CIAO1 and MMS19 deficiency: A lethal neurodegenerative phenotype caused by cytosolic Fe-S cluster protein assembly disorders.

PURPOSE: The functionality of many cellular proteins depends on cofactors; yet, they have only been implicated in a minority of Mendelian diseases. Here, we describe the first 2 inherited disorders of the cytosolic iron-sulfur protein assembly system. METHODS: Genetic testing via genome sequencing was applied to identify the underlying disease cause in 3 patients with microcephaly, congenital brain malformations, progressive developmental and neurologic impairments, recurrent infections, and a fatal outcome. Studies in patient-derived skin fibroblasts and zebrafish models were performed to investigate the biochemical and cellular consequences. RESULTS: Metabolic analysis showed elevated uracil and thymine levels in body fluids but no pathogenic variants in DPYD, encoding dihydropyrimidine dehydrogenase. Genome sequencing identified compound heterozygosity in 2 patients for missense variants in CIAO1, encoding cytosolic iron-sulfur assembly component 1, and homozygosity for an in-frame 3-nucleotide deletion in MMS19, encoding the MMS19 homolog, cytosolic iron-sulfur assembly component, in the third patient. Profound alterations in the proteome, metabolome, and lipidome were observed in patient-derived fibroblasts. We confirmed the detrimental effect of deficiencies in CIAO1 and MMS19 in zebrafish models. CONCLUSION: A general failure of cytosolic and nuclear iron-sulfur protein maturation caused pleiotropic effects. The critical function of the cytosolic iron-sulfur protein assembly machinery for antiviral host defense may well explain the recurrent severe infections occurring in our patients.

Transcriptome-wide association analyses identify an association between ARL14EP and polycystic ovary syndrome.

Polycystic ovary syndrome (PCOS) is a common endocrine disorder, which is accompanied by a variety of comorbidities including metabolic, reproductive, and psychiatric disorders. Genome-wide association studies have identified several genetic variants that are associated with PCOS. However, these variants often occur outside of coding regions and require further investigation to understand their contribution to PCOS. A transcriptome-wide association study (TWAS) was performed to uncover heritable gene expression profiles that are associated with PCOS in two independent cohorts. Causal gene prioritization was subsequently performed and expression of genes prioritized through these analyses was examined in 49 PCOS patients and 30 controls. TWAS analyses revealed that increased expression of ARL14EP was significantly associated with PCOS risk in the discovery (P = 1.6 × 10-6) and replication cohorts (P = 2.0 × 10-13). Gene prioritization pipelines provided further evidence that ARL14EP is the most likely causal gene at this locus. ARL14EP gene expression was shown to be significantly different between PCOS cases and controls, after adjusting for body mass index, age and testosterone levels (P = 1.2 × 10-13). This study has provided evidence for the role of ARL14EP in PCOS. Given that ARL14EP has been reported to play an important role in chromatin remodeling, variants affecting the expression of ARL14EP may also affect the expression of other genes that contribute to PCOS pathogenesis.

Length of Uninterrupted CAG, Independent of Polyglutamine Size, Results in Increased Somatic Instability, Hastening Onset of Huntington Disease.

Huntington disease (HD) is caused by a CAG repeat expansion in the huntingtin (HTT) gene. Although the length of this repeat is inversely correlated with age of onset (AOO), it does not fully explain the variability in AOO. We assessed the sequence downstream of the CAG repeat in HTT [reference: (CAG)n-CAA-CAG], since variants within this region have been previously described, but no study of AOO has been performed. These analyses identified a variant that results in complete loss of interrupting (LOI) adenine nucleotides in this region [(CAG)n-CAG-CAG]. Analysis of multiple HD pedigrees showed that this LOI variant is associated with dramatically earlier AOO (average of 25 years) despite the same polyglutamine length as in individuals with the interrupting penultimate CAA codon. This LOI allele is particularly frequent in persons with reduced penetrance alleles who manifest with HD and increases the likelihood of presenting clinically with HD with a CAG of 36-39 repeats. Further, we show that the LOI variant is associated with increased somatic repeat instability, highlighting this as a significant driver of this effect. These findings indicate that the number of uninterrupted CAG repeats, which is lengthened by the LOI, is the most significant contributor to AOO of HD and is more significant than polyglutamine length, which is not altered in these individuals. In addition, we identified another variant in this region, where the CAA-CAG sequence is duplicated, which was associated with later AOO. Identification of these cis-acting modifiers have potentially important implications for genetic counselling in HD-affected families.

