ijms-logo

Journal Browser

Journal Browser

Pharmacogenomics

A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Pharmacology".

Deadline for manuscript submissions: closed (31 August 2020) | Viewed by 86691

Special Issue Editor

Special Issue Information

Dear Colleagues,

It is a great pleasure for me to accept the kind invitation of the International Journal of Molecular Sciences to serve as Editor of an Special Issue on “Pharmacogenomics”. I think that this is a timely initiative which will be of interest to most medical disciplines. Cardiovascular disorders (25%–30%), cancer (20%–25%) and brain disorders (10%–15%) represent over 60%–70% of morbility and mortality in developed countries. Approximately 10%–20% of direct costs for disease management are attributed to pharmacological treatment, and, unfortunately, it is estimated that drug efficacy is restricted to 20%–30% of the cases treated with a particular drug in almost any medical specialty. Many different factors influence drug efficacy and safety, including the chemical properties of a drug, route of administration, disease stage, nutrition, compliance, drug–drug interactions, and pharmacogenomics.

In the coming years, the onset of a revolutionary transformation of protocols and strategies for drug development is expected. Pharmacogenomics is one of the doors to enter the complex building of personalized medicine.

The Regulatory Agencies should make recommendations to the pharmaceutical industry in favor of the introduction of pharmacogenomics in drug development and the inclusion of pharmacogenomic information on drug labels, with specific warnings for the population at risk. Educational programs are fundamental for drug prescribers to become familiar with personalized treatments. Pharmacogenetic testing should be gradually introduced into medical practice. The introduction of pharmacogenomics in routine clinical practice is fundamental for optimizing therapeutics and for reducing adverse drug reactions (ADRs), which are a major health concern worldwide. There are multiple causes of ADRs, some of which are preventable. Pharmacogenomics accounts for ≈80% variability in drug efficacy and safety. Over 400 genes are clinically relevant in drug metabolism, and ≈200 pharmagenes are associated with ADRs. The condition of extensive metabolizers in the Caucasian population is lower than 20%, and about 60% of patients are exposed to potential ADRs.

I would like to invite all of you, experts and beginners in the field of pharmacogeneomics, to contribute to this Special Issue with your ideas for accelerating the implementation of pharmacogenomic procedures in drug development and clinical practice.

You may choose our Joint Special Issue in Life.

Prof. Dr. Ramón Cacabelos
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. International Journal of Molecular Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. There is an Article Processing Charge (APC) for publication in this open access journal. For details about the APC please see here. 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

  • Pharmacogenomics of cardiovascular disorders
  • Pharmacogenomics of cancer
  • Pharmacogenomics of brain disorders
  • Pharmacogenomics of metabolic and endocrine disorders
  • Pharmacogenomics of gastrointestinal disorders
  • Pharmacogenomics of lipid metabolism disorders
  • Pharmacoepigenomics of pain
  • Pharmacogenomics of psychotropic drugs
  • Neurodegenerative disorders (Alzheimer, Parkinson, multiple sclerosis)
  • Pharmacogenomics of antineoplastic drugs
  • Pharmacoepigenomics

Related Special Issue

Published Papers (17 papers)

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

Research

Jump to: Review

17 pages, 2817 KiB  
Article
DRUGPATH: The Drug Gene Pathway Meta-Database
by Rajeev Jaundoo and Travis J. A. Craddock
Int. J. Mol. Sci. 2020, 21(9), 3171; https://doi.org/10.3390/ijms21093171 - 30 Apr 2020
Cited by 2 | Viewed by 3377
Abstract
The complexity of modern-day diseases often requires drug treatment therapies consisting of multiple pharmaceutical interventions, which can lead to adverse drug reactions for patients. A priori prediction of these reactions would not only improve the quality of life for patients but also save [...] Read more.
The complexity of modern-day diseases often requires drug treatment therapies consisting of multiple pharmaceutical interventions, which can lead to adverse drug reactions for patients. A priori prediction of these reactions would not only improve the quality of life for patients but also save both time and money in regards to pharmaceutical research. Consequently, the drug-gene-pathway (DRUGPATH) meta-database was developed to map known interactions between drugs, genes, and pathways among other information in order to easily identify potential adverse drug events. DRUGPATH utilizes expert-curated sources such as PharmGKB, DrugBank, and the FDA’s NDC database to identify known as well as previously unknown/overlooked relationships, and currently contains 12,940 unique drugs, 3933 unique pathways, 5185 unique targets, and 3662 unique genes. Moreover, there are 59,561 unique drug-gene interactions, 77,808 unique gene-pathway interactions, and over 1 million unique drug-pathway interactions. Full article
(This article belongs to the Special Issue Pharmacogenomics)
Show Figures

