Serum fatty acid profiles using GC-MS and multivariate statistical analysis: potential biomarkers of Alzheimer's disease

Serum metabolome profiling in patients with mild cognitive impairment reveals sex differences in lipid metabolism

Alzheimer's disease (AD) affects more women than men. Although women live longer than men, it is not longevity alone, but other factors, including metabolic changes, that contribute to the higher risk of AD in women. Metabolic pathways have been implicated in AD progression, but studies to date examined targeted pathways, leaving many metabolites unmeasured. Sex is often a neglected biological variable, and most metabolomic studies were not designed to investigate sex differences in metabolomic profiles. Here, we performed untargeted metabolomic profiling of sera from male and female patients with mild cognitive impairment (MCI), a common precursor to AD, and matched controls. We discovered significant metabolic changes in individuals with MCI, and found several pathways that were strongly associated with sex. Peptide energy metabolism demonstrated sexual dimorphism. Lipid pathways exhibited the strongest differences between female and male MCI patients, including specific phosphatidylcholine lipids, lysophospholipids, long-chain fatty acids, and monoacylglycerols. 1-palmitoleoyl glycerol and 1-arachidonoyl glycerol were higher in female MCI subjects than in male MCI subjects with no differences between control males and females. Conversely, specific dicarboxylic fatty acids were lower in female MCI subjects than male MCI subjects. In cultured astrocytes, 1-arachidonoyl glycerol promoted phosphorylation of the transcriptional regulator sphingosine kinase 2, which was inhibited by the transient receptor potential vanilloid 1 receptor antagonists, as well as chromatin remodelling. Overall, we identified novel sex-specific metabolites in MCI patients that could serve as biomarkers of MCI in both sexes, help further define AD etiology, and reveal new potential prevention strategies for AD.

Serum metabolome profiling in patients with mild cognitive impairment reveals sex differences in lipid metabolism

Alzheimer's disease (AD) affects more women than men. Although women live longer than men, it is not longevity alone, but other factors, including metabolic changes, that contribute to the higher risk of AD in women. Metabolic pathways have been implicated in AD progression, but studies to date examined targeted pathways, leaving many metabolites unmeasured. Sex is often a neglected biological variable, and most metabolomic studies were not designed to investigate sex differences in metabolomic profiles. Here, we performed untargeted metabolomic profiling of sera from male and female patients with mild cognitive impairment (MCI), a common precursor to AD, and matched controls. We discovered significant metabolic changes in individuals with MCI, and found several pathways that were strongly associated with sex. Peptide energy metabolism demonstrated sexual dimorphism. Lipid pathways exhibited the strongest differences between female and male MCI patients, including specific phosphatidylcholine lipids, lysophospholipids, long-chain fatty acids, and monoacylglycerols. 1-palmitoleoyl glycerol and 1-arachidonoyl glycerol were higher in female MCI subjects than in male MCI subjects with no differences between control males and females. Conversely, specific dicarboxylic fatty acids were lower in female MCI subjects than male MCI subjects. In cultured astrocytes, 1-arachidonoyl glycerol promoted phosphorylation of the transcriptional regulator sphingosine kinase 2, which was inhibited by the transient receptor potential vanilloid 1 receptor antagonists, as well as chromatin remodelling. Overall, we identified novel sex-specific metabolites in MCI patients that could serve as biomarkers of MCI in both sexes, help further define AD etiology, and reveal new potential prevention strategies for AD.

The effects of APOE4 and familial Alzheimer's disease mutations on free fatty acid profiles in mouse brain are age- and sex-dependent

APOE4 encoding apolipoprotein (Apo)E4 is the strongest genetic risk factor for Alzheimer's disease (AD). ApoE is key in intercellular lipid trafficking. Fatty acids are essential for brain integrity and cognitive performance and are implicated in neurodegeneration. We determined the sex- and age-dependent effect of AD and APOE4 on brain free fatty acid (FFA) profiles. FFA profiles were determined by LC-MS/MS in hippocampus, cortex, and cerebellum of female and male, young (≤3 months) and older (>5 months), transgenic APOE3 and APOE4 mice with and without five familial AD (FAD) mutations (16 groups; n = 7-10 each). In the different brain regions, females had higher levels than males of either saturated or polyunsaturated FFAs or both. In the hippocampus of young males, but not of older males, APOE4 and FAD each induced 1.3-fold higher levels of almost all FFAs. In young and older females, FAD and to a less extent APOE4-induced shifts among saturated, monounsaturated, and polyunsaturated FFAs without affecting total FFA levels. In cortex and cerebellum, APOE4 and FAD had only minor effects on individual FFAs. The effects of APOE4 and FAD on FFA levels and FFA profiles in the three brain regions were strongly dependent of sex and age, particularly in the hippocampus. Here, most FFAs that are affected by FAD are similarly affected by APOE4. Since APOE4 and FAD affected hippocampal FFA profiles already at young age, these APOE4-induced alterations may modulate the pathogenesis of AD.

Metabolomic Applications in Gut Microbiota-Host Interactions in Human Diseases

The human gut microbiota, consisting of trillions of microorganisms, encodes diverse metabolic pathways that impact numerous aspects of host physiology. One key way in which gut bacteria interact with the host is through the production of small metabolites. Several of these microbiota-dependent metabolites, such as short-chain fatty acids, have been shown to modulate host diseases. In this review, we examine how disease-associated metabolic signatures are identified using metabolomic platforms, and where metabolomics is applied in gut microbiota-disease interactions. We further explore how integration of metagenomic and metabolomic data in human studies can facilitate biomarkers discoveries in precision medicine.

Plasma lipidomics in early APP/PS1 female mouse model and its relationship with brain: Is it affected by the estrous cycle?

BACKGROUND

Alzheimer's disease (AD) is the most prevalent dementia, showing higher incidence in women. Besides, lipids play an essential role in brain, and they could be dysregulated in neurodegeneration. Specifically, impaired plasma lipid levels could predict early AD diagnosis. This work aims to identify the main plasma lipids altered in early AD female mouse model and evaluate their relationship with brain lipidome. Also, the possible involvement of the estrous cycle in lipid metabolism has been evaluated.

METHODS

Plasma samples of wild-type (n = 10) and APP/PS1 (n = 10) female mice of 5 months of age were collected, processed, and analysed using a lipidomic mass spectrometry-based method. A statistical analysis involving univariate and multivariate approaches was performed to identify significant lipid differences related to AD between groups. Also, cytology tests were conducted to confirm estrous cycle phases.

RESULTS

Three hundred thirty lipids were detected in plasma, 18 of them showed significant differences between groups; specifically, some triacylglycerols, cholesteryl esters, lysophosphatidylcholines, phosphatidylcholines, and ether-linked phosphatidylcholines, increased in early AD; while other phosphatidylcholines, phosphatidylethanolamines, ceramides, and ether-linked phosphatidylethanolamines decreased in early AD. A multivariate approach was developed from some lipid variables, showing high diagnostic indexes (70% sensitivity, 90% specificity, 80% accuracy). From brain and plasma lipidome, some significant correlations were observed, mainly in the glycerophospholipid family. Also, some differences were found in both plasma and brain lipids, according to the estrous cycle phase.

CONCLUSIONS

Therefore, lipid alterations can be identified in plasma at early AD stages in mice females, with a relationship with brain lipid metabolism for most of the lipid subfamilies, suggesting some lipids as potential AD biomarkers. In addition, the estrous cycle monitoring could be relevant in female studies.

Impact of internal standard selection on measurement results for long chain fatty acids in blood

Introduction

Internal standards correct for measurement variation due to sample loss. Isotope labeled analytes are ideal internal standards for the measurement of fatty acids in human plasma but are not always readily available. For this reason, quantification of multiple analytes at once is most often done using only a single or few internal standards. The magnitude of the impact this has on method accuracy and precision is not well studied for gas chromatography-mass spectrometry systems.

Objective

This study aims to estimate bias and changes in uncertainty associated with using alternative fatty acid isotopologue internal standards for the estimation of similar or dissimilar long chain fatty acids.

Method

Using a previously reported method for the quantification of 27 fatty acids in human plasma using 18 internal standards we obtained estimates of bias and uncertainty at up to three levels of fatty acid concentration.

