A new test for trait mean and variance detects unreported loci for blood-pressure variation.

Variability in quantitative traits has clinical, ecological, and evolutionary significance. Most genetic variants identified for complex quantitative traits have only a detectable effect on the mean of trait. We have developed the mean-variance test (MVtest) to simultaneously model the mean and log-variance of a quantitative trait as functions of genotypes and covariates by using estimating equations. The advantages of MVtest include the facts that it can detect effect modification, that multiple testing can follow conventional thresholds, that it is robust to non-normal outcomes, and that association statistics can be meta-analyzed. In simulations, we show control of type I error of MVtest over several alternatives. We identified 51 and 37 previously unreported associations for effects on blood-pressure variance and mean, respectively, in the UK Biobank. Transcriptome-wide association studies revealed 633 significant unique gene associations with blood-pressure mean variance. MVtest is broadly applicable to studies of complex quantitative traits and provides an important opportunity to detect novel loci.

Diastolic Blood Pressure Alleles Improve Congenital Heart Defect Repair Outcomes.

BACKGROUND: Congenital heart defects (CHDs) affect 40 000 US births per year, half of which require surgical intervention. Individual differences in surgical outcomes including mortality and complications are not well understood but may be due to genetic variability. We hypothesized that polygenic risk scores (PRSs) for blood pressure in adults are associated with treatments and postsurgical outcomes in children with CHD, as CHD survivors are at higher risk of negative cardiometabolic disease. METHODS: We used imputed genotype data from pediatric participants requiring surgery for CHD (median age at surgery, 201 days; nmax=2498). Base data for the systolic and diastolic blood pressure PRSs (nmax=760 226) came from published genome-wide association study. The blood pressure PRSs were tested for association with postsurgical outcomes. All effects presented are per SD increase in PRS and adjusted for age, sex, body mass index, surgical complexity score, and first 10 principal components of ancestry. RESULTS: A higher diastolic blood pressure PRS was associated with decreased in-hospital mortality risk (odds ratio, 0.57 [0.39-0.82]; P=0.0022). Additional analyses suggest an interaction between diastolic blood pressure PRS and vasopressor dose. Those with a diastolic blood pressure PRS 1 SD above the mean, receiving a vasopressor dose in the top tertile, were estimated to have 52% (32%-66%) lower risk of in-hospital mortality compared with those with a vasopressor dose in the bottom tertile. CONCLUSIONS: These results suggest a genetically determined postsurgical survival advantage for CHD patients with blood pressure increasing alleles. Further study may reveal novel mechanisms contributing to postoperative morbidity and mortality, and this approach may assist in early identification of children at risk for adverse postoperative outcomes.

Population pharmacokinetic analysis of dexmedetomidine in children using real-world data from electronic health records and remnant specimens.

AIMS: Our objectives were to perform a population pharmacokinetic analysis of dexmedetomidine in children using remnant specimens and electronic health records (EHRs) and explore the impact of patient's characteristics and pharmacogenetics on dexmedetomidine clearance. METHODS: Dexmedetomidine dosing and patient data were gathered from EHRs and combined with opportunistically sampled remnant specimens. Population pharmacokinetic models were developed using nonlinear mixed-effects modelling. Stage 1 developed a model without genotype variables; Stage 2 added pharmacogenetic effects. RESULTS: Our final study population included 354 post-cardiac surgery patients aged 0-22 years (median 16 mo). The data were best described with a 2-compartment model with allometric scaling for weight and Hill maturation function for age. Population parameter estimates and 95% confidence intervals were 27.3 L/h (24.0-31.1 L/h) for total clearance, 161 L (139-187 L) for central compartment volume of distribution, 26.0 L/h (22.5-30.0 L/h) for intercompartmental clearance and 7903 L (5617-11 119 L) for peripheral compartment volume of distribution. The estimate for postmenstrual age when 50% of adult clearance is achieved was 42.0 weeks (41.5-42.5 weeks) and the Hill coefficient estimate was 7.04 (6.99-7.08). Genotype was not statistically or clinically significant. CONCLUSION: Our study demonstrates the use of real-world EHR data and remnant specimens to perform a population pharmacokinetic analysis and investigate covariate effects in a large paediatric population. Weight and age were important predictors of clearance. We did not find evidence for pharmacogenetic effects of UGT1A4 or UGT2B10 genotype or CYP2A6 risk score.

