Worship: Are images idols?

MakaleHindu kutsal metinlerinin temel öğretisi tüm âlemin saf bilinç olan Yüce Varlıktan ortaya çıktığıdır. Metinler vasıtasıyla Hindulara kendi içlerinde, tüm varlıklarda ve evrende yani her şeyde bu Yüce Varlığı görmek öğretilir. Dağlar, nehirler, ağaçlar, hayvanlar ve gezegenler bu “Tek” olanın tezahürü olarak görüldüğünden kutsal kabul edilir. Bu husus sadece bir “inanç” meselesi değildir; Hindular açısından bir yaşam şekli olmak zorundadır. Hindu kutsal metinlerinin temel öğretisi tüm âlemin saf bilinç olan Yüce Varlıktan ortaya çıktığıdır. Metinler vasıtasıyla Hindulara kendi içlerinde, tüm varlıklarda ve evrende yani her şeyde bu Yüce Varlığı görmek öğretilir. Dağlar, nehirler, ağaçlar, hayvanlar ve gezegenler bu “Tek” olanın tezahürü olarak görüldüğünden kutsal kabul edilir. Bu husus sadece bir “inanç” meselesi değildir; Hindular açısından bir yaşam şekli olmak zorundadır

Genetic insights into resting heart rate and its role in cardiovascular disease

Resting heart rate is associated with cardiovascular diseases and mortality in observational and Mendelian randomization studies. The aims of this study are to extend the number of resting heart rate associated genetic variants and to obtain further insights in resting heart rate biology and its clinical consequences. A genome-wide meta-analysis of 100 studies in up to 835,465 individuals reveals 493 independent genetic variants in 352 loci, including 68 genetic variants outside previously identified resting heart rate associated loci. We prioritize 670 genes and in silico annotations point to their enrichment in cardiomyocytes and provide insights in their ECG signature. Two-sample Mendelian randomization analyses indicate that higher genetically predicted resting heart rate increases risk of dilated cardiomyopathy, but decreases risk of developing atrial fibrillation, ischemic stroke, and cardio-embolic stroke. We do not find evidence for a linear or non-linear genetic association between resting heart rate and all-cause mortality in contrast to our previous Mendelian randomization study. Systematic alteration of key differences between the current and previous Mendelian randomization study indicates that the most likely cause of the discrepancy between these studies arises from false positive findings in previous one-sample MR analyses caused by weak-instrument bias at lower P-value thresholds. The results extend our understanding of resting heart rate biology and give additional insights in its role in cardiovascular disease development

Application of collapsing methods for continuous traits to the Genetic Analysis Workshop 17 exome sequence data

Genetic Analysis Workshop 17 used real sequence data from the 1000 Genomes Project and simulated phenotypes influenced by a large number of rare variants. Our aim is to evaluate the performance of various collapsing methods that were developed for analysis of multiple rare variants. We apply collapsing methods to continuous phenotypes Q1 and Q2 for all 200 replicates of the unrelated individuals data. Within each gene, we collapse (1) all SNPs, (2) all SNPs with minor allele frequency (MAF) < 0.05, and (3) nonsynonymous SNPs with MAF < 0.05. We consider two tests when collapsing variants: using the proportion of variants and using the presence/absence of any variant. We also compare our results to a single-marker analysis using PLINK. For phenotype Q1, the proportion test for collapsing rare nonsynonymous SNPs often performed the best. Two genes (FLT1 and KDR) had statistically significant results. A single-marker analysis using PLINK also provided statistically significant results for some SNPs within these two genes. For phenotype Q2, collapsing rare nonsynonymous SNPs performed the best, with almost no difference between proportion and presence tests. However, neither collapsing methods nor a single-marker analysis provided statistically significant results at the true genes for Q2. We also found that a large number of noncausal genes had high correlations with causal genes for Q1 and Q2, which may account for inflated false positives

Genome-wide linkage scan reveals multiple susceptibility loci influencing lipid and lipoprotein levels in the Québec Family Study

A genome-wide linkage study was performed to identify chromosomal regions harboring genes influencing lipid and lipoprotein levels. Linkage analyses were conducted for four quantitative lipoprotein/lipid traits, i.e., total cholesterol, triglyceride, HDL-cholesterol (HDL-C), and LDL-C concentrations, in 930 subjects enrolled in the Québec Family Study. A maximum of 534 pairs of siblings from 292 nuclear families were available. Linkage was tested using both allele-sharing and variance-component linkage methods. The strongest evidence of linkage was found on chromosome 12q14.1 at marker D12S334 for HDL-C, with a logarithm of the odds (LOD) score of 4.06. Chromosomal regions harboring quantitative trait loci (QTLs) for LDL-C included 1q43 (LOD = 2.50), 11q23.2 (LOD = 3.22), 15q26.1 (LOD = 3.11), and 19q13.32 (LOD = 3.59). In the case of triglycerides, three markers located on 2p14, 11p13, and 11q24.1 provided suggestive evidence of linkage (LOD > 1.75). Tests for total cholesterol levels yielded significant evidence of linkage at 15q26.1 and 18q22.3 with the allele-sharing linkage method, but the results were nonsignificant with the variance-component method. In conclusion, this genome scan provides evidence for several QTLs influencing lipid and lipoprotein levels. Promising candidate genes were located in the vicinity of the genomic regions showing evidence of linkage