Multimodal phenotypic classification of generalized anxiety and panic using structural MRI data and psychosocial factors: machine learning results from the German National Cohort (NAKO) study.

doi:10.1038/s41398-026-04131-1

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Article

Multimodal phenotypic classification of generalized anxiety and panic using structural MRI data and psychosocial factors: machine learning results from the German National Cohort (NAKO) study.

Translational psychiatry - 28 May 2026

Gutzeit Julian, Weiß Martin, Kuhn Tierney, Klinger-König Johanna, Streit Fabian, Jockwitz Christiane, Brandes Berit, Wright Marvin N, Friedrich Christoph M, Woeckel Margarethe, Mikolajczyk Rafael, Keil Thomas, Castell Stefanie, Betker Philine, Schlett Christopher L, Bärnighausen Till W, Bamberg Fabian, Günther Matthias, Hirsch Jochen G, Pischon Tobias, Niendorf Thoralf, Leitzmann Michael F, Bohmann Patricia, Wirkner Kerstin, Krist Lilian, Wang Yanding, Berger Klaus, Walther Sebastian, Grabe Hans J, Deckert Jürgen, Caspers Svenja, Hein Grit, Erhardt-Lehmann Angelika

Abstract excerpt

Anxiety disorders are common and impairing mental health conditions. Using data from 26,378 adults in the German National Cohort Study (NAKO), we investigated psychosocial and neuroimaging predictors of generalized anxiety disorder (GAD) symptoms and panic attacks. We conducted machine-learning analyses of 246 regions of interest from whole-brain imaging data in combination with psychosocial variables....

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PMID: 42209472
DOI: 10.1038/s41398-026-04131-1
PMCID: PMC13219414

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