Markers for obese and non-obese Type 2 diabetes identified using whole blood metabolomics

An Overview of Pre-Analytical Factors Impacting Metabolomics Analyses of Blood Samples

Discrepant sample processing remains a significant challenge within blood metabolomics research, introducing non-biological variation into the measured metabolome and biasing downstream results. Inconsistency during the pre-analytical phase can influence experimental processes, producing metabolome measurements that are non-representative of in vivo composition. To minimize variation, there is a need to create and adhere to standardized pre-analytical protocols for blood samples intended for use in metabolomics analyses. This will allow for reliable and reproducible findings within blood metabolomics research. In this review article, we provide an overview of the existing literature pertaining to pre-analytical factors that influence blood metabolite measurements. Pre-analytical factors including blood tube selection, pre- and post-processing time and temperature conditions, centrifugation conditions, freeze-thaw cycles, and long-term storage conditions are specifically discussed, with recommendations provided for best practices at each stage.

Quantified Metabolomics and Lipidomics Profiles Reveal Serum Metabolic Alterations and Distinguished Metabolites of Seven Chronic Metabolic Diseases

The co-occurrence of multiple chronic metabolic diseases is highly prevalent, posing a huge health threat. Clarifying the metabolic associations between them, as well as identifying metabolites which allow discrimination between diseases, will provide new biological insights into their co-occurrence. Herein, we utilized targeted serum metabolomics and lipidomics covering over 700 metabolites to characterize metabolic alterations and associations related to seven chronic metabolic diseases (obesity, hypertension, hyperuricemia, hyperglycemia, hypercholesterolemia, hypertriglyceridemia, fatty liver) from 1626 participants. We identified 454 metabolites were shared among at least two chronic metabolic diseases, accounting for 73.3% of all 619 significant metabolite-disease associations. We found amino acids, lactic acid, 2-hydroxybutyric acid, triacylglycerols (TGs), and diacylglycerols (DGs) showed connectivity across multiple chronic metabolic diseases. Many carnitines were specifically associated with hyperuricemia. The hypercholesterolemia group showed obvious lipid metabolism disorder. Using logistic regression models, we further identified distinguished metabolites of seven chronic metabolic diseases, which exhibited satisfactory area under curve (AUC) values ranging from 0.848 to 1 in discovery and validation sets. Overall, quantitative metabolome and lipidome data sets revealed widespread and interconnected metabolic disorders among seven chronic metabolic diseases. The distinguished metabolites are useful for diagnosing chronic metabolic diseases and provide a reference value for further clinical intervention and management based on metabolomics strategy.

Highly Defective Zirconium-Based Metal-Organic Frameworks for the Efficient Adsorption and Detection of Sugar Phosphates in the Biological Sample

Enrichment and quantification of sugar phosphates (SPx) in biological samples were of great significance in biological medicine. In this work, a series of zirconium-based metal-organic frameworks (MOFs) with different degrees of defects, namely, HP-UiO-66-NH2-X, were synthesized using acetic acid as a modulator and were utilized as high-capacity adsorbents for the adsorption of SPx in biological samples. The results indicated that the addition of acetic acid altered the morphology of HP-UiO-66-NH2-X, with corresponding changes in pore size (3.99-9.28 nm) and specific surface area (894.44-1142.50 m2·g-1). HP-UiO-66-NH2-10 showed the outstanding performance by achieving complete adsorption of all four SPx using only 80 μg of the adsorbent. The excellent adsorption efficiency of HP-UiO-66-NH2-10 was also obtained with a wide pH range and short adsorption time (10 min). Adsorption experiments demonstrated that the adsorption process involved chemical adsorption and multilayer adsorption. By utilizing X-ray photoelectron spectroscopy and density functional theory to explain the adsorption mechanism, it was found that various interactions (including coordination, hydrogen bonding, and electrostatic interactions) collectively contributed to the exceptional adsorption capability of HP-UiO-66-NH2-10. Those results indicated that the defect strategy not only increased the specific surface area and pore size, providing additional adsorption sites, but also reduced the adsorption energy between HP-UiO-66-NH2-10 and SPx. Moreover, HP-UiO-66-NH2-10 showed a low limit of detection (0.001-0.01 ng·mL-1), high precision (<13.77%), and accuracy (80.10-111.83%) in serum, liver, and cells, good stability, high selectivity (SPx/glucose, 1:100 molar ratio), and high adsorption capacity (292 mg·g-1 for SPx). The practical detection of SPx from human serum was also verified, prefiguring the great potentials of defective zirconium-based MOFs for the enrichment and detection of SPx in the biological medicine.

