Identification of neurobehavioural symptom groups based on shared brain mechanisms.

Alex Ing, , Philipp G. Sämann, Congying Chu, Nicole Tay, Francesca Biondo, Gabriel Robert, Tianye Jia, Thomas Wolfers, Sylvane Desrivières, Tobias Banaschewski, Arun L. W. Bokde, Uli Bromberg, Christian Büchel, Patricia Conrod, Tahmine Fadai, Herta Flor, Vincent Frouin, Hugh Garavan, Philip A. Spechler, Penny Gowland, Yvonne Grimmer, Andreas Heinz, Bernd Ittermann, Viola Kappel, Jean-Luc Martinot, Andreas Meyer-Lindenberg, Sabina Millenet, Frauke Nees, Betteke van Noort, Dimitri Papadopoulos Orfanos, Marie-Laure Paillère Martinot, Jani Penttilä, Luise Poustka, Erin Burke Quinlan, Michael N. Smolka, Argyris Stringaris, Maren Struve, Ilya M. Veer, Henrik Walter, Robert Whelan, Ole A. Andreassen, Ingrid Agartz, Hervé Lemaitre, Edward D. Barker, John Ashburner, Elisabeth Binder, Jan Buitelaar, Andre Marquand, Trevor W. Robbins, Gunter Schumann
Nat Hum Behav. 2019-10-07; 3(12): 1306-1318
DOI: 10.1038/s41562-019-0738-8


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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.

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