The prevalence of metabolic syndrome and metabolically healthy obesity in Europe: a collaborative analysis of ten large cohort studies

Obesity phenotypes and cardiovascular risk: From pathophysiology to clinical management

Obesity epidemic reached the dimensions of a real global health crisis with more than one billion people worldwide living with obesity. Multiple obesity-related mechanisms cause structural, functional, humoral, and hemodynamic alterations with cardiovascular (CV) deleterious effects. A correct assessment of the cardiovascular risk in people with obesity is critical for reducing mortality and preserving quality of life. The correct identification of the obesity status remains difficult as recent evidence suggest that different phenotypes of obesity exist, each one associated with different degrees of CV risk. Diagnosis of obesity cannot depend only on anthropometric parameters but should include a precise assessment of the metabolic status. Recently, the World Heart Federation and World Obesity Federation provided an action plan for management of obesity-related CV risk and mortality, stressing for the instauration of comprehensive structured programs encompassing multidisciplinary teams. In this review we aim at providing an updated summary regarding the different obesity phenotypes, their specific effects on CV risk and differences in clinical management.

Relevance of body composition in phenotyping the obesities

Obesity is the most extended metabolic alteration worldwide increasing the risk for the development of cardiometabolic alterations such as type 2 diabetes, hypertension, and dyslipidemia. Body mass index (BMI) remains the most frequently used tool for classifying patients with obesity, but it does not accurately reflect body adiposity. In this document we review classical and new classification systems for phenotyping the obesities. Greater accuracy of and accessibility to body composition techniques at the same time as increased knowledge and use of cardiometabolic risk factors is leading to a more refined phenotyping of patients with obesity. It is time to incorporate these advances into routine clinical practice to better diagnose overweight and obesity, and to optimize the treatment of patients living with obesity.

NK cells vs. obesity: A tale of dysfunction & redemption

Natural killer (NK) cells are critical in protecting the body against infection and cancer. NK cells can rapidly respond to these threats by directly targeting the infected or transformed cell using their cytotoxic machinery or by initiating and amplifying the immune response via their production of cytokines. Additionally, NK cells are resident across many tissues including adipose, were their role extends from host protection to tissue homeostasis. Adipose resident NK cells can control macrophage polarization via cytokine production, whilst also regulating stressed adipocyte fate using their cytotoxic machinery. Obesity is strongly associated with increased rates of cancer and a heightened susceptibility to severe infections. This is in part due to significant obesity-related immune dysregulation, including defects in both peripheral and adipose tissue NK cells. In this review, we detail the literature to date on NK cells in the setting of obesity - outlining the consequences, mechanisms and therapeutic interventions.

Alteration of Branched-Chain and Aromatic Amino Acid Profile as a Novel Approach in Studying Polycystic Ovary Syndrome Pathogenesis

Polycystic ovary syndrome (PCOS) is a common endocrine disorder that affects reproductive-age women and predisposes them to the development of metabolic disturbances. Recent research has shown that several metabolic factors may play a role in PCOS pathogenesis, and it has been suggested that an alteration in the amino acid profile might be a predictive sign of metabolic disorders. Metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUO) are concepts that have attracted scientific attention; however, a universal definition has not been established yet for these terms. Already existing definitions of MHO involve the coexistence of obesity with the absence or minimal presence of other metabolic syndrome parameters. A group of 326 women, 209 diagnosed with PCOS and 117 healthy individuals, participated in this study. Multiple parameters were assessed, including anthropometrical, biochemical, and hormonal ones, and gas-liquid chromatography, combined with tandem mass spectrometry, was used to investigate the amino acid profile. Statistical analysis revealed noticeably higher levels of all aromatic amino acids in PCOS women compared to the control group: phenylalanine 47.37 ± 7.0 vs. 45.4 ± 6.09 nmol/mL (p = 0.01), tyrosine 61.69 ± 9.56 vs. 58.08 ± 8.89 nmol/mL (p < 0.01), and tryptophan 53.66 ± 11.42 vs. 49.81 ± 11.18 nmol/mL (p < 0.01); however, there was no significant difference in the "tryptophan ratio" between the PCOS and control group (p = 0.88). A comparison of MHO and MUO PCOS women revealed that LAP, leucine, and isoleucine concentrations were significantly higher among the MUO subgroup: respectively, 101.98 ± 34.74 vs. 55.80 ± 24.33 (p < 0.001); 153.26 ± 22.26 vs. 137.25 ± 25.76 nmol/mL (p = 0.04); and 92.92 ± 16.09 vs. 82.60 ± 18.70 nmol/mL (p = 0.02). No significant differences in BMI, fasting glucose, and HOMA-IR between MHO and MUO were found: respectively, 35.0 ± 4.8 vs. 36.1 ± 4.6 kg/m2 (p = 0.59); 88.0 ± 6.0 vs. 87.73 ± 6.28 mg/dL (p = 0.67); and 3.36 ± 1.70 vs. 4.17 ± 1.77 (p = 0.1). The identification of altered amino acid profiles in PCOS holds potential clinical implications. Amino acids may serve as biomarkers for diagnosing and monitoring the metabolic status of individuals with PCOS. The alteration of BCAAs and AAAs may be involved in PCOS pathogenesis, but the underlying mechanism should be further investigated.

Pathobiology of Metabolic-Associated Fatty Liver Disease

Metabolic-associated fatty liver disease (MAFLD), formerly known as nonalcoholic fatty liver disease, is highly associated with the metabolic syndrome. Given its high heterogeneity in patients along with unpredictable clinical outcomes, MAFLD is difficult to diagnose and manage. MAFLD is associated with obesity, diabetes, metabolic derangements, lipid disorders, cardiovascular disorders, sleep apnea, sarcopenia, gut dysbiosis, and sex hormone-related disorders. Identification of risk factors is imperative in understanding disease heterogeneity and clinical presentation to reliably diagnose and manage patients. The complexity of MAFLD pathobiology is discussed in this review in relation to its association with common metabolic and nonmetabolic disorders.

Associations of obesity phenotypes with weight change, cardiometabolic benefits, and type 2 diabetes incidence during a lifestyle intervention: results from the PREVIEW study

BACKGROUND/OBJECTIVES

Some individuals with overweight/obesity may be relatively metabolically healthy (MHO) and have a lower risk of cardiovascular disease than those with metabolically unhealthy overweight/obesity (MUO). We aimed to compare changes in body weight and cardiometabolic risk factors and type 2 diabetes incidence during a lifestyle intervention between individuals with MHO vs MUO.

METHODS

This post-hoc analysis included 1012 participants with MHO and 1153 participants with MUO at baseline in the randomized trial PREVIEW. Participants underwent an eight-week low-energy diet phase followed by a 148-week lifestyle-based weight-maintenance intervention. Adjusted linear mixed models and Cox proportional hazards regression models were used.

RESULTS

There were no statistically significant differences in weight loss (%) between participants with MHO vs MUO over 156 weeks. At the end of the study, weight loss was 2.7% (95% CI, 1.7%-3.6%) in participants with MHO and 3.0% (2.1%-4.0%) in those with MUO. After the low-energy diet phase, participants with MHO had smaller decreases in triglyceride (mean difference between MHO vs MUO 0.08 mmol·L-1 [95% CI, 0.04-0.12]; P < 0.001) but similar reductions in fasting glucose and HOMA-IR than those with MUO. However, at the end of weight maintenance, those with MHO had greater reductions in triglyceride (mean difference -0.08 mmol·L-1 [-0.12--0.04]; P < 0.001), fasting glucose, 2-hour glucose (difference -0.28 mmol·L-1 [-0.41--0.16]; P < 0.001), and HOMA-IR than those with MUO. Participants with MHO had smaller decreases in diastolic blood pressure and HbA1c and greater decreases in HDL cholesterol after weight loss than those with MUO, whereas the statistically significant differences disappeared at the end of weight maintenance. Participants with MHO had lower 3-year type 2 diabetes incidence than those with MUO (adjusted hazard ratio 0.37 [0.20-0.66]; P < 0.001).

CONCLUSIONS

Individuals with MUO had greater improvements in some cardiometabolic risk factors during the low-energy diet phase, but had smaller improvements during long-term lifestyle intervention than those with MHO.

Higher Sensitivity to Thyroid Hormones May Be Linked to Maintaining the Healthy Metabolic Condition in People with Obesity: New Insight from NHANES

INTRODUCTION

Obesity contributes to the pathogenesis of diverse metabolic diseases, yet the mechanism underlying metabolically healthy obesity (MHO) remains elusive. Thyroid hormones and sensitivity to them have a major impact on metabolism. Our study aimed to investigate the association between MHO and thyroid hormone sensitivity.

METHODS

Thyroid hormone indices, including the thyroid-stimulating hormone (TSH) index (TSHI), the Thyrotroph Thyroxine Sensitivity Index (TTSI), the Thyroid Feedback Quantile-Based Index (TFQI), and the Parametric Thyroid Feedback Quantile-Based Index (PTFQI), were calculated based on a non-institutionalized US sample in the National Health and Nutrition Examination Survey (NHANES, 2007-2012). Participants were divided into four groups (metabolically healthy non-obesity [MHNO], metabolically unhealthy non-obesity [MUNO], MHO, and metabolically unhealthy obesity [MUO]) according to their body mass index and metabolic profiles. Linear regression, logistic regression, and restricted cubic splines were employed to analyze the association between thyroid hormone indices and metabolic phenotypes.

