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The role of IL-6R/IL-6 axis in metabolic inflammation remains controversial. We determined the changes in adipose tissue expression of IL-6R and IL-6 in obese, overweight, and lean non-diabetic individuals. Subcutaneous adipose tissue biopsies were collected from 33 obese, 22 overweight, and 10 lean individuals and the expression of IL-6R, IL-6, TNF-α, MCP-1, IP-10, CD11b, CD163, and CD68 was detected by immunohistochemistry; results were also confirmed by real-time RT-PCR and confocal microscopy. The data were compared using unpaired t-test and the dependence between two variables was assessed by Pearson's correlation test. Obese individuals showed higher IL-6R expression (103.8±4.807) in the adipose tissue as compared with lean/overweight (68.06±4.179) subjects (P<0.0001). The elevated IL-6R expression correlated positively with body mass index (BMI) (r=0.80 P<0.0001) and percent body fat (r=0.69 P=0.003). The increased IL-6R expression in obesity was also confirmed by RT-PCR (Obese: 3.921±0.712 fold; Lean/Overweight: 2.191±0.445 fold; P=0.0453) and confocal microscopy. IL-6 expression was also enhanced in obese adipose tissue (127.0±15.91) as compared with lean/overweight (86.69±5.25) individuals (P=0.03) which correlated positively with BMI (r=0.58 P=0.008). IL-6 mRNA expression was concordantly higher in obese (16.60±2.214 fold) versus lean/overweight (9.376±1.656 fold) individuals (P=0.0108). These changes in the IL-6R/IL-6 expression correlated positively with the adipose tissue expression of CD11b (IL-6R r=0.44 P=0.063; IL-6 r=0.77 P<0.0001), CD163 (IL-6R r=0.45 P=0.045; IL-6 r=0.55 P=0.013), TNF-α (IL-6R r=0.73 P=0.0003; IL-6 r=0.60 P=0.008), MCP-1 (IL-6R r=0.61 P=0.005; IL-6 r=0.63 P=0.004) and IP-10 (IL-6R r=0.41 P=0.08; IL-6 r=0.50 P=0.026). It was, therefore, concluded that obesity was a positive modulator of IL-6R and IL-6 expression in the adipose tissue which might be a contributory mechanism to induce metabolic inflammation.

Spexin is a novel neuropeptide playing an emerging role in metabolic diseases such as obesity and diabetes via involvement in energy homeostasis and food intake. The present study investigated the effects of obesity and type 2 diabetes (T2D) on circulating levels of spexin and its modulation by physical exercise. Normal-weight (n = 50) and obese adults with and without T2D (n = 69 and n = 66, respectively) were enrolled in the study. A subgroup of obese participants (n = 47) underwent a supervised 3-month exercise programme. Plasma spexin levels were measured by ELISA and correlated with various markers. Plasma spexin levels decreased in obese participants with or without T2D compared with those of normal-weight participants (0.43 ± 0.11, 0.44 ± 0.12 and 0.61 ± 0.23 ng/ml, respectively; P  < 0.001). Spexin levels negatively correlated with adiposity markers and blood pressure in the whole study population ( P  < 0.05). Multiple regression analysis revealed blood pressure was the greatest predictive determinant of plasma spexin levels, which significantly increased in response to physical exercise in obese participants without and with T2D ( P  < 0.05). Spexin levels significantly increased only in responders to exercise (those with increased oxygen consumption, VO 2 max) with a concomitant improvement in metabolic profile. In conclusion, plasma spexin levels may be an indicator of response to physical exercise.

ANGPTL8 is a liver and adipose tissue produced protein that regulates the level of triglyceride in plasma as well as glucose homeostasis. This study was designed to evaluate the level of ANGPTL8 in obese and non-obese subjects before and after exercise training. A total of 82 non-obese and 62 adult obese were enrolled in this study. Subjects underwent a three months of exercise training. Both full length and C-terminal 139-198 form of ANGPTL8 were measured by ELISA. Our data show that the full length ANGPTL8 level was increased in obese subjects (1150.04 ± 108.10 pg/mL) compared to non-obese (775.54 ± 46.12) pg/mL (p-Value = 0.002). C-terminal 139-198 form of ANGPTL8 was also increased in obese subjects 0.28 ± 0.04 ng/mL vs 0.20 ± 0.02 ng/mL in non-obese (p-value = 0.058). In obese subjects, the levels of both forms were reduced after three months of exercise training; full length was reduced from 1150.04 ± 108.10 pg/mL to 852.04 ± 51.95 pg/mL (p-Values 0.015) and c-terminal form was reduced from 0.28 ± 0.04 ng/mL to 0.19 ± 0.03 ng/mL (p-Value = 0.058). Interestingly, full length ANGPTL8 was positively associated with fasting blood glucose (FBG) in non-obese (r = 0.317, p-Value = 0.006) and obese subjects (r = 0.346, p-Value = 0.006) C-terminal 139-198 form of ANGPTL8 on the other hand, did not show any correlation in both groups. In conclusion, our data demonstrate that ANGPTL8 was increased in obesity and reduced after exercise training supporting the potential therapeutic benefit of reducing ANGPTL8. The various forms of ANGPTL8 associated differently with FBG suggesting that they have different roles in glucose homeostasis.

