Evidence map›Paper›PMID 27091189›Full record

ArticleBMC psychiatry2016

Genome-wide association study of antidepressant response: involvement of the inorganic cation transmembrane transporter activity pathway.

Enrico Cocchi, Chiara Fabbri, Changsu Han, Soo-Jung Lee, Ashwin A Patkar, Prakash S Masand, Chi-Un Pae, Alessandro Serretti

Open access · goldAbstract read
In one paragraph

Article in BMC psychiatry, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 2 pooled it
6.9field-weighted citation impact, top 3% 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

14 citing papers in PubMed, 2 syntheses or guidelines pooled it, 29 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Trial
  4. Trial
  5. Genetics and Neurobiology of Treatment-Resistant Depression-A Review.International journal of molecular sciences · 2025
    Review
  6. Article
  7. Article
  8. Article
  9. Genes Involved in Neurodevelopment, Neuroplasticity and Major Depression: No Association forClinical psychopharmacology and neuroscience : the official scientific journal of the Korean College of Neuropsychopharmacology · 2019
    Article
  10. Review
  11. The Genetics of Treatment-Resistant Depression: A Critical Review and Future Perspectives.The international journal of neuropsychopharmacology · 2019
    Review
  12. Review
  13. Article
  14. 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

8 authors at 4 institutions in 3 countries.

Enrico CocchiDepartment of Biomedical and NeuroMotor Sciences, University of Bologna, Bologna, Italy.
Chiara FabbriDepartment of Psychiatry, Korea University, College of Medicine, Seoul, Republic of Korea.
Changsu HanDepartment of Psychiatry, Korea University, College of Medicine, Seoul, Republic of Korea.
Soo-Jung LeeDepartment of Psychiatry, The Catholic University of Korea College of Medicine, Seoul, Republic of Korea.
Ashwin A PatkarDepartment of Psychiatry and Behavioural Sciences, Duke University Medical Center, Durham, NC, USA.
Prakash S MasandGlobal Medical Education, New York, NY, USA.
Chi-Un PaeDepartment of Psychiatry, The Catholic University of Korea College of Medicine, Seoul, Republic of Korea. pae@catholic.ac.kr.
Alessandro SerrettiDepartment of Biomedical and NeuroMotor Sciences, University of Bologna, Bologna, Italy.
Duke University · USKorea University · KRUniversity of Bologna · ITCatholic University of Korea · KR

Funding

TREATMENT RESISTANT DEPRESSION-278990003N01MH090003 · NIMH · UNIVERSITY OF TEXAS SW MED CTR/DALLAS · 1999 to 2003
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NIMH NIH HHS N01 MH090003
6 · The paper itself

Abstract

backgroundGenome-wide association studies (GWAS) represent the current frontier in pharmacogenomics. Thousands of subjects of Caucasian ancestry have been included in previous GWAS investigating antidepressant response. GWAS focused on this phenotype are lacking in Asian populations.

methodsA sample of 109 major depressive disorder (MDD) patients of Korean origin in antidepressant treatment was collected. Phenotypes were response and remission according to the Hamilton Rating Scale for Depression (HRSD). Genome-wide genotyping was performed using the Illumina Human Omni2.5-8 platform. The same phenotypes were used in the STAR*D level 1 (n = 1677) for independent replication. In order to corroborate findings and increase the comparability between the two datasets, three levels of analysis (SNPs, genes and pathways) were carried out. Bonferroni correction, permutations, and replication across samples were used to reduce the risk of false positives.

resultsAmong the genes replicated across the two samples (permutated p < 0.05 in both of them), CTNNA3 appeared promising. The inorganic cation transmembrane transporter activity pathway (GO:0022890) was associated with antidepressant response in both samples (p = 2.9e-5 and p = 0.001 in the Korean and STAR*D samples, respectively) and this pathway included CACNA1A, CACNA1C, and CACNB2 genes.

conclusionsThe present study supported the involvement of genes coding for subunits of L-type voltage-gated calcium channel in antidepressant efficacy across different ethnicities but replication of findings is required before any definitive statement.

Indexed as

AdultAntidepressive AgentsAsian PeopleFemaleGenome-Wide Association StudyGenotypeHumansMajor Depressive DisorderMaleOrganic Cation Transport ProteinsPhenotypePolymorphism, Single NucleotideAntidepressive AgentsOrganic Cation Transport ProteinsAntidepressantCalcium channelCation transmembrane transporterGeneGWASMajor depressionPathwayPharmacogenomics

Identifiers

PMID27091189
PMCPMC4836090
OpenAlexW2336419809

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.