Modeling the Simultaneous Dynamics of Proteins in Blood Plasma and the Cerebrospinal Fluid in Human In Vivo.

The analysis of protein dynamics or turnover in patients has the potential to reveal altered protein recycling, such as in Alzheimer's disease, and to provide informative data regarding drug efficacy or certain biological processes. The observed protein dynamics in a solid tissue or a fluid is the net result of not only protein synthesis and degradation but also transport across biological compartments. We report an accurate 3-biological compartment model able to simultaneously account for the protein dynamics observed in blood plasma and the cerebrospinal fluid (CSF) including a hidden central nervous system (CNS) compartment. We successfully applied this model to 69 proteins of a single individual displaying similar or very different dynamics in plasma and CSF. This study puts a strong emphasis on the methods and tools needed to develop this type of model. We believe that it will be useful to any researcher dealing with protein dynamics data modeling.

Cerebrospinal fluid reference proteins increase accuracy and interpretability of biomarkers for brain diseases.

Cerebrospinal fluid (CSF) biomarkers reflect brain pathophysiology and are used extensively in translational research as well as in clinical practice for diagnosis of neurological diseases, e.g., Alzheimer's disease (AD). However, CSF biomarker concentrations may be influenced by non-disease related inter-individual variability. Here we use a data-driven approach to demonstrate the existence of inter-individual variability in mean standardized CSF protein levels. We show that these non-disease related differences cause many commonly reported CSF biomarkers to be highly correlated, thereby producing misleading results if not accounted for. To adjust for this inter-individual variability, we identified and evaluated high-performing reference proteins which improved the diagnostic accuracy of key CSF AD biomarkers. Our reference protein method attenuates the risk for false positive findings, and improves the sensitivity and specificity of CSF biomarkers, with broad implications for both research and clinical practice.

Diagnostic, monitoring, and prognostic value of combined detection of cerebrospinal fluid heparin-binding protein, interleukin-6, interleukin-10, and procalcitonin for post-neurosurgical intracranial infection.

OBJECTIVE: Intracranial infection is a common complication after neurosurgery and can increase the length of hospital stay, affect patient prognosis, and increase mortality. We aimed to investigate the value of the combined detection of cerebrospinal fluid (CSF) heparin-binding protein (HBP), interleukin-6 (IL-6), interleukin-10 (IL-10), and procalcitonin (PCT) for post-neurosurgical intracranial infection. METHODS: This study assessed the diagnostic values of CSF HBP, IL-6, IL-10, PCT levels, and combined assays for post-neurosurgical intracranial infection with the area under the receiver operating characteristic (ROC) curve by retrospectively analysing biomarkers of post-neurosurgical patients. RESULTS: The CSF HBP, IL-6, IL-10, and PCT levels were significantly higher in the infected group than the uninfected group and the control group (P < 0.001). The indicators in the groups with severe intracranial infections were significantly higher than those in the groups with mild intracranial infections (P < 0.001), and the groups with poor prognoses had significantly higher indexes than the groups with good prognoses. According to the ROC curve display, the AUC values of CSF HBP, IL-6, IL-10, and PCT were 0.977 (95 % CI 0.952-1.000), 0.973 (95 % CI 0.949-0.998), 0.884 (95 % CI 0.823-0.946), and 0.819 (95 % CI 0.733-0.904), respectively. The AUC of the combined test was 0.996 (95 % CI 0.989-1.000), which was higher than those of the four indicators alone. CONCLUSION: The combined detection can be an important indicator for the diagnosis and disease monitoring of post-neurosurgical intracranial infection.

Mass spectrometry-based proteomics of cerebrospinal fluid in pediatric central nervous system malignancies: a systematic review with meta-analysis of individual patient data.

