Background: Mitochondrial dysfunction is implicated in the pathogenesis of Type 2 diabetes (T2D) and the development of diabetes related complications such as cardiovascular disease and stroke. Mitochondria produce several small polypeptides that may influence mitochondrial function and may impact on insulin sensitivity, such as humanin (HN) and the mitochondrial open reading frame of the 12S rRNA type-c (MOTS-c) that are mitochondrial derived proteins (MDP). The aim of this study was to determine MDP in normal, prediabetes and diabetes subjects. Subjects and Measurements: In this cross-sectional study, we analyzed the serum concentrations of MDP and adiponectin (ADP) in 225 subjects: normal (n = 68), pre-diabetes (n = 33), T2D less than (good control; n = 31), and greater than HbA1c 7% (poor control; n = 93) subjects. The relationship of serum MDP and ADP concentrations with biochemical and anthropometric measurements were performed and assessed by multilinear regression. Results: Serum HN concentrations were lower in T2D (p < 0.0001) and negatively correlated with age (p < 0.0001), HbA1c (p < 0.0001), glucose (p < 0.0001), triglycerides (p < 0.003), ALT (p < 0.004), and TG/HDL ratio (p < 0.001). Circulating HN levels were positively correlated to cholesterol (p < 0.017), LDL (p < 0.001), and HDL (p < 0.001). Linear regression analysis showed that HbA1c and ALT were two independent predictors of circulating HN. Similarly, serum MOTS-c was significantly lower in T2D subjects compared to controls (p < 0.007). Circulating MOTS-c positively correlated with BMI (p < 0.035), total cholesterol (p < 0.0001), and LDL (p < 0.001) and negatively correlated with age (p < 0.002), HbA1c (p < 0.001), and glucose (p < 0.002). Serum ADP concentrations were lower in T2D (p < 0.002) and negatively correlated with HbA1c (p < 0.001), weight (p < 0.032) TG (p < 0.0001), and ALT (p < 0.0001); and positively correlated with HDL (p < 0.0001) and HN (p < 0.003). Linear regression analysis showed that HbA1c and weight were two independent predictors of circulating ADP. Multilinear regression showed that HN and MOT-c correlated with each other, and only HN correlated with HbA1c. Conclusion: The MDPs HN and MOT-c, similar to ADP, are decreased in T2D and correlate with HbA1c. The data provide an additional evidence that mitochondrial dysfunction contributes to glycemic dysregulation and metabolic defects in T2D.

Impaired adipogenesis plays an important role in the development of obesity-associated insulin resistance and type 2 diabetes. Adipose tissue inflammation is a crucial mediator of this process. GATA-3 plays important roles in adipogenesis and inflammation. The aim of this study is to investigate the impact of GATA-3 suppression on improving adipogenesis, lowering inflammation and reversing insulin resistance. GATA-3 levels were measured in subcutaneous (SC) and omental (OM) adipose tissues obtained from insulin sensitive (IS) and insulin resistant (IR) obese individuals during weight reduction surgeries. The effect of GATA-3 suppression on adipogenesis, expression of inflammatory cytokines and insulin resistance biomarkers was performed in 3T3L-1 mouse preadipocytes via transfection with GATA-3-specific DNAzyme. GATA-3 expression was higher in OM compared to SC adipose tissues and in stromal vascular fraction-derived differentiating preadipocytes from IR obese individuals compared to their IS counterparts. Suppression of GATA-3 expression in 3T3L-1 mouse preadipocytes with GATA-3 specific inhibitor reversed 4-hydroxynonenal-induced impaired adipogenesis and triggered changes in the expression of insulin signaling-related genes. GATA-3 inhibition also modulated the expression of IL-6 and IL-10 and lowered the expression of insulin resistance biomarkers (PAI-1 and resistin) and insulin resistance phosphoproteins (p-BAD, p-PTEN and p-GSK3β). Inhibiting GATA-3 improves adipocytes differentiation, modulates the secretion of inflammatory cytokines and improves insulin sensitivity in insulin resistant cells. Suppression of GATA-3 could be a promising tool to improve adipogenesis, restore insulin sensitivity and lower obesity-associated inflammation in insulin resistant individuals.

Background: Pregnant women with gestational diabetes mellitus (GDM) or type 2 diabetes mellitus (T2DM) are at increased risks of pre-term labor, hypertension and preeclampsia. In this study, metabolic profiling of blood samples collected from GDM, T2DM and control pregnant women was undertaken to identify potential diagnostic biomarkers in GDM/T2DM and compared to pregnancy outcome.Methods: Sixty-seven pregnant women (21 controls, 32 GDM, 14 T2DM) in their second trimester underwent targeted metabolomics of plasma samples using tandem mass spectrometry with the Biocrates MxP^®Quant 500 Kit. Linear regression models were used to identify the metabolic signature of GDM and T2DM, followed by generalized linear model (GLMNET) and Receiver Operating Characteristic (ROC) analysis to determine best predictors of GDM, T2DM and pre-term labor.Results: The gestational age at delivery was 2 weeks earlier in T2DM compared to GDM and controls and correlated negatively with maternal HbA1C and systolic blood pressure and positively with serum albumin. Linear regression models revealed elevated glutamate and branched chain amino acids in GDM + T2DM group compared to controls. Regression models also revealed association of lower levels of triacylglycerols and diacylglycerols containing oleic and linoleic fatty acids with pre-term delivery. A generalized linear model ROC analyses revealed that that glutamate is the best predictors of GDM compared to controls (area under curve; AUC = 0.81). The model also revealed that phosphatidylcholine diacyl C40:2, arachidonic acid, glycochenodeoxycholic acid, and phosphatidylcholine acyl-alkyl C34:3 are the best predictors of GDM + T2DM compared to controls (AUC = 0.90). The model also revealed that the triacylglycerols C17:2/36:4 and C18:1/34:1 are the best predictors of pre-term delivery (≤ 37 weeks) (AUC = 0.84).Conclusions: This study highlights the metabolite alterations in women in their second trimester with diabetes mellitus and identifies predictive indicators of pre-term delivery. Future studies to confirm these associations in other cohorts and investigate their functional relevance and potential utilization for targeted therapies are warranted.

