Evidence map›Paper›PMID 35101157›Full record

ReviewBJPsych open2022

Genomic and neuroimaging approaches to bipolar disorder.

Mojtaba Oraki Kohshour, Sergi Papiol, Christopher R K Ching, Thomas G Schulze

Open access · goldAbstract readReview
In one paragraph

Review in BJPsych open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
4.3field-weighted citation impact, top 5% of its field
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

11 citing papers in PubMed, 24 citations in OpenAlex.

  1. Review
  2. Early diagnosis of bipolar disorder.World journal of psychiatry · 2025
    Review
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Review
  10. Article
  11. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 4 institutions in 3 countries.

Mojtaba Oraki KohshourInstitute of Psychiatric Phenomics and Genomics, University Hospital LMU Munich, Germany; and Department of Immunology, School of Medicine, Ahvaz Jundishapur University of Medical Sciences, Iran.ORCID https://orcid.org/0000-0002-1357-2636
Sergi PapiolInstitute of Psychiatric Phenomics and Genomics, University Hospital LMU Munich, Germany; and Department of Psychiatry and Psychotherapy, University Hospital LMU Munich, Germany.ORCID https://orcid.org/0000-0001-9366-8728
Christopher R K ChingImaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, USA.ORCID https://orcid.org/0000-0003-2921-3408
Thomas G SchulzeInstitute of Psychiatric Phenomics and Genomics, University Hospital LMU Munich, Germany; and Department of Psychiatry and Behavioral Sciences, SUNY Upstate Medical University, USA.ORCID https://orcid.org/0000-0001-6624-2975
Ahvaz Jundishapur University of Medical Sciences · IRLMU Klinikum · DESUNY Upstate Medical University · USUniversity of Southern California · US

Funding

Dr. Lisa Oehler Foundation (Kassel, Germany)
6 · The paper itself

Abstract

backgroundTo date, besides genome-wide association studies, a variety of other genetic analyses (e.g. polygenic risk scores, whole-exome sequencing and whole-genome sequencing) have been conducted, and a large amount of data has been gathered for investigating the involvement of common, rare and very rare types of DNA sequence variants in bipolar disorder. Also, non-invasive neuroimaging methods can be used to quantify changes in brain structure and function in patients with bipolar disorder.

aimsTo provide a comprehensive assessment of genetic findings associated with bipolar disorder, based on the evaluation of different genomic approaches and neuroimaging studies.

methodWe conducted a PubMed search of all relevant literatures from the beginning to the present, by querying related search strings.

resultsANK3, CACNA1C, SYNE1, ODZ4 and TRANK1 are five genes that have been replicated as key gene candidates in bipolar disorder pathophysiology, through the investigated studies. The percentage of phenotypic variance explained by the identified variants is small (approximately 4.7%). Bipolar disorder polygenic risk scores are associated with other psychiatric phenotypes. The ENIGMA-BD studies show a replicable pattern of lower cortical thickness, altered white matter integrity and smaller subcortical volumes in bipolar disorder.

conclusionsThe low amount of explained phenotypic variance highlights the need for further large-scale investigations, especially among non-European populations, to achieve a more complete understanding of the genetic architecture of bipolar disorder and the missing heritability. Combining neuroimaging data with genetic data in large-scale studies might help researchers acquire a better knowledge of the engaged brain regions in bipolar disorder.

Indexed as

Bipolar disordergenome-wide association studiesneuroimagingwhole-exome sequencingwhole-genome sequencing

Identifiers

PMID35101157
PMCPMC8867895
OpenAlexW4210472784

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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 Socratic graph.