Patients with geographic barriers to health care access are prescribed a higher proportion of drugs with pharmacogenetic testing guidelines.

Pharmacogenetic (PGx) testing may be particularly beneficial in medically underserved populations by reducing the number of appointments required to optimize drug therapy and increasing the effectiveness of less expensive off-patent drugs. The objective of this study was to identify patient populations with poor health care access and assess prescribing trends for drugs with published PGx testing guidelines. We used electronic health record data from 67,753 University of Florida Health patients, geographic access scores calculated via the 2-step floating catchment area method, and a composite measure of socioeconomic status. Comparing the poorest (Q4) and greatest (Q1) access score quartiles, poor geographic access was significantly associated with fewer prescriber encounters (incidence rate ratio [IRR] 0.88, 95% confidence interval [CI] 0.86-0.91), fewer total unique drugs (IRR 0.92, 95% CI 0.9-0.95), and fewer PGx guideline drugs (IRR 0.94, 95% CI 0.9-0.99). After correcting for number of unique drugs, patients in low-access areas were prescribed a greater proportion of PGx guideline drugs (IRR 1.08, 95% CI 1.04-1.13). We detected significant interactions between Black race and access score. Compared to Q1, Black patients with Q4 access scores were disproportionately affected and had fewer encounters (IRR 0.76, 95% CI 0.7-0.82) and a higher proportion of PGx drugs (IRR 1.26, 95% CI 1.13-1.41), creating further disparity. Overall, these results suggest that improved geographic access to PGx testing may allow prescribers to make more efficient use of limited opportunities to optimize therapy for drugs with PGx testing guidelines.

Impact of study design and statistical model in pharmacogenetic studies with gene-treatment interaction.

Gene-treatment interactions, just like drug-drug interactions, can have dramatic effects on a patient response and therefore influence the clinician decision at the patient's bedside. Crossover designs, although they are known to decrease the number of subjects in drug-interaction studies, are seldom used in pharmacogenetic studies. We propose to evaluate, via realistic clinical trial simulations, to what extent crossover designs can help quantifying the gene-treatment interaction effect. We explored different scenarios of crossover and parallel design studies comparing two symptom-modifying treatments in a chronic and stable disease accounting for the impact of a one gene and one gene-treatment interaction. We varied the number of subjects, the between and within subject variabilities, the gene polymorphism frequency and the effect sizes of the treatment, gene, and gene-treatment interaction. Each simulated dataset was analyzed using three models: (i) estimating only the treatment effect, (ii) estimating the treatment and the gene effects, and (iii) estimating the treatment, the gene, and the gene-treatment interaction effects. We showed how ignoring the gene-treatment interaction results in the wrong treatment effect estimates. We also highlighted how crossover studies are more powerful to detect a treatment effect in the presence of a gene-treatment interaction and more often lead to correct treatment attribution.

Assessment of the Implementation of Pharmacogenomic Testing in a Pediatric Tertiary Care Setting.

