The Development, Validation and Implementation of a Broad-Based ADME Genotyping Assay into Research and Clinical Trials

Afin d’adresser la variabilité interindividuelle observée dans la réponse pharmacocinétique à de nombreux médicaments, nous avons créé un panel de génotypage personnalisée en utilisant des méthodes de conception et d’élaboration d’essais uniques. Celles-ci ont pour but premier de capturer les variations génétiques présentent dans les gènes clés impliqués dans les processus d'absorption, de distribution, de métabolisme et d’excrétion (ADME) de nombreux agents thérapeutiques. Bien que ces gènes et voies de signalement sont impliqués dans plusieurs mécanismes pharmacocinétiques qui sont bien connues, il y a eu jusqu’à présent peu d'efforts envers l’évaluation simultanée d’un grand nombre de ces gènes moyennant un seul outil expérimental. La recherche pharmacogénomique peut être réalisée en utilisant deux approches: 1) les marqueurs fonctionnels peuvent être utilisés pour présélectionner ou stratifier les populations de patients en se basant sur des états métaboliques connus; 2) les marqueurs Tag peuvent être utilisés pour découvrir de nouvelles corrélations génotype-phénotype. Présentement, il existe un besoin pour un outil de recherche qui englobe un grand nombre de gènes ADME et variantes et dont le contenu est applicable à ces deux modèles d'étude. Dans le cadre de cette thèse, nous avons développé un panel d’essais de génotypage de 3,000 marqueurs génétiques ADME qui peuvent satisfaire ce besoin. Dans le cadre de ce projet, les gènes et marqueurs associés avec la famille ADME ont été sélectionnés en collaboration avec plusieurs groupes du milieu universitaire et de l'industrie pharmaceutique. Pendant trois phases de développement de cet essai de génotypage, le taux de conversion pour 3,000 marqueurs a été amélioré de 83% à 97,4% grâce à l'incorporation de nouvelles stratégies ayant pour but de surmonter les zones d'interférence génomiques comprenant entre autres les régions homologues et les polymorphismes sous-jacent les régions d’intérêt. La précision du panel de génotypage a été validée par l’évaluation de plus de 200 échantillons pour lesquelles les génotypes sont connus pour lesquels nous avons obtenu une concordance > 98%. De plus, une comparaison croisée entre nos données provenant de cet essai et des données obtenues par différentes plateformes technologiques déjà disponibles sur le marché a révélé une concordance globale de > 99,5%. L'efficacité de notre stratégie de conception ont été démontrées par l'utilisation réussie de cet essai dans le cadre de plusieurs projets de recherche où plus de 1,000 échantillons ont été testés. Nous avons entre autre évalué avec succès 150 échantillons hépatiques qui ont été largement caractérisés pour plusieurs phénotypes. Dans ces échantillons, nous avons pu valider 13 gènes ADME avec cis-eQTL précédemment rapportés et de découvrir et de 13 autres gènes ADME avec cis eQTLs qui n'avaient pas été observés en utilisant des méthodes standard. Enfin, à l'appui de ce travail, un outil logiciel a été développé, Opitimus Primer, pour aider pour aider au développement du test. Le logiciel a également été utilisé pour aider à l'enrichissement de cibles génomiques pour d'expériences séquençage. Le contenu ainsi que la conception, l’optimisation et la validation de notre panel le distingue largement de l’ensemble des essais commerciaux couramment disponibles sur le marché qui comprennent soit des marqueurs fonctionnels pour seulement un petit nombre de gènes, ou alors n’offre pas une couverture adéquate pour les gènes connus d’ADME. Nous pouvons ainsi conclure que l’essai que nous avons développé est et continuera certainement d’être un outil d’une grande utilité pour les futures études et essais cliniques dans le domaine de la pharmacocinétique, qui bénéficieraient de