BACKGROUND: The cerebrospinal fluid (CSF) proteome could offer important insights into central nervous system (CNS) malignancies. To advance proteomic research in pediatric CNS cancer, the current study aims to (1) evaluate past mass spectrometry-based workflows and (2) synthesize previous CSF proteomic data, focusing on both qualitative summaries and quantitative re-analysis. MAIN: In our analysis of 11 studies investigating the CSF proteome in pediatric patients with acute lymphoblastic leukemia (ALL) or primary brain tumors, we observed significant methodological variability. This variability negatively affects comparative analysis of the included studies, as per GRADE criteria for quality of evidence. The qualitative summaries covered 161 patients and 134 non-tumor controls, while the application of validation cohort varied among the studies. The quantitative re-analysis comprised 15 B-ALL vs 6 "healthy" controls and 15 medulloblastoma patients vs 22 non-tumor controls. Certain CSF proteins were identified as potential indicators of specific malignancies or stages of neurotoxicity during chemotherapy, yet definitive conclusions were impeded by inconsistent data. There were no proteins with statistically significant differences when comparing cases versus controls that were corroborated across studies where quantitative reanalysis was feasible. From a gene ontology enrichment, we observed that age disparities between unmatched case and controls may mislead to protein correlations more indicative of age-related CNS developmental stages rather than neuro-oncological disease. Despite efforts to batch correct (HarmonizR) and impute missing values, merging of dataset proved unfeasible and thereby limited meaningful data integration across different studies. CONCLUSION: Infrequent publications on rare pediatric cancer entities, which often involve small sample sizes, are inherently prone to result in heterogeneous studies-particularly when conducted within a rapidly evolving field like proteomics. As a result, obtaining clear evidence, such as CSF proteome biomarkers for CNS dissemination or early-stage neurotoxicity, is currently impractical. Our general recommendations comprise the need for standardized methodologies, collaborative efforts, and improved data sharing in pediatric CNS malignancy research. We specifically emphasize the possible importance of considering natural age-related variations in CSF due to different CNS development stages when matching cases and controls in future studies.

A protein panel in cerebrospinal fluid for diagnostic and predictive assessment of Alzheimer's disease.

Alzheimer's disease (AD) is a neurodegenerative disease with heterogenous pathophysiological changes that develop years before the onset of clinical symptoms. These preclinical changes have generated considerable interest in identifying markers for the pathophysiological mechanisms linked to AD and AD-related disorders (ADRD). On the basis of our prior work integrating cerebrospinal fluid (CSF) and brain proteome networks, we developed a reliable and high-throughput mass spectrometry-selected reaction monitoring assay that targets 48 key proteins altered in CSF. To test the diagnostic utility of these proteins and compare them with existing AD biomarkers, CSF collected at baseline visits was assayed from 706 participants recruited from the Alzheimer's Disease Neuroimaging Initiative. We found that the targeted CSF panel of 48 proteins (CSF 48 panel) performed at least as well as existing AD CSF biomarkers (Aß42, tTau, and pTau181) for predicting clinical diagnosis, FDG PET, hippocampal volume, and measures of cognitive and dementia severity. In addition, for each of those outcomes, the CSF 48 panel plus the existing AD CSF biomarkers significantly improved diagnostic performance. Furthermore, the CSF 48 panel plus existing AD CSF biomarkers significantly improved predictions for changes in FDG PET, hippocampal volume, and measures of cognitive decline and dementia severity compared with either measure alone. A potential reason for these improvements is that the CSF 48 panel reflects a range of altered biology observed in AD/ADRD. In conclusion, we show that the CSF 48 panel complements existing AD CSF biomarkers to improve diagnosis and predict future cognitive decline and dementia severity.

ADAM10 Gene Variants in AD Patients and Their Relationship to CSF Protein Levels.

