Evidence map›Paper›PMID 30758637›Full record

ReviewDer Nervenarzt2019

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

Markus M Nöthen, Franziska Degenhardt, Andreas J Forstner

Abstract readReview
PubMed Publisher
In one paragraph

Review in Der Nervenarzt, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. [Which breakthrough?]Der Nervenarzt · 2019
    Article
  3. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Markus M NöthenInstitut für Humangenetik, Universitätsklinikum Bonn, Sigmund-Freud-Str. 25, 53127, Bonn, Deutschland. markus.noethen@uni-bonn.de.
Franziska DegenhardtInstitut für Humangenetik, Universitätsklinikum Bonn, Sigmund-Freud-Str. 25, 53127, Bonn, Deutschland.
Andreas J ForstnerInstitut für Humangenetik, Universitätsklinikum Bonn, Sigmund-Freud-Str. 25, 53127, Bonn, Deutschland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Genetic Predisposition to DiseaseMental DisordersBipolar DisorderDNA Copy Number VariationsGenome-Wide Association StudyGenomicsHumansSchizophreniaAffective disordersCopy number variantGeneticsGenome-wide association studySchizophrenia

Identifiers

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.