Importance: Pharmacogenomic (PGx) testing provides preemptive pharmacotherapeutic guidance regarding the lack of therapeutic benefit or adverse drug reactions of PGx targeted drugs. Pharmacogenomic information is of particular value among children with complex medical conditions who receive multiple medications and are at higher risk of developing adverse drug reactions. Objectives: To assess the implementation outcomes of a PGx testing program comprising both a point-of-care model that examined targeted drugs and a preemptive model informed by whole-genome sequencing that evaluated a broad range of drugs for potential therapy among children in a pediatric tertiary care setting. Design, Setting, and Participants: This cohort study was conducted at The Hospital for Sick Children in Toronto, Ontario, from January 2017 to September 2020. Pharmacogenomic analyses were performed among 172 children who were categorized into 2 groups: a point-of-care cohort and a preemptive cohort. The point-of-care cohort comprised 57 patients referred to the consultation clinic for planned therapy with PGx targeted drugs and/or for adverse drug reactions, including lack of therapeutic benefit, after the receipt of current or past medications. The preemptive cohort comprised 115 patients who received exploratory whole-genome sequencing-guided PGx testing for their heart conditions from the cardiac genome clinic at the Ted Rogers Centre for Heart Research. Exposures: Patients received PGx analysis of whole-genome sequencing data and/or multiplex genotyping of 6 pharmacogenes (CYP2C19, CYP2C9, CYP2D6, CYP3A5, VKORC1, and TPMT) that have established PGx clinical guidelines. Main Outcomes and Measures: The number of patients for whom PGx test results warranted deviation from standard dosing regimens. Results: A total of 172 children (mean [SD] age, 8.5 [5.6] years; 108 boys [62.8%]) were enrolled in the study. In the point-of-care cohort, a median of 2 target genes (range, 1-5 genes) were investigated per individual, with CYP2C19 being the most frequently examined; genotypes in 21 of 57 children (36.8%) were incompatible with standard treatment regimens. As expected from population allelic frequencies, among the 115 children in the whole-genome sequencing-guided preemptive cohort, 92 children (80.0%) were recommended to receive nonstandard treatment regimens for potential drug therapies based on their 6-gene pharmacogenetic profile. Conclusions and Relevance: In this cohort study, among both the point-of-care and preemptive cohorts, the multiplex PGx testing program provided dosing recommendations that deviated from standard regimens at an overall rate that was similar to the population frequencies of relevant variants.

Molecular Biomarker and Programmed Death-Ligand 1 Expression Testing in Patients With Advanced Stage Non-small Cell Lung Cancer Across North Carolina Community Hospitals.

BACKGROUND: Precision medicine in advanced non-small cell lung cancer (NSCLC) requires molecular biomarker testing in patients with nonsquamous and select patients with squamous histologies, and programmed death-ligand 1 (PD-L1) testing in both. RESEARCH QUESTION: What are rates of molecular and PD-L1 biomarker testing in patients with advanced NSCLC in community practices, and do rates vary by sociodemographic factors? What is the prevalence of molecular biomarker mutations and PD-L1 expression levels? STUDY DESIGN AND METHODS: From 389 stage IV NSCLC pathology reports obtained through the University of North Carolina Lineberger Comprehensive Cancer Center's Rapid Case Ascertainment Program from 38 community hospitals across North Carolina, we abstracted demographics, histology, molecular biomarker testing and results, and PD-L1 testing and expression. We geocoded patient and hospital addresses to determine travel time, distance to care, and census block level contextual variables. We compared molecular biomarker and PD-L1 testing rates, the prevalence of molecular biomarkers, and PD-L1 expression levels by race and sex, using χ2 tests. We determined predictors of testing, using multivariable logistic regression and report adjusted ORs and 95%CI. RESULTS: Among patients with nonsquamous NSCLC, 64.4% were tested for molecular biomarkers, and among all NSCLC patients 53.2% were tested for PD-L1 expression. Differences in biomarker testing rates by sociodemographic factors were not statistically significant in univariate or adjusted analyses. Adjusted analyses showed that patients living in areas with higher household internet access were more likely to undergo PD-L1 testing (adjusted OR = 1.66, 95% CI, 1.02-2.71). Sociodemographic differences in molecular biomarker prevalence and PD-L1 expression levels were not statistically significant, except for human epidermal growth factor receptor 2 (HER2) mutations, which occurred in 16.7% of males vs 0% in females, P = .05. INTERPRETATION: Biomarker testing remains underused in NSCLC. Future work should include larger populations and evaluate hospital-specific testing protocols to identify and address barriers to guideline-recommended testing.

Pharmacogenomic testing for mental health (Part I): documenting early adopter perceptions of use for eight scenarios.

Aim: We sought to understand how early adopters used pharmacogenomic (PGx) testing for treating depression and attention deficient hyperactivity disorder (ADHD). Patients & methods: We conducted a phone survey with prescribers who had previously ordered an Informed PGx (Progenity, Inc., MI, USA) test. Results: We identified 1037 prescribers in our sampling period. Respondents (n = 64) were predominantly female (61.5%) and in pediatrics (n = 42; 64.6%). PGx testing was used for multiple scenarios (mean 3.3 ± 1.6); the most common was after no response to medication was observed (80%; 51/64). Most respondents state that test results typically reveal an altered metabolizer status. Conclusion: PGx test results ordered by early adopters often reveal altered metabolizers which leads them to change the depression/ADHD medication regimen. Future work should evaluate the clinical utility of PGx testing for depression/ADHD treatment.

