SGLT1 and SGLT2 inhibition, circulating metabolites, and cerebral small vessel disease: a mediation Mendelian Randomization study.

BACKGROUND: Sodium-glucose cotransporter 2 (SGLT2) and SGLT1 inhibitors may have additional beneficial metabolic effects on circulating metabolites beyond glucose regulation, which could contribute to a reduction in the burden of cerebral small vessel disease (CSVD). Accordingly, we used Mendelian Randomization (MR) to examine the role of circulating metabolites in mediating SGLT2 and SGLT1 inhibition in CSVD. METHODS: Genetic instruments for SGLT1/2 inhibition were identified as genetic variants, which were both associated with the expression of encoding genes of SGLT1/2 inhibitors and glycated hemoglobin A1c (HbA1c) level. A two-sample two-step MR was used to determine the causal effects of SGLT1/2 inhibition on CSVD manifestations and the mediating effects of 1400 circulating metabolites linking SGLT1/2 inhibition with CSVD manifestations. RESULTS: A lower risk of deep cerebral microbleeds (CMBs) and small vessel stroke (SVS) was linked to genetically predicted SGLT2 inhibition. Better white matter structure integrity was also achieved, as evidenced by decreased mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD), as well as lower deep (DWMH) and periventrivular white matter hyperintensity (PWMH) volume. Inhibiting SGLT2 could also lessen the incidence of severe enlarged perivascular spaces (EPVS) located at white matter, basal ganglia (BG) and hippocampus (HIP). SGLT1 inhibition could preserve white matter integrity, shown as decreased MD of white matter and DWMH volume. The effect of SGLT2 inhibition on SVS and MD of white matter through the concentration of 4-acetamidobutanoate and the cholesterol to oleoyl-linoleoyl-glycerol (18:1 to 18:2) ratio, with a mediated proportion of 30.3% and 35.5% of the total effect, respectively. CONCLUSIONS: SGLT2 and SGLT1 inhibition play protective roles in CSVD development. The SGLT2 inhibition could lower the risk of SVS and improve the integrity of white matter microstructure via modulating the level of 4-acetamidobutanoate and cholesterol metabolism. Further mechanistic and clinical studies research are needed to validate our findings.

Prognostic Impact of CYP2C19 Genotypes on Long-Term Clinical Outcomes in Older Patients After Percutaneous Coronary Intervention.

BACKGROUND: Carriers of CYP2C19 loss-of-function alleles have increased adverse events after percutaneous coronary intervention, but limited data are available for older patients. We aimed to evaluate the prognostic impact of CYP2C19 genotypes on clinical outcomes in older patients after percutaneous coronary intervention. METHODS AND RESULTS: The study included 1201 older patients (aged ≥75 years) who underwent percutaneous coronary intervention and received clopidogrel-based dual antiplatelet therapy in South Korea. Patients were grouped on the basis of CYP2C19 genotypes. The primary outcome was 3-year major adverse cardiac events, defined as a composite of cardiac death, myocardial infarction, and stent thrombosis. Older patients were grouped into 3 groups: normal metabolizer (36.6%), intermediate metabolizer (48.1%), and poor metabolizer (15.2%). The occurrence of the primary outcome was significantly different among the groups (3.1, 7.0, and 6.2% in the normal metabolizer, intermediate metabolizer, and poor metabolizer groups, respectively; P=0.02). The incidence rate of all-cause death at 3 years was greater in the intermediate metabolizer and poor metabolizer groups (8.1% and 9.2%, respectively) compared with that in the normal metabolizer group (3.5%, P=0.03) without significant differences in major bleeding. In the multivariable analysis, the intermediate metabolizer and poor metabolizer groups were independent predictors of 3-year clinical outcomes. CONCLUSIONS: In older patients, the presence of any CYP2C19 loss-of-function allele was found to be predictive of a higher incidence of major adverse cardiac events within 3 years following percutaneous coronary intervention. This finding suggests a need for further investigation into an optimal antiplatelet strategy for older patients. REGISTRATION: URL: https://clinicaltrials.gov. Identifier: NCT04734028.

