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Search Results: 1 - 10 of 142654 matches for " Daniel O Stram "
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Software for tag single nucleotide polymorphism selection
Daniel O Stram
Human Genomics , 2005, DOI: 10.1186/1479-7364-2-2-144
A Kinship-Based Modification of the Armitage Trend Test to Address Hidden Population Structure and Small Differential Genotyping Errors
Cyril S. Rakovski, Daniel O. Stram
PLOS ONE , 2009, DOI: 10.1371/journal.pone.0005825
Abstract: Background/Aims We propose a modification of the well-known Armitage trend test to address the problems associated with hidden population structure and hidden relatedness in genome-wide case-control association studies. Methods The new test adopts beneficial traits from three existing testing strategies: the principal components, mixed model, and genomic control while avoiding some of their disadvantageous characteristics, such as the tendency of the principal components method to over-correct in certain situations or the failure of the genomic control approach to reorder the adjusted tests based on their degree of alignment with the underlying hidden structure. The new procedure is based on Gauss-Markov estimators derived from a straightforward linear model with an imposed variance structure proportional to an empirical relatedness matrix. Lastly, conceptual and analytical similarities to and distinctions from other approaches are emphasized throughout. Results Our simulations show that the power performance of the proposed test is quite promising compared to the considered competing strategies. The power gains are especially large when small differential differences between cases and controls are present; a likely scenario when public controls are used in multiple studies. Conclusion The proposed modified approach attains high power more consistently than that of the existing commonly implemented tests. Its performance improvement is most apparent when small but detectable systematic differences between cases and controls exist.
Methodological Issues in Multistage Genome-Wide Association Studies
Duncan C. Thomas,Graham Casey,David V. Conti,Robert W. Haile,Juan Pablo Lewinger,Daniel O. Stram
Quantitative Biology , 2010, DOI: 10.1214/09-STS288
Abstract: Because of the high cost of commercial genotyping chip technologies, many investigations have used a two-stage design for genome-wide association studies, using part of the sample for an initial discovery of ``promising'' SNPs at a less stringent significance level and the remainder in a joint analysis of just these SNPs using custom genotyping. Typical cost savings of about 50% are possible with this design to obtain comparable levels of overall type I error and power by using about half the sample for stage I and carrying about 0.1% of SNPs forward to the second stage, the optimal design depending primarily upon the ratio of costs per genotype for stages I and II. However, with the rapidly declining costs of the commercial panels, the generally low observed ORs of current studies, and many studies aiming to test multiple hypotheses and multiple endpoints, many investigators are abandoning the two-stage design in favor of simply genotyping all available subjects using a standard high-density panel. Concern is sometimes raised about the absence of a ``replication'' panel in this approach, as required by some high-profile journals, but it must be appreciated that the two-stage design is not a discovery/replication design but simply a more efficient design for discovery using a joint analysis of the data from both stages. Once a subset of highly-significant associations has been discovered, a truly independent ``exact replication'' study is needed in a similar population of the same promising SNPs using similar methods.
Consistent Association of Type 2 Diabetes Risk Variants Found in Europeans in Diverse Racial and Ethnic Groups
Kevin M. Waters ,Daniel O. Stram,Mohamed T. Hassanein,Lo?c Le Marchand,Lynne R. Wilkens,Gertraud Maskarinec,Kristine R. Monroe,Laurence N. Kolonel,David Altshuler,Brian E. Henderson,Christopher A. Haiman
PLOS Genetics , 2010, DOI: 10.1371/journal.pgen.1001078
Abstract: It has been recently hypothesized that many of the signals detected in genome-wide association studies (GWAS) to T2D and other diseases, despite being observed to common variants, might in fact result from causal mutations that are rare. One prediction of this hypothesis is that the allelic associations should be population-specific, as the causal mutations arose after the migrations that established different populations around the world. We selected 19 common variants found to be reproducibly associated to T2D risk in European populations and studied them in a large multiethnic case-control study (6,142 cases and 7,403 controls) among men and women from 5 racial/ethnic groups (European Americans, African Americans, Latinos, Japanese Americans, and Native Hawaiians). In analysis pooled across ethnic groups, the allelic associations were in the same direction as the original report for all 19 variants, and 14 of the 19 were significantly associated with risk. In summing the number of risk alleles for each individual, the per-allele associations were highly statistically significant (P<10?4) and similar in all populations (odds ratios 1.09–1.12) except in Japanese Americans the estimated effect per allele was larger than in the other populations (1.20; Phet = 3.8×10?4). We did not observe ethnic differences in the distribution of risk that would explain the increased prevalence of type 2 diabetes in these groups as compared to European Americans. The consistency of allelic associations in diverse racial/ethnic groups is not predicted under the hypothesis of Goldstein regarding “synthetic associations” of rare mutations in T2D.
