Characterizing human postprandial metabolic response using multiway data analysis.

INTRODUCTION: Analysis of time-resolved postprandial metabolomics data can improve our understanding of the human metabolism by revealing similarities and differences in postprandial responses of individuals. Traditional data analysis methods often rely on data summaries or univariate approaches focusing on one metabolite at a time. OBJECTIVES: Our goal is to provide a comprehensive picture in terms of the changes in the human metabolism in response to a meal challenge test, by revealing static and dynamic markers of phenotypes, i.e., subject stratifications, related clusters of metabolites, and their temporal profiles. METHODS: We analyze Nuclear Magnetic Resonance (NMR) spectroscopy measurements of plasma samples collected during a meal challenge test from 299 individuals from the COPSAC2000 cohort using a Nightingale NMR panel at the fasting and postprandial states (15, 30, 60, 90, 120, 150, 240 min). We investigate the postprandial dynamics of the metabolism as reflected in the dynamic behaviour of the measured metabolites. The data is arranged as a three-way array: subjects by metabolites by time. We analyze the fasting state data to reveal static patterns of subject group differences using principal component analysis (PCA), and fasting state-corrected postprandial data using the CANDECOMP/PARAFAC (CP) tensor factorization to reveal dynamic markers of group differences. RESULTS: Our analysis reveals dynamic markers consisting of certain metabolite groups and their temporal profiles showing differences among males according to their body mass index (BMI) in response to the meal challenge. We also show that certain lipoproteins relate to the group difference differently in the fasting vs. dynamic state. Furthermore, while similar dynamic patterns are observed in males and females, the BMI-related group difference is observed only in males in the dynamic state. CONCLUSION: The CP model is an effective approach to analyze time-resolved postprandial metabolomics data, and provides a compact but a comprehensive summary of the postprandial data revealing replicable and interpretable dynamic markers crucial to advance our understanding of changes in the metabolism in response to a meal challenge.

The impact of androgen levels on serum metabolic profiles in patients with polycystic ovary syndrome.

OBJECTIVE: This study aimed to investigate the impact of serum androgen levels on metabolic profiles in patients with polycystic ovary syndrome (PCOS). METHODS: We included 216 patients with PCOS and 216 healthy individuals selected as the control group. According to the measured serum androgen levels, patients with PCOS were divided into the hyperandrogenism group and non-hyperandrogenism group. Clinical metabolic indicators were assessed and compared between the two groups. Additionally, we assessed the correlation between androgen levels and clinical metabolic indicators. RESULTS: The body mass index, waist-to-hip ratio, mF-G score, and acne score, as well as T, LH, LSH/FSH, FPG, Cr, UA, TG, TC, and LDL-C levels were significantly higher in the PCOS group than in the control group. The incidence of hyperandrogenism and clinical hyperandrogenism in the PCOS group was significantly higher than that in the control group. Regarding clinical hyperandrogenism, hirsutism, acne, and acanthosis nigricans were significantly more common in the PCOS group than in the control group. Serum androgen levels were significantly correlated with the mF-G score, acne score, FSH, glucose concentration at 30 min, glucose concentration at 60 min, glucose concentration at 120 min, FINS, N120, HOMA-IR, HbA1c, AUCG, UA, TG, and hHDL-Clevels. CONCLUSION: Elevated serum androgen levels are commonly observed in patients with PCOS and are associated with multiple metabolic abnormalities. Therefore, it is recommended to regularly monitor glucose and lipid metabolism-related indicators in patients with PCOS who have elevated androgen levels.

Metabolomic signatures for blood pressure from early to late adolescence: findings from a U.S. cohort.

