Unique role for lncRNA HOTAIR in defining depot-specific gene expression patterns in human adipose-derived stem cells.

Accumulation of fat above the waist is an important risk factor in developing obesity-related comorbidities independently of BMI or total fat mass. Deciphering the gene regulatory programs of the adipose tissue precursor cells within upper body or abdominal (ABD) and lower body or gluteofemoral (GF) depots is important to understand their differential capacity for lipid accumulation, maturation, and disease risk. Previous studies identified the HOX transcript antisense intergenic RNA (HOTAIR) as a GF-specific lncRNA; however, its role in adipose tissue biology is still unclear. Using three different approaches (silencing of HOTAIR in GF human adipose-derived stem cells [GF hASCs], overexpression of HOTAIR in ABD hASCs, and ChIRP-seq) to localize HOTAIR binding in GF hASC chromatin, we found that HOTAIR binds and modulates expression, both positively and negatively, of genes involved in adipose tissue-specific pathways, including adipogenesis. We further demonstrate a direct interaction between HOTAIR and genes with high RNAPII binding in their gene bodies, especially at their 3' ends or transcription end sites. Computational analysis suggests HOTAIR binds preferentially to the 3' ends of genes containing predicted strong RNA-RNA interactions with HOTAIR. Together, these results reveal a unique function for HOTAIR in hASC depot-specific regulation of gene expression.

Activin E-ACVR1C cross talk controls energy storage via suppression of adipose lipolysis in mice.

Body fat distribution is a heritable risk factor for cardiovascular and metabolic disease. In humans, rare Inhibin beta E (INHBE, activin E) loss-of-function variants are associated with a lower waist-to-hip ratio and protection from type 2 diabetes. Hepatic fatty acid sensing promotes INHBE expression during fasting and in obese individuals, yet it is unclear how the hepatokine activin E governs body shape and energy metabolism. Here, we uncover activin E as a regulator of adipose energy storage. By suppressing ß-agonist-induced lipolysis, activin E promotes fat accumulation and adipocyte hypertrophy and contributes to adipose dysfunction in mice. Mechanistically, we demonstrate that activin E elicits its effect on adipose tissue through ACVR1C, activating SMAD2/3 signaling and suppressing PPARG target genes. Conversely, loss of activin E or ACVR1C in mice increases fat utilization, lowers adiposity, and drives PPARG-regulated gene signatures indicative of healthy adipose function. Our studies identify activin E-ACVR1C as a metabolic rheostat promoting liver-adipose cross talk to restrain excessive fat breakdown and preserve fat mass during prolonged fasting, a mechanism that is maladaptive in obese individuals.

Harnessing tissue-specific genetic variation to dissect putative causal pathways between body mass index and cardiometabolic phenotypes.

Body mass index (BMI) is a complex disease risk factor known to be influenced by genes acting via both metabolic pathways and appetite regulation. In this study, we aimed to gain insight into the phenotypic consequences of BMI-associated genetic variants, which may be mediated by their expression in different tissues. First, we harnessed meta-analyzed gene expression datasets derived from subcutaneous adipose (n = 1257) and brain (n = 1194) tissue to identify 86 and 140 loci, respectively, which provided evidence of genetic colocalization with BMI. These two sets of tissue-partitioned loci had differential effects with respect to waist-to-hip ratio, suggesting that the way they influence fat distribution might vary despite their having very similar average magnitudes of effect on BMI itself (adipose = 0.0148 and brain = 0.0149 standard deviation change in BMI per effect allele). For instance, BMI-associated variants colocalized with TBX15 expression in adipose tissue (posterior probability [PPA] = 0.97), but not when we used TBX15 expression data derived from brain tissue (PPA = 0.04) This gene putatively influences BMI via its role in skeletal development. Conversely, there were loci where BMI-associated variants provided evidence of colocalization with gene expression in brain tissue (e.g., NEGR1, PPA = 0.93), but not when we used data derived from adipose tissue, suggesting that these genes might be more likely to influence BMI via energy balance. Leveraging these tissue-partitioned variant sets through a multivariable Mendelian randomization framework provided strong evidence that the brain-tissue-derived variants are predominantly responsible for driving the genetically predicted effects of BMI on cardiovascular-disease endpoints (e.g., coronary artery disease: odds ratio = 1.05, 95% confidence interval = 1.04-1.07, p = 4.67 × 10-14). In contrast, our analyses suggested that the adipose tissue variants might predominantly be responsible for the underlying relationship between BMI and measures of cardiac function, such as left ventricular stroke volume (beta = 0.21, 95% confidence interval = 0.09-0.32, p = 6.43 × 10-4).

