Combined effect of body mass index and metabolic status on the risk of prevalent and incident chronic kidney disease: a systematic review and meta-analysis

The interplay between excess weight and hyper-glycemia on NCDs in Italy: results from a cross-sectional study

PURPOSE

To evaluate the prevalence of chronic comorbidities according to BMI classes and assess the interplay between excess body weight and blood glucose abnormalities in increasing the risk of major chronic diseases.

METHODS

The study is based on data from the Health Search/IQVIA Health LPD Longitudinal Patient Database, an Italian general practice registry, with data obtained from electronic clinical records of 800 general practitioners throughout Italy. Data relative to the year 2018 were analyzed. The study population was classified according to BMI (normal weight, overweight, and obesity classes 1, 2 and 3) and glucose metabolism status (normoglycemia-NGT; impaired fasting glucose-IFG; diabetes mellitus-DM). Comorbidities were identified through ICD-9 CM codes.

RESULTS

Data relative to 991,917 adults were analyzed. The prevalence of overweight was 39.4%, while the prevalence of obesity was 11.1% (class 1: 7.9%, class 2: 2.3%, class 3: 0.9%). In the whole population, the prevalence of DM and IFG was 8.9% and 4.2%, respectively. Both overweight and obesity were associated with an increasing prevalence of glucose metabolism alterations and a large array of different chronic conditions, including cardio-cerebrovascular diseases, heart failure, chronic kidney disease, osteoarticular diseases, depression, sleep apnea, and neoplasms of the gastrointestinal tract. Within each BMI class, the presence of IFG, and to a greater extent DM, identified subgroups of individuals with a marked increase in the risk of concomitant chronic conditions.

CONCLUSION

Addressing the double burden of excess weight and hyperglycemia represents an important challenge and a healthcare priority.

Identification of risk factors and development of a predictive model for chronic kidney disease in patients with obesity: a four-year cohort study

OBJECTIVE

The sneaky onset and dismal prognosis of chronic kidney disease (CKD) make it an important public health issue. Obesity-related kidney illness has garnered more attention in recent times. Establishing and validating a risk prediction model for chronic renal illness in overweight or obese adults was the goal of this investigation.

METHODS

Data from the China Health and Retirement Longitudinal Study were used for analysis. The definition of CKD was reduced renal function (eGFR < 60 mL/min/1.73 m²), while overweight and obesity were characterized through a body mass index exceeding 24 kg/m². The dataset was divided into derivation and validation cohorts using a 7:3 ratio. With respect to the derivation cohort, we constructed a prediction model using LASSO analysis and multivariate logistic regression. The model's performance was evaluated using Hosmer-Lemeshow tests, calibration curves, decision curve analysis, and receiver operating characteristic (ROC) curves. The validation cohort's model was subjected to additional assessment.

RESULTS

The study was based on survey data from 2011 to 2015 and comprised 3246 individuals who were overweight or obese, with 2274 being part of the derivation cohort and 972 being part of the validation cohort. The research constructed a prediction model that included age, sex, fasting blood glucose, glycated hemoglobin, triglyceride, hypertension, and BMI. The validation cohort's area under the ROC curve was 0.812 (95% CI = 0.763, 0.859) while the derivation cohort's was 0.789 (95% CI = 0.754, 0.831). Hosmer-Lemeshow tests were utilized to evaluate the model's accuracy in the validation and derivation cohorts (P = 0.681 and 0.547, respectively). The calibration curve showed a high level of consistency between the actual observations and the projected outcomes. According to decision curve analysis, the model offered significant net advantages.

CONCLUSIONS

The forecasting model established in this research has predictive value for CKD in patients with overweight or obesity. These findings could help doctors conduct early detection and intervention in clinical practice and further improve patient prognosis.

Metabolic health status and renal disorders: a cross-sectional study

Previous surveys suggests that body mass index (BMI) may be positively related to development of chronic kidney disease (CKD). However, this association might be altered by metabolic syndrome. Therefore, we aimed to evaluate the association of metabolic health status with CKD. The present cross-sectional study was carried out on 3322 representative sample of Iranian adults. Metabolic syndrome was identified based on the National Cholesterol Education Program (NCEP) Adult Treatment Panel III (ATP III) and BMI was assessed by anthropometric measurements. Estimated glomerular filtration rate (eGFR) was calculated by modification of diet in renal disease-Chronic Kidney Disease Epidemiology Collaboration (MDRD-EPI) formula. Subjects were categorized into four phenotypes: metabolically healthy normal weight (MHNW), metabolically healthy overweight and obesity (MHO), metabolically unhealthy normal weight (MUHNW), and metabolically unhealthy overweight and obesity (MUHO). Based on multivariate-adjusted models, the risk of CKD was significantly higher in MUHO compared with MHNW (OR: 1.48; p < 0.05). Although MUHNW and MUHO were associated with lower eGFR and albuminuria, the significant association was not observed in case of hematuria. Furthermore, subjects with kidney stones tended to be in MHO (OR: 1.42; p < 0.05) and MUHO phenotypes (OR: 1.64; p < 0.05), in comparison to the MHNW phenotype. The odds of kidney disorders were higher in adults with metabolic syndrome, regardless of BMI. However, this relationship might be strengthened by the concomitance of metabolic syndrome and obesity. To verify our findings, clarify the causality, and elucidate the underlying mechanisms, further research are warranted.

Metabolic phenotyping of BMI to characterize cardiometabolic risk: evidence from large population-based cohorts

Obesity is a risk factor for type 2 diabetes and cardiovascular disease. However, a substantial proportion of patients with these conditions have a seemingly normal body mass index (BMI). Conversely, not all obese individuals present with metabolic disorders giving rise to the concept of "metabolically healthy obese". We use lipidomic-based models for BMI to calculate a metabolic BMI score (mBMI) as a measure of metabolic dysregulation associated with obesity. Using the difference between mBMI and BMI (mBMIΔ), we identify individuals with a similar BMI but differing in their metabolic health and disease risk profiles. Exercise and diet associate with mBMIΔ suggesting the ability to modify mBMI with lifestyle intervention. Our findings show that, the mBMI score captures information on metabolic dysregulation that is independent of the measured BMI and so provides an opportunity to assess metabolic health to identify "at risk" individuals for targeted intervention and monitoring.

