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

Brain and serum lipidomic profiles implicate Lands cycle acyl chain remodeling association with APOEε4 and mild cognitive impairment

Introduction

At least one-third of the identified risk alleles from Genome-Wide Association Studies (GWAS) of Alzheimer's disease (AD) are involved in lipid metabolism, lipid transport, or direct lipid binding. In fact, a common genetic variant (ε4) in a cholesterol and phospholipid transporter, Apolipoprotein E (APOEε4), is the primary genetic risk factor for late-onset AD. In addition to genetic variants, lipidomic studies have reported severe metabolic dysregulation in human autopsy brain tissue, cerebrospinal fluid, blood, and multiple mouse models of AD.

Methods

We aimed to identify an overarching metabolic pathway in lipid metabolism by integrating analyses of lipidomics and transcriptomics from the Religious Order Study and Rush Memory Aging Project (ROSMAP) using differential analysis and network correlation analysis.

Results

Coordinated differences in lipids were found to be dysregulated in association with both mild cognitive impairment (MCI) and APOEε4 carriers. Interestingly, these correlations were weakened when adjusting for education. Indeed, the cognitively non-impaired APOEε4 carriers have higher education levels in the ROSMAP cohort, suggesting that this lipid signature may be associated with a resilience phenotype. Network correlation analysis identified multiple differential lipids within a single module that are substrates and products in the Lands Cycle for acyl chain remodeling. In addition, our analyses identified multiple genes in the Lands Cycle acyl chain remodeling pathway, which were associated with cognitive decline independent of amyloid-β (Aβ) load and tau tangle pathologies.

Discussion

Our studies highlight the critical differences in acyl chain remodeling in brain tissue from APOEε4 carriers and individual non-carriers with MCI. A coordinated lipid profile shift in dorsolateral prefrontal cortex from both APOEε4 carriers and MCI suggests differences in lipid metabolism occur early in disease stage and highlights lipid homeostasis as a tractable target for early disease modifying intervention.

Lipidomic Analysis of Plasma Extracellular Vesicles Derived from Alzheimer's Disease Patients

Analysis of blood-based indicators of brain health could provide an understanding of early disease mechanisms and pinpoint possible intervention strategies. By examining lipid profiles in extracellular vesicles (EVs), secreted particles from all cells, including astrocytes and neurons, and circulating in clinical samples, important insights regarding the brain's composition can be gained. Herein, a targeted lipidomic analysis was carried out in EVs derived from plasma samples after removal of lipoproteins from individuals with Alzheimer's disease (AD) and healthy controls. Differences were observed for selected lipid species of glycerolipids (GLs), glycerophospholipids (GPLs), lysophospholipids (LPLs) and sphingolipids (SLs) across three distinct EV subpopulations (all-cell origin, derived by immunocapture of CD9, CD81 and CD63; neuronal origin, derived by immunocapture of L1CAM; and astrocytic origin, derived by immunocapture of GLAST). The findings provide new insights into the lipid composition of EVs isolated from plasma samples regarding specific lipid families (MG, DG, Cer, PA, PC, PE, PI, LPI, LPE, LPC), as well as differences between AD and control individuals. This study emphasizes the crucial role of plasma EV lipidomics analysis as a comprehensive approach for identifying biomarkers and biological targets in AD and related disorders, facilitating early diagnosis and potentially informing novel interventions.

Metabolites and Cognitive Decline in a Puerto Rican Cohort

Background

Recent studies have identified plasma metabolites associated with cognitive decline and Alzheimer's disease; however, little research on this topic has been conducted in Latinos, especially Puerto Ricans.

Objective

This study aims to add to the growing body of metabolomics research in Latinos to better understand and improve the health of this population.

Methods

We assessed the association between plasma metabolites and global cognition over 12 years of follow-up in 736 participants of the Boston Puerto Rican Health Study (BPRHS). Metabolites were measured with untargeted metabolomic profiling (Metabolon, Inc) at baseline. We used covariable adjusted linear mixed models (LMM) with a metabolite * time interaction term to identify metabolites (of 621 measured) associated with ∼12 years cognitive trajectory.

Results

We observed strong inverse associations between medium-chain fatty acids, caproic acid, and the dicarboxylic acids, azelaic and sebacic acid, and global cognition. N-formylphenylalanine, a tyrosine pathway metabolite, was associated with improvement in cognitive trajectory.

Conclusions

The metabolites identified in this study are generally consistent with prior literature and highlight a role medium chain fatty acid and tyrosine metabolism in cognitive decline.

Lysophospholipids and branched chain amino acids are associated with aging: a metabolomics-based study of Chinese adults

BACKGROUND

Aging is an inevitable process associated with impairments in multiple organ systems, which increases the risk of comorbidity and disability, and reduces the health-span. Metabolomics is a powerful tool in aging research, which can reflect the characteristics of aging at the level of terminal metabolism, and may contribute to the exploration of aging mechanisms and the formulation of anti-aging strategies.

METHODS

To identify possible biomarkers and pathways associated with aging using untargeted metabolomics methods, we performed liquid chromatography-mass spectrometry (LC-MS)-based untargeted metabolomics profiling on serum samples from 32 older adults and 32 sex-matched young controls.

RESULTS

Metabolite profiling could distinguish the two groups. Among the 349 metabolites identified, 80-including lysophospholipids whose levels gradually decline-are possible candidate aging biomarkers. Valine, leucine and isoleucine degradation and biosynthesis were important pathways in aging, with reduced levels of L-isoleucine (r = - 0.30, p = 0.017) and L-leucine (r = - 0.32, p = 0.010) observed in older adults.

CONCLUSIONS

We preliminarily revealed the metabolite changes associated with aging in Chinese adults. Decreases in mitochondrial membrane-related lysophospholipids and dysfunction of branched-chain amino acid metabolism were determined to be the characteristics and promising research targets for aging.

Predictive metabolic networks reveal sex- and APOE genotype-specific metabolic signatures and drivers for precision medicine in Alzheimer's disease

INTRODUCTION

Late-onset Alzheimer's disease (LOAD) is a complex neurodegenerative disease characterized by multiple progressive stages, glucose metabolic dysregulation, Alzheimer's disease (AD) pathology, and inexorable cognitive decline. Discovery of metabolic profiles unique to sex, apolipoprotein E (APOE) genotype, and stage of disease progression could provide critical insights for personalized LOAD medicine.

METHODS

Sex- and APOE-specific metabolic networks were constructed based on changes in 127 metabolites of 656 serum samples from the Alzheimer's Disease Neuroimaging Initiative cohort.

RESULTS

Application of an advanced analytical platform identified metabolic drivers and signatures clustered with sex and/or APOE ɛ4, establishing patient-specific biomarkers predictive of disease state that significantly associated with cognitive function. Presence of the APOE ɛ4 shifts metabolic signatures to a phosphatidylcholine-focused profile overriding sex-specific differences in serum metabolites of AD patients.

DISCUSSION

These findings provide an initial but critical step in developing a diagnostic platform for personalized medicine by integrating metabolomic profiling and cognitive assessments to identify targeted precision therapeutics for AD patient subgroups through computational network modeling.

Towards a Discovery of a Zinc-Dependent Phosphate Transport Road in Plants

Owing to the impending global scarcity of high-quality sources of phosphate (Pi) fertilizers, lowering its use in crop production requires improved insights into factors stimulating Pi uptake from the soil as well as the efficacious use by plants. Following decades of extensive research on plants' adaptation to Pi deficiency with mitigated success in the field, a better understanding of how plants exposed to zinc (Zn) deficiency accumulate much more Pi provides a novel strategy in comparison to when plants are grown in Zn-rich soils. In this context, we review current knowledge and molecular events involved in the Pi and Zn signaling crosstalk in plants that will bear great significance for agronomical and rudimentary research applications.

