Project description:Pharmacogenomics holds the promise of personalized drug efficacy optimization and drug toxicity minimization. Much of the research conducted to date, however, suffers from an ascertainment bias towards European participants. Here, we leverage publicly available, whole genome sequencing data collected from global populations, evolutionary characteristics, and annotated protein features to construct a new in silico machine learning pharmacogenetic identification method called XGB-PGX. When applied to pharmacogenetic data, XGB-PGX outperformed all existing prediction methods and identified over 2000 new pharmacogenetic variants. While there are modest pharmacogenetic allele frequency distribution differences across global population samples, the most striking distinction is between the relatively rare putatively neutral pharmacogene variants and the relatively common established and newly predicted functional pharamacogenetic variants. Our findings therefore support a focus on individual patient pharmacogenetic testing rather than on clinical presumptions about patient race, ethnicity, or ancestral geographic residence. We further encourage more attention be given to the impact of common variation on drug response and propose a new 'common treatment, common variant' perspective for pharmacogenetic prediction that is distinct from the types of variation that underlie complex and Mendelian disease. XGB-PGX has identified many new pharmacovariants that are present across all global communities; however, communities that have been underrepresented in genomic research are likely to benefit the most from XGB-PGX's in silico predictions.
Project description:Genetic/genomic profiling at a single-patient level is expected to provide critical information for determining inter-individual drug toxicity and potential efficacy in cancer therapy. A better definition of cancer subtypes at a molecular level, may correspondingly complement such pharmacogenetic and pharmacogenomic approaches, for more effective personalized treatments. Current pharmacogenetic/pharmacogenomic strategies are largely based on the identification of known polymorphisms, thus limiting the discovery of novel or rarer genetic variants. Recent improvements in cost and throughput of next generation sequencing (NGS) are now making whole-genome profiling a plausible alternative for clinical procedures. Beyond classical pharmacogenetic/pharmacogenomic traits for drug metabolism, NGS screening programs of cancer genomes may lead to the identification of novel cancer-driving mutations. These may not only constitute novel therapeutic targets, but also effector determinants for metabolic pathways linked to drug metabolism. An additional advantage is that cancer NGS profiling is now leading to discovering targetable mutations, e.g., in glioblastomas and pancreatic cancers, which were originally discovered in other tumor types, thus allowing for effective repurposing of active drugs already on the market.
Project description:Pharmacogenomics (PGx) relates to the study of genetic factors determining variability in drug response. Implementing PGx testing in paediatric patients can enhance drug safety, helping to improve drug efficacy or reduce the risk of toxicity. Despite its clinical relevance, the implementation of PGx testing in paediatric practice to date has been variable and limited. As with most paediatric pharmacological studies, there are well-recognised barriers to obtaining high-quality PGx evidence, particularly when patient numbers may be small, and off-label or unlicensed prescribing remains widespread. Furthermore, trials enrolling small numbers of children can rarely, in isolation, provide sufficient PGx evidence to change clinical practice, so extrapolation from larger PGx studies in adult patients, where scientifically sound, is essential. This review paper discusses the relevance of PGx to paediatrics and considers implementation strategies from a child health perspective. Examples are provided from Canada, the Netherlands and the UK, with consideration of the different healthcare systems and their distinct approaches to implementation, followed by future recommendations based on these cumulative experiences. Improving the evidence base demonstrating the clinical utility and cost-effectiveness of paediatric PGx testing will be critical to drive implementation forwards. International, interdisciplinary collaborations will enhance paediatric data collation, interpretation and evidence curation, while also supporting dedicated paediatric PGx educational initiatives. PGx consortia and paediatric clinical research networks will continue to play a central role in the streamlined development of effective PGx implementation strategies to help optimise paediatric pharmacotherapy.
Project description:Chemokine receptor 4 and stromal-cell-derived factor 1 have been found to be related to the initiation of neuroinflammation in ischemic brain. Herein, we aimed to monitor the changes of neuorinflammation after AMD3100 treatment using a translocator protein (TSPO) specific PET tracer in a mouse model of stroke. The transient MCAO model was established with Balb/C mice. The success of the model was confirmed by magnetic resonance imaging and FDG PET. The treatment started the same day after surgery via daily intraperitoneal injection of 1 mg of AMD3100/kg for three consecutive days. [(18)F]DPA-714 was used as the TSPO imaging tracer. In vivo PET was performed at different time points after surgery in both control and treated mice. Ex vivo histological and immunofluorescence staining of brain slices was performed to confirm the lesion site and inflammatory cell activation. The TSPO level was also evaluated using Western blotting. Longitudinal PET scans revealed that the level of [(18)F]DPA-714 uptake was significantly increased in the ischemic brain area with a peak accumulation at around day 10 after surgery, and the level of uptake remained high until day 16. The in vivo PET data were consistent with those from ex vivo immunofluorescence staining. After AMD3100 treatment, the signal intensity was significantly decreased compared with that of normal saline-treated control group. In conclusion, TSPO-targeted PET imaging using [(18)F]DPA-714 can be used to monitor inflammatory response after stroke and provide a useful method for evaluating the efficacy of anti-inflammation treatment.
