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Lysosomes have many roles, including degrading macromolecules and signalling to the nucleus 1 . Lysosomal dysfunction occurs in various human conditions, such as common neurodegenerative diseases and monogenic lysosomal storage disorders (LSDs) 2 , 3 – 4 . For most LSDs, the causal genes have been identified but, in some, the function of the implicated gene is unknown, in part because lysosomes occupy a small fraction of the cellular volume so that changes in lysosomal contents are difficult to detect. Here we develop the LysoTag mouse for the tissue-specific isolation of intact lysosomes that are compatible with the multimodal profiling of their contents. We used the LysoTag mouse to study CLN3, a lysosomal transmembrane protein with an unknown function. In children, the loss of CLN3 causes juvenile neuronal ceroid lipofuscinosis (Batten disease), a lethal neurodegenerative LSD. Untargeted metabolite profiling of lysosomes from the brains of mice lacking CLN3 revealed a massive accumulation of glycerophosphodiesters (GPDs)—the end products of glycerophospholipid catabolism. GPDs also accumulate in the lysosomes of CLN3-deficient cultured cells and we show that CLN3 is required for their lysosomal egress. Loss of CLN3 also disrupts glycerophospholipid catabolism in the lysosome. Finally, we found elevated levels of glycerophosphoinositol in the cerebrospinal fluid of patients with Batten disease, suggesting the potential use of glycerophosphoinositol as a disease biomarker. Our results show that CLN3 is required for the lysosomal clearance of GPDs and reveal Batten disease as a neurodegenerative LSD with a defect in glycerophospholipid metabolism. The lysosomal transmembrane protein CLN3 is required for the lysosomal clearance of glycerophosphodiesters in mice and in human cells, suggesting that the loss of CLN3 causes Batten disease in children due to defects in glycerophospholipid metabolism.

Background Although typically curative, treatment for pediatric acute lymphoblastic leukemia (ALL) is associated with neurotoxicity and leads to chemotherapy-related cognitive impairment (CRCI) in 40–70% of survivors. Cerebrospinal fluid (CSF), which is routinely collected during intrathecal chemotherapy, offers a direct window into brain metabolism. This study characterizes longitudinal metabolic changes in the CSF of pediatric patients undergoing chemotherapy for ALL. Methods CSF samples from 45 pediatric patients enrolled on the multi-institutional Dana-Farber Cancer Institute (DFCI) ALL Consortium Protocol 16–001 were collected at five standardized timepoints over the first 20 weeks of treatment and analyzed using untargeted metabolomics. Cognitive outcomes were assessed post-treatment using age-appropriate Wechsler Intelligence scales, with the Working Memory Index (WMI) serving as the primary cognitive measure. Patients with WMI scores at least one standard deviation above ( n  = 21) or below ( n  = 24) the mean were selected for metabolomic comparison. This study constitutes an exploratory aim of the 16–001 clinical trial. Results Our analysis revealed a profound reorganization of the CSF metabolome during the first 18 days of treatment, spanning the induction phase of chemotherapy and early leukemia remission. This shift was characterized by alterations in amino acid, phospholipid, and one-carbon metabolism. Moreover, we identified a lipid-rich metabolomic signature predictive of low post-treatment WMI, implicating metabolic dysregulation in CRCI susceptibility. Conclusions These findings highlight the dynamic impact of chemotherapy on the CSF metabolome and support its utility as a matrix for monitoring neurotoxicity during pediatric ALL therapy. CSF metabolomics may enable the early identification of patients at risk for CRCI through predictive biomarkers and guide future neuroprotective interventions. Trial registration: Dana-Farber Cancer Institute ALL Consortium Protocol 16–001, clinicaltrials.gov ID NCT03020030; study start date 03/03/2017.

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.

Insight into lipids’ roles in Alzheimer’s disease (AD) pathophysiology is limited because brain membrane lipids have not been characterized in cognitively healthy (CH) individuals. Since age is a significant risk factor of AD, we hypothesize that aging renders the amyloid precursor protein (APP) more susceptible to abnormal processing because of deteriorating membrane lipids. To reflect brain membranes, we studied their lipid components in cerebrospinal fluid (CSF) and brain-derived CSF nanoparticle membranes. Based on CSF Aβ 42 /Tau levels established biomarkers of AD, we define a subset of CH participants with normal Aβ 42 /Tau (CH-NAT) and another group with abnormal or pathological Aβ 42 /Tau (CH-PAT). We report that glycerophospholipids are differentially metabolized in the CSF supernatant fluid and nanoparticle membrane fractions from CH-NAT, CH-PAT, and AD participants. Phosphatidylcholine molecular species from the supernatant fraction of CH-PAT were higher than in the CH-NAT and AD participants. Sphingomyelin levels in the supernatant fraction were lower in the CH-PAT and AD than in the CH-NAT group. The decrease in sphingomyelin corresponded with an increase in ceramide and dihydroceramide and an increase in the ceramide to sphingomyelin ratio in AD. In contrast to the supernatant fraction, sphingomyelin is higher in the nanoparticle fraction from the CH-PAT group, accompanied by lower ceramide and dihydroceramide and a decrease in the ratio of ceramide to sphingomyelin in CH-PAT compared with CH-NAT. On investigating the mechanism for the lipid changes in AD, we observed that phospholipase A 2 (PLA 2 ) activity was higher in the AD group than the CH groups. Paradoxically, acid and neutral sphingomyelinase (SMase) activities were lower in AD compared to the CH groups. Considering external influences on lipids, the clinical groups did not differ in their fasting blood lipids or dietary lipids, consistent with the CSF lipid changes originating from brain pathophysiology. The lipid accumulation in a prodromal AD biomarker positive stage identifies perturbation of lipid metabolism and disturbances in APP/Amyloid beta (Aβ) as early events in AD pathophysiology. Our results identify increased lipid turnover in CH participants with AD biomarkers, switching to a predominantly lipolytic state in dementia. This knowledge may be useful for targeting and testing new AD treatments.