Association Between Genetic Variation in Blood Pressure and Increased Lifetime Risk of Peripheral Artery Disease.

[Figure: see text].

Large-Scale Multi-Omics Studies Provide New Insights into Blood Pressure Regulation.

Recent genome-wide association studies uncovered part of blood pressure's heritability. However, there is still a vast gap between genetics and biology that needs to be bridged. Here, we followed up blood pressure genome-wide summary statistics of over 750,000 individuals, leveraging comprehensive epigenomic and transcriptomic data from blood with a follow-up in cardiovascular tissues to prioritise likely causal genes and underlying blood pressure mechanisms. We first prioritised genes based on coding consequences, multilayer molecular associations, blood pressure-associated expression levels, and coregulation evidence. Next, we followed up the prioritised genes in multilayer studies of genomics, epigenomics, and transcriptomics, functional enrichment, and their potential suitability as drug targets. Our analyses yielded 1880 likely causal genes for blood pressure, tens of which are targets of the available licensed drugs. We identified 34 novel genes for blood pressure, supported by more than one source of biological evidence. Twenty-eight (82%) of these new genes were successfully replicated by transcriptome-wide association analyses in a large independent cohort (n = ~220,000). We also found a substantial mediating role for epigenetic regulation of the prioritised genes. Our results provide new insights into genetic regulation of blood pressure in terms of likely causal genes and involved biological pathways offering opportunities for future translation into clinical practice.

Evidence that geographic variation in genetic ancestry associates with uterine fibroids.

Uterine fibroids disproportionately impact Black women. Evidence suggests Black women have earlier onset and higher cumulative risk. This risk disparity may be due an imbalance of risk alleles in one parental geographic ancestry subgroup relative to others. We investigated ancestry proportions for the 1000 Genomes phase 3 populations clustered into six geographic groups for association with fibroid traits in Black women (n = 583 cases, 797 controls) and White women (n = 1195 cases, 1164 controls). Global ancestry proportions were estimated using ADMIXTURE. Dichotomous (fibroids status and multiple fibroid status) and continuous outcomes (volume and largest dimension) were modeled for association with ancestry proportions using logistic and linear regression adjusting for age. Effect estimates are reported per 10% increase in genetically inferred ancestry proportion. Among Black women, West African (WAFR) ancestry was associated with fibroid risk, East African ancestry was associated with risk of multiple fibroids, Northern European (NEUR) ancestry was protective for multiple fibroids, Southern European ancestry was protective for fibroids and multiple fibroids, and South Asian (SAS) ancestry was positively associated with volume and largest dimension. In White women, NEUR ancestry was protective for fibroids, SAS ancestry was associated with fibroid risk, and WAFR ancestry was positively associated with volume and largest dimension. These results suggest that a proportion of fibroid risk and fibroid trait racial disparities are due to genetic differences between geographic groups. Further investigation at the local ancestry and single variant levels may yield novel insights into disease architecture and genetic mechanisms underlying ethnic disparities in fibroid risk.

Genome-wide association study identifies novel loci for type 2 diabetes-attributed end-stage kidney disease in African Americans.

BACKGROUND: End-stage kidney disease (ESKD) is a significant public health concern disproportionately affecting African Americans (AAs). Type 2 diabetes (T2D) is the leading cause of ESKD in the USA, and efforts to uncover genetic susceptibility to diabetic kidney disease (DKD) have had limited success. A prior genome-wide association study (GWAS) in AAs with T2D-ESKD was expanded with additional AA cases and controls and genotypes imputed to the higher density 1000 Genomes reference panel. The discovery analysis included 3432 T2D-ESKD cases and 6977 non-diabetic non-nephropathy controls (N = 10,409), followed by a discrimination analysis in 2756 T2D non-nephropathy controls to exclude T2D-associated variants. RESULTS: Six independent variants located in or near RND3/RBM43, SLITRK3, ENPP7, GNG7, and APOL1 achieved genome-wide significant association (P < 5 × 10-8) with T2D-ESKD. Following extension analyses in 1910 non-diabetic ESKD cases and 908 non-diabetic non-nephropathy controls, a meta-analysis of 5342 AA all-cause ESKD cases and 6977 AA non-diabetic non-nephropathy controls revealed an additional novel all-cause ESKD locus at EFNB2 (rs77113398; P = 9.84 × 10-9; OR = 1.94). Exclusion of APOL1 renal-risk genotype carriers identified two additional genome-wide significant T2D-ESKD-associated loci at GRAMD3 and MGAT4C. A second variant at GNG7 (rs373971520; P = 2.17 × 10-8, OR = 1.46) remained associated with all-cause ESKD in the APOL1-negative analysis. CONCLUSIONS: Findings provide further evidence for genetic factors associated with advanced kidney disease in AAs with T2D.

