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Statin drugs lower blood cholesterol levels for cardiovascular disease prevention. Women are more likely than men to experience adverse statin effects, particularly new-onset diabetes (NOD) and muscle weakness. Here we find that impaired glucose homeostasis and muscle weakness in statin-treated female mice are associated with reduced levels of the omega-3 fatty acid, docosahexaenoic acid (DHA), impaired redox tone, and reduced mitochondrial respiration. Statin adverse effects are prevented in females by administering fish oil as a source of DHA, by reducing dosage of the X chromosome or the Kdm5c gene, which escapes X chromosome inactivation and is normally expressed at higher levels in females than males. As seen in female mice, we find that women experience more severe reductions than men in DHA levels after statin administration, and that DHA levels are inversely correlated with glucose levels. Furthermore, induced pluripotent stem cells from women who developed NOD exhibit impaired mitochondrial function when treated with statin, whereas cells from men do not. These studies identify X chromosome dosage as a genetic risk factor for statin adverse effects and suggest DHA supplementation as a preventive co-therapy.

Abstract Statin drugs lower blood cholesterol levels for cardiovascular disease prevention. Women are more likely than men to experience adverse statin effects, particularly new-onset diabetes (NOD) and muscle weakness. Here we find that impaired glucose homeostasis and muscle weakness in statin-treated female mice are associated with reduced levels of the omega-3 fatty acid, docosahexaenoic acid (DHA), impaired redox tone, and reduced mitochondrial respiration. Statin adverse effects are prevented in females by administering fish oil as a source of DHA, by reducing dosage of the X chromosome or the Kdm5c gene, which escapes X chromosome inactivation and is normally expressed at higher levels in females than males. As seen in female mice, we find that women experience more severe reductions than men in DHA levels after statin administration, and that DHA levels are inversely correlated with glucose levels. Furthermore, induced pluripotent stem cells from women who developed NOD exhibit impaired mitochondrial function when treated with statin, whereas cells from men do not. These studies identify X chromosome dosage as a genetic risk factor for statin adverse effects and suggest DHA supplementation as a preventive co-therapy.

Pharmacogenetics can improve clinical outcomes by reducing adverse drug effects and enhancing therapeutic efficacy for commonly used drugs that treat a wide range of cardiovascular diseases. One of the major barriers to the clinical implementation of cardiovascular pharmacogenetics is limited education on this field for current healthcare providers and students. The abundance of pharmacogenetic literature underscores its promise, but it can also be challenging to learn such a wealth of information. Moreover, current clinical recommendations for cardiovascular pharmacogenetics can be confusing because they are outdated, incomplete, or inconsistent. A myriad of misconceptions about the promise and feasibility of cardiovascular pharmacogenetics among healthcare providers also has halted clinical implementation. Therefore, the main goal of this tutorial is to provide introductory education on the use of cardiovascular pharmacogenetics in clinical practice. The target audience is any healthcare provider (or student) with patients that use or have indications for cardiovascular drugs. This tutorial is organized into the following 6 steps: (1) understand basic concepts in pharmacogenetics; (2) gain foundational knowledge of cardiovascular pharmacogenetics; (3) learn the different organizations that release cardiovascular pharmacogenetic guidelines and recommendations; (4) know the current cardiovascular drugs/drug classes to focus on clinically and the supporting evidence; (5) discuss an example patient case of cardiovascular pharmacogenetics; and (6) develop an appreciation for emerging areas in cardiovascular pharmacogenetics. Ultimately, improved education among healthcare providers on cardiovascular pharmacogenetics will lead to a greater understanding for its potential in improving outcomes for a leading cause of morbidity and mortality.

INTRODUCTION: Non-Hispanic Black men experience a disproportionate rate of morbidity and mortality from hypertension, cardiovascular disease, and other chronic conditions in the United States. Studies have demonstrated the efficacy of community-based health outreach in settings not traditionally utilized for health care. Understanding how potential future participants view health care services in nontraditional settings is a necessary step to ascertain the success of these interventions in the real world. Our study objective was to explore the preferences of Black male barbershop patrons regarding health care-provided services in these nontraditional settings. METHODS: We recruited patrons of a Black-owned barbershop in the San Francisco Bay Area. Study participants were asked to complete a survey assessing individual attitudes and preferences toward the idea of receiving health care services in traditional and nontraditional settings. RESULTS: Among non-Hispanic Black males (n=17), 81% agreed or strongly agreed that they would prefer to receive health care in traditional clinics. Receiving care at the pharmacy (56% agreed or strongly agreed) and the patients own home (53% agreed or strongly agreed) were the next most preferred locations. A minority of participants agreed or strongly agreed that they preferred to receive health care in nontraditional settings: 47% for barbershops, 19% for churches, and 6% for grocery stores. DISCUSSION: Participants expressed preference for traditional over nontraditional settings, despite listing barriers that may be addressed, in part, by nontraditional settings. One potential reason for this is simply a lack of familiarity. Establishing and normalizing nontraditional clinical settings may allow for enhanced acceptance within Black communities, ultimately increasing health care access.

