The relevance of rich club regions for functional outcome post-stroke is enhanced in women.

This study aimed to investigate the influence of stroke lesions in predefined highly interconnected (rich-club) brain regions on functional outcome post-stroke, determine their spatial specificity and explore the effects of biological sex on their relevance. We analyzed MRI data recorded at index stroke and ~3-months modified Rankin Scale (mRS) data from patients with acute ischemic stroke enrolled in the multisite MRI-GENIE study. Spatially normalized structural stroke lesions were parcellated into 108 atlas-defined bilateral (sub)cortical brain regions. Unfavorable outcome (mRS > 2) was modeled in a Bayesian logistic regression framework. Effects of individual brain regions were captured as two compound effects for (i) six bilateral rich club and (ii) all further non-rich club regions. In spatial specificity analyses, we randomized the split into "rich club" and "non-rich club" regions and compared the effect of the actual rich club regions to the distribution of effects from 1000 combinations of six random regions. In sex-specific analyses, we introduced an additional hierarchical level in our model structure to compare male and female-specific rich club effects. A total of 822 patients (age: 64.7[15.0], 39% women) were analyzed. Rich club regions had substantial relevance in explaining unfavorable functional outcome (mean of posterior distribution: 0.08, area under the curve: 0.8). In particular, the rich club-combination had a higher relevance than 98.4% of random constellations. Rich club regions were substantially more important in explaining long-term outcome in women than in men. All in all, lesions in rich club regions were associated with increased odds of unfavorable outcome. These effects were spatially specific and more pronounced in women.

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.

Genetically determined NLRP3 inflammasome activation associates with systemic inflammation and cardiovascular mortality.

AIMS: Inflammation plays an important role in cardiovascular disease (CVD) development. The NOD-like receptor protein-3 (NLRP3) inflammasome contributes to the development of atherosclerosis in animal models. Components of the NLRP3 inflammasome pathway such as interleukin-1ß can therapeutically be targeted. Associations of genetically determined inflammasome-mediated systemic inflammation with CVD and mortality in humans are unknown. METHODS AND RESULTS: We explored the association of genetic NLRP3 variants with prevalent CVD and cardiovascular mortality in 538 167 subjects on the individual participant level in an explorative gene-centric approach without performing multiple testing. Functional relevance of single-nucleotide polymorphisms on NLRP3 inflammasome activation has been evaluated in monocyte-enriched peripheral blood mononuclear cells (PBMCs). Genetic analyses identified the highly prevalent (minor allele frequency 39.9%) intronic NLRP3 variant rs10754555 to affect NLRP3 gene expression. rs10754555 carriers showed significantly higher C-reactive protein and serum amyloid A plasma levels. Carriers of the G allele showed higher NLRP3 inflammasome activation in isolated human PBMCs. In carriers of the rs10754555 variant, the prevalence of coronary artery disease was significantly higher as compared to non-carriers with a significant interaction between rs10754555 and age. Importantly, rs10754555 carriers had significantly higher risk for cardiovascular mortality during follow-up. Inflammasome inducers (e.g. urate, triglycerides, apolipoprotein C3) modulated the association between rs10754555 and mortality. CONCLUSION: The NLRP3 intronic variant rs10754555 is associated with increased systemic inflammation, inflammasome activation, prevalent coronary artery disease, and mortality. This study provides evidence for a substantial role of genetically driven systemic inflammation in CVD and highlights the NLRP3 inflammasome as a therapeutic target.

Correction: Developing a common framework for evaluating the implementation of genomic medicine interventions in clinical care: the IGNITE Network's Common Measures Working Group.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Optimizing identification of resistant hypertension: Computable phenotype development and validation.