A genome-wide association study of polycystic ovary syndrome identified from electronic health records.

BACKGROUND: Polycystic ovary syndrome is the most common endocrine disorder affecting women of reproductive age. A number of criteria have been developed for clinical diagnosis of polycystic ovary syndrome, with the Rotterdam criteria being the most inclusive. Evidence suggests that polycystic ovary syndrome is significantly heritable, and previous studies have identified genetic variants associated with polycystic ovary syndrome diagnosed using different criteria. The widely adopted electronic health record system provides an opportunity to identify patients with polycystic ovary syndrome using the Rotterdam criteria for genetic studies. OBJECTIVE: To identify novel associated genetic variants under the same phenotype definition, we extracted polycystic ovary syndrome cases and unaffected controls based on the Rotterdam criteria from the electronic health records and performed a discovery-validation genome-wide association study. STUDY DESIGN: We developed a polycystic ovary syndrome phenotyping algorithm on the basis of the Rotterdam criteria and applied it to 3 electronic health record-linked biobanks to identify cases and controls for genetic study. In the discovery phase, we performed an individual genome-wide association study using the Geisinger MyCode and the Electronic Medical Records and Genomics cohorts, which were then meta-analyzed. We attempted validation of the significant association loci (P<1×10-6) in the BioVU cohort. All association analyses used logistic regression, assuming an additive genetic model, and adjusted for principal components to control for population stratification. An inverse-variance fixed-effect model was adopted for meta-analysis. In addition, we examined the top variants to evaluate their associations with each criterion in the phenotyping algorithm. We used the STRING database to characterize protein-protein interaction network. RESULTS: Using the same algorithm based on the Rotterdam criteria, we identified 2995 patients with polycystic ovary syndrome and 53,599 population controls in total (2742 cases and 51,438 controls from the discovery phase; 253 cases and 2161 controls in the validation phase). We identified 1 novel genome-wide significant variant rs17186366 (odds ratio [OR]=1.37 [1.23, 1.54], P=2.8×10-8) located near SOD2. In addition, 2 loci with suggestive association were also identified: rs113168128 (OR=1.72 [1.42, 2.10], P=5.2×10-8), an intronic variant of ERBB4 that is independent from the previously published variants, and rs144248326 (OR=2.13 [1.52, 2.86], P=8.45×10-7), a novel intronic variant in WWTR1. In the further association tests of the top 3 single-nucleotide polymorphisms with each criterion in the polycystic ovary syndrome algorithm, we found that rs17186366 (SOD2) was associated with polycystic ovaries and hyperandrogenism, whereas rs11316812 (ERBB4) and rs144248326 (WWTR1) were mainly associated with oligomenorrhea or infertility. We also validated the previously reported association with DENND1A1. Using the STRING database to characterize protein-protein interactions, we found both ERBB4 and WWTR1 can interact with YAP1, which has been previously associated with polycystic ovary syndrome. CONCLUSION: Through a discovery-validation genome-wide association study on polycystic ovary syndrome identified from electronic health records using an algorithm based on Rotterdam criteria, we identified and validated a novel genome-wide significant association with a variant near SOD2. We also identified a novel independent variant within ERBB4 and a suggestive association with WWTR1. With previously identified polycystic ovary syndrome gene YAP1, the ERBB4-YAP1-WWTR1 network suggests involvement of the epidermal growth factor receptor and the Hippo pathway in the multifactorial etiology of polycystic ovary syndrome.

