NMR metabolomics of cerebrospinal fluid differentiates inflammatory diseases of the central nervous system

Multiscale metabolomics techniques: Insights into neuroscience research

The field of metabolomics examines the overall composition and dynamic patterns of metabolites in living organisms. The primary methods used in metabolomics include liquid chromatography (LC), nuclear magnetic resonance (NMR), and mass spectrometry (MS) analysis. These methods enable the identification and examination of metabolite types and contents within organisms, as well as modifications to metabolic pathways and their connection to the emergence of diseases. Research in metabolomics has extensive value in basic and applied sciences. The field of metabolomics is growing quickly, with the majority of studies concentrating on biomedicine, particularly early disease diagnosis, therapeutic management of human diseases, and mechanistic knowledge of biochemical processes. Multiscale metabolomics is an approach that integrates metabolomics techniques at various scales, including the holistic, tissue, cellular, and organelle scales, to enable more thorough and in-depth studies of metabolic processes in organisms. Multiscale metabolomics can be combined with methods from systems biology and bioinformatics. In recent years, multiscale metabolomics approaches have become increasingly important in neuroscience research due to the nervous system's high metabolic demands. Multiscale metabolomics can offer novel concepts and approaches for the diagnosis, treatment, and development of medication for neurological illnesses in addition to a more thorough understanding of brain metabolism and nervous system function. In this review, we summarize the use of multiscale metabolomics techniques in neuroscience, address the promise and constraints of these techniques, and provide an overview of the metabolome and its applications in neuroscience.

Mass spectrometry-based proteomic approaches for salivary protein biomarkers discovery and dental caries diagnosis: A critical review

Dental caries is a multifactorial chronic disease resulting from the intricate interplay among acid-generating bacteria, fermentable carbohydrates, and several host factors such as saliva. Saliva comprises several proteins which could be utilized as biomarkers for caries prevention, diagnosis, and prognosis. Mass spectrometry-based salivary proteomics approaches, owing to their sensitivity, provide the opportunity to investigate and unveil crucial cariogenic pathogen activity and host indicators and may demonstrate clinically relevant biomarkers to improve caries diagnosis and management. The present review outlines the published literature of human clinical proteomics investigations on caries and extensively elucidates frequently reported salivary proteins as biomarkers. This review also discusses important aspects while designing an experimental proteomics workflow. The protein-protein interactions and the clinical relevance of salivary proteins as biomarkers for caries, together with uninvestigated domains of the discipline are also discussed critically.

1H NMR Using Metabolic Study in Body Fluids for Diagnosis of Cryptococcal Meningitis in Adults

Background

Cryptococcal meningitis is considered to affect HIV patients and those with impaired immune systems. Early identification and treatment are the keys to decreasing morbidity and mortality related to CM. Using 1H NMR spectroscopy, a prospective case-control study will assess the metabolic profile of adults' serum, urine, and CSF.

Methodology

The present multicentric study was conducted at Lucknow. The study included 150 participants, out of which there were 31 cryptococcal meningitis cases, 34 positive meningitis controls, and the rest, 85, were disease controls.

Result

The discriminant function analysis (DFA) of the three biofluids was used to find significant metabolites between the cases and the control group collectively. A group categorization between control group and the cases in serum, urine, and CSF samples was also made possible by the NMR spectral bin-based orthogonal signal correction and principal component analysis score plots of important metabolites produced from DFA. The cases group had a higher proportion of patients with higher CSF protein levels than the positive control group (BM and TM). Acetone was found among urine samples in both control samples, i.e., positive and negative.

Conclusion

This is the first study to explore biomarkers in serum, urine, and CSF in addition to radiological features and clinical symptoms. Hence, a quick, non-invasive prognosis and diagnosis of cryptococcal meningitis in adults can be made using clinical and microbiological investigation, as well as metabolomic analysis of urine samples. This study shows that urine can be used as a biofluid to differentiate between Cryptococcus meningitis in adults. However, when compared to the negative control, our sample size was significantly smaller, necessitating further confirmation on a larger sample size.

Metabolomic profiling of CSF and blood serum elucidates general and sex-specific patterns for mild cognitive impairment and Alzheimer's disease patients

Background

Beta-amyloid (Abeta) and tau protein in cerebrospinal fluid (CSF) are established diagnostic biomarkers for Alzheimer's disease (AD). However, these biomarkers may not the only ones existing parameters that reflect Alzheimer's disease neuropathological change. The use of quantitative metabolomics approach could provide novel insights into dementia progression and identify key metabolic alterations in CSF and serum.