Plasma Lipidomics Approach in Early and Specific Alzheimer’s Disease Diagnosis

Background: The brain is rich in lipid content, so a physiopathological pathway in Alzheimer’s disease (AD) could be related to lipid metabolism impairment. The study of lipid profiles in plasma samples could help in the identification of early AD changes and new potential biomarkers. Methods: An untargeted lipidomic analysis was carried out in plasma samples from preclinical AD (n = 11), mild cognitive impairment-AD (MCI-AD) (n = 31), and healthy (n = 20) participants. Variables were identified by means of two complementary methods, and lipid families’ profiles were studied. Then, a targeted analysis was carried out for some identified lipids. Results: Statistically significant differences were obtained for the diglycerol (DG), lysophosphatidylethanolamine (LPE), lysophosphatidylcholine (LPC), monoglyceride (MG), and sphingomyelin (SM) families as well as for monounsaturated (MUFAs) lipids, among the participant groups. In addition, statistically significant differences in the levels of lipid families (ceramides (Cer), LPE, LPC, MG, and SM) were observed between the preclinical AD and healthy groups, while statistically significant differences in the levels of DG, MG, and PE were observed between the MCI-AD and healthy groups. In addition, 18:1 LPE showed statistically significant differences in the targeted analysis between early AD (preclinical and MCI) and healthy participants. Conclusion: The different plasma lipid profiles could be useful in the early and minimally invasive detection of AD. Among the lipid families, relevant results were obtained from DGs, LPEs, LPCs, MGs, and SMs. Specifically, MGs could be potentially useful in AD detection; while LPEs, LPCs, and SM seem to be more related to the preclinical stage, while DGs are more related to the MCI stage. Specifically, 18:1 LPE showed a potential utility as an AD biomarker.

How previous treatment changes the metabolomic profile in patients with metastatic breast cancer

Purpose

Metabolites are in the spotlight of attention as promising novel breast cancer biomarkers. However, no study has been conducted concerning changes in the metabolomics profile of metastatic breast cancer patients according to previous therapy.

Methods

We performed a retrospective, single-center, nonrandomized, partially blinded, treatment-based study. Metastatic breast cancer (MBC) patients were enrolled between 03/2010 and 09/2016 at the beginning of a new systemic therapy. The endogenous metabolites in the plasma samples were analyzed using the AbsoluteIDQ^® p180 Kit (Biocrates Life Sciences AG, Innsbruck) a targeted, quality and quantitative-controlled metabolomics approach. The statistical analysis was performed using R package, version 3.3.1. ANOVA was used to statistically assess age differences within groups. Furthermore, we analyzed the CTC status of the patients using the CellSearch^™ assay.

Results

We included 178 patients in our study. Upon dividing the study population according to therapy before study inclusion, we found the following: 4 patients had received no therapy, 165 chemotherapy, and 135 anti-hormonal therapy, 30 with anti-Her2 therapy and 38 had received treatment with bevacizumab. Two metabolites were found to be significantly different, depending on the further therapy of the patients: methionine and serine. Whereas methionine levels were higher in the blood of patients who received an anti-Her2-therapy, serine was lower in patients with endocrine therapy only.

Conclusion

We identified two metabolites for which concentrations differed significantly depending on previous therapies, which could help to choose the next therapy in patients who have already received numerous different treatments.

Blood-Based Biomarkers for Alzheimer's Disease Diagnosis and Progression: An Overview

Alzheimer's Disease (AD) is a progressive neurodegenerative disease characterized by amyloid-β (Aβ) plaque deposition and neurofibrillary tangle accumulation in the brain. Although several studies have been conducted to unravel the complex and interconnected pathophysiology of AD, clinical trial failure rates have been high, and no disease-modifying therapies are presently available. Fluid biomarker discovery for AD is a rapidly expanding field of research aimed at anticipating disease diagnosis and following disease progression over time. Currently, Aβ1-42, phosphorylated tau, and total tau levels in the cerebrospinal fluid are the best-studied fluid biomarkers for AD, but the need for novel, cheap, less-invasive, easily detectable, and more-accessible markers has recently led to the search for new blood-based molecules. However, despite considerable research activity, a comprehensive and up-to-date overview of the main blood-based biomarker candidates is still lacking. In this narrative review, we discuss the role of proteins, lipids, metabolites, oxidative-stress-related molecules, and cytokines as possible disease biomarkers. Furthermore, we highlight the potential of the emerging miRNAs and long non-coding RNAs (lncRNAs) as diagnostic tools, and we briefly present the role of vitamins and gut-microbiome-related molecules as novel candidates for AD detection and monitoring, thus offering new insights into the diagnosis and progression of this devastating disease.

Alzheimer’s Disease: An Update and Insights Into Pathophysiology

Alzheimer’s disease (AD) is an irreversible brain disorder associated with slow, progressive loss of brain functions mostly in older people. The disease processes start years before the symptoms are manifested at which point most therapies may not be as effective. In the hippocampus, the key proteins involved in the JAK2/STAT3 signaling pathway, such as p-JAK2-Tyr1007 and p-STAT3-Tyr705 were found to be elevated in various models of AD. In addition to neurons, glial cells such as astrocytes also play a crucial role in the progression of AD. Without having a significant effect on tau and amyloid pathologies, the JAK2/STAT3 pathway in reactive astrocytes exhibits a behavioral impact in the experimental models of AD. Cholinergic atrophy in AD has been traced to a trophic failure in the NGF metabolic pathway, which is essential for the survival and maintenance of basal forebrain cholinergic neurons (BFCN). In AD, there is an alteration in the conversion of the proNGF to mature NGF (mNGF), in addition to an increase in degradation of the biologically active mNGF. Thus, the application of exogenous mNGF in experimental studies was shown to improve the recovery of atrophic BFCN. Furthermore, it is now coming to light that the FGF7/FGFR2/PI3K/Akt signaling pathway mediated by microRNA-107 is also involved in AD pathogenesis. Vascular dysfunction has long been associated with cognitive decline and increased risk of AD. Vascular risk factors are associated with higher tau and cerebral beta-amyloid (Aβ) burden, while synergistically acting with Aβ to induce cognitive decline. The apolipoprotein E4 polymorphism is not just one of the vascular risk factors, but also the most prevalent genetic risk factor of AD. More recently, the research focus on AD shifted toward metabolisms of various neurotransmitters, major and minor nutrients, thus giving rise to metabolomics, the most important “omics” tool for the diagnosis and prognosis of neurodegenerative diseases based on an individual’s metabolome. This review will therefore proffer a better understanding of novel signaling pathways associated with neural and glial mechanisms involved in AD, elaborate potential links between vascular dysfunction and AD, and recent developments in “omics”-based biomarkers in AD.

Targeted Lipidomics To Measure Phospholipids and Sphingomyelins in Plasma: A Pilot Study To Understand the Impact of Race/Ethnicity in Alzheimer's Disease

The number of people suffering from Alzheimer's disease (AD) is increasing rapidly every year. One aspect of AD that is often overlooked is the disproportionate incidence of AD among African American/Black populations. With the recent development of novel assays for lipidomics analysis in recent times, there has been a drastic increase in the number of studies focusing on changes of lipids in AD. However, very few of these studies have focused on or even included samples from African American/Black individuals samples. In this study, we aimed to determine if the lipidome in AD is universal across non-Hispanic White and African American/Black individuals. To accomplish this, a targeted mass spectrometry lipidomics analysis was performed on plasma samples (N = 113) obtained from cognitively normal (CN, N = 54) and AD (N = 59) individuals from African American/Black (N = 56) and non-Hispanic White (N = 57) backgrounds. Five lipids (PS 18:0_18:0, PS 18:0_20:0, PC 16:0_22:6, PC 18:0_22:6, and PS 18:1_22:6) were altered between AD and CN sample groups (p value < 0.05). Upon racial stratification, there were notable differences in lipids that were unique to African American/Black or non-Hispanic White individuals. PS 20:0_20:1 was reduced in AD in samples from non-Hispanic White but not African American/Black adults. We also tested whether race/ethnicity significantly modified the association between lipids and AD status by including a race × diagnosis interaction term in a linear regression model. PS 20:0_20:1 showed a significant interaction (p = 0.004). The discovery of lipid changes in AD in this study suggests that identifying relevant lipid biomarkers for diagnosis will require diversity in sample cohorts.

