Fatty liver as a risk factor for progression from metabolically healthy to metabolically abnormal in non-overweight individuals

The Definition and Prevalence of Obesity and Metabolic Syndrome: Correlative Clinical Evaluation Based on Phenotypes

Increase in the prevalence of obesity has become a major worldwide health problem in adults as well as among children and adolescents. In the last four decades, studies have revealed that the significant increase in the prevalence of obesity has become a pandemic. Obesity is the result of complex interactions between biological, genetic, environmental, and behavioral factors. Indeed, almost all of the children suffering from obesity in early childhood face with being overweight or obese in adolescence. Different phenotypes have different risk factors in the clinical evaluation of obesity. Individuals suffering from metabolically unhealthy obesity (MUO) are at an excess risk of developing cardiovascular diseases (CVDs), several cancer types, and metabolic syndrome (MetS), whereas the metabolically healthy obesity (MHO) phenotype has a high risk of all-cause mortality and cardiometabolic events but not MetS. While most obese individuals have the MUO phenotype, the frequency of the MHO phenotype is at most 10-20%. Over time, approximately three-quarters of obese individuals transform from MHO to MUO. Total adiposity and truncal subcutaneous fat accumulation during adolescence are positively and independently associated with atherosclerosis in adulthood. Obesity, in general, causes a large reduction in life expectancy. However, the mortality rate of morbid obesity is greater among younger than older adults. Insulin resistance (IR) develops with the central accumulation of body fat. MHO patients are insulin-sensitive like healthy normal-weight individuals and have lower visceral fat content and cardiovascular consequences than do the majority of MUO patients. MetS includes clustering of abdominal obesity, dyslipidemia, hyperglycemia, and hypertension. The average incidence of MetS is 3%, with a 1.5-fold increase in the risk of death from all causes in these patients. If lifestyle modifications, dietary habits, and pharmacotherapy do not provide any benefit, then bariatric surgery is recommended to reduce weight and improve comorbid diseases. However, obesity treatment should be continuous in obese patients by monitoring the accompanying diseases and their consequences. In addition to sodium-glucose co-transporter-2 (SGLT2) inhibitors, the long-acting glucagon-like peptide-1 (GLP-1) receptor agonist reduces the mean body weight. However, caloric restriction provides more favorable improvement in body composition than does treatment with the GLP-1 receptor (GLP1R) agonist alone. Combination therapy with orlistat and phentermine are the US Food and Drug Administration (FDA)-approved anti-obesity drugs. Recombinant leptin and synthetic melanocortin-4-receptor agonists are used in rarely occurring, monogenic obesity, which is due to loss of function in the leptin-melanocortin pathway.

Changes in glycemic control and skeletal muscle mass indices after dapagliflozin treatment in individuals with type 1 diabetes mellitus

AIMS/INTRODUCTION

Dapagliflozin is used for individuals with type 1 diabetes, although the effect of this medication on skeletal muscle mass is not well established. In addition, there are few studies examining the effects of good glycemic control on skeletal muscle mass in type 1 diabetes patients. We investigated changes in glycemic control and skeletal muscle mass with dapagliflozin in individuals with type 1 diabetes, and the association between these changes.

MATERIALS AND METHODS

This was a post-hoc analysis of a multicenter, open-label, non-randomized, prospective, interventional study in individuals with type 1 diabetes. The participants received dapagliflozin at 5 mg/day for 4 weeks, and were reviewed before and after treatment. Weight- and height-corrected appendicular skeletal muscle mass (ASM) were calculated as indices of skeletal muscle mass using bioelectrical impedance analysis.

RESULTS

A total of 36 individuals were included in the analysis. After the 4 weeks of dapagliflozin treatment, ASM/height2 decreased in the body mass index <23 group (P = 0.004). ASM / weight decreased in all men aged >60 years. The change in ASM / weight (%) was negatively correlated with the change in glycated hemoglobin (%;P = 0.023). The change in ASM / height2 (kg/m2 ) was also positively correlated with the change in time within the glucose range of 70-180 mg/dL (P = 0.036).

CONCLUSION

Dapagliflozin treatment of individuals with type 1 diabetes, particularly non-obese individuals and older men, might result in loss of skeletal muscle mass. However, good glycemic control during treatment might prevent the onset and progression of sarcopenia.

Metabolic phenotyping in people living with obesity: Implications for dietary prevention

Given the increasing number of people living with obesity and related chronic metabolic disease, precision nutrition approaches are required to increase the effectiveness of prevention strategies. This review addresses these approaches in different metabolic phenotypes (metabotypes) in obesity. Although obesity is typically associated with an increased cardiometabolic disease risk, some people with obesity are relatively protected against the detrimental effects of excess adiposity on cardiometabolic health, also referred to as 'metabolically healthy obesity' (MHO). Underlying mechanisms, the extent to which MHO is a transient state as well as lifestyle strategies to counteract the transition from MHO to metabolically unhealthy obesity (MUO) are discussed. Based on the limited resources that are available for dietary lifestyle interventions, it may be reasonable to prioritize interventions for people with MUO, since targeting high-risk patients for specific nutritional, lifestyle or weight-loss strategies may enhance the cost-effectiveness of these interventions. Additionally, the concept of tissue insulin resistant (IR) metabotypes is discussed, representing distinct etiologies towards type 2 diabetes (T2D) as well as cardiovascular disease (CVD). Recent evidence indicates that these tissue IR metabotypes, already present in individuals with obesity with a normal glucose homeostasis, respond differentially to diet. Modulation of dietary macronutrient composition according to these metabotypes may considerably improve cardiometabolic health benefits. Thus, nutritional or lifestyle intervention may improve cardiometabolic health, even with only minor or no weight loss, which stresses the importance of focusing on a healthy lifestyle and not on weight loss only. Targeting different metabotypes towards T2D and cardiometabolic diseases may lead to more effective lifestyle prevention and treatment strategies. Age and sex-related differences in tissue metabotypes and related microbial composition and functionality (fermentation), as important drivers and/or mediators of dietary intervention response, have to be taken into account. For the implementation of these approaches, more prospective trials are required to provide the knowledge base for precision nutrition in the prevention of chronic metabolic diseases.

Adiposity, hepatic steatosis, and metabolic health transitions in people with obesity: Influences of age and sex

BACKGROUND AND AIMS

Metabolically healthy (MHO) and unhealthy obesity (MUO) may be transient conditions. This study aimed to quantify and identify predictive factors of metabolic transitions in obesity, exploring influences of age and sex.

METHODS AND RESULTS

We retrospectively evaluated adults with obesity who underwent routine health evaluation. In a cross-sectional analysis of 12,118 individuals (80% male, age 44.3 ± 9.9 years), 16.8% had MHO. In a longitudinal evaluation of 4483 participants, 45.2% of individuals with MHO at baseline had dysmetabolism after a median follow-up of 3.0 (IQR 1.8-5.2) years, whereas 13.3% MUO participants became metabolically healthy (MH). Development of hepatic steatosis (HS, ultrasound) was an independent predictor of MHO conversion to dysmetabolism (OR 2.36; 95% CI 1.43, 3.91; p < 0.001), while HS persistence was inversely associated with transition from MUO to MH status (OR 0.63; 95% CI 0.47, 0.83; p = 0.001). Female sex and older age were associated with a lower chance of MUO regression. A 5% increment in body mass index (BMI) over time increased the likelihood of metabolic deterioration by 33% (p = 0.002) in females and 16% (p = 0.018) in males with MHO. A 5% reduction in BMI was associated with a 39% and 66% higher chance of MUO resolution in females and males, respectively (both p < 0.001).

