Triglyceride profiling in adipose tissues from obese insulin sensitive, insulin resistant and type 2 diabetes mellitus individuals

Moderate-intensity Combined Training Induces Lipidomic Changes in Individuals With Obesity and Type 2 Diabetes

CONTEXT

Alterations in the lipid metabolism are linked to metabolic disorders such as insulin resistance (IR), obesity and type 2 diabetes (T2D). Regular exercise, particularly combined training (CT), is a well-known nonpharmacological treatment that combines aerobic (AT) and resistance (RT) training benefits. However, it is unclear whether moderate-intensity exercise without dietary intervention induces changes in lipid metabolism to promote a "healthy lipidome."

OBJECTIVE

The study aimed to investigate the effect of 16 weeks of CT on plasma and white adipose tissue in both sexes, middle-aged individuals with normal weight, obesity (OB), and T2D using an ultra-high performance liquid chromatography-mass spectrometry (UHPLC-MS) untargeted lipidomics approach.

METHODS

Body composition, maximum oxygen consumption (VO2max), strength, and biochemical markers were evaluated before and after the control/training period and correlated with lipid changes. CT consisted of 8 to 10 RT exercises, followed by 35 minutes of AT (45%-70% VO2max), 3 times a week for 16 weeks.

RESULTS

The CT significantly reduced the levels of saturated and monounsaturated fatty acid side-chains (SFA/MUFA) in sphingolipids, glycerolipids (GL) and glycerophospholipids (GP) as well as reducing fat mass, circumferences and IR. Increased levels of polyunsaturated fatty acids in GPs and GLs were also observed, along with increased fat-free mass, VO2 max, and strength (all P < .05) after training.

CONCLUSION

Our study revealed that 16 weeks of moderate-intensity CT remodeled the lipid metabolism in OB, and T2D individuals, even without dietary intervention, establishing a link between exercise-modulated lipid markers and mechanisms that reduce IR and obesity-related comorbidities.

Causal relationships of lifestyle behaviours and body fat distribution on diabetic microvascular complications: a Mendelian randomization study

Objectives

To determine the causal correlations of lifestyle behaviours and body fat distribution on diabetic microvascular complications through a Mendelian Randomization (MR).

Methods

Genetic variants significantly associated with lifestyle behaviours, abdominal obesity, generalized obesity and diabetic microvascular complications were extracted from the UK Biobank (UKB) and FinnGen. The inverse variance weighted (IVW) method was regarded as the primary method. The main results were presented in odds ratio (OR) per standard deviation (SD) increase, and a series of sensitivity analyses were also conducted to validate the stability of the results.

Results

There was a positive causal correlation between smoking and the development of diabetic retinopathy (OR = 1.16; 95%CI: 1.04-1.30; p = 0.01). All of the indicators representing abdominal obesity had a statistically significant causal association with diabetic microvascular complications. Concerning generalized obesity, there were significant causal associations of body mass index (BMI) on diabetic nephropathy (OR = 1.92; 95%CI: 1.58-2.33; p < 0.001), diabetic retinopathy (OR = 1.27; 95%CI: 1.15-1.40; p < 0.001), and diabetic neuropathy (OR = 2.60; 95%CI: 1.95-3.45; p < 0.001). Other indicators including leg fat mass (left), and arm fat mass (left) also had a significant positive causality with diabetic microvascular complications.

Conclusion

Our findings suggested that smoking has a genetically causal association with the development of diabetic retinopathy rather than diabetic nephropathy and diabetic neuropathy. In addition, both abdominal obesity and generalized obesity are risk factors for diabetic microvascular complications. To note, abdominal obesity represented by waist circumference (WC) is the most significant risk factor.

Obesity, dyslipidemia, and cardiovascular disease: A joint expert review from the Obesity Medicine Association and the National Lipid Association 2024

Background

This joint expert review by the Obesity Medicine Association (OMA) and National Lipid Association (NLA) provides clinicians an overview of the pathophysiologic and clinical considerations regarding obesity, dyslipidemia, and cardiovascular disease (CVD) risk.

Methods

This joint expert review is based upon scientific evidence, clinical perspectives of the authors, and peer review by the OMA and NLA leadership.

Results

Among individuals with obesity, adipose tissue may store over 50% of the total body free cholesterol. Triglycerides may represent up to 99% of lipid species in adipose tissue. The potential for adipose tissue expansion accounts for the greatest weight variance among most individuals, with percent body fat ranging from less than 5% to over 60%. While population studies suggest a modest increase in blood low-density lipoprotein cholesterol (LDL-C) levels with excess adiposity, the adiposopathic dyslipidemia pattern most often described with an increase in adiposity includes elevated triglycerides, reduced high density lipoprotein cholesterol (HDL-C), increased non-HDL-C, elevated apolipoprotein B, increased LDL particle concentration, and increased small, dense LDL particles.

Conclusions

Obesity increases CVD risk, at least partially due to promotion of an adiposopathic, atherogenic lipid profile. Obesity also worsens other cardiometabolic risk factors. Among patients with obesity, interventions that reduce body weight and improve CVD outcomes are generally associated with improved lipid levels. Given the modest improvement in blood LDL-C with weight reduction in patients with overweight or obesity, early interventions to treat both excess adiposity and elevated atherogenic cholesterol (LDL-C and/or non-HDL-C) levels represent priorities in reducing the risk of CVD.

Obesity, dyslipidemia, and cardiovascular disease: A joint expert review from the Obesity Medicine Association and the National Lipid Association 2024

BACKGROUND

This joint expert review by the Obesity Medicine Association (OMA) and National Lipid Association (NLA) provides clinicians an overview of the pathophysiologic and clinical considerations regarding obesity, dyslipidemia, and cardiovascular disease (CVD) risk.

METHODS

This joint expert review is based upon scientific evidence, clinical perspectives of the authors, and peer review by the OMA and NLA leadership.

RESULTS

Among individuals with obesity, adipose tissue may store over 50% of the total body free cholesterol. Triglycerides may represent up to 99% of lipid species in adipose tissue. The potential for adipose tissue expansion accounts for the greatest weight variance among most individuals, with percent body fat ranging from less than 5% to over 60%. While population studies suggest a modest increase in blood low-density lipoprotein cholesterol (LDL-C) levels with excess adiposity, the adiposopathic dyslipidemia pattern most often described with an increase in adiposity includes elevated triglycerides, reduced high-density lipoprotein cholesterol (HDL-C), increased non-HDL-C, elevated apolipoprotein B, increased LDL particle concentration, and increased small, dense LDL particles.

CONCLUSIONS

Obesity increases CVD risk, at least partially due to promotion of an adiposopathic, atherogenic lipid profile. Obesity also worsens other cardiometabolic risk factors. Among patients with obesity, interventions that reduce body weight and improve CVD outcomes are generally associated with improved lipid levels. Given the modest improvement in blood LDL-C with weight reduction in patients with overweight or obesity, early interventions to treat both excess adiposity and elevated atherogenic cholesterol (LDL-C and/or non-HDL-C) levels represent priorities in reducing the risk of CVD.

Identification of predictive biomarkers for endometrial cancer diagnosis and treatment response monitoring using plasma metabolome profiling

BACKGROUND

Endometrial cancer (EMC) is the most common female genital tract malignancy with an increasing prevalence in many countries including Japan, a fact that renders early detection and treatment necessary to protect health and fertility. Although early detection and treatment are necessary to further improve the prognosis of women with endometrial cancer, biomarkers that accurately reflect the pathophysiology of EMC patients are still unclear. Therefore, it is clinically critical to identify biomarkers to assess diagnosis and treatment efficacy to facilitate appropriate treatment and development of new therapies for EMC.

METHODS

In this study, wide-targeted plasma metabolome analysis was performed to identify biomarkers for EMC diagnosis and the prediction of treatment responses. The absolute quantification of 628 metabolites in plasma samples from 142 patients with EMC was performed using ultra-high-performance liquid chromatography with tandem mass spectrometry.

RESULTS

The concentrations of 111 metabolites increased significantly, while the concentrations of 148 metabolites decreased significantly in patients with EMC compared to healthy controls. Specifically, LysoPC and TGs, including unsaturated fatty acids, were reduced in patients with stage IA EMC compared to healthy controls, indicating that these metabolic profiles could be used as early diagnostic markers of EMC. In contrast, blood levels of amino acids such as histidine and tryptophan decreased as the risk of recurrence increased and the stages of EMC advanced. Furthermore, a marked increase in total TG and a decrease in specific TGs and free fatty acids including polyunsaturated fatty acids levels were observed in patients with EMC. These results suggest that the polyunsaturated fatty acids in patients with EMC are crucial for disease progression.

CONCLUSIONS

Our data identified specific metabolite profiles that reflect the pathogenesis of EMC and showed that these metabolites correlate with the risk of recurrence and disease stage. Analysis of changes in plasma metabolite profiles could be applied for the early diagnosis and monitoring of the course of treatment of EMC patients.

