Association of Mediterranean-DASH Intervention for Neurodegenerative Delay (MIND) diet and metabolically unhealthy overweight/obesity phenotypes among Iranian women: a cross sectional study.

PURPOSE: Paradoxes have been found in obesity, including individuals with metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUHO), and diet may be one of the reasons for the creation of these metabolic phenotypes. Hence, the purpose of the present study was to investigate the association of the Mediterranean-DASH intervention for neurodegenerative delay (MIND) diet with metabolically unhealthy overweight/obesity (MUHOW/O) phenotypes. METHODS: In this cross-sectional study, 229 overweight and obese women (body mass index (BMI) ≥ 25 kg/m2) aged 18-48 years were examined. Anthropometric measures and biochemical parameters were collected from all participants. The body composition of each participant was assessed using a bioelectrical impedance analyzer (BIA). The MIND diet score was determined based on 15 components using a valid and reliable food frequency questionnaire (FFQ) containing 147 items. Karelis criteria was used to determine metabolically healthy/unhealthy phenotype (MH/MUH). RESULTS: Among the participants, 72.5% of individuals were identified as MUH and 27.5% as MH, with a mean ± standard deviation (SD) age of 36.16 (8.33) years. The results of our analysis showed that after controlling for age, energy intake, BMI, and physical activity, there was no significant association observed between overweight/obesity phenotypes with tertile 2 (T2) (OR: 2.01, 95% CI: 0.86-4.17, P-value = 0.10), T3 (OR: 1.89, 95% CI: 0.86-4.17, P-value = 0.11) of MIND score, and only the odds of MUH relative to MH with a marginal significant decreasing trend was observed from the second to the third tertile (1.89 vs. 2.01) (P - trend = 0.06). Also, after additional adjustment for marital status, the nonsignificant association between overweight/obesity phenotypes with tertile 2 (T2) (OR: 2.13, 95% CI: 0.89-5.10, P-value = 0.08), T3 (OR: 1.87, 95% CI: 0.83-4.23, P-value = 0.12) of MIND score remained, and the odds of MUH relative to MH with a significant decreasing trend was observed with increasing tertiles (P-trend = 0.04). CONCLUSIONS: In conclusion, no significant associations were found between adherence to MIND diet with MUH, and only a significant downward trend in the odds of MUH was observed with increasing tertiles. We suggest further studies in this field.

Association between metabolic healthy obesity and female infertility: the national health and nutrition examination survey, 2013-2020.

BACKGROUND: Obesity has been confirmed to be associated with infertility. However, the association between metabolically healthy obesity (MHO), a subset of obesity with no metabolic abnormalities, and female infertility has not yet been investigated. This study aimed to examine the association between MHO and the risk of female infertility among United States. METHODS: This study utilized a cross-sectional design and included 3542 women aged 20-45 years who were selected from the National Health and Nutrition Examination Survey (NHANES) 2013-2020 database. The association between MHO and the risk of infertility was evaluated using risk factor-adjusted logistic regression models. RESULTS: Higher BMI and WC were associated with increased infertility risk after adjusting for potential confounding factors (OR (95% CI): 1.04(1.02, 1.06), P = 0.001; OR (95% CI): 1.02 (1.01, 1.03), P < 0.001; respectively). After cross-classifying by metabolic health and obesity according to BMI and WC categories, individuals with MHO had a higher risk of infertility than those with MHN (OR (95% CI): 1.75(0.88, 3.50) for BMI criteria; OR (95% CI): 2.01(1.03, 3.95) for WC criteria). A positive linear relationship was observed between BMI/WC and infertility risk among metabolically healthy women (Pnon-linearity=0.306, 0.170; respectively). CONCLUSIONS: MHO was associated with an increased risk of infertility among reproductive-aged women in the US. Obesity itself, regardless of metabolic health status, was associated with a higher infertility risk. Our results support implementing lifestyle changes aimed at achieving and maintaining a healthy body weight in all individuals, even those who are metabolically healthy.

Long-Term Prognosis of Acute Myocardial Infarction Associated With Metabolic Health and Obesity Status.

