Identification and functional validation of novel pharmacogenomic variants using a next-generation sequencing-based approach for clinical pharmacogenomics.

Inter-individual variability in pharmacokinetics and drug response is heavily influenced by single-nucleotide variants (SNVs) and copy-number variations (CNVs) in genes with importance for drug disposition. Nowadays, a plethora of studies implement next generation sequencing to capture rare and novel pharmacogenomic (PGx) variants that influence drug response. To address these issues, we present a comprehensive end-to-end analysis workflow, beginning from targeted PGx panel re-sequencing to in silico analysis pipelines and in vitro validation assays. Specifically, we show that novel pharmacogenetic missense variants that are predicted or putatively predicted to be functionally deleterious, significantly alter protein activity levels of CYP2D6 and CYP2C19 proteins. We further demonstrate that variant priorization pipelines tailored with functional in vitro validation assays provide supporting evidence for the deleterious effect of novel PGx variants. The proposed workflow could provide the basis for integrating next-generation sequencing for PGx testing into routine clinical practice.

Discrepancies and similarities in the genome-informed guidance for psychiatric disorders amongst different regulatory bodies and research consortia using next generation sequencing-based clinical pharmacogenomics data.

Undoubtedly, pharmacogenomics (PGx) aims in optimizing drug treatment responses whilst also improving the patients' quality of life, either via a reduction of adverse drug reactions and/or an enhancement of drug treatment efficacy. To achieve this, PGx guidance is provided by the two major regulatory bodies in a worldwide level, specifically the U.S. Food and Drug Administration (FDA) and the European Medicine Agency (EMA), and occasionally some research consortia, such as the Clinical Pharmacogenetics Implementation Consortium (CPIC) or the Dutch Pharmacogenomics Working Group (DPWG). However, so far, there is a limited number of studies focusing on the delineation of the similarities and more importantly, the discrepancies in the PGx guidance by the different regulatory bodies and consortia. Herein, we use real-life clinical PGx data to highlight such discrepancies and similarities for genome-guided interventions in psychiatric disorders, thus demonstrating the need for harmonization of the guidelines and recommendations. More precisely, we used the PharmCAT genome-informed drug treatment reports from 304 Greek individuals with psychiatric disorders in order to emphasize on the discrepancies in the PGx guidance/guidelines between FDA vs EMA and CPIC vs DPWG, respectively. For example, CYP2D6-pimozide pair is characterized as 'Testing Required' according to FDA and is accompanied by a DPWG PGx guideline, whilst no EMA or CPIC PGx guidance is found for this drug-gene pair. Moreover, discrepancies are observed regarding the type of PGx guidance for CYP2C19-doxepin pair, with 89 individuals from our study cohort requiring a dose prescribing change based on FDA, whilst only 5 individuals have to receive genome-guided treatment adjustment according to CPIC. To our knowledge, this is the first study, in which discrepancies regarding the type of PGx guidance and the number of actionable drug-gene pairs amongst FDA and EMA, as well as CPIC and DPWG, are brought to light with an emphasis on psychiatric disorders.

Documentation of clinically relevant genomic biomarker allele frequencies in the next-generation FINDbase worldwide database.

FINDbase (http://www.findbase.org) is a comprehensive data resource recording the prevalence of clinically relevant genomic variants in various populations worldwide, such as pathogenic variants underlying genetic disorders as well as pharmacogenomic biomarkers that can guide drug treatment. Here, we report significant new developments and technological advancements in the database architecture, leading to a completely revamped database structure, querying interface, accompanied with substantial extensions of data content and curation. In particular, the FINDbase upgrade further improves the user experience by introducing responsive features that support a wide variety of mobile and stationary devices, while enhancing computational runtime due to the use of a modern Javascript framework such as ReactJS. Data collection is significantly enriched, with the data records being divided in a Public and Private version, the latter being accessed on the basis of data contribution, according to the microattribution approach, while the front end was redesigned to support the new functionalities and querying tools. The abovementioned updates further enhance the impact of FINDbase, improve the overall user experience, facilitate further data sharing by microattribution, and strengthen the role of FINDbase as a key resource for personalized medicine applications and personalized public health.

Leukocyte telomere length is reduced in patients with major depressive disorder.

Major depressive disorder (MDD) is a chronic, severe psychiatric illness with an incidence of 3% worldwide. MDD patients have a significantly impaired quality of life and reduced life expectancy compared to unaffected individuals, the latter being largely accounted for by an increased incidence of suicide and cardiovascular disorders. The premature mortality observed in MDD has been considered a signature of accelerated aging, a hypothesis supported by data showing altered functioning and morphology of several brain regions that are typically present in the aging population. Telomere shortening is a hallmark of cellular aging, and as such several studies explored the involvement of disrupted telomere dynamics in MDD, reporting contrasting findings. In the current study, we measured leukocyte telomere length (LTL) in a sample of 54 MDD patients and 47 non-psychiatric controls characterized for response to antidepressant treatment. After correcting for age, sex, and body mass index, we showed significantly reduced LTL in affected individuals compared to controls (beta = -.22, p = .02). There was no difference in LTL between treatment resistant or responsive MDD patients. Moreover, we observed no correlation between lifetime exposure to antidepressants and LTL. Our study showed that MDD patients have shorter telomeres compared to controls, supporting the hypothesis of accelerated aging in this disorder. However, LTL seemed not to be influenced by antidepressant treatment or to correlate with clinical response to these antidepressants. Further investigations in larger samples and possibly with longitudinal design are warranted to elucidate the role of altered telomere dynamics in MDD.

Pharmacogenomics variants are associated with BMI differences between individuals with bipolar and other psychiatric disorders.

Aim: Regardless of the plethora of next-generation sequencing studies in the field of pharmacogenomics (PGx), the potential effect of covariate variables on PGx response within deeply phenotyped cohorts remains unexplored. Materials & methods: We explored with advanced statistical methods the potential influence of BMI, as a covariate variable, on PGx response in a Greek cohort with psychiatric disorders. Results: Nine PGx variants within UGT1A6, SLC22A4, GSTP1, CYP4B1, CES1, SLC29A3 and DPYD were associated with altered BMI in different psychiatric disorder groups. Carriers of rs2070959 (UGT1A6), rs199861210 (SLC29A3) and rs2297595 (DPYD) were also characterized by significant changes in the mean BMI, depending on the presence of psychiatric disorders. Conclusion: Specific PGx variants are significantly associated with BMI in a Greek cohort with psychiatric disorders.

Prevalence of pharmacogenomic variants in 100 pharmacogenes among Southeast Asian populations under the collaboration of the Southeast Asian Pharmacogenomics Research Network (SEAPharm).

Pharmacogenomics can enhance the outcome of treatment by adopting pharmacogenomic testing to maximize drug efficacy and lower the risk of serious adverse events. Next-generation sequencing (NGS) is a cost-effective technology for genotyping several pharmacogenomic loci at once, thereby increasing publicly available data. A panel of 100 pharmacogenes among Southeast Asian (SEA) populations was resequenced using the NGS platform under the collaboration of the Southeast Asian Pharmacogenomics Research Network (SEAPharm). Here, we present the frequencies of pharmacogenomic variants and the comparison of these pharmacogenomic variants among different SEA populations and other populations used as controls. We investigated the different types of pharmacogenomic variants, especially those that may have a functional impact. Our results provide substantial genetic variations at 100 pharmacogenomic loci among SEA populations that may contribute to interpopulation variability in drug response phenotypes. Correspondingly, this study provides basic information for further pharmacogenomic investigations in SEA populations.