Sex Differences in the Metabolome of Alzheimer's Disease Progression

Alzheimer's disease (AD) is the leading cause of dementia; however, men and women face differential AD prevalence, presentation, and progression risks. Characterizing metabolomic profiles during AD progression is fundamental to understand the metabolic disruptions and the biological pathways involved. However, outstanding questions remain of whether peripheral metabolic changes occur equally in men and women with AD. Here, we evaluated differential effects of metabolomic and brain volume associations between sexes. We used three cohorts from the Alzheimer's Disease Neuroimaging Initiative (ADNI), evaluated 1,368 participants, two metabolomic platforms with 380 metabolites in total, and six brain segment volumes. Using dimension reduction techniques, we took advantage of the correlation structure of the brain volume phenotypes and the metabolite concentration values to reduce the number of tests while aggregating relevant biological structures. Using WGCNA, we aggregated modules of highly co-expressed metabolites. On the other hand, we used partial least squares regression-discriminant analysis (PLS-DA) to extract components of brain volumes that maximally co-vary with AD diagnosis as phenotypes. We tested for differences in effect sizes between sexes in the association between single metabolite and metabolite modules with the brain volume components. We found five metabolite modules and 125 single metabolites with significant differences between sexes. These results highlight a differential lipid disruption in AD progression between sexes. Men showed a greater negative association of phosphatidylcholines and sphingomyelins and a positive association of VLDL and large LDL with AD progression. In contrast, women showed a positive association of triglycerides in VLDL and small and medium LDL with AD progression. Explicitly identifying sex differences in metabolomics during AD progression can highlight particular metabolic disruptions in each sex. Our research study and strategy can lead to better-tailored studies and better-suited treatments that take sex differences into account.

Changes in the metabolic profile of human male postmortem frontal cortex and cerebrospinal fluid samples associated with heavy alcohol use

Heavy alcohol use is one of the top causes of disease and death in the world. The brain is a key organ affected by heavy alcohol use. Here, our aim was to measure changes caused by heavy alcohol use in the human brain metabolic profile. We analyzed human postmortem frontal cortex and cerebrospinal fluid (CSF) samples from males with a history of heavy alcohol use (n = 74) and controls (n = 74) of the Tampere Sudden Death Series cohort. We used a nontargeted liquid chromatography mass spectrometry-based metabolomics method. We observed differences between the study groups in the metabolite levels of both frontal cortex and CSF samples, for example, in amino acids and derivatives, and acylcarnitines. There were more significant alterations in the metabolites of frontal cortex than in CSF. In the frontal cortex, significant alterations were seen in the levels of neurotransmitters (e.g., decreased levels of GABA and acetylcholine), acylcarnitines (e.g., increased levels of acylcarnitine 4:0), and in some metabolites associated with alcohol metabolizing enzymes (e.g., increased levels of 2-piperidone). Some of these changes were also significant in the CSF samples (e.g., elevated 2-piperidone levels). Overall, these results show the metabolites associated with neurotransmitters, energy metabolism and alcohol metabolism, were altered in human postmortem frontal cortex and CSF samples of persons with a history of heavy alcohol use.

Exploration of Plasma Lipids in Mild Cognitive Impairment due to Alzheimer's Disease

BACKGROUND

Lipids have important structural roles in cell membranes and changes to these membrane lipids may influence β- and γ-secretase activities and thus contribute to Alzheimer's disease (AD) pathology.

OBJECTIVE

To explore baseline plasma lipid profiling in participants with mild cognitive impairment (MCI) with and without AD pathology.

METHODS

We identified 261 plasma lipids using reversed-phase liquid chromatography/mass spectrometry in cerebrospinal fluid amyloid positive (Aβ+) or negative (Aβ-) participants with MCI as compared to controls. Additionally, we analyzed the potential associations of plasma lipid profiles with performance on neuropsychological tests at baseline and after two years.

RESULTS

Sphingomyelin (SM) concentrations, particularly, SM(d43:2), were lower in MCI Aβ+ individuals compared to controls. Further, SM(d43:2) was also nominally reduced in MCI Aβ+ individuals compared to MCI Aβ-. No plasma lipids were associated with performance on primary neuropsychological tests at baseline or between the two time points after correction for multiple testing.

CONCLUSION

Reduced plasma concentrations of SM were associated with AD.

Metabolic Profiling of Neocortical Tissue Discriminates Alzheimer's Disease from Mild Cognitive Impairment, High Pathology Controls, and Normal Controls

Alzheimer's disease (AD) is the most common cause of dementia, accounting for an estimated 60-80% of cases, and is the sixth-leading cause of death in the United States. While considerable advancements have been made in the clinical care of AD, it remains a complicated disorder that can be difficult to identify definitively in its earliest stages. Recently, mass spectrometry (MS)-based metabolomics has shown significant potential for elucidation of disease mechanisms and identification of therapeutic targets as well diagnostic and prognostic markers that may be useful in resolving some of the difficulties affecting clinical AD studies, such as effective stratification. In this study, complementary gas chromatography- and liquid chromatography-MS platforms were used to detect and monitor 2080 metabolites and features in 48 postmortem tissue samples harvested from the superior frontal gyrus of male and female subjects. Samples were taken from four groups: 12 normal control (NC) patients, 12 cognitively normal subjects characterized as high pathology controls (HPC), 12 subjects with nonspecific mild cognitive impairment (MCI), and 12 subjects with AD. Multivariate statistics informed the construction and cross-validation (p < 0.01) of partial least squares-discriminant analysis (PLS-DA) models defined by a nine-metabolite panel of disease markers (lauric acid, stearic acid, myristic acid, palmitic acid, palmitoleic acid, and four unidentified mass spectral features). Receiver operating characteristic analysis showed high predictive accuracy of the resulting PLS-DA models for discrimination of NC (97%), HPC (92%), MCI (∼96%), and AD (∼96%) groups. Pathway analysis revealed significant disturbances in lysine degradation, fatty acid metabolism, and the degradation of branched-chain amino acids. Network analysis showed significant enrichment of 11 enzymes, predominantly within the mitochondria. The results expand basic knowledge of the metabolome related to AD and reveal pathways that can be targeted therapeutically. This study also provides a promising basis for the development of larger multisite projects to validate these candidate markers in readily available biospecimens such as blood to enable the effective screening, rapid diagnosis, accurate surveillance, and therapeutic monitoring of AD. All raw mass spectrometry data have been deposited to MassIVE (data set identifier MSV000087165).

Challenges in LC-MS-based metabolomics for Alzheimer's disease early detection: targeted approaches versus untargeted approaches

BACKGROUND

Alzheimer's disease (AD) is one of the most common causes of dementia in old people. Neuronal deficits such as loss of memory, language and problem-solving are severely compromised in affected patients. The molecular features of AD are Aβ deposits in plaques or in oligomeric structures and neurofibrillary tau tangles in brain. However, the challenge is that Aβ is only one piece of the puzzle, and recent findings continue to support the hypothesis that their presence is not sufficient to predict decline along the AD outcome. In this regard, metabolomic-based techniques are acquiring a growing interest for either the early diagnosis of diseases or the therapy monitoring. Mass spectrometry is one the most common analytical platforms used for detection, quantification, and characterization of metabolic biomarkers. In the past years, both targeted and untargeted strategies have been applied to identify possible interesting compounds.

AIM OF REVIEW

The overall goal of this review is to guide the reader through the most recent studies in which LC-MS-based metabolomics has been proposed as a powerful tool for the identification of new diagnostic biomarkers in AD. To this aim, herein studies spanning the period 2009-2020 have been reported. Advantages and disadvantages of targeted vs untargeted metabolomic approaches have been outlined and critically discussed.

