| Literature DB >> 31591521 |
Alex Ing1, Philipp G Sämann2, Congying Chu1, Nicole Tay1, Francesca Biondo1, Gabriel Robert1,3, Tianye Jia1, Thomas Wolfers4, Sylvane Desrivières1, Tobias Banaschewski5, Arun L W Bokde6, Uli Bromberg7, Christian Büchel7,8, Patricia Conrod9,10, Tahmine Fadai7, Herta Flor11,12, Vincent Frouin13, Hugh Garavan14, Philip A Spechler14, Penny Gowland15, Yvonne Grimmer5, Andreas Heinz16, Bernd Ittermann17, Viola Kappel18, Jean-Luc Martinot19, Andreas Meyer-Lindenberg20, Sabina Millenet5, Frauke Nees5,11, Betteke van Noort18, Dimitri Papadopoulos Orfanos13, Marie-Laure Paillère Martinot21,22, Jani Penttilä23, Luise Poustka24, Erin Burke Quinlan1, Michael N Smolka25, Argyris Stringaris26,27, Maren Struve25, Ilya M Veer16, Henrik Walter16, Robert Whelan28, Ole A Andreassen29,30, Ingrid Agartz30,31,32, Hervé Lemaitre33, Edward D Barker1,34, John Ashburner35, Elisabeth Binder2, Jan Buitelaar4, Andre Marquand4, Trevor W Robbins36, Gunter Schumann37,38,39,40,41.
Abstract
Most psychopathological disorders develop in adolescence. The biological basis for this development is poorly understood. To enhance diagnostic characterization and develop improved targeted interventions, it is critical to identify behavioural symptom groups that share neural substrates. We ran analyses to find relationships between behavioural symptoms and neuroimaging measures of brain structure and function in adolescence. We found two symptom groups, consisting of anxiety/depression and executive dysfunction symptoms, respectively, that correlated with distinct sets of brain regions and inter-regional connections, measured by structural and functional neuroimaging modalities. We found that the neural correlates of these symptom groups were present before behavioural symptoms had developed. These neural correlates showed case-control differences in corresponding psychiatric disorders, depression and attention deficit hyperactivity disorder in independent clinical samples. By characterizing behavioural symptom groups based on shared neural mechanisms, our results provide a framework for developing a classification system for psychiatric illness that is based on quantitative neurobehavioural measures.Entities:
Mesh:
Year: 2019 PMID: 31591521 DOI: 10.1038/s41562-019-0738-8
Source DB: PubMed Journal: Nat Hum Behav ISSN: 2397-3374