Project description:It is well known that drug responses differ among patients with regard to dose requirements, efficacy, and adverse drug reactions (ADRs). The differences in drug responses are partially explained by genetic variation. This paper highlights some examples of areas in which the different responses (dose, efficacy, and ADRs) are studied in children, including cancer (cisplatin), thrombosis (vitamin K antagonists), and asthma (long-acting ?2 agonists). For childhood cancer, the replication of data is challenging due to a high heterogeneity in study populations, which is mostly due to all the different treatment protocols. For example, the replication cohorts of the association of variants in TPMT and COMT with cisplatin-induced ototoxicity gave conflicting results, possibly as a result of this heterogeneity. For the vitamin K antagonists, the evidence of the association between variants in VKORC1 and CYP2C9 and the dose is clear. Genetic dosing models have been developed, but the implementation is held back by the impossibility of conducting a randomized controlled trial with such a small and diverse population. For the long-acting ?2 agonists, there is enough evidence for the association between variant ADRB2 Arg16 and treatment response to start clinical trials to assess clinical value and cost effectiveness of genotyping. However, further research is still needed to define the different asthma phenotypes to study associations in comparable cohorts. These examples show the challenges which are encountered in pediatric pharmacogenomic studies. They also display the importance of collaborations to obtain good quality evidence for the implementation of genetic testing in clinical practice to optimize and personalize treatment.
Project description:Sickle cell disease (SCD) is a monogenetic disease but has a wide range of phenotypic expressions. Some of these differences in phenotype can be explained by genetic polymorphisms in the human globin gene. These polymorphisms can result in different responses to typical treatment, sometimes leading to inadequate therapeutics. Research is revealing more polymorphisms, and therefore, new targets for intervention to improve outcomes in SCD. This area of pharmacogenomics is continuing to develop. We provide a brief review of the current literature on pharmacogenomics in SCD and possible targets for intervention.
Project description:The Pharmacogenomics Knowledgebase (PharmGKB) is a resource that collects, curates, and disseminates information about the impact of human genetic variation on drug responses. It provides clinically relevant information, including dosing guidelines, annotated drug labels, and potentially actionable gene-drug associations and genotype-phenotype relationships. Curators assign levels of evidence to variant-drug associations using well-defined criteria based on careful literature review. Thus, PharmGKB is a useful source of high-quality information supporting personalized medicine-implementation projects.
Project description:Osteoporosis is a complicated and preventable disease with major morbidity complications that affects millions of people. In the last 15 years, there have been numerous studies and research in the new fields of pharmacogenetics and pharmacogenomics related to osteoporosis. Numerous "candidate genes" have been identified and have been found to be associated with osteoporosis as well as the treatment of osteoporosis. Many studies have found conflicting results on different polymorphisms and whether or not they are related to bone mineral density and osteoporosis. There is a need for larger and better designed pharmacogenomic studies related to osteoporosis incorporating a greater variety of candidate genes. The evaluation of osteoporosis and fracture risk is moving from a risk stratification approach to a more individualized approach, in which an individual's absolute risk of fracture is evaluable as a constellation of the individual's environmental exposure and genetic makeup. Therefore, the identification of gene variants associated with osteoporosis phenotypes or response to therapy might help individualize the prognosis, treatment, and prevention of fracture. This review focuses on major candidate genes and what needs to be done to take the genetics of osteoporosis and incorporate them into the pharmacogenomics of the management of osteoporosis.
Project description:Cannabis and related compounds have created significant research interest as a promising therapy in many disorders. However, the individual therapeutic effects of cannabinoids and the incidence of side effects are still difficult to determine. Pharmacogenomics may provide the answers to many questions and concerns regarding the cannabis/cannabinoid treatment and help us to understand the variability in individual responses and associated risks. Pharmacogenomics research has made meaningful progress in identifying genetic variations that play a critical role in interpatient variability in response to cannabis. This review classifies the current knowledge of pharmacogenomics associated with medical marijuana and related compounds and can assist in improving the outcomes of cannabinoid therapy and to minimize the adverse effects of cannabis use. Specific examples of pharmacogenomics informing pharmacotherapy as a path to personalized medicine are discussed.