OBJECTIVE: Emerging evidence supports the favorable cardiovascular health in nonobese subjects with healthy metabolism. However, little is known regarding the prognosis across the range of metabolic phenotypes once cardiovascular disease is established. We examined the prognosis of patients with acute myocardial infarction (AMI) stratified according to metabolic health and obesity status. METHODS: This is a retrospective study on consecutive patients with AMI admitted to a tertiary hospital between 2014 and 2021. Patients were allocated into the following 4 groups based on metabolic and obesity profile: (1) metabolically healthy obese (MHO), (2) metabolically healthy nonobese (MHNO), (3) metabolically unhealthy obese (MUO), and (4) metabolically unhealthy nonobese (MUNO). Metabolic health was defined in accordance to the Biobank Standardisation and Harmonisation for Research Excellence in the European Union Healthy Obese Project. The primary outcome was all-cause mortality. The Cox regression analysis examined the independent association between mortality and metabolic phenotypes, adjusting for age, sex, AMI type, chronic kidney disease, smoking status, and left ventricular ejection fraction. RESULTS: Of 9958 patients, the majority (68.5%) were MUNO, followed by MUO (25.1%), MHNO (5.6%), and MHO (0.8%). MHO had the lowest mortality (7.4%), followed by MHNO (9.7%), MUO (19.2%), and MUNO (22.6%) (P < .001). Compared with MHNO, MUO (hazard ratio [HR], 1.737; 95% confidence interval [CI], 1.282-2.355; P < .001) and MUNO (HR, 1.482; 95% CI, 1.108-1.981; P = .008) had a significantly higher mortality risk but not MHO (HR, 1.390; 95% CI, 0.594-3.251; P = .447), after adjusting for confounders. The Kaplan-Meier curves showed favorable survival in the metabolically healthy and obesity groups, with the highest overall survival in the MHO, followed by MHNO, MUO, and MUNO (P < .001). CONCLUSION: Metabolically healthy and obese patients with AMI have favorable prognosis compared with metabolically unhealthy and nonobese patients. It is equally important to prioritize intensive metabolic risk factor management to weight reduction in the early phase after AMI.

Association of Lifelines Diet Score (LLDS) and metabolically unhealthy overweight/obesity phenotypes in women: a cross-sectional study.

BACKGROUND: Previous studies have shown the association of a number of dietary quality scores with metabolically phenotypes of obesity. Recently, the Lifelines Diet Score (LLDS), which is a fully food-based score based on the 2015 Dutch dietary guidelines and underlying international literature, has been proposed as a tool for assessing the quality of the diet. Therefore, this study was performed to investigate the association between LLDS and metabolically healthy/unhealthy overweight and obesity (MHO/MUHO) phenotypes. METHODS: This study was performed on 217 women, aged 18-48 years old. For each participant anthropometric values, biochemical test and body composition were evaluated by standard protocols and methods. The LLDS was determined based on 12 components using a valid and reliable food frequency questionnaire (FFQ) containing 147 items. The metabolically healthy (MH) was evaluated using the Karelis criteria. RESULTS: Among the total participants in this study, 31.3% of the subjects were MHO while 68.7% were MUHO. After adjustment for potential confounding variables (age, energy intake, and physical activity), participants in highest LLDS tertile had a lower odds of MUHO compared with those in the lowest tertile (OR: 1.18; 95% CI: 0.23, 5.83; P-trend = 0.03). Also, after further adjustment with BMI, provided only small changes in "OR" and did not attenuate the significance (OR: 1.28; 95% CI: 0.23, 6.91; P-trend = 0.02). CONCLUSIONS: The present evidence indicates that individuals with higher adherence to the LLDS had lower odds of metabolically unhealthy (MUH).

Metabolically Healthy Obesity (MHO)-New Research Directions for Personalised Medicine in Cardiovascular Prevention.

