Evidence map›Paper›PMID 40465332›Full record

SynthesisClinical and translational science2025

Comprehensive Characterization of Antidepressant Pharmacogenetics: A Systematic Review of Studies in Major Depressive Disorder.

Caroline W Grant, Karina Delaney, Linsey E Jackson, Justin Bobo, Leslie C Hassett, Liewei Wang, Richard M Weinshilboum, Paul E Croarkin, Melanie T Gentry, Ann M Moyer and 1 more

Abstract readSystematic Review
In one paragraph

Synthesis in Clinical and translational science, 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. Trial
  3. Big data and psychiatry: advances, constraints and future directions.World psychiatry : official journal of the World Psychiatric Association (WPA) · 2026
    Article
  4. Review
  5. Review
  6. Review
  7. Article
  8. 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

11 authors.

Caroline W GrantDepartment of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, Minnesota, USA.ORCID 0000-0001-9342-2138
Karina DelaneyDepartment of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, Minnesota, USA.ORCID 0009-0004-5052-167X
Linsey E JacksonDepartment of Clinical and Translational Sciences, Mayo Clinic, Rochester, Minnesota, USA.ORCID 0000-0002-6613-7208
Justin BoboDepartment of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, Minnesota, USA.ORCID 0009-0008-8656-3408
Leslie C HassettMayo Medical Libraries, Mayo Clinic College of Medicine, Rochester, Minnesota, USA.ORCID 0000-0002-1889-8387
Liewei WangDepartment of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, Minnesota, USA.ORCID 0000-0003-3818-8531
Richard M WeinshilboumDepartment of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, Minnesota, USA.ORCID 0000-0002-4911-7985
Paul E CroarkinDepartment of Psychiatry and Psychology, Mayo Clinic, Rochester, Minnesota, USA.ORCID 0000-0001-6843-6503
Melanie T GentryDepartment of Psychiatry and Psychology, Mayo Clinic, Rochester, Minnesota, USA.ORCID 0000-0002-9484-3206
Ann M MoyerDepartment of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA.ORCID 0000-0003-2590-7218
Arjun P AthreyaDepartment of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, Minnesota, USA.ORCID 0000-0001-9764-1768

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pharmacogenetics is a promising strategy to facilitate individualized care for patients with Major Depressive Disorder (MDD). Research is ongoing to identify the optimal genetic markers for predicting outcomes to antidepressant therapies. The primary aim of this systematic review was to summarize antidepressant pharmacogenetic studies to enhance understanding of the genes, variants, datatypes/methodologies, and outcomes investigated in the context of MDD. The secondary aim was to identify clinical genetic panels indicated for antidepressant prescribing and summarize their genes and variants. Screening of N = 5793 articles yielded N = 390 for inclusion, largely comprising adult (≥ 18 years) populations. Top-studied variants identified in the search were discussed and compared with those represented on the N = 34 clinical genetic panels that were identified. Summarization of articles revealed sources of heterogeneity across studies and low rates of replicability of pharmacogenetic associations. Heterogeneity was present in outcome definitions, treatment regimens, and differential inclusion of mediating variables in analyses. Efficacy outcomes (i.e., response, remission) were studied at greater frequency than adverse-event outcomes. Studies that used advanced analytical approaches, such as machine learning, to integrate variants with complimentary biological datatypes were fewer in number but achieved higher rates of significant associations with treatment outcomes than candidate variant approaches. As large biological datasets become more prevalent, machine learning will be an increasingly valuable tool for parsing the complexity of antidepressant response. This review provides valuable context and considerations surrounding pharmacogenetic associations in MDD which will help inform future research and translation efforts for guiding antidepressant care.

Indexed as

Antidepressive AgentsMajor Depressive DisorderPharmacogeneticsHumansPharmacogenomic TestingPharmacogenomic VariantsTreatment OutcomeAntidepressive Agentsmajor depressive disorderMDDpharmacogenetics

Identifiers

PMID40465332
PMCPMC12135885

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.