INTRODUCTION: Metabolite signatures for blood pressure (BP) may reveal biomarkers, elucidate pathogenesis, and provide prevention targets for high BP. Knowledge regarding metabolites associated with BP in adolescence remains limited. OBJECTIVES: Investigate the associations between metabolites and adolescent BP, both cross-sectionally (in early and late adolescence) and prospectively (from early to late adolescence). METHODS: Participants are from the Project Viva prospective cohort. During the early (median: 12.8 years; N = 556) and late (median: 17.4 years; N = 501) adolescence visits, we conducted untargeted plasma metabolomic profiling and measured systolic (SBP) and diastolic BP (DBP). We used linear regression to identify metabolites cross-sectionally associated with BP at each time point, and to assess prospective associations of changes in metabolite levels from early to late adolescence with late adolescence BP. We used Weighted Gene Correlation Network Analysis and Spearman's partial correlation to identify metabolite clusters associated with BP at each time point. RESULTS: In the linear models, higher androgenic steroid levels were consistently associated with higher SBP and DBP in early and late adolescence. A cluster of 59 metabolites, mainly composed of androgenic steroids, correlated with higher SBP and DBP in early adolescence. A cluster primarily composed of fatty acid lipids was marginally associated with higher SBP in females in late adolescence. Multiple metabolites, including those in the creatine and purine metabolism sub-pathways, were associated with higher SBP and DBP both cross-sectionally and prospectively. CONCLUSION: Our results shed light on the potential metabolic processes and pathophysiology underlying high BP in adolescents.

A pseudo-targeted metabolomics for discovery of potential biomarkers of cardiac hypertrophy in rats.

Cardiac hypertrophy (CH) is one of the stages in the occurrence and development of severe cardiovascular diseases, and exploring its biomarkers is beneficial for delaying the progression of severe cardiovascular diseases. In this research, we established a comprehensive and highly efficient pseudotargeted metabolomics method, which demonstrated a superior capacity to identify differential metabolites when compared to traditionaluntargeted metabolomics. The intra/inter-day precision and reproducibility results proved the method is reliable and precise. The established method was then applied to seek the potential differentiated metabolic biomarkers of cardiac hypertrophy (CH) rats, and oxylipins, phosphorylcholine (PC), lysophosphatidylcholine (LysoPC), lysophosphatidylethanolamine (LysoPE), Krebs cycle intermediates, carnitines, amino acids, and bile acids were disclosed to be the possible differentiate components. Their metabolic pathway analysis revealed that the potential metabolic alterations in CH rats were mainly associated with phenylalanine, tyrosine and tryptophan biosynthesis, phenylalanine metabolism, arachidonic acid metabolism, citrate cycle, glyoxylate and dicarboxylate metabolism, and tyrosine metabolism. In sum, this research provided a comprehensiveand reliable LC-MS/MS MRM platform for pseudo-targeted metabolomics investigation of disease condition, and some interesting potential biomarkers were disclosed for CH, which merit further exploration in the future.

Metabolic flexibility associated with flight time among combat pilots of the Brazilian air force.

INTRODUCTION: Fighter pilots must support the effects of many stressors, including physical and psychological exertion, circadian disturbance, jet lag, and environmental stress. Despite the rigorous selection of military pilots, those factors predispose to failures in physiological compensatory mechanisms and metabolic flexibility. OBJECTIVES: We compared through NMR-based metabolomics the metabolic profile of Brazilian F5 fighter pilots with different flight experiences vs. the control group of non-pilots. We hypothesized that combat pilots have metabolic flexibility associated with combat flight time. METHODS: We evaluated for the first time 34 Brazilian fighter pilots from Santa Cruz Air Base (Rio de Janeiro, RJ) allocated into three groups: pilots with lower total accumulated flight experience < 1,100 h (PC1, n = 7); pilots with higher total accumulated flight experience ≥ 1,100 h (PC2, n = 6); military non-pilots (CONT, n = 21). Data collection included anthropometric measurements, total blood count, lipidogram, markers of oxidative stress, and serum NMR-based metabolomics. RESULTS: In comparison with controls (p < 0.05), pilots exhibited decreased levels of white blood cells (-13%), neutrophils (-15%), lymphocytes (-20%), alfa-glucose (-13%), lactate (-26%), glutamine (-11%), histidine (-20%), and tyrosine (-11%), but higher isobutyrate (+ 10%) concentrations. Significant correlations were found between lactate vs. amino acids in CONT (r = 0.55-0.68, p < 0.001), and vs. glutamine in PC2 (r = 0.94, p = 0.01). CONCLUSION: Fighter pilots with lower experience showed a dysregulation in immune-metabolic function in comparison with controls, which seemed to be counteracted by the accumulation of flight hours. Those findings might have implications for the health preservation and operational training of fighter pilots.

