Towards more accurate pharmacogenomic variant effect predictions.

Tweetable abstract Accurate variant interpretation has become a key bottleneck for the translation of an individual's pharmacogenome into actionable recommendations. We recommend an integrated use of multiplexed assays, structure-based predictions and biobank data to develop more accurate effect predictors.

Profiling of pharmacogenomic variants in CYP2D6 and DPYD in indigenous Arab breast cancer patients.

Aim: The indigenous Arab population is underrepresented in genomic studies and the landscape of actionable pharmacogenomic variants among Arab breast cancer patients remains unclear. Materials & methods: Exome sequencing was performed on 220 unselected Arab female breast cancer patients and germline variants in CYP2D6 and DPYD were profiled using a deep learning method. Results: In total, 13 (5.9%) patients had clinically actionable results and 56 (25.5%) carried an allele in DYPD or CYP2D6 with unknown impact on drug metabolism. In addition, four unique novel missense variants were discovered, including one in CYP2D6 (p.Arg64Leu) with high predicted pathogenicity. Conclusion: A nontrivial subset of Arab breast cancer patients can potentially benefit from pretreatment molecular profiling, and further study is needed to improve characterization of the pharmacogenomic landscape.

Very important pharmacogenes polymorphism landscape and potential clinical relevance in the Chinese Mongolian.

PURPOSE: Our study genotyped pharmacogenes in 200 individuals from Inner Mongolia Autonomous Region, China. Aim to find distinct pharmacogenomic variations among the Mongolian population and to investigate the potential clinically operable gene-drug connection and genotype-phenotype correlation of differential variation in the Mongolian population. METHODS: We sampled 61 variations of 28 genes in PharmGKB and genotyped them using Agena MassARRAY Assay. We also obtained the allele frequency and genotype distribution data of 26 populations from the 1000 Genomes Project (1000G), and then conducted comparison and statistical analysis. RESULTS: After Bonferroni correction, there were significant genotype frequency distribution differences between the Mongolian and 26 populations: PTGS2 (rs20417), NAT2 (rs1801280, rs1799929, and rs1208), ALOX5(rs2115819), and CYP2D6 (rs1065852). It was also found that the KHV showed the smallest differences from the Mongolian and the GWD showed the largest differences. Furthermore, the differences in variants might be related to the risk of non-steroidal anti-inflammatory drug use, the slow acetylation phenotype, and other pharmacological effectiveness and toxicity in the Mongolian population. CONCLUSION: Our study demonstrates different pharmacogenomic variants in the Mongolian and fills the gaps in pharmacogenomic information of the Mongolian. Our analysis of VIPs variants in the Mongolian population may contribute to the development of safer treatment regimens and the use of personalized treatment approaches.

Population features of alleles and genotypes frequency distribution of polymorphic genetic markers of antipsychotic medications pharmacokinetics in the Kazakh population.

The presented article is relevant, as the main goals of schizophrenia treatment are to achieve a response to psychopharmacotherapy, reduction and stabilization of psychopathological symptoms, qualitative remission, which in general implies the creation of a stable quality of life for the patient. The purpose of the study was to evaluate the population features of the frequency distribution of alleles and genotypes of polymorphic genetic variants of according to genome-wide association studies analysis of pharmacokinetics-associated antipsychotic medications, in an ethnically homogeneous Kazakh population. The research material was deoxyribonucleic acid (DNA) isolated from the peripheral blood of 1,800 conditionally healthy persons of Kazakh nationality. DNA isolation was carried out by the magnetic polyvinyl alcohol magnetic particle separation method. The analysis of the frequency distribution of the studied genotypes in the Kazakh population showed their compliance with the Hardy-Weinberg equilibrium for all studied polymorphisms (p > .05). The obtained results showed that CYP2C19 (rs4244285, rs4986893) polymorphisms occurs in Kazakhs significantly more often than European and a number of Asian populations, which significantly affects the decrease in effectiveness and increases the risk of side complications during therapy with antipsychotic medications in the Kazakh population.

Fatigue in breast cancer patients on chemotherapy: a cross-sectional study exploring clinical, biological, and genetic factors.