CONCLUSION

The findings support a pathophysiological role of ectopic fat depots in metabolic transitions in obesity and identify female sex as an aggravating factor for adiposity-induced dysmetabolism, which has implications for personalized medicine.

Metabolically healthy transition and its association with body size change patterns among different adult age groups

OBJECTIVE

To explore the metabolically healthy (MH) to metabolically unhealthy (MU) transition and its association with body size change patterns according to age.

METHODS

In total, 12,910 MH subjects were evaluated in 2013 and reevaluated in 2020. A MH state was defined as a score ≤ 1, and a MU state was defined as a score > 1 on the National Cholesterol Education Program-Adult Treatment Panel III criteria.

RESULTS

Approximately 27.0% of MH individuals converted to MU status over the follow-up. Compared with young adults, middle adulthood individuals had a 1.33-fold (95% CI: 1.21-1.46) and late adulthood individuals had a 1.55-fold (95% CI: 1.41-1.70) risk of transition. The body mass index (BMI)/waist circumference (WC)-value change was positively associated with metabolic deterioration; the association weakened with age. With stable normal body size (defined by BMI) as a reference, changing phenotype categories of maximum overweight [hazard ratio (HR): 1.75; 95% CI: 1.56-1.95], non-obesity to general obesity (HR: 2.96; 95% CI: 2.47-3.54) and stable general obesity (HR: 2.44; 95% CI: 1.92-3.10) conferred a higher risk of metabolic deterioration.

CONCLUSIONS

MH status is a transient state, especially in late and middle adulthood. Individuals transitioning to an obese phenotype should receive attention for concomitant metabolic deterioration.

Association between non-alcoholic fatty liver disease and metabolically healthy deterioration across different body shape phenotypes at baseline and change patterns

Non-alcoholic fatty liver disease (NAFLD) is a hepatic manifestation of metabolic syndrome (MetS), and the relationship between NAFLD and metabolic deterioration remains unclear. This study aimed to investigate dynamic changes in metabolically healthy phenotypes and to assess the impact of non-alcoholic fatty liver disease (NAFLD) on the conversion from metabolically healthy (MH) to metabolically unhealthy (MU) phenotypes across body shape phenotypes and phenotypic change patterns. We defined body shape phenotypes using both the body mass index (BMI) and waist circumference (WC) and defined metabolic health as individuals scoring ≤ 1 on the NCEP-ATP III criteria, excluding WC. A total of 12,910 Chinese participants who were MH at baseline were enrolled in 2013 and followed-up in 2019 or 2020. During a median follow-up of 6.9 years, 27.0% (n = 3,486) of the MH individuals developed an MU phenotype. According to the multivariate Cox analyses, NAFLD was a significant predictor of conversion from the MH to MU phenotype, independent of potential confounders (HR: 1.12; 95% confidence interval: 1.02–1.22). For the MH-normal weight group, the relative risk of NAFLD in phenotypic conversion was 1.21 (95% CI 1.03–1.41, P = 0.017), which was relatively higher than that of MH-overweight/obesity group (HR: 1.14, 95% CI 1.02–1.26, P = 0.013). Interestingly, the effect of NAFLD at baseline on MH deterioration was stronger in the “lean” phenotype group than in the “non-lean” phenotype group at baseline and in the “fluctuating non-lean” phenotype change pattern group than in the “stable non-lean” phenotype change pattern group during follow-up. In conclusion, lean NAFLD is not as benign as currently considered and requires more attention during metabolic status screening.

Weight Change and the Development of Nonalcoholic Fatty Liver Disease in Metabolically Healthy Overweight Individuals

INTRODUCTION

The study sought to investigate the effect of weight change on hepatic steatosis (HS) incidence with or without liver fibrosis in metabolically healthy overweight or obese individuals.

METHODS

A cohort of 14,779 metabolically healthy men and women who were overweight or obese (body mass index ≥23 kg/m²) and free from HS and an intermediate or high probability of fibrosis at baseline were followed for a median of 5.2 years. Metabolic health was defined as freedom from the components of metabolic syndrome and a homeostatic model assessment of insulin resistance <2.5. Weight changes were calculated as differences from baseline at the next subsequent visit. The outcome was HS incidence, with or without liver fibrosis, as assessed by liver ultrasound and 2 noninvasive fibrosis scores.

RESULTS

During 76,794.6 person-years of follow-up, 3539 cases of HS incidence were identified. The multivariable adjusted hazard ratios (95% confidence intervals) for HS incidence by weight change group, <-5.0%, -5.0%-1.0%, 1.0%-5.0%, and >5.0%, relative to the no weight change group (-0.9% to 0.9%) were 0.52 (0.44-0.60), 0.83 (0.75-0.92), 1.21 (1.10-1.33), and 1.51 (1.36-1.69), respectively. Clinically relevant weight loss of >5% was also associated with a lowered risk of HS with intermediate or high probability of advanced fibrosis. In mediation analyses, associations remained significant, although adjustment for metabolic risk factors was attenuating.

DISCUSSION

Clinically relevant weight loss was associated with a reduced risk of developing nonalcoholic fatty liver disease with or without intermediate or high probability of advanced fibrosis in metabolically healthy overweight or obese individuals.

Metabolically healthy obesity: Is it really healthy for type 2 diabetes mellitus?

Metabolically healthy obese (MHO) individuals are reported to have a lower risk of developing cardiovascular diseases in comparison with individuals with metabolic syndrome. However, the association between MHO and type 2 diabetes (T2DM) is still controversial. Some studies indicated that MHO is a favorable phenotype for T2DM, but more studies showed that MHO individuals have an increased risk of developing T2DM compared with metabolically healthy normal-weight individuals, especially among those who would acquire metabolically unhealthy obesity. This has been supported by finding insulin resistance and low-grade inflammatory responses in MHO individuals with a tendency for impaired beta-cell dysfunction. Studies also showed that liver fat accumulation increased the risk of incidence of T2DM in MHO. Here, we reviewed current literature on the relationship between MHO and T2DM, discussed the determinants for the development of diabetes in MHO, and summarized the measures for the prevention of T2DM in MHO.

MRI-Derived Radiomics Features of Hepatic Fat Predict Metabolic States in Individuals without Cardiovascular Disease

RATIONALE AND OBJECTIVES

To investigate radiomics features of hepatic fat as potential biomarkers of type 2 diabetes mellitus (T2DM) and metabolic syndrome (MetS) in individuals without overt cardiovascular disease, and benchmarking against hepatic proton density fat fraction (PDFF) and the body mass index (BMI).

MATERIALS AND METHODS

This study collected liver radiomics features of 310 individuals that were part of a case-controlled imaging substudy embedded in a prospective cohort. Individuals had known T2DM (n = 39; 12.6 %) and MetS (n = 107; 34.5 %) status, and were divided into stratified training (n = 232; 75 %) and validation (n = 78; 25 %) sets. Six hundred eighty-four MRI radiomics features were extracted for each liver volume of interest (VOI) on T₁-weighted dual-echo Dixon relative fat water content (rfwc) maps. Test-retest and inter-rater variance was simulated by additionally extracting radiomics features using noise augmented rfwc maps and deformed volume of interests. One hundred and seventy-one features with test-retest reliability (ICC(1,1)) and inter-rater agreement (ICC(3,k)) of ≥0.85 on the training set were considered stable. To construct predictive random forest (RF) models, stable features were filtered using univariate RF analysis followed by sequential forward aggregation. The predictive performance was evaluated on the independent validation set with area under the curve of the receiver operating characteristic (AUROC) and balanced accuracy (Accuracy_B).

