Gene-based multiple trait analysis for exome sequencing data

The common genetic variants identified through genome-wide association studies explain only a small proportion of the genetic risk for complex diseases. The advancement of next-generation sequencing technologies has enabled the detection of rare variants that are expected to contribute significantly to the missing heritability. Some genetic association studies provide multiple correlated traits for analysis. Multiple trait analysis has the potential to improve the power to detect pleiotropic genetic variants that influence multiple traits. We propose a gene-level association test for multiple traits that accounts for correlation among the traits. Gene- or region-level testing for association involves both common and rare variants. Statistical tests for common variants may have limited power for individual rare variants because of their low frequency and multiple testing issues. To address these concerns, we use the weighted-sum pooling method to test the joint association of multiple rare and common variants within a gene. The proposed method is applied to the Genetic Association Workshop 17 (GAW17) simulated mini-exome data to analyze multiple traits. Because of the nature of the GAW17 simulation model, increased power was not observed for multiple-trait analysis compared to single-trait analysis. However, multiple-trait analysis did not result in a substantial loss of power because of the testing of multiple traits. We conclude that this method would be useful for identifying pleiotropic genes

Turning the Tables: Media Constructions of British Asians from Victims to Criminals, 1962 to 2011

Book synopsis: Media, Crime and Racism draws together contributions from scholars at the leading edge of their field across three continents to present contemporary and longstanding debates exploring the roles played by media and the state in racialising crime and criminalising racialised minorities. Comprised of empirically rich accounts and theoretically informed analysis, this dynamic text offers readers a critical and in-depth examination of contemporary social and criminal justice issues as they pertain to racialised minorities and the media. Chapters demonstrate the myriad ways in which racialised ‘others’ experience demonisation, exclusion, racist abuse and violence licensed – and often induced – by the state and the media. Together, they also offer original and nuanced analysis of how these processes can be experienced differently dependent on geography, political context and local resistance. This collection critically reflects on a number of globally significant topics including the vilification of Muslim minorities, the portrayal of the refugee ‘crisis’ and the representations and resistance of Indigenous and Black communities. This volume demonstrates that processes of racialisation and criminalisation in media and the state cannot be understood without reference to how they are underscored and inflected by gender and power. Above all, the contributors to this volume demonstrate the resistance of racialised minorities in localised contexts across the globe: against racialisation and criminalisation and in pursuit of racial justice

Quantifying Selective Reporting and the Proteus Phenomenon for Multiple Datasets with Similar Bias

Meta-analyses play an important role in synthesizing evidence from diverse studies and datasets that address similar questions. A major obstacle for meta-analyses arises from biases in reporting. In particular, it is speculated that findings which do not achieve formal statistical significance are less likely reported than statistically significant findings. Moreover, the patterns of bias can be complex and may also depend on the timing of the research results and their relationship with previously published work. In this paper, we present an approach that is specifically designed to analyze large-scale datasets on published results. Such datasets are currently emerging in diverse research fields, particularly in molecular medicine. We use our approach to investigate a dataset on Alzheimer's disease (AD) that covers 1167 results from case-control studies on 102 genetic markers. We observe that initial studies on a genetic marker tend to be substantially more biased than subsequent replications. The chances for initial, statistically non-significant results to be published are estimated to be about 44% (95% CI, 32% to 63%) relative to statistically significant results, while statistically non-significant replications have almost the same chance to be published as statistically significant replications (84%; 95% CI, 66% to 107%). Early replications tend to be biased against initial findings, an observation previously termed Proteus phenomenon: The chances for non-significant studies going in the same direction as the initial result are estimated to be lower than the chances for non-significant studies opposing the initial result (73%; 95% CI, 55% to 96%). Such dynamic patters in bias are difficult to capture by conventional methods, where typically simple publication bias is assumed to operate. Our approach captures and corrects for complex dynamic patterns of bias, and thereby helps generating conclusions from published results that are more robust against the presence of different coexisting types of selective reporting