BackgroundPrior studies of the glycemic effect of statins have been inconsistent. Also, most studies have only considered a short duration of statin use; the effect of long-term statin use on fasting glucose (FG) has not been well examined. The aim of this work is to investigate the effect of long-term statin exposure on FG levels.MethodsUsing electronic health record (EHR) data from a large and diverse longitudinal cohort, we defined long-term statin exposure in two ways: the cumulative years of statin use (cumulative supply) and the years' supply-weighted sum of doses (cumulative dose). Simvastatin, lovastatin, atorvastatin and pravastatin were included in the analysis. The relationship between statin exposure and FG was examined using linear regression with mixed effects modeling, comparing statin users before and after initiating statins and statin never-users.ResultsWe examined 593,130 FG measurements from 87,151 individuals over a median follow up of 20 years. Of these, 42,678 were never-users and 44,473 were statin users with a total of 730,031 statin prescriptions. FG was positively associated with cumulative supply of statin but not comulative dose when both measures were in the same model. While statistically significant, the annual increase in FG attributable to statin exposure was modest at only 0.14 mg/dl, with only slight and non-significant differences among statin types.ConclusionsElevation in FG level is associated with statin exposure, but the effect is modest. The results suggest that the risk of a clinically significant increase in FG attributable to long-term statin use is small for most individuals.

Genetic substudies of randomized controlled trials demonstrate that high coronary heart disease (CHD) polygenic risk score modifies statin CHD relative risk reduction; it is unknown if the association extends to statin users undergoing routine care. We sought to determine how statin effectiveness is modified by CHD polygenic risk score in a real-world cohort of participants without previous myocardial infarction. We determined CHD polygenic risk scores in participants of the Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort. Covariate-adjusted Cox regression models were used to compare the risk of cardiovascular outcomes between statin users and matched nonusers. Statin effectiveness on incident myocardial infarction showed no gradient with increasing 10-year Pooled Cohort Equations atherosclerotic cardiovascular disease (ASCVD) risk across low, borderline, intermediate, and high ASCVD risk score groups. In contrast, statin effectiveness by polygenic risk was largest in the high polygenic risk score group (hazard ratio (HR) 0.41, 95% confidence interval (CI), 0.31-0.53; P = 1.5E-11), intermediate in the intermediate polygenic risk score group (HR 0.56, 95% CI, 0.47-0.66; P = 8.4E-12), and smallest in the low polygenic risk score group (HR 0.67, 95% CI, 0.47-0.97; P = 0.03; P for high vs. low = 0.01). ASCVD risk and statin low-density lipoprotein cholesterol (LDL-C) lowering did not differ across polygenic risk score groups. In patients undergoing routine care, CHD polygenic risk modified statin relative risk reduction of incident myocardial infarction independent of LDL-C lowering. Our findings extend prior work by identifying a subset (i.e., self-identified White individuals with low CHD polygenic risk scores) with attenuated clinical benefit from statins.

The COVID-19 pandemic has overwhelmed health systems around the globe, and intensified the lethality of social and political inequality. In the United States, where public health departments have been severely defunded, Black, Native, Latinx communities and those experiencing poverty in the country's largest cities are disproportionately infected and disproportionately dying. Based on our collective ethnographic work in three global cities in the U.S. (San Francisco, Los Angeles, and Detroit), we identify how the political geography of racialisation potentiated the COVID-19 crisis, exacerbating the social and economic toll of the pandemic for non-white communities, and undercut the public health response. Our analysis is specific to the current COVID19 crisis in the U.S, however the lessons from these cases are important for understanding and responding to the corrosive political processes that have entrenched inequality in pandemics around the world.

The new Pharmacogenomics Global Research Network (PGRN) is an independent society that builds on the National Institutes of Health (NIH)–funded Pharmacogenomics Research Network that was established in 2000. Leveraging the original PGRN’s previous success, the new network continues to be a leader in the field of personalized medicine focusing on research, discovery, and translation of genomic variation influencing drug efficacy and adverse events, while simultaneously increasing inclusion in the field and expanding globally.