Genome-wide interaction with the insulin secretion locus MTNR1B reveals CMIP as a novel type 2 diabetes susceptibility gene in African Americans.

Although type 2 diabetes (T2D) results from metabolic defects in insulin secretion and insulin sensitivity, most of the genetic risk loci identified to date relates to insulin secretion. We reported that T2D loci influencing insulin sensitivity may be identified through interactions with insulin secretion loci, thereby leading to T2D. Here, we hypothesize that joint testing of variant main effects and interaction effects with an insulin secretion locus increases power to identify genetic interactions leading to T2D. We tested this hypothesis with an intronic MTNR1B SNP, rs10830963, which is associated with acute insulin response to glucose, a dynamic measure of insulin secretion. rs10830963 was tested for interaction and joint (main + interaction) effects with genome-wide data in African Americans (2,452 cases and 3,772 controls) from five cohorts. Genome-wide genotype data (Affymetrix Human Genome 6.0 array) was imputed to a 1000 Genomes Project reference panel. T2D risk was modeled using logistic regression with rs10830963 dosage, age, sex, and principal component as predictors. Joint effects were captured using the Kraft two degrees of freedom test. Genome-wide significant (P < 5 × 10-8 ) interaction with MTNR1B and joint effects were detected for CMIP intronic SNP rs17197883 (Pinteraction  = 1.43 × 10-8 ; Pjoint  = 4.70 × 10-8 ). CMIP variants have been nominally associated with T2D, fasting glucose, and adiponectin in individuals of East Asian ancestry, with high-density lipoprotein, and with waist-to-hip ratio adjusted for body mass index in Europeans. These data support the hypothesis that additional genetic factors contributing to T2D risk, including insulin sensitivity loci, can be identified through interactions with insulin secretion loci.

Genome-wide linkage and association analysis of cardiometabolic phenotypes in Hispanic Americans.

Linkage studies of complex genetic diseases have been largely replaced by genome-wide association studies, due in part to limited success in complex trait discovery. However, recent interest in rare and low-frequency variants motivates re-examination of family-based methods. In this study, we investigated the performance of two-point linkage analysis for over 1.6 million single-nucleotide polymorphisms (SNPs) combined with single variant association analysis to identify high impact variants, which are both strongly linked and associated with cardiometabolic traits in up to 1414 Hispanics from the Insulin Resistance Atherosclerosis Family Study (IRASFS). Evaluation of all 50 phenotypes yielded 83 557 000 LOD (logarithm of the odds) scores, with 9214 LOD scores ⩾3.0, 845 ⩾4.0 and 89 ⩾5.0, with a maximal LOD score of 6.49 (rs12956744 in the LAMA1 gene for tumor necrosis factor-α (TNFα) receptor 2). Twenty-seven variants were associated with P<0.005 as well as having an LOD score >4, including variants in the NFIB gene under a linkage peak with TNFα receptor 2 levels on chromosome 9. Linkage regions of interest included a broad peak (31 Mb) on chromosome 1q with acute insulin response (max LOD=5.37). This region was previously documented with type 2 diabetes in family-based studies, providing support for the validity of these results. Overall, we have demonstrated the utility of two-point linkage and association in comprehensive genome-wide array-based SNP genotypes.

The ras responsive transcription factor RREB1 is a novel candidate gene for type 2 diabetes associated end-stage kidney disease.

