Leptin as a cardiovascular risk marker in metabolically healthy obese: Hyperleptinemia in metabolically healthy obese

Mediators between body mass index and atrial fibrillation: a Mendelian randomization study

Background

Although obesity is a recognized risk factor of atrial fibrillation (AF), the mechanisms are not fully understood.

Objective

We aimed to identify the potential mediators between body mass index (BMI) and AF.

Methods

We conducted a two-sample Mendelian randomization (MR) analysis using publicly available summary-level data from genome-wide association studies. Univariable MR analyses were applied to identify potential mediators, and then the multivariable MR analyses were conducted to explore the mediated roles of circulating biomarkers, metabolic markers and comorbidities in the association between BMI and AF.

Results

This MR study found a significant causal association between BMI and AF (OR = 1.41, 95% CI = 1.33-1.50; p < 0.001), which was attenuated to 1.21 (95% CI = 1.03-1.43) after being adjusted for leptin, in which 48.78% excess risk was mediated. After further adjustment for leptin and some cormorbidies, the association was attenuated to null (adjusted for leptin and sleep apnoea: OR=1.05, 95% CI = 0.85-1.30; adjusted for leptin and coronary heart disease: OR = 1.08, 95% CI = 0.90-1.30; adjusted for leptin and systolic blood pressure: OR = 1.11, 95% CI = 0.88-1.41), resulting in 87.80%, 80.49% and 73.17% excess risk being mediated, respectively.

Conclusion

These results identified an important mediated role of leptin, particularly for individuals with sleep apnoea, coronary heart disease or hypertension, providing some clues for the underlying mechanisms behind the impact of obesity on AF risk.

The impact of the obesity onset on the inflammatory and glycemic profile of women with severe obesity

BACKGROUND

The stage of life at the onset of obesity is an important factor in assessing inflammatory state and cardiometabolic risk.

OBJECTIVES

This study aimed to evaluate the relationship between the obesity onset and the inflammatory profile in women with severe obesity.

SETTING

Public hospital, Brazil.

METHODS

Forty-eight women with severe obesity (20-59 yr old) were evaluated according to weight, height, neck circumference (NC), waist circumference (WC), and hip circumference, as well blood metabolic and inflammatory parameters. The participants were grouped according to obesity onset stage of life (early group: ≤19 yr; late group: >19 yr).

RESULTS

The demographic means of the participants were: age of 39.7 years, weight of 122.7 kg and body mass index (BMI) of 48.4 kg/m2. The late group presented significantly higher values of leptin (lep)/adiponectin (adipo) ratio and homeostatic model assessment for insulin resistance (HOMA-IR) than the early group. The late group also had a lower adipo/lep ratio. Moreover, the late group showed correlations between the lep/adipo ratio and BMI (r = .460, P = .021), NC (r = .478, P = .016), and WC (r = .535, P = .006). Adipo was also correlated with NC (r = -.418, P = .038), WC (r = -.437, P = .029), and glycated hemoglobin (HbA1C) (r = -.485, P = .019). By contrast, in the early group, the lep/adipo ratio showed correlations with insulin (r = .647, P = .004) and HOMA-B (r = .564, P = .015).

CONCLUSIONS

The inflammatory profile is correlated with anthropometric values in women with late-onset obesity. Inflammatory markers seemed to correlate with the glycemic profile in women with early-onset obesity. Furthermore, inflammation was higher in women with late-onset obesity compared to those with early-onset obesity.

Fat as a Friend or Foe of the Bone

PURPOSE OF REVIEW

The objective of this review is to summarize the literature on the prevalence and diagnosis of obesity and its metabolic profile, including bone metabolism, focusing on the main inflammatory and turnover bone mediators that better characterize metabolically healthy obesity phenotype, and to summarize the therapeutic interventions for obesity with their effects on bone health.

