748 research outputs found

    Semiparametric estimation exploiting covariate independence in two-phase randomized trials.

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    Recent results for case-control sampling suggest when the covariate distribution is constrained by gene-environment independence, semiparametric estimation exploiting such independence yields a great deal of efficiency gain. We consider the efficient estimation of the treatment-biomarker interaction in two-phase sampling nested within randomized clinical trials, incorporating the independence between a randomized treatment and the baseline markers. We develop a Newton-Raphson algorithm based on the profile likelihood to compute the semiparametric maximum likelihood estimate (SPMLE). Our algorithm accommodates both continuous phase-one outcomes and continuous phase-two biomarkers. The profile information matrix is computed explicitly via numerical differentiation. In certain situations where computing the SPMLE is slow, we propose a maximum estimated likelihood estimator (MELE), which is also capable of incorporating the covariate independence. This estimated likelihood approach uses a one-step empirical covariate distribution, thus is straightforward to maximize. It offers a closed-form variance estimate with limited increase in variance relative to the fully efficient SPMLE. Our results suggest exploiting the covariate independence in two-phase sampling increases the efficiency substantially, particularly for estimating treatment-biomarker interactions

    On Two-Stage Hypothesis Testing Procedures Via Asymptotically Independent Statistics

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    Kooperberg and LeBlanc (2008) proposed a two-stage testing procedure to screen for significant interactions in genome-wide association (GWA) studies by a soft threshold on marginal associations (MA), though its theoretical properties and generalization have not been elaborated. In this article, we discuss conditions that are required to achieve strong control of the Family-Wise Error Rate (FWER) by such procedures for low or high-dimensional hypothesis testing. We provide proof of asymptotic independence of marginal association statistics and interaction statistics in linear regression, logistic regression, and Cox proportional hazard models in a randomized clinical trial (RCT) with a rare event. In case-control studies nested within a RCT, a complementary criterion, namely deviation from baseline independence (DBI) in the case-control sample, is advocated as a screening tool for discovering significant interactions or main effects. Simulations and an application to a GWA study in Women’s Health Initiative (WHI) are presented to show utilities of the proposed two-stage testing procedures in pharmacogenetic studies

    Heterogeneity-aware integrative analyses for ancestry-specific association studies

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    Ancestry-specific proteome-wide association studies (PWAS) based on genetically predicted protein expression can reveal complex disease etiology specific to certain ancestral groups. These studies require ancestry-specific models for protein expression as a function of SNP genotypes. In order to improve protein expression prediction in ancestral populations historically underrepresented in genomic studies, we propose a new penalized maximum likelihood estimator for fitting ancestry-specific joint protein quantitative trait loci models. Our estimator borrows information across ancestral groups, while simultaneously allowing for heterogeneous error variances and regression coefficients. We propose an alternative parameterization of our model which makes the objective function convex and the penalty scale invariant. To improve computational efficiency, we propose an approximate version of our method and study its theoretical properties. Our method provides a substantial improvement in protein expression prediction accuracy in individuals of African ancestry, and in a downstream PWAS analysis, leads to the discovery of multiple associations between protein expression and blood lipid traits in the African ancestry population

    Genome-wide DNA replication profile for Drosophila melanogaster: a link between transcription and replication timing - Supplemental data.

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    Replication of the genome before mitotic cell division is a highly regulated process that ensures the fidelity of DNA duplication. DNA replication initiates at specific locations, termed origins of replication, and progresses in a defined temporal order during the S phase of the cell cycle. The relationship between replication timing and gene expression has been the subject of some speculation. A recent genome-wide analysis in Saccharomyces cerevisiae showed no association between replication timing and gene expression. In higher eukaryotes, the limited number of genomic loci analyzed has not permitted a firm conclusion regarding this association. To explore the relationship between DNA replication and gene expression in higher eukaryotes, we developed a strategy to measure the timing of DNA replication for thousands of genes in a single DNA array hybridization experiment. Using this approach, we generated a genome-wide map of replication timing for Drosophila melanogaster. Moreover, by surveying over 40% of all D. melanogaster genes, we found a strong correlation between DNA replication early in S phase and transcriptional activity. As this correlation does not exist in S. cerevisiae, this interplay between DNA replication and transcription may be a unique characteristic of higher eukaryotes

    To what extent can headteachers be held to account in the practice of social justice leadership?

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    Internationally, leadership for social justice is gaining prominence as a global travelling theme. This article draws from the Scottish contribution to the International School Leadership Development Network (ISLDN) social justice strand and presents a case study of a relatively small education system similar in size to that of New Zealand, to explore one system's policy expectations and the practice realities of headteachers (principals) seeking to address issues around social justice. Scottish policy rhetoric places responsibility with headteachers to ensure socially just practices within their schools. However, those headteachers are working in schools located within unjust local, national and international contexts. The article explores briefly the emerging theoretical analyses of social justice and leadership. It then identifies the policy expectations, including those within the revised professional standards for headteachers in Scotland. The main focus is on the headteachers' perspectives of factors that help and hinder their practice of leadership for social justice. Macro systems-level data is used to contextualize equity and outcomes issues that headteachers are working to address. In the analysis of the dislocation between policy and reality, the article asks, 'to what extent can headteachers be held to account in the practice of social justice leadership?

