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Lori C. Sakoda

Bio: Lori C. Sakoda is an academic researcher from Kaiser Permanente. The author has contributed to research in topics: Cancer & Population. The author has an hindex of 28, co-authored 92 publications receiving 2237 citations. Previous affiliations of Lori C. Sakoda include Fred Hutchinson Cancer Research Center.


Papers
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Journal ArticleDOI
TL;DR: Genome-wide association analyses based on whole-genome sequencing and imputation identify 40 new risk variants for colorectal cancer, including a strongly protective low-frequency variant at CHD1 and loci implicating signaling and immune function in disease etiology.
Abstract: To further dissect the genetic architecture of colorectal cancer (CRC), we performed whole-genome sequencing of 1,439 cases and 720 controls, imputed discovered sequence variants and Haplotype Reference Consortium panel variants into genome-wide association study data, and tested for association in 34,869 cases and 29,051 controls. Findings were followed up in an additional 23,262 cases and 38,296 controls. We discovered a strongly protective 0.3% frequency variant signal at CHD1. In a combined meta-analysis of 125,478 individuals, we identified 40 new independent signals at P < 5 × 10-8, bringing the number of known independent signals for CRC to ~100. New signals implicate lower-frequency variants, Kruppel-like factors, Hedgehog signaling, Hippo-YAP signaling, long noncoding RNAs and somatic drivers, and support a role for immune function. Heritability analyses suggest that CRC risk is highly polygenic, and larger, more comprehensive studies enabling rare variant analysis will improve understanding of biology underlying this risk and influence personalized screening strategies and drug development.

324 citations

Journal ArticleDOI
01 Aug 2015-Genetics
TL;DR: 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.
Abstract: 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.

274 citations

Journal ArticleDOI
01 Jan 2015-Genetics
TL;DR: 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.
Abstract: 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.

168 citations

Journal ArticleDOI
TL;DR: Although prior studies reported effects of ADH1B and ALDH2 on lifetime measures, such as risk of alcohol dependence, this study adds further evidence of the effect of the same genes on a cross-sectional measure of average drinking.
Abstract: Alcohol consumption is a complex trait determined by both genetic and environmental factors, and is correlated with the risk of alcohol use disorders. Although a small number of genetic loci have been reported to be associated with variation in alcohol consumption, genetic factors are estimated to explain about half of the variance in alcohol consumption, suggesting that additional loci remain to be discovered. We conducted a genome-wide association study (GWAS) of alcohol consumption in the large Genetic Epidemiology Research in Adult Health and Aging (GERA) cohort, in four race/ethnicity groups: non-Hispanic whites, Hispanic/Latinos, East Asians and African Americans. We examined two statistically independent phenotypes reflecting subjects' alcohol consumption during the past year, based on self-reported information: any alcohol intake (drinker/non-drinker status) and the regular quantity of drinks consumed per week (drinks/week) among drinkers. We assessed these two alcohol consumption phenotypes in each race/ethnicity group, and in a combined trans-ethnic meta-analysis comprising a total of 86 627 individuals. We observed the strongest association between the previously reported single nucleotide polymorphism (SNP) rs671 in ALDH2 and alcohol drinker status (odd ratio (OR)=0.40, P=2.28 × 10-72) in East Asians, and also an effect on drinks/week (beta=-0.17, P=5.42 × 10-4) in the same group. We also observed a genome-wide significant association in non-Hispanic whites between the previously reported SNP rs1229984 in ADH1B and both alcohol consumption phenotypes (OR=0.79, P=2.47 × 10-20 for drinker status and beta=-0.19, P=1.91 × 10-35 for drinks/week), which replicated in Hispanic/Latinos (OR=0.72, P=4.35 × 10-7 and beta=-0.21, P=2.58 × 10-6, respectively). Although prior studies reported effects of ADH1B and ALDH2 on lifetime measures, such as risk of alcohol dependence, our study adds further evidence of the effect of the same genes on a cross-sectional measure of average drinking. Our trans-ethnic meta-analysis confirmed recent findings implicating the KLB and GCKR loci in alcohol consumption, with strongest associations observed for rs7686419 (beta=-0.04, P=3.41 × 10-10 for drinks/week and OR=0.96, P=4.08 × 10-5 for drinker status), and rs4665985 (beta=0.04, P=2.26 × 10-8 for drinks/week and OR=1.04, P=5 × 10-4 for drinker status), respectively. Finally, we also obtained confirmatory results extending previous findings implicating AUTS2, SGOL1 and SERPINC1 genes in alcohol consumption traits in non-Hispanic whites.

