Phosphatidylcholine PC ae C44:6 in cerebrospinal fluid is a sensitive biomarker for bacterial meningitis

Phospholipids and their metabolites as diagnostic biomarkers of human diseases

Phospholipids that occur predominantly in the plasma membrane of mammalian cells are phosphatidylcholine (PC), phosphatidylserine (PS), phosphatidylethanolamine (PE), sphingomyelin (SM), and phosphatidylinositol (or phosphoinositide; PI). These membrane phospholipids are a promising source of disease-related biomarkers. Phospholipids and their metabolites are altered by the type of disease or disease progression. Metabolomics has shown that increased or decreased levels of altered phospholipids and their metabolites can be useful indicators for the diagnosis of various human diseases. In this review, we discuss the utility of the five major membrane phospholipids (PC, PS, PE, and SM, and PI) and their metabolites as diagnostic biomarkers of human diseases.

Acute neuromyelitis optica spectrum disorder patients' clinical analysis of disability-related biomarkers

BACKGROUND

The clinical features of neuromyelitis optica spectrum disorder (NMOSD) predominantly include optic neuritis and myelitis, among other symptoms. A greater level of disability during the acute phase typically suggests an unfavorable prognosis. Nevertheless, the clinical biomarkers that impact the severity of disability in NMOSD remain unclear.

METHODS

We analyzed 41 NMOSD patients and 41 normal controls to identify biomarkers associated with the disease. NMOSD patients were categorized into two groups based on their Expanded Disability Status Scale(EDSS) score: mild to moderate disability (EDSS < 4) and severe disability (EDSS ≥ 4). Correlation and ROC analyses were conducted on various biomarkers, including neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio(MLR), cerebrospinal fluid (CSF)/serum albumin quotient(QAlb), CSF/blood immunoglobulin G quotient (QIgG), CSF/blood immunoglobulin A quotient (QIgA), CSF/blood immunoglobulin M quotient (QIgM), to identify markers linked to disability severity and confirm their independence.

RESULTS

Significant differences in blood NLR, PLR, and MLR were found between NMOSD patients and normal controls (P < 0.01) in biomarker comparison analysis. Significant variations in QAlb, QIgG, QIgA, QIgM, and PLR were noted between the two groups of NMOSD patients stratified by disability severity. A correlation analysis revealed a positive association between QAlb, QIgG, QIgA, QIgM, PLR, and EDSS scores. Levels of QAlb, QIgG, QIgA, QIgM, and PLR were found to be effective indicators of NMOSD severity in Receiver Operating Characteristic (ROC) analysis (P < 0.01). Multifactor regression analysis confirmed the independence of PLR in assessing disease severity (P < 0.01).

CONCLUSION

1. QAlb, QIgG, QIgA, QIgM, and PLR have demonstrated efficacy as biomarkers for assessing the severity of NMOSD; 2. PLR has shown promise as a standalone indicator for evaluating disease severity in patients with NMOSD.

LC-MS metabolomics and lipidomics in cerebrospinal fluid from viral and bacterial CNS infections: a review

There is compelling evidence that a dysregulated immune inflammatory response in neuroinfectious diseases results in modifications in metabolic processes and altered metabolites, directly or indirectly influencing lipid metabolism within the central nervous system (CNS). The challenges in differential diagnosis and the provision of effective treatment in many neuroinfectious diseases are, in part, due to limited understanding of the pathophysiology underlying the disease. Although there are numerous metabolomics studies, there remains a deficit in neurolipidomics research to provide a comprehensive understanding of the connection between altered metabolites and changes in lipid metabolism. The brain is an inherently high-lipid organ; hence, understanding neurolipidomics is the key to future breakthroughs. This review aims to provide an integrative summary of altered cerebrospinal fluid (CSF) metabolites associated with neurolipid metabolism in bacterial and viral CNS infections, with a particular focus on studies that used liquid chromatography-mass spectrometry (LC-MS). Lipid components (phospholipids) and metabolites (carnitine and tryptophan) appear to be the most significant indicators in both bacterial and viral infections. On the basis of our analysis of the literature, we recommend employing neurolipidomics in conjunction with existing neurometabolomics data as a prospective method to enhance our understanding of the cross link between dysregulated metabolites and lipid metabolism in neuroinfectious diseases.

