603 resultados para Virginia Press Association
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Background There is some apparent confusion regarding similarities and differences between two popular physical education (PE) pedagogical frameworks, that is, the Constraints-Led Approach (CLA) and Teaching Games for Understanding (TGfU). Purpose Our aim in this commentary is to detail important theoretical and pedagogical concepts that distinguish these approaches, as well as to recognise where commonalities exist. Findings In particular, we note that TGfU had its roots in the 1960s in the absence of a substantial theoretical framework, although several attempts to retrospectively scaffold theories around TGfU have subsequently emerged in the literature. TGfU is a learner-centred approach to PE in which teachers are encouraged to design modified games to develop the learner's understanding of tactical concepts. In contrast, the CLA has arisen more recently from the umbrella of Nonlinear Pedagogy (NLP), emerging from the empirically rich theoretical framework of ecological dynamics. The CLA adopts a ‘learner–environment’ scale of analysis in which practitioners are encouraged to identify and modify interacting constraints (of task, environment and learner) to facilitate the coupling of each learner's perceptual and action systems during learning. The CLA is a broader framework which has been adapted for the design of (re)learning environments in PE, sport and movement therapy. Other key distinctions between the approaches include: the overall goals; the way in which the learner and the learning process are modelled; the use of questioning as a pedagogical tool; the focus on individual differences vs. generic concepts; and how progressions and skill interjections are planned and implemented. Conclusions Despite such distinctions, the two approaches are somewhat harmonious and key similarities include: their holistic perspective of the learner; the proposed role of the teacher and the design characteristics of learning tasks in each. Both TGfU and the CLA have a powerful central focus on the nature of learning activities undertaken by each individual learner. This clarification of TGFU and the CLA is intended to act as a catalyst for more empirical work into the complementarity of these juxtaposed pedagogical approaches to learning design.
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The zombie has long been regarded as a “fundamentally American creation” (Bishop 2010) and a western monster representing the fears and anxieties of Western society. Since the renaissance of the zombie movie in the early 2000s, a subsequent surge in international production has seen the release of movies from Norway, Cuba, Pakistan and Thailand to name a few. Although Japanese zombie movies have been far more visible for Western cult audiences than in mainstream markets, Japanese cinema has emerged as one of the more prolific producers of zombie films outside of Anglophone or Western European countries in recent years. Films such as Helldriver (2010), Zombie TV (2013), Versus (2000), Tokyo Zombie (2005), Happiness of the Katakuris (2001) and anime television series High School of the Dead (2010) have generated varying degrees of popularity and critical attention internationally. At first glance Japanese zombie films, with musical zombie interludes, undead yakuza henchmen and revenge-seeking yūrei zombies, appear fundamentally different to their Western counterparts. Yet, on closer examination, the Japanese zombie movie could be regarded as a hybrid and intertextual generic form drawing on syntactic conventions at the core of a universal zombie sub-genre established by Western filmmaking traditions, while also distilling culturally specific tropes unique to various Japanese horror cinema sub-genres. Most importantly, the Japanese zombie film extracts, emphasises and revises particular conventions and motifs common within Western zombie films that are particularly relevant to Japanese audiences. This chapter investigates the cultural resonance of key generic motifs identifiable in the Japanese zombie film. It establishes a production context and the influence of Japanese horror cinema on style and thematic concerns. It then examines the function of prominent narrative conventions, namely: the source, outbreak and spread of infection; mutation and the representation of the monster; and the inclusion of supernatural and religious motifs.
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There is some evidence that self-rated perceptions of health are predictive of objective health outcomes, including cardiovascular disease, and mortality. The objective of this study was to examine the prospective association between perceptions of health during pregnancy and cardiovascular risk factors of mothers 21 years after the pregnancy. Data used were from the Mater University Study of Pregnancy (MUSP), a community-based prospective birth cohort study begun in Brisbane, Australia, in 1981. Logistic regression analyses were conducted. Data were available for 3692 women. Women who perceived themselves as not having a straight forward pregnancy had twice the odds (adjusted OR 2.0, 95% CI 1.1–3.8) of being diagnosed with heart disease 21 years after the pregnancy when compared with women with a straight forward pregnancy (event rate of 5.2 versus 2.6%). Women who experienced complications (other than serious pregnancy complications) during their pregnancy were also at 30% increased odds (adjusted OR 1.3, 95% CI 1.0–1.6) of having hypertension 21years later (event rate of 25.7 versus 20%). As a whole, our study sug- gests that pregnant women who perceived that they had complications and did not have a straight forward preg- nancy were likely to experience poorer cardiovascular outcomes 21years after that pregnancy.