A systematic review and meta-analysis of the impacts of germline pharmacogenomics on severe toxicity and symptom burden in adult patients with cancer.

The clinical application of Pharmacogenomics (PGx) has improved patient safety. However, comprehensive PGx testing has not been widely adopted in clinical practice, and significant opportunities exist to further optimize PGx in cancer care. This systematic review and meta-analysis aim to evaluate the safety outcomes of reported PGx-guided strategies (Analysis 1) and identify well-studied emerging pharmacogenomic variants that predict severe toxicity and symptom burden (Analysis 2) in patients with cancer. We searched MEDLINE, EMBASE, CENTRAL, clinicaltrials.gov, and International Clinical Trials Registry Platform from inception to January 2023 for clinical trials or comparative studies evaluating PGx strategies or unconfirmed pharmacogenomic variants. The primary outcomes were severe adverse events (SAE; ≥ grade 3) or symptom burden with pain and vomiting as defined by trial protocols and assessed by trial investigators. We calculated pooled overall relative risk (RR) and 95% confidence interval (95%CI) using random effects models. PROSPERO, registration number CRD42023421277. Of 6811 records screened, six studies were included for Analysis 1, 55 studies for Analysis 2. Meta-analysis 1 (five trials, 1892 participants) showed a lower absolute incidence of SAEs with PGx-guided strategies compared to usual therapy, 16.1% versus 34.0% (RR = 0.72, 95%CI 0.57-0.91, p = 0.006, I2 = 34%). Meta-analyses 2 identified nine medicine(class)-variant pairs of interest across the TYMS, ABCB1, UGT1A1, HLA-DRB1, and OPRM1 genes. Application of PGx significantly reduced rates of SAEs in patients with cancer. Emergent medicine-variant pairs herald further research into the expansion and optimization of PGx to improve systemic anti-cancer and supportive care medicine safety and efficacy.

Frequency of pharmacogenomic variants affecting efficacy and safety of anti-cancer drugs in a south Asian population from Sri Lanka.

BACKGROUND: Therapy with anti-cancer drugs remain the cornerstone of treating cancer. The effectiveness and safety of anti-cancer drugs vary significantly among individuals due to genetic factors influencing the drug response and metabolism. Data on the pharmacogenomic variations in Sri Lankans related to anti-cancer therapy is sparse. As current treatment guidelines in Sri Lanka often do not consider local pharmacogenomic variants, this study aimed to explore the diversity of pharmacogenomic variants in the Sri Lankan population to pave the way for personalized treatment approaches and improve patient outcomes. METHODS: Pharmacogenomic data regarding variant-drug pairs of genes CYP2D6, DPYD, NUDT15, EPAS1, and XRCC1 with clinical annotations labelled as evidence levels 1A-2B were obtained from the Pharmacogenomics Knowledgebase database. Their frequencies in Sri Lankans were obtained from an anonymized database that was derived from 541 Sri Lankans who underwent exome sequencing at the Human Genetics Unit, Faculty of Medicine, University of Colombo. Variations in DPYD, NUDT15, and EPAS1 genes are related to increased toxicity to fluoropyrimidines, mercaptopurines, and sorafenib respectively. Variations in CYP2D6 and XRCC1 genes are related to changes in efficacy of tamoxifen and platinum compounds, respectively. Minor allele frequencies of these variants were calculated and compared with other populations. RESULTS: MAFs of rs1065852 c.100 C > T (CYP2D6), rs3918290 c.1905 + 1G > A (DPYD), rs56038477 c.1236G > A (DPYD), rs7557402 c.1035-7 C > G (EPAS1), rs116855232 c.415 C > T (NUDT15*3), and rs25487 c.1196 A > G (XRCC1) were: 12.9% [95%CI:10.9-14.9], 1.5% [95%CI:0.8-2.2], 1.2% [95%CI:0.5-1.8], 37.7% [95%CI:34.8-40.6], 8.3% [95%CI:6.7-10.0], and 64.0% [95%CI:61.1-66.8], respectively. Frequencies of rs1065852 c.100 C > T (CYP2D6), rs7557402 c.1035-7 C > G (EPAS1), and rs25487 (XRCC1) were significantly lower in Sri Lankans, while frequencies of rs116855232 c.415 C > T (NUDT15*3) and rs56038477 c.1236G > A (DPYD) were significantly higher in Sri Lankans when compared to some Western and Asian populations. CONCLUSION: Sri Lankans are likely to show lower toxicity risk with sorafenib (rs7557402 c.84,131 C > G) and, higher toxicity risk with fluoropyrimidines (rs56038477 c.1236G > A) and mercaptopurine (rs116855232 c.415 C > T), and reduced effectiveness with tamoxifen (rs1065852 c.100 C > T) and platinum compounds (rs25487). These findings highlight the potential contribution of these genetic variations to the individual variability in anti-cancer dosage requirements among Sri Lankans.

