Metabolomic Analysis of Serum and Tear Samples from Patients with Obesity and Type 2 Diabetes Mellitus

A sensitive, expandable AQC-based LC-MS/MS method to measure amino metabolites and sphingolipids in cell and serum samples

Sphingolipids are a major lipid species found in all eukaryotes. Among structurally complex and diversified lipids, sphingoid bases have been heavily linked to various metabolic diseases. However, most current LC-MS-based methods lack the sensitivity to detect low-abundant sphingoid bases. The 6-Aminoquinolyl-N-hydroxysuccinimidyl carbamate (AQC) derivatization reagent, which efficiently forms covalent bonds with amino groups, has been widely used for amino acid detection. Nevertheless, the commonly used reverse-phase HPLC method for amino acid analysis is not suitable for amphipathic sphingolipids. To address this issue, we report a robust reverse-phase HPLC-MS/MS method capable of separating and detecting hydrophilic amino acids and sphingoid bases in a single run with high sensitivity. This method is also inclusive of other amino metabolites with an expandable target list. We tested this method under various conditions and samples, demonstrating its high reproducibility and sensitivity. Using this approach, we systematically analyzed human serum samples from healthy individuals, dyslipidemia, and type II diabetes mellitus (T2DM) patients, respectively. Two sphingolipids and five amino acids were identified with significant differences between the control and T2DM groups, highlighting the potential of this method in clinical studies.

The Molecular Mechanisms of Cuproptosis and Small-Molecule Drug Design in Diabetes Mellitus

In the field of human health research, the homeostasis of copper (Cu) is receiving increased attention due to its connection to pathological conditions, including diabetes mellitus (DM). Recent studies have demonstrated that proteins associated with Cu homeostasis, such as ATOX1, FDX1, ATP7A, ATPB, SLC31A1, p53, and UPS, also contribute to DM. Cuproptosis, characterized by Cu homeostasis dysregulation and Cu overload, has been found to cause the oligomerization of lipoylated proteins in mitochondria, loss of iron-sulfur protein, depletion of glutathione, production of reactive oxygen species, and cell death. Further research into how cuproptosis affects DM is essential to uncover its mechanism of action and identify effective interventions. In this article, we review the molecular mechanism of Cu homeostasis and the role of cuproptosis in the pathogenesis of DM. The study of small-molecule drugs that affect these proteins offers the possibility of moving from symptomatic treatment to treating the underlying causes of DM.

Identifying potential breath biomarkers for early diagnosis of papillary thyroid cancer based on solid-phase microextraction gas chromatography-high resolution mass spectrometry with metabolomics

INTRODUCTION

Thyroid cancer incidence rate has increased substantially worldwide in recent years. Fine needle aspiration biopsy (FNAB) is currently the golden standard of thyroid cancer diagnosis, which however, is invasive and costly. In contrast, breath analysis is a non-invasive, safe and simple sampling method combined with a promising metabolomics approach, which is suitable for early cancer diagnosis in high volume population.

OBJECTIVES

This study aims to achieve a more comprehensive and definitive exhaled breath metabolism profile in papillary thyroid cancer patients (PTCs).

METHODS

We studied both end-tidal and mixed expiratory breath, solid-phase microextraction gas chromatography coupled with high resolution mass spectrometry (SPME-GC-HRMS) was used to analyze the breath samples. Multivariate combined univariate analysis was applied to identify potential breath biomarkers.

RESULTS

The biomarkers identified in end-tidal and mixed expiratory breath mainly included alkanes, olefins, enols, enones, esters, aromatic compounds, and fluorine and chlorine containing organic compounds. The area under the curve (AUC) values of combined biomarkers were 0.974 (sensitivity: 96.1%, specificity: 90.2%) and 0.909 (sensitivity: 98.0%, specificity: 74.5%), respectively, for the end-tidal and mixed expiratory breath, indicating of reliability of the sampling and analysis method CONCLUSION: This work not only successfully established a standard metabolomic approach for early diagnosis of PTC, but also revealed the necessity of using both the two breath types for comprehensive analysis of the biomarkers.

