskal–Wallis test for continuous variables and χ² or Fisher’s exact test for categorical variables. Correlations were assessed using Spearman’s rank test. Multivariable linear and logistic regression models were used to assess associations between NfL and GFAP and clinical measures, adjusting for age and sex.

Statistical analyses were performed using Jamovi (v2.5). Figures were generated in IBM SPSS Statistics. Statistical significance was set at p < 0.05.

Ethics

The study was conducted in accordance with the Declaration of Helsinki. Written informed consent was obtained from all participants. The local research ethics committee approved the protocol.

Results

Patient demographics

A total of 90 patients with MG (37 males [41%], 53 females [59%]) and 40 healthy controls were included. The mean age of the MG cohort was 57.2 years (SD ± 14.7, 95% CI 54.1–60.3); males were slightly older than females (59.6 ± 12.0 vs 54.7 ± 16.6 years). Sex distribution was similar between groups (χ² = 0.075, p = 0.784). Mean age differed between patients and controls but did not reach statistical significance (t = 1.734, p = 0.087). Detailed group characteristics are provided in Table 1.

Table 1. Characteristics of the patient and control groups.

Total MG patient group Control group
Patients (n, %) n=90 (100%) n=40 (100%)
Sex, male/female (n, %) 37 (41%)/53 (59%) 11 (28%)/29 (72%)
Mean age in years (SD) 57.2 (±14.7) 41.5 (±11.1)
Median disease duration (IQR), months 100.0 (±121.6) N/A
Antibody status (n, %)
 • Anti-AChR 79 (88%) N/A
 • Anti-MuSK 4 (4%)
 • Seronegative 7 (8%)
MGFA status (n, %)
 • I 14 (16%) N/A
 • IIa 15 (17%)
 • IIb 18 (20%)
 • IIIa 2 (2%)
 • IIIb 12 (13%)
 • IVb 2 (2%)
 • Total or pharmacological remission 27 (30%)
Treatment regimen (n, %)
 • AchE-I + CS + NSIS 40 (44% N/A
 • CS + NSIS 3 (3%)
 • AchE-I + NSIS 10 (11%)
 • AchE-I + CS 12 (13%)
 • AchE-I 14 (16%)
 • CS 3 (3%)
 • No therapy 8 (9%)
Additional therapy (n, %)
 • MCAB (Rituximab) 1 (1%)
 • IvIg 13 (14%)
 • PLEX 26 (29%)
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Table showing the MG and control patient demographics and clinical data. Abbreviations: AchE-I: acetylcholinesterase inhibitors; AChR: acetylcholine receptor; CS – corticosteroids; IQR: interquartile range; MG: myasthenia gravis; IvIg: intravenous immunoglobulin; MCAB: monoclonal antibodies; MGFA – Myasthenia Gravis Foundation of America, MuSK – muscle-specific kinase, N/A: not applicable; NSIS: non-steroid immunosuppressants; PLEX: plasma exchange; SD: standard deviation.

Associations of NfL and GFAP with age and sex

Age showed a strong positive association with both NfL and GFAP. Each additional year of age predicted higher plasma NfL concentrations (estimate 0.33, 95% CI 0.17–0.49, p < 0.001) and GFAP concentrations (estimate 2.70, 95% CI 1.17–4.23, p < 0.001). These relationships remained significant after adjusting for sex, disease duration, MGFA class, and treatment status. No independent effect of sex was observed.

Group comparisons (MG vs controls)

Plasma concentrations of NfL and GFAP did not differ significantly between MG patients and controls after adjustment for age and sex. The association between MG status and the studied outcome appeared weak, with wide confidence intervals suggesting substantial uncertainty and insufficient evidence for a definitive conclusion. Median concentrations for each group are shown in Table 2.

Table 2. Plasma NfL and GFAP concentration comparisons between the patient group and the control group.

