Evidence map›Paper›PMID 39827221›Full record

ReviewMolecular psychiatry2025

Treatment-resistant depression: role of genetic factors in the perspective of clinical stratification and treatment personalisation.

Chiara Fabbri

Abstract readReview
PubMed Publisher
In one paragraph

Review in Molecular psychiatry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
–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

8 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Rethinking the Treatment-Resistant Depression.Advances in experimental medicine and biology · 2026
    Review
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
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

1 author.

Chiara FabbriDepartment of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy. chiara.fabbri41@unibo.it.ORCID 0000-0003-0276-7865

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Treatment-resistant depression (TRD) is associated with chronic depression, suicidal behaviours, and reduced quality of life. TRD has a demonstrated genetic component, estimated around 8% based on common genetic variation in unrelated individuals. However, only six genome-wide association studies of TRD were published, and no replicated signals at locus or gene level have been identified; furthermore, apparently opposite results were reported in terms of genetic overlap between TRD and other traits. Other than limited power, an important issue of previous studies was the scarce consideration of TRD heterogeneity, as TRD likely comprises different groups and talking about TRDs could be more appropriate. This review points out important issues in the definition of TRD and differences across samples included in previous studies, which can be partly responsible for the inconsistency across results. Different definitions of TRD should not be expected to have similar genetic profiles, and the whole TRD group can partitioned into subgroups, based on clinical and biological features, to increase reproducibility, as exemplified by recent findings. This can be a key factor to develop/repurpose targeted treatments, or simply to aid a more personalised prescription of available medications compared to current clinical practice, that is largely concentrated on the prescription of a limited number of antidepressants compared to those available.

Indexed as

Depressive Disorder, Treatment-ResistantAntidepressive AgentsGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansPrecision MedicineQuality of LifeAntidepressive Agents

Identifiers

What OpenQuestion holds

Textmetadata
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.