Association Studies in Clinical Pharmacogenetics—Volume II

A special issue of Pharmaceutics (ISSN 1999-4923). This special issue belongs to the section "Clinical Pharmaceutics".

Deadline for manuscript submissions: closed (24 April 2024) | Viewed by 5570

Special Issue Editors


E-Mail Website
Guest Editor
Princesa Multidisciplinary Initiative for the Implementation of Pharmacogenetics (PriME-PGx), Clinical Pharmacology Department, Hospital Universitario de La Princesa, Universidad Autónoma de Madrid, 28006 Madrid, Spain
Interests: clinical pharmacogenetics; candidate gene pharmacogenetic study; clinical trials; pharmacokinetics; pharmacodynamics; therapeutic drug monitoring
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Princesa Multidisciplinary Initiative for the Implementation of Pharmacogenetics (PriME-PGx), Clinical Pharmacology Department, Hospital Universitario de La Princesa, Universidad Autónoma de Madrid, 28006 Madrid, Spain
Interests: clinical pharmacogenetics; candidate gene pharmacogenetic study; clinical trials; pharmacokinetics; pharmacodynamics; therapeutic drug monitoring
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In recent times, the progress of Clinical Pharmacogenetics has been remarkable. Its implementation in the United States and Europe is gradually increasing. At the regulatory level, agencies such as the American Food and Drug Administration (FDA) or the European Medicines Agency (EMA) already incorporate genotyping indications in drug labels (e.g., siponimod-CYP2C9 or abacavir-HLA-B*57:01). In addition, other consortia such as the Clinical Pharmacogenetics Implementation Consortium (CPIC) or the Dutch Pharmacogenetics Working Group (DPWG) or national societies such as the Spanish Society of Pharmacogenetics and Pharmacogenomics (SEFF) develop pharmacogenetic clinical guidelines with prescribing recommendations based on patient’s genotype. The drafting of such guidelines depends on the generation of pharmacogenetic evidence, which is collected, and, eventually, associations with a high level of evidence are established that may require a dose adjustment or drug change.

The aim of this issue II is to compile sound works from any field of pharmacology that will increase the pharmacogenetic knowledge of drugs without previous clinical validation (e.g., TYMS/ATIC/MTHFR and methotrexate). Papers that generate new and previously unpublished evidence will also be considered (e.g., Genome-Wide Association Studies).

Prof. Dr. Francisco Abad Santos
Dr. Pablo Zubiaur
Guest Editors

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. Pharmaceutics 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 2900 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

  • pharmacogenetics
  • pharmacogenomics
  • pharmacokinetics
  • pharmacodynamics
  • clinical trials
  • effectiveness
  • toxicity

