Zhihong Wang

Background: A recently proposed estimated glomerular filtration rate (eGFR) slope-based criterion for clinical remission of chronic kidney disease (CKD) represents an emerging therapeutic paradigm. However, clinical courses meeting this criterion after sequential combination therapy with kidney-protective agents have rarely been reported in patients with type 2 diabetes mellitus (T2DM) and CKD. Case Presentation: A 70-year-old man with long-standing T2DM, nonproliferative diabetic retinopathy, and progressive albuminuric CKD presented in May 2023 with a urine albumin-to-creatinine ratio (UACR) of 121.60 mg/g creatinine (Cr), an eGFR of 28.00 mL/min/1.73 m², hemoglobin A1c (HbA1c) of 7.5%, and serum potassium of 4.4 mmol/L. Kidney function had continued to decline despite treatment with a renin-angiotensin system inhibitor (RASi), a sodium-glucose cotransporter 2 inhibitor (SGLT2i), and insulin. Therapy was sequentially intensified with a glucagon-like peptide-1 receptor agonist (GLP-1RA) and finerenone, with close monitoring of kidney function and serum potassium. By January 2026, UACR had decreased to 26.53 mg/g Cr and eGFR had increased to 42.48 mL/min/1.73 m². No adverse event required treatment discontinuation. Results: Ordinary least-squares regression of all 10 eGFR measurements yielded a positive slope that met the recently proposed eGFR slope-based criterion for clinical remission of CKD. Conclusions: In this patient with T2DM and CKD, the eGFR slope over the full follow-up met the proposed criterion for clinical remission of CKD during sequential multidrug kidney-protective therapy with safety monitoring. These observations require confirmation in prospective controlled studies.

Aims: This study aimed to examine the association between three-year changes in body mass index (BMI) and the risk of new-onset or progressive diabetic kidney disease (DKD) among people with type 2 diabetes and a normal BMI at baseline. Methods: A total of 416 people with type 2 diabetes (T2DM) and a normal BMI were enrolled from the Chongqing Diabetes Registry (CDR, NCT03692884) cohort and were followed for incident DKD until 2025. The change in BMI at the three-year follow-up was classified as follows: stable BMI (p = 0.007]. Each 1% increase in BMI was significantly associated with an increased risk of DKD onset or progression [HR = 1.05, 95%CI: 1.02–1.07, p < 0.001]. This association remained significant after multivariable adjustment. Time-dependent receiver operating characteristic (ROC) curves showed that the area under the curve (AUC) of this indicator reached 0.683–0.729 for the prediction of new-onset or progressive DKD risk over 3–5 years. In subgroup analyses, decreased BMI was associated with a lower risk of DKD among people aged p = 0.044]. Conclusions: A ≥5% increase in BMI in three years may be a risk factor for new-onset or progressive DKD among people with T2DM and normal BMI. Conversely, a ≥5% decrease in BMI may be associated with renal protection in non-elderly individuals within the population.

Background: Ectopic fat deposition has been demonstrated to play a critical role in the onset and progression of renal dysfunction. However, research on renal parenchymal fat deposition and its association with renal dysfunction in type 2 diabetes mellitus (T2DM) remains limited, particularly regarding its association with early kidney injury. The present study aimed to further investigate the relationship between renal fat fraction (FF) and biomarkers of kidney injury, thereby providing new evidence for the potential link between intrarenal fat accumulation and early renal impairment in T2DM. Methods: This cross-sectional study enrolled 60 patients with T2DM. Renal FF was quantitatively assessed using magnetic resonance imaging (MRI). Clinical characteristics, body composition parameters, and biochemical indices were collected. Levels of kidney injury biomarkers, including tumor necrosis factor receptors 1 (TNF-R1), tumor necrosis factor receptors 2 (TNF-R2), chitinase-3-like protein 1 (YKL-40), and kidney injury molecule-1 (KIM-1), were measured using enzyme-linked immunosorbent assay (ELISA). To evaluate the correlations between fat distribution and inflammatory biomarkers, Pearson correlation analysis was performed. Furthermore, linear regression analysis was conducted to explore the associations between renal FF and kidney injury biomarkers with adjustments for potential confounders such as smoking status, diabetes duration, and visceral fat. Lasso regression was used to screen variables. Results: The results demonstrated that renal FF was significantly positively correlated with serum YKL-40 (r = 0.3, p = 0.021), TNF-R1 (r = 0.246, p = 0.042), and urinary KIM-1 (r = 0.396, p = 0.004), indicating a close association between renal fat accumulation and early kidney injury biomarkers. In regression analyses adjusted for age, sex, and duration of diabetes, the associations between renal FF and these biomarkers remained significant. After further adjustment for potential confounders, including smoking history, alcohol consumption, hypertension, renin-angiotensin-aldosterone system (RAAS) inhibitors, sodium-dependent glucose transporters 2 (SGLT2) inhibitors, glucagon-Like Peptide-1 (GLP-1) receptor agonists, and lipid-lowering drugs, renal FF remained significantly associated with TNF-R1 (β = 0.327, p = 0.015), KIM-1 (β = 0.352, p = 0.021), and YKL-40 (β = 0.275, p = 0.025). Moreover, even after additional adjustment for visceral fat, the associations of renal FF with TNF-R1 and KIM-1 persisted. After using the Benjamini–Hochberg procedure for false discovery rate, the relationship between renal FF and KIM-1 had a significant difference. Variables of age and gender were excluded to build the parsimonious modeling using Lasso regression. It suggested that renal fat accumulation may contribute to kidney injury independently of visceral adiposity. Conclusions: The study systematically demonstrates a significant association between renal FF and early biomarkers of kidney injury in T2DM, which may suggest the potential role of renal fat accumulation in the pathogenesis of diabetic nephropathy. These findings provide clinical data support for the development of a fat-targeted intervention study. Future research should further elucidate the long-term mechanistic role of renal FF in diabetic nephropathy, as well as its potential value in early diagnosis and therapeutic applications.