The association between the c.521T>C variant allele in SLCO1B1 (reference single nucleotide polymorphism (rs)4149056) and simvastatin-induced myotoxicity was discovered over a decade ago; however, whether this relationship represents a class effect is still not fully known. The aim of this study was to investigate the relationship between rs4149056 genotype and statin-induced myotoxicity in patients taking atorvastatin and lovastatin. Study participants were from the Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort. A total of 233 statin-induced myopathy + rhabdomyolysis cases met the criteria for inclusion and were matched to 2,342 controls. To validate the drug response phenotype, we replicated the previously established association between rs4149056 genotype and simvastatin-induced myotoxicity. In particular, compared with homozygous T allele carriers, there was a significantly increased risk of simvastatin-induced myopathy + rhabdomyolysis in homozygous carriers of the C allele (CC vs. TT, odds ratio [OR] 4.62, 95% confidence interval [CI] 1.58-11.90, P = 0.003). For lovastatin users, homozygous carriers of the C allele were also at increased risk of statin-induced myopathy + rhabdomyolysis (CC vs. TT, OR 4.49, 95% CI 1.68-10.80, P = 0.001). In atorvastatin users, homozygous carriers of the C allele were twice as likely to experience statin-induced myopathy, though this association did not achieve statistical significance (CC vs. TT, OR 2.00, 95% CI 0.44-6.59, P = 0.30). In summary, our findings suggest that the association of rs4149056 with simvastatin-related myotoxicity may also extend to lovastatin. More data is needed to determine the extent of the association in atorvastatin users. Altogether, these data expand the evidence base for informing guidelines of pharmacogenetic-based statin prescribing practices.

Although traditional approaches to biomarker discovery have elucidated key molecular markers that have improved drug selection (precision medicine), the discovery of biomarkers that inform optimal dose selection (precision dosing) continues to be a challenge in many therapeutic areas. Larger and more diverse study populations are necessary to discover additional biomarkers that provide the resolution needed for a more tailored dose. To generate and accommodate large datasets of drug response phenotypes, time- and cost-efficient strategies are necessary. In particular, a multitude of technological advances that originated for purposes outside of biomedical research (electronic health records, direct-to-consumer genetic testing, social media, mobile devices, and machine learning) have made it easier to communicate, connect, and gather information from consumers. Although these technologies have been used with success in the health sciences for an array of purposes, these resources have not been fully capitalized on for precision dosing. This perspective will touch on how these innovations can be used as data sources, data collection tools, and data processing tools for drug-response phenotypes with a unique focus on advancing biomarker-driven precision dosing.

BackgroundContinuous α1a-blockade is the first-line treatment for lower urinary tract symptoms (LUTS) among older men with suspected benign prostatic hyperplasia. Variable efficacy and safety for individual men necessitate a more personalized, data-driven approach to prescribing and deprescribing tamsulosin for LUTS in older men.ObjectiveWe aim to evaluate the feasibility and usability of the PERSONAL (Placebo-Controlled, Randomized, Patient-Selected Outcomes, N-of-1 Trials) mobile app for tracking daily LUTS severity and medication side effects among older men receiving chronic tamsulosin therapy.MethodsWe recruited patients from the University of California, San Francisco health care system to participate in a 2-week pilot study. The primary objectives were to assess recruitment feasibility, study completion rates, frequency of symptom tracking, duration of tracking sessions, and app usability rankings measured using a follow-up survey. As secondary outcomes, we evaluated whether daily symptom tracking led to changes in LUTS severity, perceptions of tamsulosin, overall quality of life, medication adherence between baseline and follow-up surveys, and perceived app utility.ResultsWe enrolled 19 men within 23 days, and 100% (19/19) of the participants completed the study. Each participant selected a unique combination of symptoms to track and recorded data in the PERSONAL app, with a median daily completion rate of 79% (11/14 days). The median duration of the app session was 44 (IQR 33) seconds. On a scale of 1 (strongly disagree) to 5 (strongly agree), the participants reported that the PERSONAL app was easy to use (mean 4.3, SD 1.0), that others could learn to use it quickly (mean 4.2, SD 0.9), and that they felt confident using the app (mean 4.4, SD 0.8). LUTS severity, quality of life, and medication adherence remained unchanged after the 2-week study period. Fewer men were satisfied with tamsulosin after using the app (14/19, 74% vs 17/19, 89% at baseline), although the perceived benefit from tamsulosin remained unchanged (18/19, 95% at baseline and at follow-up). In total, 58% (11/19) of the participants agreed that the PERSONAL app could help people like them manage their urinary symptoms.ConclusionsThis pilot study demonstrated the high feasibility and usability of the PERSONAL mobile app to track patient-selected urinary symptoms and medication side effects among older men taking tamsulosin to manage LUTS. We observed that daily symptom monitoring had no adverse effects on the secondary outcomes. This proof-of-concept study establishes a framework for future mobile app studies, such as digital n-of-1 trials, to collect comprehensive individual-level data for personalized LUTS management in older men.

