Clinical Diagnosis of Myelin Oligodendrocyte Glycoprotein Antibodies Based on CHO Flow Cytometry Live Cell-based Assay

Clinical Diagnosis of Myelin Oligodendrocyte Glycoprotein Antibodies Based on CHO Flow Cytometry Live Cell-based Assay | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Clinical Diagnosis of Myelin Oligodendrocyte Glycoprotein Antibodies Based on CHO Flow Cytometry Live Cell-based Assay Weiwei Zhang, Juli Gan, Hao Lu, Yiran Sun, Zehai Zhu, Junjuan Mao, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6297113/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background In this study, two cell lines, CHO and HEK293, which overexpress the full-length protein of MOG, were used to evaluate the diagnostic performance of the two cell lines in the detection of serum MOG antibodies in patients with MOGAD (MOG Antibody Disease) under different titers and CBA method. Methods Sera were collected from 36 suspected patients with clinical manifestations of MOGAD but not yet subjected to antibody assay, and the collected sera were subjected to CBA-IF (cell-based assay-immunofluorescence) and CBA-FC (cell-based assay-flow cytometry) using two cell lines, CHO and HEK293, which overexpressed MOG. Five different dilutions (1:10, 1:32, 1:100, 1:320, and 1:640) were used for both CBA-IF and CBA-FC methods for sensitivity and consistency testing. X2 test was used for gender and age. Results MOG-IgG was detected in the sera of 30 patients consistent with the clinical manifestations of multiple sclerosis, autoimmune encephalomyelitis, and optic neuromyelitis, and serum MOG-IgG was detected as a negative result in another 6 patients, including two patients who tested positive for antibody to aquaporin-4 (AQP4-IgG) and negative for MOG-IgG. The results of CBA-FC and CBA-IF results had 84% concordance and the CBA-IF titers obtained by endpoint dilution correlated with the CBA-FC titers. The highest serum dilution resulted in increased CBA-FC sensitivity but decreased specificity. Conclusion The present study demonstrated that the sensitivity of CBA-FC detection of MOG antibody using CHO cell line at antibody titer of 1:100 was higher than using 293 cell line. CHO cell line is thus expected to be further applied in the clinic. In contrast, CBA-FC has a slight advantage over CBA-IF in the detection of MOG antibodies in certain titers and can be used as a diagnostic technique for MOG-IgG in clinical practice. In addition, the combination of the two techniques can be used as a tool to differentiate non-specific binding and to overcome the limitations of a single assay in certain specific situations. Myelin oligodendrocyte glycoprotein MOGAD CHO cells HEK293 cells CBA-IF CBA-FC Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Myelin Oligodendrocyte Glycoprotein (MOG) is a highly immunogenic component on the outer surface of myelin in the Central Nervous System (CNS) (1). Its antibody, anti-MOG IgG (MOG-IgG), has been demonstrated to be associated with the development of MOG-IgG Associated Disorders (MOGAD), including Multiple Sclerosis (MS) and myelitis (2-5), and has become one of the biological diagnostic biomarkers for MOGAD which is a CNS autoimmune disorder with a broad clinical spectrum, with the most common phenotype being Optic Neuritis (ON) followed by Acute Disseminated Encephalomyelitis (ADEM) and Transverse Myelitis (TM). The prevalence of MOGAD is approximately 1.3–2.5 per 100,000, with an annual incidence of 3.4–4.8 per 100,000 (6). The clinical phenotypes of MOGAD may overlap with MS and aquaporin-4-IgG positive (AQP4-IgG + ) Neuromyelitis Optica Spectrum Disorder (NMOSD). Therefore, accurate diagnostic methods are critical to differentiate these diseases and guide appropriate therapeutic strategies. MOG-IgG can be categorized into pathogenic and non-pathogenic forms(7, 8). Pathogenic MOG-IgG specifically recognizes conformational epitopes of MOG (e.g., the N-terminal extracellular domain rather than linear epitopes), leading to extensive demyelination. Additionally, high-titer MOG-IgG antibodies more readily penetrate the Blood-Brain Barrier (BBB), bind to target antigens, and trigger inflammatory responses(9, 10). Non-pathogenic antibodies target linear epitopes (e.g., the C-terminal or intracellular domains of MOG). If antibody titers are low or affinity is poor, these antibodies fail to penetrate the BBB or effectively bind to target antigens(11, 12). Initially, MOG-IgG detection relied on Enzyme-Linked Immunosorbent Assays (ELISA) or immunoprecipitation techniques, which had limitations in distinguishing conformational from linear epitopes, often resulting in false-positive outcomes(13, 14). Currently, the Cell-Based Assay (CBA) using HEK293 cells that expresses full-length human MOG protein in its native conformation enables precise detection of pathogenic MOG-IgG targeting conformation-dependent epitopes(15). Compared to traditional ELISA or immunoprecipitation, CBA demonstrates a sensitivity exceeding 90% and specificity over 95%, significantly reducing cross-reactivity with other myelin proteins (e.g., AQP4) (13, 16). The cell-based immunofluorescence assay (CBA-IF) is now widely regarded as the gold standard for MOGAD diagnosis. However, its semi-quantitative nature and operator-dependent interpretation may introduce human bias, even when performed by experienced personnel(17, 18). Subsequently, flow cytometry-based assays (CBA-FC) emerged as a more sensitive and specific alternative method for detecting autoantibodies(19, 20). Flow Cytometry-Based Assays (CBA-FC) employ HEK293 cells transfected with enhanced fluorescently labeled full-length human MOG cDNA to express correctly folded MOG epitopes on the cell surface(21), thereby identifying pathogenic antibodies. CBA-FC is an objective, quantitative, and automated flow cytometry-based technique with higher precision than CBA-IF and minimized human interference. A recent multicenter double-blind study comparing live-cell CBA, fixed-cell CBA, and flow cytometry in detecting MOG antibodies in cerebrospinal fluid from patients with CNS inflammatory demyelinating diseases reported higher positive predictive values for live-cell CBA (100%) and flow cytometry (95.5%) than fixed-cell CBA (82.1%), enhancing clinical diagnostic utility (references). However, CBA-FC requires stringent standardization of flow cytometry parameters, as variations in equipment and timing may significantly affect results. Analytically, MOG-IgG detection via CBA-FC typically involves evaluating the ratio or difference in Mean Fluorescence Intensity (MFI) between transfected and untransfected cells. Fluorescence signals may vary due to MOG expression levels and secondary antibody usage. Despite advancements in diagnostic methodologies, variability persists across antibody testing centers, necessitating cautious interpretation of results. The diagnosis of MOGAD primarily relies on clinical manifestations, neuroimaging findings, and the presence of MOG-IgG antibodies. However, the heterogeneous clinical spectrum of MOGAD—encompassing ADEM, ON, myelitis, and atypical variants such as meningoencephalitis and brainstem encephalitis(22-24)—poses challenges in differentiating it from other demyelinating disorders, particularly MS and AQP4-IgG - seropositive NMOSD (25, 26). Consequently, serological detection of MOG-IgG remains pivotal for MOGAD diagnosis(12, 27). Expert consensus recognizes MOG-IgG as a key diagnostic biomarker for MOGAD, with antibody titers correlating with disease severity (28). High-titer serum MOG-IgG is considered a robust diagnostic indicator. Nevertheless, low-titer results require careful interpretation, as false-positive MOG-IgG findings have been reported in other conditions, including MS and AQP4-associated NMOSD (29, 30). Studies demonstrate significantly higher false-positive rates in MS patients than in high-titer cases, reflecting poor inter-laboratory concordance for low-titer samples and complicating their clinical interpretation interpretation(29, 31). Thus, while the diagnostic utility of MOG-IgG is well-established, nuanced evaluation of antibody titers remains clinically complex (32). Current clinical MOG antibody testing predominantly uses HEK293 cell lines(33, 34), which face challenges such as background noise and under detection in low-titer samples(35-37). To enhance positive detection rates in low-titer scenarios, this study explores Chinese Hamster Ovary (CHO) cells—known for easier cultivation, high protein yield, and efficient post-translational modifications—as an alternative tool. By comparing the performance of CBA-IF and CBA-FC using two MOG-expressing cell lines (HEK293 and CHO) in suspected MOGAD patients with compatible clinical features, this research aims to elucidate the advantages of CHO cell-based assays and provide novel insights for clinical diagnostic technologies. Materials and Methods Participants From December 2022 to December 2023, a total of 36 patients clinically suspected of having MOGAD (Ethics Approval Number: HMYY-RP-EC09-2023-01) were enrolled in this study at Sichuan Provincial People's Hospital, the First Affiliated Hospital of Chengdu Medical College. Their clinical presentations conformed to the 2020 “Chinese Expert Consensus on Diagnosis and Treatment of Disorders Associated with Anti-Myelin Oligodendrocyte Glycoprotein Immunoglobulin G Antibodies” and the latest international diagnostic guidelines. Patients whose data were incomplete or lost during follow-up were excluded (specific inclusion and exclusion criteria listed here). The study was conducted in accordance with the Declaration of Helsinki, and all participants provided informed consent with their information anonymized. All samples were analyzed by individuals who did not have access to clinical data. Transfection of Human Embryonic Kidney 293 (HEK293) Cells and Chinese Hamster Ovary (CHO) Cells For Live-CBA-IF, HEK293 cells (ATCC, LGC Standards GmbH, Wessels, Germany) were cultured in Dulbecco’s Modified Eagle Medium (DMEM) supplemented with 10% fetal bovine serum (FBS) (Gibco, Life Technologies, NY, USA, catalog number 12657-029), 1% penicillin/streptomycin (100 U/mL) (Gibco, NY, USA, catalog number 15140-122), and 0.1% gentamicin (100 mg/mL) (Gibco, Life Technologies, NY, USA, catalog number 15710-064) in a humidified incubator at 5% CO 2 and 37°C until they reached 60% confluence. CHO cells (ATCC, LGC Standards GmbH, Wessels, Germany) were cultured in Dulbecco’s Modified Eagle Medium/Nutrient Mixture F-12（DMEM/F-12） supplemented with 10% fetal bovine serum (FBS) (Gibco, Life Technologies, NY, USA, catalog number 12657-029), 1% penicillin/streptomycin (100 U/mL) (Gibco, NY, USA, catalog number 15140-122), and 0.1% gentamicin (100 mg/mL) (Gibco, Life Technologies, NY, USA, catalog number 15710-064) in a humidified incubator at 5% CO2 and 37°C until they reached 60% confluence. Thereafter, according to the manufacturer’s instructions, HEK293 cells and CHO cells were transfected with plasmids containing full-length human MOG (FL-MOG) α1 isoform using Fugene HD transfection reagent (Promega Corporation, WI, USA, Cat# E2311). For Live-CBA-FC, HEK293 cells and CHO cells were transfected with pIRES Ds-Red 2 expression vectors harboring the FL-MOG for the Live-CBA-IF protocol. Details of the carrier are shown in Table S1. For Live-CBA-FC, HEK293 and CHO cells were transfected with pEGFP-N1 plasmids carrying the FL-MOG fused with EGFP (MOG-EGFP). Twenty-four hours post-transfection, the cells were enzymatically dissociated with 0.05% trypsin-EDTA (Gibco, Life Technologies, NY, USA, catalog number 15400054), centrifuged, and resuspended in DMEM containing puromycin (Thermo Fisher, MO, USA, catalog number A1113803) for selection and maintenance of stably transfected cells. Western Blot (WB) To conduct the WB analysis, cells in their logarithmic growth phase are harvested. Total cellular proteins are extracted using RIPA lysis buffer. Protein quantification is performed subsequently, followed by electrophoresis through a