Pharmacogenomic testing for mental health (Part II): qualitative analysis of early adopter prescriber perceptions.

Aim: We sought to explore how early adopters use pharmacogenomic (PGx) testing for treating depression and attention-deficit/hyperactivity disorder. Patients & methods: Prescribers of the Informed PGx (Progenity, Inc., Ann Arbor, MI 48108, USA) test completed a phone survey assessing use of PGx testing for different scenarios. We conducted a qualitative thematic text analysis of transcribed audio recordings of open-ended responses (n = 62). Results: PGx testing was used when treating multiple comorbidities or resistant disease, and to ease patients' concerns with future therapy. Use of PGx testing is influenced by insurance coverage, interpretability of results and results turnaround time. Conclusion: Prescribers used PGx tests to modify medications for complex patients with depression, attention-deficit/hyperactivity disorder and other disorders to alleviate concerns related to adverse effects and lack of effectiveness.

Rates of genetic testing in patients prescribed drugs with pharmacogenomic information in FDA-approved labeling.

This study examined rates of genetic testing in two cohorts of publicly insured individuals who have newly prescribed medication with FDA pharmacogenomic labeling guidance. Genetic testing was rare (4.4% and 10.5% in Medicaid and Medicare cohorts, respectively) despite the fact that all participants selected were taking medications that contained pharmacogenomic labeling information. When testing was conducted it was typically done before the initial use of a target medication. Factors that emerged as predictors of the likelihood of undergoing genetic testing included White ethnicity (vs. Black), female gender, and age. Cost analyses indicated higher expenditures in groups receiving genetic testing vs. matched comparators with no genetic testing, as well as disparities between proactively and reactively tested groups (albeit in opposite directions across cohorts). Results are discussed in terms of the possible reasons for the low base rate of testing, mechanisms of increased cost, and barriers to dissemination and implementation of these tests.

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.

Retrospective Review of Pharmacogenetic Testing at an Academic Children's Hospital.

There is limited evidence to support pharmacogenetic (PGx) testing in children. We conducted a retrospective review of PGx testing among 452 patients at an academic children's hospital to determine the potential utility of PGx in diseases of childhood and to identify targets for future pediatric pharmacogenetic research. An actionable gene-drug pair associated with the 28 genes tested (Clinical Pharmacogenetics Implementation Consortium (CPIC) level A or B, Pharmacogenomics Knowledge Base (PharmGKB) level 1A or B, or US Food and Drug Administration (FDA) recommendation and a PharmGKB level) was present in 98.7% of patients. We identified 203 actionable gene-drug-diagnosis groups based on the indications for each actionable drug listed in Lexicomp. Among patients with an actionable gene-drug-diagnosis group, 49.3% had a diagnosis where the drug was a therapeutic option and PGx could be used to guide treatment selection. Among patients with an associated diagnosis, 30.9% had a prescription for the actionable drug allowing PGx guided dosing. Three genes (CYP2C19, CYP2D6, and CYP3A5) accounted for all the gene-drug-diagnosis groups with matching diagnoses and prescriptions. The most common gene-drug-diagnosis groups with matching diagnoses and prescriptions were CYP2C19-citalopram-escitalopram-depression 3.3% of patients tested; CYP2C19-dexlansoprazole-gastritis-esophagitis 3.1%; CYP2C19-omeprazole-gastritis-esophagitis 2.4%; CYP2D6-atomoxetine-attention deficit hyperactivity disorder 2.2%; and CYP2C19-citalopram-escitalopram-obsessive-compulsive disorder 1.5%. PGx could be used to guide selection of current treatment options or medication dosing in almost half (48.7%) of pediatric patients tested. Mood disorders and gastritis/esophagitis are promising targets for future study of PGx testing because of the high prevalence of these diagnoses and associated actionable gene-drug pairs in the pediatric population.

