Gestational Age is Dimensionally Associated with Structural Brain Network Abnormalities Across Development

Abstract

Prematurity is associated with diverse developmental abnormalities, yet few studies relate cognitive and neurostructural deficits to a dimensional measure of prematurity. Leveraging a large sample of children, adolescents, and young adults (age 8-22 years) studied as part of the Philadelphia Neurodevelopmental Cohort, we examined how variation in gestational age impacted cognition and brain structure later in development. Participants included 72 preterm youth born before 37 weeks' gestation and 206 youth who were born at term (37 weeks or later). Using a previously-validated factor analysis, cognitive performance was assessed in three domains: (1) executive function and complex reasoning, (2) social cognition, and (3) episodic memory. All participants completed T1-weighted neuroimaging at 3 T to measure brain volume. Structural covariance networks were delineated using non-negative matrix factorization, an advanced multivariate analysis technique. Lower gestational age was associated with both deficits in executive function and reduced volume within 11 of 26 structural covariance networks, which included orbitofrontal, temporal, and parietal cortices as well as subcortical regions including the hippocampus. Notably, the relationship between lower gestational age and executive dysfunction was accounted for in part by structural network deficits. Together, these findings emphasize the durable impact of prematurity on cognition and brain structure, which persists across development.

Associations Between Neonatal Brain Structure, the Home Environment, and Childhood Outcomes Following Very Preterm Birth

“…We used NNMF (see the Supplement for more information) to identify SCNs in the neonatal preterm brain in which regional brain volumes consistently covary across individuals ( N = 384). NNMF is an unsupervised multivariate dimension reduction technique that is particularly suited for investigating brain structural covariance ( 26 , 51 ). In contrast to seed-based approaches ( 52 ), NNMF derives networks in a data-driven manner.…”

“…Altered structural covariance has been reported in preterm-born adolescents ( 24 ) and young adults ( 25 ). Notably, the association between low gestational age at birth (GA) and executive deficits was shown to be mediated by altered structural covariance in orbitofrontal, temporal, parietal, and subcortical regions in a large sample of adolescents ( 26 ). However, it is unclear to what extent SCNs emerging in the neonatal period might predict developmental outcomes after preterm birth.…”

Radiomics of Contrast-Enhanced Computed Tomography: A Potential Biomarker for Pretreatment Prediction of the Response to Bacillus Calmette-Guerin Immunotherapy in Non-Muscle-Invasive Bladder Cancer

“…This can be achieved with NMF, which is an unsupervised algorithm based on decomposition by parts and a model selection mechanism. NMF has been used to iteratively select the most robust biomarkers from thousands of genes (Zhong et al, 2018;Zeng et al, 2019;Motzer et al, 2020) and to find structural covariance patterns in neuroimaging content (Nassar et al, 2019;Patel et al, 2020). In our application of NMF to radiomic features, the parts were the components of a reduced representation of the original hidden features, which may enable the recovery of biologically similar phenotypes.…”

Diagnostic Value of Diffusion Tensor Imaging for Infants’ Brain Development Retardation Caused by Pre-Eclampsia

“…Previous studies have concluded that early preterm birth is associated with a high level of attention-deficit/hyperactivity disorder (ADHD) symptoms in preschool children [ 17 ]. Gestational age is dimensionally related to structural brain network abnormalities across development [ 18 ]. In addition, lower birth weight may cause lagging brain development [ 19 ].…”