The Role of Adipokines and Myokines in the Pathogenesis of Different Obesity Phenotypes-New Perspectives

Obesity is a characteristic disease of the twenty-first century that is affecting an increasing percentage of society. Obesity expresses itself in different phenotypes: normal-weight obesity (NWO), metabolically obese normal-weight (MONW), metabolically healthy obesity (MHO), and metabolically unhealthy obesity (MUO). A range of pathophysiological mechanisms underlie the occurrence of obesity, including inflammation, oxidative stress, adipokine secretion, and other processes related to the pathophysiology of adipose tissue (AT). Body mass index (BMI) is the key indicator in the diagnosis of obesity; however, in the case of the NWO and MONW phenotypes, the metabolic disturbances are present despite BMI being within the normal range. On the other hand, MHO subjects with elevated BMI values do not present metabolic abnormalities. The MUO phenotype involves both a high BMI value and an abnormal metabolic profile. In this regard, attention has been focused on the variety of molecules produced by AT and their role in the development of obesity. Nesfatin-1, neuregulin 4, myonectin, irisin, and brain-derived neurotrophic factor (BDNF) all seem to have protective effects against obesity. The primary mechanism underlying the action of nesfatin-1 involves an increase in insulin sensitivity and reduced food intake. Neuregulin 4 sup-presses lipogenesis, decreases lipid accumulation, and reduces chronic low-grade inflammation. Myonectin lowers the amount of fatty acids in the bloodstream by increasing their absorption in the liver and AT. Irisin stimulates the browning of white adipose tissue (WAT) and consequently in-creases energy expenditure, additionally regulating glucose metabolism. Another molecule, BDNF, has anorexigenic effects. Decorin protects against the development of hyperglycemia, but may also contribute to proinflammatory processes. Similar effects are shown in the case of visfatin and chemerin, which may predispose to obesity. Visfatin increases adipogenesis, causes cholesterol accumulation in macrophages, and contributes to the development of glucose intolerance. Chemerin induces angiogenesis, which promotes the expansion of AT. This review aims to discuss the role of adipokines and myokines in the pathogenesis of the different obesity phenotypes.

Heterogeneous Comorbidity in Individuals With Different Phenotypes of Obesity

Introduction The prevalence of obesity is steadily increasing worldwide. Obesity is one of the most potent risk factors for various diseases and is simultaneously a heterogeneous condition. Different types of obesity could be identified according to body mass index (BMI), waist circumference, and visceral fat level; these conditions may present individually or in combination and pose a risk of developing certain comorbidities. However, the current obesity classification systems do not allow for accurate diagnosis and prediction of the comorbidity risk of patients, which is crucial for their clinical management. This points to the importance of studying obesity phenotyping in the context of body composition. Our study aimed to determine the contribution of obesity phenotypes in forming various comorbidities. Materials and methods This case-control study was conducted at the Clinical and Diagnostic Center of the Aviastroitelny District, Kazan. Patients were selected based on BMI per inclusion and exclusion criteria. A total of 151 patients with a median age of 43 [34.5-50] years were included in the study. The participants were distributed into six groups according to BMI and a combination of abdominal obesity (AO) and excess visceral fat. Results The participants were distributed in the following phenogroups: The first group - normal BMI without AO and excess visceral fat (n=47; 31.1%); the second group - overweight without AO and excess visceral fat (n=26; 17.2%); the third group - normal BMI with AO and without excess visceral fat (n=11; 7.3%); fourth group - overweight with AO and without excess visceral fat (n=34; 22.5%); fifth group - general obesity with AO and without excess visceral fat (n=20; 13.2%); sixth group - general obesity with AO and excess visceral fat (n=13; 8.6%). The five most frequently observed conditions in the general cohort were dyslipidemia (71.5%; n=108), disorders of the gastrointestinal tract (53.0%; n=80), cardiovascular disease (46.4%; n=70), musculoskeletal diseases (40.4%; n=61) and impaired carbohydrate metabolism (25.2%; n=38). The median number of pathological combinations in the general cohort was 5 [IQR: 3-7]. As the group number increased, the median number of comorbidities also increased. While BMI was significantly associated only with arterial hypertension, the level of visceral fat was associated with most comorbidities (obstructive sleep apnea syndrome, non-alcoholic fatty liver disease, chronic pancreatitis, hypertriglyceridemia, and prediabetes), followed by abdominal obesity (gastroesophageal reflux disease, hypertriglyceridemia, arterial hypertension, hypercholesterolemia). Conclusions In working-age people, group 1 and 4 phenotypes were more frequent than others. Abdominal obesity and visceral fat were associated with the most comorbid conditions. However, the individual types of these comorbidities were not the same.

Individual and combined associations of body mass index and waist circumference with components of metabolic syndrome among multiethnic middle-aged and older adults: A cross-sectional study

OBJECTIVES

Body mass index (BMI) and waist circumference (WC) are closely associated with metabolic syndrome and its components. Hence, a combination of these two obesity markers may be more predictive. In this study, we aimed to investigate the individual and combined associations of BMI and WC with selected components of metabolic syndrome and explored whether age, sex and ethnicity affected the aforementioned associations.

METHODS

A total of 6,298 middle-aged and older adults were included. Based on BMI and WC, the participants were divided into 4 groups: comorbid obesity (BMI ≥ 28 kg/m² and WC< 85/90 cm for women/men), abdominal obesity alone (BMI< 28 kg/m² and WC≥ 85/90 cm for women/men), general obesity alone (BMI ≥ 28 kg/m² and WC< 85/90 cm for women/men) and nonobesity subgroups (BMI< 28 kg/m² and WC< 85/90 cm for women/men). Selected components of metabolic syndrome were evaluated using the criteria recommended by the Chinese Diabetes Society. Poisson regression models with robust variance were used to evaluate the associations of obesity groups with selected components of metabolic syndrome. An interaction test was conducted to explore whether age, sex and ethnicity affect the aforementioned associations.

RESULTS

Compared with participants in the reference group (comorbid obesity), participants in the other 3 groups showed a decreased prevalence of fasting hyperglycemia (PR=0.83, 95% CI=0.73-0.94 for abdominal obesity alone, PR=0.60, 95% CI=0.38-0.96 for general obesity alone and PR=0.46, 95% CI=0.40-0.53 for nonobesity), hypertension (PR=0.86, 95% CI=0.82-0.90 for abdominal obesity alone, PR=0.80, 95% CI=0.65-0.97 for general obesity alone and PR=0.69, 95% CI = 0.66-0.73 for nonobesity) and hypertriglyceridemia (PR=0.88, 95% CI=0.82-0.95 for abdominal obesity alone, PR=0.62, 95% CI=0.47-0.81 for general obesity alone and PR=0.53, 95% CI=0.49-0.57 for nonobesity). However, participants in the abdominal obesity alone and nonobesity groups showed a decreased prevalence of low HDL-C levels while participants in the general obesity alone group did not (PR=0.65, 95% CI=0.41-1.03, p>0.05). In addition, the aforementioned associations were not affected by age, sex or ethnicity (all p for interactions>0.05).

CONCLUSIONS

Comorbid obesity is superior to general and abdominal obesity in identifying individuals at high risk of developing metabolic syndrome in middle-aged and older adults. Great importance should be attached to the combined effect of BMI and WC on the prevention and management of metabolic syndrome.

Association between metabolic obesity phenotypes and multiple myeloma hospitalization burden: A national retrospective study

Background & purpose

Obesity and metabolic disorders were associated with increased risk of MM, a disease characterized by high risk of relapsing and require frequent hospitalizations. In this study, we conducted a retrospective cohort study to explore the association of metabolic obesity phenotypes with the readmission risk of MM.

