Abstract
Inflammatory neuromuscular disorders encompass a diverse group of immune-mediated diseases with varying clinical manifestations and treatment responses. The identification of specific biomarkers has the potential to provide valuable insights into disease pathogenesis, aid in accurate diagnosis, predict disease course, and monitor treatment efficacy. However, the rarity and heterogeneity of these disorders pose significant challenges in the identification and implementation of reliable biomarkers. Here, we aim to provide a comprehensive review of biomarkers currently established in Guillain-Barré syndrome (GBS), chronic inflammatory demyelinating polyneuropathy (CIDP), myasthenia gravis (MG), and idiopathic inflammatory myopathy (IIM). It highlights the existing biomarkers in these disorders, including diagnostic, prognostic, predictive and monitoring biomarkers, while emphasizing the unmet need for additional specific biomarkers. The limitations and challenges associated with the current biomarkers are discussed, and the potential implications for disease management and personalized treatment strategies are explored. Collectively, biomarkers have the potential to improve the management of inflammatory neuromuscular disorders. However, novel strategies and further research are needed to establish clinically meaningful biomarkers.
Keywords: CIDP, biomarkers, GBS, myasthenia gravis, neuromuscular diseases, IIM, inflammation
1. Introduction: The Need for Biomarkers in Inflammatory Neuromuscular Disorders
Inflammatory neuromuscular disorders are a heterogeneous group of immune-mediated diseases with diverse underlying pathomechanisms. Epidemiology, clinical manifestations, treatment strategies, and responses vary across the spectrum of disease. Common to all is a potential severe burden of disease with conceivable long-lasting disability. Designated criteria for categorisation of affected individuals into corresponding subgroups are well-established [1]. Over the last few years, our pathophysiological understanding of autoimmune inflammatory neuromuscular disorders has steadily improved. However, essential pathogenic processes remain to be studied. In this regard, the recognition of specific biomarkers could confer additional insights while informing treatment decisions. Biomarkers are characteristic features of biological processes and are detectable and quantifiable in body fluids and tissues [2]. As valuable indicators, they serve, inter alia, diagnostic, prognostic, and therapeutic purposes in diseases.
Considering the rarity and diversity of clinical manifestation of neuromuscular disorders (NMDs), the identification of specific biomarkers for each of them is essential, particularly regarding disease course prediction and improvement of daily clinical practice. In recent years, a considerable development on this matter has emerged. However, there is still a lack of objective biomarkers suitable in NMDs.
This review has the intention to provide an overview of biomarkers currently established in Guillain-Barré syndrome (GBS), chronic inflammatory demyelinating polyneuropathy (CIDP), myasthenia gravis (MG), and idiopathic inflammatory myopathy (IIM). Our purpose is to discuss and highlight yet unmet demands concerning further parameters.
2. On the Concept of Biomarkers
The appliance of biomarkers has become increasingly relevant over the last decade. As useful tools, they serve various aspects in disease management. Biomarkers are indicators of both physiological mechanisms and pathogenic processes or responses to various interventions and treatment regimens in general [2,3]. Particularly in diagnostic, prognostic, and predictive aspects, biomarkers can contribute as helpful tools. The detection of the disease of interest is achieved by diagnostic biomarkers. The presence or alteration of a predictive biomarker forecasts probabilities of incidents following the exposure to an intervention or environmental factor [2]. Prognostic biomarkers aid in the estimation of clinical course and severity in the observed condition. Correspondingly, monitoring biomarkers can be employed in longitudinal disease assessment, detecting the status of a condition or measuring treatment effects. Detection of biomarkers may offer insights into causative pathomechanisms. Hence, biomarkers are crucial to the development of treatment strategies including targeted therapies, assisting healthcare for affected individuals and the population.
The further identification and utilization of biomarkers in clinical and scientific settings is essential in disease management. In this review, we intend to set up an overview of the so far published biomarkers in the mentioned autoimmune NMDs. We discuss relevant biomarkers by categorizing them into subgroups as mentioned above. Achieving a strict separation into the respective subsets is not always feasible, as certain biomarkers may serve multiple functions. Also, we aim to emphasize the prevailing unfulfilled need for the establishment of further specific biomarkers.
3. Biomarkers in GBS and CIDP
3.1. Current Biomarkers in GBS and CIDP
Few recognized biomarkers of GBS and CIDP are presently integrated in diagnostics and monitoring of disease courses and treatment responses. An overview of relevant biomarkers in use is given in Table 1.
Table 1.
Disease | Type of Biomarker |
Biomarker | Detection Method | Correlation | Occurence | References | Limitations/Comment |
---|---|---|---|---|---|---|---|
GBS/CIDP | Diagnostic | Lipooligosaccharides (LOS) with A, B, C, E, F and H loci; Serotype and sequence type of Campylobacter jejuni | PCR screening, genes from published LOS loci and sequencing Serum and CSF |
Identification of C. jejuni-associated GBS | GBS and Miller-Fisher syndrome (MFS) | [4,5] | |
Diagnostic | Antibodies against Campylobacter jejuni DNA-binding protein (C-Dps) |
ELISA, Western Blot Serum |
Detection of anti-C-Dps-IgG indicates C. jejuni related GBS |
Campylobacter jejuni-related GBS | [6] | Also detected in patients with C. jejuni enteritis (rarely) | |
Diagnostic | Metallo-proteinases (MMPS) (MMP-9, TIMP-1) |
ELISA Serum |
No correlation | Described in CIDP | [7] | Not disease-specific | |
Diagnostic | Antibodies to peptides from myelin proteins P0, P214–25, PMP22 and connexin 32 | Antigen-specific proliferation assay, Immunoprecipitation, Western Blot Serum |
No correlation | Described in GBS and CIDP | [8,9,10,11,12,13,14] | ||
Diagnostic Monitoring |
Sphingomyelin (SM) | Fluorescence-based assay CSF |
Correlation with disease activity, elevated in active CIDP. | Increased in GBS and CIDP | [15] | ||
Diagnostic | Cystatin C (cysteine protease inhibitor) | ELISA CSF |
Decrease may be linked to higher cathepsin B activity (cathepsin B levels increased in CSF) | Significant decrease of cystatin c levels in GBS and CIDP patients | [16,17,18,19] | Decrease also observed in MS patients | |
Diagnostic | Protein 14-3-3 | Immunoblot assay CSF |
Early detection (12 to 48 h after disease onset) in GBS | Elevated in CSF of GBS and CIDP patients | [20,21] | Not disease-specific | |
Diagnostic | IL-8 | Multiplex bead immunoassays CSF |
Aid in differentiation between CIDP and GBS, including acute-onset CIDP. CSF IL-8 in GBS > CIDP Optimal IL-8 cutoff → 70 pg/mL |
Should be measured initially during diagnostical process High specificity and positive predictive value |
[22] | Not disease-specific | |
Predictive Prognostic |
Autoantibodies to gangliosides (GM1, GA1, GD1a, GD1b, GalNAc-GD1a, 9-O-Acetyl GD1b, GD3, GM1, GT1a, GT1b, GT3, GQ1b, 0-Acetyl GT3, LM-1, GD1a/GD1b, GM1/GalNac-GD1a, GM1/PA, GM1/GD1a, GM1/GT1b, LM1/GA1) IgG and IgM |
ELISA Serum |
Correlation with clinical phenotypes and specific symptoms of GBS e.g., ophthalmoplegia and Anti-GQ1b IgG Anti-GM1 linked to Campylobacter jejuni, titers correlate with clinical recovery and therapy response GM1/GalNac-GD1a linked to respiratory infection |
High prevalence in GBS of Anti-GM1 and Anti-GT1a | [23,24,25,26,27,28,29] | ||
Predictive Prognostic |
Antibodies against nodal and paranodal proteins: Neurofascin (Nfasc155 and Nfasc140/186) Contactin-1 (CNTN1) Contactin- associated protein-1 (Caspr1) Caspr1/CNTN1 complex Gliomedin |
ELISA, Immunoprecipitation, cell-based Assays Serum |
Associated with specific clinical manifestation e.g., ataxia and tremor Poorer response to IVIg Anti-CNTN1 seem to benefit from corticosteroids |
Nfasc155 in 4–18% of CIDP cases | [30,31,32,33,34,35,36,37,38] | ||
Predictive Prognostic |
Neurofilaments Phosphorylated neurofilament heavy protein (pNFH) Neurofilament light chain (Nfl) |
ELISA, Electrochemiluminescence (ECL) based immunoassay Serum and CSF |
Indicator for neurodegeneration Positive correlation with clinical and electrophysiological presentation in GBS Association with disease progression and therapy outcome in CIDP |
Elevated in both serum and CSF of GBS and CIDP patients | [25,39,40,41,42,43] | General indicators of axonal damage, also detectable in other patient groups with evidence of structural CNS damage | |
Predictive Prognostic |
Tau-proteins | ELISA CSF |
Correlation with clinical manifestation and poorer clinical outcome | Elevated in CSF of GBS and CIDP patients | [25,42,44,45] | Also detectable in other patient groups with evidence of structural CNS damage e.g., Alzheimer’s Disease | |
Prognostic | Autoantibodies against galactocerebroside (Gal-C) |
ELISA Serum |
Association with sensory deficits and autonomic disruption in GBS Association with Mycoplasma pneumoniae infection |
GBS | [46,47] | ||
Prognostic | Neuron-specific enolase (NSE) | Enzyme immunoassay methods CSF |
Higher levels correlate with a longer duration of disease | Elevated in CSF of GBS and CIDP patients | [48,49,50] | CSF-NSE is not GBS or CIDP specific; Elevation is also observed other conditions e.g., Creutzfeldt-Jakob disease [51] | |
Prognostic Predictive Monitoring |
Cytokines Interferon gamma (IFN γ), Tumor necrosis factor α (TNF α), Transforming growth factor β1 (TGF β1), IL-1β, IL-4, IL-6, IL-10, IL-12, IL-16, IL-17, IL-18, IL-22, IL-23, IL-37 |
ELISA based assays (multiplexed fluorescent bead-based immunoassay Serum and CSF |
TNF α and IFN γ are elevated in GBS and correlate with clinical severity TGF β1 levels are decreased in the early course of GBS, downregulation correlates with clinical disability Serum levels are positively correlated with GBS disease severity and decreased after IVIg treatment (IL-17A, IL-37) CSF IL-17A levels were positively correlated with clinical manifestation of GBS Upregulation of IL-4 and IL-10 are linked to recovery phase in GBS CSF and serum levels of interleukins declined after IVIg treatment |
Cytokine elevation is described in CIDP and GBS | [52,53,54,55,56,57,58,59,60,61,62,63,64,65] | Not disease-specific. | |
Prognostic Monitoring |
Serum complement proteins C3, C3a, C5a, C5b-9 |
Nephelometry Serum |
Upregulation predicts poor prognosis High C3 correlates with complement activation with high C3a und C5a Correlation with disease activity |
Increased in GBS and CIDP | [66,67,68] | Not disease-specific | |
Prognostic Monitoring |
S100B protein (calcium-binding astroglial protein) | ELISA Serum and CSF |
Elevated in CSF and serum Association with clinical severity and poor prognosis Decrease in stable disease course |
Elevated in GBS and CIDP | [42,49,50] | Expression of S100B is not restricted to neural tissue; Serum levels can be increased after e.g., bone fractures or hepatic injury [69,70] | |
Prognostic Diagnostic |
Stem cell factor (SCF) Hepatocyte growth factor (HGF) |
Multiplex bead-based ELISA CSF |
Increased | Elevated levels in CSF CIDP > GBS Correlation with chronicity |
[71] | Value of this examination is still uncertain | |
Monitoring | Chemokines CCR2, CCL7,CCL3, CCL27, CCR1, CCR5, CXCL10, CXCR3, CXCL9, CXCL12, monocyte chemoattractant protein 1 (MCP-1) |
Multiplex bead-based ELISA Serum and CSF |
CCR2 and MCP-1 decreased in the recovery stage | Increased in GBS and CIDP | [25,72,73,74] | Not disease-specific | |
Monitoring | Intercellular adhesion molecule 1 (ICAM-1) Vascular cell adhesion molecule 1 (VCAM-1) Vascular Endothelial Growth Factor (VEGF) |
Multiplex bead-based ELISA CSF |
Decrease after therapy in studies Correlation with repair processes is currently being studied |
Increased in GBS and CIDP | [71,75,76] | Not disease-specific | |
Monitoring | MicroRNAs has-miR4717-5p (GBS) has-miR-642b-5p (GBS) miR-31-5p (CIDP) |
Microarray, droplet digital PCR Serum |
High levels of miR-31-5p correlate with longer disease duration Potential in improving personalized patient care |
Detectable in GBS and CIDP | [77,78,79,80] | ||
MG | Diagnostic Monitoring |
Anti-AChRs (muscle nicotinic acetylcholine receptors) IgG subtype 1 and 3 |
Radioimmunprecipitation assay (RIPA) with high specificity and sensitivity, fixed cell-based assays Serum |
Monitoring in patients with immunosuppressive treatment Higher levels in ocular MG are associated with conversion to generalized MG Higher levels in late-onset MG |
85% in generalized MG, highly specific for MG | [81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99] | Lower titers in ocular MG Inconsistent studies regarding correlation with disease severity and treatment response |
Diagnostic Prognostic Predictive |
Anti-MuSK (Muscle-specific kinase) IgG subtype 4 |
Radioimmunoprecipitation assay (RIPA), ELISA, cell-based assay (CBA) Serum |
Correlation with disease severity Affection of facial-bulbar muscles Early crises and challenging treatment Worse outcome Association with early onset MG and better response to rituximab |
5–8% of MG 30–50% of AChR-negative MG |
[100,101,102,103,104,105,106,107,108,109,110] | More often in female patients Highest sensitivity in detection via CBA |
|
Diagnostic | Anti-LRP4 (low-density lipoprotein receptor-related protein 4) IgG subtype 1 and 2 |
Cell-based assay (CBA) Serum |
Stronger clinical manifestation than in seronegative MG | 2% of MG; higher in non-AChR and non-MuSK cases | [111,112,113,114,115,116,117] | Higher prevalence in female patients Not specific for MG (e.g., found in ALS as well) |
|
Diagnostic Prognostic |
Anti-Titin | ELISA, Cell-based assay (CBA) Serum |
Thymoma-associated MG More frequent hospitalization |
20–40% in Anti-AChR-positive MG | [95,118,119,120] | Screening for thymoma presence should follow positive testing | |
Diagnostic Prognostic |
Anti-Kv1.4 (voltage gated potassium channel) | Cell-based assay (CBA), Radioimmunoprecipitation assay (RIPA) Serum |
Association with myasthenic crises and thymoma Association with bulbar manifestation, myocarditis and QT-Time prolongation (Japanese population) |
11–18% (Japanese MG population) | [95,121,122] | More frequent in female patients Expensive detection |
|
Diagnostic | Anti-Rapsyn | ELISA Serum |
No correlations | 15% of MG | [95,123] | Not MG-specific | |
Diagnostic Prognostic |
Anti-Cortactin | Western Blot, ELISA Serum |
Mild symptoms | 10–25% of MG | [95,124,125,126] | Not MG specific | |
Diagnostic Prognostic Predictive |
Anti-Agrin IgG subtype 1 and 3 |
ELISA; CBA; serum | Correlation with limited therapeutic response and mild to severe clinical manifestation | 2–5% of MG, mainly seropositive MG | [95,127,128] | More frequent in male patients | |
Diagnostic Prognostic Predictive |
Micro-RNAs miR-150-5p miR-21-5p miR-30e-5p let-7 miRNA family |
Microarray, droplet digital PCR Serum |
Correlation with treatment response High miR-30e-5p levels are associated with risk of generalization in ocular MG |
Studied in AchR and MuSK-positive MG | [129] | ||
IIM | Diagnostic Predictive Prognostic |
Anti-Mi-2 | ELISA, Immunoblot Serum |
Classical DM, associated with beneficial prognosis, mild myositis, lower risk of ILD, better treatment response especially to rituximab Correlation with disease activity Association with HLA-DR7 |
MSA 2–45% prevalence in DM |
[130,131,132,133,134,135] | Positive sera may also be found by ELISA in PM patients [136] Prevalence can only be estimated (varying among different countries) |
Diagnostic Predictive Prognostic |
Anti-ARS (aminoacyl-tRNA synthetases) Jo-1, PL-7, PL-12, EJ, OJ, KS, ZO, YRS |
RNA-Immunoprecipitation, ELISA, Line Blots, Serum |
Association with ASyS Higher mortality and interstitial lung disease (ILD) incidence in non-Anti-Jo-1-ARS (+) Higher treatment dosage required |
MSA Anti-Jo-1 15–30% in DM/PM Others < 5% |
[134,137,138,139,140,141] | Low prevalence of non-Anti-Jo-1-ARS RNA-Immunoprecipitation not widely available Rates of false-positive cases higher in Line Blots [140] |
|
Diagnostic Predictive Prognostic |
Anti-NXP2 (anti-nuclear matrix protein 2) | Immunoprecipitation, Western Blot Serum |
Association with calcinosis and severe myositis, cancer development Correlation with disease activity |
MSA Adult and juvenile DM 1–5% |
[134,142,143,144,145] | Immunoassays have been released and are currently discussed | |
Diagnostic Predictive Prognostic Monitoring |
Anti-MDA-5 (Melanin differentiation-associated protein-5)/CADM140 |
Immunoprecipitation, Western Blot, ELISA Serum |
Associated with clinically amyotrophic DM (CADM), ILD, poor prognosis, sever skin manifestation Titer levels linked to disease severity and outcome |
MSA 15–20% in IIM, mainly CADM |
[133,134,146,147] | Higher prevalence in Asia More frequent in women |
|
Diagnostic Prognostic |
Anti-TIF1γ/α (transcription factor 1 γ/α) | ELISA, Immunoprecipitation Serum |
Malignancy-associated DM | MSA 10–15%, higher prevalence in cancer-associated DM, rare in PM |
[134,148,149,150,151,152] | Cancer association is applied to adults [151] | |
Diagnostic Predictive Prognostic |
Anti-SAE (small ubiquitin-like modifier activating enzyme) | Immunoprecipitation, Indirect Immunofluorescence test Serum |
Cancer association Serum levels correlate with disease activity |
MSA 1–5% in DM |
[153,154,155] | ||
Diagnostic Prognostic |
Anti-SRP (Anti-signal recognition particle) |
RNA Immunoprecipitation, ELISA Serum |
Associated with a rapidly progressive disease course with severe weakness Cancer-associated SRP-IMNM |
MSA 20–25% in IMNM |
[156,157,158] | More frequent in women Primarily in adults |
|
Diagnostic Prognostic |
Anti-HMGCR (3-hydroxy-3-methylglutaryl-coenzyme A reductase) | Immunoprecipitation, ELISA Serum |
Significant association with serum creatine kinase Higher serum muscle enzymes than in other IIM Correlation with disease activity Cancer association |
MSA 6–12% in IIM |
[158,159,160,161,162,163,164,165] | Cave: Statin therapy! | |
Predictive Prognostic |
Serum soluble CD163 | ELISA Serum |
Biomarker for macrophage activation Correlation with disease severity Association with Anti-MDA5 (+) cases |
PM/DM | [166,167,168] | Not IIM-specific; supporting | |
Diagnostic | Anti-cN1A (cytosolic 5′-nucleotidase 1A) | Addressable laser bead immunoassay (ALBIA), ELISA Serum |
No correlation with disease severity | Around 50% in IBM | [169,170] | Moderate sensitivity, high specificity in ALBIA [171] Not IBM-specific, found also in known autoimmune diseases e.g., SLE [172] |
|
Diagnostic | Micro-RNAs miR-96-5p |
RTqPCR Serum |
No correlation described | Upregulation in PM, DM and Anti-Jo1 positive cases | [173] |
Immune-mediated mechanisms following antecedent infections, commonly with a subset of Campylobacter jejuni strains with ganglioside-mimicking lipooligosaccharides (LOS), result in the typical clinical phenotype of progressive ascending symmetrical paresis of the limbs with hypo- to areflexia in GBS [174]. CIDP is an autoimmune neuropathy affecting peripheral nerves. The common clinical hallmark is the symmetrical weakness of distal and proximal portions of the limbs, whereas pure motor, pure sensory, and focal subtypes are described equally. A diagnostic delay occurs frequently in CIDP [174].
