Prevalence, Risk Factors, and Genetic Traits in Metabolically Healthy and Unhealthy Obese Individuals

Exploring the association between circRNA expression and pediatric obesity based on a case-control study and related bioinformatics analysis

OBJECTIVE

Our present study utilized case-control research to explore the relationship between specific circRNAs and pediatric obesity through a literature review and bioinformatics and to predict their possible biological functions, providing ideas for epigenetic mechanism studies of pediatric obesity.

METHODS

CircRNAs related to pediatric obesity were preliminarily screened by a literature review and qRT-PCR. CircRNA expression in children with obesity (n = 75) and control individuals (n = 75) was confirmed with qRT-PCR in a case-control study. This was followed by bioinformatics analyses, such as GO analysis, KEGG pathway analysis, and ceRNA network construction. Multivariate logistic regression was utilized to analyze the effects of circRNAs on obesity. A receiver operating characteristic (ROC) curve was also drawn to explore the clinical application value of circRNAs in pediatric obesity.

RESULTS

Has_circ_0046367 and hsa_circ_0000284 were separately validated to be statistically downregulated and upregulated, respectively, in the peripheral blood mononuclear cells of children with obesity and revealed as independent indicators of increased CHD risk [hsa_circ_0046367 (OR = 0.681, 95% CI: 0.480 ~ 0.967) and hsa_circ_0000284 (OR = 1.218, 95% CI: 1.041 ~ 1.424)]. The area under the ROC curve in the combined analysis of hsa_circ_0046367 and hsa_circ_0000284 was 0.706 (95% CI: 0.623 ~ 0.789). Enrichment analyses revealed that these circRNAs were actively involved in neural plasticity mechanisms, cell secretion and signal regulation.

CONCLUSION

The present research revealed that low expression of hsa_circ_0046367 and high expression of hsa_circ_0000284 are risk factors for pediatric obesity and that neural plasticity mechanisms are closely related to obesity.

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.

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.

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.

Polymorphism rs10105606 of LPL as a Novel Risk Factor for Microalbuminuria

Introduction

An important clinical feature of metabolic syndrome is abdominal obesity. Microalbuminuria is important in predicting the risk of cardiovascular and renal complications in abdominal obesity patients. However, the association between microalbuminuria polymorphism and abdominal obesity has not been conducted. The objective of this study is to analyze the genetic polymorphism of microalbuminuria in participants with metabolically unhealthy obesity (MUO).

Methods

Among 1325 MUO participants, we identified genomic loci underlying those with microalbuminuria, compared to those without microalbuminuria. Single nucleotide polymorphisms (SNPs) were selected with P < 1 × 10⁻⁵ from the Manhattan plot. Multivariable linear regression and analysis of variance were used to analyze the association between different SNP genotypes and microalbuminuria.

Results

The analysis showed homozygous participants for the risk allele A of rs10105606 and Affx-31885823 had 1.978-fold risk and 1.921-fold increased risk of microalbuminuria, respectively. Heterozygous distribution of rs117180252, rs10105606, and Affx-31885823 also increased the risk of microalbuminuria compared to the wild type. Further analysis showed Lipoprotein lipase (LPL), RN7SL87P, and RPL30P9 were the candidate genes associated with lipid metabolism and abdominal obesity.

Conclusion

In conclusion, LPL, RN7SL87P, and RPL30P9 minor allele carriers with abdominal obesity are more susceptible to microalbuminuria, explaining the inter-individual differences of microalbuminuria in MUO patients.

The verification of the reliability of a triglyceride-glucose index and its availability as an advanced tool

BACKGROUND

The triglyceride-glucose (TyG) index has been considered as insulin resistance (IR) assessment index. The current study aimed to verify the reliability of the TyG index as an IR assessment marker; the study of plasma fatty acids and body fat composition to determine potential metabolic syndrome (MetS) participants with a body mass index (BMI) of between 25.0 and 29.9 kg/m².

METHODS

The study included 378 overweight participants with a body mass index of between 25.0 and 29.9 kg/m². They were divided into tertiles according to the homeostasis model assessment of IR (HOMA-IR) or the TyG index. The role of the IR assessment index and the relationship with IR-related diseases and the risk factors using gas chromatograph-mass spectrometry, computed tomography, and dual energy X-ray absorptiometry, was investigated.

RESULTS

It was only in the TyG index tertile that the higher TyG index participants showed considerably higher LDL-cholesterol levels. More markedly, a close relationship was observed between the TyG index and the omega-6 polyunsaturated fatty acids compared with the HOMA-IR. Unlike HOMA-IR, with regard to the risks of developing chronic diseases, the MetS, the third tertile of the TyG index, showed an approximately 33.7 times greater odds ratio (OR) of the MetS occurring, compared with the first tertile of the TyG index.