The influence of maternal prepregnancy weight and gestational weight gain on the umbilical cord blood metabolome: a case-control study.

BACKGROUND: Maternal overweight/obesity and excessive gestational weight gain (GWG) are frequently reported to be risk factors for obesity and other metabolic disorders in offspring. Cord blood metabolites provide information on fetal nutritional and metabolic health and could provide an early window of detection of potential health issues among newborns. The aim of the study was to explore the impact of maternal prepregnancy overweight/obesity and excessive GWG on cord blood metabolic profiles. METHODS: A case control study including 33 pairs of mothers with prepregnancy overweight/obesity and their neonates, 30 pairs of mothers with excessive GWG and their neonates, and 32 control mother-neonate pairs. Untargeted metabolomic profiling of umbilical cord blood samples were performed using UHPLC‒MS/MS. RESULTS: Forty-six metabolites exhibited a significant increase and 60 metabolites exhibited a significant reduction in umbilical cord blood from overweight and obese mothers compared with mothers with normal body weight. Steroid hormone biosynthesis and neuroactive ligand‒receptor interactions were the two top-ranking pathways enriched with these metabolites (P = 0.01 and 0.03, respectively). Compared with mothers with normal GWG, in mothers with excessive GWG, the levels of 63 metabolites were increased and those of 46 metabolites were decreased in umbilical cord blood. Biosynthesis of unsaturated fatty acids was the most altered pathway enriched with these metabolites (P < 0.01). CONCLUSIONS: Prepregnancy overweight and obesity affected the fetal steroid hormone biosynthesis pathway, while excessive GWG affected fetal fatty acid metabolism. This emphasizes the importance of preconception weight loss and maintaining an appropriate GWG, which are beneficial for the long-term metabolic health of offspring.

Metabolomics-driven investigation of plant defense response against pest and pathogen attack.

The advancement of metabolomics has assisted in the identification of various bewildering characteristics of the biological system. Metabolomics is a standard approach, facilitating crucial aspects of system biology with absolute quantification of metabolites using minimum samples, based on liquid/gas chromatography, mass spectrometry and nuclear magnetic resonance. The metabolome profiling has narrowed the wide gaps of missing information and has enhanced the understanding of a wide spectrum of plant-environment interactions by highlighting the complex pathways regulating biochemical reactions and cellular physiology under a particular set of conditions. This high throughput technique also plays a prominent role in combined analyses of plant metabolomics and other omics datasets. Plant metabolomics has opened a wide paradigm of opportunities for developing stress-tolerant plants, ensuring better food quality and quantity. However, despite advantageous methods and databases, the technique has a few limitations, such as ineffective 3D capturing of metabolites, low comprehensiveness, and lack of cell-based sampling. In the future, an expansion of plant-pathogen and plant-pest response towards the metabolite architecture is necessary to understand the intricacies of plant defence against invaders, elucidation of metabolic pathway operational during defence and developing a direct correlation between metabolites and biotic stresses. Our aim is to provide an overview of metabolomics and its utilities for the identification of biomarkers or key metabolites associated with biotic stress, devising improved diagnostic methods to efficiently assess pest and pathogen attack and generating improved crop varieties with the help of combined application of analytical and molecular tools.

Metabolomic profiling of the aqueous humor in patients with pediatric cataract.