In pharmacogenomic studies of quantitative change, any association between genetic variants and the pretreatment (baseline) measurement can bias the estimate of effect between those variants and drug response. A putative solution is to adjust for baseline. We conducted a series of genome-wide association studies (GWASs) for low-density lipoprotein cholesterol (LDL-C) response to statin therapy in 34,874 participants of the Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort as a case study to investigate the impact of baseline adjustment on results generated from pharmacogenomic studies of quantitative change. Across phenotypes of statin-induced LDL-C change, baseline adjustment identified variants from six loci meeting genome-wide significance (SORT/CELSR2/PSRC1, LPA, SLCO1B1, APOE, APOB, and SMARCA4/LDLR). In contrast, baseline-unadjusted analyses yielded variants from three loci meeting the criteria for genome-wide significance (LPA, APOE, and SLCO1B1). A genome-wide heterogeneity test of baseline versus statin on-treatment LDL-C levels was performed as the definitive test for the true effect of genetic variants on statin-induced LDL-C change. These findings were generally consistent with the models not adjusting for baseline signifying that genome-wide significant hits generated only from baseline-adjusted analyses (SORT/CELSR2/PSRC1, APOB, SMARCA4/LDLR) were likely biased. We then comprehensively reviewed published GWASs of drug-induced quantitative change and discovered that more than half (59%) inappropriately adjusted for baseline. Altogether, we demonstrate that (1) baseline adjustment introduces bias in pharmacogenomic studies of quantitative change and (2) this erroneous methodology is highly prevalent. We conclude that it is critical to avoid this common statistical approach in future pharmacogenomic studies of quantitative change.

In pharmacogenomic studies of quantitative change, any association between genetic variants and the pretreatment (baseline) measurement can bias the estimate of effect between those variants and drug response. A putative solution is to adjust for baseline. We conducted a series of genome-wide association studies (GWASs) for low-density lipoprotein cholesterol (LDL-C) response to statin therapy in 34,874 participants of the Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort as a case study to investigate the impact of baseline adjustment on results generated from pharmacogenomic studies of quantitative change. Across phenotypes of statin-induced LDL-C change, baseline adjustment identified variants from six loci meeting genome-wide significance (SORT/CELSR2/PSRC1, LPA, SLCO1B1, APOE, APOB, and SMARCA4/LDLR). In contrast, baseline-unadjusted analyses yielded variants from three loci meeting the criteria for genome-wide significance (LPA, APOE, and SLCO1B1). A genome-wide heterogeneity test of baseline versus statin on-treatment LDL-C levels was performed as the definitive test for the true effect of genetic variants on statin-induced LDL-C change. These findings were generally consistent with the models not adjusting for baseline signifying that genome-wide significant hits generated only from baseline-adjusted analyses (SORT/CELSR2/PSRC1, APOB, SMARCA4/LDLR) were likely biased. We then comprehensively reviewed published GWASs of drug-induced quantitative change and discovered that more than half (59%) inappropriately adjusted for baseline. Altogether, we demonstrate that (1) baseline adjustment introduces bias in pharmacogenomic studies of quantitative change and (2) this erroneous methodology is highly prevalent. We conclude that it is critical to avoid this common statistical approach in future pharmacogenomic studies of quantitative change.

Background: Lower urinary tract symptoms (LUTS) affect more than half of men over age 70 and contribute to both poor health-related quality of life and polypharmacy. Tamsulosin hydrochloride, a selective α1-blocker, is the most common medication used to treat LUTS due to presumed benign prostatic hyperplasia and is often prescribed indefinitely, although not all men benefit from long-term therapy. N-of-1 trials allow for individualized estimates of benefit and harm and could facilitate decisions regarding chronic tamsulosin therapy for LUTS, particularly among older men. Our team developed the PERSONAL (PlacEbo-controlled, Randomized, patient-Selected Outcomes, N-of-1 triALs) app to track daily urinary symptoms and medication side effects for n-of-1 trials among older men with LUTS. Materials and Methods: We will conduct a feasibility study of 20 individual randomized n-of-1 trials using the PERSONAL app to compare tamsulosin (0.4 or 0.8 mg) vs. placebo among older men taking tamsulosin for LUTS. We will include men over age 65 with a smartphone for whom temporary discontinuation of tamsulosin is safe, (e.g., no history of acute retention). Participants will work with research staff to prospectively identify the most important urinary symptoms and medication side effects that they would like to digitally track. Men will then be randomized to 2-week treatment periods of tamsulosin or placebo followed by a 1-week wash-out with placebo, for 4 distinct treatment periods and 3 wash-out periods, totaling 11 weeks. Study medications will be blinded using over-encapsulation of tamsulosin pills and matching placebo. Our primary outcomes for this study will be recruitment and retention of eligible men, completion rates of n-of-1 trials and daily questionnaires using the PERSONAL app, and participants' perceived usefulness of their n-of-1 trial for determining whether tamsulosin is effective for them. Linear mixed effects models with individual-specific intercepts and intervention effects will also be used to estimate within-individual effects of tamsulosin. Discussion: The goal of this innovative study is to establish feasibility and acceptability of using a mobile health app and n-of-1 trials to provide older men with individualized estimates of benefits and harms of chronic tamsulosin therapy for LUTS.

