Elevated host lipid metabolism revealed by iTRAQ-based quantitative proteomic analysis of cerebrospinal fluid of tuberculous meningitis patients

Tuberculous meningitis diagnosis and treatment: classic approaches and high-throughput pathways

Tuberculous meningitis (TBM), a severe form of non-purulent meningitis caused by Mycobacterium tuberculosis (Mtb), is the most critical extrapulmonary tuberculosis (TB) manifestation, with a 30-40% mortality rate despite available treatment. The absence of distinctive clinical symptoms and effective diagnostic tools complicates early detection. Recent advancements in nucleic acid detection, genomics, metabolomics, and proteomics have led to novel diagnostic approaches, improving sensitivity and specificity. This review focuses on nucleic acid-based methods, including Xpert Ultra, metagenomic next-generation sequencing (mNGS), and single-cell sequencing of whole brain Tissue, alongside the diagnostic potential of metabolomic and proteomic biomarkers. By evaluating the technical features, diagnostic accuracy, and clinical applicability, this review aims to inform the optimization of TBM diagnostic strategies and explores the integration and clinical translation of multi-omics technologies.

Spatially heterogeneous lipid dysregulation in tuberculous meningitis

Tuberculous (TB) meningitis is the deadliest form of extrapulmonary TB which disproportionately affects children and immunocompromised individuals. Studies in pulmonary TB have shown that Mycobacterium tuberculosis can alter host lipid metabolism to evade the immune system. Cholesterol lowering drugs (i.e., statins) reduce the risk of infection, making them a promising host-directed therapy in pulmonary TB. However, the effect of M. tuberculosis infection on the young or adult brain lipidome has not been studied. The brain is the second-most lipid-rich organ, after adipose tissue, with a temporally and spatially heterogeneous lipidome that changes from infancy to adulthood. The young, developing brain in children may be uniquely vulnerable to alterations in lipid composition and homeostasis, as perturbations in cholesterol metabolism can cause developmental disorders leading to intellectual disabilities. To begin to understand the alterations to the brain lipidome in pediatric TB meningitis, we utilized our previously published young rabbit model of TB meningitis and applied mass spectrometry (MS) techniques to elucidate spatial differences. We used matrix assisted laser desorption/ionization-MS imaging (MALDI-MSI) and complemented it with region-specific liquid chromatography (LC)-MS/MS developed to identify and quantify sterols and oxysterols difficult to identify by MALDI-MSI. MALDI-MSI revealed several sphingolipids, glycerolipids and glycerophospholipids that were downregulated in brain lesions. LC-MS/MS revealed the downregulation of cholesterol, several sterol intermediates along the cholesterol biosynthesis pathway and enzymatically produced oxysterols as a direct result of M. tuberculosis infection. However, oxysterols produced by oxidative stress were increased in brain lesions. Together, these results demonstrate significant spatially regulated brain lipidome dysregulation in pediatric TB meningitis.

Application of metabolomics in diagnostics and differentiation of meningitis: A narrative review with a critical approach to the literature

Due to its high mortality rate associated with various life-threatening sequelae, meningitis poses a vital problem in contemporary medicine. Numerous algorithms, many of which were derived with the aid of artificial intelligence, were brought up in a strive for perfection in predicting the status of sepsis-related survival or exacerbation. This review aims to provide key insights on the contextual utilization of metabolomics. The aim of this the metabolomic approach set of methods can be used to investigate both bacterial and host metabolite sets from both the host and its microbes in several types of specimens - even in one's breath, mainly with use of two methods - Mass Spectrometry (MS) and Nuclear Magnetic Resonance (NMR). Metabolomics, and has been used to elucidate the mechanisms underlying disease development and metabolic identification changes in a wide range of metabolite contents, leading to improved methods of diagnosis, treatment, and prognosis of meningitis. Mass spectrometry (MS) and Nuclear Magnetic Resonance (NMR) are the main analytical platforms used in metabolomics. Its high sensitivity accounts for the usefulness of metabolomics in studies into meningitis, its sequelae, and concomitant comorbidities. Metabolomics approaches are a double-edged sword, due to not only their flexibility, but also - high complexity, as even minor changes in the multi-step methods can have a massive impact on the results. Information on the differential diagnosis of meningitis act as a background in presenting the merits and drawbacks of the use of metabolomics in context of meningeal infections.