Figure 1

13 pages, 2339 KiB  
Article
Gene-Wise Burden of Coding Variants Correlates to Noncoding Pharmacogenetic Risk Variants
by Jihye Park, Soo Youn Lee, Su Youn Baik, Chan Hee Park, Jun Hee Yoon, Brian Y. Ryu and Ju Han Kim
Int. J. Mol. Sci. 2020, 21(9), 3091; https://doi.org/10.3390/ijms21093091 - 27 Apr 2020
Cited by 5 | Viewed by 2252
Abstract
Genetic variability can modulate individual drug responses. A significant portion of pharmacogenetic variants reside in the noncoding genome yet it is unclear if the noncoding variants directly influence protein function and expression or are present on a haplotype including a functionally relevant genetic [...] Read more.
Genetic variability can modulate individual drug responses. A significant portion of pharmacogenetic variants reside in the noncoding genome yet it is unclear if the noncoding variants directly influence protein function and expression or are present on a haplotype including a functionally relevant genetic variation (synthetic association). Gene-wise variant burden (GVB) is a gene-level measure of deleteriousness, reflecting the cumulative effects of deleterious coding variants, predicted in silico. To test potential associations between noncoding and coding pharmacogenetic variants, we computed a drug-level GVB for 5099 drugs from DrugBank for 2504 genomes of the 1000 Genomes Project and evaluated the correlation between the long-known noncoding variant-drug associations in PharmGKB, with functionally relevant rare and common coding variants aggregated into GVBs. We obtained the area under the receiver operating characteristics curve (AUC) by comparing the drug-level GVB ranks against the corresponding pharmacogenetic variants-drug associations in PharmGKB. We obtained high overall AUCs (0.710 ± 0.022–0.734 ± 0.018) for six different methods (i.e., SIFT, MutationTaster, Polyphen-2 HVAR, Polyphen-2 HDIV, phyloP, and GERP++), and further improved the ethnicity-specific validations (0.759 ± 0.066–0.791 ± 0.078). These results suggest that a significant portion of the long-known noncoding variant-drug associations can be explained as synthetic associations with rare and common coding variants burden of the corresponding pharmacogenes. Full article
(This article belongs to the Special Issue Pharmacogenomics)
Show Figures

Figure 1

9 pages, 519 KiB  
Article
Tamsulosin Associated with Interstitial Lung Damage in CYP2D6 Variant Alleles Carriers
by Naomi T. Jessurun, Petal A. Wijnen, Aalt Bast, Eugène P. van Puijenbroek, Otto Bekers and Marjolein Drent
Int. J. Mol. Sci. 2020, 21(8), 2770; https://doi.org/10.3390/ijms21082770 - 16 Apr 2020
Cited by 5 | Viewed by 2840
Abstract
Drugs are serious but underestimated causative agents of interstitial lung disease (ILD). Both cytotoxic and immune mechanisms may be involved in drug-induced ILD (DI-ILD). We aimed to investigate whether polymorphisms of relevant CYP enzymes involved in the metabolization of tamsulosin might explain the [...] Read more.
Drugs are serious but underestimated causative agents of interstitial lung disease (ILD). Both cytotoxic and immune mechanisms may be involved in drug-induced ILD (DI-ILD). We aimed to investigate whether polymorphisms of relevant CYP enzymes involved in the metabolization of tamsulosin might explain the pathologic mechanism of the DI-ILD in the cases with suspected tamsulosin DI-ILD. We collected 22 tamsulosin-associated DI-ILD cases at two ILD Expertise Centers in the Netherlands between 2009 and 2020. CYP2D6, CYP2C9, CYP2C19, CYP3A4, and CYP3A5 single nucleotide polymorphisms were genotyped and compared with a control group of 78 healthy Caucasian male volunteers. Nine cases were phenotyped as CYP2D6 poor metabolizers and 13 as CYP2D6 intermediate metabolizers. The phenotypes of the cases differed significantly from those of the healthy controls, with more poor metabolizers. After withdrawal of tamsulosin, the pulmonary condition of three cases had improved, six patients had stabilized, and one patient stabilized after reducing the tamsulosin dose. The described 22 cases suggest that an association between the presence of CYP2D6 allelic variants and tamsulosin-associated ILD is highly likely. These cases highlight the importance of both clinical and genetic risk stratification aimed to achieve a more accurate prevention of DI-ILD in the future and enhance the quality of life of patients. Full article
(This article belongs to the Special Issue Pharmacogenomics)
Show Figures