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Metabolites are small molecules involved in cellular metabolism, which can be detected in biological samples using metabolomic techniques. Here we present the results of genome-wide association and meta-analyses for variation in the blood serum levels of 129 metabolites as measured by the Biocrates metabolomic platform. In a discovery sample of 7,478 individuals of European descent, we find 4,068 genome- and metabolome-wide significant (Z-test, P<1.09 × 10−9) associations between single-nucleotide polymorphisms (SNPs) and metabolites, involving 59 independent SNPs and 85 metabolites. Five of the fifty-nine independent SNPs are new for serum metabolite levels, and were followed-up for replication in an independent sample (N=1,182). The novel SNPs are located in or near genes encoding metabolite transporter proteins or enzymes (SLC22A16, ARG1, AGPS and ACSL1) that have demonstrated biomedical or pharmaceutical importance. The further characterization of genetic influences on metabolic phenotypes is important for progress in biological and medical research.
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Shorter telomere length (TL) has found to be associated with lower birth weight and with lower cognitive ability and psychiatric disorders. However, the direction of causation of these associations and the extent to which they are genetically or environmentally mediated are unclear. Within-pair comparisons of monozygotic (MZ) and dizygotic (DZ) twins can throw light on these questions. We investigated correlations of within pair differences in telomere length, IQ, and anxiety/depression in an initial sample from Brisbane (242 MZ pairs, 245 DZ same sex (DZSS) pairs) and in replication samples from Amsterdam (514 MZ pairs, 233 DZSS pairs) and Melbourne (19 pairs selected for extreme high or low birth weight difference). Intra-pair differences of birth weight and telomere length were significantly correlated in MZ twins, but not in DZSS twins. Greater intra-pair differences of telomere length were observed in the 10% of MZ twins with the greatest difference in birth weight compared to the bottom 90% in both samples and also in the Melbourne sample. Intra-pair differences of telomere length and IQ, but not of TL and anxiety/depression, were correlated in MZ twins, and to a smaller extent in DZSS twins. Our findings suggest that the same prenatal effects that reduce birth weight also influence telomere length in MZ twins. The association between telomere length and IQ is partly driven by the same prenatal effects that decrease birth weight.
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Endometriosis is a complex disease that affects 6-10% of women in their reproductive years and 20-50% of women with infertility. Genome-wide and candidate-gene association studies for endometriosis have identified 10 independent risk loci, and of these, nine (rs7521902, rs13394619, rs4141819, rs6542095, rs1519761, rs7739264, rs12700667, rs1537377, and rs10859871) are polymorphic in European populations. Here we investigate the replication of nine SNP loci in 998 laparoscopically and histologically confirmed endometriosis cases and 783 disease-free controls from Belgium. SNPs rs7521902, rs13394619, and rs6542095 show nominally significant (p <.05) associations with endometriosis, while the directions of effect for seven SNPs are consistent with the original reports. Association of rs6542095 at the IL1A locus with 'All' (p =.066) and 'Grade-B' (p =.01) endometriosis is noteworthy because this is the first successful replication in an independent population. Meta-analysis with the published results yields genome-wide significant evidence for rs7521902, rs13394619, rs6542095, rs12700667, rs7739264, and rs1537377. Notably, three coding variants in GREB1 (near rs13394619) and CDKN2B-AS1 (near rs1537377) also showed nominally significant associations with endometriosis. Overall, this study provides important replication in a uniquely characterized independent population, and indicates that the majority of the original genome-wide association findings are not due to chance alone. © The Author(s) 2015.