Results

With some notable exceptions, method accuracy remained relatively stable when using an alternative internal standard (Median Relative Absolute Percent Bias: 1.76%, Median Spike-Recovery Absolute Percent Bias: 8.82%), with larger changes in method precision (Median Increase in Variance: 141%). Additionally, the degree of difference between analyte and internal standard structure was related to the magnitude of bias and uncertainty of the measurement.

Conclusion

The data presented here show that the choice of internal standard used to estimate fatty acid concentration can affect the accuracy and reliability of measurement results and, therefore, needs to be assessed carefully when developing analytical methods for the measurement of fatty acid profiles.Disclaimer: The findings and conclusions in this report are those of the author(s) and do not necessarily represent the official position of the Centers for Disease Control and Prevention/the Agency for Toxic Substances and Disease Registry. Use of trade names is for identification only and does not imply endorsement by the Centers for Disease Control and Prevention, the Public Health Service, and the US Department of Health and Human Services.

Curcumin and omega-3 polyunsaturated fatty acids as bioactive food components with synergistic effects on Alzheimer's disease

Curcumin and omega-3 polyunsaturated fatty acids (ω-3 PUFA) are multifunctional compounds which play an important role in Alzheimer's disease (AD) and little has been addressed about the role of these two compounds together in the progression of the disease. There is evidence of the beneficial effect of combined administration of ω-3 PUFA and other dietary supplements such as vitamins and polyphenols in the prevention of AD, although much remains to be understood about their possible complementary or synergistic activity. Therefore, the objective of this work is to review the research focused on studying the effect and mechanisms of action of curcumin, ω-3 PUFA, and the combination of these nutraceutical compounds, particularly on AD, and to integrate the possible ways in which these compounds can potentiate their effect. The most important pathophysiologies that manifest in AD will be addressed, in order to have a better understanding of the mechanisms of action through which these bioactive compounds exert a neuroprotective effect.

The shift in the fatty acid composition of the circulating lipidome in Alzheimer's disease

INTRODUCTION

Fatty acids (FAs) are the building blocks of complex lipids and signaling compounds; the role of the lipidome fatty acid profile (LFA) in AD progression remains unclear.

METHODS

The LFA of plasma and cerebrospinal fluid (CSF) samples from 289 participants (103 AD patients, 92 MCI patients, and 94 controls) was determined by GC-FID. The MCI subjects were followed up for 58 ± 12.5 months.

RESULTS

In controls, CSF has a more neuroprotective LFA than plasma. In CSF, a higher content of docosahexaenoic acid was associated with a reduced risk of MCI-to-AD progression. In plasma, higher oleic acid content was associated with lower risk of AD, MCI, and MCI-to-AD progression, whereas higher levels of vaccenic acid and docosahexaenoic acid were associated with greater risk of AD and MCI, and higher rate of MCI-to-AD progression, respectively.

DISCUSSION

The circulating LFA is involved in the pathogenesis and progression of AD.

HIGHLIGHTS

The lipidome fatty acid profile in CSF and plasma was markedly different. Higher levels of vaccenic acid and lower levels of oleic acid in plasma were associated with greater risk of Alzheimer's disease. In plasma, higher levels of oleic acid were associated with a reduced risk of MCI-to-AD progression. Higher levels of docosahexaenoic acid in CSF were associated with a lower risk of MCI-to-AD progression. Higher levels of docosahexaenoic acid in plasma were associated with a greater rate of MCI-to-AD progression.

A Novel Score to Predict Individual Risk for Future Alzheimer's Disease: A Longitudinal Study of the ADNI Cohort

Background

Identifying high-risk individuals with mild cognitive impairment (MCI) who are likely to progress to Alzheimer's disease (AD) is crucial for early intervention.

Objective

This study aimed to develop and validate a novel clinical score for personalized estimation of MCI-to-AD conversion.

Methods

The data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study were analyzed. Two-thirds of the MCI patients were randomly assigned to a training cohort (n = 478), and the remaining one-third formed the validation cohort (n = 239). Multivariable logistic regression was performed to identify factors associated with MCI-to-AD progression within 4 years. A prediction score was developed based on the regression coefficients derived from the logistic model and tested in the validation cohort.

Results

A lipidomics-signature was obtained that showed a significant association with disease progression. The MCI conversion scoring system (ranged from 0 to 14 points), consisting of the lipidomics-signature and five other significant variables (Apolipoprotein ɛ4, Rey Auditory Verbal Learning Test immediate and delayed recall, Alzheimer's Disease Assessment Scale delayed recall test, Functional Activities Questionnaire, and cortical thickness of the AD signature), was constructed. Higher conversion scores were associated with a higher proportion of patients converting to AD. The scoring system demonstrated good discrimination and calibration in both the training cohort (AUC = 0.879, p of Hosmer-Lemeshow test = 0.597) and the validation cohort (AUC = 0.915, p of Hosmer-Lemeshow test = 0.991). The risk classification achieved excellent sensitivity (0.84) and specificity (0.75).

Conclusions

The MCI-to-AD conversion score is a reliable tool for predicting the risk of disease progression in individuals with MCI.

Metabolic profiling of Alzheimer's disease: Untargeted metabolomics analysis of plasma samples

Alzheimer's disease (AD) is often not recognized or is diagnosed very late, which significantly reduces the effectiveness of available pharmacological treatments. Metabolomic analyzes have great potential for improving existing knowledge about the pathogenesis and etiology of AD and represent a novel approach towards discovering biomarkers that could be used for diagnosis, prognosis, and therapy monitoring. In this study, we applied the untargeted metabolomic approach to investigate the changes in biochemical pathways related to AD pathology. We used gas chromatography and liquid chromatography coupled to mass spectrometry (GC-MS and LC-MS, respectively) to identify metabolites whose levels have changed in subjects with AD diagnosis (N = 40) compared to healthy controls (N = 40) and individuals with mild cognitive impairment (MCI, N = 40). The GC-MS identified significant differences between groups in levels of metabolites belonging to the classes of benzene and substituted derivatives, carboxylic acids and derivatives, fatty acyls, hydroxy acids and derivatives, keto acids and derivatives, and organooxygen compounds. Most of the compounds identified by the LC-MS were various fatty acyls, glycerolipids and glycerophospholipids. All of these compounds were decreased in AD patients and in subjects with MCI compared to healthy controls. The results of the study indicate disturbed metabolism of lipids and amino acids and an imbalance of metabolites involved in energy metabolism in individuals diagnosed with AD, compared to healthy controls and MCI subjects.

Profiling and Cellular Analyses of Obesity-Related circRNAs in Neurons and Glia under Obesity-like In Vitro Conditions

Recent evidence indicates that the pathogenesis of neurodegenerative diseases, including Alzheimer’s disease, is associated with metabolic disorders such as diabetes and obesity. Various circular RNAs (circRNAs) have been found in brain tissues and recent studies have suggested that circRNAs are related to neuropathological mechanisms in the brain. However, there is a lack of interest in the involvement of circRNAs in metabolic imbalance-related neuropathological problems until now. Herein we profiled and analyzed diverse circRNAs in mouse brain cell lines (Neuro-2A neurons, BV-2 microglia, and C8-D1a astrocytes) exposed to obesity-related in vitro conditions (high glucose, high insulin, and high levels of tumor necrosis factor-alpha, interleukin 6, palmitic acid, linoleic acid, and cholesterol). We observed that various circRNAs were differentially expressed according to cell types with many of these circRNAs conserved in humans. After suppressing the expression of these circRNAs using siRNAs, we observed that these circRNAs regulate genes related to inflammatory responses, formation of synaptic vesicles, synaptic density, and fatty acid oxidation in neurons; scavenger receptors in microglia; and fatty acid signaling, inflammatory signaling cyto that may play important roles in metabolic disorders associated with neurodegenerative diseases.

