Plasma metabolic profiling of Alzheimer's disease by liquid chromatography/mass spectrometry

Mapping the lipidome in mitochondria-associated membranes (MAMs) in an in vitro model of Alzheimer's disease

The disruption of mitochondria-associated endoplasmic reticulum (ER) membranes (MAMs) plays a relevant role in Alzheimer's disease (AD). MAMs have been implicated in neuronal dysfunction and death since it is associated with impairment of functions regulated in this subcellular domain, including lipid synthesis and trafficking, mitochondria dysfunction, ER stress-induced unfolded protein response (UPR), apoptosis, and inflammation. Since MAMs play an important role in lipid metabolism, in this study we characterized and investigated the lipidome alterations at MAMs in comparison with other subcellular fractions, namely microsomes and mitochondria, using an in vitro model of AD, namely the mouse neuroblastoma cell line (N2A) over-expressing the APP familial Swedish mutation (APPswe) and the respective control (WT) cells. Phospholipids (PLs) and fatty acids (FAs) were isolated from the different subcellular fractions and analyzed by HILIC-LC-MS/MS and GC-MS, respectively. In this in vitro AD model, we observed a down-regulation in relative abundance of some phosphatidylcholine (PC), lysophosphatidylcholine (LPC), and lysophosphatidylethanolamine (LPE) species with PUFA and few PC with saturated and long-chain FA. We also found an up-regulation of CL, and antioxidant alkyl acyl PL. Moreover, multivariate analysis indicated that each organelle has a specific lipid profile adaptation in N2A APPswe cells. In the FAs profile, we found an up-regulation of C16:0 in all subcellular fractions, a decrease of C18:0 levels in total fraction (TF) and microsomes fraction, and a down-regulation of 9-C18:1 was also found in mitochondria fraction in the AD model. Together, these results suggest that the over-expression of the familial APP Swedish mutation affects lipid homeostasis in MAMs and other subcellular fractions and supports the important role of lipids in AD physiopathology.

Urine Metabolic Profiling for Rapid Lung Cancer Screening: A Strategy Combining Rh-Doped SrTiO3-Assisted Laser Desorption/Ionization Mass Spectrometry and Machine Learning

Lung cancer ranks among the cancers with the highest global incidence rates and mortality. Swift and extensive screening is crucial for the early-stage diagnosis of lung cancer. Laser desorption/ionization mass spectrometry (LDI-MS) possesses clear advantages over traditional analytical methods for large-scale analysis due to its unique features, such as simple sample processing, rapid speed, and high-throughput performance. As n-type semiconductors, titanate-based perovskite materials can generate charge carriers under ultraviolet light irradiation, providing the capability for use as an LDI-MS substrate. In this study, we employ Rh-doped SrTiO3 (STO/Rh)-assisted LDI-MS combined with machine learning to establish a method for urine-based lung cancer screening. We directly analyzed urine metabolites from lung cancer patients (LCs), pneumonia patients (PNs), and healthy controls (HCs) without employing any pretreatment. Through the integration of machine learning, LCs are successfully distinguished from HCs and PNs, achieving impressive area under the curve (AUC) values of 0.940 for LCs vs HCs and 0.864 for LCs vs PNs. Furthermore, we identified 10 metabolites with significantly altered levels in LCs, leading to the discovery of related pathways through metabolic enrichment analysis. These results suggest the potential of this method for rapidly distinguishing LCs in clinical applications and promoting precision medicine.

Characterization of Hair Metabolome in 5xFAD Mice and Patients with Alzheimer's Disease Using Mass Spectrometry-Based Metabolomics

Hair emerged as a biospecimen for long-term investigation of endogenous metabolic perturbations, reflecting the chemical composition circulating in the blood over the past months. Despite its potential, the use of human hair for metabolomics in Alzheimer's disease (AD) research remains limited. Here, we performed both untargeted and targeted metabolomic approaches to profile the key metabolic pathways in the hair of 5xFAD mice, a widely used AD mouse model. Furthermore, we applied the discovered metabolites to human subjects. Hair samples were collected from 6-month-old 5xFAD mice, a stage marked by widespread accumulation of amyloid plaques in the brain, followed by sample preparation and high-resolution mass spectrometry analysis. Forty-five discriminatory metabolites were discovered in the hair of 6-month-old 5xFAD mice compared to wild-type control mice. Enrichment analysis revealed three key metabolic pathways: arachidonic acid metabolism, sphingolipid metabolism, and alanine, aspartate, and glutamate metabolism. Among these pathways, six metabolites demonstrated significant differences in the hair of 2-month-old 5xFAD mice, a stage prior to the onset of amyloid plaque deposition. These findings suggest their potential involvement in the early stages of AD pathogenesis. When evaluating 45 discriminatory metabolites for distinguishing patients with AD from nondemented controls, a combination of l-valine and arachidonic acid significantly differentiated these two groups, achieving a 0.88 area under the curve. Taken together, these findings highlight the potential of hair metabolomics in identifying disease-specific metabolic alterations and developing biomarkers for improving disease detection and monitoring.

Association of metabolic dysfunction with cognitive decline and Alzheimer's disease: A review of metabolomic evidence

The discovery of new biomarkers that can distinguish Alzheimer's disease (AD) from mild cognitive impairment (MCI) in the early stages will help to provide new diagnostic and therapeutic strategies and slow the transition from MCI to AD. Patients with AD may present with a concomitant metabolic disorder, such as diabetes, obesity, and dyslipidemia, as a risk factor for AD that may be involved in the onset of both AD pathology and cognitive impairment. Therefore, metabolite profiling, or metabolomics, can be very useful in diagnosing AD, developing new therapeutic targets, and evaluating both the course of treatment and the clinical course of the disease. In addition, studying the relationship between nutritional behavior and AD requires investigation of the role of conditions such as obesity, hypertension, dyslipidemia, and elevated glucose level. Based on this literature review, nutritional recommendations, including weight loss by reducing calorie and cholesterol intake and omega-3 fatty acid supplementation can prevent cognitive decline and dementia in the elderly. The underlying metabolic causes of the pathology and cognitive decline caused by AD and MCI are not well understood. In this review article, metabolomics biomarkers for diagnosis of AD and MCI and metabolic risk factors for cognitive decline in AD were evaluated.

Lysophosphatidylcholines are associated with P-tau181 levels in early stages of Alzheimer's Disease

Background

We profiled circulating plasma metabolites to identify systemic biochemical changes in clinical and biomarker-assisted diagnosis of Alzheimer's disease (AD).

Methods

We used an untargeted approach with liquid chromatography coupled to high-resolution mass spectrometry to measure small molecule plasma metabolites from 150 clinically diagnosed AD patients and 567 age-matched healthy elderly of Caribbean Hispanic ancestry. Plasma biomarkers of AD were measured including P-tau181, Aβ40, Aβ42, total-tau, neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP). Association of individual and co-abundant modules of metabolites were tested with clinical diagnosis of AD, as well as biologically-defined AD pathological process based on P-tau181 and other biomarker levels.

