Evidence of altered phosphatidylcholine metabolism in Alzheimer's disease

Saturated and poly-unsaturated fat-rich dietary supplements during adolescence restore risky decision-making behaviour in rats pre-exposed to early-life stress

Previous studies suggest that early-life stress (ELS) induced by early maternal separation and isolation (MS) stress during the stress hyporesponsive period (SHRP) leads to increased curiosity-like and increased risky decision-making behaviour in adolescence. Evidence suggests that dietary interventions early in adolescence could play an important role in mitigating the detrimental effects of MS stress on risky decision-making behaviour. Hence, the present study hypothesized that nutritional supplements such as saturated fat (SFA) and/or polyunsaturated fat (PUFA) would be beneficial in ameliorating the impact of MS stress on risky decision-making behaviour when incorporated into the diet during early adolescence. NC and MS rats were subjected to the Risky Decision-Taking Task (RDTT) to assess the rats' ability to make decisions under risky conditions. The results showed that MS rats took less time to cross the risky zone to collect a large reward. However, when an SFA-rich and PUFA-rich diet was provided, the latency of the MS rats increased. Similarly, MS stress-induced reduction in risk assessment was restored to normal with the SFA and PUFA-rich diet. Risk-index (RI) values also showed a similar trend with reduced RI values in MS, but nutritional supplementation increased the RI values making it comparable to that NC. Correlation analysis has further revealed a direct correlation between the anxiety-like behaviour and the risk-taking tendency in MS rats and not in the NC group. SFA-rich diet led to a positive correlation between anxiety-like and risk-taking behaviour. These findings thus support the hypothesis that PUFA- and SFA-rich diet may be introduced at adolescence to mitigate MS-stress induced increased risky decision-making behaviour due to a deficit in risk assessment.

Improving quantification accuracy of a nuclear Overhauser enhancement signal at -1.6 ppm at 4.7 T using a machine learning approach

Objective.A new nuclear Overhauser enhancement (NOE)-mediated saturation transfer MRI signal at -1.6 ppm, potentially from choline phospholipids and termed NOE(-1.6), has been reported in biological tissues at high magnetic fields. This signal shows promise for detecting brain tumors and strokes. However, its proximity to the water peak and low signal-to-noise ratio makes accurate quantification challenging, especially at low fields, due to the difficulty in separating it from direct water saturation and other confounding signals. This study proposes using a machine learning (ML) method to address this challenge.Approach.The ML model was trained on a partially synthetic chemical exchange saturation transfer dataset with a curriculum learning denoising approach. The accuracy of our method in quantifying NOE(-1.6) was validated using tissue-mimicking data from Bloch simulations providing ground truth, with subsequent application to an animal tumor model at 4.7 T. The predictions from the proposed ML method were compared with outcomes from traditional Lorentzian fit and ML models trained on other data types, including measured and fully simulated data.Main results.Our tissue-mimicking validation suggests that our method offers superior accuracy compared to all other methods. The results from animal experiments show that our method, despite variations in training data size or simulation models, produces predictions within a narrower range than the ML method trained on other data types.Significance.The ML method proposed in this work significantly enhances the accuracy and robustness of quantifying NOE(-1.6), thereby expanding the potential for applications of this novel molecular imaging mechanism in low-field environments.

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 metabolic alterations in chickens upon infectious bursal disease virus infection

BACKGROUND

Infectious bursal disease virus (IBDV) is a highly contagious immunosuppressive virus of chickens. Chickens acquire infection by the oral route under natural conditions. Although the histological and pathological changes after IBDV infection are well described, the alterations in serum metabolome have not been reported. In this study, SPF chickens were infected with attenuated IBDV (atIBDV) strain LM and very virulent IBDV (vvIBDV) strain LX, respectively. On the seventh day after oral infection, serum samples of experimental chickens were identified using ultra-high performance liquid chromatography-MS/MS (UHPLC-MS/MS). The serum metabolic profiles were analyzed by multivariate statistical methods. KEGG enrichment analysis was performed to evaluate the dysregulated biological pathways.

RESULTS

We identified 368 significantly altered metabolites in response to both atIBDV and vvIBDV infection. The metabolic disorder of amino acid and lipid was associated with IBDV infection, especially tryptophan, glycerophospholipid, lysine, and tyrosine metabolism. The differential metabolites enriched in the four metabolic pathways were PC(20:4(5Z,8Z,11Z,14Z)/18:0), PE(16:0/18:2(9Z,12Z)), PE(16:0/22:6(4Z,7Z,10Z,13Z,16Z,19Z)), PE(18:0/20:4(5Z,8Z,11Z,14Z)), PE(18:0/20:4(8Z,11Z,14Z,17Z)), PE(18:0/22:6(4Z,7Z,10Z,13Z,16Z,19Z)), PE(20:3(8Z,11Z,14Z)/16:0), PE(22:6(4Z,7Z,10Z,13Z,16Z,19Z)/16:0), PE-NMe(20:5(5Z,8Z,11Z,14Z,17Z)/18:0), PS(20:3(5Z,8Z,11Z)/18:2(9Z,12Z)), 2-aminobenzoic acid, 4-(2-aminophenyl)-2,4-dioxobutanoic acid, N-acetylserotonin, 5-hydroxyindoleacetate, indole-3-acetaldehyde, indole-3-acetate, p-coumaric acid, L-tyrosine, homovanillin, and S-glutaryldihydrolipoamide.

CONCLUSION

The atIBDV and vvIBDV infection causes metabolic changes in chicken serum. The differential metabolites and dysregulated metabolic pathways reflect the host response to the IBDV infection.

The role of cerebrospinal fluid metabolites in mediating the impact of lipids on Late-Onset Alzheimer's Disease: a two-step mendelian randomization analysis

BACKGROUND

Although research has indicated correlations between lipids, cerebrospinal fluid (CSF) metabolites, and Late-Onset Alzheimer's Disease (LOAD), the specific causal relationships among these elements, as well as the roles and mechanisms of the cerebrospinal fluid metabolites, remain unclear.

METHODS

Statistical datasets derived from Genome-Wide Association Studies (GWAS) were utilized to assess the bidirectional causal relationships between lipids and LOAD. Subsequently, genetic variants associated with CSF metabolites and established lipids underwent a two-step Mendelian randomization (MR) analysis to explore potential mediators and analyze mediation effects. Sensitivity analyses were employed to assess the robustness of the detection systems.

RESULTS

Genetically predicted cholesterol (IVW OR = 0.989; 95% CI 0.982-0.996) was found to reduce the risk of LOAD, whereas Phosphatidylcholine (PC) (18:1_0:0) (IVW OR = 1.015; 95% CI 1.005-1.025) posed a risk factor. The potential mediator, CSF metabolite N-acetylneuraminate (NeuAC), was identified with a mediation proportion of 21.02% (3.25%, 45.50%). No pleiotropy or heterogeneity was detected across MR analyses.

CONCLUSIONS

The findings underscore the pivotal role of CSF metabolomics in elucidating the lipid-mediated pathogenesis of LOAD, highlighting potential diagnostic and preventative biomarkers.

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.

Palmitoyl-L-carnitine induces tau phosphorylation and mitochondrial dysfunction in neuronal cells

Alzheimer's disease (AD) is characterized by cognitive decline and memory loss, involving mechanisms such as tau hyperphosphorylation and mitochondrial dysfunction. Increasing evidence suggests that age-related alterations in metabolite levels are crucial for the pathogenesis of AD. Here, we analyzed serum metabolites from mice of various ages (2, 4, 14, and 21 months old) using mass spectrometry. We identified palmitoyl-L-carnitine as a key metabolite with significantly increased levels in aged mice. In vitro experiments with SH-SY5Y neuronal cells demonstrated that palmitoyl-L-carnitine treatment enhanced tau phosphorylation, increased mitochondrial fission, and elevated intracellular calcium levels. Furthermore, the increased levels of tau phosphorylation were significantly reduced by the inhibition of GSK-3β, CDK5, and calpain, indicating that tau kinases activated by calcium overload are directly involved in the increase of tau phosphorylation. Considering that mitochondrial fission is related to mitochondrial dysfunction, we propose that the elevated level of serum palmitoyl-L-carnitine during aging contributes to AD pathology through these pathways. These findings highlight the significant role of lipid metabolism in neurodegeneration and offer potential therapeutic targets for age-related diseases, including AD.