Recent advances in microbiological and molecular biological detection techniques of tuberculous meningitis

Tuberculous meningitis (TBM) is the most common type of central nervous system tuberculosis (TB) and has the highest mortality and disability rate. Early diagnosis is key to improving the prognosis and survival rate of patients. However, laboratory diagnosis of TBM is often difficult due to its paucibacillary nature and sub optimal sensitivity of conventional microbiology and molecular tools which often fails to detect the pathogen. The gold standard for TBM diagnosis is the presence of MTB in the CSF. The recognised methods for the identification of MTB are acid-fast bacilli (AFB) detected under CSF smear microscopy, MTB cultured in CSF, and MTB detected by polymerase chain reaction (PCR). Currently, many studies consider that all diagnostic techniques for TBM are not perfect, and no single technique is considered simple, fast, cheap, and efficient. A definite diagnosis of TBM is still difficult in current clinical practice. In this review, we summarise the current state of microbiological and molecular biological diagnostics for TBM, the latest advances in research, and discuss the advantages of these techniques, as well as the issues and challenges faced in terms of diagnostic effectiveness, laboratory infrastructure, testing costs, and clinical expertise, for clinicians to select appropriate testing methods.

Combining metabolome and clinical indicators with machine learning provides some promising diagnostic markers to precisely detect smear-positive/negative pulmonary tuberculosis

Background

Tuberculosis (TB) had been the leading lethal infectious disease worldwide for a long time (2014–2019) until the COVID-19 global pandemic, and it is still one of the top 10 death causes worldwide. One important reason why there are so many TB patients and death cases in the world is because of the difficulties in precise diagnosis of TB using common detection methods, especially for some smear-negative pulmonary tuberculosis (SNPT) cases. The rapid development of metabolome and machine learning offers a great opportunity for precision diagnosis of TB. However, the metabolite biomarkers for the precision diagnosis of smear-positive and smear-negative pulmonary tuberculosis (SPPT/SNPT) remain to be uncovered. In this study, we combined metabolomics and clinical indicators with machine learning to screen out newly diagnostic biomarkers for the precise identification of SPPT and SNPT patients.

Methods

Untargeted plasma metabolomic profiling was performed for 27 SPPT patients, 37 SNPT patients and controls. The orthogonal partial least squares-discriminant analysis (OPLS-DA) was then conducted to screen differential metabolites among the three groups. Metabolite enriched pathways, random forest (RF), support vector machines (SVM) and multilayer perceptron neural network (MLP) were performed using Metaboanalyst 5.0, “caret” R package, “e1071” R package and “Tensorflow” Python package, respectively.

Results

Metabolomic analysis revealed significant enrichment of fatty acid and amino acid metabolites in the plasma of SPPT and SNPT patients, where SPPT samples showed a more serious dysfunction in fatty acid and amino acid metabolisms. Further RF analysis revealed four optimized diagnostic biomarker combinations including ten features (two lipid/lipid-like molecules and seven organic acids/derivatives, and one clinical indicator) for the identification of SPPT, SNPT patients and controls with high accuracy (83–93%), which were further verified by SVM and MLP. Among them, MLP displayed the best classification performance on simultaneously precise identification of the three groups (94.74%), suggesting the advantage of MLP over RF/SVM to some extent.

Conclusions

Our findings reveal plasma metabolomic characteristics of SPPT and SNPT patients, provide some novel promising diagnostic markers for precision diagnosis of various types of TB, and show the potential of machine learning in screening out biomarkers from big data.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-022-07694-8.

Identification of protein biomarkers in host cerebrospinal fluid for differential diagnosis of tuberculous meningitis and other meningitis

Background and purpose

The diagnosis of tuberculous meningitis (TBM) is difficult due to the lack of sensitive methods. Identification of TBM-specific biomarkers in the cerebrospinal fluid (CSF) may help diagnose and improve our understanding of TBM pathogenesis.

Patients and methods

Of the 112 suspected patients with TBM prospectively enrolled in the study, 32 patients with inconclusive diagnosis, non-infectious meningitis, and long-term treatment with hormones and immunosuppressants were excluded. The expression of 8 proteins in the CSF was analyzed using ELISA in 22 patients with definite TBM, 18 patients with probable TBM, and 40 patients with non-TBM.

