Characterizing Race/Ethnicity and Genetic Ancestry for 100,000 Subjects in the Genetic Epidemiology Research on Adult Health and Aging (GERA) Cohort.

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 self-reported 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 Asian-European genetic ancestry were easily identified; we also observed a modest amount of European genetic ancestry in individuals self-identified 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.

Automated Assay of Telomere Length Measurement and Informatics for 100,000 Subjects in the Genetic Epidemiology Research on Adult Health and Aging (GERA) Cohort.

The Kaiser Permanente Research Program on Genes, Environment, and Health (RPGEH) Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort includes DNA specimens extracted from saliva samples of 110,266 individuals. Because of its relationship to aging, telomere length measurement was considered an important biomarker to develop on these subjects. To assay relative telomere length (TL) on this large cohort over a short time period, we created a novel high throughput robotic system for TL analysis and informatics. Samples were run in triplicate, along with control samples, in a randomized design. As part of quality control, we determined the within-sample variability and employed thresholds for the elimination of outlying measurements. Of 106,902 samples assayed, 105,539 (98.7%) passed all quality control (QC) measures. As expected, TL in general showed a decline with age and a sex difference. While telomeres showed a negative correlation with age up to 75 years, in those older than 75 years, age positively correlated with longer telomeres, indicative of an association of longer telomeres with more years of survival in those older than 75. Furthermore, while females in general had longer telomeres than males, this difference was significant only for those older than age 50. An additional novel finding was that the variance of TL between individuals increased with age. This study establishes reliable assay and analysis methodologies for measurement of TL in large, population-based human studies. The GERA cohort represents the largest currently available such resource, linked to comprehensive electronic health and genotype data for analysis.

Genotyping Informatics and Quality Control for 100,000 Subjects in the Genetic Epidemiology Research on Adult Health and Aging (GERA) Cohort.

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.