Multi-site Investigation of Genetic Determinants of Warfarin Dose Variability in Latinos.

We conducted a multi-site investigation of genetic determinants of warfarin dose variability in Latinos from the U.S. and Brazil. Patients from four institutions in the United States (n = 411) and Brazil (n = 663) were genotyped for VKORC1 c.-1639G> A, common CYP2C9 variants, CYP4F2*3, and NQO1*2. Multiple regression analysis was used in the U.S. cohort to test the association between warfarin dose and genotype, adjusting for clinical factors, with further testing in an independent cohort of Brazilians. In the U.S. cohort, VKORC1 and CYP2C9 variants were associated with lower warfarin dose (ß = -0.29, P < 2.0 × 10-16 ; ß = -0.21, P = 4.7 × 10-7 , respectively) whereas CYP4F2 and NQO1 variants were associated with higher dose (ß = 0.10, P = 2 × 10-4 ; ß = 0.10, P = 0.01, respectively). Associations with VKORC1 (ß = -0.14, P = 2.0 × 10-16 ), CYP2C9 (ß = -0.07, P = 5.6 × 10-10 ), and CYP4F2 (ß = 0.03, P = 3 × 10-3 ), but not NQO1*2 (ß = 0.01, P = 0.30), were replicated in the Brazilians, explaining 43-46% of warfarin dose variability among the cohorts from the U.S. and Brazil, respectively. We identified genetic associations with warfarin dose requirements in the largest cohort of ancestrally diverse, warfarin-treated Latinos from the United States and Brazil to date. We confirmed the association of variants in VKORC1, CYP2C9, and CYP4F2 with warfarin dose in Latinos from the United States and Brazil.

The Translational Approaches to Personalized Health Collaborative: Pharmacogenomics for African American Older Adults.

Older adults (i.e., 60 years and older), are the leading consumers of medications, and consequently are suffering the most from medication-related adverse events. Not only are older adults the largest consumers of medications, they are more likely to experience an adverse drug event contributing to increased hospitalization, utilization of emergency medical services, and mortality. Translational Approaches to Personalized Health (TAPH) is a transdisciplinary team of researchers conducting community-engaged participatory research focused on the discovery and translation of pharmacogenomic (PGx) data to improve health outcomes. Underserved and ethnically diverse older adults living in urban settings are significantly under-represented in PGx studies. To address the issue of under-representation, our study enrolls older African American adults into a community-based PGx study. Therefore, we will characterize the frequency of actionable PGx genotypes and identify novel PGx response genes in our cohort of older community dwelling African Americans. The translational component of our work is to use the PGx findings to improve therapeutic outcomes for medication management in older adults. Such findings will serve as a foundation for translational PGx studies aimed at improving medication efficacy and safety for older adults. In this article, we describe the process for launching the TAPH collaborative group, which includes the transdisciplinary team, community-engaged participatory research model, study measures, and the evaluation of PGx genes.

Characterizing Pharmacogenetic Testing Among Children's Hospitals.

Although pharmacogenetic testing is becoming increasingly common across medical subspecialties, a broad range of utilization and implementation exists across pediatric centers. Large pediatric institutions that routinely use pharmacogenetics in their patient care have published their practices and experiences; however, minimal data exist regarding the full spectrum of pharmacogenetic implementation among children's hospitals. The primary objective of this nationwide survey was to characterize the availability, concerns, and barriers to pharmacogenetic testing in children's hospitals in the Children's Hospital Association. Initial responses identifying a contact person were received from 18 institutions. Of those 18 institutions, 14 responses (11 complete and 3 partial) to a more detailed survey regarding pharmacogenetic practices were received. The majority of respondents were from urban institutions (72%) and held a Doctor of Pharmacy degree (67%). Among all respondents, the three primary barriers to implementing pharmacogenetic testing identified were test reimbursement, test cost, and money. Conversely, the three least concerning barriers were potential for genetic discrimination, sharing results with family members, and availability of tests in certified laboratories. Low-use sites rated several barriers significantly higher than the high-use sites, including knowledge of pharmacogenetics (P = 0.03), pharmacogenetic interpretations (P = 0.04), and pharmacogenetic-based changes to therapy (P = 0.03). In spite of decreasing costs of pharmacogenetic testing, financial barriers are one of the main barriers perceived by pediatric institutions attempting clinical implementation. Low-use sites may also benefit from education/outreach in order to reduce perceived barriers to implementation.