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Introduction: It is unclear whether patients diagnosed according to International Classification of Headache Disorders criteria for migraine with aura (MA) and migraine without aura (MO) experience distinct disorders or whether their migraine subtypes are genetically related. Aim: Using a novel gene-based (statistical) approach, we aimed to identify individual genes and pathways associated both with MA and MO. Methods: Gene-based tests were performed using genome-wide association summary statistic results from the most recent International Headache Genetics Consortium study comparing 4505 MA cases with 34,813 controls and 4038 MO cases with 40,294 controls. After accounting for non-independence of gene-based test results, we examined the significance of the proportion of shared genes associated with MA and MO. Results: We found a significant overlap in genes associated with MA and MO. Of the total 1514 genes with a nominally significant gene-based p value (pgene-based ≤ 0.05) in the MA subgroup, 107 also produced pgene-based ≤ 0.05 in the MO subgroup. The proportion of overlapping genes is almost double the empirically derived null expectation, producing significant evidence of gene-based overlap (pleiotropy) (pbinomial-test = 1.5 × 10–4). Combining results across MA and MO, six genes produced genome-wide significant gene-based p values. Four of these genes (TRPM8, UFL1, FHL5 and LRP1) were located in close proximity to previously reported genome-wide significant SNPs for migraine, while two genes, TARBP2 and NPFF separated by just 259 bp on chromosome 12q13.13, represent a novel risk locus. The genes overlapping in both migraine types were enriched for functions related to inflammation, the cardiovascular system and connective tissue. Conclusions: Our results provide novel insight into the likely genes and biological mechanisms that underlie both MA and MO, and when combined with previous data, highlight the neuropeptide FF-amide peptide encoding gene (NPFF) as a novel candidate risk gene for both types of migraine.
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Endometriosis is primarily characterized by the presence of tissue resembling endometrium outside the uterine cavity and is usually diagnosed by laparoscopy. The most commonly used classification of disease, the revised American Fertility Society (rAFS) system to grade endometriosis into different stages based on disease severity (I to IV), has been questioned as it does not correlate well with underlying symptoms, posing issues in diagnosis and choice of treatment. Using two independent European genome-wide association (GWA) datasets and top-level classification of the endometriosis cases based on rAFS [minimal or mild (Stage A) and moderate-to-severe (Stage B) disease], we previously showed that Stage B endometriosis has greater contribution of common genetic variation to its aetiology than Stage A disease. Herein, we extend our previous analysis to four endometriosis stages [minimal (Stage I), mild (Stage II), moderate (Stage III) and severe (Stage IV) disease] based on the rAFS classification system and compared the genetic burden across stages. Our results indicate that genetic burden increases from minimal to severe endometriosis. For the minimal disease, genetic factors may contribute to a lesser extent than other disease categories. Mild and moderate endometriosis appeared genetically similar, making it difficult to tease them apart. Consistent with our previous reports, moderate and severe endometriosis showed greater genetic burden than minimal or mild disease. Overall, our results provide new insights into the genetic architecture of endometriosis and further investigation in larger samples may help to understand better the aetiology of varying degrees of endometriosis, enabling improved diagnostic and treatment modalities.
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Endometriosis is a chronic inflammatory condition in women that results in pelvic pain and subfertility, and has been associated with decreased body mass index (BMI). Genetic variants contributing to the heritable component have started to emerge from genome-wide association studies (GWAS), although the majority remain unknown. Unexpectedly, we observed an intergenic locus on 7p15.2 that was genome-wide significantly associated with both endometriosis and fat distribution (waist-to-hip ratio adjusted for BMI; WHRadjBMI) in an independent meta-GWAS of European ancestry individuals. This led us to investigate the potential overlap in genetic variants underlying the aetiology of endometriosis, WHRadjBMI and BMI using GWAS data. Our analyses demonstrated significant enrichment of common variants between fat distribution and endometriosis (P = 3.7 x 10(-3)), which was stronger when we restricted the investigation to more severe (Stage B) cases (P = 4.5 x 10(-4)). However, no genetic enrichment was observed between endometriosis and BMI (P = 0.79). In addition to 7p15.2, we identify four more variants with statistically significant evidence of involvement in both endometriosis and WHRadjBMI (in/near KIFAP3, CAB39L, WNT4, GRB14); two of these, KIFAP3 and CAB39L, are novel associations for both traits. KIFAP3, WNT4 and 7p15.2 are associated with the WNT signalling pathway; formal pathway analysis confirmed a statistically significant (P = 6.41 x 10(-4)) overrepresentation of shared associations in developmental processes/WNT signalling between the two traits. Our results demonstrate an example of potential biological pleiotropy that was hitherto unknown, and represent an opportunity for functional follow-up of loci and further cross-phenotype comparisons to assess how fat distribution and endometriosis pathogenesis research fields can inform each other.