Figure 1

9 pages, 1118 KiB  
Article
A Machine Learning-Based Identification of Genes Affecting the Pharmacokinetics of Tacrolimus Using the DMETTM Plus Platform
by Jeong-An Gim, Yonghan Kwon, Hyun A Lee, Kyeong-Ryoon Lee, Soohyun Kim, Yoonjung Choi, Yu Kyong Kim and Howard Lee
Int. J. Mol. Sci. 2020, 21(7), 2517; https://doi.org/10.3390/ijms21072517 - 04 Apr 2020
Cited by 9 | Viewed by 2881
Abstract
Tacrolimus is an immunosuppressive drug with a narrow therapeutic index and larger interindividual variability. We identified genetic variants to predict tacrolimus exposure in healthy Korean males using machine learning algorithms such as decision tree, random forest, and least absolute shrinkage and selection operator [...] Read more.
Tacrolimus is an immunosuppressive drug with a narrow therapeutic index and larger interindividual variability. We identified genetic variants to predict tacrolimus exposure in healthy Korean males using machine learning algorithms such as decision tree, random forest, and least absolute shrinkage and selection operator (LASSO) regression. rs776746 (CYP3A5) and rs1137115 (CYP2A6) are single nucleotide polymorphisms (SNPs) that can affect exposure to tacrolimus. A decision tree, when coupled with random forest analysis, is an efficient tool for predicting the exposure to tacrolimus based on genotype. These tools are helpful to determine an individualized dose of tacrolimus. Full article
(This article belongs to the Special Issue Pharmacogenomics)
Show Figures

Figure 1

24 pages, 3033 KiB  
Article
Variability in HIV-1 Integrase Gene and 3′-Polypurine Tract Sequences in Cameroon Clinical Isolates, and Implications for Integrase Inhibitors Efficacy
by Arpan Acharya, Claude T. Tagny, Dora Mbanya, Julius Y. Fonsah, Emilienne Nchindap, Léopoldine Kenmogne, Ma Jihyun, Alfred K. Njamnshi and Georgette D. Kanmogne
Int. J. Mol. Sci. 2020, 21(5), 1553; https://doi.org/10.3390/ijms21051553 - 25 Feb 2020
Cited by 9 | Viewed by 3313
Abstract
Integrase strand-transfer inhibitors (INSTIs) are now included in preferred first-line antiretroviral therapy (ART) for HIV-infected adults. Studies of Western clade-B HIV-1 show increased resistance to INSTIs following mutations in integrase and nef 3′polypurine tract (3′-PPT). With anticipated shifts in Africa (where 25.6-million HIV-infected [...] Read more.
Integrase strand-transfer inhibitors (INSTIs) are now included in preferred first-line antiretroviral therapy (ART) for HIV-infected adults. Studies of Western clade-B HIV-1 show increased resistance to INSTIs following mutations in integrase and nef 3′polypurine tract (3′-PPT). With anticipated shifts in Africa (where 25.6-million HIV-infected people resides) to INSTIs-based ART, it is critical to monitor patients in African countries for resistance-associated mutations (RAMs) affecting INSTIs efficacy. We analyzed HIV-1 integrase and 3′-PPT sequences in 345 clinical samples from INSTIs-naïve HIV-infected Cameroonians for polymorphisms and RAMs that affect INSTIs. Phylogeny showed high genetic diversity, with the predominance of HIV-1 CRF02_AG. Major INSTIs RAMs T66A and N155K were found in two (0.6%) samples. Integrase polymorphic and accessory RAMs found included T97A, E157Q, A128T, M50I, S119R, L74M, L74I, S230N, and E138D (0.3′23.5% of samples). Ten (3.2%) samples had both I72V+L74M, L74M+T97A, or I72V+T97A mutations; thirty-one (9.8%) had 3′-PPT mutations. The low frequency of major INSTIs RAMs shows that INSTIs-based ART can be successfully used in Cameroon. Several samples had ≥1 INSTIs accessory RAMs known to reduce INSTIs efficacy; thus, INSTIs-based ART would require genetic surveillance. The 3′-PPT mutations could also affect INSTIs. For patients failing INSTIs-based ART with no INSTIs RAMs, monitoring 3′-PPT sequences could reveal treatment failure etiology. Full article
(This article belongs to the Special Issue Pharmacogenomics)
Show Figures