RESULTS

On the validation set, the radiomics RF models predicted T2DM with AUROC of 0.835 and Accuracy_B of 0.822 and MetS with AUROC of 0.838 and Accuracy_B of 0.787, outperforming the RF models trained on the benchmark parameters PDFF and BMI.

CONCLUSION

Hepatic radiomics features may serve as potential imaging biomarkers for T2DM and MetS.

Prediction of Metabolic Disorders Using NMR-Based Metabolomics: The Shanghai Changfeng Study

A metabolically healthy status, whether obese or not, is a transient stage with the potential to develop into metabolic disorders during the course of life. We investigated the incidence of metabolic disorders in 1078 metabolically healthy Chinese adults from the Shanghai Changfeng Study and looked for metabolites that discriminated the participants who would develop metabolic disorders in the future. Participants were divided into metabolically healthy overweight/obesity (MHO) and metabolically healthy normal weight (MHNW) groups according to their body mass index (BMI) and metabolic status. Their serum metabolomic profile was measured using a ¹H nuclear magnetic resonance spectrometer (¹H-NMR). The prevalence of diabetes, hypertriglyceridemia, hypercholesterolemia and metabolic syndrome was similar between the MHNW and MHO participants at baseline. After a median of 4.2 years of follow-up, more MHO participants became metabolically unhealthy than MHNW participants. However, a subgroup of MHO participants who remained metabolically healthy (MHO → MHO) had a similar prevalence of metabolic disorders as the MHNW participants at the follow-up examination, despite a significant reduction in their serum concentrations of high-density lipoprotein (HDL) and an elevation in valine, leucine, alanine and tyrosine. Further correlation analysis indicated that serum intermediate-density lipoprotein (IDL) and very low-density lipoprotein cholesterol (VLDL-CH) might be involved in the transition from metabolically healthy to unhealthy status and could be valuable to identify the MHNW and MHO with increased metabolic risks.

National digestive disease specialists survey on cardiovascular risk management in non-alcoholic fatty liver disease in spanish hospitals

BACKGROUND & AIMS

Cardiovascular disease (CVD) is the main cause of mortality among non-alcoholic fatty liver disease (NAFLD) patients. The aim was to explore the level of knowledge and clinical management of cardiovascular risk (CVR) in NAFLD patients by Digestive Disease specialists.

METHODS

An anonymous web-based survey was designed with 44 close-ended questions, divided into five sections, that were based on current guidelines on CVD prevention. Between November 2019 and January 2020, Digestive Disease specialists from Spanish hospitals were invited to participate in this survey via email and Twitter. Student's t, chi-square and Fishers' exact tests, and logistic regression were used for data analysis.

RESULTS

208 clinicians completed the survey. Most respondents (83.2%) believe that NAFLD is an independent risk factor for CVD, especially in the presence of NASH and fibrosis. Personal history of CVDs and cardiovascular risk-related comorbidities are collected by more than 75% of respondents. However, less than 17% perform an elementary physical examination to address the CVR, except weight which is evaluated by 69.8%. Over 54% of respondents do not perform or request any supplementary tests for CVR assessment, and only 10.2% use specific calculators. Furthermore, 54.3% spend less than 5 minutes giving lifestyle advice, and more than 52% do not start drug treatment after a recent diagnosis of any cardiovascular comorbidity. Only 25.6% have a multidisciplinary Unit for metabolic comorbidities in their hospitals, although 89% of the respondents would support the implementation of this Unit.

CONCLUSIONS

Cardiovascular risk management in daily clinical practice by Digestive Disease specialists in Spain remains suboptimal.

Metabolically healthy obesity is associated with longitudinal changes in high-density lipoprotein cholesterol in Chinese adults

PURPOSE

Whether metabolically healthy obesity (MHO) is associated with longitudinal changes in high-density lipoprotein cholesterol (HDL-C) remains unclear.

METHODS

MHO was defined as participants with overweight and obesity (BMI ≥ 24.0 kg/m², n = 2921), free of history of metabolic diseases, and without abnormalities of blood pressure, fasting blood glucose, hemoglobin A1c, lipid profile, carotid artery and liver ultrasonographic findings at baseline. Metabolically healthy normal weight (MHN) was defined as participants with normal weight (BMI < 24.0 kg/m², n = 9578) and without above-mentioned abnormalities. HDL-C, fasting blood glucose, hemoglobin A1c, and blood pressure were assessed annually. Glucose abnormality was considered if either FBG ≥ 5.6 mmol/L or HbA1c ≥ 5.7%; while, high blood pressure (HBP) was considered if either systolic blood pressure ≥ 130 mmHg or diastolic blood pressure ≥ 80 mmHg during 5 years of follow-up.

RESULTS

Compared with the MHN group, the adjusted mean difference in HDL-C change rate was - 0.005 mmol/L per year [95% confidence interval (CI) - 0.007, - 0.003] for MHO after adjustment for a series of potential confounders. Furthermore, transiting to abnormality of blood glucose, but not high blood pressure, was associated with lower cumulative average of HDL-C in MHN group, compared with those remained in metabolically healthy status.

CONCLUSIONS

MHO and transiting from metabolically healthy to abnormality of blood glucose were associated with HDL-C in Chinese adults.

LEVEL OF EVIDENCE

III, cohort study.

Short-Term Changes in Metabolically Healthy Overweight/Obesity Status Impact the Susceptibility to Type 2 Diabetes in Chinese Adults

PURPOSE

Changes in transition from metabolically healthy overweight/obesity (MHO) to metabolically unhealthy overweight/obesity (MUO) are associated with the risk for cardiometabolic complications. This study aims to investigate the effects of short-term dynamic changes in body mass index (BMI) and metabolic status on the risk of type 2 diabetes (T2D) and to identify biological predictors for the MHO-to-MUO transition.

PATIENTS AND METHODS

A total of 4604 subjects from the REACTION study were included for a 3-year follow-up. Subjects were categorized based on their BMI and metabolic syndrome status. Overweight/obesity was defined as BMI ≥ 24 kg/m². Metabolically healthy was defined as having two or fewer of the metabolic syndrome components proposed by the Chinese Diabetes Society. Thus, subjects were divided into four groups: metabolically healthy normal weight (MHNW), MHO, metabolically unhealthy normal weight (MUNW), and MUO.

RESULTS

Compared with MHNW, MHO was not predisposed to an increased risk for T2D (OR 1.08, 95% CI 0.64-1.83, P = 0.762). However, a 3-year transition probability of 20.6% was identified for subjects who shifted from MHO to MUO; this conversion increased the risk of T2D by 3-fold (OR 3.04, 95% CI 1.21-7.68, P = 0.018). The fatty liver index independently predicted the MHO-to-MUO transition with an OR 3.14 (95% CI 1.56-7.46, P = 0.002) when comparing the fourth quartile to the first quartile.

CONCLUSION

This study reveals that metabolic changes affect the short-term susceptibility to T2D in the overweight/obese Chinese population, and the fatty liver index is an efficient clinical parameter for identifying those with a metabolic deterioration risk.

