Sphingomyelin SM(d18:1/18:0) is significantly enhanced in cerebrospinal fluid samples dichotomized by pathological amyloid-β42, tau, and phospho-tau-181 levels

Ldlr-/- and ApoE-/- mice better mimic the human metabolite signature of increased carotid intima media thickness compared to other animal models of cardiovascular disease

BACKGROUND AND AIMS

Preclinical experiments on animal models are essential to understand the mechanisms of cardiovascular disease (CVD). Metabolomics allows access to the metabolic perturbations associated with CVD in heart and vessels. Here we assessed which potential animal CVD model most closely mimics the serum metabolite signature of increased carotid intima-media thickness (cIMT) in humans, a clinical parameter widely accepted as a surrogate of CVD.

METHODS

A targeted mass spectrometry assay was used to quantify and compare a series of blood metabolites between 1362 individuals (KORA F4 cohort) and 5 animal CVD models: ApoE^-/-, Ldlr^-/-, and klotho-hypomorphic mice (kl/kl) and SHRSP rats with or without salt feeding. The metabolite signatures were obtained using linear regressions adjusted for various co-variates.

RESULTS

In human, increased cIMT [quartile Q4 vs. Q1] was associated with 26 metabolites (9 acylcarnitines, 2 lysophosphatidylcholines, 9 phosphatidylcholines and 6 sphingomyelins). Acylcarnitines correlated preferentially with serum glucose and creatinine. Phospholipids correlated preferentially with cholesterol (total and LDL). The human signature correlated positively and significantly with Ldlr^-/- and ApoE^-/- mice, while correlation with kl/kl mice and SHRP rats was either negative and non-significant. Human and Ldlr^-/- mice shared 11 significant metabolites displaying the same direction of regulation: 5 phosphatidylcholines, 1 lysophosphatidylcholines, 5 sphingomyelins; ApoE^-/- mice shared 10.

CONCLUSIONS

The human cIMT signature was partially mimicked by Ldlr^-/- and ApoE^-/- mice. These animal models might help better understand the biochemical and molecular mechanisms involved in the vessel metabolic perturbations associated with, and contributing to metabolic disorders in CVD.

The Association Between Plasma Ceramides and Sphingomyelins and Risk of Alzheimer's Disease Differs by Sex and APOE in the Baltimore Longitudinal Study of Aging

BACKGROUND

Cellular and animal studies demonstrated relationships between sphingolipid metabolism and Alzheimer's disease (AD) pathology. High blood ceramide levels have been shown to predict cognitive impairment and AD, but these studies had small sample sizes and did not assess differences in risk by sex or APOE genotype.

OBJECTIVE

To determine whether plasma ceramides and sphingomyelins were associated with risk of AD, and whether the association varied by sex and APOE genotype.

METHODS

Participants included 626 men and 366 women, aged 55 years and older, enrolled in the Baltimore Longitudinal Study of Aging. Plasma ceramides and sphingomyelins were determined using quantitative analyses performed on a high-performance liquid chromatography coupled electrospray ionization tandem mass spectrometer. Cox proportional hazards models, stratified by sex, were used to examine the relationship of plasma ceramides and sphingomyelins with risk of AD over a mean (SD) follow-up of 15.0 (7.0) years for men and 13.1 (5.9) years for women.

RESULTS

Among men, the highest tertile of most ceramides and sphingomyelins were associated with an increased risk of AD. Among women, there were no associations between any of the ceramides and risk of AD. In contrast, women in the highest tertile of most sphingomyelins had a reduced risk of AD, which was most pronounced among APOE ɛ4 carriers.

CONCLUSION

These results provide further evidence for the role of sphingolipid metabolism in AD and highlight the importance of considering sex and APOE genotype in assessing this relationship.

CSF Lipidomics Analysis: High-Resolution Mass Spectrometry Analytical Platform

High-resolution mass spectrometry provides the resolution required for direct infusion allowing detection and characterization of a vast array of lipids with a single injection. This chapter presents the methodology utilized for both unbiased and targeted lipidomics of cerebrospinal fluid.