Patients & methods

We analyzed 34,852 patients diagnosed with MM from the Nationwide Readmissions Database (NRD), a nationally representative database from US. Hospitalization diagnosis of patients were obtained using ICD-10 diagnosis codes. According to obesity and metabolic status, the population was divided into four phenotypes: metabolically healthy non-obese (MHNO), metabolically unhealthy non-obese (MUNO), metabolically healthy obese (MHO), and metabolically unhealthy obese (MUO). The patients with different phenotypes were observed for hospital readmission at days 30-day, 60-day, 90-day and 180-day. Multivariate cox regression model was used to estimate the relationship between obesity metabolic phenotypes and readmissions risk.

Results

There were 5,400 (15.5%), 7,255 (22.4%), 8,025 (27.0%) and 7,839 (35.6%) unplanned readmissions within 30-day, 60-day, 90-day and 180-day follow-up, respectively. For 90-day and 180-day follow-up, compared with patients with the MHNO phenotype, those with metabolic unhealthy phenotypes MUNO (90-day: P = 0.004; 180-day: P = < 0.001) and MUO (90-day: P = 0.049; 180-day: P = 0.004) showed higher risk of readmission, while patients with only obesity phenotypes MHO (90-day: P = 0.170; 180-day: P = 0.090) experienced no higher risk. However, similar associations were not observed for 30-day and 60-day. Further analysis in 90-day follow-up revealed that, readmission risk elevated with the increase of the combined factor numbers, with aHR of 1.068 (CI: 1.002-1.137, P = 0.043, with one metabolic risk factor), 1.109 (CI: 1.038-1.184, P = 0.002, with two metabolic risk factors) and 1.125 (95% CI: 1.04-1.216, P = 0.003, with three metabolic risk factors), respectively.

Conclusion

Metabolic disorders, rather than obesity, were independently associated with higher readmission risk in patients with MM, whereas the risk elevated with the increase of the number of combined metabolic factors. However, the effect of metabolic disorders on MM readmission seems to be time-dependent. For MM patient combined with metabolic disorders, more attention should be paid to advance directives to reduce readmission rate and hospitalization burden.

Metabolomics and Lipidomics Signatures of Insulin Resistance and Abdominal Fat Depots in People Living with Obesity

The liver, skeletal muscle, and adipose tissue are major insulin target tissues and key players in glucose homeostasis. We and others have described diverse insulin resistance (IR) phenotypes in people at risk of developing type 2 diabetes. It is postulated that identifying the IR phenotype in a patient may guide the treatment or the prevention strategy for better health outcomes in populations at risk. Here, we performed plasma metabolomics and lipidomics in a cohort of men and women living with obesity not complicated by diabetes (mean [SD] BMI 36.0 [4.5] kg/m2, n = 62) to identify plasma signatures of metabolites and lipids that align with phenotypes of IR (muscle, liver, or adipose tissue) and abdominal fat depots. We used 2-step hyperinsulinemic-euglycemic clamp with deuterated glucose, oral glucose tolerance test, dual-energy X-ray absorptiometry and abdominal magnetic resonance imaging to assess muscle-, liver- and adipose tissue- IR, beta cell function, body composition, abdominal fat distribution and liver fat, respectively. Spearman’s rank correlation analyses that passed the Benjamini−Hochberg statistical correction revealed that cytidine, gamma-aminobutyric acid, anandamide, and citrate corresponded uniquely with muscle IR, tryptophan, cAMP and phosphocholine corresponded uniquely with liver IR and phenylpyruvate and hydroxy-isocaproic acid corresponded uniquely with adipose tissue IR (p < 7.2 × 10−4). Plasma cholesteryl sulfate (p = 0.00029) and guanidinoacetic acid (p = 0.0001) differentiated between visceral and subcutaneous adiposity, while homogentisate correlated uniquely with liver fat (p = 0.00035). Our findings may help identify diverse insulin resistance and adiposity phenotypes and enable targeted treatments in people living with obesity.

Staple Food Preference and Obesity Phenotypes: The Regional Ethnic Cohort Study in Northwest China

Staple food preference vary in populations, but evidence of its associations with obesity phenotypes are limited. Using baseline data (n = 105,840) of the Regional Ethnic Cohort Study in Northwest China, staple food preference was defined according to the intake frequency of rice and wheat. Overall and specifically abdominal fat accumulation were determined by excessive body fat percentage and waist circumference. Logistic regression and equal frequency substitution methods were used to evaluate the associations. We observed rice preference (consuming rice more frequently than wheat; 7.84% for men and 8.28% for women) was associated with a lower risk of excessive body fat (OR, 0.743; 95%CI, 0.669-0.826) and central obesity (OR, 0.886; 95%CI, 0.807-0.971) in men; and with lower risk of central obesity (OR, 0.898; 95%CI, 0.836-0.964) in women, compared with their wheat preference counterparties. Furthermore, similar but stronger inverse associations were observed in participants with normal body mass index. Wheat-to-rice (5 times/week) reallocations were associated with a 36.5% lower risk of normal-weight obesity in men and a 20.5% lower risk of normal-weight central obesity in women. Our data suggest that, compared with wheat, rice preference could be associated with lower odds ratios of certain obesity phenotypes in the Northwest Chinese population.

Association between Metabolic Phenotypes of Body Fatness and Incident Stroke: A Prospective Cohort Study of Chinese Community Residents

This study aimed to assess the association of body mass index (BMI)-based and waist circumference (WC)-based metabolic phenotypes with the risk of stroke among Chinese community residents. A total of 34,294 participants (mean ± standard deviation age: 56.05 ± 11.26 years) with no previous stroke diagnosis history were included in this cohort study. BMI-based metabolic phenotypes were classified into eight groups: metabolically healthy and normal weight (MHNW), metabolically healthy and underweight (MHUW), metabolically healthy and overweight (MHOW), metabolically healthy and obese (MHO), metabolically unhealthy and normal weight (MUNW), metabolically unhealthy and underweight (MUUW), metabolically unhealthy and overweight (MUOW), and metabolically unhealthy and obese (MUO). WC-based metabolic phenotypes were classified into four groups: metabolically healthy and normal WC (MHNWC), metabolically healthy and oversized WC (MHOWC), metabolically unhealthy and normal WC (MUNWC), and metabolically unhealthy and oversized WC (MUOWC). The association of these phenotypes with developing stroke events was examined using proportional hazards models. A total of 546 cases of first-stroke onset were recorded over a median follow-up time of 4.97 years. Compared with the reference group, the obesity phenotypes showed higher risks for stroke. The adjusted HRs (95% CIs) of MHUW, MHOW, MHO, MUNW, MUUW, MUOW, and MUO phenotypes were 1.01 (0.41, 2.49), 1.47 (1.09, 2.00), 1.33 (0.80, 2.22), 2.49 (1.87, 3.30), 3.92 (1.44, 10.72), 2.14 (1.64, 2.79), and 2.60 (1.91, 3.55), respectively. The adjusted HRs (95% CIs) of MHOWC, MUNWC, and MUOWC were 1.41 (1.02, 1.94), 2.25 (1.76, 2.87), and 2.16 (1.63, 2.87), respectively. The metabolic phenotypes defined by an alternative definition all showed significant positive associations (except for MHUW), with the adjusted HR ranging from 1.51 to 3.08 based on BMI and from 1.68 to 2.24 based on WC. The risk of stroke increased with the increase in metabolic abnormality numbers in different BMI and WC groups (all p trend < 0.001). The present study suggests that maintaining normal body weight or WC and improving metabolic health are of great significance in preventing cerebrovascular diseases.

Quantifying the phenome-wide disease burden of obesity using electronic health records and genomics

OBJECTIVE

High BMI is associated with many comorbidities and mortality. This study aimed to elucidate the overall clinical risk of obesity using a genome- and phenome-wide approach.

METHODS

This study performed a phenome-wide association study of BMI using a clinical cohort of 736,726 adults. This was followed by genetic association studies using two separate cohorts: one consisting of 65,174 adults in the Electronic Medical Records and Genomics (eMERGE) Network and another with 405,432 participants in the UK Biobank.