ObjectiveTo assess the impact of CYP2C9 variation on phenytoin patient response and clinician prescribing practice where genotype was unknown during treatment.MethodsA retrospective analysis of Resource on Genetic Epidemiology Research on Adult Health and Aging cohort participants who filled a phenytoin prescription between 1996 and 2017. We used laboratory test results, medication dispensing records, and medical notes to identify associations of CYP2C9 genotype with phenytoin blood concentration, neurologic side effects, and medication dispensing patterns reflecting clinician prescribing practice and patient response.ResultsAmong 993 participants, we identified 69% extensive, 20% high-intermediate, 10% low-intermediate, and 2% poor metabolizers based on CYP2C9 genotypes. Compared with extensive metabolizer genotype, low-intermediate/poor metabolizer genotype was associated with increased dose-adjusted phenytoin blood concentration [21.3 pg/mL, 95% confidence interval (CI): 13.6-29.0 pg/mL; P < 0.01] and increased risk of neurologic side effects (hazard ratio: 2.40, 95% CI: 1.24-4.64; P < 0.01). Decreased function CYP2C9 genotypes were associated with medication dispensing patterns indicating dose decrease, use of alternative anticonvulsants, and worse adherence, although these associations varied by treatment indication for phenytoin.ConclusionCYP2C9 variation was associated with clinically meaningful differences in clinician prescribing practice and patient response, with potential implications for healthcare utilization and treatment efficacy.

Abstract Background Prior studies of the glycemic effect of statins have been inconsistent. Also, most studies have only considered a short duration of statin use; the effect of long-term statin use on fasting glucose (FG) has not been well examined. The aim of this work is to investigate the effect of long-term statin exposure on FG levels. Methods Using electronic health record (EHR) data from a large and diverse longitudinal cohort, we defined long-term statin exposure in two ways: the cumulative years of statin use (cumulative supply) and the years’ supply-weighted sum of doses (cumulative dose). Simvastatin, lovastatin, atorvastatin and pravastatin were included in the analysis. The relationship between statin exposure and FG was examined using linear regression with mixed effects modeling, comparing statin users before and after initiating statins and statin never-users. Results We examined 593,130 FG measurements from 87,151 individuals over a median follow up of 20 years. Of these, 42,678 were never-users and 44,473 were statin users with a total of 730,031 statin prescriptions. FG was positively associated with cumulative supply of statin but not comulative dose when both measures were in the same model. While statistically significant, the annual increase in FG attributable to statin exposure was modest at only 0.14 mg/dl, with only slight and non-significant differences among statin types. Conclusions Elevation in FG level is associated with statin exposure, but the effect is modest. The results suggest that the risk of a clinically significant increase in FG attributable to long-term statin use is small for most individuals.

ABSTRACTThe high risk of maternal death in Africa has cast a shadow over representations and experiences of pregnancy and childbirth. In the 1980s, amid new awareness of disparities in maternal mortality rates between high and low-income countries, tragic anecdotes of women dying during childbirth emerged as a tool to garner political and economic support for global health interventions aimed at women. While successfully raising public concern and billions of dollars in aid, given that these stories are some of the few stories of African women so widely circulated, it is important to ask: what else does the genre of maternal death narrative do? How might discursive practices around childbirth structure the care offered to African women? What power relations are revealed in this form of knowledge production and promotion? This article examines how maternal death narratives function, circulate, and structure potential solutions to the problem of maternal mortality. In focusing on the pathways to death, women’s bodies are foregrounded as sites of knowledge production over their experiences. I use fieldwork with pregnant and birthing women in southwest Nigeria to explore the ways that women piece together different sources of care in an effort to ensure successful deliveries amidst considerable uncertainty.

BackgroundLow-density lipoprotein cholesterol (LDL-C) response to statin therapy has not been fully elucidated in real-world populations. The primary objective of this study was to characterize statin LDL-C dose-response and its heritability in a large, multiethnic population of statin users.MethodsWe determined the effect of statin dosing on lipid measures utilizing electronic health records in 33 139 statin users from the Kaiser Permanente GERA cohort (Genetic Epidemiology Research on Adult Health and Aging). The relationship between statin defined daily dose and lipid parameter response (percent change) was determined.ResultsDefined daily dose and LDL-C response was associated in a log-linear relationship (β, -6.17; SE, 0.09; P