Pediatric cataract, including congenital and developmental cataract, is a kind of pediatric vision-threatening disease with extensive phenotypic heterogeneity and multiple mechanisms. We aimed to investigate the metabolite profile of aqueous humor (AH) in patients with pediatric cataracts, and identify underlying mutual correlations between differential metabolites. Metabolomic profiles of AH were analyzed and compared between pediatric cataract patients (n = 33) and age-related cataract patients without metabolic diseases (n = 29), using global untargeted metabolomics with ultra-high-performance liquid chromatography tandem mass spectrometry. Principal component analysis, partial least squares discriminant analysis and heat map were applied. Enriched pathway analysis was conducted using Kyoto Encyclopedia of Genes and Genomes. Receiver-operating characteristic (ROC) analyses were employed to select potential biomarkers. A total of 318 metabolites were identified, of which 54 differential metabolites (25 upregulated and 29 downregulated) were detected in pediatric cataract group compared with controls (variable importance of projection >1.0, fold change ≥1.5 or ≤ 0.667 and P < 0.05). A significant accumulation of N-Acetyl-Dl-glutamic acid was observed in pediatric cataract group. The differential metabolites were mainly enriched in histidine metabolism (increased L-Histidine and decreased 1-Methylhistamine) and the tryptophan metabolism (increased N-Formylkynurenine and L-Kynurenine). 5-Aminosalicylic acid showed strong positive mutual inter-correlation with L-Tyrosinemethylester and N,N-Diethylethanolamine, both of which were down-regulated in pediatric cataract group. The ROC analysis implied 11 metabolites served as potential biomarkers for pediatric cataract patients (all area under the ROC curve ≥0.900). These results illustrated novel potential metabolites and metabolic pathways in pediatric cataract, which provides new insights into the pathophysiology of pediatric cataract.

The metabolome as a diagnostic for maximal aerobic capacity during exercise in type 1 diabetes.

AIMS/HYPOTHESIS: Our aim was to characterise the in-depth metabolic response to aerobic exercise and the impact of residual pancreatic beta cell function in type 1 diabetes. We also aimed to use the metabolome to distinguish individuals with type 1 diabetes with reduced maximal aerobic capacity in exercise defined by V ˙ O 2peak . METHODS: Thirty participants with type 1 diabetes (≥3 years duration) and 30 control participants were recruited. Groups did not differ in age or sex. After quantification of peak stimulated C-peptide, participants were categorised into those with undetectable (<3 pmol/l), low (3-200 pmol/l) or high (>200 pmol/l) residual beta cell function. Maximal aerobic capacity was assessed by V ˙ O 2peak test and did not differ between control and type 1 diabetes groups. All participants completed 45 min of incline treadmill walking (60% V ˙ O 2peak ) with venous blood taken prior to exercise, immediately post exercise and after 60 min recovery. Serum was analysed using targeted metabolomics. Metabolomic data were analysed by multivariate statistics to define the metabolic phenotype of exercise in type 1 diabetes. Receiver operating characteristic (ROC) curves were used to identify circulating metabolomic markers of maximal aerobic capacity ( V ˙ O 2peak ) during exercise in health and type 1 diabetes. RESULTS: Maximal aerobic capacity ( V ˙ O 2peak ) inversely correlated with HbA1c in the type 1 diabetes group (r2=0.17, p=0.024). Higher resting serum tricarboxylic acid cycle metabolites malic acid (fold change 1.4, p=0.001) and lactate (fold change 1.22, p=1.23×10-5) differentiated people with type 1 diabetes. Higher serum acylcarnitines (AC) (AC C14:1, F value=12.25, p=0.001345; AC C12, F value=11.055, p=0.0018) were unique to the metabolic response to exercise in people with type 1 diabetes. C-peptide status differentially affected metabolic responses in serum ACs during exercise (AC C18:1, leverage 0.066; squared prediction error 3.07). The malic acid/pyruvate ratio in rested serum was diagnostic for maximal aerobic capacity ( V ˙ O 2peak ) in people with type 1 diabetes (ROC curve AUC 0.867 [95% CI 0.716, 0.956]). CONCLUSIONS/INTERPRETATION: The serum metabolome distinguishes high and low maximal aerobic capacity and has diagnostic potential for facilitating personalised medicine approaches to manage aerobic exercise and fitness in type 1 diabetes.

Diet Mediate the Impact of Host Habitat on Gut Microbiome and Influence Clinical Indexes by Modulating Gut Microbes and Serum Metabolites.