Clinical validation of combinatorial pharmacogenomic testing and single-gene guidelines in predicting psychotropic medication blood levels and clinical outcomes in patients with depression.

We evaluated the clinical validity of a combinatorial pharmacogenomic test and single-gene Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines against patient outcomes and medication blood levels to assess their ability to inform prescribing in major depressive disorder (MDD). This is a secondary analysis of the Genomics Used to Improve DEpression Decisions (GUIDED) randomized-controlled trial, which included patients with a diagnosis of MDD, and ≥1 prior medication failure. The ability to predict increased/decreased medication metabolism was validated against blood levels at screening (adjusted for age, sex, smoking status). The ability of predicted gene-drug interactions (pharmacogenomic test) or therapeutic recommendations (single-gene guidelines) to predict patient outcomes was validated against week 8 outcomes (17-item Hamilton Depression Rating Scale; symptom improvement, response, remission). Analyses were performed for patients taking any eligible medication (outcomes N=1,022, blood levels N=1,034) and the subset taking medications with single-gene guidelines (outcomes N=584, blood levels N=372). The combinatorial pharmacogenomic test was the only significant predictor of patient outcomes. Both the combinatorial pharmacogenomic test and single-gene guidelines were significant predictors of blood levels for all medications when evaluated separately; however, only the combinatorial pharmacogenomic test remained significant when both were included in the multivariate model. There were no substantial differences when all medications were evaluated or for the subset with single-gene guidelines. Overall, this evaluation of clinical validity demonstrates that the combinatorial pharmacogenomic test was a superior predictor of patient outcomes and medication blood levels when compared with guidelines based on individual genes.

Effect of SLCO1B1 Polymorphisms on High-Dose Methotrexate Clearance in Children and Young Adults With Leukemia and Lymphoblastic Lymphoma.

High-dose (HD) methotrexate (MTX) is a critical component of treatment for hematologic malignancies in children and young adults. Therapeutic drug monitoring is necessary due to substantial interindividual variation in MTX clearance. Common function-altering polymorphisms in SLCO1B1 (encodes OATP1B1, which transports MTX) may contribute to clearance variability. We performed pharmacokinetic modeling using data for 106 children and young adults treated with HD MTX for hematologic malignancies; of 396 total courses of HD MTX, 360 consisted of 5 g/m2 over 24 hours. We evaluated the contribution of clinical covariates and SLCO1B1 genotype (388A>G and 521T>C) to MTX clearance variability. Of the clinical covariates studied, patient weight improved the pharmacokinetic model most significantly (P < 0.001). The addition of the SLCO1B1 variants individually further improved the model (P < 0.05 for each). An interaction between these variants was suggested when both were included (P = 0.017). SLCO1B1 genotype should be considered in efforts to personalize HD MTX dosing.

Acceptability, Feasibility, and Utility of Integrating Pharmacogenetic Testing into a Child Psychiatry Clinic.

Pharmacogenetic (PGx) testing is a tool to identify patients at a higher risk of adverse events or treatment failure. The concern for unwanted side effects can limit medication adherence, particularly in children and adolescents. We conducted a pragmatic study to evaluate the acceptability and feasibility and gather pilot data on the utility of PGx testing in a child and adolescent psychiatry clinic. Both physicians and families participated in the study and answered pre-survey and post-survey questionnaires to examine their attitudes toward PGx testing. Patients were randomized into implementation (N = 25) and control groups (N = 24) and underwent PGx testing at the beginning or end of the study, respectively. Clinical consult notes with genotype-guided recommendations were provided to physicians for their consideration in clinical decisions. Patient-reported symptom severity and antidepressant-related side effects were assessed at baseline and for 12 weeks. Both participating physicians and families agreed that PGx testing is a useful tool to improve medication selection. The time from sample collection to having PGx test results was ~ 10 days and 15 days to having consult notes available, which may have impaired test utility in clinical decision making. There were no differences in any clinical end point between the implementation and control arms; however, there were higher antidepressant side effect scores for CYP2D6 poor and intermediate metabolizers after the eighth week of treatment. Our findings revealed benefits and pitfalls with the use of PGx testing in the real-world clinical setting, which may inform the methodology of a larger trial focused on outcomes.