Mass-spectrometric profiling of cerebrospinal fluid reveals metabolite biomarkers for CNS involvement in varicella zoster virus reactivation

Background

Varicella zoster virus (VZV) reactivation spans the spectrum from uncomplicated segmental herpes zoster to life-threatening disseminated CNS infection. Moreover, in the absence of a small animal model for this human pathogen, studies of pathogenesis at the organismal level depend on analysis of human biosamples. Changes in cerebrospinal fluid (CSF) metabolites may reflect critical aspects of host responses and end-organ damage in neuroinfection and neuroinflammation. We therefore applied a targeted metabolomics screen of CSF to three clinically distinct forms of VZV reactivation and infectious and non-infectious disease controls in order to identify biomarkers for CNS involvement in VZV reactivation.

Methods

Metabolite profiles were determined by targeted liquid chromatography-mass spectrometry in CSF from patients with segmental zoster (shingles, n = 14), facial nerve zoster (n = 16), VZV meningitis/encephalitis (n = 15), enteroviral meningitis (n = 10), idiopathic Bell’s palsy (n = 11), and normal pressure hydrocephalus (n = 15).

Results

Concentrations of 88 metabolites passing quality assessment clearly separated the three VZV reactivation forms from each other and from the non-infected samples. Internal cross-validation identified four metabolites (SM C16:1, glycine, lysoPC a C26:1, PC ae C34:0) that were particularly associated with VZV meningoencephalitis. SM(OH) C14:1 accurately distinguished facial nerve zoster from Bell’s palsy. Random forest construction revealed even more accurate classifiers (signatures comprising 2–4 metabolites) for most comparisons. Some of the most accurate biomarkers correlated only weakly with CSF leukocyte count, indicating that they do not merely reflect recruitment of inflammatory cells but, rather, specific pathophysiological mechanisms. Across all samples, only the sum of hexoses and the amino acids arginine, serine, and tryptophan correlated negatively with leukocyte count. Increased expression of the metabolites associated with VZV meningoencephalitis could be linked to processes relating to neuroinflammation/immune activation, neuronal signaling, and cell stress, turnover, and death (e.g., autophagy and apoptosis), suggesting that these metabolites might sense processes relating to end-organ damage.

Conclusions

The results provide proof-of-concept for the value of CSF metabolites as (1) disease-associated signatures suggesting pathophysiological mechanisms, (2) degree and nature of neuroinflammation, and (3) biomarkers for diagnosis and risk stratification of VZV reactivation and, likely, neuroinfections due to other pathogens.

Trial registration

Not applicable (non-interventional study).

Electronic supplementary material

The online version of this article (10.1186/s12974-017-1041-0) contains supplementary material, which is available to authorized users.

Application of Metabolomics in Alzheimer's Disease

Progress toward the development of efficacious therapies for Alzheimer’s disease (AD) is halted by a lack of understanding early underlying pathological mechanisms. Systems biology encompasses several techniques including genomics, epigenomics, transcriptomics, proteomics, and metabolomics. Metabolomics is the newest omics platform that offers great potential for the diagnosis and prognosis of neurodegenerative diseases as an individual’s metabolome reflects alterations in genetic, transcript, and protein profiles and influences from the environment. Advancements in the field of metabolomics have demonstrated the complexity of dynamic changes associated with AD progression underscoring challenges with the development of efficacious therapeutic interventions. Defining systems-level alterations in AD could provide insights into disease mechanisms, reveal sex-specific changes, advance the development of biomarker panels, and aid in monitoring therapeutic efficacy, which should advance individualized medicine. Since metabolic pathways are largely conserved between species, metabolomics could improve the translation of preclinical research conducted in animal models of AD into humans. A summary of recent developments in the application of metabolomics to advance the AD field is provided below.

Quantitative Metabolomics in Alzheimer's Disease: Technical Considerations for Improved Reproducibility