Relationship between plasma amino acid and carnitine levels and primary angle-closure glaucoma based on mass spectrometry metabolomics

World blindness is primarily caused by glaucoma. It has been predicted that by 2040, 118 million individuals will have glaucoma. Among Asians and Africans, primary angle-closure glaucoma (PACG) is the most prevalent type of glaucoma, for which treatment options are currently very limited. At present, lowering intraocular pressure (IOP) is the primary approach for PACG treatment. However, some PACG patients with decreased IOP measurements still advance. Additionally, because of the complicated pathophysiology, there are no biomarkers for diagnosis. Metabolomics is the study of the metabolites produced by all cellular processes in a biological sample, providing a method for identifying biomarkers and early diagnosis. Nevertheless, metabolomics has infrequently been applied to PACG. Previous research conducted by our lab on plasma metabolite fatty acids in PACG patients revealed reduced free fatty acid (FFA) levels, which may be connected to lipid peroxidation. To ascertain the relationship between other metabolites and PACG. We compared levels of amino acids and carnitine in patients with PACG (n = 147) and non-glaucoma (n = 340). Using metabolomics analysis, twenty-one amino acids and twenty-six carnitines (a total of ninety-six indicators) were examined. Odds ratios (OR) and 95% confidence intervals (CI) for these metabolites in relation to PACG were calculated. The relationship between ocular measures and metabolites was assessed by Spearman's rank correlation. Predictive performance was evaluated using the receiver operating characteristic (ROC). The C8/C2 level was comparable across patients with PACG and individuals without glaucoma based on the Wilcoxon rank-sum test. The PACG group had lower levels of Arginine (Arg), Ornithine (Orn), Arg/Orn, Orn/Cit, and C26/C20 than the nonglaucoma group, whereas Cit/Arg and C4/C2 ratios were greater. Both univariate and multivariate models showed a negative correlation between Orn and Orn/Cit and PACG. In the univariate model, palmitoylcarnitine (C16) had a negative correlation with PACG. According to our findings, metabolic profiles of plasma amino acids and carnitine between PACG patients and controls are different. The combination of amino acids and carnitine increased the predictive value of PACG. The Orn and Arg were negatively correlated with the local ocular neurodegenerative pathology. We speculate lipid peroxidation may explain the reduction in C16, and the decrease in Orn may be associated with hyperammonia neurotoxicity.

Molecular insights into sex-specific metabolic alterations in Alzheimer's mouse brain using multi-omics approach

BACKGROUND

Alzheimer's disease (AD) is a progressive neurodegenerative disorder that is characterized by altered cellular metabolism in the brain. Several of these alterations have been found to be exacerbated in females, known to be disproportionately affected by AD. We aimed to unravel metabolic alterations in AD at the metabolic pathway level and evaluate whether they are sex-specific through integrative metabolomic, lipidomic, and proteomic analysis of mouse brain tissue.

METHODS

We analyzed male and female triple-transgenic mouse whole brain tissue by untargeted mass spectrometry-based methods to obtain a molecular signature consisting of polar metabolite, complex lipid, and protein data. These data were analyzed using multi-omics factor analysis. Pathway-level alterations were identified through joint pathway enrichment analysis or by separately evaluating lipid ontology and known proteins related to lipid metabolism.

RESULTS

Our analysis revealed significant AD-associated and in part sex-specific alterations across the molecular signature. Sex-dependent alterations were identified in GABA synthesis, arginine biosynthesis, and in alanine, aspartate, and glutamate metabolism. AD-associated alterations involving lipids were also found in the fatty acid elongation pathway and lysophospholipid metabolism, with a significant sex-specific effect for the latter.

CONCLUSIONS

Through multi-omics analysis, we report AD-associated and sex-specific metabolic alterations in the AD brain involving lysophospholipid and amino acid metabolism. These findings contribute to the characterization of the AD phenotype at the molecular level while considering the effect of sex, an overlooked yet determinant metabolic variable.

Alterations in intestinal microbiota and metabolites in individuals with Down syndrome and their correlation with inflammation and behavior disorders in mice

The intestinal microbiota and fecal metabolome have been shown to play a vital role in human health, and can be affected by genetic and environmental factors. We found that individuals with Down syndrome (DS) had abnormal serum cytokine levels indicative of a pro-inflammatory environment. We investigated whether these individuals also had alterations in the intestinal microbiome. High-throughput sequencing of bacterial 16S rRNA gene in fecal samples from 17 individuals with DS and 23 non-DS volunteers revealed a significantly higher abundance of Prevotella, Escherichia/Shigella, Catenibacterium, and Allisonella in individuals with DS, which was positively associated with the levels of pro-inflammatory cytokines. GC-TOF-MS-based fecal metabolomics identified 35 biomarkers (21 up-regulated metabolites and 14 down-regulated metabolites) that were altered in the microbiome of individuals with DS. Metabolic pathway enrichment analyses of these biomarkers showed a characteristic pattern in DS that included changes in valine, leucine, and isoleucine biosynthesis and degradation; synthesis and degradation of ketone bodies; glyoxylate and dicarboxylate metabolism; tyrosine metabolism; lysine degradation; and the citrate cycle. Treatment of mice with fecal bacteria from individuals with DS or Prevotella copri significantly altered behaviors often seen in individuals with DS, such as depression-associated behavior and impairment of motor function. These studies suggest that changes in intestinal microbiota and the fecal metabolome are correlated with chronic inflammation and behavior disorders associated with DS.

Lipids as Early and Minimally Invasive Biomarkers for Alzheimer's Disease

Alzheimer's disease (AD) is the most common neurodegenerative disorder worldwide. Specifically, typical late-onset AD is a sporadic form with a complex etiology that affects over 90% of patients. The current gold standard for AD diagnosis is based on the determination of amyloid status by analyzing cerebrospinal fluid samples or brain positron emission tomography. These procedures can be used widely as they have several disadvantages (expensive, invasive). As an alternative, blood metabolites have recently emerged as promising AD biomarkers. Small molecules that cross the compromised AD blood-brain barrier could be determined in plasma to improve clinical AD diagnosis at early stages through minimally invasive techniques. Specifically, lipids could play an important role in AD since the brain has a high lipid content, and they are present ubiquitously inside amyloid plaques. Therefore, a systematic review was performed with the aim of identifying blood lipid metabolites as potential early AD biomarkers. In conclusion, some lipid families (fatty acids, glycerolipids, glycerophospholipids, sphingolipids, lipid peroxidation compounds) have shown impaired levels at early AD stages. Ceramide levels were significantly higher in AD subjects, and polyunsaturated fatty acids levels were significantly lower in AD. Also, high arachidonic acid levels were found in AD patients in contrast to low sphingomyelin levels. Consequently, these lipid biomarkers could be used for minimally invasive and early AD clinical diagnosis.

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.

Identification of Serum Biomarkers Associated With Emergence Agitation After General Anesthesia in Adult Patients: A Metabolomics Analysis

Background

Emergence agitation (EA) is a conscious disturbance after general anesthesia in adult patients that can lead to severe respiratory or circulatory complications and serious physical injury to patients and caregivers. However, the pathophysiological mechanisms underlying EA remain unclear. The present study aimed to identify serum metabolites with significant alterations in EA patients after general anesthesia and enable inferences on their associations with EA.

Methods

EA patients were identified by Richmond Agitation-Sedation Scale (RASS) ≥ + 2 among a cohort of adult patients who received elective surgery under general anesthesia in Peking University Third Hospital between 01 June 2020 and 30 December 2020. We further selected sex-, age-, and surgery type-matched non-EA control patients at a 1:1.5 ratio. Postoperative serum samples were collected from both groups of patients. An untargeted metabolic method was used to identify differences in serum metabolomic profiles between the EA patients and the non-EA patients.

Results

A total of 19 EA patients and 32 matched non-EA patients were included in the study. After screening and mapping with a database, 12 metabolites showed significant postoperative alterations in EA patients compared with non-EA patients, and were mainly involved in lipid, fatty acid and amino acid metabolism pathways. Receiver operating characteristic curve analyses indicated that vanillic acid, candoxatril, tiglylglycine, 5-methoxysalicylic acid, decanoylcarnitine, and 24-epibrassinolide may be involved in EA pathogenesis after general anesthesia.

Conclusion

In this study, we found differences in the serum levels of vanillic acid, candoxatril, tiglylglycine, 5-methoxysalicylic acid, decanoylcarnitine, and 24-epibrassinolide involved in fatty acid metabolism, lipid metabolism, and amino acid metabolism pathways in EA patients compared with non-EA patients, which may demonstrate an EA pathogenesis-associated molecular pattern and contribute toward better understanding of EA occurrence.