Bi-allelic GOT2 Mutations Cause a Treatable Malate-Aspartate Shuttle-Related Encephalopathy.

Early-infantile encephalopathies with epilepsy are devastating conditions mandating an accurate diagnosis to guide proper management. Whole-exome sequencing was used to investigate the disease etiology in four children from independent families with intellectual disability and epilepsy, revealing bi-allelic GOT2 mutations. In-depth metabolic studies in individual 1 showed low plasma serine, hypercitrullinemia, hyperlactatemia, and hyperammonemia. The epilepsy was serine and pyridoxine responsive. Functional consequences of observed mutations were tested by measuring enzyme activity and by cell and animal models. Zebrafish and mouse models were used to validate brain developmental and functional defects and to test therapeutic strategies. GOT2 encodes the mitochondrial glutamate oxaloacetate transaminase. GOT2 enzyme activity was deficient in fibroblasts with bi-allelic mutations. GOT2, a member of the malate-aspartate shuttle, plays an essential role in the intracellular NAD(H) redox balance. De novo serine biosynthesis was impaired in fibroblasts with GOT2 mutations and GOT2-knockout HEK293 cells. Correcting the highly oxidized cytosolic NAD-redox state by pyruvate supplementation restored serine biosynthesis in GOT2-deficient cells. Knockdown of got2a in zebrafish resulted in a brain developmental defect associated with seizure-like electroencephalography spikes, which could be rescued by supplying pyridoxine in embryo water. Both pyridoxine and serine synergistically rescued embryonic developmental defects in zebrafish got2a morphants. The two treated individuals reacted favorably to their treatment. Our data provide a mechanistic basis for the biochemical abnormalities in GOT2 deficiency that may also hold for other MAS defects.

Glutaminase Deficiency Caused by Short Tandem Repeat Expansion in GLS.

We report an inborn error of metabolism caused by an expansion of a GCA-repeat tract in the 5' untranslated region of the gene encoding glutaminase (GLS) that was identified through detailed clinical and biochemical phenotyping, combined with whole-genome sequencing. The expansion was observed in three unrelated patients who presented with an early-onset delay in overall development, progressive ataxia, and elevated levels of glutamine. In addition to ataxia, one patient also showed cerebellar atrophy. The expansion was associated with a relative deficiency of GLS messenger RNA transcribed from the expanded allele, which probably resulted from repeat-mediated chromatin changes upstream of the GLS repeat. Our discovery underscores the importance of careful examination of regions of the genome that are typically excluded from or poorly captured by exome sequencing.

Patient-specific genetic factors predict treatment failure in sofosbuvir-treated patients with chronic hepatitis C.

BACKGROUND & AIMS: According to pivotal clinical trials, cure rates for sofosbuvir-based antiviral therapy exceed 96%. Treatment failure is usually assumed to be because of virological resistance-associated substitutions or clinical risk factors, yet the role of patient-specific genetic factors has not been well explored. We determined if patient-specific genetic factors help predict patients likely to fail sofosbuvir treatment in real-world treatment situations. METHODS: We recruited sofosbuvir-treated patients with chronic hepatitis C from five Canadian treatment sites, and performed a case-control pharmacogenomics study assessing both previously published and novel genetic polymorphisms. Specifically studied were variants predicted to impair CES1-dependent production of sofosbuvir's active metabolite, interferon-λ signalling variants expected to impact a patient's immune response to the virus and an HLA variant associated with increased spontaneous and treatment-induced viral clearance. RESULTS: Three hundred and fifty-nine sofosbuvir-treated patients were available for analyses after exclusions, with 34 (9.5%) failing treatment. We identified CES1 variants as novel predictors for treatment failure in European patients (rs115629050 or rs4513095; odds ratio (OR): 5.43; 95% confidence interval (CI): 1.64-18.01; P = .0057), replicated associations with IFNL4 variants predicted to increase interferon-λ signalling (eg rs12979860; OR: 2.25; 95% CI: 1.25-4.06; P = .0071) and discovered a novel association with a coding variant predicted to enhance the activity of IFNL4's receptor (rs2834167 in IL10RB; OR: 1.81; 95% CI: 1.01-3.24; P = .047). CONCLUSIONS: Ultimately, this work demonstrates that patient-specific genetic factors could be used as a tool to identify patients at higher risk of treatment failure and allow for these patients to receive effective therapy sooner.

