Interleukin-3 coordinates glial-peripheral immune crosstalk to incite multiple sclerosis.

Glial cells and central nervous system (CNS)-infiltrating leukocytes contribute to multiple sclerosis (MS). However, the networks that govern crosstalk among these ontologically distinct populations remain unclear. Here, we show that, in mice and humans, CNS-resident astrocytes and infiltrating CD44hiCD4+ T cells generated interleukin-3 (IL-3), while microglia and recruited myeloid cells expressed interleukin-3 receptor-ɑ (IL-3Rɑ). Astrocytic and T cell IL-3 elicited an immune migratory and chemotactic program by IL-3Rɑ+ myeloid cells that enhanced CNS immune cell infiltration, exacerbating MS and its preclinical model. Multiregional snRNA-seq of human CNS tissue revealed the appearance of IL3RA-expressing myeloid cells with chemotactic programming in MS plaques. IL3RA expression by plaque myeloid cells and IL-3 amount in the cerebrospinal fluid predicted myeloid and T cell abundance in the CNS and correlated with MS severity. Our findings establish IL-3:IL-3RA as a glial-peripheral immune network that prompts immune cell recruitment to the CNS and worsens MS.

Modifying the maternal microbiota alters the gut-brain metabolome and prevents emotional dysfunction in the adult offspring of obese dams.

Maternal obesity disturbs brain-gut-microbiota interactions and induces negative affect in the offspring, but its impact on gut and brain metabolism in the offspring (F1) are unknown. Here, we tested whether perinatal intake of a multispecies probiotic could mitigate the abnormal emotional behavior in the juvenile and adult offspring of obese dams. Untargeted NMR-based metabolomic profiling and gene-expression analysis throughout the gut-brain axis were then used to investigate the biology underpinning behavioral changes in the dams and their offspring. Prolonged high-fat diet feeding reduced maternal gut short-chain fatty acid abundance, increased markers of peripheral inflammation, and decreased the abundance of neuroactive metabolites in maternal milk during nursing. Both juvenile (postnatal day [PND] 21) and adult (PND112) offspring of obese dams exhibited increased anxiety-like behavior, which were prevented by perinatal probiotic exposure. Maternal probiotic treatment increased gut butyrate and brain lactate in the juvenile and adult offspring and increased the expression of prefrontal cortex PFKFB3, a marker of glycolytic metabolism in astrocytes. PFKFB3 expression correlated with the increase in gut butyrate in the juvenile and adult offspring. Maternal obesity reduced synaptophysin expression in the adult offspring, while perinatal probiotic exposure increased expression of brain-derived neurotrophic factor. Finally, we showed that the resilience of juvenile and adult offspring to anxiety-like behavior was most prominently associated with increased brain lactate abundance, independent of maternal group. Taken together, we show that maternal probiotic supplementation exerts a long-lasting effect on offspring neuroplasticity and the offspring gut-liver-brain metabolome, increasing resilience to emotional dysfunction induced by maternal obesity.

Ex-Vivo 13C NMR Spectroscopy of Rodent Brain: TNF Restricts Neuronal Utilization of Astrocyte-Derived Metabolites.

Tumor necrosis factor (TNF) has well-established roles in neuroinflammatory disorders, but the effect of TNF on the biochemistry of brain cells remains poorly understood. Here, we microinjected TNF into the brain to study its impact on glial and neuronal metabolism (glycolysis, pentose phosphate pathway, citric acid cycle, pyruvate dehydrogenase, and pyruvate carboxylase pathways) using 13C NMR spectroscopy on brain extracts following intravenous [1,2-13C]-glucose (to probe glia and neuron metabolism), [2-13C]-acetate (probing astrocyte-specific metabolites), or [3-13C]-lactate. An increase in [4,5-13C]-glutamine and [2,3-13C]-lactate coupled with a decrease in [4,5-13C]-glutamate was observed in the [1,2-13C]-glucose-infused animals treated with TNF. As glutamine is produced from glutamate by astrocyte-specific glutamine synthetase the increase in [4,5-13C]-glutamine reflects increased production of glutamine by astrocytes. This was confirmed by infusion with astrocyte substrate [2-13C]-acetate. As lactate is metabolized in the brain to produce glutamate, the simultaneous increase in [2,3-13C]-lactate and decrease in [4,5-13C]-glutamate suggests decreased lactate utilization, which was confirmed using [3-13C]-lactate as a metabolic precursor. These results suggest that TNF rearranges the metabolic network, disrupting the energy supply chain perturbing the glutamine-glutamate shuttle between astrocytes and the neurons. These insights pave the way for developing astrocyte-targeted therapeutic strategies aimed at modulating effects of TNF to restore metabolic homeostasis in neuroinflammatory disorders.