RECENT FINDINGS

Osteoporosis and fracture risk not only increase with age and menopause but also with metabolic diseases, such as diabetes mellitus. Thus, patients with high BMI may have a higher bone fragility and fracture risk. However, some obese individuals with healthy metabolic profiles seem to be less at risk of bone fracture. Obesity has become an alarming disease with growing prevalence and multiple metabolic comorbidities, resulting in a significant burden on healthcare and increased mortality. The imbalance between increased food ingestion and decreased energy expenditure leads to pathological adipose tissue distribution and function, with increased secretion of proinflammatory markers and harmful consequences for body tissues, including bone tissue. However, some obese individuals seem to have a healthy metabolic profile and may not develop cardiometabolic disease during their lives. This healthy metabolic profile also benefits bone turnover and is associated with lower fracture risk.

Correlation analysis of obesity phenotypes with leptin and adiponectin

Obesity can be categorized as metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUO). However, individuals with MHO are characterized by the absence of metabolic syndrome (MS) and appear to have lower inflammation levels compared to MUO. This study aimed to investigate the association of obesity phenotypes with leptin (LEP) and adiponectin (ADP). According to the inclusion and exclusion criteria, we selected 178 subjects from the previous cross-sectional survey. Based on the body mass index (BMI) and diagnostic criteria of MS, we divided the individuals into three groups, including healthy control group (HC group), metabolically healthy obesity group (MHO group) and metabolically unhealthy obesity group (MUO group). The concentrations of LEP and ADP in serum were measured, and the association of these two cytokines with different obesity phenotypes were subsequently analyzed. Compared to both the HC and MHO groups, the MUO group showed significantly higher BMI, waist circumference (WC), waist-hip ratio (WHR), triglyceride (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), fasting plasma glucose (FPG), homeostasis model assessment of insulin resistance (Homa-IR) and blood pressure (P < 0.05). In contrast, serum high-density lipoprotein cholesterol (HDL-C) was notably lower in the MUO group (P < 0.05). ADP was found to have a positive correlation with systolic blood pressure (SBP) and a negative correlation with FPG in the MHO group. In the MUO group, LEP demonstrated a positive correlation with fasting insulin (FINS) and Homa-IR, while ADP showed a positive correlation with TC and SBP. Linear regression analysis further indicated that SBP (β = 0.234, P = 0.043), TG (β = - 0.292, P = 0.001) and LDL-C (β = 0.626, P = 0.000) were independently correlated with ADP, and BMI (β = 0.398, P = 0.002) was independently correlated with LEP in obese individuals. In conclusion, ADP and LEP were closely related with glucose and lipid metabolism in obese individuals, these two cytokines might play critical roles in obesity-associated metabolic disorders.

Metabolically healthy obesity: Misleading phrase or healthy phenotype?

Obesity is a heterogenous condition with multiple different phenotypes. Among these a particular subtype exists named as metabolically healthy obesity (MHO). MHO has multiple definitions and its prevalence varies according to study. The potential mechanisms underlying the pathophysiology of MHO include the different types of adipose tissue and their distribution, the role of hormones, inflammation, diet, the intestinal microbiota and genetic factors. In contrast to the negative metabolic profile associated with metabolically unhealthy obesity (MUO), MHO has relatively favorable metabolic characteristics. Nevertheless, MHO is still associated with many important chronic diseases including cardiovascular disease, hypertension, type 2 diabetes, chronic kidney disease as well as certain types of cancer and has the risk of progression into the unhealthy phenotype. Therefore, it should not be considered as a benign condition. The major therapeutic alternatives include dietary modifications, exercise, bariatric surgery and certain medications including glucagon-like peptide-1 (GLP-1) analogs, sodium-glucose cotransporter-2 (SGLT-2) inhibitors and tirzepatide. In this review, we discuss the significance of MHO while comparing this phenotype with MUO.

Adipokines and myokines as indicators of obese phenotypes and their association with the gut microbiome diversity indices