Aim: The study aimed to explore the associations of the remnant cholesterol (RC) levels with the risk of diabetic kidney disease (DKD) in patients with type 2 diabetes mellitus (T2DM). Methods: The study collected data from 23324 patients with T2DM from the UK Biobank (UKB) cohort and 3059 patients with T2DM from the Chongqing Diabetes Registry (CDR) cohort. UKB and CDR cohort were followed for incident DKD until October 2020 and March 2023, respectively. Cox proportional hazards regression was performed to explore the relationship between RC levels and incident DKD. Results: Participants from the UKB and CDR were followed for a mean period of 13.72 years and 1.92 years, respectively. The incidences of DKD are 12.9% and 24.5%. Participants were divided into 4 groups: 0.41 mmol/L or less, 0.41 to 0.56 mmol/L, 0.56 to 0.73 mmol/L, and greater than 0.73 mmol/L according to RC levels. Lower RC levels (≤ 0.41 mmol/L) were used as a reference, multi-adjusted model showing that patients with higher RC levels (> 0.73 mmol/L) in the UKB were associated with increased risk of incident DKD [hazard ratio [HR], 1.27; 95% CI, 1.10– 1.46; P = 0.001]. These results were consistent in the CDR [HR (95% CI): 1.39 (1.03, 1.89); P = 0.034]. In the stratified analyses, we observed an increase in the risk of incident DKD with RC in the elderly patients, while not in the middle-aged patients in both UKB cohort [HR (95% CI): 1.33 (1.13, 1.57) vs 1.16 (0.89, 1.50), P for interaction = 0.043] and CDR cohort [HR (95% CI): 1.53 (1.02, 2.30) vs 1.23 (0.76, 2.00), P for interaction = 0.009]. Conclusion: High RC might be an independent risk factor for new-onset DKD in T2DM population after adjusting for traditional risk factors, especially in elderly T2DM patients.

Background: The association of sleep behaviors with microvascular complications and cardiovascular outcomes in diabetic patients is not clear. Furthermore, serum biomarkers that can be used to evaluate this association have not been characterized. Therefore, this study investigated the association of the overall sleep score with the diabetic complications and the potential underlying serum metabolic biomarkers in patients with type 2 diabetes mellitus (T2DM).Methods: This prospective cohort study included 30 915 T2DM patients without complications from the UK Biobank. The sleep score of the participants was evaluated based on sleep behaviors such as sleep duration, insomnia, snoring, chronotype, and daytime sleepiness. The potential biomarkers, including cystatin C (Cys C), apolipoprotein A (Apo A), C‐reactive protein (CRP), albumin, and γ‐glutamyl transpeptidase (GGT), were also determined to evaluate their role as potential indicators of the association between the sleep score and the diabetic complications.Results: Participants with a healthy sleep score of 4–5 had lower risks of microvascular complications (HR = 0.80 [95% CI: 0.72, 0.89]) and cardiovascular outcomes (HR = 0.70 [95% CI: 0.61, 0.81]) compared to those with a sleep score of 0–1. Furthermore, cys C showed the best effects by explaining the associations of overall healthy sleep behaviors with microvascular complications and cardiovascular outcomes by 30.36% and 14.36%, respectively.Conclusions: Our data showed that healthy sleep behaviors were associated with a reduced risk of diabetic complications. Moreover, serum biomarkers of renal function, lipids, systemic inflammation, and hepatic function partially mediated the relationship between sleep behaviors and diabetic complications.