PURPOSE OF REVIEW: To discuss new findings on the heterogeneity of obesity and associated risks. RECENT FINDINGS: Obesity is a public health problem of immense importance on a global scale. However, epidemiological findings and clinical studies have revealed that obesity is a heterogeneous phenotype and that not all obese subjects run the same risk for complications. Current research has tried to describe so-called metabolically healthy obesity (MHO), defined by lack of risk factors included in the metabolic syndrome. These subjects will not escape long-term complications, but mortality risk is not increased. However, a new definition of MHO has recently been proposed, based on the lack of hospitalisation for somatic disease for decades in middle life. MHO subjects defined in this way are characterised by being "fat and fit" and also run a lower risk of long-term complications. If MHO could be better understood, this could contribute to a more diverse clinical approach to obesity based on personalised medicine.

Metabolic abnormalities, but not obesity per se, associated with chronic kidney disease in a Taiwanese population.

BACKGROUND AND AIMS: It is inconclusive whether obesity itself or metabolic abnormalities are linked to chronic kidney disease (CKD). The aim of this study was to examine the association between different subtypes of obesity and metabolic abnormalities with CKD in adults. METHODS AND RESULTS: This study enrolled 14,983 eligible subjects stratified into metabolically healthy normal weight (MHNW), metabolically healthy overweight (MHOW), metabolically healthy obesity (MHO), metabolically unhealthy normal weight (MUNW), metabolically unhealthy overweight (MUOW), and metabolically unhealthy obesity (MUO) according to body mass index and metabolic syndrome status (ATP-III criteria). The metabolic healthy phenotype was defined as the absence of both metabolic syndrome and any known diabetes, coronary artery disease, stroke, hypertension or dyslipidemia. Early and advanced CKD were defined as eGFR<60, proteinuria, or structural abnormalities as detected by renal sonography. The prevalence of CKD was 2.5, 3.0, 4.0, 10.6, 9.5, and 10.5% in subjects with MHNW, MHOW, MHO, MUNW, MUOW, and MUO, respectively. In the multivariate analysis, the MUNW (OR:2.22, P < 0.001), MUOW (OR:2.22, P < 0.001), and MUO (OR:2.45, P < 0.001) groups were associated with early CKD. For advanced CKD, the OR was 2.56 (P < 0.001), 2.31 (P < 0.001), and 3.49 (P < 0.001) in the MUNW, MUOW, and MUO groups, respectively. The associated risks of early and advanced CKD were not significant in the MHOW and MHO group. MUOW and MUO were associated with higher risk of CKD compared with MHOW and MHO after adjusting other variables. CONCLUSIONS: Metabolic abnormalities, but neither overweight nor obesity, were associated with a higher risk of CKD in adults.

[Epicardial adipose tissue as a marker of visceral obesity and its association with metabolic parameters and remodeling of the left chambers of the heart in young people with abdominal obesity].

AIM: to study the correlation of epicardial adipose tissue (EAT) with metabolic parameters, 24-hours profile of blood pressure (BP) and left ventricular remodeling, with the volume of intraabdominal adipose tissue (IAAT), measured by multislice computed tomography (MSCT) in patients with abdominal obesity and metabolic syndrome. MATERIALS AND METHODS: the study included 80 participants with abdominal obesity (waist circumference > 80 cm in women and >94 cm in men) and without cardiovascular diseases and diabetes. Within this study the following examinations were performed: waist circumference and the body mass index measurement, blood sampling and measurements of lipid levels, uric acid, fasting glucose, insulin, HOMA index, 24-hour ambulatory blood pressure monitoring. Left ventricular (LV) mass index, relative wall thickness, LV mass/height index were estimated from echocardiographic data. EAT volume and IAAT was measured by MSCT. All patients was devided in two groups for analysis: 1 (n=28) - patients with isolated abdominal obesity, without metabolic syndrome, age was 37.5±6.43 years; 2 (n=52) - patients with metabolic syndrome, age - 38.8±5.88 years. The control group 0 included healthy individuals (n=13) without obesity, age was 30.5±5.97 years. RESULTS: A positive correlation was found between the volume of EAT with the level of insulin in the blood (r=0.2937, p.

Leptin to adiponectin ratio - A surrogate biomarker for early detection of metabolic disturbances in obesity.