RESULTS

Class 3 obesity was associated with 433 phenotypes, representing 59.3% of all billing codes in individuals with severe obesity. A genome-wide polygenic risk score for BMI, accounting for 7.5% of variance in BMI, was associated with 296 clinical diseases, including strong associations with type 2 diabetes, sleep apnea, hypertension, and chronic liver disease. In all three cohorts, 199 phenotypes were associated with class 3 obesity and polygenic risk for obesity, including novel associations such as increased risk of renal failure, venous insufficiency, and gastroesophageal reflux.

CONCLUSIONS

This combined genomic and phenomic systematic approach demonstrated that obesity has a strong genetic predisposition and is associated with a considerable burden of disease across all disease classes.

Objectively Measured Physical Activity Is Lower in Individuals with Normal Weight Obesity in the United States

The role of physical activity in normal weight obesity (NWO), which is associated with increased cardiometabolic risk, is not clear. This study aimed to determine body composition phenotype-specific differences in objectively measured physical activity and sedentary time in adults in the United States. A total of 2055 adults with a body mass index (BMI) ≥ 18.5 m² were studied using 2003-2006 National Health and Nutrition Examination Surveys. Physical activity and percent body fat (BF%) were measured using accelerometer and dual-energy X-ray absorptiometry, respectively. A BF% > 23.1% and >33.3% for men and women, respectively, was considered excess. A BMI of 18.5-24.9 kg/m² with excess BF% was defined as NWO, while those with normal BF%, as normal weight lean (NWL). A BMI of ≥25 kg/m² with excess BF% was considered overweight/obesity (OB). Compared to NWL, moderate to vigorous physical activity was significantly lower by 8.3 min (95% confidence interval/CI = -15.20, -1.40) and 10.18 min (95% CI = -14.83, -5.54) per day in NWO and OB, respectively. Low-intensity physical activity was also significantly lower by 17.71 min (95% CI = -30.61, -4.81) per day in NWO compared to NWL. However, sedentary time was not different. Objectively measured physical activity is significantly lower in NWO compared to NWL, while sedentary time is not.

Adherence to the Mediterranean Diet and Risk of Metabolically Unhealthy Obesity in Women: A Cross-Sectional Study

Some obese individuals do not present any metabolic alteration and are considered metabolically healthy (MHO). Adherence to high-quality dietary pattern may favor this phenotype. We aimed to evaluate the association between the adherence to the Mediterranean diet and risk of metabolically unhealthy obesity (MUO) in women. We conducted a cross-sectional study on 2,115 obese women. All patients underwent a medical examination, anthropometric evaluation, bioelectrical impedance, ultrasound measurements of abdominal visceral (VAT) and subcutaneous (SAT) fat, blood sampling and evaluation of adherence to the Mediterranean diet through MEDAS questionnaire. The diagnosis of MHO and MUO was made using the harmonized criteria. A multivariable logistic regression adjusted for age, BMI, fat free mass, ultrasound-estimated VAT:SAT ratio, marital status, education, past diet, antidepressant use, family history of diabetes and cardiovascular disease, menopausal status, smoking, and physical activity was used to assess the association between Mediterranean diet and MUO risk. The prevalence of MHO was 21.2% (N = 449). Compared to MUO women, MHO women were younger, had lower BMI and VAT, and had higher fat free mass and SAT. In the multivariable model, the adherence to the Mediterranean diet was not associated with the risk of MUO (OR = 0.91, 95%CI: 0.62; 1.34, P = 0.624). Given the impact of menopause on metabolic health we also carried out the analysis in pre- and post-menopausal women separately. Higher adherence to the Mediterranean diet was associated with a lower risk of MUO in postmenopausal women (OR = 0.55, 95%CI: 0.31; 0.96, P = 0.034). No association was found in premenopausal women (OR = 1.18, 95%CI: 0.70; 1.99, P = 0.532). In conclusion, adherence to the Mediterranean diet was associated with a better metabolic health in postmenopausal women. Further studies are needed to confirm the ability of the Mediterranean diet in promoting maintenance of the healthy phenotype and reversion from MUO.

Association of Gastric Myoelectrical Activity With Ghrelin, Gastrin, and Irisin in Adults With Metabolically Healthy and Unhealthy Obesity

Background and Objective: Functional disturbances of gastric myoelectrical activity (GMA) might exist in obesity. However, studies on its association with the gastric hormones in obesity phenotypes are lacking. The objective was to study the association of GMA with the serum levels of key gastric hormones in different obesity phenotypes.

Methods: A total of 139 adults (31.00 ± 11.12 years) were classified into different metabolic phenotypes of obesity: 1) normal weight-lean (NWL group): BMI <25 kg/m² and the fat-mass index (FMI) ≤9.7 kg/m² in females and ≤6.3 kg/m² in males; 2) metabolically obese normal weight (MONW group): BMI <25 kg/m² and FMI >9.7 kg/m² in females and >6.3 kg/m² in males; 3) metabolically healthy obese (MHO group): BMI ≥25 and FMI ≤9.7 kg/m² in females and ≤6.3 kg/m² in males; and 4) metabolically unhealthy obese (MUO group): BMI ≥25 and FMI >9.7 kg/m² in females and >6.3 kg/m² in males. The GMA was measured at the baseline and post-prandial state using a multichannel electrogastrography with a water load satiety test. The average power distribution by the frequency region and the average dominant frequency were used for analysis. Anthropometric measurements and bioelectric impedance analysis were performed to calculate the FMI and fat-free mass index (FFMI). Serum levels of ghrelin, gastrin, and irisin were measured by ELISA kits according to the manufacturer’s protocol.

Results: Compared to the NWL group, gastrin and ghrelin levels were significantly low in the MUO participants, while irisin was significantly high. The EGG showed significantly lower baseline and 20-min normogastria frequencies in the MHO and MUO groups. In the MHO group, baseline duodenal frequency was positively correlated with the gastrin level, while normogastria times were positively associated with the irisin level and negatively associated with the ghrelin level. In the MUO group, percentages of bradygastria frequencies at 10, 20, and 30 min were positively correlated with the BMI and FFMI. This bradygastria was correlated positively with the irisin level and negatively with the ghrelin level.

Conclusion: The EGG patterns might be associated with obesity-related gastric hormones in different obesity phenotypes. EGG may be a promising clinical tool in obesity assessment. The association of the EGG patterns with hormonal levels needs further investigation for potential practical uses.

Associations between Breastfeeding Duration and Obesity Phenotypes and the Offsetting Effect of a Healthy Lifestyle

