637 resultados para variation theory


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Using genome-wide data from 253,288 individuals, we identified 697 variants at genome-wide significance that together explained one-fifth of the heritability for adult height. By testing different numbers of variants in independent studies, we show that the most strongly associated approximately 2,000, approximately 3,700 and approximately 9,500 SNPs explained approximately 21%, approximately 24% and approximately 29% of phenotypic variance. Furthermore, all common variants together captured 60% of heritability. The 697 variants clustered in 423 loci were enriched for genes, pathways and tissue types known to be involved in growth and together implicated genes and pathways not highlighted in earlier efforts, such as signaling by fibroblast growth factors, WNT/beta-catenin and chondroitin sulfate-related genes. We identified several genes and pathways not previously connected with human skeletal growth, including mTOR, osteoglycin and binding of hyaluronic acid. Our results indicate a genetic architecture for human height that is characterized by a very large but finite number (thousands) of causal variants.

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Common diseases such as endometriosis (ED), Alzheimer's disease (AD) and multiple sclerosis (MS) account for a significant proportion of the health care burden in many countries. Genome-wide association studies (GWASs) for these diseases have identified a number of individual genetic variants contributing to the risk of those diseases. However, the effect size for most variants is small and collectively the known variants explain only a small proportion of the estimated heritability. We used a linear mixed model to fit all single nucleotide polymorphisms (SNPs) simultaneously, and estimated genetic variances on the liability scale using SNPs from GWASs in unrelated individuals for these three diseases. For each of the three diseases, case and control samples were not all genotyped in the same laboratory. We demonstrate that a careful analysis can obtain robust estimates, but also that insufficient quality control (QC) of SNPs can lead to spurious results and that too stringent QC is likely to remove real genetic signals. Our estimates show that common SNPs on commercially available genotyping chips capture significant variation contributing to liability for all three diseases. The estimated proportion of total variation tagged by all SNPs was 0.26 (SE 0.04) for ED, 0.24 (SE 0.03) for AD and 0.30 (SE 0.03) for MS. Further, we partitioned the genetic variance explained into five categories by a minor allele frequency (MAF), by chromosomes and gene annotation. We provide strong evidence that a substantial proportion of variation in liability is explained by common SNPs, and thereby give insights into the genetic architecture of the diseases.

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Population structure, including population stratification and cryptic relatedness, can cause spurious associations in genome-wide association studies (GWAS). Usually, the scaled median or mean test statistic for association calculated from multiple single-nucleotide-polymorphisms across the genome is used to assess such effects, and 'genomic control' can be applied subsequently to adjust test statistics at individual loci by a genomic inflation factor. Published GWAS have clearly shown that there are many loci underlying genetic variation for a wide range of complex diseases and traits, implying that a substantial proportion of the genome should show inflation of the test statistic. Here, we show by theory, simulation and analysis of data that in the absence of population structure and other technical artefacts, but in the presence of polygenic inheritance, substantial genomic inflation is expected. Its magnitude depends on sample size, heritability, linkage disequilibrium structure and the number of causal variants. Our predictions are consistent with empirical observations on height in independent samples of ~4000 and ~133,000 individuals.

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Genes in the TGF9 signaling pathway play important roles in the regulation of ovarian follicle growth and ovulation rate. Mutations in three genes in this pathway, growth differentiation factor 9 (GDF9), bone morphogenetic protein 15 (BMP15) and the bone morphogenetic protein receptor B 1 (BMPRB1), influence dizygotic (DZ) twinning rates in sheep. To date, only variants in GDF9 and BMP15, but not their receptors transforming growth factor ss receptor 1 (TGFBR1), bone morphogenetic protein receptor 2 (BMPR2) and BMPR1B, have been investigated with respect to their roles in human DZ twinning. We screened for rare and novel variants in TGFBR1, BMPR2 and BMPR1B in mothers of dizygotic twins (MODZT) from twin-dense families, and assessed association between genotyped and imputed variants and DZ twinning in another large sample of MODZT. Three novel variants were found: a deep intronic variant in BMPR2, and one intronic and one non-synonymous exonic variant in BMPRB1 which would result in the replacement of glutamine by glutamic acid at amino acid position 294 (p.Gln294Glu). None of these variants were predicted to have major impacts on gene function. However, the p.Gln294Glu variant changes the same amino acid as a sheep BMPR1B functional variant and may have functional consequences. Six BMPR1B variants were marginally associated with DZ twinning in the larger case-control sample, but these were no longer significant once multiple testing was taken into account. Our results suggest that variation in the TGF9 signaling pathway type II receptors has limited effects on DZ twinning rates in humans.

