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

Kvale, Mark N.; Hesselson, Stephanie; Hoffmann, Thomas J.; Cao, Yang; Chan, David; Connell, Sheryl; Croen, Lisa; Dispensa, Brad; Eshragh, Jasmin L; Finn, Andrea; Gollub, Jeremy; Iribarren, Carlos; Jorgenson, Eric; Kushi, Lawrence H.; Lao, Richard; Lu, Yontao; Ludwig, Dana; Mathauda, Gurpreet K.; McGuire, William B.; Mei, Gangwu; Miles, Sunita; Mittman, Michael; Patil, Mohini A.; Quesenberry, Charles P.; Ranatunga, Dilrini K.; Rowell, Sarah; Sadler, Marianne; Sakoda, Lori C.; Shapero, Michael H.; Shen, Lei; Shenoy, Tanu; Smethurst, David; Somkin, Carol P.; Eeden, Stephen K. Van Den; Walter, Lawrence; Wan, Eunice; Webster, Teresa A.; Whitmer, Rachel A.; Wong, Simon; Zau, Chia; Zhan, Yiping; Schaefer, Catherine; Kwok, Pui‐Yan; Risch, Neil

doi:10.1534/genetics.115.178905

Cited by 181 publications

(187 citation statements)

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“…A total of 254,438 SNPs were common to all four arrays. Genotyping was performed at the University of California, San Francisco and is described elsewhere (Kvale et al 2015).…”

Section: Genotyping and Array Assignmentmentioning

confidence: 99%

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

et al. 2015

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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.

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“…A total of 254,438 SNPs were common to all four arrays. Genotyping was performed at the University of California, San Francisco and is described elsewhere (Kvale et al 2015).…”

Section: Genotyping and Array Assignmentmentioning

confidence: 99%

“…High-quality genotype data for the GERA cohort was obtained by systematic examination and removal of SNP genotypes according to a specific protocol, as described in detail elsewhere (Kvale et al 2015). For the genetic structure analyses, only SNPs that were common across all four arrays and that had a call rate .99.5% were considered.…”

Section: Quality Controlmentioning

confidence: 99%

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

et al. 2015

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“…The KPNC program was established to research genetic and environmental influences on health and disease and is described in more detail elsewhere (17). Recruitment began in 2007.…”

Section: Kpnc Participantsmentioning

confidence: 99%

Causal Effect of Genetic Variants Associated With Body Mass Index on Multiple Sclerosis Susceptibility

Gianfrancesco¹,

Glymour²,

Walter³

et al. 2017

Am. J. Epidemiol.

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Multiple sclerosis (MS) is an autoimmune disease with both genetic and environmental risk factors. Recent studies indicate that childhood and adolescent obesity double the risk of MS, but this association may reflect unmeasured confounders rather than causal effects of obesity. We used separate-sample Mendelian randomization to estimate the causal effect of body mass index (BMI) on susceptibility to MS. Using data from non-Hispanic white members of the Kaiser Permanente Medical Care Plan of Northern California (KPNC) (2006-2014; 1,104 cases of MS and 10,536 controls) and a replication data set from Sweden (the Epidemiological Investigation of MS (EIMS) and the Genes and Environment in MS (GEMS) studies, 2005-2013; 5,133 MS cases and 4,718 controls), we constructed a weighted genetic risk score using 97 variants previously established to predict BMI. Results were adjusted for birth year, sex, education, smoking status, ancestry, and genetic predictors of MS. Estimates in KPNC and Swedish data sets suggested that higher genetically induced BMI predicted greater susceptibility to MS (odds ratio = 1.13, 95% confidence interval: 1.04, 1.22 for the KPNC sample; odds ratio = 1.09, 95% confidence interval: 1.03, 1.15 for the Swedish sample). Although the mechanism remains unclear, to our knowledge, these findings support a causal effect of increased BMI on susceptibility to MS for the first time, and they suggest a role for inflammatory pathways that characterize both obesity and the MS disease process.

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“…19,20 Samples with dish QC o0.82 or initial genotype call rateo0.97 were excluded, resulting in a total of 83 285 individuals of Europeans ancestry. 23 To improve genotype calls, SNPs were re-called within packages of plates assayed under similar conditions (array type, reagent, hybridization time, and DNA concentration). SNPs were removed if either package call rate or overall call rate (across packages) was below 90%.…”

Section: Genotyping Qc Imputation and Genetic Ancestry Of The Geramentioning

confidence: 99%

Common coding variants in the HLA-DQB1 region confer susceptibility to age-related macular degeneration

et al. 2016

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Age-related macular degeneration (AMD) risk variants in the complement system point to the important role of immune response and inflammation in the pathogenesis of AMD. Although the human leukocyte antigen (HLA) region has a central role in regulating immune response, previous studies of genetic variation in HLA genes and AMD have been limited by sample size or incomplete coverage of the HLA region by first-generation genotyping arrays and imputation panels. Here, we conducted a large-scale HLA fine-mapping study with 4841 AMD cases and 23 790 controls of non-Hispanic white ancestry from the Kaiser Permanente Genetic Epidemiology Research on Adult Health and Aging cohort. Genotyping was conducted using custom Affymetrix Axiom arrays, with dense coverage of the HLA region. Classic HLA polymorphisms were imputed using SNP2HLA, which utilizes a large reference panel to provide improved imputation accuracy of variants in this region. We examined a total of 6937 SNPs and 172 classical HLA alleles, conditioning on established AMD risk variants, which revealed novel associations with two non-synonymous SNPs in perfect linkage disequilibrium, rs9274390 and rs41563814 (odds ratio (OR) = 1.21; P = 1.4 × 10 − 11 ) corresponding to amino-acid changes at position 66 and 67 in HLA-DQB1, respectively, and the DQB1*02 classical HLA allele (OR = 1.22; P = 3.9 × 10 − 10 ) with the risk of AMD. We confirmed these association signals, again conditioning on established risk variants, in the MMAP data set of subjects with advanced AMD (rs9274390/rs41563814: OR = 1.28; P = 1.30 × 10 − 3 , DQB1*02: OR = 1.32; P = 9.00 × 10 − 4 ). These findings support a role of HLA class II alleles in the risk of AMD. European Journal of Human Genetics (2016) 24, 1049-1055; doi:10.1038/ejhg.2015.247; published online 6 January 2016 INTRODUCTION Age-related macular degeneration (AMD) is a complex, late-onset vision disorder, which is the leading cause of blindness among the elderly in developed countries. [1][2][3][4] Immune response and inflammation play a causal role in the pathogenesis and progression of AMD. [5][6][7][8][9][10][11] The human leukocyte antigen (HLA) region on chromosome 6p21.31 encodes gene products that regulate immune response. Drusen, a pathologic hallmark of AMD, contain HLA class II antigens, 12 and increased HLA class II immunoreactivity has been associated with drusen formation, 13 suggesting that HLA may influence the development of AMD. Although a few small candidate gene studies found that certain HLA class I and class II polymorphisms were associated with a predisposition to AMD, 14,15 the largest genome-wide association study (GWAS) meta-analysis conducted by the AMD Gene Consortium, which included more than 77 000 subjects, did not identify any HLA polymorphisms that were independently associated with the risk of AMD. 16 The AMD Consortium meta-analysis, although well powered to detect common variants of small effect, included a number of studies that utilized genotyping arrays, with array density ranging from 165 770 ...

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

Cited by 181 publications

References 4 publications

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

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

Causal Effect of Genetic Variants Associated With Body Mass Index on Multiple Sclerosis Susceptibility

Common coding variants in the HLA-DQB1 region confer susceptibility to age-related macular degeneration

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