Results

Over 6000 metabolomic features were measured with high accuracy. First principal component (PC) of lysophosphatidylcholines (lysoPC) that bind to or interact with docosahexaenoic acid (DHA), eicosapentaenoic acid (EPA) and arachidonic acid (AHA) was associated with decreased risk of AD (OR = 0.91 [0.89-0.96], p = 2e-04). Association was restricted to individuals without an APOE ε4 allele (OR = 0.89 [0.84-0.94], p = 8.7e-05). Among individuals carrying at least one APOE ε4 allele, PC4 of lysoPCs moderately increased risk of AD (OR = 1.37 [1.16-1.6], p = 1e-04). Essential amino acids including tyrosine metabolism pathways were enriched among metabolites associated with P-tau181 levels and heparan and keratan sulfate degradation pathways were associated with Aβ42/Aβ40 ratio.

Conclusions

Unbiased metabolic profiling can identify critical metabolites and pathways associated with β-amyloid and phosphotau pathology. We also observed an APOE-ε4 dependent association of lysoPCs with AD and biologically based diagnostic criteria may aid in the identification of unique pathogenic mechanisms.

Lipid metabolism and oxidative stress in patients with Alzheimer's disease and amnestic mild cognitive impairment

Lipid metabolism and oxidative stress are key mechanisms in Alzheimer's disease (AD). The link between plasma lipid metabolites and oxidative stress in AD patients is poorly understood. This study was to identify markers that distinguish AD and amnestic mild cognitive impairment (aMCI) from NC, and to reveal potential links between lipid metabolites and oxidative stress. We performed non-targeted lipid metabolism analysis of plasma from patients with AD, aMCI, and NC using LC-MS/MS. The plasma malondialdehyde (MDA), glutathione peroxidase (GSH-Px), and superoxide dismutase (SOD) levels were assessed. We found significant differences in lipid metabolism between patients with AD and aMCI compared to those in NC. AD severity is associated with lipid metabolites, especially TG (18:0_16:0_18:0) + NH4, TG (18:0_16:0_16:0) + NH4, LPC(16:1e)-CH3, and PE (20:0_20:4)-H. SPH (d16:0) + H, SPH (d18:1) + H, and SPH (d18:0) + H were high-performance markers to distinguish AD and aMCI from NC. The AUC of three SPHs combined to predict AD was 0.990, with specificity and sensitivity as 0.949 and 1, respectively; the AUC of three SPHs combined to predict aMCI was 0.934, with specificity and sensitivity as 0.900, 0.981, respectively. Plasma MDA concentrations were higher in the AD group than in the NC group (p = 0.003), whereas plasma SOD levels were lower in the AD (p < 0.001) and aMCI (p = 0.045) groups than in NC, and GSH-Px activity were higher in the AD group than in the aMCI group (p = 0.007). In addition, lipid metabolites and oxidative stress are widely associated. In conclusion, this study distinguished serum lipid metabolism in AD, aMCI, and NC subjects, highlighting that the three SPHs can distinguish AD and aMCI from NC. Additionally, AD patients showed elevated oxidative stress, and there are complex interactions between lipid metabolites and oxidative stress.

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.

Lysophosphatidylcholines are associated with P-tau181 levels in early stages of Alzheimer's Disease

Background

We investigated systemic biochemical changes in Alzheimer's disease (AD) by investigating the relationship between circulating plasma metabolites and both clinical and biomarker-assisted diagnosis of AD.

Methods

We used an untargeted approach with liquid chromatography coupled to high-resolution mass spectrometry to measure exogenous and endogenous small molecule metabolites in plasma from 150 individuals clinically diagnosed with AD and 567 age-matched elderly without dementia of Caribbean Hispanic ancestry. Plasma biomarkers of AD were also measured including P-tau181, Aβ40, Aβ42, total tau, neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP). Association of individual and co-expressed modules of metabolites were tested with the clinical diagnosis of AD, as well as biologically-defined AD pathological process based on P-tau181 and other biomarker levels.

Results

Over 4000 metabolomic features were measured with high accuracy. First principal component (PC) of lysophosphatidylcholines (lysoPC) that bind to or interact with docosahexaenoic acid (DHA), eicosapentaenoic acid (EPA) and arachidonic acid (AHA) was associated with decreased risk of AD (OR=0.91 [0.89-0.96], p=2e-04). Restricted to individuals without an APOE ε4 allele (OR=0.89 [0.84-0.94], p= 8.7e-05), the association remained. Among individuals carrying at least one APOE ε4 allele, PC4 of lysoPCs moderately increased risk of AD (OR=1.37 [1.16-1.6], p=1e-04). Essential amino acids including tyrosine metabolism pathways were enriched among metabolites associated with P-tau181 levels and heparan and keratan sulfate degradation pathways were associated with Aβ42/Aβ40 ratio reflecting different pathways enriched in early and middle stages of disease.

Conclusions

Our findings indicate that unbiased metabolic profiling can identify critical metabolites and pathways associated with β-amyloid and phosphotau pathology. We also observed an APOE ε4 dependent association of lysoPCs with AD and that biologically-based diagnostic criteria may aid in the identification of unique pathogenic mechanisms.

Rat Hair Metabolomics Analysis Reveals Perturbations of Unsaturated Fatty Acid Biosynthesis, Phenylalanine, and Arachidonic Acid Metabolism Pathways Are Associated with Amyloid-β-Induced Cognitive Deficits

Hair is a noninvasive valuable biospecimen for the long-term assessment of endogenous metabolic disturbance. Whether the hair is suitable for identifying biomarkers of the Alzheimer's disease (AD) process remains unknown. We aim to investigate the metabolism changes in hair after β-amyloid (Aβ1-42) exposure in rats using ultra-high-performance liquid chromatography-high-resolution mass spectrometry-based untargeted and targeted methods. Thirty-five days after Aβ1-42 induction, rats displayed significant cognitive deficits, and forty metabolites were changed, of which twenty belonged to three perturbed pathways: (1) phenylalanine metabolism and phenylalanine, tyrosine, and tryptophan biosynthesis-L-phenylalanine, phenylpyruvate, ortho-hydroxyphenylacetic acid, and phenyllactic acid are up-regulated; (2) arachidonic acid (ARA) metabolism-leukotriene B4 (LTB4), arachidonyl carnitine, and 5(S)-HPETE are upregulation, but ARA, 14,15-DiHETrE, 5(S)-HETE, and PGB2 are opposite; and (3) unsaturated fatty acid biosynthesis- eicosapentaenoic acid (EPA), docosahexaenoic acid (DHA), FA 18:3 + 1O, and FA 18:3 + 2O are downregulated. Linoleic acid metabolism belonging to the biosynthesis of unsaturated fatty acid includes the upregulation of 8-hydroxy-9,10-epoxystearic acid, 13-oxoODE, and FA 18:2 + 4O, and downregulation of 9(S)-HPODE and dihomo-γ-linolenic acid. In addition, cortisone and dehydroepiandrosterone belonging to steroid hormone biosynthesis are upregulated. These three perturbed metabolic pathways also correlate with cognitive impairment after Aβ1-42 stimulation. Furthermore, ARA, DHA, EPA, L-phenylalanine, and cortisone have been previously implicated in the cerebrospinal fluid of AD patients and show a similar changing trend in Aβ1-42 rats' hair. These data suggest hair can be a useful biospecimen that well reflects the expression of non-polar molecules under Aβ1-42 stimulation, and the five metabolites have the potential to serve as novel AD biomarkers.

