Longitudinal electronic health records on 99,785 Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort individuals provided 1,342,814 systolic and diastolic blood pressure measurements for a genome-wide association study on long-term average systolic, diastolic, and pulse pressure. We identified 39 novel among 75 significant loci (P≤5×10−8), most replicating in the combined International Consortium for Blood Pressure (ICBP, n=69,396) and UK Biobank (UKB, n=152,081) studies. Combining GERA with ICBP yielded 36 additional novel loci, most replicating in UKB. Combining all three studies (n=321,262) yielded 241 additional genome-wide significant loci, although for these no replication sample was available. All associated loci explained 2.9%/2.5%/3.1% of systolic/diastolic/pulse pressure variation in GERA non-Hispanic whites. Using multiple BP measurements in GERA doubled the variance explained. A normalized risk score was associated with time-to-onset of hypertension (hazards ratio=1.18, P=10−44). Expression quantitative trait locus analysis of BP loci showed enrichment in aorta and tibial artery.

Using genome-wide genotypes, we characterized the genetic structure of 103,006 participants in the Kaiser Permanente Northern California multi-ethnic Genetic Epidemiology Research on Adult Health and Aging Cohort and analyzed the relationship to selfreported race/ethnicity. Participants endorsed any of 23 race/ethnicity/nationality categories, which were collapsed into seven major race/ ethnicity groups. By self-report the cohort is 80.8% white and 19.2% minority; 93.8% endorsed a single race/ethnicity group, while 6.2% endorsed two or more. Principal component (PC) and admixture analyses were generally consistent with prior studies. Approximately 17% of subjects had genetic ancestry from more than one continent, and 12% were genetically admixed, considering only nonadjacent geographical origins. Self-reported whites were spread on a continuum along the first two PCs, indicating extensive mixing among European nationalities. Self-identified East Asian nationalities correlated with genetic clustering, consistent with extensive endogamy. Individuals of mixed East AsianEuropean genetic ancestry were easily identified; we also observed a modest amount of European genetic ancestry in individuals selfidentified as Filipinos. Self-reported African Americans and Latinos showed extensive European and African genetic ancestry, and Native American genetic ancestry for the latter. Among 3741 genetically identified parent-child pairs, 93% were concordant for self-reported race/ ethnicity; among 2018 genetically identified full-sib pairs, 96% were concordant; the lower rate for parent-child pairs was largely due to intermarriage. The parent-child pairs revealed a trend toward increasing exogamy over time; the presence in the cohort of individuals endorsing multiple race/ethnicity categories creates interesting challenges and future opportunities for genetic epidemiologic studies.

A genome-wide association study of 94,674 multi-ethnic Kaiser Permanente members utilizing 478,866 longitudinal untreated serum lipid electronic-health-record-derived measurements (EHRs) empowered multiple novel findings: 121 new SNP associations (46 primary, 15 conditional, 60 in meta-analysis with Global Lipids Genetic Consortium); increase of 33-42% in variance explained with multiple measurements; sex differences in genetic impact (greater in females for LDL, HDL, TC, the opposite for TG); differences in variance explained amongst non-Hispanic whites, Latinos, African Americans, and East Asians; genetic dominance and epistasis, with strong evidence for both at ABOxFUT2 for LDL; and eQTL tissue-enrichment implicating the liver, adipose, and pancreas. Utilizing EHR pharmacy data, both LDL and TG genetic risk scores (477 SNPs) were strongly predictive of age-at-initiation of lipid-lowering treatment. These findings highlight the value of longitudinal EHRs for identifying novel genetic features of cholesterol and lipoprotein metabolism with implications for lipid treatment and risk of coronary heart disease.

The success of genome-wide association studies has paralleled the development of efficient genotyping technologies. We describe the development of a next-generation microarray based on the new highly-efficient Affymetrix Axiom genotyping technology that we are using to genotype individuals of European ancestry from the Kaiser Permanente Research Program on Genes, Environment and Health (RPGEH). The array contains 674,517 SNPs, and provides excellent genome-wide as well as gene-based and candidate-SNP coverage. Coverage was calculated using an approach based on imputation and cross validation. Preliminary results for the first 80,301 saliva-derived DNA samples from the RPGEH demonstrate very high quality genotypes, with sample success rates above 94% and over 98% of successful samples having SNP call rates exceeding 98%. At steady state, we have produced 462 million genotypes per week for each Axiom system. The new array provides a valuable addition to the repertoire of tools for large scale genome-wide association studies.