Examination of the Complex Molecular Landscape in Obesity and Type 2 Diabetes

The escalating prevalence of metabolic disorders, notably type 2 diabetes (T2D) and obesity, presents a critical global health challenge, necessitating deeper insights into their molecular underpinnings. Our study integrates proteomics and metabolomics analyses to delineate the complex molecular landscapes associated with T2D and obesity. Leveraging data from 130 subjects, including individuals with T2D and obesity as well as healthy controls, we elucidate distinct molecular signatures and identify novel biomarkers indicative of disease progression. Our comprehensive characterization of cardiometabolic proteins and serum metabolites unveils intricate networks of biomolecular interactions and highlights differential protein expression patterns between T2D and obesity cohorts. Pathway enrichment analyses reveal unique mechanisms underlying disease development and progression, while correlation analyses elucidate the interplay between proteomics, metabolomics, and clinical parameters. Furthermore, network analyses underscore the interconnectedness of cardiometabolic proteins and provide insights into their roles in disease pathogenesis. Our findings may help to refine diagnostic strategies and inform the development of personalized interventions, heralding a new era in precision medicine and healthcare innovation. Through the integration of multi-omics approaches and advanced analytics, our study offers a crucial framework for deciphering the intricate molecular underpinnings of metabolic disorders and paving the way for transformative therapeutic strategies.

Research progress on ocular complications caused by type 2 diabetes mellitus and the function of tears and blepharons

The purpose of this study was to explore the related research progress of ocular complications (OCs) caused by type 2 diabetes mellitus (T2DM), tear and tarsal function, and the application of deep learning (DL) in the diagnosis of diabetes and OCs caused by it, to provide reference for the prevention and control of OCs in T2DM patients. This study reviewed the pathogenesis and treatment of diabetes retinopathy, keratopathy, dry eye disease, glaucoma, and cataract, analyzed the relationship between OCs and tear function and tarsal function, and discussed the application value of DL in the diagnosis of diabetes and OCs. Diabetes retinopathy is related to hyperglycemia, angiogenic factors, oxidative stress, hypertension, hyperlipidemia, and other factors. The increase in water content in the corneal stroma leads to corneal relaxation, loss of transparency, and elasticity, and can lead to the occurrence of corneal lesions. Dry eye syndrome is related to abnormal stability of the tear film and imbalance in neural and immune regulation. Elevated intraocular pressure, inflammatory reactions, atrophy of the optic nerve head, and damage to optic nerve fibers are the causes of glaucoma. Cataract is a common eye disease in the elderly, which is a visual disorder caused by lens opacity. Oxidative stress is an important factor in the occurrence of cataracts. In clinical practice, blood sugar control, laser therapy, and drug therapy are used to control the above eye complications. The function of tear and tarsal plate will be affected by eye diseases. Retinopathy and dry eye disease caused by diabetes will cause dysfunction of tear and tarsal plate, which will affect the eye function of patients. Furthermore, DL can automatically diagnose and classify eye diseases, automatically analyze fundus images, and accurately diagnose diabetes retinopathy, macular degeneration, and other diseases by analyzing and processing eye images and data. The treatment of T2DM is difficult and prone to OCs, which seriously threatens the normal life of patients. The occurrence of OCs is closely related to abnormal tear and tarsal function. Based on DL, clinical diagnosis and treatment of diabetes and its OCs can be carried out, which has positive application value.

Critical Factors in Sample Collection and Preparation for Clinical Metabolomics of Underexplored Biological Specimens

This review article compiles critical pre-analytical factors for sample collection and extraction of eight uncommon or underexplored biological specimens (human breast milk, ocular fluids, sebum, seminal plasma, sweat, hair, saliva, and cerebrospinal fluid) under the perspective of clinical metabolomics. These samples are interesting for metabolomics studies as they reflect the status of living organisms and can be applied for diagnostic purposes and biomarker discovery. Pre-collection and collection procedures are critical, requiring protocols to be standardized to avoid contamination and bias. Such procedures must consider cleaning the collection area, sample stimulation, diet, and food and drug intake, among other factors that impact the lack of homogeneity of the sample group. Precipitation of proteins and removal of salts and cell debris are the most used sample preparation procedures. This review intends to provide a global view of the practical aspects that most impact results, serving as a starting point for the designing of metabolomic experiments.