Biomarkers for the Clinical Diagnosis of Alzheimer's Disease: Metabolomics Analysis of Brain Tissue and Blood

With an increase in aging populations worldwide, age-related diseases such as Alzheimer's disease (AD) have become a global concern. At present, a cure for neurodegenerative disease is lacking. There is an urgent need for a biomarker that can facilitate the diagnosis, classification, prognosis, and treatment response of AD. The recent emergence of highly sensitive mass-spectrometry platforms and high-throughput technology can be employed to discover and catalog vast datasets of small metabolites, which respond to changed status in the body. Metabolomics analysis provides hope for a better understanding of AD as well as the subsequent identification and analysis of metabolites. Here, we review the state-of-the-art emerging candidate biomarkers for AD.

Serum metabolites associated with brain amyloid beta deposition, cognition and dementia progression

Metabolomics in the Alzheimer's Disease Neuroimaging Initiative cohort provides a powerful tool for mapping biochemical changes in Alzheimer's disease, and a unique opportunity to learn about the association between circulating blood metabolites and brain amyloid-β deposition in Alzheimer's disease. We examined 140 serum metabolites and their associations with brain amyloid-β deposition, cognition and conversion from mild cognitive impairment to Alzheimer's disease in the Alzheimer's Disease Neuroimaging Initiative. Processed [18F] Florbetapir PET images were used to perform a voxel-wise statistical analysis of the effect of metabolite levels on amyloid-β accumulation across the whole brain. We performed a multivariable regression analysis using age, sex, body mass index, apolipoprotein E ε4 status and study phase as covariates. We identified nine metabolites as significantly associated with amyloid-β deposition after multiple comparison correction. Higher levels of one acylcarnitine (C3; propionylcarnitine) and one biogenic amine (kynurenine) were associated with decreased amyloid-β accumulation and higher memory scores. However, higher levels of seven phosphatidylcholines (lysoPC a C18:2, PC aa C42:0, PC ae C42:3, PC ae C44:3, PC ae C44:4, PC ae C44:5 and PC ae C44:6) were associated with increased brain amyloid-β deposition. In addition, higher levels of PC ae C44:4 were significantly associated with lower memory and executive function scores and conversion from mild cognitive impairment to Alzheimer's disease dementia. Our findings suggest that dysregulation of peripheral phosphatidylcholine metabolism is associated with earlier pathological changes noted in Alzheimer's disease as measured by brain amyloid-β deposition as well as later clinical features including changes in memory and executive functioning. Perturbations in phosphatidylcholine metabolism may point to issues with membrane restructuring leading to the accumulation of amyloid-β in the brain. Additional studies are needed to explore whether these metabolites play a causal role in the pathogenesis of Alzheimer's disease or if they are biomarkers for systemic changes during preclinical phases of the disease.

Potential Neuroregenerative and Neuroprotective Effects of Uridine/Choline-Enriched Multinutrient Dietary Intervention for Mild Cognitive Impairment: A Narrative Review

In mild cognitive impairment (MCI) due to Alzheimer disease (AD), also known as prodromal AD, there is evidence for a pathologic shortage of uridine, choline, and docosahexaenoic acid [DHA]), which are key nutrients needed by the brain. Preclinical and clinical evidence shows the importance of nutrient bioavailability to support the development and maintenance of brain structure and function in MCI and AD. Availability of key nutrients is limited in MCI, creating a distinct nutritional need for uridine, choline, and DHA. Evidence suggests that metabolic derangements associated with ageing and disease-related pathology can affect the body's ability to generate and utilize nutrients. This is reflected in lower levels of nutrients measured in the plasma and brains of individuals with MCI and AD dementia, and progressive loss of cognitive performance. The uridine shortage cannot be corrected by normal diet, making uridine a conditionally essential nutrient in affected individuals. It is also challenging to correct the choline shortfall through diet alone, because brain uptake from the plasma significantly decreases with ageing. There is no strong evidence to support the use of single-agent supplements in the management of MCI due to AD. As uridine and choline work synergistically with DHA to increase phosphatidylcholine formation, there is a compelling rationale to combine these nutrients. A multinutrient enriched with uridine, choline, and DHA developed to support brain function has been evaluated in randomized controlled trials covering a spectrum of dementia from MCI to moderate AD. A randomized controlled trial in subjects with prodromal AD showed that multinutrient intervention slowed brain atrophy and improved some measures of cognition. Based on the available clinical evidence, nutritional intervention should be considered as a part of the approach to the management of individuals with MCI due to AD, including adherence to a healthy, balanced diet, and consideration of evidence-based multinutrient supplements.

CSF metabolites associate with CSF tau and improve prediction of Alzheimer's disease status

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.

Plasma phosphatidylcholines and vitamin B12/folate levels are possible prognostic biomarkers for progression of Alzheimer's disease

OBJECTIVES

In clinical practice it is important to identify patients suffering from mild cognitive impairment (MCI) who will progress to Alzheimer's disease (AD). The purpose of this study is to investigate whether lipid metabolites and vitamin B12 and folate levels are effective biomarker for an accurate prediction of MCI-to-AD conversion.

METHODS

During the standard diagnostic assessment at our memory clinic 48 cognitively healthy subjects and MCI patients were recruited. These participants were followed up after 7-9 years. Blood was collected, various biochemical markers (including vitamin B12 and folate) analysed and plasma lipids were measured using the AbsoluteIDQ p150 Kit.

RESULTS

There was no significant change in lipid levels in controls converting to MCI. However, we found significant changes in five lipids in converters from controls to AD. Interestingly, also two lipids were altered when MCI re-converted to controls. Vitamin B12 levels were not affected by conversion but folate levels significantly decreased in MCI-AD conversion.

CONCLUSIONS

Taken together, our study provides evidence that some plasma lipids are significantly altered in subjects converting to AD. Future studies will investigate whether the peripheral lipid changes correspond with changes in the brain during the course of the disease. Although this is a small study, there are indications that lipids may be suitable as prognostic markers.

Multi-omic analysis unveils biological pathways in peripheral immune system associated to minimal hepatic encephalopathy appearance in cirrhotic patients

Patients with liver cirrhosis may develop minimal hepatic encephalopathy (MHE) which affects their quality of life and life span. It has been proposed that a shift in peripheral inflammation triggers the appearance of MHE. However, the mechanisms involved in this immune system shift remain unknown. In this work we studied the broad molecular changes involved in the induction of MHE with the goal of identifying (1) altered genes and pathways in peripheral blood cells associated to the appearance of MHE, (2) serum metabolites and cytokines with modified levels in MHE patients and (3) MHE-regulated immune response processes related to changes in specific serum molecules. We adopted a multi-omic approach to profile the transcriptome, metabolome and a panel of cytokines of blood samples taken from cirrhotic patients with or without MHE. Transcriptomic analysis supports the hypothesis of alternations in the Th1/Th2 and Th17 lymphocytes cell populations as major drivers of MHE. Cluster analysis of serum molecules resulted in six groups of chemically similar compounds, suggesting that functional modules operate during the induction of MHE. Finally, the multi-omic integrative analysis suggested a relationship between cytokines CCL20, CX3CL1, CXCL13, IL-15, IL-22 and IL-6 with alteration in chemotaxis, as well as a link between long-chain unsaturated phospholipids and the increased fatty acid transport and prostaglandin production. We found altered immune pathways that may collectively contribute to the mild cognitive impairment phenotype in MHE. Our approach is able to combine extracellular and intracellular information, opening new insights to the understanding of the disease.