Multiple sclerosis (MS) is a neurodegenerative inflammatory disease where an autoimmune response to components of the central nervous system leads to a loss of myelin and subsequent neurological deterioration. People with MS can develop primary or secondary progressive disease (PPMS, SPMS) and differentiation of the specific differences in the pathogenesis of these two courses, at the molecular level, is currently unclear. Recently, lipidomics studies using human biofluids, mainly plasma and cerebrospinal fluid, have highlighted a possible role for lipids in the initiation and progression of MS. However, there is a lack of lipidomics studies in MS on CNS tissues, such as normal-appearing white matter (NAWM), where local inflammation initially occurs. Herein, we developed an untargeted reverse phase ultra-performance liquid chromatography time of flight tandem mass spectrometry (RP-UPLC-TOF MSE)-based workflow, in combination with multivariate and univariate statistical analysis, to assess significant differences in lipid profiles in brain NAWM from post-mortem cases of PPMS, SPMS and controls. Groups of eight control, nine PPMS and seven SPMS NAWM samples were used. Correlation analysis of the identified lipids by RP-UPLC-TOF MSE was undertaken to remove those lipids that correlated with age, gender and post-mortem interval as confounding factors. We demonstrate that there is a significantly altered lipid profile of control cases compared with MS cases and that progressive disease, PPMS and SPMS, can be differentiated on the basis of the lipidome of NAWM with good sensitivity, specificity and prediction accuracy based on receiver operating characteristic (ROC) curve analysis. Metabolic pathway analysis revealed that the most altered lipid pathways between PPMS and SPMS were glycerophospholipid metabolism, glycerophosphatidyl inositol (GPI) anchor synthesis and linoleic acid metabolism. Further understanding of the impact of these lipid alterations described herein associated with progression will provide an increased understanding of the mechanisms underpinning progression and highlight possible new therapeutic targets.

Introduction Cerebrospinal fluid (CSF) total tau (t‐tau) and phosphorylated tau (p‐tau) are biomarkers of Alzheimer's disease (AD), yet much is unknown about AD‐associated changes in tau metabolism and tau tangle etiology. Methods We assessed the variation of t‐tau and p‐tau explained by 38 previously identified CSF metabolites using linear regression models in middle‐age controls from the Wisconsin Alzheimer's Disease Research Center, and predicted AD/mild cognitive impairment (MCI) versus an independent set of older controls using metabolites selected by the least absolute shrinkage and selection operator (LASSO). Results The 38 CSF metabolites explained 70.3% and 75.7% of the variance in t‐tau and p‐tau, respectively. Of these, seven LASSO‐selected metabolites improved the prediction ability of AD/MCI versus older controls (area under the curve score increased from 0.92 to 0.97 and 0.78 to 0.93) compared to the base model. Discussion These tau‐correlated CSF metabolites increase AD/MCI prediction accuracy and may provide insight into tau tangle etiology.

A sensitive and accurate reversed-phase liquid chromatography coupled with electrospray ionization mass spectrometry (LC-ESIMS) method for determining glycerophospholipids and a sphingolipid was developed and validated in order to profile and quantify the classes of lipids in the cerebrospinal fluids of patient with three different illnesses. The LC-ESI-MS method was optimized for the analysis, and an Inertsil 6 ODS-3 (4.6 x 150 mm) column was utilized with a mobile phase composed of acetonitrile/methanol/triethylamine in the ratio 550/1000/25 (w/w/w) eluted isocratically at a flow rate of 1.0 mL/min. The results demonstrated that both the accuracy and precision of the intra- and inter-day assays of phosphatidylcholine (PC). phosphatidylethanolamine (PE), phosphatidylinositol ( PI), phosphatidylserine (PS) and sphingomyelin (SM) were within acceptable criteria. Clinical application demonstrated that the percentage and content of each class differed in the cerebrospinal f1uids of patients with three different