Nuclear Magnetic Resonance Analysis Implicates Sex-Specific Dysregulation of the Blood Lipids in Alzheimer's Disease: A Retrospective Health-Controlled Study

OBJECTIVE

The aging demographic landscape worldwide portends a heightened prevalence of neurodegenerative disorders. Foremost among these is Alzheimer's disease (AD), the foremost cause of dementia in older adults. The shortage of efficacious therapies and early diagnostic indicators underscores the imperative to identify non-invasive biomarkers for early detection and disease monitoring. Recently, blood metabolites have emerged as promising candidates for AD biomarkers.

METHODS

Leveraging nuclear magnetic resonance (NMR) spectroscopy on plasma specimens, we conducted a cross-sectional study encompassing 35 AD patients and 35 age-matched healthy controls. Cognitive function was evaluated using the mini-mental state examination in all participants, followed by peripheral blood sample collection. We utilized univariate and multivariate analyses to perform targeted lipidomic profiling via NMR spectroscopy.

RESULTS

Our study revealed significant differences in the expression profiles of low-density lipoprotein-associated subfractions in females and high-density lipoprotein-associated subfractions in males between AD patients and healthy controls (all p<0.05). However, there was no significant metabolite overlap between males and females. Furthermore, receiver operating characteristic curve analysis demonstrated that the combination of lipid metabolites had good diagnostic values (all area under the curve>0.70; p<0.05).

CONCLUSION

Our findings suggest that the blood plasma samples using NMR hold promise in distinguishing between AD patients and healthy controls, with significant clinical implications for advancing AD diagnostic methodologies.

α-synuclein overexpression and the microbiome shape the gut and brain metabolome in mice

Pathological forms of α-synuclein contribute to synucleinopathies, including Parkinson's disease (PD). Most cases of PD arise from gene-environment interactions. Microbiome composition is altered in PD, and gut bacteria are causal to symptoms in animal models. We quantitatively profiled nearly 630 metabolites in the gut, plasma, and brain of α-synuclein-overexpressing (ASO) mice, compared to wild-type (WT) animals, and comparing germ-free (GF) to specific pathogen-free (SPF) animals (n = 5 WT-SPF; n = 6 ASO-SPF; n = 6 WT-GF; n = 6 ASO-GF). Many differentially expressed metabolites in ASO mice are also dysregulated in human PD patients, including amine oxides, bile acids and indoles. The microbial metabolite trimethylamine N-oxide (TMAO) strongly correlates from the gut to the plasma to the brain in mice, notable since TMAO is elevated in the blood and cerebrospinal fluid of PD patients. These findings uncover broad metabolomic changes that are influenced by the intersection of host genetics and microbiome in a mouse model of PD.

Plasma lipidomic signatures of dementia with Lewy bodies revealed by machine learning, and compared to alzheimer's disease

BACKGROUND

Dementia with Lewy Bodies (DLB) is a complex neurodegenerative disorder that often overlaps clinically with Alzheimer's disease (AD), presenting challenges in accurate diagnosis and underscoring the need for novel biomarkers. Lipidomic emerges as a promising avenue for uncovering disease-specific metabolic alterations and potential biomarkers, particularly as the lipidomics landscape of DLB has not been previously explored. We aim to identify potential diagnostic biomarkers and elucidate the disease's pathophysiological mechanisms.

METHODS

This study conducted a lipidomic analysis of plasma samples from patients with DLB, AD, and healthy controls (HCs) at Xuanwu Hospital. Untargeted plasma lipidomic profiling was conducted via liquid chromatography coupled with mass spectrometry. Machine learning methods were employed to discern lipidomic signatures specific to DLB and to differentiate it from AD.

RESULTS

The study enrolled 159 participants, including 57 with AD, 48 with DLB, and 54 HCs. Significant differences in lipid profiles were observed between the DLB and HC groups, particularly in the classes of sphingolipids and phospholipids. A total of 55 differentially expressed lipid species were identified between DLB and HCs, and 17 between DLB and AD. Correlations were observed linking these lipidomic profiles to clinical parameters like Unified Parkinson's Disease Rating Scale III (UPDRS III) and cognitive scores. Machine learning models demonstrated to be highly effective in distinguishing DLB from both HCs and AD, achieving substantial accuracy through the utilization of specific lipidomic signatures. These include PC(15:0_18:2), PC(15:0_20:5), and SPH(d16:0) for differentiation between DLB and HCs; and a panel includes 13 lipid molecules: four PCs, two PEs, three SPHs, two Cers, and two Hex1Cers for distinguishing DLB from AD.

CONCLUSIONS

This study presents a novel and comprehensive lipidomic profile of DLB, distinguishing it from AD and HCs. Predominantly, sphingolipids (e.g., ceramides and SPHs) and phospholipids (e.g., PE and PC) were the most dysregulated lipids in relation to DLB patients. The lipidomics panels identified through machine learning may serve as effective plasma biomarkers for diagnosing DLB and differentiating it from AD dementia.

Multi-omics analysis reveals the key factors involved in the severity of the Alzheimer's disease

Alzheimer's disease (AD) is a debilitating neurodegenerative disorder with a global impact, yet its pathogenesis remains poorly understood. While age, metabolic abnormalities, and accumulation of neurotoxic substances are potential risk factors for AD, their effects are confounded by other factors. To address this challenge, we first utilized multi-omics data from 87 well phenotyped AD patients and generated plasma proteomics and metabolomics data, as well as gut and saliva metagenomics data to investigate the molecular-level alterations accounting the host-microbiome interactions. Second, we analyzed individual omics data and identified the key parameters involved in the severity of the dementia in AD patients. Next, we employed Artificial Intelligence (AI) based models to predict AD severity based on the significantly altered features identified in each omics analysis. Based on our integrative analysis, we found the clinical relevance of plasma proteins, including SKAP1 and NEFL, plasma metabolites including homovanillate and glutamate, and Paraprevotella clara in gut microbiome in predicting the AD severity. Finally, we validated the predictive power of our AI based models by generating additional multi-omics data from the same group of AD patients by following up for 3 months. Hence, we observed that these results may have important implications for the development of potential diagnostic and therapeutic approaches for AD patients.

Identification of the Metabolic Signature of Aging Retina

Purpose

This study aims to explore the metabolic signature of aging retina and identify the potential metabolic biomarkers for the diagnosis of retinal aging.

Methods

Retinal samples were collected from both young (two months) and aging (14 months) mice to conduct an unbiased metabolic profiling. Liquid chromatography-tandem mass spectrometry analysis was conducted to screen for the metabolic biomarkers and altered signaling pathways associated with retinal aging.

Results

We identified 166 metabolites differentially expressed between young and aged retinas using a threshold of orthogonal projection to latent structures discriminant analysis variable importance in projection >1 and P < 0.05. These metabolites were significantly enriched in several metabolic pathways, including purine metabolism, citrate cycle, phenylalanine, tyrosine and tryptophan biosynthesis, glycerophospholipid metabolism, and alanine, aspartate and glutamate metabolism. Among these significantly enriched pathways, glycerophospholipid metabolites emerged as promising candidates for retinal aging biomarkers. We assessed the potential of these metabolites as biomarkers through an analysis of their sensitivity and specificity, determined by the area under the receiver-operating characteristic (ROC) curves. Notably, the metabolites like PC (15:0/22:6), PC (17:0/14:1), LPC (P-16:0), PE (16:0/20:4), and PS (17:0/16:1) demonstrated superior performance in sensitivity, specificity, and accuracy in predicting retinal aging.