APOE Genotype Differentially Modulates Plasma Lipids in Healthy Older Individuals, with Relevance to Brain Health

Apolipoprotein E (APOE) genotype is an established genetic risk factor for sporadic Alzheimer's disease (AD) but the extent to which APOE genotype influences the plasma lipidome is unknown, even though lipids are potential diagnostic or prognostic biomarkers for AD. We quantified plasma lipids using untargeted liquid chromatography coupled mass spectrometry in a total of 152 non-demented participants aged 65-100 years carrying at least one ɛ2 or ɛ4 allele (ɛ2/ɛ2 or ɛ2/ɛ3, n = 38: ɛ4/ɛ3 or ɛ4/ɛ4, n = 38), who were roughly matched to an ɛ3/ɛ3 control by age, sex, and lipid-lowering medication (n = 76). Low density lipoprotein cholesterol levels were genotype dependent (ɛ4/ɛ4> ɛ4/ɛ3> ɛ3/ɛ3> ɛ2/ɛ3> ɛ2/ɛ2). The greatest variation in lipids was related to the ɛ2 isoform, where various lysophosphatidylcholines and all phosphatidylethanolamine (PE) subclasses were elevated relative to ɛ3/ɛ3 and ɛ4 carriers. APOEɛ4 carriers had reduced phosphatidylinositol relative to ɛ3/ɛ3 and ɛ2 carriers. Logistic regression revealed that ɛ2 carriers were at least 4 times higher odds of being in the highest tertile of PE lipid level relative to ɛ3/ɛ3. The elevation in PE and other phospholipids in ɛ2 carriers may indicate the protective effect of ɛ2 is linked to these phospholipids. Additionally, high baseline PE in cognitively normal participants predicted protection against cognitive decline six years later. Our data suggest substantial modulation of plasma lipids by APOE genotype and therefore indicates possible lipid targets and pathomechanisms involved in AD risk.

Blood-based Biomarkers of Alzheimer's Disease: The Long and Winding Road

BACKGROUND

Blood-based biomarkers can be very useful in formulating new diagnostic and treatment proposals in the field of dementia, especially in Alzheimer's disease (AD). However, due to the influence of several factors on the reproducibility and reliability of these markers, their clinical use is still very uncertain. Thus, up-to-date knowledge about the main blood biomarkers that are currently being studied is extremely important in order to discover clinically useful and applicable tools, which could also be used as novel pharmacological strategies for the AD treatment.

METHODS

A narrative review was performed based on the current candidates of blood-based biomarkers for AD to show the main results from different studies, focusing on their clinical applicability and association with AD pathogenesis.

OBJECTIVE

The aim of this paper was to carry out a literature review on the major blood-based biomarkers for AD, connecting them with the pathophysiology of the disease.

RESULTS

Recent advances in the search of blood-based AD biomarkers were summarized in this review. The biomarkers were classified according to the topics related to the main hallmarks of the disease such as inflammation, amyloid, and tau deposition, synaptic degeneration and oxidative stress. Moreover, molecules involved in the regulation of proteins related to these hallmarks were described, such as non-coding RNAs, neurotrophins, growth factors and metabolites. Cells or cellular components with the potential to be considered as blood-based AD biomarkers were described in a separate topic.

CONCLUSION

A series of limitations undermine new discoveries on blood-based AD biomarkers. The lack of reproducibility of findings due to the small size and heterogeneity of the study population, different analytical methods and other assay conditions make longitudinal studies necessary in this field to validate these structures, especially when considering a clinical evaluation that includes a broad panel of these potential and promising blood-based biomarkers.

Acyl-Alkyl-Phosphatidlycholines are Decreased in Saliva of Patients with Alzheimer's Disease as Identified by Targeted Metabolomics

Diagnosis of Alzheimer's disease (AD) is still a challenge. Salivary analysis could produce an easily accessible and inexpensive possibility to study metabolic changes in AD. In the present pilot study, we show for the first time using targeted metabolomics that acyl-alkyl phosphatidylcholines (PCae C34:1-2; PCae C36:1-2-3; PCaeC38:1c3; PCae C40:2-3) are significantly reduced in saliva of AD patients (n = 25) compared to healthy controls (n = 25). Saliva levels of PCae C36Λ1-2-3) were also decreased in patients with mild cognitive impairment (n = 25). No changes were seen for saliva diacyl-phosphatidylcholines, lyso-acyl-phosphatidylcholines, and sphinogomyelins. These data suggest specific lipid changes in the saliva of AD patients, thus salivary measures could establish new biomarkers. However, these preliminary results have to be established in larger scale studies.

Platelet and Plasma Phosphatidylcholines as Biomarkers to Diagnose Cerebral Amyloid Angiopathy

Alzheimer's disease is a severe neurodegenerative brain disorder and characterized by deposition of extracellular toxic β-amyloid (42) plaques and the formation of intracellular tau neurofibrillary tangles. In addition, β-amyloid peptide deposits are found in the walls of small to medium blood vessels termed cerebral amyloid angiopathy (CAA). However, the pathogenesis of CAA appears to differ from that of senile plaques in several aspects. The aim of the present study was to analyze different lipids [phosphatidylcholines (PCs) and lysoPCs] in platelets and plasma of a novel mouse model of sporadic CAA (1). Our data show that lipids are significantly altered in plasma of the CAA mice. Levels of eight diacyl PCs, two acyl-alkyl PCs, and five lysoPCs were significantly increased. In extracts of mouse blood platelets, four diacyl and two acyl-alkyl PCs (but not lysoPCs) were significantly altered. Our data show that lipids are changed in CAA with a specific pattern, and we provide for the first time evidence that selected platelet and plasma PCs may help to characterize CAA.

Common disbalance in the brain parenchyma of dementias: Phospholipid profile analysis between CADASIL and sporadic Alzheimer's disease

Sporadic Alzheimer's disease (SAD) is the most common form of dementia, and cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) is the most frequent hereditary ischemic small vessel disease of the brain. Relevant biomarkers or specific metabolic signatures could provide powerful tools to manage these diseases. Therefore, the main goal of this study was to compare the postmortem frontal cortex gray matter, white matter and cerebrospinal fluid (CSF) between a cognitively healthy group and CADASIL and SAD groups. We evaluated 352 individual lipids, belonging to 13 lipid classes/subclasses, using mass spectrometry, and the lipid profiles were subjected to multivariate analysis to discriminate between the dementia groups (CADASIL and SAD) and healthy controls. The main lipid molecular species showing greater discrimination by partial least squares-discriminant analysis (PLS-DA) and a higher significance multivariate correlation (sMC) index were as follows: phosphatidylserine (PS) PS(44:7) and lysophosphatidylethanolamine (LPE) LPE(18:2) in gray matter (GM); phosphatidylethanolamine (PE) PE(32:2) and phosphatidylcholine PC PC(44:6) in white matter (WM), and ether PE (ePE) ePE(38:2) and ether PC (ePC) ePC(34:3) in CSF. Common phospholipid molecular species were obtained in both dementias, such as PS(44:7) and lyso PC (LPC) LPC(22:5) in GM, PE(32:2) in WM and phosphatidic acid (PA) PA(38:5) and PC(42:7) in CFS. Our exploratory study suggests that phospholipids (PLs) involved in neurotransmission alteration, connectivity impairment and inflammation response in GM, WM and CSF are a transversal phenomenon affecting dementias such as CADASIL and SAD independent of the etiopathogenesis, thus providing a possible common prodromal phospholipidic biomarker of dementia.

Perspectives in fluid biomarkers in neurodegeneration from the 2019 biomarkers in neurodegenerative diseases course-a joint PhD student course at University College London and University of Gothenburg

Until relatively recently, a diagnosis of probable Alzheimer's disease (AD) and other neurodegenerative disorders was principally based on clinical presentation, with post-mortem examination remaining a gold standard for disease confirmation. This is in sharp contrast to other areas of medicine, where fluid biomarkers, such as troponin levels in myocardial infarction, form an integral part of the diagnostic and treatment criteria. There is a pressing need for such quantifiable and easily accessible tools in neurodegenerative diseases.In this paper, based on lectures given at the 2019 Biomarkers in Neurodegenerative Diseases Course, we provide an overview of a range of cerebrospinal fluid (CSF) and blood biomarkers in neurodegenerative disorders, including the 'core' AD biomarkers amyloid β (Aβ) and tau, as well as other disease-specific and general markers of neuroaxonal injury. We then highlight the main challenges in the field, and how those could be overcome with the aid of new methodological advances, such as assay automation, mass spectrometry and ultrasensitive immunoassays.As we hopefully move towards an era of disease-modifying treatments, reliable biomarkers will be essential to increase diagnostic accuracy, allow for earlier diagnosis, better participant selection and disease activity and treatment effect monitoring.