Reactive Thread Spray Mass Spectrometry for Localization of C═C Bonds in Free Fatty Acids: Applications for Obesity Diagnosis

Cellulose thread substrates offer a platform for microsampling and reactive ionization of free fatty acid (FFA) isomers for direct differentiation by mass spectrometry. Ambient corona discharge forms when direct current high voltage is applied to the tiny subfibers on the thread substrate in the presence of a polar spray solvent (MeOH/H2O, 2:1, v/v), facilitating chemical reactions across a C═C bond of unsaturated fatty acids. The process was applied for diagnosis of obesity, which we observed to show better discriminatory power when compared to determinations based on body mass index. Overall, the integrated reactive thread-based platform is capable of (i) microsampling and dry-state, room-temperature storage (>30 days) of the biofluids, (ii) in-capillary liquid/liquid extraction, and (iii) in situ epoxidation reactions to locate the C═C bond position in unsaturated fatty acids via reactions with reactive oxygen species present in ambient corona discharge. The study showcased the ability to correctly characterize FFAs, including degree of unsaturation, and the determination of their relative concentrations in clinical biofluid samples.

Automated Trimethyl Sulfonium Hydroxide Derivatization Method for High-Throughput Fatty Acid Profiling by Gas Chromatography-Mass Spectrometry

Fatty acid profiling on gas chromatography–mass spectrometry (GC–MS) platforms is typically performed offline by manually derivatizing and analyzing small batches of samples. A GC–MS system with a fully integrated robotic autosampler can significantly improve sample handling, standardize data collection, and reduce the total hands-on time required for sample analysis. In this study, we report an optimized high-throughput GC–MS-based methodology that utilizes trimethyl sulfonium hydroxide (TMSH) as a derivatization reagent to convert fatty acids into fatty acid methyl esters. An automated online derivatization method was developed, in which the robotic autosampler derivatizes each sample individually and injects it into the GC–MS system in a high-throughput manner. This study investigated the robustness of automated TMSH derivatization by comparing fatty acid standards and lipid extracts, derivatized manually in batches and online automatically from four biological matrices. Automated derivatization improved reproducibility in 19 of 33 fatty acid standards, with nearly half of the 33 confirmed fatty acids in biological samples demonstrating improved reproducibility when compared to manually derivatized samples. In summary, we show that the online TMSH-based derivatization methodology is ideal for high-throughput fatty acid analysis, allowing rapid and efficient fatty acid profiling, with reduced sample handling, faster data acquisition, and, ultimately, improved data reproducibility.

The role of peripheral fatty acids as biomarkers for Alzheimer's disease and brain inflammation

Alzheimer's disease (AD) is a complex and heterogeneous neurodegenerative disease. A wide range of techniques have been proposed to facilitate early diagnosis of AD, including biomarkers from the cerebrospinal fluid and blood. Although phosphorylated tau and amyloid beta are amongst the most promising biomarkers of AD, other peripheral biomarkers have been identified and in this review we synthesize the current knowledge on circulating fatty acids. Fatty acids are involved in different biological process including neurotransmission and inflammation. Interestingly, some fatty acids appear to be modulated during disease progression, including long chain saturated fatty acids, and polyunsaturated fatty acids, such as docosahexaenoic acid . However, discrepant results have been reported in the literature and there is the need for further validation and method standardization. Nonetheless, our literature review suggests that fatty acid analyses could potentially provide a valuable source of data to further inform the pathology and progression of AD.

Serum Metabolomics for Biomarker Screening of Esophageal Squamous Cell Carcinoma and Esophageal Squamous Dysplasia Using Gas Chromatography-Mass Spectrometry

BACKGROUND

Esophageal squamous cell carcinoma (ESCC) is one of the most common malignancies with poor diagnosis. Esophageal squamous dysplasia (ESD) is considered as an immediate precancerous lesion of ESCC. Lack of biomarkers for discriminating ESCC and ESD from healthy subjects limits the early diagnosis and treatment of ESCC. Therefore, a serum metabolomic strategy was conducted to identify and validate potential metabolic markers for the screening of ESCC and ESD subjects.

METHODS

A total of 74 patients with ESCC, 72 patients with ESD, and 75 normal control (NC) subjects were enrolled in this study. Gas chromatography-mass spectrometry was used to acquire serum metabolic profiles. Pathway analysis was conducted to uncover the fluctuated metabolic pathways during ESCC. Multivariate analyses were used to screen and validate the biomarkers.

RESULTS

ESCC, ESD, and NC subjects revealed progressively altered metabolic profiles, in which amino acids globally increased, while fatty acids decreased in ESCCs compared with the control groups. Pathway analysis demonstrated the activated biosynthesis of amino acids and inhibited desaturation of saturated fatty acids. The panel constructed with propanoic acid, linoleic acid, glycerol-3-phosphate, and l-glutamine showed the area under the curve (AUC), sensitivity, and specificity of 0.817, 0.75, and 0.74, respectively, in the discrimination of ESCC/ESD patients from NC subjects. The panel constructed by propanoic acid, l-leucine, and hydroxyproline revealed the AUC, sensitivity, and specificity of 0.819, 0.76, and 0.72, respectively, in the discrimination of ESD from NC subjects. The combination of hypoxanthine, 2-ketoisocaproic acid, l-glutamate, and l-aspartate showed the AUC, sensitivity, and specificity of 0.818, 0.83, and 0.74, respectively, in the discrimination of ESCC patients from ESD subjects.

CONCLUSIONS

Our study revealed the systematic landscape for metabolic alterations in sera of ESD and ESCC patients. The defined metabolite markers showed reasonable performance in the discrimination of ESCC and ESD patients, and may provide helpful reference for clinicians and biologists.

Untargeted lipidomics reveals progression of early Alzheimer's disease in APP/PS1 transgenic mice

Alzheimer's Disease (AD) is closely connected to aberrant lipid metabolism. However, how early AD-like pathology synchronously influences brain and plasma lipidome in AD mice remains unclear. The study of dynamic change of lipidome in early-stage AD mice could be of great interest for the discovery of lipid biomarkers for diagnosis and monitoring of early-stage AD. For the purpose, an untargeted lipidomic strategy was developed for the characterization of lipids (≤ 1,200 Da) perturbation occurring in plasma and brain in early-stage AD mice (2, 3 and 7 months) by ultra-high performance liquid chromatography coupled with quadrupole-time-of-flight mass spectrometry. Significant changes were detected in the levels of several lipid species including lysophospholipids, phosphatidylcholines (PCs), phosphatidylethanolamines (PEs) and Ceramides (Cers), as well as other related lipid compounds such as fatty acids (FAs), diacylglycerols (DGs) and triacylglycerols (TGs) in AD mice. In this sense, disorders of lipid metabolism appear to involve in multiple factors including overactivation of phospholipases and diacylglycerol lipases, decreased anabolism of lysophospholipids in plasma and PEs in plasma and brain, and imbalances in the levels of PCs, FAs and glycerides at different ages. We revealed the changing panels of potential lipid biomarkers with the development of early AD. The study raises the possibility of developing lipid biomarkers for diagnosis of early-stage AD.

Blood fatty acids in Alzheimer's disease and mild cognitive impairment: A meta-analysis and systematic review

Plasma fatty acids have been reported to be dysregulated in mild cognitive impairment (MCI) and Alzheimer's disease (AD), though outcomes are not always consistent, and subject numbers often small. Our aim was to use a meta-analysis and systematic review approach to identify if plasma fatty acid dysregulation would be observed in case control studies of AD and MCI. Six databases were searched for studies reporting quantified levels of fatty acids in MCI and/or AD individuals, relative to cognitively normal controls. Docosahexaenoic (DHA) and vaccenic acids were significantly lower and higher respectively in MCI relative to controls. Total fatty acids were 27.2% lower in AD relative to controls, and this was reflected almost uniformly in all specific fatty acids in AD. Changes to plasma/serum fatty acids were identified in both MCI and AD relative to age and gender matched controls. Differences were greatest in AD, in both total number of fatty acids significantly altered, and the degree of change. Docosahexaenoic acid was lower in both MCI and AD, suggesting that it may be a driver of pathology.