ADAM10 is the main α-secretase acting in the non-amyloidogenic processing of APP. We hypothesized that certain rare ADAM10 variants could increase the risk for AD by conferring the age-related downregulation of α-secretase. The ADAM10 gene was sequenced in 103 AD cases (82% familial) and 96 cognitively preserved nonagenarians. We examined rare variants (MAF < 0.01) and determined their potential association in the AD group with lower CSF protein levels, as analyzed by means of ELISA, and Western blot (species of 50 kDa, 55 kDa, and 80 kDa). Rare variants were found in 15.5% of AD cases (23% early-onset, 8% late-onset) and in 12.5% of nonagenarians, and some were group-specific. All were intronic variants except Q170H, found in three AD cases and one nonagenarian. The 3'UTR rs74016945 (MAF = 0.01) was found in 6% of the nonagenarians (OR 0.146, p = 0.057). Altogether, ADAM10 total levels or specific species were not significantly different when comparing AD with controls or carriers of rare variants versus non-carriers (except a Q170H carrier exhibiting low levels of all species), and did not differ according to the age at onset or APOE genotype. We conclude that ADAM10 exonic variants are uncommon in AD cases, and the presence of rare intronic variants (more frequent in early-onset cases) is not associated with decreased protein levels in CSF.

Population-Based Evaluation of Total Protein in Cerebrospinal Fluid.

OBJECTIVES: To present a normal range of cerebrospinal fluid (CSF) protein levels in a community-based population and to evaluate factors that contribute to CSF protein level variability. PATIENTS AND METHODS: Samples of CSF protein were obtained from participants aged 32 to 95 years who underwent lumbar puncture (LP) between November 1, 2007, and October 1, 2017, as part of the Mayo Clinic Study of Aging, a longitudinal, population-based study of residents of Olmsted County, Minnesota. RESULTS: A total of 633 participants (58.1% male; 99.1% White; mean ± SD age, 70.9±11.6 years) underwent LP with recorded CSF protein level. Mean ± SD CSF protein level was 52.2±18.4 mg/dL (to convert to mg/L, multiply by 10), with a 95% reference interval of 24.0 to 93.4 mg/dL (range, 14.0-148.0 mg/dL). Spinal stenosis and arterial hypertension were associated with higher CSF protein levels on univariable analysis (P<.001). Increasing age, male sex, and diabetes were all independently associated with higher CSF protein levels on multivariable analysis (P<.001). In the 66 participants with repeated LPs within 2.5 years, the coefficient of repeatability was 26.1 mg/dL. Eleven participants (16.7%) had a CSF protein level difference of 20 mg/dL or more between serial LPs, and 4 (6.1%) had a difference of 25 mg/dL or more. There was a trend toward greater CSF protein level variability in patients with spinal stenosis (P=.054). CONCLUSION: This large population-based study showed that CSF protein level can vary significantly among individuals. Elevated CSF protein level was independently associated with older age, male sex, and diabetes and is higher than listed in many laboratories. These findings emphasize the necessity of evidence-based reevaluation and standardization of CSF protein metrics.

Limited Proteolysis-Mass Spectrometry Reveals Aging-Associated Changes in Cerebrospinal Fluid Protein Abundances and Structures.

Cerebrospinal fluid (CSF) proteins and their structures have been implicated repeatedly in aging and neurodegenerative diseases. Limited proteolysis-mass spectrometry (LiP-MS) is a method that enables proteome-wide screening for changes in both protein abundance and structure. To screen for novel aging-associated changes in the CSF proteome, we performed LiP-MS on CSF from young and old mice with a modified analysis pipeline. We found 38 protein groups change in abundance with aging, most dominantly immunoglobulins of the IgM subclass. We discovered six high-confidence candidates that appeared to change in structure with aging, of which Kng1, Itih2, Lp-PLA2, and 14-3-3 proteins have binding partners or proteoforms known previously to change in the brain with Alzheimer's disease. Intriguingly, using orthogonal validation by Western blot we found the LiP-MS hit Cd5l forms a covalent complex with IgM in mouse and human CSF whose abundance increases with aging. SOMAmer probe signals for all six LiP-MS hits in human CSF, especially 14-3-3 proteins, significantly associate with several clinical features relevant to cognitive function and neurodegeneration. Together, our findings show that LiP-MS can uncover age-related structural changes in CSF with relevance to neurodegeneration.

Identification and Clinical Validation of Key Extracellular Proteins as the Potential Biomarkers in Relapsing-Remitting Multiple Sclerosis.