Exome Sequencing and the Management of Neurometabolic Disorders.

BACKGROUND: Whole-exome sequencing has transformed gene discovery and diagnosis in rare diseases. Translation into disease-modifying treatments is challenging, particularly for intellectual developmental disorder. However, the exception is inborn errors of metabolism, since many of these disorders are responsive to therapy that targets pathophysiological features at the molecular or cellular level. METHODS: To uncover the genetic basis of potentially treatable inborn errors of metabolism, we combined deep clinical phenotyping (the comprehensive characterization of the discrete components of a patient's clinical and biochemical phenotype) with whole-exome sequencing analysis through a semiautomated bioinformatics pipeline in consecutively enrolled patients with intellectual developmental disorder and unexplained metabolic phenotypes. RESULTS: We performed whole-exome sequencing on samples obtained from 47 probands. Of these patients, 6 were excluded, including 1 who withdrew from the study. The remaining 41 probands had been born to predominantly nonconsanguineous parents of European descent. In 37 probands, we identified variants in 2 genes newly implicated in disease, 9 candidate genes, 22 known genes with newly identified phenotypes, and 9 genes with expected phenotypes; in most of the genes, the variants were classified as either pathogenic or probably pathogenic. Complex phenotypes of patients in five families were explained by coexisting monogenic conditions. We obtained a diagnosis in 28 of 41 probands (68%) who were evaluated. A test of a targeted intervention was performed in 18 patients (44%). CONCLUSIONS: Deep phenotyping and whole-exome sequencing in 41 probands with intellectual developmental disorder and unexplained metabolic abnormalities led to a diagnosis in 68%, the identification of 11 candidate genes newly implicated in neurometabolic disease, and a change in treatment beyond genetic counseling in 44%. (Funded by BC Children's Hospital Foundation and others.).

CYP2D6 as a treatment decision aid for ER-positive non-metastatic breast cancer patients: a systematic review with accompanying clinical practice guidelines.

PURPOSE: Tamoxifen is one of the principal treatments for estrogen receptor (ER)-positive breast cancer. Unfortunately, between 30 and 50% of patients receiving this hormonal therapy relapse. Since CYP2D6 genetic variants have been reported to play an important role in survival outcomes after treatment with tamoxifen, this study sought to summarize and critically appraise the available scientific evidence on this topic. METHODS: A systematic literature review was conducted to identify studies investigating associations between CYP2D6 genetic variation and survival outcomes after tamoxifen treatment. Critical appraisal of the retrieved scientific evidence was performed, and recommendations were developed for CYP2D6 genetic testing in the context of tamoxifen therapy. RESULTS: Although conflicting literature exists, the majority of the current evidence points toward CYP2D6 genetic variation affecting survival outcomes after tamoxifen treatment. Of note, review of the CYP2D6 genotyping assays used in each of the studies revealed the importance of comprehensive genotyping strategies to accurately predict CYP2D6 metabolizer phenotypes. CONCLUSIONS AND RECOMMENDATIONS: Critical appraisal of the literature provided evidence for the value of comprehensive CYP2D6 genotyping panels in guiding treatment decisions for non-metastatic ER-positive breast cancer patients. Based on this information, it is recommended that alternatives to standard tamoxifen treatments may be considered in CYP2D6 poor or intermediate metabolizers.

The identification of novel genetic variants associated with antipsychotic treatment response outcomes in first-episode schizophrenia patients.

