Deciphering cell type-specific causal genetic effects on brain imaging-derived phenotypes and disorders with
Anyi Yang1, Xingzhong Zhao1, Xing-Ming Zhao1,2,3,4,5,6
1Department of Neurology, Zhongshan Hospital and Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.
Plos Computational Biology
|June 17, 2026
Summary
This study introduces a novel single-cell Mendelian randomization framework to map cell type-specific genetic causes of brain imaging phenotypes and disorders. It identifies key genes influencing brain traits, offering insights into biological mechanisms.
Area of Science:
- Neurogenetics
- Systems Biology
- Genomics
Background:
- Understanding the genetic underpinnings of brain-associated phenotypes is essential for elucidating biological mechanisms.
- Complex brain phenotypes, including imaging-derived phenotypes (IDPs) and brain disorders and behaviors (DBs), result from intricate genetic and cellular interactions.
Purpose of the Study:
- To develop and apply a single-cell Mendelian randomization framework to infer cell type-specific causal relationships between gene expression and brain-associated complex phenotypes.
- To identify cell type-specific causal genes (eGenes) influencing IDPs and DBs.
- To explore the spatiotemporal expression patterns and pleiotropy of these causal genes.
Main Methods:
- Integration of single-cell expression quantitative trait loci (cis-eQTLs) with genome-wide association study (GWAS) findings.
- Application of a single-cell Mendelian randomization approach to analyze gene expression and phenotype associations.
- Characterization of cell type specificity, pleiotropy, and spatiotemporal expression of identified causal genes.
Main Results:
- Identification of 254 and 217 cis-eQTL target genes (eGenes) potentially causally influencing 112 IDPs and 26 DBs across eight cell types, respectively.
- Demonstration of strong cell type specificity and varied pleiotropy for these causal eGenes.
- Revelation of putative causality routes and coordinated associations among brain-associated phenotypes based on causal eGene expression.
Conclusions:
- The study provides a comprehensive catalog of cell type-specific causal eGenes for brain structures, disorders, and behaviors.
- The developed framework enables large-scale analysis of genetic effects on complex brain phenotypes.
- Findings offer valuable insights into the genetic architecture and biological mechanisms of brain function and dysfunction.