SDS-PAGE gel. The proteins are then transferred to a PVDF membrane. A blocking step is carried out with 5% skim milk at constant temperature (37°C) for one hour on a shaking platform. The membrane is washed with TBST, after which primary antibodies (Proteintech, China, catalog number 28752-1-AP) are incubated overnight at 4°C. After thorough washing with TBST, secondary antibodies (Proteintech, China, catalog number SA00001-2) are applied at room temperature for one hour. Subsequent washes with TBST are conducted before the image is captured using Lumax Light. Immunofluorescence Microscopy For CBA-IF experiments, MOG-DsRed-transfected cells are enzymatically digested with trypsin, centrifuged, resuspended in DMEM, and placed onto slides. Overnight incubation is maintained within an incubator. Following the removal of culture medium, serum diluted at concentrations of 1:10, 1:32, 1:100, 1:320 and 1:640 is added at room temperature for one hour. Cells are washed three times with PBS, fixed with 4% paraformaldehyde, and washed again three times. Secondary antibody DyLight 594 conjugated to anti-human IgG-Fc (Abcam Scientific) is added at a dilution of 1:1000 and incubated for 40 minutes. Cells are washed three times with PBS and stained with Fluoroshield™ mounting media containing DAPI (Sigma-Aldrich). Examination under a fluorescence microscope reveals that serum positivity is determined by a cut-off value set at 1:10. For positive samples, the titer of MOG-IgG is measured through a series of threefold serial dilutions from the highest concentration. The endpoint titer is defined as the most dilute sample yielding a positive fluorescent signal. Flow Cytometry In the CBA-FC assays, five different serum dilutions (1:10, 1:32, 1:100, 1:320, and 1:640) were utilized. One million MOG-EGFP-transfected cells were collected, washed twice with PBS (pH 7.4), and incubated with patient sera at 4°C for thirty minutes. Cells were washed twice more, followed by incubation at 4°C with a secondary antibody, DyLight 594 conjugated to anti-human IgG-Fc (Thermo Scientific, Life Technologies; catalog number SA 5 -10137), at a dilution of 1:200 for another thirty minutes. Cells were washed thrice, resuspended in PBS, and analyzed using an Attune NxT flow cytometer (Thermo Scientific, Life Technologies). Each sample was evaluated in duplicate. Optimal data collection gates were established for analysis, with binding quantified as MFI. MOG-IgG titers were assessed using two methods: the ratio of MFI between cells expressing MOG and untransfected cells (rMFI) and the MFI increment (∆MFI). A cutoff value was derived from the threshold obtained using the MOG-IgG - patient cohort, calculated as the average MFI across all negative samples (rMFI and ∆MFI) plus four standard deviations. The MOG-seronegative patient cohort, defined by CBA-IF screening, comprised 3 males aged 20–25 years and 3 females aged 24–27 years. The CBA-FC MFI measured by MOG antibody negative population was added with four standard deviations as the threshold, and the serum samples of each patient were repeated for three times. Data Analysis Statistical analyses were conducted using IBM SPSS Statistics 22.0 (Armonk, NY, USA) and GraphPad Prism 5 (La Jolla, CA, USA). Flow cytometry data were analyzed using FlowJo™ Software 10 (Becton Dickinson and Company, USA). Cohen’s kappa statistic was employed to evaluate the consistency between CBA-IF and CBA-FC analyses, as well as the Spearman rank correlation coefficient assessing the relationship between CBA-IF and CBA-FC antibody titers. Receiver Operating Characteristic (ROC) curve analysis was used to determine the performance of CBA-FC in detecting blood serum MOG-IgG positivity relative to CBA-IF as a reference test. Statistical significance was considered at p-values less than 0.05. Results Patient demographics and clinical data In 36 patients, according to the CBA-IF results, the median age at onset in the Myelin Oligodendrocyte Glycoprotein IgG positive (MOG-IgG + ) group was 20 years, and 61% were female. In the MOG-IgG positive group, ON was the main disease, accounting for 55%. 7.1% had myelitis, 7% had both ON and myelitis, 29% had ADEM, and 3.6% had seizures. In the Myelin Oligodendrocyte Glycoprotein IgG negative (MOG-IgG - ) group the clinical diagnoses were as follows: 23.8% had ON, 18.5% had myelitis, 25.6% were clinically diagnosed with seronegative NMOSD, 17.7% had MS, 10.80% had rhombencephalitis, and 3.60% had other diseases. Notably, 25.6% were AQP4-IgG + in the MOG-IgG - group, and there were no AQP4-IgG + cases in the MOG-IgG + group (Table 1). Analysis of transfected MOG protein expression in HEK293 and CHO cell lines Figure 1 shows the WB of HEK293 and CHO cell lines transfected with MOG protein, and it can be found from the results of quantitative analysis in Fig. 1A WB bands and Fig. 1B that the relative expression of CHO cell lines transfected with MOG protein was significantly higher than that of HEK293 cell lines ( p <0.001), and the high expression of MOG protein has a significantly higher expression rate in the detection of MOG- IgG antibody with higher sensitivity, which is advantageous for early clinical diagnosis of patients compared with HEK293 cell line. Seropositivity analyzed by CBA-IF method We performed CBA-IF at five serum dilutions (1:10, 1:32, 1:100, 1:320, 1:640). According to the results of CBA-IF assay, out of 36 serum samples, 78.8% (n=29) were MOG-IgG + and 22.2% (n=7) were MOG-IgG - . Seven of the negative samples were below the threshold (1:10) and all had weak fluorescence emission. Figure 2A provides representative image results of CBA-IF of the same positive serum samples at two titers of 1:10 and 1:640 respectively after transfection of human full-length MOG proteins in HEK293 and CHO cell lines (Representative images with dilutions of 1:32, 1:100, and 1:320 are shown in Fig S1). It can be found that the positive luminescence intensity shown in the fluorescence image is higher at 1:10 serum dilution, and the positive luminescence shown in the fluorescence image is weak at 1:640 serum dilution. The final titer range of the MOG-IgG + group after CBA-IF assay was 1:10 to 1:640 (Figure 2B). Analysis of seropositivity by CBA-FC method Serum antibodies were detected using the CHO-MOG cell line via the CBA-FC method. Five serum dilutions (1:10, 1:32, 1:100, 1:320, 1:640) were analyzed under homogeneous conditions based on the mean fluorescence intensity (∆MFI = MFI-positive-negative cells) (Representative images with dilutions of 1:32, 1:100, and 1:320 are shown in Figure S2).The CBA-FC groups were named from 1 to 5 according to their respective acronyms: CBA-FC 1 (1:10 using ∆MFI analysis); CBA-FC 2 (1:32, using ∆MFI analysis); CBA-FC 3 (1:100, using ∆MFI analysis); CBA-FC 4 (1:320, using ∆MFI analysis); and CBA-FC 5 (1:640, using ∆MFI analysis).The MOG-IgG + group accounted for 83.3%, 58.3%, 44.4%, 11.1%, and 5.6%, respectively, in CBA-FC 1to 5. Figure 3 shows examples of sample-gated (3A), seronegative (3B), and seropositive (3C) MOG-IgG in CBA-FC. Figure3D showed that the positive and negative sample results for CBA-FC after transfection of CHO cell lines with human full-length MOG protein at two serum dilutions, 1:10 and 1:640. Under the same gating conditions, the distribution of positive and negative cell populations at the two serum dilutions was more obvious, but some false positives and false negatives inevitably existed, which may be due to non-specific binding of antibodies in the detection process or interference from other components present in the serum, so it is necessary to determine critical values to exclude the influence of non-human factors in the analysis of results. In this study, the critical values were determined by the thresholds that were determined by the mean of the MFI plus four standard deviations of a cohort of negative MOG-IgG patients (∆MFI) (Table 2). This criterion is based on the ‌normal distribution assumption‌, positing that the fluorescence intensity of negative control samples follows a normal distribution. By calculating the ‌MFI (Mean Fluorescence Intensity)‌ and ‌SD (Standard Deviation)‌ of the negative controls, the positive threshold is defined as: Cut-off = MFI (negative controls) + 4×SD (negative controls)‌. This approach excludes ‌99.99% of negative signals below the threshold‌ (statistically, 3σ covers 99.7% of data under a normal distribution, while 4σ covers 99.99%), thereby significantly reducing ‌false-positive risks‌. Comparison between CBA-FC and CBA-IF In comparing CBA-IF and CBA-FC, the results of sample detection were consistent at serum dilutions of 1:10 and 1:32 across all five dilution levels analyzed. At a dilution of 1:100, two samples showed different results; meanwhile, one sample each displayed differing results at dilutions of 1:320 and 1:640. With the established CBA-IF as a reference standard, the area under the curve (AUC) of the ROC curves were 0.872, 0.867, 0.756, 0.783, 0.710, respectively (Table 3). The sensitivity analyses of the CBA-FC1-5 were 80.0%, 70.0%, 46.7%, 66.7%, and 58.1% respectively. The specificity was 100.0%, 100.0%, 100.0%, 83.2%, and 80.1% respectively. These data indicated that sensitivity is increased at a dilution of 1:100, while specificity is enhanced at dilutions of 1:10, 1:32, and 1:100. However, as the dilution increases, specificity gradually decreases. The positive predictive values of CBA-FC 1-5 were 1.000, 0.866, 0.766, 0.633, and 0.633, and the negative predictive values were 1.000, 0.667, 0.462, 0.353, and 0.353, respectively. In figure 4, there was a strong positive correlation between the titration results obtained by immunofluorescence and the analysis results from flow cytometry, particularly at a dilution of 1:100. Analysis of titers and diagnostic results The titer and clinical diagnostic results showed that 81.5% of patients with ON were detected at low titers and 18.5% at high titers; 25.0% of patients with optic neuromyelitis were detected at low titers and 75% at high titers; 30.0% of patients with ADEM were detected at low titers and 70.0% at high titers; and an additional 30.0% of patients with ADEM were detected. Of patients with ADEM were detected in 30% at low titers and 70.0% at high titers, and one additional patient with meningitis was detected at low titers（Table 4）( p <0.05). Discussion Currently, live cell-based assays targeting the full-length native conformation of MOG are the gold standard for clinical diagnosis of MOGAD(15, 19, 38). Retrospective studies have demonstrated that early diagnosis and appropriate immunotherapy are crucial for improving clinical outcomes(39, 40). Conventional immunofluorescence (IF) assays using live HEK293 cells are often limited by human-derived interference and low sensitivity, hindering clinical diagnosis and related disease research, particularly in early disease screening and relapse prevention. Two distinct antibody incubation protocols were implemented for CBA-IF and CBA-FC, respectively, based on their differential cellular processing requirements: CBA-IF‌ typically involves cell fixation (e.g., paraformaldehyde) and permeabilization (e.g., Triton X-100) to enable antibody penetration for intracellular antigen binding, with room-temperature incubation enhancing antibody permeability. CBA-FC‌ requires cells to remain in a monodisperse state, where low-temperature incubation minimizes cellular aggregation and membrane damage. The 1-hour primary antibody incubation at room temperature in CBA-IF ensures sufficient penetration and binding to intracellular or surface antigens, whereas the 30-minute incubation for CBA-FC leverages the high sensitivity of flow cytometry to achieve efficient MOG antigen binding while reducing nonspecific interactions. CHO cells have advantages over HEK293 cells: the former enable extracellular transport of target proteins, express minimal endogenous proteins (facilitating target protein purification), and are resistant to human viral infections while allowing