Impairments of the blood-nerve barrier and the blood-cerebrospinal fluid (CSF) barrier as barriers of the PNS are concomitant with the pathophysiology underlying GBS and CIDP. Tissue of peripheral nerves, serum, and CSF compose the predominant origins of biomarkers [25]. Biomarkers can also be linked to immediate damage of the PNS. In the following, we address the studies on barrier-, infection-, immune-, and peripheral nerve system (PNS) damage-associated biomarkers in GBS and CIDP to provide an overview of biomarkers.
3.2. Diagnostic Biomarkers
Elevated total protein levels in CSF with a regular white blood cell count, termed cytoalbuminological dissociation, is a common observation in GBS and CIDP [175]. The detection is one of the first steps regarding the diagnostic approach at suspicious clinical presentation. A follow-up analysis of CSF may be useful, as protein elevation in CSF is known to increase during disease duration [176,177,178].
Zhang et al. have linked GBS to low CSF index levels of fibrinogen and prealbumin with regular levels of haptoglobin [179]. Furthermore, in CIDP patients, they demonstrated normal CSF index levels of prealbumin, elevated haptoglobin, and low fibrinogen [179]. Inconsistently in other studies, haptoglobin as a plasma protein and positive acute phase protein was found increased in CSF of GBS patients [180].
GBS can be triggered by a subgroup of Campylobacter jejuni strains incorporating ganglioside-mimicking LOS [25,181]. Thus, infection-associated biomarkers may be informative regarding pathogenesis of GBS. LOS and serotype as well as sequence type of Campylobacter strains can be applied as diagnostic biomarkers. Islam et al. implemented genotyping of C. jejuni strains from affected patients [4]. Structural analyses on the C. jejuni LOS were performed [5]. Moreover, antibodies (Abs) against C. jejuni DNA-binding protein (Anti-C-Dps IgG) were detected in C. jejuni-related GBS cases [6]. LOS of C. jejuni activate innate immune responses, thus biomarkers linked to these processes may be utilized. In this regard, numerous studies have addressed the role of cytokines, complements, and chemokines (see below).
Metalloproteinases (MMPs) have recently been described as potential biomarkers for the diagnosis of CIDP, as altered levels have been found in patients with different immune-mediated disorders. MMPs are a heterogenous group of endopeptidases involved in many pathophysiological functions such as tissue destruction and infiltration by immune cells. Patients with CIDP showed elevated serum levels of MMP-9 compared to controls [7]. Increased serum levels of MMPs are not specific for CIDP and are also found in MG patients, for example. To assess the potential utility of these new biomarkers in the clinical setting, future studies are needed.
Damage of the PNS is a pathogenic component of GBS and CIDP. Certain biomarkers depicting these processes have been identified in recent years. Abs against several peripheral myelin proteins P0, P214–25, PMP22, and connexin 32 have been described in GBS and CIDP patients [8,9,10,11]. In individuals who have demyelinating variants of GBS, there is a noticeable rise in IgG levels and heightened antibody response to P2 during the peak of the illness [11]. These factors could potentially play a role in the progression of the disease. However, the detection of these Abs is not widespread in clinical settings.
Increased levels of sphingomyelin (SM) in CSF of GBS and CIDP patients emerge as novel diagnostic biomarkers, as presented by Capodivento et al. [15]. SM appeared more elevated in active CIDP compared to stable disease course, highlighting its potential as a monitoring biomarker and a possible opportunity to adapt ongoing treatment strategies [15].
The cysteine protease inhibitor cystatin C is secreted from the choroid plexus into CSF. Enzyme-linked Immunosorbent Assay (ELISA) and proteomic studies revealed decrease of cystatin C in CSF of both GBS and CIDP patients [16,17,18,19]. Thus, decreased cystatin C could be applied as a biomarker for early diagnosis of GBS with limited specificity, as it has also been observed in MS patients.
Correspondingly not disease-specific, CSF 14-3-3 protein was identified in GBS patients as early as 12 to 48 h after disease commencement [21]. Detection of 14-3-3 protein as a diagnostic marker may benefit quicker disease identification and faster treatment initiation, which is especially crucial in clinical handling of GBS.
Notably, CSF interleukin-8 (IL-8) concentration seems to differentiate between CIDP and GBS, as it is high in both conditions, but significantly higher in GBS [22]. A cut-off value, as proposed by Breville et al., could aid setting both entities apart [22]. IL-8 is not disease-specific either. Nevertheless, knowledge of the mentioned relation may contribute to an early detection and enrollment of therapeutical steps.
Ultimately, it is evident that there is a lack of specificity regarding diagnostic biomarkers in GBS and CIDP. Particularly in non-bacteria-triggered disease development, reported markers are few to none. Concerning final disease determination, physicians apply data from clinical examination, electrophysiology, and CSF analysis, which may be time consuming. Detection of further diagnostic biomarkers could accelerate the start of treatment.
3.3. Predictive Biomarkers
Particularly in the acute stage of GBS, disease-related symptoms can develop rapidly, challenging both treating physicians and the well-being of affected individuals. In-patient stay in intensive care units is not uncommon. Thus, the knowledge of predictive biomarkers could aid further estimation of disease courses and better management of complications. Early determination of relevant biomarkers at clinical onset is crucial to initiate appropriate and strategic treatment decisions at the beginning.
Regarding damage of the myelin sheath, anti-ganglioside Abs are the most frequently communicated biomarkers. Gangliosides are sialylated glycosphingolipids located on the outer surface of nerve cells [182]. Anti-ganglioside Abs may result in complement activation and are repeatedly related to clinical phenotypes of GBS considering assorted expression of analogous antigens throughout the PNS [25,26]. IgG and IgM are the most reported subclasses of Abs to ganglioside antigens [26]. Anti-ganglioside GM1 Abs in GBS are associated with Camplyobacter jejuni infection and, interestingly, to clinical recovery and therapy response [27,28]. Serum anti-GQ1b IgG Abs are elevated in GBS and MillerFisher syndrome (MFS) and are closely linked to ophthalmoplegia [29]. Thus, auto-Abs to gangliosides seem to correlate with clinical phenotypes and symptom presentation, making them valuable for predictive purposes.
Similarly, efforts have been made to identify Abs against nodal and paranodal proteins. Auto-Abs against the nodal proteins neurofascin and gliomedin, leading ultimately to peripheral demyelination, are described in various studies [38,183,184]. Their presence is linked to a poorer response towards intravenous immunoglobulins (IVIg).
Earlier studies revealed Abs against the nodal and paranodal proteins neurofascin (Nfasc155 and Nfasc140/186), contactin-1 (CNTN1), contactin-associated protein-1 (Caspr1), and Caspr1/CNTN1 complex in CIDP patients [30]. These seropositive patients presented certain clinical manifestations, e.g., ataxia and tremor [31,33]. Importantly, Anti-Nfasc155 IgG4 antibody positive cases showed a younger age at disease onset and also a poorer response to IVIg treatment [34]. Anti-CNTN1 antibody-positive patients presented comparably low clinical improvement after IVIg, while benefiting from corticosteroids [35].
The detection of stated auto-Abs may be a valuable support for predictive purposes. Although the prevalence described in the literature is relatively low, integration into the diagnostic workup may help guide treatment options and improve case ascertainment. Therefore, systematical screening of auto-Abs in CIDP is advisable.
In consideration of PNS damage, biomarkers of direct neuronal disruption can be distinguished from those indicating myelin sheath damage. Neurofilaments are cytoskeletal intermediate filaments; their expression is amplified particularly in axons [39]. In GBS patients, CSF neurofilament levels, especially phosphorylated neurofilament heavy protein (pNFH) levels, were elevated and correlated positively with clinical and electrophysiological presentation [25,40,42]. Serum neurofilament light chain (Nfl) is associated with disease progression and therapy response in CIDP, accentuating its value as a predictive and prognostic biomarker [41]. Simultaneously, tau levels in CSF were increased in GBS patients and related mutually with clinical outcomes [25,42]. Tau proteins are involved in preservation of stability of microtubules throughout the nervous system [185]. Importantly, both neurofilaments and tau proteins are general indicators of structural central nervous system damage with limited specificity. In conclusion, auto-Abs to gangliosides as well as to nodal and paranodal proteins are the most relevant predictive biomarkers with comparably high occurrence.
3.4. Prognostic Biomarkers
Equivalent to predictive biomarkers, prognostic indicators are urgently needed to comprehend disease course. Early categorization and prognostic evaluation are essential for patients and treating physicians.
Abs against galactocerebroside (anti-Gal-C), a further component of myelin, are reportedly related to sensory deficits and autonomic disruption in GBS patients [47]. Remarkably, Gal-C-GBS is linked to antecedent Mycoplasma pneumoniae infection [47].
Anti-phospholipid Abs were reported in GBS and decreased following therapy with intravenous immunoglobulins (IVIgs) [186,187]. Neuron-specific enolase (NSE) was increased in CSF of GBS and CIDP patients and correlated with months to clinical recovery [49,50]. Importantly, neither of them exhibits disease-specificity.
Particularly in prognostic inquiries, the extensive category of cytokines plays a substantial role. Interferon gamma (IFN-γ) can potently fuel pro-inflammatory courses and correlates positively with clinical severity in GBS patients [53]. Recovery from GBS is connected to development of neutralizing auto-Abs to IFN-γ [52]. This may indicate the idea that IFN-γ can serve as a treatment target and predictive biomarker at the same time [54]. Similar observations were reported with regards to tumor necrosis factor alpha (TNF-α) [53]. IVIg treatment is associated with decreased levels of plasma TNF-α with elevated concentration of TNF-α antagonists, such as sTNFR1 [55,56]. Circulating transforming growth factor β1 (TGF β1) as an anti-inflammatory cytokine was detected decreased in the early course of GBS and downregulation appears to be linked to clinical disability [65]. CSF and plasma levels of interleukin 37 (IL-37) in GBS patients were elevated and serum levels declined after IVIg treatment [53]. Corresponding results are reported for IL-1β, IL-6, IL-12, IL-16, IL-17, IL-18, IL-22, and IL-23 [57,58,59,60,61,62]. CSF IL-17A levels were positively correlated with clinical manifestation of GBS, offering an opportunity for monitoring purposes [53]. The upregulation of IL-4 and IL-10 is linked to the subsequent recovery phase from GBS, which is associated with an improvement of clinical symptoms [14,63]. Likewise, elevation of some cytokines is reported in CIDP [64].
Importantly, serum derived from GBS patients displayed the capability to induce demyelination both in vivo and in vitro in the presence of complement components [25,188,189].
Therapeutic targeting of complement activation inhibited formation of membrane attack complex (C5b-9) and resulted in clinical improvement [54,188,189,190]. C5b-9 complexes were detected in GBS and multiple sclerosis (MS) patients [191]. Min et al. discussed probable employment of serum complement proteins as suitable biomarkers in GBS [66]. Here, C3 is linked to a higher clinical severity and longer hospitalization and is positively correlated with C3a and C5a [66]. The significance of cytokines, however, is naturally limited due to lack of specificity as well as potential alterations in the presence of comorbidities and medication.
Additional prognostic significance is attributed to the calcium-binding astroglial protein S100B. S100B serves as a glial marker and is shown to be elevated in CSF and serum of GBS patients [42,49]. Interestingly, elevated levels may be associated with clinical severity and a poor prognosis in GBS [50].
Stem cell factor (SCF) and hepatocyte growth factor (HGF) were more elevated in affected CIDP patients than in GBS patients and are considered as indicators for chronicity serving as supplementary diagnostic and monitoring biomarkers [71].
The significant drawback of prognostic biomarkers, particularly regarding cytokines, lies in their susceptibility to interference and the limited availability of specific indicators. Nevertheless, their assessment can still prove valuable in improving understanding of the disease.
3.5. Monitoring Biomarkers
To evaluate the individual disease progression, it is important to conduct both clinical monitoring and repetitive. Chemokines, as low-molecular-weight cytokines, and their corresponding receptors are crucial elements of inflammatory mechanisms. Increased CCR2 and monocyte chemoattractant protein 1 (MCP-1) levels were observed in GBS and levels declined in the recovery phase, revealing potential for ancillary monitoring markers [72]. CSF concentrations of CCL7, CCL27, CCR1, CCR5, CXCL10, CXCR3, CXCL9, and CXCL12 were elevated in GBS [71,73]. CXCL9, CXCL10, and CCL3 were increased in CIDP [74].
Identification of additional chemokines could provide possible targets for therapeutic agents in the treatment of GBS and CIDP. Other inflammatory mediators, among them ICAM-1, VCAM1, and VEGF were higher in CSF of GBS and CIDP patients compared to healthy controls [71].
Certainly, these described groups are not specific to the disease. However, their determination can be useful for assessing the course and at least reflect the trend.
In recent years, there has been an increasing emphasis on discovering more precise markers. Notably, significant breakthroughs have been made in the field of microRNAs, providing valuable insights.
MicroRNAs (miRNAs) are a group of short, non-coding, and single-stranded RNA molecules contributing to regulation of gene-expression. As circulating miRNAs, they are additionally present in various body fluids and are therefore detectable, giving possibility to serve as potential biomarkers and aid in understanding personalized patient analysis [77]. A study applying microarray technology and PCR analysis identified upregulated has-miR-4717-5p and has-miR-642b-5p in serum of GBS patients [78]. Regarding CIDP, only a few studies investigated miRNAs. Serum miR-31-5p was found and high levels are linked to IVIg treatment duration [80]. Regrettably, an insufficient quantity of monitoring biomarkers is presently available. Detection of miRNAs is helpful and promising but is still limited to centers equipped with suitable infrastructure. Thus, further research is necessary.
3.6. Required Biomarkers in GBS and CIDP
The diagnosis of GBS and CIDP are eminently challenging due to shortcomings in the identification and clinical integration of specific biomarkers. A delay in the initiation of effective immunomodulatory treatments can be the consequence. The detection of IL-8 at the beginning of clinical manifestation appears to be beneficial for disease classification. Figure 1 presents an overview of relevant biomarkers in GBS and CIDP, highlighting their significance in the respective pathogenesis. Regarding prognostic and monitoring biomarkers, chemokines and interleukins may be useful, but their increase is observed in other inflammatory processes as well, highlighting the need for more specificity. Methodological advances and unbiased analyses may help to overcome this lack. Proteomic studies showed elevated inflammation-related blood-derived proteins such as apolipoprotein A-IV, β2-microglobulin (β2-MG), vitamin D-binding protein (DBP), and α-1-antitrypsin levels in CSF of GBS patients [17,180,192,193]. Apolipoprotein E was decreased [180,194]. Transthyretin in CSF has been studied and showed disparate results with downregulation in protein profiling and upregulation when analyzed via ELISA [192,195]. Increased CSF transthyretin levels were simultaneously noticed in CIDP and MFS [195]. Their value as non-disease specific biomarkers is currently discussed in studies.
The cysteine protease inhibitor cystatin C is secreted from the choroid plexus into CSF. ELISA and proteomic studies revealed decrease of cystatin C in CSF of both GBS and CIDP patients [16,17]. It becomes evident that these described alterations also do not exhibit the necessary specificity for the disease. However, these observations, nonetheless, contribute to a better understanding of the disease onset and enable inferences to be drawn regarding mechanistic causes. Hence, further investigations are urgently required to discover disease-specific biomarkers, particularly in diagnostics.
