Shu Rong

PRDM16 is a PR domain-containing epigenetic regulator with intrinsic histone methyltransferase activity and scaffolding interactions with corepressor complexes such as CtBP1/2. Beyond its well-established roles in adipose biology, emerging evidence positions PRDM16 as a central node linking chromatin regulation, metabolic control, and cell survival in the kidney, making it a multimodal pharmacological target. In acute kidney injury, PRDM16 functions as an endogenous protective hub that simultaneously suppresses ferroptosis, apoptosis, and pyroptosis through distinct downstream pathways. In chronic and diabetic kidney disease, TGF-β/Smad-driven silencing or promoter hypermethylation of PRDM16 disrupts PGC-1α-dependent mitochondrial integrity and podocyte insulin signaling, offering opportunities for epigenetic reactivation strategies and gene therapy. In clear cell renal cell carcinoma, PRDM16 exhibits a striking duality: epigenetically silenced by CpG island hypermethylation within cancer cells yet upregulated in peritumoral adipocytes to drive a browning-associated, pro-metastatic secretome, defining a unique pharmacological dichotomy that calls for cell-type-selective interventions. This review synthesizes the molecular architecture, isoform diversity, and disease-stage-specific regulation of PRDM16 and evaluates the pharmacological toolset currently available: the expression-inducing natural product formononetin, adenoviral and lentiviral gene delivery systems, and platelet membrane-coated or PLGA-based nanoparticles (PNPs) that enable kidney-targeted delivery. We further discuss key pharmacological challenges, including the need for isoform-selective modulation to avoid oncogenic short-form upregulation, cell-type-specific targeting within the nephron and tumor microenvironment, and the development of pharmacodynamic biomarkers for clinical translation. By integrating mechanistic insights with a drug discovery perspective, this review provides a comprehensive pharmacological framework for targeting PRDM16 to restore renal homeostasis and halt disease progression.

Objectives: To investigate the effects of Roxadustat and recombinant human erythropoietin (rHuEPO) on glycemic control and glycated hemoglobin (HbA1c) in non-dialysis type 2 diabetic kidney disease (DKD) patients with anemia. Methods: This retrospective study enrolled 449 patients, who were divided into three groups—the rHuEPO group (n = 252), the Roxadustat group (n = 102), and the switch group (n = 95)—in which patients were converted from rHuEPO to Roxadustat. All treatments lasted for more than three months. Changes in HbA1c and other indicators within groups as well as differences among groups were evaluated. Results: In the rHuEPO group, HbA1c levels decreased from 7.08 ± 1.19 to 6.41 ± 0.60 (p < 0.001), and they returned to baseline levels by 6–12 months (p > 0.05). In the Roxadustat group, HbA1c fluctuated but none of the differences reached statistical significance (p > 0.05). In the switch group, HbA1c decreased during rHuEPO treatment (p < 0.05) and returned to baseline after switching to Roxadustat (p > 0.05). No significant changes in blood glucose levels were observed in any group after treatment (p > 0.05). Multivariate linear regression analysis showed that changes in iron metabolism parameters, erythrocyte parameters, inflammatory markers, and glucose-lowering or lipid-lowering regimens had no significant effect on the change in HbA1c in the Roxadustat group (F = 0.834, p = 0.620), while the multivariate model of rHuEPO group also lacked statistical significance (F = 1.142, p = 0.170). After treatment, all three groups showed improvements in anemia, iron metabolism, renal function, inflammatory markers, and lipid profiles compared with baseline (p < 0.05). Additionally, further improvements in these parameters were observed after the transition from rHuEPO to Roxadustat (p < 0.05). Compared with rHuEPO group, the Roxadustat group exhibited significantly greater increases in hemoglobin, red blood cell count, total iron-binding capacity, transferrin, and serum iron (p < 0.05). Conclusions: In non-dialysis DKD patients with anemia, rHuEPO can significantly decrease HbA1c values, while Roxadustat does not. Roxadustat offers advantages over rHuEPO in terms of efficacy and assessment of glycemic control.

