Case Report: Performing a Medication Safety Review Assisted by Pharmacogenomics to Explain a Prescribing Cascade Resulting in a Patient Fall.

Pharmacotherapy for major depressive disorder (MDD) typically consists of trial-and-error and clinician preference approaches, where patients often fail one or more antidepressants before finding an optimal regimen. Pharmacogenomics (PGx) can assist in prescribing appropriate antidepressants, thereby reducing the time to MDD remission and occurrence of adverse drug events. Since many antidepressants are metabolized by and/or inhibit cytochrome P450 enzymes (e.g., CYP2C19 or CYP2D6), drug-induced phenoconversion is common in patients on antidepressant combinations. This condition influences the interpretation of a patient's PGx results, overall risk of ineffective/adverse medication response due to multi-drug interactions, and the recommendations. This complex case describes a patient with MDD, generalized anxiety disorder, and chronic pain who experienced a fall due to excessive sedation following a prescribing cascade of fluoxetine, bupropion, and doxepin. These antidepressants delivered a significant additive sedative effect and interacted with the patient's hydrocodone, potentially contributing to uncontrolled pain, upward dose titration of hydrocodone, and a higher overall sedative burden. The PGx results and drug-induced phenoconversion described in this case report explain the patient's excessive sedation and possibly ineffective/toxic antidepressant and opioid treatment. This case report also illustrates how a more timely multi-drug interaction assessment (preferably in conjunction with preemptive PGx testing) may have informed a different prescribing pattern, reduced/avoided a prescribing cascade, and potentially prevented a drug-related fall.

Assessment of a Manual Method versus an Automated, Probability-Based Algorithm to Identify Patients at High Risk for Pharmacogenomic Adverse Drug Outcomes in a University-Based Health Insurance Program.

We compared patient cohorts selected for pharmacogenomic testing using a manual method or automated algorithm in a university-based health insurance network. The medication list was compiled from claims data during 4th quarter 2018. The manual method selected patients by number of medications by the health system's list of medications for pharmacogenomic testing. The automated method used YouScript's pharmacogenetic interaction probability (PIP) algorithm to select patients based on the probability that testing would result in detection of one or more clinically significant pharmacogenetic interactions. A total of 6916 patients were included. Patient cohorts selected by each method differed substantially, including size (manual n = 218, automated n = 286) and overlap (n = 41). The automated method was over twice as likely to identify patients where testing may reveal a clinically significant pharmacogenetic interaction than the manual method (62% vs. 29%, p < 0.0001). The manual method captured more patients with significant drug-drug or multi-drug interactions (80.3% vs. 40.2%, respectively, p < 0.0001), higher average number of significant drug interactions per patient (3.3 vs. 1.1, p < 0.0001), and higher average number of unique medications per patient (9.8 vs. 7.4, p < 0.0001). It is possible to identify a cohort of patients who would likely benefit from pharmacogenomic testing using manual or automated methods.

Genetic polymorphisms in ADRB2 and ADRB1 are associated with differential survival in heart failure patients taking ß-blockers.

Single nucleotide polymorphisms (SNPs) have been associated with differential beta-blocker (BB) effects on heart rate, blood pressure, and left ventricular ejection fraction in various patient populations. This study aimed to determine if SNPs previously associated with BB response are also associated with differential survival in heart failure (HF) patients receiving BBs. HF patient data were derived from electronic health records and the Social Security Death Index. Associations and interactions between BB dose, SNP genotype, and the outcome of death were assessed using a Cox proportional-hazard model adjusting for covariates known to be associated with differential survival in HF patients. Two SNPs, ADRB1 Arg389Gly and ADRB2 Glu27Gln, displayed significant interactions (Pint = 0.043 and Pint = 0.017, respectively) with BB dose and their association with mortality. Our study suggests that ADRB2 27Glu and ADRB1 389Arg may confer a larger survival benefit with higher BB doses in patients with HF.

Multi-Institutional Implementation of Clinical Decision Support for APOL1, NAT2, and YEATS4 Genotyping in Antihypertensive Management.