MG group Control group
Median NfL, pg/mL (IQR) 9.8 (9.3) 6.1 (4.0)
Median GFAP, pg/mL (IQR) 122.5 (99.6) 87.5 (48.5)
Median MGC score (IQR) 4.0 (8.0) N/A
Median MG-ADL scale (IQR) 3.0 (6.0) N/A
NfL correlation with age, p 0.714, p < 0.001 0.481, p = 0.002
GFAP correlation with age, p 0.618, p < 0.001 0.303, p = 0.57
NfL correlation with disease duration, p −0.165, p = 0.125 N/A
GFAP correlation with disease duration, p −0.080, p = 0.457 N/A
NfL correlation with MGC score, p −0.080, p = 0.458 N/A
NfL correlation with MG-ADL scale, p −0.052, p = 0.629 N/A
GFAP correlation with MGC score, p −0.058, p = 0.593 N/A
GFAP correlation with MG-ADL scale, p −0.079, p = 0.463 N/A
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Table showing the median plasma neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP) concentration in the myasthenia gravis and control groups, correlation with age and median results of the scales. Abbreviations: IQR: interquartile range; MG: myasthenia gravis; MGC score: Myasthenia Gravis Composite score; MG-ADL scale: Myasthenia Gravis Activities of Daily Living scale; N/A: not applicable; GFAP: plasma glial fibrillary acidic protein; NfL: plasma neurofilament; SD: standard deviation.

Associations with disease severity

Within the MG cohort, plasma NfL and GFAP concentrations were not associated with clinical severity. Neither candidate marker correlated with MGFA class (Fig 1 and Fig 2), MGC score, nor MG-ADL scale (p > 0.05 for all comparisons).

Fig 1. Plasma neurofilament light (NfL) concentration across the Myasthenia Gravis Foundation of America (MGFA) severity groups.

Fig 1

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A boxplot graph showing NfL concentration (pg/ml) across Myasthenia Gravis Foundation of America severity groups. No significant difference in NfL concentration across MGFA cgroups was found (p = 0.662).

Fig 2. Plasma glial fibrillary acidic protein (GFAP) across the MG severity groups.

Fig 2

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A boxplot graph showing NfL concentration (pg/ml) across Myasthenia Gravis Foundation of America severity groups. There was no significant difference in GFAP concentration across MGFA groups (p = 0.331).

Clinical outcomes and treatment exposures

No significant associations were identified between candidate marker concentrations and history of myasthenic crisis, exposure to rescue therapies (IVIg, PEX), or current treatment regimen. Multivariable logistic and multinomial regression analyses yielded non-significant results throughout (p > 0.05).

Discussion

This study found no significant differences in plasma concentrations of neurofilament light chain or glial fibrillary acidic protein between patients with myasthenia gravis and healthy controls. Neither candidate marker correlated with disease severity as assessed by MGFA class, MGC score, or MG-ADL, nor with history of crisis or treatment exposure. These findings suggest that, unlike in other neuroimmunological conditions, NfL and GFAP are not suitable plasma biomarkers for MG.

In contrast to earlier reports suggesting elevated NfL in MG subgroups, our age-adjusted analyses did not demonstrate a disease-specific increase. Prior studies included older patients compared with controls, whereas our cohort was more closely age-matched. Because NfL strongly correlates with age, previously reported elevations may have been driven by demographic differences rather than MG pathology. This emphasizes the need for age adjustment when interpreting NfL levels and indicates that NfL does not capture MG-specific pathophysiological changes.

Elevated NfL levels have been linked to reduced muscle performance and atrophy, features seen in MG patients who are often physically inactive [20,21]. Histopathological studies suggest that muscle fibre atrophy may occur secondary to denervation of the motor endplate, potentially contributing to neurofilament release [22–24]. Reports of increased neurofilament heavy chain in ocular MG support this mechanism, but our findings provide no evidence of such changes in plasma NfL [25]. Our findings suggest that neuromuscular junction pathology is not associated with detectable neurofilament release. While larger studies integrating histopathology, neurophysiology, and biomarker analyses could provide additional confirmation, major changes in the observed relationship are unlikely if well-defined study populations are used.