Targeted metabolomics identifies accurate CSF metabolite biomarkers for the differentiation between COVID-19 with neurological involvement and CNS infections with neurotropic viral pathogens

BACKGROUND

COVID-19 is primarily considered a respiratory tract infection, but it can also affect the central nervous system (CNS), which can result in long-term sequelae. In contrast to CNS infections by classic neurotropic viruses, SARS-CoV-2 is usually not detected in cerebrospinal fluid (CSF) from patients with COVID-19 with neurological involvement (neuro-COVID), suggesting fundamental differences in pathogenesis.

METHODS

To assess differences in CNS metabolism in neuro-COVID compared to CNS infections with classic neurotropic viruses, we applied a targeted metabolomic analysis of 630 metabolites to CSF from patients with (i) COVID-19 with neurological involvement [n = 16, comprising acute (n = 13) and post-COVID-19 (n = 3)], (ii) viral meningitis, encephalitis, or myelitis (n = 10) due to herpes simplex virus (n = 2), varicella zoster virus (n = 6), enterovirus (n = 1) and tick-borne encephalitis virus (n = 1), and (iii) aseptic neuroinflammation (meningitis, encephalitis, or myelitis) of unknown etiology (n = 21) as additional disease controls.

RESULTS

Standard CSF parameters indicated absent or low neuroinflammation in neuro-COVID. Indeed, CSF cell count was low in neuro-COVID (median 1 cell/µL, range 0-12) and discriminated it accurately from viral CNS infections (AUC = 0.99) and aseptic neuroinflammation (AUC = 0.98). 32 CSF metabolites passed quality assessment and were included in the analysis. Concentrations of differentially abundant (fold change ≥|1.5|, FDR ≤ 0.05) metabolites were both higher (9 and 5 metabolites) and lower (2 metabolites) in neuro-COVID than in the other two groups. Concentrations of citrulline, ceramide (d18:1/18:0), and methionine were most significantly elevated in neuro-COVID. Remarkably, triglyceride TG(20:1_32:3) was much lower (mean fold change = 0.09 and 0.11) in neuro-COVID than in all viral CNS infections and most aseptic neuroinflammation samples, identifying it as highly accurate biomarker with AUC = 1 and 0.93, respectively. Across all samples, TG(20:1_32:3) concentration correlated only moderately with CSF cell count (ρ = 0.65), protein concentration (ρ = 0.64), and Q-albumin (ρ = 0.48), suggesting that its low levels in neuro-COVID CSF are only partially explained by less pronounced neuroinflammation.

CONCLUSIONS

The results suggest that CNS metabolite responses in neuro-COVID differ fundamentally from viral CNS infections and aseptic neuroinflammation and may be used to discover accurate diagnostic biomarkers in CSF and to gain insights into differences in pathophysiology between neuro-COVID, viral CNS infections and aseptic neuroinflammation.

Amyloid and Tau as cerebrospinal fluid biomarkers in anti-N-Methyl-D-aspartate receptor encephalitis

INTRODUCTION

Neuroinfection is associated with the deposition of amyloid-beta (Aβ) peptides, and subsequent decrease in cerebrospinal fluid (CSF) amyloid levels. However, whether autoimmune encephalitis involves extracellular deposition of Aβ peptides in the brain is unreported.

METHODS

We examined CSF amyloid and tau values in adults with anti-N-methyl-D-aspartate receptor encephalitis (NMDAR-E). Forty-two patients with NMDAR-E, 35 patients with viral and bacterial neuroinfections, and 16 controls were included. We measured CSF Aβ1-42 (cAβ1-42), Aβ1-40 (cAβ1-40), t-Tau (ct-Tau), and p-Tau181 (cp-Tau181) levels and assessed their efficacies regarding differential diagnosis and predicting prognosis.

