Neuroanatomical signatures of chronotype in young adults

Despite extensive evidence linking chronotype to behavioral and physiological outcomes, its structural neuroanatomical correlates, especially in healthy young adults, remain insufficiently characterized, and multimodal structural investigations integrating Voxel-based morphometry (VBM), cortical thickness (CT), and brain-age metrics are still limited. We examined whether chronotype—preference for early or late sleep–wake timing—is associated with structural brain variation in 136 healthy young adults (68 early chronotypes [EC], 68 late chronotypes [LC]) using high-resolution MRI. Early and late chronotypes were defined using the Morningness–Eveningness subscale of the Chronotype Questionnaire (ChQ-ME): early chronotype (EC) scores 11–21 and late chronotype (LC) scores 22–32. The VBM analyses were conducted to assess gray and white matter morphology, complemented by CT analyses and estimation of brain-predicted age difference (Brain-PAD) as an index of biological brain aging. Sensitivity analyses additionally modeled ChQ-ME as a continuous predictor. Primary voxel-wise VBM analyses did not identify between-group differences in gray or white matter morphology that survived family-wise error (FWE) correction (p < 0.05). In pre-specified exploratory analyses (voxel-wise p < 0.001, uncorrected; cluster-level false discovery rate [FDR] correction q < 0.05), late chronotype (LC) participants showed an exploratory left cerebellar/occipital cluster with lower gray matter volume. Region-wise CT differences were nominal (p < 0.05) and did not survive FDR correction across regions. No significant differences in Brain-PAD were observed. In healthy young adults, chronotype-related structural differences were not detectable under conservative voxel-wise FWE correction; however, pre-specified exploratory analyses suggested a regionally specific cerebellar gray matter pattern and nominal CT trends. These findings motivate larger and longitudinal studies with objective sleep–wake timing measures to clarify whether sleep timing is linked to early structural variation and to test its potential modifiability.