Figure 1

16 pages, 6351 KiB  
Article
Comparison of Eight Technologies to Determine Genotype at the UGT1A1 (TA)n Repeat Polymorphism: Potential Clinical Consequences of Genotyping Errors?
by Tristan M. Sissung, Roberto H. Barbier, Douglas K. Price, Teri M. Plona, Kristen M. Pike, Stephanie D. Mellott, Ryan N. Baugher, Gordon R. Whiteley, Daniel R. Soppet, David Venzon, Arlene Berman, Arun Rajan, Giuseppe Giaccone, Paul Meltzer and William D. Figg
Int. J. Mol. Sci. 2020, 21(3), 896; https://doi.org/10.3390/ijms21030896 - 30 Jan 2020
Cited by 6 | Viewed by 3349
Abstract
To ensure accuracy of UGT1A1 (TA)n (rs3064744) genotyping for use in pharmacogenomics-based irinotecan dosing, we tested the concordance of several commonly used genotyping technologies. Heuristic genotype groupings and principal component analysis demonstrated concordance for Illumina sequencing, fragment analysis, and fluorescent PCR. However, [...] Read more.
To ensure accuracy of UGT1A1 (TA)n (rs3064744) genotyping for use in pharmacogenomics-based irinotecan dosing, we tested the concordance of several commonly used genotyping technologies. Heuristic genotype groupings and principal component analysis demonstrated concordance for Illumina sequencing, fragment analysis, and fluorescent PCR. However, Illumina sequencing and fragment analysis returned a range of fragment sizes, likely arising due to PCR “slippage”. Direct sequencing was accurate, but this method led to ambiguous electrophoregrams, hampering interpretation of heterozygotes. Gel sizing, pyrosequencing, and array-based technologies were less concordant. Pharmacoscan genotyping was concordant, but it does not ascertain (TA)8 genotypes that are common in African populations. Method-based genotyping differences were also observed in the publication record (p < 0.0046), although fragment analysis and direct sequencing were concordant (p = 0.11). Genotyping errors can have significant consequences in a clinical setting. At the present time, we recommend that all genotyping for this allele be conducted with fluorescent PCR (fPCR). Full article
(This article belongs to the Special Issue Pharmacogenomics)
Show Figures

Figure 1

16 pages, 1023 KiB  
Article
Whole Genome Expression Analyses of miRNAs and mRNAs Suggest the Involvement of miR-320a and miR-155-3p and their Targeted Genes in Lithium Response in Bipolar Disorder
by Claudia Pisanu, Eleni Merkouri Papadima, Carla Melis, Donatella Congiu, Annalisa Loizedda, Nicola Orrù, Stefano Calza, Sandro Orrù, Carlo Carcassi, Giovanni Severino, Raffaella Ardau, Caterina Chillotti, Maria Del Zompo and Alessio Squassina
Int. J. Mol. Sci. 2019, 20(23), 6040; https://doi.org/10.3390/ijms20236040 - 30 Nov 2019
Cited by 27 | Viewed by 3707
Abstract
Lithium is the mainstay in the maintenance of bipolar disorder (BD) and the most efficacious pharmacological treatment in suicide prevention. Nevertheless, its use is hampered by a high interindividual variability and important side effects. Genetic and epigenetic factors have been suggested to modulate [...] Read more.
Lithium is the mainstay in the maintenance of bipolar disorder (BD) and the most efficacious pharmacological treatment in suicide prevention. Nevertheless, its use is hampered by a high interindividual variability and important side effects. Genetic and epigenetic factors have been suggested to modulate lithium response, but findings so far have not allowed identifying molecular targets with predictive value. In this study we used next generation sequencing to measure genome-wide miRNA expression in lymphoblastoid cell lines from BD patients excellent responders (ER, n = 12) and non-responders (NR, n = 12) to lithium. These data were integrated with microarray genome-wide expression data to identify pairs of miRNA/mRNA inversely and significantly correlated. Significant pairs were prioritized based on strength of association and in-silico miRNA target prediction analyses to select candidates for validation with qRT-PCR. Thirty-one miRNAs were differentially expressed in ER vs. NR and inversely correlated with 418 genes differentially expressed between the two groups. A total of 331 of these correlations were also predicted by in-silico algorithms. miR-320a and miR-155-3p, as well as three of their targeted genes (CAPNS1 (Calpain Small Subunit 1) and RGS16 (Regulator of G Protein Signaling 16) for miR-320, SP4 (Sp4 Transcription Factor) for miR-155-3p) were validated. These miRNAs and mRNAs were previously implicated in psychiatric disorders (miR-320a and SP4), key processes of the central nervous system (CAPNS1, RGS16, SP4) or pathways involved in mental illnesses (miR-155-3p). Using an integrated approach, we identified miRNAs and their targeted genes potentially involved in lithium response in BD. Full article
(This article belongs to the Special Issue Pharmacogenomics)
Show Figures