BACKGROUND: Cancer-related fatigue (CRF) is one of the most common and distressing complaints reported by cancer patients during chemotherapy considerably impacting all aspects of a patient's life (physical, psychosocial, professional, and socioeconomic). The aim of this study was to assess the severity of cancer-related fatigue in a group of breast cancer patients undergoing chemotherapy and explore the association between fatigue scores and sociodemographic, clinical, biological, psychiatric, and genetic factors. METHODS: A cross-sectional pilot study carried out at the oncology outpatient unit of Hôtel-Dieu de France University Hospital recruited 67 breast cancer patients undergoing chemotherapy between November 2017 and June 2019 to evaluate fatigue using the EORTC QLQ-C30 scale (European Organization for the Research and Treatment of Cancer Quality of Life Questionnaire). Genotyping for seven gene polymorphisms (COMT, DRD2, OPRM1, CLOCK, PER2, CRY2, ABCB1) was performed using the Lightcycler® (Roche). RESULTS: The prevalence of fatigue was 46.3%. Multivariable analysis taking the fatigue score as the dependent variable showed that a higher number of cycles and a lower hemoglobin level were significantly associated with higher odds of exhibiting fatigue. Moreover, having at least one C allele for DRD2 SNP (vs. TT) was significantly associated with a 4.09 higher odds of expressing fatigue compared to TT patients. Finally, patients with at least one C allele for CLOCK SNP tended to display higher fatigue levels than TT patients. CONCLUSIONS: Our study showed that anemic breast cancer patients with a high number of chemotherapy cycles and those carrying at least one C allele for DRD2 and CLOCK SNPs are at greater risk of exhibiting fatigue. Since no previous research has reported such genetic results, future studies are necessary to confirm our findings.

Effect of XPD and TP53 Gene Polymorphisms on the Risk of Platinum-Based Chemotherapy Induced Toxicity in Bangladeshi Lung Cancer Patients.

BACKGROUND: Platinum-based drugs, including cisplatin and carboplatin, are the most active and extensively used agents for treating lung cancer. Genetic polymorphisms of DNA repair gene XPD and tumor suppressor gene TP53 are connected with alterations in enzyme activity. They may help explain interindividual differences in toxicity outcomes after platinum-based chemotherapy for lung cancer. Therefore, this study aimed to investigate XPD Lys751Gln and TP53 Arg72Pro polymorphisms on the risk of platinum-based chemotherapy-induced toxicity in lung cancer patients in the Bangladeshi population. PATIENTS AND METHODS: Study subjects comprised of 180 platinum-based chemotherapy treated histologically confirmed lung cancer patients. Genetic polymorphisms of XPD were ascertained by Polymerase Chain Reaction-based Restriction Fragment Length Polymorphism (PCR-RFLP), while TP53 genotypes were analyzed using the multiplex PCR-based method. Toxicity was assessed based on the Common Terminology Criteria for Adverse Events (CTCAE v5.0). RESULTS: From the results, there was no significant association observed between grade 1-2 or grade 3-4 platinum-based chemotherapy induced toxicities like anemia and XPD codon 751 (Lys/Gln: OR=1.40, 95% CI=0.75-2.64, p>0.05; Gln/Gln: OR=1.07, 95% CI=0.45-2.52, p>0.05 and Lys/Gln+Gln/Gln: OR=1.31, 95% CI=0.73-2.38, p>0.05) or TP53 codon 72 genetic polymorphisms (Arg/Pro: OR=0.64, 95% CI=0.34-1.17, p>0.05; Pro/Pro: OR=0.46, 95% CI=0.15-1.42, p>0.05 and Arg/Pro+Pro/Pro: OR=0.62, 95% CI=0.34-1.15, p>0.05). Similar results were found between neutropenia, leukopenia, thrombocytopenia and gastrointestinal toxicities and XPD Lys751Gln or TP53 Arg72Pro genetic polymorphisms. CONCLUSION: These findings indicated that no significant association was found between either XPD codon 751 or TP53 codon 72 genetic polymorphisms and platinum-based chemotherapy-related toxicities in Bangladeshi lung cancer patients.

The Genetic Makeup of Myeloproliferative Neoplasms: Role of Germline Variants in Defining Disease Risk, Phenotypic Diversity and Outcome.