The serum metabolomic profile of a distinct, inflammatory subtype of acute psychosis.

A range of studies suggest that a proportion of psychosis may have an autoimmune basis, but this has not translated through into clinical practice-there is no biochemical test able to accurately identify psychosis resulting from an underlying inflammatory cause. Such a test would be an important step towards identifying who might require different treatments and have the potential to improve outcomes for patients. To identify novel subgroups within patients with acute psychosis we measured the serum nuclear magnetic resonance (NMR) metabolite profiles of 75 patients who had identified antibodies (anti-glycine receptor [GlyR], voltage-gated potassium channel [VGKC], Contactin-associated protein-like 2 [CASPR2], leucine-rich glioma inactivated 1 [LGI1], N-methyl-D-aspartate receptor [NMDAR] antibody) and 70 antibody negative patients matched for age, gender, and ethnicity. Clinical symptoms were assessed using the positive and negative syndrome scale (PANSS). Unsupervised principal component analysis identified two distinct biochemical signatures within the cohort. Orthogonal partial least squared discriminatory analysis revealed that the serum metabolomes of NMDAR, LGI1, and CASPR2 antibody psychosis patients were indistinct from the antibody negative control group while VGKC and GlyR antibody patients had significantly decreased lipoprotein fatty acids and increased amino acid concentrations. Furthermore, these patients had more severe presentation with higher PANSS scores than either the antibody negative controls or the NMDAR, LGI1, and CASPR2 antibody groups. These results suggest that a proportion of patients with acute psychosis have a distinct clinical and biochemical phenotype that may indicate an inflammatory subtype.

HDL and LDL have distinct, opposing effects on LPS-induced brain inflammation.

Endotoxemia and sepsis induce neuroinflammation and increase the risk of neurodegenerative disorders although the mechanism by which peripheral infection leads to brain inflammation is not well understood. While circulating serum lipoproteins are known immunometabolites with the potential to modulate the acute phase response and cross the blood brain barrier, their contribution to neuroinflammation during systemic infection is unknown. The objective of this study was to elucidate the mechanisms by which lipoprotein subclasses modulate lipopolysaccharide (LPS)-induced neuroinflammation. Adult C57BL/6 mice were divided into 6 treatment groups, including a sterile saline vehicle control group (n = 9), an LPS group (n = 11), a premixed LPS + HDL group (n = 6), a premixed LPS + LDL group (n = 5), a HDL only group (n = 6) and an LDL only group (n = 3). In all cases injections were administered intraperitoneally. LPS was administered at 0.5 mg/kg, and lipoproteins were administered at 20 mg/kg. Behavioural testing and tissue collection was performed 6 h post-injection. The magnitude of peripheral and central inflammation was determined by qPCR of pro-inflammatory genes in fresh liver and brain. Metabolite profiles of liver, plasma and brain were determined by 1H NMR. Endotoxin concentration in the brain was measured by the Limulus Amoebocyte Lysate (LAL) assay. Co-administration of LPS + HDL exacerbated both peripheral and central inflammation, whilst LPS + LDL attenuated this inflammation. Metabolomic analysis identified several metabolites significantly associated with LPS-induced inflammation, which were partially rescued by LDL, but not HDL. Endotoxin was detected at significantly greater concentrations in the brains of animals that received LPS + HDL compared to LPS + saline, but not those that received LPS + LDL. These results suggest that HDL may promote neuroinflammation through direct shuttling of endotoxin to the brain. In contrast, LDL was shown to have anti-neuroinflammatory properties in this study. Our results indicate that lipoproteins may be useful targets in neuroinflammation and neurodegeneration associated with endotoxemia and sepsis.

Metabolomics detects clinically silent neuroinflammatory lesions earlier than neurofilament-light chain in a focal multiple sclerosis animal model.

