Search Results (9)

Background: Pharmacogenetics (PGx) aims to determine genetic signatures that can be used in clinical settings to individualize treatment for each patient, including anti-cancer drugs, anti-psychotics, and painkillers. Taken together, a better understanding of the impacts of genetic variants on the corresponding protein function or expression permits the prediction of the pharmacological response: responders, non-responders, and those with adverse drug reactions (ADRs). Objective: This work provides a comparison between innovative long-read sequencing (LRS) and short-read sequencing (SRS) techniques. Methods and Materials: The gene panel captured using PacBio HiFi^® sequencing was tested on thirteen clinical samples on GENTYANE’s platform. SRS, using a comprehensive pharmacogenetics panel, was performed in routine settings at the Civil Hospitals of Lyon. We focused on complex regions analysis, including copy number variations (CNVs), structural variants, repeated regions, and phasing-haplotyping for three key pharmacogenes: CYP2D6, UGT1A1, and NAT2. Results: Variants and the corresponding expected star (*) alleles were reported. Although only 38.4% concordance was found for haplotype determination and 61.5% for diplotype, this did not affect the metabolism scoring. A better accuracy of LRS was obtained for the detection of the CYP2D6*5 haplotype in the presence of the duplicated wild-type CYP2D6*2 form. A total concordance was performed for UGT1A1 TA repeat detection. Direct phasing using the LRS approach allowed us to correct certain NAT2 profiles. Conclusions: Combining an optimized variant-calling pipeline and with direct phasing analysis, LRS is a robust technique for PGx analysis that can minimize the risk of mis-haplotyping. Full article

The long-read RNA sequencing developed by Oxford Nanopore Technology provides a direct quantification of transcript isoforms. That makes the number of transcript isoforms per gene an intrinsically suitable metric for alternative splicing (AS) profiling in the application to this particular type of RNA sequencing. By using this simple metric and recruiting principal component analysis (PCA) as a tool to visualize the high-dimensional transcriptomic data, we were able to group biospecimens of normal human liver tissue and hepatocyte-derived malignant HepG2 and Huh7 cells into clear clusters in a 2D space. For the transcriptome-wide analysis, the clustering was observed regardless whether all genes were included in analysis or only those expressed in all biospecimens tested. However, in the application to a particular set of genes known as pharmacogenes, which are involved in drug metabolism, the clustering worsened dramatically in the latter case. Based on PCA data, the subsets of genes most contributing to biospecimens’ grouping into clusters were selected and subjected to gene ontology analysis that allowed us to determine the top 20 biological processes among which translation and processes related to its regulation dominate. The suggested metrics can be a useful addition to the existing metrics for describing AS profiles, especially in application to transcriptome studies with long-read sequencing. Full article

The complementary interaction of microRNAs (miRNAs) with their binding sites in the 3′untranslated regions (3′UTRs) of target gene mRNAs represses translation, playing a leading role in gene expression control. MiRNA recognition elements (MREs) in the 3′UTRs of genes often contain single nucleotide polymorphisms (SNPs), which can change the binding affinity for target miRNAs leading to dysregulated gene expression. Accumulated data suggest that these SNPs can be associated with various human pathologies (cancer, diabetes, neuropsychiatric disorders, and cardiovascular diseases) by disturbing the interaction of miRNAs with their MREs located in mRNA 3′UTRs. Numerous data show the role of SNPs in 3′UTR MREs in individual drug susceptibility and drug resistance mechanisms. In this review, we brief the data on such SNPs focusing on the most rigorously proven cases. Some SNPs belong to conventional genes from the drug-metabolizing system (in particular, the genes coding for cytochromes P450 (CYP 450), phase II enzymes (SULT1A1 and UGT1A), and ABCB3 transporter and their expression regulators (PXR and GATA4)). Other examples of SNPs are related to the genes involved in DNA repair, RNA editing, and specific drug metabolisms. We discuss the gene-by-gene studies and genome-wide approaches utilized or potentially utilizable to detect the MRE SNPs associated with individual response to drugs. Full article

Objective: This study describes the single nucleotide polymorphisms (SNPs) in amlodipine-associated genes and assesses their correlation with blood pressure control among South African adults with hypertension. Methods: In total, 304 hypertensive patients on amlodipine treatment belonging to the indigenous Swati, Xhosa and Zulu population groups of South Africa were recruited between June 2017 and June 2019. Participants were categorized into: controlled (blood pressure < 140/90 mmHg) and uncontrolled (blood pressure ≥ 140/90 mmHg) hypertension. Thirteen SNPs in amlodipine pharmacogenes with a high PharmGKB evidence base were selected and genotyped using MassArray (Agena Bioscience^TM). Logistic regression was fitted to identify significant associations between the SNPs and blood pressure control with amlodipine. Results: The majority of the participants were females (76.6%), older than 45 years (89.1%) and had uncontrolled hypertension (52.3%). Of the 13 SNPs genotyped, five SNPs, rs1042713 (minor allele frequency = 45.9%), rs10494366 (minor allele frequency = 35.3%), rs2239050 (minor allele frequency = 28.7%), rs2246709 (minor allele frequency = 51.6%) and rs4291 (minor allele frequency = 34.4%), were detected among the Xhosa participants, while none were detected among the Swati and Zulu tribal groups. Variants rs1042713 and rs10494366 demonstrated an expression frequency of 97.5% and 79.5%, respectively. Variant TA genotype of rs4291 was significantly associated with uncontrolled hypertension. No association was established between blood pressure response to amlodipine and the remaining four SNPs. Conclusions: This study reports the discovery of five SNPs in amlodipine genes (rs2239050, rs2246709, rs4291, rs1042713 and rs10494366) among the indigenous Xhosa-speaking tribe of South Africa. In addition, the TA genotype of rs4291 was associated with blood pressure control in this cohort. These findings might open doors for more pharmacogenomic studies, which could inform innovations to personalised anti-hypertensive treatment in the ethnically diverse population of South Africa. Full article

