Präzisionspsychiatrie und der Beitrag von Brain Imaging und anderen Biomarkern

 

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Zusammenfassung

Die Präzisionspsychiatrie stellt die psychiatrische Variante des übergeordneten Konzepts der Präzisionsmedizin dar. Hierbei soll eine auf Biomarkern basierte und auf die individuelle klinische, neurobiologische und genetische Konstitution des Patienten zugeschnittene Diagnostik und Behandlung angeboten werden. Die spezifische Eigenheit des Fachs Psychiatrie, in der die Krankheitsentitäten normativ anhand klinischer Erfahrungswerte definiert und damit auch maßgeblich durch zeitgeschichtliche, gesellschaftliche und philosophische Einflüsse geprägt sind, hat bisher die Suche nach psychobiologischen Zusammenhängen erschwert. Dennoch gibt es mittlerweile in allen Bereichen der psychiatrischen Forschung erhebliche Fortschritte, die vor allem durch die kritische Überprüfung und Erneuerung bisheriger Krankheits- und Psychopathologie-Konzepte, die vermehrte Ausrichtung hin zur Neurobiologie und Genetik und insbesondere die Verwendung maschineller Lernverfahren ermöglicht wurden. Vor allem letztere Analysemethoden erlauben es, hochdimensionale und multimodale Datensätze zu integrieren und Modelle zu entwickeln, die einerseits neue psychobiologische Erkenntnisse liefern und andererseits eine real anwendbare Prädiktion von Diagnose, Therapieansprechen und Prognose auf Einzelfallniveau zunehmend realistisch erscheinen lassen. Ziel der hier vorliegenden Übersichtsarbeit soll daher sein, dem interessierten Leser das Konzept der Präzisionspsychiatrie näherzubringen, die hierfür verwendeten maschinellen Lernverfahren darzustellen und sowohl den gegenwärtigen Entwicklungsstand als auch zukunftsnahe Entwicklungen in diesem neuen Feld übersichtlich darzustellen.

Abstract

‘Precision Psychiatry’ as the psychiatric variant of ‘Precision Medicine’ aims to provide high-level diagnosis and treatment based on robust biomarkers and tailored to the individual clinical, neurobiological, and genetic constitution of the patient. The specific peculiarity of psychiatry, in which disease entities are normatively defined based on clinical experience and are also significantly influenced by contemporary history, society and philosophy, has so far made the search for valid and reliable psychobiological connections difficult. Nevertheless, considerable progress has now been made in all areas of psychiatric research, made possible above all by the critical review and renewal of previous concepts of disease and psychopathology, the increased orientation towards neurobiology and genetics, and in particular the use of machine learning methods. Notably, modern machine learning methods make it possible to integrate high-dimensional and multimodal data sets and generate models which provide new psychobiological insights and offer the possibility of individualized, biomarker-driven single-subject prediction of diagnosis, therapy response and prognosis. The aim of the present review is therefore to introduce the concept of ‘Precision Psychiatry’ to the interested reader, to concisely present modern, machine learning methods required for this, and to clearly present the current state and future of biomarker-based ‘precision psychiatry’.

Publication History

Received: 31 August 2020

Accepted: 27 October 2020

Article published online:
11 December 2020

© 2020. Thieme. All rights reserved.

Georg Thieme Verlag KG
Rüdigerstraße 14, 70469 Stuttgart, Germany

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