BACKGROUND: Despite widespread searches, there are currently no validated biofluid markers for the detection of subclinical neuroinflammation in multiple sclerosis (MS). The dynamic nature of human metabolism in response to changes in homeostasis, as measured by metabolomics, may allow early identification of clinically silent neuroinflammation. Using the delayed-type hypersensitivity (DTH) MS rat model, we investigated the serum and cerebrospinal fluid (CSF) metabolomics profiles and neurofilament-light chain (NfL) levels, as a putative marker of neuroaxonal damage, arising from focal, clinically silent neuroinflammatory brain lesions and their discriminatory abilities to distinguish DTH animals from controls. METHODS: 1H nuclear magnetic resonance (NMR) spectroscopy metabolomics and NfL measurements were performed on serum and CSF at days 12, 28 and 60 after DTH lesion initiation. Supervised multivariate analyses were used to determine metabolomics differences between DTH animals and controls. Immunohistochemistry was used to assess the extent of neuroinflammation and tissue damage. RESULTS: Serum and CSF metabolomics perturbations were detectable in DTH animals (vs. controls) at all time points, with the greatest change occurring at the earliest time point (day 12) when the neuroinflammatory response was most intense (mean predictive accuracy [SD]-serum: 80.6 [10.7]%, p < 0.0001; CSF: 69.3 [13.5]%, p < 0.0001). The top discriminatory metabolites at day 12 (serum: allantoin, cytidine; CSF: glutamine, glucose) were all reduced in DTH animals compared to controls, and correlated with histological markers of neuroinflammation, particularly astrogliosis (Pearson coefficient, r-allantoin: r = - 0.562, p = 0.004; glutamine: r = - 0.528, p = 0.008). Serum and CSF NfL levels did not distinguish DTH animals from controls at day 12, rather, significant differences were observed at day 28 (mean [SEM]-serum: 38.5 [4.8] vs. 17.4 [2.6] pg/mL, p = 0.002; CSF: 1312.0 [379.1] vs. 475.8 [74.7] pg/mL, p = 0.027). Neither serum nor CSF NfL levels correlated with markers of neuroinflammation; serum NfL did, however, correlate strongly with axonal loss (r = 0.641, p = 0.001), but CSF NfL did not (p = 0.137). CONCLUSIONS: While NfL levels were elevated later in the pathogenesis of the DTH lesion, serum and CSF metabolomics were able to detect early, clinically silent neuroinflammation and are likely to present sensitive biomarkers for the assessment of subclinical disease activity in patients.

A novel serum metabolomic panel distinguishes IgG4-related sclerosing cholangitis from primary sclerosing cholangitis.

BACKGROUND & AIMS: Primary sclerosing cholangitis (PSC) and IgG4-related sclerosing cholangitis (IgG4-SC) are chronic fibro-inflammatory immune-mediated hepatobiliary conditions that are challenging to distinguish in a clinical setting. Accurate non-invasive biomarkers for discriminating PSC and IgG4-SC are important to ensure a correct diagnosis, prompt therapy and adequate cancer surveillance. METHODS: We performed nuclear magnetic resonance (NMR)-based metabolomic profiling using serum samples collected prospectively from patients with PSC (n = 100), IgG4-SC (n = 23) and healthy controls (HC; n = 16). RESULTS: Multivariate analysis of the serum metabolome discriminated PSC from IgG4-SC with greater accuracy (AUC 0.95 [95%CI 0.90-0.98]) than IgG4 titre (AUC 0.87 [95%CI 0.79-0.94]). When inflammatory bowel disease (IBD) was excluded as a comorbid condition (IgG4-SC n = 20, PSC n = 22), the diagnostic AUC increased to 1.0, suggesting that the metabolome differences identified are not a result of the increased prevalence of IBD in PSC relative to IgG4-SC patients. Serum lactate (p < .0001), glucose (p < .01) and glutamine (p < .01) metabolites were increased in IgG4-related disease (IgG4-RD) and IgG4-SC individuals compared to PSC, whereas mobile choline (p < .05), 3-hydroxybutyric acid (p < .01) and -CH3 lipoprotein resonances (p < .01) were decreased. CONCLUSIONS: Taken together, serum metabolomic profiling has the potential to be incorporated as a diagnostic criterion, independent of IgG4 titre, to improve the diagnosis of IgG4-RD and help distinguish IgG4-SC from PSC.

Mom's diet matters: Maternal prebiotic intake in mice reduces anxiety and alters brain gene expression and the fecal microbiome in offspring.