Lipophagy Impairment Is Associated With Disease Progression in NAFLD

Non-alcoholic fatty liver disease (NAFLD) is the most common cause of chronic liver disease in Western countries and is associated with aging and features of metabolic syndrome. Lipotoxicity and oxidative stress are consequent to dysregulation of lipid metabolism and lipid accumulation, leading to hepatocyte injury and inflammation. Lipophagy consists in selective degradation of intracellular lipid droplets by lysosome and mounting evidence suggests that lipophagy is dysregulated in NAFLD. Here we demonstrate lipophagy impairment in experimental models of NAFLD and in a NAFLD patient cohort by histomorphological and molecular analysis. High fat diet-fed C57BL/6J male mice and high-fat/high-glucose cultured Huh7 cells showed accumulation of both p62/SQSTM1 and LC3-II protein. In 59 NAFLD patients, lipid droplet-loaded lysosomes/lipolysosomes and p62/SQSTM1 clusters correlated with NAFLD activity score (NAS) and with NAS and fibrosis stage, respectively, and levels of expression of lysosomal genes, as well as autophagy-related genes, correlated with NAS and fibrosis stage. An increased amount of lipid droplets, lipolysosomes and autophagosomes was found in subjects with NAFLD compared to healthy subjects at ultrastructural level. In conclusion, here we observed that NAFLD is characterized by histological, ultrastructural and molecular features of altered autophagy that is associated with an impaired lipid degradation. Impaired autophagy is associated with features of advanced disease. Lipopolysosomes, as individuated with light microscopy, should be further assessed as markers of disease severity in NAFLD patients.

Pathogenesis of non-alcoholic fatty liver disease and implications on cardiovascular outcomes in liver transplantation

Along with the obesity epidemic there has been a major increase in non-alcoholic fatty liver disease (NAFLD) prevalence, paralleling a steady increase in cirrhosis of the liver and hepatocellular cancer (HCC) related to NAFLD. Currently, NAFLD (related HCC and cirrhosis) is the second most common cause for liver transplantation (LT) and it is projected to take the top spot in the next 3-5 years. Patients with NAFLD cirrhosis and HCC have a unique set of comorbidities which potentially increases their risk for cardiovascular disease (CVD) and mortality. However, a review of the published data in NAFLD patients who undergo LT, does not paint a clear picture. While CVD is the most common cause of non-graft related mortality over the long-term, the short and intermediate-term survival post LT in NAFLD cirrhosis appears to be on par with other etiologies when age and comorbidities are factored. The cardiovascular complications are increased in the immediate post-transplant period but there is a shift from ischemic complications to arrhythmias and heart failure (HF). NAFLD recurs in 80-100% patients and occurs de novo in about 50% after LT, potentially impacting their long-term morbidity and mortality. This review summarizes the available data on CVD in NAFLD patients before and after LT, explains what is currently known about the epidemiology and pathogenesis of CVD in NAFLD and posits strategies to improve wait-list and post-transplant survival.

Epidemiology and pathophysiology of the association between NAFLD and metabolically healthy or metabolically unhealthy obesity

The prevalence of nonalcoholic fatty liver disease (NAFLD) is continuing to rise in many countries, paralleling the epidemic of obesity worldwide. In the last years, the concept of metabolically healthy obesity [MHO, generally defined as obesity without metabolic syndrome (MetS)] has raised considerable scientific interest. MHO is a complex phenotype with risks intermediate between metabolically healthy individuals with normal-weight (NWMH) and patients who are obese and metabolically unhealthy (MUO, i.e. obesity with MetS). In this review we aimed to examine the association and pathophysiological link of NAFLD with MHO and MUO. Compared to NWMH individuals, patients with obesity, regardless of the presence of MetS features, are at higher risk of all-cause mortality and cardiovascular events. Moreover, MHO patients have a greater risk of NAFLD development and progression compared to NWMH individuals. However, this risk is generally lower than that of MUO patients, suggesting a stronger adverse effect of coexisting MetS disorders than obesity per se on the severity of NAFLD. Nevertheless, since MHO is a dynamic state (with a significant proportion of MHO subjects progressing to MUO over time) and NAFLD itself may predict the transition from MHO to MUO, we believe that any effort should be made to identify NAFLD in all obese individuals, although they appear to be "metabolically healthy". Future research is needed to better understand the role of NAFLD and other pathogenic factors potentially involved in the transition from MHO to MUO and to elucidate how this transition may affect the presence and severity of NAFLD.

Metabolically healthy obesity: facts and fantasies

Although obesity is typically associated with metabolic dysfunction and cardiometabolic diseases, some people with obesity are protected from many of the adverse metabolic effects of excess body fat and are considered "metabolically healthy." However, there is no universally accepted definition of metabolically healthy obesity (MHO). Most studies define MHO as having either 0, 1, or 2 metabolic syndrome components, whereas many others define MHO using the homeostasis model assessment of insulin resistance (HOMA-IR). Therefore, numerous people reported as having MHO are not metabolically healthy, but simply have fewer metabolic abnormalities than those with metabolically unhealthy obesity (MUO). Nonetheless, a small subset of people with obesity have a normal HOMA-IR and no metabolic syndrome components. The mechanism(s) responsible for the divergent effects of obesity on metabolic health is not clear, but studies conducted in rodent models suggest that differences in adipose tissue biology in response to weight gain can cause or prevent systemic metabolic dysfunction. In this article, we review the definition, stability over time, and clinical outcomes of MHO, and discuss the potential factors that could explain differences in metabolic health in people with MHO and MUO - specifically, modifiable lifestyle factors and adipose tissue biology. Better understanding of the factors that distinguish people with MHO and MUO can produce new insights into mechanism(s) responsible for obesity-related metabolic dysfunction and disease.

The visceral adiposity index is a predictor of incident nonalcoholic fatty liver disease: A population-based longitudinal study

BACKGROUND AND AIMS

Visceral adiposity index (VAI), calculated with body mass index, high-density lipoprotein cholesterol, triglyceride and waist circumference, has been proposed as a marker of visceral fat accumulation and dysfunction.

METHODS

The impact of VAI on incident nonalcoholic fatty liver disease (NAFLD) in a historical cohort study of 8399 (3773 men and 4626 women) participants. NAFLD was defined as having fatty liver diagnosed by abdominal ultrasonography. We divided the participants into two groups according to sex and into quartiles according to VAI (Q1-4). We calculated VAI using the formulas. Men: VAI = [waist circumference (WC)/39.68 + (1.88 × body mass index [BMI])] × [triglycerides (TG)/1.03] × [1.31/high-density lipoprotein cholesterol (HDL)]; women: VAI = [WC/36.58 + (1.89 × BMI)] × (TG/0.81) × (1.52/HDL). We performed Cox proportional hazard models, adjusting for age, alanine aminotransferase, fasting plasma glucose, systolic blood pressure, alcohol consumption, smoking status and exercise.

RESULTS

During the median 4.5-year follow-up for men and 4.9-year follow-up for women, 1078 participants (737 men and 341 women) developed NAFLD. The 4000 days cumulative incidence rate of NAFLD for men and women were 7.5% and 2.2% in Q1, 14.5% and 4.0% in Q2, 22.3% and 6.7% in Q3 and 33.8% and 16.7% in Q4. The hazard ratios of incident NAFLD in Q4 (VAI: men, > 1.13; women, > 0.83) were 3.69 (95% confidence interval 2.84-4.86, P < 0.001) in men and 4.93 (3.28-7.73, P < 0.001) in women, compared to Q1 (VAI: men, < 0.44; women, < 0.36).