The effect of hyperlipidemia and body fat distribution on subclinical left ventricular function in obesity: a cardiovascular magnetic resonance study.

BACKGROUND: Obesity is often associated with multiple comorbidities. However, whether obese subjects with hyperlipidemia in the absence of other complications have worse cardiac indices than metabolically healthy obese subjects is unclear. Therefore, we aimed to determine the effect of hyperlipidemia on subclinical left ventricular (LV) function in obesity and to evaluate the association of cardiac parameters with body fat distribution. MATERIALS AND METHODS: Ninety-two adults were recruited and divided into 3 groups: obesity with hyperlipidemia (n = 24, 14 males), obesity without hyperlipidemia (n = 25, 13 males), and c ntrols (n = 43, 25 males). LV strain parameters (peak strain (PS), peak diastolic strain rate (PDSR), peak systolic strain rate) derived from cardiovascular magnetic resonance tissue tracking were measured and compared. Dual-energy X-ray absorptiometer was used to measure body fat distribution. Correlations of hyperlipidemia and body fat distribution with LV strain were assessed by multivariable linear regression. RESULTS: Obese individuals with preserved LV ejection fraction showed lower global LV longitudinal, circumferential, and radial PS and longitudinal and circumferential PDSR than controls (all P < 0.05). Among obese patients, those with hyperlipidemia had lower longitudinal PS and PDSR and circumferential PDSR than those without hyperlipidemia (- 12.8 ± 2.9% vs. - 14.2 ± 2.7%, 0.8 ± 0.1 s-1 vs. 0.9 ± 0.3 s-1, 1.2 ± 0.2 s-1 vs. 1.4 ± 0.2 s-1; all P < 0.05). Multivariable linear regression demonstrated that hyperlipidemia was independently associated with circumferential PDSR (ß = - 0.477, P < 0.05) in obesity after controlling for growth differences, other cardiovascular risk factors, and central fat distribution. In addition, android fat had an independently negative relationship with longitudinal and radial PS (ß = - 0.486 and ß = - 0.408, respectively; all P < 0.05); and visceral fat was negatively associated with longitudinal PDSR (ß = - 0.563, P < 0.05). Differently, gynoid fat was positively correlated with circumferential PS and PDSR and radial PDSR (ß = 0.490, ß = 0.481, and ß = 0.413, respectively; all P < 0.05). CONCLUSION: Hyperlipidemia is independently associated with subclinical LV diastolic dysfunction in obesity. Central fat distribution (android and visceral fat) has a negative association, while peripheral fat distribution (gynoid fat) has a positive association on subclinical LV function. These results suggest that appropriate management of hyperlipidemia may be beneficial for obese patients, and that the differentiation of fat distribution in different regions may facilitate the precise management of obese patients. Clinical trials registration Effect of lifestyle intervention on metabolism of obese patients based on smart phone software (ChiCTR1900026476).

Sex-specific causality of MRI-derived body compositions on glycaemic traits: Mendelian randomization and observational study.

AIM: To investigate the sex-specific causality of body compositions in type 2 diabetes and related glycaemic traits using Mendelian randomization (MR). MATERIALS AND METHODS: We leveraged sex-specific summary-level statistics from genome-wide association studies for three adipose deposits adjusted for body mass index and height, including abdominal subcutaneous adipose tissue, visceral adipose tissue (VATadj) and gluteofemoral adipose tissue (GFATadj), measured by MRI (20 038 women; 19 038 men), and fat mass-adjusted appendicular lean mass (ALMadj) (244 730 women; 205 513 men) in the UK Biobank. Sex-specific statistics of type 2 diabetes were from the Diabetes Genetics Replication and Meta-analysis Consortium and those for fasting glucose and insulin were from the Meta-analyses of Glucose and Insulin-related Traits Consortium. Univariable and multivariable MR (MVMR) were performed. We also performed MR analyses of anthropometric traits and genetic association analyses using individual-level data of body composition as validation. RESULTS: Univariable MR analysis showed that, in women, higher GFATadj and ALMadj exerted a causally protective effect on type 2 diabetes (GFATadj: odds ratio [OR] 0.59, 95% confidence interval [CI; 0.50, 0.69]; ALMadj: OR 0.84, 95% CI [0.77, 0.91]) and VATadj to be riskier in glycaemic traits. MVMR showed that GFATadj retained a robust effect on type 2 diabetes (OR 0.57, 95% CI [0.42, 0.77]; P = 2.6 × 10-4 ) in women, while it was nominally significant in men (OR 0.58, 95% CI [0.35, 0.96]; P = 3.3 × 10-2 ), after adjustment for ASATadj and VATadj. MR analyses of anthropometric measures and genetic association analyses of glycaemic traits confirmed the results. CONCLUSIONS: Body composition has a sex-specific effect on type 2 diabetes, and higher GFATadj has an independent protective effect on type 2 diabetes in both sexes.