SERS-based biosensor for Alzheimer disease evaluation through the fast analysis of human serum

Alzheimer disease (AD) is the most common form of dementia in the elderly, progressively affecting the cognitive functions with a complex diagnostic procedure that limits the time for a prompt intervention. In this study we optimized a reliable protocol for the analysis of AD patients and healthy subjects' serum using the Surface Enhanced Raman Spectroscopy (SERS), taking into consideration the effect of different variables on the final spectra, analyzed and compared through multivariate analysis and correlated with hippocampus volume. As results, we demonstrated a statistical difference between the spectra collected from the two investigated groups, with an accuracy, precision and specificity of respectively 83%, 86%, and 86%. The correlation of these data with those obtained from MRI, demonstrated a direct correlation between Raman spectra and hippocampus degeneration showing the Raman Spectroscopy (RS) as a potential tool for the monitoring of AD progression and rehabilitation treatments.

Decreased Blood Level of MFSD2a as a Potential Biomarker of Alzheimer's Disease

The protein Major Facilitator Superfamily Domain containing 2A (MFSD2a) was recently described as the primary carrier for docosahexaenoic acid (DHA) into the brain. Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by lower DHA levels in blood lipids. The aim of this study was to investigate the expression of MFSD2a in the whole blood and brain as a potential biomarker of AD. Three groups were established: 38 healthy controls, 48 subjects with moderate AD (GDS4), and 47 with severe AD (GDS6). We analyzed postmortem brain samples from the hippocampus of 11 healthy controls and 11 severe AD patients. Fatty acid (FA) was determined in serum and brain by gas chromatography. Blood and brain MFSD2a protein expression was analyzed by Western blotting. We found a significant and progressive decline of MFSD2a levels in blood of AD patients (Control 0.83 ± 0.13, GDS4 0.72 ± 0.09, GDS6 0.48 ± 0.05*, p ˂ 0.01). We also corroborated a significant reduction of DHA and other n-3 long-chain polyunsaturated FA in serum of AD. No differences were found in MFSD2a expression or FA levels in brain of controls and AD subjects. MFSD2A carrier was analyzed in AD patients for the first time and the level of MFSD2a in the whole blood could be a potential biomarker of this disease.

Metabolism of sleep and aging: Bridging the gap using metabolomics

Sleep is a conserved behavior across the evolutionary timescale. Almost all known animal species demonstrate sleep or sleep like states. Despite extensive study, the mechanistic aspects of sleep need are not very well characterized. Sleep appears to be needed to generate resources that are utilized during the active stage/wakefulness as well as clearance of waste products that accumulate during wakefulness. From a metabolic perspective, this means sleep is crucial for anabolic activities. Decrease in anabolism and build-up of harmful catabolic waste products is also a hallmark of aging processes. Through this lens, sleep and aging processes are remarkably parallel- for example behavioral studies demonstrate an interaction between sleep and aging. Changes in sleep behavior affect neurocognitive phenotypes important in aging such as learning and memory, although the underlying connections are largely unknown. Here we draw inspiration from the similar metabolic effects of sleep and aging and posit that large scale metabolic phenotyping, commonly known as metabolomics, can shed light to interleaving effects of sleep, aging and progression of diseases related to aging. In this review, data from recent sleep and aging literature using metabolomics as principal molecular phenotyping methods is collated and compared. The present data suggests that metabolic effects of aging and sleep also demonstrate similarities, particularly in lipid metabolism and amino acid metabolism. Some of these changes also overlap with metabolomic data available from clinical studies of Alzheimer's disease. Together, metabolomic technologies show promise in elucidating interleaving effects of sleep, aging and progression of aging disorders at a molecular level.

Gas chromatography-mass spectrometry-based analytical strategies for fatty acid analysis in biological samples

Fatty acids play critical roles in biological systems. Imbalances in fatty acids are related to a variety of diseases, which makes the measurement of fatty acids in biological samples important. Many analytical strategies have been developed to investigate fatty acids in various biological samples. Due to the structural diversity of fatty acids, many factors need to be considered when developing analytical methods including extraction methods, derivatization methods, column selections, and internal standard selections. This review focused on gas chromatography-mass spectrometry (GC-MS)-based methods. We reviewed several commonly used fatty acid extraction approaches, including liquid-liquid extraction and solid-phase microextraction. Moreover, both acid and base derivatization methods and other specially designed methods were comprehensively reviewed, and their strengths and limitations were discussed. Having good separation efficiency is essential to building an accurate and reliable GC-MS platform for fatty acid analysis. We reviewed the separation performance of different columns and discussed the application of multidimensional GC for improving separations. The selection of internal standards was also discussed. In the final section, we introduced several biomedical studies that measured fatty acid levels in different sample matrices and provided hints on the relationships between fatty acid imbalances and diseases.

Association of serum total fatty acids with type 2 diabetes

BACKGROUND

Type 2 diabetes (T2D), a typical metabolic disease, is closely associated with serum free fatty acids. But the association between serum total fatty acids (TFAs, free fatty acids plus esterified fatty acids) and T2D has not been reported.

METHODS

Serum esterified fatty acids were hydrolyzed under alkaline conditions, and serum TFAs were extracted after acidizing. Fourteen of serum TFAs in 1,828 serum samples, including 543 controls, 655 prediabetes, and 630 T2D patients, were simultaneously quantified based on the calibration curves of 8 fatty acids using matrix-assisted laser desorption/ionization-Fourier transform ion cyclotron resonance mass spectrometry (MALDI-FTICR MS).

RESULTS

Correlation analysis revealed strong correlations among serum TFAs and ratios of the TFAs in T2D patients compared with controls or prediabetes both in males and females. Receiver operating characteristic analysis indicated that a panel including fasting plasma glucose, glycosylated hemoglobin type A1c, gamma-glutamyltransferase, triglyceride, C18:1, and C20:3, has a good capability to distinguish prediabetes from T2D, with the sensitivity of 87.0%, the specificity of 91.0%, and the area under curve (AUC) of 0.96.

CONCLUSIONS

In this study, rapid, absolute, and simultaneous quantification of serum TFAs was performed using MALDI-FTICR MS. C18:1 and C20:3 were significantly correlated with prediabetes and T2D.

Perturbed mitochondria-ER contacts in live neurons that model the amyloid pathology of Alzheimer's disease

The use of fixed fibroblasts from familial and sporadic Alzheimer's disease patients has previously indicated an upregulation of mitochondria-ER contacts (MERCs) as a hallmark of Alzheimer's disease. Despite its potential significance, the relevance of these results is limited because they were not extended to live neurons. Here we performed a dynamic in vivo analysis of MERCs in hippocampal neurons from McGill-R-Thy1-APP transgenic rats, a model of Alzheimer's disease-like amyloid pathology. Live FRET imaging of neurons from transgenic rats revealed perturbed 'lipid-MERCs' (gap width <10 nm), while 'Ca²⁺-MERCs' (10-20 nm gap width) were unchanged. In situ TEM showed no significant differences in the lipid-MERCs:total MERCs or lipid-MERCs:mitochondria ratios; however, the average length of lipid-MERCs was significantly decreased in neurons from transgenic rats as compared to controls. In accordance with FRET results, untargeted lipidomics showed significant decreases in levels of 12 lipids and bioenergetic analysis revealed respiratory dysfunction of mitochondria from transgenic rats. Thus, our results reveal changes in MERC structures coupled with impaired mitochondrial functions in Alzheimer's disease-related neurons.This article has an associated First Person interview with the first author of the paper.

Multivariate Analysis Illuminates the Effects of Vacuum Drying on the Extractable and Nonextractable Polyphenols Profile of Loquat Fruit

The current study evaluated the effects of vacuum drying on the whole polyphenol profile of loquat fruit, including extractive and nonextractive polyphenols. Absorbance analysis determined that total polyphenol content and antioxidant levels were higher in loquat fruit vacuum dried at 140 °C than in loquat fruit vacuum dried at 70 °C. The results of ultra-HPLC-triple quadruple mass spectrum analysis showed that 15 phenolic acids and 17 flavonoids were found in dried loquat fruit. Multivariate integrative (MINT) sparse partial least square-discriminant analysis showed that vacuum drying affects the polyphenol profile of loquat fruit. Co-analysis of principal component analysis, partial least square-discriminant analysis, and orthometric partial least square-discriminant analysis revealed that vacuum drying mainly changed the content of chlorogenic acid, cryptochlorogenic acid, protocatechuic acid, phloretin, and hesperidin in loquat fruit. Chlorogenic acid (12.020 to 39.153 µg/g d.b. [dried base weight]), the main polyphenol in dried loquat fruit, was degraded to caffeic acid (0.028 to 2.365 µg/g d.b.) and protocatechuic acid (0.014 to 18.285 µg/g d.b.) during vacuum drying. Moreover, vacuum drying also induced the isomerization of chlorogenic acid into cryptochlorogenic acid (1.628 to 12.737 µg/g d.b.). These results might be used to develop dried loquat fruit with high levels of polyphenols and antioxidant activity. PRACTICAL APPLICATION: Interests in polyphenols of loquat fruit had increased greatly because of their possible role in health benefits. This work provided a holistic insight in the effects of vacuum drying on polyphenols profile of loquat fruit. Current results have contributed to the development of vacuum-drying method, which produced loquat fruit rich in polyphenols. Furthermore, it also suggested that multivariate analysis was a feasible method to reveal the important changes of polyphenols profile during food processing.