Conclusions

This study sheds light on the molecular mechanisms underlying retinal aging by identifying distinct metabolic profiles and pathways. These findings provide a valuable foundation for developing future clinical applications in diagnosing, identifying, and treating age-related retinal degeneration.

Translational Relevance

This study sheds light on novel metabolic profiles and biomarkers in aging retinas, potentially paving the way for targeted interventions in preventing, diagnosing, and treating age-related retinal degeneration and other retinal diseases.

Double Cyclization Tandem Mass for Identification and Quantification of Phosphatidylcholines Using Isobaric Six-Plex Capillary nLC-MS/MS

Multiplexing of phosphatidylcholine analysis is hindered by a lack of appropriate derivatization. Presented here is a tagging scheme that uses a quaternary amine tag and targets the hydroxy group of the phosphate, which switches the net charge from neutral to +2. Quantitative yields were achieved from >99% reaction completion derived by dimethoxymethyl morpholinium (DMTMM) activation. Fragmentation of phosphatidylcholines (PCs) and lysophosphatidylcholines (LPCs) releases two trimethylamines and the acyl chains through neutral loss and generates a unique double cyclization constant mass reporter. Selective incorporation of isotopes onto the tag produces a six-plex set of isobaric reagents. For equivalent six-plex-labeled samples, <14% RSD was achieved, followed by a dynamic range of 1:10 without signal compression. Quantification of PCs/LPCs in human hepatic cancer cells was conducted as six-plex using data-dependent analysis tandem MS. We report a six-plex qualitative and quantitative isobaric tagging strategy expanding the limits of analyzing PCs/LPCs.

α-Synuclein Overexpression and the Microbiome Shape the Gut and Brain Metabolome in Mice

Pathological forms of the protein α-synuclein contribute to a family of disorders termed synucleinopathies, which includes Parkinson's disease (PD). Most cases of PD are believed to arise from gene-environment interactions. Microbiome composition is altered in PD, and gut bacteria are causal to symptoms and pathology in animal models. To explore how the microbiome may impact PD-associated genetic risks, we quantitatively profiled nearly 630 metabolites from 26 biochemical classes in the gut, plasma, and brain of α-synuclein-overexpressing (ASO) mice with or without microbiota. We observe tissue-specific changes driven by genotype, microbiome, and their interaction. Many differentially expressed metabolites in ASO mice are also dysregulated in human PD patients, including amine oxides, bile acids and indoles. Notably, levels of the microbial metabolite trimethylamine N-oxide (TMAO) strongly correlate from the gut to the plasma to the brain, identifying a product of gene-environment interactions that may influence PD-like outcomes in mice. TMAO is elevated in the blood and cerebral spinal fluid of PD patients. These findings uncover broad metabolomic changes that are influenced by the intersection of host genetics and the microbiome in a mouse model of PD.

Exploring the significance of lipids in Alzheimer's disease and the potential of extracellular vesicles

Lipids play a significant role in maintaining central nervous system (CNS) structure and function, and the dysregulation of lipid metabolism is known to occur in many neurological disorders, including Alzheimer's disease. Here we review what is currently known about lipid dyshomeostasis in Alzheimer's disease. We propose that small extracellular vesicle (sEV) lipids may provide insight into the pathophysiology and progression of Alzheimer's disease. This stems from the recognition that sEV likely contributes to disease pathogenesis, but also an understanding that sEV can serve as a source of potential biomarkers. While the protein and RNA content of sEV in the CNS diseases have been studied extensively, our understanding of the lipidome of sEV in the CNS is still in its infancy.

Transcriptomic Analysis of Lipid Metabolism Genes in Alzheimer's Disease: Highlighting Pathological Outcomes and Compartmentalized Immune Status

The dysregulation of lipid metabolism has been strongly associated with Alzheimer's disease (AD) and has intricate connections with various aspects of disease progression, such as amyloidogenesis, bioenergetic deficit, oxidative stress, neuroinflammation, and myelin degeneration. Here, a comprehensive bioinformatic assessment was conducted on lipid metabolism genes in the brains and peripheral blood of AD-derived transcriptome datasets, characterizing the correlation between differentially expressed genes (DEGs) of lipid metabolism and disease pathologies, as well as immune cell preferences. Through the application of weighted gene co-expression network analysis (WGCNA), modules eigengenes related to lipid metabolism were pinpointed, and the examination of their molecular functions within biological processes, molecular pathways, and their associations with pathological phenotypes and molecular networks has been characterized. Analysis of biological networks indicates notable discrepancies in the expression patterns of the DEGs between neuronal and immune cells, as well as variations in cell type enrichments within both brain tissue and peripheral blood. Additionally, drugs targeting the DEGs from central and peripheral and a diagnostic model for hub genes from the blood were retrieved and assessed, some of which were shown to be useful for therapeutic and diagnostic. These results revealed the distinctive pattern of transcriptionally abnormal lipid metabolism in central, peripheral, and immune cell activation, providing valuable insight into lipid metabolism for diagnosing and guiding more effective treatment for AD.

Integration of metabolomics and transcriptomics reveals that Da Chuanxiong Formula improves vascular cognitive impairment via ACSL4/GPX4 mediated ferroptosis

ETHNOPHARMACOLOGICAL RELEVANCE

Da Chuanxiong Formula (DCX) is a traditional herbal compound composed of Gastrodia elata Bl. and Ligusticum chuanxiong Hort, which could significantly enhance blood circulation and neuroprotection, showing promise in treating Vascular Cognitive Impairment (VCI).

AIM OF STUDY

This study aims to elucidate the potential of DCX in treating VCI and its underlying mechanism.

MATERIALS AND METHODS

Firstly, the cognitive behavior level, blood flow changes, and brain pathology changes were evaluated through techniques such as the Morris water maze, step-down, laser speckle, coagulation analysis, and pathological staining to appraise the DCX efficacy. Then, the DCX targeting pathways were decoded by merging metabolomics with transcriptomics. Finally, the levels of reactive oxygen species (ROS), Fe2+, and lipid peroxidation related to the targeting signaling pathways of DCX were detected by kit, and the expression levels of mRNAs or proteins related to ferroptosis were determined by qPCR or Western blot assays respectively.

RESULTS

DCX improved cognitive abilities and cerebral perfusion significantly, and mitigated pathological damage in the hippocampal region of VCI model rats. Metabolomics revealed that DCX was able to call back 33 metabolites in plasma and 32 metabolites in brain samples, and the majority of the differential metabolites are phospholipid metabolites. Transcriptomic analysis revealed that DCX regulated a total of 3081 genes, with the ferroptosis pathway exhibiting the greatest impact. DCX inhibited ferroptosis of VCI rates by decreasing the levels of ferrous iron, ROS, and malondialdehyde (MDA) while increasing the level of superoxide dismutase (SOD) and glutathione (GSH) in VCI rats. Moreover, the mRNA and protein levels of ACSL4, LPCAT3, ALOX15, and GPX4, which are related to lipid metabolism in ferroptosis, were also regulated by DCX.

CONCLUSION

Our research findings indicated that DCX could inhibit ferroptosis through the ACSL4/GPX4 signaling pathway, thereby exerting its therapeutic benefits on VCI.

Dynamic changes in the mouse hepatic lipidome following warm ischemia reperfusion injury

Liver failure secondary to metabolic dysfunction-associated steatotic liver disease (MASLD) has become the most common cause for liver transplantation in many parts of the world. Moreover, the prevalence of MASLD not only increases the demand for liver transplantation, but also limits the supply of suitable donor organs because steatosis predisposes grafts to ischemia-reperfusion injury (IRI). There are currently no pharmacological interventions to limit hepatic IRI because the mechanisms by which steatosis leads to increased injury are unclear. To identify potential novel mediators of IRI, we used liquid chromatography and mass spectrometry to assess temporal changes in the hepatic lipidome in steatotic and non-steatotic livers after warm IRI in mice. Our untargeted analyses revealed distinct differences between the steatotic and non-steatotic response to IRI and highlighted dynamic changes in lipid composition with marked changes in glycerophospholipids. These findings enhance our knowledge of the lipidomic changes that occur following IRI and provide a foundation for future mechanistic studies. A better understanding of the mechanisms underlying such changes will lead to novel therapeutic strategies to combat IRI.