Background: Multiple sclerosis (MS) is a demyelinating disease of the central nervous system (CNS) mediated by autoimmunity. No objective clinical indicators are available for the diagnosis and prognosis of MS. Extracellular proteins are most glycosylated and likely to enter into the body fluid to serve as potential biomarkers. Our work will contribute to the in-depth study of the functions of extracellular proteins and the discovery of disease biomarkers. Methods: MS expression profiling data of the human brain was downloaded from the Gene Expression Omnibus (GEO). Extracellular protein-differentially expressed genes (EP-DEGs) were screened by protein annotation databases. GO and KEGG were used to analyze the function and pathway of EP-DEGs. STRING, Cytoscape, MCODE and Cytohubba were used to construct a protein-protein interaction (PPI) network and screen key EP-DEGs. Key EP-DEGs levels were detected in the CSF of MS patients. ROC curve and survival analysis were used to evaluate the diagnostic and prognostic ability of key EP-DEGs. Results: We screened 133 EP-DEGs from DEGs. EP-DEGs were enriched in the collagen-containing extracellular matrix, signaling receptor activator activity, immune-related pathways, and PI3K-Akt signaling pathway. The PPI network of EP-DEGs had 85 nodes and 185 edges. We identified 4 key extracellular proteins IL17A, IL2, CD44, IGF1, and 16 extracellular proteins that interacted with IL17A. We clinically verified that IL17A levels decreased, but Del-1 and resolvinD1 levels increased. The diagnostic accuracy of Del-1 (AUC: 0.947) was superior to that of IgG (AUC: 0.740) with a sensitivity of 82.4% and a specificity of 100%. High Del-1 levels were significantly associated with better relapse-free and progression-free survival. Conclusion: IL17A, IL2, CD44, and IGF1 may be key extracellular proteins in the pathogenesis of MS. IL17A, Del-1, and resolvinD1 may co-regulate the development of MS and Del-1 is a potential biomarker of MS. We used bioinformatics methods to explore the biomarkers of MS and validated the results in clinical samples. The study provides a theoretical and experimental basis for revealing the pathogenesis of MS and improving the diagnosis and prognosis of MS.

Longitudinal Bottom-Up Proteomics of Serum, Serum Extracellular Vesicles, and Cerebrospinal Fluid Reveals Candidate Biomarkers for Early Detection of Glioblastoma in a Murine Model.

Glioblastoma Multiforme (GBM) is a brain tumor with a poor prognosis and low survival rates. GBM is diagnosed at an advanced stage, so little information is available on the early stage of the disease and few improvements have been made for earlier diagnosis. Longitudinal murine models are a promising platform for biomarker discovery as they allow access to the early stages of the disease. Nevertheless, their use in proteomics has been limited owing to the low sample amount that can be collected at each longitudinal time point. Here we used optimized microproteomics workflows to investigate longitudinal changes in the protein profile of serum, serum small extracellular vesicles (sEVs), and cerebrospinal fluid (CSF) in a GBM murine model. Baseline, pre-symptomatic, and symptomatic tumor stages were determined using non-invasive motor tests. Forty-four proteins displayed significant differences in signal intensities during GBM progression. Dysregulated proteins are involved in cell motility, cell growth, and angiogenesis. Most of the dysregulated proteins already exhibited a difference from baseline at the pre-symptomatic stage of the disease, suggesting that early effects of GBM might be detectable before symptom onset.

Assessing the Preanalytical Variability of Plasma and Cerebrospinal Fluid Processing and Its Effects on Inflammation-Related Protein Biomarkers.

