High blood pressure is a highly heritable and modifiable risk factor for cardiovascular disease. We report the largest genetic association study of blood pressure traits (systolic, diastolic, pulse pressure) to date in over one million people of European ancestry. We identify 535 novel blood pressure loci that not only offer new biological insights into blood pressure regulation but also reveal shared genetic architecture between blood pressure and lifestyle exposures. Our findings identify new biological pathways for blood pressure regulation with potential for improved cardiovascular disease prevention in the future.

In this trans-ethnic multi-omic study we reinterpret the genetic architecture of blood pressure to identify genes, tissues, phenome, and medication contexts of blood pressure homeostasis. We discovered 208 novel common blood pressure SNPs and 53 rare variants in GWASs of systolic, diastolic and pulse pressure in up to 776,078 participants from the Million Veteran Program (MVP) and collaborating studies, with analysis of the blood pressure clinical phenome in MVP. Our transcriptome-wide association study detected 4,043 blood pressure associations with genetically-predicted gene expression of 840 genes in 45 tissues, and murine renal single-cell RNA sequencing identified upregulated blood pressure genes in kidney tubule cells.

Elevated serum urate levels cause gout, and correlate with cardio-metabolic diseases via poorly understood mechanisms. We performed a trans-ethnic genome-wide association study of serum urate among 457,690 individuals, identifying 183 loci (147 novel) that improve prediction of gout in an independent cohort of 334,880 individuals. Serum urate showed significant genetic correlations with many cardio-metabolic traits, with genetic causality analyses supporting a substantial role for pleiotropy. Enrichment analysis, fine-mapping of urateassociated loci and co-localization with gene expression in 47 tissues implicated kidney and liver as main target organs and prioritized potentially causal genes and variants, including the transcriptional master regulators in liver and kidney, HNF1A and HNF4A. Experimental validation showed that HNF4A trans-activated the promoter of the major urate transporter ABCG2 in kidney cells, and that HNF4A p.Thr139Ile is a functional variant. Transcriptional coregulation within and across organs may be a general mechanism underlying the observed pleiotropy between urate and cardio-metabolic traits.

SummaryBackground and objectives Inaccurate determination of baseline kidney function can misclassify acute kidney injury (AKI) and affect the study of AKI-related outcomes. No consensus exists on how to optimally determine baseline kidney function when multiple preadmission creatinine measurements are available.Design, setting, participants, & measurements The accuracy of commonly used methods for estimating baseline serum creatinine was compared with that of a reference standard adjudicated by a panel of board-certified nephrologists in 379 patients with AKI or CKD admitted to a tertiary referral center.Results Agreement between estimating methods and the reference standard was highest when using creatinine values measured 7-365 days before admission. During this interval, the intraclass correlation coefficient (ICC) for the mean outpatient serum creatinine level (0.91 [95% confidence interval (CI), 0.88-0.92]) was higher than the most recent outpatient (ICC, 0.84 [95% CI, 0.80-0.88]; P,0.001) and the nadir outpatient (ICC, 0.83 [95% CI, 0.76-0.87; P,0.001) serum creatinine. Using the final creatinine value from a prior inpatient admission increased the ICC of the most recent outpatient creatinine method (0.88 [95% CI,). Performance of all methods declined or was unchanged when the time interval was broadened to 2 years or included serum creatinine measured within a week of admission. ConclusionsThe mean outpatient serum creatinine measured within a year of hospitalization most closely approximates nephrologist-adjudicated serum creatinine values.

Background The comparative effectiveness of sulfonylureas and metformin on cardiovascular disease (CVD) outcomes in type 2 diabetes are not well characterized. Objective To compare the effectiveness of sulfonylureas and metformin on the outcome of CVD (acute myocardial infarction, stroke) or death Design Retrospective cohort study Setting National Veterans Health Administration (VHA) databases linked to Medicare files Patients Veterans who initiated metformin or sulfonylureas for diabetes. Patients with chronic kidney disease or serious medical illness were excluded. Measurements Composite outcome of hospitalizations for acute myocardial infarction, stroke, or death. Cox regression analyses compared the incidence of the composite outcome between groups, adjusting for baseline demographics, medications, cholesterol, glycated hemoglobin, creatinine, blood pressure, body mass index, healthcare utilization and co-morbidities. Results Among 253,690 patients (98,665 sulfonylurea and 155,025 metformin initiators) the crude outcome rates were 18.2 and 10.4 per 1000 person-years in sulfonylurea and metformin users, respectively (adjusted hazard ratio [aHR] 1.21, 95% Confidence Intervals [CI] 1.13, 1.30). Results were consistent for both glyburide (aHR 1.26, 95% CI 1.16, 1.37) and glipizide (aHR 1.15, 95% CI 1.06, 1.26) as well as for those with prior history of CVD (aHR 1.25, 95% CI 1.13, 1.55) and without history of CVD (aHR: 1.16, 95% CI: 1.06, 1.29). Results were also consistent in a propensity score-matched analysis. For patients initiating sulfonylureas rather than metformin, we estimated an excess of 1 and 4 CVD events per 1000 person-years for those without and with a CVD history, respectively. Limitations Data on women and minorities is limited but reflective of the VHA population. Conclusions Use of sulfonylureas compared to metformin for initial treatment of diabetes was associated with an increased hazard of CVD events or death.

Increased levels of the urinary albumin-to-creatinine ratio (UACR) are associated with higher risk of kidney disease progression and cardiovascular events, but underlying mechanisms are incompletely understood. Here, we conduct trans-ethnic (n = 564,257) and European-ancestry specific meta-analyses of genome-wide association studies of UACR, including ancestry- and diabetes-specific analyses, and identify 68 UACR-associated loci. Genetic correlation analyses and risk score associations in an independent electronic medical records database (n = 192,868) reveal connections with proteinuria, hyperlipidemia, gout, and hypertension. Fine-mapping and trans-Omics analyses with gene expression in 47 tissues and plasma protein levels implicate genes potentially operating through differential expression in kidney (including TGFB1, MUC1, PRKCI, and OAF), and allow coupling of UACR associations to altered plasma OAF concentrations. Knockdown of OAF and PRKCI orthologs in Drosophila nephrocytes reduces albumin endocytosis. Silencing fly PRKCI further impairs slit diaphragm formation. These results generate a priority list of genes and pathways for translational research to reduce albuminuria.

Genes underneath signals from genome-wide association studies (GWAS) for kidney function are promising targets for functional studies, but prioritizing variants and genes is challenging. By GWAS meta-analysis for creatinine-based estimated glomerular filtration rate (eGFR) from the Chronic Kidney Disease Genetics Consortium and UK Biobank (n = 1,201,909), we expand the number of eGFRcrea loci (424 loci, 201 novel; 9.8% eGFRcrea variance explained by 634 independent signal variants). Our increased sample size in fine-mapping (n = 1,004,040, European) more than doubles the number of signals with resolved fine-mapping (99% credible sets down to 1 variant for 44 signals, ≤5 variants for 138 signals). Cystatin-based eGFR and/or blood urea nitrogen association support 348 loci (n = 460,826 and 852,678, respectively). Our customizable tool for Gene PrioritiSation reveals 23 compelling genes including mechanistic insights and enables navigation through genes and variants likely relevant for kidney function in human to help select targets for experimental follow-up.

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