l'évaluation d'une longue liste complète de gènes d’ADME.In order to better assess the inter-individual variability observed in a patient’s pharmacokinetic response to many medications, we have created a custom genotyping panel that uses unique assay designs to analyze variation present in key genes involved in the absorption, distribution, metabolism and excretion (ADME) of many therapeutic agents. These genes and pathways involved in most pharmacokinetic mechanisms are well known. However, as yet, there has been little effort to develop tools that can interrogate a large number of variations in most known drug metabolizing genes simultaneously within a single experimental tool. Pharmacogenomic research has historically been conducted using two approaches: targeted studies that screen a small number of specific functional markers to identify known metabolic status phenotypes, and genome-wide studies that identify novel genetic correlations with drug response phenotypes. Thus, a gap currently exists for a targeted ADME research tool that can evaluate a large number of key ADME genes and variants in a format that can be applicable to both types of study designs. As part of this thesis, we have developed a 3000 SNP broad based ADME genotyping panel that can address this need. Genes and markers for the genotyping panel were selected in collaboration with many groups from both academia and the pharmaceutical industry in an effort to capture all pertinent genes and metabolic pathways that have been implicated in drug metabolism. The final assay design was composed of over 3000 markers in 181 genes. Over three phases of iterative development, the assay conversion rate for the 3000 markers was improved from 83.0% to 97.4% through the incorporation of novel design strategies to overcome areas of genomic interference such as regions of homology and underlying polymorphisms. Accuracy of the assay was validated by screening more than 200 samples of known genotype with a concordance of 99%. Additionally, data from the assay has also been compared to data from different technological platforms and has an overall concordance of 99.5%. The effectiveness of the design strategy was demonstrated in the successful utilization of the assay in the screening of over 1000 samples which identified several novel pharmacogenetic associations between ADME variations and adverse drug reactions in children. Another goal of this thesis was to demonstrate what added benefit/utility the 3000 SNP ADME panel would have when compared to currently available genotyping assays. Using 150 extensively investigated liver samples, the broad based assay was not only able to detect and validate 13 previously reported cis eQTLs in ADME genes but further identified an additional 13 novel ADME cis eQTLs that had never been observed before, doubling the number previously identified using standard methods on the same samples. Finally, in support of this work, a number of bioinformatic tools had to be developed to help expedite this research. These tools have been further refined and are currently being used to assist with enrichment of genomic targets for next generation sequencing experiments. In conclusion, this work has led to a better understanding of ADME genetics and the nuances of assaying ADME genes. The content and designs of the developed assay sets it apart from currently available commercial assays that contain only functional markers in a small number of genes or do not have adequate coverage across ADME genes. The assay has the ability to play a significant role in pharmacogenomic studies to identify known and novel pharmacogenomic biomarkers. These will lead to improved biomarkers that will help better stratify pharmaceutical clinical trial populations or assist physicians to select better, more personalized, efficacious and safer therapies for their patients

