N-acyl Taurines and Acylcarnitines Cause an Imbalance in Insulin Synthesis and Secretion Provoking β Cell Dysfunction in Type 2 Diabetes

Estrogenic activity of E2-conjugated GLP-1 is mediated by intracellular endolysosomal acidification and estrone metabolism

OBJECTIVE

Recent modifications to glucagon-like peptide 1 (GLP-1), known for its insulinotropic and satiety-inducing effects, have focused on conjugating small molecules to enable selective delivery into GLP-1R+ tissues to achieve targeted synergy and improved metabolic outcomes. Despite continued advancements in GLP-1/small molecule conjugate strategies, the intracellular mechanisms facilitating concurrent GLP-1R signaling and small molecule cargo release remain poorly understood.

METHODS

We evaluate an estradiol (E2)-conjugated GLP-1 (GLP-1-CEX/E2) for relative differences in GLP-1R signaling and trafficking, and elucidate endolysosomal dynamics that lead to estrogenic activity using various live-cell, reporter, imaging, and mass-spectrometry techniques.

RESULTS

We find GLP-1-CEX/E2 does not differentially activate or traffic the GLP-1R relative to its unconjugated GLP-1 backbone (GLP-1-CEX), but uniquely internalizes the E2 moiety and stimulates estrogenic signaling. Endolysosomal pH-dependent proteolytic activity likely mediates E2 moiety liberation, as evidenced by clear amplification in estrogenic activity following co-administration with lysosomal VATPase activator EN6. The hypothesized liberated metabolite from GLP-1-CEX/E2, E2-3-ether, exhibits partial estrogenic efficacy through ERα, and is predisposed toward estrone-3-sulfate conversion. Finally, we identify relative increases in intracellular E2, estrone, and estrone-3-sulfate following GLP-1-CEX/E2 incubation in GLP-1R+ cells, demonstrating proof-of-principle for desired cargo release.

CONCLUSION

Together, our data suggest that GLP-1-CEX/E2 depends on GLP-1R trafficking and lysosome acidification for estrogenic efficacy, with a likely conversion of the liberated E2-3-ether metabolite into estrone-3-sulfate, resulting in a residual downstream flux into active estradiol. Our current findings aim to improve the understanding of small molecule targeting and the efficacy behind GLP-1/small molecule conjugates.

Unraveling the causal pathway between phosphatidylinositol, metabolites, and metabolic syndrome: a Mendelian randomization study

INTRODUCTION

Observational studies have increasingly acknowledged the influence of Phosphatidylinositol (PI) on metabolic syndrome (MetS). Nevertheless, the causal association between PI and MetS remains unclear due to the presence of confounding factors and the potential for reverse causation in observational settings. This study seeks to clarify the causal link between PI and MetS while investigating the role of mediating metabolites.

METHODS

A two-sample Mendelian randomization (MR) analysis was performed to examine the association between PI and MetS, utilizing aggregated data from genome-wide association studies (GWAS). Additionally, a two-step MR approach was applied to quantify the mediation effect of metabolites on the PI-MetS relationship. The inverse variance weighted (IVW) method served as the primary analytical approach, complemented by various sensitivity analyses employing alternative techniques.

RESULTS

A significant positive association was found between genetically predicted PI and a 17% increased risk of MetS. Genetically predicted metabolites, including 4-cholesten-3-one (IVW: OR 1.264, 95% CI 1.076-1.483, p = 0.004), N-acetylalliin (IVW: OR 1.189, 95% CI 1.008-1.402, p = 0.040), and the Adenosine 5'-diphosphate to 5-oxoproline ratio (IVW: OR 1.191, 95% CI 1.045-1.357, p = 0.009), were each significantly associated with an increased risks of MetS, accounting for 14.50, 11.41%, 11.87% and % of the total effect, respectively. Notably, the Retinol to oleoyl-linoleoyl-glycerol ratio (IVW: OR 0.643, 95% CI 0.466-0.887, p = 0.007) mediated 62.6% of the effect, highlighting its pivotal role in the causal pathway linking PI to MetS. Moreover, 1-palmitoyl-2-dihomo-linolenoyl-GPC (IVW: OR 0.865, 95% CI 0.752-0.995, p = 0.042) and the Creatine to carnitine ratio (IVW: OR 0.853, 95% CI 0.740-0.983, p = 0.028) were associated with a reduced risk of MetS, demonstrating inhibitory effects within their respective pathways that accounted to 35.03% and 8.45% reductions in risk, respectively.

CONCLUSIONS

Our MR analysis demonstrated a positive association between PI and an increased risk of MetS. Furthermore, the metabolite-mediated PI significantly influenced MetS risk. These findings may offer valuable insights into the pathogenesis of MetS and inform future clinical research.

Comprehensive review of the expanding roles of the carnitine pool in metabolic physiology: beyond fatty acid oxidation

Traditionally, the carnitine pool is closely related to fatty acid metabolism. However, with increasing research, the pleiotropic effects of the carnitine pool have gradually emerged. The purpose of this review is to comprehensively investigate of the emerging understanding of the pleiotropic role of the carnitine pool, carnitine/acylcarnitines are not only auxiliaries or metabolites of fatty acid oxidation, but also play more complex and diverse roles, including energy metabolism, mitochondrial homeostasis, epigenetic regulation, regulation of inflammation and the immune system, tumor biology, signal transduction, and neuroprotection. This review provides an overview of the complex network of carnitine synthesis, transport, shuttle, and regulation, carnitine/acylcarnitines have the potential to be used as communication molecules, biomarkers and therapeutic targets for multiple diseases, with profound effects on intercellular communication, metabolic interactions between organs and overall metabolic health. The purpose of this review is to comprehensively summarize the multidimensional biological effects of the carnitine pool beyond its traditional role in fatty acid oxidation and to summarize the systemic effects mediated by carnitine/acylcarnitine to provide new perspectives for pharmacological research and treatment innovation and new strategies for the prevention and treatment of a variety of diseases.

Inter-organ cross-talk in human cancer cachexia revealed by spatial metabolomics

BACKGROUND

Cancer cachexia (CCx) presents a multifaceted challenge characterized by negative protein and energy balance and systemic inflammatory response activation. While previous CCx studies predominantly focused on mouse models or human body fluids, there's an unmet need to elucidate the molecular inter-organ cross-talk underlying the pathophysiology of human CCx.

METHODS

Spatial metabolomics were conducted on liver, skeletal muscle, subcutaneous and visceral adipose tissue, and serum from cachectic and control cancer patients. Organ-wise comparisons were performed using component, pathway enrichment and correlation network analyses. Inter-organ correlations in CCx altered pathways were assessed using Circos. Machine learning on tissues and serum established classifiers as potential diagnostic biomarkers for CCx.

RESULTS

Distinct metabolic pathway alteration was detected in CCx, with adipose tissues and liver displaying the most significant (P ≤ 0.05) metabolic disturbances. CCx patients exhibited increased metabolic activity in visceral and subcutaneous adipose tissues and liver, contrasting with decreased activity in muscle and serum compared to control patients. Carbohydrate, lipid, amino acid, and vitamin metabolism emerged as highly interacting pathways across different organ systems in CCx. Muscle tissue showed decreased (P ≤ 0.001) energy charge in CCx patients, while liver and adipose tissues displayed increased energy charge (P ≤ 0.001). We stratified CCx patients by severity and metabolic changes, finding that visceral adipose tissue is most affected, especially in cases of severe cachexia. Morphometric analysis showed smaller (P ≤ 0.05) adipocyte size in visceral adipose tissue, indicating catabolic processes. We developed tissue-based classifiers for cancer cachexia specific to individual organs, facilitating the transfer of patient serum as minimally invasive diagnostic markers of CCx in the constitution of the organs.

CONCLUSIONS

These findings support the concept of CCx as a multi-organ syndrome with diverse metabolic alterations, providing insights into the pathophysiology and organ cross-talk of human CCx. This study pioneers spatial metabolomics for CCx, demonstrating the feasibility of distinguishing cachexia status at the organ level using serum.

The microbiome diversifies N-acyl lipid pools - including short-chain fatty acid-derived compounds

N-acyl lipids are important mediators of several biological processes including immune function and stress response. To enhance the detection of N-acyl lipids with untargeted mass spectrometry-based metabolomics, we created a reference spectral library retrieving N-acyl lipid patterns from 2,700 public datasets, identifying 851 N-acyl lipids that were detected 356,542 times. 777 are not documented in lipid structural databases, with 18% of these derived from short-chain fatty acids and found in the digestive tract and other organs. Their levels varied with diet, microbial colonization, and in people living with diabetes. We used the library to link microbial N-acyl lipids, including histamine and polyamine conjugates, to HIV status and cognitive impairment. This resource will enhance the annotation of these compounds in future studies to further the understanding of their roles in health and disease and highlight the value of large-scale untargeted metabolomics data for metabolite discovery.

Empirically establishing drug exposure records directly from untargeted metabolomics data

Despite extensive efforts, extracting information on medication exposure from clinical records remains challenging. To complement this approach, we developed the tandem mass spectrometry (MS/MS) based GNPS Drug Library. This resource integrates MS/MS data for drugs and their metabolites/analogs with controlled vocabularies on exposure sources, pharmacologic classes, therapeutic indications, and mechanisms of action. It enables direct analysis of drug exposure and metabolism from untargeted metabolomics data independent of clinical records. Our library facilitates stratification of individuals in clinical studies based on the empirically detected medications, exemplified by drug-dependent microbiota-derived N-acyl lipid changes in a cohort with human immunodeficiency virus. The GNPS Drug Library holds potential for broader applications in drug discovery and precision medicine.