Compelling evidence links enteric microbes to brain function and behavior. Galacto-oligosaccharide prebiotics have been shown to modulate the composition of gut flora and induce metabolic, neurochemical, and behavioral changes in adult rodents. Despite the brain being most susceptible to environmental factors, such as nutrients and toxins, during the earliest stages of development, it is unknown whether maternal prebiotic supplementation during gestation and lactation influences the offspring gut microbiome, brain, or behavior. The aim of this study was to test whether maternal galacto-oligosaccharide intake during pregnancy and lactation alters the brain and behavior in naïve and endotoxin-challenged offspring. CD1 female mice received either normal drinking water or water supplemented with Bimuno® galacto-oligosaccharides (B-GOS) during gestation and suckling. Offspring behavior was tested at weaning age or adulthood, and a cross-foster design was employed in a separate cohort to differentiate between effects of prenatal and postnatal maternal B-GOS intake. Lipopolysaccharide was also administered to pups at postnatal day 9 to determine whether maternal B-GOS influences the neurobiological and behavioral effects of a neonatal pro-inflammatory challenge in adulthood. Fecal microbiome composition and metabolites were analyzed to explore potential relationships between the maternal microbiome, the offspring gut microbiome, and the offspring brain and behavior. Maternal B-GOS supplementation increased exploratory behavior and reduced expression of hippocampal glutamate receptor genes in young, weaning-age offspring. In addition, postnatal, but not prenatal, B-GOS supplementation increased fecal butyrate and propionate levels. Finally, in adult offspring, perinatal B-GOS intake increased cortical glutamate receptor subunits in females, increased social preference, and reduced anxiety. We provide novel and comprehensive evidence for the influence of maternal prebiotic intake on offspring behavior, brain gene expression, and gut microbiome composition in mice.

Foveal changes in aquaporin-4 antibody seropositive neuromyelitis optica spectrum disorder are independent of optic neuritis and not overtly progressive.

BACKGROUND AND PURPOSE: Foveal changes were reported in aquaporin-4 antibody (AQP4-Ab) seropositive neuromyelitis optica spectrum disorder (NMOSD) patients; however, it is unclear whether they are independent of optic neuritis (ON), stem from subclinical ON or crossover from ON in fellow eyes. Fovea morphometry and a statistical classification approach were used to investigate if foveal changes in NMOSD are independent of ON and progressive. METHODS: This was a retrospective longitudinal study of 27 AQP4-IgG + NMOSD patients (49 eyes; 15 ON eyes and 34 eyes without a history of ON [NON eyes]), follow-up median (first and third quartile) 2.32 (1.33-3.28), and 38 healthy controls (HCs) (76 eyes), follow-up median (first and third quartile) 1.95 (1.83-2.54). The peripapillary retinal nerve fibre layer thickness and the volume of combined ganglion cell and inner plexiform layer as measures of neuroaxonal damage from ON were determined by optical coherence tomography. Nineteen foveal morphometry parameters were extracted from macular optical coherence tomography volume scans. Data were analysed using orthogonal partial least squares discriminant analysis and linear mixed effects models. RESULTS: At baseline, foveal shape was significantly altered in ON eyes and NON eyes compared to HCs. Discriminatory analysis showed 81% accuracy distinguishing ON vs. HCs and 68% accuracy in NON vs. HCs. NON eyes were distinguished from HCs by foveal shape parameters indicating widening. Orthogonal partial least squares discriminant analysis discriminated ON vs. NON with 76% accuracy. In a follow-up of 2.4 (20.85) years, no significant time-dependent foveal changes were found. CONCLUSION: The parafoveal area is altered in AQP4-Ab seropositive NMOSD patients suggesting independent neuroaxonal damage from subclinical ON. Longer follow-ups are needed to confirm the stability of the parafoveal structure over time.

Reliable, high-quality suppression of NMR signals arising from water and macromolecules: application to bio-fluid analysis.

Analysis of metabolites in biofluids using nuclear magnetic resonance often requires the suppression of obscuring signals arising from water and macromolecules. This paper analyses the limitations of the pulse sequence most commonly used to achieve such suppression (presat-CPMG) and proposes new pulse sequences that do not share those limitations. The utility of these improved pulse sequences is demonstrated in a metabolomic study of multiple sclerosis (MS) patients.

Distinct brain imaging characteristics of autoantibody-mediated CNS conditions and multiple sclerosis.

