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Biomedicines
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Advancing Pharmacogenetics in Pre-clinical Research: Unveiling New Avenues for Precision...
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Advancing Pharmacogenetics in Pre-clinical Research: Unveiling New Avenues for Precision Medicine

A special issue of Biomedicines (ISSN 2227-9059). This special issue belongs to the section "Drug Discovery, Development and Delivery".

Deadline for manuscript submissions: closed (31 December 2024) | Viewed by 5262

Special Issue Editors

Dr. Miriam Saiz-Rodrigez

E-Mail Website
Guest Editor
Research Unit, Fundación Burgos por la Investigación de la Salud (FBIS), Hospital Universitario de Burgos, 09006 Burgos, Spain
Interests: pharmacogenetics; pharmacogenomics; precision medicine; acute myeloid leukemia
Special Issues, Collections and Topics in MDPI journals
Dr. Shengying Qin

E-Mail Website
Co-Guest Editor
Bio-X Institutes, Shanghai Jiaotong University, Shanghai, China
Interests: pharmacogenomics; pharmacogenetics; genome medicine; psychiatry disease; multi-omics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Pharmacogenetics tailors medical treatments based on individual genetic variations, optimizing drug response, efficacy and safety. Pre-clinical research forms the foundation for translating these findings into clinical practice. This issue aims to explore the latest discoveries in pharmacogenetics, with a focus on pre-clinical research and its impact on precision medicine.

We welcome original research articles and reviews on various aspects of pharmacogenetics in pre-clinical research, including genetic variant identification, mechanistic insights, novel models and methodologies, integrating pharmacogenetic data in drug development and translational challenges. We invite your contributions to advance our understanding of pharmacogenetics and shape personalized therapeutics.

Please, refer to the journal's submission guidelines for manuscript preparation and submission instructions. Contact us with any queries or for further information. Join us in uncovering new avenues for precision medicine!

Dr. Miriam Saiz-Rodrigez
Dr. Shengying Qin
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. Biomedicines 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

  • pharmacogenetics
  • pharmacogenomics
  • precision medicine
  • individualized medicine

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Published Papers (4 papers)