AIM: To study if the leptin to adiponectin (L:A) ratio, can be a potential biomarker for postprandial triglyceride clearance, insulin resistance (IR) or leptin resistance (LR) in apparently healthy obese, and obese individuals with established metabolic disease. METHODS AND RESULTS: Fifty adult subjects with obesity (BMI ≥30); of which 36 metabolic healthy obese (MHO), and 14 metabolic dysregulated obese (MDO), with clinical and/or biochemical signs of metabolic disease were included. Seventeen healthy, normal weight subjects represented the control group. Postprandial triglyceride (TG) levels were measured in an 8 h oral fat tolerance test (OFTT). IR by HOMA-IR, L:A ratio and indirect LR were measured. In the MHO group, 71.4%, 69.4% and 86.1%, had delayed TG clearance, IR and LR, respectively; whereas in the MDO group this was detected in 85.7%, 71.4% and 91.7%, respectively. A combination of all three metabolic risk factors was found in 39.8% of the MHO and in 42.9% of the MDO patients. Receiver operating characteristics (ROC) analysis revealed that a cut-off value for the L:A ratio of >1.65 for the control group (PPV 1.0, NPV 0.91) and >3.65 for the obese subjects (PPV 0.86, NPV 0.48) predicted the delayed TG clearance with a good specificity and sensitivity. Detecting a combined risk with at least 2/3 metabolic risk factors, the ROC yielded the most suitable L:A ratio cut-off at >1.88. CONCLUSION: L:A ratio was able to detect early metabolic disturbances in obese individuals, and may be a potential useful clinical surrogate biomarker of metabolic disorders.

Evidence That Skeletal Muscles Modulate HDL-Cholesterol in Metabolic Healthy Young Adults.

The aim of this study was to investigate whether skeletal muscle (SM) mass correlates with plasma lipids in metabolic healthy young adults. The study was designed as a retrospective observational monocentric study. Data on plasma lipids and SM mass of subjects attending our institution from 1999 to 2014 were analyzed. Inclusion criteria were being 18-45 years old and in apparently good health. SM mass was evaluated by bioelectrical impedance analysis (BIA) using the equation proposed by Janssen and normalized to height as skeletal muscle index (SMI: SM mass/height2). The association between SMI and plasma lipids levels was examined using a crude and adjusted linear regression model including age, sex, BMI and waist circumference as additional covariates. The study population consisted of 450 subjects (273 females) without metabolic syndrome (12.2% with normal body weight, 33.1% overweight, and 54.7% with obesity). SMI, total-cholesterol, LDL-cholesterol, and Triglycerides were higher, whereas HDL-cholesterol was lower in overweight and obese patients as compared with normal weight subjects. SMI was inversely associated with HDL-cholesterol in female patients with obesity but not in male patients with obesity, in normal- or over-weight subjects (p < 0.05). These results suggest that changes in SM mass occurring in obesity could have a role in worsening lipid profile with special reference to HDL-cholesterol.

Impact of Synbiotic Intake on Liver Metabolism in Metabolically Healthy Participants and Its Potential Preventive Effect on Metabolic-Dysfunction-Associated Fatty Liver Disease (MAFLD): A Randomized, Placebo-Controlled, Double-Blinded Clinical Trial.

Synbiotics modulate the gut microbiome and contribute to the prevention of liver diseases such as metabolic-dysfunction-associated fatty liver disease (MAFLD). This study aimed to evaluate the effect of a randomized, placebo-controlled, double-blinded seven-week intervention trial on the liver metabolism in 117 metabolically healthy male participants. Anthropometric data, blood parameters, and stool samples were analyzed using linear mixed models. After seven weeks of intervention, there was a significant reduction in alanine aminotransferase (ALT) in the synbiotic group compared to the placebo group (-14.92%, CI: -26.60--3.23%, p = 0.013). A stratified analysis according to body fat percentage revealed a significant decrease in ALT (-20.70%, CI: -40.88--0.53%, p = 0.045) in participants with an elevated body fat percentage. Further, a significant change in microbiome composition (1.16, CI: 0.06-2.25, p = 0.039) in this group was found, while the microbial composition remained stable upon intervention in the group with physiological body fat. The 7-week synbiotic intervention reduced ALT levels, especially in participants with an elevated body fat percentage, possibly due to modulation of the gut microbiome. Synbiotic intake may be helpful in delaying the progression of MAFLD and could be used in addition to the recommended lifestyle modification therapy.

