Establishment of a comprehensive diagnostic model for neuromyelitis optica spectrum disorders based on the analysis of laboratory indicators and clinical data.

BACKGROUND: To establish a comprehensive diagnostic model for neuromyelitis optica spectrum disorders (NMOSDs) based on laboratory indicators and clinical data. METHODS: A retrospective method was used to query the medical records of patients with NMOSD from January 2019 to December 2021. At the same time, clinical data of other neurological diseases were also collected for comparison. Clinical data of the NMOSD group and non-NMOSD group were analyzed, and the diagnostic model was established based on these data. In addition, the model was evaluated and verified by the receiver operating curve. RESULTS: A total of 73 patients with NMOSD were included, and the ratio of males to females was 1:3.06. The indicators that showed differences between the NMOSD group and non NMOSD group included neutrophils (P = 0.0438), PT (P = 0.0028), APTT (P < 0.0001), CK (P = 0.002), IBIL (P = 0.0181), DBIL (P < 0.0001), TG (P = 0.0078), TC (P = 0.0117), LDL-C (P = 0.0054), ApoA1 (P = 0.0123), ApoB (P = 0.0217), TPO antibody (P = 0.012), T3 (P = 0.0446), B lymphocyte subsets (P = 0.0437), urine sg (P = 0.0123), urine pH (P = 0.0462), anti-SS-A antibody (P = 0.0036), RO-52 (P = 0.0138), CSF simplex virus antibody I-IGG (P = 0.0103), anti-AQP4 antibody (P < 0.0001), and anti-MOG antibody (P = 0.0036). Logistic regression analysis showed that changes in ocular symptoms, anti-SSA antibody, anti-TPO antibody, B lymphocyte subsets, anti-AQP4 antibody, anti-MOG antibody, TG, LDL, ApoB, and APTT had a significant impact on diagnosis. The AUC of the combined analysis was 0.959. The AUC of the new ROC for AQP4- and MOG- antibody negative NMOSD was 0.862. CONCLUSIONS: A diagnostic model was successfully established, which can play an important role in differential diagnosis of NMOSD.

Prognostic biomarker SGSM1 and its correlation with immune infiltration in gliomas.

OBJECTIVE: Glioma was the most common type of intracranial malignant tumor. Even after standard treatment, the recurrence and malignant progression of lower-grade gliomas (LGGs) were almost inevitable. The overall survival (OS) of patients with LGG varied widely, making it critical for prognostic prediction. Small G Protein Signaling Modulator 1 (SGSM1) has hardly been studied in gliomas. Therefore, we aimed to investigate the prognostic role of SGSM1 and its relationship with immune infiltration in LGGs. METHODS: We obtained RNA sequencing data from The Cancer Genome Atlas (TCGA) to analyze SGSM1 expression. Functional enrichment analyses, immune infiltration analyses, immune checkpoint analyses, and clinicopathology analyses were performed. Univariate and multivariate Cox regression analyses were used to identify independent prognostic factors. And nomogram model has been developed. Kaplan-Meier survival analysis and log-rank test were used to estimate the relationship between OS and SGSM1 expression. The survival analyses and Cox regression were validated in datasets from the Chinese Glioma Genome Atlas (CGGA). RESULTS: SGSM1 was significantly down-regulated in LGGs. Functional enrichment analyses revealed SGSM1 was correlated with immune response. Most immune cells and immune checkpoints were negatively correlated with SGSM1 expression. The Kaplan-Meier analyses showed that low SGSM1 expression was associated with a poor outcome in LGG and its subtypes. The Cox regression showed SGSM1 was an independent prognostic factor in patients with LGG (HR = 0.494, 95%CI = 0.311-0.784, P = 0.003). CONCLUSION: SGSM1 was considered to be a new prognostic biomarker for patients with LGG. And our study provided a potential therapeutic target for LGG treatment.

Potential biomarkers identified by tandem mass tags based quantitative proteomics for diagnosis and classification of Guillain-Barré syndrome.