Methods

In the present study, we quantified a set of 45 metabolites in CSF (71 patients) and 27 in serum (76 patients) in patients with mild cognitive impairment (MCI), AD, and controls using nuclear magnetic resonance (NMR)-based metabolomics.

Results

We found significantly reduced CSF (1.32-fold, p = 0.0195) and serum (1.47-fold, p = 0.0484) levels of the ketone body acetoacetate in AD and MCI patients. Additionally, we found decreased levels (1.20-fold, p = 0.0438) of the branched-chain amino acid (BCAA) valine in the CSF of AD patients with increased valine degradation pathway metabolites (such as 3-hydroxyisobutyrate and α-ketoisovalerate). Moreover, we discovered that CSF 2-hydroxybutyrate is dramatically reduced in the MCI patient group (1.23-fold, p = 0.039). On the other hand, vitamin C (ascorbate) was significantly raised in CSF of these patients (p = 0.008). We also identified altered CSF protein content, 1,5-anhydrosorbitol and fructose as further metabolic shifts distinguishing AD from MCI. Significantly decreased serum levels of the amino acid ornithine were seen in the AD dementia group when compared to healthy controls (1.36-fold, p = 0.011). When investigating the effect of sex, we found for AD males the sign of decreased 2-hydroxybutyrate and acetoacetate in CSF while for AD females increased serum creatinine was identified.

Conclusion

Quantitative NMR metabolomics of CSF and serum was able to efficiently identify metabolic changes associated with dementia groups of MCI and AD patients. Further, we showed strong correlations between these changes and well-established metabolomic and clinical indicators like Abeta.

Metabolomics Approaches for the Diagnosis, Treatment, and Better Disease Management of Viral Infections

Metabolomics is an analytical approach that involves profiling and comparing the metabolites present in biological samples. This scoping review article offers an overview of current metabolomics approaches and their utilization in evaluating metabolic changes in biological fluids that occur in response to viral infections. Here, we provide an overview of metabolomics methods including high-throughput analytical chemistry and multivariate data analysis to identify the specific metabolites associated with viral infections. This review also focuses on data interpretation and applications designed to improve our understanding of the pathogenesis of these viral diseases.

Identification of cerebrospinal fluid metabolites as biomarkers for neurobrucellosis by liquid chromatography-mass spectrometry approach

Neurobrucellosis is the most morbid form in brucellosis disease. Metabolomics is an emerging method which intends to explore the global alterations of various metabolites in samples. We aimed to identify metabolites in cerebrospinal fluid (CSF) as biomarkers that were potentially unique for neurobrucellosis. CSF samples from 25 neurobrucellosis patients and 25 normal controls (uninfected patients with hydrocephalus) were collected for metabolite detection using liquid chromatography-mass spectrometry (LC-MS) approach. Inflammatory cytokines in CSF were measured with Enzyme-linked immunosorbent assay (ELISA). The base peak chromatogram in CSF samples showed that small-molecule metabolites were well separated. Principal Component Analysis (PCA) analysis exhibited the examined samples were arranged in two main clusters in accordance with their group. Projection to Latent Structures Discriminant Analysis (PLS-DA) revealed there was a noticeable separation between neurobrucellosis and normal groups. Orthogonal Partial Least-Squares-Discriminant Analysis (OPLS-DA) could responsibly illuminate the differences between neurobrucellosis and normal controls. Neurobrucellosis showed a total of 155 differentiated metabolites. Prominent potential biomarkers including 30 metabolites were then selected out, regarded as more capable of distinguishing neurobrucellosis. TNF-α and IL-6 in CSF were remarkably increased in neurobrucellosis. We presented the heatmaps and correlation analyses among the identified 30 potential biomarkers. In conclusion, this study showed that CSF metabolomics based on LC-MS could distinguish neurobrucellosis patients from normal controls. Our data offered perspectives for diagnosis and treatment for neurobrucellosis.