CONCLUSIONS

The TyG index may be considered as an IR assessment index. In addition, the TyG index is an advanced tool that reflects the relevance of pro-inflammation levels and the presence of IR-related chronic diseases.

Obesity, metabolic health and omics: Current status and future directions

The growing obesity epidemic is becoming a major public health concern, and the associated costs represent a considerable burden on societies. Among the most common complications of severe obesity are the development of hypertension, dyslipidemia, type 2 diabetes, cardiovascular disease, and various types of cancer. Interestingly, some obese individuals have a favorable metabolic profile and appear to be somehow protected from the detrimental effects of excessive adipose tissue accumulation. These individuals remain normoglycemic, insulin sensitive, and hypotensive with proper blood lipid levels, despite their high body mass index and/or waist circumference. Multiple independent observations have led to the concept of the metabolically healthy obese (MHO) phenotype, yet no consensus has been reached to date regarding a universal definition or the main mechanism behind this phenomenon. Recent technological advances and the use of high-throughput analysis techniques have revolutionized different areas of biomedical research. A multi-omics approach, which is used to investigate changes at different molecular levels in an organism or tissue, may provide valuable insights into the interplay between the molecules or pathways and the roles of different factors involved in the mechanisms underlying metabolic health deterioration. The aim of this review is to present the current status regarding the use of omics technologies to investigate the MHO phenotype, as well as the results of targeted analyses conducted in MHO individuals.

A genetic analysis identifies haplotype at adiponectin locus: Association with the metabolic health and obesity phenotypes

BACKGROUND

Obesity and metabolic syndrome frequently co-exist and define obese individuals into different obesity phenotypes, such as metabolically healthy obese (MHO), metabolically unhealthy obese (MUO) and metabolically unhealthy normal weight (MUNW). Growing evidence suggests that genetic predisposition and environmental factors can explain the heterogeneity among these phenotypes.

METHODS

We conducted a case-control study including 130 MHO, 251 MUNW, 208 MUO and 336 health controls by genotyping 2 SNPs (rs2241766, rs1501299) in ADIPOQ to investigate possible associations between SNPs in the ADIPOQ gene with susceptibility to three obese phenotypes respectively in Chinese Han population. Unconditional logistic regressions were used to detect the association between ADIPOQ SNPs and MHO/MUNW/MUO risks.

RESULTS

Variant G allele of rs2241766 was associated with a reduced odds of MUO (additive model: Adjusted OR = 0.55; 95% CI = 0.40-0.75; P < 0.001) and no evidence of any significant association between rs2241766 and MHO phenotype (additive model: Adjusted OR = 0.84; 95% CI = 0.61-1.16; P = 0.306) or MUNW phenotype (additive model: Adjusted OR = 0.95; 95% CI = 0.73-1.24; P = 0.720) was found. Minor allele T of rs1501299 were significantly associated with decreased risk of MHO (Adjusted OR = 0.53; 95% CI = 0.37-0.76; P < 0.001) and MUNW (Adjusted OR = 0.63; 95% CI = 0.48-0.83; P = 0.001) in additive genetic model after correction for multiple testing.

CONCLUSIONS

The variant G allele of rs2241766 was negatively associated with risk of MUO and variant T allele of rs1501299 exhibited reduced odds for MHO and MUNW. Beyond that, future studies are warranted to validate and extend our findings.

Associations of Metabolic/Obesity Phenotypes with Insulin Resistance and C-Reactive Protein: Results from the CNTR Study

BACKGROUND

Obesity is a heterogeneous condition in terms of metabolic status. Different obesity phenotypes have various health risks. The aim of this work was to define different subtypes of obesity and investigate their relationship with inflammatory-cardiometabolic abnormalities among Chinese adult twins.

METHODS

The analyses used data from 1113 adult twins in 4 provinces (Shandong, Zhejiang, Jiangsu and Sichuan) from Chinese National Twin Registry (CNTR) which collected detailed information. We defined those with 0 or 1 metabolic syndrome (MetS) components excluding waist circumference as metabolically healthy, and those with waist circumference ≥90 cm (for men) and ≥85 cm (for women) as obese. The two-category obesity status and metabolic states are combined to generate four metabolic/obesity phenotypes. High sensitivity C reactive protein (hsCRP) was measured to assess underlying inflammation and homeostasis model assessment of insulin resistance (HOMA-IR) was calculated as surrogate measure of insulin resistance. Mixed-effect linear regression models and fixed-effect linear regression models were used to analyse the correlation between HOMA-IR, hsCRP and different metabolic/obesity phenotypes.