Brain imaging characteristics of MOG antibody disease are largely unknown and it is unclear whether they differ from those of multiple sclerosis and AQP4 antibody disease. The aim of this study was to identify brain imaging discriminators between those three inflammatory central nervous system diseases in adults and children to support diagnostic decisions, drive antibody testing and generate disease mechanism hypotheses. Clinical brain scans of 83 patients with brain lesions (67 in the training and 16 in the validation cohort, 65 adults and 18 children) with MOG antibody (n = 26), AQP4 antibody disease (n = 26) and multiple sclerosis (n = 31) recruited from Oxford neuromyelitis optica and multiple sclerosis clinical services were retrospectively and anonymously scored on a set of 29 predefined magnetic resonance imaging features by two independent raters. Principal component analysis was used to perform an overview of patients without a priori knowledge of the diagnosis. Orthogonal partial least squares discriminant analysis was used to build models separating diagnostic groups and identify best classifiers, which were then tested on an independent cohort set. Adults and children with MOG antibody disease frequently had fluffy brainstem lesions, often located in pons and/or adjacent to fourth ventricle. Children across all conditions showed more frequent bilateral, large, brainstem and deep grey matter lesions. MOG antibody disease spontaneously separated from multiple sclerosis but overlapped with AQP4 antibody disease. Multiple sclerosis was discriminated from MOG antibody disease and from AQP4 antibody disease with high predictive values, while MOG antibody disease could not be accurately discriminated from AQP4 antibody disease. Best classifiers between MOG antibody disease and multiple sclerosis were similar in adults and children, and included ovoid lesions adjacent to the body of lateral ventricles, Dawson's fingers, T1 hypointense lesions (multiple sclerosis), fluffy lesions and three lesions or less (MOG antibody). In the validation cohort patients with antibody-mediated conditions were differentiated from multiple sclerosis with high accuracy. Both antibody-mediated conditions can be clearly separated from multiple sclerosis on conventional brain imaging, both in adults and children. The overlap between MOG antibody oligodendrocytopathy and AQP4 antibody astrocytopathy suggests that the primary immune target is not the main substrate for brain lesion characteristics. This is also supported by the clear distinction between multiple sclerosis and MOG antibody disease both considered primary demyelinating conditions. We identify discriminatory features, which may be useful in classifying atypical multiple sclerosis, seronegative neuromyelitis optica spectrum disorders and relapsing acute disseminated encephalomyelitis, and characterizing cohorts for antibody discovery.

1H NMR-Linked Metabolomics Analysis of Liver from a Mouse Model of NP-C1 Disease.

Clinical manifestations of Niemann-Pick type C1 (NP-C1) disease include neonatal hepatosplenomegaly and in some patients progressive liver dysfunction and failure. This study involved a 1H NMR-linked metabolomics analysis of liver samples collected from a NP-C1 disease mutant mouse model in order to explore time-dependent imbalances in metabolic pathways associated with NP-C1 liver dysfunction, including fibrosis. NP-C1 mutant (Npc1-/-; NP-C1), control (Npc1+/+; WT), and NP-C1 heterozygous mice (Npc1+/-; HET) were generated from heterozygote matings. Aqueous extracts of these liver samples collected at time points of 3, 6, 9, and 11 weeks were subjected to high-resolution NMR analysis, and multivariate (MV) metabolomics analyses of data sets acquired were performed. A MV random forests (RFs) model effectively discriminated between NP-C1 and a combined WT/HET hepatic NMR profiles with very high predictive accuracy and reliability. Key distinguishing features included significant upregulations in the hepatic concentrations of phenylalanine, tyrosine, glutamate, lysine/ornithine, valine, threonine, and hypotaurine/methionine, and diminished levels of nicotinate/niacinamide, inosine, phosphoenolpyruvate, and 3-hydroxyphenylacetate. Quantitative pathway topological analysis confirmed that imbalances in tyrosine biosynthesis, and hepatic phenylalanine, tyrosine, glutamate/glutamine, and nicotinate/niacinamide metabolism were involved in the pathogenesis of NP-C1 disease-associated liver dysfunction/damage. 1H NMR-linked metabolomics analysis provides valuable biomarker information regarding hepatic dysfunction or damage in NP-C1 disease.

¹H NMR metabolic profiling of plasma reveals additional phenotypes in knockout mouse models.