RESULTS

A total of 4,857 participants (49.6% men; mean age, 42.6 years) were included, with 1,539 having obesity and 235 identified as MHO. Participants in the MHO group exhibited lower levels of TSH, TSHI, TTSI, TFQI, and PTFQI compared with the MHNO group (all p < 0.05), while the differences among MHNO, MUNO, and MUO groups were not statistically significant (all p > 0.05). Among participants with obesity, TSH, TSHI, TTSI, TFQI, and PTFQI were positively associated with metabolic abnormality (all p < 0.05).

CONCLUSION

Participants with MHO exhibited higher thyroid hormone sensitivity among various obesity phenotypes, even when compared with those with MHNO. A positive association was observed between metabolic abnormality and thyroid hormone sensitivity, while the trend of TSH was observed to be consistent with sensitivity to thyroid hormone indices in discriminating metabolic abnormality. Hence, TSH has the potential to serve as a convenient index for detecting sensitivity to thyroid hormones and further metabolic conditions.

Metabolic Syndrome Rather Than Other Phenotypes in PCOS as a Predictive Indicator for Clinical Outcomes in IVF: Comprehensive Phenotypic Assessment across All PCOS Classifications

Polycystic ovary syndrome (PCOS) is a well-recognized, multi-system metabolic disorder affecting fertility. Although various classification methods have been proposed to assess the phenotypic heterogeneity of PCOS, there is currently no reliable phenotype for predicting clinical IVF outcomes. This retrospective study, as a comprehensive phenotypic assessment across all PCOS classifications, aimed to identify dependable phenotypes that can serve as predictors for IVF and pregnancy outcomes. The study included 1313 PCOS patients who received their initial IVF treatment between January 2019 and December 2021. The phenotypes reflect the diverse metabolic and hormonal characteristics in this study. Phenotype A, within the Rotterdam criteria classification, exhibited the highest anti-Müllerian hormone levels (AMH), while phenotype D displayed the lowest Homeostasis Model Assessment of Insulin Resistance (HOMA-IR) values. Both the hyperandrogenism (HA) phenotype within HA-based classification and the overweight phenotype within the body-mass-index-based classification showed increased HOMA-IR and metabolic syndrome (MetS). The MetS phenotype had higher free androgen index and a lower AMH. Notably, the MetS-based classification system demonstrated an independent association of MetS with cumulative live birth, preterm birth, and gestational diabetes mellitus as a contributing risk factor for PCOS patients undergoing IVF (p < 0.05). These findings carry noteworthy implications for advancing clinical management strategies for PCOS.

Lipid Peroxidation as a Possible Factor Affecting Bone Resorption in Obese Subjects-Preliminary Research

Oxidative stress, which promotes bone catabolism, also affects the quality of bone tissue. We aimed to assess the impact of metabolic disorders and oxidant-antioxidant imbalance associated with primary obesity on bone resorption and formation processes. Anthropometric parameters, metabolic variables, oxidative stress indicators (malondialdehyde, vitamins A and E, uric acid, superoxide dismutase, catalase, glutathione peroxidase, type 1 paraoxonase, iron-reducing plasma antioxidant power) and markers of bone turnover (type I procollagen N-terminal propeptide and the type I collagen C-terminal cross-linked telopeptide; P1NP and CTX) were assessed in 108 Polish participants. Under the influence of oxidative stress, both enzymatic and non-enzymatic defense mechanisms were stimulated in obese subjects, especially in women, who had increased lipid peroxidation and activity of catalase (particularly in first-degree obesity) and decreased vitamin E concentration. The process of lipid peroxidation, as well as the weakening of the bone formation, was strongly manifested in women at a BMI range of 35.0-39.9 kg/m² but not at BMI > 40.0 kg/m², but it had a comprehensive negative impact on bone turnover in obese men. Obesity and its degree of advancement significantly affected the decrease in the concentration of the marker of bone formation-P1NP-only in the plasma of women. Excessive body weight had no effect on the value of the bone resorption marker in plasma, regardless of gender. Our results confirm the existence of the "obesity paradox" in the aspect of bone tissue metabolism and suggest that a specific body weight threshold changed the molecular response of the tissue.

Opportunities and challenges for sweat-based monitoring of metabolic syndrome via wearable technologies

Metabolic syndrome is a prevalent condition in adults over the age of 65 and is a risk factor for developing cardiovascular disease and type II diabetes. Thus, methods to track the condition, prevent complications and assess symptoms and risk factors are needed. Here we discuss sweat-based wearable technologies as a potential monitoring tool for patients with metabolic syndrome. We describe several key symptoms that can be evaluated that could employ sweat patches to assess inflammatory markers, glucose, sodium, and cortisol. We then discuss the challenges with material property, sensor integration, and sensor placement and provide feasible solutions to optimize them. Together with a list of recommendations, we propose a pathway toward successfully developing and implementing reliable sweat-based technologies to monitor metabolic syndrome.

Metabolic syndrome is a risk factor for developing cardiovascular disease and type II diabetes. Lyzwinski, Elgendi and colleagues discuss the potential role of sweat-based wearable technologies for monitoring metabolic syndrome along with engineering challenges towards implementation and optimization

The heterogeneity of metabolic syndrome presentation and challenges this causes in its pharmacological management: a narrative review focusing on principal risk modifiers

INTRODUCTION

Metabolic syndrome (MetS), i.e. the cluster of cardiometabolic risk factors comprising visceral obesity, impaired glucose metabolism, arterial hypertension and atherogenic dyslipidemia, is prevalent globally and exacts a heavy toll on health care expenditures.

AREAS COVERED

The pathophenotypes of individual traits of the MetS in adults are discussed first, with strong emphasis on nonalcoholic fatty liver disease (NAFLD) and sex differences. Next, I discuss recent studies on phenotypic and outcome heterogeneity of the MetS, highlighting the role of NAFLD, sex, reproductive status, and depressive disorders. In the second half of the article, the therapeutic implications of the variable MetS types and features are analyzed, focusing on the most recent developments, and guidelines.

EXPERT OPINION

I have identified physiological, pathological, social and medical sources of phenotypical heterogeneity in the MetS and its constitutive traits. Improved understanding of these variables may be utilized in the setting of future precision medicine approaches in the field of metabolic disorders and target organ damage.

Obesity and metabolic state are associated with increased healthcare resource and medication use and costs: a Finnish population-based study

AIM

To characterize healthcare resource (HCRU) and medication use and associated costs in individuals with obesity compared with individuals with normal weight or overweight in a population-based cohort of Finnish adults. The association between metabolic state and direct costs was also assessed.

METHODS

The study cohort included 5587 randomly selected individuals who participated in the national FinHealth 2017 health examination survey. Data on healthcare visits and hospital stays, including diagnoses (ICD-10), and purchases and costs of prescription medicines were collected from the nationwide registers by the Finnish Institute for Health and Welfare and Social Insurance Institution of Finland. The healthcare costs were calculated based on standard unit costs reported by the Finnish Institute for Health and Welfare.

RESULTS

The total annual direct costs were €2665 (SD €5673) and €1799 (SD €3874) per person with obesity and with normal weight or overweight, respectively. Obesity was associated with significantly increased total direct (age- and sex-adjusted cost rate ratio, RR, 1.356; p < 0.001), HCRU-related (1.273; p = 0.002), and medication (1.669; p < 0.001) costs. A vast majority (90%) of individuals with obesity were classified as metabolically unhealthy based on clinical measurements. The metabolically unhealthy state was associated with increased costs in individuals with obesity but not in individuals with normal weight or overweight.

CONCLUSION

Obesity is associated with a significant and complex direct cost burden to society, arising primarily from increased comorbidity. Metabolically healthy obesity is uncommon and obesity prevention and timely treatment should be of high priority to tackle the increasing burden of obesity.

Tirzepatide and potential use for metabolically healthy obesity

Metabolically healthy obesity or metabolically healthy overweight (MHO) is best described as being absent of any major metabolic disorder or cardiovascular diseases such as type 2 diabetes mellitus, dyslipidemia, hypertension, and atherosclerotic cardiovascular disease despite being obese or overweight. Nevertheless, MHO is being recognized as an important risk factor for the development of cardiovascular, cerebrovascular, and peripheral artery disease. In addition, these patients are at a high risk of conversion to the metabolically unhealthy phenotype. Tirzepatide is a newly developed glucose-lowering agent which acts on the glucose-dependent insulinotropic peptide (GIP) and glucagon-like peptide-1 (GLP-1) receptors. It has been shown to result in several highly beneficial outcomes including weight loss and a significant improvement in important metabolic parameters such as HbA1c, fasting serum glucose, and triglyceride/lipoprotein levels. These findings suggest that tirzepatide could potentially be beneficial to metabolically healthy obese or metabolically healthy overweight patients in reducing their risk of adverse cardiovascular outcomes and conversion to the metabolically unhealthy phenotype. In this review, we aim to discuss the potential benefits of using the novel anti-diabetic tirzepatide in the management of MHO to prevent the development of cardiovascular events and to decrease the likelihood of conversion to the unhealthy phenotype. We initially describe the clinical outcomes of MHO as well as the association of MHO with developing future cardiovascular events. We then delineate the currently available evidence behind the clinical effects of tirzepatide. We finally discuss the potential advantages of using tirzepatide in the management of MHO.