(1) Background: Clinical decision support (CDS) is a vitally important adjunct to the implementation of pharmacogenomic-guided prescribing in clinical practice. A novel CDS was sought for the APOL1, NAT2, and YEATS4 genes to guide optimal selection of antihypertensive medications among the African American population cared for at multiple participating institutions in a clinical trial. (2) Methods: The CDS committee, made up of clinical content and CDS experts, developed a framework and contributed to the creation of the CDS using the following guiding principles: 1. medical algorithm consensus; 2. actionability; 3. context-sensitive triggers; 4. workflow integration; 5. feasibility; 6. interpretability; 7. portability; and 8. discrete reporting of lab results. (3) Results: Utilizing the principle of discrete patient laboratory and vital information, a novel CDS for APOL1, NAT2, and YEATS4 was created for use in a multi-institutional trial based on a medical algorithm consensus. The alerts are actionable and easily interpretable, clearly displaying the purpose and recommendations with pertinent laboratory results, vitals and links to ordersets with suggested antihypertensive dosages. Alerts were either triggered immediately once a provider starts to order relevant antihypertensive agents or strategically placed in workflow-appropriate general CDS sections in the electronic health record (EHR). Detailed implementation instructions were shared across institutions to achieve maximum portability. (4) Conclusions: Using sound principles, the created genetic algorithms were applied across multiple institutions. The framework outlined in this study should apply to other disease-gene and pharmacogenomic projects employing CDS.

Planning and Conducting a Pharmacogenetics Association Study.

Pharmacogenetics (PGx) association studies are used to discover, replicate, and validate the association between an inherited genotype and a treatment outcome. The objective of this tutorial is to provide trainees and novice PGx researchers with an overview of the major decisions that need to be made when designing and conducting a PGx association study. The first critical decision is to determine whether the objective of the study is discovery, replication, or validation. Next, the researcher must identify a patient cohort that has all of the data necessary to conduct the intended analysis. Then, the investigator must select and define the treatment outcome, or phenotype, that will be analyzed. Next, the investigator must determine what genotyping approach and genetic data will be included in the analysis. Finally, the association between the genotype and phenotype is tested using some statistical analysis methodology. This tutorial is divided into five sections; each section describes commonly used approaches and provides suggestions and resources for designing and conducting a PGx association study. Successful PGx association studies are necessary to discover and validate associations between inherited genetic variation and treatment outcomes, which enable clinical translation to improve efficacy and reduce toxicity of treatment.

Mechanisms of CYP450 Inhibition: Understanding Drug-Drug Interactions Due to Mechanism-Based Inhibition in Clinical Practice.

In an ageing society, polypharmacy has become a major public health and economic issue. Overuse of medications, especially in patients with chronic diseases, carries major health risks. One common consequence of polypharmacy is the increased emergence of adverse drug events, mainly from drug-drug interactions. The majority of currently available drugs are metabolized by CYP450 enzymes. Interactions due to shared CYP450-mediated metabolic pathways for two or more drugs are frequent, especially through reversible or irreversible CYP450 inhibition. The magnitude of these interactions depends on several factors, including varying affinity and concentration of substrates, time delay between the administration of the drugs, and mechanisms of CYP450 inhibition. Various types of CYP450 inhibition (competitive, non-competitive, mechanism-based) have been observed clinically, and interactions of these types require a distinct clinical management strategy. This review focuses on mechanism-based inhibition, which occurs when a substrate forms a reactive intermediate, creating a stable enzyme-intermediate complex that irreversibly reduces enzyme activity. This type of inhibition can cause interactions with drugs such as omeprazole, paroxetine, macrolide antibiotics, or mirabegron. A good understanding of mechanism-based inhibition and proper clinical management is needed by clinicians when such drugs are prescribed. It is important to recognize mechanism-based inhibition since it cannot be prevented by separating the time of administration of the interacting drugs. Here, we provide a comprehensive overview of the different types of mechanism-based inhibition, along with illustrative examples of how mechanism-based inhibition might affect prescribing and clinical behaviors.

Development of Customizable Implementation Guides to Support Clinical Adoption of Pharmacogenomics: Experiences of the Implementing GeNomics In pracTicE (IGNITE) Network.