Review of recent developments in GC-MS approaches to metabolomics-based research

BACKGROUND

Metabolomics aims to identify the changes in endogenous metabolites of biological systems in response to intrinsic and extrinsic factors. This is accomplished through untargeted, semi-targeted and targeted based approaches. Untargeted and semi-targeted methods are typically applied in hypothesis-generating investigations (aimed at measuring as many metabolites as possible), while targeted approaches analyze a relatively smaller subset of biochemically important and relevant metabolites. Regardless of approach, it is well recognized amongst the metabolomics community that gas chromatography-mass spectrometry (GC-MS) is one of the most efficient, reproducible and well used analytical platforms for metabolomics research. This is due to the robust, reproducible and selective nature of the technique, as well as the large number of well-established libraries of both commercial and 'in house' metabolite databases available.

AIM OF REVIEW

This review provides an overview of developments in GC-MS based metabolomics applications, with a focus on sample preparation and preservation techniques. A number of chemical derivatization (in-time, in-liner, offline and microwave assisted) techniques are also discussed. Electron impact ionization and a summary of alternate mass analyzers are highlighted, along with a number of recently reported new GC columns suited for metabolomics. Lastly, multidimensional GC-MS and its application in environmental and biomedical research is presented, along with the importance of bioinformatics.

KEY SCIENTIFIC CONCEPTS OF REVIEW

The purpose of this review is to both highlight and provide an update on GC-MS analytical techniques that are common in metabolomics studies. Specific emphasis is given to the key steps within the GC-MS workflow that those new to this field need to be aware of and the common pitfalls that should be looked out for when starting in this area.

Evidence That Parietal Lobe Fatty Acids May Be More Profoundly Affected in Moderate Alzheimer's Disease (AD) Pathology Than in Severe AD Pathology

Brain is a lipid-rich tissue, and fatty acids (FAs) play a crucial role in brain function, including neuronal cell growth and development. This study used GC-MS to survey all detectable FAs in the human parietal cortex (Brodmann area 7). These FAs were accurately quantified in 27 cognitively normal age-matched controls, 16 cases of moderate Alzheimer's disease (AD), 30 severe AD, and 14 dementia with Lewy bodies (DLB). A total of 24 FA species were identified. Multiple comparison procedures, using stepdown permutation tests, noted higher levels of 13 FAs but the majority of changes were in moderate AD and DLB, rather than severe AD. Subjects with moderate AD and DLB pathology exhibited significantly higher levels of a number of FAs (13 FAs and 12 FAs, respectively). These included nervonic, lignoceric, cis-13,16-docosadienoic, arachidonic, cis-11,14,17-eicosatrienoic, erucic, behenic, α-linolenic, stearic, oleic, cis-10-heptanoic, and palmitic acids. The similarities between moderate AD and DLB were quite striking-arachidic acid was the only FA which was higher in moderate AD than control, and was not similarly affected in DLB. Furthermore, there were no significant differences between moderate AD and DLB. The associations between each FA and a number of variables, including diagnosis, age, gender, Aβ plaque load, tau load, and frontal tissue pH, were also investigated. To conclude, the development of AD or DLB pathology affects brain FA composition but, intriguingly, moderate AD neuropathology impacts this to a much greater extent. Post-mortem delay is a potential confounding factor, but the findings here suggest that there could be a more dynamic metabolic response in the earlier stages of the disease pathology.

Alteration of Serum Free Fatty Acids are Indicators for Progression of Pre-leukaemia Diseases to Leukaemia

Acute Leukaemia (AL) is a neoplasm of WBCs (white blood cells). Being an important class of metabolites, alteration in free fatty acids (FFAs) levels play a key role in cancer development and progression. As they involve in cell signaling, maintain membrane integrity, regulate homeostasis and effect cell and tissue functions. Considering this fact, a comprehensive analysis of FFAs was conducted to monitor their alteration in AL, pre-leukaemic diseases and healthy control. Fifteen FFAs were analyzed in 179 serum samples of myelodysplastic syndrome (MDS), aplastic anemia (APA), acute lymphoblastic leukaemia (ALL), acute myeloid leukaemia (AML) and healthy control using gas chromatography-multiple reaction monitoring-mass spectrometry (GC-MRM-MS). A multivariate statistical method of random forest (RF) was employed for chemometric analysis. Serum level of two FFAs including C18:0 and C14:0 were found discriminative among all five groups, and between ALL and AML, respectively. Moreover, C14:0 was identified as differentiated FFAs for systematic progression of pre-leukaemic conditions towards AML. C16:0 came as discriminated FFAs between APA and MDS/AML. Over all it was identified that FFAs profile not only become altered in leukaemia but also in pre-leukaemic diseases.

Validation and Verification of a Liquid Chromatography-Mass Spectrometry Method for the Determination of Total Docosahexaenoic Acid in Pig Serum

The paper presents the validation and verification of an analytical method for the determination of total docosahexaenoic acid (DHA) in pig serum by liquid chromatography-electrospray ionization-tandem mass spectrometry. The characteristics studied during the validation included precision and accuracy, limit of quantitation (LOQ), selectivity, calibration range and linearity, parallelism, and stability. A separate verification study was also performed. The method was linear over the range. Precision and accuracy met acceptance criteria at all levels, and the LOQ was determined as 1 μg/mL. Parallelism experiments were conducted to show that there was no bias introduced in using a surrogate matrix to quantify DHA. Recoveries of free DHA were obtained for quality control samples, and stability studies were conducted over 1, 7, 31, and 180 days. The results of the verification study were in line with the validation study, and in conclusion, the method was deemed fit for purpose for measuring total DHA in pig serum.

Impact of hydroxyurea therapy on serum fatty acids of β-thalassemia patients

INTRODUCTION AND OBJECTIVE

Fatty acids (FAs) influence cell and tissue metabolism, function, responsiveness to hormonal and other signals in addition to maintenance of membrane integrity of cells. β-Thalassemia is a prevalent inherited blood disorder characterized by abnormal red cell membrane structure and function. Induction of HbF by hydroxyurea (HU) is an enduring therapeutic intervention to manage this. Therefore, in the present study we have carried out the quantification of thirteen free fatty acids to disclose the prognosis of HU in β-thalassemia.

METHODS

FAs quantification was carried out using GC-MRM-MS method in the serum of 98 cases of β-thalassemia patients and out of which samples from 34 patients were collected before and after treatment with HU in addition to healthy controls (n = 31).

RESULTS

Using the combination of random forest (RF) with GC-MRM-MS we were able to establish a classification and prediction model that can discriminate the β-thalassemia from healthy as well as from HU treated group. Docosanoic acid (C-22:0) was most significantly altered in β-thalassemia as compared to healthy at p-value of 8.3 × 10^-09 while erucic acid (C-22:1 Δ^cis-13) can be used as potential marker of HU prognosis because its level became significantly dissimilar at p-value of 3.7 × 10^-04 in same patients in response to HU. However, nervonic acid (C-24:1 Δ^cis-15) was found to be the key player in effectively separating three groups.

CONCLUSION

In inference, we have noticed that HU therapy also rectifies the serum fatty acid profile in addition to its reported affect i.e. HbF induction in β-thalassemia patients.

Altered fatty acid metabolism and reduced stearoyl-coenzyme a desaturase activity in asthma

BACKGROUND

Fatty acids and lipid mediator signaling play an important role in the pathogenesis of asthma, yet this area remains largely underexplored. The aims of this study were (i) to examine fatty acid levels and their metabolism in obese and nonobese asthma patients and (ii) to determine the functional effects of altered fatty acid metabolism in experimental models.