Metabolomics is the comprehensive analysis of small molecules (metabolites) that are intermediates or endpoints of metabolism. Since metabolites change more rapidly to both external and internal stimuli than genes and proteins, metabolomics provides a more sensitive tool to study physiological changes to a wide range of factors such age, medication, or disease status. Therefore, metabolomics is being increasingly used for the study of several pathological states, including complex diseases like Alzheimer's disease (AD).Both untargeted and targeted metabolomics have been applied for AD and both have provided diagnostic algorithms that accurately discriminate healthy patients from patients with AD by combining different metabolites. However, none of these algorithms have been replicated in larger, different cohorts, and a consensus in methodology has been claimed by the scientific community. The AbsoluteIDQ^® p180 Kit (Biocrates, Life Science AG, Innsbruck, Austria) is to date the only commercially available, validated, and standardized assay that measures up to 188 metabolites in biological samples. This kit unifies methodology in a common user manual and provides quantitative measurements of metabolites, thus facilitating an easier comparison among studies and reducing the technical variability that might contribute to replication failures. Nevertheless, recent studies showed no replication even when using this kit, suggesting that additional measures should be taken to achieve replication of metabolite-based discriminative algorithms. The aim of this chapter is to provide technical guidance on how to apply quantitative metabolomic data to the definition of discriminative algorithms for the diagnosis of neurodegenerative diseases such as AD. This chapter will provide an overview of technical aspects on the whole process, from blood sampling to raw data handling, and will highlight several technical aspects in the process that could hamper replication attempts even when using validated and standardized assays, such as the AbsoluteIDQ^® p180 Kit.

Omega-3 fatty acids, lipids, and apoE lipidation in Alzheimer's disease: a rationale for multi-nutrient dementia prevention

In the last decade, it has become obvious that Alzheimer's disease (AD) is closely linked to changes in lipids or lipid metabolism. One of the main pathological hallmarks of AD is amyloid-β (Aβ) deposition. Aβ is derived from sequential proteolytic processing of the amyloid precursor protein (APP). Interestingly, both, the APP and all APP secretases are transmembrane proteins that cleave APP close to and in the lipid bilayer. Moreover, apoE4 has been identified as the most prevalent genetic risk factor for AD. ApoE is the main lipoprotein in the brain, which has an abundant role in the transport of lipids and brain lipid metabolism. Several lipidomic approaches revealed changes in the lipid levels of cerebrospinal fluid or in post mortem AD brains. Here, we review the impact of apoE and lipids in AD, focusing on the major brain lipid classes, sphingomyelin, plasmalogens, gangliosides, sulfatides, DHA, and EPA, as well as on lipid signaling molecules, like ceramide and sphingosine-1-phosphate. As nutritional approaches showed limited beneficial effects in clinical studies, the opportunities of combining different supplements in multi-nutritional approaches are discussed and summarized.

Metabolic network failures in Alzheimer's disease: A biochemical road map

INTRODUCTION

The Alzheimer's Disease Research Summits of 2012 and 2015 incorporated experts from academia, industry, and nonprofit organizations to develop new research directions to transform our understanding of Alzheimer's disease (AD) and propel the development of critically needed therapies. In response to their recommendations, big data at multiple levels are being generated and integrated to study network failures in disease. We used metabolomics as a global biochemical approach to identify peripheral metabolic changes in AD patients and correlate them to cerebrospinal fluid pathology markers, imaging features, and cognitive performance.

METHODS

Fasting serum samples from the Alzheimer's Disease Neuroimaging Initiative (199 control, 356 mild cognitive impairment, and 175 AD participants) were analyzed using the AbsoluteIDQ-p180 kit. Performance was validated in blinded replicates, and values were medication adjusted.

RESULTS

Multivariable-adjusted analyses showed that sphingomyelins and ether-containing phosphatidylcholines were altered in preclinical biomarker-defined AD stages, whereas acylcarnitines and several amines, including the branched-chain amino acid valine and α-aminoadipic acid, changed in symptomatic stages. Several of the analytes showed consistent associations in the Rotterdam, Erasmus Rucphen Family, and Indiana Memory and Aging Studies. Partial correlation networks constructed for Aβ1-42, tau, imaging, and cognitive changes provided initial biochemical insights for disease-related processes. Coexpression networks interconnected key metabolic effectors of disease.

DISCUSSION

Metabolomics identified key disease-related metabolic changes and disease-progression-related changes. Defining metabolic changes during AD disease trajectory and its relationship to clinical phenotypes provides a powerful roadmap for drug and biomarker discovery.

