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Pharmacogenetics and Pharmacogenomics in Personalized Medicine
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Pharmacogenetics and Pharmacogenomics in Personalized Medicine

A special issue of Journal of Personalized Medicine (ISSN 2075-4426). This special issue belongs to the section "Pharmacogenetics".

Deadline for manuscript submissions: closed (5 August 2023) | Viewed by 8843

Special Issue Editor

Dr. Su-Jun Lee

E-Mail Website
Guest Editor
Department of Pharmacology and Pharmacogenomics Research Center, College of Medicine, Inje University, Busan, Republic of Korea
Interests: genetic polymorphisms; functional genomics; adverse drug reactions; pharmacogenomics; personalized medicine; drug metabolism;
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Pharmacogenomics has made numerous contributions to understanding the variability and explaining the uncertainty of drug responses, and is recognized as a cornerstone of personalized medicine in the future. For the successful establishment of personalized medicine, it is very important to discover genetic and clinical factors that affect drug responses and to share them in a Special Issue of the Journal of Personalized Medicine.

The aim and scope of the Special Issue is to discover and present genetic variants, biomarkers, and research tools that can be helpful in understanding drug side effects, drug resistance, and human susceptibility to diseases.

Cutting-edge research in pharmacogenomics could be described in two stages. First, it involves studying “the interaction network” after integrating various information obtained from functional genomics, proteomics, transcriptomics, metabolomics, and medical informatics. Second, the cutting-edge research in pharmacogenomics is focused on creating a standard guideline that can be personalized and applied to humans by verifying the research results obtained through integrated network analysis in prospective clinical trials.

Suitable topics for this Special Issue include, but are not limited to: pharmacogenomics with human diseases or drugs, such as cardiovascular diseases; psychiatry diseases; gastrointestinal diseases; cancers; drug addictions; drug sensitivities; drug resistances; and a broad range of adverse drug reactions. In addition, authors are encouraged to present novel pharmacogenetic assays, methodologies, tools, modellings, and functional data. We welcome original research papers, reviews, and updated overviews in pharmacogenetics and pharmacogenomics.

Dr. Su-Jun Lee
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Personalized Medicine is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • personalized medicine
  • pharmacogenomics
  • functional genomics
  • genetic polymorphism
  • disease susceptibility
  • adverse drug reaction

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Published Papers (4 papers)

