Archives of Science
Open Access

Our Group organises 3000+ Global Conferenceseries Events every year across USA, Europe & Asia with support from 1000 more scientific Societies and Publishes 700+ Open Access Journals which contains over 50000 eminent personalities, reputed scientists as editorial board members.

Open Access Journals gaining more Readers and Citations
700 Journals and 15,000,000 Readers Each Journal is getting 25,000+ Readers

This Readership is 10 times more when compared to other Subscription Journals (Source: Google Analytics)
  • Short Communication   
  • Arch Sci 7: 164, Vol 7(4)
  • DOI: 10.4172/science.1000164

Analyzing the Proteomic Patterns of Hypertensive Nephropathy: Insights from Archival Core Human Kidney Biopsies

Kenji Takahashi*
Department of Physiology, School of Medicine, Keio University, Shinanomachi, Tokyo, Japan
*Corresponding Author: Kenji Takahashi, Department of Physiology, School of Medicine, Keio University, Shinanomachi, Tokyo, Japan, Email: Takahashi556@gmail.com

Received: 03-Jul-2023 / Manuscript No. science-23-103227 / Editor assigned: 05-Jul-2023 / PreQC No. science-23-103227 / Reviewed: 19-Jul-2023 / QC No. science-23-103227 / Revised: 24-Jul-2023 / Manuscript No. science-23-103227 / Published Date: 31-Jul-2023 DOI: 10.4172/science.1000164

Abstract

Hypertensive nephropathy is a common cause of chronic kidney disease and end-stage renal disease worldwide.However, the molecular mechanisms underlying this condition remain poorly understood. Proteomic analysis hasemerged as a powerful tool to investigate complex protein networks in various diseases, including renal disorders.Archival core human kidney biopsies, obtained from patients with a documented history of hypertension and renalimpairment, offer a unique opportunity to study the proteomic patterns associated with hypertensive nephropathy.By employing advanced proteomic techniques, researchers can analyze the proteome of these biopsies and identify differentially expressed proteins and pathways related to the disease. This article provides insights into the potential of proteomic analysis in hypertensive nephropathy, including the identification of biomarkers for early diagnosis andmonitoring, and the elucidation of molecular pathways involved in disease progression. Despite challenges associatedwith limited sample availability and protein degradation over time, advancements in proteomic technologies andbioinformatics tools hold great promise for further understanding and managing hypertensive nephropathy.

Keywords

Proteomic analysis; chronic kidney disease; Biomarkers; Proteomic technologies

Introduction

Hypertensive nephropathy, also known as hypertensive renal disease, is a common cause of chronic kidney disease (CKD) and endstage renal disease (ESRD) worldwide. It is characterized by chronic high blood pressure that leads to structural and functional changes in the kidneys [1]. Despite its prevalence, the molecular mechanisms underlying hypertensive nephropathy remain incompletely understood. In recent years, proteomic analysis has emerged as a powerful tool to unravel the complex protein networks involved in various diseases, including renal disorders [2].

Archival core human kidney biopsies present a unique opportunity to gain valuable insights into the proteomic patterns associated with hypertensive nephropathy [3]. These biopsies, obtained from patients with a documented history of hypertension and renal impairment, provide a retrospective view of the disease progression. By employing advanced proteomic techniques, researchers can analyze the proteome, i.e., the entire set of proteins expressed in a tissue, and identify differentially expressed proteins and pathways associated with hypertensive nephropathy [4].One of the primary goals of proteomic analysis in hypertensive nephropathy is to identify potential biomarkers that can aid in the early diagnosis and monitoring of the disease [5]. Early detection is crucial for implementing interventions to slow disease progression and prevent the development of ESRD. By comparing the proteomic profiles of hypertensive nephropathy patients to those with other renal pathologies or healthy individuals, researchers can pinpoint specific proteins or protein patterns that are unique to hypertensive nephropathy. These biomarkers can then be further validated and translated into clinical practice, potentially revolutionizing the management of this condition [6].

