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Metformin is the first-line oral medication for treating type 2 diabetes mellitus (T2DM). In the current study, an untargeted lipidomic analytical approach was used to investigate the alterations in the serum lipidome of a cohort of 89 participants, including healthy lean controls and obese diabetic patients, and to examine the alterations associated with metformin administration. A total of 115 lipid molecules were significantly dysregulated (64 up-regulated and 51 down-regulated) in the obese compared to lean controls. However, the levels of 224 lipid molecules were significantly dysregulated (125 up-regulated and 99 down-regulated) in obese diabetic patients compared to the obese group. Metformin administration in obese diabetic patients was associated with significant dysregulation of 54 lipid molecule levels (20 up-regulated and 34 down-regulated). Levels of six molecules belonging to five lipid subclasses were simultaneously dysregulated by the effects of obesity, T2DM, and metformin. These include two putatively annotated triacylglycerols (TGs), one plasmenyl phosphatidylcholine (PC), one phosphatidylglycerol (PGs), one sterol lipid (ST), and one Mannosyl-phosphoinositol ceramide (MIPC). This study provides new insights into our understanding of the lipidomics alterations associated with obesity, T2DM, and metformin and offers a new platform for potential biomarkers for the progression of diabetes and treatment response in obese patients.

Background: Obesity and type 2 diabetes mellitus (T2DM) are characterized by underlying low-grade chronic inflammation. Metformin has been used as the first line of therapy in T2DM as it decreases hepatic glucose production and glucose intestinal absorption, enhances insulin sensitivity and weight loss, and is known to ameliorate inflammation. The mechanisms through which metformin exerts its effect remain unclear. Proteomics has emerged as a unique approach to explore the biological changes associated with diseases, including T2DM. It provides insight into the circulating biomarkers/mediators which could be utilized for disease screening, diagnosis, and prognosis. Methods: This study evaluated the proteomic changes in obese (Ob), obese diabetics (OD), and obese diabetic patients on metformin (ODM) using a 2D DIGE MALDI-TOF mass spectrometric approach. Results: Significant changes in sixteen plasma proteins (15 up and 1 down, ANOVA, p ≤ 0.05; fold change ≥ 1.5) were observed in the ODM group when compared to the Ob and OD groups. Bioinformatic network pathway analysis revealed that the majority of these altered plasma proteins are involved in distinct pathways involving acute-phase response, inflammation, and oxidative response and were centered around HNF4A, ERK, JNK, and insulin signaling pathways. Conclusions: Our study provides important information about the possible biomarkers altered by metformin treatment in obese patients with and without T2DM. These altered plasma proteins are involved in distinct pathways involving acute-phase response, inflammation, and oxidative response and were centered around HNF4A, ERK, JNK, and insulin signaling pathways. The presented proteomic profiling approach may help in identifying potential biomarkers/mediators affected by metformin treatment in T2DM and inform the understanding of metformin’s mechanisms of action.

ANGPTL8 is recognized as a regulator of lipid metabolism through its role in inhibiting lipoprotein lipase activity. ANGPTL8 gene variants, particularly rs2278426 leading to the R59W variant in the protein, have been associated with lipid traits in various ethnicities. We aimed to use metabolomics to understand the impact of the ANGPTL8 R59W variant on metabolites in humans. We used the Biocrates-p400 kit to quantify 408 plasma metabolites in 60 adult male Arab individuals from Kuwait and identify differences in metabolite levels between individuals carrying reference genotypes and those with carrier genotypes at ANGPTL8 rs2278426. Individuals with carrier genotypes (CT+TT) compared to those carrying the reference genotype (CC) showed statistically significant differences in the following metabolites: acylcarnitine (perturbs metabolic pathways), phosphatidylcholine (supports liver function and cholesterol levels), cholesteryl ester (brings chronic inflammatory response to lipoprotein depositions in arteries), α-aminoadipic acid (modulates glucose homeostasis), histamine (regulates glucose/lipid metabolism), sarcosine (links amino acid and lipid metabolism), diacylglycerol 42:1 (regulates homeostasis of cellular lipid stores), and lysophosphatidylcholine (regulates oxidative stress and inflammatory response). Functional aspects attributed to these metabolites indicate that the ANGPTL8 R59W variant influences the concentrations of lipid- and inflammation-related metabolites. This observation further highlights the role of ANGPTL8 in lipid metabolism.