    Genome-wide Association and Population Genetic Analysis of C-Reactive Protein in African American and Hispanic American Women

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    C-reactive protein (CRP) is a systemic inflammation marker that predicts future cardiovascular risk. CRP levels are higher in African Americans and Hispanic Americans than in European Americans, but the genetic determinants of CRP in these admixed United States minority populations are largely unknown. We performed genome-wide association studies (GWASs) of 8,280 African American (AA) and 3,548 Hispanic American (HA) postmenopausal women from the Women's Health Initiative SNP Health Association Resource. We discovered and validated a CRP-associated variant of triggering receptors expressed by myeloid cells 2 (TREM2) in chromosomal region 6p21 (p = 10−10). The TREM2 variant associated with higher CRP is common in Africa but rare in other ancestral populations. In AA women, the CRP region in 1q23 contained a strong admixture association signal (p = 10−17), which appears to be related to several independent CRP-associated alleles; the strongest of these is present only in African ancestral populations and is associated with higher CRP. Of the other genomic loci previously associated with CRP through GWASs of European populations, most loci (LEPR, IL1RN, IL6R, GCKR, NLRP3, HNF1A, HNF4A, and APOC1) showed consistent patterns of association with CRP in AA and HA women. In summary, we have identified a common TREM2 variant associated with CRP in United States minority populations. The genetic architecture underlying the CRP phenotype in AA women is complex and involves genetic variants shared across populations, as well as variants specific to populations of African descent

    HNF1B and Endometrial Cancer Risk: Results from the PAGE study

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    We examined the association between HNF1B variants identified in a recent genome-wide association study and endometrial cancer in two large case-control studies nested in prospective cohorts: the Multiethnic Cohort Study (MEC) and the Women's Health Initiative (WHI) as part of the Population Architecture using Genomics and Epidemiology (PAGE) study. A total of 1,357 incident cases of invasive endometrial cancer and 7,609 controls were included in the analysis (MEC: 426 cases/3,854 controls; WHI: 931cases/3,755 controls). The majority of women in the WHI were European American, while the MEC included sizable numbers of African Americans, Japanese and Latinos. We estimated the odds ratios (ORs) per allele and 95% confidence intervals (CIs) of each SNP using unconditional logistic regression adjusting for age, body mass index, and four principal components of ancestry informative markers. The combined ORs were estimated using fixed effect models. Rs4430796 and rs7501939 were associated with endometrial cancer risk in MEC and WHI with no heterogeneity observed across racial/ethnic groups (P≥0.21) or between studies (P≥0.70). The ORper allele was 0.82 (95% CI: 0.75, 0.89; P = 5.63×10−6) for rs4430796 (G allele) and 0.79 (95% CI: 0.73, 0.87; P = 3.77×10−7) for rs7501939 (A allele). The associations with the risk of Type I and Type II tumors were similar (P≥0.19). Adjustment for additional endometrial cancer risk factors such as parity, oral contraceptive use, menopausal hormone use, and smoking status had little effect on the results. In conclusion, HNF1B SNPs are associated with risk of endometrial cancer and that the associated relative risks are similar for Type I and Type II tumors

    Leveraging Multi-ethnic Evidence for Mapping Complex Traits in Minority Populations: An Empirical Bayes Approach

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    Elucidating the genetic basis of complex traits and diseases in non-European populations is particularly challenging because US minority populations have been under-represented in genetic association studies. We developed an empirical Bayes approach named XPEB (cross-population empirical Bayes), designed to improve the power for mapping complex-trait-associated loci in a minority population by exploiting information from genome-wide association studies (GWASs) from another ethnic population. Taking as input summary statistics from two GWASs—a target GWAS from an ethnic minority population of primary interest and an auxiliary base GWAS (such as a larger GWAS in Europeans)—our XPEB approach reprioritizes SNPs in the target population to compute local false-discovery rates. We demonstrated, through simulations, that whenever the base GWAS harbors relevant information, XPEB gains efficiency. Moreover, XPEB has the ability to discard irrelevant auxiliary information, providing a safeguard against inflated false-discovery rates due to genetic heterogeneity between populations. Applied to a blood-lipids study in African Americans, XPEB more than quadrupled the discoveries from the conventional approach, which used a target GWAS alone, bringing the number of significant loci from 14 to 65. Thus, XPEB offers a flexible framework for mapping complex traits in minority populations
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