Gene Network Diagnosis Using Leukocyte Expression in ASD
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Solution Overview
Problem
Current methods struggle to elucidate the molecular mechanisms of Autism Spectrum Disorder (ASD) due to the heterogeneous genetic landscape and limited availability of early-age brain tissue, making it difficult to understand the molecular changes and their relationship with clinical heterogeneity.
Innovation Solution
A systems biology approach using leukocyte transcriptomic data from ASD and typically developing toddlers to identify a dysregulated gene network that is conserved in prenatal brain development, linked to ASD risk genes, and correlates with clinical severity, employing co-expression analysis and network construction methods.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If postmortem brain tissue from older individuals is used for study, then sufficient tissue is available for analysis, but the tissue is from ages beyond when rASD genes are at peak expression and the disorder begins
Solution Approach 1:
The patent uses leukocytes as an intermediary tissue to study molecular changes relevant to ASD. Since leukocytes are continuously regenerating and can be obtained from living toddlers, they serve as a mediator that allows researchers to study gene expression patterns without needing to obtain brain tissue from deceased individuals. The leukocyte transcriptome reflects the molecular changes occurring in the developing brain during the critical early period when rASD genes are most active.
2Measurement precision
If focused studies on single rASD genes are conducted, then molecular mechanisms of individual genes can be elucidated, but the highly heterogeneous genetic landscape and network-level interactions remain unclear
Solution Approach 1:
The patent merges the study of multiple individual rASD genes into a unified network analysis framework. By analyzing transcriptomic data from leukocytes, the study simultaneously examines the expression patterns of hundreds of rASD genes and their interactions, revealing network-level molecular organization. This approach combines information about individual gene functions with their collective behavior in biological networks, providing a comprehensive view of ASD pathogenesis that neither focused single-gene studies nor purely statistical genome-wide association studies can achieve alone.
Data Source
AI summary
The invention provides for the detection of a perturbed gene network, which includes highly expressed genes during fetal brain development, which is dysregulated in neuron models of autism spectrum disorder (ASD). High-confidence ASD risk genes are upstream regulators of the network modulating RAS/ERK, PI3K/AKT, and WNT//β-catenin signaling pathways. The invention demonstrates how the heterogeneous genetics of ASD can dysregulate a core network to influence brain development at prenatal and very early postnatal ages and, thereby, the severity of later ASD symptoms. The invention provides a model for diagnosis, prognosis determination, and optionally treatment and monitoring, for any disease by comparing molecular marker patterns in non-affected tissues in a subject with healthy controls to determine a dysregulated network in the subject based on a co-expression pattern of interacting genes.