Metabolically Healthy and Unhealthy Obese Phenotypes among Arabs and South Asians: Prevalence and Relationship with Cardiometabolic Indicators

Association between paravertebral muscle radiological parameter alterations and non-alcoholic fatty liver disease

PURPOSE

To assess changes in laboratory indices, paravertebral muscle (PVM) fat infiltration and multi b-value DWI parameters and their potential correlation with NAFLD.

METHODS

This retrospective analysis included 178 patients with histopathologically confirmed NAFLD, incluiding 76 with non-alcoholic steatohepatitis (NASH). Differences in PVM fat infiltration ratio (FIR), DWI parameters, and laboratory indices were compared between two groups. The correlation between FIR and NAFLD activity score (NAS) was also analysed. Binary logistic regression was used to identify the independent risk factors for NASH. The clinical utility of PVM fat infiltration, DWI parameters, and laboratory indices for diagnosing NASH in patients with NAFLD was evaluated using receiver operating characteristic (ROC) curves.

RESULTS

The FIRs at the L2 and L3 levels were significantly higher in the with NASH group than those in the without NASH group. The heterogeneity index (α) and perfusion fraction (f) values at the L3 level of PVM were lower in the with NASH group. Moreover, the FIR at the L3 level was positively correlated with NAS. FIR at the L3 level was an independent risk factor for NASH along with alanine aminotransferase level. The area under the ROC curve (AUC) using L3 level PVM radiological parameters and laboratory indices for diagnosing NASH in patients with NAFLD was significantly higher than that using the degree of PVM fat infiltration, DWI parameters, or laboratory indices alone.

CONCLUSIONS

Radiological parameters of the PVM were correlated with NAFLD. An integrated curve combining PVM radiological parameters may help distinguish NASH from NAFLD, thereby offering novel insights into the diagnosis of NASH.

Ethnic Variations in the Levels of Bone Biomarkers (Osteoprostegerin, Receptor Activator of Nuclear Factor Kappa-Β Ligand and Glycoprotein Non-Metastatic Melanoma Protein B) in People with Type 2 Diabetes

The global incidence of Type 2 diabetes (T2D) is on the rise, fueled by factors such as obesity, sedentary lifestyles, socio-economic factors, and ethnic backgrounds. T2D is a multifaceted condition often associated with various health complications, including adverse effects on bone health. This study aims to assess key biomarkers linked to bone health and remodeling-Osteoprotegerin (OPG), Receptor Activator of Nuclear Factor Kappa-Β Ligand (RANKL), and Glycoprotein Non-Metastatic Melanoma Protein B (GPNMB)-among individuals with diabetes while exploring the impact of ethnicity on these biomarkers. A cross-sectional analysis was conducted on a cohort of 2083 individuals from diverse ethnic backgrounds residing in Kuwait. The results indicate significantly elevated levels of these markers in individuals with T2D compared to non-diabetic counterparts, with OPG at 826.47 (405.8) pg/mL, RANKL at 9.25 (17.3) pg/mL, and GPNMB at 21.44 (7) ng/mL versus 653.75 (231.7) pg/mL, 0.21 (9.94) pg/mL, and 18.65 (5) ng/mL in non-diabetic individuals, respectively. Notably, this elevation was consistent across Arab and Asian populations, except for lower levels of RANKL observed in Arabs with T2D. Furthermore, a positive and significant correlation between OPG and GPNMB was observed regardless of ethnicity or diabetes status, with the strongest correlation (r = 0.473, p < 0.001) found among Arab individuals with T2D. Similarly, a positive and significant correlation between GPNMB and RANKL was noted among Asian individuals with T2D (r = 0.401, p = 0.001). Interestingly, a significant inverse correlation was detected between OPG and RANKL in non-diabetic Arab individuals. These findings highlight dysregulation in bone remodeling markers among individuals with T2D and emphasize the importance of considering ethnic variations in T2D-related complications. The performance of further studies is warranted to understand the underlying mechanisms and develop interventions based on ethnicity for personalized treatment approaches.