Effect of tirzepatide on body fat distribution pattern in people with type 2 diabetes.

AIMS: To describe the overall fat distribution patterns independent of body mass index (BMI) in participants with type 2 diabetes (T2D) in the SURPASS-3 MRI substudy by comparison with sex- and BMI-matched virtual control groups (VCGs) derived from the UK Biobank imaging study at baseline and Week 52. METHODS: For each study participant at baseline and Week 52 (N = 296), a VCG of ≥150 participants with the same sex and similar BMI was identified from the UK Biobank imaging study (N = 40 172). Average visceral adipose tissue (VAT), abdominal subcutaneous adipose tissue (aSAT) and liver fat (LF) levels and the observed standard deviations (SDs; standardized normal z-scores: z-VAT, z-aSAT and z-LF) were calculated based on the matched VCGs. Differences in z-scores between baseline and Week 52 were calculated to describe potential shifts in fat distribution pattern independent of weight change. RESULTS: Baseline fat distribution patterns were similar across pooled tirzepatide (5, 10 and 15 mg) and insulin degludec (IDeg) arms. Compared with matched VCGs, SURPASS-3 participants had higher baseline VAT (mean [SD] z-VAT +0.42 [1.23]; p < 0.001) and LF (z-LF +1.24 [0.92]; p < 0.001) but similar aSAT (z-aSAT -0.13 [1.11]; p = 0.083). Tirzepatide-treated participants had significant decreases in z-VAT (-0.18 [0.58]; p < 0.001) and z-LF (-0.54 [0.84]; p < 0.001) but increased z-aSAT (+0.11 [0.50]; p = 0.012). Participants treated with IDeg had a significant change in z-LF only (-0.46 [0.90]; p = 0.001), while no significant changes were observed for z-VAT (+0.13 [0.52]; p = 0.096) and z-aSAT (+0.09 [0.61]; p = 0.303). CONCLUSION: In this exploratory analysis, treatment with tirzepatide in people with T2D resulted in a significant reduction of z-VAT and z-LF, while z-aSAT was increased from an initially negative value, suggesting a possible treatment-related shift towards a more balanced fat distribution pattern with prominent VAT and LF loss.

Waistline to thigh circumference ratio as a predictor of MAFLD: a health care worker study with 2-year follow-up.

BACKGROUND: This study aimed to determine whether the waist-to-thigh ratio (WTTR) is associated with the incidence of metabolic-associated fatty liver disease (MAFLD) in health care workers. METHODS: There were 4517 health care workers with baseline data and results from 2 follow-up examinations. We divided the subjects into 3 groups according to baseline WTTR and used the Cox hazard regression model to estimate MAFLD risk. RESULTS: The WTTRs were categorized by tertiles at baseline using the values 1.58 and 1.66. Patients with higher WTTR tended to have significantly greater values for the following factors, body mass index (BMI), fasting blood glucose (FPG), systolic blood pressure, diastolic blood pressure, total cholesterol (TC), triglycerides (TG), low-density lipoprotein-cholesterol (LDL-C) and neck circumference. The incidence of MAFLD significantly increased with increasing WTTR tertiles (5.74%, 12.75% and 22.25% for the first, second and third tertiles, respectively, P < 0.05 for trend). Kaplan-Meier(K-M) survival analysis revealed a significant tendency towards increased MAFLD risk with increasing WTTR tertile. In the fully adjusted model, the hazard ratios (95% CIs) for MAFLD in the second, third WTTR tertiles compared with the first quartile were 2.17(1.58,2.98), 3.63(2.70,4.89), respectively, third neck circumference tertiles compared with the first quartile were 2.84(1.89,4.25), 8.95(6.00,13.35), respectively. Compared with those of individuals with a BMI > 23 kg/m2, the associations between WTTR and MAFLD incidence were more pronounced in subjects with a BMI < 23 kg/m2. Similarly, the difference in neck circumference was more pronounced in these patients with a BMI < 23 kg/m2. CONCLUSIONS: Our results revealed that the WTTR is an independent risk factor for MAFLD, and there was a dose‒response relationship between the WTTR and MAFLD risk. The neck circumference was significantly different in subjects with a BMI < 23 kg/m2. This approach provides a new way to predict the incidence rate of MAFLD.

Characteristics and correlation of body fat distribution and brachial-ankle pulse wave velocity in adults aged 20-59 years: a cross-sectional study.