BACKGROUND: Although antipsychotics are integral to the treatment of schizophrenia, drug efficacy varies between patients. Although it has been shown that antipsychotic treatment response outcomes are heritable, our understanding of the genetic factors that are involved remains incomplete. Therefore, this study aims to use an unbiased scan of the genome to identify the genetic variants contributing toward antipsychotic treatment response outcomes. MATERIALS AND METHODS: This study utilized whole-exome sequencing of patients on extreme ends of the treatment response spectrum (n=11) in combination with results from previous antipsychotic studies to design a panel of variants that were genotyped in two well-characterized first-episode schizophrenia cohorts (n=103 and 87). Association analyses were carried out to determine whether these variants were significantly associated with antipsychotic treatment response outcomes. RESULTS: Association analyses in the discovery cohort identified two nonsynonymous variants that were significantly associated with antipsychotic treatment response outcomes (P<2.7 × 10(-5)), which were also significantly associated with the corresponding treatment response outcome in an independent replication cohort. Computational approaches showed that both of these nonsynonymous variants--rs13025959 in MYO7B (E1647D) and rs10380 in MTRR (H622Y)--were predicted to impair the functioning of their corresponding protein products. CONCLUSION: The use of whole-exome sequencing in a subset of patients from a well-characterized cohort of first-episode schizophrenia patients, for whom longitudinal depot treatment response data were available, allowed for (i) the removal of confounding factors related to treatment progression and compliance and (ii) the identification of two genetic variants that have not been associated previously with antipsychotic treatment response outcomes and whose results were applicable across different classes of antipsychotics. Although the genes that are affected by these variants are involved in pathways that have been related previously to antipsychotic treatment outcomes, the identification of these novel genes will play an important role in improving our understanding of the specific variants involved in antipsychotic treatment response outcomes.

Characterization of CYP2B6 and CYP2A6 Pharmacogenetic Variation in Sub-Saharan African Populations.

Genetic variation in CYP2B6 and CYP2A6 is known to impact interindividual response to antiretrovirals, nicotine, and bupropion, among other drugs. However, the full catalogue of clinically relevant pharmacogenetic variants in these genes is yet to be established, especially across African populations. This study therefore aimed to characterize the star allele (haplotype) distribution in CYP2B6 and CYP2A6 across diverse and understudied sub-Saharan African (SSA) populations. We called star alleles from 961 high-depth full genomes using StellarPGx, Aldy, and PyPGx. In addition, we performed CYP2B6 and CYP2A6 star allele frequency comparisons between SSA and other global biogeographical groups represented in the new 1000 Genomes Project high-coverage dataset (n = 2,000). This study presents frequency information for star alleles in CYP2B6 (e.g., *6 and *18; frequency of 21-47% and 2-19%, respectively) and CYP2A6 (e.g., *4, *9, and *17; frequency of 0-6%, 3-10%, and 6-20%, respectively), and predicted phenotypes (for CYP2B6), across various African populations. In addition, 50 potentially novel African-ancestry star alleles were computationally predicted by StellarPGx in CYP2B6 and CYP2A6 combined. For each of these genes, over 4% of the study participants had predicted novel star alleles. Three novel star alleles in CYP2A6 (*54, *55, and *56) and CYP2B6 apiece, and several suballeles were further validated via targeted Single-Molecule Real-Time resequencing. Our findings are important for informing the design of comprehensive pharmacogenetic testing platforms, and are highly relevant for personalized medicine strategies, especially relating to antiretroviral medication and smoking cessation treatment in Africa and the African diaspora. More broadly, this study highlights the importance of sampling diverse African ethnolinguistic groups for accurate characterization of the pharmacogene variation landscape across the continent.

Next-generation sequencing of pharmacogenes: a critical analysis focusing on schizophrenia treatment.

INTRODUCTION: Because of the unmet needs of current pharmacotherapy for schizophrenia, antipsychotic pharmacogenetic research is of utmost importance. However, to date, few clinically applicable antipsychotic pharmacogenomic alleles have been identified. Nonetheless, next-generation sequencing technologies are expected to aid in the identification of clinically significant variants for this complex phenotype. The aim of this study was therefore to critically examine the ability of next-generation sequencing technologies to reliably detect variation present in pharmacogenes. MATERIALS AND METHODS: Candidate antipsychotic pharmacogenes and very important pharmacogenes were identified from the literature and the Pharmacogenomics Knowledgebase. Thereafter, the percentage sequence similarity observed between these genes and their corresponding pseudogenes and paralogues, as well as the percentage low-complexity sequence and GC content of each gene, was calculated. These sequence attributes were subsequently compared with the 'inaccessible' regions of these genes as described by the 1000 Genomes Project. RESULTS: It was found that the percentage 'inaccessible genome' correlated well with GC content (P=9.96×10), low-complexity sequence (P=0.0002) and the presence of pseudogenes/paralogues (P=8.02×10). In addition, it was found that many of the pharmacogenes were not ideally suited to next-generation sequencing because of these genomic complexities. These included the CYP and HLA genes, both of which are of importance to many fields of pharmacogenetics. CONCLUSION: Current short read sequencing technologies are unable to comprehensively capture the variation in all pharmacogenes. Therefore, until high-throughput sequencing technologies advance further, it may be necessary to combine next-generation sequencing with other genotyping strategies.

