Cerebrospinal Fluid Metabolome Research Articles

Cerebrospinal fluid metabolomes of treatment-resistant depression subtypes and ketamine response: a pilot study.

Depression is a disorder with variable presentation. Selecting treatments and dose-finding is, therefore, challenging and time-consuming. In addition, novel antidepressants such as ketamine have sparse optimization evidence. Insights obtained from metabolomics may improve the management of patients. The objective of this study was to determine whether compounds in the cerebrospinal fluid (CSF) metabolome correlate with scores on questionnaires and response to medication. We performed a retrospective pilot study to evaluate phenotypic and metabolomic variability in patients with treatment-resistant depression using multivariate data compression algorithms. Twenty-nine patients with treatment-resistant depression provided fasting CSF samples. Over 300 metabolites were analyzed in these samples with liquid chromatography-mass spectrometry. Chart review provided basic demographic information, clinical status with self-reported questionnaires, and response to medication. Of the 300 metabolites analyzed, 151 were present in all CSF samples and used in the analyses. Hypothesis-free multivariate analysis compressed the resultant data set into two dimensions using Principal Component (PC) analysis, accounting for ~ 32% of the variance. PC1 accounted for 16.9% of the variance and strongly correlated with age in one direction and 5-methyltetrahydrofolate, homocarnosine, and depression and anxiety scores in the opposite direction. PC2 accounted for 15.4% of the variance, with one end strongly correlated with autism scores, male gender, and cognitive fatigue scores, and the other end with bipolar diagnosis, lithium use, and ethylmalonate disturbance. This small pilot study suggests that complex treatment-resistant depression can be mapped onto a 2-dimensional pathophysiological domain. The results may have implications for treatment selection for depression subtypes.

Metabolomics of cerebrospinal fluid reveals candidate diagnostic biomarkers to distinguish between spinal muscular atrophy type II and type III.

Classification of spinal muscular atrophy (SMA) is associated with the clinical prognosis; however, objective classification markers are scarce. This study aimed to identify metabolic markers in the cerebrospinal fluid (CSF) of children with SMA types II and III. CSF samples were collected from 40 patients with SMA (27 with type II and 13 with type III) and analyzed for metabolites. We identified 135 metabolites associated with SMA types II and III. These were associated with lysine degradation and arginine, proline, and tyrosine metabolism. We identified seven metabolites associated with the Hammersmith Functional Motor Scale: 4-chlorophenylacetic acid, adb-chminaca,(+/-)-, dodecyl benzenesulfonic acid, norethindrone acetate, 4-(undecan-5-yl) benzene-1-sulfonic acid, dihydromaleimide beta-d-glucoside, and cinobufagin. Potential typing biomarkers, N-cyclohexylformamide, cinobufagin, cotinine glucuronide, N-myristoyl arginine, 4-chlorophenylacetic acid, geranic acid, 4-(undecan-5-yl) benzene, and 7,8-diamino pelargonate, showed good predictive performance. Among these, N-myristoyl arginine was unaffected by the gene phenotype. This study identified metabolic markers are promising candidate prognostic factors for SMA. We also identified the metabolic pathways associated with the severity of SMA. These assessments can help predict the outcomes of screening SMA classification biomarkers.

Analysis of cerebrospinal fluid metabolites affected by WenDanTang based on ultra-high-performance liquid chromatography coupled with high-resolution mass spectrometry.

WenDanTang (WDT) is a Chinese herbal formula used to treat various diseases, including neurodegenerative diseases. However, the neuroprotective metabolic pathways and the components involved in this process are not fully understood. In this study, we examined the neuroprotective metabolic pathways of WDT in rat brains using cerebrospinal fluid metabolomics and ultra-high-performance liquid chromatography-high-resolution mass spectrometry. Twelve rats were randomly divided into a WDT (administrated with WDT solution) and a control group. The ultra-high-performance liquid chromatography technique was used to explore the components of the WDT solution and cerebrospinal fluid, and secondary mass spectra of cerebrospinal fluid were used to identify possible brain-incorporating components after WDT. The results of the differential metabolism analysis showed that eight metabolites were typically altered (all p < 0.05). By comparing the secondary mass spectra of the cerebrospinal fluid of rats and WDT solution, two possible brain-incorporating components of WDT, stachydrine and α-methoxyphenylacetic acid, were identified. The data also suggested that WDT affects nucleotide metabolism, glutathione metabolism, and B-vitamin metabolic pathways, the central differential metabolic pathways. These data suggest that WDT protects neurons through its active components, such as stachydrine, and regulates biochemical metabolism to affect the brain's energy metabolism and antioxidant capacity.