Inflammatory markers may mediate the relationship between processed meat consumption and metabolic unhealthy obesity in women: a cross sectional study

Metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUHO) are known to be affected by diet and inflammatory factors (such as TGF-β1, IL-β1, MCP1). We sought to survey that consume of processed meat could effect on MHO and MUHO phenotypes, mediated through inflammatory markers, in overweight and obese Iranian women. The current cross-sectional study was done on 224 women 18-48 years, with a body mass index (BMI) ≥ 25 kg/m². A 147- item food frequency questionnaire (FFQ) was used to evaluate dietary intake. In all participants, anthropometric indices and biochemical factors, as well as metabolic health phenotypes based on Karelis score, were evaluated. According to results, 22.6% of participants had MHO and 75.7% had MUHO phenotypes. There was an association between higher adherence to processed meats and increasing odds of MUHO phenotype in Iranian women (OR:2.54; 95% CI 0.009, 7.51; P = 0.05). Moreover, we found that the relation can be affected by agents such as TGF-β1, IL-β1, and MCP1; however, more research is needed to confirm these results and finding.

Association between thyroid function and obesity phenotypes in healthy euthyroid individuals: an investigation based on Tehran Thyroid Study

AIMS

We investigated whether thyroid function could be associated with obesity phenotypes amongst euthyroid individuals.

MATERIALS AND METHODS

A cross-sectional analysis was conducted among healthy, euthyroid subjects. The study participants were chosen from the Tehran Thyroid Study (TTS). We analyzed 2988 euthyroid adults and classified them into four obesity phenotype groups: metabolically healthy normal weight (MHNW), metabolically healthy obese (MHO), metabolically unhealthy normal weight (MUNW), and metabolically unhealthy obese (MUO). The statistical differences between thyroid hormones between various obesity phenotypes according to age and sex was compared using analysis of covariance (ANCOVA).

RESULTS

It was found that MHNW participants had higher levels of FT4 when compared with metabolically healthy or unhealthy obese subjects (P < 0.001), even after adjustment for the confounding variables. No difference was observed in the levels of TSH (P = 0.260) among obesity phenotypes. In the subgroup analysis according to the age, a significant difference was observed in the level of FT4 only in subjects with age < 55 years (P = 0.001). However, analyzing men and women separately did not show a significant difference in the FT4 level among obesity phenotypes (P > 0.05).

CONCLUSION

"Metabolically abnormality" was independently related to low normal FT4 levels in overweight/obese euthyroid individuals. There is a need for further research to understand how low FT4 levels are linked to metabolically unhealthy states in euthyroid individuals.

Evaluation of systemic endothelial-dependent and endothelial-independent microvascular reactivity in metabolically healthy obesity: An observational study

BACKGROUND

Metabolically healthy obesity (MHO), a phenotype of obesity considered to be of lower cardiovascular risk, is still a controversial concept. This study aimed to investigate the presence of subclinical systemic microvascular dysfunction in individuals with MHO.

METHODS

This was a cross-sectional study in which 112 volunteers were allocated into three groups: metabolically healthy normal weight (MHNW), MHO, or metabolically unhealthy obesity (MUO). Obesity was defined as a body mass index (BMI) ≥ 30 kg/m². MHO was defined as the absence of any component of metabolic syndrome, except waist circumference. Microvascular reactivity was evaluated using cutaneous laser speckle contrast imaging.

RESULTS

Mean age was 33.2 ± 7.66 years. The median BMI in the MHNW, MHO and MUO groups was 23.6, 32.8, and 35.8 kg/m², respectively. Baseline microvascular conductance values were lower in the MUO group (0.25 ± 0.08 APU/mmHg) than in MHO (0.30 ± 0.10 APU/mmHg) and MHNW groups (0.33 ± 0.12 APU/mmHg) (P = 0.0008). There were no significant differences regarding endothelial-dependent (acetylcholine stimulation or postocclusive reactive hyperemia) or endothelial-independent (sodium nitroprusside stimulation) microvascular reactivity among the groups.

CONCLUSIONS

Individuals with MUO had lower baseline systemic microvascular flow than those with MHNW or MHO, but endothelium-dependent or endothelium-independent microvascular reactivity were not changed in any of the groups. The relatively young age of the study population, the low frequency of class III obesity, or the strict definition of MHO (absence of any metabolic syndrome criteria) might account for the lack of difference of microvascular reactivity among MHNW, MHO or MUO.

Triglyceride glucose index, pediatric NAFLD fibrosis index, and triglyceride-to-high-density lipoprotein cholesterol ratio are the most predictive markers of the metabolically unhealthy phenotype in overweight/obese adolescent boys

Introduction

The prevalence of obesity constantly increases worldwide and definitely increases the risk of premature death in early adulthood. While there is no treatment yet with proven efficacy for the metabolic clamp such as arterial hypertension, dyslipidemia, insulin resistance, diabetes type 2, and fatty liver disease, it is imperative to find a way to decrease cardiometabolic complications. Early prevention strategies beginning in childhood are the most logical step to reduce future cardiovascular morbidity and mortality. Therefore, the aim of the current study is to determine the most sensitive and specific predictive markers of the metabolically unhealthy phenotype with high cardiometabolic risk in overweight/obese adolescent boys.

Methods

This study was carried out at the Ternopil Regional Children's hospital (Western Ukraine) and involved 254 randomly chosen adolescent overweight or obese boys [median age was 16.0 (15.0,16.1) years]. A control group of 30 healthy children with proportional body weight comparable in gender and age to the main group was presented. A list of anthropometrical markers with biochemical values of carbohydrate and lipid metabolism with hepatic enzymes was determined. All overweight/obese boys were divided into three groups: 51.2% of the boys with metabolic syndrome (MetS) based on the IDF criteria; 19.7% of the boys were metabolically healthy obese (MHO) without hypertension, dyslipidemia, and hyperglycemia; and the rest of the boys (29.1%) were classified as metabolically unhealthy obese (MUO) with only one criterion (hypertension, dyslipidemia, or hyperglycemia).

Results

Based on multiple logistic regression analysis that included all anthropometric and biochemical values and calculated indexes in boys from the MHO group and MetS, it was revealed that the maximum likelihood in the prediction of MetS makes the combination of triglyceride glucose index, pediatric nonalcoholic fatty liver disease fibrosis index (PNFI), and triglyceride-to-high-density lipoprotein cholesterol ratio (R² =0.713, p<0.000). By tracing the receiver operating characteristic curve, the model is confirmed as a good predictor of MetS (AUC=0.898, odds ratio=27.111 percentage correct=86.03%) in overweight and obese boys.

Conclusion

Triglyceride glucose index, pediatric NAFLD fibrosis index, and triglyceride-to-high-density lipoprotein cholesterol ratio are a valuable combination of predictive markers of the metabolically unhealthy phenotype in Ukrainian overweight/obese boys.

Metabolic phenotypes and risk of end-stage kidney disease in patients with type 2 diabetes

BACKGROUND

Obesity often initiates or coexists with metabolic abnormalities. This study aimed to investigate the pathological characteristics and the independent or mutual relations of obesity and metabolic abnormalities with end-stage kidney disease (ESKD) in patients with type 2 diabetes (T2D) and associated diabetic kidney disease (DKD).

METHODS

A total of 495 Chinese patients with T2D and biopsy-confirmed DKD between 2003 and 2020 were enrolled in this retrospective study. The metabolic phenotypes were based on the body weight index (BMI)-based categories (obesity, BMI ≥ 25.0 kg/m2) and metabolic status (metabolically unhealthy status, ≥ 1 criterion National Cholesterol Education Program Adult Treatment Panel III (NCEP/ATP III) excluding waist circumference and hyperglycemia) and were categorized into four types: metabolically healthy non-obesity (MHNO), metabolically healthy obesity (MHO), metabolically unhealthy non-obesity (MUNO), and metabolically unhealthy obesity (MUO). The pathological findings were defined by the Renal Pathology Society classification. Cox proportional hazards models were used to estimate hazard ratios (HRs) for ESKD.

RESULTS

There are 56 (11.3%) MHNO patients, 28 (5.7%) MHO patients, 176 (35.6%) MUNO patients, and 235 (47.5%) MUO patients. The high prevalence of the Kimmelstiel-Wilson nodule and severe mesangial expansion were associated with obesity, whereas severe IFTA was related to metabolically unhealthy status. In the multivariate analysis, the adjusted HR (aHR) was 2.09 [95% confidence interval (CI) 0.99-4.88] in the MHO group, 2.16 (95% CI 1.20-3.88) in the MUNO group, and 2.31 (95% CI 1.27-4.20) in the MUO group compared with the MHNO group. Furthermore, the presence of obesity was insignificantly associated with ESKD compared with non-obese patients (aHR 1.22, 95% CI 0.88-1.68), while the metabolically unhealthy status was significantly associated with ESKD compared to the metabolically healthy status in the multivariate analysis (aHR 1.69, 95% CI 1.10-2.60).

CONCLUSION

Obesity itself was insignificantly associated with ESKD; however, adding a metabolically unhealthy status to obesity increased the risk for progression to ESKD in T2D and biopsy-proven DKD.

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.