METHODS

Medium- and long-chain fatty acid levels were quantified in serum from 161 human volunteers by LC/MS. Changes in stearoyl-coenzyme A desaturase (SCD) expression and activity were evaluated in the ovalbumin (OVA) and house dust mite (HDM) murine models. Primary human bronchial epithelial cells from asthma patients and controls were evaluated for SCD expression and activity.

RESULTS

The serum desaturation index (an indirect measure of SCD) was significantly reduced in nonobese asthma patients and in the OVA murine model. SCD1 gene expression was significantly reduced within the lungs following OVA or HDM challenge. Inhibition of SCD in mice promoted airway hyper-responsiveness. SCD1 expression was suppressed in bronchial epithelial cells from asthma patients. IL-4 and IL-13 reduced epithelial cell SCD1 expression. Inhibition of SCD reduced surfactant protein C expression and suppressed rhinovirus-induced IP-10 secretion, which was associated with increased viral titers.

CONCLUSIONS

This is the first study to demonstrate decreased fatty acid desaturase activity in humans with asthma. Experimental models in mice and human epithelial cells suggest that inhibition of desaturase activity leads to airway hyper-responsiveness and reduced antiviral defense. SCD may represent a new target for therapeutic intervention in asthma patients.

Lower brain and blood nutrient status in Alzheimer's disease: Results from meta-analyses

INTRODUCTION

Alzheimer's disease (AD) patients are at risk of nutritional insufficiencies because of physiological and psychological factors. Recently, we showed the results of the meta-analyses indicating lower plasma levels of vitamins A, B12, C, E, and folate in AD patients compared with cognitively intact elderly controls (controls). Now, additional and more extensive literature searches were performed selecting studies which compare blood and brain/cerebrospinal fluid (CSF) levels of vitamins, minerals, trace elements, micronutrients, and fatty acids in AD patients versus controls.

METHODS

The literature published after 1980 in Cochrane Central Register of Controlled Trials, Medline, and Embase electronic databases was systematically analyzed using Preferred Reporting Items for Systematic reviews and Meta-Analyses guidelines to detect studies meeting the selection criteria. Search terms used are as follows: AD patients, Controls, vitamins, minerals, trace elements, micronutrients, and fatty acids. Random-effects meta-analyses using a linear mixed model with correction for age differences between AD patients and controls were performed when four or more publications were retrieved for a specific nutrient.

RESULTS

Random-effects meta-analyses of 116 selected publications showed significant lower CSF/brain levels of docosahexaenoic acid (DHA), choline-containing lipids, folate, vitamin B12, vitamin C, and vitamin E. In addition, AD patients showed lower circulatory levels of DHA, eicosapentaenoic acid, choline as phosphatidylcholine, and selenium.

CONCLUSION

The current data show that patients with AD have lower CSF/brain availability of DHA, choline, vitamin B12, folate, vitamin C, and vitamin E. Directionally, brain nutrient status appears to parallel the lower circulatory nutrient status; however, more studies are required measuring simultaneously circulatory and central nutrient status to obtain better insight in this observation. The brain is dependent on nutrient supply from the circulation, which in combination with nutrient involvement in AD-pathophysiological mechanisms suggests that patients with AD may have specific nutritional requirements. This hypothesis could be tested using a multicomponent nutritional intervention.

Oligomeric amyloid-beta induces MAPK-mediated activation of brain cytosolic and calcium-independent phospholipase A2 in a spatial-specific manner

Alzheimer's disease (AD) is histopathologically characterized by the build-up of fibrillar amyloid beta (Aβ) in the form of amyloid plaques and the development of intraneuronal neurofibrillary tangles consisting of aggregated hyperphosphorylated Tau. Although amyloid fibrils were originally considered responsible for AD pathogenesis, recent convincing evidence strongly implicates soluble oligomeric Aβ as the primary neurotoxic species driving disease progression. A third largely ignored pathological hallmark, originally described by Alois Alzheimer, is the presence of "adipose inclusions", suggestive of aberrant lipid metabolism. The molecular mechanisms underlying these "lipoid granules", as well as their potential link to soluble and/or fibrillar Aβ remain largely unknown. Seeking to better-understand these conundrums, we took advantage of the powerful technology of multidimensional mass spectrometry-based shotgun lipidomics and an AD transgenic mouse model overexpressing mutant amyloid precursor protein (APP E693Δ-Osaka-), where AD-like pathology and neurodegeneration occur as a consequence of oligomeric Aβ accumulation in the absence of amyloid plaques. Our results revealed for the first time that APP overexpression and oligomeric Aβ accumulation lead to an additive global accumulation of nonesterified polyunsaturated fatty acids (PUFAs) independently of amyloid plaques. Furthermore, we revealed that this accumulation is mediated by an increase in phospholipase A₂ (PLA₂) activity, evidenced by an accumulation of sn-1 lysophosphatidylcholine and by MAPK-mediated phosphorylation/activation of group IV Ca²⁺-dependent cytosolic (cPLA₂) and the group VI Ca²⁺-independent PLA₂ (iPLA₂) independently of PKC. We further revealed that Aβ-induced oxidative stress also disrupts lipid metabolism via reactive oxygen species-mediated phospholipid cleavage leading to increased sn-2 lysophosphatidylcholine as well as lipid peroxidation and the subsequent accumulation of 4-hydroxynonenal. Brain histological studies implicated cPLA₂ activity with arachidonic acid accumulation within myelin-rich regions, and iPLA₂ activity with docosahexaenoic acid accumulation within pyramidal neuron-rich regions. Taken together, our results suggest that PLA₂-mediated accumulation of free PUFAs drives AD-related disruption of brain lipid metabolism.

Free Fatty Acids Profiles Are Related to Gut Microbiota Signatures and Short-Chain Fatty Acids

A growing body of evidence highlights the relevance of free fatty acids (FFA) for human health, and their role in the cross talk between the metabolic status and immune system. Altered serum FFA profiles are related to several metabolic conditions, although the underlying mechanisms remain unclear. Recent studies have highlighted the link between gut microbiota and host metabolism. However, although most of the studies have focused on different clinical conditions, evidence on the role of these mediators in healthy populations is lacking. Therefore, we have addressed the analysis of the relationship among gut microbial populations, short-chain fatty acid (SCFA) production, FFA levels, and immune mediators (IFNγ, IL-6, and MCP-1) in 101 human adults from the general Spanish population. Levels of selected microbial groups, representing the major phylogenetic types present in the human intestinal microbiota, were determined by quantitative PCR. Our results showed that the intestinal abundance of Akkermansia was the main predictor of total FFA serum levels, displaying a negative association with total FFA and the pro-inflammatory cytokine IL-6. Similarly, an altered FFA profile, identified by cluster analysis, was related to imbalanced levels of Akkermansia and Lactobacillus as well as increased fecal SCFA, enhanced IL-6 serum levels, and higher prevalence of subclinical metabolic alterations. Although no differences in nutritional intakes were observed, divergent patterns in the associations between nutrient intakes with intestinal microbial populations and SCFA were denoted. Overall, these findings provide new insights on the gut microbiota–host lipid metabolism axis and its potential relevance for human health, where FFA and SCFA seem to play an important role.

Association between the metabolome and bone mineral density in pre- and post-menopausal Chinese women using GC-MS

The present study describes for the first time, a metabolic profile reflecting the osteoporosis progression in 364 pre- and postmenopausal Chinese women using GC-MS. In order to accurately evaluate the dynamic changes of metabolites along with estrogen deficiency and osteoporosis progression, we divided these subjects into the following four groups: premenopausal women with normal bone mass density (BMD, group I), postmenopausal women with normal BMD (group II), postmenopausal women with osteopenia (group III) and postmenopausal women with osteoporosis (group IV), according to their menopause or low BMD status. Principal component analysis (PCA) and Partial least squares-discriminant analysis (PLS-DA) were used to evaluate the associations of metabolic changes with low BMD or estrogen deficiency. Twelve metabolites identified by the PLS-DA model were found to be able to differentiate low BMD groups from normal BMD groups. Of the 12 metabolites, five free fatty acids (LA, oleic acid, AA and 11,14-eicosadienoic acid) have the most potential to be used as osteoporosis biomarkers due to their better correlations with BMD, and high sensitivity and specificity in distinguishing the low BMD groups from the normal BMD groups calculated by the receiver operating characteristic curve (ROC). The lipid profile may be useful for osteoporosis prediction and diagnosis.