Cerebrospinal fluid metabolome‐wide association study of Alzheimer’s disease provides insight into molecular pathways

AbstractBackgroundMany genetic risk variants have been identified for Alzheimer’s disease (AD), but their functional consequence on molecular pathways are unclear. Quantitative trait loci (QTL) studies help elucidate the functional effect of genetic variance on (neuro)biological processes. The understanding of AD mechanisms has been limited due to the relative inaccessibility of in vivo brain tissue and its surroundings. In this study, we integrated genetic and metabolomics cerebrospinal fluid (CSF) data, to understand how AD risk variants influence neurobiological processes.MethodWe performed a genome‐wide mQTL study on 5,543 CSF metabolite levels using data from 977 subjects (age 52.7±16.6 years, 63.8%female) from the Amsterdam Dementia Cohort (n = 487; 220 controls, 87 mild cognitive impairment, 180 AD‐type dementia) and the Utrecht cohort (n = 490 controls). We measured CSF metabolites with three platforms: GC‐TOF MS (primary metabolism, 393 metabolites), CSH‐QTOF MS/MS (complex lipids, 3,532 metabolites), and HILIC‐QTOF MS/MS (biogenic amines, 1,618 metabolites). Association signals between genetic variants and CSF metabolite levels were tested using linear regression, adjusted for principal components, age, sex and site (Amsterdam/Utrecht) using a Bonferroni‐corrected genome‐wide significance threshold (5.0e−8 /754 independent CSF signals = 6.0e−11). To identify metabolites with predicted CSF levels associated with AD, we integrated metabolite summary statistics with AD summary statistics (Kunkle et al., 2019; Bellenguez et al., 2022), using a metabolome‐wide association study (MWAS) approach (FUSION software).ResultWe identified 89 genome‐wide CSF mQTLs, including 89 independent loci for 62 CSF metabolite levels. Most mQTLs were biogenic amines (81), followed by mQTLs for the primary (5) metabolism and complex lipids (3) (Figure 1). MWAS results included 24 metabolite‐AD associations with P&lt;0.05. The strongest associations included variants proximal to the CANX gene with unannotated CSF metabolite 1.09_397.32 (PBellenguez = 2.4e−6; PKunkle = 3.4e−3), and CCDC124 variants with 8.76_225.06 (PBellenguez = 2.9e−3; PKunkle = 2.8e−5) (Figure 2).ConclusionWe identified novel metabolite‐AD risk associations, including CANX and CCDC124 with unknown CSF metabolites. In future work we aim to identify these CSF metabolites using raw spectra and intensity data. This study shows that the multi‐modal integration of genetics with CSF metabolomics helps in the functional interpretation of genetic variance, and could therefore serve as useful approach for other brain‐related disorders.

High-throughput quantitation of amino acids and acylcarnitine in cerebrospinal fluid: identification of PCNSL biomarkers and potential metabolic messengers.