Chewing the fat: How lipidomics is changing our understanding of human health and disease in 2022

Lipids are biological molecules that play vital roles in all living organisms. They perform many cellular functions, such as 1) forming cellular and subcellular membranes, 2) storing and using energy, and 3) serving as chemical messengers during intra- and inter-cellular signal transduction. The large-scale study of the pathways and networks of cellular lipids in biological systems is called "lipidomics" and is one of the fastest-growing omics technologies of the last two decades. With state-of-the-art mass spectrometry instrumentation and sophisticated data handling, clinical studies show how human lipid composition changes in health and disease, thereby making it a valuable medium to collect for clinical applications, such as disease diagnostics, therapeutic decision-making, and drug development. This review gives a comprehensive overview of current workflows used in clinical research, from sample collection and preparation to data and clinical interpretations. This is followed by an appraisal of applications in 2022 and a perspective on the exciting future of clinical lipidomics.

Assessment of the Impact of Increased Physical Activity on Body Mass and Adipose Tissue Reduction in Overweight and Obese Children

(1) Background: Within the last 30 years, growing rates of child overweight and obesity have been observed as a very concerning phenomenon in most countries worldwide. The research aim was to assess what effect increased physical activity has on reducing body mass and adipose tissue in children between 10 and 11 years of age as well as to answer the question of whether physical activity could be considered as a factor in preventing child overweight and obesity when maintaining their existing diet and lifestyle. (2) Material and methods: There were 419 sports class primary school pupils in the experimental group who, in addition to four obligatory weekly physical education hours, attended six training hours. The control group comprised 485 children from parallel non-sports classes. In all pupils, height and weight measurements as well as physical fitness measurements were taken twice, at the beginning and end of the school year. Cole's method was used to assess the children's normal body weight. With the help of this method, children with excessive body weight were selected from the entire study group (N = 904), who additionally had skinfolds and adipose tissue measured using the BIA electrical bioimpedance method. The obtained results were interpreted using the variance analysis for repeated measurements and LSD test. (3) Results: The number of children with excessive body mass after 10 months of increased physical activity decreased (in the case of overweight: p = 0.0014, obesity: p = 0.0022), as did their skinfolds (p ≤ 0.001) and body fat (p ≤ 0.001), while their physical fitness considerably improved compared to the control group. (4) Conclusions: The introduction of increased physical activity in the experimental group children when maintaining their existing diet and lifestyle contributed to reducing their obesity and overweight and, at the same time, proved to be an effective factor in the process of decreasing their excessive body mass.

An integrated multi-omic approach demonstrates distinct molecular signatures between human obesity with and without metabolic complications: a case-control study

OBJECTIVES

To examine the hypothesis that obesity complicated by the metabolic syndrome, compared to uncomplicated obesity, has distinct molecular signatures and metabolic pathways.

METHODS

We analyzed a cohort of 39 participants with obesity that included 21 with metabolic syndrome, age-matched to 18 without metabolic complications. We measured in whole blood samples 754 human microRNAs (miRNAs), 704 metabolites using unbiased mass spectrometry metabolomics, and 25,682 transcripts, which include both protein coding genes (PCGs) as well as non-coding transcripts. We then identified differentially expressed miRNAs, PCGs, and metabolites and integrated them using databases such as mirDIP (mapping between miRNA-PCG network), Human Metabolome Database (mapping between metabolite-PCG network) and tools like MetaboAnalyst (mapping between metabolite-metabolic pathway network) to determine dysregulated metabolic pathways in obesity with metabolic complications.

RESULTS

We identified 8 significantly enriched metabolic pathways comprising 8 metabolites, 25 protein coding genes and 9 microRNAs which are each differentially expressed between the subjects with obesity and those with obesity and metabolic syndrome. By performing unsupervised hierarchical clustering on the enrichment matrix of the 8 metabolic pathways, we could approximately segregate the uncomplicated obesity strata from that of obesity with metabolic syndrome.

CONCLUSIONS

The data suggest that at least 8 metabolic pathways, along with their various dysregulated elements, identified via our integrative bioinformatics pipeline, can potentially differentiate those with obesity from those with obesity and metabolic complications.

Association of metabolically healthy obesity in young adulthood with myocardial structure and function

BACKGROUND

Obesity is major cause of cardiovascular diseases. Metabolically healthy obesity (MHO) may increase heart failure risk early in life, and may be reflected in impaired cardiac structure and function. Therefore, we aimed to examine the relationship between MHO in young adulthood and cardiac structure and function.

METHODS

A total of 3066 participants from the Coronary Artery Risk Development in Young Adults (CARDIA) study were included, who completed echocardiography in young adulthood and middle age. The participants were grouped by obesity status (body mass index ≥30 kg/m²) and poor metabolic health (≥2 criteria for metabolic syndrome) into four metabolic phenotypes as follows: metabolically healthy non-obesity (MHN), MHO, metabolically unhealthy non-obesity (MUN), metabolically unhealthy obesity (MUO). The associations of the metabolic phenotypes (MHN serving as the reference) with left ventricular (LV) structure and function were evaluated using multiple linear regression models.

RESULTS

At baseline, mean age was 25 years, 56.4% were women, and 44.7% were black. After a follow-up 25 years, MUN in young adulthood was associated with worse LV diastolic function (E/é ratio, β [95% CI], 0.73 [0.18, 1.28]), worse systolic function (global longitudinal strain [GLS], 0.60 [0.08, 1.12]) in comparison with MHN. MHO and MUO were associated with LV hypertrophy (LV mass index, 7.49 g/m² [4.63, 10.35]; 18.23 g/m² [12.47, 23.99], respectively), worse diastolic function (E/é ratio, 0.67 [0.31, 1.02]; 1.47 [0.79, 2.14], respectively), and worse systolic function (GLS, 0.72 [0.38, 1.06]; 1.35 [0.64, 2.05], respectively) in comparison with MHN. These results were consistent in several sensitivity analyses.

CONCLUSIONS

In this community-based cohort using data from the CARDIA study, obesity in young adulthood was significantly associated with LV hypertrophy, worse systolic and diastolic function regardless of metabolic status. Relationship of Baseline Metabolic Phenotypes with Young Adulthood and Midlife Cardiac Structure and Function. Adjusted for year 0 covariates: age, sex, race, educational level, smoking status, drinking status, and physical activity; metabolically healthy non-obesity was used as a reference category for comparison. ^† Criteria for metabolic syndrome are listed in Supplementary Table S6. MUN metabolically unhealthy non-obesity, MHO metabolically healthy obesity, LVMi left ventricular mass index, LVEF left ventricular ejection fraction, E/A early to late peak diastolic mitral flow velocity ratio, E/é mitral inflow velocity to early diastolic mitral annular velocity, CI confidence interval.

Genetic Background of Metabolically Healthy and Unhealthy Obesity Phenotypes in Hungarian Adult Sample Population

A specific phenotypic variant of obesity is metabolically healthy (MHO), which is characterized by normal blood pressure and lipid and glucose profiles, in contrast to the metabolically unhealthy variant (MUO). The genetic causes underlying the differences between these phenotypes are not yet clear. This study aims to explore the differences between MHO and MUO and the contribution of genetic factors (single nucleotide polymorphisms-SNPs) in 398 Hungarian adults (81 MHO and 317 MUO). For this investigation, an optimized genetic risk score (oGRS) was calculated using 67 SNPs (related to obesity and to lipid and glucose metabolism). Nineteen SNPs were identified whose combined effect was strongly associated with an increased risk of MUO (OR = 1.77, p < 0.001). Four of them (rs10838687 in MADD, rs693 in APOB, rs1111875 in HHEX, and rs2000813 in LIPG) significantly increased the risk of MUO (OR = 1.76, p < 0.001). Genetic risk groups based on oGRS were significantly associated with the risk of developing MUO at a younger age. We have identified a cluster of SNPs that contribute to the development of the metabolically unhealthy phenotype among Hungarian adults suffering from obesity. Our findings emphasize the significance of considering the combined effect(s) of multiple genes and SNPs in ascertaining cardiometabolic risk in obesity in future genetic screening programs.

Metabolically Healthy Obesity: Are Interventions Useful?

PURPOSE OF REVIEW

This review aims to detail the current global research state of metabolically healthy obesogenesis with regard to metabolic factors, disease prevalence, comparisons to unhealthy obesity, and targeted interventions to reverse or delay progression from metabolically healthy to unhealthy obesity.

RECENT FINDINGS

As a long-term condition with increased risk of cardiovascular, metabolic, and all-cause mortality risks, obesity threatens public health on a national level. The recent discovery of metabolically healthy obesity (MHO), a transitional condition during which obese persons carry comparatively lower health risks, has added to confusion about the true effect of visceral fat and subsequent long-term health risks. In this context, the evaluation of fat loss interventions, such as bariatric surgery, lifestyle changes (diet/exercise), and hormonal therapies require re-evaluation in light of evidence that progression to high-risk stages of obesity relies on metabolic status and that strategies to protect the metabolism may be useful in the prevention of metabolically unhealthy obesity. Typical calorie-based exercise and diet interventions have failed to reduce the prevalence of unhealthy obesity. Holistic lifestyle, psychological, hormonal, and pharmacological interventions for MHO, on the other hand, may at least prevent progression to metabolically unhealthy obesity.

Prevalence and Predictive Clinical Characteristics of Metabolically Healthy Obesity in Obese Children and Adolescents

BACKGROUND

The increasing prevalence of childhood obesity and accompanying comorbidities all over the world constitutes one of the most important public health problems of the changing world. The frequency and causes of the metabolically healthy obesity (MHO) phenotype in children is not clear.