Obesity and Chronic Kidney Disease A Current Review

Background

Obesity poses significant challenges to healthcare globally, particularly through its bi-directional relationship with co-morbid metabolic conditions such as type 2 diabetes and hypertension. There is also emerging evidence of an association between obesity and chronic kidney disease (CKD) which is less well characterized.

Methods

A literature search of electronic libraries was conducted to identify and present a narrative review of the interplay between obesity and CKD.

Findings

Obesity may predispose to CKD directly as it is linked to the histopathological finding of obesity-related glomerulopathy and indirectly through its widely recognized complications such as atherosclerosis, hypertension, and type 2 diabetes. The biochemical and endocrine products of adipose tissue contribute to pathophysiological processes such as inflammation, oxidative stress, endothelial dysfunction, and proteinuria. The prevention and management of obesity may prove critical in counteracting both the development and advancement of CKD. Moreover, measures of abdominal adiposity such as waist circumference, are generally associated with worse morbidity and mortality in individuals receiving maintenance hemodialysis.

Conclusion

Obesity is a risk factor for the onset and progression of CKD and should be recognized as a potential target for a preventative public health approach to reduce CKD rates within the general population. Future research should focus on the use of glucagon-like peptide-1 receptor agonists and sodium-glucose cotransporter 2 inhibitors in patients with CKD and obesity due to their multi-faceted actions on major outcomes.

Relationships Between Metabolic Body Composition Status and Rapid Kidney Function Decline in a Community-Based Population: A Prospective Observational Study

Obesity and metabolic syndrome are strong risk factors for incident chronic kidney disease (CKD). However, the predictive accuracy of metabolic body composition status (MBCS), which combines the status of obesity and metabolic syndrome, for rapid kidney function decline (RKFD) is unclear. The aim of this study was to investigate the relationship between MBCS and RKFD in a healthy population in a prospective community-based cohort study. In the current study, we followed changes in renal function in 731 people residing in northern Taiwan for 5 years. The participants were divided into four groups according to their MBCS, including metabolically healthy normal weight (MHNW), metabolically healthy overweight (MHOW), metabolically unhealthy normal weight (MUNW), and metabolically unhealthy overweight (MUOW). We evaluated traditional risk factors for CKD and metabolic profiles. The primary outcome was RKFD, which was defined as a 15% decline in estimated glomerular filtration rate (eGFR) within the first 4 years, and a reduction in eGFR which did not improve in the 5th year. During the study period, a total of 731 participants were enrolled. The incidence of RKFD was 17.1% (125/731). Multiple Cox logistic regression hazard analysis revealed that age, cerebrovascular accident, eGFR, urine albumin-to-creatinine ratio, use of painkillers, depressive mood, MUNW and MUOW were independent predictors of RKFD. After adjusting for age, sex, eGFR and total cholesterol, the participants with MUNW and MUOW had higher hazard ratios (HRs) for RKFD [HR: 2.19, 95% confidence interval (CI): 1.22–3.95 for MUNW; HR: 1.86, 95% CI: 1.21–2.87 for MUOW] than those with MHNW. Similar results were also observed in subgroup analysis of those aged above 65 years. On the basis of the results of this study, we conclude that MBCS was independently associated with RKFD, especially in the older adults. On the basis of our results, we suggest that MUNW and MUOW should be considered as risk factors for RKFD.

Prevalence of chronic kidney disease stages 3-5 in low- and middle-income countries in Asia: A systematic review and meta-analysis

Chronic kidney disease (CKD) is a major public health problem in low- and middle-income countries (LMICs). Although CKD prevalence has been rapidly increasing in LMICs, particularly in Asia, quantitative studies on the current epidemiology of CKD in this region are limited. This study aimed to identify the prevalence of CKD stages 3-5 in LMICs in Asia, by subregion, country economy classification, identification of CKD, traditional and non-traditional risk factors. A systematic review and meta-analysis of observational studies was conducted through a literature search of seven electronic databases and grey literature search published until November 2021. The Newcastle-Ottawa quality assessment scale (NOS) was used to assess the risk of bias of each study. A random-effects model was used to estimate pooled prevalence. The protocol is registered in the International Prospective Register of Systematic Reviews (PROSPERO CRD42019120519). Of 4,548 potentially relevant records, 110 studies with moderate and high quality were included with 4,760,147 subjects. The average prevalence (95% CI) of CKD stages 3-5 in 14 LMICs in Asia was 11.2% (9.3-13.2%). The prevalence of CKD stages 3-5 was varied among subregions and country economic classification. CKD prevalence was 8.6% (7.2-10.2%) in east Asia, 12.0% (7.7-17.0%) in south-east Asia, 13.1% (8.7-18.2%) in western Asia, and 13.5% (9.5-18.0%) in south Asia. CKD prevalence was 9.8% (8.3-11.5%) in upper-middle-income countries and 13.8% (9.9-18.3%) in lower-middle-income countries. Prevalence of CKD stage 3-5 in LMICs in Asia is comparable to global prevalence. High level of heterogeneity was observed. Study of factors and interventions that lead to the delay of CKD progression is needed.

Effects of Body Weight Change on Development of Chronic Kidney Disease in Obese Metabolic Phenotypes

Introduction

Obesity is a risk factor for chronic kidney disease (CKD), but whether the reduction of body mass index (BMI) helps prevent CKD is controversial. Recently, obese metabolic phenotypes have raised considerable interest. We thus investigated the effect of BMI change on CKD development.

Methods

We analyzed the data of 6,959 subjects who underwent annual health checkups in both 2013 and 2018. The subjects were categorized into five groups according to their BMI percentage change (ΔBMI) and classified into four obese metabolic phenotypes. By a multivariate logistic regression analysis, we investigated the association between BMI change and CKD development within the 5 years.

Results

In total subjects, compared with the maintained BMI group (ΔBMI ≥0% but <2.5%), the odd ratios (ORs) and 95% confidence intervals (CIs) of CKD development were 0.70 (95% CI 0.54–0.91) for the severe BMI decrease group (ΔBMI <−2.5%), and 1.40 (95% CI 1.08–1.81) for the severe BMI increase group (ΔBMI ≥5%). In the metabolically healthy obese (MHO) phenotype, the risks of CKD development were significantly higher in the moderate BMI increase group (ΔBMI ≥2.5% but <5%) (OR 3.04, 95% CI 1.19–7.78) and a severe BMI increase group (OR 2.88, 95% CI 1.13–7.35). Regarding the metabolically unhealthy nonobese (MUNO) phenotype, the risks of CKD development were significantly lower in the severe BMI decrease group (OR 0.43, 95% CI 0.25–0.74) and the moderate BMI decrease group (ΔBMI ≥−2.5% but <0%) (OR 0.58, 95% CI 0.35–0.98).