The impact of external factors on the human gut microbiota and how gut microbes contribute to human health is an intriguing question. Here, the gut microbiome of 3,224 individuals (496 with serum metabolome) with 109 variables is studied. Multiple analyses reveal that geographic factors explain the greatest variance of the gut microbiome and the similarity of individuals' gut microbiome is negatively correlated with their geographic distance. Main food components are the most important factors that mediate the impact of host habitats on the gut microbiome. Diet and gut microbes collaboratively contribute to the variation of serum metabolites, and correlate to the increase or decrease of certain clinical indexes. Specifically, systolic blood pressure is lowered by vegetable oil through increasing the abundance of Blautia and reducing the serum level of 1-palmitoyl-2-palmitoleoyl-GPC (16:0/16:1), but it is reduced by fruit intake through increasing the serum level of Blautia improved threonate. Besides, aging-related clinical indexes are also closely correlated with the variation of gut microbes and serum metabolites. In this study, the linkages of geographic locations, diet, the gut microbiome, serum metabolites, and physiological indexes in a Chinese population are characterized. It is proved again that gut microbes and their metabolites are important media for external factors to affect human health.

Untargeted metabolomics reveals potential plasma biomarkers for diagnosis of primary aldosteronism using liquid chromatography-mass spectrometry.

Metabolite profiling has the potential to comprehensively bridge phenotypes and complex heterogeneous physiological and pathological states. We performed a metabolomics study using parallel liquid chromatography-mass spectrometry (LC-MS) combined with multivariate data analysis to screen for biomarkers of primary aldosteronism (PA) from a cohort of 111 PA patients and 218 primary hypertension (PH) patients. Hydrophilic interaction chromatography and reversed-phase liquid chromatography separations were employed to obtain a global plasma metabolome of endogenous metabolites. The satisfactory classification between PA and PH patients was obtained using the MVDA model. A total of 35 differential metabolites were screened out and identified. A diagnostic biomarker panel was established using the least absolute shrinkage and selection operator (LASSO) binary logistic regression model and receiver operating characteristic analysis. Joint analysis with clinical indicators, including plasma supine aldosterone level, plasma orthostatic aldosterone level, body mass index, and blood potassium, revealed that the combination of metabolite biomarker panel and plasma supine aldosterone has the best clinical diagnostic efficacy.

Serum metabolomics analysis combined with network pharmacology reveals possible mechanisms of postoperative cognitive dysfunction in the treatment of Mongolian medicine Eerdun Wurile basic formula.

This study analyzed the endogenous metabolites and metabolic pathways in the serum of Sprague-Dawley (SD) rats gavaged with the Eerdun Wurile basic formula (EWB) using metabolomics methods and network pharmacology to explore the possible mechanism of action of the EWB in improving postoperative cognitive dysfunction (POCD). SD rats were divided into the basic formula group, which received the EWB, and the control group, which received equal amounts of distilled water. The blood was collected from the abdominal aorta and analyzed for metabolite profiles using ultra-high-performance liquid chromatography-mass spectrometry (UHPLC-MS). Network pharmacology predicts the targets of the differential metabolites and disease targets; takes the intersection and constructs a "metabolite-disease-target" network; and performs protein-protein interaction, Gene Ontology, and Kyoto Encyclopedia of Genes and Genomes analyses. A total of 56 metabolites were selected for significant differences between the groups, mainly affecting amphetamine addiction, alcoholism, and regulation of lipolysis in adipocytes. A total of 177 potential targets for differential metabolite action in POCD were selected. The PI3K-Akt pathway, the HIF-1 pathway, and the FoxO pathway were in key positions. The studies have shown that EWB could improve POCD through multicomponents, multitargets, and multipathways, providing new possibilities and reference values for the treatment of POCD.

Nontargeted metabolomics reveals sequential changes in amino acid and ferroptosis-related metabolism in Parkinson's disease.