GFAP, in contrast, has not previously been studied in MG. While primarily expressed in astrocytes, GFAP is also present in terminal Schwann cells at the neuromuscular junction [26,27]. In CNS disorders such as traumatic brain injury, multiple sclerosis, and Alzheimer’s disease, GFAP serves as a robust marker of astrocytic injury. Based on histopathological evidence of secondary motor endplate denervation, we hypothesized that GFAP might also be increased in MG. However, plasma concentrations did not differ between patients and controls. GFAP correlated with age only in the whole MG cohort, consistent with prior reports that increases become more evident in older populations [28–30]. Given that our age-adjusted MG and control groups were relatively young, it is possible that GFAP changes in MG might only be detectable in older cohorts [30].

The absence of biomarker utility for NfL and GFAP in MG highlights important differences between MG and other neuroimmunological disorders, such as multiple sclerosis (MS) and neuromyelitis optica spectrum disorders (NMOSD). In MS and NMOSD, NfL reflects axonal injury and GFAP indicates astrocytic damage, both of which are central to disease progression. By contrast, MG primarily affects the neuromuscular junction, where postsynaptic receptor dysfunction rather than widespread axonal or astrocytic injury drives clinical manifestations. Although secondary changes such as denervation and muscle atrophy may occur, they appear insufficient to produce robust or consistent increases in circulating NfL or GFAP [31]. These differences underscore that biomarkers validated in CNS-driven disorders cannot be assumed to translate to MG, where pathology is localised and immune-mediated in a distinct manner. Our findings therefore reinforce the necessity of developing disease-specific biomarker strategies for MG, focusing on mechanisms directly linked to its pathophysiology, such as autoantibody profiles, immune cell phenotyping, cytokine signatures, and circulating microRNAs.

This study has several limitations that should be acknowledged. The control group was relatively small and younger than the whole MG cohort, necessitating age adjustment. In addition, seronegative and MuSK-positive subgroups were underrepresented, precluding meaningful comparisons with AChR-positive patients. Finally, the distribution across MGFA severity classes was imbalanced, with small numbers in higher severity groups, requiring class combinations for analysis. These factors may have reduced the power to detect subtle subgroup differences.

In conclusion, this study demonstrates that plasma neurofilament light chain and glial fibrillary acidic protein, despite their established value as biomarkers in other neuroimmunological and neurodegenerative disorders, do not differentiate patients with myasthenia gravis from healthy controls and show no association with disease severity or treatment exposure. As the first systematic evaluation of GFAP in MG and one of the largest controlled studies of NfL in MG, our findings highlight that biomarkers validated in central nervous system diseases cannot be directly applied to MG. Future research should therefore prioritize the development of MG-specific biomarker strategies, focusing on immunological and molecular mechanisms more closely aligned with the pathophysiology of this rare disorder.

Supporting information

S1 Dataset. This is the dataset underlying the findings of this study.

(XLSX)

pone.0352017.s001.xlsx (26.4KB, xlsx)

Data Availability

All relevant data underlying the results reported in this study are provided within the paper and its Supporting information files. The anonymised minimal dataset required to replicate the study findings is available as S1 Dataset.

