Journal of Clinical Nephrology and Therapeutics

All submissions of the EM system will be redirected to Online Manuscript Submission System. Authors are requested to submit articles directly to Online Manuscript Submission System of respective journal.
Reach Us +1 (202) 780-3397

Mini Review - Journal of Clinical Nephrology and Therapeutics (2023) Volume 7, Issue 6

Genetic insights into the pathogenesis of steroid-resistant nephrotic syndrome

Zhang Yang*

Department of Nursing, Medical College of Hunan Normal University, China

*Corresponding Author:
Zhang Yang
Department of Nursing, Medical College of Hunan Normal University, China
Medical College of Hunan Normal University
China
E-mail:zhang@yang.cn

Received:02-Dec-2023,Manuscript No. AACNT-24-127352; Editor assigned:04-Dec-2023,PreQC No. AACNT-24-127352(PQ); Reviewed:18-Dec-2023,QC No. AACNT-24-127352; Revised:22-Dec-2023,Manuscript No. AACNT-24-127352(R); Published:30-Dec-2023,DOI: 10.35841/aacnt-7.6.172

Citation: Yang Z. Genetic insights into the pathogenesis of steroid-resistant nephrotic syndrome. J Clin Nephrol Ther. 2023;7(6):172

Visit for more related articles at Journal of Clinical Nephrology and Therapeutics

Introduction

A diverse range of kidney diseases collectively known as "steroid-resistant nephrotic syndrome" (SRNS) are marked by chronic proteinuria and the development of end-stage renal disease (ESRD) in spite of corticosteroid treatment. Since many genetic variants linked to SRNS have been identified during the past few decades, a great deal of work has been made in understanding the disease's genetic underpinnings. These mutations impact the glomerular filtration barrier's numerous elements, most notably the structure and function of podocytes. With an emphasis on the major genes and pathways connected to the illness, this article offers a summary of the genetic insights into the pathophysiology of SRNS.[1].

We go over the function of genes involved in cytoskeletal organisation, ion transport, and slit diaphragm integrity, as well as podocyte-specific proteins including nephrin, podocin, and alpha-actinin-4. Additionally, we investigate the clinical implications of genetic testing for SRNS patients, including prognostic information, genetic counseling, and potential implications for treatment decisions . The identification of novel disease-causing mutations has been made easier by advances in genetic sequencing technology, which have increased our understanding of the pathophysiology of SRNS and opened the door to personalised medicine strategies. Nevertheless, there are still difficulties in addressing the phenotypic variety seen in SRNS patients and converting genetic discoveries into practical treatments. To expedite the translation of genetic findings into novel therapeutic and diagnostic approaches for SRNS care, collaboration between doctors, researchers, and industry stakeholders is imperative. Despite receiving corticosteroid treatment, patients with steroid-resistant nephrotic syndrome (SRNS), a clinically heterogeneous illness, continue to experience proteinuria, hypoalbuminemia, edoema, and an increased risk of developing end-stage renal disease (ESRD). Steroid-sensitive nephrotic syndrome (SRNS) presents a major problem in clinical management because of its resistance to standard treatments and worse long-term results, even though SRNS frequently responds favourably to steroid therapy.[2].

The genetic foundation of SRNS has come to light more and more in recent years, as people with the disease have been found to carry a variety of genetic abnormalities. The proteins expressed in podocytes—specialized epithelial cells that line the glomerular basement membrane and are essential to preserving the integrity of the glomerular filtration barrier—are primarily affected by these alterations. Podocyte damage and malfunction are essential to the aetiology of leading to impaired filtration and proteinuria. ing the genetic components of SRNS has been crucial in understanding the pathophysiology of the condition itself. Through elucidating the molecular pathways perturbed in SRNS, scientists hope to pinpoint new therapeutic targets and create more potent remedies for this crippling illness. Moreover, genetic testing has become an important tool for prognostication, risk assessment, and individualised treatment planning for individuals with SRNS.[3].

The goal of this review is to present a thorough summary of the genetic discoveries on the aetiology of SRNS. We will go over the main genes and pathways linked to the illness, paying special attention to the functions of proteins unique to podocytes in preserving glomerular function. We will also discuss the clinical implications of genetic testing for patients with SRNS, including its usefulness in forecasting the course of the disease. Even though the genetic foundation of SRNS has been largely uncovered, a number of obstacles still need to be overcome. These include identifying new genes that cause the disease, clarifying genotype-phenotype relationships, and implementing genetic findings in clinical settings. Overcoming these obstacles and utilising genetic insights to create tailored treatments for SRNS care would require cooperation between researchers, doctors, and industry partners. A complex and diverse set of kidney conditions known as steroid-resistant nephrotic syndrome (SRNS) is marked by resistance to standard therapies and a significant risk of developing into end-stage renal disease (ESRD). Since many genetic variants linked to SRNS have been identified during the past few decades, a great deal of work has been made in understanding the disease's genetic underpinnings. The proteins expressed in podocytes—specialized cells essential for preserving the integrity of the glomerular filtration barrier—are primarily impacted by these alterations.[4].