Lipidomics profiling and circulating triglyceride concentrations in sub-Saharan African individuals

Elevated triglycerides (TG) are a risk factor for cardiometabolic disorders. There are limited data on lipidomics profiles associated with serum triglycerides concentrations, although these could advance our understanding of the mechanisms underlying these associations. We conducted a lipidomics study of 308 Nigerians with replication in 199 Kenyans. Regression models were used to assess the association of TG with 480 lipid metabolites. Association and mediation analyses were conducted to determine the relationship among TG, metabolites, and several cardiometabolic traits. Ninety-nine metabolites were significantly associated with TG, and 91% of these associations replicated. Overrepresentation analysis identified enrichment of diacylglycerols, monoacylglycerols, diacylglycerophosphoethanolamines, monoacylglycerophosphocholines, ceramide phosphocholines, and diacylglycerophosphocholines. TG-cardiometabolic trait associations were largely mediated by TG-associated metabolites. Associations with type 2 diabetes, waist circumference, body mass index, total cholesterol, and low-density lipoprotein cholesterol concentration were independently mediated by metabolites in multiple subpathways. This lipidomics study in sub-Saharan Africans demonstrated that TG is associated with several non-TG lipids classes, including phosphatidylethanolamines, phosphatidylcholines, lysophospholipids, and plasmalogens, some of which may mediate the effect of TG as a risk factor for cardiometabolic disorders. The study identifies metabolites that are more proximal to cardiometabolic traits, which may be useful for understanding the underlying biology as well as differences in TG-trait associations across ancestries.

Mendelian randomization demonstrates a causal link between peripheral circulating acylcarnitines and intracranial aneurysms

Intracranial aneurysm (IA) is the most prevalent type of cerebral vascular disease causing life-threatening subarachnoid hemorrhages (SAH). A long-term vascular structure remodeling is considered as the main pathophysiological feature of IAs. However, the causal factors triggering the pathophysiological process are not clear. Recently, the abnormalities of peripheral circulating proteins and metabolites have been found in IAs patients and associated with the ruptures. We comprehensively investigated the potential causal relationship between blood metabolites and proteins and IAs using the mendelian randomization (MR) analysis. We applied two-sample MR to explore the potential causal association between peripheral circulating metabolites (191 blood metabolites) and proteins (1398 proteins) and IAs using data from the FinnGen study and the GWAS datasets published by Bakker et al. We identified palmitoylcarnitine, stearoylcarnitine and 2-tetradecenoylcarnitine as causal contributors of IAs and ruptures. Further two-step mediation MR analysis suggested that hypertension as one of the contributors of IAs and ruptures mediated the causal relationship between palmitoylcarnitine, stearoylcarnitine and 2-tetradecenoylcarnitine and IAs. Together, our study demonstrates that blood metabolic palmitoylcarnitine, stearoylcarnitine and 2-tetradecenoylcarnitine are causally linked to the formation and rupture of IAs. Hypertension partially mediates the causal effects.

Metabolomic and genetic architecture of gestational diabetes subtypes

AIMS/HYPOTHESIS

Physiological gestational diabetes mellitus (GDM) subtypes that may confer different risks for adverse pregnancy outcomes have been defined. The aim of this study was to characterise the metabolome and genetic architecture of GDM subtypes to address the hypothesis that they differ between GDM subtypes.

METHODS

This was a cross-sectional study of participants in the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) study who underwent an OGTT at approximately 28 weeks' gestation. GDM was defined retrospectively using International Association of Diabetes and Pregnancy Study Groups/WHO criteria, and classified as insulin-deficient GDM (insulin secretion <25th percentile with preserved insulin sensitivity) or insulin-resistant GDM (insulin sensitivity <25th percentile with preserved insulin secretion). Metabolomic analyses were performed on fasting and 1 h serum samples in 3463 individuals (576 with GDM). Genome-wide genotype data were obtained for 8067 individuals (1323 with GDM).

RESULTS

Regression analyses demonstrated striking differences between the metabolomes for insulin-deficient or insulin-resistant GDM compared to those with normal glucose tolerance. After adjustment for covariates, 33 fasting metabolites, including 22 medium- and long-chain acylcarnitines, were uniquely associated with insulin-deficient GDM; 23 metabolites, including the branched-chain amino acids and their metabolites, were uniquely associated with insulin-resistant GDM; two metabolites (glycerol and 2-hydroxybutyrate) were associated with the same direction of association with both subtypes. Subtype differences were also observed 1 h after a glucose load. In genome-wide association studies, variants within MTNR1B (rs10830963, p=3.43×10-18, OR 1.55) and GCKR (rs1260326, p=5.17×10-13, OR 1.43) were associated with GDM. Variants in GCKR (rs1260326, p=1.36×10-13, OR 1.60) and MTNR1B (rs10830963, p=1.22×10-9, OR 1.49) demonstrated genome-wide significant association with insulin-resistant GDM; there were no significant associations with insulin-deficient GDM. The lead SNP in GCKR, rs1260326, was associated with the levels of eight of the 25 fasting metabolites that were associated with insulin-resistant GDM and ten of 41 1 h metabolites that were associated with insulin-resistant GDM.

CONCLUSIONS/INTERPRETATION

This study demonstrates that physiological GDM subtypes differ in their metabolome and genetic architecture. These findings require replication in additional cohorts, but suggest that these differences may contribute to subtype-related adverse pregnancy outcomes.

Lipidomics Analysis Unravels Aberrant Lipid Species and Pathways Induced by Zinc Oxide Nanoparticles in Kidney Cells

Zinc oxide nanoparticles (ZnO NPs) are widely used in versatile applications, from high technology to household products. While numerous studies have examined the toxic gene profile of ZnO NPs across various tissues, the specific lipid species associated with adverse effects and potential biomarkers remain elusive. In this study, we conducted a liquid chromatography-mass spectrometry based lipidomics analysis to uncover potential lipid biomarkers in human kidney cells following treatment with ZnO NPs. Furthermore, we employed lipid pathway enrichment analysis (LIPEA) to elucidate altered lipid-related signaling pathways. Our results demonstrate that ZnO NPs induce cytotoxicity in renal epithelial cells and modulate lipid species; we identified 64 lipids with a fold change (FC) > 2 and p < 0.01 with corrected p < 0.05 in HK2 cells post-treatment with ZnO NPs. Notably, the altered lipids between control HK2 cells and those treated with ZnO NPs were associated with the sphingolipid, autophagy, and glycerophospholipid pathways. This study unveils novel potential lipid biomarkers of ZnO NP nanotoxicity, representing the first lipidomic profiling of ZnO NPs in human renal epithelial cells.

Exploring the Interactions between Obesity and Diabetes: Implications for Understanding Metabolic Dysregulation in a Saudi Arabian Adult Population

The rising prevalence of obesity in Saudi Arabia is a major contributor to the nation's high levels of cardiometabolic diseases such as type 2 diabetes. To assess the impact of obesity on the diabetic metabolic phenotype presented in young Saudi Arabian adults, participants (n = 289, aged 18-40 years) were recruited and stratified into four groups: healthy weight (BMI 18.5-24.99 kg/m2) with (n = 57) and without diabetes (n = 58) or overweight/obese (BMI > 24.99 kg/m2) with (n = 102) and without diabetes (n = 72). Distinct plasma metabolic phenotypes associated with high BMI and diabetes were identified using nuclear magnetic resonance spectroscopy and ultraperformance liquid chromatography mass spectrometry. Increased plasma glucose and dysregulated lipoproteins were characteristics of obesity in individuals with and without diabetes, but the obesity-associated lipoprotein phenotype was partially masked in individuals with diabetes. Although there was little difference between diabetics and nondiabetics in the global plasma LDL cholesterol and phospholipid concentration, the distribution of lipoprotein particles was altered in diabetics with a shift toward denser and more atherogenic LDL5 and LDL6 particles, which was amplified in the presence of obesity. Further investigation is warranted in larger Middle Eastern populations to explore the dysregulation of metabolism driven by interactions between obesity and diabetes in young adults.

[Metabolic syndrome in clinical psychiatric practice]

A literature review in PubMed and Google databases was performed. Inclusion criteria: randomized clinical trials, meta-analyses and systematic reviews, relevant full-text articles on metabolic syndrome (MS) in patients with schizophrenia. Exclusion criteria: articles of poor quality. The terminology of the article corresponds to that used in the publications included in the review. The review substantiates the relevance of the problem of MS, discloses the concept and discusses its criteria, provides data on the prevalence of MS in patients with schizophrenia, discusses the relationship between MS and schizophrenia, MS and cognitive impairment in schizophrenia, and describes metabolic changes in patients with a first episode of psychosis or early stage schizophrenia. Recommendations on therapeutic tactics in the development of metabolic syndrome in patients with schizophrenia are given.