Novel Structure-Driven Predict-to-Hit Strategy for PC Double Bond Positional Isomer Identification Based on Negative LC-MRM Analysis

As the predominant phospholipids in mammalian cells, phosphatidylcholines (PCs) have been demonstrated to play a crucial role in a multitude of vital biological processes. Research has highlighted the significance of the diversity in PC isomers as instigators of both physiological and pathological responses, particularly those with variations in the position of double bonds within their fatty chains. Profiling these PC isomers is paramount to advancing our understanding of their biological functions. Despite the availability of analytical methods utilizing high-resolution secondary mass spectrometry (MS2) fragmentation, a novel approach was imperative to facilitate large-scale profiling of PC isomers while ensuring accessibility, facility, and reliability. In this study, an innovative strategy centered around structure-driven predict-to-hit profiling of the double bond positional isomers for PCs was meticulously developed, employing negative reversed-phase liquid chromatography-multiple reaction monitoring (RPLC-MRM). This novel methodology heightened the sensitivity. The analysis of rat lung tissue samples resulted in the identification of 130 distinct PC isomers. This approach transcended the confines of available PC isomer standards, thereby broadening the horizons of PC-related biofunction investigations. By optimizing the quantitation reliability, the scale of sample analysis was judiciously managed. This work pioneers a novel paradigm for the exploration of PC isomers, distinct from the conventional methods reliant on high-resolution mass spectrometry (HRMS). It equips researchers with potent tools to further explore the biofunctional aspects of lipids.

Choline metabolism in regulating inflammatory bowel disease-linked anxiety disorders: A multi-omics exploration of the gut-brain axis

Anxiety and depression caused by inflammatory bowel disease (IBD) negatively affect the mental health of patients. Emerging studies have demonstrated that the gut-brain axis (GBA) mediates IBD-induced mood disorders, but the underlying mechanisms of these findings remain unknown. Therefore, it's vital to conduct comprehensive research on the GBA in IBD. Multi-omics studies can provide an understanding of the pathological mechanisms of the GBA in the development of IBD, helping to uncover the mechanisms underlying the onset and progression of the disease. Thus, we analyzed the prefrontal cortex (PFC) of Dextran Sulfate Sodium Salt (DSS)-induced IBD mice using transcriptomics and metabolomics. We observed increased mRNA related to acetylcholine synthesis and secretion, along with decreased phosphatidylcholine (PC) levels in the PFC of DSS group compared to the control group. Fecal metagenomics also revealed abnormalities in the microbiome and lipid metabolism in the DSS group. Since both acetylcholine and PC are choline metabolites, we posited that the DSS group may experience choline deficiency and choline metabolism disorders. Subsequently, when we supplemented CDP-choline, IBD mice exhibited improvements, including decreased anxiety-like behaviors, reduced PC degradation, and increased acetylcholine synthesis in the PFC. In addition, administration of CDP-choline can restore imbalances in the gut microbiome and disruptions in lipid metabolism caused by DSS treatment. This study provides compelling evidence to suggest that choline metabolism plays a crucial role in the development and treatment of mood disorders in IBD. Choline and its metabolites appear to have a significant role in maintaining the stability of the GBA.

Multi-Omic Blood Biomarkers as Dynamic Risk Predictors in Late-Onset Alzheimer's Disease

Late-onset Alzheimer's disease is the leading cause of dementia worldwide, accounting for a growing burden of morbidity and mortality. Diagnosing Alzheimer's disease before symptoms are established is clinically challenging, but would provide therapeutic windows for disease-modifying interventions. Blood biomarkers, including genetics, proteins and metabolites, are emerging as powerful predictors of Alzheimer's disease at various timepoints within the disease course, including at the preclinical stage. In this review, we discuss recent advances in such blood biomarkers for determining disease risk. We highlight how leveraging polygenic risk scores, based on genome-wide association studies, can help stratify individuals along their risk profile. We summarize studies analyzing protein biomarkers, as well as report on recent proteomic- and metabolomic-based prediction models. Finally, we discuss how a combination of multi-omic blood biomarkers can potentially be used in memory clinics for diagnosis and to assess the dynamic risk an individual has for developing Alzheimer's disease dementia.

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.

The effect of lipid metabolism on age-associated cognitive decline: Lessons learned from model organisms and human

Lipids are required as integral building blocks of cells to support cellular structures and functions. The intricate mechanisms underpinning lipid homeostasis are essential for the health and maintenance of the central nervous system. Here we summarize the recent advances in dissecting the effect of lipid metabolism on cognitive function and its age-associated decline by reviewing relevant studies ranging from invertebrate model organisms to mammals including human.

Longitudinal associations between metabolites and immediate, short- and medium-term exposure to ambient air pollution: Results from the KORA cohort study

BACKGROUND

Short-term exposure to air pollution has been reported to be associated with cardiopulmonary diseases, but the underlying mechanisms remain unclear. This study aimed to investigate changes in serum metabolites associated with immediate, short- and medium-term exposures to ambient air pollution.

METHODS

We used data from the German population-based Cooperative Health Research in the Region of Augsburg (KORA) S4 survey (1999-2001) and two follow-up examinations (F4: 2006-08 and FF4: 2013-14). Mass-spectrometry-based targeted metabolomics was used to quantify metabolites among serum samples. Only participants with repeated metabolites measurements were included in this analysis. We collected daily averages of fine particles (PM2.5), coarse particles (PMcoarse), nitrogen dioxide (NO2), and ozone (O3) at urban background monitors located in Augsburg, Germany. Covariate-adjusted generalized additive mixed-effects models were used to examine the associations between immediate (2-day average of same day and previous day as individual's blood withdrawal), short- (2-week moving average), and medium-term exposures (8-week moving average) to air pollution and metabolites. We further performed pathway analysis for the metabolites significantly associated with air pollutants in each exposure window.

RESULTS

Of 9,620 observations from 4,261 study participants, we included 5,772 (60.0%) observations from 2,583 (60.6%) participants in this analysis. Out of 108 metabolites that passed quality control, multiple significant associations between metabolites and air pollutants with several exposure windows were identified at a Bonferroni corrected p-value threshold (p < 3.9 × 10-5). We found the highest number of associations for NO2, particularly at the medium-term exposure windows. Among the identified metabolic pathways based on the metabolites significantly associated with air pollutants, the glycerophospholipid metabolism was the most robust pathway in different air pollutants exposures.

CONCLUSIONS

Our study suggested that short- and medium-term exposure to air pollution might induce alterations of serum metabolites, particularly in metabolites involved in metabolic pathways related to inflammatory response and oxidative stress.

Association between choline supplementation and Alzheimer's disease risk: a systematic review protocol

Background and aims

There is growing evidence suggesting choline intake might have beneficial effects on cognitive function in the elderly. However, some studies report no relationship between choline intake and cognitive function or improvement in Alzheimer's disease patients. This protocol is for a systematic review of choline intake and Alzheimer's disease that aims to assess the comparative clinical effectiveness of choline supplementation on Alzheimer's disease risk.

Methods and analysis

literature search will be performed in PubMed, MEDLINE, EMBASE, CINAHL, Scopus, Cochrane, and the Web of Science electronic databases from inception until October 2023. We will follow the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Studies will be included if they compared two different time points of choline biomarkers measures in men or women (65+) with Alzheimer's Disease. The risk of bias in the included studies will be assessed within the Covidence data-management software.

Results

This review will summarize the clinical trial and quasi-experimental evidence of choline intake on Alzheimer's disease risk for adults aged 65+. The results from all eligible studies included in the analysis will be presented in tables, text, and figures. A descriptive synthesis will present the characteristics of included studies (e.g., age, sex of participants, type, length of intervention and comparator, and outcome measures), critical appraisal results, and descriptions of the main findings.