BACKGROUND AND PURPOSE: Guillain-Barré syndrome (GBS) is an acute inflammatory autoimmune and demyelinating disease of the peripheral nervous system. Currently, valid biomarkers are unavailable for the diagnosis of GBS. METHODS: A comparative proteomics analysis was performed on the cerebrospinal fluid (CSF) from 10 patients with GBS and 10 patients with noninflammatory neurological disease (NND) using the tandem mass tags technique. The differentially expressed proteins were analyzed by bioinformatics, and then the candidate proteins were validated by the enzyme-linked immunosorbent assay method in another cohort containing 160 samples (paired CSF and plasma of 40 patients with GBS, CSF of 40 NND patients and plasma of 40 healthy individuals). RESULTS: In all, 298 proteins were successfully identified in the CSF samples, of which 97 differentially expressed proteins were identified in the GBS and NND groups. Three key molecules were identified as candidate molecules for further validation. The CSF levels of TGOLN2 and NCAM1 decreased in GBS patients compared with NND patients, whereas the CSF levels of APOC3 increased. The enzyme-linked immunosorbent assay results were consistent with our proteomics analysis. Interestingly, in the validation cohort, serum APOC3 levels in the GBS group were consistent with those in the CSF samples and significantly higher than those in the healthy control group. CONCLUSIONS: Our preliminary data suggest that the CSF protein expression profile of patients with GBS is different from that of patients with NND. Moreover, alterations of TGOLN2, NCAM1and APOC3 may be used as novel biomarkers for identifying patients with GBS.

Establishment of SARS-CoV-2 Immunoglobulins (IgM, IgG) Reference Intervals for Elder Population in China based on 3,733 Samples.

BACKGROUND: Establishment of reference intervals (RIs) for different biomarkers is essential for clinical monitoring. The purpose of this study was to establish laboratory RIs of SARS-CoV-2 IgM and IgG for elder population. MATERIALS: Performance verification was conducted with reference to the Clinical and Laboratory Standards Institute (CLSI) guidelines, including linearity, imprecision, and allowable dilution ratio. Based on CLSI C28-A3 document, a total of 3,734 serum samples were collected, and 3,733 serum samples were used for the establishment of RIs for SARS-CoV-2 IgM and IgG. The subjects were grouped by gender and age. The age groups were as follows: 60 - 69 years, 70 - 79 years, 80 - 89 years, and 90 - 101 years. The RI was defined by nonparametric 95th percentile intervals. RESULTS: Percentage deviation of all the seven dilutions were all less than 12.5% during linearity evaluation. The inter-assay and intra-assay imprecision were all less than 5%. There is no significant difference between different gender and age groups for IgM (p = 0.0818, p = 0.7094), and there is significant difference between different gender and age groups for IgG (p = 0.0011, p = 0.0013). Harris-Boyd's test did not indicate partitioning for IgM and IgG. Cutoff values of RI for SARS-CoV-2 IgM and IgG were defined as 0.1523 S/CO and 0.2663 S/CO, respectively. CONCLUSIONS: RIs of SRAR-CoV-2 IgM and IgG were established for elder population, which can play an important role in the prevention and control of the epidemic.

Diagnostic and Monitoring Value of ß-2 Transferrin and Transferrin for Intracranial Infection After Neurosurgery.

BACKGROUND AND OBJECTIVES: After neurosurgery, intracranial infection is a common complication with high rates of clinical impairment and death. Traditional diagnostic approaches are time-consuming. Early and correct diagnosis improves infection control, treatment success, and survival. Novel markers are used to diagnose and classify post-neurosurgical meningitis (PNM) to overcome the difficulties of diagnosing postoperative intracranial infections and avoid the drawbacks of existing diagnostic measures. The objective was to investigate the diagnostic value of ß-2 transferrin (ß-2TF) and transferrin (TF) in the cerebrospinal fluid (CSF) for the identification of intracranial infection after neurosurgery. METHODS: Owing to their symptoms and laboratory results, 168 patients with suspected intracranial infection after neurosurgery were divided into 3 groups: post-neurosurgical bacterial meningitis (PNBM; n = 61), post-neurosurgical aseptic meningitis (PNAM; n = 45), and non-PNM (n = 62). We measured lactate (LA), ß-2TF, and TF levels in the CSF. RESULTS: CSF LA levels were significantly higher in the PNM, PNBM, and PNAM groups compared with the non-PNM group ( P < .05). The CSF ß-2TF level in PNM, PNBM, and PNAM were statistically higher than those in non-PNMs ( P < .05). CSF TF levels in the PNBM group were statistically higher than those in the PNAM and non-PNM groups ( P < .05). The PNBM and non-PNM receiver operating curve (ROC) analysis indicates that the cutoff values for the combination (LA, ß-2TF, TF) was 0.349, and the area under the curve (AUC) was 0.945 ( P < .0001), with 92.86% sensitivity and 92.98% specificity. The PNAM and non-PNM ROC analysis indicates that the cutoff values for the combination (LA, ß-2TF, TF) was 0.346, and the AUC was 0.962 ( P < .0001), with 89.29% sensitivity and 90.24% specificity. The PNM and non-PNM ROC analysis indicates that the cutoff values for the combination (LA, ß-2TF, TF) was 0.609, and the AUC was 0.941 ( P < .0001), with 96.36% sensitivity and 82.83% specificity. A Glasgow Coma Scale score ≤8, LA, ß-2TF/TF ratio, length of hospital stay, intensive care unit admission, poor surgical wound, and craniotomy were associated with poor outcomes ( P < .05). LA and ß-2TF were independent risk factors for intracranial infection. CONCLUSION: Postoperative cerebral infections can be identified using CSF ß-2TF as a particular marker protein. CSF TF helps distinguish PNBM from PNAM. Combining CSF LA with them improves diagnostic speed, sensitivity, and accuracy. LA and ß-2TF were independent risk factors for cerebral infection.