The Kaiser Permanente (KP) Research Program on Genes, Environment and Health (RPGEH), in collaboration with the University of California-San Francisco, undertook genome-wide genotyping of .100,000 subjects that constitute the Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort. The project, which generated .70 billion genotypes, represents the first large-scale use of the Affymetrix Axiom Genotyping Solution. Because genotyping took place over a short 14-month period, creating a near-real-time analysis pipeline for experimental assay quality control and final optimized analyses was critical. Because of the multi-ethnic nature of the cohort, four different ethnic-specific arrays were employed to enhance genome-wide coverage. All assays were performed on DNA extracted from saliva samples. To improve sample call rates and significantly increase genotype concordance, we partitioned the cohort into disjoint packages of plates with similar assay contexts. Using strict QC criteria, the overall genotyping success rate was 103,067 of 109,837 samples assayed (93.8%), with a range of 92.1-95.4% for the four different arrays. Similarly, the SNP genotyping success rate ranged from 98.1 to 99.4% across the four arrays, the variation depending mostly on how many SNPs were included as single copy vs. double copy on a particular array. The high quality and large scale of genotype data created on this cohort, in conjunction with comprehensive longitudinal data from the KP electronic health records of participants, will enable a broad range of highly powered genome-wide association studies on a diversity of traits and conditions. KEYWORDS genome-wide genotyping; GERA cohort; Affymetrix Axiom; saliva DNA; quality control T HE Genetic Epidemiology Research on Adult Health and Aging (GERA) resource is a cohort of .100,000 subjects who are participants in the Kaiser Permanente Medical Care Plan, Northern California Region (KPNC), Research Program on Genes, Environment and Health (RPGEH) (detailed description of the cohort and study design can be found in dbGaP, Study Accession: phs000674.v1.p1). Genome-wide genotyping was targeted for this cohort to enable large-scale genome-wide association studies by linkage to comprehensive longitudinal clinical data derived from extensive KPNC electronic health record databases. The cohort is multi-ethnic, with 20% minority representation (African American, East Asian, and Latino or mixed), and the remaining 80% nonHispanic white. For this project, four ethnic-specific arrays were designed based on the Affymetrix Axiom Genotyping System (Hoffmann et al. 2011a,b). The genotyping assay experiment took place over a 14-month period and to our knowledge, is the single largest genotyping experiment to date, producing .70 billion genotypes. The magnitude of the experiment, in conjunction with the long duration and simultaneous high throughput, required new protocols for assuring quality control (QC) during the assays and new genotyping strategies in postassay data analysis.Samp...

A genome-wide association study of prostate cancer in Kaiser Permanente health plan members (7,783 cases, 38,595 controls; 80.3% non-Hispanic white, 4.9% African-American, 7.0% East Asian, 7.8% Latino) revealed a new independent risk indel rs4646284 at the previously-identified locus 6q25.3 that replicated in PEGASUS (N=7,539) and MEC (N=4,679) (p=1.0×10−19, OR=1.18). Across the 6q25.3 locus, rs4646284 exhibited the strongest association with expression of SLC22A1 (p=1.3×10−23) and SLC22A3 (p=3.2×10−52). At the known 19q13.33 locus rs2659124 (p=1.3×10−13, OR=1.18) nominally replicated in PEGASUS. A risk score of 105 known risk SNPs was strongly associated with prostate cancer (p<1.0×10−8). Comparing the highest to lowest risk score deciles, the OR was 6.22 for non-Hispanic Whites, 5.82 for Latinos, 3.77 for African-Americans, and 3.38 for East Asians. In non-Hispanic whites, the 105 risk SNPs explained ~7.6% of disease heritability. The entire GWAS array explained ~33.4% of heritability, with a 4.3-fold enrichment within DNaseI hypersensitivity sites (p=0.004).

Prostate-specific antigen (PSA) levels have been used for detection and surveillance of prostate cancer (PCa). However, factors other than PCa—such as genetics—can impact PSA. Here we present findings from a genome-wide association study (GWAS) of PSA in 28,503 Kaiser Permanente whites and 17,428 men from replication cohorts. We detect 40 genome-wide significant (P<5 × 10−8) single-nucleotide polymorphisms (SNPs): 19 novel, 15 previously identified for PSA (14 of which were also PCa-associated), and 6 previously identified for PCa only. Further analysis incorporating PCa cases suggests that at least half of the 40 SNPs are PSA-associated independent of PCa. The 40 SNPs explain 9.5% of PSA variation in non-Hispanic whites, and the remaining GWAS SNPs explain an additional 31.7%; this percentage is higher in younger men, supporting the genetic basis of PSA levels. These findings provide important information about genetic markers for PSA that may improve PCa screening, thereby reducing over-diagnosis and over-treatment.

Background: Low-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, multi-ethnic population of statin users. Methods: We determined the effect of statin dosing on lipid measures utilizing electronic health records (EHRs) in 33,139 statin users from the Kaiser Permanente Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort. The relationship between statin defined daily dose (DDD) and lipid parameter response (percent change) was determined. Results: DDD and LDL-C response were associated in a log-linear relationship (β = −6.17, standard error [SE] = 0.09, P < 10−300) which remained significant after adjusting for pre-specified covariates (adjusted β = −5.59, SE = 0.12, P < 10−300). Statin type, sex, age, smoking status, diabetes, and East Asian race/ethnicity were significant independent predictors of statin-induced changes in LDL-C. Based on a variance-component method within the subset of statin users who had at least one first-degree relative who was also a statin user (N = 1,036), heritability of statin LDL-C response was estimated at 11.7% (SE = 8.6%, P = 0.087). Conclusions: Using EHR data, we observed a statin LDL-C dose response consistent with the “rule of 6%” from prior clinical trial data. Clinical and demographic predictors of statin LDL-C response exhibited highly significant, but modest effects. Finally, statin-induced changes in LDL-C were not found to be strongly inherited. Ultimately, these findings demonstrate (1) the utility of EHRs as a reliable source to generate robust phenotypes for pharmacogenomic research and (2) the potential role of statin precision medicine in lipid management.