OBJECTIVE

The objective is to determine the prevalence of the MHO phenotype in obese Turkish children and adolescents and to identify clinical and biochemical indicators for this phenotype.

METHODS

Eight hundred forty-seven obese children and adolescents, aged 3-18 years with BMI-SDS >+2 SD from the obesity outpatient clinic were included. Demographic, anthropometric, and physical examination information was collected from patient medical files. In addition, obesity-related comorbidities and results of laboratory tests were obtained. For study purposes, obese patients with no cardiometabolic risk factors were accepted as MHO, and those with ≥1 cardiometabolic risk factor were considered metabolically unhealthy obese (MUO). MHO was defined according to Damanhoury's criteria.

RESULTS

Out of 847 children (mean age 10.6±3.4 years) who met the study criteria, 289 (34.1%) were diagnosed with MHO. Being younger, prepubertal, having relatively low BMI, low waist/hip ratio, low insulin resistance (HOMA-IR) index, high high-density lipoprotein, low triglyceride, low fasting insulin and glucose levels, low uric acid and low alanine transaminase (ALT) levels were associated with MHO.

CONCLUSIONS

The MHO phenotype was present in just over a third of this obese pediatric cohort. The most important factors associated with MHO; age, waist-hip ratio, and BMI were determined.

Nutrients, Physical Activity, and Mitochondrial Dysfunction in the Setting of Metabolic Syndrome

Metabolic syndrome (MetS) is a cluster of metabolic risk factors for diabetes, coronary heart disease, non-alcoholic fatty liver disease, and some tumors. It includes insulin resistance, visceral adiposity, hypertension, and dyslipidemia. MetS is primarily linked to lipotoxicity, with ectopic fat deposition from fat storage exhaustion, more than obesity per se. Excessive intake of long-chain saturated fatty acid and sugar closely relates to lipotoxicity and MetS through several pathways, including toll-like receptor 4 activation, peroxisome proliferator-activated receptor-gamma regulation (PPARγ), sphingolipids remodeling, and protein kinase C activation. These mechanisms prompt mitochondrial dysfunction, which plays a key role in disrupting the metabolism of fatty acids and proteins and in developing insulin resistance. By contrast, the intake of monounsaturated, polyunsaturated, and medium-chain saturated (low-dose) fatty acids, as well as plant-based proteins and whey protein, favors an improvement in sphingolipid composition and metabolic profile. Along with dietary modification, regular exercises including aerobic, resistance, or combined training can target sphingolipid metabolism and improve mitochondrial function and MetS components. This review aimed to summarize the main dietary and biochemical aspects related to the physiopathology of MetS and its implications for mitochondrial machinery while discussing the potential role of diet and exercise in counteracting this complex clustering of metabolic dysfunctions.

Body Mass Index Measured Repeatedly over 42 Years as a Risk Factor for Ischemic Stroke: The HUNT Study

BACKGROUND

Higher BMI in middle age is associated with ischemic stroke, but little is known about BMI over adulthood, and the risk for ischemic stroke as most studies relied on a single measurement of BMI.

METHODS

BMI was measured four times over a period of 42 years. We calculated average BMI values and group-based trajectory models and related these to the prospective risk of ischemic stroke after the last examination in Cox models with a follow-up time of 12 years.

RESULTS

A total of 14,139 participants, with a mean age of 65.2 years and 55.4% women, had information on BMI from all four examinations, and we observed 856 ischemic strokes. People with overweight and obesity over adulthood had a higher risk for ischemic stroke with a multivariable-adjusted hazard ratio of 1.29 (95% CI 1.11-1.48) and 1.27 (95% CI 0.96-1.67), respectively, when compared to normal weight participants. Excess weight tended to have stronger effects earlier than later in life. A trajectory of developing obesity throughout life was associated with higher risk than other trajectories.

CONCLUSIONS

High average BMI, especially at an early age, is a risk factor for ischemic stroke. Early weight control and long-term weight reduction for those with high BMI may decrease the later occurrence of ischemic stroke.

Heart Disease and Stroke Statistics-2023 Update: A Report From the American Heart Association

BACKGROUND

The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The American Heart Association, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2023 Statistical Update is the product of a full year's worth of effort in 2022 by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. The American Heart Association strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional COVID-19 (coronavirus disease 2019) publications, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Lack of association between metabolic phenotype and food consumption by degree of food processing: results from the Study of Workers' Health (ESAT)

Introduction

Introduction: an increase in the consumption of processed and ultra-processed foods may predispose to metabolic abnormalities. Objective: to verify the association of food consumption with metabolic phenotype in workers from a quaternary hospital in Rio de Janeiro, Brazil. Methods: workers of both sexes aged > 18 years were eligible. A food frequency questionnaire and the NOVA classification were used in the food consumption analysis. Metabolic phenotype considered the presence of at least one metabolic alteration (blood glucose, serum lipids, and blood pressure) combined with BMI (eutrophic or excess weight) as follows: 1) metabolically healthy eutrophic (MHE); 2) metabolically unhealthy eutrophic (MUE); 3) metabolically healthy excess weight (MHEW); 4) metabolically unhealthy excess weight (MUEW). Results: from the included 160 participants (mean age, 45.2 ± 1.1 years; 59.4 %, women), 21.9 % self-reported arterial hypertension and 4.4 % diabetes. Most presented excess weight (74.6 %), with approximately 40 % being obese. The MUEW phenotype had higher body fat percentage and central adiposity represented by higher WC and VFA in comparison to the other phenotypes. The lean body mass was similar between the groups. The median of ultra-processed foods was 32.4 % for eutrophic, 32.7 % for overweight, and 34.3 % for obese subjects. No significant associations were observed between ultra-processed food consumption and metabolically unhealthy eutrophic (OR: 1.01; 95 % CI: 0.96-1.06), metabolically healthy excess weight (OR: 1.03; 95 % CI: 0.98-1.08), and metabolically unhealthy excess weight (OR: 1.00; 95 % CI: 0.96-1.05) in comparison to metabolically healthy eutrophic. Conclusion: consumption of ultra-processed food was high. In this cross-sectional analysis, no association of metabolic phenotypes with consumption of food groups according to degree of food processing were observed.

A phenome-wide comparative analysis of genetic discordance between obesity and type 2 diabetes

Obesity and type 2 diabetes are causally related, yet there is considerable heterogeneity in the consequences of both conditions and the mechanisms of action are poorly defined. Here we show a genetic-driven approach defining two obesity profiles that convey highly concordant and discordant diabetogenic effects. We annotate and then compare association signals for these profiles across clinical and molecular phenotypic layers. Key differences are identified in a wide range of traits, including cardiovascular mortality, fat distribution, liver metabolism, blood pressure, specific lipid fractions and blood levels of proteins involved in extracellular matrix remodelling. We find marginal differences in abundance of Bacteroidetes and Firmicutes bacteria in the gut. Instrumental analyses reveal prominent causal roles for waist-to-hip ratio, blood pressure and cholesterol content of high-density lipoprotein particles in the development of diabetes in obesity. We prioritize 17 genes from the discordant signature that convey protection against type 2 diabetes in obesity, which may represent logical targets for precision medicine approaches.

The risk for chronic kidney disease in metabolically healthy obese patients: A systematic review and meta-analysis

BACKGROUND

Chronic kidney disease (CKD) is associated with obesity and metabolic syndrome. Nevertheless, the association of CKD with phenotype referred as metabolically healthy obese or overweight is unclear. In this this systematic review and meta-analysis, we investigate the relationships between obesity and CKD independent of metabolic syndrome by appraising published evidence in studies focusing on metabolically healthy obese people.

MATERIALS AND METHODS

We performed a literature search through three databases Embase (Elsevier), the Cochrane Central Register of Controlled Trials (Wiley) and PubMed/Medline Web of Science up to March 2022 with the following terms: "chronic kidney disease", "kidney function", "obesity", "metabolic syndrome", "metabolically healthy obesity", "metabolically healthy overweight". Metabolically unhealthy was defined an individual having at least 3 of the following: abdominal obesity, high blood pressure, hypertriglyceridemia, low HDL cholesterol and hyperglycaemia. We used Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) for reporting. Prospective, retrospective, randomized and nonrandomized studies fitting the search criteria were included in our results.

RESULTS

Our final analysis included 16 studies with a total number of 4.965.285 participants. There is considerable heterogeneity in terms of study design, participant characteristics and number of participants across individual studies. In comparison to healthy normal weight patients, the risk was progressively higher in overweight (RR 1.29, 95% CI 1.27 to 1.32, p < 0.001) and obese patients (RR 1.47, 95% CI 1.31 to 1.65, p < 0.001).

CONCLUSION

Metabolically healthy overweight and obese individuals have higher risk of CKD compared to individuals without weight excess.

Association between different metabolic phenotypes and the development of hypothyroidism: 9 years follow-up of Tehran thyroid study

PURPOSE

The association between metabolic phenotypes and thyroid function has not yet been established; therefore, this study examined whether different metabolic phenotypes are associated with the development of hypothyroidism.

METHODS

Study participants were selected from the Tehran Thyroid Study (TTS). A total of 3338 euthyroid adults were included and categorized into four obesity phenotype groups: metabolically healthy normal weight (MHNW), metabolically healthy obese (MHO), metabolically unhealthy normal weight (MUNW), and metabolically unhealthy obese (MUO). The participants were assessed at baseline and during three follow-up studies at three-year intervals. Multiple logistic regression analysis was used to examine the relationship between metabolic phenotypes and the development of hypothyroidism.