Parkinson's disease (PD) is inseparable from metabolic disorders but lacks assessment of specific metabolite alteration. To explore the sequential metabolic changes in PD progression, we evenly divided 78 C57BL/6 mice (10 weeks) into six groups (one control group and five experimental groups) and collected the hippocampus tissue of mice after treating with 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine, and probenecid (twice a week) at five periods (1, 2, 3, 4, and 5 weeks) for metabolome analysis. Our study identified 567 differentially abundant metabolites (DAMs) (total 4348 metabolites). Compared with controls, 145, 146, 171, 208, and 213 DAMs were obtained from the five experimental groups, respectively. Notably, 40 shared DAMs were present in five experimental groups, of which 22 shared DAMs formed a new metabolic network based on amino acid metabolism. Compared with group W3, 84 DAMs were identified in group W5, including 12 unique DAMs. DAMs in different stages of PD were significantly enriched in amino acid metabolism pathway, lipid metabolism pathway, and ferroptosis pathway. l-Glutamine, spermidine, and l-tryptophan were the key hubs in the whole metabolic process of PD. N-Formyl-l-methionine gradually increased in abundance with PD progression, whereas 5-methylcytosine gradually decreased. The study emphasized the sequential changes in DAMs in PD progression, stimulating subsequent studies.

A multi-tissue metabolome atlas of primate pregnancy.

Pregnancy induces dramatic metabolic changes in females; yet, the intricacies of this metabolic reprogramming remain poorly understood, especially in primates. Using cynomolgus monkeys, we constructed a comprehensive multi-tissue metabolome atlas, analyzing 273 samples from 23 maternal tissues during pregnancy. We discovered a decline in metabolic coupling between tissues as pregnancy progressed. Core metabolic pathways that were rewired during primate pregnancy included steroidogenesis, fatty acid metabolism, and arachidonic acid metabolism. Our atlas revealed 91 pregnancy-adaptive metabolites changing consistently across 23 tissues, whose roles we verified in human cell models and patient samples. Corticosterone and palmitoyl-carnitine regulated placental maturation and maternal tissue progenitors, respectively, with implications for maternal preeclampsia, diabetes, cardiac hypertrophy, and muscle and liver regeneration. Moreover, we found that corticosterone deficiency induced preeclampsia-like inflammation, indicating the atlas's potential clinical value. Overall, our multi-tissue metabolome atlas serves as a framework for elucidating the role of metabolic regulation in female health during pregnancy.

Metabolomics at the tumor microenvironment interface: Decoding cellular conversations.

Cancer heterogeneity remains a significant challenge for effective cancer treatments. Altered energetics is one of the hallmarks of cancer and influences tumor growth and drug resistance. Studies have shown that heterogeneity exists within the metabolic profile of tumors, and personalized-combination therapy with relevant metabolic interventions could improve patient response. Metabolomic studies are identifying novel biomarkers and therapeutic targets that have improved treatment response. The spatial location of elements in the tumor microenvironment are becoming increasingly important for understanding disease progression. The evolution of spatial metabolomics analysis now allows scientists to deeply understand how metabolite distribution contributes to cancer biology. Recently, these techniques have spatially resolved metabolite distribution to a subcellular level. It has been proposed that metabolite mapping could improve patient outcomes by improving precision medicine, enabling earlier diagnosis and intraoperatively identifying tumor margins. This review will discuss how altered metabolic pathways contribute to cancer progression and drug resistance and will explore the current capabilities of spatial metabolomics technologies and how these could be integrated into clinical practice to improve patient outcomes.

Transcriptome and metabolome analysis reveals stage-specific metabolite accumulation during maturity of Chinese black truffle Tuber indicum.

Tuber indicum is the most economically important member of Tuber, with the highest production and widest distribution in China. However, the overexploitation of immature ascocarps not only has driven wild resources of the species toward extinction, but also has caused enconomic losses and a decline in the reputation of T.indicum quality. In this study, stage-specific metabolites of T. indicum in relation to nutritional quality and the mechanism of their accumulations were explored by transcriptome and metabolome analysis at five harvest times, representing four maturation stages. A total of 663 compounds were identified in T. indicum ascocarps by a widely targeted metabolomic approach. Lipid compounds are the most prominent metabolites (18%) in our samples and also are higher accumulation at the immature stage than at mature stage, representing 30.16% differential accumulated metabolites in this stage. Levels of some of the amino acids, such as S-(methyl) glutathione, S-adenosylmethionine, which are known truffle aroma precursors, were increased at the mature stage. The gene expression level related to the biosynthesis of volatile organic compounds were verified by qPCR. This study contributes to the preliminary understanding of metabolites variations in T. indicum ascocarps during maturity for quality evaluation and truffle biology.