Conclusions

In the MHO phenotype, an increased BMI deteriorated CKD development, and a decreased BMI ameliorated CKD development in the MUNO phenotype.

Metabolic associated fatty liver disease is a risk factor for chronic kidney disease

Background and Aims

To clarify the relationship between metabolic dysfunction‐associated fatty liver disease (MAFLD) and chronic kidney disease (CKD).

Methods

The participants were divided into four groups by the presence or absence of fatty liver disease (FLD) and metabolic dysfunction (MD). MAFLD was defined as having both FLD and MD, whereas CKD was defined as having an estimated glomerular filtration rate of <60 mL/min/1.73 m² and/or proteinuria.

Results

In this cross‐sectional study of 27,371 participants, the proportions of those in the non‐FLD without MD, non‐FLD with MD, FLD without MD, and MAFLD groups were 48.7, 28.2, 2.3, and 20.8%, respectively. Compared with non‐FLD without MD, MAFLD was associated with the risk of CKD (adjusted odds ratio 1.83 [1.66–2.01], P < 0.001), whereas FLD without MD was not (1.02 [0.79–1.33], P = 0.868). Moreover, compared with FLD without MD, MAFLD was associated with the risk of CKD (1.19 [1.09–1.31], P < 0.001). In this retrospective cohort study, 16,938 of 27,371 participants underwent a median 4.6 (2.0–8.1) years follow‐up, and incident data of non‐FLD without MD, non‐FLD with MD, FLD without MD, and MAFLD were 21.0, 31.1, 26.1, and 31.1 cases per 1,000 person‐years, respectively. Compared with the non‐FLD without MD, MAFLD was associated with the risk of incident CKD (adjusted hazard ratio 1.24 [1.14–1.36], P < 0.001), whereas FLD without MD was not (1.11 [0.85–1.41], P = 0.433).

Conclusions

MAFLD was associated with a risk of CKD, whereas FLD without MD was not a risk for CKD.

Metabolic Health, Obesity, and Renal Function: 2013-2018 National Health and Nutrition Examination Surveys

Rising rates of metabolic syndrome, obesity, and mortality from chronic kidney disease (CKD) have prompted further investigation into the association between metabolic phenotypes and CKD. Purpose: To report the frequency of strictly defined metabolic phenotypes, renal function within each phenotype, and individual risk factors associated with reduced renal function. We utilized the 2013-2018 National Health and Nutrition Examination Surveys (NHANES) and complex survey sample weighting techniques to represent 220 million non-institutionalized U.S. civilians. Metabolic health was defined as having zero of the risk factors defined by the National Cholesterol Education Program with the exception of obesity, which was defined as BMI ≥ 30 kg/m2 in non-Asians and BMI ≥ 25 kg/m2 in Asians. The metabolically healthy normal (MUN) phenotype comprised the highest proportion of the population (38.40%), whereas the metabolically healthy obese (MHO) was the smallest (5.59%). Compared to the MHN reference group, renal function was lowest in the strictly defined MUN (B = -9.60, p < 0.001) and highest in the MHO (B = 2.50, p > 0.05), and this persisted when an increased number of risk factors were used to define metabolic syndrome. Systolic blood pressure had the strongest correlation with overall eGFR (r = -0.25, p < 0.001), and individuals with low HDL had higher renal function compared to the overall sample. The MUN phenotype had the greatest association with poor renal function. While the MHO had higher renal function, this may be due to a transient state caused by renal hyperfiltration. Further research should be done to investigate the association between dyslipidemia and CKD.

Obesity Without Metabolic Abnormality and Incident CKD: A Population-Based British Cohort Study

RATIONALE & OBJECTIVE

Metabolically healthy obesity (obesity without any metabolic abnormality) is not considered to be associated with increased risk of morbidity and mortality. We examined and quantified the association between metabolically healthy overweight/obesity and the risk of incident chronic kidney disease (CKD) in a British primary care population.

STUDY DESIGN

Retrospective population-based cohort study.

SETTING & PARTICIPANTS

4,447,955 of the 5,182,908 adults in The Health Improvement Network (THIN) database (United Kingdom, 1995-2015) with a recorded body mass index (BMI) at the time of registration date who were free of CKD and cardiovascular disease.

EXPOSURE

11 body size phenotypes were created, defined by BMI categories (underweight, normal weight, overweight, and obesity) and 3 metabolic abnormalities (diabetes, hypertension, and dyslipidemia).

OUTCOME

Incident CKD defined as a recorded code for kidney replacement therapy, a recorded diagnosis of CKD, or by an estimated glomerular filtration rate of<60mL/min/1.73m² for≥90 days, or a urinary albumin-creatinine ratio>3mg/mmol for≥90 days.

RESULTS

Of the 4.5 million individuals, 1,040,921 (23.4%) and 588,909 (13.2%) had metabolically healthy overweight and metabolically healthy obesity, respectively. During a mean follow-up interval of 5.4±4.3 (SD) years, compared with individuals with a metabolically healthy normal weight (n=1,656,231), there was a higher risk of incident CKD among those who had metabolically healthy overweight (adjusted HR, 1.30 [95% CI, 1.28-1.33]) and metabolically healthy obesity (adjusted HR, 1.66 [95% CI, 1.62-1.70]). The association was stronger in those younger than 65 years of age. In all BMI categories, there was greater risk of incident CKD with a greater number of metabolic abnormalities in a graded manner.

LIMITATIONS

Potential misclassification of metabolic status due to delayed diagnosis and residual confounding due to unmeasured factors.

CONCLUSIONS

Overweight and obesity without metabolic abnormality are associated with a higher risk of incident CKD compared with those with normal body weight and no metabolic abnormality.

Combined effect of obesity and metabolic profile on glomerular dysfunction in hypertensive subjects

AIM

The aim of this study is to explore the individual and combined effects of obesity and metabolic profile on the impairment of glomerular function among hypertensive subjects.

