62 resultados para multi-view analysis


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Background: Although a large number of randomized controlled trials (RCTs) have examined the impact of the n-3 (ω-3) fatty acids EPA (20:5n-3) and DHA (22:6n-3) on blood pressure and vascular function, the majority have used doses of EPA+DHA of > 3 g per d,which are unlikely to be achieved by diet manipulation. Objective: The objective was to examine, using a retrospective analysis from a multi-center RCT, the impact of recommended, dietary achievable EPA+DHA intakes on systolic and diastolic blood pressure and microvascular function in UK adults. Design: Healthy men and women (n = 312) completed a double-blind, placebo-controlled RCT consuming control oil, or fish oil providing 0.7 g or 1.8 g EPA+DHA per d in random order each for 8 wk. Fasting blood pressure and microvascular function (using Laser Doppler Iontophoresis) were assessed and plasma collected for the quantification of markers of vascular function. Participants were retrospectively genotyped for the eNOS rs1799983 variant. Results: No impact of n-3 fatty acid treatment or any treatment * eNOS genotype interactions were evident in the group as a whole for any of the clinical or biochemical outcomes. Assessment of response according to hypertension status at baseline indicated a significant (P=0.046) fish oil-induced reduction (mean 5 mmHg) in systolic blood pressure specifically in those with isolated systolic hypertension (n=31). No dose response was observed. Conclusions: These findings indicate that, in those with isolated systolic hypertension, daily doses of EPA+DHA as low as 0.7 g bring about clinically meaningful blood pressure reductions which, at a population level, would be associated with lower cardiovascular disease risk. Confirmation of findings in an RCT where participants are prospectively recruited on the basis of blood pressure status is required to draw definite conclusions. The Journal of Nutrition NUTRITION/2015/220475 Version 4

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Genome-wide association studies (GWAS) have been widely used in genetic dissection of complex traits. However, common methods are all based on a fixed-SNP-effect mixed linear model (MLM) and single marker analysis, such as efficient mixed model analysis (EMMA). These methods require Bonferroni correction for multiple tests, which often is too conservative when the number of markers is extremely large. To address this concern, we proposed a random-SNP-effect MLM (RMLM) and a multi-locus RMLM (MRMLM) for GWAS. The RMLM simply treats the SNP-effect as random, but it allows a modified Bonferroni correction to be used to calculate the threshold p value for significance tests. The MRMLM is a multi-locus model including markers selected from the RMLM method with a less stringent selection criterion. Due to the multi-locus nature, no multiple test correction is needed. Simulation studies show that the MRMLM is more powerful in QTN detection and more accurate in QTN effect estimation than the RMLM, which in turn is more powerful and accurate than the EMMA. To demonstrate the new methods, we analyzed six flowering time related traits in Arabidopsis thaliana and detected more genes than previous reported using the EMMA. Therefore, the MRMLM provides an alternative for multi-locus GWAS.