Statistical methods and resources for biomarker discovery using metabolomics

Metabolomics is a dynamic tool for elucidating biochemical changes in human health and disease. Metabolic profiles provide a close insight into physiological states and are highly volatile to genetic and environmental perturbations. Variation in metabolic profiles can inform mechanisms of pathology, providing potential biomarkers for diagnosis and assessment of the risk of contracting a disease. With the advancement of high-throughput technologies, large-scale metabolomics data sources have become abundant. As such, careful statistical analysis of intricate metabolomics data is essential for deriving relevant and robust results that can be deployed in real-life clinical settings. Multiple tools have been developed for both data analysis and interpretations. In this review, we survey statistical approaches and corresponding statistical tools that are available for discovery of biomarkers using metabolomics.

Characterization of lipid signatures in the plasma and insulin-sensitive tissues of the C57BL/6J mice fed on obesogenic diets

Diet-induced obesity mouse models are widely utilized to investigate the underlying mechanisms of dyslipidemia, glucose intolerance, insulin resistance, hepatic steatosis, and type 2 diabetes mellitus (T2DM), as well as for screening potential drug compounds. However, there is limited knowledge regarding specific signature lipids that accurately reflect dietary disorders. In this study, we aimed to identify key lipid signatures using LC/MS-based untargeted lipidomics in the plasma, liver, adipose tissue (AT), and skeletal muscle tissues (SKM) of male C57BL/6J mice that were fed chow, LFD, or obesogenic diets (HFD, HFHF, and HFCD) for a duration of 20 weeks. Furthermore, we conducted a comprehensive lipid analysis to assess similarities and differences with human lipid profiles. The mice fed obesogenic diets exhibited weight gain, glucose intolerance, elevated BMI, glucose and insulin levels, and a fatty liver, resembling characteristics of T2DM and obesity in humans. In total, we identified approximately 368 lipids in plasma, 433 in the liver, 493 in AT, and 624 in SKM. Glycerolipids displayed distinct patterns across the tissues, differing from human findings. However, changes in sphingolipids, phospholipids, and the expression of inflammatory and fibrotic genes showed similarities to reported human findings. Significantly modulated pathways in the obesogenic diet-fed groups included ceramide de novo synthesis, sphingolipid remodeling, and the carboxylesterase pathway, while lipoprotein-mediated pathways were minimally affected.

FALCON systematically interrogates free fatty acid biology and identifies a novel mediator of lipotoxicity

Cellular exposure to free fatty acids (FFAs) is implicated in the pathogenesis of obesity-associated diseases. However, there are no scalable approaches to comprehensively assess the diverse FFAs circulating in human plasma. Furthermore, assessing how FFA-mediated processes interact with genetic risk for disease remains elusive. Here, we report the design and implementation of fatty acid library for comprehensive ontologies (FALCON), an unbiased, scalable, and multimodal interrogation of 61 structurally diverse FFAs. We identified a subset of lipotoxic monounsaturated fatty acids associated with decreased membrane fluidity. Furthermore, we prioritized genes that reflect the combined effects of harmful FFA exposure and genetic risk for type 2 diabetes (T2D). We found that c-MAF-inducing protein (CMIP) protects cells from FFA exposure by modulating Akt signaling. In sum, FALCON empowers the study of fundamental FFA biology and offers an integrative approach to identify much needed targets for diverse diseases associated with disordered FFA metabolism.

Lipidome remodeling activities of DPA-EA in palmitic acid-stimulated HepG2 cells and the in vivo anti-obesity effect of the DPA-EA and DHA-EA mixture prepared from algae oil

Background: The nuclear receptor Nur77 has been demonstrated to play a vital role in the inflammatory response and cellular metabolisms, and its ligands exhibit efficacy in the treatment of inflammation-related diseases (e.g., improving mouse acute lung injury (ALI) and obesity. Recently, ω-3 polyunsaturated fatty acid-ethanolamine derivatives (ω-3 PUFA-EAs), including DPA-EA and DHA-EA, have been reported as new Nur77-targeting anti-inflammatory agents. However, the lipid-lowering effect of ω-3 PUFA-EAs is still unknown, and lipid profile changes induced by Nur77-targeting anti-inflammatory agents also remain unclear.

Objective: This study aimed to evaluate the lipid-lowering effect and the underlying mechanism of DPA-EA acting as Nur77-targeting anti-inflammatory agents. It also aimed to investigate the in vitro and in vivo lipid-lowering effects of the DPA-EA and DHA-EA mixture prepared from algae oil.

Methods: The in vitro lipid-lowing effect of DPA-EA and its mixture with DHA-EA was first evaluated in palmitic acid-stimulated HepG2 Cells. To confirm the lipid-lowering effect and explore the underlying mechanism, we performed untargeted lipidomic analysis using ultra-performance liquid chromatography/triple quadrupole-time-of-flight (TOF) mass spectrometry coupled with multivariate statistical analysis, with another Nur77-targeting anti-inflammatory compound Celastrol (Cel) as a reference. Finally, we examined the anti-obesity effect of the DPA-EA and DHA-EA mixture synthesized from algae oil in a high-fat diet (HFD)-fed mice model.

Results: DPA-EA significantly alleviated lipid accumulation with lower toxicity than Celastrol. Nur77-targeting compounds DPA-EA and Celastrol could simultaneously reduce 14 lipids (9 TGs, 2 PCs, 1 PA, 1 SM, and 1 LacCer) and increase 13 lipids (4 DGs, 6 LPEs, 2 PEs, and 1PC) in Pal-stimulated HepG2 cells. However, Cer lipids were more sensitive to DPA-EA, while the over-downregulation of SM lipids might be associated with the off-target toxicity of Celastrol. The mixture of DPA-EA and DHA-EA synthesized from algae oil could significantly decrease TG, TC, and LDL levels and increase HDL levels in HFD-fed mice, exerting an excellent anti-obesity effect.

Conclusion: Nur77-targeting anti-inflammatory compound DAP-EA could promote the hydrolysis of PEs and TGs to ameliorate lipid accumulation. The DPA-EA and DHA-EA mixture prepared from algae oil might be a potential therapeutic agent for obesity and other inflammation-related diseases.

FALCON systematically interrogates free fatty acid biology and identifies a novel mediator of lipotoxicity

Cellular exposure to free fatty acids (FFA) is implicated in the pathogenesis of obesity-associated diseases. However, studies to date have assumed that a few select FFAs are representative of broad structural categories, and there are no scalable approaches to comprehensively assess the biological processes induced by exposure to diverse FFAs circulating in human plasma. Furthermore, assessing how these FFA- mediated processes interact with genetic risk for disease remains elusive. Here we report the design and implementation of FALCON (Fatty Acid Library for Comprehensive ONtologies) as an unbiased, scalable and multimodal interrogation of 61 structurally diverse FFAs. We identified a subset of lipotoxic monounsaturated fatty acids (MUFAs) with a distinct lipidomic profile associated with decreased membrane fluidity. Furthermore, we developed a new approach to prioritize genes that reflect the combined effects of exposure to harmful FFAs and genetic risk for type 2 diabetes (T2D). Importantly, we found that c-MAF inducing protein (CMIP) protects cells from exposure to FFAs by modulating Akt signaling and we validated the role of CMIP in human pancreatic beta cells. In sum, FALCON empowers the study of fundamental FFA biology and offers an integrative approach to identify much needed targets for diverse diseases associated with disordered FFA metabolism.

Highlights

FALCON (Fatty Acid Library for Comprehensive ONtologies) enables multimodal profiling of 61 free fatty acids (FFAs) to reveal 5 FFA clusters with distinct biological effectsFALCON is applicable to many and diverse cell typesA subset of monounsaturated FAs (MUFAs) equally or more toxic than canonical lipotoxic saturated FAs (SFAs) leads to decreased membrane fluidityNew approach prioritizes genes that represent the combined effects of environmental (FFA) exposure and genetic risk for diseaseC-Maf inducing protein (CMIP) is identified as a suppressor of FFA-induced lipotoxicity via Akt-mediated signaling.

The relationship between the CUN-BAE body fatness index and incident diabetes: a longitudinal retrospective study

BACKGROUND

The Clínica Universidad de Navarra-Body Adiposity Estimator (CUN-BAE) index has been recommended as an ideal indicator of body fat and exhibited significant correlation with cardiometabolic risk factors. However, whether the CUN-BAE index correlates with incident diabetes in Asian populations is unknown. Therefore, this longitudinal study was designed to evaluate the association between baseline CUN-BAE index and type 2 diabetes mellitus (T2DM).

METHODS

This retrospective longitudinal study involved 15,464 participants of 18-79 years of age in the NAGALA (NAfld in the Gifu Area Longitudinal Analysis) study over the period of 2004-2015. Cox proportional hazards regression was performed to test the relationship between the baseline CUN-BAE index and diabetes incidence. Further stratification analysis was conducted to ensure that the results were robust. The diagnostic utility of the CUN-BAE index was tested by the receiver operating characteristic (ROC) curve.