RESULTS

NMDAR-E patients had lower cAβ1-42 levels; however, they were higher than those of patients with bacterial meningitis. ct-Tau levels in NMDAR-E patients were lower than those in patients with neuroinfections. No changes were observed in controls. cAβ1-42 and ct-Tau were combined as an excellent marker to distinguish NMDAR-E from neuroinfections. cAβ1-42 levels in NMDAR-E patients were positively correlated with Montreal Cognitive Assessment scores. We observed an inverse relationship between cAβ1-42 levels and modified Rankin Scale scores. Patients with poor outcomes exhibited low cAβ1-42 levels and high levels of several blood parameters. cAβ1-42 was the highest quality biomarker for assessing NMDAR-E prognosis. Correlations were found between cAβ1-42 and some inflammatory indicators.

CONCLUSION

cAβ1-42 was decreased in NMDAR-E patients. cAβ1-42 levels indicated NMDAR-E severity and acted as a biomarker for its prognosis. Combining cAβ1-42 and ct-Tau levels could serve as a novel differential diagnostic marker for NMDAR-E.

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.

Elevated phospholipids and acylcarnitines C4 and C5 in cerebrospinal fluid distinguish viral CNS infections from autoimmune neuroinflammation

BACKGROUND

Viral and autoimmune encephalitis may present with similar symptoms, but require different treatments. Thus, there is a need for biomarkers to improve diagnosis and understanding of pathogenesis. We hypothesized that virus-host cell interactions lead to different changes in central nervous system (CNS) metabolism than autoimmune processes and searched for metabolite biomarkers in cerebrospinal fluid (CSF) to distinguish between the two conditions.

METHODS

We applied a targeted metabolomic/lipidomic analysis to CSF samples from patients with viral CNS infections (n = 34; due to herpes simplex virus [n = 9], varicella zoster virus [n = 15], enteroviruses [n = 10]), autoimmune neuroinflammation (n = 25; autoimmune anti-NMDA-receptor encephalitis [n = 8], multiple sclerosis [n = 17), and non-inflamed controls (n = 31; Gilles de la Tourette syndrome [n = 20], Bell's palsy with normal CSF cell count [n = 11]). 85 metabolites passed quality screening and were evaluated as biomarkers. Standard diagnostic CSF parameters were assessed for comparison.

RESULTS

Of the standard CSF parameters, the best biomarkers were: CSF cell count for viral infections vs. controls (area under the ROC curve, AUC = 0.93), Q-albumin for viral infections vs. autoimmune neuroinflammation (AUC = 0.86), and IgG index for autoimmune neuroinflammation vs. controls (AUC = 0.90). Concentrations of 2 metabolites differed significantly (p < 0.05) between autoimmune neuroinflammation and controls, with proline being the best biomarker (AUC = 0.77). In contrast, concentrations of 67 metabolites were significantly higher in viral infections than controls, with SM.C16.0 being the best biomarker (AUC = 0.94). Concentrations of 68 metabolites were significantly higher in viral infections than in autoimmune neuroinflammation, and the 10 most accurate metabolite biomarkers (AUC = 0.89-0.93) were substantially better than Q-albumin (AUC = 0.86). These biomarkers comprised six phosphatidylcholines (AUC = 0.89-0.92), two sphingomyelins (AUC = 0.89, 0.91), and acylcarnitines isobutyrylcarnitine (C4, AUC = 0.92) and isovalerylcarnitine (C5, AUC = 0.93). Elevated C4 and C5 concentrations suggested dysfunctional mitochondrial β-oxidation and correlated only moderately with CSF cell count (Spearman ρ = 0.41 and 0.44), indicating that their increase is not primarily driven by inflammation.

CONCLUSIONS

Changes in CNS metabolism differ substantially between viral CNS infections and autoimmune neuroinflammation and reveal CSF metabolites as pathophysiologically relevant diagnostic biomarkers for the differentiation between the two conditions. In viral CNS infections, the observed higher concentrations of free phospholipids are consistent with disruption of host cell membranes, whereas the elevated short-chain acylcarnitines likely reflect compromised mitochondrial homeostasis and energy generation.