Background: Due to the poor prognosis and rising occurrence, there is a crucial need to improve the diagnosis of Primary Central Nervous System Lymphoma (PCNSL), which is a rare type of non-Hodgkin's lymphoma. This study utilized targeted metabolomics of cerebrospinal fluid (CSF) to identify biomarker panels for the improved diagnosis or differential diagnosis of primary central nervous system lymphoma (PCNSL). Methods: In this study, a cohort of 68 individuals, including patients with primary central nervous system lymphoma (PCNSL), non-malignant disease controls, and patients with other brain tumors, was recruited. Their cerebrospinal fluid samples were analyzed using the Ultra-high performance liquid chromatography - tandem mass spectrometer (UHPLC-MS/MS) technique for targeted metabolomics analysis. Multivariate statistical analysis and logistic regression modeling were employed to identify biomarkers for both diagnosis (Dx) and differential diagnosis (Diff) purposes. The Dx and Diff models were further validated using a separate cohort of 34 subjects through logistic regression modeling. Results: A targeted analysis of 45 metabolites was conducted using UHPLC-MS/MS on cerebrospinal fluid (CSF) samples from a cohort of 68 individuals, including PCNSL patients, non-malignant disease controls, and patients with other brain tumors. Five metabolic features were identified as biomarkers for PCNSL diagnosis, while nine metabolic features were found to be biomarkers for differential diagnosis. Logistic regression modeling was employed to validate the Dx and Diff models using an independent cohort of 34 subjects. The logistic model demonstrated excellent performance, with an AUC of 0.83 for PCNSL vs. non-malignant disease controls and 0.86 for PCNSL vs. other brain tumor patients. Conclusion: Our study has successfully developed two logistic regression models utilizing metabolic markers in cerebrospinal fluid (CSF) for the diagnosis and differential diagnosis of PCNSL. These models provide valuable insights and hold promise for the future development of a non-invasive and reliable diagnostic tool for PCNSL.

Human Cerebrospinal Fluid Sample Preparation and Annotation for Integrated Lipidomics and Metabolomics Profiling Studies

Cerebrospinal fluid (CSF) is a metabolically diverse biofluid and a key specimen for exploring biochemical changes in neurodegenerative diseases. Detecting lipid species in CSF using mass spectrometry (MS)-based techniques remains challenging because lipids are highly complex in structure, and their concentrations span over a broad dynamic range. This work aimed to develop a robust lipidomics and metabolomics method based on commonly used two-phase extraction systems from human CSF samples. Prioritizing lipid detection, biphasic extraction methods, Folch, Bligh and Dyer (B&D), Matyash, and acidified Folch and B&D (aFolch and aB&D) were compared using 150 μL of human CSF samples for the simultaneous extraction of lipids and metabolites with a wide range of polarity. Multiple chromatographical separation approaches, including reversed-phase liquid chromatography (RPLC), hydrophilic interaction liquid chromatography (HILIC), and gas chromatography (GC), were utilized to characterize human CSF metabolome. The aB&D method was found as the most reproducible technique (RSD < 15%) for lipid extraction. The aB&D and B&D yielded the highest peak intensities for targeted lipid internal standards and displayed superior extracting power for major endogenous lipid classes. A total of 674 unique metabolites with a wide polarity range were annotated in CSF using, combining RPLC-MS/MS lipidomics (n = 219), HILIC-MS/MS (n = 304), and GC-quadrupole time of flight (QTOF) MS (n = 151). Overall, our findings show that the aB&D extraction method provided suitable lipid coverage, reproducibility, and extraction efficiency for global lipidomics profiling of human CSF samples. In combination with RPLC-MS/MS lipidomics, complementary screening approaches enabled a comprehensive metabolite signature that can be employed in an array of clinical studies.Graphical abstract

Cerebrospinal Fluid Metabolomic Pattern of Different Pituitary Stalk Lesions.