Review of -omics studies on mosquito-borne viruses of the Flavivirus genus

Arboviruses are transmitted by arthropods (arthropod-borne virus) which can be mosquitoes or other hematophagous arthropods, in which their life cycle occurs before transmission to other hosts. Arboviruses such as Dengue, Zika, Saint Louis Encephalitis, West Nile, Yellow Fever, Japanese Encephalitis, Rocio and Murray Valley Encephalitis viruses are some of the arboviruses transmitted biologically among vertebrate hosts by blood-taking vectors, mainly Aedes and Culex sp., and are associated with neurological, viscerotropic, and hemorrhagic reemerging diseases, posing as significant health and socioeconomic concern, as they become more and more adaptive to new environments, to arthropods vectors and human hosts. One of the main families that include mosquito-borne viruses is Flaviviridae, and here, we review the case of the Flavivirus genus, which comprises the viruses cited above, using a variety of research approaches published in literature, including genomics, transcriptomics, proteomics, metabolomics, etc., to better understand their structures as well as virus-host interactions, which are essential for development of future antiviral therapies.

Multi-Omics Approach to Elucidate Cerebrospinal Fluid Changes in Dogs with Intervertebral Disc Herniation

Herniation of the intervertebral disc (IVDH) is the most common cause of neurological and intervertebral disc degeneration-related diseases. Since the disc starts to degenerate before it can be observed by currently available diagnostic methods, there is an urgent need for novel diagnostic approaches. To identify molecular networks and pathways which may play important roles in intervertebral disc herniation, as well as to reveal the potential features which could be useful for monitoring disease progression and prognosis, multi-omics profiling, including high-resolution liquid chromatography-mass spectrometry (LC-MS)-based metabolomics and tandem mass tag (TMT)-based proteomics was performed. Cerebrospinal fluid of nine dogs with IVDH and six healthy controls were used for the analyses, and an additional five IVDH samples were used for proteomic data validation. Furthermore, multi-omics data were integrated to decipher a complex interaction between individual omics layers, leading to an improved prediction model. Together with metabolic pathways related to amino acids and lipid metabolism and coagulation cascades, our integromics prediction model identified the key features in IVDH, namely the proteins follistatin Like 1 (FSTL1), secretogranin V (SCG5), nucleobindin 1 (NUCB1), calcitonin re-ceptor-stimulating peptide 2 precursor (CRSP2) and the metabolites N-acetyl-D-glucosamine and adenine, involved in neuropathic pain, myelination, and neurotransmission and inflammatory response, respectively. Their clinical application is to be further investigated. The utilization of a novel integrative interdisciplinary approach may provide new opportunities to apply innovative diagnostic and monitoring methods as well as improve treatment strategies and personalized care for patients with degenerative spinal disorders.

Cerebrospinal fluid metabolomics: detection of neuroinflammation in human central nervous system disease

The high morbidity and mortality of neuroinflammatory diseases drives significant interest in understanding the underlying mechanisms involved in the innate and adaptive immune response of the central nervous system (CNS). Diagnostic biomarkers are important to define treatable neuroinflammation. Metabolomics is a rapidly evolving research area offering novel insights into metabolic pathways, and elucidation of reliable metabolites as biomarkers for diseases. This review focuses on the emerging literature regarding the detection of neuroinflammation using cerebrospinal fluid (CSF) metabolomics in human cohort studies. Studies of classic neuroinflammatory disorders such as encephalitis, CNS infection and multiple sclerosis confirm the utility of CSF metabolomics. Additionally, studies in neurodegeneration and neuropsychiatry support the emerging potential of CSF metabolomics to detect neuroinflammation in common CNS diseases such as Alzheimer's disease and depression. We demonstrate metabolites in the tryptophan-kynurenine pathway, nitric oxide pathway, neopterin and major lipid species show moderately consistent ability to differentiate patients with neuroinflammation from controls. Integration of CSF metabolomics into clinical practice is warranted to improve recognition and treatment of neuroinflammation.

Cerebrospinal fluid metabolites in tryptophan-kynurenine and nitric oxide pathways: biomarkers for acute neuroinflammation

AIM

To explore the cerebrospinal fluid (CSF) metabolite features in acute neuroinflammatory diseases and identify potential biomarkers to diagnose and monitor neuroinflammation.

METHOD

A cohort of 14 patients (five females, nine males; mean [median] age 7y 9mo [9y], range 6mo-13y) with acute encephalitis (acute disseminated encephalomyelitis n=6, unknown suspected viral encephalitis n=3, enteroviral encephalitis n=2, seronegative autoimmune encephalitis n=2, herpes simplex encephalitis n=1) and age-matched non-inflammatory neurological disease controls (n=14) were investigated using an untargeted metabolomics approach. CSF metabolites were analyzed with liquid chromatography coupled to high resolution mass spectrometry, followed by subsequent multivariate and univariate statistical methods.