CONCLUSIONS

The visceral adiposity index can be a predictor of incident NAFLD.

Immune modulating effects of additional supplementation of estradiol combined with testosterone in murine testosterone-deficient NAFLD model

Nonalcoholic fatty liver disease (NAFLD) is associated with testosterone deficiency. However, NAFLD patients generally do not respond to treatment with testosterone alone. We investigated the innate immune mechanisms underlying the effects of treatment with testosterone alone, estrogen alone, or combined testosterone and estrogen on high-fat diet (HFD)-induced NAFLD due to testosterone deficiency. Orchiectomized (OCX) male Rag2^-/- mice were used as a model of testosterone deficiency. To assess NAFLD severity, NAFLD activity score (NAS) is adopted. Moreover, immunological change was analyzed by multicolor flow cytometry. Treatment with both testosterone and estrogen significantly decreased body weight to that of the sham mice/normal diet (ND). NAS and liver fibrosis in OCX-HFD mice were significantly deteriorated, and treatment with testosterone and estrogen improved same as sham-ND mice. HFD increased the ratio of both type 2 and 3 innate lymphoid cells (ILC2s and ILC3s) to CD45-positive cells in the liver. Treatment with testosterone alone decreased the ratio of ILC2 to CD45 but not the ILC3-to-CD45 ratio. Addition of estrogen to the treatment reduced the ratios of ILC2-to-CD45 and ILC3-to-CD45 to the same level observed in sham-HFD mice. Moreover, OCX-HFD mice had a decreased proportion of M2 macrophages compared with sham-ND mice. Treatment with testosterone alone did not restore the proportion of M2 macrophages; however, combination treatment with both estrogen and testosterone increased that to the same level as that in sham-HFD mice. Treatment with both testosterone and estrogen improves liver fibrosis and decreases ILC3 and increases M2 macrophage abundance in the liver.NEW & NOTEWORTHY The progression of nonalcoholic fatty liver disease (NAFLD) is associated with testosterone deficiency. NAFLD patients generally do not respond to treatment with testosterone alone. In animal studies, treatment with testosterone and estrogen reduced the ratios of ILC2:CD45 and ILC3:CD45 and increased M2 macrophages in liver. Our study suggests, based on our immunological data, that a combination of estrogen and testosterone may be clinically relevant for the treatment of NAFLD in patients with male menopause.

Association between body size-metabolic phenotype and nonalcoholic steatohepatitis and significant fibrosis

BACKGROUND AND AIMS

Body size-metabolic phenotype may help predict whether or not individuals with nonalcoholic fatty liver disease (NAFLD) develop advanced liver disease. We studied the association of body size-metabolic phenotype with nonalcoholic steatohepatitis (NASH) and significant fibrosis.

METHODS

Our cross-sectional study included 559 subjects (mean age of 53 years; women 51%) with biopsy-proven NAFLD. Clinical, genetic, and histological characteristic features of NAFLD were evaluated. The metabolically unhealthy phenotype was defined by the presence of two or more metabolic components, while body size was categorized based on body mass index: obese (≥ 25 kg/m²) or non-obese (< 25 kg/m²). Body size-metabolic phenotypes were divided into four study groups: (1) non-obese metabolic syndrome (MS)-, (2) non-obese MS+ , (3) obese MS-, and (4) obese MS+.

RESULTS

Obese MS- and non-obese MS+ groups demonstrated comparable levels of insulin resistance, adipose tissue insulin resistance indexes, and visceral adipose tissue (VAT) areas. The VAT area was significantly higher in the obese MS+ group versus obese MS- group. However, the VAT to subcutaneous adipose tissue (SAT) ratio was highest in the non-obese MS+ group. There was no difference in histology between the non-obese MS+, obese MS-, and obese MS+ groups. Multivariate analyses adjusted for age, sex, smoking status, PNPLA3, TM6SF2, and VAT/SAT areas demonstrated an independent and dose-dependent relationship between the body size-metabolic phenotype and NASH or significant fibrosis.

CONCLUSION

The non-obese MS+ group displayed similar degree of hepatic histological severity compared to their obese MS- counterparts. Metabolic milieu beyond obesity may play a pathogenic role in non-obese MS+ individuals who develop NASH with significant hepatic fibrosis.

CLINICAL TRIAL NUMBER

NCT02206841.

Creatinine-to-bodyweight ratio is a predictor of incident non-alcoholic fatty liver disease: A population-based longitudinal study

AIM

Serum creatinine (Cre) is used as a surrogate marker of muscle mass. We investigated the impact of the Cre-to-bodyweight (BW) ratio (Cre/BW) on incident non-alcoholic fatty liver disease (NAFLD).

METHODS

Fatty liver disease was diagnosed by abdominal ultrasonography. In this historical cohort study of 13 728 participants (6397 men and 7331 women), we divided the participants into two groups by sex and into quartiles according to Cre (mg/dL)/BW (kg; Q1-4). We carried out Cox proportional hazard models, adjusting for age, alanine aminotransferase, fasting plasma glucose, systolic blood pressure, alcohol consumption, smoking status, and exercise.

RESULTS

During the 5.1-year follow up for men and 6.0-year follow up for women, 2497 participants (1696 men, 801 women) developed NAFLD. The 4000-days cumulative incidence rates of FLD for men and women were 29.6% and 16.6% in Q1, 28.2% and 10.6% in Q2, 25.5% and 8.8% in Q3, and 22.7% and 7.7% in Q4, respectively. The hazard ratios of incident NAFLD in Q1 (Cre/BW [×100]: men <1.28; women <1.17) were 1.89 (95% confidence interval 1.64-2.17, P < 0.001) in men and 2.96 (2.42-3.62, P < 0.001) in women, compared with Q4 (Cre/BW [×100]: men ≥1.61; women ≥1.51).

CONCLUSIONS

A low Cre/BW is associated with an increased risk of NAFLD. Screening Cre/BW can be used to identify individuals who are at high risk of NAFLD.

Association of [1H]-MRS quantified liver fat content with glucose metabolism status

BACKGROUND

Previous literatures have implied that the liver fat deposition plays a crucial role in the development and progression of insulin resistance. In the present study, we aimed to investigate the association of liver fat content (LFC) with glucose metabolism status in the population of newly diagnosed type 2 diabetes mellitus (nT2DM), prediabetes mellitus (PDM) and normal controls (NC), and assessing if the LFC could as an indicator for the prediction of T2DM.

METHODS

A total of 242 subjects (including 141 nT2DM patients, 48 PDM subjects and 53 NC) were enrolled. The levels of LFC were quantified by using the proton magnetic resonance spectroscopy ([¹H]-MRS) technique. Clinical and laboratory parameters of study subjects were collected by medical records and biochemical detection. One-way ANOVA or nonparametric test (Kruskal-Wallis) was applied for intergroup comparisons; intergroup comparison was performed in using of Bonferroni multiple-significance-test correction.