Lipidomic Evaluation of Feline Neurologic Disease after AAV Gene Therapy

GM1 gangliosidosis is a fatal lysosomal disorder, for which there is no effective treatment. Adeno-associated virus (AAV) gene therapy in GM1 cats has resulted in a greater than 6-fold increase in lifespan, with many cats remaining alive at >5.7 years of age, with minimal clinical signs. Glycolipids are the principal storage product in GM1 gangliosidosis whose pathogenic mechanism is not completely understood. Targeted lipidomics analysis was performed to better define disease mechanisms and identify markers of disease progression for upcoming clinical trials in humans. 36 sphingolipids and subspecies associated with ganglioside biosynthesis were tested in the cerebrospinal fluid of untreated GM1 cats at a humane endpoint (∼8 months), AAV-treated GM1 cats (∼5 years old), and normal adult controls. In untreated GM1 cats, significant alterations were noted in 16 sphingolipid species, including gangliosides (GM1 and GM3), lactosylceramides, ceramides, sphingomyelins, monohexosylceramides, and sulfatides. Variable degrees of correction in many lipid metabolites reflected the efficacy of AAV gene therapy. Sphingolipid levels were highly predictive of neurologic disease progression, with 11 metabolites having a coefficient of determination (R²) > 0.75. Also, a specific detergent additive significantly increased the recovery of certain lipid species in cerebrospinal fluid samples. This report demonstrates the methodology and utility of targeted lipidomics to examine the pathophysiology of lipid storage disorders.

Metabolomics and cognition in African American adults in midlife: the atherosclerosis risk in communities study

Clinical studies have shown alterations in metabolic profiles when patients with mild cognitive impairment and Alzheimer's disease dementia were compared to cognitively normal subjects. Associations between 204 serum metabolites measured at baseline (1987-1989) and cognitive change were investigated in 1035 middle-aged community-dwelling African American participants in the biracial Atherosclerosis Risk in Communities (ARIC) Study. Cognition was evaluated using the Delayed Word Recall Test (DWRT; verbal memory), the Digit Symbol Substitution Test (DSST; processing speed) and the Word Fluency Test (WFT; verbal fluency) at visits 2 (1990-1992) and 4 (1996-1998). In addition, Cox regression was used to analyze the metabolites as predictors of incident hospitalized dementia between baseline and 2011. There were 141 cases among 1534 participants over a median 17.1-year follow-up period. After adjustment for established risk factors, one standard deviation increase in N-acetyl-1-methylhistidine was significantly associated with greater 6-year change in DWRT scores (β=-0.66 words; P=3.65 × 10-4). Two metabolites (one unnamed and a long-chain omega-6 polyunsaturated fatty acid found in vegetable oils (docosapentaenoate (DPA, 22:5 n-6)) were significantly associated with less decline on the DSST (DPA: β=1.25 digit-symbol pairs, P=9.47 × 10-5). Two unnamed compounds and three sex steroid hormones were associated with an increased risk of dementia (all P<3.9 × 10-4). The association of 4-androstene-3beta, 17beta-diol disulfate 1 with dementia was replicated in European Americans. These results demonstrate that screening the metabolome in midlife can detect biologically plausible biomarkers that may improve risk stratification for cognitive impairment at older ages.

The effect of lead exposure on fatty acid composition in mouse brain analyzed using pseudo-catalytic derivatization

We performed toxicological study of mice exposed to lead by quantifying fatty acids in brain of the mice. This study suggests that the introduced analytical method had an extremely high tolerance against impurities such as water and extractives; thus, it led to the enhanced resolution in visualizing the spectrum of fatty acid profiles in animal brain. Furthermore, one of the biggest technical advantages achieved in this study was the quantitation of fatty acid methyl ester profiles of mouse brain using a trace amount of sample (e.g., 100 μL mixture). Methanol was screened as the most effective extraction solvent for mouse brain. The behavioral test of the mice before and after lead exposure was conducted to see the effect of lead exposure on fatty acid composition of the mice' brain. The lead exposure led to changes in disease-related behavior of the mice. Also, the lead exposure induced significant alterations of fatty acid profile (C16:0, C 18:0, and C 18:1) in brain of the mice, implicated in pathology of psychiatric diseases. The alteration of fatty acid profile of brain of the mice suggests that the derivatizing technique can be applicable to most research fields associated with the environmental neurotoxins with better resolution in a short time, as compared to the current protocols for lipid analysis.

Association of blood lipids with Alzheimer's disease: A comprehensive lipidomics analysis

INTRODUCTION

The aim of this study was to (1) replicate previous associations between six blood lipids and Alzheimer's disease (AD) (Proitsi et al 2015) and (2) identify novel associations between lipids, clinical AD diagnosis, disease progression and brain atrophy (left/right hippocampus/entorhinal cortex).

