Evidence map›Paper›PMID 42876187›Full record

ArticleClinical pharmacology and therapeutics2026

Reprocessing Mass Spectra from Therapeutic Drug Monitoring to Unveil Proton Pump Inhibitor Use and Quantify Phenoconversion of Escitalopram Metabolism in CYP2C19-Genotyped Patients.

Kristine Hole, Birgit M Wollmann, Julia Carolin Stingl, Espen Molden

Abstract read
In one paragraph

Article in Clinical pharmacology and therapeutics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

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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

4 authors.

Kristine HoleCenter for Psychopharmacology, Diakonhjemmet Hospital, Oslo, Norway.ORCID https://orcid.org/0000-0001-7300-5329
Birgit M WollmannCenter for Psychopharmacology, Diakonhjemmet Hospital, Oslo, Norway.ORCID https://orcid.org/0000-0001-7261-275X
Julia Carolin StinglDepartment of Clinical Pharmacology and Pharmacoepidemiology, University Hospital Heidelberg, Heidelberg, Germany.ORCID https://orcid.org/0000-0002-9684-7753
Espen MoldenCenter for Psychopharmacology, Diakonhjemmet Hospital, Oslo, Norway.ORCID https://orcid.org/0000-0001-6190-2751

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Escitalopram is a frequently prescribed antidepressant drug. CYP2C19 genotype is a major determinant of escitalopram metabolism and treatment outcome. However, real-life studies show a high degree of genotype-phenotype mismatch in escitalopram metabolism. The present study aimed to identify comedication with proton pump inhibitors (PPIs) and quantify phenoconversion of escitalopram metabolism in CYP2C19-genotyped patients by reprocessing high-resolution mass spectra from therapeutic drug monitoring (TDM) analyses. Patients were included from a combined TDM/pharmacogenetics (PGx) laboratory facility in Oslo, Norway. TDM profiles of escitalopram and CYP2C19 genotypes were available in the laboratory database. Reprocessing of high-resolution mass spectra by exact mass and fragment detection identified possible comedication with pantoprazole, esomeprazole/omeprazole or lansoprazole using mzCloud reference library. Patients were grouped as normal metabolizers (NMs), intermediate metabolizers (IMs), poor metabolizers (PMs), rapid metabolizers (RM), or ultrarapid metabolizers (UM). Primary outcome measure was N-desmethylescitalopram-to-escitalopram metabolic ratio (MR; CYP2C19 biomarker) in UMs vs. PMs. 2818 patients were included, constituting 2373 without and 445 (15.8%) with PPIs. Most patients were females (64.2%). Regarding CYP2C19 phenotype distribution, the cohort comprised 39.3% NMs, 29.3% IMs, 2.6% PMs, 24.6% RMs, and 4.2% UMs. Escitalopram MR was 4.5-fold higher in CYP2C19 UMs vs. PMs without PPIs (P < 0.001), while this difference was 2.8-fold in pantoprazole users (P < 0.001), and 1.8-fold in esomeprazole/omeprazole users (P = 0.2). In conclusion, PPIs show significant phenoconversion of CYP2C19-mediated escitalopram metabolism with esomeprazole/omeprazole exhibiting a stronger effect than pantoprazole. The novel method for identification of interacting comedications in TDM samples illustrates the innovative potential of high-resolution mass spectrometry in precision medicine.

Identifiers

PMID42876187
PMCPMC13669680

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