INTRODUCTION: Clinical adoption of genomic medicine has lagged behind the pace of scientific discovery. Practice-based resources can help overcome implementation challenges. METHODS: In 2015, the IGNITE (Implementing GeNomics In pracTicE) Network created an online genomic medicine implementation resource toolbox that was expanded in 2017 to incorporate the ability for users to create targeted implementation guides. This expansion was led by a multidisciplinary team that developed an evidence-based, structured framework for the guides, oversaw the technical process/build, and pilot tested the first guide, CYP2C19-Clopidogrel Testing Implementation. RESULTS: Sixty-five resources were collected from 12 institutions and categorized according to a seven-step implementation framework for the pilot CYP2C19-Clopidogrel Testing Implementation Guide. Five months after its launch, 96 CYP2C19-Clopidogrel Testing Implementation Guides had been created. Eighty percent of the resources most frequently selected by users were created by IGNITE to fill an identified resource gap. Resources most often included in guides were from the test reimbursement (22%), Implementation support gathering (22%), EHR integration (17%), and genetic testing workflow steps (17%). CONCLUSION: Lessons learned from this implementation guide development process provide insight for prioritizing development of future resources and support the value of collaborative efforts to create resources for genomic medicine implementation.

Design and Early Implementation Successes and Challenges of a Pharmacogenetics Consult Clinic.

Pharmacogenetic testing (PGT) is increasingly being used as a tool to guide clinical decisions. This article describes the development of an outpatient, pharmacist-led, pharmacogenetics consult clinic within internal medicine, its workflow, and early results, along with successes and challenges. A pharmacogenetics-trained pharmacist encouraged primary care physicians (PCPs) to refer patients who were experiencing side effects/ineffectiveness from certain antidepressants, opioids, and/or proton pump inhibitors. In clinic, the pharmacist confirmed the need for and ordered CYP2C19 and/or CYP2D6 testing, provided evidence-based pharmacogenetic recommendations to PCPs, and educated PCPs and patients on the results. Operational and clinical metrics were analyzed. In two years, 91 referred patients were seen in clinic (mean age 57, 67% women, 91% European-American). Of patients who received PGT, 77% had at least one CYP2C19 and/or CYP2D6 phenotype that would make conventional prescribing unfavorable. Recommendations suggested that physicians change a medication/dose for 59% of patients; excluding two patients lost to follow-up, 87% of recommendations were accepted. Challenges included PGT reimbursement and referral maintenance. High frequency of actionable results suggests physician education on who to refer was successful and illustrates the potential to reduce trial-and-error prescribing. High recommendation acceptance rate demonstrates the pharmacist's effectiveness in providing genotype-guided recommendations, emphasizing a successful pharmacist-physician collaboration.

How to Transition from Single-Gene Pharmacogenetic Testing to Preemptive Panel-Based Testing: A Tutorial.

There have been significant advancements in precision medicine and approaches to medication selection based on pharmacogenetic results. With the availability of direct-to-consumer genetic testing and growing awareness of genetic interindividual variability, patient demand for more precise, individually tailored drug regimens is increasing. The University of Florida (UF) Health Precision Medicine Program (PMP) was established in 2011 to improve integration of genomic data into clinical practice. In the ensuing years, the UF Health PMP has successfully implemented several single-gene tests to optimize the precision of medication prescribing across a variety of clinical settings. Most recently, the UF Health PMP launched a custom-designed pharmacogenetic panel, including pharmacogenes relevant to supportive care medications commonly prescribed to patients undergoing chemotherapy treatment, referred to as "GatorPGx." This tutorial provides guidance and information to institutions on how to transition from the implementation of single-gene pharmacogenetic testing to a preemptive panel-based testing approach. Here, we demonstrate application of the preemptive panel in the setting of an adult solid tumor oncology clinic. Importantly, the information included herein can be applied to other clinical practice settings.

Beta-Blocker Dose Stratifies Mortality Risk in a Racially Diverse Heart Failure Population.

Heart failure (HF) is highly prevalent and a major cause of death in the United States. The effect of HF medications on survival has been predicted by validated models studied in populations predominantly of European descent. This study aimed to identify medications associated with survival in a racially diverse HF population. Patients with HF were recruited and followed from 2001 to 2015. Data were collected from electronic health records and the Social Security Death Index. The primary analysis tested the association between medication dose and all-cause mortality, with a secondary analysis assessing the composite outcome of death or cardiac-related hospitalization. Circulating concentration of the fibrotic marker procollagen type III N-terminal peptide (PIIINP) was also compared with medication doses in patients with concentrations available. The study population consisted of 337 patients, of which 25.2% died and 46% were hospitalized. Increased beta-blocker (BB) dose was significantly associated with survival in the base model [hazard ratio (HR) = 0.71, P = 0.017] and marginally associated in the comprehensive model (HR = 0.75, P = 0.068). BB dose was also associated with decreased risk of the composite end point in the base model (HR = 0.80, P = 0.029) and to a lesser extent in the comprehensive model (HR = 0.83, P = 0.085). Furthermore, increased BB dose was inversely associated with circulating PIIINP concentration (P = 0.041). In conclusion, our study highlights the importance of BB dose escalation for survival and decreased hospitalization in patients with HF, regardless of race or HF type. It also suggests that benefits observed with high-dose BBs could be mediated, at least in part, by decreased cardiac fibrosis.