BACKGROUND: Fat distribution is closely related to vascular stiffness. This study aimed to investigate age and sex differences in fat distribution and brachial-ankle pulse wave velocity (baPWV), and the association between fat parameters and baPWV. METHODS: A total of 10,811 participants aged 20-59 years were recruited. Measures included waist and hip circumference, waist-to-hip ratio (WHR), body mass index (BMI), percentage body fat (PBF), subcutaneous fat area (SFA), visceral fat area (VFA), and baPWV. RESULTS: The results confirm that fat accumulates with age and that men tend to carry more abdominal fat than women in the same age group. The findings also indicate that baPWV increases with age and is significantly higher in men than in women in the same age group. In addition, WHR, VFA, and baPWV were more strongly correlated than baPWV and BMI, SFA, and PBF. Finally, the effects of age, PBF, WHR, and VFA on baPWV were greater for the higher quantiles. CONCLUSIONS: There are age and sex differences in fat distribution and baPWV. Abdominal obesity is more closely linked to arterial stiffness than overall obesity, and people with higher baPWV are more affected by obesity parameters.

Sex differences in the associations between relative fat mass and all-cause and cardiovascular mortality: A population-based prospective cohort study.

BACKGROUND AND AIMS: The novel sex-specific anthropometric equation relative fat mass (RFM) is a new estimator of whole-body fat %. The study aimed to investigate the predictive role of RFM in cardiometabolic abnormalities, cardiovascular disease (CVD), all-cause and cardiovascular mortality, and explored potential sex differences. METHODS AND RESULTS: The study analyzed data from 26,754 adults in NHANES 1999-2010, with a median follow-up of 13.8 years. The correlation between RFM and body composition as well as fat distribution assessed by dual-energy X-ray absorptiometry was investigated. Weighted multivariable generalized linear models, Cox proportional hazards models and restricted cubic spline were applied to investigate the predictive role of RFM in metabolic markers, cardiovascular risk factors, CVD, all-cause and cardiovascular mortality. RFM exhibited a robust correlation with both whole-body fat % and trunk fat %. Higher RFM exhibited a stronger association with impaired glucose homeostasis, serum lipids, the incidence of hypertension, and coronary heart disease in males, while a stronger association with C-reactive protein in females. A U-shaped association between RFM and all-cause mortality was observed only in males. The hazard ratio (HR) of all-cause and cardiovascular mortality in males increased rapidly when RFM exceeded 30. However, in females, the HR of all-cause and cardiovascular mortality fluctuated until RFM exceeded 45, after which it increased rapidly. CONCLUSION: RFM was a sex-specific estimator for both general and central obesity, sex-specific differences in predicting cardiometabolic abnormalities and adverse events using RFM might be partially attributed to differences in body composition and fat distribution between sexes.

Correlation between serum trimethylamine-N-oxide and body fat distribution in middle-aged and older adults: a prospective cohort study.

BACKGROUND: Trimethylamine-N-oxide (TMAO) is linked with obesity, while limited evidence on its relationship with body fat distribution. Herein, we investigated the associations between serum TMAO and longitudinal change of fat distribution in this prospective cohort study. METHODS: Data of 1964 participants (40-75y old) from Guangzhou Nutrition and Health Study (GNHS) during 2008-2014 was analyzed. Serum TMAO concentration was quantified by HPLC-MS/MS at baseline. The body composition was assessed by dual-energy X-ray absorptiometry at each 3-y follow-up. Fat distribution parameters were fat-to-lean mass ratio (FLR) and trunk-to-leg fat ratio (TLR). Fat distribution changes were derived from the coefficient of linear regression between their parameters and follow-up duration. RESULTS: After an average of 6.2-y follow-up, analysis of covariance (ANCOVA) and linear regression displayed women with higher serum TMAO level had greater increments in trunk FLR (mean ± SD: 1.47 ± 4.39, P-trend = 0.006) and TLR (mean ± SD: 0.06 ± 0.24, P-trend = 0.011). Meanwhile, for women in the highest TMAO tertile, linear mixed-effects model (LMEM) analysis demonstrated the annual estimated increments (95% CI) were 0.03 (95% CI: 0.003 - 0.06, P = 0.032) in trunk FLR and 1.28 (95% CI: -0.17 - 2.73, P = 0.083) in TLR, respectively. In men, there were no similar significant observations. Sensitivity analysis yielded consistent results. CONCLUSION: Serum TMAO displayed a more profound correlation with increment of FLR and TLR in middle-aged and older community-dwelling women in current study. More and further studies are still warranted in the future. TRIAL REGISTRATION: NCT03179657.

The association between fat distribution and α1-acid glycoprotein levels among adult females in the United States.