Integrative metabolomics science in Alzheimer's disease: Relevance and future perspectives

Alzheimer's disease (AD) is determined by various pathophysiological mechanisms starting 10-25 years before the onset of clinical symptoms. As multiple functionally interconnected molecular/cellular pathways appear disrupted in AD, the exploitation of high-throughput unbiased omics sciences is critical to elucidating the precise pathogenesis of AD. Among different omics, metabolomics is a fast-growing discipline allowing for the simultaneous detection and quantification of hundreds/thousands of perturbed metabolites in tissues or biofluids, reproducing the fluctuations of multiple networks affected by a disease. Here, we seek to critically depict the main metabolomics methodologies with the aim of identifying new potential AD biomarkers and further elucidating AD pathophysiological mechanisms. From a systems biology perspective, as metabolic alterations can occur before the development of clinical signs, metabolomics - coupled with existing accessible biomarkers used for AD screening and diagnosis - can support early disease diagnosis and help develop individualized treatment plans. Presently, the majority of metabolomic analyses emphasized that lipid metabolism is the most consistently altered pathway in AD pathogenesis. The possibility that metabolomics may reveal crucial steps in AD pathogenesis is undermined by the difficulty in discriminating between the causal or epiphenomenal or compensatory nature of metabolic findings.

Alteration of plasma metabolic profile and physical performance combined with metabolites is more sensitive to early screening for mild cognitive impairment

Objective

Unbiased metabolic profiling has been initiated to identify novel metabolites. However, it remains a challenge to define reliable biomarkers for rapid and accurate diagnosis of mild cognitive impairment (MCI). Our study aimed to evaluate the association of serum metabolites with MCI, attempting to find new biomarkers and combination models that are distinct for MCI.

Methods

A total of 380 participants were recruited (mean age: 72.5 ± 5.19 years). We performed an untargeted metabolomics analysis on older adults who underwent the Mini-Mental State Examination (MMSE), the Instrumental Activities of Daily Living (IADL), and physical performance tests such as hand grip, Timed Up and Go Test (TUGT), and walking speed. Orthogonal partial least squares discriminant analysis (OPLS-DA) and heat map were utilized to distinguish the metabolites that differ between groups.

Results

Among all the subjects, 47 subjects were diagnosed with MCI, and methods based on the propensity score are used to match the MCI group with the normal control (NC) group (n = 47). The final analytic sample comprised 94 participants (mean age: 75.2 years). The data process from the metabolic profiles identified 1,008 metabolites. A cluster and pathway enrichment analysis showed that sphingolipid metabolism is involved in the development of MCI. Combination of metabolite panel and physical performance were significantly increased discriminating abilities on MCI than a single physical performance test [model 1: the area under the curve (AUC) = 0.863; model 2: AUC = 0.886; and model 3: AUC = 0.870, P < 0.001].

Conclusion

In our study, untargeted metabolomics was used to detect the disturbance of metabolism that occurs in MCI. Physical performance tests combined with phosphatidylcholines (PCs) showed good utility in discriminating between NC and MCI, which is meaningful for the early diagnosis of MCI.

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.

Urinary and faecal metabolic characteristics in APP/PS1 transgenic mouse model of Alzheimer's disease with and without cognitive decline

Alzheimer's disease (AD) has been considered to be a systematic metabolic disorder, but little information is available about metabolic changes in the urine and feces. In this study, we investigated urinary and faecal metabolic profiles in amyloid precursor protein/presenilin 1 (APP/PS1) mice at 3 and 9 months of age (3 M and 9 M) and age-matched wild-type (WT) mice by using ¹H NMR-based metabolomics, and aimed to explore changes in metabolic pathways during amyloid pathology progression and identify potential metabolite biomarkers at earlier stage of AD. The results show that learning and memory abilities were impaired in APP/PS1 mice relative to WT mice at 9 M, but not at 3 M. However, metabolomics analysis demonstrates that AD disrupted metabolic phenotypes in the urine and feces of APP/PS1 mice at both 3 M and 9 M, including amino acid metabolism, microbial metabolism and energy metabolism. In addition, several potential metabolite biomarkers were identified for discriminating AD and WT mice prior to cognitive decline with the AUC values from 0.755 to 0.971, such as taurine, hippurate, urea and methylamine in the urine as well as alanine, leucine and valine in the feces. Therefore, our results not only confirmed AD as a metabolic disorder, but also contributed to the identification of potential biomarkers at earlier stage of AD.

Sex-Specific Metabolic Pathways Were Associated with Alzheimer's Disease (AD) Endophenotypes in the European Medical Information Framework for AD Multimodal Biomarker Discovery Cohort

BACKGROUND

physiological differences between males and females could contribute to the development of Alzheimer's Disease (AD). Here, we examined metabolic pathways that may lead to precision medicine initiatives.

METHODS

We explored whether sex modifies the association of 540 plasma metabolites with AD endophenotypes including diagnosis, cerebrospinal fluid (CSF) biomarkers, brain imaging, and cognition using regression analyses for 695 participants (377 females), followed by sex-specific pathway overrepresentation analyses, APOE ε4 stratification and assessment of metabolites' discriminatory performance in AD.

RESULTS

In females with AD, vanillylmandelate (tyrosine pathway) was increased and tryptophan betaine (tryptophan pathway) was decreased. The inclusion of these two metabolites (area under curve (AUC) = 0.83, standard error (SE) = 0.029) to a baseline model (covariates + CSF biomarkers, AUC = 0.92, SE = 0.019) resulted in a significantly higher AUC of 0.96 (SE = 0.012). Kynurenate was decreased in males with AD (AUC = 0.679, SE = 0.046).

CONCLUSIONS

metabolic sex-specific differences were reported, covering neurotransmission and inflammation pathways with AD endophenotypes. Two metabolites, in pathways related to dopamine and serotonin, were associated to females, paving the way to personalised treatment.