Prescribing Prevalence of Medications With Potential Genotype-Guided Dosing in Pediatric Patients.

Importance: Genotype-guided prescribing in pediatrics could prevent adverse drug reactions and improve therapeutic response. Clinical pharmacogenetic implementation guidelines are available for many medications commonly prescribed to children. Frequencies of medication prescription and actionable genotypes (genotypes where a prescribing change may be indicated) inform the potential value of pharmacogenetic implementation. Objective: To assess potential opportunities for genotype-guided prescribing in pediatric populations among multiple health systems by examining the prevalence of prescriptions for each drug with the highest level of evidence (Clinical Pharmacogenetics Implementation Consortium level A) and estimating the prevalence of potential actionable prescribing decisions. Design, Setting, and Participants: This serial cross-sectional study of prescribing prevalences in 16 health systems included electronic health records data from pediatric inpatient and outpatient encounters from January 1, 2011, to December 31, 2017. The health systems included academic medical centers with free-standing children's hospitals and community hospitals that were part of an adult health care system. Participants included approximately 2.9 million patients younger than 21 years observed per year. Data were analyzed from June 5, 2018, to April 14, 2020. Exposures: Prescription of 38 level A medications based on electronic health records. Main Outcomes and Measures: Annual prevalence of level A medication prescribing and estimated actionable exposures, calculated by combining estimated site-year prevalences across sites with each site weighted equally. Results: Data from approximately 2.9 million pediatric patients (median age, 8 [interquartile range, 2-16] years; 50.7% female, 62.3% White) were analyzed for a typical calendar year. The annual prescribing prevalence of at least 1 level A drug ranged from 7987 to 10 629 per 100 000 patients with increasing trends from 2011 to 2014. The most prescribed level A drug was the antiemetic ondansetron (annual prevalence of exposure, 8107 [95% CI, 8077-8137] per 100 000 children). Among commonly prescribed opioids, annual prevalence per 100 000 patients was 295 (95% CI, 273-317) for tramadol, 571 (95% CI, 557-586) for codeine, and 2116 (95% CI, 2097-2135) for oxycodone. The antidepressants citalopram, escitalopram, and amitriptyline were also commonly prescribed (annual prevalence, approximately 250 per 100 000 patients for each). Estimated prevalences of actionable exposures were highest for oxycodone and ondansetron (>300 per 100 000 patients annually). CYP2D6 and CYP2C19 substrates were more frequently prescribed than medications influenced by other genes. Conclusions and Relevance: These findings suggest that opportunities for pharmacogenetic implementation among pediatric patients in the US are abundant. As expected, the greatest opportunity exists with implementing CYP2D6 and CYP2C19 pharmacogenetic guidance for commonly prescribed antiemetics, analgesics, and antidepressants.

Interplay Between Statins, Cav1 (Caveolin-1), and Aldosterone.