RESULTS

A total of 35 metabolites could be discriminated statistically between the groups using supervised orthogonal partial least squares discriminant analysis and analysis of variance. The tryptophan-kynurenine pathway contributed nine key metabolites. There was a statistical increase of kynurenine, quinolinic acid, and anthranilic acid in patients with encephalitis, whereas tryptophan, 3-hydroxyanthrnailic acid, and kynurenic acid were decreased. The nitric oxide pathway contributed four metabolites, with elevated asymmetric dimethylarginine and argininosuccinic acid, and decreased arginine and citrulline in patients with encephalitis. An increase in the CSF kynurenine/tryptophan ratio (p<0.001), anthranilic acid/3-hydroxyanthranilic acid ratio (p<0.001), asymmetric dimethylarginine/arginine ratio (p<0.001), and neopterin (p<0.001) strongly predicted neuroinflammation.

INTERPRETATION

The combination of alterations in the tryptophan-kynurenine pathway, nitric oxide pathway, and neopterin represent a useful potential panel for neuroinflammation and holds potential for clinical translation practice.

WHAT THIS PAPER ADDS

The kynurenine/tryptophan and anthranilic acid/3-hydroxyanthranilic acid ratios hold great potential as biomarkers of neuroinflammation. Elevation of the asymmetric dimethylarginine/arginine ratio in acute brain inflammation shows dysregulation of the nitric oxide pathway.

Andrographolide Against Lung Cancer-New Pharmacological Insights Based on High-Throughput Metabolomics Analysis Combined with Network Pharmacology

Andrographolide (Andro) has known to treat various illnesses such as colds, diarrhea, fever and infectious diseases. However, the effect mechanism of Andro is still unclear. Therefore, we used high-throughput metabolomics analysis to discover biomarkers, metabolic profiles and pathways to reveal the pharmacological action and effective mechanism of Andro against lung cancer. The metabolic effects of Andro on lung cancer animal was explored by ultra-performance liquid chromatography-triple-time of flight/mass spectrometry (UPLC-TOF/MS) analysis. Our results showed that Andro exhibited significant protective effects against lung cancer. Compared with control group, a total of 25 metabolites biomarkers was identified in urine of model animals, which 18 of them were regulated toward the normal direction after Andro treatment, and network pharmacology analysis showed that they were related with 570 proteins. Biological pathways analysis showed that the 11 metabolism pathways were regulated by Andro treatment in lung cancer mouse, and amino acid metabolism and arachidonic acid metabolism have great potential as target pathways for Andro against lung cancer. It revealed that high-throughput metabolomics combined with network pharmacology analysis provides deeply insight into the therapeutic mechanisms of natural product for promoting medicine development and disease treatment.

NMR-based metabolomics of human cerebrospinal fluid identifies signature of brain death

INTRODUCTION

Brain death (BD) is the irreversible cessation of all functions of the entire brain, including the brainstem. Cerebrospinal fluid (CSF) is a biological liquid that circulates in brain and spine. Metabolomics is able to reveal the response of biological systems to diverse factors in a specific moment or condition. Therefore, the study of this neurological condition through metabolic profiling using high resolution Nuclear Magnetic Resonance (NMR) spectroscopy is important for understanding biochemical events.

OBJECTIVES

The aim of the current study is to identify the metabolomics signature of BD using ¹H-NMR spectroscopy in human CSF.

METHODS

¹H-NMR spectroscopy has been employed for metabolomic untargeted analysis in 46 CSF samples: 22 control and 24 with BD. Spectral data were further subjected to multivariate analysis.

RESULTS

Statistically significant multivariate models separated subject's samples with BD from controls and revealed twenty one discriminatory metabolites. The statistical analysis of control and BD subjects using Orthogonal Projections to Latent Structures Discriminant Analysis (OPLS-DA) model resulted in R²X of 0.733 and Q² of 0.635. An elevation in the concentration of statistically discriminant metabolites in BD was observed.

CONCLUSION

This study identifies a metabolic signature associated with BD and the most relevant enriched selected metabolic pathways.