Comparison of proteomic approaches used for the detection of potential biomarkers of Alzheimer's disease in blood plasma

At present, Alzheimer's disease is detected mainly using psychological tests, which can only confirm the disease in its more advanced phases. Therefore, bioanalytical possibilities for detecting this disease earlier are being investigated. To date, the results of analyses, which focus mainly on the study of lipids and proteins either in cerebrospinal fluid or much less often in blood plasma, do not provide satisfactory results. In addition, cerebrospinal fluid sampling is uncomfortable for the patients and involves many health risks. In this work, we deal with proteomic analysis using Matrix-Assisted Laser Desorption/Ionisation-Time of Flight and Liquid Chromatography coupled to tandem Mass Spectrometry of blood plasma with a focus on various ways of preanalytical sample treatments. This should lead to results improvement and facilitate the subsequent evaluation using principal component analysis and partial least squares discriminant analysis. The obtained results indicate the direction of further research, namely the study of interactions between proteins and lipids contained in blood plasma. These substances may be regarded as potential biomarkers allowing for the diagnosis of Alzheimer´s disease even in its early stages.

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.

Targeted Lipidomics of Mitochondria in a Cellular Alzheimer's Disease Model

Alzheimer's disease (AD) is neuropathologically characterized by the accumulation of Amyloid-β (Aβ) in senile plaques derived from amyloidogenic processing of a precursor protein (APP). Recently, changes in mitochondrial function have become in the focus of the disease. Whereas a link between AD and lipid-homeostasis exists, little is known about potential alterations in the lipid composition of mitochondria. Here, we investigate potential changes in the main mitochondrial phospholipid classes phosphatidylcholine, phosphatidylethanolamine and the corresponding plasmalogens and lyso-phospholipids of a cellular AD-model (SH-SY5Y APPswedish transfected cells), comparing these results with changes in cell-homogenates. Targeted shotgun-lipidomics revealed lipid alterations to be specific for mitochondria and cannot be predicted from total cell analysis. In particular, lipids containing three and four times unsaturated fatty acids (FA X:4), such as arachidonic-acid, are increased, whereas FA X:6 or X:5, such as eicosapentaenoic acid (EPA) or docosahexaenoic acid (DHA), are decreased. Additionally, PE plasmalogens are increased in contrast to homogenates. Results were confirmed in another cellular AD model, having a lower affinity to amyloidogenic APP processing. Besides several similarities, differences in particular in PE species exist, demonstrating that differences in APP processing might lead to specific changes in lipid homeostasis in mitochondria. Importantly, the observed lipid alterations are accompanied by changes in the carnitine carrier system, also suggesting an altered mitochondrial functionality.

Shotgun lipidomics of liver and brain tissue of Alzheimer's disease model mice treated with acitretin

Alzheimer’s disease (AD) is a very frequent neurodegenerative disorder characterized by an accumulation of amyloid-β (Aβ). Acitretin, a retinoid-derivative and approved treatment for Psoriasis vulgaris, increases non-amyloidogenic Amyloid-Precursor-Protein-(APP)-processing, prevents Aβ-production and elicits cognitive improvement in AD mouse models. As an unintended side effect, acitretin could result in hyperlipidemia. Here, we analyzed the impact of acitretin on the lipidome in brain and liver tissue in the 5xFAD mouse-model. In line with literature, triglycerides were increased in liver accompanied by increased PCaa, plasmalogens and acyl-carnitines, whereas SM-species were decreased. In brain, these effects were partially enhanced or similar but also inverted. While for SM and plasmalogens similar effects were found, PCaa, TAG and acyl-carnitines showed an inverse effect in both tissues. Our findings emphasize, that potential pharmaceuticals to treat AD should be carefully monitored with respect to lipid-homeostasis because APP-processing itself modulates lipid-metabolism and medication might result in further and unexpected changes. Moreover, deducing effects of brain lipid-homeostasis from results obtained for other tissues should be considered cautiously. With respect to acitretin, the increase in brain plasmalogens might display a further positive probability in AD-treatment, while other results, such as decreased SM, indicate the need of medical surveillance for treated patients.

Changes in plasma phospholipids and sphingomyelins with aging in men and women: A comprehensive systematic review of longitudinal cohort studies

BACKGROUND

Aging affects the serum levels of various metabolites which may be involved in the pathogenesis of chronic diseases. The aim of this review article is to summarize the relationship between aging and alterations in the plasma phospholipids and sphingomyelins.

METHODS

PRISMA guidelines were employed during all steps. MEDLINE (PubMed), Scopus, Embase and Web of Sciences databases and Google Scholar were searched up to October 2020. Cohort studies investigating the relationship between aging and within-person changes in sphingomyelin (SM), phosphatidyl choline (PC), lyso PC (LPC) and phosphatidyl ethanolamine (PE) were included. Newcastle-Ottawa scale was used to assess the quality of included studies.

RESULTS

A total of 1425 studies were identified. After removing 610 duplicates and 723 irrelevant studies, full texts of 92 articles were evaluated. Of these 92, 6 studies (including data from 7 independent cohorts) met the inclusion criteria and are included in this review. All study populations were healthy and included both men and women. Results by sex were reported in 3 cohorts for PC, 5 cohorts for LPC, 3 cohorts for SM, and only 1 cohort for PE. In men, PC, SM, PE and LPC decreased with aging, although results for LPC were inconsistent. In women, LPC, SM, and PE increased age, whereas changes in PC were inconsistent.

CONCLUSION

Within-person serum levels of phospholipids and sphingomyelins, decrease during aging in men and increase in women. Notably, however, there were some inconsistencies across studies of LPC in men and of PC in women.

Association of Plasma Phospholipids with Age-Related Cognitive Impairment: Results from a Cross-Sectional Study

Decreased concentration of phospholipids were observed in brain tissue from individuals with dementia compared with controls, indicating phospholipids might be a key variable in development of age-related cognitive impairment. The reflection of these phospholipid changes in blood might provide both reference for diagnosis/monitoring and potential targets for intervention through peripheral circulation. Using a full-scale targeted phospholipidomic approach, 229 molecular species of plasma phospholipid were identified and quantified among 626 senile residents; the association of plasma phospholipids with MoCA score was also comprehensively discussed. Significant association was confirmed between phospholipid matrix and MoCA score by a distance-based linear model. Additionally, the network analysis further observed that two modules containing PEs were positively associated with MoCA score, and one module containing LPLs had a trend of negative correlation with MoCA score. Furthermore, 23 phospholipid molecular species were found to be significantly associated with MoCA score independent of fasting glucose, lipidemia, lipoproteins, inflammatory variables and homocysteine. Thus, the decreased levels of pPEs containing LC-PUFA and the augmented levels of LPLs were the most prominent plasma phospholipid changes correlated with the cognitive decline, while alterations in plasma PC, PS and SM levels accompanying cognitive decline might be due to variation of lipidemia and inflammatory levels.