Inhibition of soluble epoxide hydrolase (sEH, EPHX2) elicits potent cardiovascular protective effects in preclinical models of ischemic cardiovascular disease (CVD), and genetic polymorphisms in EPHX2 have been associated with developing ischemic CVD in humans. However, it remains unknown whether EPHX2 variants are associated with prognosis following an ischemic CVD event. We evaluated the association between EPHX2 p.Lys55Arg and p.Arg287Gln genotype with survival in 667 acute coronary syndrome (ACS) patients. No association with p.Arg287Gln genotype was observed (P = 0.598). Caucasian EPHX2 Arg55 carriers (Lys/Arg or Arg/Arg) had a significantly higher risk of 5-year mortality (adjusted hazard ratio [HR] 1.61, 95% confidence interval [CI] 1.01-2.55, P = 0.045). In an independent population of 2712 ACS patients, this association was not replicated (adjusted HR 0.92, 95% CI 0.70-1.21, P = 0.559). In a secondary analysis, Caucasian homozygous Arg55 allele carriers (Arg/Arg) appeared to exhibit a higher risk of cardiovascular mortality (adjusted HR 2.60, 95% CI 1.09-6.17). These results demonstrate that EPHX2 p.Lys55Arg and p.Arg287Gln polymorphisms do not significantly modify survival after an ACS event. Investigation of other sEH metabolism biomarkers in ischemic CVD appears warranted.

AIM:To determine the projected impact of a multigene pharmacogenetic (PGx) test on medication prescribing. MATERIALS & METHODS:A retrospective analysis was conducted with 122 cardiac catheterization laboratory patients undergoing angiography for eligibility of potential PGx-guided interventions that could have occurred if multigene PGx information was pre-emptively available at the time of the procedure. Medication data and presence of actionable at-risk genotypes were used to determine eligibility of a PGx intervention. RESULTS:20% of the study population (n = 24) would have qualified for at least one PGx-based medication intervention per US FDA or Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines within 6 months of their cardiac catheterization procedure. Commonly encountered gene-drug pairs for these interventions included: CYP2C19 for clopidogrel and antidepressants, CYP2D6 for antidepressants and codeine, SLCO1B1 for simvastatin, and VKORC1/CYP2C9 for warfarin. CONCLUSION:Pre-emptive use of a multigene PGx test in the cardiac catheterization laboratory offers potential to reduce adverse medication outcomes.

We recently demonstrated that selective expression of the Rho GTPase-activating protein ARHGAP42 in smooth muscle cells (SMCs) controls blood pressure by inhibiting RhoA-dependent contractility, providing a mechanism for the blood pressure-associated locus within the ARHGAP42 gene. The goals of the current study were to identify polymorphisms that affect ARHGAP42 expression and to better assess ARHGAP42's role in the development of hypertension. Using DNase I hypersensitivity methods and ENCODE data, we have identified a regulatory element encompassing the ARHGAP42 SNP rs604723 that exhibits strong SMC-selective, allele-specific activity. Importantly, CRISPR/Cas9-mediated deletion of this element in cultured human SMCs markedly reduced endogenous ARHGAP42 expression. DNA binding and transcription assays demonstrated that the minor T allele variation at rs604723 increased the activity of this fragment by promoting serum response transcription factor binding to a cryptic cis-element. ARHGAP42 expression was increased by cell stretch and sphingosine 1-phosphate in a RhoA-dependent manner, and deletion of ARHGAP42 enhanced the progression of hypertension in mice treated with DOCA-salt. Our analysis of a well-characterized cohort of untreated borderline hypertensive patients suggested that ARHGAP42 genotype has important implications in regard to hypertension risk. Taken together, our data add insight into the genetic mechanisms that control blood pressure and provide a potential target for individualized antihypertensive therapies.

Abstract Although traditional approaches to biomarker discovery have elucidated key molecular markers that have improved drug selection (precision medicine), the discovery of biomarkers that inform optimal dose selection (precision dosing) continues to be a challenge in many therapeutic areas. Larger and more diverse study populations are necessary to discover additional biomarkers that provide the resolution needed for a more tailored dose. To generate and accommodate large datasets of drug response phenotypes, time‐ and cost‐efficient strategies are necessary. In particular, a multitude of technological advances that originated for purposes outside of biomedical research (electronic health records, direct‐to‐consumer genetic testing, social media, mobile devices, and machine learning) have made it easier to communicate, connect, and gather information from consumers. Although these technologies have been used with success in the health sciences for an array of purposes, these resources have not been fully capitalized on for precision dosing. This perspective will touch on how these innovations can be used as data sources, data collection tools, and data processing tools for drug‐response phenotypes with a unique focus on advancing biomarker‐driven precision dosing.

Cytochrome P450 (CYP)-derived epoxyeicosatrienoic acids (EETs) exhibit potent cardiovascular protective effects in preclinical models, and promoting the effects of EETs has emerged as a potential therapeutic strategy for coronary artery disease (CAD). The relationship between circulating EET levels and CAD extent in humans, however, remains unknown. A panel of free (unesterified) plasma eicosanoid metabolites was quantified in 162 patients referred for coronary angiography, and associations with extent of CAD [no apparent CAD (N = 39), nonobstructive CAD (N = 51), and obstructive CAD (N = 72)] were evaluated. A significant relationship between free EET levels and CAD extent was observed (P = 0.003) such that the presence of obstructive CAD was associated with lower circulating EET levels. This relationship was confirmed in multiple regression analysis where CAD extent was inversely and significantly associated with EET levels (P = 0.013), and with a biomarker of EET biosynthesis (P < 0.001), independent of clinical and demographic factors. Furthermore, quantitative enrichment analysis revealed that these associations were the most pronounced compared with other eicosanoid metabolism pathways. Collectively, these findings suggest that the presence of obstructive CAD is associated with lower EET metabolite levels secondary to suppressed EET biosynthesis. Novel strategies that promote the effects of EETs may have therapeutic promise for patients with obstructive CAD.