Funding Statement

VĶ - Riga Stradiņš University has granted the following funding: RSU-ZG-2024/1-0036 “Discovering biomarkers in Myastenia Gravis: Insights into Fatigue, Immune Dysregulation, and Viral Infections” \5.2.1.1.i.0/2/24/I/CFLA/005 Doctoral study grant. HZ is a Wallenberg Scholar and a Distinguished Professor at the Swedish Research Council supported by grants from the Swedish Research Council (#2023-00356, #2022-01018 and #2019-02397), the European Union’s Horizon Europe research and innovation programme under grant agreement No 101053962, Swedish State Support for Clinical Research (#ALFGBG-71320), the Alzheimer Drug Discovery Foundation (ADDF), USA (#201809-2016862), the AD Strategic Fund and the Alzheimer’s Association (#ADSF-21-831376-C, #ADSF-21-831381-C, #ADSF-21-831377-C, and #ADSF-24-1284328-C), the European Partnership on Metrology, co-financed from the European Union’s Horizon Europe Research and Innovation Programme and by the Participating States (NEuroBioStand, #22HLT07), the Bluefield Project, Cure Alzheimer’s Fund, the Olav Thon Foundation, the Erling-Persson Family Foundation, Familjen Rönströms Stiftelse, Stiftelsen för Gamla Tjänarinnor, Hjärnfonden, Sweden (#FO2022-0270), the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 860197 (MIRIADE), the European Union Joint Programme – Neurodegenerative Disease Research (JPND2021-00694), the National Institute for Health and Care Research University College London Hospitals Biomedical Research Centre, the UK Dementia Research Institute at UCL (UKDRI-1003), and an anonymous donor. KB is supported by the Swedish Research Council (#2017-00915 and #2022-00732), the Swedish Alzheimer Foundation (#AF-930351, #AF-939721, #AF-968270, and #AF-994551), Hjärnfonden, Sweden (#ALZ2022-0006, #FO2024-0048-TK-130 and FO2024-0048-HK-24), the Swedish state under the agreement between the Swedish government and the County Councils, the ALF-agreement (#ALFGBG-965240 and #ALFGBG-1006418), the European Union Joint Program for Neurodegenerative Disorders (JPND2019-466-236), the Alzheimer’s Association 2021 Zenith Award (ZEN-21-848495), the Alzheimer’s Association 2022-2025 Grant (SG-23-1038904 QC), La Fondation Recherche Alzheimer (FRA), Paris, France, the Kirsten and Freddy Johansen Foundation, Copenhagen, Denmark, Familjen Rönströms Stiftelse, Stockholm, Sweden, and an anonymous filantropist and donor. The sponsors and funders did not play any role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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Decision Letter 0

Karlo Toljan

31 Mar 2026

-->PONE-D-25-61362-->-->Limited utility of plasma neurofilament light chain and glial fibrillary acidic protein as biomarkers in myasthenia gravis: a controlled cohort study.-->-->PLOS One

Dear Dr. Kenina,

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Reviewer #1: Partly

**********

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Reviewer #1: Yes

**********

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**********

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Reviewer #1: This paper evaluates the utility of NFL and GFAP as diagnostic and prognostic biomarkers in myasthenia gravis. These two biomarkers have gained significant attention in the last 5-10 years, particularly given the correlations found in multiple sclerosis and amyotrophic lateral sclerosis. As such, their utilities in MG warrant further investigations as the authors aim to address in this paper. There are a few points that require revising before consideration for publication.

1. Why are there restrictions on data availabiity? Later the authors state that the data can be requested. If the former was a mistake, please correct it.

2. I would recommend refraining from using the word "limited" in the title. As they point out in the discussion and conclusion sections, they were unable to find statistically significant associations between these biomarkers, MG presence and various different characteristics. Therefore this paper actually supports lack of utility. Furthermore, generally phrasing the research question rather than making a statement in the title is preferable.

3. Biomarkers can be diagnostic, prognostic, predictive/risk-related, therapeutic/monitoring, or safety-related. Please define the hypothesized role of NFL and GFAP biomarkers in MG in the introduction section (which appears to be both diagnostic and prognostic based on the variables selected for studying). Additionally, these should not be referred to as biomarkers in the rest of the paper as it was not shown that they have such a role in MG.

4. In the introduction, I would recommend mentioning the role of NFL (as well as GFAP) in ALS given its relevance as both ALS and MG are neuromuscular disorders.

5. Line 79, MG is not a peripheral neuropathy. Please rephrase this sentence.

6. In the methods section, the authors should better define the variables included in this study. For example, does exposure to rescue therapies refer to any history of rescue therapy, or recently? These would have different implications. Similarly, does treatment regimen refer to current therapies? How are prior therapies factored into the analyses (given patients with prior therapy escalation likely have more severe disease)? Are different doses of treatments taken into consideration during analyses?

7. Lines 177-178, it is not clear what is meant in this sentence, please rephrase.

8. There are stylistic and scientific issues with the discussion section.

a) Lines 237-289, this sentence was already mentioned in the introduction, please do not repeat here. The authors should rather explain they chose to study these specific proteins as potential biomarkers in MG - what is the scientific rationale of potential relevance in MG? This is clarified to some extent in the following paragraphs, however this explanation should be provided early on in the paper.

b) Lines 246-247: This sentence is rather redundant and if intended to keep, should be moved to the prior paragraph.

c) Lines 252-255: This is a broad and generic sentence without justification provided - what is testing in a larger study indicated if the results from this study are negative?