Objectives: Machine learning and nomograms are widely used in predictive medicine by integrating multiple prognostic factors to estimate individualized clinical outcomes, yet their application in nephrology remains limited. This retrospective study, based on more than 14 million inpatient cases, employs machine learning and nomograms to assess the prognosis of acute kidney injury (AKI) patients initiating renal replacement therapy (RRT). Methods: AKI inpatients who underwent RRT at 24 medical centers in China between January 1, 2007 and December 31, 2022 were included, with attention to all‐cause mortality and renal recovery of this population. Machine learning techniques, including Cox analysis, LASSO analysis, logistic regression, and nomogram construction, were employed to evaluate prognosis. Receiver operating characteristic (ROC) curve and area under the curve (AUC) were used to determine the predictive accuracy and discriminability of nomograms, while inpatient data from our center were recruited for external validation. Results: After multiple rounds of screening, a total of 8992 study subjects were selected from 1,640,894 medical orders related to RRT. The median survival time was 38 days, with an overall survival rate of 57.33%, and the 360‐day renal recovery rate was 65.67%, while surviving patients had a median survival time of 703 days. The nomogram of the survival outcome included Charlson comorbidity index, urea nitrogen, chronic obstructive pulmonary disease, malignant tumor, coronary heart disease, hypertension, respiratory failure, glutamic oxaloacetic transaminase, total bilirubin, triglyceride, neutrophil percentage, hemoglobin, platelet count, D‐dimer, prothrombin time, NT‐proBNP, and pH. Nomograms of a 48‐h survival, a 30‐day renal recovery, and a 360‐day renal recovery were also established to visually express analysis results. The nomograms demonstrated acceptable performance based on the ROC/AUC analysis in both training and validation sets. Conclusion: This study successfully identified risk factors for prognosis among AKI patients receiving RRT through machine learning and developed nomograms, which were sufficiently accurate to predict the risk and prognostic factors, allowing for individualized clinical decisions in future practice.

Objectives: Managing acute gout attacks in renal failure patients on peritoneal dialysis (PD) is challenging. We report a unique case of a PD patient with recurrent pulmonary infections, heart failure, and severe anemia, who presented with refractory gout attacks successfully treated with the IL-1β monoclonal antibody Firsekibart. Case presentation: A 52-year-old female PD patient experienced recurrent swelling and pain in limb joints for one year, with acute exacerbation for three days. Laboratory tests showed serum uric acid (UA) 627 μmol/L and C-reactive protein (CRP) 16.6 mg/L. Conventional treatments with nonsteroidal anti-inflammatory drugs (NSAIDs) and glucocorticoids were ineffective. Given the patient’s high inflammatory state and multiple comorbidities, Firsekibart (200 mg) was administered. Joint pain and swelling significantly improved within 24 h. The Visual Analogue Scale (VAS) score decreased from 5 to 1 within 72 h, and CRP dropped from 16.6 mg/L to 6.5 mg/L at day 3. UA decreased from 485 μmol/L to 388.9 μmol/L at day 7. At three-month follow-up, the patient remained free of gout recurrence, with VAS 1, CRP 7.8 mg/L, and UA 393 μmol/L. At the last 7-month telephone follow-up she reported no further acute gout attacks, though mild joint swelling persisted. No injection site reactions, hypersensitivity, or infectious complications were observed throughout the entire follow-up period. Conclusions: IL-1β blockade Firsekibart may represent a safe and effective option for managing acute gout attacks in high-risk ESRD patients on PD with multiple comorbidities.

The global incidence of Chronic Kidney Disease (CKD) is steadily escalating, with discernible linkage to the intricate terrain of intestinal microecology. The intestinal microbiota orchestrates a dynamic equilibrium in the organism, metabolizing dietary-derived compounds, a process which profoundly impacts human health. Among these compounds, short-chain fatty acids (SCFAs), which result from microbial metabolic processes, play a versatile role in influencing host energy homeostasis, immune function, and intermicrobial signaling, etc. SCFAs emerge as pivotal risk factors influencing CKD’s development and prognosis. This paper review elucidates the impact of gut microbial metabolites, specifically SCFAs, on CKD, highlighting their role in modulating host inflammatory responses, oxidative stress, cellular autophagy, the immune milieu, and signaling cascades. An in-depth comprehension of the interplay between SCFAs and kidney disease pathogenesis may pave the way for their utilization as biomarkers for CKD progression and prognosis or as novel adjunctive therapeutic strategies.