Complementary Approaches to Retinal Health Focusing on Diabetic Retinopathy

Diabetes mellitus affects carbohydrate homeostasis but also influences fat and protein metabolism. Due to ophthalmic complications, it is a leading cause of blindness worldwide. The molecular pathology reveals that nuclear factor kappa B (NFκB) has a central role in the progression of diabetic retinopathy, sharing this signaling pathway with another major retinal disorder, glaucoma. Therefore, new therapeutic approaches can be elaborated to decelerate the ever-emerging "epidemics" of diabetic retinopathy and glaucoma targeting this critical node. In our review, we emphasize the role of an improvement of lifestyle in its prevention as well as the use of phytomedicals associated with evidence-based protocols. A balanced personalized therapy requires an integrative approach to be more successful for prevention and early treatment.

Utilising the precision nutrition toolkit in the path towards precision medicine

The overall aim of precision nutrition is to replace the 'one size fits all' approach to dietary advice with recommendations that are more specific to the individual in order to improve the prevention or management of chronic disease. Interest in precision nutrition has grown with advancements in technologies such as genomics, proteomics, metabolomics and measurement of the gut microbiome. Precision nutrition initiatives have three major applications in precision medicine. First, they aim to provide more 'precision' dietary assessments through artificial intelligence, wearable devices or by employing omic technologies to characterise diet more precisely. Secondly, precision nutrition allows us to understand the underlying mechanisms of how diet influences disease risk and identify individuals who are more susceptible to disease due to gene-diet or microbiota-diet interactions. Third, precision nutrition can be used for 'personalised nutrition' advice where machine-learning algorithms can integrate data from omic profiles with other personal and clinical measures to improve disease risk. Proteomics and metabolomics especially provide the ability to discover new biomarkers of food or nutrient intake, proteomic or metabolomic signatures of diet and disease, and discover potential mechanisms of diet-disease interactions. Although there are several challenges that must be overcome to improve the reproducibility, cost-effectiveness and efficacy of these approaches, precision nutrition methodologies have great potential for nutrition research and clinical application.

Comparative Analysis of Amino Acid and Biogenic Amine Compositions of Fermented Grape Beverages

Amino acids and biogenic amines are important components of food and beverages. In grape-derived products such as wine and wine vinegar, they can have different origins and can influence the odor and taste of the products. Their concentration is influenced by the grape variety, vintage, and winemaking process. In our study, we carried out an LC-MS-based comparative analysis of 22 grape-derived beverages, including three different wine types and four wine vinegar samples from the Tokaj region in Hungary. The concentrations of 23 amino acids and 10 biogenic amines were examined, and the differences among the sample types were analyzed. The differences in the concentrations of some metabolites between Aszú-Furmint pairs originating from the same wineries and year provide information on the effect of botrytized grape on wine composition. Our data can provide further evidence on how the production process shapes the metabolite content of beverages and highlight the nutritional value of wine vinegar.

Human abdominal subcutaneous-derived active beige adipocytes carrying FTO rs1421085 obesity-risk alleles exert lower thermogenic capacity

Introduction: White adipocytes store lipids, have a large lipid droplet and few mitochondria. Brown and beige adipocytes, which produce heat, are characterized by high expression of uncoupling protein (UCP) 1, multilocular lipid droplets, and large amounts of mitochondria. The rs1421085 T-to-C single-nucleotide polymorphism (SNP) of the human FTO gene interrupts a conserved motif for ARID5B repressor, resulting in adipocyte type shift from beige to white. Methods: We obtained abdominal subcutaneous adipose tissue from donors carrying FTO rs1421085 TT (risk-free) or CC (obesity-risk) genotypes, isolated and differentiated their preadipocytes into beige adipocytes (driven by the PPARγ agonist rosiglitazone for 14 days), and activated them with dibutyryl-cAMP for 4 hours. Then, either the same culture conditions were applied for additional 14 days (active beige adipocytes) or it was replaced by a white differentiation medium (inactive beige adipocytes). White adipocytes were differentiated by their medium for 28 days. Results and Discussion: RNA-sequencing was performed to investigate the gene expression pattern of adipocytes carrying different FTO alleles and found that active beige adipocytes had higher brown adipocyte content and browning capacity compared to white or inactive beige ones when the cells were obtained from risk-free TT but not from obesity-risk CC genotype carriers. Active beige adipocytes carrying FTO CC had lower thermogenic gene (e.g., UCP1, PM20D1, CIDEA) expression and thermogenesis measured by proton leak respiration as compared to TT carriers. In addition, active beige adipocytes with CC alleles exerted lower expression of ASC-1 neutral amino acid transporter (encoded by SLC7A10) and less consumption of Ala, Ser, Cys, and Gly as compared to risk-free carriers. We did not observe any influence of the FTO rs1421085 SNP on white and inactive beige adipocytes highlighting its exclusive and critical effect when adipocytes were activated for thermogenesis.