Background: The fibroblast growth factors (FGF) 19 subfamily, also referred to as endocrine FGFs, includes FGF19, FGF21, and FGF23 are metabolic hormones involved in the regulation of glucose and lipid metabolism. Fetuin-A is a hepatokine involved in the regulation of beta-cell function and insulin resistance. Endocrine FGFs and fetuin-A are dysregulated in metabolic disorders including obesity, type 2 diabetes, non-alcoholic fatty liver disease and polycystic ovary syndrome (PCOS). Our study was designed to examine the response of endocrine FGFs and fetuin-A to an acute intralipid, insulin infusion and exercise in PCOS and healthy women. Subjects and Measurements: Ten healthy and 11 PCOS subjects underwent 5-h saline infusions with a hyperinsulinemic-euglycemic clamp (HIEC) performed during the final 2 h. One week later, intralipid infusions were undertaken with a HIEC performed during the final 2 h. After an 8 week of exercise intervention the saline, intralipid, and HIEC were repeated. Plasma levels of endocrine FGFs and fetuin-A were measured. Results: Baseline fetuin-A was higher in PCOS women but FGF19, FGF21, and FGF23 did not differ and were unaffected by exercise. Insulin administration elevated FGF21 in control and PCOS, suppressed FGF19 in controls, and had no effects on FGF23 and fetuin-A. Intralipid infusion suppressed FGF19 and increased FGF21. Insulin with intralipid synergistically increased FGF21 and did not have effects on lipid-mediated suppression of FGF19 in both groups. Conclusion: Our study provides evidence for insulin and lipid regulation of endocrine FGFs in healthy and PCOS women, suggesting that FGF family members play a role in lipid and glucose metabolism. Clinical Trial Registration: www.isrctn.org, Identifier: ISRCTN42448814.

Asthma and obesity are two of the most common chronic conditions in children and adolescents. There is increasing evidence that sphingolipid metabolism is altered in childhood asthma and is linked to airway hyperreactivity. Dysregulated sphingolipid metabolism is also reported in obesity. However, the functional link between sphingolipid metabolism, asthma, and obesity is not completely understood. This paper describes the protocol of an ongoing study on sphingolipids that aims to examine the pathophysiology of sphingolipids in childhood asthma and obesity. In addition, this study aims to explore the novel biomarkers through a comprehensive multi-omics approach including genomics, genome-wide DNA methylation, RNA-Seq, microRNA (miRNA) profiling, lipidomics, metabolomics, and cytokine profiling. This is a cross-sectional study aiming to recruit 440 children from different groups: children with asthma and normal weight (n = 100), asthma with overweight or obesity (n = 100), overweight or obesity (n = 100), normal weight (n = 70), and siblings of asthmatic children with normal weight, overweight, or obesity (n = 70). These participants will be recruited from the pediatric pulmonology, pediatric endocrinology, and general pediatric outpatient clinics at Sidra Medicine, Doha, Qatar. Information will be obtained from self-reported questionnaires on asthma, quality of life, food frequency (FFQ), and a 3-day food diary that are completed by the children and their parents. Clinical measurements will include anthropometry, blood pressure, biochemistry, bioelectrical impedance, and pulmonary function tests. Blood samples will be obtained for sphingolipid analysis, serine palmitoyltransferase (SPT) assay, whole-genome sequencing (WGS), genome-wide DNA methylation study, RNA-Seq, miRNA profiling, metabolomics, lipidomics, and cytokine analysis. Group comparisons of continuous outcome variables will be carried out by a one-way analysis of variance or the Kruskal–Wallis test using an appropriate pairwise multiple comparison test. The chi-squared test or a Fisher’s exact test will be used to test the associations between categorical variables. Finally, multivariate analysis will be carried out to integrate the clinical data with multi-omics data. This study will help us to understand the role of dysregulated sphingolipid metabolism in obesity and asthma. In addition, the multi-omics data from the study will help to identify novel genetic and epigenetic signatures, inflammatory markers, and mechanistic pathways that link asthma and obesity in children. Furthermore, the integration of clinical and multi-omics data will help us to uncover the potential interactions between these diseases and to offer a new paradigm for the treatment of pediatric obesity-associated asthma.