METHODS

This is a cross-sectional study enrolling 499 hypertensive subjects. Based on body mass index values and metabolic profile, they were assigned to one of four metabolic phenotype groups: MHNO: metabolically healthy non-obese, MHO: metabolically healthy but obese, MUHNO: metabolically unhealthy but non-obese, and MUHO: metabolically unhealthy and obese. The effect of the interaction between obesity and metabolic profile was tested on an additive scale, for both microalbuminuria and reduced estimated glomerular filtration rate (eGFR).

RESULTS

After adjustment for confounding factors, the highest risk of both microalbuminuria and decreased eGFR was found among patients of the MUHO group (OR = 6.0 [2.13], p < 0.0001, OR = 5.4 [1.26], p = 0.03, respectively). Analysis of the additive interaction indicates that 51% and 53% of the risk of microalbuminuria and its combination with low eGFR respectively is explained by the co-occurrence of obesity and metabolic disorder. The mechanism of this interaction is synergistic (synergy index = 2.6, [1.5.3]).

CONCLUSION

The decline of glomerular function in hypertensive subjects is significantly exacerbated by the interaction between obesity and metabolic disorders. The management of such high-risk subjects requires, in addition to the therapeutic regimen, an adequate dietary and physical program in order to preserve glomerular function.

Obesity as a predictive factor for chronic kidney disease in adults: systematic review and meta-analysis

Chronic kidney disease (CKD) is one of the main chronic diseases affecting the world population due to its high prevalence and increasing morbidity. Similarly, obesity gained the interest of the scientific community as it directly or indirectly increases mortality from cardiovascular causes, and its prevalence characterizes a pandemic. The objective of this study was to investigate obesity measured by body mass index as a predictor for end-stage renal disease in the general adult population. A systematic review and meta-analysis was carried out by searching 10 databases for prospective or retrospective cohort studies, with no restrictions on the language of publication, including adults with obesity without previous renal disease and who evolved to CKD (diagnosed by estimated glomerular filtration rate below 60 mL&mac_middot;min^-1&mac_middot;(1.73 m²)^-1 over the follow-up period. The R software and Meta package were used for data analysis. After removing duplicates, 5431 studies were submitted to the steps of the systematic review, and 21 articles were included in the data analysis. In total, 3,504,303 patients, 521,216 with obesity, and an average follow-up time of 9.86 years were included. The relative risk of obese people for developing CKD in the random effects model was 1.81 (95%CI: 1.52-2.16). The evidence found in this meta-analysis confirmed that obese people are at higher risk of developing CKD that the non-obese population (1.81 times higher), with obesity being a priority risk factor in preventive actions.

Association between Adiposity Indexes and Kidney Disease: Findings from the Longitudinal Study of Adult Health (Elsa-Brazil)

INTRODUCTION

Chronic kidney disease (CKD) is a public health problem and it is associated with a high risk of mortality. Overweight and obesity are known as independent risk factors for CKD.

OBJECTIVE

To investigate the association between adiposity indexes and kidney disease.

METHODS

This study included 14,636 adults from ELSA-Brazil. Outcome variables: altered glomerular filtration rate (GFR), categorized as yes (GFR <60 mL/min/1.73 m²) and no (GFR ≥60 mL/min/1.73 m²), albuminuria, estimated by albumin-creatinine ratio and categorized as yes (≥30 mg/g) and no (<30 mg/g), and presence of chronic kidney disease (CKD) (altered GFR and/or albuminuria). Exposure variables: obesity and overweight (body mass index (BMI)≥30 and ≥25 kg/m², respectively), high waist circumference (WC) (≥102 cm in men and ≥88 cm in women), high waist-to-hip ratio (WHR) (≥0.90 in men and ≥0.85 in women), and high waist-to-height ratio (WHtR) (≥0.5). To estimate the association between main exposures and outcomes, logistic regression analyses were performed using models adjusted for sociodemographic variables (age, gender, race/skin color, education), behavioral (smoking, physical activity, alcohol consumption), components of the metabolic syndrome (HDL cholesterol, triglycerides, hypertension, diabetes mellitus) and history of cardiovascular disease (myocardial infarction, angina or heart failure).

RESULTS

Individuals with obesity, high WC, WHR and WHtR were more prone to albuminuria when compared to individuals with normal values for these measures. It was also observed that these altered measures were positively associated with the presence of CKD.

CONCLUSION

Adiposity indexes have a direct and significant association with albuminuria and CKD.

Association between weight status, metabolic syndrome, and chronic kidney disease among middle-aged and elderly Chinese

BACKGROUND AND AIMS

Obesity often initiates or coexists with certain metabolic abnormalities. This study sought to examine the independent and joint relations of weight and metabolic syndrome (MetS) with incident chronic kidney disease (CKD) among Chinese elderly people.

METHODS AND RESULTS

A total of 15,229 participants (mean age: 62.8 years) from the Dongfeng-Tongji cohort with complete baseline questionnaire and medical examination data were followed from 2008 to 2010 to 2013. All participants were categorized into four phenotypes: metabolically healthy non-overweight/obesity (MHNO), metabolically healthy overweight/obesity (MHO), metabolically unhealthy non-overweight/obesity (MUNO), metabolically unhealthy overweight/obesity (MUO). Multivariable-adjusted logistic regression models were applied to estimate the odds ratios (ORs) and confidence intervals (CIs) of four phenotypes with the risk of incident CKD, which was defined as estimated glomerular filtration rate (eGFR) < 60 ml/min/1.73 m². A total of 1151 CKD cases were identified during a mean of 4.6-year follow-up. After adjusting for potential confounders, both overweight/obesity and MetS were associated with higher risk of CKD, and the ORs (95% CI) were 1.32 (1.15-1.52) and 1.50 (1.31-1.73), respectively. The risk of CKD was progressively higher in MHO (1.31, 1.09-1.57), MUNO (1.54, 1.22-1.93), and MUO (2.05, 1.73-2.42) as compared with MHNO phenotype, without significant multiplicative interaction between overweight/obesity and MetS (P_interaction = 0.906). These associations were slightly stronger among those aged >60 years or with baseline diabetes.

CONCLUSION

Both overweight/obesity and MetS were associated with an increased risk of CKD. It is worth noting that MHO and MUNO also have an elevated risk. Maintaining both normal weight and healthy metabolic profile is recommended.

Abdominal obesity phenotypes and risk of kidney function decline: Tehran Lipid and Glucose Study

OBJECTIVE

Obesity and related health risk in different obesity phenotypes has always been a controversial subject. The present study was conducted with the aim of investigating the risk of kidney function decline (KFD) incidence in different abdominal obesity phenotypes.