Graphical abstract

Review

Jump to: Research

36 pages, 2015 KiB  
Review
CDK4/6 Inhibitors in Breast Cancer Treatment: Potential Interactions with Drug, Gene, and Pathophysiological Conditions
by Rossana Roncato, Jacopo Angelini, Arianna Pani, Erika Cecchin, Andrea Sartore-Bianchi, Salvatore Siena, Elena De Mattia, Francesco Scaglione and Giuseppe Toffoli
Int. J. Mol. Sci. 2020, 21(17), 6350; https://doi.org/10.3390/ijms21176350 - 01 Sep 2020
Cited by 32 | Viewed by 7958
Abstract
Palbociclib, ribociclib, and abemaciclib belong to the third generation of cyclin-dependent kinases inhibitors (CDKis), an established therapeutic class for advanced and metastatic breast cancer. Interindividual variability in the therapeutic response of CDKis has been reported and some individuals may experience increased and unexpected [...] Read more.
Palbociclib, ribociclib, and abemaciclib belong to the third generation of cyclin-dependent kinases inhibitors (CDKis), an established therapeutic class for advanced and metastatic breast cancer. Interindividual variability in the therapeutic response of CDKis has been reported and some individuals may experience increased and unexpected toxicity. This narrative review aims at identifying the factors potentially concurring at this variability for driving the most appropriate and tailored use of CDKis in the clinic. Specifically, concomitant medications, pharmacogenetic profile, and pathophysiological conditions could influence absorption, distribution, metabolism, and elimination pharmacokinetics. A personalized therapeutic approach taking into consideration all factors potentially contributing to an altered pharmacokinetic/pharmacodynamic profile could better drive safe and effective clinical use. Full article
(This article belongs to the Special Issue Pharmacogenomics)
Show Figures

Graphical abstract

20 pages, 1948 KiB  
Review
Pharmacogenomics of Antibiotics
by Gabriele Stocco, Marianna Lucafò and Giuliana Decorti
Int. J. Mol. Sci. 2020, 21(17), 5975; https://doi.org/10.3390/ijms21175975 - 19 Aug 2020
Cited by 16 | Viewed by 5447
Abstract
Although the introduction of antibiotics in medicine has resulted in one of the most successful events and in a major breakthrough to reduce morbidity and mortality caused by infectious disease, response to these agents is not always predictable, leading to differences in their [...] Read more.
Although the introduction of antibiotics in medicine has resulted in one of the most successful events and in a major breakthrough to reduce morbidity and mortality caused by infectious disease, response to these agents is not always predictable, leading to differences in their efficacy, and sometimes to the occurrence of adverse effects. Genetic variability, resulting in differences in the pharmacokinetics and pharmacodynamics of antibiotics, is often involved in the variable response, of particular importance are polymorphisms in genes encoding for drug metabolizing enzymes and membrane transporters. In addition, variations in the human leukocyte antigen (HLA) class I and class II genes have been associated with different immune mediated reactions induced by antibiotics. In recent years, the importance of pharmacogenetics in the personalization of therapies has been recognized in various clinical fields, although not clearly in the context of antibiotic therapy. In this review, we make an overview of antibiotic pharmacogenomics and of its potential role in optimizing drug therapy and reducing adverse reactions. Full article
(This article belongs to the Special Issue Pharmacogenomics)
Show Figures

Figure 1

26 pages, 1924 KiB  
Review
Pharmacogenomics of Hypertension Treatment
by Jacek Rysz, Beata Franczyk, Magdalena Rysz-Górzyńska and Anna Gluba-Brzózka
Int. J. Mol. Sci. 2020, 21(13), 4709; https://doi.org/10.3390/ijms21134709 - 01 Jul 2020
Cited by 32 | Viewed by 13151
Abstract
Hypertension is one of the strongest modifiable cardiovascular risk factors, affecting an increasing number of people worldwide. Apart from poor medication adherence, the low efficacy of some therapies could also be related to inter-individual genetic variability. Genetic studies of families revealed that heritability [...] Read more.
Hypertension is one of the strongest modifiable cardiovascular risk factors, affecting an increasing number of people worldwide. Apart from poor medication adherence, the low efficacy of some therapies could also be related to inter-individual genetic variability. Genetic studies of families revealed that heritability accounts for 30% to 50% of inter-individual variation in blood pressure (BP). Genetic factors not only affect blood pressure (BP) elevation but also contribute to inter-individual variability in response to antihypertensive treatment. This article reviews the recent pharmacogenomics literature concerning the key classes of antihypertensive drugs currently in use (i.e., diuretics, β-blockers, ACE inhibitors, ARB, and CCB). Due to the numerous studies on this topic and the sometimes-contradictory results within them, the presented data are limited to several selected SNPs that alter drug response. Genetic polymorphisms can influence drug responses through genes engaged in the pathogenesis of hypertension that are able to modify the effects of drugs, modifications in drug–gene mechanistic interactions, polymorphisms within drug-metabolizing enzymes, genes related to drug transporters, and genes participating in complex cascades and metabolic reactions. The results of numerous studies confirm that genotype-based antihypertension therapies are the most effective and may help to avoid the occurrence of major adverse events, as well as decrease the costs of treatment. However, the genetic heritability of drug response phenotypes seems to remain hidden in multigenic and multifactorial complex traits. Therefore, further studies are required to analyze all associations and formulate final genome-based treatment recommendations. Full article
(This article belongs to the Special Issue Pharmacogenomics)
Show Figures