Published Papers (4 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

Jump to: Review

18 pages, 1610 KiB  
Article
Exploring Variability in Rifampicin Plasma Exposure and Development of Anti-Tuberculosis Drug-Induced Liver Injury among Patients with Pulmonary Tuberculosis from the Pharmacogenetic Perspective
by Agnija Kivrane, Viktorija Ulanova, Solveiga Grinberga, Eduards Sevostjanovs, Anda Viksna, Iveta Ozere, Ineta Bogdanova, Maksims Zolovs and Renate Ranka
Pharmaceutics 2024, 16(3), 388; https://doi.org/10.3390/pharmaceutics16030388 - 12 Mar 2024
Viewed by 1003
Abstract
Genetic polymorphisms can exert a considerable impact on drug pharmacokinetics (PK) and the development of adverse drug reactions (ADR). However, the effect of genetic polymorphisms on the anti-tuberculosis (anti-TB) drug, and particularly rifampicin (RIF), exposure or anti-TB drug-induced liver injury (DILI) remains uncertain. [...] Read more.
Genetic polymorphisms can exert a considerable impact on drug pharmacokinetics (PK) and the development of adverse drug reactions (ADR). However, the effect of genetic polymorphisms on the anti-tuberculosis (anti-TB) drug, and particularly rifampicin (RIF), exposure or anti-TB drug-induced liver injury (DILI) remains uncertain. Here, we evaluated the relationship between single nucleotide polymorphisms (SNPs) detected in the RIF pharmacogenes (AADAC, SLCO1B1, SLCO1B3, ABCB1, and NR1I2) and RIF PK parameters, as well as anti-TB treatment-associated DILI. In total, the study enrolled 46 patients with drug-susceptible pulmonary TB. The RIF plasma concentration was measured using the LC-MS/MS method in the blood samples collected pre-dose and 2 and 6 h post-dose, whilst the DILI status was established using the results from blood biochemical analysis performed before and 10–12 days after treatment onset. The genotyping was conducted using a targeted NGS approach. After adjustment for confounders, the patients carrying the rs3732357 GA/AA genotype of the NR1I2 gene were found to have significantly lower RIF plasma AUC0–6 h in comparison to those with GG genotype, while the difference in RIF plasma Cmax was insignificant. None of the analyzed SNPs was related to DILI. Hence, we are the first to report NR1I2 intronic SNP rs3732357 as the genetic component of variability in RIF exposure. Regarding anti-TB treatment-associated DILI, the other preexisting factors promoting this ADR should be considered. Full article
(This article belongs to the Special Issue Association Studies in Clinical Pharmacogenetics—Volume II)
Show Figures

Figure 1

18 pages, 1330 KiB  
Article
Multilocus Genetic Profile Reflecting Low Dopaminergic Signaling Is Directly Associated with Obesity and Cardiometabolic Disorders Due to Antipsychotic Treatment
by Aurora Arrue, Olga Olivas, Leire Erkoreka, Francisco Jose Alvarez, Ainara Arnaiz, Noemi Varela, Ainhoa Bilbao, Jose-Julio Rodríguez, María Teresa Moreno-Calle, Estibaliz Gordo, Elena Marín, Javier Garcia-Cano, Estela Saez, Miguel Ángel Gonzalez-Torres, Mercedes Zumárraga and Nieves Basterreche
Pharmaceutics 2023, 15(8), 2134; https://doi.org/10.3390/pharmaceutics15082134 - 14 Aug 2023
Viewed by 897
Abstract
Treatment with second-generation antipsychotics (SGAs) can cause obesity and other cardiometabolic disorders linked to D2 receptor (DRD2) and to genotypes affecting dopaminergic (DA) activity, within reward circuits. We explored the relationship of cardiometabolic alterations with single genetic polymorphisms DRD2 rs1799732 (NG_008841.1:g.4750dup -> C), [...] Read more.
Treatment with second-generation antipsychotics (SGAs) can cause obesity and other cardiometabolic disorders linked to D2 receptor (DRD2) and to genotypes affecting dopaminergic (DA) activity, within reward circuits. We explored the relationship of cardiometabolic alterations with single genetic polymorphisms DRD2 rs1799732 (NG_008841.1:g.4750dup -> C), DRD2 rs6277 (NG_008841.1:g.67543C>T), COMT rs4680 (NG_011526.1:g.27009G>A), and VNTR in both DRD4 NC_000011.10 (637269-640706) and DAT1 NC_000005.10 (1392794-1445440), as well as with a multilocus genetic profile score (MLGP). A total of 285 psychiatric patients treated with SGAs for at least three months were selected. Cardiometabolic parameters were classified according to ATP-III and WHO criteria. Blood samples were taken for routinely biochemical assays and PCR genotyping. Obesity (BMI, waist (W)), high diastolic blood pressure (DBP), and hypertriglyceridemia (HTG) were present in those genetic variants related to low dopaminergic activity: InsIns genotype in rs1799732 (BMI: OR: 2.91 [1.42–5.94]), DRD4-VNTR-L allele (W: OR: 1.73 [1.04–2.87]) and 9R9R variant in DAT1-VNTR (W: OR: 2.73 [1.16–6.40]; high DBP: OR: 3.33 [1.54–7.31]; HTG: OR: 4.38 [1.85–10.36]). A low MLGP score indicated a higher risk of suffering cardiometabolic disorders (BMI: OR: 1.23 [1.05–1.45]; W: OR: 1.18 [1.03–1.34]; high DBP: OR: 1.22 [1.06–1.41]; HTG: OR: 1.20 [1.04–1.39]). The MLGP score was more sensitive for detecting the risk of suffering these alterations. Low dopaminergic system function would contribute to increased obesity, BDP, and HTG following long-term SGA treatment. Full article
(This article belongs to the Special Issue Association Studies in Clinical Pharmacogenetics—Volume II)
Show Figures

