Steroid-resistant nephrotic syndrome: pharmacogenetics and epigenetic points and views

Construction and evaluation of glucocorticoid dose prediction model based on genetic and clinical characteristics of patients with systemic lupus erythematosus

Currently, no glucocorticoid dose prediction model is available for clinical practice. This study aimed to utilise machine learning techniques to develop and validate personalised dosage models. Participants were patients with SLE who were registered at Nanfang Hospital and received prednisone. Univariate analysis was used to confirm the feature variables. Subsequently, the random forest (RF) algorithm was utilised to interpolate the absent values of the feature variables. Finally, we assessed the prediction capabilities of 11 machine learning and deep-learning algorithms (Logistic, SVM, RF, Adaboost, Bagging, XGBoost, LightGBM, CatBoost, MLP, and TabNet). Finally, a confusion matrix was used to validate the three regimens. In total, 129 patients met the inclusion criteria. The XGBoost algorithm was selected as the preferred method because of its superior performance, achieving an accuracy of 0.81. The factors exhibiting the highest correlation with the prednisone dose were CYP3A4 (rs4646437), albumin (ALB), haemoglobin (HGB), anti-double-stranded DNA antibodies (Anti-dsDNA), erythrocyte sedimentation rate (ESR), age, and HLA-DQA1 (rs2187668). Based on validation, the precision and recall rates for low-dose prednisone (⩾5 mg but <7.5 mg/d) were 100% and 40% respectively. Similarly, for medium-dose prednisone (⩾7.5 mg but <30 mg/d), the accuracy and recall rates were 88% and 88%, and for high-dose prednisone (⩾30 mg but ⩽100 mg/d), the accuracy and recall rates were 62% and 100% respectively. A robust machine learning model was developed to accurately predict prednisone dosage by integrating the identified genetic and clinical factors.

Urine-derived podocytes from steroid resistant nephrotic syndrome patients as a model for renal-progenitor derived extracellular vesicles effect and drug screening

BACKGROUND

Personalized disease models are crucial for evaluating how diseased cells respond to treatments, especially in case of innovative biological therapeutics. Extracellular vesicles (EVs), nanosized vesicles released by cells for intercellular communication, have gained therapeutic interest due to their ability to reprogram target cells. We here utilized urinary podocytes obtained from children affected by steroid-resistant nephrotic syndrome with characterized genetic mutations as a model to test the therapeutic potential of EVs derived from kidney progenitor cells (nKPCs).

METHODS

EVs were isolated from nKPCs derived from the urine of a preterm neonate. Three lines of urinary podocytes obtained from nephrotic patients' urine and a line of Alport syndrome patient podocytes were characterized and used to assess albumin permeability in response to nKPC-EVs or various drugs. RNA sequencing was conducted to identify commonly modulated pathways after nKPC-EV treatment. siRNA transfection was used to demonstrate the involvement of SUMO1 and SENP2 in the modulation of permeability.

RESULTS

Treatment with the nKPC-EVs significantly reduced permeability across all the steroid-resistant patients-derived and Alport syndrome-derived podocytes. At variance, podocytes appeared unresponsive to standard pharmacological treatments, with the exception of one line, in alignment with the patient's clinical response at 48 months. By RNA sequencing, only two genes were commonly upregulated in nKPC-EV-treated genetically altered podocytes: small ubiquitin-related modifier 1 (SUMO1) and Sentrin-specific protease 2 (SENP2). SUMO1 and SENP2 downregulation increased podocyte permeability confirming the role of the SUMOylation pathway.

CONCLUSIONS

nKPCs emerge as a promising non-invasive source of EVs with potential therapeutic effects on podocytes with genetic dysfunction, through modulation of SUMOylation, an important pathway for the stability of podocyte slit diaphragm proteins. Our findings also suggest the feasibility of developing a non-invasive in vitro model for screening regenerative compounds on patient-derived podocytes.

Molecular mechanisms of glucocorticoid resistance

BACKGROUND

As a powerful anti-inflammatory, immunosuppressive, and antiproliferative drug, glucocorticoid (GC) plays an important role in the treatment of various diseases. However, some patients may experience glucocorticoid resistance (GCR) in clinical, and its molecular mechanism have not been determined.

METHODS

The authors performed a review of the literature on GCR focusing on mutations in the NR3C1 gene and impaired glucocorticoid receptor (GR) signalling, using METSTR (2000 through May 2022) to identify original articles and reviews on this topic. The search terms included 'glucocorticoid resistance/insensitive', 'steroid resistance/insensitive', 'NR3C1', and 'glucocorticoid receptor'.