RESULTS

In the total population, the chi-square test was only significant (P=0.008) in 3^rd year with a higher prevalence of hypothyroidism in the MUNW phenotype, followed by MHO, MUO, and MHNW. Moreover, in the 3^rd and 9^th years of follow-up, hypothyroidism was more prevalent in MUO only in male subjects (P=0.002 and 0.035, respectively). In the unadjusted model, the MHO phenotype increased the odds of hypothyroidism compared with the MHNW phenotype (OR=1.51; 95% CI=1.04, 2.18; P-value=0.031). After adjusting for confounding factors, the odds of hypothyroidism were higher in the MUNW (OR=1.86; 95% CI=1.17, 2.96; P-value=0.008), MHO (OR=1.71; 95% CI=1.09, 2.67; P-value=0.018), and MUO (OR=1.64; 95% CI=1.03, 2.62; P-value=0.036) phenotypes than in the MHNW group. The MUNW phenotype increased the risk of hypothyroidism compared to MHNW, only in males. However, in females, the MHO phenotype increased the risk of hypothyroidism compared to MHNW.

CONCLUSION

Both obesity and metabolic abnormalities are associated with hyperthyroidism. Healthy metabolic and weight maintenance were associated with a lower risk of hypothyroidism in males and females.

Is insulin resistance tissue-dependent and substrate-specific? The role of white adipose tissue and skeletal muscle

Insulin resistance (IR) refers to a reduction in the ability of insulin to exert its metabolic effects in organs such as adipose tissue (AT) and skeletal muscle (SM), leading to chronic diseases such as type 2 diabetes, hepatic steatosis, and cardiovascular diseases. Obesity is the main cause of IR, however not all subjects with obesity develop clinical insulin resistance, and not all clinically insulin-resistant people have obesity. Recent evidence implies that IR onset is tissue-dependent (AT or SM) and/or substrate-specific (glucometabolic or lipometabolic). Therefore, the aims of the present review are 1) to describe the glucometabolic and lipometabolic activities of insulin in AT and SM in the maintenance of whole-body metabolic homeostasis, 2) to discuss the pathophysiology of substrate-specific IR in AT and SM, and 3) to highlight novel validated tests to assess tissue and substrate-specific IR that are easy to perform in clinical practice. In AT, glucometabolic IR reduces glucose availability for glycerol and fatty acid synthesis, thus decreasing the esterification and synthesis of signaling bioactive lipids. Lipometabolic IR in AT impairs the antilipolytic effect of insulin and lipogenesis, leading to an increase in circulating FFAs and generating lipotoxicity in peripheral tissues. In SM, glucometabolic IR reduces glucose uptake, whereas lipometabolic IR impairs mitochondrial lipid oxidation, increasing oxidative stress and inflammation, all of which lead to metabolic inflexibility. Understanding tissue-dependent and substrate-specific IR is of paramount importance for early detection before clinical manifestations and for the development of more specific treatments or direct interventions to prevent chronic life-threatening diseases.

Transition patterns of metabolism-weight phenotypes over time: A longitudinal study using the multistate Markov model in China

Background

A change in weight or metabolic status is a dynamic process, yet most studies have focused on metabolically healthy obesity (MHO) and the transition between MHO and metabolically unhealthy obesity (MUO); therefore, they have not fully revealed the nature of all possible transitions among metabolism-weight phenotypes over the years.

Methods

This was a longitudinal study based on a retrospective health check-up cohort. A total of 9,742 apparently healthy individuals aged 20-60 years at study entry were included and underwent at least two health check-ups. Six metabolism-weight phenotypes were cross-defined by body mass index (BMI) categories and metabolic status as follows: metabolically healthy normal weight (MHNW), metabolically healthy overweight (MHOW), MHO, metabolically unhealthy normal weight (MUNW), metabolically unhealthy overweight (MUOW), and MUO. A multistate Markov model was used to analyse all possible transitions among these phenotypes and assess the effects of demographic and blood indicators on the transitions.

Results

The transition intensity from MUNW to MHNW was the highest (0.64), followed by the transition from MHO to MUO (0.56). The greatest sojourn time appeared in the MHNW state (3.84 years), followed by the MUO state (2.34 years), and the shortest sojourn time appeared in the MHO state (1.16 years). Transition intensities for metabolic improvement gradually decreased with BMI level as follows: 0.64 for MUNW to MHNW, 0.44 for MUOW to MHNW, and 0.27 for MUO to MHO; however, transition intensities for metabolic deterioration, including MHNW to MUNW, MHOW to MUOW, and MHO to MUO, were 0.15, 0.38, and 0.56, respectively. In the middle-aged male group, elevated alanine aminotransferase (ALT), aspartate aminotransferase (AST), and uric acid (UA) increased the risk of deterioration in weight and metabolic status and decreased the possibility of improvement.

Conclusion

Maintaining a normal and stable BMI is important for metabolic health. More attention should be given to males and elderly people to prevent their progression to an unhealthy metabolic and/or weight status. MHO is the most unstable phenotype and is prone to convert to the MUO state, and individuals with abnormal ALT, AST and UA are at an increased risk of transitioning to an unhealthy weight and/or metabolic status; therefore, we should be alert to abnormal indicators and MHO. Intervention measures should be taken early to maintain healthy weight and metabolic status.

Role of physical activity and cardiorespiratory fitness in metabolically healthy obesity: a narrative review

Obesity has been associated with a multitude of metabolic disorders, often clustering with risk factors of cardiovascular disease and type 2 diabetes mellitus, hypertension, dyslipidaemia. Overall, obesity is a worldwide, growing health concern. However, a subgroup of obese individuals with a low burden of metabolic abnormalities have been identified and described as metabolically healthy obese (MHO). Whether the MHO phenotype is protective against obesity-related metabolic disorders in the long-term is presently unclear, and current research examining the potential transition has yielded inconsistent results. In this current narrative review, we aim to provide insights on the role of physical activity (PA) and cardiorespiratory fitness (CRF) in MHO. Lifestyle factors such as PA and CRF may influence the MHO phenotype. Limited studies have characterised energy expenditure and CRF in MHO and metabolically unhealthy obese. However, higher levels of PA, less sedentary behaviour and higher CRF have been observed in MHO individuals. Considering the multiple benefits of PA, it is high time to advocate this lifestyle change beyond its influence on energy balance in a weight loss programme to improve cardiovascular and metabolic risk factors irrespective of body weight and fat mass changes. Improved CRF via increased PA, especially exercise participation, while avoiding weight gain is not only a realistic goal, but should be the primary intervention for MHO populations to prevent the transition to an abnormal metabolic state.

Enhancing SIRT1 Gene Expression Using Small Activating RNAs: A Novel Approach for Reversing Metabolic Syndrome

Metabolic syndrome (MetS) is a pathological condition characterized by abdominal obesity, insulin resistance, hypertension, and hyperlipidemia. Sirtuin 1 (SIRT1), a highly conserved histone deacetylase, is characterized as a key metabolic regulator and protector against aging-associated pathologies, including MetS. In this study, we investigate the therapeutic potential of activating SIRT1 using small activating RNAs (saRNA), thereby reducing inflammatory-like responses and re-establishing normal lipid metabolism. SIRT1 saRNA significantly increased SIRT1 messenger RNA (mRNA) and protein levels in both lipopolysaccharide-stimulated and nonstimulated macrophages. SIRT1 saRNA significantly decreased inflammatory-like responses, by reducing mRNA levels of key inflammatory cytokines, such as Tumor Necrosis Factor alpha, Interleukin 1 beta (IL-1β), Interleukin 6 (IL-6), and chemokines Monocyte Chemoattractant Protein-1 and keratinocyte chemoattractant. SIRT1 overexpression also significantly reduced phosphorylation of nuclear factor-κB and c-Jun N-terminal kinase, both key signaling molecules for the inflammatory pathway. To investigate the therapeutic effect of SIRT1 upregulation, we treated a high-fat diet model with SIRT1 saRNA conjugated to a transferrin receptor aptamer for delivery to the liver and cellular internalization. Animals in the SIRT1 saRNA treatment arm demonstrated significantly decreased weight gain with a significant reduction in white adipose tissue, triglycerides, fasting glucose levels, and intracellular lipid accumulation. These suggest treatment-induced changes to lipid and glucose metabolism in the animals. The results of this study demonstrate that targeted activation of SIRT1 by saRNAs is a potential strategy to reverse MetS.

Comprehensive Review of Cardiovascular Disease Risk in Nonalcoholic Fatty Liver Disease

Nonalcoholic Fatty Liver Disease (NAFLD) is a growing global phenomenon, and its damaging effects in terms of cardiovascular disease (CVD) risk are becoming more apparent. NAFLD is estimated to affect around one quarter of the world population and is often comorbid with other metabolic disorders including diabetes mellitus, hypertension, coronary artery disease, and metabolic syndrome. In this review, we examine the current evidence describing the many ways that NAFLD itself increases CVD risk. We also discuss the emerging and complex biochemical relationship between NAFLD and its common comorbid conditions, and how they coalesce to increase CVD risk. With NAFLD's rising prevalence and deleterious effects on the cardiovascular system, a complete understanding of the disease must be undertaken, as well as effective strategies to prevent and treat its common comorbid conditions.