Project description:Major classes of medication in asthma management include bronchodilating beta2-agonists, anti-inflammatory inhaled corticosteroids, leukotriene modifiers and theophyllines. However, all asthmatics do not respond to the same extent to a given medication. Available data suggest that a substantial range of individual variability, as much as 70%, may be due to genetic characteristics of each patient. Pharmacogenomics offers the potential to optimize medications for individual asthmatics by using genetic information to improve efficacy or avoid adverse effects. The best-studied case of the potential contribution of pharmacogenomics to treatment response in asthma comes from studies on human beta2 adrenergic receptors. In addition, genetic variation in beta2-adrenergic receptor (Arg16Gly) may predict response to anticholinergics for the treatment of asthma. In case of inhaled corticosteroids, a recent investigation using a traditional SNP-based approach identified a gene for corticotropin releasing hormone receptor 1 as a potential marker of response. Another major pathway that has been investigated is the pathway underlying response to cysteinyl leukotriene receptor antagonist. It is likely that in the near future, pharmacogenomic approaches based on individual genetic information will be introduced into an asthma treatment guideline and this guideline will allow us to identify those who have the best chance to respond to a specific medication.
Project description:Hereditary breast cancer is known for its strong tendency of inheritance. Most hereditary breast cancers are related to BRCA1/BRCA2 pathogenic variants. The lifelong risk of breast cancer in pathogenic BRCA1 and BRCA2 variant carriers is approximately 65% and 45%, respectively, whereas that of ovarian cancer is estimated to be 39% and 11%, respectively. Therefore, understanding these variants and clinical knowledge on their occurrence in breast cancers and carriers are important. BRCA1 pathogenic variant breast cancer shows more aggressive clinicopathological features than the BRCA2 pathogenic variant breast cancer. Compared with sporadic breast cancer, their prognosis is still debated. Treatments of BRCA1/BRCA2 pathogenic variant breast cancer are similar to those for BRCA-negative breast cancer, mainly including surgery, radiotherapy, and chemotherapy. Recently, various clinical trials have investigated poly (adenosine diphosphate [ADP]-ribose) polymerase (PARP) inhibitor treatment for advanced-stage BRCA1/BRCA2 pathogenic variant breast cancer. Among the various PARP inhibitors, olaparib and talazoparib, which reached phase III clinical trials, showed improvement of median progression-free survival around three months. Preventive and surveillance strategies for BRCA pathogenic variant breast cancer to reduce cancer recurrence and improve treatment outcomes have recently received increasing attention. In this review, we provide an information on the clinical features of BRCA1/BRCA2 pathogenic variant breast cancer and clinical recommendations for BRCA pathogenic variant carriers, with a focus on treatment and prevention strategies. With this knowledge, clinicians could manage the BRCA1/BRCA2 pathogenic variant breast cancer patients more effectively.
Project description:The effectiveness of selective serotonin reuptake inhibitors (SSRIs) in patients with major depressive disorder (MDD) is controversial.The clinical outcomes of subjects with nonpsychotic MDD were reported and compared with the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study outcomes to provide guidance on the effectiveness of SSRIs.Subjects were treated with citalopram/escitalopram for up to 8 weeks. Depression was measured using the Quick Inventory of Depressive Symptomatology-Clinician Rated (QIDS-C16) and the 17-item Hamilton Depression Rating Scale.The group of subjects with at least 1 follow-up visit had a remission (QIDS-C16 ? 5) rate of 45.8% as well as a response (50% reduction in QIDS-C16) rate of 64.8%, and 79.9% achieved an improvement of 5 points or higher in QIDS-C16 score. The Pharmacogenomic Research Network Antidepressant Medication Pharmacogenomic Study subjects were more likely to achieve a response than STAR*D study subjects. After adjustment for demographic factors, the response rates were not significantly different. When reporting the adverse effect burden, 60.5% of the subjects reported no impairment, 31.7% reported a minimal-to-mild impairment, and 7.8% reported a moderate-to-severe burden at the 4-week visit.Patients contemplating initiating an SSRI to treat their MDD can anticipate a high probability of symptom improvement (79.9%) with a low probability that their symptoms will become worse. Patients with lower baseline severity have a higher probability of achieving remission. The Pharmacogenomic Research Network Antidepressant Medication Pharmacogenomic Study replicates many findings of the first phase of the STAR*D study after controlling for the differences between the studies.