Background: As an effective measurement for severe acute kidney injury (AKI), the prolonged intermittent renal replacement therapy (PIRRT) received attention. Also, machine learning has advanced and been applied to medicine. This study aimed to establish short-term prognosis prediction models for severe AKI patients who received PIRRT by machine learning. Methods: The hospitalized AKI patients who received PIRRT were assigned to this retrospective case-control study. They were grouped based on survival situation and renal recovery status. To screen the correlation, Pearson’s correlation coefficient, partial ETA square, and chi-square test were applied, eight machine learning models were used for training. Results: Among 493 subjects, the mortality rate was 51.93% and the kidney recovery rate was 30.43% at 30 days post-discharge, respectively. The indices related to survival were Sodium, Total protein, Lactate dehydrogenase (LDH), Phosphorus, Thrombin time, Liver cirrhosis, chronic kidney disease stage, number of vital organ injuries, and AKI stage, while Sodium, Total protein, LDH, Phosphorus, Thrombin time, Diabetes, peripherally inserted central catheter and AKI stage were selected to predict the 30-day renal recovery. Naive Bayes has a good performance in the prediction model for survival, Random Forest has a good performance in 30-day renal recovery prediction model, while for 90-day renal recovery prediction model, it’s K-Nearest Neighbor. Conclusions: Machine learning can not only screen out indicators influencing prognosis of AKI patients receiving PIRRT, but also establish prediction models to optimize the risk assessment of these people. Moreover, attention should be paid to serum electrolytes to improve prognosis.

Background and Purpose: Muscle protein catabolism in patients with diabetic nephropathy (DN) results in striking loss of muscle proteins, which increases morbidity and mortality risks. Evidence shows that short‐chain fatty acids (SCFAs) play an important role in health maintenance and disease development. Recently, the connection between butyrate (a SCFA) and DN has been revealed, although the relationship between butyrate and muscle atrophy remains unclear.Experimental Approach: We studied changes in serum butyrate levels in DN patients using metabolomic analyses. In db/db mice, protective effects of butyrate on DN‐induced muscle atrophy. were explored. Inhibition of muscle atrophy by butyrate and the underlying mechanism(s) were studied in C2C12 cells exposed to high glucose/lipopolysaccharide (HG/LPS).Key Results: Butyrate levels in DN patients were significantly decreased. In db/db mice, supplementing normal diet with butyrate improved intestinal barrier function. Concurrently, butyrate alleviated muscle atrophy, promoted PI3K/Akt/mTOR signalling, and suppressed oxidative stress and autophagy in skeletal muscle of db/db mice, and in HG/LPS‐exposed C2C12 cells. Further, FFA2 receptors, key components of SCFA signalling, were decreased in skeletal muscle of db/db mice and in HG/LPS‐exposed C2C12 cells. Overexpression of FFA2 receptors activated PI3K/Akt/mTOR signalling and inhibited oxidative stress and autophagy in HG/LPS‐exposed C2C12 cells. Silencing of FFA2 blocked PI3K/Akt/mTOR signalling that was improved by butyrate, as well as the suppression of oxidative stress and reduction of autophagy.Conclusion and Implication: Butyrate exerts protective effects on muscle atrophy induced by DN by enhancing intestinal barrier function and activating the FFA2 receptor‐mediated PI3K/Akt/mTOR pathway.

Background: Vascular calcification associated with chronic kidney disease (CKD) can increase the risk of mortality. Elevated serum levels of high mobility group box 1 (HMGB1) promotes vascular calcification in CKD via the Wnt/β-catenin pathway. Sirtuin 6 (SIRT6) prevents fibrosis in CKD by blocking the expression of β-catenin target genes through deacetylation. This study aimed to investigate whether the inhibition of vascular calcification by bone marrow mesenchymal stem cell (BMSC)-derived exosomes is related to SIRT6 activity and assess the regulatory relationship between HMGB1 and SIRT6. Methods: CKD characteristics, osteogenic markers, calcium deposition, and the differential expression of HMGB1 and SIRT6 have been measured in a 5/6 nephrectomized mouse CKD model fed a high-phosphate diet to induce aortic calcification. In vitro assays were also performed to validate the in vivo findings. Results: High phosphate promotes the translocation of HMGB1 from the nucleus to the cytosol and induces the expression of Runx2, osteopontin, and Msx2. However, BMSC-derived exosomes were found to alleviate CKD-related fibrosis and the induction of osteogenic genes although less significantly when SIRT6 expression is suppressed. SIRT6 was found to modulate the cytosol translocation of HMGB1 by deacetylation in vascular smooth muscle cells. Conclusion: Our results indicate that BMSC-derived exosomes inhibit high phosphate-induced aortic calcification and ameliorate renal function via the SIRT6–HMGB1 deacetylation pathway.