BACKGROUND: Visceral fat accumulation and obesity-induced chronic inflammation have been proposed as early markers for multiple disease states, especially in women. Nevertheless, the potential impact of fat distribution on α1-acid glycoprotein(AGP), a marker of inflammation, remains unclear. This research was conducted to investigate the relationships among obesity, fat distribution, and AGP levels. METHODS: A cross-sectional observational study was performed using blood samples from adult females recruited through the National Health and Nutrition Examination Survey from 2015 to 2018. Serum levels of AGP were measured using the Tina-quant α-1-Acid Glycoprotein Gen.2 assay. Based on the fat distribution data obtained from dual-energy X-ray absorptiometry assessments, body mass index (BMI), total percent fat (TPF), android percent fat (APF), gynoid percent fat (GPF), android fat/gynoid fat ratio (AGR), visceral percent fat (VPF), subcutaneous percent fat (SPF), visceral fat/subcutaneous fat ratio (VSR) were used as dependent variables. To investigate the link between fat distribution and AGP, multivariate linear regression analysis was utilized. Furthermore, a sensitivity analysis was also performed. RESULTS: The present study included 2,295 participants. After adjusting for covariates, BMI, TPF, APF, GPF, VPF, and SPF were found to be positively correlated with AGP levels (BMI: ß = 23.65 95%CI:20.90-26.40; TPF: ß = 25.91 95%CI:23.02-28.80; APF: ß = 25.21 95%CI:22.49-27.93; GPF: ß = 19.65 95%CI:16.96-22.34; VPF: ß = 12.49 95%CI:9.08-15.90; SPF: ß = 5.69, 95%CI:2.89-8.49; AGR: ß = 21.14 95%CI:18.16-24.12; VSR: ß = 9.35 95%CI:6.11-12.59, all P < 0.0001). All the above indicators exhibited a positive dose-response relationship with AGP. In terms of fat distribution, both AGR and VSR showed positive associations with AGP (P for trend < 0.0001). In particular, when compared to individuals in tertile 1 of AGR, participants in tertiles 2 and 3 had 13.42 mg/dL (95% CI 10.66-16.18) and 21.14 mg/dL (95% CI 18.16-24.12) higher AGP levels, respectively. Participants in the highest tertile of VSR were more likely to exhibit a 9.35 mg/dL increase in AGP compared to those in the lowest tertile (95% CI 6.11-12.59). CONCLUSIONS: Overall, this study revealed a positive dose-dependent relationship between fat proportion/distribution and AGP levels in women. These findings suggest that physicians can associate abnormal serum AGP and obesity with allow timely interventions.

Common obesity-related anthropometric indices and the risk of gestational diabetes mellitus in a Chinese population: a prospective cohort study.

OBJECTIVE: Anthropometric measurement provides a simple, noninvasive approach to evaluate obesity in pregnant women. We aimed to develop a predictive model utilizing anthropometric index for gestational diabetes mellitus (GDM), the most common obesity-related complications during pregnancy. METHODS: A prospective cohort of 4709 women was enrolled in Qingdao, China. Logistic regression model was constructed to determine the association of body mass index (BMI), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT) in the first trimester (<14 weeks' gestation) with GDM. The discrimination ability for GDM was assessed using areas under the receiver operating characteristic (ROC) curve (AUC). Delong tests were performed to compare AUC values between different measures. RESULTS: The GDM incidence was 19.50%. GDM risk increased with VAT during early pregnancy, and the risk increased by 117% (OR = 2.17, 95% CI: 1.23-2.83) to 326% (OR = 4.26, 95% CI: 2.29-7.91) in pregnant women with the second quartile or above after adjusting for confounders (all p<.05). Combined index using VAT and BMI demonstrated superior predictive power for GDM compared with BMI alone (p<.05), but didn't differ from VAT (p>.05). Overall, VAT was positively correlated with GDM occurrence, outperforming BMI, WHR, WHtR and SAT in the predicative model. A first-trimester VAT cutoff of 27.05 mm might be promising for GDM risk stratification. CONCLUSIONS: First-trimester routine ultrasound screening may facilitate earlier identification and intervention of GDM. Pregnant women with VAT above the optimal threshold (27.05 mm) might benefit from targeted GDM monitoring.

Body composition, lifestyle, and depression: a prospective study in the UK biobank.