PURPOSE: Computable phenotypes are constructed to utilize data within the electronic health record (EHR) to identify patients with specific characteristics; a necessary step for researching a complex disease state. We developed computable phenotypes for resistant hypertension (RHTN) and stable controlled hypertension (HTN) based on the National Patient-Centered Clinical Research Network (PCORnet) common data model (CDM). The computable phenotypes were validated through manual chart review. METHODS: We adapted and refined existing computable phenotype algorithms for RHTN and stable controlled HTN to the PCORnet CDM in an adult HTN population from the OneFlorida Clinical Research Consortium (2015-2017). Two independent reviewers validated the computable phenotypes through manual chart review of 425 patient records. We assessed precision of our computable phenotypes through positive predictive value (PPV) and test validity through interrater reliability (IRR). RESULTS: Among the 156 730 HTN patients in our final dataset, the final computable phenotype algorithms identified 24 926 patients with RHTN and 19 100 with stable controlled HTN. The PPV for RHTN in patients randomly selected for validation of the final algorithm was 99.1% (n = 113, CI: 95.2%-99.9%). The PPV for stable controlled HTN in patients randomly selected for validation of the final algorithm was 96.5% (n = 113, CI: 91.2%-99.0%). IRR analysis revealed a raw percent agreement of 91% (152/167) with Cohen's kappa statistic = 0.87. CONCLUSIONS: We constructed and validated a RHTN computable phenotype algorithm and a stable controlled HTN computable phenotype algorithm. Both algorithms are based on the PCORnet CDM, allowing for future application to epidemiological and drug utilization based research.

Genome-wide association analysis of common genetic variants of resistant hypertension.

Resistant hypertension (RHTN), defined as uncontrolled blood pressure (BP) ≥ 140/90 using three or more drugs or controlled BP (<140/90) using four or more drugs, is associated with adverse outcomes, including decline in kidney function. We conducted a genome-wide association analysis in 1194 White and Hispanic participants with hypertension and coronary artery disease from the INternational VErapamil-SR Trandolapril STudy-GENEtic Substudy (INVEST-GENES). Top variants associated with RHTN at p < 10-4 were tested for replication in 585 White and Hispanic participants with hypertension and subcortical strokes from the Secondary Prevention of Subcortical Strokes GENEtic Substudy (SPS3-GENES). A genetic risk score for RHTN was created by summing the risk alleles of replicated RHTN signals. rs11749255 in MSX2 was associated with RHTN in INVEST (odds ratio (OR) (95% CI) = 1.50 (1.2-1.8), p = 7.3 × 10-5) and replicated in SPS3 (OR = 2.0 (1.4-2.8), p = 4.3 × 10-5), with genome-wide significance in meta-analysis (OR = 1.60 (1.3-1.9), p = 3.8 × 10-8). Other replicated signals were in IFLTD1 and PTPRD. IFLTD1 rs6487504 was associated with RHTN in INVEST (OR = 1.90 (1.4-2.5), p = 1.1 × 10-5) and SPS3 (OR = 1.70 (1.2-2.5), p = 4 × 10-3). PTPRD rs324498, a previously reported RHTN signal, was among the top signals in INVEST (OR = 1.60 (1.3-2.0), p = 3.4 × 10-5) and replicated in SPS3 (OR = 1.60 (1.1-2.4), one-sided p = 0.005). Participants with the highest number of risk alleles were at increased risk of RHTN compared to participants with a lower number (p-trend = 1.8 × 10-15). Overall, we identified and replicated associations with RHTN in the MSX2, IFLTD1, and PTPRD regions, and combined these associations to create a genetic risk score.

Targeted sequencing identifies a missense variant in the BEST3 gene associated with antihypertensive response to hydrochlorothiazide.