Myeloproliferative neoplasms are hematologic malignancies typified by a substantial heritable component. Germline variants may affect the risk of developing a MPN, as documented by GWAS studies on large patient cohorts. In addition, once the MPN occurred, inherited host genetic factors can be responsible for tuning the disease phenotypic presentation, outcome, and response to therapy. This review covered the polymorphisms that have been variably associated to MPNs, discussing them in the functional perspective of the biological pathways involved. Finally, we reviewed host genetic determinants of clonal hematopoiesis, a pre-malignant state that may anticipate overt hematologic neoplasms including MPNs.

Could Cytochrome P450 2D6, 3A4 and 3A5 Polymorphisms Explain the Variability in Clinical Response to Clomiphene Citrate of Anovulatory PCOS Women?

Introduction: Cytochrome P450 2D6, 3A4 and 3A5 are involved in the metabolism of many drugs. These enzymes have a genetic polymorphism responsible for different metabolic phenotypes. They play a role in the metabolism of clomiphene citrate (CC), which is used to induce ovulation. Response to CC treatment is variable, and no predictive factors have thus far been identified. Objective: To study a possible link between the cytochrome P450 2D6, 3A4 and 3A5 polymorphisms and clinical response to CC. Study Design: Seventy-seven women with anovulatory Polycystic Ovarian Syndrome (PCOS) treated with CC were included which determined their cytochrome P450 2D6, 3A4 and 3A5 genotypes and used the results to predict ovarian response to this drug. Predicted responses based on the cytochrome genotypes were compared with the observed clinical responses using the calculation of a weighted Kappa coefficient. Main Outcome Measures: Number of dominant follicles assessed by ultrasound at the end of the follicular phase and confirmation of ovulation by blood progesterone assay in the luteal phase. Results: Concordance between the predicted and observed responses for the combination of the three cytochromes was 36.71%, with a negative Kappa coefficient (K = -0.0240), which corresponds to a major disagreement. Similarly, for predictions based on the cytochrome P450 2D6 genotype alone, only 39.24% of predictions were verified (coefficient K = -0.0609). Conclusion: The genetic polymorphism of cytochromes P450 2D6, 3A4 and 3A5 does not appear to influence clinical response to CC used to induce ovulation in anovulatory PCOS women.

Establishment of non-small-cell lung cancer risk prediction model based on prognosis-associated ADME genes.

PURPOSE: ADME genes are those involved in the absorption, distribution, metabolism, and excretion (ADME) of drugs. In the present study, a non-small-cell lung cancer (NSCLC) risk prediction model was established using prognosis-associated ADME genes, and the predictive performance of this model was evaluated and verified. In addition, multifaceted difference analysis was performed on groups with high and low risk scores. METHODS: An NSCLC sample transcriptome and clinical data were obtained from public databases. The prognosis-associated ADME genes were obtained by univariate Cox and lasso regression analyses to build a risk model. Tumor samples were divided into high-risk and low-risk score groups according to the risk score. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses of the differentially expressed genes and the differences in the immune infiltration, mutation, and medication reactions in the two groups were studied in detail. RESULTS: A risk prediction model was established with seven prognosis-associated ADME genes. Its good predictive ability was confirmed by studies of the model's effectiveness. Univariate and multivariate Cox regression analyses showed that the model's risk score was an independent prognostic factor for patients with NSCLC. The study also showed that the risk score closely correlated with immune infiltration, mutations, and medication reactions. CONCLUSION: The risk prediction model established with seven ADME genes in the present study can predict the prognosis of patients with NSCLC. In addition, significant differences in immune infiltration, mutations, and therapeutic efficacy exist between the high- and low-risk score groups.

The impact of an URAT1 polymorphism on the losartan treatment of hypertension and hyperuricemia.