Discussion

This systematic review will summarize the existing evidence on the association between Choline intake and AD and to make recommendations if appropriate. The results of this review will be considered with respect to whether there is enough evidence of benefit to merit a more definitive randomized controlled trial. The results will be disseminated through peer-reviewed journals population.

Conclusion

This protocol outlines the methodology for a systematic review of choline intake and AD. The resulting systematic review from this protocol will form an evidence-based foundation to advance nutrition care for individuals with AD or poor cognitive function.

Systematic review registration

http://www.crd.york.ac.uk/PROSPERO, identifier CRD42023395004.

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.

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.

Circulating lipid profiles are associated with cross-sectional and longitudinal changes of central biomarkers for Alzheimer's disease

Investigating the association of lipidome profiles with central Alzheimer's disease (AD) biomarkers, including amyloid/tau/neurodegeneration (A/T/N), can provide a holistic view between the lipidome and AD. We performed cross-sectional and longitudinal association analysis of serum lipidome profiles with AD biomarkers in the Alzheimer's Disease Neuroimaging Initiative cohort (N=1,395). We identified lipid species, classes, and network modules that were significantly associated with cross-sectional and longitudinal changes of A/T/N biomarkers for AD. Notably, we identified the lysoalkylphosphatidylcholine (LPC(O)) as associated with "A/N" biomarkers at baseline at lipid species, class, and module levels. Also, GM3 ganglioside showed significant association with baseline levels and longitudinal changes of the "N" biomarkers at species and class levels. Our study of circulating lipids and central AD biomarkers enabled identification of lipids that play potential roles in the cascade of AD pathogenesis. Our results suggest dysregulation of lipid metabolic pathways as precursors to AD development and progression.

Unique genetic architecture of CSF and brain metabolites pinpoints the novel targets for the traits of human wellness

Brain metabolism perturbation can contribute to traits and diseases. We conducted the first large-scale CSF and brain genome-wide association studies, which identified 219 independent associations (59.8% novel) for 144 CSF metabolites and 36 independent associations (55.6% novel) for 34 brain metabolites. Most of the novel signals (97.7% and 70.0% in CSF and brain) were tissue specific. We also integrated MWAS-FUSION approaches with Mendelian Randomization and colocalization to identify causal metabolites for 27 brain and human wellness phenotypes and identified eight metabolites to be causal for eight traits (11 relationships). Low mannose level was causal to bipolar disorder and as dietary supplement it may provide therapeutic benefits. Low galactosylglycerol level was found causal to Parkinson's Disease (PD). Our study expanded the knowledge of MQTL in central nervous system, provided insights into human wellness, and successfully demonstrates the utility of combined statistical approaches to inform interventions.

Insight into adaption to hypoxia in Tibetan chicken embryonic brains using lipidomics

Tibetan chickens (Gallus gallus; TBCs) are a good model for studying hypoxia-related challenges. However, lipid composition in TBC embryonic brains has not been elucidated. In this study, we characterized brain lipid profiles of embryonic day 18 TBCs and dwarf laying chickens (DLCs) during hypoxia (13% O₂, HTBC18, and HDLC18) and normoxia (21% O₂, NTBC18, and NDLC18) by using lipidomics. A total of 50 lipid classes, including 3540 lipid molecular species, were identified and grouped into glycerophospholipids, sphingolipids, glycerolipids, sterols, prenols, and fatty acyls. Of these lipids, 67 and 97 were expressed at different levels in the NTBC18 and NDLC18, and HTBC18 and HDLC18 samples, respectively. Several lipid species, including phosphatidylethanolamines (PEs), hexosylceramides, phosphatidylcholines (PCs), and phospha-tidylserines (PSs), were highly expressed in HTBC18. These results suggest that TBCs adapt bet-ter to hypoxia than DLCs and may have distinct cell membrane composition and nervous system development, at least partly owing to differential expression of several lipid species. One tri-glyceride, one PC, one PS, and three PE lipids were identified as potential markers that discrim-inated between lipid profiles of the HTBC18 and HDLC18 samples. The present study provides valuable information about the dynamic composition of lipids in TBCs that may explain the adaptation of this species to hypoxia.

Advances and applications of fluids biomarkers in diagnosis and therapeutic targets of Alzheimer's disease

AIMS

Alzheimer's disease (AD) is a neurodegenerative disease with challenging early diagnosis and effective treatments due to its complex pathogenesis. AD patients are often diagnosed after the appearance of the typical symptoms, thereby delaying the best opportunity for effective measures. Biomarkers could be the key to resolving the challenge. This review aims to provide an overview of application and potential value of AD biomarkers in fluids, including cerebrospinal fluid, blood, and saliva, in diagnosis and treatment.

METHODS

A comprehensive search of the relevant literature was conducted to summarize potential biomarkers for AD in fluids. The paper further explored the biomarkers' utility in disease diagnosis and drug target development.

RESULTS

Research on biomarkers mainly focused on amyloid-β (Aβ) plaques, Tau protein abnormal phosphorylation, axon damage, synaptic dysfunction, inflammation, and related hypotheses associated with AD mechanisms. Aβ₄₂ , total Tau (t-Tau), and phosphorylated Tau (p-Tau), have been endorsed for their diagnostic and predictive capability. However, other biomarkers remain controversial. Drugs targeting Aβ have shown some efficacy and those that target BACE1 and Tau are still undergoing development.

CONCLUSION

Fluid biomarkers hold considerable potential in the diagnosis and drug development of AD. However, improvements in sensitivity and specificity, and approaches for managing sample impurities, need to be addressed for better diagnosis.

The Effects of Amyloid-β on Metabolomic Profiles of Cardiomyocytes and Coronary Endothelial Cells

BACKGROUND

An increasing number of experimental and clinical studies show a link between Alzheimer's disease and heart diseases such as heart failure, ischemic heart disease, and atrial fibrillation. However, the mechanisms underlying the potential role of amyloid-β (Aβ) in the pathogenesis of cardiac dysfunction in Alzheimer's disease remain unknown. We have recently shown the effects of Aβ 1 - 40 and Aβ 1 - 42 on cell viability and mitochondrial function in cardiomyocytes and coronary artery endothelial cells.

OBJECTIVE

In this study, we investigated the effects of Aβ 1 - 40 and Aβ 1 - 42 on the metabolism of cardiomyocytes and coronary artery endothelial cells.

METHODS

Gas chromatography-mass spectrometry was used to analyze metabolomic profiles of cardiomyocytes and coronary artery endothelial cells treated with Aβ 1 - 40 and Aβ 1 - 42. In addition, we determined mitochondrial respiration and lipid peroxidation in these cells.

RESULTS

We found that the metabolism of different amino acids was affected by Aβ 1 - 42 in each cell type, whereas the fatty acid metabolism is consistently disrupted in both types of cells. Lipid peroxidation was significantly increased, whereas mitochondrial respiration was reduced in both cell types in response to Aβ 1 - 42.

CONCLUSION

This study revealed the disruptive effects of Aβ on lipid metabolism and mitochondria function in cardiac cells.

The Pathological Effects of Circulating Hydrophobic Bile Acids in Alzheimer's Disease

Recent clinical studies have revealed that the serum levels of toxic hydrophobic bile acids (deoxy cholic acid, lithocholic acid [LCA], and glycoursodeoxycholic acid) are significantly higher in patients with Alzheimer's disease (AD) and amnestic mild cognitive impairment (aMCI) when compared to control subjects. The elevated serum bile acids may be the result of hepatic peroxisomal dysfunction. Circulating hydrophobic bile acids are able to disrupt the blood-brain barrier and promote the formation of amyloid-β plaques through enhancing the oxidation of docosahexaenoic acid. Hydrophobic bile acid may find their ways into the neurons via the apical sodium-dependent bile acid transporter. It has been shown that hydrophobic bile acids impose their pathological effects by activating farnesoid X receptor and suppressing bile acid synthesis in the brain, blocking NMDA receptors, lowering brain oxysterol levels, and interfering with 17β-estradiol actions such as LCA by binding to E2 receptors (molecular modelling data exclusive to this paper). Hydrophobic bile acids may interfere with the sonic hedgehog signaling through alteration of cell membrane rafts and reducing brain 24(S)-hydroxycholesterol. This article will 1) analyze the pathological roles of circulating hydrophobic bile acids in the brain, 2) propose therapeutic approaches, and 3) conclude that consideration be given to reducing/monitoring toxic bile acid levels in patients with AD or aMCI, prior/in combination with other treatments.

