Causal relationship between basal metabolic rate and kidney function: a bidirectional two-sample mendelian randomization study.

Background: The relationship between basal metabolic rate (BMR) and Chronic kidney disease (CKD) remains unclear and controversial. In this study, we investigated the causal role of BMR in renal injury, and inversely, whether altered renal function causes changes in BMR. Methods: In this two-sample mendelian randomization (MR) study, Genetic data were accessed from published genome-wide association studies (GWAS) for BMR ((n = 454,874) and indices of renal function, i.e. estimated glomerular filtration rate (eGFR) based on creatinine (n =1, 004, 040), CKD (n=480, 698), and blood urea nitrogen (BUN) (n =852, 678) in European. The inverse variance weighted (IVW) random-effects MR method serves as the main analysis, accompanied by several sensitivity MR analyses. We also performed a reverse MR to explore the causal effects of the above indices of renal function on the BMR. Results: We found that genetically predicted BMR was negatively related to eGFR, (ß= -0.032, P = 4.95*10-12). Similar results were obtained using the MR-Egger (ß= -0.040, P = 0.002), weighted median (ß= -0.04, P= 5.35×10-11) and weighted mode method (ß= -0.05, P=9.92×10-7). Higher BMR had a causal effect on an increased risk of CKD (OR =1.36, 95% CI = 1.11-1.66, P =0.003). In reverse MR, lower eGFR was related to higher BMR (ß= -0.64, P = 2.32×10-6, IVW analysis). Bidirectional MR supports no causal association was observed between BMR and BUN. Sensitivity analyses confirmed these findings, indicating the robustness of the results. Conclusion: Genetically predicted high BMR is associated with impaired kidney function. Conversely, genetically predicted decreased eGFR is associated with higher BMR.

PM2.5 exposure aggravates kidney damage by facilitating the lipid metabolism disorder in diabetic mice.

Background: Ambient fine particulate matter ≤ 2.5 µm (PM2.5) air pollution exposure has been identified as a global health threat, the epidemiological evidence suggests that PM2.5 increased the risk of chronic kidney disease (CKD) among the diabetes mellitus (DM) patients. Despite the growing body of research on PM2.5 exposure, there has been limited investigation into its impact on the kidneys and the underlying mechanisms. Past studies have demonstrated that PM2.5 exposure can lead to lipid metabolism disorder, which has been linked to the development and progression of diabetic kidney disease (DKD). Methods: In this study, db/db mice were exposed to different dosage PM2.5 for 8 weeks. The effect of PM2.5 exposure was analysis by assessment of renal function, pathological staining, immunohistochemical (IHC), quantitative real-time PCR (qPCR) and liquid chromatography with tandem mass spectrometry (LC-MS/MS) based metabolomic analyses. Results: The increasing of Oil Red staining area and adipose differentiation related protein (ADRP) expression detected by IHC staining indicated more ectopic lipid accumulation in kidney after PM2.5 exposure, and the increasing of SREBP-1 and the declining of ATGL detected by IHC staining and qPCR indicated the disorder of lipid synthesisandlipolysis in DKD mice kidney after PM2.5 exposure. The expressions of high mobility group nucleosome binding protein 1 (HMGN1) and kidney injury molecule 1 (KIM-1) that are associated with kidney damage increased in kidney after PM2.5 exposure. Correlation analysis indicated that there was a relationship between HMGN1-KIM-1 and lipid metabolic markers. In addition, kidneys of mice were analyzed using LC-MS/MS based metabolomic analyses. PM2.5 exposure altered metabolic profiles in the mice kidney, including 50 metabolites. In conclusion the results of this study show that PM2.5 exposure lead to abnormal renal function and further promotes renal injury by disturbance of renal lipid metabolism and alter metabolic profiles.

Comparison of novel visceral obesity indexes with traditional obesity measurements in predicting of metabolically unhealthy nonobese phenotype in hemodialysis patients.

