Mixed-Sample Nucleic Acid Quantification Using SNP and MAF Data
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Solution Overview
Problem
Monitoring the health status of transplanted organs, tissues, and cells in transplant recipients is complex when they carry additional genomes from genetically distinct contributors, especially in cases of multiple transplants or pregnancies, due to the lack of prior genotype knowledge.
Innovation Solution
A computer-implemented method and system for determining the amount of contributor-derived cell-free nucleic acids in a mixed sample from a transplant recipient, using single nucleotide polymorphism (SNP) data and minor allele frequency (MAF) information to group and quantify nucleic acids from multiple genetically distinct contributors without prior genotype knowledge.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional monitoring methods are used in transplant recipients with multiple genomes from genetically distinct contributors, then the complexity of monitoring increases due to lack of prior genotype knowledge, but the ability to accurately quantify contributor-derived nucleic acids deteriorates
Solution Approach 1:
The patent segments the complex mixture of nucleic acids from multiple genetically distinct contributors by utilizing SNP-specific MAF information. Each SNP locus is analyzed independently to determine which contributor's genome is represented, allowing the complex mixed sample to be divided into distinguishable genetic components without requiring prior genotype knowledge of the contributors.
Solution Approach 2:
The patent changes the monitoring approach from using absolute genotype calls (which require prior knowledge) to using relative MAF parameters at SNP loci. By measuring the frequency of minor alleles across multiple SNPs and comparing them against expected MAF distributions, the system can quantify contributor-derived nucleic acids based on statistical parameters rather than requiring predetermined genetic information about the contributors.
2Adaptability or versatility
If prior genotype knowledge is required for monitoring, then the analysis becomes simpler, but the method loses adaptability to recipients with unknown or multiple genomic contributors
Solution Approach 1:
The patent enables the system to self-determine the genetic contributions by using MAF information inherent in the sequenced data itself. The method automatically identifies which SNPs belong to which contributor based on their MAF patterns, eliminating the need for external prior genotype knowledge. The system serves itself by deriving all necessary information from the observed MAF distributions across the SNP panel.
Solution Approach 2:
The patent introduces MAF information as an intermediary parameter that mediates between the raw sequencing data and the final quantification results. Instead of directly interpreting genotype data (which requires prior knowledge), the MAF values at SNP loci serve as an intermediate representation that can be statistically compared to determine contributor proportions, bridging the gap between data collection and analysis without requiring predetermined genetic information.
3Measurement precision
If a comprehensive SNP panel is used to distinguish all contributors, then the measurement precision improves, but the data processing complexity increases
Solution Approach 1:
The patent applies partial action by analyzing only the MAF information at SNP loci that are informative for differentiation, rather than processing every possible genetic parameter. By focusing on MAF deviations at specific SNP positions and using statistical thresholds to identify contributor-specific patterns, the system achieves accurate quantification without requiring exhaustive analysis of all genomic data, thereby reducing processing time while maintaining precision.
Data Source
AI summary
Disclosed herein are computer-implemented systems, kits, and methods for outputting an amount of contributor-derived nucleic acids in a biological sample, from a transplant recipient who has received at least two transplants, that comprises nucleic acids from at least three genetically distinct contributors. The amount of contributor-derived nucleic acids may be useful in monitoring the status of a transplant for, e.g., assessing a risk of transplant rejection. In some examples, the at least three genetically distinct contributors may comprise a recipient genomic contributor, a first transplant donor genomic contributor, and a second transplant donor genomic contributor. For example, the systems and methods determine an estimated percentage of the contributor-derived nucleic acids and/or estimated percentage of the fetal-derived nucleic acids.