Results

Significant differences in the expression of 7 proteins were detected between the TBM and non-TBM groups (P < 0.01). Unsupervised hierarchical clustering (UHC) analysis revealed a disease-specific profile consisting of 7 differentially expressed proteins for TBM diagnosis, with an accuracy of 82.5% (66/80). Logistic regression with forward stepwise analysis indicated that a combination of 3 biomarkers (APOE_APOAI_S100A8) showed a better ability to discriminate TBM from patients with non-TBM [area under the curve (AUC) = 0.916 (95%CI: 0.857–0.976)], with a sensitivity of 95.0% (95%CI: 83.1–99.4%) and a specificity of 77.5% (95%CI: 61.5–89.2%).

Conclusion

Our results confirmed the potential ability of CSF proteins to distinguish TBM from patients with non-TBM and provided a useful panel for the diagnosis of TBM.

Differences between infected and noninfected synovial fluid

AIMS

The diagnosis of joint infections is an inexact science using combinations of blood inflammatory markers and microscopy, culture, and sensitivity of synovial fluid (SF). There is potential for small molecule metabolites in infected SF to act as infection markers that could improve accuracy and speed of detection. The objective of this study was to use nuclear magnetic resonance (NMR) spectroscopy to identify small molecule differences between infected and noninfected human SF.

METHODS

In all, 16 SF samples (eight infected native and prosthetic joints plus eight noninfected joints requiring arthroplasty for end-stage osteoarthritis) were collected from patients. NMR spectroscopy was used to analyze the metabolites present in each sample. Principal component analysis and univariate statistical analysis were undertaken to investigate metabolic differences between the two groups.

RESULTS

A total of 16 metabolites were found in significantly different concentrations between the groups. Three were in higher relative concentrations (lipids, cholesterol, and N-acetylated molecules) and 13 in lower relative concentrations in the infected group (citrate, glycine, glycosaminoglycans, creatinine, histidine, lysine, formate, glucose, proline, valine, dimethylsulfone, mannose, and glutamine).

CONCLUSION

Metabolites found in significantly greater concentrations in the infected cohort are markers of inflammation and infection. They play a role in lipid metabolism and the inflammatory response. Those found in significantly reduced concentrations were involved in carbohydrate metabolism, nucleoside metabolism, the glutamate metabolic pathway, increased oxidative stress in the diseased state, and reduced articular cartilage breakdown. This is the first study to demonstrate differences in the metabolic profile of infected and noninfected human SF, using a noninfected matched cohort, and may represent putative biomarkers that form the basis of new diagnostic tests for infected SF. Cite this article: Bone Joint Res 2021;10(1):85-95.

Identification of Urinary Biomarkers for Exercise-Induced Immunosuppression by iTRAQ Proteomics

Purpose

To identify noninvasive immune biomarkers of exercise-induced immunosuppression using the iTRAQ proteomics technique.

Methods

Fifteen healthy males were recruited and subjected to a four-week incremental treadmill running training program. After each week of training, WBC counts and CD4⁺ and CD8⁺ lymphocytes were measured to monitor the immune function status. iTRAQ proteomics technology was used to identify differential proteins and their characteristics in urine.

Results

Our data showed that the WBC counts, CD4⁺ lymphocytes, and CD4⁺/CD8⁺ ratio decreased by more than 10% after four weeks of training, suggesting exercise-induced immunosuppression. A total of 1854 proteins were identified in urine during the incremental running using the iTRAQ technology. Compared with the urine before training, there were 89, 52, 77, and 148 proteins significantly upregulated and 66, 27, 68, and 114 proteins significantly downregulated after each week, respectively. Among them, four upregulated proteins, SEMG-1, PIP, PDGFRL, and NDPK, increased their abundance with the increased exercise intensity. Bioinformatics analysis indicates that these proteins are involved in stress response and immune function.

Conclusion

Four weeks of incremental treadmill running induced immunosuppression in healthy males. By using iTRAQ proteomics, four proteins in the urine, SEMG-1, PIP, PDGFRL, and NDPK, were found to increase incrementally with the increased exercise intensity, which have the potential to be used as noninvasive immune biomarkers of exercise-induced immunosuppression.

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.