BACKGROUND: Normal-weight maintenance hemodialysis (MHD) patients with abdominal obesity exhibited a more proatherogenic profile than overweight and obesity patients with abdominal obesity, highlighting the importance of early identification of metabolically unhealthy nonobese (MUNO) in this population. Visceral fat accumulation plays a crucial role in the development of MUNO. Lipid accumulation product (LAP), visceral adiposity index (VAI) have been proved as reliable visceral obesity markers. The Chinese visceral adiposity index (CVAI) and a body shape index (ABSI) are newly discovered indexes of visceral obesity and have been reported to be associated with multiple metabolic disorders. There are limited studies investigating the associations between different visceral obesity indices and risk of MUNO, especially in hemodialysis patients. Moreover, no general agreement has been reached to date regarding which of these obesity indices performs best in identifying MUNO. We aimed to investigate the prevalence of MUNO in MHD patients and compare the associations between different adiposity indices (CVAI, ABSI,VAI, LAP, body mass index (BMI), waist circumference (WC) and waist-to-hip ratio (WHtR)) with MUNO risk in this population. METHODS: We conducted a multi-center cross-sectional study in Guizhou Province, Southwest China. 1302 nonobese adult MHD patients were included in our study. MUNO was defined as being nonobese and having the presence of > = 2 components of metabolic syndrome (MetS). Nonobese was defined as BMI less than 25 kg/m2. VAI, LAP, CVAI, ABSI, BMI, WC and WHtR were calculated. Logistic regression analyses and receiver operator curve (ROC) analyses were performed. Results 65.6% participants were metabolically unhealthy. The ROC curve analysis demonstrated that of the seven obesity indices tested, the VAI (AUC 0.84 for women and 0.79 for men) followed by LAP (AUC 0.78 for women and 0.72 for men) had the highest diagnostic accuracy for MUNO phenotype while ABSI exhibited the lowest AUC value for identifying MUNO phenotype CONCLUSIONS: Metabolically unhealthy is highly prevalent in nonobese MHD patients. VAI and LAP outperformed CVAI in discriminating MUNO in MHD patients. Though ABSI could be a weak predictor of MUNO, it is not better than WHtR, WC and BMI.

Comparison of visceral, general and central obesity indices in the prediction of metabolic syndrome in maintenance hemodialysis patients.

PURPOSE: We aimed to compare the predictive ability of the anthropometric indices reflecting general, central and visceral obesity for identification of metabolic syndrome (MetS) in maintenance hemodialysis (MHD) patients. METHODS: A multicenter, cross-sectional study that consisted of 1603 adult MHD patients (54.6 ± 16 years) was conducted in Guizhou Province, Southwest China. Eight anthropometric obesity indexes including body mass index (BMI), waist circumference (WC), waist-height ratio (WHtR), conicity index (Ci) and visceral adiposity index (VAI), lipid accumulation product (LAP), a body shape index (ABSI) and body roundness index (BRI) were recorded. MetS was defined based on the criteria of the International Diabetes Federation. Participants were categorized into four groups according to quartiles of different obesity indices. Binary logistic regression analyses were used to evaluate the associations between the eight obesity parameters and MetS. Receiver operator curve (ROC) analyses were used to identify the best predictor of MetS. RESULTS: The eight anthropometric obesity indexes were independently associated with MetS risk, even after adjustment for age, sex, educational status and history of smoking. The ROC analysis revealed that all the eight obesity indices included in the study were able to discriminate MetS [all area under the ROC curves (AUCs) > 0.6, P < 0.05]. LAP showed the highest AUC and according to the maximum Youden indexes, the cut off values for men and women were 27.29 and 36.45, respectively. The AUCs of LAP, VAI, ABSI, BRI, WC, WHtR, Ci and BMI were 0.88, 0.87, 0.60, 0.78, 0.79, 0.78, 0.69 and 0.76 for men, and 0.87, 0.85, 0.65, 0.79, 0.81, 0.79, 0.73 and 0.76 for women, respectively. There was no significant difference in the AUC value between LAP and VAI, BRI/WHtR and BMI in men and between BRI/WHtR and BMI in women. The AUC value for WHtR was equal to that for BRI in identifying MetS. CONCLUSIONS: Visceral obesity marker LAP followed by VAI was the most effective predictor of MetS while ABSI followed by CI was the weakest indicator for the screening of MetS in MHD patients. BRI could be an alternative obesity measure to WHtR in assessment of MetS. LAP may be a simple and useful screening tool to identify individuals at high risk of MetS particularly in middle-aged and elderly Chinese MHD patients. LEVEL OF EVIDENCE: Level V, descriptive study.