Familial clustering and presumed genetic risk for type 2 diabetic (T2D) and non-diabetic end-stage kidney disease (ESKD) appear strong in African Americans. Examination of exome sequencing data in African American T2D-ESKD cases and non-diabetic non-nephropathy controls identified two low-frequency variants in the RREB1 gene, a repressor of the angiotensinogen (AGT) gene previously associated with kidney function, as being associated with T2D-ESKD: rs9379084 (P = 0.00087, OR = 0.26; D1171N) and rs41302867 (P = 0.00078, OR = 0.21; splice site variant). Rs41302867 replicated association in an independent sample of African Americans with T2D-ESKD [rs41302867 P = 0.033 (OR = 0.50)], and a trend towards rs9379084 association was observed (P = 0.070). In European Americans with T2D-ESKD compared with European American population based controls, both RREB1 variants replicated association [rs9379084 P = 1.67 × 10(-4) (OR = 0.54) and rs41302867 P = 0.013 (OR = 0.69)]. Rs9379084 was not associated with non-T2D-ESKD or T2D in African Americans (P = 0.55 and P = 0.37, respectively), but was associated with T2D in European Americans (P = 0.014, OR = 0.65). In African Americans, rs41302867 was associated with non-T2D-ESKD [P = 0.036 (OR = 0.54)] and hypertension attributed ESKD [H-ESKD, P = 0.029 (OR = 0.50)]. A meta-analysis combining African American and European American T2D-ESKD data revealed P = 3.52 × 10(-7) and 3.70 × 10(-5) for rs9379084 and rs41302867 association, respectfully. A locus-wide analysis evaluating putatively functional SNPs revealed several nominal associations with T2D-ESKD, non-T2D-ESKD and T2D in African and European Americans. RREB1 is a large, complex gene which codes a multidomain zinc finger binding protein and transcription factor. We posit that variants in RREB1 modulate seemingly disparate phenotypes (i.e. T2D, T2D-ESKD and non-T2D-ESKD) through altered activity resulting from splice site and missense variants.

Association of kidney structure-related gene variants with type 2 diabetes-attributed end-stage kidney disease in African Americans.

African Americans (AAs) are at higher risk for developing end-stage kidney disease (ESKD) compared to European Americans. Genome-wide association studies have identified variants associated with diabetic and non-diabetic kidney diseases. Nephropathy loci, including SLC7A9, UMOD, and SHROOM3, have been implicated in the maintenance of normal glomerular and renal tubular structure and function. Herein, 47 genes important in podocyte, glomerular basement membrane, mesangial cell, mesangial matrix, renal tubular cell, and renal interstitium structure were examined for association with type 2 diabetes (T2D)-attributed ESKD in AAs. Single-variant association analysis was performed in the discovery stage, including 2041 T2D-ESKD cases and 1140 controls (non-diabetic, non-nephropathy). Discrimination analyses in 667 T2D cases-lacking nephropathy excluded T2D-associated SNPs. Nominal associations were tested in an additional 483 T2D-ESKD cases and 554 controls in the replication stage. Meta-analysis of 4218 discovery and replication samples revealed three significant associations with T2D-ESKD at CD2AP and MMP2 (P corr < 0.05 corrected for effective number of SNPs in each locus). Removal of APOL1 renal-risk genotype carriers revealed additional association at five loci, TTC21B, COL4A3, NPHP3-ACAD11, CLDN8, and ARHGAP24 (P corr < 0.05). Genetic variants at COL4A3, CLDN8, and ARHGAP24 were potentially pathogenic. Gene-based associations revealed suggestive significant aggregate effects of coding variants at four genes. Our findings suggest that genetic variation in kidney structure-related genes may contribute to T2D-attributed ESKD in the AA population.

A comparison of type 2 diabetes risk allele load between African Americans and European Americans.

The prevalence of type 2 diabetes (T2D) is greater in populations of African descent compared to European-descent populations. Genetic risk factors may underlie the disparity in disease prevalence. Genome-wide association studies (GWAS) have identified >60 common genetic variants that contribute to T2D risk in populations of European, Asian, African and Hispanic descent. These studies have not comprehensively examined population differences in cumulative risk allele load. To investigate the relationship between risk allele load and T2D risk, 46 T2D single nucleotide polymorphisms (SNPs) in 43 loci from GWAS in European, Asian, and African-derived populations were genotyped in 1,990 African Americans (n = 963 T2D cases, n = 1,027 controls) and 1,644 European Americans (n = 719 T2D cases, n = 925 controls) ascertained and recruited using a common protocol in the southeast United States. A genetic risk score (GRS) was constructed from the cumulative risk alleles for each individual. In African American subjects, risk allele frequencies ranged from 0.024 to 0.964. Risk alleles from 26 SNPs demonstrated directional consistency with previous studies, and 3 SNPs from ADAMTS9, TCF7L2, and ZFAND6 showed nominal evidence of association (p < 0.05). African American individuals carried 38-67 (53.7 ± 4.0, mean ± SD) risk alleles. In European American subjects, risk allele frequencies ranged from 0.084 to 0.996. Risk alleles from 36 SNPs demonstrated directional consistency, and 10 SNPs from BCL11A, PSMD6, ADAMTS9, ZFAND3, ANK1, CDKN2A/B, TCF7L2, PRC1, FTO, and BCAR1 showed evidence of association (p < 0.05). European American individuals carried 38-65 (50.9 ± 4.4) risk alleles. African Americans have a significantly greater burden of 2.8 risk alleles (p = 3.97 × 10(-89)) compared to European Americans. However, GRS modeling showed that cumulative risk allele load was associated with risk of T2D in European Americans, but only marginally in African Americans. This result suggests that there are ethnic-specific differences in genetic architecture underlying T2D, and that these differences complicate our understanding of how risk allele load impacts disease susceptibility.