Background: Additional metabolic indicators ought to be combined as outcome variables when exploring the impact of breastfeeding on obesity risk. Given the role of a healthy lifestyle in reducing obesity, we aimed to assess the effect of breastfeeding duration on different obesity phenotypes according to metabolic status in children and adolescents, and to explore the offsetting effect of healthy lifestyle factors on the associations between breastfeeding duration and obesity phenotypes. Methods: A total of 8208 eligible children and adolescents aged 7–18 years were recruited from a Chinese national cross-sectional study conducted in 2013. Anthropometric indicators were measured in the survey sites, metabolic indicators were tested from fasting blood samples, and breastfeeding duration and sociodemographic factors were collected by questionnaires. According to anthropometric and metabolic indicators, obesity phenotypes were divided into metabolic healthy normal weight (MHNW), metabolic unhealthy normal weight (MUNW), metabolic healthy obesity (MHO), and metabolic unhealthy obesity (MUO). Four common obesity risk factors (dietary consumption, physical activity, screen time, and sleep duration) were used to construct a healthy lifestyle score. Scores on the lifestyle index ranged from 0 to 4 and were further divided into unfavorable lifestyles (zero or one healthy lifestyle factor), intermediate lifestyles (two healthy lifestyle factors), and favorable lifestyle (three or four healthy lifestyle factors). Multinomial logistic regression was used to estimate the odds ratio (OR) and 95% confidence interval (95% CI) for the associations between breastfeeding duration and obesity phenotypes. Furthermore, the interaction terms of breastfeeding duration and each healthy lifestyle category were tested to explore the offsetting effect of lifestyle factors. Results: The prevalence of obesity among Chinese children and adolescents aged 7–18 years was 11.0%. Among the children and adolescents with obesity, the prevalence of MHO and MUO was 41.0% and 59.0%, respectively. Compared to the children and adolescents who were breastfed for 6–11 months, prolonged breastfeeding (≥12 months) increased the risks of MUNW (OR = 1.35, 95% CI: 1.19–1.52), MHO (OR = 1.61, 95% CI: 1.27–2.05), and MUO (OR = 1.46, 95% CI: 1.20–1.76). When stratified by healthy lifestyle category, there was a typical dose–response relationship between duration of breastfeeding over 12 months and MUNW, MHO, and MUO, with an increased risk of a favorable lifestyle moved to an unfavorable lifestyle. Conclusions: Prolonged breastfeeding (≥12 months) may be associated with increased risks of MUNW, MHO, and MUO, and the benefits of breastfeeding among children and adolescents may begin to wane around the age of 12 months. The increased risks may be largely offset by a favorable lifestyle.

Corrigendum: Sex differences in metabolically healthy and metabolically unhealthy obesity among Chinese children and adolescents

[This corrects the article DOI: 10.3389/fendo.2022.980332.].

Sex differences in metabolically healthy and metabolically unhealthy obesity among Chinese children and adolescents

OBJECTIVES

To analyze sex differences in the prevalence of obesity phenotypes and their risk factors among children and adolescents aged 7-18 years in China.

METHODS

We enrolled 15,114 children and adolescents aged 7-18 years into the final analysis. Obesity phenotypes were classified by body mass index (BMI) and metabolic status as metabolically healthy or unhealthy obesity. In addition, we collected four possible influencing factors on obesity phenotypes through questionnaires, including demographic, parental, early life, and lifestyle indicators. Multinomial logistic regression analysis in a generalized linear mixed model (GLMM) was selected to estimate the odds ratio (OR) and 95% confidence interval (95% CI) for identifying risk factors and control the cluster effects of schools. More importantly, the interaction terms of sex and each indicator were established to demonstrate the sex differences.

RESULTS

The prevalence of metabolically healthy obesity (MHO), metabolically unhealthy obesity (MUO), metabolically healthy overweight and obesity (MHOO), and metabolically unhealthy overweight and obesity (MUOO) were 3.5%, 5.6%, 11.1%, and 13.0% respectively, with higher prevalence in boys (5.3% vs. 1.6%, 7.9% vs. 3.1%, 14.3% vs. 7.7%, 15.6% vs. 10.1%). In addition, younger ages, single children, parental smoking, parental history of diseases (overweight, hypertension, diabetes), caesarean, premature, and delayed delivery time, high birth weight, insufficient sleep time, and excessive screen time were considered as important risk factors of MHO and MUO among children and adolescents (p < 0.05). More notably, boys were at higher risks of MUO when they were single children (boys: OR = 1.56, 95% CI: 1.24-1.96; girls: OR = 1.12, 95% CI: 0.82-1.54), while girls were more sensitive to MUO with parental smoking (girls: OR = 1.34, 95% CI: 1.02-1.76; boys: OR = 1.16, 95% CI: 0.97-1.39), premature delivery (girls: OR = 3.11, 95% CI: 1.59-6.07; boys: OR = 1.22, 95% CI: 0.67-2.22), high birth weight (girls: OR = 2.45, 95% CI: 1.63-3.69; boys: OR = 1.28, 95% CI: 0.96-1.70), and excessive screen time (girls: OR = 1.47, 95% CI: 1.06-2.04; boys: OR = 0.97, 95% CI: 0.79-1.20), with significant interaction term for sex difference (p_interaction < 0.05).

CONCLUSIONS

MHO and MUO are becoming prevalent among Chinese children and adolescents. Significant sex differences in the prevalence of obesity phenotypes as well as their environmental and genetic risk factors suggest it might be necessary to manage obesity phenotypes problems from a sex perspective.

Obesity in Children with Leptin Receptor Gene Polymorphisms

INTRODUCTION

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

MATERIAL AND METHODS

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

RESULTS

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

CONCLUSION

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

Predictors of long-term weight loss trajectories during a behavioral weight loss intervention: An exploratory analysis

BACKGROUND

Substantial interindividual variability in response to behavioral weight loss interventions remains a critical challenge in obesity treatment. An improved understanding of the complex factors that contribute to this variability may improve obesity treatment outcomes.

OBJECTIVE

To identify weight change trajectories during a behavioral weight loss intervention and to explore differences between trajectory groups in sociodemographic, biologic, behavioral, and psychosocial factors.

METHODS

Adults (n = 170, 40 ± 9 years, BMI 34 ± 4 kg/m2, 84% female) participated in an 18-month behavioral weight loss intervention. Weight was measured at 0, 3, 6, 9, 12, 15, 18, and 24 months. Among participants with at least two weights after baseline (n = 140), clusters of longitudinal trajectories of changes in weight were identified using a latent class growth mixture model. The association between baseline factors or changes in factors over time and trajectory group was examined.

RESULTS

Two weight change trajectories were identified: "weight regainers" (n = 91) and "weight loss maintainers" (n = 49). Black participants (90%, 19/21) were more likely than non-Black participants to be regainers versus maintainers (p < 0.01). Maintainers demonstrated greater increases in device-measured physical activity, autonomous motivation for exercise, diet self-efficacy, cognitive restraint, and engagement in weight management behaviors and greater reductions in barriers for exercise, disinhibition, and depressive symptoms over 24 months versus regainers (p < 0.05).

CONCLUSION

Maintainers and regainers appear to be distinct trajectories that are associated with specific sociodemographic, behavioral, and psychosocial factors. Study results suggest potential targets for more tailored, multifaceted interventions to improve obesity treatment outcomes.

METABOLOMIC ANALYSIS OF NORMAL WEIGHT, HEALTHY AND UNHEALTHY OBESITY: AMINO ACID CHANGE ACROSS THE SPECTRUM OF METABOLIC WELLBEING IN WOMEN

Context

Obesity is a complex and heterogeneous disorder with multiple phenotypes described. Although metabolomic biomarkers of obesity have been extensively studied, biomarkers of obesity phenotypes and differences between these phenotypes and normal-weight (NW) persons have been less investigated.

Objective

The objective of this cross-sectional analysis was to investigate serum amino acids (AA) as markers of metabolic alterations in obesity phenotypes and NW.

Design

Cross-sectional.

Subjects and Methods

By targeted metabolomics we analyzed serum samples of 70 women using ultrahigh-performance liquid chromatography/mass spectrometry. Participants were divided into 3 groups: NW, metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUHO).

Results

Five AAs were significantly different between study groups: cysteine, methionine, asparagine, glutamine, and lysine (p-value <0.05 and variable importance in the projection >1). Cysteine increased linearly with metabolic unwellness from NW to MUHO. Lysine and glutamine were significantly higher, and asparagine was significantly lower in NW and MHO than in MUHO.

Conclusions

By trend and group analysis we identified specific changes in serum AAs along with the progression of metabolically unwellness.