Gene polymorphism as a cause of hemorrhagic complications in patients with non-valvular atrial fibrillation treated with oral vitamin K-independent anticoagulants.

Atrial fibrillation (AF) accounts for 40% of all cardiac arrhythmias and is associated with a high risk of stroke and systemic thromboembolic complications. Dabigatran, rivaroxaban, apixaban, and edoxaban are direct oral anticoagulants (DOACs) that have been proven to prevent stroke in patients with non-valvular AF. This review summarizes the pharmacokinetics, pharmacodynamics, and drug interactions of DOACs, as well as new data from pharmacogenetic studies of these drugs. This review is aimed at analyzing the scientific literature on the gene polymorphisms involved in the metabolism of DOACs. We searched PubMed, Cochrane, Google Scholar, and CyberLeninka (Russian version) databases with keywords: 'dabigatran', 'apixaban', 'rivaroxaban', 'edoxaban', 'gene polymorphism', 'pharmacogenetics', 'ABCB1', 'CES1', 'SULT1A', 'ABCG2', and 'CYP3A4'. The articles referred for this review include (1) full-text articles; (2) study design with meta-analysis, an observational study in patients taking DOAC; and (3) data on the single-nucleotide polymorphisms and kinetic parameters of DOACs (plasma concentration), or a particular clinical outcome, published in English and Russian languages during the last 10 years. The ages of the patients ranged from 18 to 75 years. Out of 114 reviewed works, 24 were found eligible. As per the available pharmacogenomic data, polymorphisms affecting DOACs are different. This may aid in developing individual approaches to optimize DOAC pharmacotherapy to reduce the risk of hemorrhagic complications. However, large-scale population studies are required to determine the dosage of the new oral anticoagulants based on genotyping. Information on the genetic effects is limited owing to the lack of large-scale studies. Uncovering the mechanisms of the genetic basis of sensitivity to DOACs helps in developing personalized therapy based on patient-specific genetic variants and improves the efficacy and safety of DOACs in the general population.

Gene polymorphism as a cause of hemorrhagic complications in patients with non-valvular atrial fibrillation treated with oral vitamin K-independent anticoagulantsAtrial fibrillation (AF) accounts for 40% of all cardiac arrhythmias and is associated with a high risk of stroke and systemic thromboembolic complications. Dabigatran, rivaroxaban, apixaban, and edoxaban are direct oral anticoagulants (DOACs) that have been proven to prevent stroke in patients with non-valvular AF. This review summarizes the pharmacokinetics, pharmacodynamics, and drug interactions of DOACs, as well as new data from pharmacogenetic studies of these drugs.

APF2: an improved ensemble method for pharmacogenomic variant effect prediction.