RESULTS

In cross-sectional analyses of 1113 individuals (mean [SD] age, 46.6 [12.9] years; 463 obese [41.6%]), 20.3% obese twins were metabolic healthy and 64.2% non-obese twins were metabolic unhealthy. Serum HOMA-IR level was higher in metabolically unhealthy non-obesity (MUNO) (β=0.42, 95% CI: 0.21-0.64), metabolically healthy obesity (MHO) (β=0.68, 95% CI: 0.36-1.00) and metabolically unhealthy obesity (MUO) (β=0.69, 95% CI: 0.46-0.91) twins, compared with their metabolically healthy non-obesity (MHNO) counterparts. HsCRP was similar between MHO and MUO, which differed significantly to metabolic healthy non-obesity (MHNO).

CONCLUSION

MHO and MUNO phenotypes were common in Chinese twin population. Both phenotypes were associated with elevated IR and hsCRP which may not be benign and need to be concerned.

A Metabolically Unhealthy Phenotype Is Associated with Genetic Variants and Lower Serum Adiponectin Levels

<b><i>Background:</i></b> Even though excessive adipose tissue is related to chronic metabolic disturbances, not all subjects with excess weight (EW) display metabolic alterations, and not all normal-weight (NW) subjects have a metabolically healthy (MH) phenotype, probably due to gene-environment interactions. The aim of this study was to investigate the interaction effects of <i>ADIPOQ</i> and <i>PPARG</i> genetic variants in NW and EW individuals with different metabolic phenotypes. <b><i>Methods:</i></b> Data on 345 adults from western Mexico were analyzed. The individuals were classified into NW and EW groups according to body mass index, and were categorized as MH or metabolically unhealthy (MUH), considering homeostatic model assessment insulin resistance (HOMA-IR) and National Cholesterol Education Program Adult Treatment Panel III (NCEP-ATP III) cut-off points for glucose, triglycerides, high-density lipoprotein cholesterol, and blood pressure. Subjects with ≤1 altered parameter were classified as MH. The single nucleotide polymorphisms (SNPs) –11377C&#x3e;G, –11391G&#x3e;A, +45T&#x3e;G, and +276G&#x3e;T for <i>ADIPOQ</i> and Pro12Ala for <i>PPARG</i> were analyzed by allelic discrimination. High-molecular-weight adiponectin isoform levels were measured by ELISA. <b><i>Results:</i></b> Lower serum adiponectin levels were associated with the MUH phenotype in EW subjects. NW subjects with the GG or TG genotype for the +45T&#x3e;G SNP had reduced odds of the MUH phenotype. Individuals who carried two copies of the GG haplotype at the –11391G&#x3e;A and –11377C&#x3e;G SNPs for <i>ADIPOQ</i> had lower serum adiponectin levels than those with zero copies. <b><i>Conclusion:</i></b> In this population, lower serum adiponectin levels were found in the EW-MUH phenotype, and no differences were observed between the NW-MH and the EW-MH phenotype. In addition, the +45T&#x3e;G SNP was associated with reduced odds of the MUH phenotype.

Metabolically healthy obesity: prevalence, phenotype characteristic, effectiveness of weight loss

The goal was to study the prevalence of metabolically healthy obesity (MHO), the features of this phenotype compared with metabolically unhealthy obesity (MUHO), and the effect of weight loss on cardiometabolic risk factors in patients with MHO. Material and Methods — To assess the prevalence of MHO, 389 case histories of obese patients aged 18-60 were analyzed. Three types of MHO criteria were used: 1) the definitions of metabolic syndrome (MS) according to International Diabetes Federation (IDF), 2005; 2) the HOMA-IR index (<2.7); 3) Biobank Standardisation and Harmonisation for Research Excellence in the European Union (BioSHaRE-EU) criteria, 2013. The study included comparative analysis of the medical history, anthropometry, basic metabolic parameters, and adipocytokine levels in 44 patients with MHO (taking into account the MS definitions) and 33 women with MUHO initially and with a decrease in body mass (BM) by ≥5% after 6 months. Results — The MHO prevalence was: according to the definitions of MS – 38.6%, according to HOMA-IR index – 34.5%, in BioSHaRE-EU – 9.6%. All indicators of anthropometry, carbohydrate and lipid metabolism, including the HOMA-IR index, interleukin-6, and chemerin, as well as the duration of obesity in the MHO and MUHO groups significantly differed (p<0.05). After 6 months, MHO-patients who lost ≥5% BM from the initial value (63.6%) showed an increase of adiponectin, a decrease in waist circumference, HOMA-IR index, C-reactive protein (CRP), retinol-binding protein 4 (RBP-4), and chemerin (p<0.05). Conclusion — The MHO prevalence was maximal according to the MS definitions and minimal with BioSHaRE-EU criteria. The BM decrease in MHO is accompanied by a decrease in the content of proinflammatory adipocytokines and the HOMA-IR index, which determines the need to treat obesity regardless of the phenotype.

