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A framework for a brain-derived nosology of psychiatric disorders

Lett, T. A.; Vaidya, N.; Jia, T.; Polemiti, E.; Banaschewski, T.; Bokde, A. L. W.; Flor, H.; Grigis, A.; Garavan, H.; Gowland, P.; Heinz, A.; Bruh, R.; Martinot, J.-L.; Martinot, M.-L. P.; Artiges, E.; Nees, F.; Orfano, D. P.; Lemaitre, H.; Paus, T.; Poustka, L.; Stringaris, A.; Waller, L.; Zhang, Z.; Robinson, L.; Winterer, J.; Zhang, Y.; King, S.; Smolka, M. N.; Whelan, R.; Schmidt, U.; Sinclair, J.; Walter, H.; Feng, J.; Robbins, T. W.; Desrivieres, S.; Marquand, A.; Schumann, G.

2024-05-07 psychiatry and clinical psychology
10.1101/2024.05.07.24306980 medRxiv
Show abstract

Current psychiatric diagnoses are not defined by neurobiological measures which hinders the development of therapies targeting mechanisms underlying mental illness 1,2. Research confined to diagnostic boundaries yields heterogeneous biological results, whereas transdiagnostic studies often investigate individual symptoms in isolation. There is currently no paradigm available to comprehensively investigate the relationship between different clinical symptoms, individual disorders, and the underlying neurobiological mechanisms. Here, we propose a framework that groups clinical symptoms derived from ICD-10/DSM-V according to shared brain mechanisms defined by brain structure, function, and connectivity. The reassembly of existing ICD-10/DSM-5 symptoms reveal six cross-diagnostic psychopathology scores related to mania symptoms, depressive symptoms, anxiety symptoms, stress symptoms, eating pathology, and fear symptoms. They were consistently associated with multimodal neuroimaging components in the training sample of young adults aged 23, the independent test sample aged 23, participants aged 14 and 19 years, and in psychiatric patients. The identification of symptom groups of mental illness robustly defined by precisely characterized brain mechanisms enables the development of a psychiatric nosology based upon quantifiable neurobiological measures. As the identified symptom groups align well with existing diagnostic categories, our framework is directly applicable to clinical research and patient care.

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