Cortical Morphometry in the Psychosis Risk Period: A Comprehensive Perspective of Surface Features.

BACKGROUND

Gyrification features reflect brain development in the early prenatal environment. Clarifying the nature of these features in psychosis can help shed light on the role of early developmental insult. However, the literature is currently widely discrepant, which may reflect confounds related to formally psychotic patient populations or overreliance on a single feature of cortical surface morphometry (CSM).

METHODS

This study compares CSM features of gyrification in clinical high-risk (n = 43) youths during the prodromal risk period to typically developing control subjects over two time points across three metrics: local gyrification index, mean curvature index, and sulcal depth (improving resolution and examination of change over 1 year).

RESULTS

Gyrification was stable over time, supporting the idea that gyrification reflects early insult rather than abnormal development or reorganization associated with the disease state. Each of the indices highlighted unique, aberrant features in the clinical high-risk group with respect to control subjects. Specifically, the local gyrification index reflected hypogyrification in the lateral orbitofrontal cortex, superior bank of the superior temporal sulcus, anterior isthmus of the cingulate gyrus, and temporal poles; the mean curvature index indicated sharper gyral and flatter or wider sulcal peaks in the cingulate, postcentral, and lingual gyrus; sulcal depth identified shallow features in the parietal, superior temporal sulcus, and cingulate regions. Further, both the mean curvature index and sulcal depth converged on abnormal features in the parietal cortex.

CONCLUSIONS

Gyrification metrics suggest early developmental insult and provide support for neurodevelopmental hypotheses. Observations of stable CSM features across time provide context for interpreting extant studies and speak to CSM as a promising stable marker and/or endophenotype. Collectively, findings support the importance of considering multiple CSM features.