State-of-the-art mass spectrometry imaging applications in biomedical research

Mass spectrometry imaging has advanced from a niche technique to a widely applied spatial biology tool operating at the forefront of numerous fields, most notably making a significant impact in biomedical pharmacological research. The growth of the field has gone hand in hand with an increase in publications and usage of the technique by new laboratories, and consequently this has led to a shift from general MSI reviews to topic-specific reviews. Given this development, we see the need to recapitulate the strengths of MSI by providing a more holistic overview of state-of-the-art MSI studies to provide the new generation of researchers with an up-to-date reference framework. Here we review scientific advances for the six largest biomedical fields of MSI application (oncology, pharmacology, neurology, cardiovascular diseases, endocrinology, and rheumatology). These publications thereby give examples for at least one of the following categories: they provide novel mechanistic insights, use an exceptionally large cohort size, establish a workflow that has the potential to become a high-impact methodology, or are highly cited in their field. We finally have a look into new emerging fields and trends in MSI (immunology, microbiology, infectious diseases, and aging), as applied MSI is continuously broadening as a result of technological breakthroughs.

Human Pancreatic Islets React to Glucolipotoxicity by Secreting Pyruvate and Citrate

Progressive decline in pancreatic beta-cell function is central to the pathogenesis of type 2 diabetes (T2D). Here, we explore the relationship between the beta cell and its nutritional environment, asking how an excess of energy substrate leads to altered energy production and subsequent insulin secretion. Alterations in intracellular metabolic homeostasis are key markers of islets with T2D, but changes in cellular metabolite exchanges with their environment remain unknown. We answered this question using nuclear magnetic resonance-based quantitative metabolomics and evaluated the consumption or secretion of 31 extracellular metabolites from healthy and T2D human islets. Islets were also cultured under high levels of glucose and/or palmitate to induce gluco-, lipo-, and glucolipotoxicity. Biochemical analyses revealed drastic alterations in the pyruvate and citrate pathways, which appear to be associated with mitochondrial oxoglutarate dehydrogenase (OGDH) downregulation. We repeated these manipulations on the rat insulinoma-derived beta-pancreatic cell line (INS-1E). Our results highlight an OGDH downregulation with a clear effect on the pyruvate and citrate pathways. However, citrate is directed to lipogenesis in the INS-1E cells instead of being secreted as in human islets. Our results demonstrate the ability of metabolomic approaches performed on culture media to easily discriminate T2D from healthy and functional islets.

Spatially Resolved Metabolites in Stable and Unstable Human Atherosclerotic Plaques Identified by Mass Spectrometry Imaging

BACKGROUND

Impairments in carbohydrate, lipid, and amino acid metabolism drive features of plaque instability. However, where these impairments occur within the atheroma remains largely unknown. Therefore, we sought to characterize the spatial distribution of metabolites within stable and unstable atherosclerosis in both the fibrous cap and necrotic core.

METHODS

Atherosclerotic tissue specimens from 9 unmatched individuals were scored based on the Stary classification scale and subdivided into stable and unstable atheromas. After performing mass spectrometry imaging on these samples, we identified over 850 metabolite-related peaks. Using MetaboScape, METASPACE, and Human Metabolome Database, we confidently annotated 170 of these metabolites and found over 60 of these were different between stable and unstable atheromas. We then integrated these results with an RNA-sequencing data set comparing stable and unstable human atherosclerosis.

RESULTS

Upon integrating our mass spectrometry imaging results with the RNA-sequencing data set, we discovered that pathways related to lipid metabolism and long-chain fatty acids were enriched in stable plaques, whereas reactive oxygen species, aromatic amino acid, and tryptophan metabolism were increased in unstable plaques. In addition, acylcarnitines and acylglycines were increased in stable plaques whereas tryptophan metabolites were enriched in unstable plaques. Evaluating spatial differences in stable plaques revealed lactic acid in the necrotic core, whereas pyruvic acid was elevated in the fibrous cap. In unstable plaques, 5-hydroxyindoleacetic acid was enriched in the fibrous cap.

CONCLUSIONS

Our work here represents the first step to defining an atlas of metabolic pathways involved in plaque destabilization in human atherosclerosis. We anticipate this will be a valuable resource and open new avenues of research in cardiovascular disease.

Gene-based microbiome representation enhances host phenotype classification

With the concomitant advances in both the microbiome and machine learning fields, the gut microbiome has become of great interest for the potential discovery of biomarkers to be used in the classification of the host health status. Shotgun metagenomics data derived from the human microbiome is composed of a high-dimensional set of microbial features. The use of such complex data for the modeling of host-microbiome interactions remains a challenge as retaining de novo content yields a highly granular set of microbial features. In this study, we compared the prediction performances of machine learning approaches according to different types of data representations derived from shotgun metagenomics. These representations include commonly used taxonomic and functional profiles and the more granular gene cluster approach. For the five case-control datasets used in this study (Type 2 diabetes, obesity, liver cirrhosis, colorectal cancer, and inflammatory bowel disease), gene-based approaches, whether used alone or in combination with reference-based data types, allowed improved or similar classification performances as the taxonomic and functional profiles. In addition, we show that using subsets of gene families from specific functional categories of genes highlight the importance of these functions on the host phenotype. This study demonstrates that both reference-free microbiome representations and curated metagenomic annotations can provide relevant representations for machine learning based on metagenomic data. IMPORTANCE Data representation is an essential part of machine learning performance when using metagenomic data. In this work, we show that different microbiome representations provide varied host phenotype classification performance depending on the dataset. In classification tasks, untargeted microbiome gene content can provide similar or improved classification compared to taxonomical profiling. Feature selection based on biological function also improves classification performance for some pathologies. Function-based feature selection combined with interpretable machine learning algorithms can generate new hypotheses that can potentially be assayed mechanistically. This work thus proposes new approaches to represent microbiome data for machine learning that can potentiate the findings associated with metagenomic data.

Feeding of fish oil and medium-chain triglycerides to canines impacts circulating structural and energetic lipids, endocannabinoids, and non-lipid metabolite profiles

Introduction

The effect of medium-chain fatty acid-containing triglycerides (MCT), long-chain polyunsaturated fatty acid-containing triglycerides from fish oil (FO), and their combination (FO+MCT) on the serum metabolome of dogs (Canis familiaris) was evaluated.

Methods

Dogs (N = 64) were randomized to either a control food, one with 7% MCT, one with FO (0.18% eicosapentaenoate and 1.3% docosahexaenoate), or one with FO+MCT for 28 days following a 14-day washout period on the control food. Serum metabolites were analyzed via chromatography followed by mass spectrometry.

Results

Additive effects of serum metabolites were observed for a number of metabolite classes, including fatty acids, phospholipids, acylated amines including endocannabinoids, alpha-oxidized fatty acids, and methyl donors. Some effects of the addition of FO+MCT were different when the oils were combined compared with when each oil was fed separately, namely for acylcarnitines, omega-oxidized dicarboxylic acids, and amino acids. Several potentially beneficial effects on health were observed, including decreased circulating triglycerides and total cholesterol with the addition of FO (with or without MCT) and decreases in N-acyl taurines with the addition of MCT, FO, or FO+MCT.

Discussion

Overall, the results of this study provide a phenotypic characterization of the serum lipidomic response to dietary supplementation of long-chain n3-polyunsaturated and medium-chain saturated fats in canines.

Succinate mediates inflammation-induced adrenocortical dysfunction

The hypothalamus-pituitary-adrenal (HPA) axis is activated in response to inflammation leading to increased production of anti-inflammatory glucocorticoids by the adrenal cortex, thereby representing an endogenous feedback loop. However, severe inflammation reduces the responsiveness of the adrenal gland to adrenocorticotropic hormone (ACTH), although the underlying mechanisms are poorly understood. Here, we show by transcriptomic, proteomic, and metabolomic analyses that LPS-induced systemic inflammation triggers profound metabolic changes in steroidogenic adrenocortical cells, including downregulation of the TCA cycle and oxidative phosphorylation, in mice. Inflammation disrupts the TCA cycle at the level of succinate dehydrogenase (SDH), leading to succinate accumulation and disturbed steroidogenesis. Mechanistically, IL-1β reduces SDHB expression through upregulation of DNA methyltransferase 1 (DNMT1) and methylation of the SDHB promoter. Consequently, increased succinate levels impair oxidative phosphorylation and ATP synthesis and enhance ROS production, leading to reduced steroidogenesis. Together, we demonstrate that the IL-1β-DNMT1-SDHB-succinate axis disrupts steroidogenesis. Our findings not only provide a mechanistic explanation for adrenal dysfunction in severe inflammation, but also offer a potential target for therapeutic intervention.

Quantitative, Targeted Analysis of Gut Microbiota Derived Metabolites Provides Novel Biomarkers of Early Diabetic Kidney Disease in Type 2 Diabetes Mellitus Patients

Diabetic kidney disease (DKD) is one of the most debilitating complications of type 2 diabetes mellitus (T2DM), as it progresses silently to end-stage renal disease (ESRD). The discovery of novel biomarkers of early DKD becomes acute, as its incidence is reaching catastrophic proportions. Our study aimed to quantify previously identified metabolites from serum and urine through untargeted ultra-high-performance liquid chromatography coupled with electrospray ionization-quadrupole-time of flight-mass spectrometry (UHPLC-QTOF-ESI+-MS) techniques, such as the following: arginine, dimethylarginine, hippuric acid, indoxyl sulfate, p-cresyl sulfate, L-acetylcarnitine, butenoylcarnitine and sorbitol. The study concept was based on the targeted analysis of selected metabolites, using the serum and urine of 20 healthy subjects and 90 T2DM patients with DKD in different stages (normoalbuminuria-uACR < 30 mg/g; microalbuminuria-uACR 30-300 mg/g; macroalbuminuria-uACR > 300 mg/g). The quantitative evaluation of metabolites was performed with pure standards, followed by the validation methods such as the limit of detection (LOD) and the limit of quantification (LOQ). The following metabolites from this study resulted as possible biomarkers of early DKD: in serum-arginine, dimethylarginine, hippuric acid, indoxyl sulfate, butenoylcarnitine and sorbitol and in urine-p-cresyl sulfate.