Clinical Insights into Mitochondrial Neurodevelopmental and Neurodegenerative Disorders: Their Biosignatures from Mass Spectrometry-Based Metabolomics

Mitochondria are dynamic multitask organelles that function as hubs for many metabolic pathways. They produce most ATP via the oxidative phosphorylation pathway, a critical pathway that the brain relies on its energy need associated with its numerous functions, such as synaptic homeostasis and plasticity. Therefore, mitochondrial dysfunction is a prevalent pathological hallmark of many neurodevelopmental and neurodegenerative disorders resulting in altered neurometabolic coupling. With the advent of mass spectrometry (MS) technology, MS-based metabolomics provides an emerging mechanistic understanding of their global and dynamic metabolic signatures. In this review, we discuss the pathogenetic causes of mitochondrial metabolic disorders and the recent MS-based metabolomic advances on their metabolomic remodeling. We conclude by exploring the MS-based metabolomic functional insights into their biosignatures to improve diagnostic platforms, stratify patients, and design novel targeted therapeutic strategies.

Brain Lipid Dynamics in Amyloid Precursor Protein/Presenilin 1 Mouse Model of Early Alzheimer's Disease by Desorption Electrospray Ionization and Matrix Assisted Laser Desorption Ionization-Mass Spectrometry Imaging Techniques

Alzheimer's disease (AD) is closely associated with lipid metabolism dysfunction. However, space distribution and metabolism of aberrant lipids in the brain of early-stage AD mouse remain unclear. In our current work, a novel lipidomics method based on mass spectrometry imaging was developed to visually disclose molecular perturbation and characterize space distribution in the brain of double transgenic amyloid precursor protein/presenilin 1 mouse (2 and 3 months old). Significant changes were detected, including phosphatidylethanolamines, phosphatidylcholines, fatty acids, lysophospholipids, and glycerides in AD mouse brain. The results in this study suggest that these significantly altered lipid metabolic pathways (glycerophospholipid metabolism) may be implicated in early-stage AD. Our work deepens the understanding of the physio-pathologic mechanism of early-stage AD.

Direct detection of inorganic ions and underivatized amino acids in seconds using high-speed capillary electrophoresis coupled with back-scatter interferometry

High speed capillary electrophoresis (HSCE) combined with refractive index (RI) detection is developed for the rapid separation and detection of inorganic ions and amino acids. A mixture of three inorganic ions (K⁺, Na⁺, Li⁺) and eight amino acids (Lys, Arg, Ala, Gly, Val, Thr, Trp, Asp) are detected using back scatter interferometry (BSI), without the need for chemical modifications or contrast. A thin-walled separation capillary (50 μm i.d. by 80 μm o.d.) helps mitigate Joule heating at the high field strengths required for rapid separations. This, combined with a short 8 cm length-to-detector (10 cm total length), enables separations on the seconds time scale. Using a background electrolyte (BGE) of 4 M acetic acid (pH 1.6) and a field strength of 900 V cm^-1, all 11 analytes are separated in less than 40 s. Moreover, peaks in the BSI signal arising from the sample injection and EOF, enable electrophoretic mobilities to readily be obtained from apparent mobilities. This leads to excellent repeatability, with analyte electrophoretic mobilities varying from 0.39 to 1.56 % RSD over eight consecutive separations. The universal detection of inorganic ions and amino acids without prior chemical modification or additives in the BGE is an advantage of refractive index detection. A disadvantage arises from modest detection limits. Here, however, we show that submicromolar detection is possible with careful thermostatting of the thin separation capillary. A series of electropherograms are used to quantify arginine concentrations from 700 nM to 500 μM, using 50 μM Li⁺ as an internal standard. The resulting calibration curve leads to a calculated LOD of 376 nM and a LOQ of 1.76 μM. Diagnostically relevant amino acid panels are also separated, illustrating the potential for future applications in neurodegenerative and metabolic disease diagnostics. HSCE combined with BSI detection, therefore, is shown to be a rapid, sensitive, and universal approach for analyzing sample mixtures.

Detection of Glycine as a Model Protein in Blood Serum Using 2D-IR Spectroscopy

Glycine (Gly) is used as a model system to evaluate the ability of ultrafast two-dimensional infrared (2D-IR) spectroscopy to detect and quantify the low-molecular-weight proteinaceous components of blood serum. Combining data acquisition schemes to suppress absorption bands of H₂O that overlap with the protein amide I band with analysis of peak patterns appearing in the off-diagonal region of the 2D-IR spectrum allows separation of the Gly spectral signature from that of the dominant protein fraction of serum in a transmission-mode 2D-IR measurement without any sample manipulation, e.g., filtration or drying. 2D-IR spectra of blood serum samples supplemented with varying concentrations of Gly were obtained, and a range of data analysis methods compared, leading to a detection limit of ∼3 mg/mL for Gly. The reported methodology provides a platform for a critical assessment of the sensitivity of 2D-IR for measuring the concentrations of amino acids, peptides, and low-molecular-weight proteins present in serum samples. We conclude that, in the case of several clinically relevant diagnostic molecules and their combinations, the potential exists for 2D-IR to complement IR absorption methods as the benefits of the second frequency dimension offered by 2D-IR spectroscopy outweigh the added technical complexity of the measurement.

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.

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.

Perspective: The Potential Role of Circulating Lysophosphatidylcholine in Neuroprotection against Alzheimer Disease

Alzheimer disease (AD), the most common cause of dementia, is a progressive disorder involving cognitive impairment, loss of learning and memory, and neurodegeneration affecting wide areas of the cerebral cortex and hippocampus. AD is characterized by altered lipid metabolism in the brain. Lower concentrations of long-chain PUFAs have been described in the frontal cortex, entorhinal cortex, and hippocampus in the brain in AD. The brain can synthesize only a few fatty acids; thus, most fatty acids must enter the brain from the blood. Recent studies show that PUFAs such as DHA (22:6) are transported across the blood-brain barrier (BBB) in the form of lysophosphatidylcholine (LPC) via a specific LPC receptor at the BBB known as the sodium-dependent LPC symporter 1 (MFSD2A). Higher dietary PUFA intake is associated with decreased risk of cognitive decline and dementia in observational studies; however, PUFA supplementation, with fatty acids esterified in triacylglycerols did not prevent cognitive decline in clinical trials. Recent studies show that LPC is the preferred carrier of PUFAs across the BBB into the brain. An insufficient pool of circulating LPC containing long-chain fatty acids could potentially limit the supply of long-chain fatty acids to the brain, including PUFAs such as DHA, and play a role in the pathobiology of AD. Whether adults with low serum LPC concentrations are at greater risk of developing cognitive decline and AD remains a major gap in knowledge. Preventing and treating cognitive decline and the development of AD remain a major challenge. The LPC pathway is a promising area for future investigators to identify modifiable risk factors for AD.