Dissociation Between Insulin Resistance and Abnormalities in Lipoprotein Particle Concentrations and Sizes in Normal-Weight Chinese Adults

Insulin resistance in obesity coincides with abnormalities in lipid profile and lipoprotein subclass distribution and size even before abnormalities in glucose homeostasis manifest. We aimed to assess this relationship in the absence of obesity. Insulin sensitivity (3-h intravenous glucose tolerance test and minimal modeling) and lipoprotein particle concentrations and sizes (proton nuclear magnetic resonance spectroscopy) were evaluated in 15 insulin-resistant and 15 insulin-sensitive lean Asians of Chinese descent with normal glucose tolerance, matched on age, sex, and body mass index. Despite a ~50% lower insulin sensitivity index (Si) in insulin-resistant than in insulin-sensitive subjects, which was accompanied by significantly greater acute insulin response to glucose (AIRg) and fasting insulin concentration but not different fasting glucose concentration, there were no significant differences between groups in the blood lipid profile (p ≥ 0.44) or the lipoprotein subclass concentrations (p ≥ 0.30) and particle sizes (p ≥ 0.43). We conclude that, contrary to observations in subjects with obesity, insulin resistance is not accompanied by unfavorable changes in the plasma lipid profile and lipoprotein particle concentrations and sizes in lean Asians with normal glucose tolerance. Therefore, insulin resistance at the level of glucose metabolism is mechanistically or temporally dissociated from lipid and lipoprotein metabolism.

Trial Registration:clinicaltrials.gov, NCT03264001.

Gut Microbiota Associations with Metabolic Health and Obesity Status in Older Adults

Emerging evidence links the gut microbiota with several chronic diseases. However, the relationships between metabolic syndrome (MetS), obesity and the gut microbiome are inconsistent. This study aimed to investigate associations between gut microbiota composition and diversity and metabolic health status in older adults (n = 382; median age = 69.91 [± 5 years], male = 50.79%) with and without obesity. Gut microbiome composition was determined by sequencing 16S rRNA gene amplicons. Results showed that alpha diversity and richness, as indicated by the Chao1 index (p = 0.038), phylogenetic diversity (p = 0.003) and observed species (p = 0.038) were higher among the metabolically healthy non-obese (MHNO) individuals compared to their metabolically unhealthy non-obese (MUNO) counterparts. Beta diversity analysis revealed distinct differences between the MHNO and MUNO individuals on the phylogenetic distance scale (R² = 0.007, p = 0.004). The main genera contributing to the gut composition among the non-obese individuals were Prevotella, unclassified Lachnospiraceae, and unclassified Ruminococcaceae. Prevotella, Blautia, Bacteroides, and unclassified Ruminococcaceae mainly contributed to the variation among the obese individuals. Co-occurrence network analysis displayed different modules pattern among different metabolic groups and revealed groups of microbes significantly correlated with individual metabolic health markers. These findings confirm relationships between metabolic health status and gut microbiota composition particularly, among non-obese older adults.

Abdominal Obesity Phenotypes and Incidence of Thyroid Autoimmunity: A 9-Year Follow-up

PURPOSE

The association between obesity and autoimmune diseases has been suggested by several previous studies. The objective of our study was to assess the association of abdominal obesity phenotypes with thyroid autoimmunity.

MATERIALS AND METHODS

This study was conducted within the framework of a population-based cohort study, Tehran Thyroid Study (TTS) on 4708 subjects without thyroid autoimmunity at baseline. Participants were categorized into four abdominal obesity phenotypes according to waist circumference (WC) and other metabolic syndrome components. Serum concentrations of thyroid peroxidase antibody (TPOAb), free T4 (FT4), thyrotropin (TSH), glucose, and lipid profiles were measured after 3, 6 and 9 years of follow-up. Cox proportional hazard models were used to evaluate associations of different phenotypes with the incidence of thyroid autoimmunity, adjusted for age, sex, FT4, and TSH.

RESULTS

Highest and lowest incidence rates of TPOAb positivity were observed among metabolically unhealthy, non-abdominally obese (MUNAO) [8.78 (7.31-10.55) per 1000 person-years of follow-up] and metabolically unhealthy abdominally obese (MUAO) [4.98 (3.88-6.41) per 1000 person-years of follow-up] phenotypes. Considering the metabolically healthy non-abdominal obese (MHNAO) individuals as reference, none of metabolically healthy abdominally obese (MHAO), MUNAO, and MUAO phenotypes were associated with increased risk of developing TPOAb positivity. Compared to individuals with high WC, the incidence rate (95%CI) of TPOAb positivity was higher among those with normal WC: 8.44 (7.13-10.0) vs 5.11 (4.01-6.51) per 1000 person-years, respectively. Higher WC was not associated with incident TPOAb positivity.

CONCLUSION

There was no significant association between baseline abdominal obesity phenotype status and development of TPOAb positivity over 9 years of follow-up.

Evaluation of Transcriptomic Regulations behind Metabolic Syndrome in Obese and Lean Subjects

Multiple mechanisms have been suggested to confer to the pathophysiology of metabolic syndrome (MetS), however despite great interest from the scientific community, the exact contribution of each of MetS risk factors still remains unclear. The present study aimed to investigate molecular signatures in peripheral blood of individuals affected by MetS and different degrees of obesity. Metabolic health of 1204 individuals from 1000PLUS cohort was assessed, and 32 subjects were recruited to four study groups: MetS lean, MetS obese, “healthy obese”, and healthy lean. Whole-blood transcriptome next generation sequencing with functional data analysis were carried out. MetS obese and MetS lean study participants showed the upregulation of genes involved in inflammation and coagulation processes: granulocyte adhesion and diapedesis (p < 0.0001, p = 0.0063), prothrombin activation pathway (p = 0.0032, p = 0.0091), coagulation system (p = 0.0010, p = 0.0155). The results for “healthy obese” indicate enrichment in molecules associated with protein synthesis (p < 0.0001), mitochondrial dysfunction (p < 0.0001), and oxidative phosphorylation (p < 0.0001). Our results suggest that MetS is related to the state of inflammation and vascular system changes independent of excess body weight. Furthermore, “healthy obese”, despite not fulfilling the criteria for MetS diagnosis, seems to display an intermediate state with a lower degree of metabolic abnormalities, before they proceed to a full blown MetS.

Psychological features in obesity: A network analysis

OBJECTIVE

Enhanced understanding of psychosocial factors associated with obesity may improve knowledge of their interplay mechanisms. The aim of this study was to assess the relationship between psychosocial variables in individuals with obesity using a network analysis.

METHODS

Patients seeking treatment for obesity were consecutively recruited from a rehabilitative residential treatment program for severe obesity between January 2016 and March 2019. Each patient completed the following questionnaires: Eating Disorder Examination Questionnaire, Symptom Checklist-90, Obesity Related Well-Being, and Weight Bias Internalization Scale. In addition, current body mass index (BMI) was measured, and maximum acceptable and dream BMI were assessed.

RESULTS

The sample comprised 996 patients with obesity (age 52.3 [SD = 16.0] years; BMI 41.8 [SD = 7.8] kg/m² ; 65.7% women; 52.2% married or living with a partner). Network analysis showed that interpersonal sensitivity and shape-weight concern, but also internalized weight stigma, were the most central and highly interconnected nodes in the network. In contrast, objective binge-eating episodes and dietary restraint were the most peripheral and least connected nodes. Eating disorder features and psychological distress formed two clearly separate clusters. No difference in network structure was found between men and women.

CONCLUSIONS

The pattern of network node connections supports the importance of assessing psychological distress, interpersonal sensitivity, shape-weight concern, and internalized weight stigma in patients seeking treatment for obesity.