Lack of efficacy or adverse drug response are common phenomena in pharmacological therapy causing considerable morbidity and mortality. It is estimated that 20-30% of this variability in drug response stems from variations in genes encoding drug targets or factors involved in drug disposition. Leveraging such pharmacogenomic information for the preemptive identification of patients who would benefit from dose adjustments or alternative medications thus constitutes an important frontier of precision medicine. Computational methods can be used to predict the functional effects of variant of unknown significance. However, their performance on pharmacogenomic variant data has been lackluster. To overcome this limitation, we previously developed an ensemble classifier, termed APF, specifically designed for pharmacogenomic variant prediction. Here, we aimed to further improve predictions by leveraging recent key advances in the prediction of protein folding based on deep neural networks. Benchmarking of 28 variant effect predictors on 530 pharmacogenetic missense variants revealed that structural predictions using AlphaMissense were most specific, whereas APF exhibited the most balanced performance. We then developed a new tool, APF2, by optimizing algorithm parametrization of the top performing algorithms for pharmacogenomic variations and aggregating their predictions into a unified ensemble score. Importantly, APF2 provides quantitative variant effect estimates that correlate well with experimental results (R2 = 0.91, p = 0.003) and predicts the functional impact of pharmacogenomic variants with higher accuracy than previous methods, particularly for clinically relevant variations with actionable pharmacogenomic guidelines. We furthermore demonstrate better performance (92% accuracy) on an independent test set of 146 variants across 61 pharmacogenes not used for model training or validation. Application of APF2 to population-scale sequencing data from over 800,000 individuals revealed drastic ethnogeographic differences with important implications for pharmacotherapy. We thus think that APF2 holds the potential to improve the translation of genetic information into pharmacogenetic recommendations, thereby facilitating the use of Next-Generation Sequencing data for stratified medicine.

Impacts of gene variants on drug effects-the foundation of genotype-guided pharmacologic therapy for long QT syndrome and short QT syndrome.

The clinical significance of optimal pharmacotherapy for inherited arrhythmias such as short QT syndrome (SQTS) and long QT syndrome (LQTS) has been increasingly recognised. The advancement of gene technology has opened up new possibilities for identifying genetic variations and investigating the pathophysiological roles and mechanisms of genetic arrhythmias. Numerous variants in various genes have been proven to be causative in genetic arrhythmias. Studies have demonstrated that the effectiveness of certain drugs is specific to the patient or genotype, indicating the important role of gene-variants in drug response. This review aims to summarize the reported data on the impact of different gene-variants on drug response in SQTS and LQTS, as well as discuss the potential mechanisms by which gene-variants alter drug response. These findings may provide valuable information for future studies on the influence of gene variants on drug efficacy and the development of genotype-guided or precision treatment for these diseases.

Polygenic scores for cardiovascular risk factors improve estimation of clinical outcomes in CCB treatment compared to pharmacogenetic variants alone.

Pharmacogenetic variants are associated with clinical outcomes during Calcium Channel Blocker (CCB) treatment, yet whether the effects are modified by genetically predicted clinical risk factors is unknown. We analyzed 32,000 UK Biobank participants treated with dihydropiridine CCBs (mean 5.9 years), including 23 pharmacogenetic variants, and calculated polygenic scores for systolic and diastolic blood pressures, body fat mass, and other patient characteristics. Outcomes included treatment discontinuation and heart failure. Pharmacogenetic variant rs10898815-A (NUMA1) increased discontinuation rates, highest in those with high polygenic scores for fat mass. The RYR3 variant rs877087 T-allele alone modestly increased heart failure risks versus non-carriers (HR:1.13, p = 0.02); in patients with high polygenic scores for fat mass, lean mass, and lipoprotein A, risks were substantially elevated (HR:1.55, p = 4 × 10-5). Incorporating polygenic scores for adiposity and lipoprotein A may improve risk estimates of key clinical outcomes in CCB treatment such as treatment discontinuation and heart failure, compared to pharmacogenetic variants alone.

Influence of pharmacogenomic polymorphisms on allopurinol-induced cutaneous adverse drug reactions in Thai patients.