9. In both the conclusion paragraph and abstract section, authors claim that this is the first study to systematically assess the role of NFL (and GFAP) in MG. This is not true, especially with regards to NFL. There are other studies which looked at NFL in MG: PMID: 40988756, PMID: 36712429. Please change this sentence to focus on novelty rather than a claim of primacy.

**********

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**********

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PLoS One. 2026 Jul 7;21(7):e0352017. doi: 10.1371/journal.pone.0352017.r002

Author response to Decision Letter 1

31 May 2026

Response to the Editor and Reviewer

We thank the Editor and the Reviewers for their careful and thorough evaluation of our manuscript and for their constructive comments. We have revised the manuscript accordingly and believe these changes have improved the paper’s clarity and quality. Below, we provide a detailed, point-by-point response to each comment. All revisions have been incorporated into the manuscript and highlighted in the revised version.

We hope that the revisions and responses adequately address the reviewers’ comments and improve the manuscript. We appreciate the opportunity to revise our work and look forward to your further consideration.

Editorial comments

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

Response. We thank the editors for this guidance. The manuscript has been revised to comply with PLOS ONE style requirements, including formatting, structure, and file naming, using the provided templates.

2. Your ethics statement should only appear in the Methods section of your manuscript. If your ethics statement is written in any section besides the Methods, please delete it from any other section.

Response. We confirm that the ethics statement appears only in the Methods section of the revised manuscript (page 8, lines 157-160).

3. We note that you have indicated that there are restrictions to data sharing for this study. For studies involving human research participant data or other sensitive data, we encourage authors to share de-identified or anonymized data. However, when data cannot be publicly shared for ethical reasons, we allow authors to make their data sets available upon request. For information on unacceptable data access restrictions, please see http://journals.plos.org/plosone/s/data-availability#loc-unacceptable-data-access-restrictions.

Before we proceed with your manuscript, please address the following prompts:

a) If there are ethical or legal restrictions on sharing a de-identified data set, please explain them in detail (e.g., data contain potentially identifying or sensitive patient information, data are owned by a third-party organization, etc.) and who has imposed them (e.g., a Research Ethics Committee or Institutional Review Board, etc.). Please also provide contact information for a data access committee, ethics committee, or other institutional body to which data requests may be sent.

b) If there are no restrictions, please upload the minimal anonymized data set necessary to replicate your study findings to a stable, public repository and provide us with the relevant URLs, DOIs, or accession numbers. Please see http://www.bmj.com/content/340/bmj.c181.long for guidelines on how to de-identify and prepare clinical data for publication. For a list of recommended repositories, please see https://journals.plos.org/plosone/s/recommended-repositories. You also have the option of uploading the data as Supporting Information files, but we would recommend depositing data directly to a data repository if possible.

Please update your Data Availability statement in the submission form accordingly.

Response. We agree with the importance of ensuring transparency and reproducibility. In the original submission, the wording regarding data availability did not align with PLOS policy and may have caused confusion. We have now revised this to ensure compliance. The dataset underlying the findings of this study will be provided as Supplementary Information accompanying the revised manuscript (Supplementary information, file name - S1_Dataset).

4. In the online submission form, you indicated that anonymised data that support the findings of this study are available from the corresponding author upon reasonable request.

All PLOS journals now require all data underlying the findings described in their manuscript to be freely available to other researchers, either 1. In a public repository, 2. Within the manuscript itself, or 3. Uploaded as supplementary information.

This policy applies to all data except where public deposition would breach compliance with the protocol approved by your research ethics board. If your data cannot be made publicly available for ethical or legal reasons (e.g., public availability would compromise patient privacy), please explain your reasons on resubmission and your exemption request will be escalated for approval.

Response. We thank the editor for highlighting this important issue. In the original submission, the Data Availability Statement was not fully aligned with PLOS ONE policy and may have caused confusion. We have now revised this to ensure full compliance. The minimal anonymised dataset required to replicate the study’s findings is provided in the Supporting Information accompanying the manuscript (S1_Dataset). The dataset has been fully de-identified and does not contain any personally identifiable information. Data sharing complies with ethical approval and applicable data protection regulations.