Screening and identification of potential protein biomarkers for evaluating the efficacy of intensive therapy in pulmonary tuberculosis

This research aimed to discover potential biomarkers for evaluating the therapeutic efficacy of intensive therapy in pulmonary tuberculosis (TB). Protein profiles in 2-months intensively treated TB patients, untreated TB patients, and healthy controls were investigated with iTRAQ-2DLC-MS/MS technique. 71 differential proteins were identified in 2-months intensively treated TB patients. Significant differences in complement component C7 (CO7), apolipoprotein A-IV (APOA4), apolipoprotein C-II (APOC2), and angiotensinogen (ANGT) were found by ELISA validation. CO7 and ANGT were also found significantly different in sputum negative patients, compared with sputum positive patients after intensive treatment. Clinical analysis showed that after 2-months intensive treatment several indicators were significantly changed, and the one-year cure rate of sputum negative patients were significantly higher than sputum positive patients. Diagnostic models consisting of APOC2, CO7 and APOA4 were established to distinguish intensively treated TB patients from untreated TB patients and healthy controls with the AUC value of 0.910 and 0.935. Meanwhile, ANGT and CO7 were combined to identify sputum negative and sputum positive TB patients after intensive treatment with 89.36% sensitivity, 71.43% specificity, and the AUC value of 0.853. The results showed that APOC2, CO7, APOA4, and ANGT may be potential biomarkers for evaluating the efficacy of intensive anti-TB therapy.

Dietary cholesterol intake and stroke risk: a meta-analysis

Background/Objectives

The association between dietary cholesterol and stroke risk has remained controversial over the past two decades. The aim of this meta-analysis was to assess the relationship between dietary cholesterol and stroke risk.

Results

Seven prospective studies including 269,777 non-overlapping individuals (4,604 strokes) were included. The combined RR of stroke for higher cholesterol intake (> 300 mg/day) was 0.98 (95% CI, 0.90–1.07), and the combined RR of stroke for higher cholesterol intake (> 300 mg/day) in females (age of ≥ 60 years or body mass index of ≥ 24 kg/m²) was 1.18 (95% CI, 1.02–1.36).

Materials and Methods

The PubMed, Medline, Embase, Web of Knowledge, and Google Scholar databases were searched. Relevant studies were identified by searching these online databases through September 2017. The relative risk (RR) and 95% confidence interval (CI) were used to investigate the strength of the association.

Conclusions

Higher cholesterol intake has no association with the overall stroke risk. Age and body mass index affect the relationship between dietary cholesterol intake and stroke risk. However, the association between higher dietary cholesterol and stroke risk in males remains unclear.

Lenalidomide regulates osteocytes fate and related osteoclastogenesis via IL-1β/NF-κB/RANKL signaling

Osteolytic diseases are closely associated with osteocyte fate, indicating a more efficient and crucial role of osteocyte-targeting strategy in inhibiting osteoclastogenesis. Here, we investigated the effects of lenalidomide (Lena) on osteocyte fate in order to regulate osteoclastogenesis via effective cascade-controlling response. Our data revealed that lenalidomide treatment notably rescued IL-1β induced loss of osteocyte viability by inhibiting osteocyte apoptosis with decreased osteoclast-related factors, RANKL and Sclerostin, as demonstrated by the restricted osteoclast formation and reduced bone resorption. Additionally, iTRAQ assay revealed that IL-1β induced activation of NF-κB inhibitor α/β were remarkably downregulated by lenalidomide, showing that lenalidomide impaired NF-κB signaling in osteocytes for inhibiting the expression of osteoclast specific genes in osteoclasts, which was further confirmed by KEGG pathway analysis and Western blot. More interestingly, the in vivo analysis of osteocyte apoptosis and osteoclastogenesis in osteoarthritis mice model indicated a role of lenalidomide in the regulation of osteocyte fate and the consequent inhibition of RANKL-induced osteoclastogenesis. Together, these results suggest that lenalidomide regulates osteocyte fate by attenuating IL-1β/NF-κB signaling, thereby inhibiting RANKL expression for the attenuated osteoclastogenesis both in vitro and vivo, indicating a more efficient remedy among future anti-osteoclastogenesis approaches.

Cerebral tryptophan metabolism and outcome of tuberculous meningitis: an observational cohort study

BACKGROUND

Immunopathology contributes to the high mortality of tuberculous meningitis, but the biological pathways involved are mostly unknown. We aimed to compare cerebrospinal fluid (CSF) and serum metabolomes of patients with tuberculous meningitis with that of controls without tuberculous meningitis, and assess the link between metabolite concentrations and mortality.

METHODS

In this observational cohort study at the Hasan Sadikin Hospital (Bandung, Indonesia) we measured 425 metabolites using liquid chromatography-mass spectrometry in CSF and serum from 33 HIV-negative Indonesian patients with confirmed or probable tuberculous meningitis and 22 control participants with complete clinical data between March 12, 2009, and Oct 27, 2013. Associations of metabolite concentrations with survival were validated in a second cohort of 101 patients from the same centre. Genome-wide single nucleotide polymorphism typing was used to identify tryptophan quantitative trait loci, which were used for survival analysis in a third cohort of 285 patients.

