Evidence map›Paper›PMID 41048387›Full record

ArticlePeerJ2025

Peng Wang, Xiao-Xia Hu, Jun-Wei Li

Abstract read
In one paragraph

Article in PeerJ, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Peng Wang *Department of Clinical Pharmacy, Jinhua People's Hospital, Affiliated Jinhua Hospital of Wenzhou Medical University, Jinhua, Zhejiang, China.ORCID 0000-0001-9325-359X
Xiao-Xia Hu *Department of Clinical Pharmacy, Affiliated Jinhua Hospital, Zhejiang University School of Medicine, Jinhua, Zhejiang, China.ORCID 0000-0002-8807-5036
Jun-Wei LiSchool of Pharmaceutical Sciences, Wenzhou Medical University, Wenzhou, ZheJiang, China.ORCID 0000-0002-0727-7112

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Objectives: The main goal of this study was to functionally characterize 30 CYP2C19 variants in citalopram metabolism, most of which were rare or novel variants identified in the Chinese Han population. Methods: An Results: In this study, compared to the wild-type enzyme (CYP2C19*1), 73% (22/30) of the CYP2C19 variants showed significantly different metabolic activities in citalopram metabolism. Among them, two variants, CYP2C19*29 and L16F, showed significantly increased intrinsic clearance (nearly 5-fold and 1.5-fold, respectively). Eighteen variants-CYP2C19*2C, *2F, *2G, *2J, *6, *18, *30, *31, *32, *33, N231T, R124Q, R261W, I327T, A430V, R125G, M255T, and I331V-exhibited significantly decreased intrinsic clearance (18.02-63.16%). Two variants, CYP2C19*3 and 35FS, demonstrated weak or no activity. Moreover, the remaining 27% (8/30) of the CYP2C19 variants showed similar metabolic activities to that of the wild-type enzyme. Conclusion: These CYP2C19 variants require specific attention from physicians and researchers, as their altered metabolic activities may influence the safety and efficacy of citalopram treatment. This work greatly expands the previously underexplored knowledge about the metabolic activities of rare or novel CYP2C19 variants in relation to citalopram medication. These findings may further facilitate the precision use of citalopram in personalized medicine.

Indexed as

CitalopramCytochrome P-450 CYP2C19Selective Serotonin Reuptake InhibitorsAnimalsEast Asian PeopleHumansPolymorphism, GeneticCitalopramCYP2C19 protein, humanCytochrome P-450 CYP2C19Selective Serotonin Reuptake InhibitorsAntidepressantCitalopramCytochrome P450 2C19Drug metabolismPharmacogeneticsPolymorphism

Identifiers

PMID41048387
PMCPMC12490513

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.