To describe the cerebrospinal fluid (CSF) metabolomic pattern of pituitary stalk lesions. CSF was collected from patients with different pituitary stalk lesions treated at Peking Union Medical College Hospital: germ cell tumor (GCT, n = 27); hypophysitis (n = 10); and Langerhans cell histiocytosis (LCH) or Erdheim-Chester disease (ECD) (LCH + ECD, n = 10). The CSF metabolome profiles were characterized by liquid chromatography-mass spectrometry (LC-MS). There were 44 metabolites that significantly differed between patients with GCT and those with hypophysitis (P < .05). Between patients with GCT with CSF level of beta subunit of human chorionic gonadotrophin (β-hCG) < 5 mIU/mL and those with hypophysitis, there were 15 differential metabolites (P < .05, fold change > 1.5 or < 1/1.5). All of the metabolites had an area under the curve (AUC) above 0.7. There were 9 metabolites that significantly differed between patients with GCT and those with LCH + ECD (P < .05) and 7 metabolites had significant differences between GCT (CSF β-hCG < 5 mIU/mL) and LCH + ECD (P < .05, fold change > 1.5 or < 1/1.5). We found 6 metabolites that were significantly different between patients with hypophysitis and those with LCH + ECD (P < .05) and 5 of these had fold change more than 1.5 or less than 1/1.5. Three metabolites, 5-deoxydiplosporin, cloversaponin I, and phytosphingosine, showed excellent capabilities to differentiate the 3 disease categories. Furthermore, we identified 67 metabolites associated with clinical test results (ρ > 0.2, P < .05) and 29 metabolites showed strong correlation (ρ > 0.4, P < .05). Our study is the first to systematically investigate the metabolomics of CSF in different pituitary stalk lesions. CSF metabolomics is a useful strategy for biomarker discovery.

Potential CSF biomarkers of postpartum depression following delivery via caesarian section

BackgroundPostpartum depression (PPD), the depressive episodes following delivery, is a serious and frequent psychiatric disorder. While numerous screening tools existed for depressive episodes, e.g., the Edinburgh Postnatal Depression Scale (EPDS), there are no objective biological measures for predicting PPD. Despite several studies done to identify biomarkers in PPD, there has been limited exploration into cerebrospinal fluid (CSF) which directly interfaces with the brain. Consequently, novel potential biomarkers of CSF are required to predict PPD, so as to target specific preventive interventions. MethodsSeventy-five parturients undergoing caesarean delivery were enrolled for CSF collection at delivery. Of the twenty-eight subjects who didn't meet any exclusion criteria, the number of the healthy parturients whose score of EPDS 6-weeks postpartum (6-wpp) < 5 and PPD patients whose EPDS 6-wpp ≥ 13 was ten respectively. Gas chromatography–mass spectrometry (GC–MS) analysis of CSF was used for metabolomic assessments. ResultsWe found that capric acid, dodecanoic acid, arachidic acid and behenic acid in CSF were significantly negatively correlated with PPD symptoms, meanwhile L-tryptophan had an obvious positive correlation. Moreover, these five biomarkers can be used as effective predictive biomarkers for PPD. LimitationsThe main limitations are the inclusion of only parturients who underwent caesarean sections and a small sample size. ConclusionsThis study innovatively investigated potential predictive biomarkers of PPD before the onset through intrapartum maternal CSF metabolomics, which offered a more objective approach to predict and diagnose PPD, leading to help identify high-risk parturients for early initiation of secondary prevention to reduce global PPD burden.

Cerebrospinal Fluid Metabolomics Identified Ongoing Analgesic Medication in Neuropathic Pain Patients.

Cerebrospinal fluid (CSF) can reasonably be hypothesized to mirror central nervous system pathophysiology in chronic pain conditions. Metabolites are small organic molecules with a low molecular weight. They are the downstream products of genes, transcripts and enzyme functions, and their levels can mirror diseased metabolic pathways. The aim of this metabolomic study was to compare the CSF of patients with chronic neuropathic pain (n = 16) to healthy controls (n = 12). Nuclear magnetic resonance spectroscopy was used for analysis of the CSF metabolome. Multivariate data analysis by projection discriminant analysis (OPLS-DA) was used to separate information from noise and minimize the multiple testing problem. The significant OPLS-DA model identified 26 features out of 215 as important for group separation (R2 = 0.70, Q2 = 0.42, p = 0.017 by CV-ANOVA; 2 components). Twenty-one out of twenty-six features were statistically significant when comparing the two groups by univariate statistics and remained significant at a false discovery rate of 10%. For six out of the top ten metabolite features, the features were absent in all healthy controls. However, these features were related to medication, mainly acetaminophen (=paracetamol), and not to pathophysiological processes. CSF metabolomics was a sensitive method to detect ongoing analgesic medication, especially acetaminophen.