BACKGROUND: This study was designed to evaluate the impact of polymorphisms in the urate transporter 1 (URAT1) gene on the uricosuric action of losartan therapy in hypertensive patients suffering from hyperuricemia. METHODS: A MassARRAY approach was used to detect single nucleotide polymorphism (SNP) loci in the URAT1 and CYP2C9 genes (16 and 2 loci, respectively) in 111 patients with hypertension and hyperuricemia taking losartan and in 121 healthy controls. In addition, we compared serum urate (SUA) levels and other key clinical biochemistry indices between these two patient groups. RESULTS: We detected significant differences between the two patient groups with respect to age, SUA, urea, creatine, triglycerides, high-density lipoprotein, low-density lipoprotein, and fasting plasma glucose (all p < 0.05). In addition, we found that hypertensive patients with hyperuricemia were more likely to exhibit the rs3825016(C/T) (36.9% vs 21.5%, p = 0.03), and we determined that a 2-week treatment course with losartan was associated with significant decreases in SUA values (p < 0.001). CONCLUSION: Our findings indicate that the URAT1 rs3825016 polymorphism may influence the uricosuric action of losartan.

A novel machine learning-based approach for the computational functional assessment of pharmacogenomic variants.

BACKGROUND: The field of pharmacogenomics focuses on the way a person's genome affects his or her response to a certain dose of a specified medication. The main aim is to utilize this information to guide and personalize the treatment in a way that maximizes the clinical benefits and minimizes the risks for the patients, thus fulfilling the promises of personalized medicine. Technological advances in genome sequencing, combined with the development of improved computational methods for the efficient analysis of the huge amount of generated data, have allowed the fast and inexpensive sequencing of a patient's genome, hence rendering its incorporation into clinical routine practice a realistic possibility. METHODS: This study exploited thoroughly characterized in functional level SNVs within genes involved in drug metabolism and transport, to train a classifier that would categorize novel variants according to their expected effect on protein functionality. This categorization is based on the available in silico prediction and/or conservation scores, which are selected with the use of recursive feature elimination process. Toward this end, information regarding 190 pharmacovariants was leveraged, alongside with 4 machine learning algorithms, namely AdaBoost, XGBoost, multinomial logistic regression, and random forest, of which the performance was assessed through 5-fold cross validation. RESULTS: All models achieved similar performance toward making informed conclusions, with RF model achieving the highest accuracy (85%, 95% CI: 0.79, 0.90), as well as improved overall performance (precision 85%, sensitivity 84%, specificity 94%) and being used for subsequent analyses. When applied on real world WGS data, the selected RF model identified 2 missense variants, expected to lead to decreased function proteins and 1 to increased. As expected, a greater number of variants were highlighted when the approach was used on NGS data derived from targeted resequencing of coding regions. Specifically, 71 variants (out of 156 with sufficient annotation information) were classified as to "Decreased function," 41 variants as "No" function proteins, and 1 variant in "Increased function." CONCLUSION: Overall, the proposed RF-based classification model holds promise to lead to an extremely useful variant prioritization and act as a scoring tool with interesting clinical applications in the fields of pharmacogenomics and personalized medicine.

Mapping the miRNA-mRNA Interactome in Human Hepatocytes and Identification of Functional mirSNPs in Pharmacogenes.

MiRNAs regulate the expression of hepatic genes involved in pharmacokinetics and pharmacodynamics. Genetic variants affecting miRNA binding (mirSNPs) have been associated with altered drug response, but previously used methods to identify miRNA binding sites and functional mirSNPs in pharmacogenes are indirect and limited by low throughput. We utilized the high-throughput chimeric-eCLIP assay to directly map thousands of miRNA-mRNA interactions and define the miRNA binding sites in primary hepatocytes. We then used the high-throughput PASSPORT-seq assay to functionally test 262 potential mirSNPs with coordinates overlapping the identified miRNA binding sites. Using chimeric-eCLIP, we identified a network of 448 miRNAs that collectively target 11,263 unique genes in primary hepatocytes pooled from 100 donors. Our data provide an extensive map of miRNA binding of each gene, including pharmacogenes, expressed in primary hepatocytes. For example, we identified the hsa-mir-27b-DPYD interaction at a previously validated binding site. A second example is our identification of 19 unique miRNAs that bind to CYP2B6 across 20 putative binding sites on the transcript. Using PASSPORT-seq, we then identified 24 mirSNPs that functionally impacted reporter mRNA levels. To our knowledge, this is the most comprehensive identification of miRNA binding sites in pharmacogenes. Combining chimeric-eCLIP with PASSPORT-seq successfully identified functional mirSNPs in pharmacogenes that may affect transcript levels through altered miRNA binding. These results provide additional insights into potential mechanisms contributing to interindividual variability in drug response.