Today, metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUO) are distinguished. Adipose and muscle tissues can determine the obese phenotype due to adipokine and myokine production. Gut microbial community is also involved in MHO. The study was aimed to reveal the features of adipokine and myokine levels and their association with the gut microbiome alpha diversity in patients with MHO and MUO. A total of 265 subjects were divided into two groups: healthy individuals and obese patients. The latter were divided into two subgroups: patients with MHO and patients with MUO. Body mass index, waist circumference, HOMA-IR, adipokine and myokine levels, gut microbiome taxonomic composition, alpha diversity indices were defined in all the surveyed individuals, lipid and carbohydrate metabolism was also assessed. Significant differences in the adipokine and myokine levels and their association with the gut microbiome diversity indicators were revealed in patients with different obese phenotypes. Patients with MHO and MUO showed significantly lower adiponectin levels (р < 0.05) and significantly higher leptin and asprosin levels (р < 0.05) than healthy individuals. Patients with MUO had lower adiponectin and leptin levels (p < 0.05) than patients with MHO. Significantly higher FGF21 levels were observed in patients with MUO. Large-scale correlation analysis revealed the relationship between the glucose levels and the gut microbiome diversity indices that was missing in patients with MUO. This indicated the loss of the microbiota diversity effects on the blood glucose control in individuals with MUO, as well as different regulatory roles in the gut microbiome‒liver‒muscle/adipose tissue axes of individuals with MHO and MUO played by gut microbiota. The findings show the relationship between the gut microbiome diversity and the obese phenotype.

Association between different metabolic phenotypes of obesity and thyroid disorders among Chinese adults: a nationwide cross-sectional study

Background

Increased body mass index (BMI) and metabolic abnormalities both have potential associations with thyroid disease. The aim of this study was to investigate the correlation between different metabolic phenotypes of obesity and thyroid disorders using nationwide data from China.

Methods

Data were collected from a cross-sectional survey called the Thyroid Disorders, Iodine Status, and Diabetes Epidemiological Survey conducted between 2015 and 2017 in China. A total of 69007 subjects aged 18 years or older were defined and divided into six groups on the basis of BMI and metabolic health status: metabolically healthy normal weight (MHNW), metabolically unhealthy normal weight (MUNW), metabolically healthy overweight (MHOW), metabolically unhealthy overweight (MUOW), metabolically healthy obesity (MHO), and metabolically unhealthy obesity (MUO). We estimated the odds ratios (ORs) and confidence intervals [CIs] for different thyroid disorders according to metabolic phenotypes using multivariate logistic regression models.

Results

In our study, we found that the prevalence of subclinical hypothyroidism was almost as high in the MUNW group as in the MUO group, the prevalence of overt hyperthyroidism was highest in the MUNW group and Graves' disease was highest in the MHO group. Our results also suggested that the prevalence of goiter and thyroid nodules increased with increased BMI values and that the MUO group had the highest incidence. Multivariate logistic regression analysis indicated that subjects with unhealthy metabolic phenotypes (MUNW, MUOW, and MUO) all had an increased risk of subclinical hypothyroidism, regardless of their BMI. MUNW subjects had an approximately 1.6-fold higher risk of overt hyperthyroidism and a 1.8-fold higher risk of Graves' disease than their metabolically healthy counterparts (MHNW). The present study also demonstrated that the MUO group had the highest risk of goiter and thyroid nodules among the metabolic phenotypes of obesity.

Conclusion

Based on our study, we found that metabolic abnormalities and obesity play different roles in various thyroid diseases. Metabolically unhealthy individuals, both with and without obesity, have a higher risk of thyroid disorders than metabolically healthy individuals without obesity.

Factors of Obesity and Metabolically Healthy Obesity in Asia

The East Asian region (China, Japan, and South Korea) is comprised of almost 1.5 billion people and recent industrialization has brought with it a pandemic of rising obesity, even in children. As these countries are rapidly aging and functioning at sub-replacement birthrates, the burgeoning costs of obesity-related care may threaten socialized healthcare systems and quality of life. However, a condition called metabolically healthy obesity (MHO) has been found to be without immediate cardiopulmonary or diabetic risk. Thus, maintenance of the MHO condition for the obese in East Asia could buffer the burden of long-term obesity care on medical systems and knowledge of the biochemical, genetic, and physiological milieu associated with it could also provide new targets for intervention. Diverse physiological, psychological, environmental, and social factors play a role in obesogenesis and the transition of MHO to a metabolically unhealthy obesity. This review will give a broad survey of the various causes of obesity and MHO, with special emphasis on the East Asian population and studies from that region.