Integrated network pharmacology analysis and serum metabolomics to reveal the cognitive improvement effect of Bushen Tiansui formula on Alzheimer's disease

ETHNOPHARMACOLOGICAL RELEVANCE

Bushen Tiansui Formula (BSTSF) is a traditional Chinese medicine formula used clinically to treat Alzheimer's disease (AD) for many years. Previously, we have partially elucidated the mechanisms involved in the therapeutic effects of BSTSF on AD. However, the underlying mechanisms remain largely unclear.

AIM OF THE STUDY

The aim of this study was to further investigate the therapeutic effects of BSTSF on AD using an integrated strategy of network pharmacology and serum metabolomics.

MATERIALS AND METHODS

The rat models of AD were established using Aβ 1-42 injection, and morris water maze test was used to evaluate the efficacy of BSTSF on AD. Next, network pharmacology analysis was applied to identify the active compounds and target genes, which might be responsible for the effect of BSTSF. Then, a metabolomics strategy has been developed to find the possible significant serum metabolites and metabolic pathway induced by BSTSF. Additionally, two parts of the results were integrated to confirm each other.

RESULTS

The results of the network pharmacology analysis showed 37 compounds and 64 potential target genes related to the treatment of AD with BSTSF. The functional enrichment analysis indicated that the potential mechanism was mainly associated with the tumor necrosis factor signaling pathway and phosphatidylinositol 3 kinase/protein kinase B signaling pathway. Based on metabolomics, 78 differential endogenous metabolites were identified as potential biomarkers related to the BSTSF for treating AD. These metabolites were mainly involved in the relevant pathways of linoleic acid metabolism, α-linolenic acid metabolism, glycerophospholipid metabolism, tryptophan metabolism, and arginine and proline metabolism. These findings were partly consistent with the findings of the network pharmacology analysis.

CONCLUSIONS

In conclusion, our results solidly supported and enhanced out current understanding of the therapeutic effects of BSTSF on AD. Meanwhile, our work revealed that the proposed network pharmacology-integrated metabolomics strategy was a powerful means for identifying active components and mechanisms contributing to the pharmacological effects of traditional Chinese medicine.

Increased plasma phosphatidylcholine/lysophosphatidylcholine ratios in patients with Parkinson's disease

RATIONALE

Changes in lipid composition might be associated with the onset and progression of various neurodegenerative diseases. Herein, we investigated the changes in the plasma phosphatidylcholine (PC)/lysophosphatidylcholine (LPC) ratios in patients with Parkinson's disease (PD) in comparison with healthy subjects and their correlation with clinico-pathological features.

METHODS

The study included 10 controls and 25 patients with PD. All patients were assigned to groups based on clinico-pathological characteristics (gender, age at examination, duration of disease and Hoehn and Yahr (H&Y) stage). The analysis of the PC/LPC intensity ratios in plasma lipid extracts was performed using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry.

RESULTS

PD patients exhibited an increased PC/LPC intensity ratio in comparison with the control group of healthy subjects. Furthermore, the investigated ratio was shown to be correlated with clinico-pathological parameters, in particular with H&Y stage and disease duration. The PC/LPC intensity ratio in plasma samples of PD patients was found to be elevated in all examined H&Y stages and throughout the disease duration.

CONCLUSIONS

To our knowledge, this is the first study examining the PC/LPC ratios in plasma of patients with PD and illustrating their correlation with clinico-pathological features. Although the presented results may be considered as preliminary due to the limited number of participants, the observed alterations of PC/LPC ratios in plasma might be a first step in the characterization of plasma lipid changes in PD patients and an indicator of lipid reconfiguration.

Altered Brain Metabolome Is Associated with Memory Impairment in the rTg4510 Mouse Model of Tauopathy

Alzheimer’s disease (AD) is characterized, amongst other features, by the pathologic accumulation of abnormally phosphorylated tau filaments in neurons that lead to neurofibrillary tangles. However, the molecular mechanisms by which the abnormal processing of tau leads to neurodegeneration and cognitive impairment remain unknown. Metabolomic techniques can comprehensively assess disturbances in metabolic pathways that reflect changes downstream from genomic, transcriptomic and proteomic systems. In the present study, we undertook a targeted metabolomic approach to determine a total of 187 prenominated metabolites in brain cortex tissue from wild type and rTg4510 animals (a mice model of tauopathy), in order to establish the association of metabolic pathways with cognitive impairment. This targeted metabolomic approach revealed significant differences in metabolite concentrations of transgenic mice. Brain glutamine, serotonin and sphingomyelin C18:0 were found to be predictors of memory impairment. These findings provide informative data for future research on AD, since some of them agree with pathological alterations observed in diseased humans.

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.

Recent advances from metabolomics and lipidomics application in alzheimer's disease inspiring drug discovery

Introduction: Although age is a major risk factor for Alzheimer's disease (AD), it is not an inevitable consequence of aging nor is it exclusively an old-age disease. Several other major risk factors for AD are strongly associated with metabolism and include lack of exercise, obesity, diabetes, high blood pressure and cholesterol, over-consumption of alcohol and depression in addition to low educational level, social isolation, and cognitive inactivity. Approaches for Alzheimer prevention and treatment through manipulation of metabolism and utilization of active metabolites have great potential either as a primary or secondary treatment avenue or as a preventative strategy in high-risk individuals.Areas covered: This review outlines the current knowledge concerning the relationship between AD and metabolism and the novel treatments attempting to correct changes in AD patients determined through metabolomics or lipidomic analyses.Expert opinion: Metabolites are one of the main driving factors and indicators of AD and can offer many possible avenues for prevention and treatment. However, with the highly interconnected effects of metabolites and metabolism, as well as the many different routes for metabolism dysfunction, successful treatment would have to include the correction of metabolic errors as well as errors in transport and metabolite processing in order to affect and revert AD progression.

The standardization of cerebrospinal fluid markers and neuropathological diagnoses brings to light the frequent complexity of concomitant pathology in Alzheimer's disease: The next challenge for biochemical markers?

During the last two decades, neuropathological examination of the brain has evolved both technically and scientifically. The increasing use of immunohistochemistry to detect protein aggregates paralleled a better understanding of neuroanatomical progression of protein deposition. As a consequence, an international effort was achieved to standardize hyperphosphorylated-Tau (phospho-TAU), ßAmyloid (Aß), alpha syncuclein (alpha-syn), phosphorylated transactive response DNA-binding protein 43 (phospho-TDP43) and vascular pathology detection. Meanwhile harmonized staging systems emerged in order to increase inter rater reproducibility. Therefore, a refined definition of Alzheimer's disease was recommended., a clearer picture of the neuropathological lesions diversity emerged secondarily to the systematic assessment of concomitant pathology highlighting finally a low rate of pure AD pathology. This brings new challenges to laboratory medicine in the field of cerebrospinal fluid (CSF) markers of Alzheimer's disease: how to further validate total Tau, phospho-TAU, Aß40 and Aß42 and new marker level cut-offs while autopsy rates are declining?