Evidence in support of chromosomal sex influencing plasma based metabolome vs APOE genotype influencing brain metabolome profile in humanized APOE male and female mice

Late onset Alzheimer’s disease (LOAD) is a progressive neurodegenerative disease with four well-established risk factors: age, APOE4 genotype, female chromosomal sex, and maternal history of AD. Each risk factor impacts multiple systems, making LOAD a complex systems biology challenge. To investigate interactions between LOAD risk factors, we performed multiple scale analyses, including metabolomics, transcriptomics, brain magnetic resonance imaging (MRI), and beta-amyloid assessment, in 16 months old male and female mice with humanized human APOE3 (hAPOE3) or APOE4 (hAPOE4) genes. Metabolomic analyses indicated a sex difference in plasma profile whereas APOE genotype determined brain metabolic profile. Consistent with the brain metabolome, gene and pathway-based RNA-Seq analyses of the hippocampus indicated increased expression of fatty acid/lipid metabolism related genes and pathways in both hAPOE4 males and females. Further, female transcription of fatty acid and amino acids pathways were significantly different from males. MRI based imaging analyses indicated that in multiple white matter tracts, hAPOE4 males and females exhibited lower fractional anisotropy than their hAPOE3 counterparts, suggesting a lower level of white matter integrity in hAPOE4 mice. Consistent with the brain metabolomic and transcriptomic profile of hAPOE4 carriers, beta-amyloid generation was detectable in 16-month-old male and female brains. These data provide therapeutic targets based on chromosomal sex and APOE genotype. Collectively, these data provide a framework for developing precision medicine interventions during the prodromal phase of LOAD, when the potential to reverse, prevent and delay LOAD progression is greatest.

The Differences of Serum Metabolites Between Patients With Early-Stage Alzheimer's Disease and Mild Cognitive Impairment

Background: Mild cognitive impairment (MCI) is regarded as a transition phase between normal aging and Alzheimer's disease (AD). Identification of novel and non-invasive biomarkers that can distinguish AD at an early stage from MCI is warranted for therapeutic and support planning. The goal of this study was to identify the differences of serum metabolomic profiles between MCI and early-stage AD, which could be potential non-invasive biomarkers for early diagnosis of AD.

Methods: The subjects enrolled in the study were classified into two diagnostic groups: MCI (n = 40) and early-stage AD (n = 40). Targeted metabolomics analysis of serum samples was performed using the Biocrates Absolute-IDQ P180 kit. Targeted metabolic data were analyzed by TargetLynx, and MetIDQ software was applied to integrate the metabolites by automated calculation of metabolite concentrations.

Results: The datasets of targeted metabolite analysis were analyzed by the orthogonal-projection-to-latent-structure–discriminant-analysis (OPLS-DA) model. The OPLS-DA score plots demonstrated considerable separation between the MCI and early-stage AD patients. The levels of pimelylcarnitine, putrescine, SM (OH) C24:1, and SM C24:0 were significantly lower, whereas the levels of acetylornithine, methionine sulfoxide, and PC ae C44:3 were significantly higher in early-stage AD patients as compared with MCI patients. Receiver operating characteristic curve analysis of a combination of three lipid metabolites [SM (OH) C24:1, SM C24:0, and PC ae C44:3] showed an acceptable discrimination between the early-stage AD and MCI patients (area under the curve = 0.788).

Conclusions: Our results characterized the differences of serum metabolic profiles between MCI and early-stage AD patients. The positive findings from this study indicate that the minimally invasive method of blood sampling may help to identify patients with AD at an early stage from those with MCI.

Bile acids targeted metabolomics and medication classification data in the ADNI1 and ADNIGO/2 cohorts

Alzheimer's disease (AD) is the most common cause of dementia. The mechanism of disease development and progression is not well understood, but increasing evidence suggests multifactorial etiology, with a number of genetic, environmental, and aging-related factors. There is a growing body of evidence that metabolic defects may contribute to this complex disease. To interrogate the relationship between system level metabolites and disease susceptibility and progression, the AD Metabolomics Consortium (ADMC) in partnership with AD Neuroimaging Initiative (ADNI) is creating a comprehensive biochemical database for patients in the ADNI1 cohort. We used the Biocrates Bile Acids platform to evaluate the association of metabolic levels with disease risk and progression. We detail the quantitative metabolomics data generated on the baseline samples from ADNI1 and ADNIGO/2 (370 cognitively normal, 887 mild cognitive impairment, and 305 AD). Similar to our previous reports on ADNI1, we present the tools for data quality control and initial analysis. This data descriptor represents the third in a series of comprehensive metabolomics datasets from the ADMC on the ADNI.

Validation and Application of Biocrates AbsoluteIDQ® p180 Targeted Metabolomics Kit Using Human Milk

Human-milk-targeted metabolomics analysis offers novel insights into milk composition and relationships with maternal and infant phenotypes and nutritional status. The Biocrates AbsoluteIDQ® p180 kit, targeting 40 acylcarnitines, 42 amino acids/biogenic amines, 91 phospholipids, 15 sphingolipids, and sum of hexoses, was evaluated for human milk using the AB Sciex 5500 QTRAP mass-spectrometer in liquid chromatography-tandem mass-spectrometry (LC-MS/MS) and flow-injection analysis (FIA) mode. Milk (<6 months lactation) from (A) Bangladeshi apparently healthy mothers (body mass index (BMI) > 18.5; n = 12) and (B) Bangladeshi mothers of stunted infants (height-for-age Z (HAZ)-score <-2; n = 13) was analyzed. Overall, 123 of the possible 188 metabolites were detected in milk. New internal standards and adjusted calibrator levels were used for improved precision and concentration ranges for milk metabolites. Recoveries ranged between 43% and 120% (coefficient of variation (CV): 2.4%-24.1%, 6 replicates). Milk consumed by stunted infants vs. that from mothers with BMI > 18.5 was lower in 6 amino acids/biogenic amines but higher in isovalerylcarnitine, two phospholipids, and one sphingomyelin (p < 0.05 for all). Associations between milk metabolites differed between groups. The AbsoluteIDQ® p180 kit is a rapid analysis tool suitable for human milk analysis and reduces analytical bias by allowing the same technique for different specimens. More research is needed to examine milk metabolite relationships with maternal and infant phenotypes.

Novel serum metabolites associate with cognition phenotypes among Bogalusa Heart Study participants

BACKGROUND

Metabolomics study provides an opportunity to identify novel molecular determinants of altered cognitive function.

METHODS

During 2013 to 2016 Bogalusa Heart Study (BHS) visit, 1,177 participants underwent untargeted, ultrahigh performance liquid chromatography-tandem mass spectroscopy metabolomics profiling. Global cognition and five cognition domains were also assessed. The cross-sectional associations of single metabolites with cognition were tested using multiple linear regression models. Weighted correlation network analysis was used to examine the covariable-adjusted correlations of modules of co-abundant metabolites with cognition. Analyses were conducted in the overall sample and according to both ethnicity and sex.

RESULTS

Five known metabolites and two metabolite modules robustly associated with cognition across overall and stratified analyses. Two metabolites were from lipid sub-pathways including fatty acid metabolism [9-hydroxystearate; minimum P-value (min-P)=1.11×10-5], and primary bile acid metabolism (glyco-alpha-muricholate; min-P=4.10×10-5). One metabolite from the glycogen metabolism sub-pathway (maltose; min-P=9.77×10-6), one from the polyamine metabolism sub-pathway (N-acetyl-isoputreanine; min-P=1.03×10-5), and one from the purine metabolism sub-pathway (7-methylguanine; min-P=1.19×10-5) were also identified. Two metabolite modules reflecting bile acid metabolism and androgenic steroids correlated with cognition (min-P=5.00×10-4 and 3.00×10-3, respectively).