The Potential for Enhancing the Power of Genetic Association Studies in African Americans through the Reuse of Existing Genotype Data
Gary K. Chen,Robert C. Millikan,Esther M. John,Christine B. Ambrosone,Leslie Bernstein,Wei Zheng,Jennifer J. Hu,Stephen J. Chanock,Regina G. Ziegler,Elisa V. Bandera,Brian E. Henderson,Christopher A. Haiman,Daniel O. Stram
PLOS Genetics , 2010, DOI: 10.1371/journal.pgen.1001096
Abstract: We consider the feasibility of reusing existing control data obtained in genetic association studies in order to reduce costs for new studies. We discuss controlling for the population differences between cases and controls that are implicit in studies utilizing external control data. We give theoretical calculations of the statistical power of a test due to Bourgain et al (Am J Human Genet 2003), applied to the problem of dealing with case-control differences in genetic ancestry related to population isolation or population admixture. Theoretical results show that there may exist bounds for the non-centrality parameter for a test of association that places limits on study power even if sample sizes can grow arbitrarily large. We apply this method to data from a multi-center, geographically-diverse, genome-wide association study of breast cancer in African-American women. Our analysis of these data shows that admixture proportions differ by center with the average fraction of European admixture ranging from approximately 20% for participants from study sites in the Eastern United States to 25% for participants from West Coast sites. However, these differences in average admixture fraction between sites are largely counterbalanced by considerable diversity in individual admixture proportion within each study site. Our results suggest that statistical correction for admixture differences is feasible for future studies of African-Americans, utilizing the existing controls from the African-American Breast Cancer study, even if case ascertainment for the future studies is not balanced over the same centers or regions that supplied the controls for the current study.
Population Genetic Structure and Origins of Native Hawaiians in the Multiethnic Cohort Study
Sung K. Kim, Christopher R. Gignoux, Jeffrey D. Wall, Annette Lum-Jones, Hansong Wang, Christopher A. Haiman, Gary K. Chen, Brian E. Henderson, Laurence N. Kolonel, Loic Le Marchand, Daniel O. Stram, Richa Saxena, Iona Cheng
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0047881
Abstract: The population genetic structure of Native Hawaiians has yet to be comprehensively studied, and the ancestral origins of Polynesians remain in question. In this study, we utilized high-resolution genome-wide SNP data and mitochondrial genomes of 148 and 160 Native Hawaiians, respectively, to characterize their population structure of the nuclear and mitochondrial genomes, ancestral origins, and population expansion. Native Hawaiians, who self-reported full Native Hawaiian heritage, demonstrated 78% Native Hawaiian, 11.5% European, and 7.8% Asian ancestry with 99% belonging to the B4 mitochondrial haplogroup. The estimated proportions of Native Hawaiian ancestry for those who reported mixed ancestry (i.e. 75% and 50% Native Hawaiian heritage) were found to be consistent with their self-reported heritage. A significant proportion of Melanesian ancestry (mean = 32%) was estimated in 100% self-reported Native Hawaiians in an ADMIXTURE analysis of Asian, Melanesian, and Native Hawaiian populations of K = 2, where K denotes the number of ancestral populations. This notable proportion of Melanesian admixture supports the “Slow-Boat” model of migration of ancestral Polynesian populations from East Asia to the Pacific Islands. In addition, approximately 1,300 years ago a single, strong expansion of the Native Hawaiian population was estimated. By providing important insight into the underlying population structure of Native Hawaiians, this study lays the foundation for future genetic association studies of this U.S. minority population.