Chromosome 12q15 was identified in Genetic Epidemiology of Response Assessment (GERA) and replicated in Pharmacogenomic Evaluation of Antihypertensive Responses (PEAR) for its association with blood pressure (BP) response to hydrochlorothiazide (HCTZ). However, the functional variant is unknown and we aimed to identify the likely functional variants through targeted sequencing. The chromosome 12q15 region was sequenced in 397 best and worst responders to HCTZ in PEAR (N=199) and GERA (N=198) hypertensive study participants. Logistic regression was used for the association analysis adjusting for age, sex, race, and principal components 1 and 2. For validation, the significant single nucleotide polymorphism was tested for association with the change in systolic (ΔSBP) and diastolic BP (ΔDBP) post-treatment in the entire PEAR (N=370) and GERA (N=570) cohorts. A novel missense polymorphism (G>A, Pro383Leu) in BEST3, rs61747221, was significantly associated with better HCTZ response (P=0.0021, odds ratio=2.05). It was validated in the entire cohort of PEAR (ΔSBP: P=0.021, ß=-1.60, ΔDBP: P=0.023, ß=-1.08) and GERA (ΔSBP: P=0.028, ß=-1.95, ΔDBP: P=0.032, ß=-1.28). BEST3 encodes the calcium sensitive chloride channel in the vascular smooth muscle implicated in the regulation of BP, especially in response to vasoconstrictors like angiotensin II. These results suggest that BEST3 is involved in the chronic BP lowering mechanism of thiazides and highlight its importance as a genetic predictor of the BP response to thiazide diuretics.

Developing a common framework for evaluating the implementation of genomic medicine interventions in clinical care: the IGNITE Network's Common Measures Working Group.

PurposeImplementation research provides a structure for evaluating the clinical integration of genomic medicine interventions. This paper describes the Implementing Genomics in Practice (IGNITE) Network's efforts to promote (i) a broader understanding of genomic medicine implementation research and (ii) the sharing of knowledge generated in the network.MethodsTo facilitate this goal, the IGNITE Network Common Measures Working Group (CMG) members adopted the Consolidated Framework for Implementation Research (CFIR) to guide its approach to identifying constructs and measures relevant to evaluating genomic medicine as a whole, standardizing data collection across projects, and combining data in a centralized resource for cross-network analyses.ResultsCMG identified 10 high-priority CFIR constructs as important for genomic medicine. Of those, eight did not have standardized measurement instruments. Therefore, we developed four survey tools to address this gap. In addition, we identified seven high-priority constructs related to patients, families, and communities that did not map to CFIR constructs. Both sets of constructs were combined to create a draft genomic medicine implementation model.ConclusionWe developed processes to identify constructs deemed valuable for genomic medicine implementation and codified them in a model. These resources are freely available to facilitate knowledge generation and sharing across the field.

Hypertension in Florida: Data From the OneFlorida Clinical Data Research Network.

INTRODUCTION: Hypertension is highly prevalent in Florida, but surveillance through the Behavioral Risk Factor Surveillance System (BRFSS) is limited to self-reported hypertension and does not capture data on undiagnosed hypertension or measure blood pressure. We aimed to characterize the hypertensive population in the OneFlorida Clinical Research Consortium by using electronic health records and provide proof-of-concept for using routinely collected clinical data to augment surveillance efforts. METHODS: We identified patients with hypertension, defined as having at least 1 outpatient visit from January 2012 through June 2016 with an ICD-9-CM or ICD-10-CM diagnosis code for hypertension, or in the absence of a diagnosis, an elevated blood pressure (systolic ≥140 mm Hg or diastolic ≥90 mm Hg) recorded in the electronic health record at the most recent visit. The hypertensive population was characterized and mapped by zip code of patient residence to county prevalence. RESULTS: Of 838,469 patients (27.9% prevalence) who met the criteria for hypertension, 68% had received a diagnosis and 61% had elevated blood pressure. The geographic distribution of hypertension differed between diagnosed hypertension (highest prevalence in northern Florida) and undiagnosed hypertension (highest prevalence along eastern coast, in southern Florida, and in some rural western Panhandle counties). Uncontrolled hypertension was concentrated in southern Florida and the western Panhandle. CONCLUSION: Our use of clinical data, representing usual care for Floridians, allows for identifying cases of uncontrolled hypertension and potentially undiagnosed cases, which are not captured by existing surveillance methods. Large-scale pragmatic research networks, like OneFlorida, may be increasingly important for tailoring future health care services, trials, and public health programs.