5. Please include captions for your Supporting Information files at the end of your manuscript, and update any in-text citations to match accordingly. Please see our Supporting Information guidelines for more information: http://journals.plos.org/plosone/s/supporting-information.

Response. We have added Supporting Information at the end of the manuscript (page 21, line 416), which includes a caption for the supplementary file (the dataset underlying the study's findings).

6. We note that there is identifying data in the Supporting Information file <Ethics_Committee_Approval_English.docx>. Due to the inclusion of these potentially identifying data, we have removed this file from your file inventory. Prior to sharing human research participant data, authors should consult with an ethics committee to ensure data are shared in accordance with participant consent and all applicable local laws.

Response. The file “Ethics_Committee_Approval_English.docx” contains the Ethics Committee's official decision, including the names of the committee members as part of the formal approval document. These names refer to institutional representatives acting in their professional capacity and do not constitute research participant data. Nevertheless, we fully acknowledge the importance of safeguarding potentially identifying information. In accordance with your guidance, we have removed the file from the Supporting Information. If required, we are happy to provide a redacted version of the document or submit the approval confidentially for editorial review.

7. If the reviewer comments include a recommendation to cite specific previously published works, please review and evaluate these publications to determine whether they are relevant and should be cited. There is no requirement to cite these works unless the editor has indicated otherwise.

Reviewer 1.

1. Why are there restrictions on data availabiity? Later the authors state that the data can be requested. If the former was a mistake, please correct it.

Response. We thank the reviewer for highlighting this point. As stated above in the response to editorial comments, we agree with the importance of ensuring transparency and reproducibility. In the original submission, the wording regarding data availability did not align with PLOS policy and may have caused confusion. We have now revised this to ensure compliance.

The dataset underlying the findings of this study will be provided as Supplementary Information accompanying the revised manuscript. We confirm that the data have been fully anonymized and do not contain any identifiable personal information, and their sharing is in accordance with applicable ethical and data protection regulations.

2. I would recommend refraining from using the word "limited" in the title. As they point out in the discussion and conclusion sections, they were unable to find statistically significant associations between these biomarkers, MG presence and various different characteristics. Therefore this paper actually supports lack of utility. Furthermore, generally phrasing the research question rather than making a statement in the title is preferable.

Response. We agree with this important suggestion. The title has been revised to remove interpretative wording (“limited utility”) and instead reflect the research question in a neutral manner (page 1, lines 1-3).

3. Biomarkers can be diagnostic, prognostic, predictive/risk-related, therapeutic/monitoring, or safety-related. Please define the hypothesized role of NFL and GFAP biomarkers in MG in the introduction section (which appears to be both diagnostic and prognostic based on the variables selected for studying). Additionally, these should not be referred to as biomarkers in the rest of the paper as it was not shown that they have such a role in MG.

Response. We thank the reviewer for this important comment. We agree that the original wording could overstate the established role of NfL and GFAP in MG. We have revised the Introduction to clarify that NfL and GFAP were investigated as candidate biomarkers with hypothesised diagnostic and prognostic/monitoring relevance in MG (page 5, lines 99-100)

We also revised the wording throughout the manuscript to avoid implying that the utility of biomarkers has been demonstrated in MG, replacing the word “biomarker” with “NfL and GFAP” or “candidate markers” where appropriate.

4. In the introduction, I would recommend mentioning the role of NFL (as well as GFAP) in ALS given its relevance as both ALS and MG are neuromuscular disorders.

Response. We thank the reviewer for this helpful suggestion. We have revised the Introduction to include the established role of NfL and GFAP in ALS, highlighting their relevance in neuromuscular disorders and further supporting the rationale for investigating these biomarkers in MG (page 5, lines 79-86).

5. Line 79, MG is not a peripheral neuropathy. Please rephrase this sentence.

Response. We agree with this note. The sentence has been rephrased so that it does not include incorrect terminology (pages 4-5, lines 76-78).