Pharmacogenomic landscape of COVID-19 therapies from Indian population genomes.

Aim: Numerous drugs are being widely prescribed for COVID-19 treatment without any direct evidence for the drug safety/efficacy in patients across diverse ethnic populations. Materials & methods: We analyzed whole genomes of 1029 Indian individuals (IndiGen) to understand the extent of drug-gene (pharmacogenetic), drug-drug and drug-drug-gene interactions associated with COVID-19 therapy in the Indian population. Results: We identified 30 clinically significant pharmacogenetic variants and 73 predicted deleterious pharmacogenetic variants. COVID-19-associated pharmacogenes were substantially overlapped with those of metabolic disorder therapeutics. CYP3A4, ABCB1 and ALB are the most shared pharmacogenes. Fifteen COVID-19 therapeutics were predicted as likely drug-drug interaction candidates when used with four CYP inhibitor drugs. Conclusion: Our findings provide actionable insights for future validation studies and improved clinical decisions for COVID-19 therapy in Indians.

Pharmacogenetic variants of infliximab response in young patients with inflammatory bowel disease.

Infliximab is commonly used in inflammatory bowel disease (IBD), however, differences in clinical response among patients are common. Several studies have considered the possibility that these differences are caused by genetic variability even if no unique marker has been yet identified in pediatric patients. We evaluated the impact of two candidate single-nucleotide polymorphisms (SNPs) rs396991 in FCGR3A and rs1800629 in TNFα genes on infliximab response in an Italian cohort of 76 pediatric patients with IBD. Results showed that patients with the variant FCGR3A allele had a reduced clinical response at the end of induction (p value = 0.004), at 22 weeks (p value = 0.001), and at 52 weeks of treatment (p value = 0.01). A significant association between the FCGR3A variant and median infliximab levels measured during maintenance therapy was also observed: patients with wild type genotype had higher infliximab levels compared to patient with variant allele. Furthermore, patients with the variant allele had a higher probability to produce antidrug antibodies (ADAs). No association was found among the TNFα SNP, clinical response, and infliximab levels. This study addressed for the first time in pediatric patients with IBD, the association of FCGR3A SNP, infliximab response, and ADA production.

A novel gene associated with small bowel bleeding in patients taking low-dose aspirin.

OBJECTIVE: We have previously revealed the clinical factors and genetic polymorphisms associated with gastrointestinal mucosal injury and bleeding, induced by low-dose aspirin (LDA). After performing genome-wide analysis of single nucleotide polymorphisms (SNPs) using the Drug Metabolizing Enzymes and Transporters (DMET) system among drug metabolism and transporter genes, certain SNPs were found to increase the risk for LDA-induced small bowel bleeding. The aim of this study was to identify the SNPs involved in LDA-induced small bowel bleeding. SUBJECTS AND METHODS: Subjects were patients taking LDA, with small bowel bleeding diagnosed using capsule endoscopy. We investigated the clinical characteristics and the previously identified SNPs, that were examined by the DNA direct sequence method. RESULTS: 56 patients with bleeding and 410 controls taking LDA were enrolled. The risk factors associated with small bowel bleeding included smoking, cerebrovascular diseases, chronic renal failure, non-steroidal anti-inflammatory drug (NSAID) or anticoagulants combination, and two SNPs (CYP4F11 20043G>A (D446N) rs1060463, GSTP1 313A>G rs1695). After propensity score matching, GSTP1 rs1695 was significantly associated with small bowel bleeding. CONCLUSION: The GSTP1 SNP may be a predictive marker for small bowel bleeding among patients taking LDA.

Management of Women With Breast Cancer and Pathogenic Variants in Genes Other Than BRCA1 or BRCA2.

The Oncology Grand Rounds series is designed to place original reports published in the Journal into clinical context. A case presentation is followed by a description of diagnostic and management challenges, a review of the relevant literature, and a summary of the authors' suggested management approaches. The goal of this series is to help readers better understand how to apply the results of key studies, including those published in the Journal of Clinical Oncology, to patients seen in their own clinical practice.

Computational Tools to Assess the Functional Consequences of Rare and Noncoding Pharmacogenetic Variability.