Pharmacogenomics (PGx) entails the study of heritability of drug response. This may include both variability in genes related to pharmacokinetics (drug absorption, distribution, metabolism and excretion) and pharmacodynamics (e.g., drug receptors or signaling pathways). Individualizing drug therapy taking into account the genetic profile of the patient has the potential to make drug therapy safer and more effective. Currently, this approach relies on the determination of genetic variants in pharmacogenes by genotyping. However, it is widely acknowledged that large variability in gene expression is attributed to non-structural genetic variants. Therefore, at least from a theoretical viewpoint individualizing drug therapy based upon expression of pharmacogenes rather than on genotype may be advantageous but has been difficult to implement in the clinical setting. Extracellular vesicles (EVs) are lipid encapsulated structures that contain cargo such as lipids, nucleic acids and proteins. Since their cargo is tissue- and cell-specific they can be used to determine the expression of pharmacogenes in the liver. In this review, we describe methods of EV isolation and the potential of EVs isolated from liquid biopsies as a tool to determine the expression of pharmacogenes for use in personalized medicine. Full article

A transcriptome-wide analysis of human liver for demonstrating differences between young and old humans has not yet been performed. However, identifying major age-related alterations in hepatic gene expression may pinpoint ontogenetic shifts with important hepatic and systemic consequences, provide novel pharmacogenetic information, offer clues to efficiently counteract symptoms of old age, and improve the overarching understanding of individual decline. Next-generation sequencing (NGS) data analyzed by the Mann–Whitney nonparametric test and Ensemble Feature Selection (EFS) bioinformatics identified 44 transcripts among 60,617 total and 19,986 protein-encoding transcripts that significantly (p = 0.0003 to 0.0464) and strikingly (EFS score > 0.3:16 transcripts; EFS score > 0.2:28 transcripts) differ between young and old livers. Most of these age-related transcripts were assigned to the categories ‘regulome’, ‘inflammaging’, ‘regeneration’, and ‘pharmacogenes’. NGS results were confirmed by quantitative real-time polymerase chain reaction. Our results have important implications for the areas of ontogeny/aging and the age-dependent increase in major liver diseases. Finally, we present a broadly substantiated and testable hypothesis on a genetically governed ‘aging cascade’, wherein PPP1R10 acts as a putative ontogenetic master regulator, prominently flanked by IGFALS and DUSP1. This transcriptome-wide analysis of human liver offers potential clues towards developing safer and improved therapeutic interventions against major liver diseases and increased insights into key mechanisms underlying aging. Full article

Individual response to drugs is highly variable and largely influenced by genetic variants and gene-expression profiles. In addition, it has been shown that response to drugs is strongly sex-dependent, both in terms of efficacy and toxicity. To expand current knowledge on sex differences in the expression of genes relevant for drug response, we generated a catalogue of differentially expressed human transcripts encoded by 289 genes in 41 human tissues from 838 adult individuals of the Genotype-Tissue Expression project (GTEx, v8 release) and focused our analysis on relevant transcripts implicated in drug response. We detected significant sex-differentiated expression of 99 transcripts encoded by 59 genes in the tissues most relevant for human pharmacology (liver, lung, kidney, small intestine terminal ileum, skin not sun-exposed, and whole blood). Among them, as expected, we confirmed significant differences in the expression of transcripts encoded by the cytochromes in the liver, CYP2B6, CYP3A7, CYP3A5, and CYP1A1. Our systematic investigation on differences between male and female in the expression of drug response-related genes, reinforce the need to overcome the sex bias of clinical trials. Full article

Pharmacogenomics is an evolving tool of precision medicine. Recently, due to the introduction of next-generation sequencing and projects generating “Big Data”, a plethora of new genetic variants in pharmacogenes have been discovered. Cancer resistance is a major complication often preventing successful anticancer treatments. Pharmacogenomics of both somatic mutations in tumor cells and germline variants may help optimize targeted treatments and improve the response to conventional oncological therapy. In addition, integrative approaches combining copy number variations and long noncoding RNA profiling with germline and somatic variations seem to be a promising approach as well. In pharmacology, expression and enzyme activity are traditionally the more studied aspects of ATP-binding cassette transporters and cytochromes P450. In this review, we briefly introduce the field of pharmacogenomics and the advancements driven by next-generation sequencing and outline the possible roles of genetic variation in the two large pharmacogene superfamilies. Although the evidence needs further substantiation, somatic and copy number variants as well as rare variants and common polymorphisms in these genes could all affect response to cancer therapy. Regulation by long noncoding RNAs has also been shown to play a role. However, in all these areas, more comprehensive studies on larger sets of patients are needed. Full article

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