RESULTS

Over the course of an average follow-up of 5.4 years, 373 (2.41%) participants developed diabetes. A higher diabetes incidence was associated with higher CUN-BAE quartiles (P for trend< 0.001). Each 1 unit increase in CUN-BAE index was associated with a 1.08-fold and 1.14-fold increased risk of diabetes after adjustment for confounders in males and females, respectively (both P < 0.001). Stratification analysis demonstrated a consistent positive correlation between baseline CUN-BAE and diabetes incidence. Moreover, based on ROC analysis, CUN-BAE exhibited a better capacity for diabetes prediction than both body mass index (BMI) and waist circumference (WC) in both sexes.

CONCLUSIONS

The baseline CUN-BAE level was independently related to the incidence of diabetes. Increased adiposity determined by CUN-BAE could be used as a strong nonlaboratory predictor of incident diabetes in clinical practice.

Ethyl acetate extract of Caesalpinia sappan L. for the treatment of atherosclerosis in ApoE-/- mice and its mechanism

The ethyl acetate extract of Caesalpinia sappan L. is a traditional Chinese medicine extract commonly used in the treatment of atherosclerosis. However, the mechanism of its use in the treatment of AS is not yet clear, which seriously affects the wide-scale application of this drug. In this study, a combination of metabolomics and lipidomics was used to analyze cardiac tissue to obtain differential metabolites and differential lipid molecules, bioinformatic analysis was performed on the significantly different metabolites and subclass analysis, cluster analysis, and chain length and chain saturation analyses were performed on screened lipid molecules showing significant differences. A correlation network diagram of the screened differential metabolites and differential lipid molecules was constructed. Hematoxylin and eosin staining of thoracic aorta in rats confirmed its therapeutic effect. This study found that the ethyl acetate extract of C. sappan L. upregulates D-mannose through the lysosome pathway, enhances lysosomal function, mediates autophagy, and indirectly regulates the levels of lipid subtypes such as lysophosphatidylinositol and phosphatidylserine, thereby improving AS.

Lonicerae Japonicae Flos extract and chlorogenic acid attenuates high-fat-diet- induced prediabetes via CTRPs-AdipoRs-AMPK/PPARα axes

Prediabetes is considered an important reversible checkpoint in T2DM development, which can be delayed and prevented by early interventions. Lonicerae Japonicae Flos (LJF), an edible-medicinal herb, is rich in chlorogenic acid (CGA, 5-O-caffeoylquinic acid) and exerts anti-diabetes effects, but its role in prediabetes remains unclear. The purpose of this study was to explore the effects of LJF extract and CGA on rat with prediabetes. Sprague-Dawley rats were given high-fat diet (HFD) to induce prediabetes, and glycolipid metabolism parameters and molecular mechanisms were evaluated. LJF (the LJF extract treatment group) and CGA (the pure CGA treatment group) significantly attenuated HFD-induced prediabetes with impaired glucose tolerance and dyslipidemia, but their mechanisms of action are not exactly the same. Specifically, LJF prioritizes increasing protective lipid species [such as increasing blood polyunsaturated fatty acids (PUFA)-containing diacylglycerol (DAG) species, high-density lipoprotein-cholesterol (HDL-C)], whereas CGA prioritizes reducing detrimental lipid species [such as saturated fatty acid-containing DAG species, low-density lipoprotein-cholesterol (LDL-C), total cholesterol (TC)]. In addition, CGA significantly increased the content of blood very-long-chain fatty-acid (VLCFA)-containing ceramides species. This could be explained mechanically by a distinction between LJF and CGA's effects on C1q/TNF-related proteins (CTRPs) which activate adiponectin receptors, triggering several downstream reactions. Because both LJF and CGA upregulated liver expression of adiponectin receptors (AdipoR1 and AdipoR2) and enhanced the activity of downstream AMPK. LJF also increased serum levels of CTRP3 and CTRP9, especially CTRP9, whereas CGA had higher serum CTRP3 and upregulated liver PPARa expression. Additionally, ELOVL6 expression in the liver was greater in CGA than LJF. This study demonstrates that LJF and CGA exert hypoglycemic and lipid modulation capacity to prevent prediabetes may through the CTRPs-AdipoRs-AMPK/PPARα axes and promoting ELOVL6 protein expression.

Comparing the Metabolic Profiles Associated with Fitness Status between Insulin-Sensitive and Insulin-Resistant Non-Obese Individuals

(1) Background: Young non-obese insulin-resistant (IR) individuals could be at risk of developing metabolic diseases including type 2 diabetes mellitus. The protective effect of physical activity in this apparently healthy group is expected but not well characterized. In this study, clinically relevant metabolic profiles were determined and compared among active and sedentary insulin-sensitive (IS) and IR young non-obese individuals. (2) Methods: Data obtained from Qatar Biobank for 2110 young (20-30 years old) non-obese (BMI ≤ 30) healthy participants were divided into four groups, insulin-sensitive active (ISA, 30.7%), insulin-sensitive sedentary (ISS, 21.4%), insulin-resistant active (IRA, 20%), and insulin-resistant sedentary (IRS, 23.3%), using the homeostatic model assessment of insulin resistance (HOMA-IR) and physical activity questionnaires. The effect of physical activity on 66 clinically relevant biochemical tests was compared among the four groups using linear models. (3) Results: Overall, non-obese IR participants had significantly (p ≤ 0.001) worse vital signs, blood sugar profiles, inflammatory markers, liver function, lipid profiles, and vitamin D levels than their IS counterparts. Physical activity was positively associated with left handgrip (p ≤ 0.01) and levels of creatine kinase (p ≤ 0.001) and creatine kinase-2 (p ≤ 0.001) in both IS and IR subjects. Furthermore, physical activity was positively associated with levels of creatinine (p ≤ 0.01) and total vitamin D (p = 0.006) in the IR group and AST (p = 0.001), folate (p = 0.001), and hematocrit (p = 0.007) in the IS group. Conversely, physical inactivity was negatively associated with the white blood cell count (p = 0.001) and an absolute number of lymphocytes (p = 0.003) in the IR subjects and with triglycerides (p = 0.005) and GGT-2 (p ≤ 0.001) in the IS counterparts. (4) Conclusions: An independent effect of moderate physical activity was observed in non-obese apparently healthy individuals a with different HOMA-IR index. The effect was marked by an improved health profile including higher vitamin D and lower inflammatory markers in IRA compared to IRS, and a higher oxygen carrying capacity and lipid profile in ISA compared to the ISS counterparts.

In Vitro and In Vivo Validation of GATA-3 Suppression for Induction of Adipogenesis and Improving Insulin Sensitivity

Impaired adipogenesis is associated with the development of insulin resistance and an increased risk of type 2 diabetes (T2D). GATA Binding Protein 3 (GATA3) is implicated in impaired adipogenesis and the onset of insulin resistance. Therefore, we hypothesize that inhibition of GATA3 could promote adipogenesis, restore healthy fat distribution, and enhance insulin signaling. Primary human preadipocytes were treated with GATA3 inhibitor (DNAzyme hgd40). Cell proliferation, adipogenic capacity, gene expression, and insulin signaling were measured following well-established protocols. BALB/c mice were treated with DNAzyme hgd40 over a period of 2 weeks. Liposomes loaded with DNAzyme hgd40, pioglitazone (positive), or vehicle (negative) controls were administered subcutaneously every 2 days at the right thigh. At the end of the study, adipose tissues were collected and weighed from the site of injection, the opposite side, and the omental depot. Antioxidant enzyme (superoxide dismutase and catalase) activities were assessed in animals’ sera, and gene expression was measured using well-established protocols. In vitro GATA3 inhibition induced the adipogenesis of primary human preadipocytes and enhanced insulin signaling through the reduced expression of p70S6K. In vivo GATA3 inhibition promoted adipogenesis at the site of injection and reduced MCP-1 expression. GATA3 inhibition also reduced omental tissue size and PPARγ expression. These findings suggest that modulating GATA3 expression offers a potential therapeutic benefit by correcting impaired adipogenesis, promoting healthy fat distribution, improving insulin sensitivity, and potentially lowering the risk of T2D.

Identification of Prognostic Metabolomic Biomarkers at the Interface of Mortality and Morbidity in Pre-Existing TB Cases Infected With SARS-CoV-2

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection currently remains one of the biggest global challenges that can lead to acute respiratory distress syndrome (CARDS) in severe cases. In line with this, prior pulmonary tuberculosis (TB) is a risk factor for long-term respiratory impairment. Post-TB lung dysfunction often goes unrecognized, despite its relatively high prevalence and its association with reduced quality of life. In this study, we used a metabolomics analysis to identify potential biomarkers that aid in the prognosis of COVID-19 morbidity and mortality in post-TB infected patients. This analysis involved blood samples from 155 SARS-CoV-2 infected adults, of which 23 had a previous diagnosis of TB (post-TB), while 132 did not have a prior or current TB infection. Our analysis indicated that the vast majority (~92%) of post-TB individuals showed severe SARS-CoV-2 infection, required intensive oxygen support with a significantly high mortality rate (52.2%). Amongst individuals with severe COVID-19 symptoms, we report a significant decline in the levels of amino acids, notably the branched chains amino acids (BCAAs), more so in the post-TB cohort (FDR <= 0.05) in comparison to mild and asymptomatic cases. Indeed, we identified betaine and BCAAs as potential prognostic metabolic biomarkers of severity and mortality, respectively, in COVID-19 patients who have been exposed to TB. Moreover, we identified serum alanine as an important metabolite at the interface of severity and mortality. Hence, our data associated COVID-19 mortality and morbidity with a long-term metabolically driven consequence of TB infection. In summary, our study provides evidence for a higher mortality rate among COVID-19 infection patients who have history of prior TB infection diagnosis, which mandates validation in larger population cohorts.