BACKGROUND: Allopurinol has been causing substantial morbidity and mortality particularly in Asian population by producing cutaneous adverse drug reactions (cADRs). Nonetheless, there are no data describing whether other genetics are a valid marker for prediction of allopurinol-induced cADRs patients in addition to HLA-B*58:01 allele. The goal of this study was to identify suitable single nucleotide polymorphisms (SNPs) for allopurinol induced cADRs among Thai patients. METHODS: We conducted a case-control association study after enrolling 57 Thai patients with allopurinol induced cADRs and 101 allopurinol-tolerant controls. The genetic biomarkers and associated SNPs located on chromosome 6p21 were examined by TaqMan® SNP genotyping assays in both the cases and the controls. RESULTS: Out of fifteen SNPs in nine genes, we found four combined SNPs (rs3099844 of HCP5, rs9263726 of PSORS1C1, rs9263733 of POLR2LP, and rs9263745 of CCHCR1) were significantly associated with allopurinol-induced cADRs compared to the tolerant controls (OR 73.2; 95% CI 24.2-266.8; P = 1.9 × 10- 24). The overall sensitivity, specificity, positive predictive value and negative predictive value of these combinations were 84%, 94%, 9%, and 100%, respectively. However, the variant alleles of these SNP combinations were detected in 89.5% (51/57) of the cases. Moreover, the HLA-B*58:01 allele was observed in 86.0% of patients with allopurinol-induced cADRs, but only in 4.0% of tolerant controls (OR: 137.2; 95% CI: 38.3-670.5 and p-value = 1.7 × 10- 27). CONCLUSIONS: Thus, this research confirms the association between the specific HLA-B*58:01 allele and all phenotypes of allopurinol-induced cADRs in Thais. Furthermore, there was found the combined four SNPs (rs3099844, rs9263726, rs9263733, and rs9263745) could be used as alternative novel biomarkers for predicting cADRs in patients taking allopurinol.

Factors associated with clopidogrel resistance and clinical outcomes in ischemic cerebrovascular disease: A retrospective study.

OBJECTIVE: Clopidogrel resistance may lead to the recurrence of cerebrovascular diseases. We aimed to identify potential factors associated with clopidogrel resistance and evaluate the clinical outcomes of the patients. MATERIALS AND METHODS: In this retrospective study, patients with ischemic cerebrovascular disease treated with clopidogrel were included and classified into 2 groups according to the adenosine diphosphate (ADP)-induced platelet aggregation. Patients with the ADP inhibition rate of <30 % were included in clopidogrel resistance group, otherwise were included in clopidogrel sensitive group. CYP2C19 genotype and other clinical data were analyzed to identify factors and clinical features in the multivariate analysis. The outcomes were vascular events in 6 months. RESULTS: In total, 139 patients were enrolled with 81 (58.27 %) in clopidogrel sensitive group and 58 (41.73 %) in clopidogrel resistance group. Female and CYP2C19 *2*3 carrying were risk factors for clopidogrel resistance, and female was an independent risk factor (OR 2.481, 95 % CI 1.066-5.771, P=0.035). The clopidogrel resistance group showed a higher use rate of argatroban (P=0.030) and a lower arachidonic acid-induced inhibition of platelet aggregation (P=0.036). Clopidogrel resistance was related to the progressing stroke (HR 3.521, 95 % CI 1.352-9.170, P=0.010), but had no influence on the bleeding events (P>0.05). CONCLUSIONS: The risk of clopidogrel resistance increased significantly in female patients. Patients with clopidogrel resistance may have an increased incidence of stroke progression in the acute phase.

Frequencies of CYP2C19 and CYP2D6 gene variants in a German inpatient sample with mood and anxiety disorders.

OBJECTIVES: Previous results demonstrated that CYP2D6 and CYP2C19 gene variants affect serum concentrations of antidepressants. We implemented a PGx service determining gene variants in CYP2D6 and CYP2C19 in our clinical routine care and report on our first patient cohort. METHODS: We analysed CYP2D6 and CYP2C19 allele, genotype, and phenotype frequencies, and actionable pharmacogenetic variants in this German psychiatric inpatient cohort. Two-tailed z-test was used to investigate for differences in CYP2D6 and CYP2C19 phenotypes and actionable/non-actionable genetic variant frequencies between our cohort and reference cohorts. RESULTS: Out of the 154 patients included, 44.8% of patients were classified as CYP2D6 normal metabolizer, 38.3% as intermediate metabolizers, 8.4% as poor metabolizers, and 2.6% as ultrarapid metabolizers. As for CYP2C19, 40.9% of patients were classified as normal metabolizers, 19.5% as intermediate metabolizers, 2.6% as poor metabolizers, 31.2% as rapid metabolizers, and 5.8% as ultrarapid metabolizers. Approximately, 80% of patients had at least one actionable PGx variant. CONCLUSION: There is a high prevalence of actionable PGx variants in psychiatric inpatients which may affect treatment response. Physicians should refer to PGx-informed dosing guidelines in carriers of these variants. Pre-emptive PGx testing in general may facilitate precision medicine also for other drugs metabolised by CYP2D6 and/or CYP2C19.