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Innovation enables organisations to endure by responding to emergence and to improve efficiency. Innovation in a complex organisation can be difficult due to complexities contributing to slow decision-making. Complex projects fail due to an inability to respond to emergence which consumes finances and impacts on resources and organisational success. Therefore, for complex organisations to improve on performance and resilience, it would be advantageous to understand how to improve the management of innovation and thus, the ability to respond to emergence. The benefits to managers are an increase in the number of successful projects and improved productivity. This study will explore innovation management in a complex project based organisation. The contribution to the academic literature will be an in-depth, qualitative exploration of innovation in a complex project based organisation using a comparative case study approach.

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This paper develops theory that quantifies transit route passenger-relative load factor and distinguishes it from occupancy load factor. The ratio between these measures is defined as the load diversity coefficient, which as a single measure characterizes the diversity of passenger load factor between route segments according to the origin-destination profile. The relationship between load diversity coefficient and route coefficient of variation in occupancy load factor is quantified. Two tables are provided that enhance passenger capacity and quality of service (QoS) assessment regarding onboard passenger load. The first expresses the transit operator’s perspective of load diversity and the passengers’ perspective of load factor relative to the operator’s, across six service levels corresponding to ranges of coefficient of variation in occupancy load factor. The second interprets the relationships between passenger average travel time and each of passenger-relative load factor and occupancy load factor. The application of this methodology is illustrated using a case study of a premium radial bus route in Brisbane, Australia. The methodology can assist in benchmarking and decision making regarding route and schedule design. Future research will apply value of time to QoS measurement, reflecting perceived passenger comfort through crowding and average time spent aboard. This would also assist in transit service quality econometric modeling.

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Endometriosis is a complex disease involving multiple susceptibility genes and environmental factors. Our previous studies on endometriosis identified a region of significant linkage on chromosome 10q. Two biological candidate genes (CYP17A1 and IFIT1) located on chromosome 10q, have previously been implicated in endometriosis and/or uterine function. We hypothesized that variation in CYP17A1 and/or IFIT1 could contribute to the risk of endometriosis and may account for some of the linkage signal on chromosome 10q. We genotyped 17 single nucleotide polymorphisms (SNPs) in the CYP17A1 and IFIT1 genes including SNP rs743572 previously associated with endometriosis in 768 endometriosis cases and 768 unrelated controls. We found no evidence for association between endometriosis and individual SNPs or SNP haplotypes in CYP17A1 and IFIT1. Common variation in these genes does not appear to be a major contributor to endometriosis susceptibility in our Australian sample.

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BACKGROUND Tumour necrosis factor (TNF) is a pleiotropic cytokine with a wide range of immunoregulatory effects. Variation in the promoter region of TNF and the neighbouring lymphotoxin alpha (LTA) gene might be associated with endometriosis. METHODS We examined the association between endometriosis and common single-nucleotide polymorphisms (SNPs) or haplotypes in the TNF/LTA region in an Australian sample by analysing 26 SNPs in 958 endometriosis cases and 959 unrelated controls. We selected functional SNPs in the coding and the promoter region of the TNF gene and HapMap tagging SNPs and typed them on a Sequenom MassARRAY platform. A key SNP (rs1800630) in the promoter region typed in previous studies did not give reliable results. Therefore, we also examined a statistically identical (r(2) = 1) SNP (siSNP) (rs2844482), identified using the web based program ssSNPer. RESULTS Genotype completion rate was 99.5% for SNPs spanning a region of 15.5 kb across the TNF/LTA locus. There was no evidence for association between endometriosis and TNF/LTA SNPs or SNP haplotypes in our case-control study. CONCLUSIONS Our data suggest both TNF and LTA genes are not major susceptibility genes for endometriosis.

