Evidence map›Paper›PMID 30546092›Full record

ArticleTranslational psychiatry2018

Improving pharmacogenetic prediction of extrapyramidal symptoms induced by antipsychotics.

Daniel Boloc, Anna Gortat, Jia Qi Cheng-Zhang, Susana García-Cerro, Natalia Rodríguez, Mara Parellada, Jeronimo Saiz-Ruiz, Manolo J Cuesta, Patricia Gassó, Amalia Lafuente and 2 more

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in Translational psychiatry, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
3.1field-weighted citation impact, top 8% 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, 1 synthesis or guideline pooled it, 25 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. Article
  6. Biomedicines · 2022
    Article
  7. Article
  8. Review
  9. A primer on machine learning techniques for genomic applications.Computational and structural biotechnology journal · 2021
    Review
  10. Article
  11. Challenges and Future Prospects of Precision Medicine in Psychiatry.Pharmacogenomics and personalized medicine · 2020
    Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors at 3 institutions in 1 country.

Daniel BolocDepartment of Medicine, University of Barcelona, Barcelona, Spain.
Anna GortatDepartment of Clinical Foundations, Pharmacology Unit, University of Barcelona, Barcelona, Spain.
Jia Qi Cheng-ZhangDepartment of Clinical Foundations, Pharmacology Unit, University of Barcelona, Barcelona, Spain.
Susana García-CerroDepartment of Clinical Foundations, Pharmacology Unit, University of Barcelona, Barcelona, Spain.
Natalia RodríguezDepartment of Clinical Foundations, Pharmacology Unit, University of Barcelona, Barcelona, Spain.
Mara ParelladaCentro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Carlos III Health Institute, Barcelona, Spain.
Jeronimo Saiz-RuizCentro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Carlos III Health Institute, Barcelona, Spain.
Manolo J CuestaCentro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Carlos III Health Institute, Barcelona, Spain.
Patricia GassóDepartment of Clinical Foundations, Pharmacology Unit, University of Barcelona, Barcelona, Spain.
Amalia LafuenteDepartment of Clinical Foundations, Pharmacology Unit, University of Barcelona, Barcelona, Spain.
Miquel BernardoDepartment of Medicine, University of Barcelona, Barcelona, Spain. bernardo@clinic.ub.es.
Sergi MasDepartment of Clinical Foundations, Pharmacology Unit, University of Barcelona, Barcelona, Spain. sergimash@ub.edu.ORCID http://orcid.org/0000-0003-3336-6298
Universitat de Barcelona · ESInstituto de Salud Carlos III · ESUniversidad de Alcalá · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In previous work we developed a pharmacogenetic predictor of antipsychotic (AP) induced extrapyramidal symptoms (EPS) based on four genes involved in mTOR regulation. The main objective is to improve this predictor by increasing its biological plausibility and replication. We re-sequence the four genes using next-generation sequencing. We predict functionality "in silico" of all identified SNPs and test it using gene reporter assays. Using functional SNPs, we develop a new predictor utilizing machine learning algorithms (Discovery Cohort, N = 131) and replicate it in two independent cohorts (Replication Cohort 1, N = 113; Replication Cohort 2, N = 113). After prioritization, four SNPs were used to develop the pharmacogenetic predictor of AP-induced EPS. The model constructed using the Naive Bayes algorithm achieved a 66% of accuracy in the Discovery Cohort, and similar performances in the replication cohorts. The result is an improved pharmacogenetic predictor of AP-induced EPS, which is more robust and generalizable than the original.

Indexed as

AdultAntipsychotic AgentsCohort StudiesComputer SimulationFemaleHumansMachine LearningMalePharmacogenomic TestingPolymorphism, Single NucleotideRisperidoneYoung AdultAntipsychotic AgentsRisperidone

Identifiers

PMID30546092
PMCPMC6293322
OpenAlexW2903801932

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.