The Emerging Role and Promise of Circular RNAs in Obesity and Related Metabolic Disorders

Circular RNAs (circRNAs) are genome transcripts that are produced from back-splicing of specific regions of pre-mRNA. These single-stranded RNA molecules are widely expressed across diverse phyla and many of them are stable and evolutionary conserved between species. Growing evidence suggests that many circRNAs function as master regulators of gene expression by influencing both transcription and translation processes. Mechanistically, circRNAs are predicted to act as endogenous microRNA (miRNA) sponges, interact with functional RNA-binding proteins (RBPs), and associate with elements of the transcriptional machinery in the nucleus. Evidence is mounting that dysregulation of circRNAs is closely related to the occurrence of a range of diseases including cancer and metabolic diseases. Indeed, there are several reports implicating circRNAs in cardiovascular diseases (CVD), diabetes, hypertension, and atherosclerosis. However, there is very little research addressing the potential role of these RNA transcripts in the occurrence and development of obesity. Emerging data from in vitro and in vivo studies suggest that circRNAs are novel players in adipogenesis, white adipose browning, obesity, obesity-induced inflammation, and insulin resistance. This study explores the current state of knowledge on circRNAs regulating molecular processes associated with adipogenesis and obesity, highlights some of the challenges encountered while studying circRNAs and suggests some perspectives for future research directions in this exciting field of study.

Updates on Monogenic Obesity in a Multifactorial Disease

Obesity is a worldwide epidemic with rates nearly doubling over the last 30 years. Despite increasing prevalence, the multifactorial pathogenesis of obesity continues to be widely misunderstood. Investigating genetic drivers in the development of obesity is an important area of focus, as genetics move to the forefront of medicine and personalized treatment evolves. Thus, this narrative review focused on four genes which have genome-wide association study-documented links to obesity and obesity syndromes. We explored their involvement in the predisposition, progression, and prognosis of obesity. Leptin, leptin receptor, pro-opiomelanocortin, and melanocortin 4 receptor are our four genes of interest, and herein we elaborated on the current literature, pathogenesis, and available treatments for patients with these specific genetic mutations.

Obesity subtypes, related biomarkers & heterogeneity

Obesity is a serious medical condition worldwide, which needs new approaches and recognized international consensus in treating diseases leading to morbidity. The aim of this review was to examine heterogeneous links among the various phenotypes of obesity in adults. Proteins and associated genes in each group were analysed to differentiate between biomarkers. A variety of terms for classification and characterization within this pathology are currently in use; however, there is no clear consensus in terminology. The most significant groups reviewed include metabolically healthy obese, metabolically abnormal obese, metabolically abnormal, normal weight and sarcopenic obese. These phenotypes do not define particular genotypes or epigenetic gene regulation, or proteins related to inflammation. There are many other genes linked to obesity, though the value of screening all of those for diagnosis has low predictive results, as there are no significant biomarkers. It is important to establish a consensus in the terminology used and the characteristics attributed to obesity subtypes. The identification of specific molecular biomarkers is also required for better diagnosis in subtypes of obesity.

Genetic and nongenetic factors explaining metabolically healthy and unhealthy phenotypes in participants with excessive adiposity: relevance for personalized nutrition

BACKGROUND

Different genetic and environmental factors can explain the heterogeneity of obesity-induced metabolic alterations between individuals. In this study, we aimed to screen factors that predict metabolically healthy (MHP) and unhealthy (MUP) phenotypes using genetic and lifestyle data in overweight/obese participants.

METHODS

In this cross-sectional study we enrolled 298 overweight/obese Spanish adults. The Adult Treatment Panel III criteria for metabolic syndrome were used to categorize MHP (at most, one trait) and MUP (more than one feature). Blood lipid and inflammatory profiles were measured by standardized methods. Body composition was determined by dual-energy X-ray absorptiometry. A total of 95 obesity-predisposing single-nucleotide polymorphisms (SNPs) were genotyped by a predesigned next-generation sequencing system. SNPs associated with a MUP were used to compute a weighted genetic-risk score (wGRS). Information concerning lifestyle (dietary intake and physical activity level) was collected using validated questionnaires.

