Obesity, metabolic dysfunction, and risk of kidney stone disease: a national cross-sectional study.

BACKGROUND: This study aimed to investigate the association between different metabolic syndrome-body mass index (MetS-BMI) phenotypes and the risk of kidney stones. MATERIALS AND METHODS: Participants aged 20-80 years from six consecutive cycles of the NHANES 2007-2018 were included in this study. According to their MetS status and BMI, the included participants were allocated into six mutually exclusive groups: metabolically healthy normal weight (MHN)/overweight (MHOW)/obesity (MHO) and metabolically unhealthy normal weight (MUN)/overweight (MUOW)/obesity (MUO). To explore the association between MetS-BMI phenotypes and the risk of kidney stones, binary logistic regression was used to determine the odds ratios (ORs). RESULTS: A total of 13,589 participants were included. It was revealed that all the phenotypes with obesity displayed higher risks of kidney stones (OR = 1.38, p < 0.01 for MHO & OR = 1.80, p < 0.001 for MUO, in the fully adjusted model). The risk increased significantly when metabolic dysfunction coexisted with overweight and obesity (OR = 1.39, p < 0.05 for MUOW & OR = 1.80, p < 0.001 for MUO, in the fully adjusted model). Of note, the ORs for the MUO and MUOW groups were higher than those for the MHO and MHOW groups, respectively. CONCLUSIONS: Obesity and unhealthy metabolic status can jointly increase the risk of kidney stones. Assessing the metabolic status of all individuals may be beneficial for preventing kidney stones.

ARNTL2 facilitates bladder cancer progression through potentiating ENO1-mediated glycolysis in a SLC31A1-independent and -dependent manner.

BACKGROUND: Basic helix-loop-helix ARNT like 2 (ARNTL2) is a transcription factor that controls the circadian rhythm. Amounts of studies have demonstrated the carcinogenic function of ARNTL2 in human malignant tumors albeit the underlying mechanisms remain poorly understood. We aimed to study the significance of ARNTL2 in bladder cancer (BLCA). METHODS: Immunohistochemical staining, immunoblotting and the database from TCGA were used to analyze the clinical relevance of ARNTL2, enolase 1 (ENO1) and solute carrier family 31 member 1 (SLC31A1) in BLCA. The function of ARNTL2 was explored by cell proliferation assay, apoptosis, colony formation and xenografted tumorigenesis. The molecular mechanisms of ARNTL2-driving BLCA development were investigated by RT-qPCR, immunoblotting and luciferase assays. Glycolysis was checked by measuring glucose consumption and lactate production. ENO1 activity was assessed by using indicated assay kit. RESULTS: Overexpression of ARNTL2 facilitates the proliferation and tumorigenesis of BLCA cells through suppression of apoptosis and enhancement of glycolysis. Up-regulation of SLC31A1, ENO1, and enhancement of SLC31A1-mediated ENO1 activity were critical for ARNTL2-triggered glycolysis and malignant growth in BLCA cells. ARNTL2 was positively correlated with SLC31A1 and ENO1 in BLCA patients. High expression of ARNTL2, SLC31A1 or ENO1 predicted the poor prognosis of BLCA patients. Depletion of SLC31A1 and inhibition of glycolysis completely blunted the growth ability of BLCA cells. CONCLUSION: In summary, ARNTL2 facilitates the progression of BLCA via activating ENO1-mediated glycolysis in a SLC31A1-independent and -dependent manner. Inhibiting SLC31A1 and glycolysis may be an aspirational approach for the treatment of BLCA patients with overexpression of ARNTL2.

National analysis of urinary cadmium concentration and kidney stone: Evidence from NHANES (2011-2020).

Background: The association between urinary cadmium and kidney stone risk is inconsistent in previous studies, which needs further exploration. This study was performed to explore the association between urinary cadmium and kidney stone. Materials and methods: Data from the National Health and Nutrition Examination Survey (2011-2020) were included and further analyzed. Urinary cadmium was stratified into quartiles with quartile 1 (Q1: 0.025-0.104 µg/L) and quartile 4 (Q4: 0.435-7.581 µg/L). Further weighted logistic regression was adopted to evaluate the association between urinary cadmium and kidney stone. A subgroup analysis was used to verify the findings. The non-linear association was examined using the restricted cubic spline (RCS) regression. Results: A total of 9,056 adults aged 20 years and above were included in this study. In the fully adjusted model, an increased risk of kidney stones was identified for quartile 2 (OR = 1.40, 95% CI = 1.06-1.84, P < 0.05), quartile 3 (OR = 1.18, 95% CI = 0.88-1.59, P > 0.05), and quartile 4 (OR = 1.54, 95% CI = 1.10-2.06, P < 0.05). A similar association was found between continuous cadmium increase and OR of kidney stones in the fully adjusted model (OR = 1.13, 95% CI = 1.01-1.26, P < 0.05). The RCS also indicated a non-linear association between urinary cadmium concentration and kidney stone risk (P for non-linear < 0.001). Conclusion: In summary, cadmium exposure is identified as a risk factor for kidney stones in this study. Their non-linear association makes demands on early intervention for the cadmium-exposed population. Medical interventions for kidney stone prevention should take cadmium exposure into account.