Transcriptome-wide analysis associates ID2 expression with combined pre- and post-capillary pulmonary hypertension.

Heart failure with preserved ejection fraction (HFpEF) patients who develop pulmonary hypertension (PH) have an increased risk of death, with combined pre- and post-capillary PH (CpcPH) having the highest risk. However, the mechanism behind PH development in HFpEF is poorly understood. We aimed to identify transcriptomic associations with PH development in HFpEF. Blood was collected from 30 HFpEF patients: 10 without PH, 10 with isolated post-capillary PH, and 10 with CpcPH. Gene expression measurements were completed using transcriptome-wide RNA sequencing. Gene expression differences were compared using a quasi-likelihood method adjusting for age, sex, race, and smoking-status. Biological pathways were compared using global gene expression differences. A replication in 34 additional heart failure patients and a validation in lung tissue from a representative mouse model were completed using quantitative PCR. Six differentially expressed genes were identified when comparing transcriptomics between subjects with CpcPH and those without PH. When tested in additional subjects, only the association with ID2 replicated. Consistent with clinical findings, Id2 expression was also upregulated in mice with HFpEF and PH. Pathway analysis identified proliferative and mitochondrial pathways associated with CpcPH. Thus, these patients may possess systemic pathophysiological differences similar to those observed in pulmonary arterial hypertension patients.

A stepwise approach to implementing pharmacogenetic testing in the primary care setting.

Pharmacogenetic testing can help identify primary care patients at increased risk for medication toxicity, poor response or treatment failure and inform drug therapy. While testing availability is increasing, providers are unprepared to routinely use pharmacogenetic testing for clinical decision-making. Practice-based resources are needed to overcome implementation barriers for pharmacogenetic testing in primary care.The NHGRI's IGNITE I Network (Implementing GeNomics In pracTicE; www.ignite-genomics.org) explored practice models, challenges and implementation barriers for clinical pharmacogenomics. Based on these experiences, we present a stepwise approach pharmacogenetic testing in primary care: patient identification; pharmacogenetic test ordering; interpretation and application of test results, and patient education. We present clinical factors to consider, test-ordering processes and resources, and provide guidance to apply test results and counsel patients. Practice-based resources such as this stepwise approach to clinical decision-making are important resources to equip primary care providers to use pharmacogenetic testing.

IGNITE network: Response of patients to genomic medicine interventions.

BACKGROUND: The IGNITE network funds six genomic medicine projects. Though interventions varied, we hypothesized that synergies across projects could be leveraged to better understand the participant experiences with genomic medicine interventions. Therefore, we performed cross-network analyses to identify associations between participant demographics and attitudes toward the intervention (attitude), plan to share results (share), and quality of life (QOL). METHODS: Data collection for demographics, attitude, share, and QOL surveys were standardized across projects. Recruitment and survey administration varied by each project's protocol. RESULTS: Participants (N = 6,817) were 67.2% (N = 4,584) female, and 37.4% (N = 3,544) were minority. Mean age = 54.0 (sd 14.a). Younger participants were as follows: (1) more positive in attitude pre-intervention (1.15-fold decrease/10-year age increase (OR)) and more negative after (1.14-fold increase OR); (2) higher in QOL pre-intervention (1.07-fold increase OR) and postintervention; (3) more likely to share results (1.12-fold increase OR). Race was significant when sharing results (white participants increased OR = 1.88), but not for change in QOL pre-postintervention or attitude. CONCLUSION: Our findings demonstrate the feasibility of this approach and identified a few key themes which are as follows: age was consistently significant across the three outcomes, whereas race had less of an impact than expected. However, these are only associations and thus warrant further study.

Endothelial nitric oxide synthase genotype is associated with pulmonary hypertension severity in left heart failure patients.