Clinical outcomes of obese and nonobese patients with atrial fibrillation according to associated metabolic abnormalities: A report from the COOL-AF registry.

BACKGROUND: The primary objective was to determine the influence of obesity and associated metabolic status on clinical outcomes of Asian patients with atrial fibrillation (AF). METHODS: This study was based on a prospective multicenter of patients with nonvalvular AF. Patients were classified as obese and nonobese and being metabolic unhealthy was defined as having at least one of the three cardiovascular risk factors including dyslipidemia, hypertension, or diabetes mellitus. Outcomes were a primary composite outcome of all-cause death, ischemic stroke/systemic embolism (SSE), acute myocardial infarction (MI), and heart failure (HF), as well as the individual end points. RESULTS: There were a total of 3141 enrolled patients (mean age 67.4 ± 11.1 years; 41.0% female), of whom 1566 (49.9%) were obese and 2564 (81.6%) were metabolic unhealthy. During a mean follow-up of 32.2 ± 8.3 months, the incidence rate of the composite outcome, all-cause death, SSE, MI, and HF were 7.21 (6.63-7.82), 3.86 (3.45-4.30), 1.48 (1.23-1.77), 0.47 (0.33-0.64), and 2.84 (2.48-3.23) per 100 person-years, respectively. Metabolic unhealthy nonobese subjects were at higher risk of the composite outcomes than metabolic unhealthy obese subjects with hazard ratio (HR) 1.39, 95% confidence interval (CI) 1.17-1.66, p < .001. Metabolic unhealthy obese subjects tend to have an increased risk of the composite outcomes compared to those metabolic healthy obese (HR 1.36, 95% CI 0.91-2.02, p = .133). Metabolic healthy obese subjects were not associated with increased risk. CONCLUSIONS: Metabolic unhealthy obese subjects were associated with an increased risk of adverse outcomes in AF patients, whereas metabolically healthy obesity was not associated with an increased risk.

Comparative analyses of surrogates of metabolic syndrome in children and adolescents with metabolically healthy obesity vs. metabolically unhealthy obesity according to Damanhoury's criteria.

OBJECTIVES: Metabolically healthy obesity (MHO) has been reported with varying frequencies in children. The reasons of metabolically healthy phenotype in some obese subjects are unclear. Our aim was to identify the frequency of MHO in obese subjects, to assess the potential associations of demographic characteristics, serum uric acid, alanine transaminase (ALT), pediatric nonalcoholic fatty liver disease fibsosis score probability (PNFS p) with MHO status and to evaluate the differences between MHO and metabolically unhealthy obesity (MUO) with regard to metabolic syndrome surrogates. METHODS: 251 consecutive obese subjects (125 females) aged 7-18 years were included. Subjects were classified as having MHO according to Damanhoury's criteria. Several metabolic variables were measured, PNFS p was calculated by using the formula: z=1.1+(0.34*sqrt(ALT))+ (0.002*ALP)-(1.1*log(platelets)-(0.02*GGT). RESULTS: Median age of the subjects was 12.5 yr (range: 7.0-17.0 yr). The frequency of MHO was 41 %. Subjects with MHO were significantly younger, had lower waist circumference (WC) and waist height ratio (WHtR) and lower HOMA-IR than those without MHO(p<0.05 for all). Frequencies of hyperuricemia, hypertransaminasemia, hepatosteatosis and PNFS p values≥8 were similar betwen the groups. When putatively influential factors associated with MHO status were assessed with logistic regression analysis, only WC(ß=1.03) and HOMA-IR(ß=1.166) emerged as significant factors(Nagelkerke R2=0.142). None of the investigated demographic factors were associated with MHO status. CONCLUSIONS: We found a remarkably high frequency of MHO status. Nevertheless, the absence of decreased frequencies of hyperuricemia, hypertransaminasemia and PNFS in subjects with MHO may suggest the need to reconsider the validity of the criteria defining MHO.