Optimization of pretreatment methods for cerebrospinal fluid metabolomics based on ultrahigh performance liquid chromatography/mass spectrometry

Sample pretreatment of cerebrospinal fluid (CSF) in metabolomics plays an important role in metabolic profiling study, especially for samples related to central nervous system diseases. However, there is few study about optimization of CSF metabolomics pretreatment. Therefore, it is an urgent need to optimize CSF pretreatment in order to promote the extraction efficiency of metabolites. In this study, CSF samples were separately subjected to nine different protein precipitation solvents and five different reconstitution solvents to establish the most effective pretreatment method before hydrophilic interaction (HILIC) and reverse-phase (RP) ultrahigh performance liquid chromatography mass spectrometry (UPLC/MS) analysis. The optimal conditions for different sample pretreatment methods were analyzed based on coverage (number of detected potential metabolites), stability (the relative standard deviation (RSD) distribution of metabolites) and the reproducibility of the data. Our results suggested that using EtOH or MeOH-EtOH-ACN (1:1:1, v/v/v) as the protein precipitation solvents and H₂O-MeOH-ACN (2:1:1, v/v/v) as the reconstitution solvent were optimal methods for T3 column analysis. For HILIC column analysis, using EtOH to precipitate protein and H₂O-MeOH-ACN (2:1:1, v/v/v) to reconstitute or MeOH to precipitate and 5 %ACN to reconstitute performed best. This developed UPLC/MS pretreatment method could provide better protein precipitation solvents and reconstitution solvents for global CSF metabolic analysis, potentially facilitating the comprehensive understanding of many central nervous system diseases.

Metabolic Profiling of Suprachiasmatic Nucleus Reveals Multifaceted Effects in an Alzheimer's Disease Mouse Model

BACKGROUND

Circadian rhythm disturbance is commonly observed in Alzheimer's disease (AD). In mammals, these rhythms are orchestrated by the superchiasmatic nucleus (SCN). Our previous study in the Tg2576 AD mouse model suggests that inflammatory responses, most likely manifested by low GABA production, may be one of the underlying perpetrators for the changes in circadian rhythmicity and sleep disturbance in AD. However, the mechanistic connections between SCN dysfunction, GABA modulation, and inflammation in AD is not fully understood.

OBJECTIVE

To reveal influences of amyloid pathology in Tg2576 mouse brain on metabolism in SCN and to identify key metabolic sensors that couple SCN dysfunction with GABA modulation and inflammation.

METHODS

High resolution magic angle spinning (HR-MAS) NMR in conjunction with multivariate analysis was applied for metabolic profiling in SCN of control and Tg2576 female mice. Immunohistochemical analysis was used to detect neurons, astrocytes, expression of GABA transporter 1 (GAT1) and Bmal1.

RESULTS

Metabolic profiling revealed significant metabolic deficits in SCN of Tg2576 mice. Reductions in glucose, glutamate, GABA, and glutamine provide hints toward an impaired GABAergic glucose oxidation and neurotransmitter cycling in SCN of AD mice. In addition, decreased redox co-factor NADPH and glutathione support a redox disbalance. Immunohistochemical examinations showed low expression of the core clock protein, Bmal1, especially in activated astrocytes. Moreover, decreased expression of GAT1 in astrocytes indicates low GABA recycling in this cell type.

CONCLUSION

Our results suggest that redox disbalance and compromised GABA signaling are important denominators and connectors between neuroinflammation and clock dysfunction in AD.

Cutaneous Thermal Injury Modulates Blood and Skin Metabolomes Differently in a Murine Model

As the field of metabolomics develops further, investigations of how the metabolome is affected following thermal injury may be helpful to inform diagnostics and guide treatments. In this study, changes to the metabolome were tested and validated in a murine burn injury model. After a 30% total body surface scald injury or sham procedure sera and skin biopsies were collected at 1, 2, 6, or 24 hr.

Burn-specific changes in the metabolome were detected compared to sham animals. The sera metabolome exhibited a more rapid response to burn injury than that of the skin and it peaked more proximal to injury (6 vs 24 hr). Progression of metabolic response in the skin was less synchronous and showed a higher overlap of the significantly modified metabolites (SMMs) among tested time-points. Top affected pathways identified by SMMs of skin included inositol phosphate metabolism, ascorbate and alderate metabolism, caffeine metabolism, and the pentose phosphate pathway. Future research is warranted in human and larger animal models to further elucidate the role of metabolomic perturbations and the pathophysiology following burn injury.