Introduction of the AmpliChip CYP450 Test to a South African cohort: a platform comparative prospective cohort study.

BACKGROUND: Adverse drug reactions and lack of therapeutic efficacy associated with currently prescribed pharmacotherapeutics may be attributed, in part, to inter-individual variability in drug metabolism. Studies on the pharmacogenetics of Cytochrome P450 (CYP) enzymes offer insight into this variability. The objective of this study was to compare the AmpliChip CYP450 Test® (AmpliChip) to alternative genotyping platforms for phenotype prediction of CYP2C19 and CYP2D6 in a representative cohort of the South African population. METHODS: AmpliChip was used to screen for thirty-three CYP2D6 and three CYP2C19 alleles in two different cohorts. As a comparison cohort 2 was then genotyped using a CYP2D6 specific long range PCR with sequencing (CYP2D6 XL-PCR + Sequencing) platform and a PCR-RFLP platform for seven CYP2C19 alleles. RESULTS: Even though there was a low success rate for the AmpliChip, allele frequencies for both CYP2D6 and CYP2C19 were very similar between the two different cohorts. The CYP2D6 XL-PCR + Sequencing platform detected CYP2D6*5 more reliably and could correctly distinguish between CYP2D6*2 and *41 in the Black African individuals. Alleles not covered by the AmpliChip were identified and four novel CYP2D6 alleles were also detected. CYP2C19 PCR-RFLP identified CYP2C19*9,*15, *17 and *27 in the Black African individuals, with *2, *17 and *27 being relatively frequent in the cohort. Eliminating mismatches and identifying additional alleles will contribute to improving phenotype prediction for both enzymes. Phenotype prediction differed between platforms for both genes. CONCLUSION: Comprehensive genotyping of CYP2D6 and CYP2C19 with the platforms used in this study, would be more appropriate than AmpliChip for phenotypic prediction in the South African population. Pharmacogenetically important novel alleles may remain undiscovered when using assays that are designed according to Caucasian specific variation, unless alternate strategies are utilised.

Association Between HLA-DPB1 and Antineutrophil Cytoplasmic Antibody-Associated Vasculitis in Children.

OBJECTIVE: Antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) is a rare, life-threatening inflammation of blood vessels that can affect both adults and children. Compared to adult-onset disease, AAV is especially rare in children, with an annual prevalence of 0.5-6.4 cases per million children. The etiology of AAV remains largely unknown, and both environmental and genetic factors are likely involved. The present study was undertaken to explore the genetic susceptibility factors recently identified in adult patients, including HLA-DP and HLA-DQ, in pediatric patients. METHODS: We performed a genome-wide association study of pediatric AAV in patients of European ancestry (n = 63 AAV cases, n = 315 population-matched controls). RESULTS: We identified a significant genetic association between pediatric AAV and the HLA-DPB1*04:01 allele (P = 1.5 × 10-8 , odds ratio [OR] 3.5), with a stronger association observed in children with proteinase 3-ANCA positivity than in children with myeloperoxidase-ANCA positivity. Among the HLA alleles, the HLA-DPB1*04:01 allele was the most highly associated with AAV, although not significantly, in a follow-up adult AAV cohort (P = 2.6 × 10-4 , OR 0.4). T cell receptor and interferon signaling pathways were also shown to be enriched in the pediatric AAV cohort. CONCLUSION: The HLA-DPB1 locus showed an association with pediatric AAV, as similarly shown previously in adult AAV. Despite the difference in the age of onset, these findings suggest that childhood- and adult-onset vasculitis share a common genetic predisposition. The identification of genetic variants contributing to AAV is an important step to improved classification tools and treatment strategies.

Characterization of CYP2D6 Pharmacogenetic Variation in Sub-Saharan African Populations.