RESULTS

The prevalence of MHP and MUP was 44.3% and 55.7%, respectively, in this sample. Overall, 12 obesity-related genetic variants were associated with the MUP. Multiple logistic regression analyses revealed that wGRS (OR = 4.133, p < 0.001), total dietary fat [odds ratio (OR) = 1.105, p = 0.002], age (OR = 1.064, p = 0.001), and BMI (OR = 1.408, p < 0.001) positively explained the MUP, whereas female sex (OR = 0.330, p = 0.009) produced a protective effect. The area under the receiver operating characteristic curve using the multivariable model was high (0.8820). Interestingly, the wGRS was the greatest contributor to the MUP (squared partial correlation = 0.3816, p < 0.001).

CONCLUSIONS

The genetic background is an important factor explaining MHP and MUP related to obesity, in addition to lifestyle variables. This information could be useful to metabolically categorize individuals, as well as for the design/implementation of personalized nutrition interventions aimed at promoting metabolic health and nutritional wellbeing.

Why primary obesity is a disease?

Obesity must be considered a real pathology. In the world wide, obesity represent one of the major public health issue associated with increased morbidity and mortality. Overweight or obesity, in fact, significantly increases the risk of contracting diseases, such as: arterial hypertension, dyslipidemia, type 2 diabetes mellitus, coronary heart disease, cerebral vasculopathy, gallbladder lithiasis, arthropathy, ovarian polycytosis, sleep apnea syndrome, and some neoplasms. Despite numerous informative campaigns, unfortunately, the fight against obesity does not seem to work: in the last years, the prevalence continued to increase. The progressive and rapid increase in the incidence of obesity, which has characterized most of the economically advanced countries in the last decade, has been the main stimulus for the research of the mechanisms underlying this pathology and the related disorders. The aims of this review is to provide a revision of the literature in order to define obesity as diseases, secondly to highlight the limits and the inaccuracy of common tools used for the diagnosis of obesity, and as a third thing to strengthen the concept of the complexity of obesity as a disease among political health care providers. Obesity may be viewed as a multifactorial pathology and chronic low-grade inflammatory disease. In fact, people affected by obesity have greater risk of developing comorbility and morbility, respect to healthy. Hence, the absolute therapeutic benefit is directly proportional to the basic risk. So, internationally interest on early diagnosis of obesity is growing to avoid under- and overdiagnosis consequences. Therefore, the consequences are an aggravation of the disease and an increase in obesity related pathology like diabetes, cardiovascular disease, and cancer. The most widely used parameter for diagnosis, body mass index (BMI) is not suitable for assessing the body fat. In fact, several studies demonstrate that BMI alone cannot define obesity, which consists not so much in weight gain as in excess fat mass. The use of suitable tools for the assessment of fat mass percentage combined with clinical and genetic analysis allowed to identify different phenotypes of obesity, which explain the various paradoxes of obesity. It is essential to adopt all possible strategies to be able to combat obesity, ameliorate the suffering of patients, and reduce the social and treatment costs of obesity.

Is it Possible to Easily Identify Metabolically Healthy Obese Women?

Background: Obesity is recognized as a major risk factor for the development of several metabolic complications. However, some obese individuals have a favorable metabolic profile.

Objective: The aim of this study was to identify an easy parameter for recognizing metabolically healthy obese (MHO) women.

Methods: A total of 292 non-diabetic women with a body mass index (BMI) ≥ 30 kg/m² were selected, and 239 composed the final cohort. We classified the participants according to their metabolic state determined by homeostasis model assessment (HOMA) into MHO or metabolically unhealthy obese (MUO). Both groups were compared regarding biochemical, anthropometric, and body composition characteristics.

Results: The average age of the cohort was 43.9 ± 10.9 years and the average BMI was 37.2 ± 5.3 kg/m². In total, 75.7% of the participants were classified as MHO by HOMA. A cutoff of 108.2 cm for waist circumference (WC) identified MHO participants with a sensitivity of 72.4% (95% confidence interval [CI]: 59.8-82.3%), specificity of 66.9% (95% CI: 59.71-73.3%), and negative likelihood ratio of 0.41 (95% CI: 0.36-0.47). Additionally, a visceral adiposity index cutoff value of 99.2 identified MHO women with a sensitivity of 89.7% (95% CI: 79.2-95.2%), specificity of 48.6% (95% CI: 41.4-55.9%), and negative likelihood ratio of 0.21 (95% CI: 0.15-0.30).