Project description:BackgroundCoronary artery disease (CAD) is the most common reason for mortality and disability-adjusted life years (DALYs) lost globally. This study aimed to suggest a new gene list for the treatment of CAD by a systematic review of bioinformatics analyses of pharmacogenomics impacts of potential genes and variants.MethodsPubMed search was filtered by the title including Coronary Artery Disease during 2020-2023. To find the genes with pharmacogenetic impact on the CAD, additional filtrations were considered according to the variant annotations. Protein-Protein Interactions (PPIs), Gene-miRNA Interactions (GMIs), Protein-Drug Interactions (PDIs), and variant annotation assessments (VAAs) performed by STRING-MODEL (ver. 12), Cytoscape (ver. 3.10), miRTargetLink.2., NetworkAnalyst (ver 0.3.0), and PharmGKB.ResultsResults revealed 5618 publications, 1290 papers were qualified, and finally, 650 papers were included. 4608 protein-coding genes were extracted, among them, 1432 unique genes were distinguished and 530 evidence-based repeated genes remained. 71 genes showed a pharmacogenetics-related variant annotation in at least (entirely 6331 annotations). Variant annotation assessment (VAA) showed 532 potential variants for the final report, and finally, the concluding PGs list represented 175 variants. Based on the function and MAF, 57 nonsynonymous variants of 29 Pharmacogenomics-related genes were associated with CAD.ConclusionConclusively, evaluating circulating miR33a in individuals' plasma with CAD, and genotyping of rs2230806, rs2230808, rs2487032, rs12003906, rs2472507, rs2515629, and rs4149297 (ABCA1 variants) lead to precisely prescribing of well-known drugs. Also, the findings of this review can be used in both whole-genome sequencing (WGS) and whole-exome sequencing (WES) analysis in the prognosis and diagnosis of CAD.
Project description:IntroductionDespite the effectiveness of exercise-based interventions on symptom management and disease progression, many people with Parkinson's Disease (PwPD) do not exercise regularly. In line with the ubiquitous use of digital health technology, the MoveONParkinson digital solution was developed, comprising a Web Platform and a Mobile App with a Conversational Agent (CA). The interface features were designed based on the principles of Social Cognitive Theory with the goal of fostering behavior change in PwPD for sustained exercise participation and improved disease management.MethodsUsing a mixed methods approach, this study aimed to collect feedback, assess the acceptability of the Mobile App and the Web Platform, and evaluate the usability of the latter. Quantitative data, which included questionnaire responses and the System Usability Scale (SUS) scores, were analyzed using descriptive statistics, heatmaps, and correlation matrices. Qualitative data, comprising semi-structured and thinking-aloud interview transcripts, were subjected to an inductive thematic analysis. A total of 28 participants were involved in the study, comprising 20 physiotherapists (average age: 34.50 ± 10.4), and eight PwPD (average age: 65.75 ± 8.63; mean Hoehn & Yahr: 2.0 (± 0.76)).ResultsThree main themes emerged from the thematic analysis of the interviews, namely: Self-management (Theme 1), User Engagement (Theme 2), and Recommendations (Theme 3). The assessment of the Mobile App and the CA (mean score: 4.42/5.0 ± 0.79) suggests that PwPD were able to navigate this interface without notable difficulties. The mean SUS score of 79.50 (± 12.40%) with a 95% confidence interval ranging from 73.70 to 85.30, reveal good usability.DiscussionThese findings indicate a high level of acceptability of the MoveONParkinson digital solution, serving as a foundation for assessing its impact on exercise engagement and, subsequently, its influence on symptom management and quality of life of PwPD.
Project description:Pain is a common symptom that can be complex to treat. Analgesic medications are the mainstay treatment, but there is wide interindividual variability in analgesic response and adverse effects. Pharmacogenomics is the study of inherited genetic traits that result in these individual responses to drugs. This narrative review will attempt to cover the current understanding of the pharmacogenomics of pain, examining common genes affecting metabolism of analgesic medications, their distribution throughout the body, and end organ effects.