human-compatible glycosylation modifications(41-43). These advantages make CHO cells a preferred host for producing therapeutic proteins and antibodies(44). Using CHO cell-based assays, Jaśkiewicz et al. specifically identified serum antibodies against three major myelin autoantigens: myelin basic protein (MBP), proteolipid protein (PLP), and MOG(45). IgG autoantibody titers against membrane-bound recombinant myelin antigens were most significantly elevated for PLP but not for MBP or MOG. These findings suggest that CHO cell-based assays for recombinant myelin antigen autoantibodies may serve as a valuable serological tool for diagnosing and monitoring MS progression(45). Built on these advantages, our study utilized CHO cells transfected with full-length human MOG (CHO-MOG cell line) for serum MOG-IgG detection. Immunofluorescence (IF) and WB results (Figure 1) confirmed high and stable exogenous protein expression, enhancing MOG-IgG detection sensitivity. In comparative CBA with flow cytometry (CBA-FC) analyses of serum samples at equivalent dilutions, the CHO-MOG cell line exhibited significantly higher fluorescence values than the HEK293-MOG cell line upon MOG-IgG binding, indicating stronger antigen-antibody interaction. This suggests that CBA-FC-based MOG-IgG detection may perform better in early and relapsing MOGAD cases. Flow cytometry for live cell detection, which quantifies patient serum binding to MOG-expressing cells, is a widely used, accurate, and reliable method that eliminates human-derived interference. Lopez et al. compared a simplified CBA-FC with research-grade assays in demyelinating disease patients, reporting high concordance (98%–100%) in MOG antibody detection. The simplified assay also showed improved intra- and inter-batch error rates(46). In a study of 202 MOG-IgG-seropositive adult MOGAD patients, validated flow cytometry-based live cell assays confirmed serum MOG-IgG and epitope binding. The authors correlated assay results with epitopes, disease duration, and clinical relapses, finding that MOG-IgG titers predicted relapsing courses in most patients. Early detection and targeted treatment could minimize disability and improve long-term prognosis(47). In our study, CHO-based live cell CBA with flow cytometry (CBA-FC) and immunofluorescence (CBA-IF) were used to detect MOG-IgG. with CBA-IF as the standard, Δ median fluorescence intensity (ΔMFI) of CBA-FC method was compared across five serum dilutions (1:10, 1:32, 1:100, 1:320, and 1:640), where CBA-FC and CBA-IF showed high concordance (kappa >0.8) at high titers (1:10 and 1:32),while CBA-FC demonstrated slightly higher sensitivity than CBA-IF at lower titers, enabling positive diagnosis in low-titer MOG-IgG cases. Notably, a single false-positive result occurred at 1:640 dilution, highlighting the need for combined CBA-IF and imaging data to mitigate reduced specificity at high sensitivity. Among the five CBA-FC analyses, the 1:10 dilution (CBA-FC1) achieved the highest area under the curve (AUC), while the 1:100 dilution (CBA-FC3) offered optimal sensitivity. CBA-FC analyzed at lower serum dilutions (CBA-FC 1, 2, 3) had higher specificity.CBA-FC3 also showed strong concordance with CBA-IF titers, aligning closely with established CBA-IF protocols. Given the diversity of MOG-associated diseases, different disease courses, and confounding factors that may lead to non-specific binding in human serum, antibody titres may show variability in different patients, leading to misdiagnosis or missed diagnoses. Therefore, standardized high-sensitivity assays are critical. MOG antibody titers cannot differentiate MOGAD phenotypes(34, 38), and inconsistent definitions/methods across centers necessitate clear thresholds for low-positive cases to avoid diagnostic errors. This is vital for differentiating treatment strategies for MOGAD and AQP4-IgG + NMOSD. Prior studies suggested CBA-FC as a feasible diagnostic tool for MOG antibody detection. Our study evaluated CHO-based CBA-FC across titers, finding that ΔMFI at 1:10 dilution (CBA-FC1) correlated strongly with CBA-IF, while 1:100 dilution (CBA-FC3) maintained specificity with higher sensitivity. The optimal dilution for CBA-FC appears to be 1:100. The combination of both methods may help distinguish nonspecific binding, overcoming limitations of single assays. Despite advantages of flow cytometry over traditional methods(15, 19, 48), further arguments are needed to translate these research assays into pathology-based diagnostics due to variations in CBA-FC protocols, data analysis, and positivity thresholds. This study acknowledges limitations, including small sample size, short follow-up, retrospective design biases, and geographic sample restrictions. Future large-scale longitudinal studies with extended follow-up are needed to clarify the relationship between titers and relapse patterns. Conclusion While HEK293-based CBA remains the gold standard for MOG antibody detection, it suffers from background interference and false results. Our findings indicate that the CHO cell line-based assay vector has higher MOG expression than the HEK293 cell line, possesses a higher detection rate, and can be used as an auxiliary diagnostic technique for MOG-IgG in clinical applications. CHO cell-based CBA-FC was highly consistent with CBA-IF and had higher sensitivity than CBA-IF. Furthermore, when using 1:100 antibody titer and ΔMFI values, CBA-FC showed high concordance with CBA-IF and high sensitivity. Therefore, for patients with low-titer sera but high clinical suspicion, adopting a dual comparison of both CHO cell-based CBA-IF and CBA-FC methods at multiple testing facilities will facilitate accurate diagnosis, thus helping physicians to develop precise and effective treatment strategies. Declarations Acknowledgments We thank the patients and their families for their participation and contribution. The study was supported by Chengdu Hemer Yunyin Medical Laboratory Co. In addition, we would also like to thank Tong Peng and Shijie Ni from Sichuan University for their valuable modifications to the methodology and language of the article, respectively. Funding This project was mainly sponsored by the Chengdu Medical College-Chengdu Hemer Yunyin Medical Laboratory Co. joint fund (No. CMC Contract 2021-168 and CMC Contract 2024-565). Conflict of interest The authors declare that there are no conflicts of interest relevant to this work. Ethical approval We confirm that we have read the Journal’s position on issues involved in ethical publication and that this work is consistent with those guidelines. Approval for this study was obtained from the local institutional review boards (Ethics Approval Number: HMYY-RP-EC09-2023-01. The Ethics Committee of Chengdu HeimerYunyin medical laboratory Ltd.,China.). Written informed consent was obtained from each patient. Data availability No data was used for the research described in the article. Consent for publication Not Applicable References Reindl M, Di Pauli F, Rostásy K, Berger T. The spectrum of MOG autoantibody-associated demyelinating diseases. Nat Rev Neurol. 2013;9(8):455-61. Loos J, Pfeuffer S, Pape K, Ruck T, Luessi F, Spreer A, et al. MOG encephalomyelitis: distinct clinical, MRI and CSF features in patients with longitudinal extensive transverse myelitis as first clinical presentation. J Neurol. 2020;267(6):1632-42. Waters P, Woodhall M, O'Connor KC, Reindl M, Lang B, Sato DK, et al. MOG cell-based assay detects non-MS patients with inflammatory neurologic disease. Neurol Neuroimmunol Neuroinflamm. 2015;2(3):e89. Ramanathan S, Reddel SW, Henderson A, Parratt JD, Barnett M, Gatt PN, et al. 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Real-world clinical experience with serum MOG and AQP4 antibody testing by live versus fixed cell-based assay. Ann Clin Transl Neurol. 2025. Waters PJ, Komorowski L, Woodhall M, Lederer S, Majed M, Fryer J, et al. A multicenter comparison of MOG-IgG cell-based assays. Neurology. 2019;92(11):e1250-e5. de Mol CL, Wong Y, van Pelt ED, Wokke B, Siepman T, Neuteboom RF, et al. The clinical spectrum and incidence of anti-MOG-associated acquired demyelinating syndromes in children and adults. Mult Scler. 2020;26(7):806-14. Marchionatti A, Woodhall M, Waters PJ, Sato DK. Detection of MOG-IgG by cell-based assay: moving from discovery to clinical practice. Neurol Sci. 2021;42(1):73-80. Jarius S, Paul F, Aktas O, Asgari N, Dale RC, de Seze J, et al. MOG encephalomyelitis: international recommendations on diagnosis and antibody testing. J Neuroinflammation. 2018;15(1):134. Jarius S, Pellkofer H, Siebert N, Korporal-Kuhnke M, Hümmert MW, Ringelstein M, et al. Cerebrospinal fluid findings in patients with myelin oligodendrocyte glycoprotein (MOG) antibodies. Part 1: Results from 163 lumbar punctures in 100 adult patients. J Neuroinflammation. 2020;17(1):261. Matsumoto Y, Kaneko K, Takahashi T, Takai Y, Namatame C, Kuroda H, et al. Diagnostic implications of MOG-IgG detection in sera and cerebrospinal fluids. Brain. 2023;146(9):3938-48. Bartels F, Lu A, Oertel FC, Finke C, Paul F, Chien C. Clinical and neuroimaging findings in MOGAD-MRI and OCT. Clin Exp Immunol. 2021;206(3):266-81. Salama S, Khan M, Shanechi A, Levy M, Izbudak I. MRI differences between MOG antibody disease and AQP4 NMOSD. Mult Scler. 2020;26(14):1854-65. Cacciaguerra L, Flanagan EP. Updates in NMOSD and MOGAD Diagnosis and Treatment: A Tale of Two Central Nervous System Autoimmune Inflammatory Disorders. Neurol Clin. 2024;42(1):77-114. Hu X. Chinese expert consensus on diagnosis and treatment of MOG-IgG associated disorders. Chinese Journal of Neuroimmunology and Neurology. 2020;27(2):86-95. Sechi E, Cacciaguerra L, Chen JJ, Mariotto S, Fadda G, Dinoto A, et al. Myelin Oligodendrocyte Glycoprotein Antibody-Associated Disease (MOGAD): A Review of Clinical and MRI Features, Diagnosis, and Management. Front Neurol. 2022;13:885218. Tisavipat N, Stiebel-Kalish H, Palevski D, Bialer OY, Moss HE, Chaitanuwong P, et al. Acute Optic Neuropathy in Older Adults: Differentiating Between MOGAD Optic Neuritis and Nonarteritic Anterior Ischemic Optic Neuropathy. Neurol Neuroimmunol Neuroinflamm. 2024;11(3):e200214. Perez-Giraldo G, Caldito NG, Grebenciucova E. Transverse myelitis in myelin oligodendrocyte glycoprotein antibody-associated disease. Front Neurol. 2023;14:1210972. Risi M, Greco G, Masciocchi S, Rigoni E, Colombo E, Businaro P, et al. MOG-IgG testing strategies in accordance with the 2023 MOGAD criteria: a clinical-laboratory assessment. J Neurol. 2024;271(5):2840-3. Jitprapaikulsan J, Chen JJ, Flanagan EP, Tobin WO, Fryer JP, Weinshenker BG, et al. Aquaporin-4 and Myelin Oligodendrocyte Glycoprotein Autoantibody Status Predict Outcome of Recurrent Optic Neuritis. Ophthalmology. 2018;125(10):1628-37. Cobo-Calvo A, Sepúlveda M, d'Indy H, Armangué T, Ruiz A, Maillart E, et al. Usefulness of MOG-antibody titres at first episode to predict the future clinical course in adults. J Neurol. 2019;266(4):806-15. Graham FL, Smiley J, Russell WC, Nairn R. Characteristics of a human cell line transformed by DNA from human adenovirus type 5. J Gen Virol. 1977;36(1):59-74. Li J, Wei S, Cao C, Chen K, He H, Gao G. Retrovectors packaged in CHO cells to generate GLP-1-Fc stable expression CHO cell lines. Electron J Biotechnol. 2019;41:56-9. Chin CL, Goh JB, Srinivasan H, Liu KI, Gowher A, Shanmugam R, et al. A human expression system based on HEK293 for the stable production of recombinant erythropoietin. Sci Rep. 2019;9(1):16768. Tea F, Lopez JA, Ramanathan S, Merheb V, Lee FXZ, Zou A, et al. Characterization of the human myelin oligodendrocyte glycoprotein antibody response in demyelination. Acta Neuropathol Commun. 2019;7(1):145. Jarius S, Ruprecht K, Kleiter I, Borisow N, Asgari N, Pitarokoili K, et al. MOG-IgG in NMO and related disorders: a multicenter study of 50 patients. Part 2: Epidemiology, clinical presentation, radiological and laboratory features, treatment responses, and long-term outcome. J Neuroinflammation. 