Figure 1

35 pages, 2042 KiB  
Review
Pharmacogenomics and Pharmacogenetics in Osteosarcoma: Translational Studies and Clinical Impact
by Claudia Maria Hattinger, Maria Pia Patrizio, Silvia Luppi and Massimo Serra
Int. J. Mol. Sci. 2020, 21(13), 4659; https://doi.org/10.3390/ijms21134659 - 30 Jun 2020
Cited by 10 | Viewed by 4002
Abstract
High-grade osteosarcoma (HGOS) is a very aggressive bone tumor which primarily affects adolescents and young adults. Although not advanced as is the case for other cancers, pharmacogenetic and pharmacogenomic studies applied to HGOS have been providing hope for an improved understanding of the [...] Read more.
High-grade osteosarcoma (HGOS) is a very aggressive bone tumor which primarily affects adolescents and young adults. Although not advanced as is the case for other cancers, pharmacogenetic and pharmacogenomic studies applied to HGOS have been providing hope for an improved understanding of the biology and the identification of genetic biomarkers, which may impact on clinical care management. Recent developments of pharmacogenetics and pharmacogenomics in HGOS are expected to: i) highlight genetic events that trigger oncogenesis or which may act as drivers of disease; ii) validate research models that best predict clinical behavior; and iii) indicate genetic biomarkers associated with clinical outcome (in terms of treatment response, survival probability and susceptibility to chemotherapy-related toxicities). The generated body of information may be translated to clinical settings, in order to improve both effectiveness and safety of conventional chemotherapy trials as well as to indicate new tailored treatment strategies. Here, we review and summarize the current scientific evidence for each of the aforementioned issues in view of possible clinical applications. Full article
(This article belongs to the Special Issue Pharmacogenomics)
Show Figures

Graphical abstract

82 pages, 20289 KiB  
Review
Pharmacogenomics of Cognitive Dysfunction and Neuropsychiatric Disorders in Dementia
by Ramon Cacabelos
Int. J. Mol. Sci. 2020, 21(9), 3059; https://doi.org/10.3390/ijms21093059 - 26 Apr 2020
Cited by 25 | Viewed by 7172
Abstract
Symptomatic interventions for patients with dementia involve anti-dementia drugs to improve cognition, psychotropic drugs for the treatment of behavioral disorders (BDs), and different categories of drugs for concomitant disorders. Demented patients may take >6–10 drugs/day with the consequent risk for drug–drug interactions and [...] Read more.
Symptomatic interventions for patients with dementia involve anti-dementia drugs to improve cognition, psychotropic drugs for the treatment of behavioral disorders (BDs), and different categories of drugs for concomitant disorders. Demented patients may take >6–10 drugs/day with the consequent risk for drug–drug interactions and adverse drug reactions (ADRs >80%) which accelerate cognitive decline. The pharmacoepigenetic machinery is integrated by pathogenic, mechanistic, metabolic, transporter, and pleiotropic genes redundantly and promiscuously regulated by epigenetic mechanisms. CYP2D6, CYP2C9, CYP2C19, and CYP3A4/5 geno-phenotypes are involved in the metabolism of over 90% of drugs currently used in patients with dementia, and only 20% of the population is an extensive metabolizer for this tetragenic cluster. ADRs associated with anti-dementia drugs, antipsychotics, antidepressants, anxiolytics, hypnotics, sedatives, and antiepileptic drugs can be minimized by means of pharmacogenetic screening prior to treatment. These drugs are substrates, inhibitors, or inducers of 58, 37, and 42 enzyme/protein gene products, respectively, and are transported by 40 different protein transporters. APOE is the reference gene in most pharmacogenetic studies. APOE-3 carriers are the best responders and APOE-4 carriers are the worst responders; likewise, CYP2D6-normal metabolizers are the best responders and CYP2D6-poor metabolizers are the worst responders. The incorporation of pharmacogenomic strategies for a personalized treatment in dementia is an effective option to optimize limited therapeutic resources and to reduce unwanted side-effects. Full article
(This article belongs to the Special Issue Pharmacogenomics)
Show Figures