Background The hepatokine fetuin-A is linked to obesity and type 2 diabetes, but its presence and expression in adipose tissue remain unclear. In this study, we aimed to assess the circulating levels of fetuin-A and its expression in subcutaneous adipose tissue (SAT) from diabetic and non-diabetic obese subjects and their modulation by exercise. Methods SAT and blood were obtained from adults obese (diabetic, n =118 and non-diabetic, n =166) before and after a 3-month exercise program (diabetic, n =40 and non-diabetic, n =36, respectively). Plasma fetuin-A was assayed using ELISA. The presence and expression of fetuin-A in SAT, peripheral blood mononuclear cells (PBMCs) and cell lines (3T3-L1, THP-1, HepG2, RAW 264.7) were analysed using confocal microscopy, immunoblotting and qRT-PCR. Results Plasma fetuin-A level did not significantly differ between diabetic and non-diabetic obese subjects. However, when the non-diabetic group was divided into metabolically healthy and unhealthy phenotypes, significantly higher fetuin-A level was observed in the unhealthy sub-group. Circulating fetuin-A was mainly associated with glycaemic markers. In SAT, fetuin-A protein level was significantly higher in the diabetic obese subjects but its mRNA was not detected. Similarly, fetuin-A protein was detected in PBMCs, but its mRNA was not. In line with this, the use of various cell lines and culture media indicated that the presence of fetuin-A in SAT and PBMCs was due to its uptake from circulation rather than its endogenous expression. Finally, physical exercise decreased fetuin-A levels in both plasma and SAT in both groups. Conclusions Fetuin-A levels increased in association with diabetes in SAT but not in circulation in the obese subjects. Moreover, physical exercise decreased fetuin-A level. Fetuin-A potentially acts as a hepatokine taken up by other tissues, such as adipose tissue.

This is a retrospective single-center study of 417 consecutive patients with coronavirus disease 2019 (COVID-19) admitted to Jaber Al-Ahmad Hospital in Kuwait between February 24, 2020 and May 24, 2020. In total, 39.3% of patients were asymptomatic, 41% were symptomatic with mild/moderate symptoms, 19.7% were admitted to the intensive care unit (ICU). Most common symptoms in cohort patients were fever (34.3%) and dry cough (32.6%) while shortness in breath was reported in (75.6%) of ICU admissions. Reported complications requiring ICU admission included Sepsis (68.3%), acute respiratory distress syndrome (95.1%) and heart failure (63.4%). ICU patients were more likely to have comorbidities, in comparison to non-ICU patients, including diabetes (35.4% vs 20.3%) and hypertension (40.2% vs 26.9%). Mortality rate of cohort was 14.4% and mean age of death was 54.20 years (± 11.09) and 90% of death cases were males. Chest high-resolution computed tomography for ICU cases reveled multifocal large patchy areas of ground glass opacification mixed with dense consolidation. Cases admitted to ICU showed abnormal levels of markers associated with infection, inflammation, abnormal blood clotting, heart problems and kidney problems. Mean hospital stay for asymptomatic cases was 20.69 days ±8.57 and for mild/moderate cases was 21.4 days ±8.28. Mean stay in ICU to outcome for survivors was 11.95 days ±8.96 and for death cases 13.15 days ±10.02. In this single-center case series of 417 hospitalized COVID-19 patients in Kuwait 39.3% were asymptomatic cases, 41% showed mild/moderate symptoms and 18.7% were admitted to ICU with a mortality rate of 14.4%.