RESULTS

There were significantly increased LFC levels in nT2DM (14.72% ± 6.37%) than in PDM (9.62% ± 4.41%) and that of NC groups (5.11% ± 3.66%) (all p < 0.001). The prevalence of nonalcoholic fatty liver disease (NAFLD) was also found to be increased in nT2DM (91.48%) than in PDM (85.41%) and that of NC (32.07%) groups. Correlation analysis revealed that the increase of LFC positively associated with fast plasma glucose (FPG), 2 h plasma glucose (PG), Delta G30 and homeostatic model assessment of insulin resistance (HOMA-IR), negatively associated with Delta Ins30, Delta C30, Ins30/G30 _AUC, CP30/G30 _AUC, Ins _AUC/G _AUC, CP _AUC/G _AUC, homeostatic model assessment for β-cell function index (HOMA-β) and matsuda insulin sensitivity index (Matsuda ISI). Multilinear regression analysis showed that LFC, body mass index (BMI) and diastolic blood pressure (DBP) contributed for the prediction of HOMA-IR, and total cholesterol (TC), age, waist circumference (WC) and low-density lipoprotein cholesterol (LDL-C) were the significant contributors for HOMA-β.

CONCLUSIONS

Our study revealed an increased LFC level and prevalence of NAFLD in nT2DM than in PDM and that of NC groups, the increase of LFC was closely associated with insulin resistance and impaired glucose metabolism status, may be regarded as potential indicator contributing to the development and progression of T2DM.

Clinic, Anthropometric And Metabolic Changes In Adults With Class III Obesity Classified As Metabolically Healthy And Metabolically Unhealthy

PURPOSE

To describe clinical, biochemical and anthropometric profiles in adults with class III obesity classified as metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUHO).

PATIENTS AND METHODS

This is a cross-sectional study with patients classified as MHO and MUHO according to the NCEP-ATP III. Anthropometric, biochemical and clinical variables were analyzed.

RESULTS

A total of 223 subjects were evaluated and 32.73% were classified as MHO and 67.26% as MUHO, respectively. The insulin resistance homeostasis model (HOMA-IR) showed elevation in the MUHO group (p=0.003) and anthropometric variables were correlated with bone markers [body index mass (BMI) vs phosphorus: r=0.31, p<0.001; BMI vs 25(OH)D: r=-0.31, p=0.041]. Visceral adiposity index was lower in MHO (p=0.001). Negative correlations between inflammatory markers and bone markers were observed in the MHO group (calcium vs C-reactive protein: -0.30, p=0.017; parathyroid hormone vs HOMA-IR: r=-0.28, p=0.017.

CONCLUSION

MHO individuals showed important metabolic changes, such as those observed in MUHO, despite lower prevalence and severity. Continuous monitoring of these individuals is suggested, given the transient nature of the MHO phenotype.

Nonalcoholic fatty liver disease is an early predictor of metabolic diseases in a metabolically healthy population

Aims

The relationship between nonalcoholic fatty liver disease and incident metabolic syndrome in metabolically healthy subjects is unknown. We aimed to investigate whether nonalcoholic fatty liver disease is a predictor of future metabolic syndrome in metabolically healthy subjects.

Materials and methods

Subjects who underwent health evaluation at least twice between 2009 and 2015 from the National Health Insurance Service-National Sample Cohort in South Korea were included. Patients without obesity who had no metabolic syndrome components were finally analyzed (n = 28,880). The definition of nonalcoholic fatty liver disease was based on both the hepatic steatosis and fatty liver indices. The incidence of metabolic syndrome, prediabetes/type 2 diabetes, hypertension, and dyslipidemia was compared between the subjects with and without nonalcoholic fatty liver disease.

Results

The presence of nonalcoholic fatty liver disease was associated with a higher risk of incident metabolic syndrome, prediabetes/type 2 diabetes, hypertension, and dyslipidemia in the entire cohort (metabolic syndrome: adjusted hazard ratio, 2.10; 95% confidence interval, 1.18–3.71; prediabetes/type 2 diabetes: adjusted hazard ratio, 1.42; 95% confidence interval, 1.06–1.90; hypertension: adjusted hazard ratio, 2.36; 95% confidence interval, 1.35–4.12; dyslipidemia: adjusted hazard ratio, 1.49; 95% confidence interval, 1.07–2.06). A similar finding was observed in the age-, sex-, smoking status-, and body mass index-based 1:5 propensity score-matched cohort of 1,092 subjects (metabolic syndrome: adjusted hazard ratio, 3.56; 95% confidence interval, 1.79–7.07; prediabetes/type 2 diabetes: adjusted hazard ratio, 1.97; 95% confidence interval, 1.04–3.73; hypertension: adjusted hazard ratio, 2.57; 95% confidence interval, 1.35–4.88; dyslipidemia: adjusted hazard ratio, 1.61; 95% confidence interval, 1.12–2.32).

Conclusions

Nonalcoholic fatty liver disease is an early predictor of metabolic dysfunction even in metabolically healthy populations.

Association Between Nonalcoholic Fatty Liver Disease and Future Deterioration of Metabolic Health: A Cohort Study

OBJECTIVE

It was hypothesized that the presence of nonalcoholic fatty liver disease (NAFLD) at baseline predicts future conversion from the metabolically healthy (MH) to the metabolically unhealthy (MU) phenotype according to body fat mass.

METHODS

A total of 22,551 Korean participants (13,601 men and 8,950 women) aged 18 to 78 years in the Kangbuk Samsung Health Study cohort were enrolled from 2007 to 2013.

RESULTS

During a median of 5.1 years of follow-up (interquartile range 2.1-9.8 years), 23.5% (n = 5,298) of MH individuals converted to the MU phenotype. NAFLD at baseline predicted conversion independent of age, sex, BMI, lifestyle factors, individual components of metabolic syndrome, and insulin resistance (HR, 1.29; 95% CI: 1.19-1.39; P < 0.0001). In participants with lower BMI and fat mass, NAFLD was strongly associated with conversion; however, as BMI and fat mass increased, the risk decreased, and there was no association in participants with higher BMI and fat mass (P < 0.0001 for trend).

CONCLUSIONS

NAFLD at baseline was independently associated with future conversion from the MH to the MU phenotype.

Fasting triglycerides and glucose index is more suitable for the identification of metabolically unhealthy individuals in the Chinese adult population: A nationwide study

AIMS/INTRODUCTION

Metabolic unhealth can be defined by the components of metabolic syndrome, which is closely connected to insulin resistance. We aimed to determine a simple index to identify metabolic unhealth in the Chinese adult population.

MATERIALS AND METHODS

A total of 30,291 individuals were screened from the China National Diabetes and Metabolic Disorders Study carried out from June 2007 to May 2008. Metabolic unhealth was defined using components of metabolic syndrome, except waist circumference. We compared the three surrogate indices of insulin resistance: the product of fasting triglycerides and glucose (TyG), triglycerides divided by high-density lipoprotein cholesterol and the metabolic score for insulin resistance for the evaluation of metabolic status.

RESULTS

All indices had high sensitivity and specificity for the identification of metabolic unhealth, especially the TyG index with an area under the curve of 0.863 for men and 0.867 for women. Participants were divided into subgroups for further analysis. The TyG index also showed high diagnostic values, especially for younger individuals and men with normal waist circumference. Sex-specific cut-offs for three indices were also used to define metabolic unhealth. The TyG index showed the highest agreement with κ values of 0.603 and 0.605 for men and women between the components of metabolic syndrome and three indices.

