Exploring the Interactions between Obesity and Diabetes: Implications for Understanding Metabolic Dysregulation in a Saudi Arabian Adult Population.

The rising prevalence of obesity in Saudi Arabia is a major contributor to the nation's high levels of cardiometabolic diseases such as type 2 diabetes. To assess the impact of obesity on the diabetic metabolic phenotype presented in young Saudi Arabian adults, participants (n = 289, aged 18-40 years) were recruited and stratified into four groups: healthy weight (BMI 18.5-24.99 kg/m2) with (n = 57) and without diabetes (n = 58) or overweight/obese (BMI > 24.99 kg/m2) with (n = 102) and without diabetes (n = 72). Distinct plasma metabolic phenotypes associated with high BMI and diabetes were identified using nuclear magnetic resonance spectroscopy and ultraperformance liquid chromatography mass spectrometry. Increased plasma glucose and dysregulated lipoproteins were characteristics of obesity in individuals with and without diabetes, but the obesity-associated lipoprotein phenotype was partially masked in individuals with diabetes. Although there was little difference between diabetics and nondiabetics in the global plasma LDL cholesterol and phospholipid concentration, the distribution of lipoprotein particles was altered in diabetics with a shift toward denser and more atherogenic LDL5 and LDL6 particles, which was amplified in the presence of obesity. Further investigation is warranted in larger Middle Eastern populations to explore the dysregulation of metabolism driven by interactions between obesity and diabetes in young adults.

Metabolic Phenotype of Obesity in a Saudi Population.

Metabolic phenotyping of obese populations can shed light on understanding environmental interactions underpinning obesogenesis. Obesity and its comorbidities are a major health and socioeconomic concern globally and are highly prevalent in the Middle East. We employed nuclear magnetic resonance spectroscopy to characterize the metabolic signature of urine and blood plasma for a cohort of obese (n = 50) compared to non-obese (n = 48) Saudi participants. The urinary metabolic phenotype of obesity was characterized by higher concentrations of N-acetyl glycoprotein fragments, bile acids, lysine, and methylamines and lower concentrations of tricarboxylic acid cycle intermediates, glycine, and gut microbial metabolites. The plasma metabolic phenotype of obesity was dominated by sugars, branched chain amino acids, and lipids, particularly unsaturated lipids, with lower levels of plasma phosphorylcholine and HDL. Serum hepatic enzymes, triglycerides, and cholesterol mapped to specific metabolic phenotypes, potentially indicating the dysregulation of multiple distinct obesity-related pathways. Differences between urine and plasma phenotypes of obesity for this Saudi population and that reported for Caucasian individuals indicate population disparities in pathways relating to ketogenesis (more apparent in the Saudi obese population), dysregulated liver function, and the gut microbiome. Mapping population-specific metabolic perturbations may hold promise in establishing population differences relevant to disease risk and stratification of individuals with respect to discovery of new therapeutic targets.

Ethnicity and skin autofluorescence-based risk-engines for cardiovascular disease and diabetes mellitus.

Skin auto fluorescence (SAF) is used as a proxy for the accumulation of advanced glycation end products (AGEs) and has been proposed to stratify patients into cardiovascular disease (CVD) and diabetes mellitus (DM) risk groups. This study evaluates the effects of seven different ethnicities (Arab, Central-East African, Eastern Mediterranean, European, North African, South Asian and Southeast Asian) and gender on SAF as well as validating SAF assessment as a risk estimation tool for CVD and DM in an Arabian cohort. SAF data from self-reported healthy 2,780 individuals, collated from three independent studies, has been linear modelled using age and gender as a covariate. A cross-study harmonized effect size (Cohens'd) is provided for each ethnicity. Furthermore, new data has been collected from a clinically well-defined patient group of 235 individuals, to evaluate SAF as a clinical tool for DM and CVD-risk estimation in an Arab cohort. In an Arab population, SAF-based CVD and/or DM risk-estimation can be improved by referencing to ethnicity and gender-specific SAF values. Highest SAF values were observed for the North African population, followed by East Mediterranean, Arab, South Asian and European populations. The South Asian population had a slightly steeper slope in SAF values with age compared to other ethnic groups. All ethnic groups except Europeans showed a significant gender effect. When compared with a European group, effect size was highest for Eastern Mediterranean group and lowest for South Asian group. The Central-East African and Southeast Asian ethnicity matched closest to the Arab and Eastern Mediterranean ethnicities, respectively. Ethnic and gender-specific data improves performance in SAF-based CVD and DM risk estimation. The provided harmonized effect size allows a direct comparison of SAF in different ethnicities. For the first time, gender differences in SAF are described for North African and East Mediterranean populations.