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Activation of G protein-coupled receptors by agonists leads to receptor phosphorylation, internalization of ligand receptor complexes, and desensitization of hormonal response. The role of parathyroid hormone (PTH) receptor 1, PTHR1, is well characterized and known to regulate cellular responsiveness in vitro. However, the role of PTHR1 phosphorylation in bone formation is yet to be investigated. We have previously demonstrated that impaired internalization and sustained cAMP stimulation of phosphorylation-deficient (PD) PTHR1 leads to exaggerated cAMP response to subcutaneous PTH infusion in a PD knockin mouse model. To understand the physiological role of receptor internalization on PTH bone anabolic action, we examined bone parameters of wild-type (WT) and PD knockin female and male mice following PTH treatment. We found a decrease in total and diaphyseal bone mineral density in female but not in male PD mice compared with WT controls at 3-6 mo of age. This effect was attenuated at older age groups. PTH administration displayed increased bone volume and trabecular thickness in the vertebrae and distal femora of both WT and PD animals. These results suggest that PTHR1 phosphorylation does not play a major role in the anabolic action of PTH. [ABSTRACT FROM AUTHOR]

Phosphorylation, internalization, and desensitization of G protein-coupled receptors, such as the parathyroid hormone (PTH) and PTH-related peptide (PTHrP) receptor (PTH1R), are well characterized and known to regulate the cellular responsiveness in vitro. However, the role of PTH1R receptor phosphorylation in bone formation and osteoblast functions has not yet been elucidated. In previous studies, we demonstrated impaired internalization and sustained cAMP stimulation of a phosphorylation-deficient (pd) PTH1R in vitro, and exaggerated cAMP and calcemic responses to s.c. PTH infusion in pdPTH1R knock-in mouse model. In this study, we examined the impact of impaired PTH1R phosphorylation on the skeletal phenotype of mice maintained on normal, low, and high calcium diets. The low calcium diet moderately reduced (P≤0.05) bone volume and trabecular number, and increased trabecular spacing in both wild-type (WT) and pd mice. The effects, however, seem to be less pronounced in the female pd compared to WT mice. In primary calvarial osteoblasts isolated from 2-week-old pd or WT mice, PTH and PTHrP decreased phosphorylated extracellular signalregulated kinases 1/2 (pERK1/2), a member of mitogenactivated protein kinase, and cyclin D1, a G1/S phase cyclin, in vitro. In contrast to WT osteoblasts, down-regulation of cyclin D1 was sustained for longer periods of time in osteoblasts isolated from the pd mice. Our results suggest that adaptive responses of intracellular signaling pathways in the pd mice may be important for maintaining bone homeostasis. [ABSTRACT FROM AUTHOR]

Corticotropin-releasing factor receptor 1 (CRFR1) mediates the physiological actions of corticotropin-releasing factor in the anterior pituitary gland and the central nervous system. Using chemical cross-linking we have previously reported that residue 16 of sauvagine (SVG) is in a close proximity to the second extracellular loop of CRFR1. Here we introduced p-benzoylphenylalanine (Bpa) at position 17 of a sauvagine analog, [Tyr0, Gln¹, Bpa17]SVG, to covalently label CRFR1 and characterize the cross-linking site. Using a combination of receptor mutagenesis, peptide mapping, and N-terminal sequencing, we identified His117 within the first transmembrane domain (TM1) of CRFR1 as the cross-linking site for Bpa17 of 125I-[Tyr0, Gln¹, Bpa17]SVG. These data indicate that, within the SVG-CRFR1 complex, residue 17 of the ligand lies within a 9 Å distance from residue 117 of the TM1 of CRFR1. The molecular proximity between residue 17 of the ligand and TM1 of CRFR1 described here and between residue 16 of the ligand and the CRFR1 second extracellular loop described previously provides useful molecular constraints for modeling ligand-receptor interaction in mammalian cells expressing CRFR1. [ABSTRACT FROM AUTHOR]

There is variability in the metabolic health status among individuals presenting with obesity; some may be metabolically healthy, while others may have developed the metabolic syndrome, a cluster including insulin resistance, hypertension, dyslipidemia, and increased risk of cardiovascular disease and type 2 diabetes. The mechanisms contributing to this metabolic heterogeneity are not fully understood. To address this question, plasma samples from 48 individuals with BMI ≥ 35 kg/m2 were examined (27 with and 21 without metabolic syndrome). Fasting plasma samples were subjected to Olink proteomics analysis for 184 cardiometabolic and inflammation-enriched proteins. Data analysis showed a clear differentiation between the two groups with distinct plasma protein expression profiles. Twenty-four proteins were differentially expressed (DEPs) between the two groups. Pathways related to immune cell migration, leukocyte chemotaxis, chemokine signaling, mucosal inflammatory response, tissue repair and remodeling were enriched in the group with metabolic syndrome. Functional analysis of DEPs revealed upregulation of 15 immunological pathways. The study identifies some of the pathways that are altered and reflect metabolic health in individuals with obesity. This provides valuable insights into some of the underlying mechanisms and can lead to identification of therapeutic targets to improve metabolic health in individuals with obesity. [ABSTRACT FROM AUTHOR]