Figure 1

13 pages, 1067 KiB  
Review
Naltrexone Use in Treating Hypersexuality Induced by Dopamine Replacement Therapy: Impact of OPRM1 A/G Polymorphism on Its Effectiveness
by Audrey Verholleman, Caroline Victorri-Vigneau, Edouard Laforgue, Pascal Derkinderen, Celine Verstuyft and Marie Grall-Bronnec
Int. J. Mol. Sci. 2020, 21(8), 3002; https://doi.org/10.3390/ijms21083002 - 24 Apr 2020
Cited by 11 | Viewed by 5637
Abstract
Hypersexuality is a well-known adverse side effect of dopamine replacement therapy (DRT), and anti-craving drugs could be an effective therapeutic option. Our aim was to update the knowledge on this issue, particularly on the influence of an Opioid Receptor Mu 1 (OPRM1 [...] Read more.
Hypersexuality is a well-known adverse side effect of dopamine replacement therapy (DRT), and anti-craving drugs could be an effective therapeutic option. Our aim was to update the knowledge on this issue, particularly on the influence of an Opioid Receptor Mu 1 (OPRM1) genetic polymorphism. A systematic review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. We also analyzed a case of iatrogenic hypersexuality that occurred in a patient treated with DRT. An analysis of the OPRM1 gene was performed on said patient. Our search identified 597 publications, of which only 7 were included in the final data synthesis. All seven publications involved naltrexone use. Five of them were case reports. None of the publications mentioned DRT side effects, nor did they report genetic data. Regarding our case report, the introduction of naltrexone corresponded with the resolution of the patient’s hypersexuality. Moreover, the patient carried the A/G genotype, which has been reported to be associated with a stronger response to naltrexone for patients with an alcohol use disorder. Although studies are inconclusive so far, naltrexone could be an interesting therapeutic option for resistant hypersexuality due to DRT. Carrying the A/G genotype could help explain a good response to treatment. Full article
(This article belongs to the Special Issue Pharmacogenomics)
Show Figures