Metabolomic signatures of low- and high-adiposity neonates differ based on maternal BMI

Maternal obesity [body mass index (BMI) > 30 kg/m²] is associated with greater neonatal adiposity, cord blood (CB) insulin levels, and a proinflammatory phenotype at birth, contributing to risk of future cardiometabolic disease in the offspring. Variation in neonatal adiposity within maternal BMI groups is underappreciated, and it remains unclear whether the metabolic impairments at birth are an outcome of maternal obesity or excess fetal fat accrual. We examined the hypothesis that CB metabolites associated with fetal fat accrual differ between offspring of normal-weight and obese women. Umbilical venous blood was collected at the time of scheduled cesarean delivery from 50 normal-weight women (LE; pregravid BMI = 22.3 ± 1.7 kg/m²) and 50 obese women (OB; BMI = 34.5 ± 3.0 kg/m²). Neonatal adiposity was estimated from flank skinfold thickness. The first (low adiposity, LA) and third (high adiposity, HA) tertiles of neonatal %body fat were used to create four groups: OBLA, OBHA, LELA, and LEHA. CB metabolites were measured via untargeted metabolomics. Broadly, the LA offspring of OB women (OBLA) metabolite signature differed from other groups. Lauric acid (C12:0) was 82-118% higher in OBLA vs. all other groups [false discovery rate (FDR) < 0.01]. Several other fatty acids, including palmitate, stearate, and linoleate, were higher in OBLA vs. OBHA groups. CB metabolites, such as lauric acid, a medium-chain fatty acid that may improve insulin sensitivity, were associated with neonatal adiposity differently between offspring of women with and without obesity. Changes in metabolically active lipids at birth may have long-term consequences for offspring metabolism.NEW & NOTEWORTHY Using untargeted metabolomics in 100 newborns, we found that cord blood metabolite signatures associated with neonatal adiposity differed between offspring of women with and without obesity.

Metabolic risk factors of ovarian cancer: a review

Ovarian cancer continues to be the leading cause of death from gynecological cancers. Despite inconsistent results, patients with metabolic abnormalities, including obesity and diabetes mellitus (DM), have poorer outcomes, showing a correlation with ovarian cancer incidence and ovarian cancer survival. Since ovarian cancer is the most common cancer in women, and considering the increasing prevalence of obesity and DM, this paper reviews the literature regarding the relationship between the aforementioned metabolic derangements and ovarian cancer, with a focus on ovarian cancer incidence, mortality, and likely mechanisms behind them. Several systematic reviews and meta-analyses have shown that obesity is associated with a higher incidence and poorer survival in ovarian cancer. Although more studies are required to investigate the etiological relation of DM and ovarian cancer, sufficient biological evidence indicates poorer outcomes and shorter survival in DM women with ovarian cancer. A variety of pathologic factors may contribute to ovarian cancer risk, development, and survival, including altered adipokine expression, increased levels of circulating growth factors, altered levels of sex hormones, insulin resistance, hyperinsulinemia, and chronic inflammation. Thus, obesity and DM, as changeable risk factors, can be targeted for intervention to prevent ovarian cancer and improve its outcomes.

Fibroblast growth factor 21 reverses high‐fat diet‐induced impairment of vascular function via the anti‐oxidative pathway in ApoE knockout mice

Circulating endothelial progenitor cells (EPCs), which function in vascular repair, are the markers of endothelial dysfunction and vascular health. Fibroblast growth factor 21 (FGF21), a liver‐secreted protein, plays a crucial role in glucose homeostasis and lipid metabolism. FGF21 has been reported to attenuate the progression of atherosclerosis, but its impact on EPCs under high oxidative stress conditions remains unclear. In vitro studies showed that the β‐klotho protein was expressed in cultured EPCs and that its expression was upregulated by FGF21 treatment. Hydrogen peroxide (H₂O₂)‐induced oxidative stress impaired EPC function, including cell viability, migration and tube formation. Pretreatment with FGF21 restored the functions of EPCs after the exposure to H₂O₂. Administration of N(ω)‐nitro‐L‐arginine methyl ester (L‐NAME), an inhibitor of nitric oxide synthase, inhibited the effects of FGF21 in alleviating oxidative injury by suppressing endothelial nitric oxide synthase (eNOS). In an in vivo study, the administration of FGF21 significantly reduced total cholesterol (TC) and blood glucose levels in apolipoprotein E (ApoE)‐deficient mice that were fed a high‐fat diet (HFD). Endothelial function, as reflected by acetylcholine‐stimulated aortic relaxation, was improved after FGF21 treatment in ApoE‐deficient mice. Analysis of mRNA levels in the aorta indicated that FGF21 increased the mRNA expression of eNOS and upregulated the expression of the antioxidant genes superoxide dismutase (SOD)1 and SOD2 in ApoE‐deficient mice. These data suggest that FGF21 improves EPC functions via the Akt/eNOS/nitric oxide (NO) pathway and reverses endothelial dysfunction under oxidative stress. Therefore, administration of FGF21 may ameliorate a HFD‐induced vascular injury in ApoE‐deficient mice.

Serum metabolite profiling yields insights into health promoting effect of A. muciniphila in human volunteers with a metabolic syndrome

Reduction of A. muciniphila relative abundance in the gut microbiota is a widely accepted signature associated with obesity-related metabolic disorders. Using untargeted metabolomics profiling of fasting plasma, our study aimed at identifying metabolic signatures associated with beneficial properties of alive and pasteurized A. muciniphila when administrated to a cohort of insulin-resistant individuals with metabolic syndrome. Our data highlighted either shared or specific alterations in the metabolome according to the form of A. muciniphila administered with respect to a control group. Common responses encompassed modulation of amino acid metabolism, characterized by reduced levels of arginine and alanine, alongside several intermediates of tyrosine, phenylalanine, tryptophan, and glutathione metabolism. The global increase in levels of acylcarnitines together with specific modulation of acetoacetate also suggested induction of ketogenesis through enhanced β-oxidation. Moreover, our data pinpointed some metabolites of interest considering their emergence as substantial compounds pertaining to health and diseases in the more recent literature.

Metabolic Signatures of Type 2 Diabetes Mellitus and Hypertension in COVID-19 Patients With Different Disease Severity

Introduction: Increased COVID-19 disease severity is higher among patients with type 2 diabetes mellitus and hypertension. However, the metabolic pathways underlying this association are not fully characterized. This study aims to identify the metabolic signature associated with increased COVID-19 severity in patients with diabetes mellitus and hypertension. Methods: One hundred and fifteen COVID-19 patients were divided based on disease severity, diabetes status, and hypertension status. Targeted metabolomics of serum samples from all patients was performed using tandem mass spectrometry followed by multivariate and univariate models. Results: Reduced levels of various triacylglycerols were observed with increased disease severity in the diabetic patients, including those containing palmitic (C16:0), docosapentaenoic (C22:5, DPA), and docosahexaenoic (C22:6, DHA) acids (FDR < 0.01). Functional enrichment analysis revealed triacylglycerols as the pathway exhibiting the most significant changes in severe COVID-19 in diabetic patients (FDR = 7.1 × 10^-27). Similarly, reduced levels of various triacylglycerols were also observed in hypertensive patients corresponding with increased disease severity, including those containing palmitic, oleic (C18:1), and docosahexaenoic acids. Functional enrichment analysis revealed long-chain polyunsaturated fatty acids (n-3 and n-6) as the pathway exhibiting the most significant changes with increased disease severity in hypertensive patients (FDR = 0.07). Conclusions: Reduced levels of triacylglycerols containing specific long-chain unsaturated, monounsaturated, and polyunsaturated fatty acids are associated with increased COVID-19 severity in diabetic and hypertensive patients, offering potential novel diagnostic and therapeutic targets.

Untargeted Metabolomics Analysis of the Serum Metabolic Signature of Childhood Obesity

Obesity rates among children are growing rapidly worldwide, placing massive pressure on healthcare systems. Untargeted metabolomics can expand our understanding of the pathogenesis of obesity and elucidate mechanisms related to its symptoms. However, the metabolic signatures of obesity in children have not been thoroughly investigated. Herein, we explored metabolites associated with obesity development in childhood. Untargeted metabolomic profiling was performed on fasting serum samples from 27 obese Caucasian children and adolescents and 15 sex- and age-matched normal-weight children. Three metabolomic assays were combined and yielded 726 unique identified metabolites: gas chromatography–mass spectrometry (GC–MS), hydrophilic interaction liquid chromatography coupled to mass spectrometry (HILIC LC–MS/MS), and lipidomics. Univariate and multivariate analyses showed clear discrimination between the untargeted metabolomes of obese and normal-weight children, with 162 significantly differentially expressed metabolites between groups. Children with obesity had higher concentrations of branch-chained amino acids and various lipid metabolites, including phosphatidylcholines, cholesteryl esters, triglycerides. Thus, an early manifestation of obesity pathogenesis and its metabolic consequences in the serum metabolome are correlated with altered lipid metabolism. Obesity metabolite patterns in the adult population were very similar to the metabolic signature of childhood obesity. Identified metabolites could be potential biomarkers and used to study obesity pathomechanisms.