Objectives: To examine the hypothesis that obesity complicated by the metabolic syndrome, compared to uncomplicated obesity, has distinct molecular signatures and metabolic pathways. Methods: We analyzed a cohort of 39 participants with obesity that included 21 with metabolic syndrome, age-matched to 18 without metabolic complications. We measured in whole blood samples 754 human microRNAs (miRNAs), 704 metabolites using unbiased mass spectrometry metabolomics, and 25,682 transcripts, which include both protein coding genes (PCGs) as well as non-coding transcripts. We then identified differentially expressed miRNAs, PCGs, and metabolites and integrated them using databases such as mirDIP (mapping between miRNA-PCG network), Human Metabolome Database (mapping between metabolite-PCG network) and tools like MetaboAnalyst (mapping between metabolite-metabolic pathway network) to determine dysregulated metabolic pathways in obesity with metabolic complications. Results: We identified 8 significantly enriched metabolic pathways comprising 8 metabolites, 25 protein coding genes and 9 microRNAs which are each differentially expressed between the subjects with obesity and those with obesity and metabolic syndrome. By performing unsupervised hierarchical clustering on the enrichment matrix of the 8 metabolic pathways, we could approximately segregate the uncomplicated obesity strata from that of obesity with metabolic syndrome. Conclusions: The data suggest that at least 8 metabolic pathways, along with their various dysregulated elements, identified via our integrative bioinformatics pipeline, can potentially differentiate those with obesity from those with obesity and metabolic complications. [ABSTRACT FROM AUTHOR]

Background: Obesity coexists with variable features of metabolic syndrome, which is associated with dysregulated metabolic pathways. We assessed potential associations between serum metabolites and features of metabolic syndrome in Arabic subjects with obesity. Methods: We analyzed a dataset of 39 subjects with obesity only (OBO, n = 18) age-matched to subjects with obesity and metabolic syndrome (OBM, n = 21). We measured 1069 serum metabolites and correlated them to clinical features. Results: A total of 83 metabolites, mostly lipids, were significantly different (p < 0.05) between the two groups. Among lipids, 22 sphingomyelins were decreased in OBM compared to OBO. Among non-lipids, quinolinate, kynurenine, and tryptophan were also decreased in OBM compared to OBO. Sphingomyelin is negatively correlated with glucose, HbA1C, insulin, and triglycerides but positively correlated with HDL, LDL, and cholesterol. Differentially enriched pathways include lysine degradation, amino sugar and nucleotide sugar metabolism, arginine and proline metabolism, fructose and mannose metabolism, and galactose metabolism. Conclusions: Metabolites and pathways associated with chronic inflammation are differentially expressed in subjects with obesity and metabolic syndrome compared to subjects with obesity but without the clinical features of metabolic syndrome. [ABSTRACT FROM AUTHOR]

Metabolic pathways that are corrupted at early stages of insulin resistance (IR) remain elusive. This study investigates changes in body metabolism in clinically healthy and otherwise asymptomatic subjects that may become apparent already under compromised insulin sensitivity (IS) and prior to IR. 47 clinically healthy Arab male subjects with a broad range of IS, determined by hyperinsulinemic-euglycemic clamp (HIEC), were investigated. Untargeted metabolomics and complex lipidomics were conducted on serum samples collected under fasting and HIEC conditions. Linear models were used to identify associations between metabolites concentrations and IS levels. Among 1896 identified metabolites, 551 showed significant differences between fasting and HIEC, reflecting the metabolic switch in energy utilization. At fasting, 336 metabolites, predominantly di- and tri-acylglycerols, showed significant differences between subjects with low and high levels of IS. Changes in amino acid, carbohydrate and fatty acid metabolism in response to insulin were impaired in subjects with low IS. Association of altered mannose and amino acids with IS was also replicated in an independent cohort of T2D patients. We identified metabolic phenotypes that characterize clinically healthy Arab subjects with low levels of IS at their fasting state. Our study is providing further insights into the metabolic pathways that precede IR. [ABSTRACT FROM AUTHOR]

Prediabetes is a condition leading to increased risk of diabetes and its complications and cardiovascular disease. Annually, ∼10% prediabetic subjects progress to T2D. We, and other investigators, reported that grape skin extract (GSE) impacts postprandial glycemia through alpha glucosidase inhibition. This study aims to examine the effect of GSE on glycemic response to a starch challenge in healthy prediabetic subjects. The study was approved by the IRB of Hamad Medical Corporation. Subjects were screened from a high-risk population based on family history and/or fasting glucose (5.7-7.3 mmol) and IGT confirmed with 75 gram OGTT. Subjects were randomized to GSE capsule 600 (N=4), 1200 (N=8), 1800 (N=15) or 2400 mg (N=14). Each received a meal of 35 gram (uncooked weight) rice with or without the assigned dose of GSE and blood glucose was measured at time 0, 15, 30, 60 and 120 minutes. Area under the curve (AUC) was calculated using the trapezoidal method and the subjects were classified into "responders" or "non-responders" if AUC after GSE was reduced by at least 1 SD. A total of 41 eligible subjects (83% male; age 29±8 years; BMI 23.2%±5.9, 34% Arab, 24% African, 17% Asian, 24% Indian) with prediabetes were enrolled. A total of 4 (9.7%)subjects decreased AUC by 2SD; 24% decreased by 1 SD and the remainder had no positive response to a single dose of GSE. There were no responders to 600 mg; 2 in 1200 mg; 4 in 1800 mg; and 3 in 2400 mg dose. There were no differences between the responders and non-responders in clinical or biochemical characteristics. In conclusion, 24% of prediabetic subjects had a positive response to GSE in a starch challenge test. The value of the test in characterizing prediabetic subjects who may benefit from GSE to reverse their prediabetic condition is currently under further investigation. In Qatar, the prevalence of diabetes is 17% and expected to increase. Studies to develop natural products to prevent diabetes are of great public health interest. Disclosure: M. Alkasem: None. I. Abdalhakam: None. N.N. Suleiman: None. A.N. Iskandarani: None. T.A. Samra: None. F.A. Mir: None. R.M. Mohammad: None. A. Abou-Samra: None. K. Zhou: None. M.C. Skarulis: None. Funding: Qatar National Research Fund [ABSTRACT FROM AUTHOR]