Genome-Wide Association Study of Atorvastatin Pharmacokinetics: Associations With SLCO1B1, UGT1A3, and LPP.

In a genome-wide association study of atorvastatin pharmacokinetics in 158 healthy volunteers, the SLCO1B1 c.521T>C (rs4149056) variant associated with increased area under the plasma concentration-time curve from time zero to infinity (AUC0-∞) of atorvastatin (P = 1.2 × 10-10), 2-hydroxy atorvastatin (P = 4.0 × 10-8), and 4-hydroxy atorvastatin (P = 2.9 × 10-8). An intronic LPP variant, rs1975991, associated with reduced atorvastatin lactone AUC0-∞ (P = 3.8 × 10-8). Three UGT1A variants linked with UGT1A3*2 associated with increased 2-hydroxy atorvastatin lactone AUC0-∞ (P = 3.9 × 10-8). Furthermore, a candidate gene analysis including 243 participants suggested that increased function SLCO1B1 variants and decreased activity CYP3A4 variants affect atorvastatin pharmacokinetics. Compared with individuals with normal function SLCO1B1 genotype, atorvastatin AUC0-∞ was 145% (90% confidence interval: 98-203%; P = 5.6 × 10-11) larger in individuals with poor function, 24% (9-41%; P = 0.0053) larger in those with decreased function, and 41% (16-59%; P = 0.016) smaller in those with highly increased function SLCO1B1 genotype. Individuals with intermediate metabolizer CYP3A4 genotype (CYP3A4*2 or CYP3A4*22 heterozygotes) had 33% (14-55%; P = 0.022) larger atorvastatin AUC0-∞ than those with normal metabolizer genotype. UGT1A3*2 heterozygotes had 16% (5-25%; P = 0.017) smaller and LPP rs1975991 homozygotes had 34% (22-44%; P = 4.8 × 10-5) smaller atorvastatin AUC0-∞ than noncarriers. These data demonstrate that genetic variation in SLCO1B1, UGT1A3, LPP, and CYP3A4 affects atorvastatin pharmacokinetics. This is the first study to suggest that LPP rs1975991 may reduce atorvastatin exposure. [Correction added on 6 April, after first online publication: An incomplete sentence ("= 0.017) smaller in heterozygotes for UGT1A3*2 and 34% (22%, 44%; P × 10-5) smaller in homozygotes for LPP noncarriers.") has been corrected in this version.].

Very important pharmacogenetic variants landscape and potential clinical relevance in the Zhuang population from Yunnan province.

The gradual evolution of pharmacogenomics has shed light on the genetic basis for inter-individual drug response variations across diverse populations. This study aimed to identify pharmacogenomic variants that differ in Zhuang population compared with other populations and investigate their potential clinical relevance in gene-drug and genotypic-phenotypic associations. A total of 48 variants from 24 genes were genotyped in 200 Zhuang subjects using the Agena MassARRAY platform. The allele frequencies and genotype distribution data of 26 populations were obtained from the 1000 Genomes Project, followed by a comparison and statistical analysis. After Bonferroni correction, significant differences in genotype frequencies were observed of CYP3A5 (rs776746), ACE (rs4291), KCNH2 (rs1805123), and CYP2D6 (rs1065852) between the Zhuang population and the other 26 populations. It was also found that the Chinese Dai in Xishuangbanna, China, Han Chinese in Beijing, China, and Southern Han Chinese, China showed least deviation from the Zhuang population. The Esan in Nigeria, Gambian in Western Division, The Gambia, and Yoruba in Ibadan, Nigeria exhibited the largest differences. This was also proved by structural analysis, Fst analysis and phylogenetic tree. Furthermore, these differential variants may be associated with the pharmacological efficacy and toxicity of Captopril, Amlodipine, Lisinopril, metoclopramide, and alpha-hydroxymetoprolol in the Zhuang population. Our study has filled the gap of pharmacogenomic information in the Zhuang population and has provided a theoretical framework for the secure administration of drugs in the Zhuang population.

