Etchell, A. C. | bioRxiv Science

bioRxiv2019

Linking lysosomal enzyme targeting genes and energy metabolism with altered gray matter volume in children with persistent stuttering

Developmental stuttering is a childhood onset neurodevelopmental disorder with an unclear etiology. Subtle changes in brain structure and function are present in both children and adults who stutter. It is a highly heritable disorder, and up to 12-20% of stuttering cases may carry a mutation in one of four genes involved in mannose-6-phosphate mediated protein intracellular trafficking. To better understand the relationship between genetic factors and brain structural changes, we used gene expression data from the Allen Institute for Brain Science (AIBS) and voxel-based morphometry (VBM) to investigate the spatial correspondence between gene expression patterns and differences in gray matter volume (GMV) between children with persistent stuttering (n=26, 87 scans) and their fluent peers (n=44, 139 scans). We found that expression patterns of two stuttering-related genes (GNPTG and NAGPA) in the brain exhibit a strong positive spatial correlation with the magnitude of GMV differences between groups. Further gene set enrichment analyses revealed that genes whose expression was highly correlated with the GMV differences were enriched for glycolysis and oxidative metabolism in mitochondria. Although the results are correlational and cannot inform us about underlying casual mechanisms, our results suggest a possibility that regions with high expression level of genes associated with stuttering may be particularly vulnerable to the effect of alterations in these genes. This effect may be further exacerbated by the relatively high energy utilization in those brain during the period of a sharp increase in brain energy utilization, which coincides with a period of rapid language development and the onset of stuttering during childhood.

neuroscience↗

bioRxiv2018

Topological segregation of functional networks increases in developing brains

A growing literature conceptualises human brain development from a network perspective, but it remains unknown how functional brain networks are refined during the preschool years. The extant literature diverges in its characterisation of functional network development, with little agreement between haemodynamic- and electrophysiology-based measures. In children aged from 4 to 12 years, as well as adults, age appropriate magnetoencephalography was used to estimate unbiased network topology, using minimum spanning tree (MST) constructed from phase synchrony between beamformer-reconstructed time-series. During childhood, network topology becomes increasingly segregated, while cortical regions decrease in centrality. We propose a heuristic MST model, in which a clear developmental trajectory for the emergence of complex brain networks is delineated. Our results resolve topological reorganisation of functional networks across temporal and special scales in youth and fill a gap in the literature regarding neurophysiological mechanisms of functional brain maturation during the preschool years.

neuroscience↗