SARS-CoV-2, a severe respiratory disease primarily targeting the lungs, was the leading cause of death worldwide during the pandemic. Understanding the interplay between the oral microbiome and inflammatory cytokines during acute infection is crucial for elucidating host immune responses. This study aimed to explore the relationship between the oral microbiome and cytokines in COVID-19 patients, particularly those with and without sputum production. Saliva and blood samples from 50 COVID-19 patients were subjected to 16S ribosomal RNA gene sequencing for oral microbiome analysis, and 65 saliva and serum cytokines were assessed using Luminex multiplex analysis. The Mann-Whitney test was used to compare cytokine levels between individuals with and without sputum production. Logistic regression machine learning models were employed to evaluate the predictive capability of oral microbiome, salivary, and blood biomarkers for sputum production. Significant differences were observed in the membership (Jaccard dissimilarity: p = 0.016) and abundance (PhILR dissimilarity: p = 0.048; metagenomeSeq) of salivary microbial communities between patients with and without sputum production. Seven bacterial genera, including Prevotella , Streptococcus , Actinomyces , Atopobium , Filifactor , Leptotrichia , and Selenomonas , were more prevalent in patients with sputum production (p<0.05, Fisher’s exact test). Nine genera, including Prevotella , Megasphaera , Stomatobaculum , Selenomonas , Leptotrichia , Veillonella , Actinomyces , Atopobium , and Corynebacteria , were significantly more abundant in the sputum-producing group, while Lachnoanaerobaculum was more prevalent in the non-sputum-producing group (p<0.05, ANCOM-BC). Positive correlations were found between salivary IFN-gamma and Eotaxin2/CCL24 with sputum production, while negative correlations were noted with serum MCP3/CCL7, MIG/CXCL9, IL1 beta, and SCF (p<0.05, Mann-Whitney test). The machine learning model using only oral bacteria input outperformed the model that included all data: blood and saliva biomarkers, as well as clinical and demographic variables, in predicting sputum production in COVID-19 subjects. The performance metrics were as follows, comparing the model with only bacteria input versus the model with all input variables: precision (95% vs. 75%), recall (100% vs. 50%), F1-score (98% vs. 60%), and accuracy (82% vs. 66%).

Optical coherence tomography (OCT) with retinal segmentation analysis is a valuable tool in assessing axonal loss and neuro-degeneration in multiple sclerosis (MS) by in-vivo imaging, delineation and quantification of retinal layers. There is evidence of deep retinal involvement in MS beyond the inner retinal layers. The ultra-structural retinal changes in MS in different MS phenotypes can reflect differences in the pathophysiologic mechanisms. There is limited data on the pattern of deeper retinal layer involvement in progressive MS (PMS) versus relapsing remitting MS (RRMS). We have compared the OCT segmentation analysis in patients with relapsing-remitting MS and progressive MS. Cross-sectional study of 113 MS patients (226 eyes) (29 PMS, 84 RRMS) and 38 healthy controls (72 eyes). Spectral domain OCT (SDOCT) using the macular cube acquisition protocol (Cirrus HDOCT 5000; Carl Zeiss Meditec) and segmentation of the retinal layers for quantifying the thicknesses of the retinal layers. Segmentation of the retinal layers was carried out utilizing Orion software (Voxeleron, USA) for quantifying the thicknesses of individual retinal layers. The retinal nerve finer layer (RNFL) (p = 0.023), the ganglion-cell/inner plexiform layer (GCIPL) (p = 0.006) and the outer plexiform layer (OPL) (p = 0.033) were significantly thinner in PMS compared to RRMS. There was significant negative correlation between the outer nuclear layer (ONL) and EDSS (r = -0.554, p = 0.02) in PMS patients. In RRMS patients with prior optic neuritis, the GCIPL correlated negatively (r = -0.317; p = 0.046), while the photoreceptor layer (PR) correlated positively with EDSS (r = 0.478; p = 0.003). Patients with PMS exhibit more atrophy of both the inner and outer retinal layers than RRMS. The ONL in PMS and the GCIPL and PR in RRMS can serve as potential surrogate of disease burden and progression (EDSS). The specific retinal layer predilection and its correlation with disability may reflect different pathophysiologic mechanisms and various stages of progression in MS.