Status of Metabolomic Measurement for Insights in Alzheimer's Disease Progression-What Is Missing?

Alzheimer's disease (AD) is an aging-related neurodegenerative disease, leading to the progressive loss of memory and other cognitive functions. As there is still no cure for AD, the growth in the number of susceptible individuals represents a major emerging threat to public health. Currently, the pathogenesis and etiology of AD remain poorly understood, while no efficient treatments are available to slow down the degenerative effects of AD. Metabolomics allows the study of biochemical alterations in pathological processes which may be involved in AD progression and to discover new therapeutic targets. In this review, we summarized and analyzed the results from studies on metabolomics analysis performed in biological samples of AD subjects and AD animal models. Then this information was analyzed by using MetaboAnalyst to find the disturbed pathways among different sample types in human and animal models at different disease stages. We discuss the underlying biochemical mechanisms involved, and the extent to which they could impact the specific hallmarks of AD. Then we identify gaps and challenges and provide recommendations for future metabolomics approaches to better understand AD pathogenesis.

Discovering Hair Biomarkers of Alzheimer's Disease Using High Resolution Mass Spectrometry-Based Untargeted Metabolomics

Hair may be a potential biospecimen to discover biomarkers for Alzheimer's disease (AD) since it reflects the integral metabolic profiles of body burden over several months. Here, we described the AD biomarker discovery in the hair using a high-resolution mass spectrometry (HRMS)-based untargeted metabolomics approach. A total of 24 patients with AD and 24 age- and sex-matched cognitively healthy controls were recruited. The hair samples were collected 0.1-cm away from the scalp and further cut into 3-cm segments. Hair metabolites were extracted by ultrasonication with methanol/phosphate-buffered saline 50/50 (v/v) for 4 h. A total of 25 discriminatory chemicals in hair between the patients with AD and controls were discovered and identified. The AUC value achieved 0.85 (95% CI: 0.72~0.97) in patients with very mild AD compared to healthy controls using a composite panel of the 9 biomarker candidates, indicating high potential for the initiation or promotion phase of AD dementia in the early stage. A metabolic panel combined with the nine metabolites may be used as biomarkers for the early detection of AD. The hair metabolome can be used to reveal metabolic perturbations for biomarker discovery. Investigating perturbations of the metabolites will offer insight into the pathogenesis of AD.

Comprehensive Lipidomic Workflow for Multicohort Population Phenotyping Using Stable Isotope Dilution Targeted Liquid Chromatography-Mass Spectrometry

Dysregulated lipid metabolism underpins many chronic diseases including cardiometabolic diseases. Mass spectrometry-based lipidomics is an important tool for understanding mechanisms of lipid dysfunction and is widely applied in epidemiology and clinical studies. With ever-increasing sample numbers, single batch acquisition is often unfeasible, requiring advanced methods that are accurate and robust to batch-to-batch and interday analytical variation. Herein, an optimized comprehensive targeted workflow for plasma and serum lipid quantification is presented, combining stable isotope internal standard dilution, automated sample preparation, and ultrahigh performance liquid chromatography-tandem mass spectrometry with rapid polarity switching to target 1163 lipid species spanning 20 subclasses. The resultant method is robust to common sources of analytical variation including blood collection tubes, hemolysis, freeze-thaw cycles, storage stability, analyte extraction technique, interinstrument variation, and batch-to-batch variation with 820 lipids reporting a relative standard deviation of <30% in 1048 replicate quality control plasma samples acquired across 16 independent batches (total injection count = 6142). However, sample hemolysis of ≥0.4% impacted lipid concentrations, specifically for phosphatidylethanolamines (PEs). Low interinstrument variability across two identical LC-MS systems indicated feasibility for intra/inter-lab parallelization of the assay. In summary, we have optimized a comprehensive lipidomic protocol to support rigorous analysis for large-scale, multibatch applications in precision medicine. The mass spectrometry lipidomics data have been deposited to massIVE: data set identifiers MSV000090952 and 10.25345/C5NP1WQ4S.

Biomarkers of diagnosis, prognosis, pathogenesis, response to therapy: Convergence or divergence? Lessons from Alzheimer's disease and synucleinopathies

Alzheimer's disease (AD) is the most common disorder associated with cognitive impairment. Recent observations emphasize the pathogenic role of multiple factors inside and outside the central nervous system, supporting the notion that AD is a syndrome of many etiologies rather than a "heterogeneous" but ultimately unifying disease entity. Moreover, the defining pathology of amyloid and tau coexists with many others, such as α-synuclein, TDP-43, and others, as a rule, not an exception. Thus, an effort to shift our AD paradigm as an amyloidopathy must be reconsidered. Along with amyloid accumulation in its insoluble state, β-amyloid is becoming depleted in its soluble, normal states, as a result of biological, toxic, and infectious triggers, requiring a shift from convergence to divergence in our approach to neurodegeneration. These aspects are reflected-in vivo-by biomarkers, which have become increasingly strategic in dementia. Similarly, synucleinopathies are primarily characterized by abnormal deposition of misfolded α-synuclein in neurons and glial cells and, in the process, depleting the levels of the normal, soluble α-synuclein that the brain needs for many physiological functions. The soluble to insoluble conversion also affects other normal brain proteins, such as TDP-43 and tau, accumulating in their insoluble states in both AD and dementia with Lewy bodies (DLB). The two diseases have been distinguished by the differential burden and distribution of insoluble proteins, with neocortical phosphorylated tau deposition more typical of AD and neocortical α-synuclein deposition peculiar to DLB. We propose a reappraisal of the diagnostic approach to cognitive impairment from convergence (based on clinicopathologic criteria) to divergence (based on what differs across individuals affected) as a necessary step for the launch of precision medicine.

Combined with UPLC-Triple-TOF/MS-based plasma lipidomics and molecular pharmacology reveals the mechanisms of schisandrin against Alzheimer's disease

BACKGROUND

Alzheimer's disease (AD), a type of neurodegeneration disease, is characterized by Aβ deposition and tangles of nerve fibers. Schisandrin is one of the main components of Fructus Schisandrae Chinensis. Researches showed that schisandrin can improve the cognitive impairment and memory of AD mice, but the specific mechanism has not been fully elucidated.

PURPOSE

The purpose of this study is to investigate the possible mechanism of schisandrin in improving AD pathology.

METHODS

The Morris water maze test was executed to detect spatial learning and memory. Ultra performance liquid chromatography-Triple time of flight mass spectrometry (UPLC-Triple-TOF/MS)-based plasma lipidomics was used to study the changes of plasma lipids. Moreover, we measured the levels of protein and mRNA expression of APOE and ABCA1 in the rat brains and in BV2 microglia.

RESULTS

Our study found that schisandrin could improve learning and memory, and reduce Aβ deposition in AD rats. Furthermore, we found that schisandrin can improve plasma lipid metabolism disorders. Therefore, we hypothesized schisandrin might act via LXR and the docking results showed that schisandrin interacts with LXRβ. Further, we found schisandrin increased the protein and mRNA expression of LXR target genes APOE and ABCA1 in the brain of AD rats and in BV2 microglia.

CONCLUSION

Our study reveals the neuroprotective effect and mechanism of schisandrin improves AD pathology by activating LXR to produce APOE and ABCA1.