2016;13(1):280. Ramanathan S, Mohammad S, Tantsis E, Nguyen TK, Merheb V, Fung VSC, et al. Clinical course, therapeutic responses and outcomes in relapsing MOG antibody-associated demyelination. J Neurol Neurosurg Psychiatry. 2018;89(2):127-37. Hu J, Han J, Li H, Zhang X, Liu LL, Chen F, et al. Human Embryonic Kidney 293 Cells: A Vehicle for Biopharmaceutical Manufacturing, Structural Biology, and Electrophysiology. Cells Tissues Organs. 2018;205(1):1-8. Stepanenko AA, Dmitrenko VV. HEK293 in cell biology and cancer research: phenotype, karyotype, tumorigenicity, and stress-induced genome-phenotype evolution. Gene. 2015;569(2):182-90. Zehetner L, Széliová D, Kraus B, Graninger M, Zanghellini J, Hernandez Bort JA. Optimizing VLP production in gene therapy: Opportunities and challenges for in silico modeling. Biotechnol J. 2023;18(7):e2200636. Fischer S, Handrick R, Otte K. The art of CHO cell engineering: A comprehensive retrospect and future perspectives. Biotechnol Adv. 2015;33(8):1878-96. Jaśkiewicz E, Michałowska-Wender G, Pyszczek A, Wender M. Recombinant forms of myelin antigens expressed on Chinese hamster ovary (CHO) cells as a tool for identification of autoantibodies in serum of multiple sclerosis patients. Folia Neuropathol. 2010;48(1):45-8. Lopez JA, Houston SD, Tea F, Merheb V, Lee FXZ, Smith S, et al. Validation of a Flow Cytometry Live Cell-Based Assay to Detect Myelin Oligodendrocyte Glycoprotein Antibodies for Clinical Diagnostics. J Appl Lab Med. 2022;7(1):12-25. Liyanage G, Trewin BP, Lopez JA, Andersen J, Tea F, Merheb V, et al. The MOG antibody non-P42 epitope is predictive of a relapsing course in MOG antibody-associated disease. J Neurol Neurosurg Psychiatry. 2024;95(6):544-53. Reindl M, Schanda K, Woodhall M, Tea F, Ramanathan S, Sagen J, et al. International multicenter examination of MOG antibody assays. Neurol Neuroimmunol Neuroinflamm. 2020;7(2). Tables TABLE1|Patient clinical data Sample of the CBA-IF results MOG-IgG testing(N=36) P-vaule MOG-IgG + (N=30) MOG-IgG - (N=6) Age of onset (age), median 20.0 20.5 0.038 Female, N (%) 62.0 38.0 Clinical diagnostic results ON (%) 55.0 23.8 Myelitis (%) 0.1 0.2 ON and myelitis (%) 0.1 — NMOSD (%) — 0.3 ADEM (%) 0.3 — MS (%) — 10.1 Encephalitis/seizures (%) 6.5 — Others (%) — 3.6 CBA-IF，Cell-Based Immunofluorescence Assay；MOG-IgG, Anti-Myelin Oligodendrocyte Glycoprotein; MOG-IgG + , Myelin Oligodendrocyte Glycoprotein IgG positive; MOG-IgG - , Myelin Oligodendrocyte Glycoprotein IgG negative; ON, Optic Neuritis; NMOSD, Neuromyelitis Optica Spectrum Disorder; ADEM, Acute Disseminated Encephalomyelitis; MS, Multiple Sclerosis. TABLE 2 | Data of CBA-FC analysis Analyses Cutoff MOG-IgG + MOG-IgG - MFI (range)positive samples CBA-FC1 Dilution 1:10 ΔMFI 1070 30 (83.4%) 6 (16.6%) 10272 (1070) CBA-FC2 Dilution 1:32 ΔMFI 680 26 (72.2%) 9 (17.8%) 11420 (696) CBA-FC3 Dilution 1:100 ΔMFI 782 23 (63.8%) 13 (36.0%) 11706 (782) CBA-FC4 Dilution 1:320 ΔMFI 309 19 (52.7%) 17 (47.3%) 5369 (309) CBA-FC5 Dilution 1:640 ΔMFI 277 19 (52.7%) 17 (47.3%) 3535 (277) MOG-IgG + , Myelin Oligodendrocyte Glycoprotein IgG positive; MOG-IgG - , Myelin Oligodendrocyte Glycoprotein IgG negative; MFI, mean fluorescent intensity; ΔMFI, delta MFI. TABLE 3| Data analysis comparing CBA-IF and CBA-FC CBA-FC1 95%CI CBA-FC2 95%CI CBA-FC3 95%CI CBA-FC4 95%CI CBA-FC5 95%CI (AUC) of the RoC 0.872 0.806 to 0.989 0.867 0.740 to 0.994 0.756 0.864 to 0.947 0.783 0.796 to 0.971 0.710 0.737 to 0.883 Sensitivity 0.816 0.722 0.887 0.667 0.581 Specificity 1.000 1.000 1.000 0.832 0.801 Positive Predictive Value 1.000 0.866 0.766 0.633 0.633 Negative Predictive Value 1.000 0.667 0.462 0.353 0.353 Kappa coefficient values 0.821 0.809 0.672 0.722 0.770 Spearman's coefficient values 0.811 0.772 0.711 0.793 0.787 TABLE4|Analysis of titers and diagnostic results Low titer High titer Total P -value Diagnostic results ON 13 (81.5%) 3 (18.5%) 16 0.026 NMO 1 (25.0%) 3 (75.0%) 4 ADEM 3 (30.0%) 7 (70.0%) 10 Brain fever 1 (100.0%) - 1 Total 18（58.0%） 13 (42.0%) 31 ON, Optic Neuritis; NMO, Neuromyelitis Optica; ADEM, Acute Disseminated Encephalomyelitis. Additional Declarations No competing interests reported. Supplementary Files TableS1vector.pdf FigureS1.jpg FigureS2.tif wb.pdf Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6297113","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":466087576,"identity":"2c53ca08-79d9-4bd4-9a40-82c463bc974b","order_by":0,"name":"Weiwei Zhang","email":"","orcid":"","institution":"Chengdu Medical College","correspondingAuthor":false,"prefix":"","firstName":"Weiwei","middleName":"","lastName":"Zhang","suffix":""},{"id":466087577,"identity":"1972a924-9cf2-4df5-8f28-d25ca98657eb","order_by":1,"name":"Juli Gan","email":"","orcid":"","institution":"Chengdu Medical College","correspondingAuthor":false,"prefix":"","firstName":"Juli","middleName":"","lastName":"Gan","suffix":""},{"id":466087578,"identity":"c88f732e-02f4-4764-963f-f007dd8cc85c","order_by":2,"name":"Hao Lu","email":"","orcid":"","institution":"Chengdu Medical College","correspondingAuthor":false,"prefix":"","firstName":"Hao","middleName":"","lastName":"Lu","suffix":""},{"id":466087579,"identity":"19b97336-a7ea-4a4e-8daa-a9805d93d2cb","order_by":3,"name":"Yiran Sun","email":"","orcid":"","institution":"Chengdu Medical College","correspondingAuthor":false,"prefix":"","firstName":"Yiran","middleName":"","lastName":"Sun","suffix":""},{"id":466087580,"identity":"cd5c1cca-67de-424f-82cd-e276b1a7b85e","order_by":4,"name":"Zehai Zhu","email":"","orcid":"","institution":"Chengdu Medical College","correspondingAuthor":false,"prefix":"","firstName":"Zehai","middleName":"","lastName":"Zhu","suffix":""},{"id":466087581,"identity":"f4c895d1-0fb7-496f-abd5-55f62b304315","order_by":5,"name":"Junjuan Mao","email":"","orcid":"","institution":"Chengdu HeimerYunyin medical laboratory Ltd.","correspondingAuthor":false,"prefix":"","firstName":"Junjuan","middleName":"","lastName":"Mao","suffix":""},{"id":466087582,"identity":"fb3c9bc9-3555-4b60-aecc-36717ceef8d0","order_by":6,"name":"Xianwei Zou","email":"","orcid":"","institution":"Chengdu HeimerYunyin medical laboratory Ltd.","correspondingAuthor":false,"prefix":"","firstName":"Xianwei","middleName":"","lastName":"Zou","suffix":""},{"id":466087583,"identity":"7db976f2-c897-44f2-88c1-39e387f2b706","order_by":7,"name":"Bin Liu","email":"","orcid":"","institution":"The Third People's Hospital of Hefei (The Third Clinical College of Anhui Medical University)","correspondingAuthor":false,"prefix":"","firstName":"Bin","middleName":"","lastName":"Liu","suffix":""},{"id":466087584,"identity":"2c57165e-ea53-4e03-af9c-537bf10867d5","order_by":8,"name":"Quekun Peng","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5klEQVRIiWNgGAWjYBADAwYG5gMQ5gHitbAlkKyFx4A4LebsvYdfvG2zMTa43fPx040aBjm+GwmMHz7m4NZi2XMuzXJuW5qZwZ2zm6VzjjEYS95IYJacuQ2Pg27kmBnzth22MbiRu405t4EhccONBDZmXnxa7r8BafkP1JLzDKSlnrCWGzzGj3nbDpgBtbCBtCQYENJi2ZNjxjjnXDLQC2nGQL9IGM4887AZr1/M2c8Yf3hTZmfYdyP54eecGht5vuPJBz98xOcwYBRK8CD4EkDM2IBbPUQL8wcevEpGwSgYBaNgxAMAtkpTD4xO2EUAAAAASUVORK5CYII=","orcid":"","institution":"Chengdu Medical College","correspondingAuthor":true,"prefix":"","firstName":"Quekun","middleName":"","lastName":"Peng","suffix":""}],"badges":[],"createdAt":"2025-03-24 16:10:23","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6297113/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6297113/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":84337871,"identity":"b2890085-1654-41cf-8446-b3314860f196","added_by":"auto","created_at":"2025-06-10 18:02:45","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":26943158,"visible":true,"origin":"","legend":"\u003cp\u003eWB and IF analysis of MOG protein expression in HEK293-MOG and CHO-MOG cells. After transfection of full-length human MOG protein with HEK293 cells and CHO cells, the expression of MOG protein in CHO-MOG cells was significantly higher than that in HEK293-MOG cells (Figure1A, C). In addition, immunofluorescence microscopy showed the same trend of fluorescence expression as WB (Figure1B, D). (Comparisons among multiple groups were performed by one-way ANOVA followed by Fisher’s least significant difference (LSD) test. ***\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001.)\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-6297113/v1/0d76ecb036e4f83371e63bb0.png"},{"id":84337870,"identity":"39e3a110-e6d0-498f-9ef8-fa5c9b3ec886","added_by":"auto","created_at":"2025-06-10 18:02:45","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":17992839,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of MOG-IgG\u003csup\u003e+\u003c/sup\u003e samples by live CBA-IF. Figure (A) Representative fluorescence images of HEK293-MOG and CHO-MOG cells tested positive (serum dilution 1:10 and 1:640, respectively). Green fluorescent EGFP is a binding human serum MOG antibody, and blue fluorescent is a nuclear DAPI marker. Images were obtained using a 40× inverted fluorescence microscope. Figure (B) represents quantification of CBA-IF binding scores representing negative and positive samples.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-6297113/v1/5e67bf6752f142862b488ef3.png"},{"id":84337868,"identity":"5b0ea725-1b5a-4fe6-8a0d-2fcad4cd76f4","added_by":"auto","created_at":"2025-06-10 18:02:45","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":13421454,"visible":true,"origin":"","legend":"\u003cp\u003eScatter plot of live cell-based flow cytometry (CBA-FC) analysis |. (A) Gating of representative flow cytometry strategies for CHO cells. The gate of flow cytometry data is based on forward scattering (FSC-A) and lateral scattering (SSC-A) using FlowJo™. (B, C) Representative flow diagrams of MOG-IgG\u003csup\u003e- \u003c/sup\u003eand MOG-IgG\u003csup\u003e+\u003c/sup\u003e samples. The X-axis represents the MOG-EGFP transfection marker. (D) Serum dilutions of 1:10 and 1:640 representative images of negative and positive test results\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-6297113/v1/944673d9f5ff581965c8dc9a.png"},{"id":84338940,"identity":"7ec0d0ad-7b9a-410f-a323-a33b0515c0de","added_by":"auto","created_at":"2025-06-10 18:10:45","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":4750457,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation of MOG-IgG titers and MFI values determined by CBA-IF and CBA-FC assays. The analysis was generated using CBA-IF and (A) CBA-FC1, (B) CBA-FC2, (C) CBA-FC3, (D) CBA-FC4, (E) CBA-FC5.The graphs are expressed as logarithmic scale, and the correlation values were calculated using the non-parametric Spearman correlation and correlation coefficient (r) are shown in the graph.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-6297113/v1/9fec72747df19e1b7580b09b.png"},{"id":88780526,"identity":"179b1327-210f-4c80-ac98-9cb1b8c396d1","added_by":"auto","created_at":"2025-08-11 10:47:27","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":48251255,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6297113/v1/59913d80-63fb-4d3c-b17b-57df3fe522c5.pdf"},{"id":84337863,"identity":"4054c610-893d-443e-b336-2f1739abdcb9","added_by":"auto","created_at":"2025-06-10 18:02:44","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":286971,"visible":true,"origin":"","legend":"","description":"","filename":"TableS1vector.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6297113/v1/2ae7e9079c050eadff5945d7.pdf"},{"id":84338939,"identity":"027c1ace-1600-4f99-b8f5-fde4b70885ed","added_by":"auto","created_at":"2025-06-10 18:10:44","extension":"jpg","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":1882851,"visible":true,"origin":"","legend":"","description":"","filename":"FigureS1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6297113/v1/2915c49dd5c1f18f1c59f098.jpg"},{"id":84337867,"identity":"db7498ae-02a4-41c0-8184-bd04fc38b083","added_by":"auto","created_at":"2025-06-10 18:02:45","extension":"tif","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":5257792,"visible":true,"origin":"","legend":"","description":"","filename":"FigureS2.tif","url":"https://assets-eu.researchsquare.com/files/rs-6297113/v1/7a122684f0e88c7cc9d62354.tif"},{"id":84337865,"identity":"0721ffdc-8185-431d-a665-7dfb47d6ce72","added_by":"auto","created_at":"2025-06-10 18:02:45","extension":"pdf","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":205730,"visible":true,"origin":"","legend":"","description":"","filename":"wb.