METHODS

We performed untargeted lipidomic analysis on 148 AD and 152 elderly control plasma samples and used univariate and multivariate analysis methods.

RESULTS

We replicated our previous lipids associations and reported novel associations between lipids molecules and all phenotypes. A combination of 24 molecules classified AD patients with >70% accuracy in a test and a validation data set, and we identified lipid signatures that predicted disease progression (R2 = 0.10, test data set) and brain atrophy (R2 ≥ 0.14, all test data sets except left entorhinal cortex). We putatively identified a number of metabolic features including cholesteryl esters/triglycerides and phosphatidylcholines.

DISCUSSION

Blood lipids are promising AD biomarkers that may lead to new treatment strategies.

Role of Glia in Memory Deficits Following Traumatic Brain Injury: Biomarkers of Glia Dysfunction

Historically, glial cells have been recognized as a structural component of the brain. However, it has become clear that glial cells are intimately involved in the complexities of neural networks and memory formations. Astrocytes, microglia, and oligodendrocytes have dynamic responsibilities which substantially impact neuronal function and activities. Moreover, the importance of glia following brain injury has come to the forefront in discussions to improve axonal regeneration and functional recovery. The numerous activities of glia following injury can either promote recovery or underlie the pathobiology of memory deficits. This review outlines the pathological states of glial cells which evolve from their positive supporting roles to those which disrupt synaptic function and neuroplasticity following injury. Evidence suggests that glial cells interact extensively with neurons both chemically and physically, reinforcing their role as pivotal for higher brain functions such as learning and memory. Collectively, this mini review surveys investigations of how glial dysfunction following brain injury can alter mechanisms of synaptic plasticity and how this may be related to an increased risk for persistent memory deficits. We also include recent findings, that demonstrate new molecular avenues for clinical biomarker discovery.

Blood metabolite markers of preclinical Alzheimer's disease in two longitudinally followed cohorts of older individuals

INTRODUCTION

Recently, quantitative metabolomics identified a panel of 10 plasma lipids that were highly predictive of conversion to Alzheimer's disease (AD) in cognitively normal older individuals (n = 28, area under the curve [AUC] = 0.92, sensitivity/specificity of 90%/90%).

METHODS

Quantitative targeted metabolomics in serum using an identical method as in the index study.

RESULTS

We failed to replicate these findings in a substantially larger study from two independent cohorts-the Baltimore Longitudinal Study of Aging ([BLSA], n = 93, AUC = 0.642, sensitivity/specificity of 51.6%/65.7%) and the Age, Gene/Environment Susceptibility-Reykjavik Study ([AGES-RS], n = 100, AUC = 0.395, sensitivity/specificity of 47.0%/36.0%). In analyses applying machine learning methods to all 187 metabolite concentrations assayed, we find a modest signal in the BLSA with distinct metabolites associated with the preclinical and symptomatic stages of AD, whereas the same methods gave poor classification accuracies in the AGES-RS samples.

DISCUSSION

We believe that ours is the largest blood biomarker study of preclinical AD to date. These findings underscore the importance of large-scale independent validation of index findings from biomarker studies with relatively small sample sizes.

The ratio of phosphatidylcholines to lysophosphatidylcholines in plasma differentiates healthy controls from patients with Alzheimer's disease and mild cognitive impairment

BACKGROUND

Metabolomic processes have been identified as being strongly linked to the development of Alzheimer's disease (AD). Thus, lipid metabolites appear to be highly useful as diagnostic substrates for the diagnosis of AD and mild cognitive impairment (MCI) in plasma.

METHODS

We analyzed plasma samples from controls (n = 35), MCI (n = 33), and AD patients (n = 43) using the AbsoluteIDQ p180 Kit (Biocrates Life Sciences), which included quantitative analysis of 40 acylcarnitines, 21 amino acids, 19 biogenic amines, 15 sphingolipids, 90 glycerophospholipids, and sum of hexoses.

RESULTS

We found that individual lipid metabolites can differentiate controls from MCI and AD with relevant significance. However, the ratio between PC aa C34:4 and lysoPC a C18:2 differentiates controls from MCI (P = .0000007) and from AD (P = .0000009) with greater significance.

CONCLUSIONS

The results provide evidence that the ratio of these two lipid metabolites is useful for diagnosing MCI and AD with an accuracy of 82%-85%.