Characterization of plasma metal profiles in Alzheimer's disease using multivariate statistical analysis

The exact cause of Alzheimer's disease (AD) and the role of metals in its etiology remain unclear. We have used an analytical approach, based on inductively coupled plasma mass spectrometry coupled with multivariate statistical analysis, to study the profiles of a wide range of metals in AD patients and healthy controls. AD cannot be cured and the lack of sensitive biomarkers that can be used in the early stages of the disease may contribute to this treatment failure. In the present study, we measured plasma levels of amyloid-β1-42(0.142±0.029μg/L)and furin(2.292±1.54μg/L), together with those of the metalloproteinases, insulin-degrading enzyme(1.459±1.14μg/L) and neprilysin(0.073±0.015μg/L), in order to develop biomarkers for AD. Partial least squares discriminant analysis models were used to refine intergroup differences and we discovered that four metals(Mn, Al, Li, Cu) in peripheral blood were strongly associated with AD. Aberration in homeostasis of these metals may alter levels of proteinases, such as furin, which are associated with neurodegeneration in AD and can be a used as plasma-based biomarkers.

Multivariate analyses of peripheral blood leukocyte transcripts distinguish Alzheimer's, Parkinson's, control, and those at risk for developing Alzheimer's

The need for a reliable, simple, and inexpensive blood test for Alzheimer's disease (AD) suitable for use in a primary care setting is widely recognized. This has led to a large number of publications describing blood tests for AD, which have, for the most part, not been replicable. We have chosen to examine transcripts expressed by the cellular, leukocyte compartment of blood. We have used hypothesis-based cDNA arrays and quantitative PCR to quantify the expression of selected sets of genes followed by multivariate analyses in multiple independent samples. Rather than a single study with no replicates, we chose an experimental design in which there were multiple replicates using different platforms and different sample populations. We have divided 177 blood samples and 27 brain samples into multiple replicates to demonstrate the ability to distinguish early clinical AD (Clinical Dementia Rating scale 0.5), Parkinson's disease (PD), and cognitively unimpaired APOE4 homozygotes, as well as to determine persons at risk for future cognitive impairment with significant accuracy. We assess our methods in a training/test set and also show that the variables we use distinguish AD, PD, and control brain. Importantly, we describe the variability of the weights assigned to individual transcripts in multivariate analyses in repeated studies and suggest that the variability we describe may be the cause of inability to repeat many earlier studies. Our data constitute a proof of principle that multivariate analysis of the transcriptome related to cell stress and inflammation of peripheral blood leukocytes has significant potential as a minimally invasive and inexpensive diagnostic tool for diagnosis and early detection of risk for AD.

Suitability of selected chromatographic columns for analysis of fatty acids in dialyzed patients

Gas chromatography-mass spectrometry is a preferred method for fatty acid (FA) analysis in biofluids from patients with metabolic diseases. Complex characteristics of FAs make their analysis particularly challenging. Selection of an appropriate chromatographic column is particularly important component of the process as it provides optimal separation and detection of possibly all FAs present in the sample. However, no accurate protocol for comparative evaluation of capillary columns for the analysis of whole serum FA profile in patients with chronic kidney disease (CKD) has been developed thus far. Therefore, in the present study four columns were examined to select the one providing optimal separation and determination of FA profiles in this group of patients. Moreover, serum FA profiles obtained with the selected column in CKD patients subjected to peritoneal dialysis and healthy controls were compared. Thirty-seven component FAME Mix and sera from CKD patients were used to optimize chromatographic conditions and to select the most appropriate column. The ZB-5 column turned out to be the most appropriate for the analysis of whole FA profile in CKD patients' sera. Then, this column was used to compare FA profiles in patients subjected to peritoneal dialysis and in healthy controls. The analysis demonstrated many abnormalities in the FA profile of CKD patients. Further studies involving larger groups of patients presenting with other stages of CKD are required to explain the impact of the disease progression on composition of serum FAs.

Meta-analysis of genome-wide association studies identifies three novel loci for saturated fatty acids in East Asians

PURPOSE

We aimed to characterize common genetic variants that influence saturated fatty acid concentrations in East Asians.

METHODS

Meta-analysis of genome-wide association studies for circulating SFAs was conducted in two population-based cohorts comprising 3521 participants of Chinese ancestry.

RESULTS

We identified two novel 14:0-associated loci at LMX1A (LIM homeobox transcription factor 1) and AMPD3 (AMP deaminase 3) (P = 5.08 × 10-9 and P = 4.33 × 10-8, respectively), and a novel 20:0-associated locus at CERS4 (ceramide synthase 4) (P = 1.76 × 10-10). We also confirmed the previously reported association of FADS1/2-rs102275 with 18:0 (P = 1.12 × 10-5). In addition, the A alleles of rs11042834 in AMPD3 and rs17159388 in CERS4 also exhibited evidence of associations with high-density lipoprotein cholesterol (P = 0.0162 and P = 0.0161, respectively).

CONCLUSIONS

To our knowledge, this is the first GWAS analysis to examine SFA concentrations in East Asian populations. Our findings provide novel evidence that genetic variations of several genes from multiple pathways are associated with SFA concentrations in human body.

Amelioration of cognitive impairments in APPswe/PS1dE9 mice is associated with metabolites alteration induced by total salvianolic acid

Purpose

Total salvianolic acid (TSA) is extracted from salvia miltiorrhiza; however, to date, there has been limited characterization of its effects on metabolites in Alzheimer’s disease model-APPswe/PS1dE9 mice. The main objective of this study was to investigate the metabolic changes in 7-month-old APPswe/PS1dE9 mice treated with TSA, which protects against learning and memory impairment.

Methods

APPswe/PS1dE9 mice were treated with TSA (30 mg/kg·d and 60 mg/kg·d, i.p.) and saline (i.p.) daily from 3.5 months old for 14 weeks; saline-treated (i.p.) WT mice were included as the controls. The effects of TSA on learning and memory were assessed by a series of behavioral tests, including the NOR, MWM and step-through tasks. The FBG and plasma lipid levels were subsequently assessed using the GOPOD and enzymatic color methods, respectively. Finally, the concentrations of Aβ42, Aβ40 and metabolites in the hippocampus of the mice were detected via ELISA and GC-TOF-MS, respectively.

Results

At 7 months of age, the APPswe/PS1dE9 mice treated with TSA exhibited an improvement in the preference index (PI) one hour after the acquisition phase in the NOR and the preservation of spatial learning and memory in the MWM. Treatment with TSA substantially decreased the LDL-C level, and 60 mg/kg TSA decreased the CHOL level compared with the plasma level of the APPswe/PS1dE9 group. The Aβ42 and Aβ40 levels in the hippocampus were decreased in the TSA-treated group compared with the saline-treated APPswe/PS1dE9 group. The regulation of metabolic pathways relevant to TSA predominantly included carbohydrate metabolism, such as sorbitol, glucose-6-phosphate, sucrose-6-phosphate and galactose, vitamin metabolism involved in cholecalciferol and ascorbate in the hippocampus.

Conclusions

TSA induced a remarkable amelioration of learning and memory impairments in APPswe/PS1dE9 mice through the regulation of Aβ42, Aβ40, carbohydrate and vitamin metabolites in the hippocampus and LDL-C and CHOL in the plasma.

Metabolomic-guided discovery of Alzheimer's disease biomarkers from body fluid

The rapid increase in the older population has made age-related diseases like Alzheimer's disease (AD) a global concern. Given that there is still no cure for this neurodegenerative disease, the drastic growth in the number of susceptible individuals represents a major emerging threat to public health. The poor understanding of the mechanisms underlying AD is deemed the greatest stumbling block against progress in definitive diagnosis and management of this disease. There is a dire need for biomarkers that can facilitate early diagnosis, classification, prognosis, and treatment response. Efforts have been directed toward discovery of reliable and distinctive AD biomarkers but with very little success. With the recent emergence of high-throughput technology that is able to collect and catalogue vast datasets of small metabolites, metabolomics offers hope for a better understanding of AD and subsequent identification of biomarkers. This review article highlights the potential of using multiple metabolomics platforms as useful means in uncovering AD biomarkers from body fluids. © 2017 Wiley Periodicals, Inc.