Aromatase expression is increased in BRCA1 mutation carriers

<p>Abstract</p> <p>Background</p> <p>Until recently, the molecular mechanisms explaining increased incidence of ovarian and breast cancers in carriers of <it>BRCA1 </it>gene mutations had not been clearly understood. Of significance is the finding that BRCA1 negatively regulates aromatase expression <it>in vitro</it>. Our objective was to characterise aromatase gene <it>(CYP19A1) </it>and its promoter expression in breast adipose and ovarian tissue in <it>BRCA1 </it>mutation carriers and unaffected controls.</p> <p>Methods</p> <p>We measured aromatase transcripts, total and promoter-specific (PII, PI.3, PI.4) in prophylactic oophorectomy or mastectomy, therapeutic mastectomy, ovarian and breast tissue from unaffected women.</p> <p>Results</p> <p>We demonstrate that the lack of functional BRCA1 protein correlates to higher aromatase levels in 85% of <it>BRCA1 </it>mutation carriers. This increase is mediated by aberrant transcriptional regulation of aromatase; in breast adipose by increases in promoter II/I.3 and I.4-specific transcripts; and in the ovary with elevation in promoter I.3 and II-specific transcripts.</p> <p>Conclusion</p> <p>Understanding the link between BRCA1 and aromatase is significant in terms of understanding why carcinogenesis is restricted to estrogen-producing tissues in <it>BRCA1 </it>mutation carriers.</p

Who Sets the Agenda? Analyzing Key Actors and Dynamics of Economic Diversification in Kazakhstan Throughout 2011–2016

This contribution attempts to answer the key question: Who sets the agenda for economic diversification in the context of Kazakhstan? This question remains critical in current scholarly debates. Although Kazakhstan, a young post-Soviet developing nation, has received fair scholarly attention with regard to the agenda setting stage of the policy cycle, the existing literature has yet failed to (1) empirically establish who actually sets the agenda for a certain policy issue and (2) employ the Internet research methods. This paper seeks to fill these gaps. The literature review of Kazakh-specific agenda setting publications suggests that among the major actors, the government tends to exert predominant influence, though other actors may also play a role, for example, media and academia. This research is driven by Internet penetration rate data and focuses on the period from January 2011 until December 2016. The findings lead to two key conclusions. First, think tanks seem to set the government agenda for economic diversification policy in Kazakhstan. Second, the government, while exhibiting the larger agenda setting magnitude vis-à-vis the other actors, shapes the subsequent debates as measured by the number of relevant references in media, think tanks, and academic publications. This research seeks to contribute to existing agenda setting theories in the Internet era by defining the most important actor(s), specifically in the Kazakh context based on longitudinal dynamics in attention

Ideological Labels in America

This paper extends Ellis and Stimson’s (Ideology in America. New York: Cambridge UniversityPress, 2012) study of the operational-symbolic paradox using issue-level measures of ideological incongruence based on respondent positions and symbolic labels for these positions across 14 issues. Like Ellis and Stimson, we find that substantial numbers—over 30 %—of Americans experience conflicted conservatism. Our issue-level data reveal, furthermore, that conflicted conservatism is most common on the issues of education and welfare spending. In addition, we also find that 20 % of Americans exhibit conflicted liberalism. We then replicate Ellis and Stimson’s finding that conflicted conservatism is associated with low sophistication and religiosity, but also find that it is associated with being socialized in a post-1960s generation and using Fox News as a main news source. Finally, we show the important role played by identities, with both conflicted conservatism and conflicted liberalism linked with partisan and ideological identities, and conflicted liberalism additionally associated with ethnic identities

Disruption of Mitochondrial DNA Replication in Drosophila Increases Mitochondrial Fast Axonal Transport In Vivo