Abstract Background TdP is a form of polymorphic ventricular tachycardia which develops in the setting of a prolonged QT interval. There are limited data describing risk factors, treatment, and outcomes of this potentially fatal arrhythmia. Objective Our goals were as follows: (1) to validate cases presenting with Torsade de Pointes (TdP), (2) to identify modifiable risk factors, and (3) to describe the management strategies used for TdP and its prognosis in a real‐world healthcare setting. Methods Case–control study (with 2:1 matching on age, sex, and race/ethnicity) nested within the Genetic Epidemiology Research on Aging (GERA) cohort. Follow‐up of the cohort for case ascertainment was between January 01, 2005 and December 31, 2018. Results A total of 56 cases of TdP were confirmed (incidence rate = 3.6 per 100,000 persons/years). The average (SD) age of the TdP cases was 74 (13) years, 55 percent were female, and 16 percent were non‐white. The independent predictors of TdP were potassium concentration 480 ms (OR = 4.4) and prior history of coronary artery disease (OR = 2.6). Exposure to furosemide and amiodarone was significantly greater in cases than in controls. The most common treatment for TdP was IV magnesium (78.6%) and IV potassium repletion (73.2%). The in‐hospital and 1‐year mortality rates for TdP cases were 10.7% and 25.0% percent, respectively. Conclusions These findings may inform quantitative multivariate risk indices for the prediction of TdP and could guide practitioners on which patients may qualify for continuous ECG monitoring and/or electrolyte replacement therapy.

BackgroundMobile health (mHealth) apps may provide an efficient way for patients with lower urinary tract symptoms (LUTS) to log and communicate symptoms and medication side effects with their clinicians. ObjectiveThe aim of this study was to explore the perceptions of older men with LUTS after using an mHealth app to track their symptoms and tamsulosin side effects. MethodsStructured phone interviews were conducted after a 2-week study piloting the daily use of a mobile app to track the severity of patient-selected LUTS and tamsulosin side effects. Quantitative and qualitative data were considered. ResultsAll 19 (100%) pilot study participants completed the poststudy interviews. Most of the men (n=13, 68%) reported that the daily questionnaires were the right length, with 32% (n=6) reporting that the questionnaires were too short. Men with more severe symptoms were less likely to report changes in perception of health or changes in self-management; 47% (n=9) of the men reported improved awareness of symptoms and 5% (n=1) adjusted fluid intake based on the questionnaire. All of the men were willing to share app data with their clinicians. Thematic analysis of qualitative data yielded eight themes: (1) orientation (setting up app, format, symptom selection, and side-effect selection), (2) triggers (routine or habit and symptom timing), (3) daily questionnaire (reporting symptoms, reporting side effects, and tailoring), (4) technology literacy, (5) perceptions (awareness, causation or relevance, data quality, convenience, usefulness, and other apps), (6) self-management, (7) clinician engagement (communication and efficiency), and (8) improvement (reference materials, flexibility, language, management recommendations, and optimize clinician engagement). ConclusionsWe assessed the perceptions of men using an mHealth app to monitor and improve management of LUTS and medication side effects. LUTS management may be further optimized by tailoring the mobile app experience to meet patients’ individual needs, such as tracking a greater number of symptoms and integrating the app with clinicians’ visits. mHealth apps are likely a scalable modality to monitor symptoms and improve care of older men with LUTS. Further study is required to determine the best ways to tailor the mobile app and to communicate data to clinicians or incorporate data into the electronical medical record meaningfully.