Pharmacogenetic Associations of ß1-Adrenergic Receptor Polymorphisms With Cardiovascular Outcomes in the SPS3 Trial (Secondary Prevention of Small Subcortical Strokes).

BACKGROUND AND PURPOSE: Functional polymorphisms (Ser49Gly and Arg389Gly) in ADRB1 have been associated with cardiovascular and ß-blocker response outcomes. Herein we examined associations of these polymorphisms with major adverse cardiovascular events (MACE), with and without stratification by ß-blocker treatment in patients with a history of stroke. METHODS: Nine hundred and twenty-six participants of the SPS3 trial's (Secondary Prevention of Small Subcortical Strokes) genetic substudy with hypertension were included. MACE included stroke, myocardial infarction, and all-cause death. Kaplan-Meier and multivariable Cox regression analyses were used. Because the primary component of MACE was ischemic stroke, we tested the association of Ser49Gly with ischemic stroke among 41 475 individuals of European and African ancestry in the NINDS (National Institute of Neurological Disorders and Stroke) SiGN (Stroke Genetics Network). RESULTS: MACE was higher in carriers of the Gly49 allele than in those with the Ser49Ser genotype (10.5% versus 5.4%, log-rank P=0.005). Gly49 carrier status was associated with MACE (hazard ratio, 1.62; 95% confidence interval, 1.00-2.68) and ischemic stroke (hazard ratio, 1.81; 95% confidence interval, 1.01-3.23) in SPS3 and with small artery ischemic stroke (odds ratio, 1.14; 95% confidence interval, 1.03-1.26) in SiGN. In SPS3, ß-blocker-treated Gly49 carriers had increased MACE versus non-ß-blocker-treated individuals and noncarriers (hazard ratio, 2.03; 95% confidence interval, 1.20-3.45). No associations were observed with the Arg389Gly polymorphism. CONCLUSION: Among individuals with previous small artery ischemic stroke, the ADRB1 Gly49 polymorphism was associated with MACE, particularly small artery ischemic stroke, a risk that may be increased among ß-blocker-treated individuals. Further research is needed to define ß-blocker benefit among ischemic stroke patients by ADRB1 genotype. CLINICAL TRIAL REGISTRATION: URL: http://www.clinicaltrials.gov. Unique identifier: NCT00059306.

Gene-centric meta-analysis in 87,736 individuals of European ancestry identifies multiple blood-pressure-related loci.

Blood pressure (BP) is a heritable risk factor for cardiovascular disease. To investigate genetic associations with systolic BP (SBP), diastolic BP (DBP), mean arterial pressure (MAP), and pulse pressure (PP), we genotyped ~50,000 SNPs in up to 87,736 individuals of European ancestry and combined these in a meta-analysis. We replicated findings in an independent set of 68,368 individuals of European ancestry. Our analyses identified 11 previously undescribed associations in independent loci containing 31 genes including PDE1A, HLA-DQB1, CDK6, PRKAG2, VCL, H19, NUCB2, RELA, HOXC@ complex, FBN1, and NFAT5 at the Bonferroni-corrected array-wide significance threshold (p < 6 × 10(-7)) and confirmed 27 previously reported associations. Bioinformatic analysis of the 11 loci provided support for a putative role in hypertension of several genes, such as CDK6 and NUCB2. Analysis of potential pharmacological targets in databases of small molecules showed that ten of the genes are predicted to be a target for small molecules. In summary, we identified previously unknown loci associated with BP. Our findings extend our understanding of genes involved in BP regulation, which may provide new targets for therapeutic intervention or drug response stratification.

Loci influencing blood pressure identified using a cardiovascular gene-centric array.