Landscape of pharmacogenetic variants associated with non-insulin antidiabetic drugs in the Indian population.

INTRODUCTION: Genetic variants contribute to differential responses to non-insulin antidiabetic drugs (NIADs), and consequently to variable plasma glucose control. Optimal control of plasma glucose is paramount to minimizing type 2 diabetes-related long-term complications. India's distinct genetic architecture and its exploding burden of type 2 diabetes warrants a population-specific survey of NIAD-associated pharmacogenetic (PGx) variants. The recent availability of large-scale whole genomes from the Indian population provides a unique opportunity to generate a population-specific map of NIAD-associated PGx variants. RESEARCH DESIGN AND METHODS: We mined 1029 Indian whole genomes for PGx variants, drug-drug interaction (DDI) and drug-drug-gene interactions (DDGI) associated with 44 NIADs. Population-wise allele frequencies were estimated and compared using Fisher's exact test. RESULTS: Overall, we found 76 known and 52 predicted deleterious common PGx variants associated with response to type 2 diabetes therapy among Indians. We report remarkable interethnic differences in the relative cumulative counts of decreased and increased response-associated alleles across NIAD classes. Indians and South Asians showed a significant excess of decreased metformin response-associated alleles compared with other global populations. Network analysis of shared PGx genes predicts high DDI risk during coadministration of NIADs with other metabolic disease drugs. We also predict an increased CYP2C19-mediated DDGI risk for CYP3A4/3A5-metabolized NIADs, saxagliptin, linagliptin and glyburide when coadministered with proton-pump inhibitors (PPIs). CONCLUSIONS: Indians and South Asians have a distinct PGx profile for antidiabetes drugs, marked by an excess of poor treatment response-associated alleles for various NIAD classes. This suggests the possibility of a population-specific reduced drug response in atleast some NIADs. In addition, our findings provide an actionable resource for accelerating future diabetes PGx studies in Indians and South Asians and reconsidering NIAD dosing guidelines to ensure maximum efficacy and safety in the population.

Attempted replication of pharmacogenetic association of variants in PPP1R14C and CCDC148 with aromatase inhibitor-induced musculoskeletal symptoms.

Third-generation aromatase inhibitors (AI) are the standard treatment for patients with hormone receptor positive (HR+) breast cancer. While effective, AI can lead to severe adverse events, including AI-induced musculoskeletal syndrome (AIMSS). Genetic predictors of AIMSS have the potential to personalize AI treatment and improve outcomes. We attempted to replicate results from a previous genome-wide association study that found a lower risk of AIMSS in patients carrying PPP1R14C rs912571 and a higher risk in patients carrying CCDC148 rs79048288. AIMSS data were collected prospectively from patients with HR+ breast cancer prior to starting and after 3 and 6 months of adjuvant AI via the Patient-Reported Outcome Measurement Information System and Functional Assessment of Cancer Therapy-Endocrine Symptom. Germline genotypes for PPP1R14C rs912571 and CCDC148 rs79048288 were tested for a similar association with AIMSS as previously reported via $2 tests. Of the 143 patients with AIMSS and genetics data were included in the analysis. There was no association identified between PPP1R14C rs912571 and AIMSS risk ( P  > 0.05). Patients carrying CCDC148 rs79048288 variant alleles had lower AIMSS incidence in a secondary analysis ( P  = 0.04); however, this was in the opposite direction of the previous finding. The study did not replicate previously reported associations with AIMSS risk for genetic variants in PPP1R14C and CCDC148 and AIMSS risk. Further research is needed to discover and validate genetic predictors of AIMSS that can be used to personalize treatment in patients with HR+ breast cancer.

The landscape of very important pharmacogenes variants and potential clinical relevance in the Chinese Jingpo population: a comparative study with worldwide populations.