4. Biomarkers in MG
4.1. Current Biomarkers in MG
MG is a chronic antibody-mediated autoimmune disease leading to focal or generalized muscle fatigability including respiratory symptoms or dysarthria [196,197]. Exclusive ocular symptoms (ocular MG) are possible and often represent the first clinical manifestation. Disease exacerbations inducing myasthenic crisis and ICU admission are still frequently observed. Causative auto-Abs target different components of the neuromuscular junction (NMJ) and disrupt regular transmission [198]. The prevalence is stated to be around 150–300 per million population [199]. The age of 50 years is used to distinguish between early-onset MG (EOMG) and late-onset MG (LOMG), as two peaks of incidence have been recognized [200,201]. In most cases (85%), auto-Abs against the extracellular domain of muscle nicotinic acetylcholine receptors (AChRs) are detected [84,85,86]. Biomarkers applied in MG are primarily disease-underlying auto-Abs and antigenic structures. An overview is given in Table 1. Specifically in the case of MG, the assignment of biomarkers to the initially introduced subgroups is rather ambiguous, as many functions are simultaneously fulfilled.
4.2. Diagnostic Biomarkers
As of now, serological testing for the detection of anti-AChR Abs is integrated in clinical practice. Anti-AChR Abs are mainly members of IgG1 and IgG3 subgroups [87]. Binding leads to heterogeneous pathogenic pathways, including the blockade of transmission and receptor internalization, followed by the formation of the membrane attack complex (MAC) [88,89,90,91,202]. Although Masuda et al. showed positive correlation between titer levels of Abs against the main immunogenic region of AChR and clinical severity [92,93], many studies, such as Vincent and Newsom-Davis, cannot confirm this coherency [197]. Anti-AChR seems to be very heterogeneous in its characteristics between individuals [203]. Differences in the specificity of AChR Abs, their ability to activate complement, the immunoglobulin subclass, or variations in serum antibody concentrations could be potential reasons for the insufficient correlation [91,105]. Using absolute serum levels of AChR Abs is not recommended to accurately predict the disease course or response to therapy in patients. The most common detection method for anti-AChR Abs is the radioimmunoprecipitation assay (RIPA), providing high specificity and sensitivity, which are described to be approximately 85% in generalized MG and 50% in ocular MG. Newer RIPAs were able to expose auto-Abs in formerly seronegative MG patients and enhanced diagnostic certainty [95,96]. Fixed cell-based assays (CBA) showed even higher sensitivity in some studies, indicating possible detection alternatives [97,98].
In 2001, Hoch et al. identified a novel determinable antibody in seronegative MG patients [100]. Muscle-specific kinase (MuSK) is a receptor tyrosine kinase required for signaling between motor neurons and skeletal muscles [102,204]. Anti-MuSK Abs mainly targets the extracellular domain of MuSK and belong mainly to the IgG4 antibody subclass [103,107]. They are detected in around 8% of MG cases and in around 30 to 50% of anti-AChR-Ab-negative MG [95,100,105]. According to AChR Abs, MuSK Abs are generally detected via RIPA [108,205]. Constant efforts are made towards developing testing alternatives, such as CBAs and ELISAs [98,206]. Utilization of CBAs has been shown to enlarge detected cases of double-positive MG patients with Abs to more than one target antigen [95,207].
Furthermore, the low-density lipoprotein receptor-related protein 4 (LRP4) contributes to NMJ upkeep as a transmembrane protein and has been described to be another target antigen in MG [111,117]. Anti-LRP4 Abs are associated primarily with IgG1 and IgG2 subclasses and initiate pathogenic complement activation [116]. Anti-LRP4-Ab-positive patients showed more pronounced clinical manifestation than in seronegative cases [114]. Prevalence of anti-LRP4 Abs is higher in women, varies widely throughout the literature, and seems to be influenced by detection assays and the investigated population [113]. Essentially, anti-LRP4 Abs are not specific for MG, as they have also been identified in serum and CSF of amyotrophic lateral sclerosis patients [112,115]. Regardless, their consideration may strengthen diagnostic definiteness.
Several other antigenic spots of interest in MG have been analyzed in the recent past, covering titin, Kv1.4 potassium channels, rapsyn, cortactin, and agrin. Their corresponding worth for diagnostic, prognostic, or monitoring ambitions has not been sufficiently clarified.
Titin Abs are detected in 20 to 40% of anti-AChR-Ab-positive patients and are tightly linked to thymoma-associated MG [95,118,120]. One limitation is their additional occurrence in MG patients over the age of 50 without presence of thymoma [208,209]. Therefore, positive testing for titin Abs in MG patients should be followed by comprehensive assessment for thymoma, particularly in patients under 50 years of age.
Kv1.4 is a voltage-gated potassium channel contributing to presynaptic acetylcholine release. Suzuki et al. identified anti-Kv1.4 Abs in sera from MG patients, associated with distinct clinical symptoms, conveying possible diagnostic and prognostic value [121,122]. Rapsyn Abs have not been identified exclusively in MG, but in several other autoimmune diseases [123]. Simultaneously, Abs against the cytoplasmic protein cortactin were encountered particularly in seronegative MG cases, but also in other immune-mediated disorders and even in healthy controls [124].
Abs against agrin, which is connected to activation of MuSK [102], have been found in formerly seronegative MG patients that turned seropositive [127]. Agrin-MG is related to EOMG, limited therapeutic response, and mild to severe clinical manifestation (see below). Thus, their quick identification could assist in clinical practice [115].
Recently, the role of free serum light chains (FLC) has been suggested as a diagnostic biomarker for MG [210]. Significantly elevated levels of FLC have been measured in MG patients via a turbidimetric assay and could be used to support the diagnosis of MG. A further association between serum FLC levels and clinical manifestations, disease severity, age at MG onset, thymoma, or treatment could not be established [210].
4.3. Predictive Biomarkers
In contrast to GBS and CIDP, there are no biomarkers in MG that fulfill purely predictive functions. Rather, the indicators identified for diagnostic purposes also incidentally serve predictive roles. Anti-MuSK Abs are more often detected in female patients and appear to be associated with crises and poorer outcomes [104,211,212]. In contrast to patients with anti-AChR-Abs, they additionally predict a better treatment response to rituximab [109,110]. The presence of agrin Abs correlates with a limited therapeutic response [127,128]. In clinical practice, the use of these two biomarkers with a predictive intention is relatively limited.
4.4. Prognostic Biomarkers
As with predictive, there are only very limited prognostic biomarkers. In this context, biomarkers tend to fulfill multiple functions simultaneously. Compatibly, anti-MuSK Ab levels are reported to correlate with disease severity, implying possible prognostic worth [106]. Since they are members of the IgG4 antibody subclass and thus do not activate the complement system, their presence could be considered as a biomarker of response to anti-CD20 therapies such as rituximab and not to complement inhibitors. Titin Abs are related to thymoma-associated MG and more frequent hospitalization [118,120]. Anti-Kv1.4. Abs associate with myasthenic crises, myocarditis, thymoma, and prolongation of QT-time [122]. While the presence of Anti-cortactin Abs is linked to rather mild clinical manifestation, Anti-agrin Abs correlate with possible severe clinical symptoms [95,126,127].
4.5. Monitoring Biomarkers
Monitoring in the context of Myasthenia Gravis is a delicate matter. The determination of biomarkers for this purpose is highly limited. Currently, in clinical practice, alongside regular physical examinations, clinical parameters such as vital signs and lung vital capacity play a significant orienting role. Interestingly, serum anti-AChR Abs were detected ahead of clinical manifestation of MG and even progressively elevated throughout the time, indicating possible potential as a monitoring biomarker, next to diagnostic purposes [94]. Since AChR Abs belong mainly to IgG1 and IgG3 subgroups, FcRn-targeting therapies such as efgartigimod can assist reducing pathogenic IgG autoantibody levels [213]. From this perspective, serum IgG and AChR Ab titers could also serve as useful biomarkers for monitoring treatment response in patients receiving FcRn-antagonists.
However, it is important to acknowledge that within a limited subset of patients with MG (approximately 17%), the standard RIPA using human AChR may fail to detect AChR. For these individuals, a titration method involving a combination of normal and denervated AChR might offer an opportunity to enhance assay sensitivity and diminish background precipitation. This refinement could prove valuable for affirming positive results in both monitoring and diagnostic capacities. Furthermore, one must also remain cognizant of instances where anti-AChR antibodies appear in monozygotic twins or first-degree relatives even in the absence of clinical myasthenic symptoms [198].
4.6. Required Biomarkers in MG
Present diagnostic tests for MG, including clinical examination, antibody analysis, and neurophysiological assessments, do not automatically mirror disease course. Consequently, solid prognostic markers are urgently required. Figure 2 provides a comprehensive view of relevant biomarkers in MG.
Observations of ongoing efforts can be noted in the identification of additional helpful indicators for MG. Serum metabolic profiles in EOMG and LOMG patients were examined by Lu et al. and revealed significant metabolite alterations between both disease onsets and compared to healthy controls [214]. Gamma-aminobutyric acid (GABA) was reduced, while levels of sphingosine 1-phosphate (S1P) were elevated [214]. Moreover, significant metabolite changes in MG were seen in pipecolic acid, 5,8-tetradecadienoic acid, bisnorcholic acid, chenodeoxycholylglycerine, coprocholic acid, coenzyme Q4, and cholylglcine [214].
Serum levels of circulating follicular helper T cells appear to be associated with disease severity and decreased after immunotherapy [215]. Similarly, calprotectin titers are increased in MG patients and are discussed to correlate with clinical manifestations [216]. Nevertheless, it must be noted that these parameters have found limited incorporation into routine assessment practices.
In anti-AChR- and anti-MuSK-Ab-positive MG cases, several elevated circulating miRNAs were found (Table 1). Interestingly, high miR-30e-5p levels are associated with risk of generalization in ocular MG [129]. Further studies of circulating miRNAs in agrin and anti-LRP4-Ab-positive MG are still required. Importantly, detected miRNAs in anti-AChR- and anti-MuSK-Ab-positive MG appear to correlate with treatment response [129,217]. Hence, further investigation may help in predictive estimations of affected patients.
Seronegative MG cases might be detected as such due to insufficiency of current standard tests [218,219]. Final categorization as seronegative MG should be held back to non-immunosuppressed patients. Efforts to establish criteria for seronegative MG subgroups aim to improve early recognition and tailored therapeutic approaches. Additionally, the expanding knowledge of different antibodies, including junctional and non-junctional types, offers potential markers for treatment response prediction [220].
The lack of specificity and the limited availability of well-established prognostic biomarkers pose significant challenges in MG. Despite previous discussions suggesting that serum autoantibody titers, particularly anti-AChR Abs, could serve as indicators of disease severity, recent studies have cast doubt on their reliability [221,222].
A notable study by Obaid et al. employed a flow cytometric approach to explore the correlation between anti-AChR-Ab titers, MAC formation, and the Myasthenia gravis composite score (MGC). Surprisingly, their findings revealed inconsistencies in a subset of patients, as there was no significant correlation observed between MAC formation, anti-AChR-Ab levels, and disease severity [91].
These discrepancies may stem from several factors, including the heterogeneity of anti-AChR Abs and the absence of standardized measurement techniques. Furthermore, variations in antibody pathogenicity add complexity to the use of anti-AChR antibody levels as reliable biomarkers for individual patients. These limitations underscore the need for further research to identify more specific and robust prognostic biomarkers for MG.
5. Biomarkers in IIM
5.1. Current Biomarkers in IIM
Idiopathic inflammatory myopathies (IIM) are a rare heterogenous cluster of autoimmune-mediated diseases affecting mainly skeletal muscles. Alongside typical manifestations with muscle weakness and fatiguing, IIMs are often accompanied by specific organ manifestations, including skin and lungs, among others. IIMs can be subclassified into different groups—dermatomyositis (DM), polymyositis (PM), immune-mediated necrotizing myopathy (IMNM), antisynthetase syndrome (ASyS), inclusion body myositis (IBM), and overlap myositis (OM) [223]. Importantly, clinical presentations, treatment responses, and prognoses differ strongly throughout subgroups [224]. Several supporting biomarkers, almost all of them auto-Abs, have been identified in the past and serve understanding causative mechanisms (Table 1). Nevertheless, IIMs are still deeply underdiagnosed.
Non-specific muscle enzymes including creatine kinase (CK), aspartate aminotransferase (AST), alanine aminotransferase (ALT), lactate dehydrogenase (LDH), and aldolase are elevated due to muscle damage and do not necessarily correlate with clinical severity or disease activity [225]. Due to the challenges involved in accurately assigning biomarkers to specific subgroups in IIMs, we have chosen to focus separately on myositis-specific Abs (MSAs) and further biomarkers of interest. The respective classifications can be found in Table 1, delineating the different categories.
5.2. Myositis-Specific Autoantibodies (MSA)
Some of the following MSAs can be supportive in the diagnostic workup, but their prevalence ranges only around 20–50% [134,226,227]. Detection of more than one MSA in a single patient is rather rare, though has been described before [228]. In addition to MSAs, the literature also describes myositis-associated Abs (MAAs). However, in contrast, MAAs exhibit less disease specificity, as they are found in other systemic autoimmune rheumatic diseases as well and are often associated with conditions of disease overlap [134,229].
Typical MSAs identified in patients with DM are anti-Mi-2 Abs, anti-aminoacyl-tRNA synthetase (ARS) Abs, anti-nuclear matrix protein 2 (anti-NXP2) Abs, Abs against transcription intermediary factor 1γ (TIF1γ/α), and anti-small ubiquitin-like modifier activating enzyme Abs (Anti-SAE) [133,154,155]. Abs against Mi-2, NXP2, and SAE appear to correlate with disease activity in DM. Moreover, their sequential testing may be supportive for predictive purposes [133]. Anti-Jo-1 Abs are the most frequent Abs reported among the group of anti-ARS Abs (around 15–30%). Their presence is associated with a better response to rituximab [230]. Notably, patients with non-Jo-1-anti-tRNA-synthetase Abs display reduced survival rates compared to anti-Jo-1-positive cases [137]. Anti-Mi-2 Abs also indicate a better treatment response and a favorable outcome, although they have also been sporadically detected in PM patients [131]. In addition, it is known that type I interferons are increased in patients with DM and Janus kinase inhibition improved clinical status in a proof-of-concept study [148]. Besides that, Anti-NXP2 Abs are conjoined to a specific clinical phenotype (in particular calcinosis cutis) and cancer development, showing diagnostic and prognostic potential [143,231]. Abs to TIF1γ/α are equally associated with coincident malignancy and poorer outcome [149]. As a biomarker, TIF1γ/α could aid identifying cancer-associated IIM and influence disease management. In terms of clinically amyopathic DM (CADM), anti-MDA5 Abs have a diagnostic value and are associated with vasculopathic skin ulcerations, poor prognosis, and high prevalence of interstitial lung disease (ILD) [232]. Ab titer levels appear to be positively correlated with disease severity and outcome [146]. Serial monitoring could contribute to sooner recognition of remission or relapse [147].
Patients with ASyS, characterized by a clinical syndrome of myositis, arthritis, ILD, mechanics hands, and Raynaud’s phenomenon often express anti-ARS Abs [233]. Due to ILD being more present in ASyS than in other IIMs, detection should arouse alertness for complicative clinical developments [138].
In IMNM, anti-signal recognition particle (SRP), Abs are utilized as serological indicators [156]. Correspondingly, seral 3-hydroxy-3-methylglutaryl-coenzyme A reductase (HMGCR) auto-Abs were detected in patients with IIM and particularly with IMNM [159,234]. Statins are known to potentially cause induction of anti-HMGCR in a subset of HMGCR-IMNM [158].
In seropositive IBM cases, anti-cytosolic 5′-nucleotidase 1A (cN1A) Abs were identified and appear to have a high specificity and rather moderate sensitivity but lack correlation with clinical severity [169].
5.3. Further Biomarkers
Biomarkers for macrophage activation can also serve as meaningful indicators with pathogenetic relevance in disease management. Serum soluble CD163 is discussed to be a predictive biomarker in PM and DM, especially in anti-MDA5 Ab positive cases. Here, titers decreased significantly after treatment [167]. Similarly, serum soluble CD206 levels exhibited a notable increase in patients with DM and showed a correlation with the presence of ILD [235]. Heightened serum neopterin levels were notably linked to rapidly progressive ILD and decreased survival among individuals with DM [236].
5.4. Required Biomarkers in IIM
To date, prevailing biomarkers in IIMs are primarily applicable for prognostic and predictive perspectives. They also assist in guiding classification into correct IIM subgroups. For diagnostic purposes, Abs are not sufficient alone but rather support disease identification alongside other testing tools. The actual prevalence of the referred MSAs in IIMs should also be in the focus of supplementary future studies. This is especially important to define more homogeneous clinical patient cohorts. Additionally, miRNA profiling has not been conclusively investigated in IIMs. An outline of MSAs and IIIM-associated biomarkers is found in Figure 3.
Evidently, there is a tremendous deficiency regarding monitoring biomarkers. Standardized appliances to observe disease activity are required. Treatment responses and outcomes in IIMs are still disappointing [237]. Even if subcategorizing IIM types helps in terms of estimating known complications e.g., ILD, the single variants display large variances in their respective course. Further identification of underlying pathophysiological pathways could contribute to the development of target-guided treatment options.
6. Outlook
Inflammatory neuromuscular disorders encompass a heterogeneous group of immune-mediated diseases, each characterized by distinct underlying mechanisms that contribute to their pathogenesis. Given the current state, pathomechanisms have not been comprehensively understood. It is therefore reasonable to anticipate that additional mechanistic backgrounds and potentially promising target structures will be identified in the years to come. This also extends to the expectation that novel suitable biomarkers will be incorporated into the standard protocols for managing these conditions.