The Harm of Metabolically Healthy Obese and the Effect of Exercise on Their Health Promotion

Obesity and obesity-related diseases [type 2 diabetes, cardiovascular disease (CVD), and cancer] are becoming more common, which is a major public health concern. Metabolically healthy obesity (MHO) has become a type of obesity, accounting for a large proportion of obese people. MHO is still harmful to health. It was discovered that MHO screening criteria could not well reflect health hazards, whereas visceral fat, adiponectin pathway, oxidative stress, chronic inflammation, and histological indicators at the microlevel could clearly distinguish MHO from health control, and the biological pathways involved in these micro indicators were related to MHO pathogenesis. This review reveals that MHO’s micro metabolic abnormality is the initial cause of the increase of disease risk in the future. Exploring the biological pathway of MHO is important in order to develop an effective mechanism-based preventive and treatment intervention strategy. Exercise can correct the abnormal micro metabolic pathway of MHO, regulate metabolic homeostasis, and enhance metabolic flexibility. It is a supplementary or possible alternative to the traditional healthcare prevention/treatment strategy as well as an important strategy for reducing MHO-related health hazards.

Obesity-Mediated Immune Modulation: One Step Forward, (Th)2 Steps Back

Over the past decades, the relationship between the immune system and metabolism has become a major research focus. In this arena of immunometabolism the capacity of adipose tissue to secrete immunomodulatory molecules, including adipokines, within the underlying low-grade inflammation during obesity brought attention to the impact obesity has on the immune system. Adipokines, such as leptin and adiponectin, influence T cell differentiation into different T helper subsets and their activation during immune responses. Furthermore, within the cellular milieu of adipose tissue nutrient availability regulates differentiation and activation of T cells and changes in cellular metabolic pathways. Upon activation, T cells shift from oxidative phosphorylation to oxidative glycolysis, while the differential signaling of the kinase mammalian target of rapamycin (mTOR) and the nuclear receptor PPARγ, amongst others, drive the subsequent T cell differentiation. While the mechanisms leading to a shift from the typical type 2-dominated milieu in lean people to a Th1-biased pro-inflammatory environment during obesity are the subject of extensive research, insights on its impact on peripheral Th2-dominated immune responses become more evident. In this review, we will summarize recent findings of how Th2 cells are metabolically regulated during obesity and malnutrition, and how these states affect local and systemic Th2-biased immune responses.

Association of Metabolically Healthy and Unhealthy Obesity Phenotype with Markers Related to Obesity, Diabetes among Young, Healthy Adult Men. Analysis of MAGNETIC Study

Adipose tissue secretes many regulatory factors called adipokines. Adipokines affect the metabolism of lipids and carbohydrates. They also influence the regulation of the immune system and inflammation. The current study aimed to evaluate the association between markers related to obesity, diabesity and adipokines and metabolically healthy and unhealthy obesity in young men. The study included 98 healthy participants. We divided participants into three subgroups based on body mass index and metabolic health definition: 49 metabolically healthy normal-weight patients, 27 metabolically healthy obese patients and 22 metabolically unhealthy obese patients. The 14 metabolic markers selected were measured in serum or plasma. The analysis showed associations between markers related to obesity, diabesity and adipokines in metabolically healthy and unhealthy obese participants. The decreased level of adipsin (p < 0.05) was only associated with metabolically healthy obesity, not with metabolically unhealthy obesity. The decreased level of ghrelin (p < 0.001) and increased level of plasminogen activator inhibitor-1 (p < 0.01) were only associated with metabolically unhealthy obesity, not with metabolically healthy obesity. The decreased level of adiponectin and increased levels of leptin, c-peptide, insulin and angiopoietin-like 3 protein were associated with metabolically healthy and unhealthy obesity. In conclusion, our data show that metabolically healthy obesity was more similar to metabolically unhealthy obesity in terms of the analyzed markers related to obesity and diabesity.

Obesity in Children with Leptin Receptor Gene Polymorphisms

INTRODUCTION

The study of single nucleotide polymorphisms (SNPs) of the leptin receptor gene (LEPR) based on next generation genomic sequencing (NGS) data is becoming an increasingly important aspect of diagnosis, treatment and prevention of both metabolically healthy (MHO) and metabolically unhealthy obesity (MUO) phenotypes.