The International Mouse Phenotyping Consortium program has been established to ascribe biological functions to systematically knocked-out (KO) genes by in vivo and ex vivo phenotyping. The plasma clinical chemistry screen includes an assessment of liver, kidney, and bone function and provides a basic lipid profile and histopathology reports on 32 tissues. We report on the inclusion of plasma analysis by proton nuclear magnetic resonance ((1)H NMR) spectroscopy. (1)H NMR spectroscopy data are summarized from 116 running baseline controls with 18 homozygous and 2 heterozygous KO mouse lines along with wild-type controls (typically n = 7 per gender). For the baseline group, the intersample variation of (1)H NMR glucose measurement was 12%, and the (1)H NMR spectroscopy data were influenced by gender and feeding status. There were good correlations between the clinical chemistry and the (1)H NMR spectroscopy measurements for glucose, triglycerides, and HDL cholesterol. Significant differences were observed in two KO lines, Agl (MGI: 1924809) and Bbs5 (MGI: 1919819), by (1)H NMR spectroscopy, clinical chemistry, and histopathology. In a further two KO lines, Elmod1 (MGI: 3583900) and Emc10 (MGI: 1916933), (1)H NMR metabolic differences were observed, but no other ex vivo changes were detected. In the remaining 16 lines, no ex vivo abnormal phenotypes were observed. Plasma (1)H NMR spectroscopy can therefore provide a novel perspective on the function of knocked-out genes.

Solution NMR analyses of the C-type carbohydrate recognition domain of DC-SIGNR protein reveal different binding modes for HIV-derived oligosaccharides and smaller glycan fragments.

The C-type lectin DC-SIGNR (dendritic cell-specific ICAM-3-grabbing non-integrin-related; also known as L-SIGN or CD299) is a promising drug target due to its ability to promote infection and/or within-host survival of several dangerous pathogens (e.g. HIV and severe acute respiratory syndrome coronavirus (SARS)) via interactions with their surface glycans. Crystallography has provided excellent insight into the mechanism by which DC-SIGNR interacts with small glycans, such as (GlcNAc)2Man3; however, direct observation of complexes with larger, physiological oligosaccharides, such as Man9GlcNAc2, remains elusive. We have utilized solution-state nuclear magnetic resonance spectroscopy to investigate DC-SIGNR binding and herein report the first backbone assignment of its active, calcium-bound carbohydrate recognition domain. Direct interactions with the small sugar fragments Man3, Man5, and (GlcNAc)2Man3 were investigated alongside Man9GlcNAc derived from recombinant gp120 (present on the HIV viral envelope), providing the first structural data for DC-SIGNR in complex with a virus-associated ligand, and unique binding modes were observed for each glycan. In particular, our data show that DC-SIGNR has a different binding mode for glycans on the HIV viral envelope compared with the smaller glycans previously observed in the crystalline state. This suggests that using the binding mode of Man9GlcNAc, instead of those of small glycans, may provide a platform for the design of DC-SIGNR inhibitors selective for high mannose glycans (like those on HIV). (15)N relaxation measurements provided the first information on the dynamics of the carbohydrate recognition domain, demonstrating that it is a highly flexible domain that undergoes ligand-induced conformational and dynamic changes that may explain the ability of DC-SIGNR to accommodate a range of glycans on viral surfaces.

New analytical methods focusing on polar metabolite analysis in mass spectrometry and NMR-based metabolomics.

Following in the footsteps of genomics and proteomics, metabolomics has revolutionised the way we investigate and understand biological systems. Rapid development in the last 25 years has been driven largely by technical innovations in mass spectrometry and nuclear magnetic resonance spectroscopy. However, despite the modest size of metabolomes relative to proteomes and genomes, methodological capabilities for robust, comprehensive metabolite analysis remain a major challenge. Therefore, development of new methods and techniques remains vital for progress in the field. Here, we review developments in LC-MS, GC-MS and NMR methods in the last few years that have enhanced quantitative and comprehensive metabolome coverage, highlighting the techniques involved, their technical capabilities, relative performance, and potential impact.

Unique pathways downstream of TLR-4 and TLR-7 activation: sex-dependent behavioural, cytokine, and metabolic consequences.