The diagnosis of GBS and CIDP poses significant challenges due to limitations in identifying and clinically integrating specific biomarkers. Consequently, a delay in the initiation of effective immunomodulatory treatments can occur. The potential consequences can be severe for affected individuals, especially in the case of GBS, as it can lead to the need for mechanical ventilation and intensive medical care to ensure adequate treatment. The employed serum cytokines, chemokines, and complement proteins have the capacity to reflect trends in disease progression; however, they lack the required specificity.
In this field, it is crucial to concentrate efforts on the identification and implementation of specific biomarkers that can be readily and easily measured in routine clinical practice. It is worthwhile to critically note that the assessment of certain promising biomarkers is restricted to specialized centers equipped with the necessary technical infrastructure and expertise. As a result, access to these biomarker assessments is not uniformly available across all clinical sites. Consequently, there may be a potential temporal delay in the implementation of disease management strategies.
When it comes to MG, there are only a handful of biomarkers that are utilized in clinical practice. Remarkably, there are hardly any predictive biomarkers established in MG. If described, they are often linked to occurrence of postoperative myasthenic crises and not MG itself [238,239]. Alongside the “classical” biomarkers, including anti-AChR, anti-MuSK, and anti-LRP4-Abs, the remaining biomarkers listed are not disease-specific and should be regarded more as “complementary biomarkers” that contribute to a deeper understanding of the pathophysiology. Metalloproteinases such as MMP-2 and MMP-9 seem to have the potential to serve as biomarkers for tracking disease severity. Both generalized MG and CIDP patients have exhibited elevated plasma levels of MMP-9 and decreased levels of MMP-2. Furthermore, there appears to be a correlation between the concentration of MMP-2 and disease severity in MG patients [240]. While these findings are preliminary, they provide a promising foundation for further research into the role of MMPs in these conditions. Overall, it becomes abundantly clear that at this stage, there are not enough biomarkers to adequately address the disease and individual courses in affected individuals, thereby complicating the clinical management of MG.
The most prominent challenge faced by IIMs does not lie in the specificity of commonly used Abs but rather in the relatively low prevalence and subsequent lack of prompt diagnosis of this group of disorders. Additionally, there is a need for the implementation of standardized, cost-effective, and rapid detection methods.
MiRNAs are currently explored extensively in multiple studies, including research on the field of inflammatory NMDs. Currently, in IIMs and CIDP, there are barely a few studies addressing miRNAs and their potential practicality. As methods are evolving, we expect miRNAs to become increasingly important as tools for personalized medicine and as sources for treatment management. However, detection of miRNAs is still far from being applied as point of care testing assets. The requirement of reliable and fast laboratory assays is still an unmet need.
7. Conclusions
In summary, inflammatory neuromuscular disorders represent a diverse group of immune-mediated conditions, each characterized by distinct underlying mechanisms contributing to their pathogenesis. While our current understanding of these disorders has come a long way, there is still much to uncover. The complex nature of these diseases makes the search for reliable and specific biomarkers a crucial aspect of research and clinical practice.
Diagnosing the discussed conditions presents unique challenges. The limitations in identifying and effectively integrating specific biomarkers into clinical practice can lead to delays in initiating appropriate treatments. These delays can have severe consequences for affected individuals, particularly in cases such as GBS, where mechanical ventilation and intensive medical care may be required.
Currently, serum cytokines, chemokines, and complement proteins are used to track disease progression, but they lack the requisite specificity needed for precise diagnosis and tailored treatment. Therefore, it is imperative to focus research efforts on identifying and implementing readily measurable, specific biomarkers that can be easily incorporated into routine clinical practice. This would ensure broad accessibility and timely implementation of effective disease management strategies.
In the realm of MG, the scarcity of biomarkers hampers our ability to comprehensively understand and manage the disease. While a few biomarkers are used in clinical practice, predictive biomarkers for MG itself are notably absent. Promising biomarkers, such as microRNAs (miRNAs), are emerging, but their practical application for diagnosis and management is still in its infancy.
For IIMs, the primary challenge lies not in the specificity of commonly used antibodies but rather in their relatively low prevalence and the subsequent delay in diagnosis. Moreover, there is a pressing need for the implementation of standardized, cost-effective, and rapid detection methods to improve the diagnosis and management of these disorders.
The potential of miRNAs, although still in the early stages of practical application, is an exciting development in the field of inflammatory neuromuscular disorders. As detection methods for miRNAs evolve, they are expected to become valuable tools for personalized medicine and treatment management. However, the development of reliable and rapid laboratory assays for miRNA detection remains an unmet need.
In conclusion, ongoing research and advancements in biomarker discovery and detection methods hold the potential to significantly improve the diagnosis and management of these complex autoimmune neuromuscular disorders. As we continue to unravel the intricacies of these diseases and identify specific, easily measurable biomarkers, we move closer to enhancing the care and outcomes for individuals affected by them. The journey ahead is challenging but promising, with the ultimate goal of improving the quality of life for those living with these conditions.
Acknowledgments
A.H. was supported by the Jürgen Manchot Stiftung.
Author Contributions
C.B.S. and C.N. conceived of the presented project. M.O. and A.H. devised the main conceptual ideas and proof outline wrote the manuscript with support from C.B.S., C.N., A.H., P.Q., L.T. and T.R.; C.B.S., C.N., S.G.M. and T.R. supervised the project. All authors have read and agreed to the published version of the manuscript.
Conflicts of Interest
The authors declare no conflict of interest.
Funding Statement
This work was supported by the Heinrich Heine University Düsseldorf.
Footnotes
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References
- 1.Punga A.R., Maddison P., Heckmann J.M., Guptill J.T., Evoli A. Epidemiology, diagnostics, and biomarkers of autoimmune neuromuscular junction disorders. Lancet Neurol. 2022;21:176–188. doi: 10.1016/S1474-4422(21)00297-0. [DOI] [PubMed] [Google Scholar]
- 2.Califf R.M. Biomarker definitions and their applications. Exp. Biol. Med. 2018;243:213–221. doi: 10.1177/1535370217750088. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Robb M.A., McInnes P.M., Califf R.M. Biomarkers and Surrogate Endpoints: Developing Common Terminology and Definitions. JAMA. 2016;315:1107–1108. doi: 10.1001/jama.2016.2240. [DOI] [PubMed] [Google Scholar]
- 4.Islam Z., van Belkum A., Wagenaar J.A., Cody A.J., de Boer A.G., Tabor H., Jacobs B.C., Talukder K.A., Endtz H.P. Comparative genotyping of Campylobacter jejuni strains from patients with Guillain-Barré syndrome in Bangladesh. PLoS ONE. 2009;4:e7257. doi: 10.1371/journal.pone.0007257. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Godschalk P.C., Kuijf M.L., Li J., St Michael F., Ang C.W., Jacobs B.C., Karwaski M.F., Brochu D., Moterassed A., Endtz H.P., et al. Structural characterization of Campylobacter jejuni lipooligosaccharide outer cores associated with Guillain-Barre and Miller Fisher syndromes. Infect. Immun. 2007;75:1245–1254. doi: 10.1128/IAI.00872-06. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Kawamura N., Piao H., Minohara M., Matsushita T., Kusunoki S., Matsumoto H., Ikenaka K., Mizunoe Y., Kira J. Campylobacter jejuni DNA-binding protein from starved cells in Guillain-Barré syndrome patients. J. Neuroimmunol. 2011;240–241:74–78. doi: 10.1016/j.jneuroim.2011.09.004. [DOI] [PubMed] [Google Scholar]
- 7.Cosentino G., Di Stefano V., Presti R.L., Montana M., Todisco M., Gastaldi M., Cortese A., Alfonsi E., Tassorelli C., Fierro B., et al. Expression pattern of matrix metalloproteinases-2 and -9 and their tissue inhibitors in patients with chronic inflammatory demyelinating polyneuropathy. Neurol. Sci. 2021;42:4297–4300. doi: 10.1007/s10072-021-05314-y. [DOI] [PubMed] [Google Scholar]
- 8.Csurhes P.A., Sullivan A.A., Green K., Pender M.P., McCombe P.A. T cell reactivity to P0, P2, PMP-22, and myelin basic protein in patients with Guillain-Barre syndrome and chronic inflammatory demyelinating polyradiculoneuropathy. J. Neurol. Neurosurg. Psychiatry. 2005;76:1431–1439. doi: 10.1136/jnnp.2004.052282. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Kwa M.S., van Schaik I.N., Brand A., Baas F., Vermeulen M. Investigation of serum response to PMP22, connexin 32 and P(0) in inflammatory neuropathies. J. Neuroimmunol. 2001;116:220–225. doi: 10.1016/S0165-5728(01)00307-1. [DOI] [PubMed] [Google Scholar]
- 10.Gabriel C.M., Gregson N.A., Hughes R.A. Anti-PMP22 antibodies in patients with inflammatory neuropathy. J. Neuroimmunol. 2000;104:139–146. doi: 10.1016/S0165-5728(99)00269-6. [DOI] [PubMed] [Google Scholar]
- 11.Inglis H.R., Csurhes P.A., McCombe P.A. Antibody responses to peptides of peripheral nerve myelin proteins P0 and P2 in patients with inflammatory demyelinating neuropathy. J. Neurol. Neurosurg. Psychiatry. 2007;78:419–422. doi: 10.1136/jnnp.2006.106617. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Makowska A., Pritchard J., Sanvito L., Gregson N., Peakman M., Hayday A., Hughes R. Immune responses to myelin proteins in Guillain-Barré syndrome. J. Neurol. Neurosurg. Psychiatry. 2008;79:664–671. doi: 10.1136/jnnp.2007.123943. [DOI] [PubMed] [Google Scholar]
- 13.D’Urso D., Ehrhardt P., Müller H.W. Peripheral myelin protein 22 and protein zero: A novel association in peripheral nervous system myelin. J. Neurosci. 1999;19:3396–3403. doi: 10.1523/JNEUROSCI.19-09-03396.1999. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Dahle C., Ekerfelt C., Vrethem M., Samuelsson M., Ernerudh J. T helper type 2 like cytokine responses to peptides from P0 and P2 myelin proteins during the recovery phase of Guillain-Barré syndrome. J. Neurol. Sci. 1997;153:54–60. doi: 10.1016/S0022-510X(97)00178-0. [DOI] [PubMed] [Google Scholar]
- 15.Capodivento G., De Michelis C., Carpo M., Fancellu R., Schirinzi E., Severi D., Visigalli D., Franciotta D., Manganelli F., Siciliano G., et al. CSF sphingomyelin: A new biomarker of demyelination in the diagnosis and management of CIDP and GBS. J. Neurol. Neurosurg. Psychiatry. 2021;92:303–310. doi: 10.1136/jnnp-2020-324445. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Nagai A., Murakawa Y., Terashima M., Shimode K., Umegae N., Takeuchi H., Kobayashi S. Cystatin C and cathepsin B in CSF from patients with inflammatory neurologic diseases. Neurology. 2000;55:1828–1832. doi: 10.1212/WNL.55.12.1828. [DOI] [PubMed] [Google Scholar]
- 17.Yang Y.R., Liu S.L., Qin Z.Y., Liu F.J., Qin Y.J., Bai S.M., Chen Z.Y. Comparative proteomics analysis of cerebrospinal fluid of patients with Guillain-Barré syndrome. Cell Mol. Neurobiol. 2008;28:737–744. doi: 10.1007/s10571-007-9257-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Li P., Wang S., Zhang R., Pei J., Chen L., Cao Y., Zhang H., Yang G. Identification of CSF biomarkers by proteomics in Guillain-Barré syndrome. Exp. Med. 2018;15:5177–5182. doi: 10.3892/etm.2018.6117. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Yang Y., Liu S., Qin Z., Cui Y., Qin Y., Bai S. Alteration of cystatin C levels in cerebrospinal fluid of patients with Guillain-Barré Syndrome by a proteomical approach. Mol. Biol. Rep. 2009;36:677–682. doi: 10.1007/s11033-008-9228-1. [DOI] [PubMed] [Google Scholar]
- 20.Bersano A., Allaria S., Nobile-Orazio E. 14-3-3 protein in the CSF of inflammatory peripheral neuropathies. J. Peripher. Nerv. Syst. 2004;9:108. doi: 10.1111/j.1085-9489.2004.009209o.x. [DOI] [Google Scholar]
- 21.Bersano A., Fiorini M., Allaria S., Zanusso G., Fasoli E., Gelati M., Monaco H., Squintani G., Monaco S., Nobile-Orazio E. Detection of CSF 14-3-3 protein in Guillain-Barré syndrome. Neurology. 2006;67:2211–2216. doi: 10.1212/01.wnl.0000249150.98891.d1. [DOI] [PubMed] [Google Scholar]
- 22.Breville G., Lascano A.M., Roux-Lombard P., Vuilleumier N., Lalive P.H. Interleukin 8, a Biomarker to Differentiate Guillain-Barré Syndrome From CIDP. Neurol. Neuroimmunol. Neuroinflamm. 2021;8:e1031. doi: 10.1212/NXI.0000000000001031. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Koga M., Yuki N., Ariga T., Hirata K. Antibodies to GD3, GT3, and O-acetylated species in Guillain-Barré and Fisher’s syndromes: Their association with cranial nerve dysfunction. J. Neurol. Sci. 1999;164:50–55. doi: 10.1016/S0022-510X(98)00331-1. [DOI] [PubMed] [Google Scholar]
- 24.Shahrizaila N., Kokubun N., Sawai S., Umapathi T., Chan Y.C., Kuwabara S., Hirata K., Yuki N. Antibodies to single glycolipids and glycolipid complexes in Guillain-Barré syndrome subtypes. Neurology. 2014;83:118–124. doi: 10.1212/WNL.0000000000000577. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Wang Y., Sun S., Zhu J., Cui L., Zhang H.L. Biomarkers of Guillain-Barré Syndrome: Some Recent Progress, More Still to Be Explored. Mediat. Inflamm. 2015;2015:564098. doi: 10.1155/2015/564098. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Sekiguchi Y., Uncini A., Yuki N., Misawa S., Notturno F., Nasu S., Kanai K., Noto Y., Fujimaki Y., Shibuya K., et al. Antiganglioside antibodies are associated with axonal Guillain-Barré syndrome: A Japanese-Italian collaborative study. J. Neurol. Neurosurg. Psychiatry. 2012;83:23–28. doi: 10.1136/jnnp-2011-300309. [DOI] [PubMed] [Google Scholar]
- 27.Rees J.H., Gregson N.A., Hughes R.A. Anti-ganglioside GM1 antibodies in Guillain-Barré syndrome and their relationship to Campylobacter jejuni infection. Ann. Neurol. 1995;38:809–816. doi: 10.1002/ana.410380516. [DOI] [PubMed] [Google Scholar]
- 28.Jacobs B.C., van Doorn P.A., Schmitz P.I., Tio-Gillen A.P., Herbrink P., Visser L.H., Hooijkass H., van der Meché F.G. Campylobacter jejuni infections and anti-GM1 antibodies in Guillain-Barré syndrome. Ann. Neurol. 1996;40:181–187. doi: 10.1002/ana.410400209. [DOI] [PubMed] [Google Scholar]
- 29.Chiba A., Kusunoki S., Obata H., Machinami R., Kanazawa I. Serum anti-GQ1b IgG antibody is associated with ophthalmoplegia in Miller Fisher syndrome and Guillain-Barré syndrome: Clinical and immunohistochemical studies. Neurology. 1993;43:1911–1917. doi: 10.1212/WNL.43.10.1911. [DOI] [PubMed] [Google Scholar]