Differences in the levels of inflammatory markers between metabolically healthy obese and other obesity phenotypes in adults: A systematic review and meta-analysis

AIMS

The aim of this study was to systematically review and analyze differences in the levels of C-reactive protein (CRP), interleukin-6 (IL-6), and tumor necrosis factor-alpha (TNF-α) comparing metabolically healthy but obese (MHO) with metabolically healthy non-obese (MHNO), metabolically unhealthy non-obese (MUNO), and metabolically unhealthy obese (MUO) subjects.

DATA SYNTHESIS

We searched PubMed, Embase, Web of Science, and Scopus for studies that matched the relevant search terms. Differences in inflammatory marker levels between MHO and the other three phenotypes were pooled as standardized mean differences (SMD) or differences of medians (DM) using a random-effects model. We included 91 studies reporting data on 435,007 individuals. The CRP levels were higher in MHO than in MHNO subjects (SMD = 0.63, 95% CI: 0.49, 0.76; DM = 0.83 mg/L, 95% CI: 0.56, 1.11). The CRP levels were higher in MHO than in MUNO subjects (SMD = 0.16, 95% CI: 0.05, 0.28; DM = 0.39 mg/L, 95% CI: 0.09, 0.69). The CRP levels were lower in MHO than in MUO individuals (SMD = -0.43, 95% CI: -0.54, -0.31; DM = -0.82 mg/L, 95% CI: -1.16, -0.48). The IL-6 levels in MHO were higher than in MHNO while lower than in MUO subjects. The TNF-α levels in MHO were higher than in MHNO individuals.

CONCLUSIONS

This review provides evidence that CRP levels in MHO are higher than in MHNO and MUNO subjects but lower than in MUO individuals. Additionally, IL-6 levels in MHO are higher than in MHNO but lower than in MUO subjects, and TNF-α levels in MHO are higher than in MHNO individuals.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO number: CRD42021234948.

Metabolic phenotyping of BMI to characterize cardiometabolic risk: evidence from large population-based cohorts

Obesity is a risk factor for type 2 diabetes and cardiovascular disease. However, a substantial proportion of patients with these conditions have a seemingly normal body mass index (BMI). Conversely, not all obese individuals present with metabolic disorders giving rise to the concept of "metabolically healthy obese". We use lipidomic-based models for BMI to calculate a metabolic BMI score (mBMI) as a measure of metabolic dysregulation associated with obesity. Using the difference between mBMI and BMI (mBMIΔ), we identify individuals with a similar BMI but differing in their metabolic health and disease risk profiles. Exercise and diet associate with mBMIΔ suggesting the ability to modify mBMI with lifestyle intervention. Our findings show that, the mBMI score captures information on metabolic dysregulation that is independent of the measured BMI and so provides an opportunity to assess metabolic health to identify "at risk" individuals for targeted intervention and monitoring.

Shared and Distinct Gut Microbial Profiles in Saudi Women with Metabolically Healthy and Unhealthy Obesity

BACKGROUND

Mounting evidence suggests a pivotal role for the gut microbiome in energy disequilibrium characteristic of obesity. The clinical utility of microbial profiling for the distinction between metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUO) remains ill-defined. We aim to probe microbial composition and diversity in young adult Saudi females with MHO and MUO. This observational study included anthropometric and biochemical measurements and shotgun sequencing of stool DNA for 92 subjects. α- and β-diversity metrics were calculated to determine the richness and variability in microbial communities, respectively. Results showed that Bacteroides and Bifidobacterium merycicum were less abundant in MUO compared to healthy and MHO groups. BMI was negatively correlated with B. adolescentis, B. longum, and Actinobacteria in MHO, while being positively correlated with Bacteroides thetaiotaomicron in both MHO and MUO. Positive correlations between waist circumference and B. merycicum and B. thetaiotaomicron were observed in MHO and MUO, respectively. Compared to MHO and MUO groups, higher α-diversity was detected in healthy individuals who also had higher β-diversity compared to those with MHO. We conclude that modulation of the gut microbiome cohorts through prebiotics, probiotics, and fecal microbiota transplantation may be a promising preventive and therapeutic approach to obesity-associated disease.