Brain energy metabolism and multiple sclerosis: progress and prospects

Multiple sclerosis (MS) is an autoimmune disease accompanied with nerve pain and paralysis. Although various pathogenic causes of MS have been suggested, including genetic and environmental factors, how MS occurs remains unclear. Moreover, MS should be diagnosed based on clinical experiences because of no disease-specific biomarker and currently available treatments for MS just can reduce relapsing frequency or severity with little effects on disease disability. Therefore, more efforts are required to identify pathophysiology of MS and diagnosis markers. Recent evidence indicates another aspect of MS pathogenesis, energy failure in the central nervous system (CNS). For instance, inflammation that is a characteristic MS symptom and occurs frequently in the CNS of MS patients can result into energy failure in mitochondria and cytosol. Indeed, metabolomics studies for MS have reported energy failure in oxidative phosphorylation and alteration of aerobic glycolysis. Therefore, studies on the metabolism in the CNS may provide another insight for understanding complexity of MS and pathogenesis, which would facilitate the discovery of promising strategies for developing therapeutics to treat MS. This review will provide an overview on recent progress of metabolomic studies for MS, with a focus on the fluctuation of energy metabolism in MS.

The Current Status of Enteric Fever Diagnostics and Implications for Disease Control

Enteric (typhoid) fever remains a problem in low- and middle-income countries that lack the infrastructure to maintain sanitation and where inadequate diagnostic methods have restricted our ability to identify and control the disease more effectively. As we move into a period of potential disease elimination through the introduction of typhoid conjugate vaccine (TCV), we again need to reconsider the role of typhoid diagnostics in how they can aid in facilitating disease control. Recent technological advances, including serology, transcriptomics, and metabolomics, have provided new insights into how we can detect signatures of invasive Salmonella organisms interacting with the host during infection. Many of these new techniques exhibit potential that could be further explored with the aim of creating a new enteric fever diagnostic to work in conjunction with TCV. We need a sustained effort within the enteric fever field to accelerate, validate, and ultimately introduce 1 (or more) of these methods to facilitate the disease control initiative. The window of opportunity is still open, but we need to recognize the need for communication with other research areas and commercial organizations to assist in the progression of these diagnostic approaches. The elimination of enteric fever is now becoming a real possibility, but new diagnostics need to be part of the equation and factored into future calculations for disease control.

Pursuing Experimental Reproducibility: An Efficient Protocol for the Preparation of Cerebrospinal Fluid Samples for NMR-based Metabolomics and Analysis of Sample Degradation

NMR-based metabolomics investigations of human biofluids offer great potential to uncover new biomarkers. In contrast to protocols for sample collection and biobanking, procedures for sample preparation prior to NMR measurements are still heterogeneous, thus compromising the comparability of the resulting data. Herein, we present results of an investigation of the handling of cerebrospinal fluid (CSF) samples for NMR metabolomics research. Origins of commonly observed problems when conducting NMR experiments on this type of sample are addressed, and suitable experimental conditions in terms of sample preparation and pH control are discussed. Sample stability was assessed by monitoring the degradation of CSF samples by NMR, hereby identifying metabolite candidates, which are potentially affected by sample storage. A protocol was devised yielding consistent spectroscopic data as well as achieving overall sample stability for robust analysis. We present easy to adopt standard operating procedures with the aim to establish a shared sample handling strategy that facilitates and promotes inter-laboratory comparison, and the analysis of sample degradation provides new insights into sample stability.

Mass spectrometry-based proteomic techniques to identify cerebrospinal fluid biomarkers for diagnosing suspected central nervous system infections. A systematic review

OBJECTIVES

Central nervous system (CNS) infections account for considerable death and disability every year. An urgent research priority is scaling up diagnostic capacity, and introduction of point-of-care tests. We set out to assess current evidence for the application of mass spectrometry (MS) peptide sequencing in identification of diagnostic biomarkers for CNS infections.

METHODS

We performed a systematic review (PROSPEROCRD42018104257) using PRISMA guidelines on use of MS to identify cerebrospinal fluid (CSF) biomarkers for diagnosing CNS infections. We searched PubMed, Embase, Web of Science, and Cochrane for articles published from 1 January 2000 to 1 February 2019, and contacted experts. Inclusion criteria involved primary research except case reports, on the diagnosis of infectious diseases except HIV, applying MS to human CSF samples, and English language.

RESULTS

4,620 papers were identified, of which 11 were included, largely confined to pre-clinical biomarker discovery, and eight (73%) published in the last five years. 6 studies performed further work termed verification or validation. In 2 of these studies, it was possible to extract data on sensitivity and specificity of the biomarkers detected by ELISA, ranging from 89-94% and 58-92% respectively.

CONCLUSIONS

The findings demonstrate feasibility and potential of the methods in a variety of infectious diseases, but emphasise the need for strong interdisciplinary collaborations to ensure appropriate study design and biomarker validation.