Blood pressure (BP) is a heritable determinant of risk for cardiovascular disease (CVD). To investigate genetic associations with systolic BP (SBP), diastolic BP (DBP), mean arterial pressure (MAP) and pulse pressure (PP), we genotyped ∼50 000 single-nucleotide polymorphisms (SNPs) that capture variation in ∼2100 candidate genes for cardiovascular phenotypes in 61 619 individuals of European ancestry from cohort studies in the USA and Europe. We identified novel associations between rs347591 and SBP (chromosome 3p25.3, in an intron of HRH1) and between rs2169137 and DBP (chromosome1q32.1 in an intron of MDM4) and between rs2014408 and SBP (chromosome 11p15 in an intron of SOX6), previously reported to be associated with MAP. We also confirmed 10 previously known loci associated with SBP, DBP, MAP or PP (ADRB1, ATP2B1, SH2B3/ATXN2, CSK, CYP17A1, FURIN, HFE, LSP1, MTHFR, SOX6) at array-wide significance (P < 2.4 × 10(-6)). We then replicated these associations in an independent set of 65 886 individuals of European ancestry. The findings from expression QTL (eQTL) analysis showed associations of SNPs in the MDM4 region with MDM4 expression. We did not find any evidence of association of the two novel SNPs in MDM4 and HRH1 with sequelae of high BP including coronary artery disease (CAD), left ventricular hypertrophy (LVH) or stroke. In summary, we identified two novel loci associated with BP and confirmed multiple previously reported associations. Our findings extend our understanding of genes involved in BP regulation, some of which may eventually provide new targets for therapeutic intervention.

The influence of human GSTZ1 gene haplotype variations on GSTZ1 expression.

BACKGROUND/OBJECTIVES: The zeta-1 family isoform of GST biotransforms the investigational drug dichloroacetate (DCA) and certain other halogenated carboxylic acids. Haplotype variability in GSTZ1 influences the kinetics and, possibly, the toxicity of DCA. DCA metabolism correlates with expression of the GSTZ1 protein, so it is important to document variables that affect expression. Following up on a limited previous study, we tested the hypothesis that a coding single nucleotide polymorphism (SNP), the lysine (K) amino acid (E32>K) in GSTZ1 haplotypes linked to a promoter region SNP results in lower hepatic expression of GSTZ1. MATERIALS AND METHODS: The influence of K carrier and non-K carrier haplotypes on GSTZ1 expression was determined by analyzing 78 liver samples from individuals aged 7-84 years of various racial and ethnic backgrounds. GSTZ1 expression data were analyzed on the basis of the presence or absence of lysine 32. RESULTS: GSTZ1 protein expression differed significantly between K carrier and non-K carrier haplotypes (P=0.001) in Whites, but not in African-Americans (P=0.277). We attribute this difference in GSTZ1 expression among K carrier haplotypes in Whites to the linkage disequilibrium between the K or A allele from the G>A SNP (rs7975), within the promoter G>A-1002 SNP (rs7160195) A allele. There is no linkage disequilibrium between these two polymorphisms in African-Americans. CONCLUSION: We conclude that the lower expression of GSTZ1 in Whites who possess the K carrier haplotype results in lower enzymatic activity and slower metabolism of DCA, compared with those who possess the non-K carrier haplotype. These results further define safe, genetics-based dosing regimens for chronic DCA administration.

Large-scale gene-centric meta-analysis across 32 studies identifies multiple lipid loci.