Targeted Metabolomics Revealed a Sex-Dependent Signature for Metabolic Syndrome in the Mexican Population

Metabolic syndrome (MetS) is a group of several metabolic conditions predisposing to chronic diseases. Individuals diagnosed with MetS are physiologically heterogeneous, with significant sex-specific differences. Therefore, we aimed to investigate the potential sex-specific serum modifications of amino acids and acylcarnitines (ACs) and their relationship with MetS in the Mexican population. This study included 602 participants from the Health Workers Cohort Study. Forty serum metabolites were analyzed using a targeted metabolomics approach. Multivariate regression models were used to test associations of clinical and biochemical parameters with metabolomic profiles. Our findings showed a serum amino acid signature (citrulline and glycine) and medium-chain ACs (AC14:1, AC10, and AC18:10H) associated with MetS. Glycine and AC10 were specific metabolites representative of discrimination according to sex-dependent MetS. In addition, we found that glycine and short-chain ACs (AC2, AC3, and AC8:1) are associated with age-dependent MetS. We also reported a significant correlation between body fat and metabolites associated with sex-age-dependent MetS. In conclusion, the metabolic profile varies by MetS status, and these differences are sex-age-dependent in the Mexican population.

Risk Factors and Prediction Models for Nonalcoholic Fatty Liver Disease Based on Random Forest

Objective

To establish a risk prediction model of nonalcoholic fatty liver disease (NAFLD) and provide management strategies for preventing this disease.

Methods

A total of 200 inpatients and physical examinees were collected from the Department of Gastroenterology and Endocrinology and Physical Examination Center. The data of physical examination, laboratory examination, and abdominal ultrasound examination were collected. All subjects were randomly divided into a training set (70%) and a verification set (30%). A random forest (RF) prediction model is constructed to predict the occurrence risk of NAFLD. The receiver operating characteristic (ROC) curve is used to verify the prediction effect of the prediction models.

Results

The number of NAFLD patients was 44 out of 200 enrolled patients, and the cumulative incidence rate was 22%. The prediction models showed that BMI, TG, HDL-C, LDL-C, ALT, SUA, and MTTP mutations were independent influencing factors of NAFLD, all of which has statistical significance (P < 0.05). The area under curve (AUC) of logistic regression and the RF model was 0.940 (95% CI: 0.870~0.987) and 0.945 (95% CI: 0.899~0.994), respectively.

Conclusion

This study established a prediction model of NAFLD occurrence risk based on the RF, which has a good prediction value.

Type 2 Diabetes Mellitus Facilitates Shift of Adipose-Derived Stem Cells Ex Vivo Differentiation toward Osteogenesis among Patients with Obesity

Objective: Sedentary behavior with overnutrition provokes the development of obesity, insulin resistance, and type 2 diabetes mellitus (T2DM). The main progenitor cells of adipose tissue are adipose-derived stem cells (ADSCs) which can change differentiation, metabolic, and secretory phenotypes under obesity conditions. The purpose of this study was to evaluate ADSC osteogenesis activity among patients with obesity in normal glucose tolerance (NGT) and T2DM conditions. Methods: In the study, ADSCs from donors with obesity were used. After clinical characterization, all patients underwent bariatric surgery and ADSCs were isolated from subcutaneous fat biopsies. ADSCs were subjected to osteogenic differentiation, stained with Alizarin Red S, and harvested for real-time PCR and Western blotting. Cell senescence was evaluated with a β-galactosidase-activity-based assay. Results: Our results demonstrated the significantly increased calcification of ADSC on day 28 of osteogenesis in the T2DM group. These data were confirmed by the statistically significant enhancement of RUNX2 gene expression, which is a master regulator of osteogenesis. Protein expression analysis showed the increased expression of syndecan 1 and collagen I before and during osteogenesis, respectively. Moreover, T2DM ADSCs demonstrated an increased level of cellular senescence. Conclusion: We suggest that T2DM-associated cellular senescence can cause ADSC differentiation to shift toward osteogenesis, the impaired formation of new fat depots in adipose tissue, and the development of insulin resistance. The balance between ADSC adipo- and osteogenesis commitment is crucial for the determination of the metabolic fate of patients and their adipose tissue.