EVALUATING THE RELATIONSHIPS BETWEEN GENETIC ANCESTRY AND THE CLINICAL PHENOME.

There is a desire in research to move away from the concept of race as a clinical factor because it is a societal construct used as an imprecise proxy for geographic ancestry. In this study, we leverage the biobank from Vanderbilt University Medical Center, BioVU, to investigate relationships between genetic ancestry proportion and the clinical phenome. For all samples in BioVU, we calculated six ancestry proportions based on 1000 Genomes references: eastern African (EAFR), western African (WAFR), northern European (NEUR), southern European (SEUR), eastern Asian (EAS), and southern Asian (SAS). From PheWAS, we found phecode categories significantly enriched neoplasms for EAFR, WAFR, and SEUR, and pregnancy complication in SEUR, NEUR, SAS, and EAS (p < 0.003). We then selected phenotypes hypertension (HTN) and atrial fibrillation (AFib) to further investigate the relationships between these phenotypes and EAFR, WAFR, SEUR, and NEUR using logistic regression modeling and non-linear restricted cubic spline modeling (RCS). For EAS and SAS, we chose renal failure (RF) for further modeling. The relationships between HTN and AFib and the ancestries EAFR, WAFR, and SEUR were best fit by the linear model (beta p < 1x10-4 for all) while the relationships with NEUR were best fit with RCS (HTN ANOVA p = 0.001, AFib ANOVA p < 1x10-4). For RF, the relationship with SAS was best fit with a linear model (beta p < 1x10-4) while RCS model was a better fit for EAS (ANOVA p < 1x10-4). In this study, we identify relationships between genetic ancestry and phenotypes that are best fit with non-linear modeling techniques. The assumption of linearity for regression modeling is integral for proper fitting of a model and there is no knowing a priori to modeling if the relationship is truly linear.

Genome-wide analysis in over 1 million individuals of European ancestry yields improved polygenic risk scores for blood pressure traits.

Hypertension affects more than one billion people worldwide. Here we identify 113 novel loci, reporting a total of 2,103 independent genetic signals (P < 5 × 10-8) from the largest single-stage blood pressure (BP) genome-wide association study to date (n = 1,028,980 European individuals). These associations explain more than 60% of single nucleotide polymorphism-based BP heritability. Comparing top versus bottom deciles of polygenic risk scores (PRSs) reveals clinically meaningful differences in BP (16.9 mmHg systolic BP, 95% CI, 15.5-18.2 mmHg, P = 2.22 × 10-126) and more than a sevenfold higher odds of hypertension risk (odds ratio, 7.33; 95% CI, 5.54-9.70; P = 4.13 × 10-44) in an independent dataset. Adding PRS into hypertension-prediction models increased the area under the receiver operating characteristic curve (AUROC) from 0.791 (95% CI, 0.781-0.801) to 0.826 (95% CI, 0.817-0.836, ∆AUROC, 0.035, P = 1.98 × 10-34). We compare the 2,103 loci results in non-European ancestries and show significant PRS associations in a large African-American sample. Secondary analyses implicate 500 genes previously unreported for BP. Our study highlights the role of increasingly large genomic studies for precision health research.