Recent breast cancer incidence trends according to hormone therapy use: the California Teachers Study cohort
Sarah F Marshall, Christina A Clarke, Dennis Deapen, Katherine Henderson, Joan Largent, Susan L Neuhausen, Peggy Reynolds, Giske Ursin, Pamela L Horn-Ross, Daniel O Stram, Claire Templeman, Leslie Bernstein
Breast Cancer Research , 2010, DOI: 10.1186/bcr2467
Abstract: We used the prospective California Teachers Study to evaluate changes in self-reported use of menopausal hormone therapy (HT) between 1995 to 1996 and 2005 to 2006 and age-adjusted breast cancer incidence among 74,647 participants aged 50 years or older. Breast cancer occurrence was determined by linkage with the California Cancer Registry.During 517,286 woman years of follow up, 565 in situ and 2,668 invasive breast cancers were diagnosed. In situ breast cancer incidence rates in this population did not change significantly from 2000 to 2002 to 2003 to 2005, whereas rates of invasive breast cancer declined significantly by 26.0% from 528.0 (95% confidence intervals (CI) = 491.1, 564.9) per 100,000 women in 2000 to 2002 to 390.6 (95% CI = 355.6, 425.7) in 2003 to 2005. The decline in invasive breast cancer incidence rates was restricted to estrogen receptor-positive tumors. In 1996 to 1999 and 2000 to 2002 invasive breast cancer incidence was higher for women who reported current HT use especially estrogen-progestin (EP) use at baseline than for never or past users; but by 2003 to 2005 rates were comparable between these groups. For women who were taking EP in 2001 to 2002,75% of whom had stopped use by 2005 to 2006, incidence had declined 30.6% by 2003 to 2005 (P = 0.001); whereas incidence did not change significantly for those who never took HT (P = 0.33).Few data resources can examine prospectively individual HT use and breast cancer diagnosis. Stable in situ breast cancer rates imply consistent levels of screening and suggest recent declines in invasive breast cancer to be explained predominantly by changes in HT use.Several reports document recent declines in the incidence of invasive breast cancer in the US [1-7] and throughout developed countries [8-13]. The reasons for and timing of these declines is controversial. Most researchers have suggested that the sharp decline observed in 2002 followed widespread reductions in prescribing [14] and use of menopausal
A comprehensive analysis of common genetic variation in prolactin (PRL) and PRL receptor (PRLR) genes in relation to plasma prolactin levels and breast cancer risk: the Multiethnic Cohort
Sulggi A Lee, Christopher A Haiman, Noel P Burtt, Loreall C Pooler, Iona Cheng, Laurence N Kolonel, Malcolm C Pike, David Altshuler, Joel N Hirschhorn, Brian E Henderson, Daniel O Stram
BMC Medical Genetics , 2007, DOI: 10.1186/1471-2350-8-72
Abstract: We evaluated genetic variation in the PRL and PRL receptor (PRLR) genes as predictors of plasma PRL levels and breast cancer risk among African-American, Native Hawaiian, Japanese-American, Latina, and White women in the Multiethnic Cohort Study (MEC). We selected single nucleotide polymorphisms (SNPs) from both the public (dbSNP) and private (Celera) databases to construct high density SNP maps that included up to 20 kilobases (kb) upstream of the transcription initiation site and 10 kb downstream of the last exon of each gene, for a total coverage of 59 kb in PRL and 210 kb in PRLR. We genotyped 80 SNPs in PRL and 173 SNPs in PRLR in a multiethnic panel of 349 unaffected subjects to characterize linkage disequilibrium (LD) and haplotype patterns. We sequenced the coding regions of PRL and PRLR in 95 advanced breast cancer cases (19 of each racial/ethnic group) to uncover putative functional variation. A total of 33 and 60 haplotype "tag" SNPs (tagSNPs) that allowed for high predictability (Rh2 ≥ 0.70) of the common haplotypes in PRL and PRLR, respectively, were then genotyped in a multiethnic breast cancer case-control study of 1,615 invasive breast cancer cases and 1,962 controls in the MEC. We also assessed the association of common genetic variation with circulating PRL levels in 362 postmenopausal controls without a history of hormone therapy use at blood draw. Because of the large number of comparisons being performed we used a relatively stringent type I error criteria (p < 0.0005) for evaluating the significance of any single association to correct for performing approximately 100 independent tests, close to the number of tagSNPs genotyped for both genes.We observed no significant associations between PRL and PRLR haplotypes or individual SNPs in relation to breast cancer risk. A nominally significant association was noted between prolactin levels and a tagSNP (tagSNP 44, rs2244502) in intron 1 of PRL. This SNP showed approximately a 50% increase in levels
Constitutively decreased TGFBR1 allelic expression is a common finding in colorectal cancer and is associated with three TGFBR1 SNPs