RESULTS

Primary GCR is mainly caused by NR3C1 gene mutation, and 31 NR3C1 gene mutations have been reported so far. Secondary GCR is caused by impaired GC signalling pathways, including decreased expression of GR, impaired nuclear translocation of GR, and impaired binding of GR to GC and GR to target genes. However, the current research is more on the expression level of GR, and there are relatively few studies on other mechanisms. In addition, methods for improving GC sensitivity are rarely reported.

CONCLUSION

The molecular mechanisms of GCR are complex and may differ in different diseases or different patients. In future studies, when exploring the mechanism of GCR, methods to improve GC sensitivity should also be investigated.

The Role of Cytokines in Nephrotic Syndrome

Idiopathic nephrotic syndrome (INS) is an important primary glomerular disease characterized by severe proteinuria. Evidence supports a role for T cell dysfunction in the pathogenesis of INS. Glucocorticoids are the primary therapy for INS; however, steroid-resistant NS (SRNS) patients are at a higher risk of drug-induced side effects and harbor poor prognosis. Although the exact mechanism of the resistance is unknown, the imbalances of T helper subtype 1 (Th1), Th2, and regulatory T cells (Tregs) and their cytokines may be involved in the pathogenesis of glucocorticoid responsiveness. Up to now, no confirmed biomarkers have been able to predict SRNS; however, a panel of cytokines may predict responsiveness and identify SRNS patients. Thus, the introduction of distinctive cytokines as novel biomarkers of SRNS enables both preventions of drug-related toxicity and earlier switch to more effective therapies. This review highlights the impacts of T cell population imbalances and their downstream cytokines on response to glucocorticoid responsiveness state in INS.

Steroid-resistant Nephrotic Syndrome in Children: A Mini-review on Genetic Mechanisms, Predictive Biomarkers and Pharmacotherapy Strategies

Steroid-resistant nephrotic syndrome (SRNS) constitutes the second most frequent cause of chronic kidney disease in childhood. The etiology of SRNS remains largely unknown and no standardized treatment exists. Recent advances in genomics have helped to build understanding of the molecular mechanisms and pathogenesis of the disease. The genetic polymorphisms in genes encoding proteins which are involved in the pharmacokinetics and pharmacodynamics of glucocorticoids (GCs) partially account for the different responses between patients with nephrotic syndrome. More importantly, single-gene causation in podocytes-associated proteins was found in approximately 30% of SRNS patients. Some potential biomarkers have been tested for their abilities to discriminate against pediatric patients who are sensitive to GCs treatment and patients who are resistant to the same therapy. This article reviews the recent findings on genetic mechanisms, predictive biomarkers and current therapies for SRNS with the goal to improve the management of children with this syndrome.

Glucocorticoid receptors and their upstream epigenetic regulators in adults with steroid-resistant nephrotic syndrome

Steroid-resistant nephrotic syndrome (SRNS) is a clinical challenge with variable clinical outcomes. In patients with SRNS, unsuccessful anti-inflammatory and anti-proteinuric effects of steroids lead to end-stage renal disease (ESRD). Our objective was to define the expression pattern of the glucocorticoid receptors (GR) α and β and their epigenetic regulators (miR-24, miR-30a, and miR-370) in a group of adults with SRNS. In this regard, sixty primary NS patients with focal segmental glomerulosclerosis (FSGS, N = 30) and membranous glomerulonephritis (MGN, N = 30) and also healthy volunteers (N = 24) were enrolled. Real-time PCR was performed to evaluate the expression levels of the aforementioned genes in peripheral blood mononuclear cell (PBMC) samples. Furthermore, an in-silico analysis was performed to understand the signaling pathways and biological procedures that may be targeted by these microRNAs in NS. The decreased and increased levels of GRα and GRβ were not significant, respectively. Statistically significant reduced miR-24 levels were observed between control/MGN (p = .022) and MGN/FSGS (p = .032) groups. Additionally, a decrease was detected in miR-30a between MGN and FSGS (p = .049) groups. There was a significant increase in miR-370 expression level between control and NS groups (p = .029), as well as control/MGN (p = .008), and MGN/FSGS (p = .046). Bioinformatics analysis predicted the possible targets of the studied genes including genes involved in TGF-β, Notch1, and p53 signaling pathways, regulation of gene expression, intracellular signal transduction, negative regulation of response to the stimulus, cell-cell signaling, and cell activation in the pathogenesis of SRNS. Taken all together, dysregulated levels of GRα, GRβ were not attributed to SRNS in our patients. It seems that pharmacokinetics and the genetic variations in podocyte-related genes may be associated with the steroid-resistance in our adult patients with NS rather than GR expression.