Proteomics studies are important for the discovery of new biomarkers as clinical tools for diagnosis and disease monitoring. However, preanalytical variations caused by differences in sample handling protocol pose challenges for assessing biomarker reliability and comparability between studies. The purpose of this study was to examine the effects of delayed centrifuging on measured protein levels in plasma and cerebrospinal fluid (CSF). Blood from healthy individuals and patients with multiple sclerosis along with CSF from patients with suspected neurological disorders were left at room temperature for different periods (blood: 1, 24, 48, 72 h; CSF: 1 and 6 h) prior to centrifuging. Ninety-one inflammation-related proteins were analyzed using a proximity extension assay, a high-sensitivity multiplex immunoassay. Additional metabolic and neurology-related markers were also investigated in CSF. In summary, many proteins, particularly in plasma, had increased levels with longer delays in processing likely due in part to intracellular leakage. Levels of caspase 8, interleukin 8, interleukin 18, sirtuin 2, and sulfotransferase 1A1 increased 2-fold to 10-fold in plasma after 24 h at room temperature. Similarly, levels of cathepsin H, ectonucleoside triphosphate diphosphohydrolase 5, and WW domain containing E3 ubiquitin protein ligase 2 differentiated in CSF with <6 h delay in processing. However, the rate of change for many proteins was relatively consistent; therefore, we were able to characterize biomarkers for detecting sample handling variability. Our findings highlight the importance of timely and consistent sample collection and the need for increased awareness of protein susceptibility to sample handling bias. In addition, suggested biomarkers may be used in certain situations to detect and correct for preanalytical variation in future studies.

Proteomic landscape of Alzheimer's Disease: novel insights into pathogenesis and biomarker discovery.

Mass spectrometry-based proteomics empowers deep profiling of proteome and protein posttranslational modifications (PTMs) in Alzheimer's disease (AD). Here we review the advances and limitations in historic and recent AD proteomic research. Complementary to genetic mapping, proteomic studies not only validate canonical amyloid and tau pathways, but also uncover novel components in broad protein networks, such as RNA splicing, development, immunity, membrane transport, lipid metabolism, synaptic function, and mitochondrial activity. Meta-analysis of seven deep datasets reveals 2,698 differentially expressed (DE) proteins in the landscape of AD brain proteome (n = 12,017 proteins/genes), covering 35 reported AD genes and risk loci. The DE proteins contain cellular markers enriched in neurons, microglia, astrocytes, oligodendrocytes, and epithelial cells, supporting the involvement of diverse cell types in AD pathology. We discuss the hypothesized protective or detrimental roles of selected DE proteins, emphasizing top proteins in "amyloidome" (all biomolecules in amyloid plaques) and disease progression. Comprehensive PTM analysis represents another layer of molecular events in AD. In particular, tau PTMs are correlated with disease stages and indicate the heterogeneity of individual AD patients. Moreover, the unprecedented proteomic coverage of biofluids, such as cerebrospinal fluid and serum, procures novel putative AD biomarkers through meta-analysis. Thus, proteomics-driven systems biology presents a new frontier to link genotype, proteotype, and phenotype, accelerating the development of improved AD models and treatment strategies.

Higher CSF sTNFR1-related proteins associate with better prognosis in very early Alzheimer's disease.

Neuroinflammation is associated with Alzheimer's disease, but the application of cerebrospinal fluid measures of inflammatory proteins may be limited by overlapping pathways and relationships between them. In this work, we measure 15 cerebrospinal proteins related to microglial and T-cell functions, and show them to reproducibly form functionally-related groups within and across diagnostic categories in 382 participants from the Alzheimer's Disease Neuro-imaging Initiative as well participants from two independent cohorts. We further show higher levels of proteins related to soluble tumor necrosis factor receptor 1 are associated with reduced risk of conversion to dementia in the multi-centered (p = 0.027) and independent (p = 0.038) cohorts of people with mild cognitive impairment due to predicted Alzheimer's disease, while higher soluble TREM2 levels associated with slower decline in the dementia stage of Alzheimer's disease. These inflammatory proteins thus provide prognostic information independent of established Alzheimer's markers.

Serum and cerebrospinal fluid host proteins indicate stroke in children with tuberculous meningitis.

