Testing relationships between multimodal modes of brain structural variation and age, sex and polygenic scores for neuroticism in children and adolescents

Norbom et al. Translational Psychiatry (2020)10:251 https://doi.org/10.1038/s41398-020-00931-1 ARTICLE Translational Psychiatry Open Access Testing relationships between multimodal modes of brain structural variation and age, sex and polygenic scores for neuroticism in children and adolescents 1234567890():,; 1234567890():,; 1234567890():,; 1234567890():,; Linn B. Norbom 1,2,3, Jaroslav Rokicki1,4, Dennis van der Meer 1,5, Dag Alnæs 1, Nhat Trung Doan1, Torgeir Moberget1,4, Tobias Kaufmann 1, Ole A. Andreassen1, Lars T. Westlye 1,4 and Christian K. Tamnes 1,2,3 Abstract Human brain development involves spatially and temporally heterogeneous changes, detectable across a wide range of magnetic resonance imaging (MRI) measures. Investigating the interplay between multimodal MRI and polygenic scores (PGS) for personality traits associated with mental disorders in youth may provide new knowledge about typical and atypical neurodevelopment. We derived independent components across cortical thickness, cortical surface area, and grey/white matter contrast (GWC) (n = 2596, 3–23 years), and tested for associations between these components and age, sex and-, in a subsample (n = 878), PGS for neuroticism. Age was negatively associated with a single-modality component reflecting higher global GWC, and additionally with components capturing common variance between global thickness and GWC, and several multimodal regional patterns. Sex differences were found for components primarily capturing global and regional surface area (boys > girls), but also regional cortical thickness. For PGS for neuroticism, we found weak and bidirectional associations with a component reflecting right prefrontal surface area. These results indicate that multimodal fusion is sensitive to age and sex differences in brain structure in youth, but only weakly to polygenic load for neuroticism. Introduction The cerebral cortex and subjacent white matter undergo substantial modifications and refinement during childhood and adolescence1–3, paralleled by the qualitative and quantitative evolution of cognitive abilities4,5. These developmental changes coincide with increasing risk for mental disorders6,7. Mapping variation in brain development using magnetic resonance imaging (MRI) may therefore not only inform ontogenetic models of neurocognitive development, Correspondence: Linn B. Norbom () 1 NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway 2 PROMENTA Research Center, Department of Psychology, University of Oslo, Oslo, Norway Full list of author information is available at the end of the article but also delineate aberrant spatiotemporal patterns related to emerging psychopathology. Cortical development is multifaceted, with cortical volume and its subcomponents thickness and surface area showing distinct developmental patterns8–10, and genetic underpinnings11,12. Less explored measures of signal intensity variation in the T1-weighted image may reflect additional and partly distinct neurobiological properties13–16. Specifically, the contrast between cortical grey matter (GM) and closely subjacent white matter (WM) intensities, the grey/white matter contrast (GWC), has been shown to be heritable16, and associated with development14, aging13,17 and schizophrenia18. Although the underlying biology of GWC is complex and debated, the measure has been linked to differential intracortical and WM myelination13. © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. Norbom et al. Translational Psychiatry (2020)10:251 The onset of puberty, as well as the pubertal period, differs between adolescent boys and girls19,20. There have also been reports of sex specific shifts in the onset of developmental psychopathology, as well as variations in overall risk for mental disorders7,21. Results concerning both the extent, and metric specificity of sex related neurodevelopmental differences are, however, inconclusive8,9,22 and no studies have investigated sex related developmental differences in GWC. The relationships between distinct brain structural properties captured by different MRI measures are poorly understood, but might be informed by methods such as linked independent component analysis (LICA), which can parse the common and unique variance across multiple modalities into separate components of shared variance23. LICA studies have reported unique structural patterns sensitive to lifespan development24,25, and psychopathology26,27. Multimodal fusion, also including GWC, thus shows promise for capturing both typical brain developmental patterns and patterns associated with susceptibility for mental illness. High levels of neuroticism is associated with several forms of psychopathology28,29, including the overarching “p factor” from dimensional psychopathology models30,31, and internalizing symptoms from core domain models28, which captures vulnerability toward mood and anxiety disorders31,32. Twin and family studies have shown that genetic differences account for about 40% of the trait variance33, and genome-wide association studies (GWAS) have documented a highly polygenic signal34, in line with most complex traits35. Polygenic scores (PGS) are defined as the weighted sum of an ensemble of trait-associated alleles36, and reflect the individual level of cumulative genetic signal across the genome. Only one prior neuroimaging study has investigated the association between PGS for neuroticism and brain structure, reporting negative associations with regional cortical surface area in two adult samples37. Studies in youth are lacking, but may provide insight into the brain structural correlates of genetic dispositions for broad psychopathology-associated traits in a period of life when many mental disorders typically emerge. To this end, we combined cortical thickness, surface area, and GWC using FLICA (FMRIB’s LICA) in 2596 youths (3–23 years), and tested for associations between the resulting multimodal modes of variation and age, sex and-, in a subsample (n = 878), PGS for neuroticism and two of its subcomponents (depressed a (...truncated)