Human cortex development is shaped by molecular and cellular brain systems
Creators: name: Lotter, Leon
name: Saberi, Amin
name: Jansen, Justine Y.
name: Misic, Bratislav
name: Barker, Gareth J.
name: Bokde, Arun L. W.
name: Desrivíeres, Sylvane
name: Flor, Herta
name: Grigis, Antoine
name: Garavan, Hugh
name: Gowland, Penny
name: Heinz, Andreas
name: Brühl, Rüdiger
name: Martinot, Jean-Luc
name: Paillére, Marie-Paure
name: Artiges, Eric
name: Orfanos, Dimitri Papadopoulos
name: Paus, Tomáš
name: Poustka, Luise
name: Hohmann, Sarah
name: Fröhner, Juliane H.
name: Smolka, Michael N.
name: Vaidya, Nilakshi
name: Walter, Henrik
name: Whelan, Robert
name: Schumann, Gunter
name: Nees, Frauke
name: Banaschewski, Tobias
name: Eickhoff, Simon
name: Dukart, Jürgen
Publisher: name: Forschungzentrum Jülich
Year: 2023

description: Organization for Human Brain Mapping (OHBM), Montreal, Canada, 21 Jul 2023 - 26 Jul 2023
description: Introduction:Human cerebral cortex morphology is subject to complex developmental changes, with developmental trajectories varying across brain regions (Bethlehem et al., 2022; Rutherford et al., 2022). Several biological factors influencing cortical thickness (CT) development have been discussed, but naturally, human data are scarce. As especially neurodevelopmental disorders are characterized by atypical cortex development (Bethlehem et al., 2020; Rutherford et al., 2022), knowledge about drivers of typical development may shed light on the pathophysiology of deviating neurodevelopment. In this study, we demonstrate that population-average and single-subject CT trajectories colocalize with, and are explained by, spatial distributions of brain metabolism and immunity features, neurotransmitter systems, cortical myelin, as well as neuronal and glial cell populations. We provide novel information on human cortex development within a framework that facilitates easy transfer to new cohorts, paving the way for individualized and biologically interpretable brain-based biomarkers.Methods:We included 49 atlases of molecular and cellular brain systems derived from healthy adult data (Hansen et al., 2022; Dukart et al., 2021; Hawrylycz et al., 2012). Atlases were parcellated in 148 bilateral cortex regions and reduced to 18 factors (factor analysis retaining dimensions explaining ≥ 1% of variance). First, we extracted 50th percentile "representative" CT data from a normative CT model estimated on 58,836 subjects from 82 sites (5-90 years) (Rutherford et al., 2022). To test for relationships between CT change patterns and multilevel brain systems, we (i) estimated the spatial colocalization (Spearman's ρ) between each factor and CT at each timepoint (Vidal-Pineiro et al., 2020) and (ii) fitted multivariate linear models "predicting" CT change from the multilevel factors using a sliding window approach (5-year-steps). The results were validated in longitudinal CT data from the ABCD (n = 6,315; 20 sites; ~10-12 years; Casey et al., 2018) and IMAGEN (n = 985-1177; 8 sites; ~14-22 years; Schumann et al., 2010) cohort studies. Analyses were performed with JuSpyce (Lotter and Dukart, 2022), a toolbox for large-scale spatial association analyses, using strict spatial autocorrelation-preserving permutation testing and false discovery rate correction.Results:Spatial Spearman colocalization analyses between cross-selctional CT and biological brain systems revealed diverse colocalization trajectories with a general pattern of strongest changes in early and late phases of life. The combined biological systems at molecular and cellular levels explained up to 54% of the spatial variance in modeled CT changes across the lifespan with peaks at about 20-35 (molecular) and 15-20 (cellular) years of age, respectively. Subsequent analyses accounting for shared variance showed that the 9 strongest associated brain systems jointly explained up to 58% of CT change. Of particular relevance for early cortex development were D1/2 dopaminergic receptors, microglia, and somatostatin-expressing interneurons, while dopaminergic and cholinergic neurotransmission was associated with midlife CT maturation patterns. Normative model-based results replicated in single-subject data, albeit showing considerably higher variance (cohort-average R2 = 25-56%; individual R2 9-18%, range 0-59%).Conclusions:Factors shaping human brain morphology over the lifespan are poorly understood. Here we demonstrate that the complex patterns in which the human cerebral cortex develops and matures colocalize with specific biological systems on molecular and cellular levels. Our findings support roles of the dopaminergic system, microglia and somatostatin-expressing interneurons in early CT development, whereas cholinergic and dopaminergic neurotransmission are associated with CT changes across adulthood. Our results not only have implications for the study of typical neurodevelopment, but also hold promise for the value of neurodevelopmental cross-modal association analyses for future clinical research applications.