Identification of Cerebrospinal Fluid Metabolites as Biomarkers for Enterovirus Meningitis

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.

Biomarkers and genotypes in patients with Central nervous system infection caused by enterovirus

PURPOSE

Enteroviruses (EV) comprises many different types and are the most common cause of aseptic meningitis. How the virus affects the brain including potential differences between types are largely unknown. Measuring biomarkers in CSF is a tool to estimate brain damage caused by CNS infections.

METHODS

A retrospective study was performed in samples from 38 patients with acute neurological manifestations and positive CSF-EV RNA (n = 37) or serum-IgM (n = 1). The EV in 17 samples were typed by sequencing. The biomarkers neurofilament light (NFL), glial fibrillary acidic protein (GFAP), S-100B protein, amyloid-β (Aβ) 40 and Aβ42, total-tau (T-tau) and phosphorylated tau (P-tau) were measured and compared with data derived from a control group (n = 19).

RESULTS

There were no increased levels of GFAP (p ≤ 0.1) nor NFL (p ≤ 0.1) in the CSF of patients with EV meningitis (n = 38) compared with controls. However, we found decreased levels of Aβ42 (p < 0.001), Aβ40 (p < 0.001), T-tau (p ≥ 0.01), P-tau (p ≤ 0.001) and S-100B (p ≤ 0.001). E30 (n = 9) and CVB5 (n = 6) were the most frequent EV-types identified, but no differences in biomarker levels or other clinical parameters were found between the infecting virus type. Seven patients who were followed for longer than one month reported remaining cognitive impairment, although no correlations with biomarker concentrations were observed.

CONCLUSION

There are no indication of neuronal or astrocyte damage in patients with EV meningitis. Yet, decreased concentrations of Aβ40, Aβ42, P-tau and T-tau were shown, a finding of unknown importance. Cognitive impairment after acute disease occurs, but with only a limited number of patients analysed, no conclusion can be drawn concerning any association with biomarker levels or EV types.

Molecular Amplification and Cell Culturing Efficiency for Enteroviruses' Detection in Cerebrospinal Fluids of Algerian Patients Suffering from Meningitis

Enteroviruses (EVs) represent a major cause of viral meningitis, being responsible for nearly 1 billion infections each year worldwide. Several techniques were developed to obtain better diagnostic results of EV infections. Herein, we evaluated the efficiency of EV detection through isolation on both Rhabdomyosarcoma (RD) and Vero cell line cultures, conventional reverse transcription-polymerase chain reaction (RT-PCR) and real-time RT-PCR. Thus, 50 cerebrospinal fluid (CSF) samples belonging to patients suspected to have viral meningitis in northern Algeria were collected, anonymously numbered from 1 to 50 and subjected to the above-mentioned techniques for EV detection. Using real-time RT-PCR, 34 CSF samples were revealed to be positive for viral origin of meningitis (68%). Thirteen of them were positive when the conventional RT-PCR was used (26%), and only three samples gave positive results when the cell culture technique was used (6%). Surprisingly, two cell culture-positive CSF samples, namely, 31 and 39, were negative using RT-PCR directly on the original samples. However, they turned to be positive when amplification was carried out on their corresponding cell culture supernatant. The cell-cultured viral isolates were then identified by sequencing their viral genome's VP1 regions. All of them were revealed to belong to the echovirus 27 strain. This investigation demonstrates that RT-PCR techniques are often more sensitive, accurate and much faster, providing reliable results within a clinically acceptable timeframe. However, viral isolation on cell cultures remains crucial to obtain enough viral load for serological tests or even to avoid the rare, but existing, false negative PCR.

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.

Recent advances in LC-MS-based metabolomics for clinical biomarker discovery

The employment of liquid chromatography-mass spectrometry (LC-MS) untargeted and targeted metabolomics has led to the discovery of novel biomarkers and improved the understanding of various disease mechanisms. Numerous strategies have been reported to expand the metabolite coverage in LC-MS-untargeted and targeted metabolomics. To improve the sensitivity of low-abundance or poor-ionized metabolites for reducing the amount of clinical sample, chemical derivatization methods are used to target different functional groups. Proper sample preparation is beneficial for reducing the matrix effect, maintaining the stability of the LC-MS system, and increasing the metabolite coverage. Machine learning has recently been integrated into the workflow of LC-MS metabolomics to accelerate metabolite identification and data-processing automation, and increase the accuracy of disease classification and clinical outcome prediction. Due to the rapidly growing utility of LC-MS metabolomics in discovering disease markers, this review will address the recent advances in the field and offer perspectives on various strategies for expanding metabolite coverage, chemical derivatization, sample preparation, clinical disease markers, and machining learning for disease modeling.