Conclusion: Women classified as MHO exhibited smaller WC measurements and lower body fat percentages, as well as lower blood glucose and insulin levels. WC emerged as an easy parameter for identifying MHO women.

Weight bias in nutritional practice: a study with nutrition students

Obesity is associated with psychosocial problems like stigma, discrimination, and bias. Studies have found that nutritionists and nutrition students display negative attitudes and biases toward obese individuals. This study examined the existence of nutrition students' bias toward obese individuals. The students answered questionnaires by completing on-line forms with demographic data and self-reported weight and height and were assigned to one of four randomly selected hypothetical cases of patients referred to a nutritionist after receiving a diagnosis of lactose intolerance (normal weight man; normal weight woman; obese man; and obese woman). Except for weight, body mass index (BMI), and daily energy intake, all information on diet, habits, and health conditions were identical for profiles of the same sex. The questionnaire included questions on the indication of procedures and approaches during the consultation, consultation time, counseling strategies, dietary and health evaluation, and students' affective and behavioral reactions. Three hundred and thirty-five students participated, mostly women, with mean BMI of 23kg/m². Patient's weight influenced consultation time and students' perceptions and treatment approaches and strategies. The study revealed biases and negative attitudes mainly involving the students' perceptions and reactions to obese patients, and obese women generally received the worse evaluations.

Role of Physical Activity and Fitness in the Characterization and Prognosis of the Metabolically Healthy Obesity Phenotype: A Systematic Review and Meta-analysis

The aims of the present article are to systematically review and meta-analyze the existing evidence on: 1) differences in physical activity (PA), sedentary behavior (SB), cardiorespiratory fitness (CRF) and muscular strength (MST) between metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUO); and 2) the prognosis of all-cause mortality and cardiovascular disease (CVD) mortality/morbidity in MHO individuals, compared with the best scenario possible, i.e., metabolically healthy normal-weight (MHNW), after adjusting for PA, SB, CRF or MST. Our systematic review identified 67 cross-sectional studies to address aim 1, and 11 longitudinal studies to address aim 2. The major findings and conclusions from the current meta-analysis are: 1) MHO individuals are more active, spend less time in SB, and have a higher level of CRF (yet no differences in MST) than MUO individuals, suggesting that their healthier metabolic profile could be at least partially due to these healthier lifestyle factors and attributes. 2) The meta-analysis of cohort studies which accounted for PA (N = 10 unique cohorts, 100% scored as high-quality) support the notion that MHO individuals have a 24-33% higher risk of all-cause mortality and CVD mortality/morbidity compared to MHNW individuals. This risk was borderline significant/non-significant, independent of the length of the follow-up and lower than that reported in previous meta-analyses in this topic including all type of studies, which could be indicating a modest reduction in the risk estimates as a consequence of accounting for PA. 3) Only one study has examined the role of CRF in the prognosis of MHO individuals. This study suggests that the differences in the risk of all-cause mortality and CVD mortality/morbidity between MHO and MHNW are largely explained by differences in CRF between these two phenotypes.

Waist Circumference Is an Anthropometric Parameter That Identifies Women with Metabolically Unhealthy Phenotypes

Metabolically healthy (MH) and metabolically unhealthy (MUH) phenotypes can be present in any subject independently of their body mass index (BMI). However, factors related to the presence of these phenotypes are poorly understood. Therefore, the aim of this cross-sectional study is to describe the prevalence and characteristics associated with the MH and MUH phenotypes in Mexican subjects with different BMI categories. Anthropometric and biochemical parameters were evaluated after 12 h of fasting. HMW (High Molecular Weight) adiponectin and insulin levels were measured by ELISA (enzyme-linked immunosorbent assay). A total of 345 subjects were included, of which, 73.9% were women. The prevalence of the MH phenotype was 69.9%, 46.7%, and 19% in normal weight, overweight, and obesity, respectively. ROC (receiver operating characteristic) curve analysis showed that the waist circumference demonstrated a statistical significance (p < 0.01) in detecting the MUH phenotype in each BMI group only in women. Furthermore, subjects with lower HMW adiponectin levels showed a 2.1 increased risk of presenting the MUH phenotype. In conclusion, in this Mexican population, waist circumference was an anthropometric parameter that identified women with the MUH phenotype in all BMI categories and hypoadiponectinemia was a risk factor for the presence of this phenotype.