Introduction: Post-infection syndromes are characterised by fatigue, muscle pain, anhedonia, and cognitive impairment; mechanistic studies exploring these syndromes have focussed on pathways downstream of Toll-like receptor (TLR) 4 activation. Here, we investigated the mechanistic interplay between behaviour, metabolism, and inflammation downstream of TLR-7 activation compared to TLR-4 activation in male and female CD1 mice. Methods: Animals received either a TLR-4 (LPS; 0.83 mg/kg) or TLR-7 (R848, 5 mg/kg) agonist, or saline, and behaviour was analysed in an Open Field (OF) at 24 h (n = 20/group). Plasma, liver, and prefrontal cortex (PFC) were collected for gene expression analysis at 24 h and 1H-NMR metabolomics. Results: TLR-4 and TLR-7 activation decreased distance travelled and rearing in the OF, but activation of each receptor induced distinct cytokine responses and metabolome profiles. LPS increased IL-1ß expression and CXCL1 in the PFC, but TLR7 activation did not and strongly induced PFC CXCL10 expression. Thus, TLR7 induced sickness behaviour is independent of IL-1ß expression. In both cases, the behavioural response to TLR activation was sexually dimorphic: females were more resilient. However, dissociation was observed between the resilient female mice behaviour and the levels of gene cytokine expression, which was, in general, higher in the female mice. However, the metabolic shifts induced by immune activation were better correlated with the sex-dependent behavioural dimorphisms; increased levels of antioxidant potential in the female brain are intrinsic male/female metabolome differences. A common feature of both TLR4 and TLR7 activation was an increase in N-acetyl aspartate (NAA) in the PFC, which is likely be an allostatic response to the challenges as sickness behaviour is inversely correlated with NAA levels. Discussion: The results highlight how the cytokine profile induced by one PAMP cannot be extrapolated to another, but they do reveal how the manipulation of the conserved metabolome response might afford a more generic approach to the treatment of post-infection syndromes.

Plasma H3Cit-DNA Discriminates Between Cancer and Inflammation in a Cohort of Patients with Unspecific Cancer Symptoms.

Cancer detection is challenging, especially in patients with unspecific cancer symptoms. Biomarkers could identify patients at high risk of cancer. Prior studies indicate that neutrophil extracellular traps (NETs) are associated with cancer, but also with autoimmune and infectious diseases. The objective of this prospective study was to investigate markers associated with NET formation (nucleosomal citrullinated histone 3 [H3Cit-DNA], cell free DNA [cfDNA] and neutrophil elastase [NE]), and c-reactive protein (CRP) in patients with unspecific cancer symptoms, such as fatigue, weight loss or radiological sign of malignancy without an apparent primary tumor, referred to the Diagnostic Center at Danderyd Hospital in Sweden. Blood samples were drawn on admission, before cancer diagnosis. Out of 475 patients, 160 (34%) were diagnosed with cancer, 56 (12%) with autoimmune disease, 32 (7%) with infectious disease, 71 (15%) with other diseases and 156 (33%) received no diagnosis. H3Cit-DNA, cfDNA, NE and CRP were significantly higher in patients with cancer compared to patients without cancer (p < 0.0001, p < 0.0001, p = 0.004, and p = 0.0002 respectively). H3Cit-DNA, but not cfDNA, NE or CRP, was significantly elevated in patients with cancer compared to patients with autoimmune disease (p = 0.0001). H3Cit-DNA, cfDNA, NE or CRP did not differ between cancer and infectious disease. In conclusion, H3Cit-DNA is elevated in patients diagnosed with cancer compared to non-cancer patients with the same symptomatology. Further studies should evaluate if H3Cit-DNA could aid in selecting patients that would benefit the most from a rapid cancer diagnostic work-up.

A multivariate blood metabolite algorithm stably predicts risk and resilience to major depressive disorder in the general population.