The association and prediction value of acylcarnitine on diabetic nephropathy in Chinese patients with type 2 diabetes mellitus

BACKGROUND

Acylcarnitines play a role in type 2 diabetes mellitus (T2DM), but the relationship between acylcarnitine and diabetic nephropathy was unclear. We aimed to explore the association of acylcarnitine metabolites with diabetic nephropathy and estimate the predictive value of acylcarnitine for diabetic nephropathy.

METHODS

A total of 1032 (mean age: 57.24 ± 13.82) T2DM participants were derived from Liaoning Medical University First Affiliated Hospital. Mass Spectrometry was utilized to measure levels of 25 acylcarnitine metabolites in fasting plasma. Diabetic nephropathy was ascertained based on the medical records. Factor analysis was used to reduce the dimensions and extract factors of the 25 acylcarnitine metabolites. Logistic regression was used to estimate the relationship between factors extracted from the 25 acylcarnitine metabolites and diabetic nephropathy. Receiver operating characteristic curves were used to test the predictive values of acylcarnitine factors for diabetic nephropathy.

RESULTS

Among all T2DM participants, 138 (13.37%) patients had diabetic nephropathy. Six factors were extracted from 25 acylcarnitines, which account for 69.42% of the total variance. In multi-adjusted logistic regression models, the odds ratio (OR, 95% confidence interval [CI]) of diabetic nephropathy on factor 1 (including butyrylcarnitine/glutaryl-carnitine/hexanoylcarnitine/octanoylcarnitine/decanoylcarnitine/lauroylcarnitine/tetradecenoylcarnitine), factor 2 (including propionylcarnitine/palmitoylcarnitine/hydroxypalmitoleyl-carnitine/octadecanoylcarnitine/arachidiccarnitine), and factor 3 (including tetradecanoyldiacylcarnitine/behenic carnitine/tetracosanoic carnitine/hexacosanoic carnitine) were 1.33 (95%CI 1.12-1.58), 0.76 (95%CI 0.62-0.93), and 1.24 (95%CI 1.05-1.47), respectively. The area under the curve for diabetic nephropathy prediction was significantly increased after the complement of factors 1, 2, and 3 in traditional factors model (P < 0.01).

CONCLUSIONS

Some plasma acylcarnitine metabolites extracted in factors 1 and 3 were higher in diabetic nephropathy, while factor 2 was lower in diabetic nephropathy among T2DM patients. The addition of acylcarnitine to traditional factors model improved the predictive value for diabetic nephropathy.

A cross-sectional study identifying disparities in serum metabolic profiles among hypertensive patients with ISH, IDH and SDH subtypes

Background

It has been well acknowledged that disordered intestinal microflora and their fermented products play crucial role during the development of hypertension (HTN). Aberrant profiles of fecal bacteria have been documented in subjects with isolated systolic HTN (ISH) and isolated diastolic HTN (IDH) previously. Nevertheless, evidence regarding the association of metabolic products in the bloodstream with ISH, IDH and combined systolic and diastolic HTN (SDH) remains scarce.

Methods

We performed a cross-sectional study and conducted untargeted liquid chromatography-mass spectrometry (LC/MS) analysis on serum samples of 119 participants, including 13 subjects with normotension (SBP < 120/DBP < 80 mm Hg), 11 individuals with ISH (SBP ≥ 130/DBP < 80 mm Hg), 27 patients with IDH (SBP < 130/DBP ≥ 80 mm Hg), and 68 SDH patients (SBP ≥ 130, DBP ≥ 80 mm Hg).

Results

Here, the results showed clearly separated clusters in PLS-DA and OPLS-DA score plots for patients suffering from ISH, IDH and SDH when compared with normotension controls. The ISH group was characterized by elevated levels of 3,5-tetradecadien carnitine and notable reduction of maleic acid. While IDH patients were enriched with metabolites in L-lactic acid and depleted in citric acid. Stearoylcarnitine was identified to be specifically enriched in SDH group. The differentially abundant metabolites between ISH and controls were involved in tyrosine metabolism pathways, and in biosynthesis of phenylalanine for those between SDH and controls. Potential linkages between the gut microbial and serum metabolic signatures were detected within ISH, IDH and SDH groups. Furthermore, we found the association of discriminatory metabolites with the characteristics of patients.

Conclusion

Our findings demonstrate disparate blood metabolomics signatures across ISH, IDH and SDH, with differentially enriched metabolites and potential functional pathways identified, reveal the underlying microbiome and metabolome network in HTN subtypes, and provide potential targets for disease classification and therapeutic strategy in clinical practice.

To metabolomics and beyond: a technological portfolio to investigate cancer metabolism

Tumour cells have exquisite flexibility in reprogramming their metabolism in order to support tumour initiation, progression, metastasis and resistance to therapies. These reprogrammed activities include a complete rewiring of the bioenergetic, biosynthetic and redox status to sustain the increased energetic demand of the cells. Over the last decades, the cancer metabolism field has seen an explosion of new biochemical technologies giving more tools than ever before to navigate this complexity. Within a cell or a tissue, the metabolites constitute the direct signature of the molecular phenotype and thus their profiling has concrete clinical applications in oncology. Metabolomics and fluxomics, are key technological approaches that mainly revolutionized the field enabling researchers to have both a qualitative and mechanistic model of the biochemical activities in cancer. Furthermore, the upgrade from bulk to single-cell analysis technologies provided unprecedented opportunity to investigate cancer biology at cellular resolution allowing an in depth quantitative analysis of complex and heterogenous diseases. More recently, the advent of functional genomic screening allowed the identification of molecular pathways, cellular processes, biomarkers and novel therapeutic targets that in concert with other technologies allow patient stratification and identification of new treatment regimens. This review is intended to be a guide for researchers to cancer metabolism, highlighting current and emerging technologies, emphasizing advantages, disadvantages and applications with the potential of leading the development of innovative anti-cancer therapies.

Validation of a fast and sensitive UPLC-MS/MS quantitative method for N-acyl taurine analysis in biological samples

The recent discovery of N-acyl taurines (NATs) as a class of endogenous bioactive lipids and the perspective of their possible pharmacological applications stimulated the development of mass spectrometry-based methods for their quantitative measurements in biological tissues and fluids. We report here for the first time a procedure validated both in liver surrogate matrix and neat solvent (MeOH) based on UPLC-ESI-QqQ analysis for the identification and quantification of NATs in biological tissue extracts. The LC-MS method was based on five representative lipid analogues, including saturated, monounsaturated and polyunsaturated species, namely N-palmitoyl taurine (C16:0 NAT), N-oleoyl taurine (C18:1 NAT), N-arachidonoyl taurine (C20:4 NAT), N-docosanoyl taurine (C22:0 NAT) and N-nervonoyl taurine (C24:1 NAT), and evaluated for specificity, linearity, matrix effect, recovery, repeatability and intermediate precision and accuracy. The method validated in MeOH by internal standard approach (d₄-C20:4 NAT) showed excellent linearity in the range 1-300 ng/ml with R always ≥ 0.9996 for all NATs; intra-day and inter-day precision and accuracy were always within the acceptable range. Specificity was assessed on NAT standards in MeOH, applying the confirmation ratio of two diagnostic MRM ion transitions for product ions at m/z 80 and m/z 107 to true samples in the adopted BEH C18 UPLC conditions. Limit of detection (LOD) and limit of quantification (LOQ) were 0.3-0.4 and 1 ng/ml, respectively, for all compounds. The method was successfully applied to assess the levels of NATs in the mouse liver and, for the first time, in varying sections of the intestine (duodenum, jejunum, ileum and colon). NAT levels increased from duodenum to colon, evidencing a remarkable prevalence in the large intestine of C22:0 NAT, typically occurring mainly in the central nervous system. These findings prompt further studies to disclose the biological function of the various members of this class in different peripheral tissues.

Interaction of N-acyltaurines with phosphatidylcholines

N-acyltaurines (NATs) are biologically active amphiphilic lipids. They come under the group of compounds known as N-acyl amino acids. NATs were first detected in the brain and other tissues in mice lacking the enzyme fatty acid amide hydrolase FAAH (-/-). N-arachidonoyltaurine (20:4 NAT) acts as an excellent ligand for the subset of transient receptor potential (TRP) channels, especially vanilloid type channels TRPV1 and TRPV4. Also, hydrophobic and hydrophilic regions of NATs enable them to interact with membrane lipids. Here, we have investigated the interaction of NATs, N-myristoyltaurine (NMT), and N-palmitoyltaurine (NPT) with their corresponding diacyl phosphatidylcholines (PCs), dimyristoylphosphatidylcholine (DMPC), and dipalmitoylphosphatidylchoine (DPPC). The miscibility and phase behavior of the hydrated binary mixtures have been investigated by differential scanning calorimetry (DSC). Studies on the interaction of NMT/NPT with DMPC/DPPC revealed that the two amphiphiles mix well up to 50 mol% of NAT and phase separation is observed at higher contents of the NAT. The phase transition of the equimolar mixtures of NAT:PC (50:50) studied by fluorescence, also supported the DSC results. PXRD and FTIR analysis show that the NAT:PC equimolar mixture (50:50) forms different supramolecular structures when compared to that of individual NATs and PCs. From transmission electron microscopic studies it is observed that the equimolar mixtures of NMT and NPT with their corresponding diacylphosphatidylcholines (50:50, mol/mol) forms unilamellar vesicles whose diameter range between 30 and 50 nm.