The pathophysiological understanding of SRNS through genetics has shed light on the underlying molecular pathways causing podocyte damage and dysfunction. By figuring out these pathways, scientists hope to find new therapeutic targets and create SRNS medicines that work better. Additionally, genetic testing has become a valuable tool for risk stratification, prognostication, and personalized management of SRNS patients. However, there are still a number of obstacles to overcome before applying genetic discoveries to therapeutic settings. These include the discovery of new genes that cause disease, the clarification of genotype-phenotype relationships, and the creation of focused treatments grounded in genetic knowledge. Furthermore, the reported phenotypic diversity among patients with SRNS emphasises the necessity of customised methods to diagnosis and treatment . Overcoming these obstacles and utilising genetic insights to create tailored treatments for SRNS care would require cooperation between researchers, doctors, and industry partners. By incorporating genetic testing into standard clinical procedures, physicians can enhance patient-specific treatment plans, better identify risk factors, and eventually enhance outcomes for SRNS patients.[5].

Conclusion

In conclusion, a better knowledge of the pathophysiology of SRNS has been made possible by genetic insights into the disease and hold promise for the development of personalized approaches to diagnosis and treatment. Continued research efforts are needed to further elucidate the genetic basis of SRNS, validate novel therapeutic targets, and translate genetic discoveries into clinical practice, ultimately improving outcomes for patients with this challenging condition.

References

References

  1. Bhutani H, Smith V, Rahbari-Oskoui F, et al. A comparison of ultrasound and magnetic resonance imaging shows that kidney length predicts chronic kidney disease in autosomal dominant polycystic kidney disease. Kidney int. 2015;88(1):146-51.

    2. Indexed at, Google scholar, Cross ref

     

  2. Momeny M, Neshat AA, Hussain MA, et al . Learning-to-augment strategy using noisy and denoised data: Improving generalizability of deep CNN for the detection of COVID-19 in X-ray images. Comput Biol Med. 2021;136:104704.

    3. Indexed at, Google scholar , Cross ref

     

  3. Hohmann E. Editorial commentary: Big data and machine learning in medicine. J Arthrosc Relat Surg. 2022;38(3):848-9.

    4. Indexed at, Google scholar, Cross ref

     

  4. Sigmund M, Ferstl R. Panel vector autoregression in R with the package panelvar. Q Rev Econ Finance. 2021; 80:693-720.

    5. Indexed at, Google scholar

     

  5. Yang X, Le Minh H, Cheng KT, et al. Renal compartment segmentation in DCE-MRI images. Med Image Anal. 2016;32:269-80.

    6. Indexed at, Google scholar, Cross ref

     

  6. Cardenas CE, Yang J, Anderson BM, et al. Advances in auto-segmentation. Semin radiat oncol. 2019;29(3):185-197.

    7. Indexed at, Google scholar, Cross ref

     

  7. Kistler AD, Poster D, Krauer F, et al. Increases in kidney volume in autosomal dominant polycystic kidney disease can be detected within 6months. Kidney int. 2009;75(2):235-41.

    8. Indexed at, Google scholar, Cross ref

     

  8. Chapman AB, Devuyst O, Eckardt KU, et al. Autosomal-dominant polycystic kidney disease (ADPKD): Executive summary from a Kidney Disease: Improving Global Outcomes (KDIGO) Controversies Conference. Kidney Int. 2015;88(1):17-27.

    9. Indexed at, Google scholar, Cross ref

     

  9. Hohmann E. Editorial commentary: Big data and machine learning in medicine. J Arthrosc Relat Surg. 2022;38(3):848-9.

    10. Indexed at, Google scholar, Cross ref

     

  10. Momeny M, Neshat AA, Hussain MA, et al . Learning-to-augment strategy using noisy and denoised data: Improving generalizability of deep CNN for the detection of COVID-19 in X-ray images. Comput Biol Med. 2021;136:104704.

    11. Indexed at, Google scholar , Cross ref

Get the App