Brain regions show different metabolic and protein arginine methylation phenotypes in frontotemporal dementias and Alzheimer's disease

Frontotemporal dementia (FTD) is a heterogeneous neurodegenerative disease with multiple histopathological subtypes. FTD patients share similar symptoms with Alzheimer's disease (AD). Hence, FTD patients are commonly misdiagnosed as AD, despite the consensus clinical diagnostic criteria. It is therefore of great clinical need to identify a biomarker that can distinguish FTD from AD and control individuals, and potentially further differentiate between FTD pathological subtypes. We conducted a metabolomic analysis on post-mortem human brain tissue from three regions: cerebellum, frontal cortex and occipital cortex from control, FTLD-TDP type A, type A-C9, type C and AD. Our results indicate that the brain subdivisions responsible for different functions show different metabolic patterns. We further explored the region-specific metabolic characteristics of different FTD subtypes and AD patients. Different FTD subtypes and AD share similar metabolic phenotypes in the cerebellum, but AD exhibited distinct metabolic patterns in the frontal and occipital regions compared to FTD. The identified brain region-specific metabolite biomarkers could provide a tool for distinguishing different FTD subtypes and AD and provide the first insights into the metabolic changes of FTLD-TDP type A, type A-C9, type C and AD in different regions of the brain. The importance of protein arginine methylation in neurodegenerative disease has come to light, so we investigated whether the arginine methylation level contributes to disease pathogenesis. Our findings provide new insights into the relationship between arginine methylation and metabolic changes in FTD subtypes and AD that could be further explored, to study the molecular mechanism of pathogenesis.

Combined metabolic activators improve cognitive functions in Alzheimer's disease patients: a randomised, double-blinded, placebo-controlled phase-II trial

BACKGROUND

Alzheimer's disease (AD) is associated with metabolic abnormalities linked to critical elements of neurodegeneration. We recently administered combined metabolic activators (CMA) to the AD rat model and observed that CMA improves the AD-associated histological parameters in the animals. CMA promotes mitochondrial fatty acid uptake from the cytosol, facilitates fatty acid oxidation in the mitochondria, and alleviates oxidative stress.

METHODS

Here, we designed a randomised, double-blinded, placebo-controlled phase-II clinical trial and studied the effect of CMA administration on the global metabolism of AD patients. One-dose CMA included 12.35 g L-serine (61.75%), 1 g nicotinamide riboside (5%), 2.55 g N-acetyl-L-cysteine (12.75%), and 3.73 g L-carnitine tartrate (18.65%). AD patients received one dose of CMA or placebo daily during the first 28 days and twice daily between day 28 and day 84. The primary endpoint was the difference in the cognitive function and daily living activity scores between the placebo and the treatment arms. The secondary aim of this study was to evaluate the safety and tolerability of CMA. A comprehensive plasma metabolome and proteome analysis was also performed to evaluate the efficacy of the CMA in AD patients.

RESULTS

We showed a significant decrease of AD Assessment Scale-cognitive subscale (ADAS-Cog) score on day 84 vs day 0 (P = 0.00001, 29% improvement) in the CMA group. Moreover, there was a significant decline (P = 0.0073) in ADAS-Cog scores (improvement of cognitive functions) in the CMA compared to the placebo group in patients with higher ADAS-Cog scores. Improved cognitive functions in AD patients were supported by the relevant alterations in the hippocampal volumes and cortical thickness based on imaging analysis. Moreover, the plasma levels of proteins and metabolites associated with NAD + and glutathione metabolism were significantly improved after CMA treatment.

CONCLUSION

Our results indicate that treatment of AD patients with CMA can lead to enhanced cognitive functions and improved clinical parameters associated with phenomics, metabolomics, proteomics and imaging analysis. Trial registration ClinicalTrials.gov NCT04044131 Registered 17 July 2019, https://clinicaltrials.gov/ct2/show/NCT04044131.

Lipidomic changes of cerebral cortex in aldehyde dehydrogenase-2 knock-in heterozygote mice after chronic alcohol exposure

Introduction

Alcohol is the main legal drug in the world, and excessive consumption of alcohol seriously damages the morphological structure and function of various organs. The insufficiency of an essential enzyme in ethanol metabolism, aldehyde dehydrogenase-2 (ALDH2), will aggravate the alcohol-induced brain injury. The effect of ALDH2 after chronic alcohol exposure on global lipid profiling of the brain remains unclear.

Methods

In this study, ALDH2*2 knock-in mice were fed the Lieber-DeCarli liquid diet containing ethanol for 8 weeks. Blood alcohol and acetaldehyde levels were examined, and the mice were tested through novel object recognition and the Y-maze test to evaluate cognitive impairment toward the end of the study. The lipidome profiling of cerebral cortex samples was investigated using a lipidomics method based on ultra-high performance liquid tandem chromatography quadrupole time of flight mass spectrometry (UHPLC-QTOFMS).

Results and Discussion

Compared with similarly treated wild-type (WT) mice, ALDH2*2 mice exhibited poor cognitive performance, though the result did not achieve statistical significance. The lipidomics results indicated that 74 differential lipid species were selected in WT mice, of which 57 species were up-regulated, and 17 were down-regulated. Moreover, 99 differential lipids were identified in ALDH2*2 mice, of which 73 were up-regulated, and 26 were down-regulated. For ALDH2*2 mice, the number of changed significantly glycerophospholipids (GPs) subtypes was lower than that of WT mice. Interestingly, compared with WT mice, a lower proportion of polyunsaturated fatty acids (PUFAs) was found in ALDH2*2 mice. Collectively, the results provide clear evidence for a lipidomic signature of marked changes in the cerebral cortex of ALDH2*2 mice after chronic alcohol exposure.

Highlights

• The cerebral cortex of heterozygous ALDH2*2 mice showed more significant changes in lipidome profiles after chronic alcohol exposure than wild-type mice.• Most lipids were significantly up-regulated in both groups of mice, whereas the increase in TAG was restricted to WT mice.• For ALDH2*2 mice, GPs substances changed significantly, and SHexCer and SM subclasses in sphingolipids also deserved attention.

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.

Comprehensive metabolomics and lipidomics profiling uncovering neuroprotective effects of Ginkgo biloba L. leaf extract on Alzheimer's disease

Introduction: Ginkgo biloba L. leaf extract (GBLE) has been reported to be effective for alleviating cognitive and memory impairment in Alzheimer's disease (AD). Nevertheless, the potential mechanism remains unclear. Herein, this study aimed to explore the neuroprotective effects of GBLE on AD and elaborate the underlying therapeutic mechanism. Methods: Donepezil, the most widely prescribed drug for AD, was used as a positive control. An integrated metabolomics and lipidomics approach was adopted to characterize plasma metabolic phenotype of APP/PS1 double transgenic mice and describe the metabolomic and lipidomic fingerprint changes after GBLE intervention. The Morris water maze test and immunohistochemistry were applied to evaluate the efficacy of GBLE. Results: As a result, administration of GBLE significantly improved the cognitive function and alleviated amyloid beta (Aβ) deposition in APP/PS1 mice, showing similar effects to donepezil. Significant alterations were observed in metabolic signatures of APP/PS1 mice compared with wild type (WT) mice by metabolomic analysis. A total of 60 markedly altered differential metabolites were identified, including 28 lipid and lipid-like molecules, 13 organic acids and derivatives, 11 organic nitrogen compounds, and 8 other compounds, indicative of significant changes in lipid metabolism of AD. Further lipidomic profiling showed that the differential expressed lipid metabolites between APP/PS1 and WT mice mainly consisted of phosphatidylcholines, lysophosphatidylcholines, triglycerides, and ceramides. Taking together all the data, the plasma metabolic signature of APP/PS1 mice was primarily characterized by disrupted sphingolipid metabolism, glycerophospholipid metabolism, glycerolipid metabolism, and amino acid metabolism. Most of the disordered metabolites were ameliorated after GBLE treatment, 19 metabolites and 24 lipids of which were significantly reversely regulated (adjusted-p<0.05), which were considered as potential therapeutic targets of GBLE on AD. The response of APP/PS1 mice to GBLE was similar to that of donepezil, which significantly reversed the levels of 23 disturbed metabolites and 30 lipids. Discussion: Our data suggested that lipid metabolism was dramatically perturbed in the plasma of APP/PS1 mice, and GBLE might exert its neuroprotective effects by restoring lipid metabolic balance. This work provided a basis for better understanding the potential pathogenesis of AD and shed new light on the therapeutic mechanism of GBLE in the treatment of AD.

