Fetal cfDNA Variant Assignment Using Fragment Size and Fetal Fraction
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Solution Overview
Problem
Current non-invasive prenatal screening methods have low resolution and require invasive procedures for comprehensive genetic screening of the fetal genome, posing risks to the mother and fetus.
Innovation Solution
A high-resolution non-invasive fetal sequencing (NIFS) method using probabilistic models to assign maternal or fetal origin to genetic variants in cell-free DNA based on fetal fraction and DNA fragment size, enabling accurate detection of single nucleotide variants, indels, and copy number variations without paternal or separate maternal samples.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If non-invasive prenatal screening methods are used, then safety is improved by eliminating invasive procedures, but measurement precision deteriorates due to low resolution in detecting fetal genetic variants
Solution Approach 1:
The patent transforms the cfDNA sequencing data by applying probabilistic models that incorporate multiple parameters including fetal fraction estimates and DNA fragment size distributions. This allows high-resolution detection of fetal genetic variants from low-concentration fetal DNA in maternal blood, resolving the precision limitation while maintaining non-invasive safety
Solution Approach 2:
The patent uses computational probabilistic models as intermediaries to interpret the mixed maternal-fetal cfDNA sequencing data. These models act as mediators that deconvolute the composite signal to identify fetal-specific variants, enabling high-resolution fetal genotyping without direct fetal sampling
2Measurement precision
If comprehensive genetic screening is performed on cfDNA, then measurement precision is improved for detecting fetal variants, but device complexity increases due to need for multiple samples and complex analysis
Solution Approach 1:
The patent extracts and utilizes specific characteristics of fetal cfDNA fragments (particularly fragment size distribution) from the mixed maternal-fetal cfDNA pool. By focusing on these distinctive features through probabilistic modeling, the method achieves comprehensive fetal genetic screening using only maternal blood samples, eliminating the need for complex multi-sample processing
Solution Approach 2:
The probabilistic modeling framework serves multiple functions simultaneously: it estimates fetal fraction, characterizes fragment size distributions, and identifies fetal genetic variants. This multi-functional approach enables comprehensive fetal genomic analysis from a single maternal blood sample, reducing overall system complexity
Data Source
AI summary
Provided herein are computer-implemented methods for assigning maternal or fetal origin to one or more genetic variants in cell free DNA (cfDNA) from a sample from a pregnant mammal, preferably a pregnant human, using a probabilistic model for assigning maternal or fetal origin to genetic variants in DNA from a sample obtained from a pregnant mammal, wherein the model assigns maternal or fetal origin based on a combination of fetal fraction and DNA fragment size.