Gas Chromatography-Mass Spectrometry-Based Cerebrospinal Fluid Metabolomics to Reveal the Protection of Coptisine against Transient Focal Cerebral Ischemia-Reperfusion Injury via Anti-Inflammation and Antioxidant.

Coptisine (Cop) exerts a neuroprotective effect on central nervous system disease, particularly ischemic stroke. However, its protective mechanism is still unclear. This study aimed to investigate the protective effect of Cop on cerebral ischemia-reperfusion (IR) rats with a middle cerebral artery occlusion model by integrating a gas chromatography-mass spectrometry (GC-MS)-based metabolomics approach with biochemical assessment. Our results showed that Cop could improve neurobehavioral function and decrease the ischemia size in IR rats. In addition, Cop was found to decrease inflammatory mediators (e.g., prostaglandin D2 (PGD2) and tumor necrosis factor-α (TNF-α) and attenuate oxidative stress response (e.g., increase the superoxide dismutase (SOD) expression and decrease 8-iso-PGF2α level). Furthermore, the GC-MS-based cerebrospinal fluid (CSF) metabolomics analysis indicated that Cop influenced the level of glycine, 2,3,4-trihydroxybutyric acid, oleic acid, glycerol, and ribose during IR injury. Cop exhibited a good neuroprotective effect against cerebral IR injury and metabolic alterations, which might be mediated through its antioxidant and anti-inflammatory properties.

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

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. 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. 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. 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.

BSLD-05 ESTABLISHMENT AND CHARACTERIZATION OF MOUSE MODELS OF LEPTOMENINGEAL METASTASIS

Abstract There is critical need to study leptomeningeal metastasis (LM), a fatal complication of cancer accompanied by severe neurological deficits. LM occurs when cancer cells enter the leptomeninges, float in the cerebrospinal fluid (CSF), and adhere to the surface of the brain and spinal cord. Understanding the molecular basis of LM requires reliable models of the disease that can recapitulate the complex microenvironment that supports LM cell growth. Here, we define a protocol for iterative in vivo selection of cancer cells competent to colonize the leptomeninges (LeptoM cells) from a larger population of primary tumor cells that stably express GFP and luciferase. We use these LeptoM cells to establish tractable models of leptomeningeal disease in both syngeneic and xenograft mice. With these models, we modulate disease severity and capture snapshots of hallmark LM characteristics over time. We demonstrate the fidelity of these mouse models to human disease in several dimensions: 1. Biochemically, through CSF proteomics and metabolomics; 2. Immunologically, via flow cytometry and cytokine profiling; 3. Transcriptionally through RNA sequencing; and 4. Neurologically by accumulation of neurological signs. They are freely available to the academic community. These models provide robust, reproducible tools for discovery and mechanistic dissection. They will enable identification of critical disease mechanisms, and assays of novel treatment modalities against LM.

Day-night fluctuations in choroid plexus transcriptomics and cerebrospinal fluid metabolomics.

The cerebrospinal fluid (CSF) provides mechanical protection for the brain and serves as a brain dispersion route for nutrients, hormones, and metabolic waste. The CSF secretion rate is elevated in the dark phase in both humans and rats, which could support the CSF flow along the paravascular spaces that may be implicated in waste clearance. The similar diurnal CSF dynamics pattern observed in the day-active human and the nocturnal rat suggests a circadian regulation of this physiological variable, rather than sleep itself. To obtain a catalog of potential molecular drivers that could provide the day-night-associated modulation of the CSF secretion rate, we determined the diurnal fluctuation in the rat choroid plexus transcriptomic profile with RNA-seq and in the CSF metabolomics with ultraperformance liquid chromatography combined with mass spectrometry. We detected significant fluctuation of 19 CSF metabolites and differential expression of 2,778 choroid plexus genes between the light and the dark phase, the latter of which encompassed circadian rhythm-related genes and several choroid plexus transport mechanisms. The fluctuating components were organized with joint pathway analysis, of which several pathways demonstrated diurnal regulation. Our results illustrate substantial transcriptional and metabolic light-dark phase-mediated changes taking place in the rat choroid plexus and its encircling CSF. The combined data provide directions toward future identification of the molecular pathways governing the fluctuation of this physiological process and could potentially be harnessed to modulate the CSF dynamics in pathology.