METHODS

In this prospective observational cohort study, 7002 individuals (56.1% female), aged ≥20 years, were followed for the incidence of KFD defined as 40% decline in eGFR. Abdominal obesity was defined based on waist circumference cut-offs ≥89/91cm for men/women, respectively. Metabolic health was defined as ≤1 criterion of the metabolic syndrome criteria, according to the Joint Interim Statement (JIS) definition.

RESULTS

At baseline 4273 individuals (61.0%) were abdominally obese, among whom, 1188 (27.8%) belonged to the metabolically healthy abdominal obese (MHAO) phenotype. Totally, 251 incidences of KFD was indicated throughout the 12-year follow-up. After adjusting for the confounding variables, MHAO phenotype was not associated with increased risk of KFD in both males and females. Furthermore, results indicated that hazard ratios (HRs) for incidence of KFD did not increase in males with unhealthy obesity phenotypes. However, females with metabolically unhealthy abdominal obese (MUAO) phenotype had increased risk of KFD.

CONCLUSION

Findings of this study indicated that MHAO phenotype was not associated with KFD incidence, regardless of the participants gender. Furthermore, MUAO phenotype was associated with higher risk of KFD only in females. Further studies with longer follow up and larger sample size are needed to shed more light upon the regarded relationship and the influential role of gender.

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.

Impact of metabolically healthy obesity on the risk of incident gastric cancer: a population-based cohort study

BACKGROUND

The risk of colon or breast cancer in metabolically healthy obese (MHO) were lower than that in metabolically abnormal obese (MAO). We hypothesized that the risk of incident gastric cancer in MHO is lower than that in MAO.

METHODS

This historical cohort study included 19,685 Japanese individuals who received health-checkup programs from 2003 to 2016. Each subject was classified as metabolically healthy (MH) (no metabolic abnormalities) or metabolically abnormal (MA) (one or more metabolic abnormalities), according to four metabolic factors (hypertension, impaired fasting glucose, hypertriglyceridemia and low HDL-cholesterol). Obese (O) or non-obese (NO) was classified by a BMI cutoff of 25.0 kg/m². Hazard ratios of metabolic phenotypes for incident gastric cancer were calculated by the Cox proportional hazard model with adjustments for age, sex, alcohol consumption, smoking and exercise.

RESULTS

Over the median follow-up period of 5.5 (2.9-9.4) years, incident rate of gastric cancer was 0.65 per 1000 persons-years. Incident rate of MHNO, MHO, MANO and MAO were 0.33, 0.25, 0.80 and 1.21 per 1000 persons-years, respectively. Compared with MHNO, the adjusted hazard ratios for development of gastric cancer were 0.69 (95% CI 0.04-3.39, p = 0.723) in MHO, 1.16 (95% CI 0.63-2.12, p = 0.636) in MANO and 2.09 (95% CI 1.10-3.97, p = 0.024) in MAO.

CONCLUSIONS

This study shows that individuals with MAO, but not those with MHO, had an elevated risk for incident gastric cancer. Thus, we should focus more on the presence of metabolic abnormalities rather than obesity itself for incident gastric cancer.

Metabolically Healthy Obesity and Risk of Incident Chronic Kidney Disease in a Korean Cohort Study

BACKGROUND

The incident of chronic kidney disease (CKD) of metabolically healthy obesity (MHO) has not been consistently determined.

METHODS

This study used data of Anseong Ansan community-based cohort, a part of the Korean Genome and Epidemiology Study (KoGES) provided by the Korea Center for Disease Control and Prevention (KCDC). Surveys were received from the Anseung and Ansan residents every two years between 2001-2002 and 2015-2016 for a total of 7 surveys over all. The subjects were divided into 4 phenotypes based on the presenting obesity and metabolic syndrome; 1) metabolically healthy normal weight (MHNW), 2) metabolically healthy obesity (MHO), 3) metabolically abnormal normal weight (MANW), and 4) metabolically abnormal obesity (MAO). Data were analyzed using the Cox proportional hazards regression model.

RESULTS

Of 8,865 subjects, 1,551 cases of 49,995 person-year (3.1%) developed incident CKD. At an adjusted hazard ratio (HR) of 1.13, the MHO group was not associated with a higher risk of incident CKD (95% confidence interval (CI): 0.92-1.41, P =0.234, using MHNW as the reference). The adjusted HRs of the MANW and MAO groups for incident CKD were significantly higher than those of the MHNW groups: 1.31 (95% CI: 1.05-1.64, P=0.017) for MANW and 1.49 (95% CI: 1.23-1.79, P<0.001) for MAO.

CONCLUSION

MHO is not associated with a high risk of CKD, and that MANW and MAO increase the risk of the incident CKD. Thus, it is important to consider metabolic health status rather than obesity when evaluating CKD risk.

Do worse baseline risk factors explain the association of healthy obesity with increased mortality risk? Whitehall II Study

OBJECTIVE

To describe 20-year risk factor trajectories according to initial weight/health status and investigate the extent to which baseline differences explain greater mortality among metabolically healthy obese (MHO) individuals than healthy non-obese individuals.

METHODS

The sample comprised 6529 participants in the Whitehall II study who were measured serially between 1991-1994 and 2012-2013. Baseline weight (non-obese or obese; body mass index (BMI) ≥30 kg/m2) and health status (healthy or unhealthy; two or more of hypertension, low high-density lipoprotein cholesterol (HDL-C), high triglycerides, high glucose, and high homeostatic model assessment of insulin resistance (HOMA-IR)) were defined. The relationships of baseline weight/health status with 20-year trajectories summarizing ~25,000 observations of systolic and diastolic blood pressures, HDL-C, triglycerides, glucose, and HOMA-IR were investigated using multilevel models. Relationships of baseline weight/health status with all-cause mortality up until July 2015 were investigated using Cox proportional hazards regression.

RESULTS

Trajectories tended to be consistently worse for the MHO group compared to the healthy non-obese group (e.g., glucose by 0.21 (95% CI 0.09, 0.33; p < 0.001) mmol/L at 20-years of follow-up). Consequently, the MHO group had a greater risk of mortality (hazard ratio 2.11 (1.24, 3.58; p = 0.006)) when the referent group comprised a random sample of healthy non-obese individuals. This estimate, however, attenuated (1.34 (0.85, 2.13; p = 0.209)) when the referent group was matched to the MHO group on baseline risk factors.