Spatial metabolomics reveals skeletal myofiber subtypes

Skeletal muscle myofibers are heterogeneous in their metabolism. However, metabolomic profiling of single myofibers has remained difficult. Mass spectrometry imaging (MSI) is a powerful tool for imaging molecular distributions. In this work, we optimized the workflow of matrix-assisted laser desorption/ionization (MALDI)-based MSI from cryosectioning to metabolomics data analysis to perform high-spatial resolution metabolomic profiling of slow- and fast-twitch myofibers. Combining the advantages of MSI and liquid chromatography-MS (LC-MS), we produced spatial metabolomics results that were more reliable. After the combination of high-spatial resolution MSI and LC-MS metabolomic analysis, we also discovered a new subtype of superfast type 2B myofibers that were enriched for fatty acid oxidative metabolism. Our technological workflow could serve as an engine for metabolomics discoveries, and our approach has the potential to provide critical insights into the metabolic heterogeneity and pathways that underlie fundamental biological processes and disease states.

The relationship between islet β-cell function and metabolomics in overweight patients with Type 2 diabetes

A cross-sectional study was performed using metabolomics in overweight patients with Type 2 diabetes (T2D) at different stages of the disease. We aimed to identify potential metabolites for assessing islet β-cell function in order to investigate the correlation between islet β-cell dysfunction and metabolite changes in overweight patients with T2D. We selected 60 overweight adults (24 ≤ body mass index [BMI] < 28 kg/m2) with T2D who had been admitted to our hospital. The participants were equally divided into three groups according to disease duration: H1 (duration ≤ 5 years), H2 (5 years < duration ≤ 10 years), and H3 (duration > 10 years). Questionnaires, physical examinations, laboratory tests, and imaging studies were administered to all participants. The modified homeostasis model of assessment (HOMA) index was calculated using fasting C-peptide levels, and metabolite assays were performed using mass spectrometry. The results showed that HOMA-β and visceral fat area (VFA) were negatively correlated with diabetes duration. The VFA was positively correlated with arginine, cysteine, methionine, proline, and succinyl/methylmalonylcarnitine levels. The HOMA-β was negatively correlated with the serine and tetradecanoyldiacylcarnitine levels, and positively correlated with the aspartic acid, cysteine, homocysteine, piperamide, proline, and valine levels. The HOMA-IR was negatively correlated with hydroxypalmitoylcarnitine levels and positively correlated with the myristoylcarnitine levels. Thus, at different stages of T2D progression in overweight patients, serine, aspartic acid, cysteine, homocysteine, piperamide, proline, valine, and tetradecanoyldiacylcarnitine may be associated with HOMA-β and represent potential novel biomarkers for evaluating islet β-cell function.

Berberis microphylla G. Forst Intake Reduces the Cardiovascular Disease Plasmatic Markers Associated with a High-Fat Diet in a Mice Model

Polyphenols are bioactive substances that participate in the prevention of chronic illnesses. High content has been described in Berberis microphylla G. Forst (calafate), a wild berry extensively distributed in Chilean-Argentine Patagonia. We evaluated its beneficial effect through the study of mouse plasma metabolome changes after chronic consumption of this fruit. Characterized calafate extract was administered in water, for four months, to a group of mice fed with a high-fat diet and compared with a control diet. Metabolome changes were studied using UHPLC-DAD-QTOF-based untargeted metabolomics. The study was complemented by the analysis of protein biomarkers determined using Luminex technology, and quantification of OH radicals by electron paramagnetic resonance spectroscopy. Thirteen features were identified with a maximum annotation level-A, revealing an increase in succinic acid, activation of tricarboxylic acid and reduction of carnitine accumulation. Changes in plasma biomarkers were related to inflammation and cardiovascular disease, with changes in thrombomodulin (-24%), adiponectin (+68%), sE-selectin (-34%), sICAM-1 (-24%) and proMMP-9 (-31%) levels. The production of OH radicals in plasma was reduced after calafate intake (-17%), especially for the group fed with a high-fat diet. These changes could be associated with protection against atherosclerosis due to calafate consumption, which is discussed from a holistic and integrative point of view.

Emerging Computational Methods in Mass Spectrometry Imaging

Mass spectrometry imaging (MSI) is a powerful analytical technique that generates maps of hundreds of molecules in biological samples with high sensitivity and molecular specificity. Advanced MSI platforms with capability of high-spatial resolution and high-throughput acquisition generate vast amount of data, which necessitates the development of computational tools for MSI data analysis. In addition, computation-driven MSI experiments have recently emerged as enabling technologies for further improving the MSI capabilities with little or no hardware modification. This review provides a critical summary of computational methods and resources developed for MSI data analysis and interpretation along with computational approaches for improving throughput and molecular coverage in MSI experiments. This review is focused on the recently developed artificial intelligence methods and provides an outlook for a future paradigm shift in MSI with transformative computational methods.

The fatal trajectory of pulmonary COVID-19 is driven by lobular ischemia and fibrotic remodelling

BACKGROUND

COVID-19 is characterized by a heterogeneous clinical presentation, ranging from mild symptoms to severe courses of disease. 9-20% of hospitalized patients with severe lung disease die from COVID-19 and a substantial number of survivors develop long-COVID. Our objective was to provide comprehensive insights into the pathophysiology of severe COVID-19 and to identify liquid biomarkers for disease severity and therapy response.

METHODS

We studied a total of 85 lungs (n = 31 COVID autopsy samples; n = 7 influenza A autopsy samples; n = 18 interstitial lung disease explants; n = 24 healthy controls) using the highest resolution Synchrotron radiation-based hierarchical phase-contrast tomography, scanning electron microscopy of microvascular corrosion casts, immunohistochemistry, matrix-assisted laser desorption ionization mass spectrometry imaging, and analysis of mRNA expression and biological pathways. Plasma samples from all disease groups were used for liquid biomarker determination using ELISA. The anatomic/molecular data were analyzed as a function of patients' hospitalization time.

FINDINGS

The observed patchy/mosaic appearance of COVID-19 in conventional lung imaging resulted from microvascular occlusion and secondary lobular ischemia. The length of hospitalization was associated with increased intussusceptive angiogenesis. This was associated with enhanced angiogenic, and fibrotic gene expression demonstrated by molecular profiling and metabolomic analysis. Increased plasma fibrosis markers correlated with their pulmonary tissue transcript levels and predicted disease severity. Plasma analysis confirmed distinct fibrosis biomarkers (TSP2, GDF15, IGFBP7, Pro-C3) that predicted the fatal trajectory in COVID-19.

INTERPRETATION

Pulmonary severe COVID-19 is a consequence of secondary lobular microischemia and fibrotic remodelling, resulting in a distinctive form of fibrotic interstitial lung disease that contributes to long-COVID.

FUNDING

This project was made possible by a number of funders. The full list can be found within the Declaration of interests / Acknowledgements section at the end of the manuscript.

Nontargeted and Targeted Metabolomic Profiling Reveals Novel Metabolite Biomarkers of Incident Diabetes in African Americans

Nontargeted metabolomics methods have increased potential to identify new disease biomarkers, but assessments of the additive information provided in large human cohorts by these less biased techniques are limited. To diversify our knowledge of diabetes-associated metabolites, we leveraged a method that measures 305 targeted or "known" and 2,342 nontargeted or "unknown" compounds in fasting plasma samples from 2,750 participants (315 incident cases) in the Jackson Heart Study (JHS)-a community cohort of self-identified African Americans-who are underrepresented in omics studies. We found 307 unique compounds (82 known) associated with diabetes after adjusting for age and sex at a false discovery rate of <0.05 and 124 compounds (35 known, including 11 not previously associated) after further adjustments for BMI and fasting plasma glucose. Of these, 144 and 68 associations, respectively, replicated in a multiethnic cohort. Among these is an apparently novel isomer of the 1-deoxyceramide Cer(m18:1/24:0) with functional geonomics and high-resolution mass spectrometry. Overall, known and unknown metabolites provided complementary information (median correlation ρ = 0.29), and their inclusion with clinical risk factors improved diabetes prediction modeling. Our findings highlight the importance of including nontargeted metabolomics methods to provide new insights into diabetes development in ethnically diverse cohorts.