Figure 1

14 pages, 695 KiB  
Article
Genetic Variation in CYP2D6 and SLC22A1 Affects Amlodipine Pharmacokinetics and Safety
by Paula Soria-Chacartegui, Pablo Zubiaur, Dolores Ochoa, Gonzalo Villapalos-García, Manuel Román, Miriam Matas, Laura Figueiredo-Tor, Gina Mejía-Abril, Sofía Calleja, Alejandro de Miguel, Marcos Navares-Gómez, Samuel Martín-Vilchez and Francisco Abad-Santos
Pharmaceutics 2023, 15(2), 404; https://doi.org/10.3390/pharmaceutics15020404 - 25 Jan 2023
Cited by 1 | Viewed by 1799
Abstract
Amlodipine is an antihypertensive drug with unknown pharmacogenetic biomarkers. This research is a candidate gene study that looked for associations between amlodipine pharmacokinetics and safety and pharmacogenes. Pharmacokinetic and safety data were taken from 160 volunteers from eight bioequivalence trials. In the exploratory [...] Read more.
Amlodipine is an antihypertensive drug with unknown pharmacogenetic biomarkers. This research is a candidate gene study that looked for associations between amlodipine pharmacokinetics and safety and pharmacogenes. Pharmacokinetic and safety data were taken from 160 volunteers from eight bioequivalence trials. In the exploratory step, 70 volunteers were genotyped for 44 polymorphisms in different pharmacogenes. CYP2D6 poor metabolizers (PMs) showed higher half-life (t1/2) (univariate p-value (puv) = 0.039, multivariate p-value (pmv) = 0.013, β = −5.31, R2 = 0.176) compared to ultrarapid (UMs), normal (NMs) and intermediate metabolizers (IMs). SLC22A1 rs34059508 G/A genotype was associated with higher dose/weight-corrected area under the curve (AUC72/DW) (puv = 0.025; pmv = 0.026, β = 578.90, R2 = 0.060) compared to the G/G genotype. In the confirmatory step, the cohort was increased to 160 volunteers, who were genotyped for CYP2D6, SLC22A1 and CYP3A4. In addition to the previous associations, CYP2D6 UMs showed a lower AUC72/DW (puv = 0.046, pmv = 0.049, β = −68.80, R2 = 0.073) compared to NMs, IMs and PMs and the SLC22A1 rs34059508 G/A genotype was associated with thoracic pain (puv = 0.038) and dizziness (puv = 0.038, pmv = 0.014, log OR = 10.975). To our knowledge, this is the first work to report a strong relationship between amlodipine and CYP2D6 and SLC22A1. Further research is needed to gather more evidence before its application in clinical practice. Full article
(This article belongs to the Special Issue Association Studies in Clinical Pharmacogenetics—Volume II)
Show Figures