- 30.Querol L., Nogales-Gadea G., Rojas-Garcia R., Martinez-Hernandez E., Diaz-Manera J., Suárez-Calvet X., Navas M., Araque J., Gallardo E., Illa I. Antibodies to contactin-1 in chronic inflammatory demyelinating polyneuropathy. Ann. Neurol. 2013;73:370–380. doi: 10.1002/ana.23794. [DOI] [PubMed] [Google Scholar]
- 31.Pascual-Goñi E., Fehmi J., Lleixà C., Martín-Aguilar L., Devaux J., Höftberger R., Delmont E., Doppler K., Sommer C., Radunovic A., et al. Antibodies to the Caspr1/contactin-1 complex in chronic inflammatory demyelinating polyradiculoneuropathy. Brain. 2021;144:1183–1196. doi: 10.1093/brain/awab014. [DOI] [PubMed] [Google Scholar]
- 32.Cortese A., Lombardi R., Briani C., Callegari I., Benedetti L., Manganelli F., Luigetti M., Ferrari S., Clerici A.M., Marfia G.A., et al. Antibodies to neurofascin, contactin-1, and contactin-associated protein 1 in CIDP: Clinical relevance of IgG isotype. Neurol. Neuroimmunol. Neuroinflamm. 2020;7:e639. doi: 10.1212/NXI.0000000000000639. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Ogata H., Yamasaki R., Hiwatashi A., Oka N., Kawamura N., Matsuse D., Kuwahara M., Suzuki H., Kusunoki S., Fujimoto Y., et al. Characterization of IgG4 anti-neurofascin 155 antibody-positive polyneuropathy. Ann. Clin. Transl. Neurol. 2015;2:960–971. doi: 10.1002/acn3.248. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Devaux J.J., Miura Y., Fukami Y., Inoue T., Manso C., Belghazi M., Sekiguchi K., Kokubun N., Ichikawa H., Wong A.H., et al. Neurofascin-155 IgG4 in chronic inflammatory demyelinating polyneuropathy. Neurology. 2016;86:800–807. doi: 10.1212/WNL.0000000000002418. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Miura Y., Devaux J.J., Fukami Y., Manso C., Belghazi M., Wong A.H., Yuki N. Contactin 1 IgG4 associates to chronic inflammatory demyelinating polyneuropathy with sensory ataxia. Brain. 2015;138:1484–1491. doi: 10.1093/brain/awv054. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Shelly S., Klein C.J., Dyck P.J.B., Paul P., Mauermann M.L., Berini S.E., Howe B., Fryer J.P., Basal E., Bakri H.M., et al. Neurofascin-155 Immunoglobulin Subtypes: Clinicopathologic Associations and Neurologic Outcomes. Neurology. 2021;97:e2392–e2403. doi: 10.1212/WNL.0000000000012932. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Ng J.K., Malotka J., Kawakami N., Derfuss T., Khademi M., Olsson T., Linington C., Odaka M., Tackenberg B., Prüss H., et al. Neurofascin as a target for autoantibodies in peripheral neuropathies. Neurology. 2012;79:2241–2248. doi: 10.1212/WNL.0b013e31827689ad. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.Lonigro A., Devaux J.J. Disruption of neurofascin and gliomedin at nodes of Ranvier precedes demyelination in experimental allergic neuritis. Brain. 2009;132:260–273. doi: 10.1093/brain/awn281. [DOI] [PubMed] [Google Scholar]
- 39.Yuan A., Rao M.V., Veeranna, Nixon R.A. Neurofilaments at a glance. J. Cell Sci. 2012;125:3257–3263. doi: 10.1242/jcs.104729. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.Petzold A., Hinds N., Murray N.M., Hirsch N.P., Grant D., Keir G., Thompson E.J., Reilly M.M. CSF neurofilament levels: A potential prognostic marker in Guillain-Barré syndrome. Neurology. 2006;67:1071–1073. doi: 10.1212/01.wnl.0000237334.69665.92. [DOI] [PubMed] [Google Scholar]
- 41.Godelaine J., De Schaepdryver M., Bossuyt X., Van Damme P., Claeys K.G., Poesen K. Prognostic value of neurofilament light chain in chronic inflammatory demyelinating polyneuropathy. Brain Commun. 2021;3 doi: 10.1093/braincomms/fcab018. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Wang X.K., Zhang H.L., Meng F.H., Chang M., Wang Y.Z., Jin T., Mix E., Zhu J. Elevated levels of S100B, tau and pNFH in cerebrospinal fluid are correlated with subtypes of Guillain-Barré syndrome. Neurol. Sci. 2013;34:655–661. doi: 10.1007/s10072-012-1092-z. [DOI] [PubMed] [Google Scholar]
- 43.Limberg M., Disanto G., Barro C., Kuhle J. Neurofilament Light Chain Determination from Peripheral Blood Samples. Methods Mol. Biol. 2016;1304:93–98. doi: 10.1007/7651_2015_206. [DOI] [PubMed] [Google Scholar]
- 44.Kmezic I., Samuelsson K., Finn A., Upate Z., Blennow K., Zetterberg H., Press R. Neurofilament light chain and total tau in the differential diagnosis and prognostic evaluation of acute and chronic inflammatory polyneuropathies. Eur. J. Neurol. 2022;29:2810–2822. doi: 10.1111/ene.15428. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 45.Medeiros R., Baglietto-Vargas D., LaFerla F.M. The role of tau in Alzheimer’s disease and related disorders. CNS Neurosci. 2011;17:514–524. doi: 10.1111/j.1755-5949.2010.00177.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46.Kusunoki S., Chiba A., Hitoshi S., Takizawa H., Kanazawa I. Anti-Gal-C antibody in autoimmune neuropathies subsequent to mycoplasma infection. Muscle Nerve. 1995;18:409–413. doi: 10.1002/mus.880180407. [DOI] [PubMed] [Google Scholar]
- 47.Samukawa M., Hamada Y., Kuwahara M., Takada K., Hirano M., Mitsui Y., Sonoo M., Kusunoki S. Clinical features in Guillain-Barré syndrome with anti-Gal-C antibody. J. Neurol. Sci. 2014;337:55–60. doi: 10.1016/j.jns.2013.11.016. [DOI] [PubMed] [Google Scholar]
- 48.Sterk M., Oenings A., Eymann E., Roos W. Development of a new automated enzyme immunoassay for the determination of neuron-specific enolase. Anticancer Res. 1999;19:2759–2762. [PubMed] [Google Scholar]
- 49.Nagamatsu M., Mokuno K., Sugimura K., Kiyosawa K., Aoki S., Takahashi A., Kato K. Cerebrospinal fluid levels of S-100b protein and neuron-specific enolase in chronic inflammatory demyelinating polyneuropathy. Acta Neurol. Scand. 1995;91:483–487. doi: 10.1111/j.1600-0404.1995.tb00450.x. [DOI] [PubMed] [Google Scholar]
- 50.Mokuno K., Kiyosawa K., Sugimura K., Yasuda T., Riku S., Murayama T., Yanagi T., Takahashi A., Kato K. Prognostic value of cerebrospinal fluid neuron-specific enolase and S-100b protein in Guillain-Barré syndrome. Acta Neurol. Scand. 1994;89:27–30. doi: 10.1111/j.1600-0404.1994.tb01628.x. [DOI] [PubMed] [Google Scholar]
- 51.Kropp S., Zerr I., Schulz-Schaeffer W.J., Riedemann C., Bodemer M., Laske C., Kretzschmar H.A., Poser S. Increase of neuron-specific enolase in patients with Creutzfeldt-Jakob disease. Neurosci. Lett. 1999;261:124–126. doi: 10.1016/S0304-3940(98)00992-6. [DOI] [PubMed] [Google Scholar]
- 52.Elkarim R.A., Dahle C., Mustafa M., Press R., Zou L.P., Ekerfelt C., Ernerudh J., Link H., Bakhiet M. Recovery from Guillain-Barré syndrome is associated with increased levels of neutralizing autoantibodies to interferon-gamma. Clin. Immunol. Immunopathol. 1998;88:241–248. doi: 10.1006/clin.1998.4573. [DOI] [PubMed] [Google Scholar]
- 53.Li C., Zhao P., Sun X., Che Y., Jiang Y. Elevated levels of cerebrospinal fluid and plasma interleukin-37 in patients with Guillain-Barré syndrome. Mediat. Inflamm. 2013;2013:639712. doi: 10.1155/2013/639712. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 54.Zhang H.-L., Wu L., Wu X., Zhu J. Can IFN-γ be a therapeutic target in Guillain-Barré syndrome? Expert Opin. Ther. Targets. 2014;18:355–363. doi: 10.1517/14728222.2014.882899. [DOI] [PubMed] [Google Scholar]
- 55.Radhakrishnan V.V., Sumi M.G., Reuben S., Mathai A., Nair M.D. Serum tumour necrosis factor-alpha and soluble tumour necrosis factor receptors levels in patients with Guillain-Barre syndrome. Acta Neurol. Scand. 2004;109:71–74. doi: 10.1034/j.1600-0404.2003.00179.x. [DOI] [PubMed] [Google Scholar]
- 56.Deng H., Yang X., Jin T., Wu J., Hu L.S., Chang M., Sun X.J., Adem A., Winblad B., Zhu J. The role of IL-12 and TNF-alpha in AIDP and AMAN. Eur. J. Neurol. 2008;15:1100–1105. doi: 10.1111/j.1468-1331.2008.02261.x. [DOI] [PubMed] [Google Scholar]
- 57.Li S., Jin T., Zhang H.L., Yu H., Meng F., Concha Quezada H., Zhu J. Circulating Th17, Th22, and Th1 cells are elevated in the Guillain-Barré syndrome and downregulated by IVIg treatments. Mediat. Inflamm. 2014;2014:740947. doi: 10.1155/2014/740947. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 58.Jander S., Stoll G. Interleukin-18 is induced in acute inflammatory demyelinating polyneuropathy. J. Neuroimmunol. 2001;114:253–258. doi: 10.1016/S0165-5728(00)00460-4. [DOI] [PubMed] [Google Scholar]
- 59.Sun T., Chen X., Shi S., Liu Q., Cheng Y. Peripheral Blood and Cerebrospinal Fluid Cytokine Levels in Guillain Barré Syndrome: A Systematic Review and Meta-Analysis. Front. Neurosci. 2019;13:717. doi: 10.3389/fnins.2019.00717. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 60.Bao L., Lindgren J.U., van der Meide P., Zhu S., Ljunggren H.G., Zhu J. The critical role of IL-12p40 in initiating, enhancing, and perpetuating pathogenic events in murine experimental autoimmune neuritis. Brain Pathol. 2002;12:420–429. doi: 10.1111/j.1750-3639.2002.tb00459.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 61.Zhang Z.Y., Zhang Z., Fauser U., Schluesener H.J. Expression of interleukin-16 in sciatic nerves, spinal roots and spinal cords of experimental autoimmune neuritis rats. Brain Pathol. 2009;19:205–213. doi: 10.1111/j.1750-3639.2008.00172.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 62.Debnath M., Nagappa M., Murari G., Taly A.B. IL-23/IL-17 immune axis in Guillain Barré Syndrome: Exploring newer vistas for understanding pathobiology and therapeutic implications. Cytokine. 2018;103:77–82. doi: 10.1016/j.cyto.2017.12.029. [DOI] [PubMed] [Google Scholar]
- 63.Hohnoki K., Inoue A., Koh C.S. Elevated serum levels of IFN-gamma, IL-4 and TNF-alpha/unelevated serum levels of IL-10 in patients with demyelinating diseases during the acute stage. J. Neuroimmunol. 1998;87:27–32. doi: 10.1016/S0165-5728(98)00053-8. [DOI] [PubMed] [Google Scholar]
- 64.Beppu M., Sawai S., Misawa S., Sogawa K., Mori M., Ishige T., Satoh M., Nomura F., Kuwabara S. Serum cytokine and chemokine profiles in patients with chronic inflammatory demyelinating polyneuropathy. J. Neuroimmunol. 2015;279:7–10. doi: 10.1016/j.jneuroim.2014.12.017. [DOI] [PubMed] [Google Scholar]
- 65.Créange A., Bélec L., Clair B., Degos J.D., Raphaël J.C., Gherardi R.K. Circulating transforming growth factor beta 1 (TGF-beta1) in Guillain-Barré syndrome: Decreased concentrations in the early course and increase with motor function. J. Neurol. Neurosurg. Psychiatry. 1998;64:162–165. doi: 10.1136/jnnp.64.2.162. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 66.Min Y.G., Ju W., Seo J.-W., Ha Y.-E., Ban J.-J., Kwon Y.N., Jeong H.-Y., Shin J.-Y., Kim S.-M., Hong Y.-H., et al. Serum C3 complement levels predict prognosis and monitor disease activity in Guillain-Barré syndrome. J. Neurol. Sci. 2023;444:120512. doi: 10.1016/j.jns.2022.120512. [DOI] [PubMed] [Google Scholar]
- 67.Quast I., Keller C.W., Hiepe F., Tackenberg B., Lünemann J.D. Terminal complement activation is increased and associated with disease severity in CIDP. Ann. Clin. Transl. Neurol. 2016;3:730–735. doi: 10.1002/acn3.331. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 68.Querol L.A., Hartung H.P., Lewis R.A., van Doorn P.A., Hammond T.R., Atassi N., Alonso-Alonso M., Dalakas M.C. The Role of the Complement System in Chronic Inflammatory Demyelinating Polyneuropathy: Implications for Complement-Targeted Therapies. Neurotherapeutics. 2022;19:864–873. doi: 10.1007/s13311-022-01221-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 69.Undén J., Bellner J., Eneroth M., Alling C., Ingebrigtsen T., Romner B. Raised serum S100B levels after acute bone fractures without cerebral injury. J. Trauma. 2005;58:59–61. doi: 10.1097/01.TA.0000130613.35877.75. [DOI] [PubMed] [Google Scholar]
- 70.Kim M.J., Kim J.H., Jung J.H., Kim S.E., Kim H.S., Jang M.K., Park S.H., Lee M.S., Suk K.T., Kim D.J., et al. Serum S100B Levels in Patients with Liver Cirrhosis and Hepatic Encephalopathy. Diagnostics. 2023;13:333. doi: 10.3390/diagnostics13030333. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 71.Sainaghi P.P., Collimedaglia L., Alciato F., Leone M.A., Naldi P., Molinari R., Monaco F., Avanzi G.C. The expression pattern of inflammatory mediators in cerebrospinal fluid differentiates Guillain-Barré syndrome from chronic inflammatory demyelinating polyneuropathy. Cytokine. 2010;51:138–143. doi: 10.1016/j.cyto.2010.05.005. [DOI] [PubMed] [Google Scholar]
- 72.Orlikowski D., Chazaud B., Plonquet A., Poron F., Sharshar T., Maison P., Raphaël J.C., Gherardi R.K., Créange A. Monocyte chemoattractant protein 1 and chemokine receptor CCR2 productions in Guillain-Barré syndrome and experimental autoimmune neuritis. J. Neuroimmunol. 2003;134:118–127. doi: 10.1016/S0165-5728(02)00393-4. [DOI] [PubMed] [Google Scholar]
- 73.Kieseier B.C., Tani M., Mahad D., Oka N., Ho T., Woodroofe N., Griffin J.W., Toyka K.V., Ransohoff R.M., Hartung H.P. Chemokines and chemokine receptors in inflammatory demyelinating neuropathies: A central role for IP-10. Brain. 2002;125:823–834. doi: 10.1093/brain/awf070. [DOI] [PubMed] [Google Scholar]
- 74.Mahad D.J., Howell S.J., Woodroofe M.N. Expression of chemokines in cerebrospinal fluid and serum of patients with chronic inflammatory demyelinating polyneuropathy. J. Neurol. Neurosurg. Psychiatry. 2002;73:320–323. doi: 10.1136/jnnp.73.3.320. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 75.Musso A.M., Zanusso G.L., Bonazzi M.L., Tomelleri G., Bonetti B., Moretto G., Vio M., Monaco S. Increased serum levels of ICAM-1, ELAM-1 and TNF-alpha in inflammatory disorders of the peripheral nervous system. Ital. J. Neurol. Sci. 1994;15:267–271. doi: 10.1007/BF02339236. [DOI] [PubMed] [Google Scholar]
- 76.Feng Y., Feng F., Pan S., Zhang J., Li W. Fingolimod ameliorates chronic experimental autoimmune neuritis by modulating inflammatory cytokines and Akt/mTOR/NF-κB signaling. Brain Behav. 2023;13:e2965. doi: 10.1002/brb3.2965. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 77.O’Brien J., Hayder H., Zayed Y., Peng C. Overview of MicroRNA Biogenesis, Mechanisms of Actions, and Circulation. Front. Endocrinol. 2018;9 doi: 10.3389/fendo.2018.00402. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 78.Lv Z., Shi Q., Huang W., Xing C., Hao Y., Feng X., Yang Y., Zhang A., Kong Q., Yuki N., et al. MicroRNA expression profiling in Guillain-Barré syndrome. J. Neuroimmunol. 2016;301:12–15. doi: 10.1016/j.jneuroim.2016.10.014. [DOI] [PubMed] [Google Scholar]
- 79.Huang P., Xu M., He X.Y. Correlations between microRNA-146a and immunoglobulin and inflammatory factors in Guillain-Barré syndrome. J. Int. Med. Res. 2020;48:300060520904842. doi: 10.1177/0300060520904842. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 80.Dziadkowiak E., Baczyńska D., Wieczorek M., Olbromski M., Moreira H., Mrozowska M., Budrewicz S., Dzięgiel P., Barg E., Koszewicz M. miR-31-5p as a Potential Circulating Biomarker and Tracer of Clinical Improvement for Chronic Inflammatory Demyelinating Polyneuropathy. Oxid. Med. Cell Longev. 2023;2023:2305163. doi: 10.1155/2023/2305163. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 81.Heldal A.T., Eide G.E., Romi F., Owe J.F., Gilhus N.E. Repeated acetylcholine receptor antibody-concentrations and association to clinical myasthenia gravis development. PLoS ONE. 2014;9:e114060. doi: 10.1371/journal.pone.0114060. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 82.Behbehani R., Ali A., Al-Moosa A. Ocular Myasthenia: Clinical Course and the Diagnostic Utility of Assaying Acetylcholine Receptor Antibodies. Neuroophthalmology. 2022;46:220–226. doi: 10.1080/01658107.2022.2037662. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 83.Monte G., Spagni G., Damato V., Iorio R., Marino M., Evoli A. Acetylcholine receptor antibody positivity rate in ocular myasthenia gravis: A matter of age? J. Neurol. 2021;268:1803–1807. doi: 10.1007/s00415-020-10342-3. [DOI] [PubMed] [Google Scholar]