Immunologic biomarkers for bacterial meningitis

Meningitis is defined as the inflammation of the meninges that is most often caused by various bacterial and viral pathogens, and is associated with high rates of mortality and morbidity. Early detection of bacterial meningitis is essential to appropriate antibiotic therapy. Alterations in immunologic biomarkers levels have been considered the diagnostic approach in medical laboratories for the identifying of infections. The early increasing immunologic mediators such as cytokines and acute phase proteins (APPs) during bacterial meningitis have made they significant indicators for laboratory diagnosis. Immunology biomarkers showed wide variable sensitivity and specificity values that influenced by different reference values, selected a certain cutoff point, methods of detection, patient characterization and inclusion criteria, as well as etiology of meningitis and time of CSF or blood specimens' collection. This study provides an overview of different immunologic biomarkers as diagnostic markers for the identification of bacterial meningitis and their efficiencies in the differentiating of bacterial from viral meningitis.

Integrated lipidomic and transcriptomic analysis reveals clarithromycin-induced alteration of glycerophospholipid metabolism in the cerebral cortex of mice

Clarithromycin (CLA) has been widely used in the treatment of bacterial infection. Research reveals the adverse effects on the central nervous system among patients receiving CLA treatment; whereas, a relevant underlying mechanism remains considerably unclear. According to our research, an integrated lipidomic and transcriptomic analysis was applied to explore the effect of CLA on neurobehavior. CLA treatment caused anxiety-like behaviors dose-dependently during open field as well as elevated plus maze trials on mice. Transcriptomes and LC/MS-MS-based metabolomes were adopted for investigating how CLA affected lipidomic profiling as well as metabolic pathway of the cerebral cortex. CLA exposure greatly disturbed glycerophospholipid metabolism and the carbon chain length of fatty acids. By using whole transcriptome sequencing, we found that CLA significantly downregulated the mRNA expression of CEPT1 and CHPT1, two key enzymes involved in the synthesis of glycerophospholipids, supporting the findings from the lipidomic profiling. Also, CLA causes changes in neuronal morphology and function in vitro, which support the existing findings concerning neurobehavior in vivo. We speculate that altered glycerophospholipid metabolism may be involved in the neurobehavioral effect of CLA. Our findings contribute to understanding the mechanisms of CLA-induced adverse effects on the central nervous system. 1. Clarithromycin treatment caused anxiety-like behavior with dose-dependent response both in the open field and elevated plus maze test in mice; 2. Clarithromycin exposing predominately disturbed the metabolism of glycerophospholipids in the cerebral cortex of mice; 3. Clarithromycin application remarkably attenuated CEPT1 and CHPT1 gene expression, which participate in the last step in the synthesis of glycerophospholipids; 4. The altered glycerophospholipid metabolomics may be involved in the abnormal neurobehavior caused by clarithromycin.

Ventriculitis: Infection or Inflammation

Ventriculitis, or infection of the cerebrospinal fluid, in the presence of external ventricular drains (EVD), is an important complication and associated with substantial mortality, morbidity, and healthcare costs. Further, the conditions that require the insertion of an EVD, such as neurotrauma and subarachnoid hemorrhage, are themselves associated with inflammation of the cerebrospinal fluid. Phenotypically, patients with inflammation of the cerebrospinal fluid can present with very similar symptoms, signs, and laboratory findings to those with infection. This review examines various controversies relating to the definitions, diagnosis, challenges of differentiating infection from inflammation, prevention, and treatment of ventriculitis in patients with EVDs.

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.

Elevated Free Phosphatidylcholine Levels in Cerebrospinal Fluid Distinguish Bacterial from Viral CNS Infections