Cytochrome P450 2D6 (CYP2D6) is a key enzyme in drug response owing to its involvement in the metabolism of ~ 25% of clinically prescribed medications. The encoding CYP2D6 gene is highly polymorphic, and many pharmacogenetics studies have been performed worldwide to investigate the distribution of CYP2D6 star alleles (haplotypes); however, African populations have been relatively understudied to date. In this study, the distributions of CYP2D6 star alleles and predicted drug metabolizer phenotypes-derived from activity scores-were examined across multiple sub-Saharan African populations based on bioinformatics analysis of 961 high-depth whole genome sequences. This was followed by characterization of novel star alleles and suballeles in a subset of the participants via targeted high-fidelity Single-Molecule Real-Time resequencing (Pacific Biosciences). This study revealed varying frequencies of known CYP2D6 alleles and predicted phenotypes across different African ethnolinguistic groups. Twenty-seven novel CYP2D6 star alleles were predicted computationally and two of them were further validated. This study highlights the importance of studying variation in key pharmacogenes such as CYP2D6 in the African context to better understand population-specific allele frequencies. This will aid in the development of better genotyping panels and star allele detection approaches with a view toward supporting effective implementation of precision medicine strategies in Africa and across the African diaspora.

A Systematic Review and Analysis of the Use of Polygenic Scores in Pharmacogenomics.

Polygenic scores (PGSs) have emerged as promising tools for complex trait risk prediction. The application of these scores to pharmacogenomics provides new opportunities to improve the prediction of treatment outcomes. To gain insight into this area of research, we conducted a systematic review and accompanying analysis. This review uncovered 51 papers examining the use of PGSs for drug-related outcomes, with the majority of these papers focusing on the treatment of psychiatric disorders (n = 30). Due to difficulties in collecting large cohorts of uniformly treated patients, the majority of pharmacogenomic PGSs were derived from large-scale genome-wide association studies of disease phenotypes that were related to the pharmacogenomic phenotypes under investigation (e.g., schizophrenia-derived PGSs for antipsychotic response prediction). Examination of the research participants included in these studies revealed that the majority of cohort participants were of European descent (78.4%). These biases were also reflected in research affiliations, which were heavily weighted towards institutions located in Europe and North America, with no first or last authors originating from institutions in Africa or South Asia. There was also substantial variability in the methods used to develop PGSs, with between 3 and 6.6 million variants included in the PGSs. Finally, we observed significant inconsistencies in the reporting of PGS analyses and results, particularly in terms of risk model development and application, coupled with a lack of data transparency and availability, with only three pharmacogenomics PGSs deposited on the Polygenic Score Catalog. These findings highlight current gaps and key areas for future pharmacogenomic PGS research.

PharmVar GeneFocus: CYP3A5.

The Pharmacogene Variation Consortium (PharmVar) catalogs star (*) allele nomenclature for the polymorphic human CYP3A5 gene. Genetic variation within the CYP3A5 gene locus impacts the metabolism of several clinically important drugs, including the immunosuppressants tacrolimus, sirolimus, cyclosporine, and the benzodiazepine midazolam. Variable CYP3A5 activity is of clinical importance regarding tacrolimus metabolism. This GeneFocus provides a CYP3A5 gene summary with a focus on aspects regarding standardized nomenclature. In addition, this review also summarizes recent changes and updates, including the retirement of several allelic variants and provides an overview of how PharmVar CYP3A5 star allele nomenclature is utilized by the Pharmacogenomics Knowledgebase (PharmGKB) and the Clinical Pharmacogenetics Implementation Consortium (CPIC).

A pharmacogenomic investigation of the cardiac safety profile of ondansetron in children and pregnant women.

BACKGROUND: Ondansetron is a highly effective antiemetic for the treatment of nausea and vomiting. However, this medication has also been associated with QT prolongation. Pharmacogenomic information on therapeutic response to ondansetron exists, but no investigation has been performed on genetic factors that influence the cardiac safety of this medication. METHODS: Three patient groups receiving ondansetron were recruited and followed prospectively (pediatric post-surgical patients n = 101; pediatric oncology patients n = 98; pregnant women n = 62). Electrocardiograms were conducted at baseline, and 5- and 30-min post-ondansetron administration, to determine the effect of ondansetron treatment on QT interval. Pharmacogenomic associations were assessed via analyses of comprehensive CYP2D6 genotyping and genome-wide association study data. RESULTS: In the entire cohort, 62 patients (24.1%) met the criteria for prolonged QT, with 1.2% of the cohort exhibiting unsafe QT prolongation. The most significant shift from baseline occurred at five minutes post-ondansetron administration (P = 9.8 × 10-4). CYP2D6 activity score was not associated with prolonged QT. Genome-wide analyses identified novel associations with a missense variant in TLR3 (rs3775291; P = 2.00 × 10-7) and a variant linked to the expression of SLC36A1 (rs34124313; P = 1.97 × 10-7). CONCLUSIONS: This study has provided insight into the genomic basis of ondansetron-induced cardiac changes and has emphasized the importance of genes that have been implicated in serotonin-related traits. These biologically-relevant findings represent the first step towards understanding this adverse event with the overall goal to improve the safety of this commonly used antiemetic medication.