Recombinant human GLP-1 beinaglutide regulates lipid metabolism of adipose tissues in diet-induced obese mice

GLP-1 analogs are a class of glucose-lowering agents with multiple benefits in diabetes, but its role in adipose tissues remains to be elucidated. The aim of this study was to determine the action of recombinant human GLP-1 (rhGLP-1) Beinaglutide (BN) in the insulin sensitivity and lipid metabolism of adipose tissues. We have shown that, after BN injection, obese mice displayed lower body weight, fat mass, and plasma lipid levels. In addition, BN promoted the insulin sensitivity in the white adipose tissues. Furthermore, we have found that the BN treatment caused significant changes in content and composition of different lipid classes, including glycerolipids, glycerophospholipids, and sphingolipids, as well as expression of genes in lipid metabolic pathways in the adipose tissues. Taken together, our data demonstrate that BN could resist HFD-induced obesity by targeting the composition of major lipid classes and the expression of genes in lipid metabolism of adipose tissues.

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Recombinant human GLP-1 Beinaglutide (BN) reduces high-fat-diet-induced obesity

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BN increases insulin sensitivity of adipocytes in vivo and in vitro

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BN alters lipidomic and transcriptomic profiles in adipose tissues of obese mice

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BN promotes thermogenic gene expression in adipose tissues

One-anastomosis gastric bypass modulates the serum levels of pro- and anti-inflammatory oxylipins, which may contribute to the resolution of inflammation

BACKGROUND/OBJECTIVES

Oxylipins are polyunsaturated fatty acid derivatives involved in the regulation of various processes, including chronic inflammation, insulin resistance and hepatic steatosis. They can be synthesized in various tissues, including adipose tissue. There is some evidence that obesity is associated with the deregulation of serum oxylipin levels. The aim of this study was to evaluate the effect of bariatric surgery (one-anastomosis gastric bypass) on the serum levels of selected oxylipins and their fatty acid precursors and to verify the hypothesis that their changes after surgery can contribute to the resolution of inflammation. Moreover, we compared the oxylipin levels (prostaglandin E2, 13-HODE, maresin 1 and resolvin E1), fatty acids and the expression of enzymes that synthesize oxylipins in adipose tissue of lean controls and subjects with severe obesity.

SUBJECTS/METHODS

The study included 50 patients with severe obesity that underwent bariatric surgery and 41 subjects in lean, control group. Fatty acid content was analyzed by GC-MS, oxylipin concentrations were measured with immunoenzymatic assay kits and real-time PCR analysis was used to assess mRNA levels in adipose tissue.

RESULTS

Our results show increased expression of some enzymes that synthesize oxylipins in adipose tissue and alterations in the levels of oxylipins in both adipose tissue and serum of subjects with obesity. After bariatric surgery, the levels of anti-inflammatory oxylipins increased, whereas pro-inflammatory oxylipins decreased.

CONCLUSIONS

In patients with obesity, the metabolism of oxylipins is deregulated in adipose tissue, and their concentrations in serum are altered. Bariatric surgery modulates the serum levels of pro- and anti-inflammatory oxylipins, which may contribute to the resolution of inflammation.

Cord Blood Metabolome and BMI Trajectory from Birth to Adolescence: A Prospective Birth Cohort Study on Early Life Biomarkers of Persistent Obesity

There is increasing recognition on the role of early life metabolic programming in childhood obesity. This study sought to investigate whether newborn cord blood metabolome can predict future BMI. It included 946 children in the Boston Birth Cohort, a sample of high-risk yet understudied US urban, low-income, predominantly Black and Hispanic children, who were enrolled at birth and followed prospectively up to age 18 years. A total of 376 metabolites were measured in cord blood plasma. Longitudinal BMI trajectories were defined and categorized into three distinct patterns: early onset overweight and obesity (early-OWO), late onset OWO (late-OWO), and normal weight trajectory (NW). Multinomial logistic regression models were used to identify metabolites individually or as network modules associated with BMI trajectories. Of the 946 children, 388, 254, and 304 were classified as early-OWO, late-OWO, and NW, respectively. Of the seven co-metabolomic network modules defined, two were inversely correlated with early-OWO. Among the 68 metabolites within the two modules, 22 triacylglycerols and diacylglycerols were negatively associated with early-OWO; 5 cholesterol esters were positively associated with early-OWO. In this prospective birth cohort, we demonstrated distinctive longitudinal BMI trajectories and identified multiple cord plasma metabolites in relevant biological pathways that were associated with early-OWO.

Hepatic steatosis is associated with anthropometry, cardio-metabolic disease risk, sex, age and urbanisation, but not with ethnicity in adult Kenyans

OBJECTIVE

We aimed to determine the associations of non-alcoholic fatty liver disease (NAFLD) with cardio-metabolic risk factors for diabetes in adult Kenyans.

METHODS

A cross-sectional study was undertaken among rural and urban Kenyans of different ethnic origin. Ultrasonography scanning (USS) methods were used for the assessment of hepatic fat accumulation for NAFLD assessment and abdominal fat distribution, and simple anthropometry measurements were performed. All participants underwent a 2-h oral glucose tolerance test, and biochemical, haemodynamic and lifestyle data were obtained. Multivariate logistic regression analyses were used to assess sex, age, residency and ethnic differences in the association between NAFLD and various metabolic parameters.

RESULTS

In total, 743 individuals (59.1% women) with a mean age of 38.0 (range 18-68) years participated in the study. Overall, 118 individuals (15.9%) had NAFLD, of whom 94.1% had mild steatosis. Age >40 years was significantly associated with having NAFLD compared with <30 years of age with no difference found in NAFLD between ethnic groups (Luo, Kamba, Maasai). All body composition and clinical measurements were associated with NAFLD (p < 0.045 for OR).

CONCLUSION

Finding lower odds for NAFLD in men was unexpected, as was the lack of differences in NAFLD among the ethnic groups, while higher odds for NAFLD with increasing age and in urban vs. rural populations was expected. Especially the sex-specific results warrant further studies in black African populations on biology of body composition for having NAFLD, and whether this translates into insulin resistance and higher risk of diabetes and consequently cardiovascular disease in black African women.

Hypertrophied human adipocyte spheroids as in vitro model of weight gain and adipose tissue dysfunction

KEY POINTS

Adipocyte enlargement is a key feature of obesity and associated with insulin resistance and metabolic disease The cause and consequences of adipocyte enlargement have remained hard to study in vitro due to a lack of human cell models with representative morphology This paper provides an easily set up spheroid culture method, HUVAS (human unilocular vascularized adipocyte spheroids), for the differentiation and culturing of human adipocytes with a more unilocular morphology We show that providing adipocyte progenitors with a vascular differentiation niche is key for achieving in vitro differentiated adipocytes with large lipid droplets Lipid treatment of the HUVAS spheroids can further adipocyte enlargement and induce cellular dysfunction, mimicking the in vivo effects of weight gain The model will allow a wider research community to perform mechanistic studies of the factors impacting human adipocyte differentiation and growth, increasing our understanding of how obesity develops and why it has such detrimental consequences on whole body metabolism ABSTRACT: The rise in obesity prevalence has created an urgent need for new and improved methods to study human adipocytes and the pathogenic effects of weight gain in vitro. Despite the proven advantage of culturing adipocyte progenitors as 3D structures, the majority of studies continue using traditional 2D cultures which result in small, multilocular adipocytes with poor representability. We hypothesized that providing differentiating pre-adipocytes with a vascular growth niche would mimic in vivo adipogenesis and improve the differentiation into unilocular adipocytes. Here we present HUVAS (human unilocular vascularized adipocyte spheroids), a simple, easily applicable culture protocol that allows for the differentiation of human adipocytes with a more unilocular morphology and larger lipid droplets than previous protocols. Moreover, we offer a protocol for inducing adipocyte enlargement in vitro, resulting in larger lipid droplets and development of several key features of adipocyte dysfunction, including altered adipokine secretion, impaired lipolysis and insulin resistance. Taken together, our HUVAS model offers an improved culture system for studying the cellular and molecular mechanisms causing metabolic dysfunction and inflammation in human adipose tissue during weight gain. This article is protected by copyright. All rights reserved.