Identification of potential biomarkers for neuromyelitis optica by quantitative proteomics.

OBJECTIVE: Neuromyelitis optica (NMO) was a serious autoimmune inflammatory condition affecting the central nervous system. Currently, there was a lack of diagnostic biomarkers for AQP4-IgG-negative NMO patients. METHODS: A comparative proteomic analysis was conducted on the CSF of 10 patients with NMO and 10 patients with non-inflammatory neurological disorders (NND) using tandem mass tagging technology. Differentially expressed proteins (DEPs) were analyzed using bioinformatic methods. The candidate proteins were then validated through ELISAs in a subsequent cohort of 160 samples, consisting of paired CSF and plasma samples from 50 NMO patients, CSF samples from 30 NND patients, and plasma samples from 30 healthy individuals. RESULTS: We identified 389 proteins via proteomics, screening 79 DEPs. NCAM1, SST and AHSG were selected as candidate molecules for further validation. Compared to NND patients, there were decreased levels of AHSG in CSF and increased levels of NCAM1 and SST in NMO patients. The ELISA results revealed significantly higher levels of AHSG, SST and NCAM1 in the CSF of the NMO group compared to the NND group. Similarly, the serum levels of these three proteins were also higher in the NMO group compared to the healthy control group. It was found that serum NCAM1 levels significantly decreased in patients with non-relapsed NMO compared to patients with relapsed NMO and CSF NCAM1 level increased in patients with bilateral NMO compared to patients with unilateral NMO. Furthermore, CSF SST levels increased in AQP4 antibody-positive NMO patients compared to AQP4 antibody-negative patients. INTERPRETATION: CSF NCAM1, serum NCAM1 and serum SST may serve as potential biomarkers for NMO patients and aid in the diagnosis of AQP4 antibody-negative NMO patients.

Serum apoptosis-associated speck-like protein containing a caspase-recruitment domain (ASC) is a novel stroke biomarker.

BACKGROUND: Apoptosis-associated speck-like protein containing a caspase-recruitment domain (ASC) is a promising stroke biomarker. However, a large study of human serum ASC has not yet to be reported; additionally, the diagnostic value of prehospital concentration and practicality of ASC remains unknown. METHODS: We recruited 774 Chinese stroke patients, including 523 with ischemic stroke (IS) and 251 with hemorrhagic stroke (HS) within 14 days following symptom onset in the emergency department, alongside 481 healthy individuals and 64 cognitive impairment patients as controls. Serum ASC concentrations were determined using automated chemiluminescence immunoassay, exploring the relationship between serum ASC concentration and subtypes, severity, and sampling timepoints of stroke. RESULTS: ASC concentrations were significantly higher in stroke patients compared with all controls (P < 0.001). HS patients had greater ASC concentrations than IS patients (P < 0.05). With increasing ASC concentration, the proportion of severe cases increased. The area under the receiver operating characteristic curve (AUC) for differentiating between healthy individuals and stroke patients in the hyperacute phase was 0.78; this markedly improved (0.90) when considering samples from healthy individuals and patients with subarachnoid hemorrhage (SAH) ≤ 3  h from last-known-well (LKW). CONCLUSIONS: Serum ASC is a valuable biomarker for stroke differentiation and aids in the clinical diagnosis of stroke severity and subtypes.

Identification of heterogeneous subtypes and a prognostic model for gliomas based on mitochondrial dysfunction and oxidative stress-related genes.

