Establishing the relationship between brain cellular senescence and brain structure.

Significant correlations between neuroimaging-associated and cellular senescence gene expression signatures were observed in excitatory neurons and microglia, especially for volume-related neuroimaging features.

• The study integrated structural neuroimaging with gene and protein expression data from prefrontal cortex tissue collected from individuals who underwent neurosurgery.
• Cell-type-specific signatures were identified and replicated in several independent datasets.
• Correlations were particularly prominent for volume-related neuroimaging features rather than other structural measures.
• Two specific cell types — excitatory neurons and microglia — showed the strongest associations between neuroimaging and senescence signatures.

Associations between neuroimaging-related and senescence-related gene expression signatures in excitatory neurons were observed in an independent brain gene expression dataset from individuals below 5 years of age.

• The finding was replicated in a developmental dataset comprising individuals younger than 5 years of age.
• This observation implies a role for cellular senescence during brain development, not only during aging.
• The replication in young individuals suggests the molecular mechanisms are not exclusive to late-life brain changes.
• Excitatory neurons showed this association in both the primary neurosurgery cohort and the independent developmental dataset.

Brain cellular senescence and brain atrophy share underlying biological mechanisms as revealed by integrating structural neuroimaging with prefrontal cortex gene and protein expression data.

• Both cellular senescence and brain atrophy are associated with brain aging, motivating the hypothesis that they share biological mechanisms.
• Prefrontal cortex tissue was collected from individuals who underwent neurosurgery, providing a unique resource linking in vivo neuroimaging with ex vivo molecular data.
• Gene and protein expression data were both utilized to characterize the molecular signatures.
• The study describes the approach as 'a deep characterization of molecular signatures linking brain structure and cellular senescence across different life stages.'

Mechanisms supporting brain development may also contribute to volume reduction observed during aging.

• The convergence of developmental and aging findings across excitatory neurons supports a shared mechanistic framework.
• This conclusion was drawn from the observation that senescence-neuroimaging associations found in adult surgical patients were also present in children under 5 years old.
• The study suggests senescence-related processes are not solely degenerative but may have roles in normal developmental biology.
• This interpretation bridges findings from neurosurgery patients with an independent pediatric gene expression dataset.

Cell-type-specific gene expression signatures associated with both neuroimaging features and cellular senescence were identified and replicated in several independent datasets.

• Replication across multiple independent datasets strengthens confidence in the identified signatures.
• The signatures were cell-type-specific, meaning they differed across distinct brain cell populations.
• Both gene expression and protein expression data from the prefrontal cortex were used in the primary analyses.
• The replication strategy included datasets beyond the primary neurosurgery cohort, including at minimum a pediatric brain gene expression dataset.