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De Bellis, M.

Publications and source records attributed to De Bellis, M..

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Alcohol Use Disrupts Age-Appropriate Cortical Thinning in Adolescence: A Data Driven Approach

ObjectiveCortical thickness changes dramatically during development and is influenced by adolescent drinking. However, previous findings have been inconsistent and limited by region-of-interest approaches that are underpowered because they do not conform to the underlying heterogeneity from the effects of alcohol. MethodsAdolescents (n=657; 12-22 years at baseline) from the National Consortium on Alcohol and Neurodevelopment in Adolescence (NCANDA) who endorsed little to no alcohol use at baseline were assessed with structural MRI and followed longitudinally at four yearly intervals. Seven unique spatially covarying patterns of cortical thickness were obtained from the baseline scans by applying a novel data-driven method called non-negative matrix factorization (NMF). The cortical thickness maps of all participants longitudinal scans were projected onto vertex-level cortical patterns to obtain participant-specific coefficients for each pattern. Linear mixed-effects models were fit to each pattern to investigate longitudinal effects of alcohol consumption on cortical thickness. ResultsIn most NMF-derived cortical thickness patterns, the longitudinal rate of decline in no/low drinkers was similar for all age cohorts, among moderate drinkers the decline was faster in the younger cohort and slower in the older cohort, among heavy drinkers the decline was fastest in the younger cohort and slowest in the older cohort (FDR corrected p-values < 0.01). ConclusionsThe NMF method can delineate spatially coordinated patterns of cortical thickness at the vertex level that are unconstrained by anatomical features. Age-appropriate cortical thinning is more rapid in younger adolescent drinkers and slower in older adolescent drinkers.

neuroscience

Structural Covariance Networks in Post-Traumatic Stress Disorder: A Multisite ENIGMA-PGC Study

IntroductionCortical thickness (CT) and surface area (SA) are established biomarkers of brain pathology in posttraumatic stress disorder (PTSD). Structural covariance networks (SCN) constructed from CT and SA may represent developmental associations, or unique interactions between brain regions, possibly influenced by a common causal antecedent. The ENIGMA-PGC PTSD Working Group aggregated PTSD and control subjects data from 29 cohorts in five countries (n=3439). MethodsUsing Destrieux Atlas, we built SCNs and compared centrality measures between PTSD subjects and controls. Centrality is a graph theory measure derived using SCN. ResultsNotable nodes with higher CT-based centrality in PTSD compared to controls were left fusiform gyrus, left superior temporal gyrus, and right inferior temporal gyrus. We found sex-based centrality differences in bilateral frontal lobe regions, left anterior cingulate, left superior occipital cortex and right ventromedial prefrontal cortex (vmPFC). Comorbid PTSD and MDD showed higher CT-based centrality in the right anterior cingulate gyrus, right parahippocampal gyrus and lower SA-based centrality in left insular gyrus. ConclusionUnlike previous studies with smaller sample sizes ([&le;]318), our study found differences in centrality measures using a sample size of 3439 subjects. This is the first cross-sectional study to examine SCN interactions with age, sex, and comorbid MDD. Although limited to group level inferences, centrality measures offer insights into a nodes relationship to the entire functional connectome unlike approaches like seed-based connectivity or independent component analysis. Nodes having higher centrality have greater structural or functional connections, lending them invaluable for translational treatments like neuromodulation.

neuroscience