Objective: Mitochondrial dysfunction and oxidative stress are known to involved in tumor occurrence and progression. This study aimed to explore the molecular subtypes of lower-grade gliomas (LGGs) based on oxidative stress-related and mitochondrial-related genes (OMRGs) and construct a prognostic model for predicting prognosis and therapeutic response in LGG patients. Methods: A total of 223 OMRGs were identified by the overlap of oxidative stress-related genes (ORGs) and mitochondrial-related genes (MRGs). Using consensus clustering analysis, we identified molecular subtypes of LGG samples from TCGA database and confirmed the differentially expressed genes (DEGs) between clusters. We constructed a risk score model using LASSO regression and analyzed the immune-related profiles and drug sensitivity of different risk groups. The prognostic role of the risk score was confirmed using Cox regression and Kaplan-Meier curves, and a nomogram model was constructed to predict OS rates. We validated the prognostic role of OMRG-related risk score in three external datasets. Quantitative real-time PCR (qRT-PCR) and immunohistochemistry (IHC) staining confirmed the expression of selected genes. Furthermore, wound healing and transwell assays were performed to confirm the gene function in glioma. Results: We identified two OMRG-related clusters and cluster 1 was significantly associated with poor outcomes (P<0.001). The mutant frequencies of IDH were significantly lower in cluster 1 (P<0.05). We found that the OMRG-related risk scores were significantly correlated to the levels of immune infiltration and immune checkpoint expression. High-risk samples were more sensitive to most chemotherapeutic agents. We identified the prognostic role of OMRG-related risk score in LGG patients (HR=2.665, 95%CI=1.626-4.369, P<0.001) and observed that patients with high-risk scores were significantly associated with poor prognosis (P<0.001). We validated our findings in three external datasets. The results of qRT-PCR and IHC staining verified the expression levels of the selected genes. The functional experiments showed a significant decrease in the migration of glioma after knockdown of SCNN1B. Conclusion: We identified two molecular subtypes and constructed a prognostic model, which provided a novel insight into the potential biological function and prognostic significance of mitochondrial dysfunction and oxidative stress in LGG. Our study might help in the development of more precise treatments for gliomas.

High ECM2 Expression Predicts Poor Clinical Outcome and Promotes the Proliferation, Migration, and Invasiveness of Glioma.

OBJECTIVE: Glioma is the most prevalent and fatal intracranial malignant tumor. Extracellular matrix protein 2 (ECM2) has rarely been studied in gliomas. Therefore, we explored the role of ECM2 in lower-grade gliomas (LGGs). METHODS: The RNA-seq and clinicopathology data were obtained from the TCGA database. The immunohistochemical (IHC) staining was used to verify the expression of ECM2. Functional enrichment analyses, immune-related analyses, drug sensitivity, and mutation profile analyses were further conducted. Cox regression and Kaplan-Meier curves were utilized for survival analyses, while four external datasets were used to validate the prognostic role of ECM2. Furthermore, qRT-PCR, CCK-8, wound healing, and transwell assays were performed to confirm the function of ECM2 in gliomas. RESULTS: The study found a significant upregulation of ECM2 expression with increasing glioma grades and a significant association between ECM2 expression and tumor immune infiltration. Cox regression verified the prognostic role of ECM2 in LGG patients (HR = 1.656, 95%CI = 1.055-2.600, p = 0.028). High ECM2 expression was significantly associated with poor outcome (p < 0.001). Four external datasets validated its prognostic value. After the knockdown of ECM2, the functional experiments showed a significant decrease in proliferation, migration, and invasion in glioma cell lines. CONCLUSION: The study suggested the potential of ECM2 as a novel immune-associated prognostic biomarker and therapeutic target for glioma patients.

Effect of Follow-Up Cerebrospinal Fluid Cultures in Post-Neurosurgical Patients' Outcome with Gram-Negative Bacterial Meningitis/Encephalitis.