Damming the genomic data flood using a comprehensive analysis and storage data structure

Data generation, driven by rapid advances in genomic technologies, is fast outpacing our analysis capabilities. Faced with this flood of data, more hardware and software resources are added to accommodate data sets whose structure has not specifically been designed for analysis. This leads to unnecessarily lengthy processing times and excessive data handling and storage costs. Current efforts to address this have centered on developing new indexing schemas and analysis algorithms, whereas the root of the problem lies in the format of the data itself. We have developed a new data structure for storing and analyzing genotype and phenotype data. By leveraging data normalization techniques, database management system capabilities and the use of a novel multi-table, multidimensional database structure we have eliminated the following: (i) unnecessarily large data set size due to high levels of redundancy, (ii) sequential access to these data sets and (iii) common bottlenecks in analysis times. The resulting novel data structure horizontally divides the data to circumvent traditional problems associated with the use of databases for very large genomic data sets. The resulting data set required 86% less disk space and performed analytical calculations 6248 times faster compared to a standard approach without any loss of information

Epidemiology, practice of ventilation and outcome for patients at increased risk of postoperative pulmonary complications

BACKGROUND Limited information exists about the epidemiology and outcome of surgical patients at increased risk of postoperative pulmonary complications (PPCs), and how intraoperative ventilation was managed in these patients. OBJECTIVES To determine the incidence of surgical patients at increased risk of PPCs, and to compare the intraoperative ventilation management and postoperative outcomes with patients at low risk of PPCs. DESIGN This was a prospective international 1-week observational study using the ‘Assess Respiratory Risk in Surgical Patients in Catalonia risk score’ (ARISCAT score) for PPC for risk stratification. PATIENTS AND SETTING Adult patients requiring intraoperative ventilation during general anaesthesia for surgery in 146 hospitals across 29 countries. MAIN OUTCOME MEASURES The primary outcome was the incidence of patients at increased risk of PPCs based on the ARISCAT score. Secondary outcomes included intraoperative ventilatory management and clinical outcomes. RESULTS A total of 9864 patients fulfilled the inclusion criteria. The incidence of patients at increased risk was 28.4%. The most frequently chosen tidal volume (VT) size was 500 ml, or 7 to 9 ml kg1 predicted body weight, slightly lower in patients at increased risk of PPCs. Levels of positive end-expiratory pressure (PEEP) were slightly higher in patients at increased risk of PPCs, with 14.3% receiving more than 5 cmH2O PEEP compared with 7.6% in patients at low risk of PPCs (P < 0.001). Patients with a predicted preoperative increased risk of PPCs developed PPCs more frequently: 19 versus 7%, relative risk (RR) 3.16 (95% confidence interval 2.76 to 3.61), P < 0.001) and had longer hospital stays. The only ventilatory factor associated with the occurrence of PPCs was the peak pressure. CONCLUSION The incidence of patients with a predicted increased risk of PPCs is high. A large proportion of patients receive high VT and low PEEP levels. PPCs occur frequently in patients at increased risk, with worse clinical outcome

Epidemiology, practice of ventilation and outcome for patients at increased risk of postoperative pulmonary complications: LAS VEGAS - An observational study in 29 countries

BACKGROUND Limited information exists about the epidemiology and outcome of surgical patients at increased risk of postoperative pulmonary complications (PPCs), and how intraoperative ventilation was managed in these patients. OBJECTIVES To determine the incidence of surgical patients at increased risk of PPCs, and to compare the intraoperative ventilation management and postoperative outcomes with patients at low risk of PPCs. DESIGN This was a prospective international 1-week observational study using the ‘Assess Respiratory Risk in Surgical Patients in Catalonia risk score’ (ARISCAT score) for PPC for risk stratification. PATIENTS AND SETTING Adult patients requiring intraoperative ventilation during general anaesthesia for surgery in 146 hospitals across 29 countries. MAIN OUTCOME MEASURES The primary outcome was the incidence of patients at increased risk of PPCs based on the ARISCAT score. Secondary outcomes included intraoperative ventilatory management and clinical outcomes. RESULTS A total of 9864 patients fulfilled the inclusion criteria. The incidence of patients at increased risk was 28.4%. The most frequently chosen tidal volume (V T) size was 500 ml, or 7 to 9 ml kg−1 predicted body weight, slightly lower in patients at increased risk of PPCs. Levels of positive end-expiratory pressure (PEEP) were slightly higher in patients at increased risk of PPCs, with 14.3% receiving more than 5 cmH2O PEEP compared with 7.6% in patients at low risk of PPCs (P ˂ 0.001). Patients with a predicted preoperative increased risk of PPCs developed PPCs more frequently: 19 versus 7%, relative risk (RR) 3.16 (95% confidence interval 2.76 to 3.61), P ˂ 0.001) and had longer hospital stays. The only ventilatory factor associated with the occurrence of PPCs was the peak pressure. CONCLUSION The incidence of patients with a predicted increased risk of PPCs is high. A large proportion of patients receive high V T and low PEEP levels. PPCs occur frequently in patients at increased risk, with worse clinical outcome.</p

Velocity-space sensitivity of the time-of-flight neutron spectrometer at JET

The velocity-space sensitivities of fast-ion diagnostics are often described by so-called weight functions. Recently, we formulated weight functions showing the velocity-space sensitivity of the often dominant beam-target part of neutron energy spectra. These weight functions for neutron emission spectrometry (NES) are independent of the particular NES diagnostic. Here we apply these NES weight functions to the time-of-flight spectrometer TOFOR at JET. By taking the instrumental response function of TOFOR into account, we calculate time-of-flight NES weight functions that enable us to directly determine the velocity-space sensitivity of a given part of a measured time-of-flight spectrum from TOFOR

Relationship of edge localized mode burst times with divertor flux loop signal phase in JET