Metabolically Healthy Obesity-Heterogeneity in Definitions and Unconventional Factors

The concept of heterogeneity among obese individuals in their risk for developing metabolic dysfunction and associated complications has been recognized for decades. At the origin of the heterogeneity idea is the acknowledgement that individuals with central obesity are more prone to developing type 2 diabetes and cardiovascular disease than those with peripheral obesity. There have been attempts to categorize subjects according to their metabolic health and degree of obesity giving rise to different obese and non-obese phenotypes that include metabolically unhealthy normal-weight (MUHNW), metabolically healthy obese (MHO), and metabolically unhealthy obese (MUO). Individuals belonging to the MHO phenotype are obese according to their body mass index although exhibiting fewer or none metabolic anomalies such as type 2 diabetes, dyslipidemia, hypertension, and/or unfavorable inflammatory and fribinolytic profiles. However, some authors claim that MHO is only transient in nature. Additionally, the phenotype categorization is controversial as it lacks standardized definitions possibly blurring the distinction between obesity phenotypes and confounding the associations with health outcomes. To add to the discussion, the factors underlying the origin or protection from metabolic deterioration and cardiometabolic risk for these subclasses are being intensely investigated and several hypotheses have been put forward. In the present review, we compare the different definitions of obesity phenotypes and present several possible factors underlying them (adipose tissue distribution and cellularity, contaminant accumulation on the adipose tissue, dysbiosis and metabolic endotoxemia imposing on to the endocannabinoid tone and inflammasome, and nutrient intake and dietary patterns) having inflammatory activation at the center.

Metabolically Healthy, but Obese Individuals and Associations with Echocardiographic Parameters and Inflammatory Biomarkers: Results from the CARLA Study

INTRODUCTION

The research on heterogeneity among obese individuals has identified the metabolically healthy, but obese (MHO) phenotype as a distinct group that does not experience the typical cardiovascular-related diseases (CVD). It is unclear if this group differs with regard to preconditions for CVDs. Our aim was to assess differences in echocardiographic parameters and inflammatory biomarkers between MHO and metabolically healthy, normal weight individuals (MHNW).

METHODS

The analyses used data from 1412 elderly participants from a German population-based cohort study (CARLA), which collected detailed information on demographic, biochemical, and echocardiographic variables. Participants were subdivided into four groups (MHNW, MHO, MUNW (metabolically unhealthy, normal weight) and MUO (metabolically unhealthy, obese)) based on BMI≥30 kg/m² (obese or normal weight) and presence of components of the metabolic syndrome. The clinical characteristics of the 4 groups were compared with ANOVA or Chi-Square test, in addition to two linear regression models for 16 echocardiographic parameters. The difference in inflammatory biomarkers (hsCRP, IL-6 and sTNF-RI) between the groups was examined with a multinomial logistic regression model.

RESULTS

The MHO individuals were on average 64.2±8.4 years old, with a higher proportion of women (71.6%), low percentage of smokers, larger waist circumference (109.3±10.5 cm vs 89.1±10.8 cm, p<0.0001) and higher odds ratios for hsCRP, IL-6 and sTNF-RI compared to MHNW individuals. Linear regression models revealed greater left atrial (LA) diameter (2.73 (95% CI: 1.35-4.11) mm), LA volume (7.86 (95% CI: 2.88-12.83) mL), and left ventricular mass index (LVMI) (11.82 (95% CI: 4.43-19.22) g/m^1.7) in the MHO group compared to the MHNW group.

CONCLUSION

The MHO phenotype is associated with echocardiographic markers of cardiac remodeling (LA diameter, volume and LVMI) and higher odds ratios for inflammatory biomarkers.

Genetic Architecture of Human Obesity Traits in the Rhesus Macaque

OBJECTIVE

Whereas the metabolic consequences of obesity have been studied extensively in the rhesus macaque, corollary genetic studies of obesity are nonexistent. This study assessed genetic contributions to spontaneous adiposity in this species.

METHODS

Phenotypic variation by age class and sex for BMI, waist to height ratio, waist to thigh ratio, and waist circumference was assessed in 583 macaques. Total and sex-specific heritability for all traits was estimated, including waist to thigh ratio adjusted for BMI, as well as genotypic and phenotypic correlations. In addition, functional genetic variation at BDNF, FTO, LEP, LEPR, MC4R, PCSK1, POMC, and SIM1 was assessed in four animals with extreme spontaneous adiposity.

RESULTS

Trait heritability in the combined sample was low to moderate (0.14-0.32), whereas sex-specific heritability was more substantial (0.20-0.67). Heritability was greater in females for all traits except BMI. All traits were robustly correlated, with genetic correlations of 0.63 to 0.93 indicating substantial pleiotropy. Likely functional variants were discovered in the four macaques at all eight human obesity genes, including six missense mutations in BDNF, FTO, LEP, LEPR, and PCSK1 and, notably, one nonsense mutation in LEPR.

CONCLUSIONS

A moderate polygenic contribution to adiposity in rhesus macaques was found, as well as mutations with potentially larger effects in multiple genes that influence obesity in humans.

Rapid Assessment of Reward-Related Eating: The RED-X5

OBJECTIVE

The prevalence of obesity has created a plethora of questionnaires characterizing psychological aspects of eating behavior, such as reward-related eating (RRE). The Reward-based Eating Drive questionnaires (RED-9, RED-13) broadly and deeply assess the RRE construct. However, large-sample research designs require shorter questionnaires that capture RRE quickly and precisely. This study sought to develop a brief, reliable, and valid version of the RED questionnaire.

METHODS

All-subset correlation was used to find a subset that maximally associated with the full RED-13 in two separate samples. Results were validated in a third independent sample. Internal consistency, test-retest reliability, and ability to explain variance in external outcomes were also assessed.

RESULTS

A five-item questionnaire (RED-X5) correlated strongly with RED-13 in the independent sample (r = 0.95). RED-X5 demonstrated high internal consistency (omega total ≥ 0.80) and 6-month test-retest reliability (r = 0.72). RED-X5 accurately reproduced known associations between RED-13 and BMI, diabetes status, and craving for sweet and savory foods. As a novel finding, RED questionnaires predicted laboratory intake of chips.

CONCLUSIONS

RED-X5 is a short, reliable, and valid measure of the RRE construct and can be readily implemented in large-sample research designs in which questionnaire space is limited.

Protective role of skeletal muscle mass against progression from metabolically healthy to unhealthy phenotype

OBJECTIVE

Metabolically healthy individuals are known to be resistant to cardiovascular disease development. However, a considerable fraction of those individuals shows deteriorated metabolic health over time. Although skeletal muscle is the primary insulin-responsive target organ, a longitudinal investigation of the skeletal muscle mass in relation to the development of metabolically unhealthy phenotype has not been performed. We aimed to evaluate whether greater skeletal muscle mass is an independent protective factor for the development of metabolically unhealthy phenotype.

DESIGN, PARTICIPANTS AND MEASUREMENTS

We conducted a retrospective cohort study with 9033 metabolically healthy volunteers who underwent routine health examinations in 2012 and a follow-up examination in 2016. Obesity was defined as Asian-Pacific body mass index criterion ≥25 kg/m² . Subjects with fewer than two risk factors (elevated blood pressure, triglyceride, glucose, high-sensitivity C-reactive protein, insulin resistance and decreased high-density lipoprotein cholesterol levels) were characterized as metabolically healthy using Wildman criteria.

RESULTS

At the 4-year follow-up, approximately one-fourth of the nonobese participants and half of the participants with obesity showed metabolic deterioration. In nonobese men and women, higher appendicular skeletal muscle mass (ASM)/weight at baseline was significantly associated with decreased risk of metabolic deterioration. Compared to the lowest quartile of ASM/weight, the adjusted odds ratios (95% confidence intervals) of the highest quartile were 0.68 (0.52-0.89) in nonobese men and 0.64 (0.46-0.90) in nonobese women. However, this association was not observed in obese subjects.

CONCLUSIONS

Greater skeletal muscle mass at baseline is significantly associated with maintenance of metabolically healthy status, especially in nonobese individuals.

Association Between Thyroid Function and Development of Different Obesity Phenotypes in Euthyroid Adults: A Nine-Year Follow-Up

BACKGROUND

Considering inconsistent and conflicting data on associations of thyroid function, within the reference range, with anthropometric measures and metabolic syndrome, this study aimed to investigate the relationship between thyroid function and different obesity phenotypes over nine years of follow-up.