Purpose To investigate the renal fat deposition on Dixon-based magnetic resonance imaging (MRI) and to explore the predictive value of renal fat biomarkers of magnetic resonance (MR-RFBs) for early kidney damage in obesity. Methods This prospective study included 56 obese volunteers and 47 non-obese healthy volunteers. All volunteers underwent renal magnetic resonance examinations. The differences in MR-RFBs [including renal proton density fat fraction (PDFF), renal sinus fat volume (RSFV), and perirenal fat thickness (PRFT)] measured on Dixon-based MRI between the obese and non-obese volunteers were analyzed using a general linear model, taking sex, age, diabetes, and hypertension as covariates. The relationship between estimated glomerular filtration rate (eGFR) and demographic, laboratory, and imaging parameters in obese volunteers was examined by correlation analysis. Results Obese volunteers had higher MR-RFBs than non-obese volunteers after controlling for confounders (all p < 0.001). Renal PDFF (r = − 0.383; p = 0.004), RSFV (r = − 0.368; p = 0.005), and PRFT (r = − 0.451; p < 0.001) were significantly negatively correlated with eGFR in obesity. After adjusting for age, sex, body mass index, diabetes, hypertension, visceral adipose tissue, subcutaneous adipose tissue, renal PDFF, and RSFV, PRFT remained independently negatively associated with eGFR (β = − 0.587; p = 0.003). Conclusions All MR-RFBs are negatively correlated with eGFR in obesity. The MR-RFBs, especially PRFT, may have predictive value for early kidney damage in obesity. Graphical Abstract

Background: Endoplasmic reticulum stress plays a crucial role in the pathogenesis of neuroinflammation and chronic pain. This study hypothesized that PRKR-like endoplasmic reticulum kinase (PERK) and inositol-requiring enzyme type 1 (IRE1) regulate lipocalin-2 (LCN2) and Nod-like receptor family pyrin domain containing 3 (NLRP3) expression in astrocytes, thereby contributing to morphine tolerance and hyperalgesia. Methods: The study was performed in Sprague–Dawley rats and C57/Bl6 mice of both sexes. The expression of LCN2 and NLRP3 was assessed by Western blotting. The tail-flick, von Frey, and Hargreaves tests were used to evaluate nociceptive behaviors. Chromatin immunoprecipitation was conducted to analyze the binding of activating transcription factor 4 (ATF4) to the promoters of LCN2 and TXNIP. Whole-cell patch-clamp recordings were used to evaluate neuronal excitability. Results: Pharmacologic inhibition of PERK and IRE1 attenuated the development of morphine tolerance and hyperalgesia in male (tail latency on day 7, 8.0 ± 1.13 s in the morphine + GSK2656157 [10 μg] group vs. 5.8 ± 0.65 s in the morphine group; P = 0.04; n = 6 rats/group) and female (tail latency on day 7, 6.0 ± 0.84 s in the morphine + GSK2656157 [10 μg] group vs. 3.1 ± 1.09 s in the morphine group; P = 0.0005; n = 6 rats/group) rats. Activation of PERK and IRE1 upregulated expression of LCN2 and NLRP3 in vivo and in vitro. Chromatin immunoprecipitation analysis showed that ATF4 directly bound to the promoters of the LCN2 and TXNIP. Lipocalin-2 induced neuronal hyperexcitability in the spinal cord and dorsal root ganglia via melanocortin-4 receptor. Conclusions: Astrocyte endoplasmic reticulum stress sensors PERK and IRE1 facilitated morphine tolerance and hyperalgesia through upregulation of LCN2 and NLRP3 in the spinal cord. Editor’s Perspective: What We Already Know about This Topic: What This Article Tells Us That Is New:

Background: Individuals in the workplace are exposed to various environments, tasks, and schedules. Previous studies have indicated a link between occupational exposures and an increased risk of chronic kidney disease (CKD). However, the social conditions of the work environment may also be a crucial contributing factor to CKD. Furthermore, individuals may encounter multiple occupational-related risk factors simultaneously, underscoring the importance of investigating the joint risk of different working conditions on CKD. Methods: A prospective analysis of 65,069 UK Biobank participants aged 40 to 69 years without CKD at baseline (2006–2010) was performed. A self-administered questionnaire assessed working conditions and a working conditions risk score were developed. Participants who answered “sometimes” or “often” exposure to occupational heat or occupational secondhand cigarette smoke; involved in shift work or heavy workloads (“usually” or “always”), were grouped as high-risk working conditions. Each working condition was scored as 1 if grouped as high-risk, and 0 if not. The working conditions risk score was equal to the sum of these four working conditions. Cox proportional hazard regression models were used to estimate the associations between working conditions and CKD incidence. Results: The mean follow-up time was 6.7 years. After adjusting for demographic, lifestyle, and working time factors, the hazard ratios for the development of CKD for heavy workloads, shift work, occupational secondhand cigarette smoke exposure, and occupational heat exposure were 1.24 (95%CI = 1.03, 1.51), 1.33 (95%CI = 1.10, 1.62), 1.13 (95%CI = 1.01, 1.26), 1.11 (95%CI = 0.99, 1.24), respectively. The risk of CKD was found to be significantly associated with an increasing working conditions risk score. Individuals with a working conditions risk score of 4 had an 88.0% (95% CI = 1.05, 3.35) higher risk of developing CKD when compared to those with a working conditions risk score of 0. Conclusions: Adverse working conditions, particularly when considered in combination, can significantly elevate the risk of chronic kidney disease (CKD). These results provide a reference for implementing measures to prevent CKD.