6. In the methods section, the authors should better define the variables included in this study. For example, does exposure to rescue therapies refer to any history of rescue therapy, or recently? These would have different implications. Similarly, does treatment regimen refer to current therapies? How are prior therapies factored into the analyses (given patients with prior therapy escalation likely have more severe disease)? Are different doses of treatments taken into consideration during analyses?

Response. We thank the reviewer for highlighting the need for clearer definitions of treatment-related variables.

Specifically, “exposure to rescue therapies” referred to any documented prior use of intravenous immunoglobulin (IVIg) or plasma exchange (PEX) at any time during the disease course, rather than only recent treatment exposure. “Treatment regimen” referred to the patient’s current maintenance therapy at the time of blood sampling. This has now been described in the Methods section (page 7, lines 142-144).

We agree that prior treatment escalation may reflect more severe disease. To address this, the history of rescue therapy exposure and current treatment category were analysed separately from clinical severity measures and were interpreted as exploratory variables rather than independent markers of disease activity.

Regarding treatment dosages, the primary purpose of treatment-related analyses was to explore whether patients receiving immunosuppressive therapies differed in NfL/GFAP concentrations compared with other treatment groups, rather than to evaluate dose-response relationships. This has been clarified in the Methods section (page 7, lines 144-147).

7. Lines 177-178, it is not clear what is meant in this sentence, please rephrase.

Response. We thank the reviewer for pointing this out. The sentence has been rephrased to clarify that the association with MG and NfL and/or GFAP was weak and that the wide confidence intervals provided insufficient evidence for conclusions (page 10, lines 186-188).

8. There are stylistic and scientific issues with the discussion section.

a) Lines 237-289, this sentence was already mentioned in the introduction, please do not repeat here. The authors should rather explain they chose to study these specific proteins as potential biomarkers in MG - what is the scientific rationale of potential relevance in MG? This is clarified to some extent in the following paragraphs, however this explanation should be provided early on in the paper.

Response. We agree with the remark and have removed the repeated sentence from the discussion section.

b) Lines 246-247: This sentence is rather redundant and if intended to keep, should be moved to the prior paragraph.

Response. We agree with the remark and have removed the sentence from the discussion section.

c) Lines 252-255: This is a broad and generic sentence without justification provided - what is testing in a larger study indicated if the results from this study are negative?

Response. We thank the reviewer for pointing this out and have rephrased the sentence to better reflect the interpretation of our findings. The revised text now emphasises that our study did not demonstrate a meaningful association between neuromuscular junction pathology and detectable neurofilament release, and that while larger studies may provide additional confirmation, substantially different results are unlikely if appropriately selected and well-characterised study groups are used (page 13, lines 259-263).

9. In both the conclusion paragraph and abstract section, authors claim that this is the first study to systematically assess the role of NFL (and GFAP) in MG. This is not true, especially with regards to NFL. There are other studies which looked at NFL in MG: PMID: 40988756, PMID: 36712429. Please change this sentence to focus on novelty rather than a claim of primacy.

Response. We thank the reviewer for this important comment. We agree that the original wording overstated the novelty of the study, particularly with respect to NfL, as previous studies have already investigated NfL in MG (PMID: 40988756, PMID: 36712429). We have therefore revised the sentence in both the Abstract (page 3, line 48) and Discussion (page 15, lines 299-300) sections to avoid claims of primacy.

Other minor correctios:

• The last name of the first author has been changed to Arta Grosmane-Bataraga.

• One sentence was modified and another removed (page 14, lines 281-283 in the original manuscript) from the Discussion section, as they described limitations of an earlier statistical design that is not relevant to either the original or the revised manuscript.

Attachment

Submitted filename: point-to-point response.docx

pone.0352017.s003.docx (24.6KB, docx)

Decision Letter 1

Karlo Toljan

5 Jun 2026

Evaluation of plasma neurofilament light chain and glial fibrillary acidic protein in myasthenia gravis: a controlled cohort study

PONE-D-25-61362R1

Dear Dr. Kenina,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

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Karlo Toljan

Academic Editor

PLOS One

Acceptance letter

Karlo Toljan

PONE-D-25-61362R1

PLOS One

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