Whether genetic factors influence the associations of fatty acids with the risk of sudden cardiac arrest (SCA) is largely unknown. To investigate possible gene-fatty acid interactions on SCA risk, we used a case-only approach and measured fatty acids in erythrocyte samples from 1869 SCA cases in a population-based repository with genetic data. We selected 191 SNP in ENCODE-identified regulatory regions of fifty-five candidate genes in fatty acid metabolic pathways. Using linear regression and additive genetic models, we investigated the association of the selected SNP with erythrocyte levels of fatty acids, including DHA, EPA and trans-fatty acids among the SCA cases. The assumption of no association in non-cases was supported by analysis of publicly available datasets containing over 8000 samples. None of the SNP-fatty acid associations tested among the cases reached statistical significance after correction for multiple comparisons. One SNP, rs4654990 near PLA2G2A, with an allele frequency of 0·33, was nominally associated with lower levels of DHA and EPA and higher levels of trans-fatty acids. The strongest association was with DHA levels (exponentiated coefficient for one unit (1 % of total fatty acids), 0·90, 95 % CI 0·85, 0·97; P = 0·003), indicating that for subjects with a coded allele, the OR of SCA associated with one unit higher DHA is about 90 % what it is for subjects with one fewer coded allele. These findings suggest that the associations of circulating n-3 and trans-fatty acids with SCA risk may be more pronounced in carriers of the rs4654990 G allele.
Pubmed ID: 27313848 RIS Download
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Encyclopedia of DNA elements consisting of list of functional elements in human genome, including elements that act at protein and RNA levels, and regulatory elements that control cells and circumstances in which gene is active. Enables scientific and medical communities to interpret role of human genome in biology and disease. Provides identification of common cell types to facilitate integrative analysis and new experimental technologies based on high-throughput sequencing. Genome Browser containing ENCODE and Epigenomics Roadmap data. Data are available for entire human genome.
View all literature mentionsOpen source whole genome association analysis toolset, designed to perform range of basic, large scale analyses in computationally efficient manner. Used for analysis of genotype/phenotype data. Through integration with gPLINK and Haploview, there is some support for subsequent visualization, annotation and storage of results. PLINK 1.9 is improved and second generation of the software.
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