MATERIAL AND METHODS

35 obese children 6-18 years old were examined by the NGS method with bioinformatic analysis. The main group (n = 18) was formed by children with MUO, according to the recommendations of the expert group of the National Heart, Lung, and Blood Institute. The control group (n = 17) was represented by children with MHO. Statistical methods were used: analysis of variance, Wald's sequential analysis, Spearman's correlation analysis, analysis of nominal data and multiple discriminant analysis.

RESULTS

10 types of non-synonymous SNPs (rs3790435, rs1137100, rs2186248, rs70940803, rs79639154, rs1359482195, rs1137101, rs1805094, rs13306520, rs13306522) of the LEPR gene in obese children have been identified. Multiple discriminant analysis demonstrated that the following LEPR SNPs are of greatest importance in the development of MUO: rs3790435, rs13306522, rs13306520. Analysis of nominal data revealed significant differences in the groups for Copy number variation (CNV) rs3790435 of the LEPR gene. Wald's analysis allowed us to identify 6 important predictors of MUO (І ≥ 0.5): 2 CNV rs3790435 (Relative Risk, RR = 2, Prognostic coefficient, PC = +2.76); male gender of the child (RR = 1.3, PC = +1.35); rs3790435 (RR = 1.9, PC = +2.76); hyperleptinemia more than 40.56 ng/ml (RR = 2, PC = +3); CNV rs1359482195 ≥ 3 (RR = 1.9, PC = +5.8); SNP of the LEPR gene ≥4 (RR = 3.8, PC = +5.8).

CONCLUSION

Children with the genotype rs3790435 gene LEPR had signs of MUO more often.

Effects of short-term dietary restriction on plasma metabolites and the subcutaneous fat area according to metabolic status in obese individuals: a case-control study

BACKGROUND

Research elucidating the metabolic mechanisms that differentiate subtypes of obesity has been increasing. We aimed to investigate the effects of a 12-week dietary intervention on the metabolomic profiles of obese subjects.

METHODS

Subjects followed a 12-week dietary restriction protocol consisting of a 300 kcal/day reduction in their usual caloric intake. Twenty-nine obese subjects were included and divided into two groups: the metabolic status maintenance group (n = 17, controls) and the metabolic status improvement group (n = 12, tests). We analyzed the somatometric and biochemical parameters and performed ultra-performance liquid chromatography-mass spectrometry analysis of the plasma metabolites.

RESULTS

At 12 weeks, the fat percentage, whole fat area (WFA), subcutaneous fat area (SFA) at the L1 vertebra, and the levels of triglycerides, gamma-glutamyltransferase (gamma-GT), and leptin were markedly decreased in the metabolic status improvement group, while the level of high-density lipoprotein cholesterol increased compared with that in the metabolic status maintenance group. Metabolomic profiling at 12 weeks showed substantial differences in 4-aminobutyraldehyde (p = 0.005) and 4'-apo-β-carotenal (p = 0.024) between the two groups. Furthermore, an AUC value of 0.89 was obtained for the following seven featured biomarkers: triglycerides, gamma-GT, leptin, fat percentage, WFA, and SFA at the L1 vertebra, and 4-aminobutyraldehyde.

CONCLUSIONS

We demonstrated that 4-aminobutyraldehyde and related regional fat distribution parameters were strongly associated with obesity according to metabolic status. Thus, these biomarkers are potentially valuable in confirming the efficacy of short-term interventions and predicting metabolic status in obese individuals.

TRIALS REGISTRATION

This study was registered at ClinicalTrials.gov under NCT03135132 (registered 1 May 2017-retrospectively registered).

Adiponectin, Leptin and Cardiovascular Disorders

The landmark discoveries of leptin and adiponectin firmly established adipose tissue as a sophisticated and highly active endocrine organ, opening a new era of investigating adipose-mediated tissue crosstalk. Both obesity-associated hyperleptinemia and hypoadiponectinemia are important biomarkers to predict cardiovascular outcomes, suggesting a crucial role for adiponectin and leptin in obesity-associated cardiovascular disorders. Normal physiological levels of adiponectin and leptin are indeed essential to maintain proper cardiovascular function. Insufficient adiponectin and leptin signaling results in cardiovascular dysfunction. However, a paradox of high levels of both leptin and adiponectin is emerging in the pathogenesis of cardiovascular disorders. Here, we (1) summarize the recent progress in the field of adiponectin and leptin and its association with cardiovascular disorders, (2) further discuss the underlying mechanisms for this new paradox of leptin and adiponectin action, and (3) explore the possible application of partial leptin reduction, in addition to increasing the adiponectin/leptin ratio as a means to prevent or reverse cardiovascular disorders.