Statin use is associated with lower aldosterone levels. We hypothesized that caveolin-1 may be important for the uptake of statins into the adrenal gland and would affect statin's aldosterone-lowering effects. The aim of this study was to test whether the caveolin-1 risk allele (rs926198) would affect aldosterone levels associated with statin use. The Hypertensive Pathotype database includes healthy and hypertensive individuals who have undergone assessment of adrenal hormones. Individuals were studied off antihypertensive medications but were maintained on statins if prescribed by their personal physician. Adrenal hormones were measured at baseline and after 1 hour of angiotensin II stimulation on both high- and low-sodium diets. A mixed-model repeated-measures analysis was employed with a priori selected covariates of age, sex, body mass index, and protocol (low versus high sodium, baseline versus angiotensin II stimulated aldosterone). A total of 250 individuals were included in the study; 31 individuals were taking statins (12.4%) and 219 were not. Among statin users, carrying a caveolin-1 risk allele resulted in a 25% (95% CI, 1-43.2) lower aldosterone level (P=0.04). However, among nonstatin users, carrying a caveolin-1 risk allele resulted in no significant effect on aldosterone levels (P=0.38). Additionally, the interaction between caveolin-1 risk allele and statin use on aldosterone levels was significant (P=0.03). These findings suggest caveolin-1 risk allele carrying individuals are likely to receive the most benefit from statin's aldosterone-lowering properties; however, due to the observational nature of this study, these findings need further investigation.

A Genome-Wide Pharmacogenetic Study of Growth Hormone Responsiveness.

CONTEXT: Individual patients vary in their response to growth hormone (GH). No large-scale genome-wide studies have looked for genetic predictors of GH responsiveness. OBJECTIVE: To identify genetic variants associated with GH responsiveness. DESIGN: Genome-wide association study (GWAS). SETTING: Cohorts from multiple academic centers and a clinical trial. PATIENTS: A total of 614 individuals from 5 short stature cohorts receiving GH: 297 with idiopathic short stature, 276 with isolated GH deficiency, and 65 born small for gestational age. INTERVENTION: Association of more than 2 million variants was tested. MAIN OUTCOME MEASURES: Primary analysis: individual single nucleotide polymorphism (SNP) association with first-year change in height standard deviation scores. Secondary analyses: SNP associations in clinical subgroups adjusted for clinical variables; association of polygenic score calculated from 697 genome-wide significant height SNPs with GH responsiveness. RESULTS: No common variant associations reached genome-wide significance in the primary analysis. The strongest suggestive signals were found near the B4GALT4 and TBCE genes. After meta-analysis including replication data, signals at several loci reached or retained genome-wide significance in secondary analyses, including variants near ST3GAL6. There was no significant association with variants previously reported to be associated with GH response nor with a polygenic predicted height score. CONCLUSIONS: We performed the largest GWAS of GH responsiveness to date. We identified 2 loci with a suggestive effect on GH responsiveness in our primary analysis and several genome-wide significant associations in secondary analyses that require further replication. Our results are consistent with a polygenic component to GH responsiveness, likely distinct from the genetic regulators of adult height.

CYP2C19 Allele Frequencies in Over 2.2 Million Direct-to-Consumer Genetics Research Participants and the Potential Implication for Prescriptions in a Large Health System.

Understanding the prevalence of clinically relevant pharmacogenetic variants using large unselected populations is critical for gauging the potential clinical impact of widespread preemptive pharmacogenetic testing. To this end, we assessed the frequencies and ethnic distribution of the three most common CYP2C19 alleles (*2, *3, and *17) in 2.29 million direct-to-consumer genetics research participants (23andMe, Sunnyvale, CA). The overall frequencies of *2, *3, and *17 were 15.2%, 0.3%, and 20.4%, respectively, but varied by ethnicity. The most common variant diplotypes were *1/*17 at 26% and *1/*2 at 19.4%. The less common *2/*17, *17/*17, and *2/*2 genotypes occurred at 6.0%, 4.4%, and 2.5%, respectively. Overall, 58.3% of participants had at least one increased-function or no-function CYP2C19 allele. To better understand how this high frequency might impact a real patient population, we examined the prescription rates (Rx) of high-pharmacogenetic-risk medications metabolized by CYP2C19 using the University of California at San Francisco (UCSF) health system's anonymized database of over 1.25 million patients. Between 2012 and 2019, a total of 151,068 UCSF patients (15.8%) representing 5 self-reported ethnicities were prescribed one or more high-pharmacogenetic-risk CYP2C19 medications: proton pump inhibitors (145,243 Rx), three selective serotonin reuptake inhibitor antidepressants (54,463 Rx), clopidogrel (14,376 Rx), and voriconazole (2,303 Rx).