Bile acid conjugation deficiency causes hypercholanemia, hyperphagia, islet dysfunction, and gut dysbiosis in mice

Bile acid-CoA: amino acid N-acyltransferase (BAAT) catalyzes bile acid conjugation, the last step in bile acid synthesis. BAAT gene mutation in humans results in hypercholanemia, growth retardation, and fat-soluble vitamin insufficiency. The current study investigated the physiological function of BAAT in bile acid and lipid metabolism using Baat-/- mice. The bile acid composition and hepatic gene expression were analyzed in 10-week-old Baat-/- mice. They were also challenged with a westernized diet (WD) for additional 15 weeks to assess the role of BAAT in bile acid, lipid, and glucose metabolism. Comprehensive lab animal monitoring system and cecal 16S ribosomal RNA gene sequencing were used to evaluate the energy metabolism and microbiome structure of the mice, respectively. In Baat-/- mice, hepatic bile acids were mostly unconjugated and their levels were significantly increased compared with wild-type mice. Bile acid polyhydroxylation was markedly up-regulated to detoxify unconjugated bile acid accumulated in Baat-/- mice. Although the level of serum marker of bile acid synthesis, 7α-hydroxy-4-cholesten-3-one, was higher in Baat-/- mice, their bile acid pool size was smaller. When fed a WD, the Baat-/- mice showed a compromised body weight gain and impaired insulin secretion. The gut microbiome of Baat-/- mice showed a low level of sulfidogenic bacteria Bilophila. Conclusion: Mouse BAAT is the major taurine-conjugating enzyme. Its deletion protected the animals from diet-induced obesity, but caused glucose intolerance. The gut microbiome of the Baat-/- mice was altered to accommodate the unconjugated bile acid pool.

High-risk Growth Trajectory Related to Childhood Overweight/Obesity and Its Predictive Model at Birth

CONTEXT

Childhood obesity increases the risk of chronic disease in adulthood.

OBJECTIVE

To construct an early predictive model for a growth trajectory that is highly related to childhood overweight/obesity.

DESIGN

Prospective cohort study.

SETTINGS

Shanghai Birth Cohort (SBC) and US Collaborative Perinatal Project (CPP).

PARTICIPANTS

A total of 848 mother-child pairs in the SBC (2013-2016) and 22 691 pairs in the CPP (1959-1965) with 2- and 7-year follow-up, respectively.

MAIN OUTCOME MEASURES

A high-risk postnatal growth trajectory intimately associated with childhood overweight/obesity and its predictive model.

RESULTS

We demonstrated that the shifts of postnatal body mass index (BMI) percentile had been completed around 1 year of age and identified a high-risk growth trajectory that was closely related to overweight/obesity [odds ratio 6.5 (95% CI 5.9, 7.2)] at 7 years old. Children with this trajectory presented with a consistent BMI around the 85th percentile after the age of 1 year. It could be recognized early after birth using a predictive model with 4 metabolites (tyrosine, glycine, octenoylcarnitine, and stearoylcarnitine), combined with sex, birth weight, and maternal prepregnancy BMI. The model had an area under the receiver operating characteristic curve of 0.869 (95% CI 0.779, 0.932), a sensitivity of 83.3% (95% CI 51.6%, 97.9%), and a specificity of 81.1% (95% CI 70.3%, 89.3%) in the validation data set.

CONCLUSION

Children with postnatal high-risk growth trajectories were significantly associated with subsequent overweight/obesity at 7 years old. Metabolite profiles at birth combined with clinical measures were able to predict at-risk children before overweight/obesity occurrence.

N-acylethanolamide metabolizing enzymes are upregulated in human neural progenitor-derived neurons exposed to sub-lethal oxidative stress

N-acyl amides (NAAs) are a class of lipids that consist of an acyl group N-linked to an amino acid, neurotransmitter, taurine or ethanolamide group (N-acylethanolamines or NAEs) and include some endocannabinoids (eCB) such as anandamide. These lipids are synthesized in a wide variety of organisms and in multiple cell types, including neurons. NAEs are involved in numerous cellular and physiological processes and their concentrations are elevated in response to ischemia and physical trauma to play a role in neuroprotection. The neuroprotective properties of eCB NAEs make the protein targets of these compounds attractive targets for clinical intervention for a variety of conditions. The most promising of these targets include cannabinoid receptor type 1 (CB1), cannabinoid receptor type 2 (CB2), fatty acid amide hydrolase (FAAH), N-acylethanolamine acid amidase (NAAA), and N-acyl phosphatidylethanolamine phospholipase D (NAPE-PLD). Further characterization of these targets in a more contemporary model system of neurodegeneration and neuroprotection will allow us to fully describe their role and mechanism of action in neuroprotection against oxidative stress leading to better utilization in the clinical setting. Human stem cell-derived or human neural progenitor cell-derived cells, such as ReN cells, have become more utilized for the study of human neuronal development and neurodegenerative diseases. ReN cells can be easily differentiated thereby circumventing the need for using transformed cell lines and primary neurons as cell model systems. In this study, we determined whether ReN cells, a superior cell model system for studying neurodevelopment, differentiation, and neuroprotection, express proteins involved in canonical eCB NAE signaling and whether oxidative stress can induce their expression. We determined that sublethal oxidative stress upregulates the expression of all eCB proteins tested. In addition, we determined that oxidative stress increases the nuclear localization of FAAH, and to a lesser extent, NAAA and NAPE-PLD. This study is a first step toward determining how oxidative stress affects CB1, CB2, FAAH, NAAA, and NAPE-PLD expression and their potential defense against oxidative stress. As such, our data is important for further determining the role of eCB metabolizing proteins and eCB receptors against oxidative stress.

Spatially resolved multi-omics deciphers bidirectional tumor-host interdependence in glioblastoma

Glioblastomas are malignant tumors of the central nervous system hallmarked by subclonal diversity and dynamic adaptation amid developmental hierarchies. The source of dynamic reorganization within the spatial context of these tumors remains elusive. Here, we characterized glioblastomas by spatially resolved transcriptomics, metabolomics, and proteomics. By deciphering regionally shared transcriptional programs across patients, we infer that glioblastoma is organized by spatial segregation of lineage states and adapts to inflammatory and/or metabolic stimuli, reminiscent of the reactive transformation in mature astrocytes. Integration of metabolic imaging and imaging mass cytometry uncovered locoregional tumor-host interdependence, resulting in spatially exclusive adaptive transcriptional programs. Inferring copy-number alterations emphasizes a spatially cohesive organization of subclones associated with reactive transcriptional programs, confirming that environmental stress gives rise to selection pressure. A model of glioblastoma stem cells implanted into human and rodent neocortical tissue mimicking various environments confirmed that transcriptional states originate from dynamic adaptation to various environments.

Integrative Pathway Analysis of SNP and Metabolite Data Using a Hierarchical Structural Component Model

Integrative multi-omics analysis has become a useful tool to understand molecular mechanisms and drug discovery for treatment. Especially, the couplings of genetics to metabolomics have been performed to identify the associations between SNP and metabolite. However, while the importance of integrative pathway analysis is increasing, there are few approaches to utilize pathway information to analyze phenotypes using SNP and metabolite. We propose an integrative pathway analysis of SNP and metabolite data using a hierarchical structural component model considering the structural relationships of SNPs, metabolites, pathways, and phenotypes. The proposed method utilizes genome-wide association studies on metabolites and constructs the genetic risk scores for metabolites referred to as genetic metabolomic scores. It is based on the hierarchical model using the genetic metabolomic scores and pathways. Furthermore, this method adopts a ridge penalty to consider the correlations between genetic metabolomic scores and between pathways. We apply our method to the SNP and metabolite data from the Korean population to identify pathways associated with type 2 diabetes (T2D). Through this application, we identified well-known pathways associated with T2D, demonstrating that this method adds biological insights into disease-related pathways using genetic predispositions of metabolites.

Elucidating the metabolic characteristics of pancreatic β-cells from patients with type 2 diabetes (T2D) using a genome-scale metabolic modeling

Diabetes is a global health problem caused primarily by the inability of pancreatic β-cells to secrete adequate insulin. Despite extensive research, the identity of factors contributing to the dysregulated metabolism-secretion coupling in the β-cells remains elusive. The present study attempts to capture some of these factors responsible for the impaired β-cell metabolism-secretion coupling that contributes to diabetes pathogenesis. The metabolic-flux profiles of pancreatic β-cells were predicted using genome-scale metabolic modeling for ten diabetic patients and ten control subjects. Analysis of these flux states shows reduction in the mitochondrial fatty acid oxidation and mitochondrial oxidative phosphorylation pathways, that leads to decreased insulin secretion in diabetes. We also observed elevated reactive oxygen species (ROS) generation through peroxisomal fatty acid β-oxidation. In addition, cellular antioxidant defense systems were found to be attenuated in diabetes. Our analysis also uncovered the possible changes in the plasma metabolites in diabetes due to the β-cells failure. These efforts subsequently led to the identification of seven metabolites associated with cardiovascular disease (CVD) pathogenesis, thus establishing its link as a secondary complication of diabetes.

Morus alba L. water extract changes gut microbiota and fecal metabolome in mice induced by high-fat and high-sucrose diet plus low-dose streptozotocin

Gut microbiota plays a key role in the pathophysiology of type 2 diabetes mellitus (T2D). Mulberry leaf has a hypoglycemic effect, but the potential mechanism is not fully understood. This study aimed to explore the influences and potential mechanisms of mulberry leaf water extract (MLWE) intervention on mice with T2D induced through a high-fat and high-sucrose diet combined with streptozotocin by the combination of fecal metabolomics and gut microbiota analysis. Results showed that MLWE could decrease fasting blood glucose and body weight while ameliorating lipid profiles, insulin resistance, liver inflammation, and the accumulation of lipid droplets in T2D mice. MLWE could reverse the abundances of the phyla Actinobacteria and Bacteroidetes and the ratio of Firmicutes/Bacteroidetes, and increase the abundances of the phyla Cyanobacteria and Epsilonbacteraeota in the feces of T2D mice. The abundances of genera Alloprevotella, Parabacteroides, Muribaculaceae, and Romboutsia in the feces of T2D mice could be reversed, while Oscillatoriales_cyanobacterium and Gastranaerophilales could be reinforced by MLWE supplementation. The levels of nine metabolites in the feces of T2D mice were improved, among which glycine, Phe-Pro, urocanic acid, phylloquinone, and lactate were correlated with Romboutsia and Gastranaerophilales. Taken together, we conclude that MLWE can effectively alleviate T2D by mediating the host-microbial metabolic axis.

