Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Review
. 2022 Mar;22(2):136-144.
doi: 10.1038/s41397-022-00268-6. Epub 2022 Jan 31.

Evaluation of the EMPAR study population on the basis of metabolic phenotypes of selected pharmacogenes

Affiliations
Review

Evaluation of the EMPAR study population on the basis of metabolic phenotypes of selected pharmacogenes

Jochen Fracowiak et al. Pharmacogenomics J. 2022 Mar.

Abstract

The impact of genetic variability of pharmacogenes as a possible risk factor for adverse drug reactions is elucidated in the EMPAR (Einfluss metabolischer Profile auf die Arzneimitteltherapiesicherheit in der Routineversorgung/English: influence of metabolic profiles on the safety of drug therapy in routine care) study. EMPAR evaluates possible associations of pharmacogenetically predicted metabolic profiles relevant for the metabolism of frequently prescribed cardiovascular drugs. Based on a German study population of 10,748 participants providing access to healthcare claims data and DNA samples for pharmacogenetic assessment, first analyses were performed and evaluated. The aim of this first evaluation was the characterization of the study population with regard to general parameters such as age, gender, comorbidity, and polypharmacy at baseline (baseline year) as well as important combinations of cardiovascular drugs with relevant genetic variants and predicted metabolic phenotypes. The study was registered in the German Clinical Trials Register (DRKS) on July 6, 2018 (DRKS00013909).

PubMed Disclaimer

Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1. Recruitment scheme of the EMPAR study in 2018–2020.
Dropouts occurred in the provision of suitable DNA samples (11.1% in 2018–2019 and 13.1% in 2020), due to insufficient quality or a lack of genotype data (2.2%) and due to insufficient quality of healthcare claims data for matching (0.4%). PGx pharmacogenetic.
Fig. 2
Fig. 2. Age and sex evaluation.
Age distributions of male and female participants in each study collective of the complete study population (anticoagulant: anticoagulant/antiplatelet collective, cholesterol reducer: cholesterol-lowering drug collective, Y-diagnosis: Y57.9! diagnosis collective) at baseline.
Fig. 3
Fig. 3. Elixhauser comorbidity score distributions (in %).
All diagnosis codes (ICD-10) of the individual baseline year were taken into account. The score distribution reflects the comorbidity status of the complete study population in the baseline year grouped by age and gender.
Fig. 4
Fig. 4. Abundance of concomitant medication prescribed during the individual baseline year grouped by age and collective.
Anticoagulant: anticoagulant/antiplatelet.
Fig. 5
Fig. 5. Relevant actionable variants in the EMPAR population.
A Number of carriers of pharmacogenetic markers with PharmGKB Evidence level 1A/1B with regard to cardiovascular indications. Major allele here defined as wild type (W); M: minor allele or actionable variant respectively; NA: information not available; MW: actionable variant/wild type. B Proportions of participants in the complete study population with 1, 2, 3, 4, and ≥5 actionable variants shown in A.

References

    1. Meier F, Maas R, Sonst A, Patapovas A, Müller F, Plank-Kiegele B, et al. Adverse drug events in patients admitted to an emergency department: an analysis of direct costs. Pharmacoepidemiol Drug Saf. 2015;24:176–86. doi: 10.1002/pds.3663. - DOI - PubMed
    1. Leendertse AJ, Egberts AC, Stoker LJ, van den Bemt PM. Frequency of and risk factors for preventable medication-related hospital admissions in the Netherlands. Arch Intern Med. 2008;168:1890–6. - PubMed
    1. Ji Y, Skierka JM, Blommel JH, Moore BE, VanCuyk DL, Bruflat JK, et al. Preemptive pharmacogenomic testing for precision medicine: a comprehensive analysis of five actionable pharmacogenomic genes using next-generation DNA sequencing and a customized CYP2D6 genotyping cascade. J Mol Diagn. 2016;18:438–45. doi: 10.1016/j.jmoldx.2016.01.003. - DOI - PMC - PubMed
    1. Unternehmensdaten | Die Techniker – Presse und Politik. 2021 https://www.tk.de/presse/tk-unternehmensdaten-2051018. Accessed 20 July 2020.
    1. Ingelman-Sundberg M. Human drug metabolising cytochrome P450 enzymes: properties and polymorphisms. Naunyn Schmiedebergs Arch Pharm. 2004;369:89–104. doi: 10.1007/s00210-003-0819-z. - DOI - PubMed

Publication types