FINDINGS

Concentrations of 250 (70%) of 351 metabolites detected in CSF were higher in patients with tuberculous meningitis than in controls, especially in those who died during follow-up. Only five (1%) of the 390 metobolites detected in serum differed between patients with tuberculous meningitis and controls. CSF tryptophan concentrations showed a pattern different from most other CSF metabolites; concentrations were lower in patients who survived compared with patients who died (9-times) and to controls (31-times). The association of low CSF tryptophan with patient survival was confirmed in the validation cohort (hazard ratio 0·73; 95% CI 0·64-0·83; p<0·0001; per each halving). 11 genetic loci predictive for CSF tryptophan concentrations in tuberculous meningitis were identified (p<0·00001). These quantitative trait loci predicted survival in a third cohort of 285 HIV-negative patients in a prognostic index including age and sex, also after correction for possible confounders (p=0·0083).

INTERPRETATION

Cerebral tryptophan metabolism, which is known to affect Mycobacterium tuberculosis growth and CNS inflammation, is important for the outcome of tuberculous meningitis. CSF tryptophan concentrations in tuberculous meningitis are under strong genetic influence, probably contributing to the variable outcomes of tuberculous meningitis. Interventions targeting tryptophan metabolism could improve outcomes of tuberculous meningitis.

FUNDING

Royal Dutch Academy of Arts and Sciences; Netherlands Foundation for Scientific Research; Radboud University; National Academy of Sciences; Ministry of Research, Technology, and Higher Education, Indonesia; European Research Council; and PEER-Health.

iTRAQ-Based Proteomics Suggests Ephb6 as a Potential Regulator of the ERK Pathway in the Prefrontal Cortex of Chronic Social Defeat Stress Model Mice

PURPOSE

Major depressive disorder (MDD) is a worldwide concern and devastating psychiatric disease. The World Health Organization claims that MDD leads to at least 11.9% of the global burden of disease. However, the underlying pathophysiology mechanisms of MDD remain largely unknown.

EXPERIMENTAL DESIGN

Herein, we proteomic-based strategy is used to compare the prefrontal cortex (PFC) in chronic social defeat stress (CSDS) model mice with a control group. Based on pooled samples, differential proteins are identified in the PFC proteome using iTRAQ coupled with LC-MS/MS.

RESULTS

Ingenuity Pathway Analysis (IPA) is then followed to predict relevant pathways, with the ephrin receptor signaling pathway selected for further research. Additionally, as the selected key proteins of the ephrin receptor signaling pathway, ephrin type-B receptor 6 (EphB6) and the ERK pathway are validated by Western blotting.

CONCLUSION AND CLINICAL RELEVANT

Altogether, increased understanding of the ephrin receptor signaling pathway in MDD is provided, which implicates further investigation of PFC dysfunction induced by CSDS treatment.

Electronegative Low-Density Lipoprotein L5 Impairs Viability and NGF-Induced Neuronal Differentiation of PC12 Cells via LOX-1

There have been striking associations of cardiovascular diseases (e.g., atherosclerosis) and hypercholesterolemia with increased risk of neurodegeneration including Alzheimer's disease (AD). Low-density lipoprotein (LDL), a cardiovascular risk factor, plays a crucial role in AD pathogenesis; further, L5, a human plasma LDL fraction with high electronegativity, may be a factor contributing to AD-type dementia. Although L5 contributing to atherosclerosis progression has been studied, its role in inducing neurodegeneration remains unclear. Here, PC12 cell culture was used for treatments with human LDLs (L1, L5, or oxLDL), and subsequently cell viability and nerve growth factor (NGF)-induced neuronal differentiation were assessed. We identified L5 as a neurotoxic LDL, as demonstrated by decreased cell viability in a time- and concentration-dependent manner. Contrarily, L1 had no such effect. L5 caused cell damage by inducing ATM/H2AX-associated DNA breakage as well as by activating apoptosis via lectin-like oxidized LDL receptor-1 (LOX-1) signaling to p53 and ensuring cleavage of caspase-3. Additionally, sublethal L5 long-termly inhibited neurite outgrowth in NGF-treated PC12 cells, as evidenced by downregulation of early growth response factor-1 and neurofilament-M. This inhibitory effect was mediated via an interaction between L5 and LOX-1 to suppress NGF-induced activation of PI3k/Akt cascade, but not NGF receptor TrkA and downstream MAPK pathways. Together, our data suggest that L5 creates a neurotoxic stress via LOX-1 in PC12 cells, thereby leading to impairment of viability and NGF-induced differentiation. Atherogenic L5 likely contributes to neurodegenerative disorders.