Background: To investigate the factors associated with follow-up CSF cultures (FUCCs) in post-neurosurgical patients with gram-negative bacterial meningitis/encephalitis and the effect of FUCCs on treatment management and patient outcomes. Methods: This single-centered retrospective cohort study enrolled post-neurosurgical patients with gram-negative bacterial meningitis/encephalitis at a tertiary-care university hospital between 2012 and 2022. The risk factors for 28-day mortality were evaluated using multivariate Cox analysis. FUCC-related risk factors were also analyzed. Results: Among the 844 enrolled patients, 504 (59.7%) underwent FUCC, and FUCC was found to be associated with lower rates of both all-cause (hazard ratio (HR) 0.391; 95% confidence interval (CI), 0.235-0.651; p<0.001) and attributable mortality (HR 0.463; 95% CI, 0.239-0.897; p=0.023) in Post-neurosurgical patients diagnosed with Gram-negative bacterial meningitis/encephalitis. Moreover, the results of the study underscored that patients with persistent gram-negative bacterial meningitis/encephalitis had a lower all-cause/attributable short-term survival rate according to 28-day mortality Kaplan-Meier analysis (P=0.001/0.006). Conclusion: Performing FUCC has been demonstrated to lower mortality rates in Post-neurosurgical patients suffering from Gram-negative bacterial meningitis/encephalitis. The higher mortality rate observed in patients with persistent gram-negative bacterial meningitis/encephalitis suggests that performing FUCC is a crucial component of proper patient care and management, and is therefore recommended for use by clinicians as a standard practice. This finding underscores the significance of consistent implementation of FUCC in the management and prognosis of patients with Post-neurosurgical infections.

The analysis of serum lipids profile in Guillain-Barre syndrome.

Background: Guillain-Barre syndrome (GBS) is an immune-mediated inflammatory peripheral neuropathy. This study aimed to conduct a systematic analysis of the serum lipids profile in GBS. Methods: We measured the serum lipids profile in 85 GBS patients and compared it with that of 85 healthy controls matched for age and sex. Additionally, we analyzed the correlation between lipids and the severity, subtypes, precursor infections, clinical outcomes, clinical symptoms, immunotherapy, and other laboratory markers of GBS. Results: Compared to the healthy controls, GBS exhibited significantly elevated levels of Apolipoprotein B (APOB), Apolipoprotein C2 (APOC2), Apolipoprotein C3 (APOC3), Apolipoprotein E (APOE), triglycerides (TG), and residual cholesterol (RC). Conversely, Apolipoprotein A1 (APOA1), Apolipoprotein A2 (APOA2), and high-density lipoprotein (HDL) were substantially lower in GBS. Severe GBS displayed noticeably higher levels of APOC3 and total cholesterol (TC) compared to those with mild disease. Regarding different clinical outcomes, readmitted GBS demonstrated higher RC expression than those who were not readmitted. Moreover, GBS who tested positive for neuro-virus antibody IGG in cerebrospinal fluid (CSF) exhibited heightened expression of APOC3 in comparison to those who tested negative. GBS with cranial nerve damage showed significantly reduced expression of HDL and APOA1 than those without such damage. Additionally, GBS experiencing limb pain demonstrated markedly decreased HDL expression. Patients showed a significant reduction in TC after intravenous immunoglobulin therapy. We observed a significant positive correlation between lipids and inflammatory markers, including TNF-α, IL-1ß, erythrocyte sedimentation rate (ESR), white blood cells, monocytes, and neutrophils in GBS. Notably, APOA1 exhibited a negative correlation with ESR. Furthermore, our findings suggest a potential association between lipids and the immune status of GBS. Conclusion: The research demonstrated a strong connection between lipids and the severity, subtypes, clinical outcomes, precursor infections, clinical symptoms, immunotherapy, inflammation, and immune status of GBS. This implies that a low-fat diet or the use of lipid-lowering medications may potentially serve as an approach for managing GBS, offering a fresh viewpoint for clinical treatment of this condition.

Remnant Cholesterol and Dyslipidemia Are Risk Factors for Guillain-Barré Syndrome and Severe Guillain-Barré Syndrome by Promoting Monocyte Activation.

Background: Guillain-Barré syndrome (GBS) is the most common severe acute paralytic neuropathy, with a mortality rate of 5% and permanent sequelae rate of 10%. Currently, the cause of GBS remains unclear. Therefore, we sought to determine potential predictors for GBS and its severity. Methods: A case-control study was performed at Tiantan Hospital in Beijing from January 2017 to December 2021. Laboratory and clinical characteristics were assessed in recruited GBS patients and healthy control individuals (matched by sex and age). The potential risk factors for GBS and severe GBS were assessed using a logistic regression analysis. The mRNA levels of toll-like receptor 4 (TLR4), toll-like receptor 2 (TLR2) and nuclear factor κB (NF-κB) in GBS patients and control PBMCs were detected by fluorescence quantitative PCR. THP-1 cells were costimulated with LPS and free cholesterol to demonstrate the effect of free cholesterol on monocyte activation. Results: A total of 147 GBS patients and 153 healthy individuals were included in the study. Logistic regression analyses showed that preceding infection, alcohol consumption, remnant cholesterol, homocysteine and the dyslipidemia index were correlated with a higher risk of GBS. In contrast, increased HDL cholesterol was correlated with a lower risk of GBS. Moreover, remnant cholesterol and the dyslipidemia index were significantly correlated with severe GBS. The mRNA levels of TLR4, TLR2 and NF-κB in the PBMCs of GBS patients were significantly higher than those of healthy individuals. LPS activated THP-1 cells, and free cholesterol treatment increased the expression of TLR4, TLR2, NF-κB and IL-1ß mRNA in LPS-activated THP-1 cells. Conclusion: Dyslipidemia was correlated with the risk of GBS and severe GBS. Remnant cholesterol may promote the activation of monocytes in GBS patients. It may be valuable to control lipid levels in the prevention of GBS and severe GBS.