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Endometriosis is a common gynaecological disease with symptoms of pelvic pain and infertility which affects 7-10% of women in their reproductive years. Activation of an oncogenic allele of Kirsten rat sarcoma viral oncogene homologue (KRAS) in the reproductive tract of mice resulted in the development of endometriosis. We hypothesized that variation in KRAS may influence risk of endometriosis in humans. Thirty tagSNPs spanning a region of 60.7 kb across the KRAS locus were genotyped using iPLEX chemistry on a MALDI-TOF MassARRAY platform in 959 endometriosis cases and 959 unrelated controls, and data were analysed for association with endometriosis. Genotypes were obtained for most individuals with a mean completion rate of 99.1%. We identified six haplotype blocks across the KRAS locus in our sample. There were no significant differences between cases and controls in the frequencies of individual single-nucleotide polymorphisms (SNPs) or haplotypes. We also developed a rapid method to screen for 11 common KRAS and BRAF mutations on the Sequenom MassARRAY system. The assay detected all mutations previously identified by direct sequencing in a panel of positive controls. No germline variants for KRAS or BRAF were detected. Our results demonstrate that any risk of endometriosis in women because of common variation in KRAS must be very small.

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I agree with Costanza and Finkelstein (2015) that it is futile to further invest in the study of generational differences in the work context due to a lack of appropriate theory and methods. The key problem with the generations concept is that splitting continuous variables such as age or time into a few discrete units involves arbitrary cutoffs and atheoretical groupings of individuals (e.g., stating that all people born between the early 1960s and early 1980s belong to Generation X). As noted by methodologists, this procedure leads to a loss of information about individuals and reduced statistical power (MacCallum, Zhang, Preacher, & Rucker, 2002). Due to these conceptual and methodological limitations, I regard it as very difficult if not impossible to develop a “comprehensive theory of generations” (Costanza & Finkelstein, p. 20) and to rigorously examine generational differences at work in empirical studies.

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Background Excessive speed is a primary contributing factor to young novice road trauma, including intentional and unintentional speeds above posted limits or too fast for conditions. The objective of this research was to conduct a systematic review of recent investigations into novice drivers’ speed selection, with particular attention to applications and limitations of theory and methodology. Method Systematic searches of peer-reviewed and grey literature were conducted during September 2014. Abstract reviews identified 71 references potentially meeting selection criteria of investigations since the year 2000 into factors that influence (directly or indirectly) actual speed (i.e., behaviour or performance) of young (age <25 years) and/or novice (recently-licensed) drivers. Results Full paper reviews resulted in 30 final references: 15 focused on intentional speeding and 15 on broader speed selection investigations. Both sets identified a range of individual (e.g., beliefs, personality) and social (e.g., peer, adult) influences, were predominantly theory-driven and applied cross-sectional designs. Intentional speed investigations largely utilised self-reports while other investigations more often included actual driving (simulated or ‘real world’). The latter also identified cognitive workload and external environment influences, as well as targeted interventions. Discussion and implications Applications of theory have shifted the novice speed-related literature beyond a simplistic focus on intentional speeding as human error. The potential to develop a ‘grand theory’ of intentional speeding emerged and to fill gaps to understand broader speed selection influences. This includes need for future investigations of vehicle-related and physical environment-related influences and methodologies that move beyond cross-sectional designs and rely less on self-reports.