Metabolomic Signatures of Alzheimer's Disease Indicate Brain Region-Specific Neurodegenerative Progression.

Pathological mechanisms contributing to Alzheimer's disease (AD) are still elusive. Here, we identified the metabolic signatures of AD in human post-mortem brains. Using 1H NMR spectroscopy and an untargeted metabolomics approach, we identified (1) metabolomic profiles of AD and age-matched healthy subjects in post-mortem brain tissue, and (2) region-common and region-unique metabolome alterations and biochemical pathways across eight brain regions revealed that BA9 was the most affected. Phenylalanine and phosphorylcholine were mainly downregulated, suggesting altered neurotransmitter synthesis. N-acetylaspartate and GABA were upregulated in most regions, suggesting higher inhibitory activity in neural circuits. Other region-common metabolic pathways indicated impaired mitochondrial function and energy metabolism, while region-unique pathways indicated oxidative stress and altered immune responses. Importantly, AD caused metabolic changes in brain regions with less well-documented pathological alterations that suggest degenerative progression. The findings provide a new understanding of the biochemical mechanisms of AD and guide biomarker discovery for personalized risk prediction and diagnosis.

A Targeted Mass Spectrometry Approach to Identify Peripheral Changes in Metabolic Pathways of Patients with Alzheimer's Disease.

Alzheimer's disease (AD), a neurodegenerative disorder, is the most common cause of dementia in the elderly population. Since its original description, there has been intense debate regarding the factors that trigger its pathology. It is becoming apparent that AD is more than a brain disease and harms the whole-body metabolism. We analyzed 630 polar and apolar metabolites in the blood of 20 patients with AD and 20 healthy individuals, to determine whether the composition of plasma metabolites could offer additional indicators to evaluate any alterations in the metabolic pathways related to the illness. Multivariate statistical analysis showed that there were at least 25 significantly dysregulated metabolites in patients with AD compared with the controls. Two membrane lipid components, glycerophospholipids and ceramide, were upregulated, whereas glutamic acid, other phospholipids, and sphingolipids were downregulated. The data were analyzed using metabolite set enrichment analysis and pathway analysis using the KEGG library. The results showed that at least five pathways involved in the metabolism of polar compounds were dysregulated in patients with AD. Conversely, the lipid pathways did not show significant alterations. These results support the possibility of using metabolome analysis to understand alterations in the metabolic pathways related to AD pathophysiology.

Capillary electrophoresis-mass spectrometry as a tool for Caenorhabditis elegans metabolomics research.

INTRODUCTION: Polar metabolites in Caenorhabditis elegans (C. elegans) have predominantly been analyzed using hydrophilic interaction liquid chromatography coupled to mass spectrometry (HILIC-MS). Capillary electrophoresis coupled to mass spectrometry (CE-MS) represents another complementary analytical platform suitable for polar and charged analytes. OBJECTIVE: We compared CE-MS and HILIC-MS for the analysis of a set of 60 reference standards relevant for C. elegans and specifically investigated the strengths of CE separation. Furthermore, we employed CE-MS as a complementary analytical approach to study polar metabolites in C. elegans samples, particularly in the context of longevity, in order to address a different part of its metabolome. METHOD: We analyzed 60 reference standards as well as metabolite extracts from C. elegans daf-2 loss-of-function mutants and wild-type (WT) samples using HILIC-MS and CE-MS employing a Q-ToF-MS instrument. RESULTS: CE separations showed narrower peak widths and a better linearity of the estimated response function across different concentrations which is linked to less saturation of the MS signals. Additionally, CE exhibited a distinct selectivity in the separation of compounds compared to HILIC-MS, providing complementary information for the analysis of the target compounds. Analysis of C. elegans metabolites of daf-2 mutants and WT samples revealed significant alterations in shared metabolites identified through HILIC-MS, as well as the presence of distinct metabolites. CONCLUSION: CE-MS was successfully applied in C. elegans metabolomics, being able to recover known as well as identify novel putative biomarkers of longevity.