METHODS

This study was conducted on 1938 individuals from an ongoing population-based cohort study, the Tehran Thyroid Study. Participants were categorized into four obesity phenotypes based on body mass index and metabolic status. To investigate the associations of thyrotropin and free thyroxine (fT4) with incidence of different obesity phenotypes across the study period, a multivariate approach based on a generalized estimating equation method was used.

RESULTS

At baseline, individuals with the metabolically healthy normal weight (MHNW) phenotype had higher serum fT4 levels (1.2 ± 0.16 ng/dL vs. 1.14 ± 0.14 ng/dL, 1.16 ± 0.14 ng/dL, and 1.17 ± 0.15 ng/dL in metabolically healthy obese [MHO], metabolically unhealthy normal weight, and metabolically unhealthy obese individuals, respectively). The results of the generalized estimating equation analysis after multivariate adjustment for age, sex, smoking, physical activity, education level, thyroid peroxidase antibody status, and homeostasis model assessment-insulin resistance showed that each 1 ng/dL increment in fT4 levels within the reference range was accompanied with a 1.65-fold [confidence interval (CI) 1.09-2.5] increase of developing the MHNW phenotype during 9.2 years of follow-up. Moreover, each 1.0 ng/dL increment in fT4 within the reference range was associated with a 50% decreased risk of developing the MHO phenotype (odds ratio = 0.50 [CI 0.32-0.76]). Meanwhile, a significant positive association was found between serum thyrotropin levels and development of the metabolically unhealthy normal weight phenotype (odds ratio = 1.22 [CI 1.01-1.48]).

CONCLUSIONS

Serum fT4 concentrations within the reference range are associated with the development of some obesity phenotypes, including the MHNW and MHO phenotypes, after consideration of potential confounders.

Free-Living Responses in Energy Balance to Short-Term Overfeeding in Adults Differing in Propensity for Obesity

OBJECTIVE

Free-living adaptive responses to short-term overfeeding (OF) were explored as predictors of longitudinal weight change in adults classified as having obesity resistance (OR) or obesity proneness (OP) based on self-identification and personal/family weight history.

METHODS

Adults identified as OP (n = 21; BMI: 23.8 ± 2.5 kg/m² ) and OR (n = 20; BMI: 20.2 ± 2.1 kg/m² ) completed 3 days of eucaloric feeding (EU; 100% of energy needs) and 3 days of OF (140% of energy needs). Following each condition, adaptive responses in physical activity (PA), total daily energy expenditure, ad libitum energy intake, and energy balance were objectively measured for 3 days in a free-living environment. Body mass and composition were measured annually by using dual-energy x-ray absorptiometry for 5 years. Adaptive responses to OF were correlated with 5-year changes in body mass and composition.

RESULTS

Increases in sedentary time correlated with longitudinally measured changes in fat mass (r = 0.34, P = 0.04) in the cohort taken as a whole. Those with OP reduced their levels of PA following OF, whereas those with OR maintained or increased their PA. No other variables were found to correlate with weight gain.

CONCLUSIONS

Failure to decrease sedentary behavior following short-term OF is one mechanism that may be contributing to fat mass gain.

Cycling Efficiency During Incremental Cycle Ergometry After 24 Hours of Overfeeding or Fasting

OBJECTIVE

The objective of this study was to determine whether net cycling efficiency (NET) is altered by 24-hour fasting or overfeeding and whether it correlates with dietary-related energy expenditure (EE) and future weight change.

METHODS

In a crossover design, healthy subjects fasted or were overfed for 24 hours while in a whole-room calorimeter using five diets with doubled energy needs: standard, high-carbohydrate (75%), high-fat (60%), high-protein (30%), and low-protein (3%) diets. Graded cycling exercise at low power outputs (10-25-50 W) was performed the day before and after each dietary intervention.

RESULTS

NET did not change following any dietary intervention (all P > 0.05 vs. 0). Individual changes in NET did not correlate with EE responses to dietary interventions. However, the change in NET after low-protein overfeeding was inversely correlated with baseline body fat (r = -0.60, P = 0.01); that is, NET increased in lean but decreased in overweight subjects (Δ = 0.010 ± 0.010 vs. -0.013 ± 0.009, P = 0.0003). Increased NET following the low-protein diet was associated with weight gain after 6 months (r = 0.60, P = 0.05).

CONCLUSIONS

Despite no substantial effect of acute overfeeding or fasting on NET, the change in NET following low-protein overfeeding depends on adiposity and may influence weight change, suggesting that increased efficiency in a setting of protein scarcity is an adaptive response that may ultimately lead to weight gain.

Predictors of incident obesity phenotype in nonobese healthy adults

BACKGROUND

Despite their different cardiovascular consequences, little is known about predictors of metabolically healthy (MHO) and metabolically unhealthy obesity (MUHO). This cohort study was designed to address this question in participants of the Tehran Lipid and Glucose Study.

MATERIALS AND METHODS

Employing the Joint Interim Statement (JIS) metabolic syndrome criteria to define MHO/MUHO phenotypes, nonobese, otherwise healthy individuals, aged > 20 years (n = 3489) were recruited and followed up for a median of 13·4 years.

RESULTS

At the follow-up, MHO incidence rate in obese individuals was 36·6%. Comparing MHO vs. MUHO, female gender [odds ratio (OR) = 3·28, 95% confidence interval (CI) 1·27, 8·46)], increased body mass index (BMI; OR = 1·32, 95% CI: 1·12, 1·60) and elevated high-density lipoprotein cholesterol (HDL-C) levels (OR = 1·04, 95% CI: 1·02, 1·07) were related to higher odds of incident MHO, while older age (OR = 0·95, 95% CI: 0·92, 0·98), increased waist circumference (WC; OR = 0·86, 95% CI: 0·81, 0·91), higher WC gain (OR = 0·91, 95% CI: 0·87, 0·95) and increased diastolic blood pressure (DBP; OR = 0·94, 95% CI: 0·91, 0·98) prevented progression towards MHO.

CONCLUSIONS

While baseline BMI and WC were detrimental for developing MHO vs. MUHO, gender was the strongest predictor of incident obesity phenotype in healthy nonobese individuals.

[Adipokines Level in Metabolically Healthy Obese Saint-Petersburg Inhabitants (ESSE-RF)]

AIM

to elucidate prevalence of phenotypes of metabolically heathy obesity (MHO) among inhabitants of Saint-Petersburg using various criteria and assess dependence levels of adipokines on obesity phenotype.

MATERIAL AND METHODS

Within a framework of epidemiologic study ESSE-RF we formed a random sample of 1600 Saint-Petersburg inhabitants stratified according to gender and age. Examination of participants included anthropometry with measurement of waist circumference CRP and estimation of body mass index (BMI), measurement of arterial pressure, determination of fasting blood glucose, insulin (with calculation of index of insulin resistance -IIR), lipid spectrum, C-reactive protein (CRP), adiponectin, leptin. In subjects with obesity (BMI more or equal 30 kg/m) we used Meigs and Wildman MHO criteria. To Wildman criteria we applied 3 variants of definition of elevated CRP and IIR: 90th percentile among subjects with BMI <25 kg/m (variant 1) or among all participants (variant 2), and (variant 3) definition from publication by E.Oliveros et al. (2014).

RESULTS

Obesity (BMI more or equal 30 kg/m) was found in 430 participants. Numbers/rates of MHO according to the Wildman criteria were the following: variant 1 - 49/12% (among them 13/10% men and 36/14% women, =0.15); variant 2 - 85/22% (24/18% men, 61/23% women, =0.13); variant 3 - 59/15% (13/10% men, 46/18% women, =0.02). Portion of MHO according to Meigs criteria was 138/35% (among them 48/36% men, 90/35% women, =0.4). Significant differences in adipokines levels between subjects with MHO and metabolically unhealthy obesity (MUHO) were revealed only among women. There was no difference in leptin level between subjects with MHO and MUHO irrespective of gender.