PTIP Deficiency in B Lymphocytes Reduces Subcutaneous Fat Deposition in Mice

Recent studies have predominantly focused on the role of B cells in metabolic diseases, yet the function of B cells in adipose homeostasis remains unclear. Pax transactivation domain-interacting protein (PTIP), a licensing factor for humoral immunity, is necessary for B cell development and activation. Here, using mice that lack PTIP in B cells (PTIP^-/- mice), we explored the role of B cells in adipose homeostasis under physiological conditions. Fat deposition in 8-week-old mice was measured by micro-CT, and PTIP^-/- mice presented a marked decrease in the deposition of subcutaneous adipose tissue (SAT). Untargeted lipidomics revealed that the triglyceride composition in SAT was altered in PTIP^-/- mice. In addition, there was no difference in the number of adipocyte progenitor cells in the SAT of wild-type (WT) and PTIP^-/- mice as measured by flow cytometry. To study the effects of steady-state IgM and IgG antibody levels on fat deposition, PTIP^-/- mice were injected intraperitoneally with serum from WT mice once every 3-4 days for 4 weeks. The iSAT mass of the recipient mice showed no significant increase in comparison to the controls after 4 weeks of injections. Our findings reveal that PTIP plays an essential role in regulating subcutaneous adipocyte size, triglyceride composition, and fat deposition under physiological conditions by controlling B cells. The decreased subcutaneous fat deposition in PTIP^-/- mice does not appear to be related to the number of adipocyte progenitor cells. The steady-state levels of IgM and IgG antibodies in vivo are not associated with the subcutaneous fat deposition.

Wide-Targeted Metabolome Analysis Identifies Potential Biomarkers for Prognosis Prediction of Epithelial Ovarian Cancer

Epithelial ovarian cancer (EOC) is a fatal gynecologic cancer, and its poor prognosis is mainly due to delayed diagnosis. Therefore, biomarker identification and prognosis prediction are crucial in EOC. Altered cell metabolism is a characteristic feature of cancers, and metabolomics reflects an individual’s current phenotype. In particular, plasma metabolome analyses can be useful for biomarker identification. In this study, we analyzed 624 metabolites, including uremic toxins (UTx) in plasma derived from 80 patients with EOC using ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS). Compared with the healthy control, we detected 77 significantly increased metabolites and 114 significantly decreased metabolites in EOC patients. Especially, decreased concentrations of lysophosphatidylcholines and phosphatidylcholines and increased concentrations of triglycerides were observed, indicating a metabolic profile characteristic of EOC patients. After calculating the parameters of each metabolic index, we found that higher ratios of kynurenine to tryptophan correlates with worse prognosis in EOC patients. Kynurenine, one of the UTx, can affect the prognosis of EOC. Our results demonstrated that plasma metabolome analysis is useful not only for the diagnosis of EOC, but also for predicting prognosis with the variation of UTx and evaluating response to chemotherapy.

Comparing Levels of Metabolic Predictors of Coronary Heart Disease between Healthy Lean and Overweight Females

Screening for the metabolomic signature of coronary heart disease (CHD) before disease onset could help in early diagnosis and potentially disease prevention. In this study, the levels of 17 CHD metabolic biomarkers in apparently healthy overweight females were compared to lean counterparts, and their associations with conventional clinical risk factors were determined. Clinical and metabolic data from 200 apparently healthy non-obese Qatari females were collected from Qatar Biobank (discovery cohort). Logistic regression was used to assess the association between body mass index (BMI) groups and 17 CHD metabolic biomarkers, and receiver operating characteristic (ROC) analysis was used to evaluate the prognostic value of CHD metabolic biomarkers in overweight. Stepwise linear regression was performed to identify the classical risk factors associated with CHD metabolites differentiating the two BMI groups. Validation of the association of CHD metabolic biomarkers with BMI groups was performed in 107 subjects (replication cohort). Out of the tested CHD metabolic biomarkers, five were significantly different between lean and overweight females in the discovery cohort (AUC = 0.73). Among these, the association of mannose, asparagine, and linoleate with BMI groups was confirmed in the replication cohort (AUC = 0.97). Significant correlations between predictors of CHD in overweight healthy women and classical risk factors were observed, including serum levels of cholesterol, testosterone, triiodothyronine, thyroxine, creatinine, albumin, bilirubin, glucose, c-peptide, uric acid, calcium and chloride. Apparently, healthy overweight females exhibit significantly different levels of specific CHD metabolites compared to their lean counterparts, offering a prognostic potential with preventative value.

Metabolomics of Lean/Overweight Insulin-Resistant Females Reveals Alterations in Steroids and Fatty Acids

BACKGROUND

The global diabetes epidemic is largely attributed to obesity-triggered metabolic syndrome. However, the impact of insulin resistance (IR) prior to obesity on the high prevalence of diabetes and the molecular mediators remain largely unknown. This study aims to compare the metabolic profiling of apparently healthy lean/overweight participants with IR and insulin sensitivity (IS), and identify the metabolic pathways underlying IR.

METHODS

In this cross-sectional study, clinical and metabolic data for 200 seemingly healthy young female participants (100 IR and 100 IS) was collected from Qatar Biobank. Orthogonal partial least square analysis was performed to assess the extent of separation between individuals from the 2 groups based on measured metabolites. Classical linear models were used to identify the metabolic signature of IR, followed by elastic-net-regularized generalized linear model (GLMNET) and receiver operating characteristic (ROC) analysis to determine top metabolites associated with IR.

RESULTS

Compared to lean/overweight participants with IS, those with IR showed increased androgenic steroids, including androsterone glucuronide, in addition to various microbiota byproducts, such as the phenylalanine derivative carboxyethylphenylalanine. On the other hand, participants with IS had elevated levels of long-chain fatty acids. A ROC analysis suggested better discriminatory performance using 20 metabolites selected by GLMNET in comparison to the classical clinical traits (area under curve: 0.93 vs 0.73, respectively).

CONCLUSION

Our data confirm the multifactorial mechanism of IR with a diverse spectrum of emerging potential biomarkers, including steroids, long-chain fatty acids, and microbiota metabolites. Further studies are warranted to validate these markers for diagnostic and therapeutic applications.

GATA-3 as a Potential Therapeutic Target for Insulin Resistance and Type 2 Diabetes Mellitus

Impaired adipogenesis plays an important role in the development of obesity-associated insulin resistance and type 2 diabetes as it leads to ectopic fat deposition. The anti-adipogenic transcription factor GATA-3 was identified as one of the potential molecular targets responsible for the impairment of adipogenesis. The expression of GATA-3 is higher in insulinresistant obese individuals compared to BMI-matched insulin-sensitive counterparts. Adipose tissue inflammation is a crucial mediator of this process. Hyperglycemia mediates the activation of the immune system, partially through upregulation of GATA- 3, causing exacerbation of the inflammatory state associated with obesity. This review discusses the evidence supporting the inhibition of GATA-3 as a useful therapeutic strategy in obesity-associated insulin resistance and type 2 diabetes, through up-regulation adipogenesis and amelioration of the immune response.

Metabolomic Profiling of Pregnancies With Polycystic Ovary Syndrome Identifies a Unique Metabolic Signature and Potential Predictive Biomarkers of Low Birth Weight

BACKGROUND

Polycystic ovary syndrome (PCOS) is a complex syndrome with clinical features of an endocrine/metabolic disorder. Various metabolites show significant association with PCOS; however, studies comparing the metabolic profile of pregnant women with and without PCOS are lacking. In this study, metabolomics analysis of blood samples collected from PCOS women and age and BMI matched controls in the second trimester of pregnancy was performed to identify metabolic differences between the two groups and determine their association with pregnancy outcome.

METHODS

Sixteen PCOS and fifty-two healthy women in their second trimester underwent targeted metabolomics of plasma samples using tandem mass spectrometry with the Biocrates MxP^® Quant 500 Kit. Linear regression models were used to identify the metabolic alterations associated with PCOS, followed by enrichment and Receiver Operating Characteristic (ROC) analyses to determine the best indicators of pregnancy outcomes.

RESULTS

PCOS women had lower birth weight babies compared to healthy controls. As a group, systolic blood pressure (SBP) at both second trimester and at delivery negatively correlated with birth weight. Regression models indicated significant increases in the triglycerides C20:4_C34:3 and C18:2_C38:6 in the PCOS group [false discovery rate (FDR) <0.05]. Enrichment analysis revealed significant elevations in triglycerides containing arachidonic acid, linoleic acid and palmitic acid in the PCOS group. A number of indicators of baby birth weight were identified including SBP at delivery, hexosylceramide (d18:2/24:0), ceramide (d18.0/24.1) and serine, with an AUC for all predictors combined for low birth weight (≤2500grams) of 0.88 (95%CI: 0.75-1.005, p<0.001).

CONCLUSIONS

PCOS pregnancies resulted in babies with a lower birth weight, marked by a unique metabolic signature that was enriched with specific triglycerides and unsaturated fatty acids. The functional significance of these associations needs further investigation.