The biological mechanisms behind the development of pulmonary hypertension in the setting of left heart failure (HF-PH), including combined pre- and post-capillary pulmonary hypertension (Cpc-PH), remains unclear. This study aimed to use candidate polymorphisms in nitric oxide synthase (NOS) genes to explore the role of NOS in HF-PH. DNA samples from 118 patients with HF-PH were genotyped for the NOS3 rs1799983 and NOS2 rs3730017 polymorphisms. A multiple regression model was used to compare hemodynamic measurements between genotype groups. Patients with the T/T genotype at rs1799983 possessed a nearly 10 mmHg increased transpulmonary gradient (TPG) compared to those with other genotypes ( P = 0.006). This finding was replicated in an independent cohort of 94 HF-PH patients ( P = 0.005). However, when tested in a cohort of 162 pre-capillary pulmonary arterial hypertension patients, no association was observed. In a combined analysis of both HF-PH cohorts, mean pulmonary artery pressure (mPAP), diastolic pulmonary gradient (DPG), and CpcPH status were also associated with rs1799983 genotype ( P = 0.005, P = 0.03, and P = 0.02, respectively). In patients with HF-PH, the NOS3 rs1799983 polymorphism is associated with TPG, and potentially mPAP and DPG as well. These findings suggest that endothelial NOS (encoded by NOS3) may be involved in the pulmonary vascular remodeling observed in Cpc-PH and warrants further study.

Genome Wide Association Study Identifies the HMGCS2 Locus to be Associated With Chlorthalidone Induced Glucose Increase in Hypertensive Patients.

BACKGROUND: Thiazide and thiazide-like diuretics are first-line medications for treating uncomplicated hypertension. However, their use has been associated with adverse metabolic events, including hyperglycemia and incident diabetes mellitus, with incompletely understood mechanisms. Our goal was to identify genomic variants associated with thiazide-like diuretic/chlorthalidone-induced glucose change. METHODS AND RESULTS: Genome-wide analysis of glucose change after treatment with chlorthalidone was performed by race among the white (n=175) and black (n=135) participants from the PEAR-2 (Pharmacogenomic Evaluation of Antihypertensive Responses-2). Single-nucleotide polymorphisms with P<5×10-8 were further prioritized using in silico analysis based on their expression quantitative trait loci function. Among blacks, an intronic single-nucleotide polymorphism (rs9943291) in the HMGCS2 was associated with increase in glucose levels following chlorthalidone treatment (ß=12.5; P=4.17×10-8). G-allele carriers of HMGCS2 had higher glucose levels (glucose change=+16.29 mg/dL) post chlorthalidone treatment compared with noncarriers of G allele (glucose change=+2.80 mg/dL). This association was successfully replicated in an independent replication cohort of hydrochlorothiazide-treated participants from the PEAR study (ß=5.54; P=0.023). A meta-analysis of the 2 studies was performed by race in Meta-Analysis Helper, where this single-nucleotide polymorphism, rs9943291, was genome-wide significant with a meta-analysis P value of 3.71×10-8. HMGCS2, a part of the HMG-CoA synthase family, is important for ketogenesis and cholesterol synthesis pathways that are essential in glucose homeostasis. CONCLUSIONS: These results suggest that HMGCS2 is a promising candidate gene involved in chlorthalidone and Hydrochlorothiazide (HCTZ)-induced glucose change. This may provide insights into the mechanisms involved in thiazide-induced hyperglycemia that may ultimately facilitate personalized approaches to antihypertensive selection for hypertension treatment. CLINICAL TRIAL REGISTRATION: URL: http://www.clinicaltrials.gov. Unique identifiers: NCT00246519 and NCT01203852.

Optimization of Voriconazole Therapy for the Treatment of Invasive Fungal Infections in Adults.

Therapeutic concentrations of voriconazole in invasive fungal infections (IFIs) are ensured using a drug monitoring approach, which relies on attainment of steady-state pharmacokinetics. For voriconazole, time to reach steady state can vary from 5-7 days, not optimal for critically ill patients. We developed a population pharmacokinetic/pharmacodynamic model-based approach to predict doses that can maximize the net benefit (probability of efficacy-probability of adverse events) and ensure therapeutic concentrations, early on during treatment. The label-recommended 200 mg voriconazole dose resulted in attainment of targeted concentrations in ≥80% patients in the case of Candida spp. infections, as compared to only 40-50% patients, with net benefit ranging from 5.8-61.8%, in the case of Aspergillus spp. infections. Voriconazole doses of 300-600 mg were found to maximize the net benefit up to 51-66.7%, depending on the clinical phenotype (due to CYP2C19 status and pantoprazole use) of the patient and type of Aspergillus infection.

Pharmacogenomics of hypertension and heart disease.