Genome-wide association studies (GWASs) have identified many SNPs underlying variations in plasma-lipid levels. We explore whether additional loci associated with plasma-lipid phenotypes, such as high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), total cholesterol (TC), and triglycerides (TGs), can be identified by a dense gene-centric approach. Our meta-analysis of 32 studies in 66,240 individuals of European ancestry was based on the custom ∼50,000 SNP genotyping array (the ITMAT-Broad-CARe array) covering ∼2,000 candidate genes. SNP-lipid associations were replicated either in a cohort comprising an additional 24,736 samples or within the Global Lipid Genetic Consortium. We identified four, six, ten, and four unreported SNPs in established lipid genes for HDL-C, LDL-C, TC, and TGs, respectively. We also identified several lipid-related SNPs in previously unreported genes: DGAT2, HCAR2, GPIHBP1, PPARG, and FTO for HDL-C; SOCS3, APOH, SPTY2D1, BRCA2, and VLDLR for LDL-C; SOCS3, UGT1A1, BRCA2, UBE3B, FCGR2A, CHUK, and INSIG2 for TC; and SERPINF2, C4B, GCK, GATA4, INSR, and LPAL2 for TGs. The proportion of explained phenotypic variance in the subset of studies providing individual-level data was 9.9% for HDL-C, 9.5% for LDL-C, 10.3% for TC, and 8.0% for TGs. This large meta-analysis of lipid phenotypes with the use of a dense gene-centric approach identified multiple SNPs not previously described in established lipid genes and several previously unknown loci. The explained phenotypic variance from this approach was comparable to that from a meta-analysis of GWAS data, suggesting that a focused genotyping approach can further increase the understanding of heritability of plasma lipids.

Differential effects of MYH9 and APOL1 risk variants on FRMD3 Association with Diabetic ESRD in African Americans.

Single nucleotide polymorphisms (SNPs) in MYH9 and APOL1 on chromosome 22 (c22) are powerfully associated with non-diabetic end-stage renal disease (ESRD) in African Americans (AAs). Many AAs diagnosed with type 2 diabetic nephropathy (T2DN) have non-diabetic kidney disease, potentially masking detection of DN genes. Therefore, genome-wide association analyses were performed using the Affymetrix SNP Array 6.0 in 966 AA with T2DN and 1,032 non-diabetic, non-nephropathy (NDNN) controls, with and without adjustment for c22 nephropathy risk variants. No associations were seen between FRMD3 SNPs and T2DN before adjusting for c22 variants. However, logistic regression analysis revealed seven FRMD3 SNPs significantly interacting with MYH9-a finding replicated in 640 additional AA T2DN cases and 683 NDNN controls. Contrasting all 1,592 T2DN cases with all 1,671 NDNN controls, FRMD3 SNPs appeared to interact with the MYH9 E1 haplotype (e.g., rs942280 interaction p-value = 9.3E⁻7 additive; odds ratio [OR] 0.67). FRMD3 alleles were associated with increased risk of T2DN only in subjects lacking two MYH9 E1 risk haplotypes (rs942280 OR = 1.28), not in MYH9 E1 risk allele homozygotes (rs942280 OR = 0.80; homogeneity p-value = 4.3E⁻4). Effects were weaker stratifying on APOL1. FRMD3 SNPS were associated with T2DN, not type 2 diabetes per se, comparing AAs with T2DN to those with diabetes lacking nephropathy. T2DN-associated FRMD3 SNPs were detectable in AAs only after accounting for MYH9, with differential effects for APOL1. These analyses reveal a role for FRMD3 in AA T2DN susceptibility and accounting for c22 nephropathy risk variants can assist in detecting DN susceptibility genes.

Characteristics and Predictors of Apparent Treatment-Resistant Hypertension in Real-World Populations Using Electronic Health Record-Based Data.

