Altered connectome topology in newborns at risk for cognitive developmental delay: a cross-etiologic study

Speckert, A.; Payette, K. M.; Knirsch, W.; von Rhein, M.; Grehten, P.; Kottke, R.; Hagmann, C.; Natalucci, G.; Moehrlen, U.; Mazzone, L.; Ochsenbein-Kölble, N.; Padden, B.; SPINA BIFIDA STUDY GROUP ZURICH,; Latal, B.; Jakab, A.

doi:10.1101/2024.06.20.599853

bioRxiv · 10.1101/2024.06.20.599853

Altered connectome topology in newborns at risk for cognitive developmental delay: a cross-etiologic study

Speckert, A.·Payette, K. M.·Knirsch, W.·von Rhein, M.·Grehten, P.·Kottke, R.·Hagmann, C.·Natalucci, G.·Moehrlen, U.·Mazzone, L.·Ochsenbein-Kölble, N.·Padden, B.·SPINA BIFIDA STUDY GROUP ZURICH,·Latal, B.·Jakab, A.

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Abstract

The human brain connectome is characterized by the duality of highly modular structure and efficient integration, supporting information processing. Newborns with congenital heart disease (CHD), prematurity, or spina bifida aperta (SBA) constitute a population at risk for altered brain development and developmental delay (DD). We hypothesize that, independent of etiology, alterations of connectomic organization reflect neural circuitry impairments in cognitive DD. Our study aim is to address this knowledge gap by using a multi-etiologic neonatal dataset to reveal potential commonalities and distinctions in the structural brain connectome and their associations with DD. We used diffusion tensor imaging (DTI) of 187 newborns (42 controls, 51 with CHD, 51 with prematurity, and 43 with SBA). Structural weighted connectomes were constructed using constrained spherical deconvolution based probabilistic tractography and the Edinburgh Neonatal Atlas. Assessment of brain network topology encompassed the analysis of global graph features, network-based statistics, and low-dimensional representation of global and local graph features. The Cognitive Composite Score of the Bayley Scales of Infant and Toddler Development 3rd edition was used as outcome measure at corrected 2 years for the preterm born individuals and SBA patients, and at 1 year for the healthy controls and CHD. We revealed differences in the connectomic structure of newborns across the four groups after visualizing the connectomes in a two-dimensional space defined by network integration and segregation. Further, ANCOVA analyses revealed differences in global efficiency (p < 0.0001), modularity (p < 0.0001), mean rich club coefficient (p = 0.017) and small-worldness (p = 0.016) between groups after adjustment for postmenstrual age at scan and gestational age at birth. Moreover, small-worldness was significantly associated with poorer cognitive outcome, specifically in the CHD cohort (r = -0.41, p = 0.005). Our cross-etiologic study identified divergent structural brain connectome profiles linked to deviations from optimal network integration and segregation in newborns at risk for DD. Small-worldness emerges as a key feature, associating with early cognitive outcomes, especially within the CHD cohort, emphasizing small-worldness crucial role in shaping neurodevelopmental trajectories. Neonatal connectomic alterations associated with DD may serve as a marker identifying newborns at-risk for DD and provide early therapeutic interventions.

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Speckert, A., Payette, K. M., Knirsch, W., von Rhein, M., Grehten, P., Kottke, R., Hagmann, C., Natalucci, G., Moehrlen, U., Mazzone, L., Ochsenbein-Kölble, N., Padden, B., SPINA BIFIDA STUDY GROUP ZURICH,, Latal, B., Jakab, A.. 2024-06-24. Altered connectome topology in newborns at risk for cognitive developmental delay: a cross-etiologic study. https://doi.org/10.1101/2024.06.20.599853

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