Multi-omics profiling of CSF from spinal muscular atrophy type 3 patients after nusinersen treatment: a 2-year follow-up multicenter retrospective study

Spinal muscular atrophy (SMA) is a neurodegenerative disorder caused by mutations in the SMN1 gene resulting in reduced levels of the SMN protein. Nusinersen, the first antisense oligonucleotide (ASO) approved for SMA treatment, binds to the SMN2 gene, paralogue to SMN1, and mediates the translation of a functional SMN protein. Here, we used longitudinal high-resolution mass spectrometry (MS) to assess both global proteome and metabolome in cerebrospinal fluid (CSF) from ten SMA type 3 patients, with the aim of identifying novel readouts of pharmacodynamic/response to treatment and predictive markers of treatment response. Patients had a median age of 33.5 [29.5; 38.25] years, and 80% of them were ambulant at time of the enrolment, with a median HFMSE score of 37.5 [25.75; 50.75]. Untargeted CSF proteome and metabolome were measured using high-resolution MS (nLC-HRMS) on CSF samples obtained before treatment (T0) and after 2 years of follow-up (T22). A total of 26 proteins were found to be differentially expressed between T0 and T22 upon VSN normalization and LIMMA differential analysis, accounting for paired replica. Notably, key markers of the insulin-growth factor signaling pathway were upregulated after treatment together with selective modulation of key transcription regulators. Using CombiROC multimarker signature analysis, we suggest that detecting a reduction of SEMA6A and an increase of COL1A2 and GRIA4 might reflect therapeutic efficacy of nusinersen. Longitudinal metabolome profiling, analyzed with paired t-Test, showed a significant shift for some aminoacid utilization induced by treatment, whereas other metabolites were largely unchanged. Together, these data suggest perturbation upon nusinersen treatment still sustained after 22 months of follow-up and confirm the utility of CSF multi-omic profiling as pharmacodynamic biomarker for SMA type 3. Nonetheless, validation studies are needed to confirm this evidence in a larger sample size and to further dissect combined markers of response to treatment.

Cerebrospinal fluid metabolite alterations in patients with different etiologies, diagnoses, and prognoses of disorders of consciousness.

Medical management of disorders of consciousness (DoC) is a growing issue imposing a major burden on families and societies. Recovery rates vary widely among patients with DoC, and recovery predictions strongly influence decisions on medical care. However, the specific mechanisms underlying different etiologies, consciousness levels, and prognoses are still unclear. We analyzed the comprehensive cerebrospinal fluid (CSF) metabolome through liquid chromatography-mass spectrometry. Metabolomic analyses were used to identify the metabolic differences between patients with different etiologies, diagnoses, and prognoses. We found that the CSF levels of multiple acylcarnitines were lower in patients with traumatic DoC, suggesting mitochondrial function preservation in the CNS, which might contribute to the better consciousness outcomes of these patients. Metabolites related to glutamate and GABA metabolism were altered and showed a good ability to distinguish the patients in the minimally conscious state and the vegetative state. Moreover, we identified 8 phospholipids as potential biomarkers to predict the recovery of consciousness. Our findings shed light on the differences in physiological activities underlying DoC with different etiologies and identified some potential biomarkers used for DoC diagnosis and prognosis.

Metabolomics of cerebrospinal fluid reveals prognostic biomarkers in pediatric status epilepticus.