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Research

13 pages, 502 KiB  
Article
Exploring the Influence of VDR Genetic Variants TaqI, ApaI, and FokI on COVID-19 Severity and Long-COVID-19 Symptoms
by Ghayda’ Alhammadin, Yazun Jarrar, Abdalla Madani and Su-Jun Lee
J. Pers. Med. 2023, 13(12), 1663; https://doi.org/10.3390/jpm13121663 - 28 Nov 2023
Cited by 2 | Viewed by 1838
Abstract
There is increasing evidence regarding the importance of vitamin D in the prognosis of coronavirus disease 2019 (COVID-19). Genetic variants in the vitamin D receptor (VDR) gene affect the response to vitamin D and have been linked to various diseases. This [...] Read more.
There is increasing evidence regarding the importance of vitamin D in the prognosis of coronavirus disease 2019 (COVID-19). Genetic variants in the vitamin D receptor (VDR) gene affect the response to vitamin D and have been linked to various diseases. This study investigated the associations of the major VDR genetic variants ApaI, FokI, and TaqI with the severity and long post-infection symptoms of COVID-19. In total, 100 Jordanian patients with confirmed COVID-19 were genotyped for the VDR ApaI, FokI, and TaqI variants using the polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method. COVID-19 severity, the most commonly reported long-COVID-19 symptoms that lasted for >4 weeks from the onset of infection, and other variables were analyzed according to VDR genetic variants. In this study, ApaI and FokI polymorphisms showed no significant associations with COVID-19 severity (p > 0.05). However, a significant association was detected between the TaqI polymorphism and the severity of symptoms after infection with the SARS-CoV-2 virus (p = 0.04). The wild-type TaqI genotype was typically present in patients with mild illness, whereas the heterozygous TaqI genotype was present in asymptomatic patients. With regard to long-COVID-19 symptoms, the VDR heterozygous ApaI and wild-type TaqI genotypes were significantly associated with persistent fatigue and muscle pain after COVID-19 (p ˂ 0.05). Most carriers of the heterozygous ApaI genotype and carriers of the wild-type TaqI genotype reported experiencing fatigue and muscle pain that lasted for more than 1 month after the onset of COVID-19. Furthermore, the TaqI genotype was associated with persistent shortness of breath after COVID-19 (p = 0.003). Shortness of breath was more common among individuals with homozygous TaqI genotype than among individuals with the wild-type or heterozygous TaqI genotype. VDR TaqI is a possible genetic variant related to both COVID-19 severity and long-COVID-19 symptoms among Jordanian individuals. The associations between VDR TaqI polymorphisms and long-COVID-19 symptoms should be investigated in larger and more diverse ethnic populations. Full article
(This article belongs to the Special Issue Pharmacogenetics and Pharmacogenomics in Personalized Medicine)
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12 pages, 1152 KiB  
Article
Patient-Level Exposure to Actionable Pharmacogenomic Medications in a Nationally Representative Insurance Claims Database
by Monica L. Bianchini, Christina L. Aquilante, David P. Kao, James L. Martin and Heather D. Anderson
J. Pers. Med. 2023, 13(11), 1574; https://doi.org/10.3390/jpm13111574 - 3 Nov 2023
Viewed by 1081
Abstract
Background: The prevalence of exposure to pharmacogenomic medications is well established but little is known about how long patients are exposed to these medications. Aim: Our objective was to describe the amount of exposure to actionable pharmacogenomic medications using patient-level measures among a [...] Read more.
Background: The prevalence of exposure to pharmacogenomic medications is well established but little is known about how long patients are exposed to these medications. Aim: Our objective was to describe the amount of exposure to actionable pharmacogenomic medications using patient-level measures among a large nationally representative population using an insurance claims database. Methods: Our retrospective cohort study included adults (18+ years) from the IQVIA PharMetrics® Plus for Academics claims database with incident fills of 72 Clinical Pharmacogenetics Implementation Consortium level A, A/B, or B medications from January 2012 through September 2018. Patient-level outcomes included the proportion of days covered (PDC), number of fills, and average days supplied per fill over a 12-month period. Results: Over 1 million fills of pharmacogenetic medications were identified for 605,355 unique patients. The mean PDC for all medications was 0.21 (SD 0.3), suggesting patients were exposed 21% (77 days) of the year. Medications with the highest PDC (0.55–0.89) included ivacaftor, tamoxifen, clopidogrel, HIV medications, transplant medications, and statins; with the exception of statins, these medications were initiated by fewer patients. Pharmacogenomic medications were filled an average of 2.8 times (SD 3.0, range 1–81) during the year following the medication’s initiation, and the average days supplied for each fill was 22.3 days (SD 22.4, range 1–180 days). Conclusion: Patient characteristics associated with more medication exposure were male sex, older age, and comorbid chronic conditions. Prescription fill data provide patient-level exposure metrics that can further our understanding of pharmacogenomic medication utilization and help inform opportunities for pharmacogenomic testing. Full article