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6297113/v1/ac11a7f4494bfd08394791b3.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Clinical Diagnosis of Myelin Oligodendrocyte Glycoprotein Antibodies Based on CHO Flow Cytometry Live Cell-based Assay","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMyelin Oligodendrocyte Glycoprotein (MOG) is a highly immunogenic component on the outer surface of myelin in the Central Nervous System (CNS) (1). Its antibody, anti-MOG IgG (MOG-IgG), has been demonstrated to be associated with the development of MOG-IgG Associated Disorders (MOGAD), including Multiple Sclerosis (MS) and myelitis (2-5), and has become one of the biological diagnostic biomarkers for MOGAD which is a CNS autoimmune disorder with a broad clinical spectrum, with the most common phenotype being Optic Neuritis (ON) followed by Acute Disseminated Encephalomyelitis (ADEM) and Transverse Myelitis (TM). The prevalence of MOGAD is approximately 1.3\u0026ndash;2.5 per 100,000, with an annual incidence of 3.4\u0026ndash;4.8 per 100,000 (6). The clinical phenotypes of MOGAD may overlap with MS and aquaporin-4-IgG positive (AQP4-IgG\u003csup\u003e+\u003c/sup\u003e) Neuromyelitis Optica Spectrum Disorder (NMOSD). Therefore, accurate diagnostic methods are critical to differentiate these diseases and guide appropriate therapeutic strategies.\u003c/p\u003e\n\u003cp\u003eMOG-IgG can be categorized into pathogenic and non-pathogenic forms(7, 8). Pathogenic MOG-IgG specifically recognizes conformational epitopes of MOG (e.g., the N-terminal extracellular domain rather than linear epitopes), leading to extensive demyelination. Additionally, high-titer MOG-IgG antibodies more readily penetrate the Blood-Brain Barrier (BBB), bind to target antigens, and trigger inflammatory responses(9, 10). Non-pathogenic antibodies target linear epitopes (e.g., the C-terminal or intracellular domains of MOG). If antibody titers are low or affinity is poor, these antibodies fail to penetrate the BBB or effectively bind to target antigens(11, 12). Initially, MOG-IgG detection relied on Enzyme-Linked Immunosorbent Assays (ELISA) or immunoprecipitation techniques, which had limitations in distinguishing conformational from linear epitopes, often resulting in false-positive outcomes(13, 14).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCurrently, the Cell-Based Assay (CBA) using HEK293 cells that expresses full-length human MOG protein in its native conformation enables precise detection of pathogenic MOG-IgG targeting conformation-dependent epitopes(15). Compared to traditional ELISA or immunoprecipitation, CBA demonstrates a sensitivity exceeding 90% and specificity over 95%, significantly reducing cross-reactivity with other myelin proteins (e.g., AQP4) (13, 16). The cell-based immunofluorescence assay (CBA-IF) is now widely regarded as the gold standard for MOGAD diagnosis. However, its semi-quantitative nature and operator-dependent interpretation may introduce human bias, even when performed by experienced personnel(17, 18).\u003c/p\u003e\n\u003cp\u003eSubsequently, flow cytometry-based assays (CBA-FC) emerged as a more sensitive and specific alternative method for detecting autoantibodies(19, 20). Flow Cytometry-Based Assays (CBA-FC) employ HEK293 cells transfected with enhanced fluorescently labeled full-length human MOG cDNA to express correctly folded MOG epitopes on the cell surface(21), thereby identifying pathogenic antibodies. CBA-FC is an objective, quantitative, and automated flow cytometry-based technique with higher precision than CBA-IF and minimized human interference. A recent multicenter double-blind study comparing live-cell CBA, fixed-cell CBA, and flow cytometry in detecting MOG antibodies in cerebrospinal fluid from patients with CNS inflammatory demyelinating diseases reported higher positive predictive values for live-cell CBA (100%) and flow cytometry (95.5%) than fixed-cell CBA (82.1%), enhancing clinical diagnostic utility (references). However, CBA-FC requires stringent standardization of flow cytometry parameters, as variations in equipment and timing may significantly affect results. Analytically, MOG-IgG detection via CBA-FC typically involves evaluating the ratio or difference in Mean Fluorescence Intensity (MFI) between transfected and untransfected cells. Fluorescence signals may vary due to MOG expression levels and secondary antibody usage. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDespite advancements in diagnostic methodologies, variability persists across antibody testing centers, necessitating cautious interpretation of results. The diagnosis of MOGAD primarily relies on clinical manifestations, neuroimaging findings, and the presence of MOG-IgG antibodies. However, the heterogeneous clinical spectrum of MOGAD\u0026mdash;encompassing ADEM, ON, myelitis, and atypical variants such as meningoencephalitis and brainstem encephalitis(22-24)\u0026mdash;poses challenges in differentiating it from other demyelinating disorders, particularly MS and AQP4-IgG\u003csup\u003e-\u003c/sup\u003eseropositive NMOSD (25, 26). Consequently, serological detection of MOG-IgG remains pivotal for MOGAD diagnosis(12, 27). Expert consensus recognizes MOG-IgG as a key diagnostic biomarker for MOGAD, with antibody titers correlating with disease severity (28). High-titer serum MOG-IgG is considered a robust diagnostic indicator. Nevertheless, low-titer results require careful interpretation, as false-positive MOG-IgG findings have been reported in other conditions, including MS and AQP4-associated NMOSD (29, 30). Studies demonstrate significantly higher false-positive rates in MS patients than in high-titer cases, reflecting poor inter-laboratory concordance for low-titer samples and complicating their clinical interpretation interpretation(29, 31). Thus, while the diagnostic utility of MOG-IgG is well-established, nuanced evaluation of antibody titers remains clinically complex (32).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Current clinical MOG antibody testing predominantly uses HEK293 cell lines(33, 34), which face challenges such as background noise and under detection in low-titer samples(35-37). To enhance positive detection rates in low-titer scenarios, this study explores Chinese Hamster Ovary (CHO) cells\u0026mdash;known for easier cultivation, high protein yield, and efficient post-translational modifications\u0026mdash;as an alternative tool. By comparing the performance of CBA-IF and CBA-FC using two MOG-expressing cell lines (HEK293 and CHO) in suspected MOGAD patients with compatible clinical features, this research aims to elucidate the advantages of CHO cell-based assays and provide novel insights for clinical diagnostic technologies.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003e\u003cstrong\u003eParticipants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFrom December 2022 to December 2023, a total of 36 patients clinically suspected of having MOGAD (Ethics Approval Number: HMYY-RP-EC09-2023-01) were enrolled in this study at Sichuan Provincial People\u0026apos;s Hospital, the First Affiliated Hospital of Chengdu Medical College. Their clinical presentations conformed to the 2020 \u0026ldquo;Chinese Expert Consensus on Diagnosis and Treatment of Disorders Associated with Anti-Myelin Oligodendrocyte Glycoprotein Immunoglobulin G Antibodies\u0026rdquo; and the latest international diagnostic guidelines. Patients whose data were incomplete or lost during follow-up were excluded (specific inclusion and exclusion criteria listed here). The study was conducted in accordance with the Declaration of Helsinki, and all participants provided informed consent with their information anonymized. All samples were analyzed by individuals who did not have access to clinical data.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTransfection of Human Embryonic Kidney 293 (HEK293) Cells and Chinese Hamster Ovary (CHO) Cells\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor Live-CBA-IF, HEK293 cells (ATCC, LGC Standards GmbH, Wessels, Germany) were cultured in Dulbecco\u0026rsquo;s Modified Eagle Medium (DMEM) supplemented with 10% fetal bovine serum (FBS) (Gibco, Life Technologies, NY, USA, catalog number 12657-029), 1% penicillin/streptomycin (100 U/mL) (Gibco, NY, USA, catalog number 15140-122), and 0.1% gentamicin (100 mg/mL) (Gibco, Life Technologies, NY, USA, catalog number 15710-064) in a humidified incubator at 5% CO\u003csub\u003e2\u003c/sub\u003e and 37\u0026deg;C until they reached 60% confluence. CHO cells (ATCC, LGC Standards GmbH, Wessels, Germany) were cultured in Dulbecco\u0026rsquo;s Modified Eagle Medium/Nutrient Mixture F-12（DMEM/F-12）\u0026nbsp;supplemented with 10% fetal bovine serum (FBS) (Gibco, Life Technologies, NY, USA, catalog number 12657-029), 1% penicillin/streptomycin (100 U/mL) (Gibco, NY, USA, catalog number 15140-122), and 0.1% gentamicin (100 mg/mL) (Gibco, Life Technologies, NY, USA, catalog number 15710-064) in a humidified incubator at 5% CO2 and 37\u0026deg;C until they reached 60% confluence. Thereafter, according to the manufacturer\u0026rsquo;s instructions, HEK293 cells and CHO cells were transfected with plasmids containing full-length human MOG (FL-MOG) \u0026alpha;1 isoform using Fugene HD transfection reagent (Promega Corporation, WI, USA, Cat# E2311).\u003c/p\u003e\n\u003cp\u003eFor Live-CBA-FC, HEK293 cells and CHO cells were transfected with pIRES Ds-Red 2 expression vectors harboring the FL-MOG for the Live-CBA-IF protocol. Details of the carrier are shown in Table S1.\u003c/p\u003e\n\u003cp\u003eFor Live-CBA-FC, HEK293 and CHO cells were transfected with pEGFP-N1 plasmids carrying the FL-MOG fused with EGFP (MOG-EGFP). Twenty-four hours post-transfection, the cells were enzymatically dissociated with 0.05% trypsin-EDTA (Gibco, Life Technologies, NY, USA, catalog number 15400054), centrifuged, and resuspended in DMEM containing puromycin (Thermo Fisher, MO, USA, catalog number A1113803) for selection and maintenance of stably transfected cells.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWestern Blot (WB)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo conduct the WB analysis, cells in their logarithmic growth phase are harvested. Total cellular proteins are extracted using RIPA lysis buffer. Protein quantification is performed subsequently, followed by electrophoresis through a SDS-PAGE gel. The proteins are then transferred to a PVDF membrane. A blocking step is carried out with 5% skim milk at constant temperature (37\u0026deg;C) for one hour on a shaking platform. The membrane is washed with TBST, after which primary antibodies (Proteintech, China, catalog number 28752-1-AP) are incubated overnight at 4\u0026deg;C. After thorough washing with TBST, secondary antibodies (Proteintech, China, catalog number SA00001-2) are applied at room temperature for one hour. Subsequent washes with TBST are conducted before the image is captured using Lumax Light.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eImmunofluorescence Microscopy\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor CBA-IF experiments, MOG-DsRed-transfected cells are enzymatically digested with trypsin, centrifuged, resuspended in DMEM, and placed onto slides. Overnight incubation is maintained within an incubator. Following the removal of culture medium, serum diluted at concentrations of 1:10, 1:32, 1:100, 1:320 and 1:640 is added at room temperature for one hour. Cells are washed three times with PBS, fixed with 4% paraformaldehyde, and washed again three times. Secondary antibody DyLight 594 conjugated to anti-human IgG-Fc (Abcam Scientific) is added at a dilution of 1:1000 and incubated for 40 minutes. Cells are washed three times with PBS and stained with Fluoroshield\u0026trade; mounting media containing DAPI (Sigma-Aldrich). Examination under a fluorescence microscope reveals that serum positivity is determined by a cut-off value set at 1:10. For positive samples, the titer of MOG-IgG is measured through a series of threefold serial dilutions from the highest concentration. The endpoint titer is defined as the most dilute sample yielding a positive fluorescent signal.