Status epilepticus (SE) is the most common neurological emergency in pediatric patients. This study aimed to screen for prognostic biomarkers of SE in the cerebrospinal fluid (CSF) using metabolomics. Ultra-performance liquid chromatography quadrupole time-of-flight tandem mass spectrometry (UPLC-QTOF-MS) was conducted to identify prognostic biomarkers in CSF metabolomics by comparing the poor outcome group (N = 13) with the good outcome group (N = 15) of children with SE. Differentially expressed metabolites were identified using Mann-Whitney U test corrected by Benjamini-Hochberg and partial least squares discriminant analysis (PLS-DA). The PLS-DA model identified and validated significant metabolic differences between the poor and good outcome groups of children with SE (PLS-DA with R2 Y = 0.992 and Q2  = 0.798). A total of 49 prognosis-related metabolites were identified. Of these metabolites, 20 including glutamyl-glutamine, 3-iodothyronamine, and L-fucose had an area under the curve (AUC) ≥ 80% in prognostic prediction of SE. The logistic regression model combining glutamyl-glutamine and 3-iodothyronamine produced an AUC value of 0.976, with a sensitivity of 0.863 and specificity of 0.956. Pathway analysis revealed that dysregulation of the citrate cycle (TCA) and arginine biosynthesis may contribute to poor SE prognosis. This study highlighted the prognosis-related metabolomic disturbances in the CSF of children with SE and identified potential prognostic biomarkers. A prognostic prediction model combining glutamyl-glutamine and 3-iodothyronamine with high predictive value was established.

Defining diurnal fluctuations in mouse choroid plexus and CSF at high molecular, spatial, and temporal resolution

Transmission and secretion of signals via the choroid plexus (ChP) brain barrier can modulate brain states via regulation of cerebrospinal fluid (CSF) composition. Here, we developed a platform to analyze diurnal variations in male mouse ChP and CSF. Ribosome profiling of ChP epithelial cells revealed diurnal translatome differences in metabolic machinery, secreted proteins, and barrier components. Using ChP and CSF metabolomics and blood-CSF barrier analyses, we observed diurnal changes in metabolites and cellular junctions. We then focused on transthyretin (TTR), a diurnally regulated thyroid hormone chaperone secreted by the ChP. Diurnal variation in ChP TTR depended on Bmal1 clock gene expression. We achieved real-time tracking of CSF-TTR in awake TtrmNeonGreen mice via multi-day intracerebroventricular fiber photometry. Diurnal changes in ChP and CSF TTR levels correlated with CSF thyroid hormone levels. These datasets highlight an integrated platform for investigating diurnal control of brain states by the ChP and CSF.

Porcine cardiac blood - Salvia miltiorrhiza root alleviates cerebral ischemia reperfusion injury by inhibiting oxidative stress induced apoptosis through PI3K/AKT/Bcl-2/Bax signaling pathway