Atlas of exercise metabolism reveals time-dependent signatures of metabolic homeostasis

Tissue sensitivity and response to exercise vary according to the time of day and alignment of circadian clocks, but the optimal exercise time to elicit a desired metabolic outcome is not fully defined. To understand how tissues independently and collectively respond to timed exercise, we applied a systems biology approach. We mapped and compared global metabolite responses of seven different mouse tissues and serum after an acute exercise bout performed at different times of the day. Comparative analyses of intra- and inter-tissue metabolite dynamics, including temporal profiling and blood sampling across liver and hindlimb muscles, uncovered an unbiased view of local and systemic metabolic responses to exercise unique to time of day. This comprehensive atlas of exercise metabolism provides clarity and physiological context regarding the production and distribution of canonical and novel time-dependent exerkine metabolites, such as 2-hydroxybutyrate (2-HB), and reveals insight into the health-promoting benefits of exercise on metabolism.

Acylcarnitines: Can They Be Biomarkers of Diabetic Nephropathy?

Diabetic nephropathy (DN), one of the most serious microvascular complications of diabetes mellitus (DM), may progress to end-stage renal disease (ESRD). Current biochemical biomarkers, such as urinary albumin excretion rate (UAER), have limitations for early screening and monitoring of DN. Recent studies have identified some metabolites as candidate biomarkers for early detection of DN. In this review, we summarize the role of dysregulated acylcarnitines (AcylCNs) in DN pathophysiology. Lower abundance of short- and medium-chain AcylCNs and higher long-chain AcylCNs often occurred in DM with normal albuminuria and microalbuminuria, compared with advanced stages of DN. The increase of long-chain AcylCNs was supposed to be an adaptive compensation in fat acids (FAs) oxidation in the early stage of DN. Conversely, the decrease of long-chain AcylCNs was due to incomplete oxidation of FAs in advanced stage of DN. Thus, AcylCNs may serve as sensitive biomarkers in predicting the risk of DN.

Identification of Sex-Specific Plasma Biomarkers Using Metabolomics for Major Depressive Disorder in Children and Adolescents

BACKGROUND

Children and adolescents are at a high risk of major depressive disorder (MDD) with known sex differences in epidemiology. However, there are currently no objective laboratory-based sex-specific biomarkers available to support the diagnoses of male and female patients with MDD.

METHODS

Here, a male set of 42 cases and 27 healthy controls (HCs) and a female set of 42 cases and 22 HCs were recruited. This study investigated the sex differences of plasma metabolite biomarkers in young patients with MDD by the application of ultra-high-performance liquid chromatography equipped with quadrupole time-of-flight mass spectrometry.

RESULTS

The metabolic profiles showed clear separations in both male and female sets. In total, this study identified 57 male-related and 53 female-related differential metabolites. Compared with HCs, both male and female subjects with MDD displayed four significantly altered pathways. Notably, biliverdin was selected as an independent diagnostic male-specific biomarker with an area under the receiver operating characteristic curve of 0.966, and phosphatidylcholine (10:0/14:1) was selected as a female-specific biomarker, achieving an area under the curve (AUC) of 0.957.

CONCLUSION

This metabolomics study may aid in the development of a plasma-based test for the diagnosis of male and female children and adolescents with MDD, as well as give new insight into the pathophysiology of sex differences in children and adolescents with MDD.

Plasma Acylcarnitines during Pregnancy and Neonatal Anthropometry: A Longitudinal Study in a Multiracial Cohort

As surrogate readouts reflecting mitochondrial dysfunction, elevated levels of plasma acylcarnitines have been associated with cardiometabolic disorders, such as obesity, gestational diabetes, and type 2 diabetes. This study aimed to examine prospective associations of acylcarnitine profiles across gestation with neonatal anthropometry, including birthweight, birthweight z score, body length, sum of skinfolds, and sum of body circumferences. We quantified 28 acylcarnitines using electrospray ionization tandem mass spectrometry in plasma collected at gestational weeks 10–14, 15–26, 23–31, and 33–39 among 321 pregnant women from the National Institute of Child Health and Human Development (NICHD) Fetal Growth Studies-Singletons. A latent-class trajectory approach was applied to identify trajectories of acylcarnitines across gestation. We examined the associations of individual acylcarnitines and distinct trajectory groups with neonatal anthropometry using weighted generalized linear models adjusting for maternal age, race/ethnicity, education, parity, gestational age at blood collection, and pre-pregnancy body mass index (BMI). We identified three distinct trajectory groups in C2, C3, and C4 and two trajectory groups in C5, C10, C5–DC, C8:1, C10:1, and C12, respectively. Women with nonlinear decreasing C12 levels across gestation (5.7%) had offspring with significantly lower birthweight (−475 g; 95% CI, −942, −6.79), birthweight z score (−0.39, −0.71, −0.06), and birth length (−1.38 cm, −2.49, −0.27) than those with persistently stable C12 levels (94.3%) (all nominal p value < 0.05). Women with consistently higher levels of C10 (6.1%) had offspring with thicker sum of skinfolds (4.91 mm, 0.85, 8.98) than did women with lower levels (93.9%) during pregnancy, whereas women with lower C10:1 levels (12.6%) had offspring with thicker sum of skinfolds (3.23 mm, 0.19, 6.27) than did women with abruptly increasing levels (87.4%) (p < 0.05). In conclusion, this study suggests that distinctive trajectories of C10, C10:1, and C12 acylcarnitine levels throughout pregnancy were significantly associated with neonatal anthropometry.

Patterns of carbon-bound exogenous compounds in lung cancer patients and association with disease pathophysiology

Asymptomatic anthracosis is the accumulation of black carbon particles in adult human lungs. It is a common occurrence, but the pathophysiological significance of anthracosis is debatable. Using in situ high mass resolution matrix-assisted laser desorption/ionization (MALDI) fourier-transform ion cyclotron resonance (FT-ICR) mass spectrometry imaging analysis, we discovered noxious carbon-bound exogenous compounds, such as polycyclic aromatic hydrocarbons (PAHs), tobacco-specific nitrosamines, or aromatic amines, in a series of 330 lung cancer patients in highly variable and unique patterns. The characteristic nature of carbon-bound exogenous compound had a strong association with patient outcome, tumor progression, the tumor immune microenvironment, PD-L1 expression, and DNA damage. Spatial correlation network analyses revealed substantial differences in the metabolome of tumor cells compared to tumor stroma depending on carbon-bound exogenous compounds. Overall, the bioactive pool of exogenous compounds is associated with several changes in lung cancer pathophysiology and correlates with patient outcome. Given the high prevalence of anthracosis in the lungs of adult humans, future work should investigate the role of carbon-bound exogenous compounds in lung carcinogenesis and lung cancer therapy.

Diet-induced alteration of intestinal stem cell function underlies obesity and prediabetes in mice

Excess nutrient uptake and altered hormone secretion in the gut contribute to a systemic energy imbalance, which causes obesity and an increased risk of type 2 diabetes and colorectal cancer. This functional maladaptation is thought to emerge at the level of the intestinal stem cells (ISCs). However, it is not clear how an obesogenic diet affects ISC identity and fate. Here we show that an obesogenic diet induces ISC and progenitor hyperproliferation, enhances ISC differentiation and cell turnover and changes the regional identities of ISCs and enterocytes in mice. Single-cell resolution of the enteroendocrine lineage reveals an increase in progenitors and peptidergic enteroendocrine cell types and a decrease in serotonergic enteroendocrine cell types. Mechanistically, we link increased fatty acid synthesis, Ppar signaling and the Insr-Igf1r-Akt pathway to mucosal changes. This study describes molecular mechanisms of diet-induced intestinal maladaptation that promote obesity and therefore underlie the pathogenesis of the metabolic syndrome and associated complications.

Metabolic profiling in early pregnancy and associated factors of folate supplementation: A cross-sectional study

BACKGROUND

Pregnancy generally alters the balance of maternal metabolism, but the molecular profiles in early pregnancy and associated factors of folate supplementation in pregnant women remains incompletely understood.

METHODS

Untargeted metabonomics based on high-performance liquid chromatography-high-resolution mass spectrometry integrated with multivariate metabolic pathway analysis were applied to characterize metabolite profiles and associated factors of folate supplements in early pregnancy. The metabolic baseline of early pregnancy was determined by metabolic analysis of 510 serum samples from 131 non-pregnant and 379 pregnant healthy Chinese women. The pathophysiology of adaptive reactions and metabolic challenges induced by folate supplementation in early pregnancy was further compared between pregnant women with (n = 168) and without (n = 184) folate supplements.