Diagnostic accuracy of the waist-to-height ratio and other anthropometric indices for metabolically healthy obesity in the working population

Approximately one-third of overweight individuals, and half of those with obesity, do not have cardiometabolic disorders. For this reason, a phenotype called metabolically healthy obese (MHO) has emerged to describe this population group. The early detection of this situation could save costs associated with the development of comorbidities or pharmacological interventions. Therefore, the aim is to know the prevalence of MHO in the working population and propose variables for its detection. Cross-sectional descriptive study of 635 workers of the Cordoba City Council was carried out based on the results of the 2016 health surveillance. The outcome variables were the MHO, established based on the criteria of the IDF, NCEP-ATP III, and Aguilar-Salinas. In addition, the degree of agreement between the different MHO criteria was studied using Cohen's kappa (k), and the predictive capacity of the anthropometric variables was assessed with Receiver Operator Curves. The prevalence of MHO ranged from 6.6 to 9%. The highest agreement was reached between the IDF and NCEP-ATP III definitions (k = 0.811; 95% CI 0.724-0.898; p < 0.001). The waist-to-height ratio (WHtR) showed the highest discriminant capacity for MHO, with its best cut-off point at 0.55 for all criteria used. Sensitivity ranged from 84 to 93%. The prevalence of MHO in the working population differed according to the criteria used for diagnosis. The anthropometric variable with the highest discriminant capacity for MHO was WHtR, presenting the same cut-off point in the three criteria analyzed. Therefore, WHtR is the variable that best detects the presence of MHO.

Association of cumulative excess weight and waist circumference exposure with transition from metabolically healthy obesity to metabolically unhealthy

BACKGROUND AND AIMS

The association between obesity severity and duration with the transition from metabolically healthy obese/overweight (MHO) phenotype to metabolically unhealthy obese (MUO) phenotype is not well understood.

METHODS AND RESULTS

This study includes the Tehran Lipid and Glucose Study participants who were initially classed as MHO. Cumulative excess weight (CEW) and cumulative excess waist circumference (CEWC) scores, which represent the accumulation of body mass index and waist circumference deviations from expected values over time (kg/m² ∗ y and cm ∗ y, respectively), were calculated until the transition from MHO to MUO or the end of follow-up. The sex-stratified association of CEW and CWEC with the transition from MHO to MUO was investigated by time-dependent Cox models, adjusting for confounders. Out of 2525 participants, 1732 (68.5%) were women. During 15 years of follow-up, 1886 (74.6%) participants transitioned from MHO to MUO. A significant association was found between CEW and CEWC quartiles with the development of MUO among women participants (fully adjusted hazard ratios in the fourth quartile of CEW and CEWC [95% (CI)]:1.65 [1.37-1.98] and [95% CI]: 1.83 [1.53-2.19]). There was no significant association between CEW and CEWC with the MHO transition to MUO among men participants.

CONCLUSION

Over 15 years of follow-up in TLGS, general and central obesity accumulation was associated with the increased transition from MHO to MUO among women participants. More research with a larger sample size is needed to confirm and explain why the results are different for men and women.

Relationship between metabolically healthy obesity and the development of hypertension: a nationwide population-based study

BACKGROUND

Metabolically healthy obesity (MHO), has been recognized as a transient phenotype with few cardiometabolic diseases; however, little is known regarding the development of hypertension in subjects with an absence of cardiometabolic abnormalities and general obesity evaluated by body mass index (BMI) or abdominal obesity evaluated by waist circumference (WC).

METHODS

A total of 4764 participants were enrolled from the China Health and Nutrition Survey and followed up from 2009 to 2015, whose fasting blood samples were collected in 2009. Obesity was classified as abdominal obesity (WC ≥ 90 cm in men and ≥ 80 cm in women) and general obesity (BMI ≥ 25.0 kg/m²). Logistic regression was used to analyze the relationship between MHO and prehypertension (120 < SBP < 140 mmHg or 80 < DBP < 90 mmHg) and hypertension (SBP ≥ 140 or DBP ≥ 90 mmHg). The age- and sex-specific impacts were further analyzed.

RESULTS

There were 412 (37.9%) participants with prehypertension and 446 (41.0%) participants with hypertension and metabolically healthy abdominal obesity (MHAO). The participants with the MHAO phenotype had significantly higher risks of prehypertension [odds ratio (OR) = 1.89 (1.51-2.36), p < 0.001] and hypertension [OR = 2.58 (2.02-3.30), p < 0.001] than those metabolically healthy but without abdominal obesity. Similar associations were observed in the subjects with metabolically healthy general obesity (MHGO) phenotype, particularly those aged under 64 years. Men with the MHAO phenotype seemed to have higher risks of prehypertension [2.42 (1.52-3.86) in men vs. 1.76 (1.36-2.29) in women] and hypertension [3.80 (2.38-6.06) in men vs. 2.22 (1.64-3.00) in women] than women, when compared with those metabolically healthy but without abdominal obesity.

CONCLUSION

The MHO phenotype, regardless of the presence of general or abdominal obesity, showed a worse effect on the development of prehypertension and hypertension, particularly in young adults. Abdominal adiposity with a healthy metabolic state is significantly associated with incident hypertension in both men and women. These findings can guide the establishment of risk-stratified obesity treatments.

Body fat and muscle were associated with metabolically unhealthy phenotypes in normal weight and overweight/obesity in Yi people: A cross-sectional study in Southwest China

This study aimed to determine the association between the absolute mass, distribution, and relative ratio of body fat and muscle with the metabolically unhealthy (MU) phenotypes in normal weight and overweight/obesity in Yi people in China. The cross-sectional data from the Yi Migrants Study was used, which included 3,053 Yi people aged 20-80 years from the rural and urban sets. Participants were classified according to body mass index and metabolic status. Body composition including body fat percentage (BFP), fat mass index (FMI), visceral fat grade (VFG), muscle mass index (MMI), and muscle/fat ratio (M/F) were measured by bioelectrical impedance analysis. Restricted cubic spline and logistics regression models were used to test the associations between body composition parameters with MU phenotypes. Receiver-operating characteristic curves (ROC) were used to analyze the predictive value of MU phenotypes. Among the normal weight and overweight/obesity, 26.31% (497/1,889) and 52.15% (607/1,164) were metabolically unhealthy. Stratified by BMI, covariance analysis showed higher body fat (BFP, FMI, and VFG) and MMI in MU participants than in healthy participants. BFP, FMI, VFG, and MMI were positively associated with MU phenotypes both in normal weight and overweight/obesity after adjustment. M/F was significantly lower than MU participants and was negatively associated with MU phenotypes. BFP, FMI, VFG, and M/F could better predict MU phenotypes than BMI. We concluded that BFP, FMI, and VFG were positively associated with MU phenotypes, while M/F was negatively associated with MU phenotypes across the BMI categories in Yi people. Body fat and muscle measurement could be a valuable approach for obesity management.

The Levels of Bioelements in Postmenopausal Women with Metabolic Syndrome

(1) Metabolic syndrome is a set of factors that considerably increase the risk of developing atherosclerosis, type 2 diabetes, and their cardiovascular complications. Studies show that menopause and the levels of elements may be significantly associated with increased risk of MetS. The present study evaluated the relationship between element levels (Ca, P, Na, K, Fe, Mg, Cu, Zn, Sr) and the incidence of MetS and concomitant metabolic disorders in peri-menopausal women. (2) The study involved 170 perimenopausal women. The methods used were: survey, anthropometric measurement (WC, height, BMI, WHtR), blood pressure measurement, and biochemical analysis of venous blood (lipid profile, glucose, insulin, HbA1C). (3) The study demonstrated statistically significantly higher WC, WHtR, SBP, and DBP values in women with pre-Mets than in those with Mets and the control group. Significantly higher FPG, TG, LDL, HbA1C, insulin, TG/HDL ratio, and TC/HDL ratio were recorded in the MetS group compared to the rest of respondents. In addition, post hoc analysis revealed statistically significant differences in mean K concentrations between pre-MetS and MetS women. (4) Low blood K levels in perimenopausal women are associated with an increased risk of MetS. Significantly higher Cu levels were observed in overweight women. The concentration of Cu negatively correlates with the values of TC, LDL, and SBP.

Identification of genetic variants related to metabolic syndrome by next-generation sequencing

BACKGROUND

Metabolic syndrome (MetS) is a cluster of conditions associated with glucose intolerance, hypertension, abdominal obesity, dyslipidemia, and insulin resistance that increase the risk of cardiovascular diseases (CVD) and type 2 diabetes (T2D). Since MetS is known as a complex symptom with a high incidence of genetic factors, it is important to identify genetic variants for each clinical characteristic of MetS.

METHODS

We performed targeted next-generation sequencing (NGS) to identify genetic variants related to obesity, blood glucose, triacylglycerol (TG), and high-density lipoprotein (HDL)-cholesterol level, and hypertension in 48 subjects with MetS and in 48 healthy subjects.

RESULTS

NGS analysis revealed that 26 of 48 subjects (54.2%) with MetS had putative non-synonymous variants related to the clinical features of MetS. Of the subjects with MetS, 8 (16.7%) had variants in 4 genes (COL6A2, FTO, SPARC, and MTHFR) related to central obesity, 17 (35.4%) had variants in 6 genes (APOB, SLC2A2, LPA, ABCG5, ABCG8, and GCKR) related to hyperglycemia, 3 (6.3%) had variants in 4 genes (APOA1, APOC2, APOA4, and LMF1) related to hypertriglyceridemia, 8 (16.7%) had variants in 4 genes (ABCA1, CETP, SCARB1, and LDLR) related to low HDL-cholesterolemia, and 5 (10.4%) had variants in ADD1 related to hypertension.