The identification of CSF biomarkers for bacterial meningitis can potentially improve diagnosis and understanding of pathogenesis, and the differentiation from viral CNS infections is of particular clinical importance. Considering that substantial changes in CSF metabolites in CNS infections have recently been demonstrated, we compared concentrations of 188 metabolites in CSF samples from patients with bacterial meningitis (n = 32), viral meningitis/encephalitis (n = 34), and noninflamed controls (n = 66). Metabolite reprogramming in bacterial meningitis was greatest among phosphatidylcholines, and concentrations of all 54 phosphatidylcholines were significantly (p = 1.2 × 10⁻²⁵–1.5 × 10⁻⁴) higher than in controls. Indeed, all biomarkers for bacterial meningitis vs. viral meningitis/encephalitis with an AUC ≥ 0.86 (ROC curve analysis) were phosphatidylcholines. Four of the five most accurate (AUC ≥ 0.9) phosphatidylcholine biomarkers had higher sensitivity and negative predictive values than CSF lactate or cell count. Concentrations of the 10 most accurate phosphatidylcholine biomarkers were lower in meningitis due to opportunistic pathogens than in meningitis due to typical meningitis pathogens, and they correlated most strongly with parameters reflecting blood–CSF barrier dysfunction and CSF lactate (r = 0.73–0.82), less so with CSF cell count, and not with blood CRP. In contrast to the elevated phosphatidylcholine concentrations in CSF, serum concentrations remained relatively unchanged. Taken together, these results suggest that increased free CSF phosphatidylcholines are sensitive biomarkers for bacterial meningitis and do not merely reflect inflammation but are associated with local disease and a shift in CNS metabolism.

Obeticholic Acid Inhibits Anxiety via Alleviating Gut Microbiota-Mediated Microglia Accumulation in the Brain of High-Fat High-Sugar Diet Mice

Anxiety is one of the complications of metabolic disorders (MDs). Obeticholic acid (OCA), the bile acids (BAs) derivative, is a promising agent for improving MDs in association with gut dysbiosis. Yet, its protective effect on MDs-driven anxiety remains unknown. Here, we assessed the serum biochemical parameters and behavioral performance by open field and Morris water maze tests in HFHS diet-induced MDs mice after OCA intervention for nine and 18 weeks. Moreover, antibiotics intervention for microbial depletion was conducted simultaneously. We found that OCA treatment inhibited the initiation and progression of anxiety in HFHS diet-MDs mice via a microbiota–BAs–brain axis: OCA decreased the neuroinflammatory microglia and IL-1β expression in the hippocampus, reversed intestinal barrier dysfunction and serum proinflammatory LPS to a normal level, modified the microbial community, including the known anxiety-related Rikenellaceae and Alistipes, and improved the microbial metabolites especially the increased BAs in feces and circulation. Moreover, the OCA-reversed bile acid taurocholate linked disordered serum lipid metabolites and indole derivatives to anxiety as assessed by network analysis. Additionally, microbial depletion with antibiotics also improved the anxiety, microgliosis and BAs enrichment in the experimental MDs mice. Together, these findings provide microbiota–BAs–brain axis as a novel therapeutic target for MDs-associated neuropsychiatric disorders.

Targeted metabolomic profiling of cerebrospinal fluid from patients with progressive multifocal leukoencephalopathy

Progressive multifocal leukoencephalopathy (PML), caused by JC polyomavirus, is a demyelinating disease of the central nervous system that primarily affects oligodendrocytes. It can cause significant morbidity and mortality. An early diagnosis is of high relevance as timely immune reconstitution is essential. However, diagnosis can be challenging if virus detection via cerebrospinal fluid (CSF) PCR remains negative. Hence, identifying CSF biomarkers for this disease is of crucial importance. We applied a targeted metabolomic screen to CSF from 23 PML patients and eight normal pressure hydrocephalus (NPH) patients as controls. Out of 188 potentially detectable metabolites, 48 (13 amino acids, 4 biogenic amines, 1 acylcarnitine, 21 phosphatidylcholines, 8 sphingolipids, and the sum of hexoses) passed the quality screen and were included in the analyses. Even though there was a tendency towards lower concentrations in PML (mostly of phosphatidylcholines and sphingomyelins), none of the differences between PML and controls in individual metabolite concentrations reached statistical significance (lowest p = 0.104) and there were no potential diagnostic biomarkers (highest area under the ROC curve 0.68). Thus, CSF metabolite changes in PML are likely subtle and possibly larger group sizes and broader metabolite screens are needed to identify potential CSF metabolite biomarkers for PML.