Discussion

Moreover, proteomic analysis can provide valuable insights into the underlying molecular pathways implicated in the pathogenesis of hypertensive nephropathy [7]. By identifying differentially expressed proteins and mapping them to known biological pathways, researchers can unravel the intricate molecular networks involved in the disease.

This knowledge can aid in understanding the mechanisms leading to renal damage, inflammation, fibrosis, and other pathological processes associated with hypertensive nephropathy [8]. Furthermore, it can pave the way for the development of targeted therapies aimed at modulating these pathways and ameliorating disease progression.One of the challenges in proteomic analysis of archival core human kidney biopsies is the limited availability of samples and potential degradation of proteins over time [9]. However, advancements in proteomic technologies, such as mass spectrometry and protein microarrays, have enabled the analysis of small sample sizes and degraded proteins, thereby maximizing the information that can be obtained from these valuable specimens. Additionally, the integration of bioinformatics tools and data mining algorithms allows for the identification of potential protein-protein interactions and key signaling pathways involved in hypertensive nephropathy [10].

Conclusion

Analyzing the proteomic patterns of hypertensive nephropathy using archival core human kidney biopsies offers a unique opportunity to gain insights into the molecular mechanisms underlying this prevalent renal disorder. The identification of specific protein markers and pathways associated with the disease can facilitate early diagnosis, risk stratification, and the development of targeted therapies. While challenges exist, continued advancements in proteomic technologies and bioinformatics tools will undoubtedly enhance our understanding of hypertensive nephropathy and potentially transform patient care in the future.

References

  1. Pantanowitz L (2012) Experience with multimodality telepathology at the University of Pittsburgh Medical Center. J Pathol Inf 3:45-55.
  2. Indexed at, Google Scholar, Crossref

  3. Dietz RL, Hartman DJ (2019) Systematic review of the use of telepathology during intraoperative consultation. Am J Clin Pathol 153: 198–209.
  4. Indexed at, Google Scholar, Crossref

  5. Azancot M A (2014) the reproducibility and predictive value on outcome of renal biopsies from expanded criteria donors. Kidney Int 85: 1161–1168.
  6. Indexed at, Google Scholar, Crossref

  7. Liapis H (2017) Banff histopathological consensus criteria for preimplantation kidney biopsies. Am J Transpl 17: 140–152
  8. Indexed at, Google Scholar, Crossref

  9. Barisoni L (2012) Novel quantitative method to evaluate globotriaosylceramide inclusions in renal per tubular capillaries by virtual microscopy in patients with Fabry disease. Arch Pathol Lab Med 136: 816–824.
  10. Indexed at, Google Scholar, Crossref

  11. Pantanowitz L, Szymas J, Yagi Y (2012) Whole slide imaging for educational purposes. J Pathol Inf 3: 46 -48.
  12. Indexed at, Google Scholar, Crossref

  13. Saco A, Bombi JA, Garcia A (2016) Current status of whole-slide imaging in education. Pathobiology 83:79–88.
  14. Indexed at, Google Scholar, Crossref

  15. Kumar N, Gupta R (2020) Whole slide imaging (WSI) in pathology: current perspectives and future directions. J Digit Imaging 25: 55-58.
  16. Indexed at, Google Scholar, Crossref

  17. Barisoni L (2017) Digital pathology imaging as a novel platform for standardization and globalization of quantitative nephropathology. Clin Kidney J 10: 176–187.
  18. Indexed at, Google Scholar, Crossref

  19. Barisoni L (2013) Digital pathology evaluation in the multicenter nephrotic syndrome study network (NEPTUNE). Clin J Am Soc Nephrol 8: 1449–1459.
  20. Indexed at, Google Scholar, Crossref

Citation: Takahashi K (2023) Analyzing the Proteomic Patterns of HypertensiveNephropathy: Insights from Archival Core Human Kidney Biopsies. Arch Sci 7: 164. DOI: 10.4172/science.1000164

Copyright: © 2023 Takahashi K. This is an open-access article distributed underthe terms of the Creative Commons Attribution License, which permits unrestricteduse, distribution, and reproduction in any medium, provided the original author andsource are credited.

Top