CONCLUSION

Rate of MHO phenotype in a sample of inhabitants of Saint-Petersburg varied from 12 to 35% depending on criteria used. Gender differences in MHO rates were minimal and depended on selected criteria. Elevated adiponectin level among obese women could be presumably related to more favorable metabolic profile.

Complex relationship of obesity and obesity paradox in heart failure - higher risk of developing heart failure and better outcomes in established heart failure

Heart failure (HF) and obesity are major public health problems. Studies have shown that obesity may increase the risk of developing new HF but after patients have developed HF, obesity may be associated with improved outcomes. This paradoxical association of obesity with HF remains poorly understood. It is believed that the obesity paradox may in part be due to the inherent limitations of body mass index (BMI) as a measure of obesity. BMI may not appropriately measure important components of body mass like body fat, fat distribution, lean body mass, and body fluid content and may not be ideal for examining the relationship of body composition with health outcomes. Differentiating between body fat and lean body mass may explain some of the paradoxical association between higher BMI and better prognosis in patients with HF. Paradoxical outcomes in HF may also be due to phenotypes of obesity. Future studies need to develop and test metrics that may better measure body composition and may serve as a better tool for the estimation of the true association of obesity and outcomes in HF and determine whether the association may vary by obesity phenotypes. KEY MESSAGES Obesity predisposes to heart failure in all age groups. But obesity in heart failure is an area of controversy, because of obesity paradox, the apparent protective effect of overweight and mild obesity on mortality after development of heart failure. Traditional markers of obesity do not measure different components of body weight like muscle mass, fat, water, and skeletal weight. Body Mass Index in heart failure subjects does not measure accurately body fat or fluid retention. So new markers of obesity like visceral adiposity index, body composition analysis, sarcopenic status assessment may be helpful in the assessment of heart failure outcomes. Different phenotypes of obesity may be responsible for the different morbidity, mortality as well as therapeutic outcomes in heart failure.

Increased aerobic capacity reduces susceptibility to acute high-fat diet-induced weight gain

OBJECTIVE

Aerobic capacity is the most powerful predictor of all-cause mortality in humans; however, its role in the development of obesity and susceptibility for high-fat diet (HFD)-induced weight gain is not completely understood.

METHODS

Herein, a rodent model system of divergent intrinsic aerobic capacity [high capacity running (HCR) and low capacity running (LCR)] was utilized to evaluate the role of aerobic fitness on 1-week HFD-induced (45% and 60% kcal) weight gain. Food/energy intake, body composition analysis, and brown adipose tissue gene expression were assessed as important potential factors involved in modulating HFD-induced weight gain.

RESULTS

HCR rats had reduced 1-week weight gain on both HFDs compared with LCR. Reduced HFD-induced weight gain was associated with greater adaptability to decrease food intake following initiation of the HFDs. Further, the HCR rats were observed to have reduced feeding efficiency and greater brown adipose mass and expression of genes involved in thermogenesis.

CONCLUSIONS

Rats with high intrinsic aerobic capacity have reduced susceptibility to 1-week HFD-induced weight gain, which is associated with greater food intake adaptability to control intake of energy-dense HFDs, reduced weight gain per kcal consumed, and greater brown adipose tissue mass and thermogenic gene expression.

Disconnect between adipose tissue inflammation and cardiometabolic dysfunction in Ossabaw pigs

OBJECTIVE

The Ossabaw pig is emerging as an attractive model of human cardiometabolic disease because of its size and susceptibility to atherosclerosis, among other characteristics. The relationship between adipose tissue inflammation and metabolic dysfunction in this model was investigated here.

METHODS

Young female Ossabaw pigs were fed a Western-style high-fat diet (HFD) (n = 4) or control low-fat diet (LFD) (n = 4) for a period of 9 months and compared for cardiometabolic outcomes and adipose tissue inflammation.

RESULTS

The HFD-fed "OBESE" pigs were 2.5 times heavier (P < 0.001) than LFD-fed "LEAN" pigs and developed severe obesity. HFD feeding caused pronounced dyslipidemia, hypertension, and insulin resistance (systemic and adipose), as well as induction of inflammatory genes, impairments in vasomotor reactivity to insulin, and atherosclerosis in the coronary arteries. Remarkably, visceral, subcutaneous, and perivascular adipose tissue inflammation (via FACS analysis and RT-PCR) was not increased in OBESE pigs, nor were circulating inflammatory cytokines.

CONCLUSIONS

These findings reveal a disconnect between adipose tissue inflammation and cardiometabolic dysfunction induced by Western diet feeding in the Ossabaw pig model.

Ectopic adiposity is associated with autonomic risk factors and subclinical cardiovascular disease in young adults

OBJECTIVE

To examine the relationship between ectopic adiposity and markers of cardiometabolic risk, autonomic control, and subclinical cardiovascular disease (CVD).

METHODS

Cross-sectional analyses were performed in 324 subjects with overweight and obesity. Single-slice CT images were analyzed to calculate thigh muscle attenuation (MA), a measure of ectopic adiposity. Autonomic control was assessed using low-frequency to respiratory-frequency heart rate variability (LFa/RFa ratio). Carotid intima-media thickness (IMT) was a marker of subclinical CVD.

RESULTS

Among overweight participants, those with low MA had lower HDL-c, higher LFa/RFa ratio, and subcutaneous thigh fat compared to high MA individuals despite no difference in visceral fat or insulin resistance. Significant associations were not observed in the class I obese group. In the class II obese group, those with high MA had higher triglycerides and insulin levels, yet there was no difference in visceral fat compared to the low MA group. Mean IMT was significantly higher in the low MA compared to the high MA overweight group (0.63 mm vs. 0.58 mm, P = 0.04) but was similar between the low and high MA class II obese groups.

CONCLUSIONS

Excess ectopic adiposity in muscle tissue is associated with metabolic and autonomic risk factors and subclinical CVD, most notably in overweight individuals, independent of insulin resistance and visceral abdominal fat.

Burden of subclinical cardiovascular disease in "metabolically benign" and "at-risk" overweight and obese women: the Study of Women's Health Across the Nation (SWAN)

BACKGROUND

Metabolically benign obese individuals have a 10-year cardiovascular disease (CVD) risk comparable to healthy normal weight individuals. However, the burden of subclinical CVD among metabolically benign obese is not well known.

METHODS

In cross-sectional analyses of 475 mid-life women, we compared common carotid artery intima media thickness (CCA-IMT), aortic pulse wave velocity (aPWV) and coronary (CAC) and aortic calcification (AC) among three groups: healthy normal weight, metabolically benign overweight/obese (<3 metabolic syndrome components/elevated CRP), and at-risk overweight/obese (≥3 metabolic syndrome components/elevated CRP).

RESULTS

The mean (SD) CCA-IMT and aPWV were lowest in the normal weight group (n=145), followed by the benign overweight/obese (n=260) and at-risk overweight/obese (n=70) groups [CCA-IMT: 0.64 (0.08) vs. 0.68 (0.09) vs. 0.73 (0.13) mm, p<0.001; aPWV: 731.0 (176.4) vs. 809.9 (182.3) vs. 875.7 (228.8) cm/s, p<0.001]. Similar results were found for the frequency (%) of women with increased CAC and AC [CAC: 13 (9%) vs. 53(20%) vs. 28(40%), p<0.001; AC: 47(32%) vs. 130 (50%) vs. 55(79%), p<0.001]. These differences remained significant after multivariable adjustment. Further adjustment for BMI attenuated the statistical significance of differences in aPWV and calcification between benign and at-risk overweight/obese women, but had little effect on the magnitude of these differences.

CONCLUSIONS

Metabolically benign overweight/obese women have a significantly greater subclinical CVD burden than normal weight women, despite published data finding similar CVD event rates between the two groups. Prospective studies tracking the progression of subclinical atherosclerosis to clinical CVD in these women are needed.