A genetically supported drug repurposing pipeline for diabetes treatment using electronic health records.

BACKGROUND: The identification of new uses for existing drug therapies has the potential to identify treatments for comorbid conditions that have the added benefit of glycemic control while also providing a rapid, low-cost approach to drug (re)discovery. METHODS: We developed and tested a genetically-informed drug-repurposing pipeline for diabetes management. This approach mapped genetically-predicted gene expression signals from the largest genome-wide association study for type 2 diabetes mellitus to drug targets using publicly available databases to identify drug-gene pairs. These drug-gene pairs were then validated using a two-step approach: 1) a self-controlled case-series (SCCS) using electronic health records from a discovery and replication population, and 2) Mendelian randomization (MR). FINDINGS: After filtering on sample size, 20 candidate drug-gene pairs were validated and various medications demonstrated evidence of glycemic regulation including two anti-hypertensive classes: angiotensin-converting enzyme inhibitors as well as calcium channel blockers (CCBs). The CCBs demonstrated the strongest evidence of glycemic reduction in both validation approaches (SCCS HbA1c and glucose reduction: -0.11%, p = 0.01 and -0.85 mg/dL, p = 0.02, respectively; MR: OR = 0.84, 95% CI = 0.81, 0.87, p = 5.0 x 10-25). INTERPRETATION: Our results support CCBs as a strong candidate medication for blood glucose reduction in addition to cardiovascular disease reduction. Further, these results support the adaptation of this approach for use in future drug-repurposing efforts for other conditions. FUNDING: National Institutes of Health, Medical Research Council Integrative Epidemiology Unit at the University of Bristol, UK Medical Research Council, American Heart Association, and Department of Veterans Affairs (VA) Informatics and Computing Infrastructure and VA Cooperative Studies Program.

Systematic replication of smoking disease associations using survey responses and EHR data in the All of Us Research Program.

OBJECTIVE: The All of Us Research Program (All of Us) aims to recruit over a million participants to further precision medicine. Essential to the verification of biobanks is a replication of known associations to establish validity. Here, we evaluated how well All of Us data replicated known cigarette smoking associations. MATERIALS AND METHODS: We defined smoking exposure as follows: (1) an EHR Smoking exposure that used International Classification of Disease codes; (2) participant provided information (PPI) Ever Smoking; and, (3) PPI Current Smoking, both from the lifestyle survey. We performed a phenome-wide association study (PheWAS) for each smoking exposure measurement type. For each, we compared the effect sizes derived from the PheWAS to published meta-analyses that studied cigarette smoking from PubMed. We defined two levels of replication of meta-analyses: (1) nominally replicated: which required agreement of direction of effect size, and (2) fully replicated: which required overlap of confidence intervals. RESULTS: PheWASes with EHR Smoking, PPI Ever Smoking, and PPI Current Smoking revealed 736, 492, and 639 phenome-wide significant associations, respectively. We identified 165 meta-analyses representing 99 distinct phenotypes that could be matched to EHR phenotypes. At P < .05, 74 were nominally replicated and 55 were fully replicated. At P < 2.68 × 10-5 (Bonferroni threshold), 58 were nominally replicated and 40 were fully replicated. DISCUSSION: Most phenotypes found in published meta-analyses associated with smoking were nominally replicated in All of Us. Both survey and EHR definitions for smoking produced similar results. CONCLUSION: This study demonstrated the feasibility of studying common exposures using All of Us data.

Using Mendelian randomisation to identify opportunities for type 2 diabetes prevention by repurposing medications used for lipid management.