The mediatory role of inflammatory markers on the relationship between the NOVA classification system and obesity phenotypes among obese and overweight adult women: a cross-sectional study.

Background: Diet and inflammation both play important roles in the occurrence of obesity. We aimed to investigate the role of inflammation in the development of both metabolically healthy obese (MHO) and metabolically unhealthy obese (MUHO) individuals. Methods: This cross-sectional study included 221 overweight and obese women aged 18-56 years. The study assessed the metabolic health phenotypes of the participants using the Karelis criterion score. Additionally, dietary intakes were evaluated using a 147-item semi-quantitative questionnaire and the NOVA classification system (comprising 37 food groups and beverages). The study also collected and analyzed the blood parameters, as well as biochemical and anthropometric indices, for all participants. Results: Among the women included in the study, 22.9% had MHO phenotypes but 77.1% had MUHO phenotypes. A significant association between the third quartile of the NOVA classification system and the increased likelihood of having the MUHO phenotype was observed (OR = 1.40, 95% CI = 1.09-4.92, p = 0.04). Regarding the potential role of inflammatory markers, high-sensitivity C-reactive protein (hs-CRP) (p = 0.84), transforming growth factor-ß (TGF-ß) (p = 0.50), monocyte chemoattractant protein-1 (MCP-1) (p = 0.49), plasminogen activator inhibitor-1 (PAI-1) (p = 0.97), and homeostatic model assessment for insulin resistance (HOMA-IR) (p = 0.92) were found to be mediators. Conclusion: We observed a significant positive association between ultra-processed food (UPF) consumption and the MUHO phenotype in overweight and obese women. This association appeared to be mediated by some inflammatory markers, such as hs-CRP, TGF-ß, MCP-1, PAI-1, and HOMA-IR. Additional studies are needed to validate these findings.

Evaluation of microalbuminuria in obesity phenotypes.

BACKGROUND: Obesity is a universal health issue of the present time. Nearly 2 billion people were estimated to be either overweight or obese in 2020, with nearly 3.4 million deaths worldwide. Proteinuria is now widely known to be a significant predictor of renal pathologies including end-stage renal disease. This study aimed to assess the relationship between the presence of microalbuminuria (MA) in obese individuals. MATERIALS AND METHODS: This cross-sectional study was conducted among patients attending the outpatient department of Jawaharlal Nehru Medical College and Acharya Vinoba Bhave Rural Hospital, Sawangi (Meghe), Wardha. From the subjects meeting the study criteria, selected 150 individuals with BMI ≥ 25 that formed the obese group. Obese individuals were further subdivided as metabolic healthy obese (MHO) and metabolic abnormal obese (MAO) based on metablic syndrome criteria. From the non-obese patients (BMI≤25), one age and gender matched control was selected for each obese subject. All subjects were tested for MA by dipstick method. Data was analyzed using SPSS and Chi-square test was performed to test for statistical significance. RESULTS: The study reflected the association of MA in the groups studied. The metabolic abnormal obese group was noted as having the highest percentage of positive cases (53.7%) of MA, followed by the MHO group (31.3%). A significant association of prevalence of MA was seen in MHO and MAO obese individuals (P < 0.001). MA was present in the urine samples of 26 (31.3%) obese subjects in the MHO group, 36 (53.7%) in the MAO group, and 8 (5.3%) in the control population. CONCLUSION: Both MHO and MAO subgroups of obese individuals showed higher proportion of MA indicating adverse renal function. Therefore, primary prophylactic measures such as health education and lifestyle modification should be promoted for the obese to reduce their body weight and thereby possibly reduce the risk of future obesity-related renal complications.

Correlations between Coffee Consumption and Metabolic Phenotypes, Plasma Folate, and Vitamin B12: NHANES 2003 to 2006.