CONCLUSION

The novel associations of 5 known metabolites and 2 metabolite modules with cognition provide insights into the physiological mechanisms regulating cognitive function.

Longitudinal association between phosphatidylcholines, neuroimaging measures of Alzheimer's disease pathophysiology, and cognition in the Mayo Clinic Study of Aging

Plasma phosphatidylcholines (PCs) have been examined in the context of Alzheimer's disease dementia. However, their association with longitudinal changes in amyloid deposition remains unknown. This study investigated the associations of 8 plasma PC levels (PC aa [14:0_14:0], PC aa [16:0_16:0], PC aa [16:0_18:2], PC aa [16:0_22:6], PC aa [18:0_18:0], PC aa [18:0_18:1], PC aa [18:0_20:4], PC aa [18:1_18:1]) with cross-sectional and longitudinal measures of amyloid deposition, Alzheimer's disease-associated neurodegeneration (glucose metabolism and cortical thickness), and cognition (global- and domain-specific) of 1440 cognitively unimpaired participants (47% female, aged 50.7-95.3 years) in the Mayo Clinic Study of Aging. Longitudinally, higher baseline levels of PC aa [16:0_18:2], PC aa [18:0_18:1], and PC aa [18:1_18:1] were associated with slower decline in performance on tests of global cognition and specific cognitive domains. Furthermore, higher baseline levels of plasma PC aa (14:0_14:0) were associated with slower amyloid deposition and cortical thinning after multiple covariable adjustment (age, sex, education, medical comorbidity, dyslipidemia, statin use, and APOE4 allele presence). Our study findings support an independent association between plasma PC aa (14:0_14:0) with slower amyloid deposition and cortical thinning among cognitively unimpaired older adults.

Childhood growth and neurocognition are associated with distinct sets of metabolites

BACKGROUND

Undernutrition is a serious global problem that contributes to increased child morbidity and mortality, impaired neurocognitive development, and decreased educational and economic attainment. Current interventions are only marginally effective, and identification of associated metabolic pathways can offer new strategies for intervention.

METHODS

Plasma samples were collected at 9 and 36 months from a subset of the PROVIDE child cohort (n = 130). Targeted metabolomics was performed on bile acids, acylcarnitines, amino acids, phosphatidylcholines, and sphingomyelins. Metabolic associations with linear growth and neurocognitive outcomes at four years were evaluated using correlation and penalized-linear regression analysis as well as conditional random forest modeling.

FINDINGS

Different metabolites were associated with growth and neurocognitive outcomes. Improved growth outcomes were associated with higher concentrations of hydroxy-sphingomyelin and essential amino acids and lower levels of acylcarnitines and bile acid conjugation. Neurocognitive scores were largely associated with phosphatidylcholine species and early metabolic indicators of inflammation. All metabolites identified explain ~45% of growth and neurocognitive variation.

INTERPRETATION

Growth outcomes were predominantly associated with metabolites measured early in life (9 months), many of which were biomarkers of insufficient diet, environmental enteric dysfunction, and microbiome disruption. Hydroxy-sphingomyelin was a significant predictor of improved growth. Neurocognitive outcome was predominantly associated with 36 month phosphatidylcholines and inflammatory metabolites, which may serve as important biomarkers of optimal neurodevelopment. The distinct sets of metabolites associated with growth and neurocognition suggest that intervention may require targeted approaches towards distinct metabolic pathways. FUND: Bill & Melinda Gates Foundation (OP1173478); National Institutes of Health (AI043596, CA044579).

[Neuroprotectors in the correction of cognitive impairment]

The main groups of neuroprotectors, which are active in preventing the processes of the death of the nerve cells of vascular, traumatic, toxic and other etiologies and can decrease the severity of cognitive impairment, include phosphatidylcholine, phosphatidylserine, preparations based on ginkgo biloba, group B vitamins, folic acid. Preparations based on ginkgo biloba have the same effect as synthetic nootropics. The antioxidant and membrane-stabilizing effects of neuroprotectors are highlighted. In view of practical applications, attention is given to the advantages of the combinations of different neuroprotectors. Cerebrovin as one of these drugs can be recommended for treatment of cognitive impairment in the elderly.

An Updated Review of Lysophosphatidylcholine Metabolism in Human Diseases

Lysophosphatidylcholine (LPC) is increasingly recognized as a key marker/factor positively associated with cardiovascular and neurodegenerative diseases. However, findings from recent clinical lipidomic studies of LPC have been controversial. A key issue is the complexity of the enzymatic cascade involved in LPC metabolism. Here, we address the coordination of these enzymes and the derangement that may disrupt LPC homeostasis, leading to metabolic disorders. LPC is mainly derived from the turnover of phosphatidylcholine (PC) in the circulation by phospholipase A₂ (PLA₂). In the presence of Acyl-CoA, lysophosphatidylcholine acyltransferase (LPCAT) converts LPC to PC, which rapidly gets recycled by the Lands cycle. However, overexpression or enhanced activity of PLA₂ increases the LPC content in modified low-density lipoprotein (LDL) and oxidized LDL, which play significant roles in the development of atherosclerotic plaques and endothelial dysfunction. The intracellular enzyme LPCAT cannot directly remove LPC from circulation. Hydrolysis of LPC by autotaxin, an enzyme with lysophospholipase D activity, generates lysophosphatidic acid, which is highly associated with cancers. Although enzymes with lysophospholipase A₁ activity could theoretically degrade LPC into harmless metabolites, they have not been found in the circulation. In conclusion, understanding enzyme kinetics and LPC metabolism may help identify novel therapeutic targets in LPC-associated diseases.

Alterations in the Plasma Levels of Specific Choline Phospholipids in Alzheimer's Disease Mimic Accelerated Aging

Alzheimer’s disease (AD) is the most common neurodegenerative disease and of continuously rising prevalence. The identification of easy-to-measure biomarkers capable to assist in the prediction and early diagnosis of AD is currently a main research goal. Lipid metabolites in peripheral blood of human patients have recently gained major attention in this respect. Here, we analyzed plasma of 174 participants (not demented at baseline; mean age: 75.70±0.44 years) of the Vienna Transdanube Aging (VITA) study, a longitudinal, population-based birth cohort study, at baseline and after 90 months or at diagnosis of probable AD. We determined the levels of specific choline phospholipids, some of which have been suggested as potential biomarkers for the prediction of AD. Our results show that during normal aging the levels of lysophosphatidylcholine, choline plasmalogen, and lyso-platelet activating factor increase significantly. Notably, we observed similar but more pronounced changes in the group that developed probable AD. Thus, our results imply that, in terms of choline-containing plasma phospholipids, the conversion to AD mimics an accelerated aging process. We conclude that age, even in the comparatively short time frame between 75 and 82.5 years, is a crucial factor in the quest for plasma lipid biomarkers for AD that must be carefully considered in future studies and trials.

Can targeted metabolomics predict depression recovery? Results from the CO-MED trial

Metabolomics is a developing and promising tool for exploring molecular pathways underlying symptoms of depression and predicting depression recovery. The AbsoluteIDQ™ p180 kit was used to investigate whether plasma metabolites (sphingomyelins, lysophosphatidylcholines, phosphatidylcholines, and acylcarnitines) from a subset of participants in the Combining Medications to Enhance Depression Outcomes (CO-MED) trial could act as predictors or biologic correlates of depression recovery. Participants in this trial were assigned to one of three pharmacological treatment arms: escitalopram monotherapy, bupropion-escitalopram combination, or venlafaxine-mirtazapine combination. Plasma was collected at baseline in 159 participants and again 12 weeks later at study exit in 83 of these participants. Metabolite concentrations were measured and combined with clinical and sociodemographic variables using the hierarchical lasso to simultaneously model whether specific metabolites are particularly informative of depressive recovery. Increased baseline concentrations of phosphatidylcholine C38:1 showed poorer outcome based on change in the Quick Inventory of Depressive Symptoms (QIDS). In contrast, an increased ratio of hydroxylated sphingomyelins relative to non-hydroxylated sphingomyelins at baseline and a change from baseline to exit suggested a better reduction of symptoms as measured by QIDS score. All metabolite-based models performed superior to models only using clinical and sociodemographic variables, suggesting that metabolomics may be a valuable tool for predicting antidepressant outcomes.

