Evidence map›Paper›PMID 32084067›Full record

ReviewInternational clinical psychopharmacology2020

Genetics and major depressive disorder: clinical implications for disease risk, prognosis and treatment.

Chiara Fabbri, Stuart Montgomery, Cathryn M Lewis, Alessandro Serretti

Open access · hybridAbstract readReview
In one paragraph

Review in International clinical psychopharmacology, 2020. 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
4.1field-weighted citation impact, top 6% 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, 34 citations in OpenAlex.

  1. Article
  2. Article
  3. Navigating the Intersection of Technology and Depression Precision Medicine.Advances in experimental medicine and biology · 2024
    Review
  4. Article
  5. Article
  6. Clinical Utility of Fluid Biomarker in Depressive Disorder.Clinical psychopharmacology and neuroscience : the official scientific journal of the Korean College of Neuropsychopharmacology · 2022
    Review
  7. Review
  8. Genetics in psychiatry: Methods, clinical applications and future perspectives.PCN reports : psychiatry and clinical neurosciences · 2022
    Review
  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 3 institutions in 2 countries.

Chiara FabbriSocial, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London.
Stuart MontgomeryImperial College School of Medicine, London, UK.
Cathryn M LewisSocial, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London.
Alessandro SerrettiDepartment of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy.
King's College London · GBImperial College London · GBUniversity of Bologna · IT

Funding

Department of Health
6 · The paper itself

Abstract

In the post-genomic era, genetics has led to limited clinical applications in the diagnosis and treatment of major depressive disorder (MDD). Variants in genes coding for cytochrome enzymes are included in guidelines for assisting in antidepressant choice and dosing, but there are no recommendations involving genes responsible for antidepressant pharmacodynamics and no consensus applications for guiding diagnosis or prognosis. However, genetics has contributed to a better understanding of MDD pathogenesis and the mechanisms of antidepressant action, also thanks to recent methodological innovations that overcome the challenges posed by the polygenic architecture of these traits. Polygenic risk scores can be used to estimate the risk of disease at the individual level, which may have clinical relevance in cases with extremely high scores (e.g. top 1%). Genetic studies have also shed light on a wide genetic overlap between MDD and other psychiatric disorders. The relationships between genes/pathways associated with MDD and known drug targets are a promising tool for drug repurposing and identification of new pharmacological targets. Increase in power thanks to larger samples and methods integrating genetic data with gene expression, the integration of common variants and rare variants, are expected to advance our knowledge and assist in personalized psychiatry.

Indexed as

Drug DevelopmentDrug RepositioningGenetic Predisposition to DiseaseHumansMajor Depressive DisorderMultifactorial InheritancePrecision Medicine

Identifiers

PMID32084067
PMCPMC7390499
OpenAlexW3007381443

What OpenQuestion 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 OpenQuestion graph.