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Updated: Sep 11, 2026
Integrated Photoacoustic, Ultrasound, and Angiographic Tomography (PAUSAT) for NonInvasive Whole-Brain Imaging of Ischemic Stroke
Published on: June 2, 2023
Integrative transcriptomic- neuroimaging analysis reveals polygenic correlates of interhemispheric functional
Ri-Bo Chen1,2, Yu-Xuan He3, Xin Huang4
1School of Medical Engineering, Henan Medical University, Xinxiang, Henan, China.
Background:
Functional magnetic resonance imaging (fMRI) has revealed abnormal brain activity patterns in stroke patients, yet the genetic correlates underlying functional homotopy - defined as synchronized spontaneous activity between bilateral homologous brain regions - remain poorly characterized. This study investigates the genetic basis of voxel-mirrored homotopic connectivity (VMHC) abnormalities in stroke patients.
Methods:
We analyzed resting-state fMRI data from 50 stroke patients and 50 healthy controls (HC) to quantify VMHC. Spatial transcriptome-neuroimaging correlations were established using the Allen Human Brain Atlas (AHBA) to identify VMHC-associated genes. Transcriptomic analyses combined pathway-centric functional annotation (DAVID) with protein-protein interaction (PPI) network modeling (STRING v12.0).
Results:
Stroke patients exhibited significantly reduced VMHC in the rectus gyrus, superior temporal gyrus, middle occipital gyrus, cuneus, and right calcarine/left posterior cingulate gyrus (p < 0.05, GRF-corrected). VMHC alterations correlated positively and negatively with 1,198 genes each. Transcriptomic profiling revealed significant enrichment in synaptic vesicle trafficking, mitochondrial energy metabolism, and neuroinflammation-related pathways. PPI mapping uncovered multi-tiered networks with hub genes including BRCA1, CDK9, ACTB, and ATP6V1A/F involved in transcriptional regulation, cytoskeletal dynamics, and vesicular acidification.
Conclusion:
This multimodal integration study elucidates polygenic correlates of post-stroke VMHC abnormalities, demonstrating that interhemispheric coordination may depend on synergistic interactions among functionally diverse gene clusters. Our findings provide a molecular framework for understanding post-stroke neural network reorganization and offer a link between functional neuroimaging phenotypes and gene expression, though all associations remain correlational and require mechanistic validation.