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Measures of transit accessibility are important in evaluating transit services, planning for future services and investment on land use development. Existing tools measure transit accessibility using averaged walking distance or walking time to public transit. Although the mode captivity may have significant implications on one’s willingness to walk to use public transit, this has not been addressed in the literature to date. Failed to distinguish transit captive users may lead to overestimated ridership and spatial coverage of transit services. The aim of this research is to integrate the concept of transit captivity into the analysis of walking access to public transit. The conventional way of defining “captive” and “choice” transit users showed no significant difference in their walking times according to a preliminary analysis. A cluster analysis technique is used to further divide “choice” users by three main factors, namely age group, labour force status and personal income. After eliminating “true captive” users, defined as those without driver’s licence or without a car in respective household, “non-true captive” users were classified into a total of eight groups having similar socio-economic characteristics. The analysis revealed significant differences in the walking times and patterns by their level of captivity to public transit. This paper challenges the rule-of-thumb of 400m walking distance to bus stops. In average, people’s willingness to walk dropped drastically at 268m and continued to drop constantly until it reached the mark of 670m, where there was another drastic drop of 17%, which left with only 10% of the total bus riders willing to walk 670m or more. This research found that mothers working part time were the ones with lowest transit captivity and thus most sensitive to the walking time, followed by high-income earners and the elderly. The level of captivity increases when public transit users earned lesser income, such as students and students working part time.

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The adequacy and efficiency of existing legal and regulatory frameworks dealing with corporate phoenix activity have been repeatedly called into question over the past two decades through various reviews, inquiries, targeted regulatory operations and the implementation of piecemeal legislative reform. Despite these efforts, phoenix activity does not appear to have abated. While there is no law in Australia that declares ‘phoenix activity’ to be illegal, the behaviour that tends to manifest in phoenix activity can be capable of transgressing a vast array of law, including for example, corporate law, tax law, and employment law. This paper explores the notion that the persistence of phoenix activity despite the sheer extent of this law suggests that the law is not acting as powerfully as it might as a deterrent. Economic theories of entrepreneurship and innovation can to some extent explain why this is the case and also offer a sound basis for the evaluation and reconsideration of the existing law. The challenges facing key regulators are significant. Phoenix activity is not limited to particular corporate demographic: it occurs in SMEs, large companies and in corporate groups. The range of behaviour that can amount to phoenix activity is so broad, that not all phoenix activity is illegal. This paper will consider regulatory approaches to these challenges via analysis of approaches to detection and enforcement of the underlying law capturing illegal phoenix activity. Remedying the mischief of phoenix activity is of practical importance. The benefits include continued confidence in our economy, law that inspires best practice among directors, and law that is articulated in a manner such that penalties act as a sufficient deterrent and the regulatory system is able to detect offenders and bring them to account. Any further reforms must accommodate and tolerate legal phoenix activity, at least to some extent. Even then, phoenix activity pushes tolerance of repeated entrepreneurial failure to its absolute limit. The more limited liability is misused and abused, the stronger the argument to place some restrictions on access to limited liability. This paper proposes that such an approach is a legitimate next step for a robust and mature capitalist economy.

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The current state of the practice in Blackspot Identification (BSI) utilizes safety performance functions based on total crash counts to identify transport system sites with potentially high crash risk. This paper postulates that total crash count variation over a transport network is a result of multiple distinct crash generating processes including geometric characteristics of the road, spatial features of the surrounding environment, and driver behaviour factors. However, these multiple sources are ignored in current modelling methodologies in both trying to explain or predict crash frequencies across sites. Instead, current practice employs models that imply that a single underlying crash generating process exists. The model mis-specification may lead to correlating crashes with the incorrect sources of contributing factors (e.g. concluding a crash is predominately caused by a geometric feature when it is a behavioural issue), which may ultimately lead to inefficient use of public funds and misidentification of true blackspots. This study aims to propose a latent class model consistent with a multiple crash process theory, and to investigate the influence this model has on correctly identifying crash blackspots. We first present the theoretical and corresponding methodological approach in which a Bayesian Latent Class (BLC) model is estimated assuming that crashes arise from two distinct risk generating processes including engineering and unobserved spatial factors. The Bayesian model is used to incorporate prior information about the contribution of each underlying process to the total crash count. The methodology is applied to the state-controlled roads in Queensland, Australia and the results are compared to an Empirical Bayesian Negative Binomial (EB-NB) model. A comparison of goodness of fit measures illustrates significantly improved performance of the proposed model compared to the NB model. The detection of blackspots was also improved when compared to the EB-NB model. In addition, modelling crashes as the result of two fundamentally separate underlying processes reveals more detailed information about unobserved crash causes.