The Same Risk Gene, Different Effects Across Brain Cells: Nature Study Identifies Cell-Specific Disease Mechanisms

The same disease-risk gene can act differently depending on the type of brain cell, according to a new study.

According to the international journal Nature on the 23rd (local time), a team led by Professor Panos Roussos of the Icahn School of Medicine at Mount Sinai in the United States used single-nucleus transcriptome analysis to confirm that genes linked to psychiatric and neurological disorders cause abnormalities only in specific brain cells. Researcher Woo Jeon-i participated as a co-first author.

Most genetic risk for brain disorders such as schizophrenia, bipolar disorder and Alzheimer’s disease lies in noncoding regions that do not produce proteins. These regions regulate gene expression levels in specific cells.

Previous studies measured average expression levels by homogenizing entire brain tissue. But because neurons, astrocytes, microglia and oligodendrocytes each have different roles, it was difficult to determine which cells showed changes based on average values.

The research team used single-nucleus RNA sequencing data from the dorsolateral prefrontal cortex made available by the PsychAD Consortium. The data include more than 6 million cell nuclei from 1,494 donors of European, African and admixed American ancestry.

Using these data, the team built “single-nucleus transcriptome imputation models” (snTIMs) for major brain cell types. The models predict gene expression levels in each brain cell based on an individual’s genotype, then combine those predictions with genome-wide association study (GWAS) data for diseases to determine which cells show abnormalities in specific genes.

When the models were applied to GWAS data for 12 psychiatric and neurodegenerative disorders, they identified thousands of new gene-phenotype associations that had not been detected at all in conventional tissue-average analyses. Some signals appeared only in excitatory neurons, while others appeared only in astrocytes, microglia or oligodendrocytes.

The team also conducted cross-validation in the Million Veteran Program, which includes about 600,000 participants. The results showed that cell-type-specific regulatory abnormalities were consistent across multiple racial groups, including people of African and Latino ancestry, indicating that the findings were not chance results limited to a particular racial group.

The study is also expected to help guide the development of treatment strategies. Knowing which cells a risk gene acts in can help identify points for intervention, and genes with abnormalities in only a specific cell subtype could allow researchers to narrow targets and reduce systemic side effects.

The team said the imputation models extend single-nucleus sequencing data to the broader population, providing “virtual single-cell readouts” for individuals. However, the team added that the model predictions will require final confirmation through future functional experiments.