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High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions
Published on: March 5, 2022
BrainEnrich: Revealing Biological Insights for Imaging-Derived Phenotypes Through Transcriptomic Enrichment.
Zhipeng Cao1,2, Dekang Yuan3, Jinmei Qin1
1Shanghai Xuhui Mental Health Center, Shanghai, China.
Human Brain Mapping
|July 13, 2026
Summary
BrainEnrich, an R package, links brain gene expression with imaging data for functional enrichment analysis. It enables novel individual-level analysis, revealing molecular signatures of brain traits and inter-individual variability.
Area of Science:
- Neuroscience
- Genomics
- Bioinformatics
Background:
- Imaging transcriptomics faces challenges in functional enrichment analysis.
- Integrating whole-brain gene expression with in vivo imaging-derived phenotypes (IDPs) is crucial.
Purpose of the Study:
- Introduce BrainEnrich, an R package for spatial coupling analysis between molecular profiles and IDPs.
- Enable group-level and novel individual-level enrichment analysis.
Main Methods:
- Integrates Allen Human Brain Atlas (AHBA) data with IDPs.
- Offers flexible association methods, aggregation strategies, and predefined gene sets.
- Includes competitive and self-contained null models for statistical power examination.
Main Results:
- BrainEnrich controls Type 1 error and retains sensitivity in simulations.
- Group-level analysis associated major depressive disorder cortical thickness with synaptic signaling and lipid regulation pathways.
- Individual-level analysis showed associations between synaptic gene sets and cognitive measures.
Conclusions:
- BrainEnrich provides a flexible framework for molecular contextualization of IDPs.
- Enables exploration of inter-individual variability in molecular signatures.
- Facilitates integration of macro-level IDPs with micro-level transcriptomic profiles.