BACKGROUND: Obesity has been related to depression and adhering healthy lifestyle was beneficial to lower the risk of depression; however, little is known about the relationship between body composition and fat distribution with depression risk and the influence of body composition and fat distribution on the association of lifestyle and depression. Therefore, we aimed to investigate whether body composition and fat distribution were associated with the adverse events of depression and the relationship between lifestyle and depression. METHODS: We included 330,131 participants without depression at baseline in the UK Biobank (mean age, 56.9 years; 53.83% females). The assessment of depression was sourced from health outcomes across self-report, primary care, hospital inpatient data, and death data. Body composition was determined by bioelectrical impedance. Seven lifestyles (no current smoking, moderate alcohol consumption, regular physical activity, healthy diet, less sedentary behavior, healthy sleep pattern, and appropriate social connection) were used to generate a lifestyle score. RESULTS: During a median of 11.7 years of follow-up, 7576 incident depression occurred. All the body composition measures were positively associated with depression risk, with the Hazard ratios (HR) for the uppermost tertile (T3) versus the lowest tertile (T1) ranging from 1.26 (95% CI: 1.15-1.39) for trunk fat-free mass (TFFM) to 1.78 (1.62-1.97) for leg fat percentage (LFP). In addition, we found significant interactions between fat mass-related indices, especially leg fat mass (LFM) (p = 1.65 × 10-9), and lifestyle score on the risk of depression, for which the beneficial associations of a healthy lifestyle with the risk of depression were more evident among participants with low body fat measurement. CONCLUSIONS: High levels of body composition measures were associated with an increased depression risk. Adverse body composition measures may weaken the link between a healthy lifestyle and a reduced risk of depression.

Zonulin and copeptin relation to some metabolic markers in school-aged obese children.

BACKGROUND: Using Zonulin and Copeptin as potential obesity markers in children, hasn't yet been focused. AIM: To evaluate the association between serum levels of both Zonulin and Copeptin with the obesity markers, and to assess their role as metabolic disturbance predictors in obese children. METHODS: A case-control study comprised 111 Egyptian children (45 males and 66 females); aged 6-10 years to avoid the effect of puberty (prepubertal). They were classified according to their body mass index (BMI) percentiles into: 72 obese (BMI ≥ 95th ), and 39 control ones (BMI > 15th - <85th ), based on the Egyptian Growth Charts for children and adolescents. Anthropometric parameters and blood pressure were measured, and body composition analysis, lipid profile, Zonulin, and Copeptin levels were assessed. RESULTS: The obese group showed a significantly higher value of Copeptin and a lower value of Zonulin than the control one Also, the obese group showed significant negative correlations between Zonulin and both anthropometric obesity markers and body composition, whereas Copeptin showed significant positive ones. Moreover, significant positive correlations were found between Copeptin and both body weight and fat distribution. Insignificant correlations were observed between both serum Zonulin and Copeptin levels and blood pressure and lipid profile. CONCLUSION: Zonulin and Copeptin cannot be used as metabolic disturbance predictors, among Egyptian children, as they were insignificantly correlated with lipid profile or blood pressure.

Fat distribution measurements by chemical shift-encoded transition region extraction predict the risk of hyperglycaemia, dyslipidaemia and metabolic syndrome in mice.

Metabolically healthy or unhealthy obesity is closely related to metabolic syndrome (MetS). To validate a more accurate diagnostic method for obesity that reflects the risk of metabolic disorders in a pre-clinical mouse model, C57BL/6J mice were fed high-sucrose-high-fat and chow diets for 12 weeks to induce obesity. MRI was performed and analysed by chemical shift-encoded fat-water separation based on the transition region extraction method. Abdominal fat was divided into upper and lower abdominal regions at the horizontal lower border of the liver. Blood samples were collected, and the glucose level, lipid profile, liver function, HbA1c and insulin were tested. k-means clustering and stepwise logistic regression were applied to validate the diagnosis of hyperglycaemia, dyslipidaemia and MetS, and to ascertain the predictive effect of MRI-derived parameters to the metabolic disorders. Pearson or Spearman correlation was used to assess the relationship between MRI-derived parameters and metabolic traits. The receiver-operating characteristic curve was used to evaluate the diagnostic effect of each logistic regression model. A two-sided p value less than 0.05 was considered to indicate statistical significance for all tests. We made the precise diagnosis of obesity, dyslipidaemia, hyperglycaemia and MetS in mice. In all, 14 mice could be diagnosed as having MetS, and the levels of body weight, HbA1c, triglyceride, total cholesterol and low-density lipoprotein cholesterol were significantly higher than in the normal group. Upper abdominal fat better predicted dyslipidaemia (odds ratio, OR = 2.673; area under the receiver-operating characteristic curve, AUCROC = 0.9153) and hyperglycaemia (OR = 2.456; AUCROC = 0.9454), and the abdominal visceral adipose tissue (VAT) was better for predicting MetS risk (OR = 1.187; AUCROC = 0.9619). We identified the predictive effect of fat volume and distribution in dyslipidaemia, hyperglycaemia and MetS. The upper abdominal fat played a better predictive role for the risk of dyslipidaemia and hyperglycaemia, and the abdominal VAT played a better predictive role for the risk of MetS.