CONCLUSIONS

We propose that the TyG index, just read in one blood laboratory test report, is simpler and more suitable for the identification of metabolically unhealthy individuals as well as who have high risk of cardiometabolic diseases of the Chinese adult population.

Obesity genetics and cardiometabolic health: Potential for risk prediction

The increasing burden of obesity worldwide and its effect on cardiovascular disease (CVD) risk is an opportunity for evaluation of preventive approaches. Both obesity and CVD have a genetic background and polymorphisms within genes which enhance expression of variant proteins that influence CVD in obesity. Genome-based prediction may therefore be a feasible strategy, but the identification of genetically driven risk factors for CVD manifesting as clinically recognized phenotypes is a major challenge. Clusters of such risk factors include hyperglycaemia, hypertension, ectopic liver fat, and inflammation. All involve multiple genetic pathways having complex interactions with variable environmental influences. The factors that make significant contributions to CVD risk include altered carbohydrate homeostasis, ectopic deposition of fat in muscle and liver, and inflammation, with contributions from the gut microbiome. A futuristic model depends on harnessing the predictive power of plausible genetic variants, phenotype reversibility, and effective therapeutic choices based on genotype-phenotype interactions. Inverting disease phenotypes into ideal cardiovascular health metrics could improve genetic and epigenetic assessment, and form the basis of a future model for risk detection and early intervention.

Low urine pH is a risk for non-alcoholic fatty liver disease: A population-based longitudinal study

BACKGROUND

Low urine pH has a close association with insulin resistance. This study was aimed to investigate the association between urine pH and incident non-alcoholic fatty liver disease (NAFLD), which is associated with insulin resistance.

SUBJECTS AND METHODS

In this historical cohort study of 11,012 participants (5503 men and 5509 women), we investigated the effect of urine pH on incident NAFLD. NAFLD was defined as having fatty liver diagnosed by abdominal ultrasonography and excluding the participants consumed ethanol over 60g/day for men and 40g/day for women. We divided the participants into three groups according to urine pH; the lowest group (urine pH≤5.5), the middle group (urine pH=6.0) and the highest group (urine pH≥6.5). Cox proportional hazards models was performed to investigate the effect of urine pH on incident NAFLD, adjusting for age, sex, body mass index, smoking, exercise, alcohol consumption, alanine aminotransferase, triglycerides, systolic blood pressure, uric acid and fasting plasma glucose.

RESULTS

Over the median 6.8-year follow-up duration, 2023 participants developed NAFLD, and the crude proportions were 20.3% (case/N=1104/5447) in the lowest urine pH group, 16.3% (487/2989) in the middle urine pH group and 16.8% (432/2576) in the highest urine pH group. The lowest urine pH group showed a significantly higher risk for incident NAFLD than the highest urine pH group (adjusted hazard ratio 1.48, 95% confidence interval 1.31-1.66, P<0.001).

CONCLUSION

Low urine pH is associated with incident NAFLD. Our findings indicate that urine pH can be an additional data when considering further diagnostic investigation for NAFLD in patients who have other risk factors.

Impact of respiratory function on the progression from metabolically healthy non-overweight to metabolically abnormal phenotype

BACKGROUND AND AIMS

Recent studies identified that metabolically abnormal non-overweight phenotype is a risk factor for cardiovascular diseases. However, only little is known about risk factors for the progression from metabolically healthy non-overweight (MHNO) to metabolically abnormal phenotype. In this study, we investigated the impact of respiratory function on the progression from MHNO to metabolically abnormal phenotype.

METHODS AND RESULTS

In this retrospective cohort study, 8949 (3872 men and 5077 women) individuals with MHNO, who participated in a health-checkup program from 2004 to 2015, were enrolled. Four metabolic factors (high-normal blood pressure or hypertension, impaired fasting glucose or diabetes, hypertriglyceridemia, and low HDL cholesterol concentration) were used to define metabolically healthy (less than two factors) or metabolically abnormal (two or more factors) phenotypes. Respiratory function was measured by spirometry. Over a median 4.0 years of follow-up, 927 participants progressed to metabolically abnormal phenotype. The percentage of FVC for predicted values (HR 0.98, 95% CI 0.93-1.03, p = 0.418) was not associated with the progression to metabolically abnormal phenotype after adjusting for covariates, including age, sex, alcohol consumption, exercise, smoking status, and body mass index, whereas the percentage of FEV₁ for predicted values (%FEV₁) (HR 0.87, 95% CI 0.84-0.91, p < 0.001) and the FEV₁/FVC ratio (HR 0.86, 95% CI 0.78-0.95, p = 0.004) were associated with the progression to metabolically abnormal phenotype.

CONCLUSION

Decrease in respiratory function in terms of %FEV₁ and the FEV₁/FVC ratio is associated with the progression to metabolically abnormal phenotype in individuals with MHNO.

Metabolically healthy obesity and risk of leukoaraiosis; a population based cross-sectional study

Metabolically healthy obese (MHO) individual is known to be defended from the metabolic complications of obesity. Leukoaraiosis, which is commonly detected on brain magnetic resonance imaging (MRI), is now recognized as a risk of stroke, dementia and death. However, the association between MHO and the prevalence of leukoaraiosis is unclear. In this cross-sectional study of 796 participants who received a medical examination program, we investigated the association between MHO and the prevalence of leukoaraiosis. We used common clinical markers for definition of metabolic healthy status: blood pressure, fasting plasma glucose, triglycerides and high-density lipoprotein cholesterol concentrations. Obesity was defined by body mass index ≥25.0 kg/m². We diagnosed leukoaraiosis by fluid-attenuated inversion recovery without hypointensity on T1-weighted images or the presence of a hyperintensity on T2-weighted images. The crude prevalence proportion of leukoaraiosis was 44.5% (case/n = 171/384) in metabolically healthy nonobese (MHNO) individual, 46.3% (44/95) in MHO individual, 62.3% (114/183) in metabolically unhealthy nonobese (MUNO) individual or 56.6% (77/136) in MUO individual. The odds ratios of prevalence of leukoaraiosis were 1.19 (95% CI 0.74-1.90, p = 0.471) for MHO, 1.79 (1.22-2.62, p = 0.003) for MUNO and 1.56 (1.03-2.37, p = 0.037) for MUO individuals after adjusting for sex, age, smoking statues, habit of exercise and alcohol, compared with MHNO individual. We revealed that MHO individuals were not related with the higher risk of leukoaraiosis, whereas MUNO and MUO individuals were.

Intake of Carbohydrate to Fiber Ratio Is a Useful Marker for Metabolic Syndrome in Patients with Type 2 Diabetes: A Cross-Sectional Study

BACKGROUND/AIMS

The effect of low carbohydrate diet on human health is still controversial. Whole grain, which is carbohydrate rich in fiber, has protective effects on human health. Thus, we assumed that intake of carbohydrate to fiber ratio has an important role in human health.

METHODS

This is a post-hoc analysis of a cross-sectional study of 164 patients with type 2 diabetes. Habitual food and nutrient intake were assessed and estimated by a self-administered diet history questionnaire. Intake of carbohydrate to fiber ratio was defined as carbohydrate (g)/fiber intake (g). Logistic regression analyses were performed to reveal the association between intake of carbohydrate to fiber ratio and metabolic syndrome (MetS).

