PBMC Transcriptomic Signatures for Predicting IPF FVC Decline

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Solution Overview

Problem

Current clinical models fail to accurately predict lung function decline in idiopathic pulmonary fibrosis (IPF), hindering the development of effective therapies, as they rely on cross-sectional data that does not account for dynamic gene expression changes associated with disease activity.

Innovation Solution

Development of a transcriptomic predictor using longitudinal within-patient gene expression changes in peripheral blood mononuclear cells (PBMCs) to identify patients at risk for forced vital capacity (FVC) decline, utilizing a set of genes including ALDH4A1, APTX, CNR2, GYPA, ITLN1, MAZ, MSR1, NT5E, PAWR, PLA2G4A, and PNMA5, to generate a prognostic signature for FVC decline.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Device complexity

If clinical prediction models using cross-sectional data are used, then model simplicity is maintained, but prediction accuracy for FVC decline deteriorates

Engineering Contradiction:

Improvemodel complexityVSAvoidprediction accuracy

Core Design Contradiction:

Device complexityVSMeasurement precision

Solution Approach 1:

The patent transitions from static cross-sectional data to dynamic longitudinal data, tracking gene expression changes over time within patients. This dynamic approach captures the evolving nature of fibrosis activity, enabling accurate prediction of FVC decline while maintaining model interpretability through temporal patterns rather than complex multi-variable analysis

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The patent identifies and measures gene expression changes that occur before FVC decline becomes apparent clinically. By detecting molecular markers of fibrosis activity in advance, the model enables early intervention and accurate prediction of future lung function deterioration, transforming reactive clinical assessment into proactive detection

Inventive Principle:

Principle #10Preliminary action

2Reliability

If FVC decline is used as a marker, then disease severity is captured, but disease activity and modifiability are not reflected

Engineering Contradiction:

Improvemarker validityVSAvoiddisease activity detection

Core Design Contradiction:

ReliabilityVSAdaptability or versatility

Solution Approach 1:

The patent introduces gene expression profiles as an intermediary marker that mediates between clinical FVC measurements and underlying disease processes. These molecular markers reflect active fibrosis pathways and can be modulated by therapy, providing a bridge between structural lung damage and dynamic disease activity that guides treatment decisions

Inventive Principle:

Principle #24Intermediary (Mediator)

Data Source

PatentUS12480960B2Compositions and methods for predicting lung function decline in idiopathic pulmonary fibrosis

Publication Date: 2025.11.25 UNIV OF VIRGINIA PATENT FOUND

AI summary

Provided are methods for generating prognostic signatures for subject diagnosed with Idiopathic Pulmonary Fibrosis (IPF) with respect to decline in lung Forced Vital Capacity (FVC). The methods can include determining first expression levels for one or more genes as set forth herein in a first biological sample obtained from a subject diagnosed with IPF, determining a second expression level for the same one or more genes in a second biological sample obtained from the subject, and comparing the first and second expression levels for the one or more genes to provide a prognostic signature. The first and second biological samples can include peripheral blood mononuclear cells (PBMCs) and/or nucleic acids extracted from PBMCs. Also provided are methods for classifying subjects with IPF as being at risk for FVC decline, for identifying and treating at risk subjects, and for monitoring the progress of treatments.