Figure 1

15 pages, 344 KiB  
Review
Precision Medicine in Childhood Asthma: Omic Studies of Treatment Response
by Javier Perez-Garcia, Esther Herrera-Luis, Fabian Lorenzo-Diaz, Mario González, Olaia Sardón, Jesús Villar and Maria Pino-Yanes
Int. J. Mol. Sci. 2020, 21(8), 2908; https://doi.org/10.3390/ijms21082908 - 21 Apr 2020
Cited by 11 | Viewed by 3910
Abstract
Asthma is a heterogeneous and multifactorial respiratory disease with an important impact on childhood. Difficult-to-treat asthma is not uncommon among children, and it causes a high burden to the patient, caregivers, and society. This review aims to summarize the recent findings on pediatric [...] Read more.
Asthma is a heterogeneous and multifactorial respiratory disease with an important impact on childhood. Difficult-to-treat asthma is not uncommon among children, and it causes a high burden to the patient, caregivers, and society. This review aims to summarize the recent findings on pediatric asthma treatment response revealed by different omic approaches conducted in 2018–2019. A total of 13 studies were performed during this period to assess the role of genomics, epigenomics, transcriptomics, metabolomics, and the microbiome in the response to short-acting beta agonists, inhaled corticosteroids, and leukotriene receptor antagonists. These studies have identified novel associations of genetic markers, epigenetic modifications, metabolites, bacteria, and molecular mechanisms involved in asthma treatment response. This knowledge will allow us establishing molecular biomarkers that could be integrated with clinical information to improve the management of children with asthma. Full article
(This article belongs to the Special Issue Pharmacogenomics)
25 pages, 422 KiB  
Review
Role of Genetic Variations in the Hepatic Handling of Drugs
by Jose J. G. Marin, Maria A. Serrano, Maria J. Monte, Anabel Sanchez-Martin, Alvaro G. Temprano, Oscar Briz and Marta R. Romero
Int. J. Mol. Sci. 2020, 21(8), 2884; https://doi.org/10.3390/ijms21082884 - 20 Apr 2020
Cited by 13 | Viewed by 3478
Abstract
The liver plays a pivotal role in drug handling due to its contribution to the processes of detoxification (phases 0 to 3). In addition, the liver is also an essential organ for the mechanism of action of many families of drugs, such as [...] Read more.
The liver plays a pivotal role in drug handling due to its contribution to the processes of detoxification (phases 0 to 3). In addition, the liver is also an essential organ for the mechanism of action of many families of drugs, such as cholesterol-lowering, antidiabetic, antiviral, anticoagulant, and anticancer agents. Accordingly, the presence of genetic variants affecting a high number of genes expressed in hepatocytes has a critical clinical impact. The present review is not an exhaustive list but a general overview of the most relevant variants of genes involved in detoxification phases. The available information highlights the importance of defining the genomic profile responsible for the hepatic handling of drugs in many ways, such as (i) impaired uptake, (ii) enhanced export, (iii) altered metabolism due to decreased activation of prodrugs or enhanced inactivation of active compounds, and (iv) altered molecular targets located in the liver due to genetic changes or activation/downregulation of alternative/compensatory pathways. In conclusion, the advance in this field of modern pharmacology, which allows one to predict the outcome of the treatments and to develop more effective and selective agents able to overcome the lack of effect associated with the existence of some genetic variants, is required to step forward toward a more personalized medicine. Full article
(This article belongs to the Special Issue Pharmacogenomics)
12 pages, 519 KiB  
Review
GALNT14: An Emerging Marker Capable of Predicting Therapeutic Outcomes in Multiple Cancers
by Wey-Ran Lin and Chau-Ting Yeh
Int. J. Mol. Sci. 2020, 21(4), 1491; https://doi.org/10.3390/ijms21041491 - 21 Feb 2020
Cited by 23 | Viewed by 2875
Abstract
Members of the polypeptide N-acetylgalactosaminyltransferase (GALNT) family function as the initiating enzymes that catalyze mucin-type O-glycosylation of proteins, and their dysregulated expression can alter cancer cell behaviors such as de novo occurrence, proliferation, migration, metastasis, and drug resistance. Recent studies have demonstrated [...] Read more.
Members of the polypeptide N-acetylgalactosaminyltransferase (GALNT) family function as the initiating enzymes that catalyze mucin-type O-glycosylation of proteins, and their dysregulated expression can alter cancer cell behaviors such as de novo occurrence, proliferation, migration, metastasis, and drug resistance. Recent studies have demonstrated that one of the family’s members, GALNT14, is aberrantly expressed in multiple cancers and involved in a variety of biological functions. Moreover, the single nucleotide polymorphisms (SNPs) of GALNT14-rs9679162 have been shown to predict therapeutic outcomes in patients with hepatocellular carcinoma as well as several other different types of gastrointestinal cancer. This review summarizes the structural features of GANLT14, its functional roles, and the predictive values of GALNT14 genotypes and enzyme levels in multiple cancers receiving distinct anticancer therapies. Full article
(This article belongs to the Special Issue Pharmacogenomics)
Show Figures

Figure 1

15 pages, 227 KiB  
Review
Precision Psychiatry Applications with Pharmacogenomics: Artificial Intelligence and Machine Learning Approaches
by Eugene Lin, Chieh-Hsin Lin and Hsien-Yuan Lane
Int. J. Mol. Sci. 2020, 21(3), 969; https://doi.org/10.3390/ijms21030969 - 01 Feb 2020
Cited by 56 | Viewed by 9451
Abstract
A growing body of evidence now suggests that precision psychiatry, an interdisciplinary field of psychiatry, precision medicine, and pharmacogenomics, serves as an indispensable foundation of medical practices by offering the accurate medication with the accurate dose at the accurate time to patients with [...] Read more.
A growing body of evidence now suggests that precision psychiatry, an interdisciplinary field of psychiatry, precision medicine, and pharmacogenomics, serves as an indispensable foundation of medical practices by offering the accurate medication with the accurate dose at the accurate time to patients with psychiatric disorders. In light of the latest advancements in artificial intelligence and machine learning techniques, numerous biomarkers and genetic loci associated with psychiatric diseases and relevant treatments are being discovered in precision psychiatry research by employing neuroimaging and multi-omics. In this review, we focus on the latest developments for precision psychiatry research using artificial intelligence and machine learning approaches, such as deep learning and neural network algorithms, together with multi-omics and neuroimaging data. Firstly, we review precision psychiatry and pharmacogenomics studies that leverage various artificial intelligence and machine learning techniques to assess treatment prediction, prognosis prediction, diagnosis prediction, and the detection of potential biomarkers. In addition, we describe potential biomarkers and genetic loci that have been discovered to be associated with psychiatric diseases and relevant treatments. Moreover, we outline the limitations in regard to the previous precision psychiatry and pharmacogenomics studies. Finally, we present a discussion of directions and challenges for future research. Full article
(This article belongs to the Special Issue Pharmacogenomics)
Back to TopTop