(1) Background: Type 1 diabetes mellitus (T1D) is a chronic autoimmune disease caused by the destruction of pancreatic insulin-producing beta cells. T1D is one of the most common endocrine and metabolic disorders occurring in children. Autoantibodies against pancreatic insulin-producing beta cells are important immunological and serological markers of T1D. Zinc transporter 8 autoantibody (ZnT8) is a recently identified autoantibody in T1D; however, no data on ZnT8 autoantibody in the Saudi Arabian population have been reported. Thus, we aimed to investigate the prevalence of islet autoantibodies (IA-2 and ZnT8) in adolescents and adults with T1D according to age and disease duration. (2) Methods: In total, 270 patients were enrolled in this cross-sectional study. After meeting the study’s inclusion and exclusion criteria, 108 patients with T1D (50 men and 58 women) were assessed for T1D autoantibody levels. Serum ZnT8 and IA-2 autoantibodies were measured using commercial enzyme-linked immunosorbent assay kits. (3) Results: IA-2 and ZnT8 autoantibodies were present in 67.6% and 54.6% of patients with T1D, respectively. Autoantibody positivity was found in 79.6% of the patients with T1D. Both the IA-2 and ZnT8 autoantibodies were frequently observed in adolescents. The prevalence of IA-2 and ZnT8 autoantibodies in patients with a disease duration < 1 year was 100% and 62.5%, respectively, which declined with an increase in disease duration (p < 0.020). Logistic regression analysis revealed a significant relationship between age and autoantibodies (p < 0.004). (4) Conclusions: The prevalence of IA-2 and ZnT8 autoantibodies in the Saudi Arabian T1D population appears to be higher in adolescents. The current study also showed that the prevalence of autoantibodies decreased with disease duration and age. IA-2 and ZnT8 autoantibodies are important immunological and serological markers for T1D diagnosis in the Saudi Arabian population.

Endometrial cancer (EC) is the most common form of gynecological cancer. Type 2 diabetes mellitus is associated with an increased risk of EC. Currently, no proteomic studies have investigated the role of diabetes in endometrial cancers from clinical samples. The present study aims to elucidate the molecular link between diabetes and EC using a proteomic approach. Endometrial tissue samples were obtained from age-matched patients (EC Diabetic and EC Non-Diabetic) during surgery. Untargeted proteomic analysis of the endometrial tissues was carried out using a two-dimensional difference in gel electrophoresis (2D-DIGE) coupled with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI TOF). A total of 53 proteins were identified, with a significant difference in abundance (analysis of variance (ANOVA) test, p ≤ 0.05; fold-change ≥ 1.5) between the two groups, among which 30 were upregulated and 23 downregulated in the EC Diabetic group compared to EC Non-Diabetic. The significantly upregulated proteins included peroxiredoxin-1, vinculin, endoplasmin, annexin A5, calreticulin, and serotransferrin. The significantly downregulated proteins were myosin regulatory light polypeptide 9, Retinol dehydrogenase 12, protein WWC3, intraflagellar transport protein 88 homolog, superoxide dismutase [Cu-Zn], and retinal dehydrogenase 1. The network pathway was related to connective tissue disorder, developmental disorder, and hereditary disorder, with the identified proteins centered around dysregulation of ERK1/2 and F Actin signaling pathways. Cancer-associated protein alterations such as upregulation of peroxiredoxin-1, annexin 5, and iNOS, and downregulation of RDH12, retinaldehyde dehydrogenase 1, SOD1, and MYL 9, were found in the EC tissues of the diabetic group. Differential expression of proteins linked to cancer metastasis, such as the upregulation of vinculin and endoplasmin and downregulation of WWC3 and IFT88, was seen in the patients with diabetes. Calreticulin and alpha-enolase, which might have a role in the interplay between diabetes and EC, need further investigation.