122 citations

Journal ArticleDOI
TL;DR: Taken together, the findings of independent risk variants, ethnic variation in existing SNP replication, and remaining unexplained heritability have important implications for further clarifying the genetic risk of prostate cancer.
Abstract: A genome-wide association study (GWAS) 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, and 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 the Multiethnic Cohort ( N = 4,679) with an overall 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 approximately 7.6% of disease heritability. The entire GWAS array explained approximately 33.4% of heritability, with a 4.3-fold enrichment within DNaseI hypersensitivity sites ( P = 0.004). Significance: Taken together, our findings of independent risk variants, ethnic variation in existing SNP replication, and remaining unexplained heritability have important implications for further clarifying the genetic risk of prostate cancer. Our findings also suggest that there may be much promise in evaluating understudied variation, such as indels and ethnically diverse populations. Cancer Discov; 5(8); 878–91. ©2015 AACR . This article is highlighted in the In This Issue feature, [p. 783][1] [1]: /lookup/volpage/5/783?iss=8

115 citations


Cited by
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01 Feb 2015
TL;DR: In this article, the authors describe the integrative analysis of 111 reference human epigenomes generated as part of the NIH Roadmap Epigenomics Consortium, profiled for histone modification patterns, DNA accessibility, DNA methylation and RNA expression.
Abstract: The reference human genome sequence set the stage for studies of genetic variation and its association with human disease, but epigenomic studies lack a similar reference. To address this need, the NIH Roadmap Epigenomics Consortium generated the largest collection so far of human epigenomes for primary cells and tissues. Here we describe the integrative analysis of 111 reference human epigenomes generated as part of the programme, profiled for histone modification patterns, DNA accessibility, DNA methylation and RNA expression. We establish global maps of regulatory elements, define regulatory modules of coordinated activity, and their likely activators and repressors. We show that disease- and trait-associated genetic variants are enriched in tissue-specific epigenomic marks, revealing biologically relevant cell types for diverse human traits, and providing a resource for interpreting the molecular basis of human disease. Our results demonstrate the central role of epigenomic information for understanding gene regulation, cellular differentiation and human disease.

4,409 citations

Journal ArticleDOI
Naomi R. Wray1, Stephan Ripke2, Stephan Ripke3, Stephan Ripke4  +259 moreInstitutions (79)
TL;DR: A genome-wide association meta-analysis of individuals with clinically assessed or self-reported depression identifies 44 independent and significant loci and finds important relationships of genetic risk for major depression with educational attainment, body mass, and schizophrenia.
Abstract: Major depressive disorder (MDD) is a common illness accompanied by considerable morbidity, mortality, costs, and heightened risk of suicide. We conducted a genome-wide association meta-analysis based in 135,458 cases and 344,901 controls and identified 44 independent and significant loci. The genetic findings were associated with clinical features of major depression and implicated brain regions exhibiting anatomical differences in cases. Targets of antidepressant medications and genes involved in gene splicing were enriched for smaller association signal. We found important relationships of genetic risk for major depression with educational attainment, body mass, and schizophrenia: lower educational attainment and higher body mass were putatively causal, whereas major depression and schizophrenia reflected a partly shared biological etiology. All humans carry lesser or greater numbers of genetic risk factors for major depression. These findings help refine the basis of major depression and imply that a continuous measure of risk underlies the clinical phenotype.

1,898 citations

01 Jan 2010
TL;DR: In this paper, the authors show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait, revealing patterns with important implications for genetic studies of common human diseases and traits.
Abstract: Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P < 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.

1,751 citations

DOI
18 Feb 2015

1,457 citations