RESULTS

Intake of carbohydrate to fiber ratio has closely associated with metabolic parameters, including triglycerides (r = 0.21, p = 0.007) and high-density lipoprotein cholesterol (r = -0.23, p = 0.003). Intake of carbohydrate to fiber ratio was associated with MetS (OR 1.06 [95% CI 1.00-1.13], p = 0.047) after adjusting for covariates, whereas carbohydrate intake (1.00 [0.99-1.01], p = 0.752) or carbohydrate energy/total energy (1.00 [0.94-1.07], p = 0.962) was not associated with MetS.

CONCLUSIONS

Intake of carbohydrate to fiber ratio was associated with MetS, whereas carbohydrate intake was not.

Late-night-dinner is associated with poor glycemic control in people with type 2 diabetes: The KAMOGAWA-DM cohort study

Skipping breakfast or irregular breakfast is associated with poor glycemic control. However, a relationship between the timing of dinner and glycemic control in people with type 2 diabetes remains indefinite. Therefore, we investigated the relationship between late-night-dinner and glycemic control in people with type 2 diabetes. We performed questionnaire survey for lifestyle factors in this cross-sectional study. We defined having dinner later than eight pm as late-night-dinner. We examined the differences in clinical and metabolic parameters between those who have late-night-dinner and those who do not have. We also examined the relationship between late-night-dinner and HbA1c, using multiple regression analysis. Ninety-five people (23.2%) had a late-night-dinner, among 409 people with type 2 diabetes. Metabolic parameters (mean (SD) or median (interquartile range)) of people with late-night-dinner were worse than those of without, including body mass index (BMI) (24.4 (4.0) vs. 23.2 (3.4) kg/m², p = 0.006), triglycerides (1.5 (1.1-2.1) vs. 1.2 (0.8-1.7) mmol/L, p < 0.001), HDL-cholesterol (1.4 (0.4) vs. 1.6 (0.4) mmol/L, p = 0.004) and hemoglobin A1c (58.1 (13.3) vs. 55.2 (10.2) mmol/mol, (7.5 (1.2) vs. 7.2 (0.9) %), p = 0.023)). Late-night-dinner (standardized regression coefficient = 0.13, p = 0.028) was associated with hemoglobin A1c after adjusting for age, BMI, sex, duration of diabetes, smoking, exercise, alcohol, snacking after dinner, nighttime sleep duration, time from dinner to bedtime, skipping breakfast, and medication for diabetes. Late-night-dinner is independently associated with poor glycemic control in people with type 2 diabetes.

The role of NAFLD in cardiometabolic disease: an update

Non-alcoholic fatty liver disease (NAFLD) is the most common cause of chronic liver disease in the world, yet the complex pathogenesis remains to be fully elucidated. The prevalence of NAFLD has risen precipitously in recent years and is now a leading indication for liver transplantation. New waitlist registrants with non-alcoholic steatohepatitis–induced cirrhosis increased by 170% from 2004 to 2013. In addition, patients with NAFLD are at increased risk of both cardiovascular disease and type II diabetes. In this update, recent studies contributing to the understanding of the place of NAFLD in cardiometabolic disease will be discussed.

Hypertension, diabetes, atherosclerosis and NASH: Cause or consequence?

Non-alcoholic fatty liver disease (NAFLD) has become one of the most common forms of chronic liver disease worldwide and its prevalence is expected to continue rising. NAFLD has traditionally been considered a consequence of metabolic syndrome (MetS). However, the link between NAFLD and MetS components, especially type 2 diabetes mellitus (T2DM), hypertension (HTN), and cardiovascular disease (CVD) is more complex than previously thought. Indeed, the adverse effects of NAFLD extend far beyond the liver, with a large body of clinical evidence now suggesting that NAFLD may precede and/or promote the development of T2DM, HTN and atherosclerosis/CVD. The risk of developing these cardiometabolic diseases parallels the underlying severity of NAFLD. Accumulating evidence suggests that the presence and severity of NAFLD is associated with an increased risk of incident T2DM and HTN. Moreover, long-term prospective studies indicate that the presence and severity of NAFLD independently predicts fatal and nonfatal CVD events. In this review, we critically discuss the rapidly expanding body of clinical evidence that supports the existence of a bi-directional relationship between NAFLD and various components of MetS, particularly T2DM and HTN, as well as the current knowledge regarding a strong association between NAFLD and CVD morbidity and mortality. Finally, we discuss the most updated putative biological mechanisms through which NAFLD may contribute to the development of HTN, T2DM and CVD.

Metabolically healthy obesity without fatty liver and risk of incident type 2 diabetes: A meta-analysis of prospective cohort studies

OBJECTIVE

A meta-analysis indicated that metabolically healthy obesity (MHO) presents a risk of incident type 2 diabetes, but it has not yet been established whether MHO without fatty liver (w/o FL) also presents a risk of incident diabetes.

METHODS

plus the presence of non or one of the following factors: hypertension, impaired fasting glucose, low high-density lipoprotein cholesterol, and hypertriglyceridemia. Using a random effects model, we calculated the pooled relative risks (RRs) and 95% confidence intervals (CIs) of incident diabetes.

RESULTS

Our meta-analysis included three studies from the databases plus the NAGALA study, with a total of 134,667 subjects, including 8675 MHO subjects w/o FL and 7218 MHO subjects with fatty liver (wFL). Compared to the metabolically healthy non-overweight subjects w/o FL, the RRs of incident diabetes in the MHO w/o FL and MHO wFL groups were 1.42 (95%CI 1.11-1.77) and 3.28 (95%CI 2.30-4.67).

CONCLUSIONS

Our meta-analysis results demonstrate that the MHO phenotype, with or without fatty liver, presents a risk of the development of type 2 diabetes. Individuals with MHO who do not have fatty liver should be monitored carefully - similarly to those with fatty liver - for the development of diabetes.

Prevention of Tamoxifen-related Nonalcoholic Fatty Liver Disease in Breast Cancer Patients

BACKGROUND

Tamoxifen is commonly used to prevent breast cancer recurrence. Studies have confirmed the association between tamoxifen and nonalcoholic fatty liver disease (NAFLD), with the results indicating the need for aggressive management of this side effect. We assessed the potential risk factors for and identified the possible protective factors of tamoxifen-related fatty liver.

MATERIALS AND METHODS

We enrolled patients with a history of breast cancer, aged 20 to 70 years, who had received with tamoxifen treatment within the past 5 years. We obtained the initial data and performed a follow-up blood test and ultrasound examination to compare the differences before and after tamoxifen treatment. The patients were divided into relatively normal and fatty liver groups.

RESULTS

Of the 266 enrolled tamoxifen-treated patients, 143 (53.8%) and 123 (46.2%) were in the relatively normal and fatty liver groups, respectively. The initial body weight (57.6 ± 9.3 kg vs. 60.9 ± 10.3 kg; P = .006) and body mass index (BMI; 23.4 ± 3.8 kg/m² vs. 25.0 ± 4.2 kg/m²; P < .001) were lower in the relatively normal group. An initial BMI of ≥ 22 kg/m² was a potential risk factor for tamoxifen-related NAFLD (hazard ratio [HR], 1.58; 95% confidence interval [CI], 1.00-2.48; P = .048). In contrast, a weekly exercise duration of ≥ 150 minutes reduced the risk (HR, 0.47; 95% CI, 0.31-0.69; P < .001).

CONCLUSION

The results from our study suggest that a BMI of ≥ 22 kg/m² is a potential risk factor for tamoxifen-related fatty liver and exercise is a possible protective factor.