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFlow Cytometry\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn the CBA-FC assays, five different serum dilutions (1:10, 1:32, 1:100, 1:320, and 1:640) were utilized. One million MOG-EGFP-transfected cells were collected, washed twice with PBS (pH 7.4), and incubated with patient sera at 4\u0026deg;C for thirty minutes. Cells were washed twice more, followed by incubation at 4\u0026deg;C with a secondary antibody, DyLight 594 conjugated to anti-human IgG-Fc (Thermo Scientific, Life Technologies; catalog number SA 5 -10137), at a dilution of 1:200 for another thirty minutes. Cells were washed thrice, resuspended in PBS, and analyzed using an Attune NxT flow cytometer (Thermo Scientific, Life Technologies). Each sample was evaluated in duplicate. Optimal data collection gates were established for analysis, with binding quantified as MFI. MOG-IgG titers were assessed using two methods: the ratio of MFI between cells expressing MOG and untransfected cells (rMFI) and the MFI increment (∆MFI). A cutoff value was derived from the threshold obtained using the MOG-IgG\u003csup\u003e-\u003c/sup\u003e patient cohort, calculated as the average MFI across all negative samples (rMFI and ∆MFI) plus four standard deviations.\u0026nbsp;The MOG-seronegative patient cohort, defined by CBA-IF screening, comprised 3 males aged 20\u0026ndash;25 years and 3 females aged 24\u0026ndash;27 years.\u0026nbsp;The CBA-FC MFI measured by MOG antibody negative population was added with four standard deviations as the threshold, and the serum samples of each patient were repeated for three times.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Analysis\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStatistical analyses were conducted using IBM SPSS Statistics 22.0 (Armonk, NY, USA) and GraphPad Prism 5 (La Jolla, CA, USA). Flow cytometry data were analyzed using FlowJo\u0026trade; Software 10 (Becton Dickinson and Company, USA). Cohen\u0026rsquo;s kappa statistic was employed to evaluate the consistency between CBA-IF and CBA-FC analyses, as well as the Spearman rank correlation coefficient assessing the relationship between CBA-IF and CBA-FC antibody titers. Receiver Operating Characteristic (ROC) curve analysis was used to determine the performance of CBA-FC in detecting blood serum MOG-IgG positivity relative to CBA-IF as a reference test. Statistical significance was considered at p-values less than 0.05.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003ePatient demographics and clinical data\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn 36 patients, according to the CBA-IF results, the median age at onset in the \u0026nbsp;Myelin Oligodendrocyte Glycoprotein\u0026nbsp;IgG positive\u0026nbsp;(MOG-IgG\u003csup\u003e+\u003c/sup\u003e) group was 20 years, and 61% were female. In the MOG-IgG positive group, ON was the main disease, accounting for 55%. 7.1% had myelitis, 7% had both ON and myelitis, 29% had\u0026nbsp;ADEM, and 3.6% had seizures. In the\u0026nbsp;Myelin Oligodendrocyte Glycoprotein\u0026nbsp;IgG negative (MOG-IgG\u003csup\u003e-\u003c/sup\u003e) group the clinical diagnoses were as follows: 23.8% had ON, 18.5% had myelitis, 25.6% were clinically diagnosed with seronegative NMOSD, 17.7% had MS, 10.80% had rhombencephalitis, and 3.60% had other diseases. Notably, 25.6% were\u0026nbsp;AQP4-IgG\u003csup\u003e+\u003c/sup\u003e in the MOG-IgG\u003csup\u003e-\u0026nbsp;\u003c/sup\u003egroup, and there were no\u0026nbsp;AQP4-IgG\u003csup\u003e+\u003c/sup\u003e cases in the MOG-IgG\u003csup\u003e+\u003c/sup\u003e group (Table 1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAnalysis of transfected MOG protein expression in HEK293 and CHO cell lines\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFigure 1 shows the WB of HEK293 and CHO cell lines transfected with MOG protein, and it can be found from the results of quantitative analysis in Fig. 1A WB bands and Fig. 1B that the relative expression of CHO cell lines transfected with MOG protein was significantly higher than that of HEK293 cell lines (\u003cem\u003ep\u003c/em\u003e\u0026lt;0.001), and the high expression of MOG protein has a significantly higher expression rate in the detection of MOG- IgG antibody with higher sensitivity, which is advantageous for early clinical diagnosis of patients compared with HEK293 cell line.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSeropositivity analyzed by CBA-IF method\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe performed CBA-IF at five serum dilutions (1:10, 1:32, 1:100, 1:320, 1:640). According to the results of CBA-IF assay, out of 36 serum samples, 78.8% (n=29) were MOG-IgG\u003csup\u003e+\u003c/sup\u003e and 22.2% (n=7) were MOG-IgG\u003csup\u003e-\u003c/sup\u003e. Seven of the negative samples were below the threshold (1:10) and all had weak fluorescence emission. Figure 2A provides representative image results of CBA-IF of the same positive serum samples at two titers of 1:10 and 1:640 respectively after transfection of human full-length MOG proteins in HEK293 and CHO cell lines (Representative images with dilutions of 1:32, 1:100, and 1:320 are shown in Fig S1). It can be found that the positive luminescence intensity shown in the fluorescence image is higher at 1:10 serum dilution, and the positive luminescence shown in the fluorescence image is weak at 1:640 serum dilution. The final titer range of the MOG-IgG\u003csup\u003e+\u003c/sup\u003e group after CBA-IF assay was 1:10 to 1:640 (Figure 2B).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAnalysis of seropositivity by CBA-FC method\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSerum antibodies were detected using the CHO-MOG cell line via the CBA-FC method. Five serum dilutions (1:10, 1:32, 1:100, 1:320, 1:640) were analyzed under homogeneous conditions based on the mean fluorescence intensity (∆MFI = MFI-positive-negative cells) (Representative images with dilutions of 1:32, 1:100, and 1:320 are shown in Figure S2).The CBA-FC groups were named from 1 to 5 according to their respective acronyms: CBA-FC 1 (1:10 using ∆MFI analysis); CBA-FC 2 (1:32, using ∆MFI analysis); CBA-FC 3 (1:100, using ∆MFI analysis); CBA-FC 4 (1:320, using ∆MFI analysis); and CBA-FC 5 (1:640, using ∆MFI analysis).The MOG-IgG\u003csup\u003e+\u003c/sup\u003e group accounted for 83.3%, 58.3%, 44.4%, 11.1%, and 5.6%, respectively, in CBA-FC 1to 5. Figure 3 shows examples of sample-gated (3A), seronegative (3B), and seropositive (3C) MOG-IgG in CBA-FC. Figure3D showed that the positive and negative sample results for CBA-FC after transfection of CHO cell lines with human full-length MOG protein at two serum dilutions, 1:10 and 1:640. Under the same gating conditions, the distribution of positive and negative cell populations at the two serum dilutions was more obvious, but some false positives and false negatives inevitably existed, which may be due to non-specific binding of antibodies in the detection process or interference from other components present in the serum, so it is necessary to determine critical values to exclude the influence of non-human factors in the analysis of results. In this study, the critical values were determined by the thresholds that were determined by the mean of the MFI plus four standard deviations of a cohort of negative MOG-IgG patients (∆MFI) (Table 2). This criterion is based on the \u0026zwnj;normal distribution assumption\u0026zwnj;, positing that the fluorescence intensity of negative control samples follows a normal distribution. By calculating the \u0026zwnj;MFI (Mean Fluorescence Intensity)\u0026zwnj; and \u0026zwnj;SD (Standard Deviation)\u0026zwnj; of the negative controls, the positive threshold is defined as: Cut-off = MFI (negative controls) + 4\u0026times;SD (negative controls)\u0026zwnj;. This approach excludes \u0026zwnj;99.99% of negative signals below the threshold\u0026zwnj; (statistically, 3\u0026sigma; covers 99.7% of data under a normal distribution, while 4\u0026sigma; covers 99.99%), thereby significantly reducing \u0026zwnj;false-positive risks\u0026zwnj;.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eComparison between CBA-FC and CBA-IF\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn comparing CBA-IF and CBA-FC, the results of sample detection were consistent at serum dilutions of 1:10 and 1:32 across all five dilution levels analyzed. At a dilution of 1:100, two samples showed different results; meanwhile, one sample each displayed differing results at dilutions of 1:320 and 1:640. With the established CBA-IF as a reference standard, the area under the curve (AUC) of the ROC curves were 0.872, 0.867, 0.756, 0.783, 0.710, respectively (Table 3). The sensitivity analyses of the CBA-FC1-5 were 80.0%, 70.0%, 46.7%, 66.7%, and 58.1% respectively. The specificity was 100.0%, 100.0%, 100.0%, 83.2%, and 80.1% respectively. These data indicated that sensitivity is increased at a dilution of 1:100, while specificity is enhanced at dilutions of 1:10, 1:32, and 1:100. However, as the dilution increases, specificity gradually decreases. The positive predictive values of CBA-FC 1-5 were 1.000, 0.866, 0.766, 0.633, and 0.633, and the negative predictive values were 1.000, 0.667, 0.462, 0.353, and 0.353, respectively. In figure 4, there was a strong positive correlation between the titration results obtained by immunofluorescence and the analysis results from flow cytometry, particularly at a dilution of 1:100.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAnalysis of titers and diagnostic results\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe titer and clinical diagnostic results showed that 81.5% of patients with ON were detected at low titers and 18.5% at high titers; 25.0% of patients with optic neuromyelitis were detected at low titers and 75% at high titers; 30.0% of patients with ADEM were detected at low titers and 70.0% at high titers; and an additional 30.0% of patients with ADEM were detected. Of patients with ADEM were detected in 30% at low titers and 70.0% at high titers, and one additional patient with meningitis was detected at low titers（Table 4）(\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05).\u003c/p\u003e\n"},{"header":"Discussion","content":"\u003cp\u003eCurrently, live cell-based assays targeting the full-length native conformation of MOG are the gold standard for clinical diagnosis of MOGAD(15, 19, 38). Retrospective studies have demonstrated that early diagnosis and appropriate immunotherapy are crucial for improving clinical outcomes(39, 40). Conventional immunofluorescence (IF) assays using live HEK293 cells are often limited by human-derived interference and low sensitivity, hindering clinical diagnosis and related disease research, particularly in early disease screening and relapse prevention. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTwo distinct antibody incubation protocols were implemented for CBA-IF and CBA-FC, respectively, based on their differential cellular processing requirements: CBA-IF\u0026zwnj; typically involves cell fixation (e.g., paraformaldehyde) and permeabilization (e.g., Triton X-100) to enable antibody penetration for intracellular antigen binding, with room-temperature incubation enhancing antibody permeability. CBA-FC\u0026zwnj; requires cells to remain in a monodisperse state, where low-temperature incubation minimizes cellular aggregation and membrane damage. The 1-hour primary antibody incubation at room temperature in CBA-IF ensures sufficient penetration and binding to intracellular or surface antigens, whereas the 30-minute incubation for CBA-FC leverages the high sensitivity of flow cytometry to achieve efficient MOG antigen binding while reducing nonspecific interactions.