Metabolic syndrome (MetS) is prevalent not only among the overweight and obese but also normal weight individuals, and the phenotype is referred to as a metabolically unhealthy phenotype (MUHP). Besides normal weight individuals, overweight/obese individuals are also protected from MetS, and the phenotype is known as a metabolically healthy phenotype (MHP). Epidemiological studies indicate that coffee and micronutrients such as plasma folate or vitamin B12 (vit. B12) are inversely associated with MetS. However, correlations among coffee consumption metabolic phenotypes, plasma folate, and vit. B12 remain unknown. Our objective was to investigate the correlation between coffee consumption, metabolic phenotypes, plasma folate, and vit. B12 as well as to understand associations between plasma folate, vit. B12, and metabolic phenotypes. Associations among coffee consumption metabolic phenotypes, plasma folate, and vit. B12 were assessed in a cross-sectional study of 2201 participants, 18 years or older, from 2003-2004 and 2005-2006 National Health and Nutrition Examination Surveys (NHANES). MUHP was classified as having > three metabolic abnormalities. Coffee consumption was not associated with metabolic phenotypes, but negatively correlated with several metabolic variables, including BMI (p < 0.001). Plasma folate was positively associated with MUHP (p < 0.004), while vit. B12 was inversely associated with MUHP (p < 0.035). Our results suggest the potential protective impact of coffee on individual components of MetS and indicate a positive correlation between coffee consumption and MUHP among overweight individuals. Identifying possible dietary factors may provide practical and low-cost dietary intervention targets, specifically for early intervention. Larger and randomized intervention studies and prospective longitudinal studies are required to further evaluate these associations.

Proteomic analysis to identify differentially expressed proteins between subjects with metabolic healthy obesity and non-alcoholic fatty liver disease.

Obese subjects with non-alcoholic fatty liver disease (NAFLD) and considered metabolically healthy have not been well differentiated. In this study, obese subjects were divided into metabolic healthy obesity (MHO) and NAFLD groups. Liver tissues were sampled from these two types of subjects undergoing bariatric surgery, and proteins in the liver tissues that expressed differently between the two groups of subjects were identified by Tandem Mass Tags (TMT) assay. Compared with the MHO group, 132 proteins were found to be upregulated and 84 proteins were found to be downregulated (mainly localized in mitochondria) in NAFLD group. The KEGG pathway analysis showed that significantly upregulated metabolic pathways include PPAR signaling, ECM-receptor interaction and oxidative phosphorylation was significantly downregulated. The GO analysis revealed that upregulated proteins were involved in extracellular structure organization, extracellular matrix organization and downregulated proteins took part in the oxidation-reduction process and so on. FBLN5 and DHRS2 were further validated by Western blot, immunohistochemistry and ELISA. All results demonstrate that FBLN5 expression was significantly upregulated but DHRS2 was significantly downregulated. SIGNIFICANCE: The variation between MHO and NAFLD was studied by mass spectroscopy to evaluate the mechanism with which MHO subjects resist the harmful effects induced by obesity.

ANGPTL4 gene E40K variation protects against obesity-associated dyslipidemia in participants with obesity.

OBJECTIVE: ANGPTL4 inhibits lipoprotein lipase in adipose tissue, regulating plasma triglycerides levels. In persons with obesity plasma ANGPTL4 levels have been positively correlated with body fat mass, TG levels and low HDL. A loss-of-function E40K mutation in ANGPTL4 prevents LPL inhibition, resulting in lower TGs and higher HDLc in the general population. Since obesity determines metabolic alterations and consequently is a major risk factor for cardiovascular disease, the aim was to explore if obesity-related metabolic abnormalities are modified by the ANGPTL4-E40K mutation. METHODS: ANGPTL4-E40K was screened in 1206 Italian participants, of which 863 (71.5%) with obesity. All subjects without diabetes underwent OGTT with calculation of indices of insulin-sensitivity. RESULTS: Participants with obesity carrying the E40K variant had significantly lower TG (p = 0.001) and higher HDLc levels (p = 0.024). Also in the whole population low TGs and high HDLc were confirmed in E40K carriers. In the obese subpopulation it was observed that almost all E40K carriers were within the lowest quartile of TGs (p = 1.1 × 10-9). E40K had no substantial effect of on glucose metabolism. Finally, none of the obese E40K carriers had T2D, and together with the favourable lipid profile, they resemble a metabolically healthy obese (MHO) phenotype, compared to 38% of E40E wild-type obese that had diabetes and/or dyslipidaemia (p = 0.0106). CONCLUSIONS: In participants with obesity the ANGPTL4-E40K variant protects against dyslipidemia. The phenotype of obese E40K carriers is that of a patient with obesity without metabolic alterations, similar to the phenotype described as metabolic healthy obesity.