Plasma lipids metabolism in mild cognitive impairment and Alzheimer's disease

OBJECTIVES

Expression of phospholipids and related molecules could provide panels of multiple biomarkers searching for the signature of Alzheimer's disease (AD). The aim of the present study was to quantify ten phospholipids and simultaneously determine phospholipase A₂ (PLA₂) activity in blood of mild cognitive impairment (MCI) and AD patients.

METHODS

Thirty-four AD, 20 MCI and 25 controls were enrolled. The phospholipids where analysed using the AbsoluteIDQ^® p180 Kit. PLA₂ activities were accessed in platelets by a radio-enzymatic assay.

RESULTS

The study failed to fix the ten phospholipids as a panel to predict AD; the levels of PCaaC36:6, PCaaC40:6 and C16:1-OH were lower in MCI than in controls (P = 0.041, P = 0.012, P = 0.044 respectively). PCaaC40:2 levels were lower in MCI than in AD (P = 0.041). The converters MCI-AD showed at baseline lower levels of PCaaC40:2 (P = 0.050) and PCaaC40:6 (P = 0.037) than controls. iPLA₂ activity was reduced in AD and MCI than in controls (P < 0.001). We found positive correlation in the control group between PCaaC38:6 and tPLA₂ (r = 0.680; P = 0.001) and sPLA₂ (r = 0.601; P = 0.004); PCaaC40:1 and iPLA₂ (r = 0.503; P = 0.020); PCaaC40:6 and tPLA₂ (r = 0.532; P = 0.013) and sPLA₂ (r = 0.523; P = 0.015).

CONCLUSIONS

Lipids metabolites in plasma might indirectly indicate changes in neuronal membrane and this deregulation can outline the transition between healthy and diseased brains.

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.

Tissue-Specific Metabolomics Analysis Identifies the Liver as a Major Organ of Metabolic Disorders in Amyloid Precursor Protein/Presenilin 1 Mice of Alzheimer's Disease

Alzheimer's disease (AD) is regarded as a metabolic disorder, and more attention has been paid to brain metabolism. However, AD may also affect metabolism in the peripheral organs beyond the brain. In this study, therefore, we investigated metabolic changes in the liver, kidney, and heart of amyloid precursor protein/presenilin 1 (APP/PS1) mice at 1, 5, and 10 months of age by using ¹H NMR-based metabolomics and chemometrics. Metabolomic results reveal that the liver was the earliest affected organ in APP/PS1 mice during amyloid pathology progression, followed by the kidney and heart. Moreover, a hypometabolic state was found in the liver of APP/PS1 mice at 5 months of age, and the disturbed metabolites were mainly involved in energy metabolism, amino acid metabolism, nucleic acid metabolism, as well as ketone and fatty acid metabolism. In conclusion, our results suggest that AD is a systemic metabolic dysfunction, and hepatic metabolic abnormality may reflect amyloid pathology progression.

Next-generation biomarker discovery in Alzheimer's disease using metabolomics - from animal to human studies

Alzheimer's disease (AD) is a complex disease driven mainly by neuronal loss due to accumulation of intracellular neurofibrillary tangles and amyloid β aggregates in the brain. The diagnosis of AD currently relies on clinical symptoms while the disease can only be confirmed at autopsy. The few available biomarkers allowing for diagnosis are typically detected many years after the onset of the disease. New diagnostic approaches, particularly in easily-accessible biofluids, are essential. By providing an exhaustive information of the phenotype, metabolomics is an ideal approach for identification of new biomarkers. This review investigates the current position of metabolomics in the field of AD research, focusing on animal and human studies, and discusses the improvements carried out over the past decade.

Lab-on-chip technology for chronic disease diagnosis

Various types of chronic diseases (CD) are the leading causes of disability and death worldwide. While those diseases are chronic in nature, accurate and timely clinical decision making is critically required. Current diagnosis procedures are often lengthy and costly, which present a major bottleneck for effective CD healthcare. Rapid, reliable and low-cost diagnostic tools at point-of-care (PoC) are therefore on high demand. Owing to miniaturization, lab-on-chip (LoC) technology has high potential to enable improved biomedical applications in terms of low-cost, high-throughput, ease-of-operation and analysis. In this direction, research toward developing new LoC-based PoC systems for CD diagnosis is fast growing into an emerging area. Some studies in this area began to incorporate digital and mobile technologies. Here we review the recent developments of this area with the focus on chronic respiratory diseases (CRD), diabetes, and chronic kidney diseases (CKD). We conclude by discussing the challenges, opportunities and future perspectives of this field.

Lysophospholipid-Related Diseases and PPARγ Signaling Pathway

The nuclear receptor superfamily includes ligand-inducible transcription factors that play diverse roles in cell metabolism and are associated with pathologies such as cardiovascular diseases. Lysophosphatidic acid (LPA) belongs to a family of lipid mediators. LPA and its naturally occurring analogues interact with G protein-coupled receptors on the cell surface and an intracellular nuclear hormone receptor. In addition, several enzymes that utilize LPA as a substrate or generate it as a product are under its regulatory control. Recent studies have demonstrated that the endogenously produced peroxisome proliferator-activated receptor gamma (PPARγ) antagonist cyclic phosphatidic acid (cPA), which is structurally similar to LPA, inhibits cancer cell invasion and metastasis in vitro and in vivo. We recently observed that cPA negatively regulates PPARγ function by stabilizing the binding of the co-repressor protein, a silencing mediator of retinoic acid, and the thyroid hormone receptor. We also showed that cPA prevents neointima formation, adipocyte differentiation, lipid accumulation, and upregulation of PPARγ target gene transcription. The present review discusses the arbitrary aspects of the physiological and pathophysiological actions of lysophospholipids in vascular and nervous system biology.

Metabolic profiling of the effects of ginsenoside Re in an Alzheimer's disease mouse model

Alzheimer's disease (AD) is one of the major neurological diseases among the elderly, and there are presently no approved treatments that can slow its progression. It has been reported that ginsenoside Re (G-Re), an active pharmacological component of ginseng, can ameliorate the symptoms of AD, but the underlying mechanisms are not clear. The current study was designed to test the effects of G-Re by investigating the metabolite profiles of AD mice. An AD animal model was induced by intracerebroventricular injection of β-amyloid in Kunming mice. Model mice were administered G-Re intragastrically (4mg/kg/day as a high dose and 1mg/kg/day as a low dose) for 30days. Cognitive function of the mice was tested using a Morris water maze, and pathological changes in the brain tissue were assessed by immunohistochemistry. Global metabolite profiling using ultra performance liquid chromatography-mass spectrometry was carried out to identify the metabolites that were differentially expressed in the plasma of mice. A total of 10 potential biomarkers were identified in AD mice. The peak intensities of tryptophan, hexadecasphinganine, phytosphingosine, and various lysophosphatidylcholines were lower whereas that of phenylalanine was higher in the AD mice than in the control mice. G-Re treatment (4mg/kg) affected all of these metabolic pathways. This is the first metabonomics study to biochemically profile the plasma metabolic pathways of AD animals affected by G-Re. These outcomes provide reliable evidence that illuminates the biochemical mechanisms of AD and facilitates investigation of the therapeutic benefits of G-Re in AD treatment.