Cardiometabolic Syndrome: An Update on Available Mouse Models

Cardiometabolic syndrome (CMS), a disease entity characterized by abdominal obesity, insulin resistance (IR), hypertension, and hyperlipidemia, is a global epidemic with approximately 25% prevalence in adults globally. CMS is associated with increased risk for cardiovascular disease (CVD) and development of diabetes. Due to its multifactorial etiology, the development of several animal models to simulate CMS has contributed significantly to the elucidation of the disease pathophysiology and the design of therapies. In this review we aimed to present the most common mouse models used in the research of CMS. We found that CMS can be induced either by genetic manipulation, leading to dyslipidemia, lipodystrophy, obesity and IR, or obesity and hypertension, or by administration of specific diets and drugs. In the last decade, the ob/ob and db/db mice were the most common obesity and IR models, whereas Ldlr-/- and Apoe-/- were widely used to induce hyperlipidemia. These mice have been used either as a single transgenic or combined with a different background with or without diet treatment. High-fat diet with modifications is the preferred protocol, generally leading to increased body weight, hyperlipidemia, and IR. A plethora of genetically engineered mouse models, diets, drugs, or synthetic compounds that are available have advanced the understanding of CMS. However, each researcher should carefully select the most appropriate model and validate its consistency. It is important to consider the differences between strains of the same animal species, different animals, and most importantly differences to human when translating results.

Sample Preparation Methods for Lipidomics Approaches Used in Studies of Obesity

Obesity is associated with alterations in the composition and amounts of lipids. Lipids have over 1.7 million representatives. Most lipid groups differ in composition, properties and chemical structure. These small molecules control various metabolic pathways, determine the metabolism of other compounds and are substrates for the syntheses of different derivatives. Recently, lipidomics has become an important branch of medical/clinical sciences similar to proteomics and genomics. Due to the much higher lipid accumulation in obese patients and many alterations in the compositions of various groups of lipids, the methods used for sample preparations for lipidomic studies of samples from obese subjects sometimes have to be modified. Appropriate sample preparation methods allow for the identification of a wide range of analytes by advanced analytical methods, including mass spectrometry. This is especially the case in studies with obese subjects, as the amounts of some lipids are much higher, others are present in trace amounts, and obese subjects have some specific alterations of the lipid profile. As a result, it is best to use a method previously tested on samples from obese subjects. However, most of these methods can be also used in healthy, nonobese subjects or patients with other dyslipidemias. This review is an overview of sample preparation methods for analysis as one of the major critical steps in the overall analytical procedure.

Associations of region-specific visceral adiposity with subclinical atrial dysfunction and outcomes of heart failure

AIMS

Excessive visceral adiposity (VAT) plays an essential role in metabolic derangements with those close to heart further mediates myocardial homeostasis. The disparate biological links between region-specific VAT and cardiometabolic profiles as mediators influencing atrial kinetics remain unexplored.

METHODS AND RESULTS

Among 1326 asymptomatic individuals, region-specific VAT including peri-aortic root fat (PARF) and total pericardial fat (PCF) of cardiac region, together with thoracic peri-aortic adipose tissue (TAT), was assessed using multiple-detector computed tomography. VAT measures were related to functional left atrial (LA) metrics assessed by speckle-tracking algorithm and clinical outcomes of atrial fibrillation (AF) and heart failure (HF). Multivariate linear regression models incorporating body fat, metabolic syndrome, and E/TDI-e' consistently demonstrated independent associations of larger PARF/PCF with peak atrial longitudinal systolic strain (PALS) reduction, higher LA stiffness, and worsened strain rate components; instead, TAT was independently associated with cardiometabolic profiles. PARF rather than PCF or TAT conferred independent prognostic values for incident AF/HF by multivariate Cox regression (adjusted hazard ratio: 1.56, 95% confidence interval: 1.17-2.08, P = 0.002) during a median of 1790 days (interquartile range: 25th to 75th: 1440-1927 days) of follow-up, with subjects categorized into worst PALS and largest VAT tertiles demonstrating highest events (all log-rank P < 0.001). Mediation analysis showed that higher triglyceride and lower high-density lipoproteins may serve as intermediary factors for effects between VAT and LA functional metrics, with lesser role by glucose level.

CONCLUSIONS

Visceral adiposity surrounding atrial region was tightly associated with subclinical atrial dysfunction and incident AF or HF beyond metabolic factors. Instead, peri-aortic adiposity may mediate their toxic effects mainly through circulating cardiometabolic profiles.

Metabolic profiling of pre-gestational and gestational diabetes mellitus identifies novel predictors of pre-term delivery

Background

Pregnant women with gestational diabetes mellitus (GDM) or type 2 diabetes mellitus (T2DM) are at increased risks of pre-term labor, hypertension and preeclampsia. In this study, metabolic profiling of blood samples collected from GDM, T2DM and control pregnant women was undertaken to identify potential diagnostic biomarkers in GDM/T2DM and compared to pregnancy outcome.

Methods

Sixty-seven pregnant women (21 controls, 32 GDM, 14 T2DM) in their second trimester underwent targeted metabolomics of plasma samples using tandem mass spectrometry with the Biocrates MxP^® Quant 500 Kit. Linear regression models were used to identify the metabolic signature of GDM and T2DM, followed by generalized linear model (GLMNET) and Receiver Operating Characteristic (ROC) analysis to determine best predictors of GDM, T2DM and pre-term labor.

Results

The gestational age at delivery was 2 weeks earlier in T2DM compared to GDM and controls and correlated negatively with maternal HbA1C and systolic blood pressure and positively with serum albumin. Linear regression models revealed elevated glutamate and branched chain amino acids in GDM + T2DM group compared to controls. Regression models also revealed association of lower levels of triacylglycerols and diacylglycerols containing oleic and linoleic fatty acids with pre-term delivery. A generalized linear model ROC analyses revealed that that glutamate is the best predictors of GDM compared to controls (area under curve; AUC = 0.81). The model also revealed that phosphatidylcholine diacyl C40:2, arachidonic acid, glycochenodeoxycholic acid, and phosphatidylcholine acyl-alkyl C34:3 are the best predictors of GDM + T2DM compared to controls (AUC = 0.90). The model also revealed that the triacylglycerols C17:2/36:4 and C18:1/34:1 are the best predictors of pre-term delivery (≤ 37 weeks) (AUC = 0.84).

Conclusions

This study highlights the metabolite alterations in women in their second trimester with diabetes mellitus and identifies predictive indicators of pre-term delivery. Future studies to confirm these associations in other cohorts and investigate their functional relevance and potential utilization for targeted therapies are warranted.

Mass spectrometry-based determination of lipids and small molecules composing adipose tissue with a focus on brown adipose tissue

Adipose tissue has been the subject of research for a very long time. Many studies perform a comprehensive analysis of different types of adipose tissue with an emphasis on brown adipose tissue. Mass spectrometry-based approaches are particularly useful in the exploration not only of the metabolic composition of adipose tissue but also its function. In the presented review, a complex and critical overview of publications devoted to the analysis of adipose tissue by means of mass spectrometry was performed. Detailed investigation of analytical aspects related to either untargeted or targeted analysis of adipose tissue was performed, leading to the formation of a collection of hints at the available analytical methods. Moreover, a profound analysis of the metabolic composition of brown adipose tissue was performed. Brown adipose tissue metabolome was characterized on structural and functional levels, providing information about its exact metabolic composition but also connecting these molecules and placing them into biochemical pathways. All our work resulted in a very broad picture of the analysis of adipose tissue, starting from the analytical aspects and finishing on the current knowledge about its composition.

Lipidomics of human adipose tissue reveals diversity between body areas

BACKGROUND AND AIMS

Adipose tissue plays a pivotal role in storing excess fat and its composition reflects the history of person's lifestyle and metabolic health. Broad profiling of lipids with mass spectrometry has potential for uncovering new knowledge on the pathology of obesity, metabolic syndrome, diabetes and other related conditions. Here, we developed a lipidomic method for analyzing human subcutaneous adipose biopsies. We applied the method to four body areas to understand the differences in lipid composition between these areas.

MATERIALS AND METHODS

Adipose tissue biopsies from 10 participants were analyzed using ultra-high-performance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry. The sample preparation optimization included the optimization of the lipid extraction, the sample amount and the sample dilution factor to detect lipids in an appropriate concentration range. Lipidomic analyses were performed for adipose tissue collected from the abdomen, breast, thigh and lower back. Differences in lipid levels between tissues were visualized with heatmaps.

RESULTS

Lipidomic analysis on human adipose biopsies lead to the identification of 186lipids in 2 mg of sample. Technical variation of the lipid-class specific internal standards were below 5%, thus indicating acceptable repeatability. Triacylglycerols were highly represented in the adipose tissue samples, and lipids from 13 lipid classes were identified. Long polyunsaturated triacylglycerols in higher levels in thigh (q<0.05), when compared with the abdomen, breast and lower back, indicating that the lipidome was area-specific.

CONCLUSION

The method presented here is suitable for the analysis of lipid profiles in 2 mg of adipose tissue. The amount of fat across the body is important for health but we argue that also the distribution and the particular profile of the lipidome may be relevant for metabolic outcomes. We suggest that the method presented in this paper could be useful for detecting such aberrations.