Omics-based Biomarkers for the Early Alzheimer Disease Diagnosis and Reliable Therapeutic Targets Development

BACKGROUND

Alzheimer's disease (AD), the most common cause of dementia in adulthood, has great medical, social, and economic impact worldwide. Available treatments result in symptomatic relief, and most of them are indicated from the early stages of the disease. Therefore, there is an increasing body of research developing accurate and early diagnoses, as well as diseasemodifying therapies.

OBJECTIVE

Advancing the knowledge of AD physiopathological mechanisms, improving early diagnosis and developing effective treatments from omics-based biomarkers.

METHODS

Studies using omics technologies to detect early AD, were reviewed with a particular focus on the metabolites/lipids, micro-RNAs and proteins, which are identified as potential biomarkers in non-invasive samples.

RESULTS

This review summarizes recent research on metabolomics/lipidomics, epigenomics and proteomics, applied to early AD detection. Main research lines are the study of metabolites from pathways, such as lipid, amino acid and neurotransmitter metabolisms, cholesterol biosynthesis, and Krebs and urea cycles. In addition, some microRNAs and proteins (microglobulins, interleukins), related to a common network with amyloid precursor protein and tau, have been also identified as potential biomarkers. Nevertheless, the reproducibility of results among studies is not good enough and a standard methodological approach is needed in order to obtain accurate information.

CONCLUSION

The assessment of metabolomic/lipidomic, epigenomic and proteomic changes associated with AD to identify early biomarkers in non-invasive samples from well-defined participants groups will potentially allow the advancement in the early diagnosis and improvement of therapeutic interventions.

Dynamic Monitoring of the Oxidation Process of Phosphatidylcholine Using SERS Analysis

Phosphatidylcholine oxidation is closely related to many neurodegenerative diseases. In this paper, Raman spectroscopy was proposed to continuously monitor the oxidation of phosphatidylcholine and provide deep understanding of this biochemical process. To increase the detection sensitivity, surface-enhanced Raman spectroscopy (SERS) with a micro-nanosilver-complex substrate was prepared by electrodeposition. The prepared SERS substrate had an enhancement factor as high as 7.8 × 10⁷, ensuring detection sensitivity in the phosphatidylcholine-oxidation process. It was illustrated that the oxidation of phosphatidylcholine in an ethanol-water solution under the experimental conditions could be monitored and well described by second-order kinetics by continuously measuring and analyzing the SERS spectra of phosphatidylcholine-oxidation intermediates in 20 days. Meanwhile, the oxidation products were confirmed by mass spectrometry, and the oxidation process was in good concordance with mass-spectrometry detection. The use of SERS in following a biochemical process has advantages, including simple instrumentation, a low cost, a short detection time, and no sample pretreatment. Therefore, as a kind of vibration spectrum, SERS is preferable to traditional detection approaches such as MS, HPLC, and MRI for the dynamic monitoring and analysis of complex biochemical processes.

High-Throughput Direct Mass Spectrometry-Based Metabolomics to Characterize Metabolite Fingerprints Associated with Alzheimer's Disease Pathogenesis

Direct mass spectrometry-based metabolomics has been widely employed in recent years to characterize the metabolic alterations underlying Alzheimer's disease development and progression. This high-throughput approach presents great potential for fast and simultaneous fingerprinting of a vast number of metabolites, which can be applied to multiple biological matrices including serum/plasma, urine, cerebrospinal fluid and tissues. In this review article, we present the main advantages and drawbacks of metabolomics based on direct mass spectrometry compared with conventional analytical techniques, and provide a comprehensive revision of the literature on the use of these tools in the investigation of Alzheimer's disease.

Potential Metabolomic Linkage in Blood between Parkinson's Disease and Traumatic Brain Injury

The etiologic basis for sporadic forms of neurodegenerative diseases has been elusive but likely represents the product of genetic predisposition and various environmental factors. Specific gene-environment interactions have become more salient owing, in part, to the elucidation of epigenetic mechanisms and their impact on health and disease. The linkage between traumatic brain injury (TBI) and Parkinson's disease (PD) is one such association that currently lacks a mechanistic basis. Herein, we present preliminary blood-based metabolomic evidence in support of potential association between TBI and PD. Using untargeted and targeted high-performance liquid chromatography-mass spectrometry we identified metabolomic biomarker profiles in a cohort of symptomatic mild TBI (mTBI) subjects (n = 75) 3⁻12 months following injury (subacute) and TBI controls (n = 20), and a PD cohort with known PD (n = 20) or PD dementia (PDD) (n = 20) and PD controls (n = 20). Surprisingly, blood glutamic acid levels in both the subacute mTBI (increased) and PD/PDD (decreased) groups were notably altered from control levels. The observed changes in blood glutamic acid levels in mTBI and PD/PDD are discussed in relation to other metabolite profiling studies. Should our preliminary results be replicated in comparable metabolomic investigations of TBI and PD cohorts, they may contribute to an "excitotoxic" linkage between TBI and PD/PDD.

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.

LPCAT1 controls phosphate homeostasis in a zinc-dependent manner

All living organisms require a variety of essential elements for their basic biological functions. While the homeostasis of nutrients is highly intertwined, the molecular and genetic mechanisms of these dependencies remain poorly understood. Here, we report a discovery of a molecular pathway that controls phosphate (Pi) accumulation in plants under Zn deficiency. Using genome-wide association studies, we first identified allelic variation of the Lyso-PhosphatidylCholine (PC) AcylTransferase 1 (LPCAT1) gene as the key determinant of shoot Pi accumulation under Zn deficiency. We then show that regulatory variation at the LPCAT1 locus contributes significantly to this natural variation and we further demonstrate that the regulation of LPCAT1 expression involves bZIP23 TF, for which we identified a new binding site sequence. Finally, we show that in Zn deficient conditions loss of function of LPCAT1 increases the phospholipid Lyso-PhosphatidylCholine/PhosphatidylCholine ratio, the expression of the Pi transporter PHT1;1, and that this leads to shoot Pi accumulation.

LPCAT1 controls phosphate homeostasis in a zinc-dependent manner

All living organisms require a variety of essential elements for their basic biological functions. While the homeostasis of nutrients is highly intertwined, the molecular and genetic mechanisms of these dependencies remain poorly understood. Here, we report a discovery of a molecular pathway that controls phosphate (Pi) accumulation in plants under Zn deficiency. Using genome-wide association studies, we first identified allelic variation of the Lyso-PhosphatidylCholine (PC) AcylTransferase 1 (LPCAT1) gene as the key determinant of shoot Pi accumulation under Zn deficiency. We then show that regulatory variation at the LPCAT1 locus contributes significantly to this natural variation and we further demonstrate that the regulation of LPCAT1 expression involves bZIP23 TF, for which we identified a new binding site sequence. Finally, we show that in Zn deficient conditions loss of function of LPCAT1 increases the phospholipid Lyso-PhosphatidylCholine/PhosphatidylCholine ratio, the expression of the Pi transporter PHT1;1, and that this leads to shoot Pi accumulation.

Metabolomics analysis of multidrug-resistant breast cancer cellsin vitrousing methyl-tert-butyl ether method

MTBE-based cellular lipidomics to investigate the mechanisms of multidrug resistance of breast cancer.