Effects of storage temperature and time on metabolite profiles measured in dried blood spots, dried blood microsamplers, and plasma

The practical advantages of capillary whole blood collection over venipuncture plasma collection for human exposome research are well known. However, before epidemiologists, clinicians, and public health researchers employ these microvolume sample collections, a rigorous evaluation of pre-analytical storage conditions is needed to develop protocols that maximize sample stability and reliability over time. Therefore, we performed a controlled experiment of dried whole blood collected on 10 μL Mitra microsamplers (DBM), 5-mm punches of whole blood from a dried blood spot (DBS), and 10 μL of plasma, and evaluated the effects of storage conditions at 4 °C, -20 °C, or -80 °C for up to 6 months on the resulting metabolite profiles measured with untargeted liquid chromatography-high resolution mass spectrometry (LC-HRMS). At -80 °C storage conditions, metabolite profiles from DBS, DBM, and plasma showed similar stability. While DBS and DBM metabolite profiles remained similarly stable at -20 °C storage, plasma profiles showed decreased stability at -20 °C compared to -80 °C storage. At refrigerated temperatures (4 °C), metabolite profiles collected on DBM were more stable than plasma or DBS, particularly for lipid classes. These results inform robust capillary blood sample storage protocols for DBM and DBS at potentially warmer temperatures than -80 °C, which may facilitate blood collections for populations outside of a clinical setting.

The Role of GLP-1, GIP, MCP-1 and IGFBP-7 Biomarkers in the Development of Metabolic Disorders: A Review and Predictive Analysis in the Context of Diabetes and Obesity

Metabolic illnesses, including obesity and type 2 diabetes, have become worldwide epidemics that have an effect on public health. Clinical investigations and further exploration of these mechanisms could lead to innovative, effective, and personalized treatment strategies for individuals. It is important to screen biomarkers in previous studies to discover what is missing. Glucagon-like peptide-1's role in insulin secretion and glucose control highlights its diagnostic and therapeutic potential. Glucose-dependent insulinotropic peptide's influence on postprandial satiety and weight management signifies its importance in understanding metabolic processes. Monocyte chemoattractant protein-1's involvement in inflammation and insulin resistance underlines its value as a diagnostic marker. Insulin-like growth factor-binding protein-7's association with insulin sensitivity and kidney function presents it as a potential target for these diseases' management. In validating these biomarkers, it will be easier to reflect pathophysiological processes, and clinicians will be able to better assess disease severity, monitor disease progression, and tailor treatment strategies. The purpose of the study was to elucidate the significance of identifying novel biomarkers for type 2 diabetes mellitus and obesity, which can revolutionize early detection, risk assessment, and personalized treatment strategies. Standard literature searches of PubMed (MEDLINE), EMBASE, and Cochrane Library were conducted in the year 2023 to identify both original RCTs and recent systematic reviews that have explored the importance of identifying novel biomarkers for T2D and obesity. This search produced 1964 results, and then was reduced to randomized controlled trial and systematic reviews, producing 145 results and 44 results, respectively. Researchers have discovered potential associations between type 2 diabetes mellitus and obesity and the biomarkers glucagon-like peptide-1, glucose-dependent insulinotropic peptide, monocyte chemoattractant protein-1, and insulin-like growth factor-binding protein-7. Understanding the role of those biomarkers in disease pathogenesis offers hope for improving diagnostics, personalized treatment, and prevention strategies.