BACKGROUND: Socioeconomic pressures, sex, and physical health status strongly influence the development of major depressive disorder (MDD) and mask other contributing factors in small cohorts. Resilient individuals overcome adversity without the onset of psychological symptoms, but resilience, as for susceptibility, has a complex and multifaceted molecular basis. The scale and depth of the UK Biobank affords an opportunity to identify resilience biomarkers in rigorously matched, at-risk individuals. Here, we evaluated whether blood metabolites could prospectively classify and indicate a biological basis for susceptibility or resilience to MDD. METHODS: Using the UK Biobank, we employed random forests, a supervised, interpretable machine learning statistical method to determine the relative importance of sociodemographic, psychosocial, anthropometric, and physiological factors that govern the risk of prospective MDD onset (total n = 15,710). We then used propensity scores to rigorously match individuals with a history of MDD (n = 491) against a resilient subset of individuals without an MDD diagnosis (retrospectively or during follow-up; n = 491) using an array of key social, demographic, and disease-associated drivers of depression risk. 381 blood metabolites and clinical chemistry variables and 4 urine metabolites were integrated to generate a multivariate random forest-based algorithm using 10-fold cross-validation to predict prospective MDD risk and resilience. OUTCOMES: In unmatched individuals, a first case of MDD, with a median time-to-diagnosis of 72 years, can be predicted using random forest classification probabilities with an area under the receiver operator characteristic curve (ROC AUC) of 0.89. Prospective resilience/susceptibility to MDD was then predicted with a ROC AUC of 0.72 (x˜ = 3.2 years follow-up) and 0.68 (x˜ = 7.2 years follow-up). Increased pyruvate was identified as a key biomarker of resilience to MDD and was validated retrospectively in the TwinsUK cohort. INTERPRETATION: Blood metabolites prospectively associate with substantially reduced MDD risk. Therapeutic targeting of these metabolites may provide a framework for MDD risk stratification and reduction. FUNDING: New York Academy of Sciences' Interstellar Programme Award; Novo Fonden; Lincoln Kingsgate award; Clarendon Fund; Newton-Abraham studentship (University of Oxford). The funders had no role in the development of the present study.

Factors predicting the transition from acute to persistent pain in people with 'sciatica': the FORECAST longitudinal prognostic factor cohort study protocol.

INTRODUCTION: Sciatica is a common condition and is associated with higher levels of pain, disability, poorer quality of life, and increased use of health resources compared with low back pain alone. Although many patients recover, a third develop persistent sciatica symptoms. It remains unclear, why some patients develop persistent sciatica as none of the traditionally considered clinical parameters (eg, symptom severity, routine MRI) are consistent prognostic factors.The FORECAST study (factors predicting the transition from acute to persistent pain in people with 'sciatica') will take a different approach by exploring mechanism-based subgroups in patients with sciatica and investigate whether a mechanism-based approach can identify factors that predict pain persistence in patients with sciatica. METHODS AND ANALYSIS: We will perform a prospective longitudinal cohort study including 180 people with acute/subacute sciatica. N=168 healthy participants will provide normative data. A detailed set of variables will be assessed within 3 months after sciatica onset. This will include self-reported sensory and psychosocial profiles, quantitative sensory testing, blood inflammatory markers and advanced neuroimaging. We will determine outcome with the Sciatica Bothersomeness Index and a Numerical Pain Rating Scale for leg pain severity at 3 and 12 months.We will use principal component analysis followed by clustering methods to identify subgroups. Univariate associations and machine learning methods optimised for high dimensional small data sets will be used to identify the most powerful predictors and model selection/accuracy.The results will provide crucial information about the pathophysiological drivers of sciatica symptoms and may identify prognostic factors of pain persistence. ETHICS AND DISSEMINATION: The FORECAST study has received ethical approval (South Central Oxford C, 18/SC/0263). The dissemination strategy will be guided by our patient and public engagement activities and will include peer-reviewed publications, conference presentations, social media and podcasts. TRIAL REGISTRATION NUMBER: ISRCTN18170726; Pre-results.

Depressive symptoms in non-alcoholic fatty liver disease are identified by perturbed lipid and lipoprotein metabolism.

Non-alcoholic fatty liver disease (NAFLD) and depression are common disorders and have bidirectional contributing relationships to metabolic syndrome. We aimed to determine whether a fasting serum signature of recent, self-reported depressive symptoms could be identified in a heterogeneous NAFLD cohort using nuclear magnetic resonance (NMR)-based metabolomics integrated with clinical chemistry. Serum nuclear magnetic resonance (NMR) metabolite profiles and corresponding clinical chemistry were compared between patients with depressive symptoms in the last 12-months (n = 81) and patients without recent depressive symptoms (n = 137 controls) using multivariate statistics. Orthogonal partial least squares discriminant analysis (OPLS-DA) of the biochemical and metabolomic data identified NAFLD patients with recent depression with a cross-validated accuracy of 61.5%, independent of age, sex, medication, and other comorbidities. This led to the development of a diagnostic algorithm with AUC 0.83 for future testing in larger clinical cohorts. Serum triglycerides, VLDL cholesterol, and the inflammatory biomarker GlycA were key metabolites increased in patients with recent depressive symptoms, while serum glutamine level was reduced. Here, serum NMR metabolite analysis provides a link between disturbed lipid metabolism, inflammation, and active mental health issues in NAFLD, irrespective of disease severity.