Distinct Metabolomic Profiling of Serum Samples from High-Fat-Diet-Induced Insulin-Resistant Mice

High-fat-diet (HFD)-induced obesity is associated with an elevated risk of insulin resistance (IR), which may precede the onset of type 2 diabetes mellitus and associated metabolic complications. Being a heterogeneous metabolic condition, it is pertinent to understand the metabolites and metabolic pathways that are altered during the development and progression of IR toward T2DM. Serum samples were collected from C57BL/6J mice fed with HFD or chow diet (CD) for 16 weeks. Collected samples were analyzed by gas chromatography-tandem mass spectrometry (GC-MS/MS). Data on the identified raw metabolites were evaluated using a combination of univariate and multivariate statistical methods. Mice fed with HFD had glucose and insulin intolerance associated with impairment of insulin signaling in key metabolic tissues. From the GC-MS/MS analysis of serum samples, a total of 75 common annotated metabolites were identified between HFD- and CD-fed mice. In the t-test, 22 significantly altered metabolites were identified. Out of these, 16 metabolites were up-accumulated, whereas 6 metabolites were down-accumulated. Pathway analysis identified 4 significantly altered metabolic pathways. In particular, primary bile acid biosynthesis and linoleic acid metabolism were upregulated, whereas the TCA cycle and pentose and glucuronate interconversion were downregulated in HFD-fed mice in comparison to CD-fed mice. These results show the distinct metabolic profiles associated with the onset of IR that could provide promising metabolic biomarkers for diagnostic and clinical applications.

Metabolomic Characteristics of Cecum Contents in High-Fat-Diet-Induced Obese Mice Intervened with Different Fibers

The aim of this study was to demonstrate the effect of single or mixed fibers (arabinoxylan, β-glucan, xyloglucan, and inulin) on the metabolome of cecum content in mice with obesity caused by a high-fat diet. Twenty-eight six-week-old male mice were divided randomly into seven groups (n = 4/group), including a normal-diet group (CON), a high-fat-diet group (HFD), and groups with the same high-fat diet but supplemented with arabinoxylan (HFAX), arabinoxylan + β-glucan (HFAβ), arabinoxylan + xyloglucan (HFAG), xyloglucan (HFXG), and xyloglucan + inulin (HFXI). A total of 66 molecules were identified and quantified in cecum content by proton nuclear magnetic resonance (1 H-NMR). The metabolomic profiles combined with statistical analysis revealed compounds distinguishing the control group from those supplemented with fibers. In detail, a high-fat diet could significantly elevate the concentrations of acetone and methionine (p < 0.05) while decreasing the levels of methanol, arabinose, acetate, and 3-hydroxyphenylacetate (p < 0.05) in the cecum contents of mice. Compared to HFD, the supplementation caused higher levels of fumarate and hypoxanthine (p < 0.05) and lower levels of phenylacetate, acetate, fucose, formate, proline, betaine, and trimethylamine N-oxide (TMAO) (p < 0.05). An enrichment analysis highlighted that the pathways mainly altered were amino sugar metabolism, aspartate metabolism, and arginine and proline metabolism. In conclusion, non-starch polysaccharide (NSP) supplementation could change the metabolomic profiles of cecum contents in obese mice as a result of a high-fat diet. Moreover, mixed NSPs exhibited more beneficial effects than singular form on gut metabolism.

Chemical Barrier Proteins in Human Body Fluids

Chemical barriers are composed of those sites of the human body where potential pathogens can contact the host cells. A chemical barrier is made up by different proteins that are part of the antimicrobial and immunomodulatory protein/peptide (AMP) family. Proteins of the AMP family exert antibacterial, antiviral, and/or antifungal activity and can modulate the immune system. Besides these proteins, a wide range of proteases and protease inhibitors can also be found in the chemical barriers maintaining a proteolytic balance in the host and/or the pathogens. In this review, we aimed to identify the chemical barrier components in nine human body fluids. The interaction networks of the chemical barrier proteins in each examined body fluid were generated as well.