Differential Cortical Volume and Surface Morphometry in Youth With Chronic Health Conditions.
Sara A HeynRyan J HerringaAnne L ErsigPublished in: Biological research for nursing (2023)
Up to 1 in 3 youth in the United States have a childhood-onset chronic health condition (CHC), which can lead to neurodevelopmental disruptions in cognitive functioning and brain structure. However, the nature and extent of structural neurobiomarkers that may be consistent across a broad spectrum of CHCs are unknown. Thus, the purpose of this study was to identify potential differences in brain structure in youth with and without chronic physical health conditions (e.g., diabetes, hemophilia). Here, 49 T1 structural magnetic resonance imaging (MRI) images were obtained from youth with ( n = 26) and without ( n = 23) CHCs. Images were preprocessed using voxel-based morphometry (VBM) to generate whole-brain voxel-wise gray matter volume maps and whole-brain extracted estimates of cortical surface area and cortical thickness. Multi-scanner harmonization was implemented on surface-based estimates and linear models were used to estimate significant main effects of the group. We detected widespread decreases in brain structure in youth with CHCs as compared to controls in regions of the prefrontal, cingulate, and visual association areas. The insula exhibited the opposite effect, with cases having increased surface area as compared to controls. To our knowledge, these findings identify a novel structural biomarker of childhood-onset CHCs, with consistent alterations identified in gray matter of regions in the prefrontal cortex and insula involved in emotion regulation and executive function. These findings, while exploratory, may reflect an impact of chronic health stress in the adolescent brain, and suggest that more comprehensive assessment of stress and neurodevelopment in youth with CHCs may be appropriate.
Keyphrases
- mental health
- resting state
- functional connectivity
- physical activity
- young adults
- healthcare
- magnetic resonance imaging
- white matter
- public health
- health information
- type diabetes
- deep learning
- cerebral ischemia
- computed tomography
- social media
- cardiovascular disease
- convolutional neural network
- health promotion
- working memory
- machine learning
- magnetic resonance
- climate change
- insulin resistance
- blood brain barrier
- early life