CONCLUSIONS

Worse baseline risk factors may explain any difference in mortality risk between obese and non-obese groups both labelled as healthy, further challenging the concept of MHO.

Risk factors in metabolic syndrome predict the progression of diabetic nephropathy in patients with type 2 diabetes

BACKGROUND

While metabolic syndrome can independently predict the development of diabetic kidney disease (DKD) in patients with type 2 diabetes, the risk factors for DKD progression have rarely been discussed. The purpose of this study is to evaluate the association between metabolic syndrome and the progression of DKD in patients with type 2 diabetes.

MATERIAL AND METHODS

This retrospective observational cohort study lasted approximately five years. We defined metabolic syndrome using the criteria of the National Cholesterol Education Program Adult Treatment Panel III with the Asian definition of obesity. The progression of DKD was demonstrated by either the progression of albuminuria or worsening renal function. Progression of albuminuria was defined by the transition from normoalbuminuria (<30 mg/g) to microalbuminuria (30-300 mg/g) or from micro- to macroalbuminuria (>300 mg/g). Worsening renal function was defined by a reduction of eGFR to 50% of the baseline or the doubling of serum creatinine. We adopted multivariate Cox-regression analysis to determine the risk factors associated with DKD progression.

RESULTS

This study consisted of 935 type 2 diabetic patients with a mean age of 64.62 years. We found progression of albuminuria in 172 patients (18.4%) and worsened renal function in 41 patients (4.4%). After Cox regression analysis, the multivariable-adjusted HR for the progression of albuminuria and worsened renal function was 1.65 (95% C.I.:1.07-2.53 P = 0.022) and 2.62 (95% C.I.:1.01-6.79 P = 0.047) respectively, for those with metabolic syndrome compared to those without metabolic syndrome.

CONCLUSION

The presence of metabolic syndrome independently predicts DKD progression in patients with type 2 diabetes.

Combined Associations of Body Mass Index and Metabolic Health Status on Medical and Dental Care Days and Costs in Japanese Male Employees: A 4-Year Follow-Up Study

BACKGROUND

The combined associations of body mass index (BMI) levels and metabolic dysfunction with medical and dental care utilizations is unclear.

METHODS

A 4-year follow-up study was performed in 16,386 Japanese male employees (mean age 48.2 [standard deviation, 11.0] years) without a history of cardiovascular disease (CVD), cancer, or renal failure. They were classified into eight phenotypes based on four BMI levels (underweight, <18.5; normal weight, 18.5-24.9; overweight, 25.0-29.9; and obese, ≥30.0 kg/m²) and the presence or absence of ≥2 of 4 metabolic abnormalities: high blood pressure, high triglycerides, low high-density-lipoprotein cholesterol, and high blood sugar. Based on their health insurance claims data, we compared medical and dental care days and costs among the eight different BMI/metabolic phenotypes during 2010-2013.

RESULTS

The combinations of BMI levels and metabolic status were significantly associated with the adjusted mean and median medical outpatient days and costs and the median dental outpatient days and costs. The obese/unhealthy subjects had the highest medical outpatient days and costs, and the underweight/unhealthy subjects had the highest dental outpatient days and costs. The underweight/unhealthy subjects also had the highest medical inpatient days and hospitalization rates of CVD, and had higher medical costs compared with the obese/healthy subjects. The differences in median medical costs between healthy and unhealthy phenotypes were larger year by year across all BMI levels.

CONCLUSIONS

Identification of obesity phenotypes using both BMI levels (including the underweight level) and metabolic status may more precisely predict healthcare days and costs compared with either BMI or metabolic status alone.

Associations of body condition score with health conditions related to overweight and obesity in cats

OBJECTIVES

To explore the associations of cat body condition score with various health conditions, such as diabetes mellitus, dermatological conditions and hypertension, that have been shown to relate to overweight and/or obesity in cats, dogs or humans.

MATERIALS AND METHODS

Electronic patient records between January 3, 2005 and June 21, 2015 were obtained from a cat-focused primary accession clinic in metropolitan Sydney where the body condition score of cats was routinely evaluated. Binomial logistic regression modelling was conducted to investigate the associations, after adjusting for age, sex and breed, between 21 health conditions and body condition score recorded on a 9-point scale.

RESULTS

Fourteen of the 21 health conditions examined showed significant associations with an increased body condition score, particularly those of 7 and above. These were dermatological conditions, atopic dermatitis, musculoskeletal conditions, arthritis, hypertension, respiratory conditions, asthma, oral conditions, diarrhoea, general and lower urinary tract conditions, ophthalmic conditions, diabetes mellitus and allergic conditions. Additionally, cats with body condition score of 8 or 9 had significantly higher odds for gastrointestinal conditions and upper urinary tract conditions when compared with cats with body condition score of 5.

CLINICAL SIGNIFICANCE

As far as we know, this is the first study reporting positive associations of high body condition score with atopic dermatitis, hypertension, asthma, diarrhoea, ophthalmic conditions and allergic conditions in cats. A large number of positive associations between health conditions and high body condition score indicates that excess fat mass should be given a greater emphasis in preventive health care for cats.

The magnitude of obesity and metabolic syndrome among diabetic chronic kidney disease population: A nationwide study

Background

Although the prevalence of obesity and metabolic syndrome (MetS) among dialysis patients has been exceeding than general population, little is known regarding obesity and MetS in non-dialysis chronic kidney disease (CKD). We aimed to find the magnitude of obesity and MetS and their associations with impaired renal function among type 2 diabetes mellitus (T2DM) patients.

Methods

A national survey of T2DM patients was collected in the Thai National Health Security Office database during 2014–5. The sampling frame was designated as distinct geographic regions throughout the country. A stratified two-stage cluster sampling was used to select the study population. Anthropometry and 12-hour fasting blood samples were obtained by trained personnel. BMI of ≥25 kg/m² was classified as obesity. MetS was defined as having elevated waist circumference (>90 and >80 cm in men and women, respectively) plus any two of the followings: triglyceride ≥150 mg/dL, HDL-C <40 in men or <50 mg/dL in women, blood pressure ≥130/85 mmHg, and fasting blood sugar ≥100 mg/dL. CKD was defined as an impaired renal function (eGFR <60 mL/min/1.73m² according to the CKD-EPI equation). Logistic regression analysis was performed to examine the relationship between obesity and MetS with the presence of CKD.