An Obesity Paradox: Increased Body Mass Index Is Associated with Decreased Aortic Atherosclerosis

Brodsky et al. (Cardiovasc Pathol 25(6), 515-520, 2016) recently have reported that there was an unexpected and highly significant inverse correlation between body mass index (BMI) and atherosclerosis of the aortas of morbidly obese decedents (BMI >40 kg/m²). In a series of 304 decedents, 65 of whom were morbidly obese, minimal or no atherosclerosis was seen in 46 of them (70%) versus 20 (30%) who had severe atherosclerosis (P = 0.008). This obesity paradox was unexpected and raises important questions about the etiology and pathogenesis of atherosclerosis, which will be the subject of this commentary. The concept of healthy versus unhealthy adiposity may in part provide an explanation for the "obesity paradox." Another factor that will be considered is the possible role of adipokines and their genetic determinants that may significantly reduce the risk of developing aortic atherosclerosis in morbidly obese individuals. Considering the marked variability in the pattern and extent of atherosclerosis of the aorta, hemodynamic factors and endothelial cell shear stress may be the most important determinants that might explain the obesity paradox that we have observed. Finally, the possible role of gut microbiota and inflammation as factors in the etiopathogenesis of atherosclerosis will be considered, but their importance is less clear than that of hemodynamic factors. We conclude with the remarkable finding that a 5300-year-old, well-preserved mummy of the "Iceman," Ötzi had atherosclerotic disease of a number of major arteries and the interesting questions that this raises.

Serum 25(OH)D and adipokines levels in people with abdominal obesity

Abdominal obesity is a risk factor for cardiovascular disease and diabetes mellitus and has been associated with vitamin D deficiency. Some studies have suggested an association between obesity and adipokine levels as well as low serum 25-hydroxyvitamin D (25(OH)D) level but the underlying mechanisms of the interlink between vitamin D status and serum leptin and adiponectin concentrations are still disputed. We included 435 residents (132 males) from St. Petersburg, Russia into this study. All subjects had physical examination and demographics noted. Blood was collected after an overnight fast and plasma glucose, insulin, serum lipids, 25(OH)D and adipokines (adiponectin and leptin) concentrations were determined at baseline in all participants. Abdominal obesity was diagnosed in 310 (71.3%) subjects (251 females and 59 males). Vitamin D insufficiency and deficiency were found in 314 (72.2%) subjects. Mean (95% CI) age, body mass index (BMI) and serum 25(OH)D for the cohort were 47.6±11.3years; 28.7±0.2kg/m2 and 62.5±24.3nmol/l respectively. Serum 25(OH)D level inversely correlated with body weight, waist circumference (WC) and BMI in females but not in males, was lower in diabetic than non-diabetic subjects, and was not significantly different in subjects with and without MetS. WC was positively correlated with leptin and negatively correlated with adiponectin. We found correlation between leptin and serum 25(OH)D level (r=-0.15, p=0.01) but this finding was a characteristic seen only in women. Our study showed a high prevalence of abdominal obesity, vitamin D deficiency and insufficiency in residents from North-West region of Russia, close association between adipokine (leptin, adiponectin) concentrations as well as vitamin D status and body composition (WC, BMI). However in our study the interlink between leptin level and 25(OH)D was found only in females. Further investigations are required to study the relationship between serum 25(OH)D level, obesity and serum adipokine levels.

The prevalence of metabolically healthy obesity according to the sample of the Moscow region

Introduction. Obesity is a major factor for cardiometabolic risk. However, there is a category of obese patients without disorders of lipid, carbohydrate metabolism and cardiovascular disease metabolically healthy obese (MHO). Aim. Our goal was to investigate the prevalence and characteristics of this phenotype compared to patients with metabolic syndrome (MS). Materials and methods. To evaluate the prevalence of the MHO phenotype we analyzed 389 medical records of females aged 1860 years with obesity. Three types of MHO criteria were used: 1) HOMA index (2.7); 2) IDF-criteria of metabolic syndrome, 2005; 3) the BioSHaRE-EU 2013 criteria (obese patients without any symptoms of MS). We conducted a comparative analysis of anthropometry, status of lipid and carbohydrate metabolism, the functional state of the liver. Results. The MHO prevalence was: 34.5% according to HOMA index, according to the definitions of MS 2005 38.6%, in BioSHaRE-EU 9.6%. In groups of MHO and MS dyslipidemia was observed in 27.3 and 49.5% (p0.05), hypertension in 25% and 71.6% (p0.05), steatogepatosis in 47.7% vs 51.3% (p0.05) of observations, respectively. Among comorbidities the gynecological pathology was most prevalent - 50.8 and 61.4% (p0.05), disorders of carbohydrate metabolism differed significantly in frequency- 6.82 and 39.1% of patients (p0.05). Patients with MHO had a shorter duration of the existence of obesity than MS (18.7 vs. 24 years) (p=0.0004) and less likely to have attempted to reduce weight 85.8% and 91.6%. Average BMI, waist circumference, hip circumference, fasting glucose, total cholesterol, insulin basal, basal C-peptide, HOMA index in groups of MHO and MS differed significantly (p0.05). Median ALT was 20 and 23.2 U/l, AST 20 and 23 U/l, triglycerides 1.1 and 1.8 mmol/l, high-density lipoprotein 1.4 and 1.1 mmol/l, respectively. Conclusions. The MHO prevalence was maximal according to the MS definitions from 2005, and minimal with BioSHaRE-EU criteria. The main analyzed indicators differed significantly in groups MHO and MS. Longer obesity existence in the MS group may suggest an instability of MHO phenotype over time.