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.

NMR based CSF metabolomics in tuberculous meningitis: correlation with clinical and MRI findings

We report the potential role of ¹H Nuclear Magnetic Resonance (NMR) based metabolomics in tuberculous meningitis (TBM). We also correlate the significant metabolites with clinical-radiological parameters. Forty-three patients with TBM were included, and their severity of meningitis was graded as stages I to III, and patients with positive Mycobacterium tuberculosis or its nucleic acid was considered as definite TBM. ¹H NMR-based metabolomic study was performed on (CSF) samples, and the significant metabolites compared to healthy controls were identified. Outcome at three months was defined as death, poor and good based on the modified Rankin Scale. These metabolites were compared between definite and probable groups of TBM, and also correlated with MRI findings. About 11 metabolites were found to be significant for distinguishing TBM from the controls. In TBM, lactate, glutamate, alanine, arginine, 2-hydroxyisobutyrate, formate, and cis-aconitate were upregulated, and glucose, fructose, glutamine, and myo-inositol were downregulated compared to the controls. For differentiating TBM from the controls, the AUC of the ROC curve generated using these significant metabolites was 0.99, with a 95% confidence interval from 0.96 to 1, demonstrating that these metabolites were able to classify cases with good sensitivity and specificity. Lactate concentration in CSF correlated with hemoglobin, CSF glucose, and infarction. The outcome did not correlate with metabolomics parameters. NMR-based CSF metabolomics have a potential role in differentiating TBM from the controls.

Metabolomic Characterization of Cerebrospinal Fluid from Intracranial Bacterial Infection Pediatric Patients: A Pilot Study

Intracranial bacterial infection remains a major cause of morbidity and mortality in neurosurgical cases. Metabolomic profiling of cerebrospinal fluid (CSF) holds great promise to gain insights into the pathogenesis of central neural system (CNS) bacterial infections. In this pilot study, we analyzed the metabolites in CSF of CNS infection patients and controls in a pseudo-targeted manner, aiming at elucidating the metabolic dysregulation in response to postoperative intracranial bacterial infection of pediatric cases. Untargeted analysis uncovered 597 metabolites, and screened out 206 differential metabolites in case of infection. Targeted verification and pathway analysis filtered out the glycolysis, amino acids metabolism and purine metabolism pathways as potential pathological pathways. These perturbed pathways are involved in the infection-induced oxidative stress and immune response. Characterization of the infection-induced metabolic changes can provide robust biomarkers of CNS bacterial infection for clinical diagnosis, novel pathways for pathological investigation, and new targets for treatment.

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.

Sera and lungs metabonomics reveals key metabolites of resveratrol protecting against PAH in rats

Pulmonary arterial hypertension (PAH) is a type of high morbidity and mortality disease. Currently, the intrinsic metabolic alteration and potential mechanism of PAH are still not fully uncovered. Previously, we have found that polyphenol resveratrol (Rev) reversed the remodeling of the pulmonary vasculature and decreased the number of mitochondria in pulmonary arterial smooth muscle cells (PASMCs) (Lei Yu et al. (2017)). However, potential effects of Rev on the changed metabolic molecules derived from lung tissue and serum have no fully elucidated. Thus, we conducted a systematic elaboration through the metabonomics method. Various of metabolites in different pathways including amino acid metabolism, tricarboxylic acid cycle (TCA), acetylcholine metabolism, fatty acid metabolism and biosynthesis in male Wistar rats' sera and lung tissues were explored in three groups (normal group, PAH group, PAH and Rev treatment group). We found that leucine and isoleucine degradation, valine, leucine and isoleucine biosynthesis, tryptophan metabolism and aminoacyl-tRNA biosynthesis were involved in the development of PAH. Hydroxyphenyllactic, isopalmitic acid and cytosine might be significant key metabolites. Further work in this area may inform personalized treatment approaches in clinical practice of PAH through elucidating pathophysiology mechanisms of experimental verification.