MiRNAs and mRNAs Analysis during Abdominal Preadipocyte Differentiation in Chickens

Simple Summary

We sequenced the miRNAs and mRNAs of preabdominal fat cells and differentiated adipocytes, and target genes of miRNA combined with mRNA transcriptome data jointly. We found that the MAPK signal pathway, insulin signal pathway, fatty acid metabolism, ECM( extracellular matrix)–receptor interaction, and other signal pathways were involved in the differentiation of preabdominal fat cells. In addition, we found that some miRNAs–mRNAs combinations were strongly related to the differentiation of fat cells (miR-214−ACSBG2, NFKB2, CAMK2A, ACLY, CCND3, PLK3, ITGB2; miR-148a-5p−ROCK2; miR-10a-5p−ELOVL5; miR-146b-5p−LAMA4; miR-6615-5p−FLNB; miR-1774−COL6A1). Our findings provide important resources for the study of adipocyte differentiation.

Abstract

The excessive deposition of abdominal fat has become an important factor in restricting the production efficiency of chickens, so reducing abdominal fat deposition is important for improving growth rate. It has been proven that miRNAs play an important role in regulating many physiological processes of organisms. In this study, we constructed a model of adipogenesis by isolating preadipocytes (Ab-Pre) derived from abdominal adipose tissue and differentiated adipocytes (Ab-Ad) in vitro. Deep sequencing of miRNAs and mRNAs expressed in Ab-Pre and Ab-Ad groups was conducted to explore the effect of miRNAs and mRNAs on fat deposition. We identified 80 differentially expressed miRNAs (DEMs) candidates, 58 of which were up-regulated and 22 down-regulated. Furthermore, six miRNAs and six mRNAs were verified by qRT-PCR, and the results showed that the expression of the DEMs and differentially expressed genes (DEGs) in the two groups was consistent with our sequencing results. When target genes of miRNA were combined with mRNA transcriptome data, a total of 891 intersection genes were obtained, we predicted the signal pathways of cross genes enrichment to the MAPK signal pathway, insulin signal pathway, fatty acid metabolism, and ECM–receptor interaction. Meanwhile, we constructed miRNA and negatively correlated mRNA target networks, including 12 miRNA–mRNAs pairs, which showed a strong association with the abdominal adipocyte differentiation (miR-214−ACSBG2, NFKB2, CAMK2A, ACLY, CCND3, PLK3, ITGB2; miR-148a-5p−ROCK2; miR-10a-5p−ELOVL5; miR-146b-5p−LAMA4; miR-6615-5p−FLNB; miR-1774−COL6A1). Overall, these findings provide a background for further research on lipid metabolism. Thus, we can better understand the molecular genetic mechanism of chicken abdominal fat deposition.

Targeted lipidomics and transcriptomics profiling reveal the heterogeneity of visceral and subcutaneous white adipose tissue

AIMS

The depot-specific differences in lipidome of visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) reflect heterogeneity of white adipose tissue (WAT), which plays a central role in its distinct response to outside stimuli. However, the detailed lipidome of depot-specific WAT is largely unknown, especially the minor constitutes including phospholipid and sphingolipid.

MATERIALS AND METHODS

To investigate this field, we applied a high-coverage targeted lipidomics approach of VAT and SAT in male C57BL/6J mice to compare the basal level of their lipid profiles. Applying microarray and quantitative real-time polymerase chain reaction, we analyzed the transcriptome of twodepot-specific WAT and verified the differences in individual genes.

KEY FINDINGS

In total, 342 lipid species from 19 lipid classes were identified. Our results showed the composition of TAG and FFA were different in length of chain and saturation. Interestingly, low abundance phospholipid, sphingolipid and cardiolipin were significantly higher in SAT. Lipid correlation network analysis vindicated that TAG and phospholipid formed distinct subnet and had more connections with other lipid species. Enriched ontology analysis of gene screened from LIPID MAPS and microarray suggested the differences were mainly involved in lipid metabolism, insulin resistance and inflammatory response.

SIGNIFICANCE

Our comprehensive lipidomics and transcriptomics analyses revealed differences in lipid composition and lipid metabolism of two depot-specific WAT, which would offer new insights into the investigation of heterogeneity of visceral and subcutaneous white adipose tissue.

A Prospective Analysis of Circulating Plasma Metabolites Associated with Ovarian Cancer Risk

Ovarian cancer has few known risk factors, hampering identification of high-risk women. We assessed the association of prediagnostic plasma metabolites (N = 420) with risk of epithelial ovarian cancer, including both borderline and invasive tumors. A total of 252 cases and 252 matched controls from the Nurses' Health Studies were included. Multivariable logistic regression was used to estimate ORs and 95% confidence intervals (CI), comparing the 90th-10th percentile in metabolite levels, using the permutation-based Westfall and Young approach to account for testing multiple correlated hypotheses. Weighted gene coexpression network analysis (WGCNA; n = 10 metabolite modules) and metabolite set enrichment analysis (n = 23 metabolite classes) were also evaluated. An increase in pseudouridine levels from the 10th to the 90th percentile was associated with a 2.5-fold increased risk of overall ovarian cancer (OR = 2.56; 95% CI, 1.48-4.45; P = 0.001/adjusted P = 0.15); a similar risk estimate was observed for serous/poorly differentiated tumors (n = 176 cases; comparable OR = 2.38; 95% CI, 1.33-4.32; P = 0.004/adjusted P = 0.55). For nonserous tumors (n = 34 cases), pseudouridine and C36:2 phosphatidylcholine plasmalogen had the strongest statistical associations (OR = 9.84; 95% CI, 2.89-37.82; P < 0.001/adjusted P = 0.07; and OR = 0.11; 95% CI, 0.03-0.35; P < 0.001/adjusted P = 0.06, respectively). Five WGCNA modules and 9 classes were associated with risk overall at FDR ≤ 0.20. Triacylglycerols (TAG) showed heterogeneity by tumor aggressiveness (case-only heterogeneity P < 0.0001). The TAG association with risk overall and serous tumors differed by acyl carbon content and saturation. In summary, this study suggests that pseudouridine may be a novel risk factor for ovarian cancer and that TAGs may also be important, particularly for rapidly fatal tumors, with associations differing by structural features. SIGNIFICANCE: Pseudouridine represents a potential novel risk factor for ovarian cancer and triglycerides may be important particularly in rapidly fatal ovarian tumors.

Metabolic signature of obesity-associated insulin resistance and type 2 diabetes

Background

Obesity is associated with an increased risk of insulin resistance and type 2 diabetes mellitus (T2DM). However, some obese individuals maintain their insulin sensitivity and exhibit a lower risk of associated comorbidities. The underlying metabolic pathways differentiating obese insulin sensitive (OIS) and obese insulin resistant (OIR) individuals remain unclear.

Methods

In this study, 107 subjects underwent untargeted metabolomics of serum samples using the Metabolon platform. Thirty-two subjects were lean controls whilst 75 subjects were obese including 20 OIS, 41 OIR, and 14 T2DM individuals.

Results

Our results showed that phospholipid metabolites including choline, glycerophosphoethanolamine and glycerophosphorylcholine were significantly altered from OIS when compared with OIR and T2DM individuals. Furthermore, our data confirmed changes in metabolic markers of liver disease, vascular disease and T2DM, such as 3-hydroxymyristate, dimethylarginine and 1,5-anhydroglucitol, respectively.

Conclusion

This pilot data has identified phospholipid metabolites as potential novel biomarkers of obesity-associated insulin sensitivity and confirmed the association of known metabolites with increased risk of obesity-associated insulin resistance, with possible diagnostic and therapeutic applications. Further studies are warranted to confirm these associations in prospective cohorts and to investigate their functionality.

Metal Oxide Laser Ionization Mass Spectrometry Imaging (MOLI MSI) Using Cerium(IV) Oxide

Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI) is a powerful technique for spatially resolved metabolomics. A variation on MALDI, termed metal oxide laser ionization (MOLI), capitalizes on the unique property of cerium(IV) oxide (CeO2) to induce laser-catalyzed fatty acyl cleavage from lipids and has been utilized for bacterial identification. In this study, we present the development and utilization of CeO2 as an MSI catalyst. The method was developed using a MALDI TOF instrument in negative ion mode, equipped with a high frequency laser. Instrument parameters for MOLI MS fatty acid catalysis with CeO2 were optimized with phospholipid standards and fatty acid catalysis was confirmed using lipid extracts from reference bacterial strains, and sample preparation was optimized using mouse brain tissue. MOLI MSI was applied to the imaging of normal mouse brain revealing differentiable fatty acyl pools in myelinated and nonmyelinated regions. Similarly, MOLI MSI showed distinct fatty acyl composition in tumor regions of a patient derived xenograft mouse model of glioblastoma. To assess the potential of MOLI MSI to detect pathogens directly from tissue, a pseudoinfection model was prepared by spotting Escherichia coli lipid extracts on mouse brain tissue sections and imaged by MOLI MSI. The spotted regions were molecularly resolved from the supporting mouse brain tissue by the diagnostic odd-chained fatty acids and reflected control bacterial MOLI MS signatures. We describe MOLI MSI for the first time and highlight its potential for spatially resolved fatty acyl analysis, characterization of fatty acyl composition in tumors, and its potential for pathogen detection directly from tissue.