Project description:The objective of this study was to evaluate the potential benefit of utilizing a pharmacogenomic testing report to guide the selection and dosing of psychotropic medications in an outpatient psychiatric practice. The non-randomized, open label, prospective cohort study was conducted from September 2009 to July 2010. In the first cohort, depressed patients were treated without the benefit of pharmacogenomic testing (the unguided group). A DNA sample was obtained from patients in the unguided group, but the results were not shared with either the physicians or patients until the end of the 8-week study period. In the second cohort (the guided group), testing results were provided at the beginning of the 8-week treatment period. Depression ratings were collected at baseline and after 2 weeks, 4 weeks and 8 weeks of treatment using the Quick Inventory of Depressive Symptomatology, Clinician Rated (QIDS-C16) and the 17-item Hamilton Rating Scale for Depression (HAM-D17). Clinician and patient satisfaction was also assessed. The reduction in depressive symptoms achieved within the guided treatment group was greater than the reduction of depressive symptoms in the unguided treatment group using either the QIDS-C16 (P=0.002) or HAM-D17 (P=0.04). We concluded that a rapidly available pharmacogenomic interpretive report provided clinical guidance that was associated with improved clinical outcomes for depressed patients treated in an outpatient psychiatric clinic setting.
Project description:In a mouse model of Niemann-Pick disease type C1 (NPC1), a combination therapy (COMBI) of miglustat (MIGLU), the neurosteroid allopregnanolone (ALLO) and the cyclic oligosaccharide 2-hydroxypropyl-β-cyclodextrin (HPßCD) has previously resulted in, among other things, significantly improved motor function. The present study was designed to compare the therapeutic effects of the COMBI therapy with that of MIGLU or HPßCD alone on body and brain weight and the behavior of NPC1-/- mice in a larger cohort, with special reference to gender differences. A total of 117 NPC1-/- and 123 NPC1+/+ mice underwent either COMBI, MIGLU only, HPßCD only, or vehicle treatment (Sham), or received no treatment at all (None). In male and female NPC1-/- mice, all treatments led to decreased loss of body weight and, partly, brain weight. Concerning motor coordination, as revealed by the accelerod test, male NPC1-/- mice benefited from COMBI treatment, whereas female mice benefited from COMBI, MIGLU, and HPßCD treatment. As seen in the open field test, the reduced locomotor activity of male and female NPC1-/- mice was not significantly ameliorated in either treatment group. Our results suggest that in NPC1-/- mice, each drug treatment scheme had a beneficial effect on at least some of the parameters evaluated compared with Sham-treated mice. Only in COMBI-treated male and female NPC+/+ mice were drug effects seen in reduced body and brain weights. Upon COMBI treatment, the increased dosage of drugs necessary for anesthesia in Sham-treated male and female NPC1-/- mice was almost completely reduced only in the female groups.
Project description:Lack of efficacy or adverse drug response are common phenomena in pharmacological therapy causing considerable morbidity and mortality. It is estimated that 20-30% of this variability in drug response stems from variations in genes encoding drug targets or factors involved in drug disposition. Leveraging such pharmacogenomic information for the preemptive identification of patients who would benefit from dose adjustments or alternative medications thus constitutes an important frontier of precision medicine. Computational methods can be used to predict the functional effects of variant of unknown significance. However, their performance on pharmacogenomic variant data has been lackluster. To overcome this limitation, we previously developed an ensemble classifier, termed APF, specifically designed for pharmacogenomic variant prediction. Here, we aimed to further improve predictions by leveraging recent key advances in the prediction of protein folding based on deep neural networks. Benchmarking of 28 variant effect predictors on 530 pharmacogenetic missense variants revealed that structural predictions using AlphaMissense were most specific, whereas APF exhibited the most balanced performance. We then developed a new tool, APF2, by optimizing algorithm parametrization of the top performing algorithms for pharmacogenomic variations and aggregating their predictions into a unified ensemble score. Importantly, APF2 provides quantitative variant effect estimates that correlate well with experimental results (R2 = 0.91, p = 0.003) and predicts the functional impact of pharmacogenomic variants with higher accuracy than previous methods, particularly for clinically relevant variations with actionable pharmacogenomic guidelines. We furthermore demonstrate better performance (92% accuracy) on an independent test set of 146 variants across 61 pharmacogenes not used for model training or validation. Application of APF2 to population-scale sequencing data from over 800,000 individuals revealed drastic ethnogeographic differences with important implications for pharmacotherapy. We thus think that APF2 holds the potential to improve the translation of genetic information into pharmacogenetic recommendations, thereby facilitating the use of Next-Generation Sequencing data for stratified medicine.