Metabolomics dissection of depression heterogeneity and related cardiometabolic risk.

BACKGROUND: A recent hypothesis postulates the existence of an 'immune-metabolic depression' (IMD) dimension characterized by metabolic dysregulations. Combining data on metabolomics and depressive symptoms, we aimed to identify depressions associated with an increased risk of adverse metabolic alterations. METHOD: Clustering data were from 1094 individuals with major depressive disorder in the last 6 months and measures of 149 metabolites from a 1H-NMR platform and 30 depressive symptoms (IDS-SR30). Canonical correlation analyses (CCA) were used to identify main independent metabolite-symptom axes of variance. Then, for the replication, we examined the association of the identified dimensions with metabolites from the same platform and cardiometabolic diseases in an independent population-based cohort (n = 6572). RESULTS: CCA identified an overall depression dimension and a dimension resembling IMD, in which symptoms such as sleeping too much, increased appetite, and low energy level had higher relative loading. In the independent sample, the overall depression dimension was associated with lower cardiometabolic risk, such as (i.e. per s.d.) HOMA-1B -0.06 (95% CI -0.09 - -0.04), and visceral adipose tissue -0.10 cm2 (95% CI -0.14 - -0.07). In contrast, the IMD dimension was associated with well-known cardiometabolic diseases such as higher visceral adipose tissue 0.08 cm2 (95% CI 0.04-0.12), HOMA-1B 0.06 (95% CI 0.04-0.09), and lower HDL-cholesterol levels -0.03 mmol/L (95% CI -0.05 - -0.01). CONCLUSIONS: Combining metabolomics and clinical symptoms we identified a replicable depression dimension associated with adverse metabolic alterations, in line with the IMD hypothesis. Patients with IMD may be at higher cardiometabolic risk and may benefit from specific treatment targeting underlying metabolic dysregulations.

The association between adiposity and atypical energy-related symptoms of depression: A role for metabolic dysregulations.

BACKGROUND: Adiposity has been shown to be linked with atypical energy-related symptoms (AES) of depression. We used genomics to separate the effect of adiposity from that of metabolic dysregulations to examine whether the link between obesity and AES is dependent on the presence of metabolic dysregulations. METHOD: Data were from NEO (n = 5734 individuals) and NESDA (n = 2238 individuals) cohorts, in which the Inventory of Depressive Symptomatology (IDS-SR30) was assessed. AES profile was based on four symptoms: increased appetite, increased weight, low energy level, and leaden paralysis. We estimated associations between AES and two genetic risk scores (GRS) indexing increasing total body fat with (metabolically unhealthy adiposity, GRS-MUA) and without (metabolically healthy adiposity, GRS-MHA) metabolic dysregulations. RESULTS: We validated that both GRS-MUA and GRS-MHA were associated with higher total body fat in NEO study, but divergently associated with biomarkers of metabolic health (e.g., fasting glucose and HDL-cholesterol) in both cohorts. In the pooled results, per standard deviation, GRS-MUA was specifically associated with a higher AES score (ß = 0.03, 95%CI: 0.01; 0.05), while there was no association between GRS-MHA and AES (ß = -0.01, 95%CI: -0.03; 0.01). CONCLUSION: These results suggest that the established link between adiposity and AES profile emerges in the presence of metabolic dysregulations, which may represent the connecting substrate between the two conditions.

Associations between plasma sulfur amino acids and specific fat depots in two independent cohorts: CODAM and The Maastricht Study.

PURPOSE: Sulfur amino acids (SAAs) have been associated with obesity and obesity-related metabolic diseases. We investigated whether plasma SAAs (methionine, total cysteine (tCys), total homocysteine, cystathionine and total glutathione) are related to specific fat depots. METHODS: We examined cross-sectional subsets from the CODAM cohort (n = 470, 61.3% men, median [IQR]: 67 [61, 71] years) and The Maastricht Study (DMS; n = 371, 53.4% men, 63 [55, 68] years), enriched with (pre)diabetic individuals. SAAs were measured in fasting EDTA plasma with LC-MS/MS. Outcomes comprised BMI, skinfolds, waist circumference (WC), dual-energy X-ray absorptiometry (DXA, DMS), body composition, abdominal subcutaneous and visceral adipose tissues (CODAM: ultrasound, DMS: MRI) and liver fat (estimated, in CODAM, or MRI-derived, in DMS, liver fat percentage and fatty liver disease). Associations were examined with linear or logistic regressions adjusted for relevant confounders with z-standardized primary exposures and outcomes. RESULTS: Methionine was associated with all measures of liver fat, e.g., fatty liver disease [CODAM: OR = 1.49 (95% CI 1.19, 1.88); DMS: OR = 1.51 (1.09, 2.14)], but not with other fat depots. tCys was associated with overall obesity, e.g., BMI [CODAM: ß = 0.19 (0.09, 0.28); DMS: ß = 0.24 (0.14, 0.34)]; peripheral adiposity, e.g., biceps and triceps skinfolds [CODAM: ß = 0.15 (0.08, 0.23); DMS: ß = 0.20 (0.12, 0.29)]; and central adiposity, e.g., WC [CODAM: ß = 0.16 (0.08, 0.25); DMS: ß = 0.17 (0.08, 0.27)]. Associations of tCys with VAT and liver fat were inconsistent. Other SAAs were not associated with body fat. CONCLUSION: Plasma concentrations of methionine and tCys showed distinct associations with different fat depots, with similar strengths in the two cohorts.