Leptin Concentrations in Non-Obese and Obese Non-Diabetes Nigerian-Africans

BACKGROUND

Controversial findings exist on the role of leptin in obesity and its correlation with metabolic variables, with few data emanating from Nigerian-Africans. Plasma leptin was therefore determined in obese and non-obese. Its relationship with obesity indices and metabolic variables were further envisaged.

MATERIALS AND METHODS

A cross-sectional comparative study on 87 randomly-selected non-diabetes Nigerians distributed into 3 groups (24 normal, 23 pre-obese and 40 obese). Obesity indices, fasting Insulin (FI) and homeostasis model assessment-insulin resistance (HOMA-IR) were determined. Plasma leptin was determined by sandwich enzyme-linked immunosorbent assay. Mann-Whitney U-test, Independent Kruskal-Wallis test, Spearman correlation and Step-wise Multivariate Logistic Regression analysis determined outcomes.

RESULTS

Median+IQR leptin concentrations were higher in obese {61.8(40.8, 91.4) ng/mL, p<0.001} than pre-obese {42.7(28.0, 51.7) ng/mL, p=0.003} and normal {28.6(20.7, 39.8) ng/mL, p=0.03} BMI categories. Leptin was higher (p<0.001) in females than males {Median+IQR, 52.0 (35.0, 80.0) ng/mL versus 34.0(24, 65.0 ng/mL)}. Leptin was positively correlated with body fat percentage (BFP), r=0.57; waist circumference (WC), r=0.46 and body mass index (BMI), r=0.50, p<0.001, respectively in all subjects, with higher correlation coefficient in males than females. Leptin showed sex-specific correlations to age, FI and HOMA-IR. In the unadjusted models, central obesity/generalized obesity, WC, BMI, BFP, combined pre-obesity/obesity, younger age and female sex were significantly (p<0.001) associated with log-transformed leptin. WC (OR: 1.2, 95% CI, 1.05-1.38, p=0.009), BFP (OR: 1.41, 95% CI, 1.07-1.84, p=0.013) and BMI (OR: 1.6, 95% CI, 1.13-2.31, p=0.008) in men and all subjects, were independently associated with hyperleptinaemia following adjustments.

CONCLUSION

Plasma leptin concentrations, fasting insulin and insulin resistance are higher in obese and pre-obese than normal controls, with females showing higher leptin concentrations than males. Leptin is independently related to BMI, BFP, WC, female sex and generalized/central obesity in Nigerian-Africans especially males. It showed sex-specific relations to age, fasting insulin and HOMA-IR.

An Overview of the Role of Adipokines in Cardiometabolic Diseases

Obesity as an independent risk factor for cardiovascular diseases (CVDs) leads to an increase in morbidity, mortality, and a shortening of life span. The changes in heart structure and function as well as metabolic profile are caused by obese people, including those free of metabolic disorders. Obesity alters heart function structure and affects lipid and glucose metabolism, blood pressure, and increase inflammatory cytokines. Adipokines, specific cytokines of adipocytes, are involved in the progression of obesity and the associated co-morbidities. In the current study, we review the scientific evidence on the effects of obesity on CVDs, focusing on the changes in adipokines. Several adipokines have anti-inflammatory and cardioprotective effects comprising omentin, apelin, adiponectin, and secreted frizzled-related protein (Sfrp-5). Other adipokines have pro-inflammatory impacts on the cardiovascular system and obesity including leptin, tumor necrosis factor (TNF), retinol-binding protein4 (RBP-4), visfatin, resistin, and osteopontin. We found that obesity is associated with multiple CVDs, but can only occur in unhealthy metabolic patients. However, more studies should be designed to clarify the association between obesity, adipokine changes, and the occurrence of CVDs.