RESULTS

Compared with non-pregnant participants, 106 metabolites, majority of which are related to amino acids and lysophosphatidylcholine/phosphatidylcholine, and 13 metabolic pathways were significantly changed in early pregnancy. The supplementation of folate in early pregnancy induced marked changes in N-acyl ethanolamine 22:0, N-acyl taurine 18:2, glycerophosphoserine 44:1 and 8,11,14-eicosatrienoate, proline, and aminoimidazole ribotide levels.

CONCLUSIONS

During early pregnancy, the metabolism of amino acids significantly changes to meet the physiological requirements of pregnant women. Folate intake may change glucose and lipid metabolism. These findings provide a comprehensive landscape for understanding the basic characteristics and gestational metabolic networks of early pregnancy and folate supplementation. This study provides a basis for further research into the relationship between metabolic markers and pregnancy diseases.

TRIAL REGISTRATION

This study protocol was registered on www.ClinicalTrials.gov, NCT03651934, on August 29, 2018 (prior to recruitment).

Strategy for Nontargeted Metabolomic Annotation and Quantitation Using a High-Resolution Spectral-Stitching Nanoelectrospray Direct-Infusion Mass Spectrometry with Data-Independent Acquisition

Direct-infusion nanoelectrospray ionization high-resolution mass spectrometry (DI-nESI-HRMS) is an alternative approach to chromatography-MS-based techniques for nontargeted metabolomics, offering a high sample throughout. However, its annotation accuracy of analytes is still full of challenges. In this study, we proposed a strategy for the annotation and quantitation of nontargeted metabolomic data using a spectral-stitching DI-nESI-HRMS with data-independent acquisition. The metabolite annotation strategy included the isotopic distribution, MS/MS spectrum similarity, and precursor and product ion correlation as well as matching of the extracted metabolite features along with the targeted metabolite precursors. Two groups of mixed standard solutions containing 40 and 79 metabolites were, respectively, used to establish the metabolite annotation strategy and validate its reliability. The results showed that the detected standards could be well annotated at top three explanations and total qualitative percentages were 100% (40 of 40) for the standard solution and 94.9% (74 of 78) for the standards spiked into the serum matrix. The intensity of the precursor ions was used for quantitation except for isomers, which were quantified by the intensities of the characteristic product ions if available. Finally, the strategy was applied to study serum metabolomics in diabetes, and the results demonstrated that it is promising for a large-scale cohort metabolomic study.

Function and therapeutic potential of N-acyl amino acids

N-acyl amino acids (NAAs) are amphiphilic molecules, with different potential fatty acid and head group moieties. NAAs are the largest family of anandamide congener lipids discovered to date. In recent years, several NAAs have been identified as potential ligands, engaging novel binding sites and mechanisms for modulation of membrane proteins such as G-protein coupled receptors (GPRs), nuclear receptors, ion channels, and transporters. NAAs play a key role in a variety of physiological functions as lipid signaling molecules. Understanding the structure, function roles, and pharmacological potential of these NAAs is still in its infancy, and the biochemical roles are also mostly unknown. This review will provide a summary of the literature on NAAs and emphasize their therapeutic potential.

Postpartum circulating microRNA enhances prediction of future type 2 diabetes in women with previous gestational diabetes

AIMS/HYPOTHESIS

Type 2 diabetes mellitus is a major cause of morbidity and death worldwide. Women with gestational diabetes mellitus (GDM) have greater than a sevenfold higher risk of developing type 2 diabetes in later life. Accurate methods for postpartum type 2 diabetes risk stratification are lacking. Circulating microRNAs (miRNAs) are well recognised as biomarkers/mediators of metabolic disease. We aimed to determine whether postpartum circulating miRNAs can predict the development of type 2 diabetes in women with previous GDM.

METHODS

In an observational study, plasma samples were collected at 12 weeks postpartum from 103 women following GDM pregnancy. Utilising a discovery approach, we measured 754 miRNAs in plasma from type 2 diabetes non-progressors (n = 11) and type 2 diabetes progressors (n = 10) using TaqMan-based real-time PCR on an OpenArray platform. Machine learning algorithms involving penalised logistic regression followed by bootstrapping were implemented.

RESULTS

Fifteen miRNAs were selected based on their importance in discriminating type 2 diabetes progressors from non-progressors in our discovery cohort. The levels of miRNA miR-369-3p remained significantly different (p < 0.05) between progressors and non-progressors in the validation sample set (n = 82; 71 non-progressors, 11 progressors) after adjusting for age and correcting for multiple comparisons. In a clinical model of prediction of type 2 diabetes that included six traditional risk factors (age, BMI, pregnancy fasting glucose, postpartum fasting glucose, cholesterol and triacylglycerols), the addition of the circulating miR-369-3p measured at 12 weeks postpartum improved the prediction of future type 2 diabetes from traditional AUC 0.83 (95% CI 0.68, 0.97) to an AUC 0.92 (95% CI 0.84, 1.00).

CONCLUSIONS

This is the first demonstration of miRNA-based type 2 diabetes prediction in women with previous GDM. Improved prediction will facilitate early lifestyle/drug intervention for type 2 diabetes prevention.

Long-Chain Acylcarnitines Decrease the Phosphorylation of the Insulin Receptor at Tyr1151 Through a PTP1B-Dependent Mechanism

The accumulation of lipid intermediates may interfere with energy metabolism pathways and regulate cellular energy supplies. As increased levels of long-chain acylcarnitines have been linked to insulin resistance, we investigated the effects of long-chain acylcarnitines on key components of the insulin signalling pathway. We discovered that palmitoylcarnitine induces dephosphorylation of the insulin receptor (InsR) through increased activity of protein tyrosine phosphatase 1B (PTP1B). Palmitoylcarnitine suppresses protein kinase B (Akt) phosphorylation at Ser473, and this effect is not alleviated by the inhibition of PTP1B by the insulin sensitizer bis-(maltolato)-oxovanadium (IV). This result indicates that palmitoylcarnitine affects Akt activity independently of the InsR phosphorylation level. Inhibition of protein kinase C and protein phosphatase 2A does not affect the palmitoylcarnitine-mediated inhibition of Akt Ser473 phosphorylation. Additionally, palmitoylcarnitine markedly stimulates insulin release by suppressing Akt Ser473 phosphorylation in insulin-secreting RIN5F cells. In conclusion, long-chain acylcarnitines activate PTP1B and decrease InsR Tyr1151 phosphorylation and Akt Ser473 phosphorylation, thus limiting the cellular response to insulin stimulation.

Perilipin 2 downregulation in β cells impairs insulin secretion under nutritional stress and damages mitochondria

Perilipin 2 (PLIN2) is a lipid droplet (LD) protein in β cells that increases under nutritional stress. Downregulation of PLIN2 is often sufficient to reduce LD accumulation. To determine whether PLIN2 positively or negatively affects β cell function under nutritional stress, PLIN2 was downregulated in mouse β cells, INS1 cells, and human islet cells. β Cell–specific deletion of PLIN2 in mice on a high-fat diet reduced glucose-stimulated insulin secretion (GSIS) in vivo and in vitro. Downregulation of PLIN2 in INS1 cells blunted GSIS after 24-hour incubation with 0.2 mM palmitic acid. Downregulation of PLIN2 in human pseudoislets cultured at 5.6 mM glucose impaired both phases of GSIS, indicating that PLIN2 is critical for GSIS. Downregulation of PLIN2 decreased specific OXPHOS proteins in all 3 models and reduced oxygen consumption rates in INS1 cells and mouse islets. Moreover, we found that PLIN2-deficient INS1 cells increased the distribution of a fluorescent oleic acid analog to mitochondria and showed signs of mitochondrial stress, as indicated by susceptibility to fragmentation and alterations of acyl-carnitines and glucose metabolites. Collectively, PLIN2 in β cells has an important role in preserving insulin secretion, β cell metabolism, and mitochondrial function under nutritional stress.

Retinol-Binding Protein 4 Activates STRA6, Provoking Pancreatic β-Cell Dysfunction in Type 2 Diabetes

Pancreatic β-cell dysfunction plays a decisive role in the progression of type 2 diabetes. Retinol-binding protein 4 (RBP4) is a prominent adipokine in type 2 diabetes, although its effect on β-cell function remains elusive, and the underlying mechanisms are unknown. Here, we found that elevated circulating RBP4 levels were inversely correlated with pancreatic β-cell function in db/db mice across different glycemic stages. RBP4 directly suppressed glucose-stimulated insulin secretion (GSIS) in primary isolated islets and INS-1E cells in a dose- and time-dependent manner. RBP4 transgenic (RBP4-Tg) overexpressing mice showed a dynamic decrease of GSIS, which appeared as early as 8 weeks old, preceding the impairment of insulin sensitivity and glucose tolerance. Islets isolated from RBP4-Tg mice showed a significant decrease of GSIS. Mechanistically, we demonstrated that the stimulated by retinoic acid 6 (STRA6), RBP4's only known specific membrane receptor, is expressed in β-cells and mediates the inhibitory effect of RBP4 on insulin synthesis through the Janus kinase 2/STAT1/ISL-1 pathway. Moreover, decreasing circulating RBP4 level could effectively restore β-cell dysfunction and ameliorate hyperglycemia in db/db mice. These observations revealed a role of RBP4 in pancreatic β-cell dysfunction, which provides new insight into the diabetogenic effect of RBP4.