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.

Metabolic Reprogramming of Host Cells in Response to Enteroviral Infection

Enterovirus 71 (EV71) infection is an endemic disease in Southeast Asia and China. We have previously shown that EV71 virus causes functional changes in mitochondria. It is speculative whether EV71 virus alters the host cell metabolism to its own benefit. Using a metabolomics approach, we demonstrate that EV71-infected Vero cells had significant changes in metabolism. Glutathione and its related metabolites, and several amino acids, such as glutamate and aspartate, changed significantly with the infectious dose of virus. Other pathways, including glycolysis and tricarboxylic acid cycle, were also altered. A change in glutamine/glutamate metabolism is critical to the viral infection. The presence of glutamine in culture medium was associated with an increase in viral replication. Dimethyl α-ketoglutarate treatment partially mimicked the effect of glutamine supplementation. In addition, the immunoblot analysis revealed that the expression of glutamate dehydrogenase (GDH) and trifunctional carbamoyl-phosphate synthetase 2, aspartate transcarbamylase, and dihydroorotase (CAD) increased during infection. Knockdown of expression of glutaminase (GLS), GDH and CAD drastically reduced the cytopathic effect (CPE) and viral replication. Furthermore, we found that CAD bound VP1 to promote the de novo pyrimidine synthesis. Our findings suggest that virus may induce metabolic reprogramming of host cells to promote its replication through interactions between viral and host cell proteins.

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

Background

The timely diagnosis of bacterial meningitis is of utmost importance due to the need to institute antibiotic treatment as early as possible. Moreover, the differentiation from other causes of meningitis/encephalitis is critical because of differences in management such as the need for antiviral or immunosuppressive treatments. Considering our previously reported association between free membrane phospholipids in cerebrospinal fluid (CSF) and CNS involvement in neuroinfections we evaluated phosphatidylcholine PC ae C44:6, an integral constituent of cell membranes, as diagnostic biomarker for bacterial meningitis.

Methods

We used tandem mass spectrometry to measure concentrations of PC ae C44:6 in cell-free CSF samples (n = 221) from patients with acute bacterial meningitis, neuroborreliosis, viral meningitis/encephalitis (herpes simplex virus, varicella zoster virus, enteroviruses), autoimmune neuroinflammation (anti-NMDA-receptor autoimmune encephalitis, multiple sclerosis), facial nerve and segmental herpes zoster (shingles), and noninflammatory CNS disorders (Bell’s palsy, Tourette syndrome, normal pressure hydrocephalus).

Results

PC ae C44:6 concentrations were significantly higher in bacterial meningitis than in all other diagnostic groups, and were higher in patients with a classic bacterial meningitis pathogen (e.g. Streptococcus pneumoniae, Neisseria meningitidis, Staphylococcus aureus) than in those with less virulent or opportunistic pathogens as causative agents (P = 0.026). PC ae C44:6 concentrations were only moderately associated with CSF cell count (Spearman’s ρ = 0.45; P = 0.009), indicating that they do not merely reflect neuroinflammation. In receiver operating characteristic curve analysis, PC ae C44:6 equaled CSF cell count in the ability to distinguish bacterial meningitis from viral meningitis/encephalitis and autoimmune CNS disorders (AUC 0.93 both), but had higher sensitivity (91% vs. 41%) and negative predictive value (98% vs. 89%). A diagnostic algorithm comprising cell count, lactate and PC ae C44:6 had a sensitivity of 97% (specificity 87%) and negative predictive value of 99% (positive predictive value 61%) and correctly diagnosed three of four bacterial meningitis samples that were misclassified by cell count and lactate due to low values not suggestive of bacterial meningitis.

Conclusions

Increased CSF PC ae C44:6 concentrations in bacterial meningitis likely reflect ongoing CNS cell membrane stress or damage and have potential as additional, sensitive biomarker to diagnose bacterial meningitis in patients with less pronounced neuroinflammation.