Ethnopharmacological relevanceSalvia miltiorrhiza Bge. mixed with porcine cardiac blood (PCB-DS) is mainly employed for the treatment of brain ischemia-induced mental disturbances, palpitations and phlegm confusion based on the traditional principle of Menghe medical sect. PCB is the guide to DS and enhances the effect of DS. However, the potential mechanism of PCB-DS preventing cerebral ischemia/reperfusion injury (CIRI) from the perspective of oxidative stress induced cell apoptosis remains unknown. Aim of the studyTo investigate the pharmacological activity and molecular mechanism of PCB-DS against CIRI. Materials and methodsDS samples processed with different methods were prepared and UPLC-Q-TOF-MS/MS was employed for qualitative analysis of the respective processing product. The middle cerebral artery occlusion reperfusion model was then established to investigate the pharmacological activities of PCB-DS. Pathological changes in the rat brain were observed by triphenyl tetrazolium chloride (TTC), hematoxylin-eosin, and TUNEL staining. The levels of IL-6, IL-1β, and TNF-α were detected by ELISA to evaluate the inflammatory damage. Metabolomics of cerebrospinal fluid was further used to explore the potential mechanism of PCB-DS in preventing CIRI. Based on this, the levels of oxidative stress-related lactate dehydrogenase (LDH), reactive oxygen species (ROS), malondialdehyde (MDA), and superoxide dismutase (SOD) were determined. The protein levels of PI3K, AKT, Bcl-2, Bax, cleaved-caspase-3, and cleaved-caspase-9 proteins of the cerebral infarct zone were finally measured by western blotting. ResultsForty-seven components were identified in four processing products. Compared to DS, the content of total aqueous components in PCB-DS was significantly increased including salvianolic acid B isomer, salvianolic acid D, salvianolic acid F, and salvianolic acid H/I/J. Among the DS, DS processed with wine, DS processed with pig blood, and DS processed with porcine cardiac blood, PCB-DS best alleviated the CIRI through the neurological score, brain infarct volume, brain histopathology and the levels of inflammatory factors in the brain. Twenty-five significant metabolites in the cerebrospinal fluid were screened out between the sham and I/R groups. They were mainly involved in the beta-alanine metabolism, histidine metabolism, and lysine degradation, which indicated that PCB-DS may inhibit oxidative stress-induced apoptosis to achieve treating ischemic stroke. The results of biomedical examination showed that PCB-DS could alleviate oxidative damage, significantly downregulate the expression of Bax, cleaved caspase-3 and cleaved caspase-9, and upregulate the expression of p-PI3K, p-AKT, and Bcl-2. ConclusionIn summary, this study demonstrated that PCB-DS alleviated CIRI and the molecular mechanism may be related to inhibiting the oxidative stress induced apoptosis through PI3K/AKT/Bcl-2/Bax signaling pathway.

Large-scale proteome and metabolome analysis of CSF implicates altered glucose and carbon metabolism and succinylcarnitine in Alzheimer's disease.

A hallmark of Alzheimer's disease (AD) is the aggregation of proteins (amyloid beta [A] and hyperphosphorylated tau [T]) in the brain, making cerebrospinal fluid (CSF) proteins of particular interest. We conducted a CSF proteome-wide analysis among participants of varying AT pathology (n=137 participants; 915 proteins) with nine CSF biomarkers of neurodegeneration and neuroinflammation. We identified 61 proteins significantly associated with the AT category (P<5.46×10-5 ) and 636 significant protein-biomarker associations (P<6.07×10-6 ). Proteins from glucose and carbon metabolism pathways were enriched among amyloid- and tau-associated proteins, including malate dehydrogenase and aldolase A, whose associations with tau were replicated in an independent cohort (n=717). CSF metabolomics identified and replicated an association of succinylcarnitine with phosphorylated tau and other biomarkers. These results implicate glucose and carbon metabolic dysregulation and increased CSF succinylcarnitine levels with amyloid and tau pathology in AD. Cerebrospinal fluid (CSF) proteome enriched for extracellular, neuronal, immune, and protein processing. Glucose/carbon metabolic pathways enriched among amyloid/tau-associated proteins. Key glucose/carbon metabolism protein associations independently replicated. CSF proteome outperformed other omics data in predicting amyloid/tau positivity. CSF metabolomics identified and replicated a succinylcarnitine-phosphorylated tau association.

CSF metabolomics alterations after aneurysmal subarachnoid hemorrhage: what do we know?

The purpose of this mini review is to describe metabolomics in cerebrospinal fluid (CSF) and its potential in aneurysmal subarachnoid hemorrhage (aSAH). In brain injury, patients' micro dialysis enables detecting biochemical change in brain tissue. Indicators for ischemia were detected such as lactate, pyruvate, glucose, and glutamate. In aSAH patients, the pathophysiology and the factor for poor outcome are not completely understood yet. Routine use of biomarkers in CSF, particularly in aSAH patients, is still lacking. This mini review was performed on the role of metabolomics alterations after aneurysmal subarachnoid hemorrhage. We identified five clinical studies that addressed metabolomics in patients with aneurysmal subarachnoid hemorrhage. There is increasing evidence suggesting that biomarkers can give insight in the pathogenesis and can serve as an outcome predictor. In this mini review, we present a brief overview of metabolomics profiling in neuroscience and wish to discuss the predictive and therapeutic value in aSAH patients.