BACKGROUND: Apparent treatment-resistant hypertension (aTRH) is defined as uncontrolled blood pressure (BP) despite using ≥3 antihypertensive classes or controlled BP while using ≥4 antihypertensive classes. Patients with aTRH have a higher risk for adverse cardiovascular outcomes compared with patients with controlled hypertension (HTN). Although there have been prior reports on the prevalence, characteristics, and predictors of aTRH, these have been broadly derived from smaller datasets, randomized controlled trials, or closed healthcare systems. METHODS: We extracted patients with HTN defined by ICD-9 and ICD-10 codes during 1/1/2015-12/31/2018, from 2 large electronic health record databases: the OneFlorida Data Trust (n = 223,384) and Research Action for Health Network (REACHnet) (n = 175,229). We applied our previously validated aTRH and stable controlled HTN computable phenotype algorithms and performed univariate and multivariate analyses to identify the prevalence, characteristics, and predictors of aTRH in these populations. RESULTS: The prevalence of aTRH among patients with HTN in OneFlorida (16.7%) and REACHnet (11.3%) was similar to prior reports. Both populations had a significantly higher proportion of Black patients with aTRH compared with those with stable controlled HTN. aTRH in both populations shared similar significant predictors, including Black race, diabetes, heart failure, chronic kidney disease, cardiomegaly, and higher body mass index. In both populations, aTRH was significantly associated with similar comorbidities, when compared with stable controlled HTN. CONCLUSIONS: In 2 large, diverse real-world populations, we observed similar comorbidities and predictors of aTRH as prior studies. In the future, these results may be used to improve healthcare professionals' understanding of aTRH predictors and associated comorbidities.

Integrated metabolomics analysis reveals mechanistic insights into variability in blood pressure response to thiazide diuretics and beta blockers.

Hypertensive patients with a higher proportion of genetic West African ancestry (%GWAA) have better blood pressure (BP) response to thiazide diuretics (TDs) and worse response to ß-blockers (BBs) than those with lower %GWAA, associated with their lower plasma renin activity (PRA). TDs and BBs are suggested to reduce BP in the long term through vasodilation via incompletely understood mechanisms. This study aimed at identifying pathways underlying ancestral differences in PRA, which might reflect pathways underlying BP-lowering mechanisms of TDs and BBs. Among hypertensive participants enrolled in the Pharmacogenomics Evaluation of Antihypertensive Responses (PEAR) and PEAR-2 trials, we previously identified 8 metabolites associated with baseline PRA and 4 metabolic clusters (including 39 metabolites) that are different between those with GWAA <45% versus ≥45%. In the current study, using Ingenuity Pathway Analysis (IPA), we integrated these signals. Three overlapping metabolic signals within three significantly enriched pathways were identified as associated with both PRA and %GWAA: ceramide signaling, sphingosine 1- phosphate signaling, and endothelial nitric oxide synthase signaling. Literature indicates that the identified pathways are involved in the regulation of the Rho kinase cascade, production of the vasoactive agents nitric oxide, prostacyclin, thromboxane A2, and endothelin 1; the pathways proposed to underlie TD- and BB-induced vasodilatation. These findings may improve our understanding of the BP-lowering mechanisms of TDs and BBs. This might provide a possible step forward in personalizing antihypertensive therapy by identifying patients expected to have robust BP-lowering effects from these drugs.

Use of CYP2D6 Inhibitors with CYP2D6 Opioids: Association with Emergency Department Visits for Pain.

Hydrocodone, tramadol, codeine, and oxycodone are commonly prescribed opioids that rely on activation by cytochrome P450 2D6 (CYP2D6). CYP2D6 inhibitors can significantly decrease CYP2D6 activity, leading to reduced generation of active metabolites, and impairing pain control. To understand this impact, we assessed emergency department (ED) visits in patients initiating these CYP2D6-dependent opioids while on CYP2D6-inhibitor antidepressants vs. antidepressants that do not inhibit CYP2D6. This retrospective cohort study included adult patients prescribed CYP2D6-dependent opioids utilizing electronic health records data from the University of Florida Health (2015-2021). The association between ED visits and inhibitor exposure was tested using multivariable logistic regression. The primary analysis had 12,118 patients (72% female; mean (SD) age, 55 (13.4)) in the hydrocodone/tramadol/codeine cohort and 5,547 patients (64% female; mean (SD) age, 53.6 (14.2)) in the oxycodone cohort. Hydrocodone/tramadol/codeine-treated patients exposed to CYP2D6-inhibitor antidepressants (n = 7,043) had a higher crude rate of pain-related ED visits than those taking other antidepressants (n = 5,075) (3.28% vs. 1.87%), with an adjusted odds ratio (aOR) of 1.75 (95% CI: 1.36 to 2.24). Similarly, in the oxycodone cohort, CYP2D6-inhibitor antidepressant-exposed individuals (n = 3,206) had a higher crude rate of ED visits than individuals exposed to other antidepressants (n = 2,341) (5.02% vs. 3.37%), with aOR of 1.70 (95% CI: 1.27-2.27). Similar findings were observed in secondary and sensitivity analyses. Our findings suggest patients with concomitant use of hydrocodone/tramadol/codeine or oxycodone and CYP2D6 inhibitors have more frequent ED visits for pain, which may be due to inadequate pain control.

