Genetic risk for schizophrenia and developmental delay is associated with shape and microstructure of midline white matter structures

Abstract

Genomic copy number variants (CNVs) are amongst the most highly penetrant genetic risk factors for neuropsychiatric disorders. The scarcity of carriers of individual CNVs and their phenotypical heterogeneity limits investigations of the associated neural mechanisms and endophenotypes. We applied a novel design based on CNV penetrance for schizophrenia and developmental delay that allows us to identify structural sequelae that are most relevant to neuropsychiatric disorders. Our focus on brain structural abnormalities was based on the hypothesis that convergent mechanisms contributing to neurodevelopmental disorders would likely manifest in the macro-and microstructure of white matter and cortical and subcortical grey matter. 21 adult participants carrying neuropsychiatric risk CNVs (including those located at 22q11.2, 15q11.2, 1q21.1, 16p11.2, and 17q12) and 15 ageand gender matched controls underwent T1-weighted structural, diffusion and quantitative T1 relaxometry MRI.The macro-and microstructural properties of the cingulum bundles were associated with penetrance for both developmental delay and schizophrenia, in particular curvature along the anterior-posterior axis (Sz: p corr =0.026; DD: p corr =0.035) and intracellular volume fraction (Sz: p corr =0.019; DD: p corr =0.064) Further principal component analysis showed alterations in the interrelationships between the volumes of several mid-line white matter structures (Sz: p corr =0.055; DD : p corr =0.027). In particular, the ratio of volumes in the splenium and body of the corpus callosum was significantly associated with both penetrance scores (Sz: p=0.037; DD; p=0.006). Our results are consistent with the notion that a significant alteration in developmental trajectories of mid-line white-matter structures constitutes a common neurodevelopmental aberration contributing to risk for schizophrenia and intellectual disability.

Surface-based tracking for short association fibre tractography

“…that a proportion of variability within and between subjects is explained by the occurrence of such streamlines owing to the fundamental limitations of a chosen tractography algorithm. Shape-based(Drakesmith et al (2019);Parker et al (2016)) exclusion of noisy streamlines could be undertaken in the future; however, the lack of detailed histological or tracer injection validation data for SAF on the whole-brain scale makes identification of such streamlines difficult. Development of better scanning hardware and tractography/optimisation algorithms will facilitate greater fidelity of has previously been addressed Zhang et al (2010).…”