- 84.Kordas G., Lagoumintzis G., Sideris S., Poulas K., Tzartos S.J. Direct proof of the in vivo pathogenic role of the AChR autoantibodies from myasthenia gravis patients. PLoS ONE. 2014;9:e108327. doi: 10.1371/journal.pone.0108327. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 85.Kostelidou K., Trakas N., Tzartos S.J. Extracellular domains of the beta, gamma and epsilon subunits of the human acetylcholine receptor as immunoadsorbents for myasthenic autoantibodies: A combination of immunoadsorbents results in increased efficiency. J. Neuroimmunol. 2007;190:44–52. doi: 10.1016/j.jneuroim.2007.07.018. [DOI] [PubMed] [Google Scholar]
- 86.Tindall R.S. Humoral immunity in myasthenia gravis: Biochemical characterization of acquired antireceptor antibodies and clinical correlations. Ann. Neurol. 1981;10:437–447. doi: 10.1002/ana.410100506. [DOI] [PubMed] [Google Scholar]
- 87.Rødgaard A., Nielsen F.C., Djurup R., Somnier F., Gammeltoft S. Acetylcholine receptor antibody in myasthenia gravis: Predominance of IgG subclasses 1 and 3. Clin. Exp. Immunol. 1987;67:82–88. [PMC free article] [PubMed] [Google Scholar]
- 88.Drachman D.B., Angus C.W., Adams R.N., Michelson J.D., Hoffman G.J. Myasthenic antibodies cross-link acetylcholine receptors to accelerate degradation. N. Engl. J. Med. 1978;298:1116–1122. doi: 10.1056/NEJM197805182982004. [DOI] [PubMed] [Google Scholar]
- 89.Fazekas A., Komoly S., Bózsik B., Szobor A. Myasthenia gravis: Demonstration of membrane attack complex in muscle end-plates. Clin. Neuropathol. 1986;5:78–83. [PubMed] [Google Scholar]
- 90.Engel A.G., Arahata K. The membrane attack complex of complement at the endplate in myasthenia gravis. Ann. N. Y. Acad. Sci. 1987;505:326–332. doi: 10.1111/j.1749-6632.1987.tb51301.x. [DOI] [PubMed] [Google Scholar]
- 91.Obaid A.H., Zografou C., Vadysirisack D.D., Munro-Sheldon B., Fichtner M.L., Roy B., Philbrick W.M., Bennett J.L., Nowak R.J., O’Connor K.C. Heterogeneity of Acetylcholine Receptor Autoantibody-Mediated Complement Activity in Patients With Myasthenia Gravis. Neurol. Neuroimmunol. Neuroinflamm. 2022;9:e1169. doi: 10.1212/NXI.0000000000001169. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 92.Masuda T., Motomura M., Utsugisawa K., Nagane Y., Nakata R., Tokuda M., Fukuda T., Yoshimura T., Tsujihata M., Kawakami A. Antibodies against the main immunogenic region of the acetylcholine receptor correlate with disease severity in myasthenia gravis. J. Neurol. Neurosurg. Psychiatry. 2012;83:935–940. doi: 10.1136/jnnp-2012-302705. [DOI] [PubMed] [Google Scholar]
- 93.Tzartos S.J., Barkas T., Cung M.T., Kordossi A., Loutrari H., Marraud M., Papadouli I., Sakarellos C., Sophianos D., Tsikaris V. The main immunogenic region of the acetylcholine receptor. Structure and role in myasthenia gravis. Autoimmunity. 1991;8:259–270. doi: 10.3109/08916939109007633. [DOI] [PubMed] [Google Scholar]
- 94.Strijbos E., Verschuuren J., Kuks J.B.M. Serum Acetylcholine Receptor Antibodies Before the Clinical Onset of Myasthenia Gravis. J. Neuromuscul. Dis. 2018;5:261–264. doi: 10.3233/JND-180313. [DOI] [PubMed] [Google Scholar]
- 95.Lazaridis K., Tzartos S.J. Myasthenia Gravis: Autoantibody Specificities and Their Role in MG Management. Front. Neurol. 2020;11:596981. doi: 10.3389/fneur.2020.596981. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 96.Hong Y., Zisimopoulou P., Trakas N., Karagiorgou K., Stergiou C., Skeie G.O., Hao H.J., Gao X., Owe J.F., Zhang X., et al. Multiple antibody detection in ‘seronegative’ myasthenia gravis patients. Eur. J. Neurol. 2017;24:844–850. doi: 10.1111/ene.13300. [DOI] [PubMed] [Google Scholar]
- 97.Mirian A., Nicolle M.W., Edmond P., Budhram A. Comparison of fixed cell-based assay to radioimmunoprecipitation assay for acetylcholine receptor antibody detection in myasthenia gravis. J. Neurol. Sci. 2022;432:120084. doi: 10.1016/j.jns.2021.120084. [DOI] [PubMed] [Google Scholar]
- 98.Chang T., Leite M.I., Senanayake S., Gunaratne P.S., Gamage R., Riffsy M.T., Jacobson L.W., Adhikari M., Perera S., Vincent A. Clinical and serological study of myasthenia gravis using both radioimmunoprecipitation and cell-based assays in a South Asian population. J. Neurol. Sci. 2014;343:82–87. doi: 10.1016/j.jns.2014.05.037. [DOI] [PubMed] [Google Scholar]
- 99.Fichtner M.L., Hoarty M.D., Vadysirisack D.D., Munro-Sheldon B., Nowak R.J., O’Connor K.C. Myasthenia gravis complement activity is independent of autoantibody titer and disease severity. PLoS ONE. 2022;17:e0264489. doi: 10.1371/journal.pone.0264489. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 100.Hoch W., McConville J., Helms S., Newsom-Davis J., Melms A., Vincent A. Auto-antibodies to the receptor tyrosine kinase MuSK in patients with myasthenia gravis without acetylcholine receptor antibodies. Nat. Med. 2001;7:365–368. doi: 10.1038/85520. [DOI] [PubMed] [Google Scholar]
- 101.Rodolico C., Bonanno C., Toscano A., Vita G. MuSK-Associated Myasthenia Gravis: Clinical Features and Management. Front. Neurol. 2020;11:660. doi: 10.3389/fneur.2020.00660. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 102.Valenzuela D.M., Stitt T.N., DiStefano P.S., Rojas E., Mattsson K., Compton D.L., Nuñez L., Park J.S., Stark J.L., Gies D.R., et al. Receptor tyrosine kinase specific for the skeletal muscle lineage: Expression in embryonic muscle, at the neuromuscular junction, and after injury. Neuron. 1995;15:573–584. doi: 10.1016/0896-6273(95)90146-9. [DOI] [PubMed] [Google Scholar]
- 103.Koneczny I., Stevens J.A., De Rosa A., Huda S., Huijbers M.G., Saxena A., Maestri M., Lazaridis K., Zisimopoulou P., Tzartos S., et al. IgG4 autoantibodies against muscle-specific kinase undergo Fab-arm exchange in myasthenia gravis patients. J. Autoimmun. 2017;77:104–115. doi: 10.1016/j.jaut.2016.11.005. [DOI] [PubMed] [Google Scholar]
- 104.König N., Stetefeld H.R., Dohmen C., Mergenthaler P., Kohler S., Schönenberger S., Bösel J., Lee D.-H., Gerner S.T., Huttner H.B., et al. MuSK-antibodies are associated with worse outcome in myasthenic crisis requiring mechanical ventilation. J. Neurol. 2021;268:4824–4833. doi: 10.1007/s00415-021-10603-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 105.Meriggioli M.N., Sanders D.B. Muscle autoantibodies in myasthenia gravis: Beyond diagnosis? Expert Rev. Clin. Immunol. 2012;8:427–438. doi: 10.1586/eci.12.34. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 106.Bartoccioni E., Scuderi F., Minicuci G.M., Marino M., Ciaraffa F., Evoli A. Anti-MuSK antibodies: Correlation with myasthenia gravis severity. Neurology. 2006;67:505–507. doi: 10.1212/01.wnl.0000228225.23349.5d. [DOI] [PubMed] [Google Scholar]
- 107.Skriapa L., Zisimopoulou P., Trakas N., Grapsa E., Tzartos S.J. Expression of extracellular domains of muscle specific kinase (MuSK) and use as immunoadsorbents for the development of an antigen-specific therapy. J. Neuroimmunol. 2014;276:150–158. doi: 10.1016/j.jneuroim.2014.09.013. [DOI] [PubMed] [Google Scholar]
- 108.Kwon Y.N., Woodhall M., Sung J.-J., Kim K.-K., Lim Y.-M., Kim H., Kim J.-E., Baek S.-H., Kim B.-J., Park J.-S., et al. Clinical pitfalls and serological diagnostics of MuSK myasthenia gravis. J. Neurol. 2023;270:1478–1486. doi: 10.1007/s00415-022-11458-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 109.Di Stefano V., Lupica A., Rispoli M.G., Di Muzio A., Brighina F., Rodolico C. Rituximab in AChR subtype of myasthenia gravis: Systematic review. J. Neurol. Neurosurg. Psychiatry. 2020;91:392–395. doi: 10.1136/jnnp-2019-322606. [DOI] [PubMed] [Google Scholar]
- 110.Marino M., Basile U., Spagni G., Napodano C., Iorio R., Gulli F., Todi L., Provenzano C., Bartoccioni E., Evoli A. Long-Lasting Rituximab-Induced Reduction of Specific-But Not Total-IgG4 in MuSK-Positive Myasthenia Gravis. Front. Immunol. 2020;11:613. doi: 10.3389/fimmu.2020.00613. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 111.Shen C., Lu Y., Zhang B., Figueiredo D., Bean J., Jung J., Wu H., Barik A., Yin D.M., Xiong W.C., et al. Antibodies against low-density lipoprotein receptor-related protein 4 induce myasthenia gravis. J. Clin. Investig. 2013;123:5190–5202. doi: 10.1172/JCI66039. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 112.Tzartos J.S., Zisimopoulou P., Rentzos M., Karandreas N., Zouvelou V., Evangelakou P., Tsonis A., Thomaidis T., Lauria G., Andreetta F., et al. LRP4 antibodies in serum and CSF from amyotrophic lateral sclerosis patients. Ann. Clin. Transl. Neurol. 2014;1:80–87. doi: 10.1002/acn3.26. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 113.Zisimopoulou P., Evangelakou P., Tzartos J., Lazaridis K., Zouvelou V., Mantegazza R., Antozzi C., Andreetta F., Evoli A., Deymeer F., et al. A comprehensive analysis of the epidemiology and clinical characteristics of anti-LRP4 in myasthenia gravis. J. Autoimmun. 2014;52:139–145. doi: 10.1016/j.jaut.2013.12.004. [DOI] [PubMed] [Google Scholar]
- 114.Rivner M.H., Quarles B.M., Pan J.X., Yu Z., Howard J.F., Jr., Corse A., Dimachkie M.M., Jackson C., Vu T., Small G., et al. Clinical features of LRP4/agrin-antibody-positive myasthenia gravis: A multicenter study. Muscle Nerve. 2020;62:333–343. doi: 10.1002/mus.26985. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 115.Rivner M.H., Liu S., Quarles B., Fleenor B., Shen C., Pan J., Mei L. Agrin and low-density lipoprotein-related receptor protein 4 antibodies in amyotrophic lateral sclerosis patients. Muscle Nerve. 2017;55:430–432. doi: 10.1002/mus.25438. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 116.Higuchi O., Hamuro J., Motomura M., Yamanashi Y. Autoantibodies to low-density lipoprotein receptor-related protein 4 in myasthenia gravis. Ann. Neurol. 2011;69:418–422. doi: 10.1002/ana.22312. [DOI] [PubMed] [Google Scholar]
- 117.Li M., Han J., Zhang Y., Lv J., Zhang J., Zhao X., Ren L., Fang H., Yang J., Zhang Y., et al. Clinical analysis of Chinese anti-low-density-lipoprotein-receptor-associated protein 4 antibodies in patients with myasthenia gravis. Eur. J. Neurol. 2019;26:1296-e84. doi: 10.1111/ene.13979. [DOI] [PubMed] [Google Scholar]
- 118.Kim K.H., Kim S.W., Cho J., Chung H.Y., Shin H.Y. Anti-titin antibody is associated with more frequent hospitalization to manage thymoma-associated myasthenia gravis. Front. Neurol. 2022;13:978997. doi: 10.3389/fneur.2022.978997. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 119.Chen X.J., Qiao J., Xiao B.G., Lu C.Z. The significance of titin antibodies in myasthenia gravis--correlation with thymoma and severity of myasthenia gravis. J. Neurol. 2004;251:1006–1011. doi: 10.1007/s00415-004-0479-z. [DOI] [PubMed] [Google Scholar]
- 120.Szczudlik P., Szyluk B., Lipowska M., Ryniewicz B., Kubiszewska J., Dutkiewicz M., Gilhus N.E., Kostera-Pruszczyk A. Antititin antibody in early- and late-onset myasthenia gravis. Acta Neurol. Scand. 2014;130:229–233. doi: 10.1111/ane.12271. [DOI] [PubMed] [Google Scholar]
- 121.Suzuki S., Satoh T., Yasuoka H., Hamaguchi Y., Tanaka K., Kawakami Y., Suzuki N., Kuwana M. Novel autoantibodies to a voltage-gated potassium channel Kv1.4 in a severe form of myasthenia gravis. J. Neuroimmunol. 2005;170:141–149. doi: 10.1016/j.jneuroim.2005.08.017. [DOI] [PubMed] [Google Scholar]
- 122.Suzuki S., Utsugisawa K., Yoshikawa H., Motomura M., Matsubara S., Yokoyama K., Nagane Y., Maruta T., Satoh T., Sato H., et al. Autoimmune targets of heart and skeletal muscles in myasthenia gravis. Arch. Neurol. 2009;66:1334–1338. doi: 10.1001/archneurol.2009.229. [DOI] [PubMed] [Google Scholar]
- 123.Losen M., Stassen M.H., Martínez-Martínez P., Machiels B.M., Duimel H., Frederik P., Veldman H., Wokke J.H., Spaans F., Vincent A., et al. Increased expression of rapsyn in muscles prevents acetylcholine receptor loss in experimental autoimmune myasthenia gravis. Brain. 2005;128:2327–2337. doi: 10.1093/brain/awh612. [DOI] [PubMed] [Google Scholar]
- 124.Gallardo E., Martínez-Hernández E., Titulaer M.J., Huijbers M.G., Martínez M.A., Ramos A., Querol L., Díaz-Manera J., Rojas-García R., Hayworth C.R., et al. Cortactin autoantibodies in myasthenia gravis. Autoimmun. Rev. 2014;13:1003–1007. doi: 10.1016/j.autrev.2014.08.039. [DOI] [PubMed] [Google Scholar]
- 125.Labrador-Horrillo M., Martínez M.A., Selva-O’Callaghan A., Trallero-Araguás E., Grau-Junyent J.M., Vilardell-Tarrés M., Juarez C. Identification of a novel myositis-associated antibody directed against cortactin. Autoimmun. Rev. 2014;13:1008–1012. doi: 10.1016/j.autrev.2014.08.038. [DOI] [PubMed] [Google Scholar]
- 126.Illa I., Cortés-Vicente E., Martínez M.Á., Gallardo E. Diagnostic utility of cortactin antibodies in myasthenia gravis. Ann. N. Y. Acad. Sci. 2018;1412:90–94. doi: 10.1111/nyas.13502. [DOI] [PubMed] [Google Scholar]
- 127.Gasperi C., Melms A., Schoser B., Zhang Y., Meltoranta J., Risson V., Schaeffer L., Schalke B., Kröger S. Anti-agrin autoantibodies in myasthenia gravis. Neurology. 2014;82:1976–1983. doi: 10.1212/WNL.0000000000000478. [DOI] [PubMed] [Google Scholar]
- 128.Wang S., Yang H., Guo R., Wang L., Zhang Y., Lv J., Zhao X., Zhang J., Fang H., Zhang Q., et al. Antibodies to Full-Length Agrin Protein in Chinese Patients With Myasthenia Gravis. Front. Immunol. 2021;12:753247. doi: 10.3389/fimmu.2021.753247. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 129.Sabre L., Punga T., Punga A.R. Circulating miRNAs as Potential Biomarkers in Myasthenia Gravis: Tools for Personalized Medicine. Front. Immunol. 2020;11:213. doi: 10.3389/fimmu.2020.00213. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 130.Ghirardello A., Zampieri S., Iaccarino L., Tarricone E., Bendo R., Gambari P.F., Doria A. Anti-Mi-2 antibodies. Autoimmunity. 2005;38:79–83. doi: 10.1080/08916930400022681. [DOI] [PubMed] [Google Scholar]
- 131.Liang L., Zhang Y.M., Chen H., Ye L.F., Li S.S., Lu X., Wang G.C., Peng Q.L. Anti-Mi-2 antibodies characterize a distinct clinical subset of dermatomyositis with favourable prognosis. Eur. J. Derm. 2020 doi: 10.1684/ejd.2020.3750. [DOI] [PubMed] [Google Scholar]
- 132.Ogawa-Momohara M., Muro Y., Akiyama M. Anti-Mi-2 antibody titers and cutaneous manifestations in dermatomyositis. J. Cutan. Immunol. Allergy. 2019;2:49–52. doi: 10.1002/cia2.12048. [DOI] [Google Scholar]
- 133.Lu X., Peng Q., Wang G. Biomarkers of disease activity in dermatomyositis. Curr. Opin. Rheumatol. 2022;34:289–294. doi: 10.1097/BOR.0000000000000905. [DOI] [PubMed] [Google Scholar]
- 134.Satoh M., Tanaka S., Ceribelli A., Calise S.J., Chan E.K. A Comprehensive Overview on Myositis-Specific Antibodies: New and Old Biomarkers in Idiopathic Inflammatory Myopathy. Clin. Rev. Allergy Immunol. 2017;52:1–19. doi: 10.1007/s12016-015-8510-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 135.dos Passos Carvalho M.I.C., Shinjo S.K. Frequency and clinical relevance of anti-Mi-2 autoantibody in adult Brazilian patients with dermatomyositis. Adv. Rheumatol. 2019;59:27. doi: 10.1186/s42358-019-0071-y. [DOI] [PubMed] [Google Scholar]