Metabolically healthy obese and metabolically unhealthy non-obese phenotypes in a Russian population

INTRODUCTION

The aim of the study was to estimate the prevalence of metabolically healthy obese (MHO) and metabolically unhealthy non-obese (MUNO) phenotypes in Russian population.

DESIGN AND METHODS

In cross-sectional epidemiology survey "Epidemiology of cardiovascular diseases and its risk factors in some regions of the Russian Federation" a random sampling of 21,121 subjects (25-65 years), stratified by age and sex was involved. Anthropometry, blood pressure (BP) measurement and fasting blood-tests (glucose, lipids) were performed according to standard protocols. Criteria for MHO-body mass index (BMI) ≥30 kg/m² and ≤2 of markers: HDL < 1.30 (females)/1.04 (males) mmol/l; triglycerides ≥1.7 mmol/l; glucose ≥5.6 mmol/l or treatment; waist >88 (females)/102 (males) cm and BP ≥ 130/85 mm Hg or therapy. Criteria for MUNO was BMI < 30 kg/m² and ≥2 markers listed above. Simple tabulations, descriptive statistics, post-stratification weights and logistic regression were used for analyses.

RESULTS

MHO phenotype was detected in 2856 (41.5%) obese people; MUNO phenotype-in 4762 (34.4%) non-obese subjects. Aging was negatively associated with MHO and positively with MUNO prevalence. Gender was registered as determinant only of MUNO probability. No dramatic differences in lifestyle risk factors between 3 BMI groups (lean, overweight, obese) were found out.

CONCLUSION

Half of obese Russian inhabitants are metabolically healthy. At the same time, metabolic abnormalities were detected in one third of non-obese participants with a shift to male gender.

Metabolically healthy obesity across the life course: epidemiology, determinants, and implications

In recent years, different subphenotypes of obesity have been described, including metabolically healthy obesity (MHO), in which a proportion of obese individuals, despite excess body fat, remain free of metabolic abnormalities and increased cardiometabolic risk. In the absence of a universally accepted set of criteria to classify MHO, the reported prevalence estimates vary widely. Our understanding of the determinants and stability of MHO over time and the associated cardiometabolic and mortality risks is improving, but many questions remain. For example, whether MHO is truly benign is debatable, and whether risk stratification of obese individuals on the basis of their metabolic health status may offer new opportunities for more personalized approaches in diagnosis, intervention, and treatment of diabetes remains speculative. Furthermore, as most of the research to date has focused on MHO in adults, little is known about childhood MHO. In this review, we focus on the epidemiology, determinants, stability, and health implications of MHO across the life course.

Gut Microbiota and Metabolic Health: The Potential Beneficial Effects of a Medium Chain Triglyceride Diet in Obese Individuals

Obesity and associated metabolic complications, such as non-alcoholic fatty liver disease (NAFLD) and type 2 diabetes (T2D), are in constant increase around the world. While most obese patients show several metabolic and biometric abnormalities and comorbidities, a subgroup of patients representing 3% to 57% of obese adults, depending on the diagnosis criteria, remains metabolically healthy. Among many other factors, the gut microbiota is now identified as a determining factor in the pathogenesis of metabolically unhealthy obese (MUHO) individuals and in obesity-related diseases such as endotoxemia, intestinal and systemic inflammation, as well as insulin resistance. Interestingly, recent studies suggest that an optimal healthy-like gut microbiota structure may contribute to the metabolically healthy obese (MHO) phenotype. Here, we describe how dietary medium chain triglycerides (MCT), previously found to promote lipid catabolism, energy expenditure and weight loss, can ameliorate metabolic health via their capacity to improve both intestinal ecosystem and permeability. MCT-enriched diets could therefore be used to manage metabolic diseases through modification of gut microbiota.