(This article belongs to the Special Issue Pharmacogenetics and Pharmacogenomics in Personalized Medicine)
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16 pages, 2064 KiB  
Article
Pharmacogenetic Variants Associated with Fluoxetine Pharmacokinetics from a Bioequivalence Study in Healthy Subjects
by Carlos Alejandro Díaz-Tufinio, José Antonio Palma-Aguirre and Vanessa Gonzalez-Covarrubias
J. Pers. Med. 2023, 13(9), 1352; https://doi.org/10.3390/jpm13091352 - 1 Sep 2023
Cited by 1 | Viewed by 2889
Abstract
Fluoxetine is one of the most prescribed antidepressants, yet it still faces challenges due to high intersubject variability in patient response. Mainly metabolized by the highly polymorphic gene CYP2D6, important differences in plasma concentrations after the same doses are found among individuals. [...] Read more.
Fluoxetine is one of the most prescribed antidepressants, yet it still faces challenges due to high intersubject variability in patient response. Mainly metabolized by the highly polymorphic gene CYP2D6, important differences in plasma concentrations after the same doses are found among individuals. This study investigated the association of fluoxetine pharmacokinetics (PK) with pharmacogenetic variants. A bioequivalence crossover trial (two sequences, two periods) was conducted with fluoxetine 20 mg capsules, in 24 healthy subjects. Blood samples for fluoxetine determination were collected up to 72 h post-dose. Subjects were genotyped and single nucleotide variants (SNV) were selected using a candidate gene approach, and then associated with the PK parameters. Bioequivalence was confirmed for the test formulation. We found 34 SNV on 10 genes with a quantifiable impact on the PK of fluoxetine in the randomized controlled trial. Out of those, 29 SNVs belong to 7 CYPs (CYP1A2, CYP2B6, CYP2C9, CYP2C19, CYP2D6, CYP3A4, CYP3A5), and 5 SNVs to 3 genes impacting the pharmacodynamics and efficacy of fluoxetine (SLC6A4, TPH1, ABCB1). Moreover, decreased/no function SNVs of CYP2D6 (rs1065852, rs28371703, rs1135840) and CYP2C19 (rs12769205) were confirmed phenotypically. Our research contributes to deepening the catalog of genotype-phenotype associations in pharmacokinetics, aiming to increase pharmacogenomics knowledge for rational treatment schemes of antidepressants. Full article
(This article belongs to the Special Issue Pharmacogenetics and Pharmacogenomics in Personalized Medicine)
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11 pages, 961 KiB  
Article
Tumor Microenvironment and Genes Affecting the Prognosis of Temozolomide-Treated Glioblastoma
by Yena Jang, Wooyong Cheong, Gyurin Park, Yeongmin Kim, Junbeom Ha and Sangzin Ahn
J. Pers. Med. 2023, 13(2), 188; https://doi.org/10.3390/jpm13020188 - 20 Jan 2023
Cited by 2 | Viewed by 2389
Abstract
Glioblastoma (GBM) is the most frequent primary brain tumor in adults and has a poor prognosis due to its resistance to Temozolomide (TMZ). However, there is limited research regarding the tumor microenvironment and genes related to the prognosis of TMZ-treated GBM patients. This [...] Read more.
Glioblastoma (GBM) is the most frequent primary brain tumor in adults and has a poor prognosis due to its resistance to Temozolomide (TMZ). However, there is limited research regarding the tumor microenvironment and genes related to the prognosis of TMZ-treated GBM patients. This study aimed to identify putative transcriptomic biomarkers with predictive value in patients with GBM who were treated with TMZ. Publicly available datasets from The Cancer Genome Atlas and Gene Expression Omnibus were analyzed using CIBERSORTx and Weighted Gene Co-expression Network Analysis (WGCNA) to obtain types of highly expressed cell types and gene clusters. Differentially Expressed Genes analysis was performed and was intersected with the WGCNA results to obtain a candidate gene list. Cox proportional-hazard survival analysis was performed to acquire genes related to the prognosis of TMZ-treated GBM patients. Inflammatory microglial cells, dendritic cells, myeloid cells, and glioma stem cells were highly expressed in GBM tissue, and ACP7, EPPK1, PCDHA8, RHOD, DRC1, ZIC3, and PRLR were significantly associated with survival. While the listed genes have been previously reported to be related to glioblastoma or other types of cancer, ACP7 was identified as a novel gene related to the prognosis of GBM. These findings may have potential implications for developing a diagnostic tool to predict GBM resistance and optimize treatment decisions. Full article
(This article belongs to the Special Issue Pharmacogenetics and Pharmacogenomics in Personalized Medicine)
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