Association of total body fat and fat distribution with bone mineral density among children and adolescents aged 6-17 years from Guangzhou, China.

This study aimed to assess the associations of total body fat and fat distribution with bone mineral density (BMD) among children and adolescents in this cross-sectional study. A total of 1032 boys and 897 girls aged 6-17 years were enrolled between May 2019 and June 2019 in Guangzhou, China. BMD, total body fat (fat mass index [FMI] and body fat percentage [BF%]), and fat distribution (trunk-to-limb and android-to-gynoid ratios) were measured by dual-energy X-ray absorptiometry. Inverse probability of treatment weighting regression was used to explore the association between fat and BMD. Traditional regression of covariate adjustment was applied as sensitivity analysis. Regression with inverse probability weighting suggested BF% and android-to-gynoid ratio were negatively associated with BMD in boys (ß = - 0.12 and - 0.16, respectively; P < 0.05). Android-to-gynoid ratio was also inversely associated with BMD in girls (ß = - 0.08, P < 0.05). When stratified by age, the negative associations were retained in boys aged 12-17 years (ß = - 0.23 and - 0.25, respectively; P < 0.001). But for girls, it showed a positive association of FMI with BMD in the 6-9 years group (ß = 0.33, P < 0.001) and a negative association between the android-to-gynoid ratio and BMD in the 10-17 years group (ß = - 0.10, P < 0.05). Traditional regression supported the robustness of the results.  Conclusion: Total body fat is positively associated with BMD in younger girls but inversely associated in older boys. As for abdominal adipose, it is associated with lower BMD in both older boys and girls. What is Known: • The lean mass has been consistently positively associated with bone mineral density (BMD) among children and adolescents. However, the impact of fat mass on BMD remained controversial. • Beyond total body fat, site-specific fat mass, especially abdominal adiposity, might impede bone formation. What is New: • The associations of total body fat and fat distribution with BMD in children and adolescents were gender- and age-specific. • More attention should be paid to the abdominal fat accumulation to promote bone health in older children.

Age-related adiposity and beta-cell function: impact on prediabetes and diabetes prevalence in middle-aged and older Han Chinese adults.

PURPOSE: To investigate the effect of aging on the prevalence of prediabetes and diabetes, and the influence of aging on the associations among adipose mass, redistribution, ß cell function, and the prevalence of hyperglycaemia. METHOD: This urban-based cross-sectional study included 1033 Chinese Han people, aged 40-65 years. The abdominal subcutaneous fat area (SFA) and visceral fat area (VFA) were determined by magnetic resonance imaging. The prevalence rates of prediabetes and diabetes were analyzed according to age group (40-49, 50-59, and 60-65 years). The effects of aging on abdominal fat mass, adipose distribution, insulin action indexes were also assessed. RESULTS: Prediabetes and diabetes prevalence gradually increased with age. Both SFA and VFA increased, while SFA/VFA decreased, in the 50-59 and 60-65 years age groups compared to the 40-49 years group. Homeostatic model assessment of insulin resistance (HOMA-IR) increased with fat mass. Homeostatic model assessment of beta-cell function (HOMA-ß) and early-phase insulin secretion (∆I30/∆G30) were decreased in the 60-65 years group compared to the younger age groups. Increased age, VFA, and HOMA-IR, as well as decreased HOMA-ß, were risk factors for the development of prediabetes and diabetes. The associations between central obesity and the development of prediabetes and diabetes, but not the associations of SFA/VFA, HOMA-IR, and HOMA-ß with hyperglycaemia prevalence, weakened with age. CONCLUSIONS: The prevalence of prediabetes and diabetes increased with age. Central obesity may be related stronger to the development of hyperglycaemia in younger people.