Serum miR-503 is a Candidate Biomarker for Differentiating Metabolic Healthy Obesity from Metabolic Unhealthy Obesity

PURPOSE

Overweight and obesity are associated with metabolic diseases. However, a subgroup of the overweight/obese population does not present metabolic abnormalities. Hence, there is an urgent need to identify biomarkers that can distinguish different obesity phenotypes and metabolic status.

PATIENTS AND METHODS

A total of 98 individuals were divided into three groups: metabolically healthy normal weight (MHNW), metabolically healthy obese (MHO), and metabolically unhealthy obese (MUO). Participants were evaluated for anthropometric and biochemical parameters and serum BMPR1A concentration and miR-503 level. Receiver operating characteristic (ROC) curve analysis and logistic regression analysis were performed.

RESULTS

The level of miR-503 was significantly higher in the MHO group compared with that in the MUO group, but no difference was observed between the MHNW and MHO groups. Meanwhile, no significant differences in serum BMPR1A concentration were observed between the three groups. ROC curve analysis showed that miR-503 could be used as a marker to distinguish the MUO from the MHO. Logistic regression analysis suggested that miR-503 was an important related factor associated with an unhealthy metabolic state in overweight/obese subjects.

CONCLUSION

miR-503 can be considered as a suitable biomarker to distinguish between the MUO and MHO, which may be a related factor for the incidence of metabolic disorders in overweight/obese subjects.

Adipokine profiles in preeclampsia

Objectives: Hypertensive disorders of pregnancy (HDP), including preeclampsia (PE), are associated with short- and long-term maternal health complications, and obesity is a leading attributable risk factor for HDP. Yet, most women identified as obese [by body mass index (BMI) ≥ 30 kg/m²] do not develop HDP, indicating limited predictability of BMI alone. In nonpregnant populations, increased visceral fat mass (VFM) is an obesity-associated phenotype increasing the risk of developing hypertension. We sought to assess whether, in pregnancy, obese women with PE would have higher circulating levels of adipokines preferential to VFM compared to obese women without PE.Study Design: We performed a case-control study of women with and without PE, including obese (n = 65; BMI ≥ 30 kg/m²) and normal weight (n = 52; BMI 18.4-24.9 kg/m²) women. Plasma concentrations of adipokines preferential to VFM (visfatin, resistin), adipokines reflecting overall adiposity (leptin, adiponectin), and inflammatory cytokines were compared.Results: We found that among obese women, cases had significantly higher levels of VFM-associated adipokines and cytokines compared to controls [visfatin (p < .01, t = -3.8), resistin (p = .002, t = 1.12), IFN gamma (p = .04, t = -2.0), IL-6 (p < .01, t = -2.65), IL1-beta (p < .01, t = -4.1), IL-2 (p < .01, t = -3.9)]. Interestingly, however, obese and normal weight cases had similar VFM-adipokine and cytokine levels [visfatin (p = .34, t = -0.35), resistin (p = .55, t = -0.25)], and inflammatory marker concentrations [IFN gamma (p = .86, t = -0.76), IL-6 (p = .91, t = -0.53), IL-1beta (p = .67, t = 1.18), and IL-2 (p = .45, t = -1.16)]. These data possibly suggest an association between VFM and PE that is present independent of BMI.Conclusion: In summary, we demonstrated that, in normal-weight and obese women, PE was associated with higher concentrations of VFM-preferential adipokines compared to normal-weight and obese controls without PE.

Leptin Levels and Insulin Dependence in Latent Autoimmune Diabetes in Adults

Latent autoimmune diabetes in adults (LADA) is an autoimmune type of diabetes accounting for up to 10% of all cases of diabetes initially diagnosed as type 2 diabetes mellitus. It has been demonstrated that LADA patients with a lower body mass index (BMI) undergo a faster depletion of beta cell function and require insulin therapy earlier. In this study, we assayed a panel of adipokines (leptin, adiponectin, omentin, resistin, visfatin) and proinflammatory cytokines (interleukin 2, interleukin 6, tumor necrosis factor-α) in 71 LADA patients and tested the association with a number of clinical and immunological features. Among men, leptin was positively and significantly correlated with BMI and fat mass (r = 0.487 and r = 0.664, respectively), resistin was positively and significantly correlated with total and low-density lipoprotein cholesterol (r = 0.644 and r = 0.746, P < 0.0001) and with interleukin 2 (r = 0.688, P < 0.01). Omentin showed an inverse correlation with systolic blood pressure in women (r = -0.359, P < 0.001) and a positive correlation with interleukin 2 in both genders (r = 0.395, P < 0.01). The Cox regression analysis showed that leptin levels were inversely and significantly related with the risk of early insulin dependence. Higher leptin secretion may exert a direct effect on beta cell function leading to more insulin sensitivity.

