Lyme Disease Detection via Host Gene Expression Profiling
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Solution Overview
Problem
Current diagnostic methods for Lyme disease are inadequate for early detection, as they often rely on non-specific clinical findings and have low sensitivity, particularly in the acute stage, leading to delayed or inappropriate treatment.
Innovation Solution
The method involves measuring gene expression in peripheral blood mononuclear cells using transcriptome profiling and a panel of specific genes to calculate a Lyme disease score, enabling accurate detection of acute Lyme disease through RNA expression analysis and machine learning algorithms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If serological testing is used for Lyme disease diagnosis, then the method is simple and widely available, but the sensitivity is low in early acute infection (misses up to 40% of early cases)
Solution Approach 1:
The patent uses host gene expression profiles as an intermediary biomarker to detect Lyme disease indirectly. Instead of directly detecting Borrelia burgdorferi or antibodies (which have low sensitivity early in infection), the method measures the host's transcriptional response to infection. This intermediary approach allows detection of acute Lyme disease before serological markers become positive, achieving 94.4% sensitivity in early acute cases while maintaining a practical diagnostic workflow.
2Reliability
If nucleic acid testing is used to detect Borrelia burgdorferi, then direct pathogen detection is achieved, but sensitivity is limited due to low titers in blood (20-62% detection rate)
Solution Approach 1:
The patent replaces direct mechanical/pathological detection of low-abundance pathogen DNA with a molecular biology approach that detects high-abundance host RNA transcripts. By substituting the detection target from pathogen nucleic acid (low concentration) to host gene expression (high concentration), the method overcomes the limitation of low pathogen titers in blood, achieving superior sensitivity without requiring culture or direct pathogen visualization.
3Reliability
If transcriptome profiling of multiple genes is performed, then detection sensitivity and specificity are improved (94.4% sensitivity), but the complexity of the assay increases
Solution Approach 1:
The patent segments the complex transcriptome into a focused panel of 20 specific genes that are most informative for Lyme disease detection. Rather than analyzing the entire transcriptome (which would be highly complex), the method identifies and measures only the most relevant genes through targeted RNA sequencing or qPCR. This segmentation maintains high diagnostic accuracy (94.4% sensitivity) while reducing assay complexity to a manageable 20-gene panel that can be implemented with current clinical technologies.
Data Source
AI summary
The present disclosure relates to measuring gene expression of cells of a blood sample obtained from a mammalian subject suspected of having a tick-borne disease. In particular, the present disclosure provides tools for determining whether a human subject has acute Lyme disease by transcriptome profiling a peripheral blood mononuclear cell sample from the subject.