Effects of breviscapine on amyloid beta 1-42 induced Alzheimer's disease mice: A HPLC-QTOF-MS based plasma metabonomics study

Herba Erigerontis has long been used to cure apoplexy hemiplegia and precordial pain in China. In addition, the bioactivities of its total flavonoids-breviscapine included inhibiting amyloid beta (Aβ) fibril formation, antioxidation and metal chelating, which are beneficial to treat Alzheimer's disease (AD). Hence, A HPLC-QTOF-MS based plasma metabonomics approach was applied to investigate the neuroprotective effects of breviscapine on intracerebroventricular injection of aggregated Aβ 1-42 induced AD mice for the first time in the study. Ten potential biomarkers were screened out by multivariate statistical analysis, eight of which were further identified as indoleacrylic acid, C16 sphinganine, LPE (22:6), sulfolithocholic acid, LPC (16:0), PA (22:1/0:0), taurodeoxycholic acid, and PC (0:0/18:0). According to their metabolic pathways, it was supposed that breviscapine ameliorated the learning and memory deficits of AD mice predominantly by regulating phospholipids metabolism, elevating serotonin level and lowering cholesterols content in vivo.

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.

Metabolomics for the masses: The future of metabolomics in a personalized world

Current clinical practices focus on a small number of biochemical directly related to the pathophysiology with patients and thus only describe a very limited metabolome of a patient and fail to consider the interations of these small molecules. This lack of extended information may prevent clinicians from making the best possible therapeutic interventions in sufficient time to improve patient care. Various post-genomics '('omic)' approaches have been used for therapeutic interventions previously. Metabolomics now a well-established'omics approach, has been widely adopted as a novel approach for biomarker discovery and in tandem with genomics (especially SNPs and GWAS) has the potential for providing systemic understanding of the underlying causes of pathology. In this review, we discuss the relevance of metabolomics approaches in clinical sciences and its potential for biomarker discovery which may help guide clinical interventions. Although a powerful and potentially high throughput approach for biomarker discovery at the molecular level, true translation of metabolomics into clinics is an extremely slow process. Quicker adaptation of biomarkers discovered using metabolomics can be possible with novel portable and wearable technologies aided by clever data mining, as well as deep learning and artificial intelligence; we shall also discuss this with an eye to the future of precision medicine where metabolomics can be delivered to the masses.

What success can teach us about failure: the plasma metabolome of older adults with superior memory and lessons for Alzheimer's disease

As the world population ages, primary prevention of age-related cognitive decline and disability will become increasingly important. Prevention strategies are often developed from an understanding of disease pathobiology, but models of biological success may provide additional useful insights. Here, we studied 224 older adults, some with superior memory performance (n = 41), some with normal memory performance (n = 109), and some with mild cognitive impairment or Alzheimer's disease (AD; n = 74) to understand metabolomic differences which might inform future interventions to promote cognitive health. Plasma metabolomics revealed significant differential abundance of 12 metabolites in those with superior memory relative to controls (receiver operating characteristic area under the curve [AUC] = 0.89) and the inverse abundance pattern in the mild cognitive impairment, AD (AUC = 1.0) and even preclinical AD groups relative to controls (AUC = 0.97). The 12 metabolites are components of key metabolic pathways regulating oxidative stress, inflammation, and nitric oxide bioavailability. These findings from opposite ends of the cognitive continuum highlight the role of these pathways in superior memory abilities and whose failure may contribute to age-related memory impairment. These pathways may be targeted to promote successful cognitive aging.

Endogenous N-acyl taurines regulate skin wound healing

The intracellular serine amidase, fatty acid amide hydrolase (FAAH), degrades a heterogeneous family of lipid-derived bioactive molecules that include amides of long-chain fatty acids with taurine [N-acyl-taurines (NATs)]. The physiological functions of the NATs are unknown. Here we show that genetic or pharmacological disruption of FAAH activity accelerates skin wound healing in mice and stimulates motogenesis of human keratinocytes and differentiation of human fibroblasts in primary cultures. Using untargeted and targeted lipidomics strategies, we identify two long-chain saturated NATs-N-tetracosanoyl-taurine [NAT(24:0)] and N-eicosanoyl-taurine [NAT(20:0)]-as primary substrates for FAAH in mouse skin, and show that the levels of these substances sharply decrease at the margins of a freshly inflicted wound to increase again as healing begins. Additionally, we demonstrate that local administration of synthetic NATs accelerates wound closure in mice and stimulates repair-associated responses in primary cultures of human keratinocytes and fibroblasts, through a mechanism that involves tyrosine phosphorylation of the epidermal growth factor receptor and an increase in intracellular calcium levels, under the permissive control of transient receptor potential vanilloid-1 receptors. The results point to FAAH-regulated NAT signaling as an unprecedented lipid-based mechanism of wound-healing control in mammalian skin, which might be targeted for chronic wound therapy.

Gender differences of peripheral plasma and liver metabolic profiling in APP/PS1 transgenic AD mice

Alzheimer's disease (AD) is a neurodegenerative disorder characterized by progressive cognitive impairment. Currently, there is less knowledge of the involvement of the peripheral biofluid/organ in AD, compared with the central nervous system. In addition, with reported high morbidity in women in particular, it has become very important to explore whether gender difference in the peripheral metabolome is associated with AD. Here, we investigated metabolic responses of both plasma and liver tissues using an APP/PS1 double mutant transgenic mouse model with NMR spectroscopy, as well as analysis from serum biochemistry and histological staining. Fatty acid composition from plasma and liver extracts was analyzed using GC-FID/MS. We found clear gender differences in AD transgenic mice when compared with their wild-type counterparts. Female AD mice displayed more intensive responses, which were highlighted by higher levels of lipids, 3-hydroxybutyrate and nucleotide-related metabolites, together with lower levels of glucose. These observations indicate that AD induces oxidative stress and impairs cellular energy metabolism in peripheral organs. Disturbances in AD male mice were milder with depletion of monounsaturated fatty acids. We also observed a higher activity of delta-6-desaturate and suppressed activity of delta-5-desaturate in female mice, whereas inhibited stearoyl-CoA-desaturase in male mice suggested that AD induced by the double mutant genes results in different fatty acids catabolism depending on gender. Our results provide metabolic clues into the peripheral biofluid/organs involved in AD, and we propose that a gender-specific scheme for AD treatment in men and women may be required.