A phase relationship is identified between sequential edge localized modes (ELMs) occurrence times in a set of H-mode tokamak plasmas to the voltage measured in full flux azimuthal loops in the divertor region. We focus on plasmas in the Joint European Torus where a steady H-mode is sustained over several seconds, during which ELMs are observed in the Be II emission at the divertor. The ELMs analysed arise from intrinsic ELMing, in that there is no deliberate intent to control the ELMing process by external means. We use ELM timings derived from the Be II signal to perform direct time domain analysis of the full flux loop VLD2 and VLD3 signals, which provide a high cadence global measurement proportional to the voltage induced by changes in poloidal magnetic flux. Specifically, we examine how the time interval between pairs of successive ELMs is linked to the time-evolving phase of the full flux loop signals. Each ELM produces a clear early pulse in the full flux loop signals, whose peak time is used to condition our analysis. The arrival time of the following ELM, relative to this pulse, is found to fall into one of two categories: (i) prompt ELMs, which are directly paced by the initial response seen in the flux loop signals; and (ii) all other ELMs, which occur after the initial response of the full flux loop signals has decayed in amplitude. The times at which ELMs in category (ii) occur, relative to the first ELM of the pair, are clustered at times when the instantaneous phase of the full flux loop signal is close to its value at the time of the first ELM

Mutations in ZMYND10, a Gene Essential for Proper Axonemal Assembly of Inner and Outer Dynein Arms in Humans and Flies, Cause Primary Ciliary Dyskinesia

Primary ciliary dyskinesia (PCD) is a ciliopathy characterized by airway disease, infertility, and laterality defects, often caused by dual loss of the inner dynein arms (IDAs) and outer dynein arms (ODAs), which power cilia and flagella beating. Using whole-exome and candidate-gene Sanger resequencing in PCD-affected families afflicted with combined IDA and ODA defects, we found that 6/38 (16%) carried biallelic mutations in the conserved zinc-finger gene BLU (ZMYND10). ZMYND10 mutations conferred dynein-arm loss seen at the ultrastructural and immunofluorescence level and complete cilia immotility, except in hypomorphic p.Val16Gly (c.47T&gt;G) homozygote individuals, whose cilia retained a stiff and slowed beat. In mice, Zmynd10 mRNA is restricted to regions containing motile cilia. In a Drosophila model of PCD, Zmynd10 is exclusively expressed in cells with motile cilia: chordotonal sensory neurons and sperm. In these cells, P-element-mediated gene silencing caused IDA and ODA defects, proprioception deficits, and sterility due to immotile sperm. Drosophila Zmynd10 with an equivalent c.47T&gt;G (p.Val16Gly) missense change rescued mutant male sterility less than the wild-type did. Tagged Drosophila ZMYND10 is localized primarily to the cytoplasm, and human ZMYND10 interacts with LRRC6, another cytoplasmically localized protein altered in PCD. Using a fly model of PCD, we conclude that ZMYND10 is a cytoplasmic protein required for IDA and ODA assembly and that its variants cause ciliary dysmotility and PCD with laterality defects

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Use of sequenom sample ID plus® SNP genotyping in identification of FFPE tumor samples

Short tandem repeat (STR) analysis, such as the AmpFlSTR® Identifiler® Plus kit, is a standard, PCR-based human genotyping method used in the field of forensics. Misidentification of cell line and tissue DNA can be costly if not detected early; therefore it is necessary to have quality control measures such as STR profiling in place. A major issue in large-scale research studies involving archival formalin-fixed paraffin embedded (FFPE) tissues is that varying levels of DNA degradation can result in failure to correctly identify samples using STR genotyping. PCR amplification of STRs of several hundred base pairs is not always possible when DNA is degraded. The Sample ID Plus® panel from Sequenom allows for human DNA identification and authentication using SNP genotyping. In comparison to lengthy STR amplicons, this multiplexing PCR assay requires amplification of only 76-139 base pairs, and utilizes 47 SNPs to discriminate between individual samples. In this study, we evaluated both STR and SNP genotyping methods of sample identification, with a focus on paired FFPE tumor/normal DNA samples intended for next-generation sequencing (NGS). The ability to successfully validate the identity of FFPE samples can enable cost savings by reducing rework