Relations of major dietary patterns and metabolically unhealthy overweight/obesity phenotypes among Iranian women.

OBJECTIVE: No studies have examined the contribution of major dietary patterns to MUH phenotypes in obese and overweight people based on Karelis criteria. This study was conducted to evaluate the association of major dietary patterns with MUHOW/O and MHOW/O phenotypes. METHODS: This cross-sectional study was conducted on 290 overweight and obese women aged 18-50 (BMI≥25 kg/m2). Anthropometric measurements were assessed in all participants. The MH phenotype was defined according to the Karelis criteria. Major dietary patterns were determined using factor analysis of 21 foods groups using a valid and reliable FFQ containing 147 items. Participants' body composition was assessed by BIA. Serum HDL, LDL, TG, insulin, and hs-CRP levels were quantified by ELISA. RESULTS: By the use of factor analysis, 3 major dietary patterns were extracted: healthy dietary pattern (HDP), western dietary pattern (WDP) and unhealthy dietary pattern (UNHDP). Binary logistic analysis showed that participants in the in the upper category of WDP had greater odds of MUH phenotype (OR = 2.33, 95%CI = 1.11-4.91, P = 0.02), after confounder factor control. Individuals with high adherence to the UNHDP score had high odds of MUH phenotype (OR = 1.75, 95%CI = 0.98-3.10, P = 0.05), after adjustment for BMI, age, and total EI, compared to those with low adherence. A positive relation was observed between WDP and levels of hs-CRP, HOMA-IR (OR = 1.94, 95%CI = 0.91-4.10, P = 0.05 and OR = 2.53, 95%CI = 1.26-5.11, P = 0.009) as well as a positive association between UHDP and plasma level of LDL (OR = 1.90, 95%CI = 1.04-3.47, P = 0.03), but an inverse association between HDP and hs-CRP level (OR = 0.56, 95%CI = 0.29-0.92, P = 0.03). CONCLUSIONS: The present evidence indicates various significant associations among major dietary patterns and MUHOW/O phenotypes.

The long-term prognosis of heart diseases for different metabolic phenotypes: a systematic review and meta-analysis of prospective cohort studies.

PURPOSE: This meta-analysis aimed to assess the association of different categories of weight and metabolic status with risk of heart diseases including myocardial infarction (MI), cardiovascular diseases (CVDs), and heart failure (HF). METHODS: Data from relevant studies were identified systematically by searching PubMed and Scopus search engines up to 29 May 2018. Prospective studies were included in the analyses with metabolically healthy normal weight (MHNW) as the reference. Pooled RRs and 95% CI were calculated using random-effects or fixed-effect models when appropriate. Subgroup analysis was applied to define possible sources of heterogeneity. RESULTS: Overall, 21 studies (n = 778,401 participants) were eligible for the present meta-analysis. Generally, the risk of CVDs for all metabolic phenotypes in metabolically unhealthy obese increased compared with the MHNW group. A significant positive association between all metabolic phenotypes and the risk of HF was also observed expect for MHOW (RR = 1.10, 95% CI: 0.60-2.00, P = 0.76) and MHO phenotypes (RR = 0.96, 95% CI: 0.25-3.77, P = 0.95). Moreover, MUHO phenotype was associated with greater risk of MI compared with the MHNW phenotype (RR = 1.82, 95% CI: 1.50-2.22, P < 0.001, respectively). CONCLUSIONS: Our findings showed that all metabolically unhealthy phenotypes in different categories of weight were associated with increased incident of CVDs/HF and MI. Furthermore, healthy overweight and obese subjects had increased risk of CVDs.