Figure 1

Review

Jump to: Research

13 pages, 1369 KiB  
Review
Correlation between PPARG Pro12Ala Polymorphism and Therapeutic Responses to Thiazolidinediones in Patients with Type 2 Diabetes: A Meta-Analysis
by Eun Jeong Jang, Da Hoon Lee, Sae-Seul Im, Jeong Yee and Hye Sun Gwak
Pharmaceutics 2023, 15(6), 1778; https://doi.org/10.3390/pharmaceutics15061778 - 20 Jun 2023
Cited by 2 | Viewed by 1342
Abstract
Background: Thiazolidinediones (TZDs) are a type of oral drug that are utilized for the treatment of type 2 diabetes mellitus (T2DM). They function by acting as agonists for a nuclear transcription factor known as peroxisome proliferator-activated receptor-gamma (PPAR-γ). TZDs, such as pioglitazone and [...] Read more.
Background: Thiazolidinediones (TZDs) are a type of oral drug that are utilized for the treatment of type 2 diabetes mellitus (T2DM). They function by acting as agonists for a nuclear transcription factor known as peroxisome proliferator-activated receptor-gamma (PPAR-γ). TZDs, such as pioglitazone and rosiglitazone, help enhance the regulation of metabolism in individuals with T2DM by improving their sensitivity to insulin. Previous studies have suggested a relationship between the therapeutic efficacy of TZDs and the PPARG Pro12Ala polymorphism (C > G, rs1801282). However, the small sample sizes of these studies may limit their applicability in clinical settings. To address this limitation, we conducted a meta-analysis assessing the influence of the PPARG Pro12Ala polymorphism on the responsiveness of TZDs. Method: We registered our study protocol with PROSPERO, number CRD42022354577. We conducted a comprehensive search of the PubMed, Web of Science, and Embase databases, including studies published up to August 2022. We examined studies investigating the association between the PPARG Pro12Ala polymorphism and metabolic parameters such as hemoglobin A1C (HbA1C), fasting plasma glucose (FPG), triglyceride (TG), low-density lipoprotein cholesterol (LDL), high-density lipoprotein cholesterol (HDL), and total cholesterol (TC). The mean difference (MD) and 95% confidence intervals (CIs) between pre- and post-drug administration were evaluated. The quality of the studies included in the meta-analysis was assessed by using the Newcastle–Ottawa Scale (NOS) tool for cohort studies. Heterogeneity across studies was assessed by using the I2 value. An I2 value greater than 50% indicated substantial heterogeneity, and a random-effects model was used for meta-analysis. If the I2 value was below 50%, a fixed-effects model was employed instead. Both Begg’s rank correlation test and Egger’s regression test were performed to detect publication bias, using R Studio software. Results: Our meta-analysis incorporated 6 studies with 777 patients for blood glucose levels and 5 studies with 747 patients for lipid levels. The included studies were published between 2003 and 2016, with the majority involving Asian populations. Five of the six studies utilized pioglitazone, while the remaining study employed rosiglitazone. The quality scores, as assessed with the NOS, ranged from 8 to 9. Patients carrying the G allele exhibited a significantly greater reduction in HbA1C (MD = −0.3; 95% CI = −0.55 to −0.05; p = 0.02) and FPG (MD = −10.91; 95% CI = −19.82 to −2.01; p = 0.02) levels compared to those with the CC genotype. Furthermore, individuals with the G allele experienced a significantly larger decrease in TG levels than those with the CC genotype (MD = −26.88; 95% CI = −41.30 to −12.46; p = 0.0003). No statistically significant differences were observed in LDL (MD = 6.69; 95% CI = −0.90 to 14.29; p = 0.08), HDL (MD = 0.31; 95% CI = −1.62 to 2.23; p = 0.75), and TC (MD = 6.4; 95% CI = −0.05 to 12.84; p = 0.05) levels. No evidence of publication bias was detected based on Begg’s test and Egger’s test results. Conclusions: This meta-analysis reveals that patients with the Ala12 variant in the PPARG Pro12Ala polymorphism are more likely to exhibit positive responses to TZD treatment in terms of HbA1C, FPG, and TG levels compared to those with the Pro12/Pro12 genotype. These findings suggest that genotyping the PPARG Pro12Ala in diabetic patients may be advantageous for devising personalized treatment strategies, particularly for identifying individuals who are likely to respond favorably to TZDs. Full article
(This article belongs to the Special Issue Association Studies in Clinical Pharmacogenetics—Volume II)
Show Figures

Figure 1

Back to TopTop