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Nervenarzt. 2019 Feb;90(2):99-106. doi: 10.1007/s00115-018-0670-6.

[Breakthrough in understanding the molecular causes of psychiatric disorders].

[Article in German]

Author information

1
Institut für Humangenetik, Universitätsklinikum Bonn, Sigmund-Freud-Str. 25, 53127, Bonn, Deutschland. markus.noethen@uni-bonn.de.
2
Institut für Humangenetik, Universitätsklinikum Bonn, Sigmund-Freud-Str. 25, 53127, Bonn, Deutschland.
3
Zentrum für Humangenetik, Philipps-Universität Marburg, Baldingerstraße, 35033, Marburg, Deutschland.

Abstract

A long-established hypothesis is that genetic factors contribute to the development of psychiatric diseases, including common illnesses such as schizophrenia and the affective disorders; however, reliable molecular identification of these factors represents a far more recent innovation. This has been rendered possible by technological advances in the individual characterization of the human genome and the combining of large genetic datasets at the international level. For the first time, the results of genome-wide analyses provide researchers with systematic insights into disease-relevant biological mechanisms. Here, the integrated analysis of different omics level data generates important insights into the functional interpretation of the genetic findings. The results of genetic studies also demonstrated the degree of etiological overlap between differing psychiatric disorders, with the greatest commonality having been observed to date between schizophrenia and bipolar affective disorder. Although the translation of genetic findings into routine clinical practice is being pursued at various levels, elaborate follow-up studies are typically necessary. The diagnostic investigation of rare genomic deletions/duplications (so-called copy number variants) in patients with schizophrenia is likely to represent one of the first examples of routine clinical application. The necessary prerequisites for this are currently being defined.

KEYWORDS:

Affective disorders; Copy number variant; Genetics; Genome-wide association study; Schizophrenia

PMID:
30758637
DOI:
10.1007/s00115-018-0670-6

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