Background Hypertension is a risk factor for both cardiovascular diseases (CVDs) and type 2 diabetes (T2D). Angiopoietin-like proteins (ANGPTLs), mainly ANGPTL3, ANGPTL4 and ANGPTL8, are associated with increased plasma lipid content due to their role in regulating the activity of lipoprotein lipase, a key enzyme in metabolism of the lipoprotein in circulation. Dyslipidaemia is a risk factor for hypertension development; however, the roles of ANGPTL3, ANGPTL4 and ANGPTL8 in subjects with hypertension have not yet been established. This study compared the plasma and adipose tissue levels of ANGPTL3, ANGPTL4 and ANGPTL8 in age- and body mass index-matched subjects with and without hypertension. Methods A total of 119 subjects, including 69 hypertensive and 50 non-hypertensive subjects, were enrolled. ANGPTL3, ANGPTL4 and ANGPTL8 plasma levels were measured by ELISA, whereas their levels in adipose tissue were assessed via real-time PCR. Results We found that ANGPTL4 (202.49 ± 17.44 ng/mL vs. 160.64 ± 10.36 ng/mL, p  = 0.04) and ANGPTL8 levels (2310.96 ± 194.88 pg/mL vs. 1583.35 ± 138.27 pg/mL, p  = 0.001) were higher in hypertensive subjects than non-hypertensive subjects. However, ANGPTL3 levels were not significantly different between the two populations. Similarly, ANGPTL4 and ANGPTL8 levels were also elevated in subjects with T2D and hypertension than in those with T2D but not hypertension. Additionally, people with highest tertiles of ANGPTL8 had higher odds of having hypertension (odd ratio [OR] = 3.8, 95% confidence interval [CI] = (1.5-9.8), p -Value = 0.005. Similar to its plasma levels, ANGPTL4 and ANGPTL8 were higher in adipose tissue. Conclusions In conclusion, our data illustrate that ANGPTL4 and ANGPTL8 levels in both plasma and adipose tissues are increased in subjects with hypertension. The elevated levels of ANGPTL4 and ANGPTL8 in hypertensive subjects highlight their potential involvement, their potential role as biomarkers for hypertension and their therapeutic value in hypertension given their roles in regulating lipid metabolism.

Background/Objectives: Obesity is increasing worldwide, driven by unhealthy dietary habits and sedentary lifestyles. Genetic variations in taste receptor genes, particularly TAS1R2 and TAS2R38, may influence taste preferences, dietary intake, and obesity risk. This study examined associations between TAS1R2 and TAS2R38 polymorphisms, sugar-sweetened beverage (SSB) intake, and obesity risk in Kuwaiti adolescents. Methods: A cross-sectional study was conducted among 260 adolescents aged 11–14 years recruited from public schools in Kuwait. Genotyping of five single-nucleotide polymorphisms (SNPs) was performed using TaqMan assays. Associations between SNPs, SSB intake, and obesity parameters were evaluated using multinomial logistic regression and non-parametric tests, adjusted for age, sex, nationality, BMI z-scores, basal metabolic rate, and physical activity. p-values were corrected using the Benjamini–Hochberg method. Results: The rs713598 SNP in TAS2R38 showed a marginal association with BMI percentiles and z-scores. Adolescents carrying the CC genotype of rs10246939 SNP in TAS2R38 had significantly lower odds of high SSB consumption (>3 servings/week) compared with T-allele carriers (p = 0.018, OR= 0.24, 95% CI = 0.08–0.79). No significant associations were detected for TAS1R2 SNPs. Conclusions: Variations in TAS2R38 were linked to obesity measures and beverage intake in Kuwaiti adolescents, supporting a potential genetic contribution to dietary behaviors. These findings highlight the importance of taste receptor genetics in obesity research, though replication in larger and more diverse populations is required.

Background Hypertriglyceridemia is associated with increased risk for cardiovascular diseases and type 2 diabetes (T2D). Angiopoietin like proteins particularly 3, 4 and recently 8 are well established regulators of plasma triglyceride level through regulating the activity of lipoprotein lipase. Plasma level and association between ANGPTL3, 4 and 8 is not well established in human subjects. This study was designed to establish the level of these proteins in plasma and adipose tissues and investigate the association between ANGPTL8 with ANGPTL3 and 4 in T2D and non-diabetics subjects. Methods A total of 235 subjects were enrolled in this study, 144 non-diabetics and 91 T2D. ANGPTL 3, 4 and 8 levels were measured in plasma by ELISA and using real time RT-PCR in adipose tissues. Results In this study, we showed that ANGPTL3, 4 and 8 were higher in T2D subjects. Dividing the non-diabetic subjects according to their BMI showed higher level of ANGPTL3, 4 and 8 in obese subjects compared to non-obese subjects. No significant difference was observed between the T2D subjects. ANGPTL8 was showed positive correlation with ANGPTL3 in the non-diabetic subjects in the non-obese ( r  = 0.2437, p -Value = 0.0543) and obese subjects ( r  = 0.418, p -Value = 0.0125). No association was observed in the T2D subjects. On the other hand, ANGPTL4 was positively associated with the obese subjects in both the non-diabetics ( r  = 0.3322, p -Value = 0.0316) and the obese T2D subjects ( r  = 0.3161, p -Value = 0.0211). Conclusion In conclusion, our data shows that ANGPTL3, 4 and 8 are increased in obesity and T2D. ANGPTL8 associates with ANGPTL3 in the non-diabetic subjects while it associated more with ANGPTL4 in the obese and T2D subjects. Taken together, this data highlight the role of these proteins in metabolic diseases and how they interact with each other’s under different physiological and pathophysiological conditions.