- 136.Roux S., Seelig H.P., Meyer O. Significance of Mi-2 autoantibodies in polymyositis and dermatomyositis. J. Rheumatol. 1998;25:395–396. [PubMed] [Google Scholar]
- 137.Aggarwal R., Cassidy E., Fertig N., Koontz D.C., Lucas M., Ascherman D.P., Oddis C.V. Patients with non-Jo-1 anti-tRNA-synthetase autoantibodies have worse survival than Jo-1 positive patients. Ann. Rheum. Dis. 2014;73:227–232. doi: 10.1136/annrheumdis-2012-201800. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 138.Witt L.J., Curran J.J., Strek M.E. The Diagnosis and Treatment of Antisynthetase Syndrome. Clin. Pulm. Med. 2016;23:218–226. doi: 10.1097/CPM.0000000000000171. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 139.Love L.A., Leff R.L., Fraser D.D., Targoff I.N., Dalakas M., Plotz P.H., Miller F.W. A new approach to the classification of idiopathic inflammatory myopathy: Myositis-specific autoantibodies define useful homogeneous patient groups. Medicine. 1991;70:360–374. doi: 10.1097/00005792-199111000-00002. [DOI] [PubMed] [Google Scholar]
- 140.Mecoli C.A., Albayda J., Tiniakou E., Paik J.J., Zahid U., Danoff S.K., Casciola-Rosen L., Casal-Dominguez M., Pak K., Pinal-Fernandez I., et al. Myositis Autoantibodies: A Comparison of Results From the Oklahoma Medical Research Foundation Myositis Panel to the Euroimmun Research Line Blot. Arthritis Rheumatol. 2020;72:192–194. doi: 10.1002/art.41088. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 141.Shinoda K., Okumura M., Yamaguchi S., Matsui A., Tsuda R., Hounoki H., Suzuki S., Tobe K. A Comparison of Line Blots, Enzyme-linked Immunosorbent, and RNA-immunoprecipitation Assays of Antisynthetase Antibodies in Serum Samples from 44 Patients. Intern. Med. 2022;61:313–322. doi: 10.2169/internalmedicine.7824-21. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 142.Fredi M., Cavazzana I., Ceribelli A., Cavagna L., Barsotti S., Bartoloni E., Benucci M., De Stefano L., Doria A., Emmi G., et al. An Italian Multicenter Study on Anti-NXP2 Antibodies: Clinical and Serological Associations. Clin. Rev. Allergy Immunol. 2022;63:240–250. doi: 10.1007/s12016-021-08920-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 143.Yan T.T., Zhang X., Yang H.H., Sun W.J., Liu L., Du Y., Xue J. Association of anti-NXP2 antibody with clinical characteristics and outcomes in adult dermatomyositis: Results from clinical applications based on a myositis-specific antibody. Clin. Rheumatol. 2021;40:3695–3702. doi: 10.1007/s10067-021-05667-x. [DOI] [PubMed] [Google Scholar]
- 144.Ghirardello A., Bettio S., Bassi N., Gatto M., Beggio M., Lundberg I., Vattemi G., Iaccarino L., Punzi L., Doria A. Autoantibody testing in patients with myositis: Clinical accuracy of a multiparametric line immunoassay. Clin. Exp. Rheumatol. 2017;35:176–177. [PubMed] [Google Scholar]
- 145.Mahler M., Betteridge Z., Bentow C., Richards M., Seaman A., Chinoy H., McHugh N. Comparison of Three Immunoassays for the Detection of Myositis Specific Antibodies. Front. Immunol. 2019;10:848. doi: 10.3389/fimmu.2019.00848. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 146.Li L., Wang Q., Yang F., Wu C., Chen S., Wen X., Liu C., Li Y. Anti-MDA5 antibody as a potential diagnostic and prognostic biomarker in patients with dermatomyositis. Oncotarget. 2017;8:26552–26564. doi: 10.18632/oncotarget.15716. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 147.Nombel A., Fabien N., Coutant F. Dermatomyositis With Anti-MDA5 Antibodies: Bioclinical Features, Pathogenesis and Emerging Therapies. Front. Immunol. 2021;12:773352. doi: 10.3389/fimmu.2021.773352. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 148.Ladislau L., Suárez-Calvet X., Toquet S., Landon-Cardinal O., Amelin D., Depp M., Rodero M.P., Hathazi D., Duffy D., Bondet V., et al. JAK inhibitor improves type I interferon induced damage: Proof of concept in dermatomyositis. Brain. 2018;141:1609–1621. doi: 10.1093/brain/awy105. [DOI] [PubMed] [Google Scholar]
- 149.Shimizu K., Kobayashi T., Kano M., Hamaguchi Y., Takehara K., Matsushita T. Anti-transcriptional intermediary factor 1-γ antibody as a biomarker in patients with dermatomyositis. J. Derm. 2020;47:64–68. doi: 10.1111/1346-8138.15128. [DOI] [PubMed] [Google Scholar]
- 150.Targoff I.N., Mamyrova G., Trieu E.P., Perurena O., Koneru B., O’Hanlon T.P., Miller F.W., Rider L.G. A novel autoantibody to a 155-kd protein is associated with dermatomyositis. Arthritis Rheum. 2006;54:3682–3689. doi: 10.1002/art.22164. [DOI] [PubMed] [Google Scholar]
- 151.Fujimoto M., Hamaguchi Y., Kaji K., Matsushita T., Ichimura Y., Kodera M., Ishiguro N., Ueda-Hayakawa I., Asano Y., Ogawa F., et al. Myositis-specific anti-155/140 autoantibodies target transcription intermediary factor 1 family proteins. Arthritis Rheum. 2012;64:513–522. doi: 10.1002/art.33403. [DOI] [PubMed] [Google Scholar]
- 152.Selickaja S., Galindo-Feria A.S., Dani L., Mimori T., Rönnelid J., Holmqvist M., Lundberg I.E., Venalis P. ELISA, protein immunoprecipitation and line blot assays for anti-TIF1-gamma autoantibody detection in cancer-associated dermatomyositis. Rheumatology. 2022;61:4991–4996. doi: 10.1093/rheumatology/keac288. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 153.Muro Y., Sugiura K., Nara M., Sakamoto I., Suzuki N., Akiyama M. High incidence of cancer in anti-small ubiquitin-like modifier activating enzyme antibody-positive dermatomyositis. Rheumatology. 2015;54:1745–1747. doi: 10.1093/rheumatology/kev247. [DOI] [PubMed] [Google Scholar]
- 154.Ge Y., Lu X., Shu X., Peng Q., Wang G. Clinical characteristics of anti-SAE antibodies in Chinese patients with dermatomyositis in comparison with different patient cohorts. Sci. Rep. 2017;7:188. doi: 10.1038/s41598-017-00240-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 155.Tarricone E., Ghirardello A., Rampudda M., Bassi N., Punzi L., Doria A. Anti-SAE antibodies in autoimmune myositis: Identification by unlabelled protein immunoprecipitation in an Italian patient cohort. J. Immunol. Methods. 2012;384:128–134. doi: 10.1016/j.jim.2012.07.019. [DOI] [PubMed] [Google Scholar]
- 156.Suzuki S., Nishikawa A., Kuwana M., Nishimura H., Watanabe Y., Nakahara J., Hayashi Y.K., Suzuki N., Nishino I. Inflammatory myopathy with anti-signal recognition particle antibodies: Case series of 100 patients. Orphanet J. Rare Dis. 2015;10:61. doi: 10.1186/s13023-015-0277-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 157.Kassardjian C.D., Lennon V.A., Alfugham N.B., Mahler M., Milone M. Clinical Features and Treatment Outcomes of Necrotizing Autoimmune Myopathy. JAMA Neurol. 2015;72:996–1003. doi: 10.1001/jamaneurol.2015.1207. [DOI] [PubMed] [Google Scholar]
- 158.Ma X., Bu B.T. Anti-SRP immune-mediated necrotizing myopathy: A critical review of current concepts. Front. Immunol. 2022;13:1019972. doi: 10.3389/fimmu.2022.1019972. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 159.Limaye V., Bundell C., Hollingsworth P., Rojana-Udomsart A., Mastaglia F., Blumbergs P., Lester S. Clinical and genetic associations of autoantibodies to 3-hydroxy-3-methyl-glutaryl-coenzyme a reductase in patients with immune-mediated myositis and necrotizing myopathy. Muscle Nerve. 2015;52:196–203. doi: 10.1002/mus.24541. [DOI] [PubMed] [Google Scholar]
- 160.Werner J.L., Christopher-Stine L., Ghazarian S.R., Pak K.S., Kus J.E., Daya N.R., Lloyd T.E., Mammen A.L. Antibody levels correlate with creatine kinase levels and strength in anti-3-hydroxy-3-methylglutaryl-coenzyme A reductase-associated autoimmune myopathy. Arthritis Rheum. 2012;64:4087–4093. doi: 10.1002/art.34673. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 161.Musset L., Allenbach Y., Benveniste O., Boyer O., Bossuyt X., Bentow C., Phillips J., Mammen A., Van Damme P., Westhovens R., et al. Anti-HMGCR antibodies as a biomarker for immune-mediated necrotizing myopathies: A history of statins and experience from a large international multi-center study. Autoimmun. Rev. 2016;15:983–993. doi: 10.1016/j.autrev.2016.07.023. [DOI] [PubMed] [Google Scholar]
- 162.Prieto-Peña D., Ocejo-Vinyals J.G., Mazariegos-Cano J., Pelayo-Negro A.L., Remuzgo-Martínez S., Genre F., García-Dorta A., Renuncio-García M., Martínez-Taboada V.M., García-Ibarbia C., et al. Epidemiological and genetic features of anti-3-hydroxy-3-methylglutaryl-CoA reductase necrotizing myopathy: Single-center experience and literature review. Eur. J. Intern. Med. 2022;101:86–92. doi: 10.1016/j.ejim.2022.04.017. [DOI] [PubMed] [Google Scholar]
- 163.Kadoya M., Hida A., Hashimoto Maeda M., Taira K., Ikenaga C., Uchio N., Kubota A., Kaida K., Miwa Y., Kurasawa K., et al. Cancer association as a risk factor for anti-HMGCR antibody-positive myopathy. Neurol. Neuroimmunol. Neuroinflamm. 2016;3:e290. doi: 10.1212/NXI.0000000000000290. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 164.Szczesny P., Barsotti S., Nennesmo I., Danielsson O., Dastmalchi M. Screening for Anti-HMGCR Antibodies in a Large Single Myositis Center Reveals Infrequent Exposure to Statins and Diversiform Presentation of the Disease. Front. Immunol. 2022;13:866701. doi: 10.3389/fimmu.2022.866701. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 165.Mohassel P., Mammen A.L. Anti-HMGCR Myopathy. J. Neuromuscul. Dis. 2018;5:11–20. doi: 10.3233/JND-170282. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 166.Peng Q.L., Zhang Y.L., Shu X.M., Yang H.B., Zhang L., Chen F., Lu X., Wang G.C. Elevated Serum Levels of Soluble CD163 in Polymyositis and Dermatomyositis: Associated with Macrophage Infiltration in Muscle Tissue. J. Rheumatol. 2015;42:979–987. doi: 10.3899/jrheum.141307. [DOI] [PubMed] [Google Scholar]
- 167.Enomoto Y., Suzuki Y., Hozumi H., Mori K., Kono M., Karayama M., Furuhashi K., Fujisawa T., Enomoto N., Nakamura Y., et al. Clinical significance of soluble CD163 in polymyositis-related or dermatomyositis-related interstitial lung disease. Arthritis Res. 2017;19:9. doi: 10.1186/s13075-016-1214-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 168.Kawasumi H., Katsumata Y., Nishino A., Hirahara S., Kawaguchi Y., Kuwana M., Yamanaka H. Association of Serum Soluble CD163 with Polymyositis and Dermatomyositis, Especially in Anti-MDA5 Antibody-positive Cases. J. Rheumatol. 2018;45:947–955. doi: 10.3899/jrheum.170997. [DOI] [PubMed] [Google Scholar]
- 169.Paul P., Liewluck T., Ernste F.C., Mandrekar J., Milone M. Anti-cN1A antibodies do not correlate with specific clinical, electromyographic, or pathological findings in sporadic inclusion body myositis. Muscle Nerve. 2021;63:490–496. doi: 10.1002/mus.27157. [DOI] [PubMed] [Google Scholar]
- 170.Tawara N., Yamashita S., Zhang X., Korogi M., Zhang Z., Doki T., Matsuo Y., Nakane S., Maeda Y., Sugie K., et al. Pathomechanisms of anti-cytosolic 5’-nucleotidase 1A autoantibodies in sporadic inclusion body myositis. Ann. Neurol. 2017;81:512–525. doi: 10.1002/ana.24919. [DOI] [PubMed] [Google Scholar]
- 171.Amlani A., Choi M.Y., Tarnopolsky M., Brady L., Clarke A.E., Garcia-De La Torre I., Mahler M., Schmeling H., Barber C.E., Jung M., et al. Anti-NT5c1A Autoantibodies as Biomarkers in Inclusion Body Myositis. Front. Immunol. 2019;10:745. doi: 10.3389/fimmu.2019.00745. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 172.Herbert M.K., Stammen-Vogelzangs J., Verbeek M.M., Rietveld A., Lundberg I.E., Chinoy H., Lamb J.A., Cooper R.G., Roberts M., Badrising U.A., et al. Disease specificity of autoantibodies to cytosolic 5′-nucleotidase 1A in sporadic inclusion body myositis versus known autoimmune diseases. Ann. Rheum. Dis. 2016;75:696–701. doi: 10.1136/annrheumdis-2014-206691. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 173.Parkes J.E., Thoma A., Lightfoot A.P., Day P.J., Chinoy H., Lamb J.A. MicroRNA and mRNA profiling in the idiopathic inflammatory myopathies. BMC Rheumatol. 2020;4:25. doi: 10.1186/s41927-020-00125-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 174.Di Stefano V., Barbone F., Ferrante C., Telese R., Vitale M., Onofrj M., Di Muzio A. Inflammatory polyradiculoneuropathies: Clinical and immunological aspects, current therapies, and future perspectives. Eur. J. Inflamm. 2020;18:2058739220942340. doi: 10.1177/2058739220942340. [DOI] [Google Scholar]
- 175.Illes Z., Blaabjerg M. Cerebrospinal fluid findings in Guillain-Barré syndrome and chronic inflammatory demyelinating polyneuropathies. Handb. Clin. Neurol. 2017;146:125–138. doi: 10.1016/b978-0-12-804279-3.00009-5. [DOI] [PubMed] [Google Scholar]
- 176.Wong A.H., Umapathi T., Nishimoto Y., Wang Y.Z., Chan Y.C., Yuki N. Cytoalbuminologic dissociation in Asian patients with Guillain-Barré and Miller Fisher syndromes. J. Peripher. Nerv. Syst. 2015;20:47–51. doi: 10.1111/jns.12104. [DOI] [PubMed] [Google Scholar]
- 177.Hegen H., Ladstätter F., Bsteh G., Auer M., Berek K., Di Pauli F., Walde J., Wanschitz J., Zinganell A., Deisenhammer F. Cerebrospinal fluid protein in Guillain-Barré syndrome: Need for age-dependent interpretation. Eur. J. Neurol. 2021;28:965–973. doi: 10.1111/ene.14600. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 178.Fokke C., van den Berg B., Drenthen J., Walgaard C., van Doorn P.A., Jacobs B.C. Diagnosis of Guillain-Barré syndrome and validation of Brighton criteria. Brain. 2014;137:33–43. doi: 10.1093/brain/awt285. [DOI] [PubMed] [Google Scholar]
- 179.Zhang H.L., Zhang X.M., Mao X.J., Deng H., Li H.F., Press R., Fredrikson S., Zhu J. Altered cerebrospinal fluid index of prealbumin, fibrinogen, and haptoglobin in patients with Guillain-Barré syndrome and chronic inflammatory demyelinating polyneuropathy. Acta Neurol. Scand. 2012;125:129–135. doi: 10.1111/j.1600-0404.2011.01511.x. [DOI] [PubMed] [Google Scholar]
- 180.Jin T., Hu L.S., Chang M., Wu J., Winblad B., Zhu J. Proteomic identification of potential protein markers in cerebrospinal fluid of GBS patients. Eur. J. Neurol. 2007;14:563–568. doi: 10.1111/j.1468-1331.2007.01761.x. [DOI] [PubMed] [Google Scholar]
- 181.van den Berg B., Walgaard C., Drenthen J., Fokke C., Jacobs B.C., van Doorn P.A. Guillain-Barré syndrome: Pathogenesis, diagnosis, treatment and prognosis. Nat. Rev. Neurol. 2014;10:469–482. doi: 10.1038/nrneurol.2014.121. [DOI] [PubMed] [Google Scholar]
- 182.Schnaar R.L. Gangliosides of the Vertebrate Nervous System. J. Mol. Biol. 2016;428:3325–3336. doi: 10.1016/j.jmb.2016.05.020. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 183.Yan W., Nguyen T., Yuki N., Ji Q., Yiannikas C., Pollard J.D., Mathey E.K. Antibodies to neurofascin exacerbate adoptive transfer experimental autoimmune neuritis. J. Neuroimmunol. 2014;277:13–17. doi: 10.1016/j.jneuroim.2014.09.012. [DOI] [PubMed] [Google Scholar]
- 184.Devaux J.J. Antibodies to gliomedin cause peripheral demyelinating neuropathy and the dismantling of the nodes of Ranvier. Am. J. Pathol. 2012;181:1402–1413. doi: 10.1016/j.ajpath.2012.06.034. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 185.Weingarten M.D., Lockwood A.H., Hwo S.Y., Kirschner M.W. A protein factor essential for microtubule assembly. Proc. Natl. Acad. Sci. USA. 1975;72:1858–1862. doi: 10.1073/pnas.72.5.1858. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 186.Nakos G., Tziakou E., Maneta-Peyret L., Nassis C., Lekka M.E. Anti-phospholipid antibodies in serum from patients with Guillain-Barré syndrome. Intensive Care Med. 2005;31:1401–1408. doi: 10.1007/s00134-005-2736-8. [DOI] [PubMed] [Google Scholar]