Interindividual differences in drug response are a common concern in both drug development and across layers of care. While genetics clearly influences drug response and toxicity of many drugs, a substantial fraction of the heritable pharmacological and toxicological variability remains unexplained by known genetic polymorphisms. In recent years, population-scale sequencing projects have unveiled tens of thousands of coding and noncoding pharmacogenetic variants with unclear functional effects that might explain at least part of this missing heritability. However, translating these personalized variant signatures into drug response predictions and actionable advice remains challenging and constitutes one of the most important frontiers of contemporary pharmacogenomics. Conventional prediction methods are primarily based on evolutionary conservation, which drastically reduces their predictive accuracy when applied to poorly conserved pharmacogenes. Here, we review the current state-of-the-art of computational variant effect predictors across variant classes and critically discuss their utility for pharmacogenomics. Besides missense variants, we discuss recent progress in the evaluation of synonymous, splice, and noncoding variations. Furthermore, we discuss emerging possibilities to assess haplotypes and structural variations. We advocate for the development of algorithms trained on pharmacogenomic instead of pathogenic data sets to improve the predictive accuracy in order to facilitate the utilization of next-generation sequencing data for personalized clinical decision support and precision pharmacogenomics.

Association analysis of genetic variants in the ghrelin and tumor necrosis factor α genes and the risk for non-Hodgkin's lymphoma in Kuwaitis.

BACKGROUND: Non-Hodgkin's lymphoma (NHL) is the most common hematological malignancy in the world. Many etiologic factors have been implicated in the risk of developing NHL, including genetic susceptibility and obesity. Single-nucleotide polymorphisms (SNPs) in Ghrelin (GHRL), an anti-inflammatory hormone, and tumor necrosis factor α (TNF-α), an inflammatory cytokine, have been independently associated with the risk for obesity and NHL. OBJECTIVE: To investigate the association between SNPs in GHRL and TNF-α and the risk for NHL and obesity in Kuwaitis. METHODS: We recruited 154 Kuwaiti NHL patients and 217 controls. Genotyping was performed for rs1629816 (GHRL promoter region), rs35684 (GHRL 3' untranslated region), and rs1800629 (TNF-α promoter region). Logistic regression analysis was performed to assess the association of the investigated SNPs with NHL and the relationship between the selected SNPs with BMI in each group separately. RESULTS: We show that rs1629816 GG was associated with an increased risk for NHL in our sample (p= 0.0003, OR 1.82; CI: 1.31-2.54). None of the investigated SNPs were associated with obesity, nor was obesity found to be associated with the risk for NHL. CONCLUSIONS: Our study demonstrates an association between rs1629816, a SNP in the GHRL regulatory region, and NHL in Kuwaitis.

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.

Actionable pharmacogenetic variants in Hong Kong Chinese exome sequencing data and projected prescription impact in the Hong Kong population.

Preemptive pharmacogenetic testing has the potential to improve drug dosing by providing point-of-care patient genotype information. Nonetheless, its implementation in the Chinese population is limited by the lack of population-wide data. In this study, secondary analysis of exome sequencing data was conducted to study pharmacogenomics in 1116 Hong Kong Chinese. We aimed to identify the spectrum of actionable pharmacogenetic variants and rare, predicted deleterious variants that are potentially actionable in Hong Kong Chinese, and to estimate the proportion of dispensed drugs that may potentially benefit from genotype-guided prescription. The projected preemptive pharmacogenetic testing prescription impact was evaluated based on the patient prescription data of the public healthcare system in 2019, serving 7.5 million people. Twenty-nine actionable pharmacogenetic variants/ alleles were identified in our cohort. Nearly all (99.6%) subjects carried at least one actionable pharmacogenetic variant, whereas 93.5% of subjects harbored at least one rare deleterious pharmacogenetic variant. Based on the prescription data in 2019, 13.4% of the Hong Kong population was prescribed with drugs with pharmacogenetic clinical practice guideline recommendations. The total expenditure on actionable drugs was 33,520,000 USD, and it was estimated that 8,219,000 USD (24.5%) worth of drugs were prescribed to patients with an implicated actionable phenotype. Secondary use of exome sequencing data for pharmacogenetic analysis is feasible, and preemptive pharmacogenetic testing has the potential to support prescription decisions in the Hong Kong Chinese population.