Gene Expression Endotyping for Lupus Nephritis Stage Classification
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Solution Overview
Problem
The immune mechanisms of lupus nephritis (LN) disease progression and risk factors for end-stage renal disease are poorly understood, necessitating a better understanding of molecular pathways to identify and optimize therapies.
Innovation Solution
A method for assessing LN disease state using transcriptomic analysis of lupus-prone mice to identify molecular pathways and risk factors, employing gene expression-based clustering to classify disease stages into molecular endotypes, and developing targeted therapies to stop, slow, or reverse disease progression.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If gene expression-based clustering is used to classify LN disease stages, then disease classification accuracy is improved, but the complexity of the analysis system increases
Solution Approach 1:
The patent segments the LN disease spectrum into distinct molecular endotypes (acute LN, transitional LN, chronic LN) based on gene expression profiles. This segmentation allows for precise classification while managing complexity by focusing on biologically relevant disease stages rather than attempting to analyze all possible disease states simultaneously.
Solution Approach 2:
The patent utilizes changes in gene expression parameters to define and distinguish different LN endotypes. By monitoring specific gene expression thresholds and patterns, the system achieves accurate disease stage classification without requiring complex multi-parameter analysis, thus improving precision while controlling system complexity.
2Loss of information
If transcriptomic analysis of lupus prone mice is performed, then understanding of molecular pathways is improved, but the time required for analysis increases
Solution Approach 1:
The patent performs preliminary transcriptomic analysis in lupus-prone mice to identify and validate molecular pathways and risk factors before applying these insights to human LN patients. This preliminary action in a controlled animal model accelerates the overall discovery process by pre-characterizing disease mechanisms that would otherwise require extensive time-consuming human studies.
Solution Approach 2:
The patent uses mouse models as copies of human LN disease to study molecular pathways. The mouse model replicates key features of human LN, allowing researchers to perform rapid transcriptomic analysis and identify biomarkers that can then be validated in human patients, thereby reducing the total time required for disease mechanism elucidation.
3Reliability
If targeted therapy is developed based on molecular endotypes, then treatment effectiveness is improved, but the difficulty of identifying and optimizing therapies increases
Solution Approach 1:
The patent applies local quality by developing targeted therapies specific to each LN molecular endotype (acute, transitional, chronic) rather than using a single universal treatment approach. By tailoring therapy to the specific molecular characteristics and disease stage of each patient subset, treatment effectiveness is improved while the complexity of therapy selection is managed through clear endotype-specific guidelines.
Solution Approach 2:
The patent incorporates feedback mechanisms where gene expression profiles are continuously monitored to assess response to therapy and guide treatment optimization. This feedback loop allows for real-time adjustment of targeted therapies based on disease progression or response, improving treatment effectiveness while simplifying the optimization process through data-driven decision making.
Data Source
AI summary
A method for assessing a lupus nephritis disease state of a patient, the method comprising: analyzing a data set comprising or derived from gene expression measurement data of at least 2 genes or human orthologs thereof selected from the genes listed in Tables 19-1 to 19-36, Tables 19A-1 to 19A-36, Table 20, Table 21, Table 22, Tables 23-1 to 23-28, Tables 25-1 to 25-32, Tables 26-1 to 26-60, Tables 27-1 to 27-48, and Tables 28-1 to 28-22 in a biological sample from the patient, to classify the lupus nephritis disease state of the patient.