Results

A total of 32,616 diabetic patients were finally recruited from 997 hospitals. The mean age was 61.5±10.9 years with 67.5% women. Of the participants, 35.4% were CKD patients. The prevalence of obesity was 46.5% in CKD and 54.1% in non-CKD patients with T2DM (p<0.001). In contrast, the prevalence of MetS in CKD patients was higher than their non-CKD counterparts (71.3 vs 68.8%, p<0.001). Moreover, there was an association between the prevalence of MetS with CKD stage from 3a to 5 (70.1, 72.3, 73.4, and 72.7%, respectively, p trend = 0.02). MetS, but not obesity, had a significant association with CKD in T2DM patients after adjusting for age, sex, and comorbidities [OR 1.14; 95% CI 1.06–1.22, p<0.001]. When stratified by each component of MetS, only high serum triglyceride and low HDL-C levels were increased in patients with CKD stage 4 and 5 compared with CKD stage 3 (p<0.001) and had a significant relationship with impaired renal function.

Conclusion

There were relatively high prevalences of both obesity and MetS in T2DM patients. A higher prevalence of MetS, but lower prevalence of obesity, was observed among diabetic CKD group compared with their non-CKD counterparts. MetS, as a surrogate of insulin resistance, appeared to be more important than obesity in the development of impaired renal function in diabetic population.

Metabolically Healthy Obesity and Risk of Kidney Function Decline

OBJECTIVE

The aim of this study was to examine the association between BMI categories, stratified by metabolic health status, and the risk of kidney function decline (KFD).

METHODS

In this study, 42,128 adult patients with a stable BMI were classified over a 3-year baseline window by BMI and metabolic health status (assessed by Adult Treatment Panel-III criteria). KFD was defined as an estimated glomerular filtration rate (eGFR) decline ≥ 30%, eGFR < 15 mL/min/1.73 m² , or receipt of dialysis and/or transplant.

RESULTS

Over a median of 5.1 years (interquartile range 2.1-8.9), 6,533 (15.5%) individuals developed KFD. Compared with the normal weight, metabolically healthy category, metabolically healthy obesity was associated with a higher risk of KFD (adjusted hazard ratio [aHR] 1.52; 95% CI: 1.22-1.89). aHRs for KFD were 1.17 (95% CI: 0.89-1.53), 2.21 (95% CI: 1.59-3.08), and 2.20 (95% CI: 1.55-3.11) for metabolically healthy obesity with BMI 30 to 34.9, BMI 35 to 39.9, and BMI ≥ 40 kg/m² . These associations were consistent among men and women, patients with eGFR ≥ or < 90 mL/min/1.73 m² , and age ≥ or < 55 years. The risk of KFD was highest among metabolically unhealthy individuals with BMI ≥ 40 (aHR 4.02; 95% CI: 3.40-4.75 vs. metabolically healthy individuals with normal weight).

CONCLUSIONS

Obesity, whether in the presence or absence of metabolic health, is a risk factor for KFD.

The relationships among hyperuricemia, body mass index and impaired renal function in type 2 diabetic patients

Chronic kidney disease (CKD) is a common chronic microvascular complication and the major cause of death in diabetic patients. This study was conceived to explore the possible mechanisms of how hyperuricemia and obesity contribute to renal function impairment in type 2 diabetic (T2DM) patients. A cross-sectional study in 609 participants recruited from a T2DM population in North China was conducted. The multiplicative interaction between body mass index (BMI) and uric acid (UA) level was assessed using an interaction term in a logistic regression analysis. Our results indicate that male T2DM patients having higher BMI (OR 1.711, p = 0.038), blood urine nitrogen (BUN) (OR 1.100, p = 0.034), and 24-hour urinary micro-albumin levels (OR 1.004, p = 0.021) were much more likely to have high UA. Whereas, for female T2DM patients, the OR of BMI, BUN, and triglyceride were 1.169 (p = 0.001), 1.337 (p = 0.000), and 1.359 (p = 0.006), respectively. In this study population, obesity and elevated UA work together to increase the risk of renal injury. In vitro experiments indicate that reactive oxygen species (ROS) production increased with UA treatment in human renal glomerular endothelial cells (HRGECs), while endothelial nitric oxide synthase (eNOS) production level dropped. UA also increased monocyte chemotactic protein-1 (MCP-1) expression and nuclear factor kappa B (NF-κB) activation. Taken together, our results indicate that high concentrations of UA lead to endothelial dysfunction through the activation of the inflammatory response and induction of oxidative stress, even in non-obese T2DM patients.

Carotid artery wall shear stress is independently correlated with renal function in the elderly

Hemodynamic has increasingly been regarded as an important factor of renal function. However, the relationship between carotid artery wall shear stress (WSS) and renal function is not clarified. To investigate the relationship between carotid WSS and renal function, we recruited 761 older subjects aged 60 years and over from community-dwelling in the Shandong area, China. Carotid WSS, endothelial function, and estimated glomerular filtration rate (eGFR) were assessed in all subjects. Subjects were grouped by the interquartile of the carotid artery mean WSS. We found that the eGFRs derived from serum creatinine and/or cystatin C using three CKD-EPI equations were significantly higher and albumin/creatinine ratio was lower in the higher interquartile groups than in the lower interquartile groups (P <0.05). The mean WSS was independently correlated with eGFRs even after adjustment for confounders. Similar findings were found between carotid artery peak WSS and eGFRs and albumin/creatinine ratio. In addition, we found that endothelial function was strongly related to carotid WSS and renal function after adjustment for confounders. In conclusion, there is an independent correlation of carotid WSS with renal function in the elderly. The local rheologic forces may play an important role in renal function changing. The correlation may be mediated by regulation of endothelial function.