Mutations in mitochondrial DNA polymerase (pol γ) cause several progressive human diseases including Parkinson's disease, Alper's syndrome, and progressive external ophthalmoplegia. At the cellular level, disruption of pol γ leads to depletion of mtDNA, disrupts the mitochondrial respiratory chain, and increases susceptibility to oxidative stress. Although recent studies have intensified focus on the role of mtDNA in neuronal diseases, the changes that take place in mitochondrial biogenesis and mitochondrial axonal transport when mtDNA replication is disrupted are unknown. Using high-speed confocal microscopy, electron microscopy and biochemical approaches, we report that mutations in pol γ deplete mtDNA levels and lead to an increase in mitochondrial density in Drosophila proximal nerves and muscles, without a noticeable increase in mitochondrial fragmentation. Furthermore, there is a rise in flux of bidirectional mitochondrial axonal transport, albeit with slower kinesin-based anterograde transport. In contrast, flux of synaptic vesicle precursors was modestly decreased in pol γ−α mutants. Our data indicate that disruption of mtDNA replication does not hinder mitochondrial biogenesis, increases mitochondrial axonal transport, and raises the question of whether high levels of circulating mtDNA-deficient mitochondria are beneficial or deleterious in mtDNA diseases

A 32 kb Critical Region Excluding Y402H in CFH Mediates Risk for Age-Related Macular Degeneration

Complement factor H shows very strong association with Age-related Macular Degeneration (AMD), and recent data suggest that multiple causal variants are associated with disease. To refine the location of the disease associated variants, we characterized in detail the structural variation at CFH and its paralogs, including two copy number polymorphisms (CNP), CNP147 and CNP148, and several rare deletions and duplications. Examination of 34 AMD-enriched extended families (N = 293) and AMD cases (White N = 4210 Indian = 134; Malay = 140) and controls (White N = 3229; Indian = 117; Malay = 2390) demonstrated that deletion CNP148 was protective against AMD, independent of SNPs at CFH. Regression analysis of seven common haplotypes showed three haplotypes, H1, H6 and H7, as conferring risk for AMD development. Being the most common haplotype H1 confers the greatest risk by increasing the odds of AMD by 2.75-fold (95% CI = [2.51, 3.01]; p = 8.31×10−109); Caucasian (H6) and Indian-specific (H7) recombinant haplotypes increase the odds of AMD by 1.85-fold (p = 3.52×10−9) and by 15.57-fold (P = 0.007), respectively. We identified a 32-kb region downstream of Y402H (rs1061170), shared by all three risk haplotypes, suggesting that this region may be critical for AMD development. Further analysis showed that two SNPs within the 32 kb block, rs1329428 and rs203687, optimally explain disease association. rs1329428 resides in 20 kb unique sequence block, but rs203687 resides in a 12 kb block that is 89% similar to a noncoding region contained in ΔCNP148. We conclude that causal variation in this region potentially encompasses both regulatory effects at single markers and copy number

Epistatic Module Detection for Case-Control Studies: A Bayesian Model with a Gibbs Sampling Strategy

The detection of epistatic interactive effects of multiple genetic variants on the susceptibility of human complex diseases is a great challenge in genome-wide association studies (GWAS). Although methods have been proposed to identify such interactions, the lack of an explicit definition of epistatic effects, together with computational difficulties, makes the development of new methods indispensable. In this paper, we introduce epistatic modules to describe epistatic interactive effects of multiple loci on diseases. On the basis of this notion, we put forward a Bayesian marker partition model to explain observed case-control data, and we develop a Gibbs sampling strategy to facilitate the detection of epistatic modules. Comparisons of the proposed approach with three existing methods on seven simulated disease models demonstrate the superior performance of our approach. When applied to a genome-wide case-control data set for Age-related Macular Degeneration (AMD), the proposed approach successfully identifies two known susceptible loci and suggests that a combination of two other loci—one in the gene SGCD and the other in SCAPER—is associated with the disease. Further functional analysis supports the speculation that the interaction of these two genetic variants may be responsible for the susceptibility of AMD. When applied to a genome-wide case-control data set for Parkinson's disease, the proposed method identifies seven suspicious loci that may contribute independently to the disease