\u003c/p\u003e\n\u003cp\u003eCHO cells have advantages over HEK293 cells: the former enable extracellular transport of target proteins, express minimal endogenous proteins (facilitating target protein purification), and are resistant to human viral infections while allowing human-compatible glycosylation modifications(41-43). These advantages make CHO cells a preferred host for producing therapeutic proteins and antibodies(44). Using CHO cell-based assays, Jaśkiewicz et al. specifically identified serum antibodies against three major myelin autoantigens: myelin basic protein (MBP), proteolipid protein (PLP), and MOG(45). IgG autoantibody titers against membrane-bound recombinant myelin antigens were most significantly elevated for PLP but not for MBP or MOG. These findings suggest that CHO cell-based assays for recombinant myelin antigen autoantibodies may serve as a valuable serological tool for diagnosing and monitoring MS progression(45). Built on these advantages, our study utilized CHO cells transfected with full-length human MOG (CHO-MOG cell line) for serum MOG-IgG detection. Immunofluorescence (IF) and WB results (Figure 1) confirmed high and stable exogenous protein expression, enhancing MOG-IgG detection sensitivity. In comparative CBA with flow cytometry (CBA-FC) analyses of serum samples at equivalent dilutions, the CHO-MOG cell line exhibited significantly higher fluorescence values than the HEK293-MOG cell line upon MOG-IgG binding, indicating stronger antigen-antibody interaction. This suggests that CBA-FC-based MOG-IgG detection may perform better in early and relapsing MOGAD cases. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFlow cytometry for live cell detection, which quantifies patient serum binding to MOG-expressing cells, is a widely used, accurate, and reliable method that eliminates human-derived interference. Lopez et al. compared a simplified CBA-FC with research-grade assays in demyelinating disease patients, reporting high concordance (98%\u0026ndash;100%) in MOG antibody detection. The simplified assay also showed improved intra- and inter-batch error rates(46). In a study of 202 MOG-IgG-seropositive adult MOGAD patients, validated flow cytometry-based live cell assays confirmed serum MOG-IgG and epitope binding. The authors correlated assay results with epitopes, disease duration, and clinical relapses, finding that MOG-IgG titers predicted relapsing courses in most patients. Early detection and targeted treatment could minimize disability and improve long-term prognosis(47). In our study, CHO-based live cell CBA with flow cytometry (CBA-FC) and immunofluorescence (CBA-IF) were used to detect MOG-IgG. with CBA-IF as the standard, \u0026Delta; median fluorescence intensity (\u0026Delta;MFI) of CBA-FC method was compared across five serum dilutions (1:10, 1:32, 1:100, 1:320, and 1:640), where CBA-FC and CBA-IF showed high concordance (kappa \u0026gt;0.8) at high titers (1:10 and 1:32),while CBA-FC demonstrated slightly higher sensitivity than CBA-IF at lower titers, enabling positive diagnosis in low-titer MOG-IgG cases. Notably, a single false-positive result occurred at 1:640 dilution, highlighting the need for combined CBA-IF and imaging data to mitigate reduced specificity at high sensitivity. Among the five CBA-FC analyses, the 1:10 dilution (CBA-FC1) achieved the highest area under the curve (AUC), while the 1:100 dilution (CBA-FC3) offered optimal sensitivity. CBA-FC analyzed at lower serum dilutions (CBA-FC 1, 2, 3) had higher specificity.CBA-FC3 also showed strong concordance with CBA-IF titers, aligning closely with established CBA-IF protocols. \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eGiven the diversity of MOG-associated diseases, different disease courses, and confounding factors that may lead to non-specific binding in human serum, antibody titres may show variability in different patients, leading to misdiagnosis or missed diagnoses. \u0026nbsp; Therefore, standardized high-sensitivity assays are critical. MOG antibody titers cannot differentiate MOGAD phenotypes(34, 38), and inconsistent definitions/methods across centers necessitate clear thresholds for low-positive cases to avoid diagnostic errors. This is vital for differentiating treatment strategies for MOGAD and AQP4-IgG\u003csup\u003e+\u003c/sup\u003e NMOSD. Prior studies suggested CBA-FC as a feasible diagnostic tool for MOG antibody detection. Our study evaluated CHO-based CBA-FC across titers, finding that \u0026Delta;MFI at 1:10 dilution (CBA-FC1) correlated strongly with CBA-IF, while 1:100 dilution (CBA-FC3) maintained specificity with higher sensitivity. The optimal dilution for CBA-FC appears to be 1:100. The combination of both methods may help distinguish nonspecific binding, overcoming limitations of single assays. Despite advantages of flow cytometry over traditional methods(15, 19, 48), further arguments are needed to translate these research assays into pathology-based diagnostics due to variations in CBA-FC protocols, data analysis, and positivity thresholds.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis study acknowledges limitations, including small sample size, short follow-up, retrospective design biases, and geographic sample restrictions. Future large-scale longitudinal studies with extended follow-up are needed to clarify the relationship between titers and relapse patterns. \u0026nbsp;\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eWhile HEK293-based CBA remains the gold standard for MOG antibody detection, it suffers from background interference and false results. Our findings indicate that the CHO cell line-based assay vector has higher MOG expression than the HEK293 cell line, possesses a higher detection rate, and can be used as an auxiliary diagnostic technique for MOG-IgG in clinical applications. CHO cell-based CBA-FC was highly consistent with CBA-IF and had higher sensitivity than CBA-IF. Furthermore, when using 1:100 antibody titer and \u0026Delta;MFI values, CBA-FC showed high concordance with CBA-IF and high sensitivity. Therefore, for patients with low-titer sera but high clinical suspicion, adopting a dual comparison of both CHO cell-based CBA-IF and CBA-FC methods at multiple testing facilities will facilitate accurate diagnosis, thus helping physicians to develop precise and effective treatment strategies.\u003c/p\u003e\n"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank the patients and their families for their participation and contribution. The study was supported by Chengdu Hemer Yunyin Medical Laboratory Co. In addition, we would also like to thank Tong Peng and Shijie Ni from Sichuan University for their valuable modifications to the methodology and language of the article, respectively.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis project was mainly sponsored by the Chengdu Medical College-Chengdu Hemer Yunyin Medical Laboratory Co. joint fund (No. CMC Contract 2021-168 and CMC Contract 2024-565).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that there are no conflicts of interest relevant to this work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe confirm that we have read the Journal\u0026rsquo;s position on issues involved in ethical publication and that this work is consistent with those guidelines. Approval for this study was obtained from the local institutional review boards (Ethics Approval Number: HMYY-RP-EC09-2023-01. The Ethics Committee of Chengdu HeimerYunyin medical laboratory Ltd.,China.). Written informed consent was obtained from each patient.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo data was used for the research described in the article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot Applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eReindl M, Di Pauli F, Rost\u0026aacute;sy K, Berger T. The spectrum of MOG autoantibody-associated demyelinating diseases. Nat Rev Neurol. 2013;9(8):455-61.\u003c/li\u003e\n\u003cli\u003eLoos J, Pfeuffer S, Pape K, Ruck T, Luessi F, Spreer A, et al. 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Part 2: Epidemiology, clinical presentation, radiological and laboratory features, treatment responses, and long-term outcome. J Neuroinflammation. 2016;13(1):280.\u003c/li\u003e\n\u003cli\u003eRamanathan S, Mohammad S, Tantsis E, Nguyen TK, Merheb V, Fung VSC, et al. Clinical course, therapeutic responses and outcomes in relapsing MOG antibody-associated demyelination. J Neurol Neurosurg Psychiatry. 2018;89(2):127-37.\u003c/li\u003e\n\u003cli\u003eHu J, Han J, Li H, Zhang X, Liu LL, Chen F, et al. Human Embryonic Kidney 293 Cells: A Vehicle for Biopharmaceutical Manufacturing, Structural Biology, and Electrophysiology. Cells Tissues Organs. 2018;205(1):1-8.\u003c/li\u003e\n\u003cli\u003eStepanenko AA, Dmitrenko VV. HEK293 in cell biology and cancer research: phenotype, karyotype, tumorigenicity, and stress-induced genome-phenotype evolution. Gene. 2015;569(2):182-90.\u003c/li\u003e\n\u003cli\u003eZehetner L, Sz\u0026eacute;liov\u0026aacute; D, Kraus B, Graninger M, Zanghellini J, Hernandez Bort JA. Optimizing VLP production in gene therapy: Opportunities and challenges for in silico modeling. Biotechnol J. 2023;18(7):e2200636.\u003c/li\u003e\n\u003cli\u003eFischer S, Handrick R, Otte K. The art of CHO cell engineering: A comprehensive retrospect and future perspectives. Biotechnol Adv. 2015;33(8):1878-96.\u003c/li\u003e\n\u003cli\u003eJaśkiewicz E, Michałowska-Wender G, Pyszczek A, Wender M. Recombinant forms of myelin antigens expressed on Chinese hamster ovary (CHO) cells as a tool for identification of autoantibodies in serum of multiple sclerosis patients. Folia Neuropathol. 2010;48(1):45-8.\u003c/li\u003e\n\u003cli\u003eLopez JA, Houston SD, Tea F, Merheb V, Lee FXZ, Smith S, et al. Validation of a Flow Cytometry Live Cell-Based Assay to Detect Myelin Oligodendrocyte Glycoprotein Antibodies for Clinical Diagnostics. 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Neurol Neuroimmunol Neuroinflamm. 2020;7(2).\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTABLE1|Patient clinical data\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"558\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 180px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSample\u0026nbsp;of\u0026nbsp;the\u0026nbsp;CBA-IF\u0026nbsp;results\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 282px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eMOG-IgG\u0026nbsp;testing(N=36)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-vaule\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eMOG-IgG\u003csup\u003e+\u003c/sup\u003e(N=30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003eMOG-IgG\u003csup\u003e-\u003c/sup\u003e(N=6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u0026nbsp;of\u0026nbsp;onset\u0026nbsp;(age), median\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e20.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e20.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"11\" valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.038\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003eFemale, N (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e62.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e38.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eClinical\u0026nbsp;diagnostic\u0026nbsp;results\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 282px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003eON (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e55.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e23.