BACKGROUND: Pharmacogenomics is a facet of personalized medicine that explores how genetic variants affect drug metabolism and adverse drug reactions. Therefore, this study aims to detect distinct pharmacogenomic variations among the Jingpo population and explore their clinical correlation with drug metabolism and toxicity. METHODS: Agena MassARRAY Assay was used to genotype 57 VIP variants in 28 genes from 159 unrelated Jingpo participants. Subsequently, the chi-squared test and Bonferroni's statistical tests were utilized to conduct a comparative analysis of genotypes and allele frequencies between the Jingpo population and the other 26 populations from the 1000 Genome Project. RESULTS: We discovered that the KHV (Kinh in Ho ChiMinh City, Vietnam), CHS (Southern Han Chi-nese, China) and JPT (Japanese in Tokyo, Japan) exhibited the smallest differences from the Jingpo with only 4 variants, while ESN (Esan in Nigeria) exhibited the largest differences with 30 variants. Besides, a total of six considerably different loci (rs4291 in ACE, rs20417 in PTGS2, rs1801280 and rs1799929 in NAT2, rs2115819 in ALOX5, rs1065852 in CYP2D6, p < 3.37 × 10-5) were identified in this study. According to PharmGKB, rs20417 (PTGS2), rs4291 (ACE), rs2115819 (ALOX5) and rs1065852 (CYP2D6) were found to be associated with the metabolism efficiency of non-steroidal anti-inflammatory drugs (NSAIDs), aspirin, montelukast and tamoxifen, respectively. Meanwhile, rs1801280 and rs1799929 (NAT2) were found to be related to drug poisoning with slow acetylation. CONCLUSION: Our study unveils distinct pharmacogenomic variants in the Jingpo population and discovers their association with the metabolic efficiency of NSAIDs, montelukast, and tamoxifen.

Should secondary pharmacogenomic variants be actively screened and reported when diagnostic genome-wide sequencing is performed in a child?

This white paper was prepared by the Global Alliance for Genomics and Health Regulatory and Ethics Work Stream's Pediatric Task Team to review and provide perspective with respect to ethical, legal, and social issues regarding the return of secondary pharmacogenomic variants in children who have a serious disease or developmental disorder and are undergoing exome or genome sequencing to identify a genetic cause of their condition. We discuss actively searching for and reporting pharmacogenetic/genomic variants in pediatric patients, different methods of returning secondary pharmacogenomic findings to the patient/parents and/or treating clinicians, maintaining these data in the patient's health record over time, decision supports to assist using pharmacogenetic results in future treatment decisions, and sharing information in public databases to improve the clinical interpretation of pharmacogenetic variants identified in other children. We conclude by presenting a series of points to consider for clinicians and policymakers regarding whether, and under what circumstances, routine screening and return of pharmacogenomic variants unrelated to the indications for testing is appropriate in children who are undergoing genome-wide sequencing to assist in the diagnosis of a suspected genetic disease.

Combined impact of hypoalbuminemia and pharmacogenomic variants on voriconazole trough concentration: data from a real-life clinical setting in the Chinese population.

Voriconazole (VRC) displays highly variable pharmacokinetics impacting treatment efficacy and safety. To provide evidence for optimizing VRC therapy regimens, the authors set out to determine the factors impacting VRC steady-state trough concentration (Cmin) in patients with various albumin (Alb) level. A total of 275 blood samples of 120 patients and their clinical characteristics and genotypes of CYP2C19, CYP3A4, CYP3A5, CYP2C9, FMO3, ABCB1, POR, NR1I2 and NR1I3 were included in this study. Results of multivariate linear regression analysis demonstrated that C-reactive protein (CRP) and total bilirubin (T-Bil) were predictors of the VRC Cmin adjusted for dose in patients with hypoalbuminemia (Alb < 35 g/L) (R2 = 0.16, P < 0.001). Additionally, in patients with normal albumin level (Alb ≥ 35 g/L), it resulted in a significant model containing factors of the poor metabolizer (PM) CYP2C19 genotype and CRP level (R2 = 0.26, P < 0.001). Therefore, CRP and T-Bil levels ought to receive greater consideration than genetic factors in patients with hypoalbuminemia.