Boris Pasche, Kari B Wisinski, Maureen Sadim, Virginia Kaklamani, Michael J Pennison, Qinghua Zeng, Naresh Bellam, Jacquelyn Zimmerman, Nengjun Yi, Kui Zhang, John Baron, Daniel O Stram, M Geoffrey Hayes
Journal of Experimental & Clinical Cancer Research , 2010, DOI: 10.1186/1756-9966-29-57
Abstract: We assessed the frequency of constitutively decreased TGFBR1 allelic expression and association with SNPs covering the TGFBR1 locus using RNA and DNA extracted from the peripheral blood lymphocytes of 118 consecutive patients with biopsy-proven adenocarcinoma of the colon or the rectum.We found that 11(9.3%) of 118 patients exhibited decreased TGFBR1 allelic expression (TGFBR1 ASE). TGFBR1 ASE was strongly associated with three SNPs in linkage disequilibrium with each other: rs7034462 (p = 7.2 × 10-4), TGFBR1*6A (p = 1.6 × 10-4) and rs11568785 (p = 1.4 × 10-4).These results confirm the high prevalence of constitutively decreased TGFBR1 allelic expression among patients with colorectal cancer. The association of this phenotype with TGFBR1*6A, rs7034462 and rs1156875 suggests an association between TGFBR1 SNPs and colorectal cancer, which warrants additional studies.Clues regarding important genetic targets in colorectal cancer have come from the study of two hereditary neoplastic syndromes: Familial Adenomatous Polyposis (FAP) and Lynch syndrome, formerly named hereditary non-polyposis colorectal cancer (HNPCC). Although the genetic mechanisms underlying FAP and Lynch syndrome are well-understood, they only account for approximately 0.2% and 2% of all colorectal cancers, respectively. Inherited variants of the MYH gene have been shown to cause MYH-associated polyposis and are thought to account for an additional 1% of all colorectal cancers. Germline mutations of the STK11 gene underlie the Peutz-Jeghers syndrome, and mutations of SMAD4 and BMPR1A cause juvenile polyposis. Collectively, these syndromes account for 3 to 6% of all colorectal cancers[1].Much of the remaining familial colorectal cancers and a large proportion of sporadic cases are likely due to low-penetrance mutations, i.e. mutations that have low frequency of association with a specific phenotype[2]. Several recent genome-wide association studies have identified ten additional low penetrance susceptibi
Joint Effects of Known Type 2 Diabetes Susceptibility Loci in Genome-Wide Association Study of Singapore Chinese: The Singapore Chinese Health Study
Zhanghua Chen, Mark A. Pereira, Mark Seielstad, Woon-Puay Koh, E. Shyong Tai, Yik-Ying Teo, Jianjun Liu, Chris Hsu, Renwei Wang, Andrew O. Odegaard, Bharat Thyagarajan, Revati Koratkar, Jian-Min Yuan, Myron D. Gross, Daniel O. Stram
PLOS ONE , 2014, DOI: 10.1371/journal.pone.0087762
Abstract: Background Genome-wide association studies (GWAS) have identified genetic factors in type 2 diabetes (T2D), mostly among individuals of European ancestry. We tested whether previously identified T2D-associated single nucleotide polymorphisms (SNPs) replicate and whether SNPs in regions near known T2D SNPs were associated with T2D within the Singapore Chinese Health Study. Methods 2338 cases and 2339 T2D controls from the Singapore Chinese Health Study were genotyped for 507,509 SNPs. Imputation extended the genotyped SNPs to 7,514,461 with high estimated certainty (r2>0.8). Replication of known index SNP associations in T2D was attempted. Risk scores were computed as the sum of index risk alleles. SNPs in regions ±100 kb around each index were tested for associations with T2D in conditional fine-mapping analysis. Results Of 69 index SNPs, 20 were genotyped directly and genotypes at 35 others were well imputed. Among the 55 SNPs with data, disease associations were replicated (at p<0.05) for 15 SNPs, while 32 more were directionally consistent with previous reports. Risk score was a significant predictor with a 2.03 fold higher risk CI (1.69–2.44) of T2D comparing the highest to lowest quintile of risk allele burden (p = 5.72×10?14). Two improved SNPs around index rs10923931 and 5 new candidate SNPs around indices rs10965250 and rs1111875 passed simple Bonferroni corrections for significance in conditional analysis. Nonetheless, only a small fraction (2.3% on the disease liability scale) of T2D burden in Singapore is explained by these SNPs. Conclusions While diabetes risk in Singapore Chinese involves genetic variants, most disease risk remains unexplained. Further genetic work is ongoing in the Singapore Chinese population to identify unique common variants not already seen in earlier studies. However rapid increases in T2D risk have occurred in recent decades in this population, indicating that dynamic environmental influences and possibly gene by environment interactions complicate the genetic architecture of this disease.
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