Investigation into the underlying molecular mechanisms of hypertensive nephrosclerosis using bioinformatics analyses

Hypertensive nephrosclerosis (HNS) is a major risk factor for end-stage renal disease. However, the underlying pathogenesis of HNS remains to be fully determined. The gene expression profile of GSE20602, which consists of 14 glomeruli samples from patients with HNS and 4 normal glomeruli control samples, was obtained from the Gene Expression Omnibus database. Gene ontology (GO) and pathway enrichment analyses were performed in order to investigate the functions and pathways of differentially expressed genes (DEGs). Pathway relation and co‑expression networks were constructed in order to identify key genes and signaling pathways involved in HNS. In total, 483 DEGs were identified to be associated with HNS, including 302 upregulated genes and 181 downregulated genes. Furthermore, GO analysis revealed that DEGs were significantly enriched in the small molecule metabolic process. In addition, pathway analysis also revealed that DEGs were predominantly involved in metabolic pathways. The tricarboxylic acid (TCA) cycle was identified as the hub pathway in the pathway relation network, whereas the sorbitol dehydrogenase (SORD) and cubulin (CUBN) genes were revealed to be the hub genes in the co‑expression network. The present study revealed that the SORD, CUBN and albumin genes as well as the TCA cycle and metabolic pathways are involved in the pathogenesis of HNS. The results of the present study may contribute to the determination of the molecular mechanisms underlying HNS, and provide insight into the exploration of novel targets for the diagnosis and treatment of HNS.

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.

Weight gain since age of 20 as risk of metabolic syndrome even in non-overweight individuals

PURPOSE

Metabolic syndrome (MetS), regardless of the presence of obesity, is known as a risk of diabetes and cardiovascular disease. Weight gain after age 20 reported to be associated with these diseases. Impact of the difference between the body mass index (BMI) at examination and BMI at age 20 (ΔBMI_exa-20y) on MetS, especially in non-overweight individuals, remains to be elucidated.

METHODS

We analyzed the data of 24,363 individuals (14,301 men and 10,062 women) in this cross-sectional study. The diagnosis of MetS was diagnosed when three or more of the following criteria were present: hypertension, hyperglycemia, hypertriglyceridemia, low HDL-cholesterol level, and abdominal obesity. Logistic regression was performed to calculate odds ratios (ORs) and 95% confidence intervals (CIs) adjusting for age, alcohol, smoking, exercise, and BMI at examination.

RESULTS

Compared to the lowest ΔBMI_exa-20y tertile (ΔBMI_exa-20y < 1.2 kg/m² in men and ≤0 kg/m² in women), the highest tertile (ΔBMI_exa-20y ≥ 3.2 kg/m² in men and ≥2.0 kg/m² in women) was associated with the risk of the presence of MetS (multivariate OR = 1.80, 95%CI 1.53-2.11, p < 0.001 in men and OR = 3.27, 95%CI 2.22-4.96, p < 0.001 in women). This result was also applicable in non-overweight individuals (multivariate OR = 2.06, 95%CI 1.46-2.92, p < 0.001 in men and OR = 2.49, 95%CI 1.40-4.64, p < 0.001 in women).

CONCLUSIONS

Our analyses showed that ΔBMI_exa-20y is associated with the risk of the presence of MetS, even in non-overweight individuals. It is thus important to check weight changes from early adulthood, even in non-overweight individuals.

Green Tea Polyphenols Ameliorate the Early Renal Damage Induced by a High-Fat Diet via Ketogenesis/SIRT3 Pathway

SCOPE

Several reports in the literature have suggested the renoprotective effects of ketone bodies and green tea polyphenols (GTPs). Our previous study found that GTP consumption could elevate the renal expression of the ketogenic rate-limiting enzyme, which was decreased by a high-fat diet (HFD) in rats. Here, we investigated whether ketogenesis can mediate renoprotection by GTPs against an HFD.

METHODS AND RESULTS

Wistar rats were fed a standard or HFD with or without GTPs for 18 weeks. The renal oxidative stress level, kidney function, renal expression, and activity levels of mitochondrial 3-hydroxy-3-methylglutaryl-CoA (HMG-CoA) synthase 2 (HMGCS2) and sirtuin 3(SIRT3) were detected. The increased renal oxidative stress and the loss of renal function induced by the HFD were ameliorated by GTPs. Renal ketogenesis and SIRT3 expression and activity levels, which were reduced by the HFD, were restored by GTPs. In vitro, HEK293 cells were transfected with the eukaryotic expression plasmid pcDNA HMGCS2. GTP treatment could upregulate HMGCS2 and SIRT3 expression. Although SIRT3 expression was not affected by HMGCS2 transfection, the 4-hydroxy-2-nonenal (4-HNE) level and the acetyl-MnSOD (K122)/MnSOD ratio were reduced in HMGCS2-transfected cells in the context of H₂O₂.

CONCLUSION

The ketogenesis/SIRT3 pathway mediates the renoprotection of GTPs against the oxidative stress induced by an HFD.

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

PURPOSE

Recent studies identified that metabolically abnormal non-obese phenotype is a risk factor for cardiovascular diseases. However, little is known about risk factor for progression from metabolically healthy non-overweight to metabolically abnormal phenotype. We hypothesized that fatty liver had a clinical impact on progression from metabolically healthy non-overweight to metabolically abnormal phenotype.

METHODS

In this retrospective cohort study, 14,093 Japanese (7557 men and 6736 women), who received the health-checkup program from 2004 to 2012, were enrolled. Overweight and obesity were defined as body mass index 23.0-25.0 and ≥25.0 kg/m². Four metabolic factors (impaired fasting glucose, hypertension, hypertriglyceridemia and low high density lipoprotein-cholesterol concentration) were used for definition of metabolically healthy (less than two factors) or metabolically abnormal (two or more). We divided the participants into three groups: metabolically healthy non-overweight (9755 individuals, men/women = 4290/5465), metabolically healthy overweight (2547 individuals, 1800/747) and metabolically healthy obesity (1791 individuals, 1267/524). Fatty liver was diagnosed by ultrasonography.

RESULTS

Over the median follow-up period of 5.3 years, 873 metabolically healthy non-overweight, 512 metabolically healthy overweight and 536 metabolically healthy obesity individuals progressed to metabolically abnormal. The adjusted hazard risks of fatty liver on progression were 1.49 (95% confidence interval 1.20-1.83, p = 0.005) in metabolically healthy non-overweight, 1.37 (1.12-1.66, p = 0.002) in metabolically healthy overweight and 1.38 (1.15-1.66, p < 0.001) in metabolically healthy obesity, after adjusting for age, sex, alcohol, smoking, exercise, impaired fasting glucose, hypertension, hypertriglyceridemia, low high density lipoprotein-cholesterol concentration, and abdominal obesity.

CONCLUSIONS

Fatty liver is an independent risk factor for progression from metabolically healthy status to metabolically abnormal phenotype, even in non-overweight individuals.