Insights into the human brain proteome: Disclosing the biological meaning of protein networks in cerebrospinal fluid

Cerebrospinal fluid (CSF) is an excellent source of biological information regarding the nervous system, once it is in close contact and accurately reflects alterations in this system. Several studies have analyzed differential protein profiles of CSF samples between healthy and diseased human subjects. However, the pathophysiological mechanisms and how CSF proteins relate to diseases are still poorly known. By applying bioinformatics tools, we attempted to provide new insights on the biological and functional meaning of proteomics data envisioning the identification of putative disease biomarkers. Bioinformatics analysis of data retrieved from 99 mass spectrometry (MS)-based studies on CSF profiling highlighted 1985 differentially expressed proteins across 49 diseases. A large percentage of the modulated proteins originate from exosome vesicles, and the majority are involved in either neuronal cell growth, development, maturation, migration, or neurotransmitter-mediated cellular communication. Nevertheless, some diseases present a unique CSF proteome profile, which were critically analyzed in the present study. For instance, 48 proteins were found exclusively upregulated in the CSF of patients with Alzheimer's disease and are mainly involved in steroid esterification and protein activation cascade processes. A higher number of exclusively upregulated proteins were found in the CSF of patients with multiple sclerosis (76 proteins) and with bacterial meningitis (70 proteins). Whereas in multiple sclerosis, these proteins are mostly involved in the regulation of RNA metabolism and apoptosis, in bacterial meningitis the exclusively upregulated proteins participate in inflammation and antibacterial humoral response, reflecting disease pathogenesis. The exploration of the contribution of exclusively upregulated proteins to disease pathogenesis will certainly help to envision potential biomarkers in the CSF for the clinical management of nervous system diseases.

Cerebrospinal fluid metabolomic profiling in tuberculous and viral meningitis: Screening potential markers for differential diagnosis

BACKGROUND

Tuberculous meningitis (TBM) is the most severe and frequent form of central nervous system tuberculosis. The current lack of efficient diagnostic tests makes it difficult to differentiate TBM from other common types of meningitis, especially viral meningitis (VM). Metabolomics is an important tool to identify disease-specific biomarkers. However, little metabolomic information is available on adult TBM.

METHODS

We used ¹H nuclear magnetic resonance-based metabolomics to investigate the metabolic features of the CSF from 18 TBM and 20 VM patients. Principal component analysis and orthogonal signal correction-partial least squares-discriminant analysis (OSC-PLS-DA) were applied to analyze profiling data. Metabolites were identified using the Human Metabolome Database and pathway analysis was performed with MetaboAnalyst 3.0.

RESULTS

The OSC-PLS-DA model could distinguish TBM from VM with high reliability. A total of 25 key metabolites that contributed to their discrimination were identified, including some, such as betaine and cyclohexane, rarely reported before in TBM. Pathway analysis indicated that amino acid and energy metabolism was significantly different in the CSF of TBM compared with VM.

CONCLUSIONS

Twenty-five key metabolites identified in our study may be potential biomarkers for TBM differential diagnosis and are worthy of further investigation.

Laboratory Diagnosis of Central Nervous System Infection

Central nervous system (CNS) infections are potentially life threatening if not diagnosed and treated early. The initial clinical presentations of many CNS infections are non-specific, making a definitive etiologic diagnosis challenging. Nucleic acid in vitro amplification-based molecular methods are increasingly being applied for routine microbial detection. These methods are a vast improvement over conventional techniques with the advantage of rapid turnaround and higher sensitivity and specificity. Additionally, molecular methods performed on cerebrospinal fluid samples are considered the new gold standard for diagnosis of CNS infection caused by pathogens, which are otherwise difficult to detect. Commercial diagnostic platforms offer various monoplex and multiplex PCR assays for convenient testing of targets that cause similar clinical illness. Pan-omic molecular platforms possess potential for use in this area. Although molecular methods are predicted to be widely used in diagnosing and monitoring CNS infections, results generated by these methods need to be carefully interpreted in combination with clinical findings. This review summarizes the currently available armamentarium of molecular assays for diagnosis of central nervous system infections, their application, and future approaches.