BACKGROUND: Maintaining a healthy lifestyle to reduce type 2 diabetes (T2D) risk is challenging and additional strategies for T2D prevention are needed. We evaluated several lipid control medications as potential therapeutic options for T2D prevention using tissue-specific predicted gene expression summary statistics in a two-sample Mendelian randomisation (MR) design. METHODS: Large-scale European genome-wide summary statistics for lipids and T2D were leveraged in our multi-stage analysis to estimate changes in either lipid levels or T2D risk driven by tissue-specific predicted gene expression. We incorporated tissue-specific predicted gene expression summary statistics to proxy therapeutic effects of three lipid control medications [i.e., statins, icosapent ethyl (IPE), and proprotein convertase subtilisin/kexin type-9 inhibitors (PCSK-9i)] on T2D susceptibility using two-sample Mendelian randomisation (MR). FINDINGS: IPE, as proxied via increased FADS1 expression, was predicted to lower triglycerides and was associated with a 53% reduced risk of T2D. Statins and PCSK-9i, as proxied by reduced HMGCR and PCSK9 expression, respectively, were predicted to lower LDL-C levels but were not associated with T2D susceptibility. INTERPRETATION: Triglyceride lowering via IPE may reduce the risk of developing T2D in populations of European ancestry. However, experimental validation using animal models is needed to substantiate our results and to motivate randomized control trials (RCTs) for IPE as putative treatment for T2D prevention. FUNDING: Only summary statistics were used in this analysis. Funding information is detailed under Acknowledgments.

Genetic architecture of heart failure with preserved versus reduced ejection fraction.

Pharmacologic clinical trials for heart failure with preserved ejection fraction have been largely unsuccessful as compared to those for heart failure with reduced ejection fraction. Whether differences in the genetic underpinnings of these major heart failure subtypes may provide insights into the disparate outcomes of clinical trials remains unknown. We utilize a large, uniformly phenotyped, single cohort of heart failure sub-classified into heart failure with reduced and with preserved ejection fractions based on current clinical definitions, to conduct detailed genetic analyses of the two heart failure sub-types. We find different genetic architectures and distinct genetic association profiles between heart failure with reduced and with preserved ejection fraction suggesting differences in underlying pathobiology. The modest genetic discovery for heart failure with preserved ejection fraction (one locus) compared to heart failure with reduced ejection fraction (13 loci) despite comparable sample sizes indicates that clinically defined heart failure with preserved ejection fraction likely represents the amalgamation of several, distinct pathobiological entities. Development of consensus sub-phenotyping of heart failure with preserved ejection fraction is paramount to better dissect the underlying genetic signals and contributors to this highly prevalent condition.

Associations of biogeographic ancestry with hypertension traits.

OBJECTIVES: Ethnic disparities in hypertension prevalence are well documented, though the influence of genetic ancestry is unclear. The aim of this study was to evaluate associations of geographic genetic ancestry with hypertension and underlying blood pressure traits. METHODS: We tested genetically inferred ancestry proportions from five 1000 Genomes reference populations (GBR, PEL, YRI, CHB, and LWK) for association with four continuous blood pressure (BP) traits (SBP, DBP, PP, MAP) and the dichotomous outcomes hypertension and apparent treatment-resistant hypertension in 220 495 European American, 59 927 African American, and 21 273 Hispanic American individuals from the Million Veteran Program. Ethnicity stratified results were meta-analyzed to report effect estimates per 10% difference for a given ancestry proportion in all samples. RESULTS: Percentage GBR was negatively associated with BP (P = 2.13 × 10-19, 7.92 × 10-8, 4.41 × 10-11, and 3.57 × 10-13 for SBP, DBP, PP, and MAP, respectively; coefficient range -0.10 to -0.21 mmHg per 10% increase in ancestry proportion) and was protective against hypertension [P = 2.59 × 10-5, odds ratio (OR) = 0.98] relative to other ancestries. YRI percentage was positively associated with BP (P = 1.63 × 10-23, 1.94 × 10-26, 0.012, and 3.26 × 10-29 for SBP, DBP, PP, and MAP, respectively; coefficient range 0.06-0.32 mmHg per 10% increase in ancestry proportion) and was positively associated with hypertension risk (P = 3.10 × 10-11, OR = 1.04) and apparent treatment-resistant hypertension risk (P = 1.86 × 10-4, OR = 1.04) compared with other ancestries. Percentage PEL was inversely associated with DBP (P = 2.84 × 10-5, beta = -0.11 mmHg per 10% increase in ancestry proportion). CONCLUSION: These results demonstrate that risk for BP traits varies significantly by genetic ancestry. Our findings provide insight into the geographic origin of genetic factors underlying hypertension risk and establish that a portion of BP trait ethnic disparities are because of genetic differences between ancestries.