Preeclampsia biomarkers: An assessment of maternal cardiometabolic health

Preeclampsia is a serious pregnancy condition defined as new-onset hypertension and proteinuria, commonly characterized as either early, 'placental', or late onset, 'maternal', using a cut-off of 34 weeks gestation. However, it may be more useful to differentiate between the vascular remodelling and placental invasion vs. inflammation and metabolic pathophysiology that underlie these forms of preeclampsia. Due to rising rates of obesity, the late-onset, maternal form is increasingly occurring earlier in pregnancy. Predictive tests for preeclampsia typically include biophysical markers such as maternal body mass index and mean arterial pressure, indicating the importance of cardiovascular and metabolic health in its pathophysiology. In contrast, the placental, inflammatory, endothelial and/or metabolic biomarkers used in these tests are generally thought to indicate an abnormal response to placentation and predict the disease. However, many of these non-placental biomarkers are known to predict impaired metabolic health in non-pregnant subjects with obesity (metabolically unhealthy obesity) and coronary artery disease or stroke in people at risk for cardiovascular events. Similarities between the performance of these markers in the prediction of cardiovascular and metabolic health outside of pregnancy suggests that they may be more indicative of maternal health than predictive for preeclampsia. This paper reviews the biophysical and biochemical markers in preeclampsia prediction and compares their performance to tests assessing metabolic health and risk of cardiovascular disease, particularly in the obese population.

Leptin and Leptin Resistance in the Pathogenesis of Obstructive Sleep Apnea: A Possible Link to Oxidative Stress and Cardiovascular Complications

Obesity-related sleep breathing disorders such as obstructive sleep apnea (OSA) and obesity hypoventilation syndrome (OHS) cause intermittent hypoxia (IH) during sleep, a powerful trigger of oxidative stress. Obesity also leads to dramatic increases in circulating levels of leptin, a hormone produced in adipose tissue. Leptin acts in the hypothalamus to suppress food intake and increase metabolic rate. However, obese individuals are resistant to metabolic effects of leptin. Leptin also activates the sympathetic nervous system without any evidence of resistance, possibly because these effects occur peripherally without a need to penetrate the blood-brain barrier. IH is a potent stimulator of leptin expression and release from adipose tissue. Hyperleptinemia and leptin resistance may upregulate generation of reactive oxygen species, increasing oxidative stress and promoting inflammation. The current review summarizes recent data on a possible link between leptin and oxidative stress in the pathogenesis of sleep breathing disorders.

Leptin, An Adipokine With Central Importance in the Global Obesity Problem

Leptin has central importance in the global obesity and cardiovascular disease problem. Leptin is principally secreted by adipocytes and acts in the hypothalamus to suppress appetite and food intake, increase energy expenditure, and regulate body weight. Based on clinical translation of specific and networked actions, leptin affects the cardiovascular system and may be a marker and driver of cardiometabolic risk factors with interventions that are actionable by cardiologists. Leptin subnetwork analysis demonstrates a statistically significant role for ethnoculturally and socioeconomically appropriate lifestyle intervention in cardiovascular disease. Emergent mechanistic components and potential diagnostic or therapeutic targets include hexokinase 3, urocortins, clusterin, sialic acid-binding immunoglobulin-like lectin 6, C-reactive protein, platelet glycoprotein VI, albumin, pentraxin 3, ghrelin, obestatin prepropeptide, leptin receptor, neuropeptide Y, and corticotropin-releasing factor receptor 1. Emergent associated symptoms include weight change, eating disorders, vascular necrosis, chronic fatigue, and chest pain. Leptin-targeted therapies are reported for lipodystrophy and leptin deficiency, but they are investigational for leptin resistance, obesity, and other chronic diseases.