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003eMyelitis (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003eON\u0026nbsp;and\u0026nbsp;myelitis (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003eNMOSD (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003eADEM (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003eMS (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e10.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003eEncephalitis/seizures (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e6.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003eOthers (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e3.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eCBA-IF，Cell-Based Immunofluorescence Assay；MOG-IgG,\u0026nbsp;Anti-Myelin Oligodendrocyte Glycoprotein; MOG-IgG\u003csup\u003e+\u003c/sup\u003e, Myelin Oligodendrocyte Glycoprotein IgG positive; MOG-IgG\u003csup\u003e-\u003c/sup\u003e, Myelin Oligodendrocyte Glycoprotein IgG negative; ON, Optic Neuritis; NMOSD, Neuromyelitis Optica Spectrum Disorder; ADEM, Acute Disseminated Encephalomyelitis; MS, Multiple Sclerosis.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;TABLE 2 | Data of CBA-FC analysis\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"590\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eAnalyses\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eCutoff\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eMOG-IgG\u003csup\u003e+\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eMOG-IgG\u003csup\u003e-\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eMFI (range)positive\u0026nbsp;samples\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCBA-FC1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDilution\u0026nbsp;1:10\u003c/p\u003e\n \u003cp\u003e\u0026Delta;MFI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1070\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e30 (83.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6 (16.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e10272 (1070)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCBA-FC2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDilution\u0026nbsp;1:32\u003c/p\u003e\n \u003cp\u003e\u0026Delta;MFI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e680\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e26 (72.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e9 (17.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e11420 (696)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCBA-FC3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDilution\u0026nbsp;1:100\u003c/p\u003e\n \u003cp\u003e\u0026Delta;MFI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e782\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e23 (63.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e13 (36.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e11706 (782)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCBA-FC4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDilution\u0026nbsp;1:320\u003c/p\u003e\n \u003cp\u003e\u0026Delta;MFI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e309\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e19 (52.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e17 (47.3%)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5369 (309)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCBA-FC5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDilution\u0026nbsp;1:640\u003c/p\u003e\n \u003cp\u003e\u0026Delta;MFI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e277\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e19\u0026nbsp;(52.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e17\u0026nbsp;(47.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3535 (277)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eMOG-IgG\u003csup\u003e+\u003c/sup\u003e, Myelin Oligodendrocyte Glycoprotein IgG positive; MOG-IgG\u003csup\u003e-\u003c/sup\u003e, Myelin Oligodendrocyte Glycoprotein IgG negative; MFI, mean fluorescent intensity; \u0026Delta;MFI, delta MFI.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;TABLE 3| Data analysis comparing CBA-IF and CBA-FC\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"606\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCBA-FC1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95%CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCBA-FC2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95%CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCBA-FC3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95%CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCBA-FC4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95%CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCBA-FC5\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95%CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e(AUC) of the RoC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e0.872\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e0.806 to 0.989\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e0.867\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e0.740\u0026nbsp;to\u0026nbsp;0.994\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e0.756\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e0.864 to 0.947\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e0.783\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e0.796 to 0.971\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e0.710\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e0.737 to 0.883\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eSensitivity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e0.816\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e0.722\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e0.887\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e0.667\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e0.581\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eSpecificity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e0.832\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e0.801\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003ePositive Predictive\u003c/p\u003e\n \u003cp\u003eValue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e0.866\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e0.766\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e0.633\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e0.633\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eNegative\u003c/p\u003e\n \u003cp\u003ePredictive\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eValue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e0.667\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;0.462\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e0.353\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e0.353\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eKappa\u003c/p\u003e\n \u003cp\u003ecoefficient\u003c/p\u003e\n \u003cp\u003evalues\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e0.821\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e0.809\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e0.672\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e0.722\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e0.770\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eSpearman\u0026apos;s\u003c/p\u003e\n \u003cp\u003ecoefficient\u0026nbsp;\u003c/p\u003e\n \u003cp\u003evalues\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e0.811\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e0.772\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;0.711\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e0.793\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e0.787\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTABLE4|Analysis of titers and diagnostic results\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eLow titer\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eHigh titer\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eDiagnostic results\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eON\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e13 (81.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3 (18.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"5\"\u003e\n \u003cp\u003e0.026\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eNMO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1 (25.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3 (75.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eADEM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3 (30.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7 (70.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eBrain\u0026nbsp;fever\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1 (100.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e18（58.0%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e13 (42.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eON, Optic Neuritis; NMO, Neuromyelitis Optica; ADEM, Acute Disseminated Encephalomyelitis.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Myelin oligodendrocyte glycoprotein, MOGAD, CHO cells, HEK293 cells, CBA-IF, CBA-FC","lastPublishedDoi":"10.21203/rs.3.rs-6297113/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6297113/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e In this study, two cell lines, CHO and HEK293, which overexpress the full-length protein of MOG, were used to evaluate the diagnostic performance of the two cell lines in the detection of serum MOG antibodies in patients with MOGAD (MOG Antibody Disease) under different titers and CBA method.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e Sera were collected from 36 suspected patients with clinical manifestations of MOGAD but not yet subjected to antibody assay, and the collected sera were subjected to CBA-IF (cell-based assay-immunofluorescence) and CBA-FC (cell-based assay-flow cytometry) using two cell lines, CHO and HEK293, which overexpressed MOG. Five different dilutions (1:10, 1:32, 1:100, 1:320, and 1:640) were used for both CBA-IF and CBA-FC methods for sensitivity and consistency testing. X2 test was used for gender and age.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e MOG-IgG was detected in the sera of 30 patients consistent with the clinical manifestations of multiple sclerosis, autoimmune encephalomyelitis, and optic neuromyelitis, and serum MOG-IgG was detected as a negative result in another 6 patients, including two patients who tested positive for antibody to aquaporin-4 (AQP4-IgG) and negative for MOG-IgG. The results of CBA-FC and CBA-IF results had 84% concordance and the CBA-IF titers obtained by endpoint dilution correlated with the CBA-FC titers. The highest serum dilution resulted in increased CBA-FC sensitivity but decreased specificity.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e The present study demonstrated that the sensitivity of CBA-FC detection of MOG antibody using CHO cell line at antibody titer of 1:100 was higher than using 293 cell line. CHO cell line is thus expected to be further applied in the clinic. In contrast, CBA-FC has a slight advantage over CBA-IF in the detection of MOG antibodies in certain titers and can be used as a diagnostic technique for MOG-IgG in clinical practice. In addition, the combination of the two techniques can be used as a tool to differentiate non-specific binding and to overcome the limitations of a single assay in certain specific situations.\u003c/p\u003e","manuscriptTitle":"Clinical Diagnosis of Myelin Oligodendrocyte Glycoprotein Antibodies Based on CHO Flow Cytometry Live Cell-based Assay","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-10 18:02:40","doi":"10.21203/rs.3.rs-6297113/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ee08f7ca-3439-4da6-a034-e59bd37d1b7e","owner":[],"postedDate":"June 10th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-08-11T10:38:30+00:00","versionOfRecord":[],"versionCreatedAt":"2025-06-10 18:02:40","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6297113","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6297113","identity":"rs-6297113","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}