INTRODUCTION: Stroke is a common complication in children with tuberculous meningitis (TBM). Host proteins may give us insight into the mechanisms of stroke in TBM and serve as biomarkers for detection of stroke, however, they have not been widely explored. In this study, we compared the concentrations of cerebrospinal fluid (CSF) and serum proteins between children who had TBM-related stroke and children with TBM without stroke. METHODS: We collected CSF and serum from 47 children consecutively admitted to the Tygerberg Academic Hospital in Cape Town, South Africa between November 2016, and November 2017, on suspicion of having TBM. A multiplex platform was used to measure the concentrations of 69 host proteins in CSF and serum from all study participants. RESULTS: After classification of study participants, 23 (48.9%) out of the 47 study participants were diagnosed with TBM, of which 14 (60.9%) demonstrated radiological arterial ischemic infarction. The levels of lipocalin-2, sRAGE, IP-10/ CXCL10, sVCAM-1, MMP-1, and PDGF-AA in CSF samples and the levels of D-dimer, ADAMTS13, SAA, ferritin, MCP-1/ CCL2, GDF-15 and IL-13 in serum samples were statistically different between children who had TBM-related stroke and children with TBM without stroke. After correcting for multiple testing, only the levels of sVCAM-1, MMP-1, sRAGE, and IP-10/ CXCL10 in CSF were statistically different between the two groups. CSF and serum protein biosignatures indicated stroke in children diagnosed with TBM with up to 100% sensitivity and 88.9% specificity. CONCLUSION: Serum and CSF proteins may serve as biomarkers for identifying individuals with stroke amongst children diagnosed with TBM at admission and may guide us to understand the biology of stroke in TBM. This was a pilot study, and thus further investigations in larger studies are needed.

Cerebrospinal fluid findings in patients with psychotic symptoms-a retrospective analysis.

In current international classification systems (ICD-10, DSM5), the diagnostic criteria for psychotic disorders (e.g. schizophrenia and schizoaffective disorder) are based on symptomatic descriptions since no unambiguous biomarkers are known to date. However, when underlying causes of psychotic symptoms, like inflammation, ischemia, or tumor affecting the neural tissue can be identified, a different classification is used ("psychotic disorder with delusions due to known physiological condition" (ICD-10: F06.2) or psychosis caused by medical factors (DSM5)). While CSF analysis still is considered optional in current diagnostic guidelines for psychotic disorders, CSF biomarkers could help to identify known physiological conditions. In this retrospective, partly descriptive analysis of 144 patients with psychotic symptoms and available CSF data, we analyzed CSF examinations' significance to differentiate patients with specific etiological factors (F06.2) from patients with schizophrenia, schizotypal, delusional, and other non-mood psychotic disorders (F2). In 40.3% of all patients, at least one CSF parameter was out of the reference range. Abnormal CSF-findings were found significantly more often in patients diagnosed with F06.2 (88.2%) as compared to patients diagnosed with F2 (23.8%, p < 0.00001). A total of 17 cases were identified as probably caused by specific etiological factors (F06.2), of which ten cases fulfilled the criteria for a probable autoimmune psychosis linked to the following autoantibodies: amphiphysin, CASPR2, CV2, LGl1, NMDA, zic4, and titin. Two cases presented with anti-thyroid tissue autoantibodies. In four cases, further probable causal factors were identified: COVID-19, a frontal intracranial tumor, multiple sclerosis (n = 2), and neurosyphilis. Twenty-one cases remained with "no reliable diagnostic classification". Age at onset of psychotic symptoms differed between patients diagnosed with F2 and F06.2 (p = 0.014), with the latter group being older (median: 44 vs. 28 years). Various CSF parameters were analyzed in an exploratory analysis, identifying pleocytosis and oligoclonal bands (OCBs) as discriminators (F06.2 vs. F2) with a high specificity of > 96% each. No group differences were found for gender, characteristics of psychotic symptoms, substance dependency, or family history. This study emphasizes the great importance of a detailed diagnostic workup in diagnosing psychotic disorders, including CSF analysis, to detect possible underlying pathologies and improve treatment decisions.

Cerebrospinal fluid analysis in dogs: Main patterns and prevalence of albuminocytological dissociation.

