TY - JOUR
T1 - Age-related brain deviations and aggression
AU - Holz, Nathalie E.
AU - Floris, Dorothea L.
AU - Llera, Alberto
AU - Aggensteiner, Pascal M.
AU - Kia, Seyed Mostafa
AU - Wolfers, Thomas
AU - Baumeister, Sarah
AU - Böttinger, Boris
AU - Glennon, Jeffrey C.
AU - Hoekstra, Pieter J.
AU - Dietrich, Andrea
AU - Saam, Melanie C.
AU - Schulze, Ulrike M.E.
AU - Lythgoe, David J.
AU - Williams, Steve C.R.
AU - Santosh, Paramala
AU - Rosa-Justicia, Mireia
AU - Bargallo, Nuria
AU - Castro-Fornieles, Josefina
AU - Arango, Celso
AU - Penzol, Maria J.
AU - Walitza, Susanne
AU - Meyer-Lindenberg, Andreas
AU - Zwiers, Marcel
AU - Franke, Barbara
AU - Buitelaar, Jan
AU - Naaijen, Jilly
AU - Brandeis, Daniel
AU - Beckmann, Christian
AU - Banaschewski, Tobias
AU - Marquand, Andre F.
N1 - Funding Information:
This project has received funding from the European Union's Seventh Framework Programme for research, technological development and demonstration under grant agreement 602805 (AGGRESSOTYPE) and no 603016 (MATRICS). This manuscript reflects only the author's view and the European Union is not liable for any use that may be made of the information contained herein. NEH and TB gratefully acknowledge grant support from the German Research Foundation (grant numbers DFG HO 5674/2-1, GRK2350/1). NEH further acknowledges funding from the Olympia Morata Program of the University of Heidelberg, the Ministry of Science, Research and the Arts of the State of Baden-Württemberg, Germany (Special support program SARS CoV-2 pandemic), and the Radboud Excellence Fellowship. DLF is supported by funding from the European Union's Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No 101025785. BF received additional funding from a personal Vici grant of the Dutch Organisation for Scientific Research (grant 016-130-669) and from a grant for the Dutch National Science Agenda for the NWA NeurolabNL project (grant 400 17 602). AML acknowledges grant support by the German Research Foundation (DFG, Research Training Group GRK2350/1 project B02, Collaborative Research Center SFB 1158 project B09, Collaborative Research Center TRR 265 project S02, grant ME 1591/4-1), German Federal Ministry of Education and Research (BMBF, grants 01EF1803A, 01ZX1314G, 01GQ1003B), European Union's Seventh Framework Programme (FP7, grants 602450, 602805, 115300, HEALTH-F2-2010-241909) (Horizon2020 CANDY grant 847818 and Eat2beNICE grant 728018), Innovative Medicines Initiative Joint Undertaking (IMI, grant 115008, PRISM grant 115916, EU-AIMS grant 115300, and AIMS-2-TRIALS grant 777394) and Ministry of Science, Research and the Arts of the State of Baden-Wuerttemberg, Germany (MWK, grant 42-04HV.MED(16)/16/1). CA and MJP have been supported by the Spanish Ministry of Science and Innovation. Instituto de Salud Carlos III (SAM16PE07CP1, PI16/02012, PI19/024), co-financed by ERDF Funds from the European Commission, ‘A way of making Europe’, CIBERSAM. Madrid Regional Government (B2017/BMD-3740 AGES-CM-2), Fundación Familia Alonso and Fundación Alicia Koplowitz. JN received additional funding from a personal Veni grant of the Dutch Organisation for Scientific Research (NWO grant V1.Veni.194.032). CFB gratefully acknowledges support from the Dutch Organisation for Scientific Research (NWO VICI grant 17854) and funding from the Wellcome Trust (Collaborative Award in Science 215573/Z/19/Z). AFM gratefully acknowledges support from the Dutch Organisation for Scientific Research (VIDI grant 016.156.415).
Publisher Copyright:
Copyright © The Author(s), 2022. Published by Cambridge University Press.
PY - 2022/4/22
Y1 - 2022/4/22
N2 - Background Disruptive behavior disorders (DBD) are heterogeneous at the clinical and the biological level. Therefore, the aims were to dissect the heterogeneous neurodevelopmental deviations of the affective brain circuitry and provide an integration of these differences across modalities. Methods We combined two novel approaches. First, normative modeling to map deviations from the typical age-related pattern at the level of the individual of (i) activity during emotion matching and (ii) of anatomical images derived from DBD cases (n = 77) and controls (n = 52) aged 8-18 years from the EU-funded Aggressotype and MATRICS consortia. Second, linked independent component analysis to integrate subject-specific deviations from both modalities. Results While cases exhibited on average a higher activity than would be expected for their age during face processing in regions such as the amygdala when compared to controls these positive deviations were widespread at the individual level. A multimodal integration of all functional and anatomical deviations explained 23% of the variance in the clinical DBD phenotype. Most notably, the top marker, encompassing the default mode network (DMN) and subcortical regions such as the amygdala and the striatum, was related to aggression across the whole sample. Conclusions Overall increased age-related deviations in the amygdala in DBD suggest a maturational delay, which has to be further validated in future studies. Further, the integration of individual deviation patterns from multiple imaging modalities allowed to dissect some of the heterogeneity of DBD and identified the DMN, the striatum and the amygdala as neural signatures that were associated with aggression.
AB - Background Disruptive behavior disorders (DBD) are heterogeneous at the clinical and the biological level. Therefore, the aims were to dissect the heterogeneous neurodevelopmental deviations of the affective brain circuitry and provide an integration of these differences across modalities. Methods We combined two novel approaches. First, normative modeling to map deviations from the typical age-related pattern at the level of the individual of (i) activity during emotion matching and (ii) of anatomical images derived from DBD cases (n = 77) and controls (n = 52) aged 8-18 years from the EU-funded Aggressotype and MATRICS consortia. Second, linked independent component analysis to integrate subject-specific deviations from both modalities. Results While cases exhibited on average a higher activity than would be expected for their age during face processing in regions such as the amygdala when compared to controls these positive deviations were widespread at the individual level. A multimodal integration of all functional and anatomical deviations explained 23% of the variance in the clinical DBD phenotype. Most notably, the top marker, encompassing the default mode network (DMN) and subcortical regions such as the amygdala and the striatum, was related to aggression across the whole sample. Conclusions Overall increased age-related deviations in the amygdala in DBD suggest a maturational delay, which has to be further validated in future studies. Further, the integration of individual deviation patterns from multiple imaging modalities allowed to dissect some of the heterogeneity of DBD and identified the DMN, the striatum and the amygdala as neural signatures that were associated with aggression.
KW - Aggression
KW - disruptive behavior disorders
KW - emotion processing
KW - fMRI
KW - normative modeling
UR - http://www.scopus.com/inward/record.url?scp=85129836510&partnerID=8YFLogxK
U2 - 10.1017/S003329172200068X
DO - 10.1017/S003329172200068X
M3 - Article
AN - SCOPUS:85129836510
SN - 0033-2917
SP - 1
EP - 10
JO - Psychological Medicine
JF - Psychological Medicine
M1 - 003329172200068
ER -