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Research

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15 pages, 1580 KiB  
Article
Theoretical Models and Simulations of Gene Delivery with Polyurethane: The Importance of Polyurethane as a Vector in Personalized Therapy
by Roxana Maria Jeleriu, Roxana-Karin Hajaj, Iuliana-Anamaria Trăilă, Mihaela Zaharie and Maria Puiu
Biomedicines 2025, 13(3), 692; https://doi.org/10.3390/biomedicines13030692 - 11 Mar 2025
Viewed by 674
Abstract
Background/Objectives: Advancements in personalized medicine have revolutionized drug delivery, enabling tailored treatments based on genetic and molecular profiles. Non-viral vectors, such as polyurethane (PU)-based systems, offer promising alternatives for gene therapy. This study develops mathematical models to analyze PU degradation, DNA/RNA release kinetics, [...] Read more.
Background/Objectives: Advancements in personalized medicine have revolutionized drug delivery, enabling tailored treatments based on genetic and molecular profiles. Non-viral vectors, such as polyurethane (PU)-based systems, offer promising alternatives for gene therapy. This study develops mathematical models to analyze PU degradation, DNA/RNA release kinetics, and cellular interactions, optimizing their application in personalized therapy. Methods: This theoretical study utilized mathematical modeling and numerical simulations to analyze PU-based gene delivery, focusing on diffusion, degradation, and cellular uptake. Implemented in Python 3.9, it employed differential equation solvers and adsorption/internalization models to predict vector behavior and optimize delivery efficiency. Results: This study demonstrated that PU degrades in biological environments following first-order kinetics, ensuring a controlled and predictable release of genetic material. The Higuchi diffusion model confirmed a gradual, sustained DNA/RNA release, essential for efficient gene delivery. Simulations of PU adsorption onto cellular membranes using the Langmuir model showed saturation-dependent binding, while the endocytosis model revealed a balance between uptake and degradation. These findings highlight PU’s potential as a versatile gene delivery vector, offering controlled biodegradability, optimized release profiles, and effective cellular interaction. Conclusions: Our results confirm that PU-based vectors enable controlled biodegradability, sustained DNA/RNA release, and efficient cellular uptake. Mathematical modeling provides a framework for improving PU’s properties, enhancing transport efficiency and therapeutic potential in personalized medicine and gene therapy applications. Full article
(This article belongs to the Special Issue Advancing Pharmacogenetics in Pre-clinical Research: Unveiling New Avenues for Precision Medicine)
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28 pages, 2001 KiB  
Article
Pharmacogenomic Study of SARS-CoV-2 Treatments: Identifying Polymorphisms Associated with Treatment Response in COVID-19 Patients
by Alexandre Serra-Llovich, Natalia Cullell, Olalla Maroñas, María José Herrero, Raquel Cruz, Berta Almoguera, Carmen Ayuso, Rosario López-Rodríguez, Elena Domínguez-Garrido, Rocio Ortiz-Lopez, María Barreda-Sánchez, Marta Corton, David Dalmau, Esther Calbo, Lucía Boix-Palop, Beatriz Dietl, Anna Sangil, Almudena Gil-Rodriguez, Encarna Guillén-Navarro, Esther Mancebo, Saúl Lira-Albarrán, Pablo Minguez, Estela Paz-Artal, Gladys G. Olivera, Sheila Recarey-Rama, Luis Sendra, Enrique G. Zucchet, Miguel López de Heredia, Carlos Flores, José A. Riancho, Augusto Rojas-Martinez, Pablo Lapunzina, Ángel Carracedo, María J. Arranz and SCOURGE COHORT GROUPadd Show full author list remove Hide full author list
Biomedicines 2025, 13(3), 553; https://doi.org/10.3390/biomedicines13030553 - 21 Feb 2025
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Abstract
Background/Objectives: The COVID-19 pandemic resulted in 675 million cases and 6.9 million deaths by 2022. Despite substantial declines in case fatalities following widespread vaccination campaigns, the threat of future coronavirus outbreaks remains a concern. Current treatments for COVID-19 have been repurposed from [...] Read more.
Background/Objectives: The COVID-19 pandemic resulted in 675 million cases and 6.9 million deaths by 2022. Despite substantial declines in case fatalities following widespread vaccination campaigns, the threat of future coronavirus outbreaks remains a concern. Current treatments for COVID-19 have been repurposed from existing therapies for other infectious and non-infectious diseases. Emerging evidence suggests a role for genetic factors in both susceptibility to SARS-CoV-2 infection and response to treatment. However, comprehensive studies correlating clinical outcomes with genetic variants are lacking. The main aim of our study is the identification of host genetic biomarkers that predict the clinical outcome of COVID-19 pharmacological treatments. Methods: In this study, we present findings from GWAS and candidate gene and pathway enrichment analyses leveraging diverse patient samples from the Spanish Coalition to Unlock Research of Host Genetics on COVID-19 (SCOURGE), representing patients treated with immunomodulators (n = 849), corticoids (n = 2202), and the combined cohort of both treatments (n = 2487) who developed different outcomes. We assessed various phenotypes as indicators of treatment response, including survival at 90 days, admission to the intensive care unit (ICU), radiological affectation, and type of ventilation. Results: We identified significant polymorphisms in 16 genes from the GWAS and candidate gene studies (TLR1, TLR6, TLR10, CYP2C19, ACE2, UGT1A1, IL-1α, ZMAT3, TLR4, MIR924HG, IFNG-AS1, ABCG1, RBFOX1, ABCB11, TLR5, and ANK3) that may modulate the response to corticoid and immunomodulator therapies in COVID-19 patients. Enrichment analyses revealed overrepresentation of genes involved in the innate immune system, drug ADME, viral infection, and the programmed cell death pathways associated with the response phenotypes. Conclusions: Our study provides an initial framework for understanding the genetic determinants of treatment response in COVID-19 patients, offering insights that could inform precision medicine approaches for future epidemics. Full article
(This article belongs to the Special Issue Advancing Pharmacogenetics in Pre-clinical Research: Unveiling New Avenues for Precision Medicine)
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15 pages, 1782 KiB  
Article
PPP3R1 Promoter Polymorphism (Allelic Variation) Affects Tacrolimus Treatment Efficacy by Modulating E2F6 Binding Affinity
by Xinyi Zheng, Shengying Qin, Mingkang Zhong, Qinxia Xu, Cong Huai and Xiaoyan Qiu
Biomedicines 2024, 12(12), 2896; https://doi.org/10.3390/biomedicines12122896 - 19 Dec 2024
Viewed by 823
Abstract
Background: Tacrolimus is widely used as a first-line immunosuppressant in transplant immunology; however, its clinical application is constrained by the narrow therapeutic index and considerable interindividual variability. In this study, we identified the potential regulatory role of a novel PPP3R1 promoter polymorphism, rs4519508 [...] Read more.
Background: Tacrolimus is widely used as a first-line immunosuppressant in transplant immunology; however, its clinical application is constrained by the narrow therapeutic index and considerable interindividual variability. In this study, we identified the potential regulatory role of a novel PPP3R1 promoter polymorphism, rs4519508 C > T, in the tacrolimus pharmacodynamic pathway. Methods: Dual-luciferase reporter assays and bioinformatic analysis were applied to assess the impact of allelic variation. Electrophoretic mobility shift assays (EMSA) validated the altered binding of transcription factors. Quantitative real-time PCR (qRT-PCR), enzyme-linked immunosorbent assay (ELISA) and Western blots were used to determine the immunosuppressive effect of tacrolimus. Results: Assays revealed that rs4519508 C > T markedly enhanced PPP3R1 promoter activity. EMSA assays validated the binding of E2F6 to rs4519508 C (wild-type) and the binding was significantly weaker to the rs4519508 T (mutant-type). The overexpression of E2F6 significantly reduced the transcriptional activity and expression of PPP3R1 when the rs4519508 site presented as major C allele, an effect that was not observed with the rs4519508 T allele. Furthermore, the downregulation of E2F6 raises the level of downstream immune cytokines inhibited by TAC. Conclusions: This study proposed that E2F6 suppresses the expression of PPP3R1, while rs4519508 C > T impairs the binding of E2F6, and thus elevates the level of PPP3R1, so that the inhibition of the downstream immune cytokines by TAC is attenuated. Our findings reported the potential regulatory role of a novel polymorphism, PPP3R1 rs4519508 C > T, which may serve as pharmacodynamic-associated pharmacogenetic biomarker indicating individual response variability of tacrolimus, and thus aid the clinical management of transplant immunology. Full article
(This article belongs to the Special Issue Advancing Pharmacogenetics in Pre-clinical Research: Unveiling New Avenues for Precision Medicine)
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Review