BACKGROUND: Albuminocytological dissociation (ACD) of the cerebrospinal fluid (CSF) is defined as an increased total protein concentration with normal total nucleated cell count. It is suspected to occur in diseases that alter the blood-brain barrier, increase the production of protein or obstruct the flow of CSF. The purposes of this study were to review the CSF analysis results of a large cohort of dogs with neurological conditions, to analyse the total prevalence of ACD and to describe which diseases have a higher prevalence of ACD. STUDY DESIGN AND METHODS: Medical records were retrospectively searched for dogs whom CSF was sampled from 2012-2019. Data collected included signalment, body weight, site of collection of the CSF, CSF analysis results, and final diagnosis. RESULTS: A total of 497 dogs met the inclusion criteria. ACD was identified in 16.5% (82/497) of dogs. The diseases with higher proportion of ACD were cranial nerve neuropathy (6/10; 60.0%), brain tumour (10/24; 41.7%), idiopathic vestibular disease (7/17; 41.2%) and brain vascular disease (4/13; 30.8%). CLINICAL SIGNIFICANCE: This study describes the CSF patterns of the most common neurological conditions in dogs, also characterizing, for the first time in dogs, the prevalence and causes of ACD, which was identified in 16.5% of the samples. The diseases with highest proportions of ACD were cranial nerve neuropathy, brain tumour, idiopathic vestibular disease and brain vascular disease.

Cerebrospinal fluid proteome shows disrupted neuronal development in multiple sclerosis.

Despite intensive research, the aetiology of multiple sclerosis (MS) remains unknown. Cerebrospinal fluid proteomics has the potential to reveal mechanisms of MS pathogenesis, but analyses must account for disease heterogeneity. We previously reported explorative multivariate analysis by hierarchical clustering of proteomics data of MS patients and controls, which resulted in two groups of individuals. Grouping reflected increased levels of intrathecal inflammatory response proteins and decreased levels of proteins involved in neural development in one group relative to the other group. MS patients and controls were present in both groups. Here we reanalysed these data and we also reanalysed data from an independent cohort of patients diagnosed with clinically isolated syndrome (CIS), who have symptoms of MS without evidence of dissemination in space and/or time. Some, but not all, CIS patients had intrathecal inflammation. The analyses reported here identified a common protein signature of MS/CIS that was not linked to elevated intrathecal inflammation. The signature included low levels of complement proteins, semaphorin-7A, reelin, neural cell adhesion molecules, inter-alpha-trypsin inhibitor heavy chain H2, transforming growth factor beta 1, follistatin-related protein 1, malate dehydrogenase 1 cytoplasmic, plasma retinol-binding protein, biotinidase, and transferrin, all known to play roles in neural development. Low levels of these proteins suggest that MS/CIS patients suffer from abnormally low oxidative capacity that results in disrupted neural development from an early stage of the disease.

Inflammatory Leptomeningeal Cytokines Mediate COVID-19 Neurologic Symptoms in Cancer Patients.

SARS-CoV-2 infection induces a wide spectrum of neurologic dysfunction that emerges weeks after the acute respiratory infection. To better understand this pathology, we prospectively analyzed of a cohort of cancer patients with neurologic manifestations of COVID-19, including a targeted proteomics analysis of the cerebrospinal fluid. We find that cancer patients with neurologic sequelae of COVID-19 harbor leptomeningeal inflammatory cytokines in the absence of viral neuroinvasion. The majority of these inflammatory mediators are driven by type II interferon and are known to induce neuronal injury in other disease states. In these patients, levels of matrix metalloproteinase-10 within the spinal fluid correlate with the degree of neurologic dysfunction. Furthermore, this neuroinflammatory process persists weeks after convalescence from acute respiratory infection. These prolonged neurologic sequelae following systemic cytokine release syndrome lead to long-term neurocognitive dysfunction. Our findings suggest a role for anti-inflammatory treatment(s) in the management of neurologic complications of COVID-19 infection.