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BACKGROUND There has been intensive debate whether migraine with aura (MA) and migraine without aura (MO) should be considered distinct subtypes or part of the same disease spectrum. There is also discussion to what extent migraine cases collected in specialised headache clinics differ from cases from population cohorts, and how female cases differ from male cases with respect to their migraine. To assess the genetic overlap between these migraine subgroups, we examined genome-wide association (GWA) results from analysis of 23,285 migraine cases and 95,425 population-matched controls. METHODS Detailed heterogeneity analysis of single-nucleotide polymorphism (SNP) effects (odds ratios) between migraine subgroups was performed for the 12 independent SNP loci significantly associated (p < 5 x 10(-8); thus surpassing the threshold for genome-wide significance) with migraine susceptibility. Overall genetic overlap was assessed using SNP effect concordance analysis (SECA) at over 23,000 independent SNPs. RESULTS: Significant heterogeneity of SNP effects (p het < 1.4 x 10(-3)) was observed between the MA and MO subgroups (for SNP rs9349379), and between the clinic- and population-based subgroups (for SNPs rs10915437, rs6790925 and rs6478241). However, for all 12 SNPs the risk-increasing allele was the same, and SECA found the majority of genome-wide SNP effects to be in the same direction across the subgroups. CONCLUSIONS Any differences in common genetic risk across these subgroups are outweighed by the similarities. Meta-analysis of additional migraine GWA datasets, regardless of their major subgroup composition, will identify new susceptibility loci for migraine.
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Migraine is a debilitating neurological disorder affecting around 1 in 7 people worldwide, but its molecular mechanisms remain poorly understood. Some debate exists over whether migraine is a disease of vascular dysfunction, or a result of neuronal dysfunction with secondary vascular changes. Genome-wide association (GWA) studies have thus far identified 13 independent loci associated with migraine. To identify new susceptibility loci, we performed the largest genetic study of migraine to date, comprising 59,674 cases and 316,078 controls from 22 GWA studies. We identified 45 independent single nucleotide polymorphisms (SNPs) significantly associated with migraine risk (P < 5 x 10-8) that map to 38 distinct genomic loci, including 28 loci not previously reported and the first locus identified on chromosome X. Furthermore, a subset analysis for migraine without aura (MO) identified seven of the same loci as from the full sample, whereas no loci reached genome-wide significance in the migraine with aura (MA) subset. In subsequent computational analyzes, the identified loci showed enrichment for genes expressed in vascular and smooth muscle tissues, consistent with a predominant theory of migraine that highlights vascular etiologies.
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STUDY QUESTION: Do DNA variants in the growth regulation by estrogen in breast cancer 1 (GREB1) region regulate endometrial GREB1 expression and increase the risk of developing endometriosis in women? SUMMARY ANSWER: We identified new single nucleotide polymorphisms (SNPs) with strong association with endometriosis at the GREB1 locus although we did not detect altered GREB1 expression in endometriosis patients with defined genotypes. WHAT IS ALREADY KNOWN: Genome-wide association studies have identified the GREB1 region on chromosome 2p25.1 for increasing endometriosis risk. The differential expression of GREB1 has also been reported by others in association with endometriosis disease phenotype. STUDY DESIGN, SIZE, DURATION: Fine mapping studies comprehensively evaluated SNPs within the GREB1 region in a large-scale data set (>2500 cases and >4000 controls). Publicly available bioinformatics tools were employed to functionally annotate SNPs showing the strongest association signal with endometriosis risk. Endometrial GREB1 mRNA and protein expression was studied with respect to phases of the menstrual cycle (n = 2-45 per cycle stage) and expression quantitative trait loci (eQTL) analysis for significant SNPs were undertaken for GREB1 [mRNA (n = 94) and protein (n = 44) in endometrium]. PARTICIPANTS/MATERIALS, SETTING, METHODS: Participants in this study are females who provided blood and/or endometrial tissue samples in a hospital setting. The key SNPs were genotyped using Sequenom MassARRAY. The functional roles and regulatory annotations for identified SNPs are predicted by various publicly available bioinformatics tools. Endometrial GREB1 expression work employed qRT-PCR, western blotting and immunohistochemistry studies. MAIN RESULTS AND THE ROLE OF CHANCE: Fine mapping results identified a number of SNPs showing stronger association (0.004 < P < 0.032) with endometriosis risk than the original GWAS SNP (rs13394619) (P = 0.034). Some of these SNPs were predicted to have functional roles, for example, interaction with transcription factor motifs. The haplotype (a combination of alleles) formed by the risk alleles from two common SNPs showed significant association (P = 0.026) with endometriosis and epistasis analysis showed no evidence for interaction between the two SNPs, suggesting an additive effect of SNPs on endometriosis risk. In normal human endometrium, GREB1 protein expression was altered depending on the cycle stage (significantly different in late proliferative versus late secretory, P < 0.05) and cell type (glandular epithelium, not stromal cells). However, GREB1 expression in endometriosis cases versus controls and eQTL analyses did not reveal any significant changes. LIMITATIONS, REASONS FOR CAUTION: In silico prediction tools are generally based on cell lines different to our tissue and disease of interest. Functional annotations drawn from these analyses should be considered with this limitation in mind. We identified cell-specific and hormone-specific changes in GREB1 protein expression. The lack of a significant difference observed following our GREB1 expression studies may be the result of moderate power on mixed cell populations in the endometrial tissue samples. WIDER IMPLICATIONS OF THE FINDINGS: This study further implicates the GREB1 region on chromosome 2p25.1 and the GREB1 gene with involvement in endometriosis risk. More detailed functional studies are required to determine the role of the novel GREB1 transcripts in endometriosis pathophysiology. STUDY FUNDING/COMPETING INTERESTS: Funding for this work was provided by NHMRC Project Grants APP1012245, APP1026033, APP1049472 and APP1046880. There are no competing interests.