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21 pages, 853 KiB  
Review
Harnessing Pharmacomultiomics for Precision Medicine in Diabetes: A Comprehensive Review
by Dhoha Dhieb, Dana Mustafa, Maryam Hassiba, May Alasmar, Mohamed Haitham Elsayed, Ameer Musa, Mahmoud Zirie and Kholoud Bastaki
Biomedicines 2025, 13(2), 447; https://doi.org/10.3390/biomedicines13020447 - 12 Feb 2025
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Abstract
Type 2 diabetes (T2D) is the fastest-growing non-communicable disease worldwide, accounting for around 90% of all diabetes cases and imposing a significant health burden globally. Due to its phenotypic heterogeneity and composite genetic underpinnings, T2D requires a precision medicine approach personalized to individual [...] Read more.
Type 2 diabetes (T2D) is the fastest-growing non-communicable disease worldwide, accounting for around 90% of all diabetes cases and imposing a significant health burden globally. Due to its phenotypic heterogeneity and composite genetic underpinnings, T2D requires a precision medicine approach personalized to individual molecular profiles, thereby shifting away from the traditional “one-size-fits-all” medical methods. This review advocates for a thorough pharmacomultiomics approach to enhance precision medicine for T2D. It emphasizes personalized treatment strategies that enhance treatment efficacy while minimizing adverse effects by integrating data from genomics, proteomics, metabolomics, transcriptomics, microbiomics, and epigenomics. We summarize key findings on candidate genes impacting diabetic medication responses and explore the potential of pharmacometabolomics in predicting drug efficacy. The role of pharmacoproteomics in prognosis and discovering new therapeutic targets is discussed, along with transcriptomics’ contribution to understanding T2D pathophysiology. Additionally, pharmacomicrobiomics is explored to understand gut microbiota interactions with antidiabetic drugs. Emerging evidence on utilizing epigenomic profiles in improving drug efficacy and personalized treatment is also reviewed, illustrating their implications in personalized medicine. In this paper, we discuss the integration of these layers of omics data, examining recently developed paradigms that leverage complex data to deepen our understanding of diabetes. Such integrative approaches advance precision medicine strategies to tackle the disease by better understanding its complex biology. Full article
(This article belongs to the Special Issue Advancing Pharmacogenetics in Pre-clinical Research: Unveiling New Avenues for Precision Medicine)
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