Correlation between Mild Cognitive Impairment and Sarcopenia: The Prospective Role of Lipids and Basal Metabolic Rate in the Link

There is evidence of correlation between mild cognitive impairment (MCI) and sarcopenia (SA). However, the influencing factors and the mechanism, such as age-related lipid redistribution, remain unknown. This study aimed to clarify the role of dietary fats and erythrocyte lipids profile combined with basal metabolic rate (BMR) in the link between MCI and SA. A total of 1050 participants aged 65 to 85 were divided into control, MCI, SA and MCI and SA groups. Bioelectrical impedance analysis was used to evaluate appendicular lean mass and BMR. Cognition and dietary nutrition were detected by neuropsychological tests and food frequency questionnaires. UHPLC-QExactive-MS/MS and UHPLC-Qtrap-MS/MS were used to conduct the lipidomics analysis. Lower dietary intake of different phospholipids, unsaturated fatty acids and kinds of choline were significantly associated with MCI and SA. Least absolute shrinkage and selection operator, multivariate logistic regression, receiver operating characteristic curve and validation tests provided evidence that specific phospholipids, unsaturated fatty acids and BMR might be the critical factors in the processing of MCI and SA, as well as in their link. The lipidomic analysis observed a clear discrimination of the lipid profiles in the individuals who are in MCI, SA, or MCI and SA, compared with the control. Lower expressions in certain phospholipid species, such as sphingomyelin and phosphatidylethanolamines, decreased phosphatidylcholine with more unsaturated double bonds, lower level of lipids with C20:5 and C20:4, higher level of lipids with C18:2 and lipids with a remodeled length of acyl chain, might be closely related to the link between MCI and SA. Inadequate dietary intake and lower concentrations of the erythrocyte lipid profile of phospholipids and unsaturated fatty acids with a lower level of BMR might be the key points that lead to progress in MCI and SA, as well as in their link. They could be used as the prospective biomarkers for the higher risk of cognitive decline and/or SA in elderly population.

Serum unsaturated phosphatidylcholines predict longitudinal basal forebrain degeneration in Alzheimer's disease

Basal forebrain cholinergic neurons are among the first cell types affected by Alzheimer's disease pathology, but the cause of their early vulnerability is unknown. The lipid phosphatidylcholine is an essential component of the cell membrane, and phosphatidylcholine levels have been shown to be abnormal in the blood and brain of Alzheimer's disease patients. We hypothesized that disease-related changes in phosphatidylcholine metabolism may disproportionately affect basal forebrain cholinergic neurons due to their extremely large size, plasticity in adulthood and unique reliance on phosphatidylcholine for acetylcholine synthesis. To test this hypothesis, we examined whether serum phosphatidylcholine levels predicted longitudinal basal forebrain degeneration in Alzheimer's disease. All data were collected by the Alzheimer's Disease Neuroimaging Initiative. Participants were divided into a normal CSF group (controls; n = 77) and an abnormal CSF group (preclinical and clinical Alzheimer's disease; n = 236) based on their CSF ratios of phosphorylated tau and amyloid beta at baseline. Groups were age-matched (t = 0.89, P > 0.1). Serum lipidomics data collected at baseline were clustered by chemical similarity, and enrichment analyses were used to determine whether serum levels of any lipid clusters differed between the normal and abnormal CSF groups. In a subset of patients with longitudinal structural MRI (normal CSF n = 62, abnormal CSF n = 161), two timepoints of MRI data were used to calculate grey matter annual percent change for each participant. Multivariate partial least squares analyses tested for relationships between neuroimaging and lipidomics data which are moderated by CSF pathology. Our clustering analyses produced 23 serum lipid clusters. Of these clusters, six were altered in the abnormal CSF group, including a cluster of unsaturated phosphatidylcholines. In the subset of participants with longitudinal structural MRI data, a priori nucleus basalis of Meynert partial least squares analyses detected a relationship between unsaturated phosphatidylcholines and degeneration in the nucleus basalis which is moderated by Alzheimer's disease CSF pathology (P = 0.0008). Whole-brain grey matter partial least squares analyses of all 23 lipid clusters revealed that only unsaturated phosphatidylcholines and unsaturated acylcarnitines exhibited an Alzheimer's disease-dependent relationship with longitudinal degeneration (P = 0.0022 and P = 0.0018, respectively). Only the unsaturated phosphatidylcholines predicted basal forebrain degeneration in the whole-brain analyses. Overall, this study provides in vivo evidence for a selective relationship between phosphatidylcholine and basal forebrain degeneration in human Alzheimer's disease, highlighting the importance of phosphatidylcholine to basal forebrain grey matter integrity.

Phospholipid imbalance impairs autophagosome completion

Autophagy, a conserved eukaryotic intracellular catabolic pathway, maintains cell homeostasis by lysosomal degradation of cytosolic material engulfed in double membrane vesicles termed autophagosomes, which form upon sealing of single-membrane cisternae called phagophores. While the role of phosphatidylinositol 3-phosphate (PI3P) and phosphatidylethanolamine (PE) in autophagosome biogenesis is well-studied, the roles of other phospholipids in autophagy remain rather obscure. Here we utilized budding yeast to study the contribution of phosphatidylcholine (PC) to autophagy. We reveal for the first time that genetic loss of PC biosynthesis via the CDP-DAG pathway leads to changes in lipid composition of autophagic membranes, specifically replacement of PC by phosphatidylserine (PS). This impairs closure of the autophagic membrane and autophagic flux. Consequently, we show that choline-dependent recovery of de novo PC biosynthesis via the CDP-choline pathway restores autophagosome formation and autophagic flux in PC-deficient cells. Our findings therefore implicate phospholipid metabolism in autophagosome biogenesis.

Longitudinal associations between metabolites and long-term exposure to ambient air pollution: Results from the KORA cohort study

BACKGROUND

Long-term exposure to air pollution has been associated with cardiopulmonary diseases, while the underlying mechanisms remain unclear.

OBJECTIVES

To investigate changes in serum metabolites associated with long-term exposure to air pollution and explore the susceptibility characteristics.

METHODS

We used data from the German population-based Cooperative Health Research in the Region of Augsburg (KORA) S4 survey (1999-2001) and two follow-up examinations (F4: 2006-08 and FF4: 2013-14). Mass-spectrometry-based targeted metabolomics was used to quantify metabolites among serum samples. Only participants with repeated metabolites measurements were included in the current analysis. Land-use regression (LUR) models were used to estimate annual average concentrations of ultrafine particles, particulate matter (PM) with an aerodynamic diameter less than 10 μm (PM₁₀), coarse particles (PM_coarse), fine particles, PM_2.5 absorbance (a proxy of elemental carbon related to traffic exhaust, PM_2.5abs), nitrogen oxides (NO₂, NO_x), and ozone at individuals' residences. We applied confounder-adjusted mixed-effects regression models to examine the associations between long-term exposure to air pollution and metabolites.

RESULTS

Among 9,620 observations from 4,261 KORA participants, we included 5,772 (60.0%) observations from 2,583 (60.6%) participants in this analysis. Out of 108 metabolites that passed stringent quality control across three study points in time, we identified nine significant negative associations between phosphatidylcholines (PCs) and ambient pollutants at a Benjamini-Hochberg false discovery rate (FDR) corrected p-value < 0.05. The strongest association was seen for an increase of 0.27 μg/m³ (interquartile range) in PM_2.5abs and decreased phosphatidylcholine acyl-alkyl C36:3 (PC ae C36:3) concentrations [percent change in the geometric mean: -2.5% (95% confidence interval: -3.6%, -1.5%)].

CONCLUSIONS

Our study suggested that long-term exposure to air pollution is associated with metabolic alterations, particularly in PCs with unsaturated long-chain fatty acids. These findings might provide new insights into potential mechanisms for air pollution-related adverse outcomes.