- 187.Harris E.N., Englert H., Derve G., Hughes G.R., Gharavi A. Antiphospholipid antibodies in acute Guillain-Barré syndrome. Lancet. 1983;2:1361–1362. doi: 10.1016/S0140-6736(83)91113-3. [DOI] [PubMed] [Google Scholar]
- 188.Saida T., Saida K., Lisak R.P., Brown M.J., Silberberg D.H., Asbury A.K. In vivo demyelinating activity of sera from patients with Guillain-Barré syndrome. Ann. Neurol. 1982;11:69–75. doi: 10.1002/ana.410110112. [DOI] [PubMed] [Google Scholar]
- 189.Sawant-Mane S., Clark M.B., Koski C.L. In vitro demyelination by serum antibody from patients with Guillain-Barré syndrome requires terminal complement complexes. Ann. Neurol. 1991;29:397–404. doi: 10.1002/ana.410290410. [DOI] [PubMed] [Google Scholar]
- 190.Halstead S.K., Zitman F.M., Humphreys P.D., Greenshields K., Verschuuren J.J., Jacobs B.C., Rother R.P., Plomp J.J., Willison H.J. Eculizumab prevents anti-ganglioside antibody-mediated neuropathy in a murine model. Brain. 2008;131:1197–1208. doi: 10.1093/brain/awm316. [DOI] [PubMed] [Google Scholar]
- 191.Sanders M.E., Koski C.L., Robbins D., Shin M.L., Frank M.M., Joiner K.A. Activated terminal complement in cerebrospinal fluid in Guillain-Barré syndrome and multiple sclerosis. J. Immunol. 1986;136:4456–4459. doi: 10.4049/jimmunol.136.12.4456. [DOI] [PubMed] [Google Scholar]
- 192.D’Aguanno S., Franciotta D., Lupisella S., Barassi A., Pieragostino D., Lugaresi A., Centonze D., D’Eril G.M., Bernardini S., Federici G., et al. Protein profiling of Guillain-Barrè syndrome cerebrospinal fluid by two-dimensional electrophoresis and mass spectrometry. Neurosci. Lett. 2010;485:49–54. doi: 10.1016/j.neulet.2010.08.060. [DOI] [PubMed] [Google Scholar]
- 193.Liu M.Q., Wang J., Huang C.N., Qi Y., Zhang L.J., Yi M., Chang S.H., Sun L.S., Yang L. Elevated cerebrospinal fluid levels of beta-2-microglobulin in patients with Guillain-Barré syndrome and their correlations with clinical features. Neurol. Sci. 2021;42:4249–4255. doi: 10.1007/s10072-021-05108-2. [DOI] [PubMed] [Google Scholar]
- 194.Pritchard J., Hughes R.A., Rees J.H., Willison H.J., Nicoll J.A. Apolipoprotein E genotypes and clinical outcome in Guillain-Barré syndrome. J. Neurol. Neurosurg. Psychiatry. 2003;74:971–973. doi: 10.1136/jnnp.74.7.971. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 195.Chiang H.L., Lyu R.K., Tseng M.Y., Chang K.H., Chang H.S., Hsu W.C., Kuo H.C., Chu C.C., Wu Y.R., Ro L.S., et al. Analyses of transthyretin concentration in the cerebrospinal fluid of patients with Guillain-Barré syndrome and other neurological disorders. Clin. Chim. Acta. 2009;405:143–147. doi: 10.1016/j.cca.2009.04.022. [DOI] [PubMed] [Google Scholar]
- 196.Compston D.A., Vincent A., Newsom-Davis J., Batchelor J.R. Clinical, pathological, HLA antigen and immunological evidence for disease heterogeneity in myasthenia gravis. Brain. 1980;103:579–601. doi: 10.1093/brain/103.3.579. [DOI] [PubMed] [Google Scholar]
- 197.Vincent A., Newsom-Davis J. Acetylcholine receptor antibody characteristics in myasthenia gravis. I. Patients with generalized myasthenia or disease restricted to ocular muscles. Clin. Exp. Immunol. 1982;49:257–265. [PMC free article] [PubMed] [Google Scholar]
- 198.Vincent A., Newsom-Davis J. Acetylcholine receptor antibody as a diagnostic test for myasthenia gravis: Results in 153 validated cases and 2967 diagnostic assays. J. Neurol. Neurosurg. Psychiatry. 1985;48:1246–1252. doi: 10.1136/jnnp.48.12.1246. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 199.Carr A.S., Cardwell C.R., McCarron P.O., McConville J. A systematic review of population based epidemiological studies in Myasthenia Gravis. BMC Neurol. 2010;10:46. doi: 10.1186/1471-2377-10-46. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 200.Batocchi A.P., Evoli A., Palmisani M.T., Lo Monaco M., Bartoccioni M., Tonali P. Early-onset myasthenia gravis: Clinical characteristics and response to therapy. Eur J. Pediatr. 1990;150:66–68. doi: 10.1007/BF01959485. [DOI] [PubMed] [Google Scholar]
- 201.Aarli J.A. Late-onset myasthenia gravis: A changing scene. Arch. Neurol. 1999;56:25–27. doi: 10.1001/archneur.56.1.25. [DOI] [PubMed] [Google Scholar]
- 202.Howard J., Jr. F. Myasthenia gravis: The role of complement at the neuromuscular junction. Ann. N. Y. Acad. Sci. 2018;1412:113–128. doi: 10.1111/nyas.13522. [DOI] [PubMed] [Google Scholar]
- 203.Eymard B. Anticorps dans la myasthénie. Rev. Neurol. 2009;165:137–143. doi: 10.1016/j.neurol.2008.11.020. [DOI] [PubMed] [Google Scholar]
- 204.Burden S.J., Yumoto N., Zhang W. The role of MuSK in synapse formation and neuromuscular disease. Cold Spring Harb. Perspect. Biol. 2013;5:a009167. doi: 10.1101/cshperspect.a009167. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 205.Matthews I., Chen S., Hewer R., McGrath V., Furmaniak J., Rees Smith B. Muscle-specific receptor tyrosine kinase autoantibodies--a new immunoprecipitation assay. Clin. Chim. Acta. 2004;348:95–99. doi: 10.1016/j.cccn.2004.05.008. [DOI] [PubMed] [Google Scholar]
- 206.Han J., Zhang J., Li M., Zhang Y., Lv J., Zhao X., Wang S., Wang L., Yang H., Han S., et al. A novel MuSK cell-based myasthenia gravis diagnostic assay. J. Neuroimmunol. 2019;337:577076. doi: 10.1016/j.jneuroim.2019.577076. [DOI] [PubMed] [Google Scholar]
- 207.Tsonis A.I., Zisimopoulou P., Lazaridis K., Tzartos J., Matsigkou E., Zouvelou V., Mantegazza R., Antozzi C., Andreetta F., Evoli A., et al. MuSK autoantibodies in myasthenia gravis detected by cell based assay--A multinational study. J. Neuroimmunol. 2015;284:10–17. doi: 10.1016/j.jneuroim.2015.04.015. [DOI] [PubMed] [Google Scholar]
- 208.Buckley C., Newsom-Davis J., Willcox N., Vincent A. Do titin and cytokine antibodies in MG patients predict thymoma or thymoma recurrence? Neurology. 2001;57:1579–1582. doi: 10.1212/WNL.57.9.1579. [DOI] [PubMed] [Google Scholar]
- 209.Yamamoto A.M., Gajdos P., Eymard B., Tranchant C., Warter J.-M., Gomez L., Bourquin C., Bach J.-F., Garchon H.-J. Anti-Titin Antibodies in Myasthenia Gravis: Tight Association With Thymoma and Heterogeneity of Nonthymoma Patients. Arch. Neurol. 2001;58:885–890. doi: 10.1001/archneur.58.6.885. [DOI] [PubMed] [Google Scholar]
- 210.Gambino C.M., Agnello L., Lo Sasso B., Giglio R.V., Di Stefano V., Candore G., Pappalardo E.M., Ciaccio A.M., Brighina F., Vidali M., et al. The role of serum free light chain as biomarker of Myasthenia Gravis. Clin. Chim. Acta. 2022;528:29–33. doi: 10.1016/j.cca.2022.01.004. [DOI] [PubMed] [Google Scholar]
- 211.Guptill J.T., Sanders D.B., Evoli A. Anti-MuSK antibody myasthenia gravis: Clinical findings and response to treatment in two large cohorts. Muscle Nerve. 2011;44:36–40. doi: 10.1002/mus.22006. [DOI] [PubMed] [Google Scholar]
- 212.Nelke C., Stascheit F., Eckert C., Pawlitzki M., Schroeter C.B., Huntemann N., Mergenthaler P., Arat E., Öztürk M., Foell D., et al. Independent risk factors for myasthenic crisis and disease exacerbation in a retrospective cohort of myasthenia gravis patients. J. Neuroinflamm. 2022;19:89. doi: 10.1186/s12974-022-02448-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 213.Di Stefano V., Alonge P., Rini N., Militello M., Lupica A., Torrente A., Brighina F. Efgartigimod beyond myasthenia gravis: The role of FcRn-targeting therapies in stiff-person syndrome. J. Neurol. 2023 doi: 10.1007/s00415-023-11970-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 214.Lu Y., Wang C., Chen Z., Zhao H., Chen J., Liu X., Kwan Y., Lin H., Ngai S.M. Serum metabolomics for the diagnosis and classification of myasthenia gravis. Metabolomics. 2011;8:704–713. doi: 10.1007/s11306-011-0364-6. [DOI] [Google Scholar]
- 215.Ashida S., Ochi H., Hamatani M., Fujii C., Kimura K., Okada Y., Hashi Y., Kawamura K., Ueno H., Takahashi R., et al. Immune Skew of Circulating Follicular Helper T Cells Associates With Myasthenia Gravis Severity. Neurol.-Neuroimmunol. Neuroinflamm. 2021;8:e945. doi: 10.1212/NXI.0000000000000945. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 216.Stascheit F., Hotter B., Hoffmann S., Kohler S., Lehnerer S., Sputtek A., Meisel A. Calprotectin as potential novel biomarker in myasthenia gravis. J. Transl. Autoimmun. 2021;4:100111. doi: 10.1016/j.jtauto.2021.100111. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 217.Punga A.R., Punga T. Circulating microRNAs as potential biomarkers in myasthenia gravis patients. Ann. N. Y. Acad. Sci. 2018;1412:33–40. doi: 10.1111/nyas.13510. [DOI] [PubMed] [Google Scholar]
- 218.Leite M.I., Jacob S., Viegas S., Cossins J., Clover L., Morgan B.P., Beeson D., Willcox N., Vincent A. IgG1 antibodies to acetylcholine receptors in ‘seronegative’ myasthenia gravis†. Brain. 2008;131:1940–1952. doi: 10.1093/brain/awn092. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 219.McConville J., Farrugia M.E., Beeson D., Kishore U., Metcalfe R., Newsom-Davis J., Vincent A. Detection and characterization of MuSK antibodies in seronegative myasthenia gravis. Ann. Neurol. 2004;55:580–584. doi: 10.1002/ana.20061. [DOI] [PubMed] [Google Scholar]
- 220.Vinciguerra C., Bevilacqua L., Lupica A., Ginanneschi F., Piscosquito G., Rini N., Rossi A., Barone P., Brighina F., Di Stefano V. Diagnosis and Management of Seronegative Myasthenia Gravis: Lights and Shadows. Brain Sci. 2023;13:1286. doi: 10.3390/brainsci13091286. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 221.Vincent A. Using AChR antibody titres to predict treatment responses in myasthenia gravis. J. Neurol. Neurosurg. Psychiatry. 2021;92:915. doi: 10.1136/jnnp-2021-326480. [DOI] [PubMed] [Google Scholar]
- 222.Kojima Y., Uzawa A., Ozawa Y., Yasuda M., Onishi Y., Akamine H., Kawaguchi N., Himuro K., Noto Y.I., Mizuno T., et al. Rate of change in acetylcholine receptor antibody levels predicts myasthenia gravis outcome. J. Neurol. Neurosurg. Psychiatry. 2021;92:963–968. doi: 10.1136/jnnp-2020-325511. [DOI] [PubMed] [Google Scholar]
- 223.Rider L.G., Ruperto N., Pistorio A., Erman B., Bayat N., Lachenbruch P.A., Rockette H., Feldman B.M., Huber A.M., Hansen P., et al. 2016 ACR-EULAR adult dermatomyositis and polymyositis and juvenile dermatomyositis response criteria—Methodological aspects. Rheumatology. 2017;56:1884–1893. doi: 10.1093/rheumatology/kex226. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 224.Lundberg I.E., Fujimoto M., Vencovsky J., Aggarwal R., Holmqvist M., Christopher-Stine L., Mammen A.L., Miller F.W. Idiopathic inflammatory myopathies. Nat. Rev. Dis. Primers. 2021;7:86. doi: 10.1038/s41572-021-00321-x. [DOI] [PubMed] [Google Scholar]
- 225.Volochayev R., Csako G., Wesley R., Rider L.G., Miller F.W. Laboratory Test Abnormalities are Common in Polymyositis and Dermatomyositis and Differ Among Clinical and Demographic Groups. Open Rheumatol. J. 2012;6:54–63. doi: 10.2174/1874312901206010054. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 226.Nakashima R. Clinical significance of myositis-specific autoantibodies. Immunol. Med. 2018;41:103–112. doi: 10.1080/25785826.2018.1531188. [DOI] [PubMed] [Google Scholar]
- 227.Srivastava P., Dwivedi S., Misra R. Myositis-specific and myositis-associated autoantibodies in Indian patients with inflammatory myositis. Rheumatol. Int. 2016;36:935–943. doi: 10.1007/s00296-016-3494-3. [DOI] [PubMed] [Google Scholar]
- 228.Van Horebeek N., Vulsteke J.B., Bossuyt X., Claeys K.G., Dillaerts D., Poesen K., Lenaerts J., Van Damme P., Blockmans D., De Haes P., et al. Detection of multiple myositis-specific autoantibodies in unique patients with idiopathic inflammatory myopathy: A single centre-experience and literature review: Systematic review. Semin. Arthritis Rheum. 2021;51:486–494. doi: 10.1016/j.semarthrit.2021.03.012. [DOI] [PubMed] [Google Scholar]
- 229.Bonroy C., Piette Y., Allenbach Y., Bossuyt X., Damoiseaux J. Positioning of myositis-specific and associated autoantibody (MSA/MAA) testing in disease criteria and routine diagnostic work-up. J. Transl. Autoimmun. 2022;5:100148. doi: 10.1016/j.jtauto.2022.100148. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 230.Reed A.M., Crowson C.S., Hein M., de Padilla C.L., Olazagasti J.M., Aggarwal R., Ascherman D.P., Levesque M.C., Oddis C.V. Biologic predictors of clinical improvement in rituximab-treated refractory myositis. BMC Musculoskelet Disord. 2015;16:257. doi: 10.1186/s12891-015-0710-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 231.Fiorentino D.F., Chung L.S., Christopher-Stine L., Zaba L., Li S., Mammen A.L., Rosen A., Casciola-Rosen L. Most patients with cancer-associated dermatomyositis have antibodies to nuclear matrix protein NXP-2 or transcription intermediary factor 1γ. Arthritis Rheum. 2013;65:2954–2962. doi: 10.1002/art.38093. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 232.Bobirca A., Alexandru C., Musetescu A.E., Bobirca F., Florescu A.T., Constantin M., Tebeica T., Florescu A., Isac S., Bojinca M., et al. Anti-MDA5 Amyopathic Dermatomyositis-A Diagnostic and Therapeutic Challenge. Life. 2022;12:1108. doi: 10.3390/life12081108. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 233.Marco J.L., Collins B.F. Clinical manifestations and treatment of antisynthetase syndrome. Best Pr. Res. Clin. Rheumatol. 2020;34:101503. doi: 10.1016/j.berh.2020.101503. [DOI] [PubMed] [Google Scholar]
- 234.Christopher-Stine L., Casciola-Rosen L.A., Hong G., Chung T., Corse A.M., Mammen A.L. A novel autoantibody recognizing 200-kd and 100-kd proteins is associated with an immune-mediated necrotizing myopathy. Arthritis Rheum. 2010;62:2757–2766. doi: 10.1002/art.27572. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 235.Shen Y.W., Zhang Y.M., Huang Z.G., Wang G.C., Peng Q.L. Increased Levels of Soluble CD206 Associated with Rapidly Progressive Interstitial Lung Disease in Patients with Dermatomyositis. Mediat. Inflamm. 2020;2020:7948095. doi: 10.1155/2020/7948095. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 236.Peng Q.-L., Zhang Y.-M., Liang L., Liu X., Ye L.-F., Yang H.-B., Zhang L., Shu X.-M., Lu X., Wang G.-C. A high level of serum neopterin is associated with rapidly progressive interstitial lung disease and reduced survival in dermatomyositis. Clin. Exp. Immunol. 2020;199:314–325. doi: 10.1111/cei.13404. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 237.Lilleker J., Murphy S., Cooper R. Selected aspects of the current management of myositis. Adv. Musculoskelet Dis. 2016;8:136–144. doi: 10.1177/1759720X16655126. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 238.Leuzzi G., Meacci E., Cusumano G., Cesario A., Chiappetta M., Dall’armi V., Evoli A., Costa R., Lococo F., Primieri P., et al. Thymectomy in myasthenia gravis: Proposal for a predictive score of postoperative myasthenic crisis. Eur. J. Cardiothorac Surg. 2014;45:e76–e88. doi: 10.1093/ejcts/ezt641. discussion e88. [DOI] [PubMed] [Google Scholar]
- 239.Wei B., Lu G., Zhang Y. Predictive factors for postoperative myasthenic crisis in patients with myasthenia gravis. Interdiscip. Cardiovasc. Thorac. Surg. 2023;36 doi: 10.1093/icvts/ivad040. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 240.Di Stefano V., Tubiolo C., Gagliardo A., Presti R.L., Montana M., Todisco M., Lupica A., Caimi G., Tassorelli C., Fierro B., et al. Metalloproteinases and Tissue Inhibitors in Generalized Myasthenia Gravis. A Preliminary Study. Brain Sci. 2022;12:1439. doi: 10.3390/brainsci12111439. [DOI] [PMC free article] [PubMed] [Google Scholar]