Integrating disease and drug-related phenotypes for improved identification of pharmacogenomic variants.

Aim: To improve the identification and interpretation of pharmacogenetic variants through the integration of disease and drug-related traits. Materials & methods: We hypothesized that integrating genome-wide disease and pharmacogenomic data may drive new insights into drug toxicity and response by identifying shared genetic architecture. Pleiotropic variants were identified using a methodological framework incorporating colocalization analysis. Results: Using genome-wide association studies summary statistics from the UK Biobank, European Bioinformatics Institute genome-wide association studies catalog and the Pharmacogenomics Research Network, we validated pleiotropy at the ABCG2 locus between allopurinol response and gout and identified novel pleiotropy between antihypertensive-induced new-onset diabetes, Crohn's disease and inflammatory bowel disease at the IL18RAP/SLC9A4 locus. Conclusion: New mechanistic insights and genetic loci can be uncovered by identifying pleiotropy between disease and drug-related traits.

Lay abstract Disease-focused genome-wide association studies (GWAS) have identified a plethora of actionable genetic variants over the last 20 years. International collaboration and technological breakthroughs have enabled rapid genotyping and data collection, which has correspondingly increased sample size and power. Contrastingly, recruitment of well-characterized cohorts of patients for pharmacogenomics research has proven challenging. Given the greater number of associated genetic variants and larger cohort sizes in common disease GWAS, we hypothesized that integrating genome-wide disease and pharmacogenomic data may drive new insights into drug toxicity and drug efficacy phenotypes, beyond the standard scope of current pharmacogenetic analyses. Using GWAS summary statistics from the UK Biobank, European Bioinformatics Institute GWAS catalog, and the Pharmacogenomics Research Network, and a methodological framework incorporating colocalization analysis, we validated pleiotropy at the ABCG2 locus between allopurinol response, gout, and serum urate and identified novel pleiotropy between antihypertensive-induced new-onset diabetes, Crohn's disease and inflammatory bowel disease at the IL18RAP/SLC9A4 locus.

StellarPGx: A Nextflow Pipeline for Calling Star Alleles in Cytochrome P450 Genes.

Bioinformatics pipelines for calling star alleles (haplotypes) in cytochrome P450 (CYP) genes are important for the implementation of precision medicine. Genotyping CYP genes using high throughput sequencing data is complicated, e.g., by being highly polymorphic, not to mention the structural variations especially in CYP2D6, CYP2A6, and CYP2B6. Genome graph-based variant detection approaches have been shown to be reliable for genotyping HLA alleles. However, their application to enhancing star allele calling in CYP genes has not been extensively explored. We present StellarPGx, a Nextflow pipeline for accurately genotyping CYP genes by combining genome graph-based variant detection, read coverage information from the original reference-based alignments, and combinatorial diplotype assignments. The implementation of StellarPGx using Nextflow facilitates its portability, reproducibility, and scalability on various user platforms. StellarPGx is currently able to genotype 12 important pharmacogenes belonging to the CYP1, 2, and 3 families. For purposes of validation, we use CYP2D6 as a model gene owing to its high degree of polymorphisms (over 130 star alleles defined to date, including complex structural variants) and clinical importance. We applied StellarPGx and three existing callers to 109 whole genome sequenced samples for which the Genetic Testing Reference Material Coordination Program (GeT-RM) has recently provided consensus truth CYP2D6 diplotypes. StellarPGx had the highest CYP2D6 diplotype concordance (99%) with GeT-RM compared with Cyrius (98%), Aldy (82%), and Stargazer (84%). This exemplifies the high accuracy of StellarPGx and highlights its importance for both research and clinical pharmacogenomics applications. The StellarPGx pipeline is open-source and available from https://github.com/SBIMB/StellarPGx.