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Prior genome-wide association studies (GWAS) of major depressive disorder (MDD) have met with limited success. We sought to increase statistical power to detect disease loci by conducting a GWAS mega-analysis for MDD. In the MDD discovery phase, we analyzed more than 1.2 million autosomal and X chromosome single-nucleotide polymorphisms (SNPs) in 18 759 independent and unrelated subjects of recent European ancestry (9240 MDD cases and 9519 controls). In the MDD replication phase, we evaluated 554 SNPs in independent samples (6783 MDD cases and 50 695 controls). We also conducted a cross-disorder meta-analysis using 819 autosomal SNPs with P<0.0001 for either MDD or the Psychiatric GWAS Consortium bipolar disorder (BIP) mega-analysis (9238 MDD cases/8039 controls and 6998 BIP cases/7775 controls). No SNPs achieved genome-wide significance in the MDD discovery phase, the MDD replication phase or in pre-planned secondary analyses (by sex, recurrent MDD, recurrent early-onset MDD, age of onset, pre-pubertal onset MDD or typical-like MDD from a latent class analyses of the MDD criteria). In the MDD-bipolar cross-disorder analysis, 15 SNPs exceeded genome-wide significance (P<5 x 10(-8)), and all were in a 248 kb interval of high LD on 3p21.1 (chr3:52 425 083-53 822 102, minimum P=5.9 x 10(-9) at rs2535629). Although this is the largest genome-wide analysis of MDD yet conducted, its high prevalence means that the sample is still underpowered to detect genetic effects typical for complex traits. Therefore, we were unable to identify robust and replicable findings. We discuss what this means for genetic research for MDD. The 3p21.1 MDD-BIP finding should be interpreted with caution as the most significant SNP did not replicate in MDD samples, and genotyping in independent samples will be needed to resolve its status.
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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.
Inference of the genetic architecture underlying BMI and height with the use of 20,240 sibling pairs
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Evidence that complex traits are highly polygenic has been presented by population-based genome-wide association studies (GWASs) through the identification of many significant variants, as well as by family-based de novo sequencing studies indicating that several traits have a large mutational target size. Here, using a third study design, we show results consistent with extreme polygenicity for body mass index (BMI) and height. On a sample of 20,240 siblings (from 9,570 nuclear families), we used a within-family method to obtain narrow-sense heritability estimates of 0.42 (SE = 0.17, p = 0.01) and 0.69 (SE = 0.14, p = 6 x 10(-)(7)) for BMI and height, respectively, after adjusting for covariates. The genomic inflation factors from locus-specific linkage analysis were 1.69 (SE = 0.21, p = 0.04) for BMI and 2.18 (SE = 0.21, p = 2 x 10(-10)) for height. This inflation is free of confounding and congruent with polygenicity, consistent with observations of ever-increasing genomic-inflation factors from GWASs with large sample sizes, implying that those signals are due to true genetic signals across the genome rather than population stratification. We also demonstrate that the distribution of the observed test statistics is consistent with both rare and common variants underlying a polygenic architecture and that previous reports of linkage signals in complex traits are probably a consequence of polygenic architecture rather than the segregation of variants with large effects. The convergent empirical evidence from GWASs, de novo studies, and within-family segregation implies that family-based sequencing studies for complex traits require very large sample sizes because the effects of causal variants are small on average.