Dual-detection fluorescent immunochromatographic assay for quantitative detection of SARS-CoV-2 spike RBD-ACE2 blocking neutralizing antibody.

The global effort against the COVID-19 pandemic dictates that routine quantitative detection of SARS-CoV-2 neutralizing antibodies is vital for assessing immunity following periodic revaccination against new viral variants. Here, we report a dual-detection fluorescent immunochromatographic assay (DFIA), with a built-in self-calibration process, that enables rapid quantitative detection of neutralizing antibodies that block binding between the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein and the angiotensin-converting enzyme 2 (ACE2). Thus, this assay is based on the inhibition of binding between ACE2 and the RBD of the SARS-CoV-2 spike protein by neutralizing antibodies, and the affinity of anti-human immunoglobulins for these neutralizing antibodies. Our self-calibrating DFIA shows improved precision and sensitivity with a wider dynamic linear range, due to the incorporation of a ratiometric algorithm of two-reverse linkage signals responding to an analyte. This was evident by the fact that no positive results (0/14) were observed in verified negative samples, while 22 positives were detected in 23 samples from verified convalescent plasma. A comparative analysis of the ability to detect neutralizing antibodies in 266 clinical serum samples including those from vaccine recipients, indicated that the overall percent agreement between DFIA and the commercial ELISA kit was 90.98%. Thus, the proposed DFIA provides a more reliable and accurate rapid test for detecting SARS-CoV-2 infections and vaccinations in the community. Therefore, the DFIA based strategy for detecting biomarkers, which uses a ratiometric algorithm based on affinity and inhibition reactions, may be applied to improve the performance of immunochromatographic assays.

Discovery of Novel Biomarkers for Diagnosing and Predicting the Progression of Multiple Sclerosis Using TMT-Based Quantitative Proteomics.

Objective: Here, we aimed to identify protein biomarkers that could rapidly and accurately diagnose multiple sclerosis (MS) using a highly sensitive proteomic immunoassay. Methods: Tandem mass tag (TMT) quantitative proteomic analysis was performed to determine the differentially expressed proteins (DEPs) in cerebrospinal fluid (CSF) samples collected from 10 patients with MS and 10 non-inflammatory neurological controls (NINCs). The DEPs were analyzed using bioinformatics tools, and the candidate proteins were validated using the ELISA method in another cohort comprising 160 samples (paired CSF and plasma of 40 patients with MS, CSF of 40 NINCs, and plasma of 40 healthy individuals). Receiver operating characteristic (ROC) curves were used to determine the diagnostic potential of this method. Results: Compared to NINCs, we identified 83 CSF-specific DEPs out of a total of 343 proteins in MS patients. Gene ontology (GO) enrichment analysis revealed that these DEPs are mainly involved in platelet degranulation, negative regulation of proteolysis, and post-translational protein modification. Pathway enrichment analysis revealed that the complement and coagulation cascades, Ras signaling pathway, and PI3K-Akt signaling pathway are the main components. Insulin-like growth factor-binding protein 7 (IGFBP7), insulin-like growth factor 2 (IGF2), and somatostatin (SST) were identified as the potential proteins with high scores, degree, and centrality in the protein-protein interaction (PPI) network. We validated the expression of these three proteins using ELISA. Compared to NINCs, the level of CSF IGFBP7 was significantly upregulated, and the level of CSF SST was significantly downregulated in the MS group. Conclusion: Our results suggest that SST and IGFBP7 might be associated with the pathogenesis of MS and would be helpful in diagnosing MS. Since IGFBP7 was used to classify relapsing remitting MS (RRMS) and secondary progressive MS (SPMS) patients, therefore, it may act as a potential key marker and therapeutic target in MS.