BackgroundContinuous α1a-blockade is the first-line treatment for lower urinary tract symptoms (LUTS) among older men with suspected benign prostatic hyperplasia. Variable efficacy and safety for individual men necessitate a more personalized, data-driven approach to prescribing and deprescribing tamsulosin for LUTS in older men. ObjectiveWe aim to evaluate the feasibility and usability of the PERSONAL (Placebo–Controlled, Randomized, Patient-Selected Outcomes, N-of-1 Trials) mobile app for tracking daily LUTS severity and medication side effects among older men receiving chronic tamsulosin therapy. MethodsWe recruited patients from the University of California, San Francisco health care system to participate in a 2-week pilot study. The primary objectives were to assess recruitment feasibility, study completion rates, frequency of symptom tracking, duration of tracking sessions, and app usability rankings measured using a follow-up survey. As secondary outcomes, we evaluated whether daily symptom tracking led to changes in LUTS severity, perceptions of tamsulosin, overall quality of life, medication adherence between baseline and follow-up surveys, and perceived app utility. ResultsWe enrolled 19 men within 23 days, and 100% (19/19) of the participants completed the study. Each participant selected a unique combination of symptoms to track and recorded data in the PERSONAL app, with a median daily completion rate of 79% (11/14 days). The median duration of the app session was 44 (IQR 33) seconds. On a scale of 1 (strongly disagree) to 5 (strongly agree), the participants reported that the PERSONAL app was easy to use (mean 4.3, SD 1.0), that others could learn to use it quickly (mean 4.2, SD 0.9), and that they felt confident using the app (mean 4.4, SD 0.8). LUTS severity, quality of life, and medication adherence remained unchanged after the 2-week study period. Fewer men were satisfied with tamsulosin after using the app (14/19, 74% vs 17/19, 89% at baseline), although the perceived benefit from tamsulosin remained unchanged (18/19, 95% at baseline and at follow-up). In total, 58% (11/19) of the participants agreed that the PERSONAL app could help people like them manage their urinary symptoms. ConclusionsThis pilot study demonstrated the high feasibility and usability of the PERSONAL mobile app to track patient-selected urinary symptoms and medication side effects among older men taking tamsulosin to manage LUTS. We observed that daily symptom monitoring had no adverse effects on the secondary outcomes. This proof-of-concept study establishes a framework for future mobile app studies, such as digital n-of-1 trials, to collect comprehensive individual-level data for personalized LUTS management in older men.

Background Long QT has been associated with ventricular dysrhythmias, cardiovascular disease (CVD) mortality, and sudden cardiac death. However, no studies to date have investigated the dynamics of within‐person QT change over time in relation to risk of incident CVD and all‐cause mortality in a real‐world setting. Methods and Results A cohort study among members of an integrated health care delivery system in Northern California including 61 455 people (mean age, 62 years; 60% women, 42% non‐White) with 3 or more ECGs (baseline in 2005–2009; mean±SD follow‐up time, 7.6±2.6 years). In fully adjusted models, tertile 3 versus tertile 1 of average QT corrected (using the Fridericia correction) was associated with cardiac arrest (hazard ratio [HR], 1.66), heart failure (HR, 1.62), ventricular dysrhythmias (HR, 1.56), all CVD (HR, 1.31), ischemic heart disease (HR, 1.28), total stroke (HR, 1.18), and all‐cause mortality (HR, 1.24). Tertile 3 versus tertile 2 of the QT corrected linear slope was associated with cardiac arrest (HR, 1.22), ventricular dysrhythmias (HR, 1.12), and all‐cause mortality (HR, 1.09). Tertile 3 versus tertile 1 of the QT corrected root mean squared error was associated with ventricular dysrhythmias (HR, 1.34), heart failure (HR, 1.28), all‐cause mortality (HR, 1.20), all CVD (HR, 1.14), total stroke (HR, 1.08), and ischemic heart disease (HR, 1.07). Conclusions Our results demonstrate improved predictive ability for CVD outcomes using longitudinal information from serial ECGs. Long‐term average QT corrected was more strongly associated with CVD outcomes than the linear slope or the root mean squared error. This new evidence is clinically relevant because ECGs are frequently used, noninvasive, and inexpensive.

Objectives Patients and caregivers are the primary stakeholders in ambulatory safety, given they perform daily chronic disease self-management, medication administration and outpatient follow-up. However, little attention has been given to their role in adverse events. We identified themes related to patient and caregiver factors and challenges in ambulatory safety incident reports from a Patient Safety Organization.Methods We conducted a mixed-methods analysis of ambulatory incident reports submitted to the Collaborative Healthcare Patient Safety Organization, including 450 hospitals or clinic members in 13 US states. We included events that had patient and/or caregiver behavioural, socioeconomic and clinical factors that may have contributed to the event. Two members of the team independently coded patient/caregiver factors, with dual coding of 20% of events. We then conducted a ‘frequent item set’ analysis to identify which factors most frequently co-occurred. We applied inductive analysis to the most frequent sets to interpret themes. Our team included a diverse stakeholder advisory council of patients, caregivers and healthcare staff.Results We analysed 522 incident reports and excluded 73 for a final sample of 449 events. Our co-occurrence analysis found the following three themes: (1) clinical advice may conflict with patient priorities; (2) breakdowns in communication and patient education cause medication adverse events and (3) patients with disabilities are vulnerable to the external environment.Conclusions Ambulatory safety reports capture both structural and behavioural factors contributing to adverse events. Actionable takeaways include the following: improving clinician counselling of patients to convey medical advice to elicit priorities, enhanced education regarding medication adverse events and expanding safety precautions for patients with disabilities at home. Ambulatory safety reporting must include patients in reporting and event review for better mitigation of future harm.