Heart disease is a leading cause of death in the United States, and hypertension is a predominant risk factor. Thus, effective blood pressure control is important to prevent adverse sequelae of hypertension, including heart failure, coronary artery disease, atrial fibrillation, and ischemic stroke. Over half of Americans have uncontrolled blood pressure, which may in part be explained by interpatient variability in drug response secondary to genetic polymorphism. As such, pharmacogenetic testing may be a supplementary tool to guide treatment. This review highlights the pharmacogenetics of antihypertensive response and response to drugs that treat adverse hypertension-related sequelae, particularly coronary artery disease and atrial fibrillation. While pharmacogenetic evidence may be more robust for the latter with respect to clinical implementation, there is increasing evidence of genetic variants that may help predict antihypertensive response. However, additional research and validation are needed before clinical implementation guidelines for antihypertensive therapy can become a reality.

Alteration in fasting glucose after prolonged treatment with a thiazide diuretic.

AIMS: Thiazide diuretics are recommended as first line antihypertensive treatment, but may contribute to new onset diabetes. We aimed to describe change in fasting glucose (FG) during prolonged thiazide treatment in an observational setting. METHODS: We conducted an observational, non-randomized, open label, follow-up study of the Pharmacogenomic Evaluation of Antihypertensive Responses (PEAR) and PEAR-2 studies. We enrolled previous participants from the PEAR or PEAR-2 studies with at least 6 months of continuous treatment with either hydrochlorothiazide (HCTZ) or chlorthalidone. Linear regression was used to identify associations with changes in FG after prolonged thiazide and thiazide-like diuretic treatment. RESULTS: A total of 40 participants were included with a mean 29 (range 8-72) months of thiazide treatment. FG increased 6.5 (SD 13.0) mg/dL during short-term thiazide treatment and 3.6 (SD 15.3) mg/dL FG during prolonged thiazide treatment. Increased FG at follow-up was associated with longer thiazide treatment duration (ß=0.34, p=0.008) and lower baseline FG (ß=-0.46, p=0.02). ß blocker treatment in combination with prolonged thiazide diuretic treatment was also associated with increased FG and increased 2-h glucose obtained from OGTT. CONCLUSIONS: Our results indicate that prolonged thiazide treatment duration is associated with increased FG and that overall glycemic status worsens when thiazide/thiazide-like diuretics are combined with ß blockers.

Impact of TCF7L2 single nucleotide polymorphisms on hydrochlorothiazide-induced diabetes.

OBJECTIVE: Thiazide diuretics have been associated with increased risk for new onset diabetes (NOD), but pharmacogenetic markers of thiazide-induced NOD are not well studied. Single nucleotide polymorphisms (SNPs) in the transcription factor 7-like 2 gene (TCF7L2) represent the strongest and most reproducible genetic associations with diabetes. We investigated the association of tag SNPs in TCF7L2 with thiazide-induced NOD. METHODS: We identified cases that developed NOD and age, sex, and race/ethnicity-matched controls from the INternational VErapamil SR-Trandolapril STudy (INVEST). INVEST compared cardiovascular outcomes between two antihypertensive treatment strategies in ethnically diverse patients with hypertension and coronary artery disease. We genotyped 101 TCF7L2 tag SNPs and used logistic regression to test for pharmacogenetic (SNP×hydrochlorothiazide treatment) interactions. Permuted interaction P values were corrected with the PACT test and adjusted for diabetes-related variables. RESULTS: In INVEST whites, we observed three TCF7L2 SNPs with significant SNP×treatment interactions for NOD. The strongest pharmacogenetic interaction was observed for rs7917983 [synergy index 3.37 (95% CI 1.72-6.59), P=5.0×10, PACT=0.03], which was associated with increased NOD risk in hydrochlorothiazide-treated patients [odds ratio 1.53 (1.04-2.25), P=0.03] and decreased NOD risk in non hydrochlorothiazide-treated patients [odds ratio 0.48 (0.27-0.86), P=0.02]. The TCF7L2 SNP rs4506565, previously associated with diabetes, showed a similar, significant pharmacogenetic association. CONCLUSION: Our results suggest that hydrochlorothiazide treatment is an environmental risk factor that increases diabetes risk beyond that attributed to TCF7L2 variation in white, hypertensive patients. Further study and replication of our results is needed to confirm pharmacogenetic influences of TCF7L2 SNPs on thiazide-induced NOD.