CONCLUSIONS

Our findings may contribute to broadening the genetic spectrum of risk variants related to the development of MetS.

Metabolic Obesity Phenotypes and Risk of Lung Cancer: A Prospective Cohort Study of 450,482 UK Biobank Participants

(1) Background: The association between metabolic obesity phenotypes and incident lung cancer (LC) remains unclear. (2) Methods: Based on the combination of baseline BMI categories and metabolic health status, participants were categorized into eight groups: metabolically healthy underweight (MHUW), metabolically unhealthy underweight (MUUW), metabolically healthy normal (MHN), metabolically unhealthy normal (MUN), metabolically healthy overweight (MHOW), metabolically unhealthy overweight (MUOW), metabolically healthy obesity (MHO), and metabolically unhealthy obesity (MUO). The Cox proportional hazards model and Mendelian randomization (MR) were applied to assess the association between metabolic obesity phenotypes with LC risk. (3) Results: During a median follow-up of 9.1 years, 3654 incident LC patients were confirmed among 450,482 individuals. Compared with participants with MHN, those with MUUW had higher rates of incident LC (hazard ratio (HR) = 3.24, 95% confidence interval (CI) = 1.33-7.87, p = 0.009). MHO and MHOW individuals had a 24% and 18% lower risk of developing LC, respectively (MHO: HR = 0.76, 95% CI = 0.61-0.95, p = 0.02; MHO: HR = 0.82, 95% CI = 0.70-0.96, p = 0.02). No genetic association of metabolic obesity phenotypes and LC risk was observed in MR analysis. (4) Conclusions: In this prospective cohort study, individuals with MHOW and MHO phenotypes were at a lower risk and MUUW were at a higher risk of LC. However, MR failed to reveal any evidence that metabolic obesity phenotypes would be associated with a higher risk of LC.

Commentary-fat but fit…and cold? Potential evolutionary and environmental drivers of metabolically healthy obesity

As global obesity rates continue to rise, it is important to understand the origin, role and range of human variation of body mass index (BMI) in assessing health and healthcare. A growing body of evidence suggests that BMI is a poor indicator of health across populations, and that there may be a metabolically healthy obese phenotype. Here, we review the reasons why BMI is an inadequate tool for assessing cardiometabolic health. We then suggest that cold climate adaptations may also render BMI an uninformative metric. Underlying evolutionary and environmental drivers may allow for heat conserving larger body sizes without necessarily increasing metabolic health risks. However, there may also be a potential mismatch between modern obesogenic environments and adaptations to cold climates, highlighting the need to further investigate the potential for metabolically healthy obese phenotypes among circumpolar and other populations as well as the broader meaning for metabolic health.

The Relationship between Metabolic Syndrome and Frailty in Older People: A Systematic Review and Meta-Analysis

AIMS

Both metabolic syndrome (MetS) and frailty are associated with increased all-cause mortality, yet the complex interplay between these two conditions has not adequately been elucidated. We aim to analyse the relationship between MetS and frailty through a systematic review of the literature with meta-analyses.

METHODS

A literature search was conducted via MEDLINE and EMBASE. Studies were included if validated frameworks for defining frailty and MetS (presence of at least 3 out of the five constitutive components: abdominal obesity, high fasting blood glucose, hypertension, hypertriglyceridaemia, and low high-density lipoprotein level) were utilised, in addition to the inclusion of participants aged 60 or older.

RESULTS

Eleven studies were included, all observational. All were in community-dwelling older people, 9 cross-sectional and 2 longitudinal. Most of the studies used Fried's frailty phenotype. The prevalence of frailty ranged from 0.9% to 14.8% in population-based studies and 35.6% in the outpatient clinic setting. The prevalence of MetS was also higher in the outpatient clinic setting at 47.5%, compared to 17.5-41.0% in the community-dwelling populations. The meta-analysis of 11 studies showed that MetS was associated with an increased risk of frailty (pooled OR 1.73, 95% CI, 1.41-2.13).

CONCLUSION

This systematic review and meta-analysis suggest that frailty was more prevalent in older people with MetS compared to older people without MetS. The study findings suggest the importance of frailty screening in older people with MetS and a distinct role of managing MetS in preventing frailty in older people.

Metabolic dysfunction and obesity-related cancer: Beyond obesity and metabolic syndrome

OBJECTIVES

The metabolic dysfunction driven by obesity, including hyperglycemia and dyslipidemia, increases risk for developing at least 13 cancer types. The concept of "metabolic dysfunction" is often defined by meeting various combinations of criteria for metabolic syndrome. However, the lack of a unified definition of metabolic dysfunction makes it difficult to compare findings across studies. This review summarizes 129 studies that evaluated variable definitions of metabolic dysfunction in relation to obesity-related cancer risk and mortality after a cancer diagnosis. Strategies for metabolic dysfunction management are also discussed.

METHODS

A comprehensive search of relevant publications in MEDLINE (PubMed) and Google Scholar with review of references was conducted.

RESULTS

Metabolic dysfunction, defined as metabolic syndrome diagnosis or any number of metabolic syndrome criteria out of clinical range, inflammatory biomarkers, or markers of metabolic organ function, has been associated with risk for, and mortality from, colorectal, pancreatic, postmenopausal breast, and bladder cancers. Metabolic dysfunction associations with breast and colorectal cancer risk have been observed independently of BMI, with increased risk in individuals with metabolically unhealthy normal weight or overweight/obesity compared with metabolically healthy normal weight.

CONCLUSION

Metabolic dysfunction is a key risk factor for obesity-related cancer, regardless of obesity status. Nonetheless, a harmonized definition of metabolic dysfunction will further clarify the magnitude of the relationship across cancer types, enable better comparisons across studies, and further guide criteria for obesity-related cancer risk stratification.

Lipidomic Approaches to Study HDL Metabolism in Patients with Central Obesity Diagnosed with Metabolic Syndrome

The metabolic syndrome (MetS) is a cluster of cardiovascular risk factors characterised by central obesity, atherogenic dyslipidaemia, and changes in the circulating lipidome; the underlying mechanisms that lead to this lipid remodelling have only been partially elucidated. This study used an integrated "omics" approach (untargeted whole serum lipidomics, targeted proteomics, and lipoprotein lipidomics) to study lipoprotein remodelling and HDL composition in subjects with central obesity diagnosed with MetS (vs. controls). Compared with healthy subjects, MetS patients showed higher free fatty acids, diglycerides, phosphatidylcholines, and triglycerides, particularly those enriched in products of de novo lipogenesis. On the other hand, the "lysophosphatidylcholines to phosphatidylcholines" and "cholesteryl ester to free cholesterol" ratios were reduced, pointing to a lower activity of lecithin cholesterol acyltransferase (LCAT) in MetS; LCAT activity (directly measured and predicted by lipidomic ratios) was positively correlated with high-density lipoprotein cholesterol (HDL-C) and negatively correlated with body mass index (BMI) and insulin resistance. Moreover, many phosphatidylcholines and sphingomyelins were significantly lower in the HDL of MetS patients and strongly correlated with BMI and clinical metabolic parameters. These results suggest that MetS is associated with an impairment of phospholipid metabolism in HDL, partially led by LCAT, and associated with obesity and underlying insulin resistance. This study proposes a candidate strategy to use integrated "omics" approaches to gain mechanistic insights into lipoprotein remodelling, thus deepening the knowledge regarding the molecular basis of the association between MetS and atherosclerosis.

The Interaction Between Dietary Total Antioxidant Capacity and MC4R Gene and HOMA-IR in Metabolically Healthy and Unhealthy Overweight and Obese Women

Introduction

The current prevalence of the metabolically healthy obesity is about 3%. Genetic and nutrition are influencers of such phenotypes. The main goal of this study was to assess the interaction between Dietary Total Antioxidant Capacity (DTAC) and the genotypes of MC4R and Insulin resistance in metabolically healthy/unhealthy overweight and obese women in Iran.

Material And Methods

This cross-sectional study was conducted on 237 overweight-obese women with a mean age of 36. The value of Dietary total antioxidant capacity (DTAC) was calculated using the following indices: Total reactive antioxidant potential (TRAP), Trolox equivalent antioxidant capacity (TEAC), and ferric reducing ability of plasma (FRAP). The Metabolic health status was evaluated using the Karelis criteria. Melanocortin 4 receptor single nucleotide polymorphisms were determined by the restriction fragment length polymorphism (PCR-RFLP) method. Also, insulin resistance was evaluated through homeostasis model assessment (HOMA).

Result

Our data noted that 72.96% of participants presented Unhealthy Metabolically and 26.94% Healthy Metabolically including 33.5% of the total had T/T genotype, 23.8% had the C/T genotype, and 42.5% had the C/C genotype (P = .05). A linear regression model test showed that the probability of metabolically healthy obesity was significantly higher in patients with the T/C genotype. The test value was statistically significant (95% CI: 0.000-0.001; P = .056, β = 0). No statistically significant relation was observed between study parameters and DTAC values. HOMA-Index was higher in all unhealthy subjects significantly.

Conclusions

The findings indicated that there are significant associations between genotypes of rs1333048 SNP and DTAC. The C/C genotype subjects with higher DTAC had a better lipid profile and were metabolically healthier.