EXT1/EXT2 Kidney Tissue Markers for Membranous Nephropathy Risk
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Solution Overview
Problem
Current methods fail to accurately predict the progression of membranous nephropathy to end-stage kidney disease, limiting effective treatment strategies.
Innovation Solution
Identify kidney tissue expression of EXT1 and EXT2 polypeptides using immunohistochemistry or laser microdissection and mass spectrometry to classify membranous nephropathy as likely or unlikely to progress to end-stage kidney disease, and administer immunosuppressive agents like corticosteroids or Rituximab to slow progression.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current diagnostic methods are used to identify membranous nephropathy, then diagnosis can be made, but accurate prediction of disease progression to end-stage kidney disease cannot be achieved
Solution Approach 1:
The patent performs preliminary classification of membranous nephropathy into EXT1/EXT2-positive and EXT1/EXT2-negative types before treatment initiation. This preliminary action enables accurate prediction of disease progression and guides appropriate treatment selection, resolving the contradiction between diagnostic capability and progression prediction accuracy.
Solution Approach 2:
The patent introduces EXT1 and EXT2 polypeptide detection as an intermediary marker system. This intermediary enables the connection between initial diagnosis and future disease progression outcomes, allowing clinicians to predict progression to end-stage kidney disease with high accuracy while maintaining reliable treatment strategy formulation.
2Reliability
If immunosuppressive agents are administered without disease progression classification, then treatment is provided, but treatment effectiveness is reduced due to inability to identify high-risk patients
Solution Approach 1:
The patent implements preliminary risk stratification based on EXT1/EXT2 polypeptide status before administering immunosuppressive therapy. This preliminary classification identifies high-risk patients likely to progress to end-stage kidney disease, ensuring that intensive treatment is targeted to those who will benefit most, thereby improving overall treatment effectiveness without excessive complexity.
3Measurement precision
If EXT1 and EXT2 polypeptide detection is implemented, then accurate disease progression prediction is achieved, but diagnostic process complexity increases
Solution Approach 1:
The patent employs EXT1 and EXT2 polypeptide detection as intermediary biomarkers that bridge initial diagnosis and progression prediction. These intermediaries provide accurate progression prediction through relatively straightforward detection methods, resolving the contradiction between achieving high measurement precision and maintaining acceptable diagnostic process complexity.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Accurately predicts disease progression and enables targeted treatment to reduce the risk of end-stage kidney disease, allowing for effective management of membranous nephropathy.
Implementation Method 1
determining if kidney tissue from the mammal expresses a polypeptide, wherein the polypeptide is an exostosin 1 (EXT1) polypeptide or an exostosin 2 (EXT2) polypeptide
Implementation Method 2
laser microdissection and mass spectrometry
Implementation Method 3
laser microdissection and mass spectrometry
Data Source
Figure 1
Figure 2A~2F
Figure 3A~3F
AI summary
This document provides methods and materials involved in identifying and treating mammals (e.g., humans) having membranous nephropathy. For example, methods and materials for determining the likelihood that a mammal (e.g., a human) having membranous nephropathy (e.g., lupus membranous nephropathy) will progress to end stage kidney disease are provided. Methods and materials for treating membranous nephropathy likely to develop end stage kidney disease also are provided.