Assessing the Performance of In silico Tools and Molecular Dynamics Simulations for Predicting Pharmacogenetic Variant Impact.

The ability of freely available in silico tools to predict the effect of non-synonymous single nucleotide polymorphisms (nsSNPs) in pharmacogenes on protein function is not well defined. We assessed the performance of seven sequence-based (SIFT, PolyPhen2, mutation accessor, FATHMM, PhD-SNP, MutPred2, and SNPs & Go) and five structure-based (mCSM, SDM, DDGun, CupSat, and MAESTROweb) tools in predicting the impact of 118 nsSNPs in the CYP2C19, CYP2C9, CYP2B6, CYP2D6, and DPYD genes with known function (24 normal, one increased, 42 decreased, and 51 no-function). Sequence-based tools had a higher median (IQR) positive predictive value (89% [89-94%] vs. 12% [10-15%], P < 0.001) and lower negative predictive value (30% [24-34%] vs. 90% [80-93%], P < 0.001) than structure-based tools. Accuracy did not significantly differ between sequence-based (59% [37-67%]) and structure-based (34% [23-44%]) tools (P = 0.070). Notably, the no-function CYP2C9*3 allele and decreased function CYP2C9*8 allele were predicted incorrectly as tolerated by 100% of sequenced-based tools and as stabilizing by 60% and 20% of structure-based tools, respectively. As a case study, we performed mutational analysis for the CYP2C9*1, *3 (I359L), and *8 (R150H) proteins through molecular dynamic (MD) simulations using S-warfarin as the substrate. The I359L variant increased the distance of the major metabolic site of S-warfarin to the oxy-ferryl center of CYP2C9, and I359L and R150H caused shifts in the conformation of S-warfarin to a position less favorable for metabolism. These data suggest that MD simulations may better capture the impact of nsSNPs in pharmacogenes than other tools.

Using electronic health records for clinical pharmacology research: Challenges and considerations.

Electronic health records (EHRs) contain a vast array of phenotypic data on large numbers of individuals, often collected over decades. Due to the wealth of information, EHR data have emerged as a powerful resource to make first discoveries and identify disparities in our healthcare system. While the number of EHR-based studies has exploded in recent years, most of these studies are directed at associations with disease rather than pharmacotherapeutic outcomes, such as drug response or adverse drug reactions. This is largely due to challenges specific to deriving drug-related phenotypes from the EHR. There is great potential for EHR-based discovery in clinical pharmacology research, and there is a critical need to address specific challenges related to accurate and reproducible derivation of drug-related phenotypes from the EHR. This review provides a detailed evaluation of challenges and considerations for deriving drug-related data from EHRs. We provide an examination of EHR-based computable phenotypes and discuss cutting-edge approaches to map medication information for clinical pharmacology research, including medication-based computable phenotypes and natural language processing. We also discuss additional considerations such as data structure, heterogeneity and missing data, rare phenotypes, and diversity within the EHR. By further understanding the complexities associated with conducting clinical pharmacology research using EHR-based data, investigators will be better equipped to design thoughtful studies with more reproducible results. Progress in utilizing EHRs for clinical pharmacology research should lead to significant advances in our ability to understand differential drug response and predict adverse drug reactions.