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10.1186/s12920-018-0373-7 http://scihub22266oqcxt.onion/10.1186/s12920-018-0373-7 C6011398!6011398!29925367     free     free     free Deprecated: Implicit conversion from float 215.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 215.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 215.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 215.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 215.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 249.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 249.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       BMC+Med+Genomics 2018 ; 11 (ä): ä Nephropedia Template TP {{tp|p=29925367|t=2018. Genetic interaction effects reveal lipid-metabolic and inflammatory pathways underlying common metabolic disease risks |pdf=|usr=}}{{29925367}} gab.com Text Genetic interaction effects reveal lipid-metabolic and inflammatory pathways underlying common metabolic disease risks JO: BMC Med Genomics http://www.kidney.de/pget.php?&tw=1&pmid=29925367 #FOAvip Background: Common metabolic diseases, including type 2 diabetes, coronary artery disease, and hypertension, arise from disruptions of the body?s metabolic homeostasis, with relatively strong contributions from genetic risk factors and substantial comorbidity with obesity. Although genome-wide association studies have revealed many genomic loci robustly associated with these diseases, biological interpretation of such association is challenging because of the difficulty in mapping single-nucleotide polymorphisms (SNPs) onto the underlying causal genes and pathways. Furthermore, common diseases are typically highly polygenic, and conventional single variant-based association testing does not adequately capture potentially important large-scale interaction effects between multiple genetic factors. Methods: We analyzed moderately sized case-control data sets for type 2 diabetes, coronary artery disease, and hypertension to characterize the genetic risk factors arising from non-additive, collective interaction effects, using a recently developed algorithm (discrete discriminant analysis). We tested associations of genes and pathways with the disease status while including the cumulative sum of interaction effects between all variants contained in each group. Results: In contrast to non-interacting SNP mapping, which produced few genome-wide significant loci, our analysis revealed extensive arrays of pathways, many of which are involved in the pathogenesis of these metabolic diseases but have not been directly identified in genetic association studies. They comprised cell stress and apoptotic pathways for insulin-producing ?-cells in type 2 diabetes, processes covering different atherosclerotic stages in coronary artery disease, and elements of both type 2 diabetes and coronary artery disease risk factors (cell cycle, apoptosis, and hemostasis) associated with hypertension. Conclusions: Our results support the view that non-additive interaction effects significantly enhance the level of common metabolic disease associations and modify their genetic architectures and that many of the expected genetic factors behind metabolic disease risks reside in smaller genotyping samples in the form of interacting groups of SNPs. Electronic supplementary material: The online version of this article (10.1186/s12920-018-0373-7) contains supplementary material, which is available to authorized users. Twit Text FOAVip Genetic interaction effects reveal lipid-metabolic and inflammatory pathways underlying common metabolic disease risks ????BMC Med Genomics http://www.kidney.de/pget.php?&tw=1&pmid=29925367 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=29925367 #FOAvip English Wikipedia <ref>{{Cite pmid|29925367}}</ref> Genetic interaction effects reveal lipid-metabolic and inflammatory pathways underlying common metabolic disease risks #MMPMID29925367 Woo HJ; Reifman J BMC Med Genomics 2018[]; 11 (ä): ä PMID29925367show ga Background: Common metabolic diseases, including type 2 diabetes, coronary artery disease, and hypertension, arise from disruptions of the body?s metabolic homeostasis, with relatively strong contributions from genetic risk factors and substantial comorbidity with obesity. Although genome-wide association studies have revealed many genomic loci robustly associated with these diseases, biological interpretation of such association is challenging because of the difficulty in mapping single-nucleotide polymorphisms (SNPs) onto the underlying causal genes and pathways. Furthermore, common diseases are typically highly polygenic, and conventional single variant-based association testing does not adequately capture potentially important large-scale interaction effects between multiple genetic factors. Methods: We analyzed moderately sized case-control data sets for type 2 diabetes, coronary artery disease, and hypertension to characterize the genetic risk factors arising from non-additive, collective interaction effects, using a recently developed algorithm (discrete discriminant analysis). We tested associations of genes and pathways with the disease status while including the cumulative sum of interaction effects between all variants contained in each group. Results: In contrast to non-interacting SNP mapping, which produced few genome-wide significant loci, our analysis revealed extensive arrays of pathways, many of which are involved in the pathogenesis of these metabolic diseases but have not been directly identified in genetic association studies. They comprised cell stress and apoptotic pathways for insulin-producing ?-cells in type 2 diabetes, processes covering different atherosclerotic stages in coronary artery disease, and elements of both type 2 diabetes and coronary artery disease risk factors (cell cycle, apoptosis, and hemostasis) associated with hypertension. Conclusions: Our results support the view that non-additive interaction effects significantly enhance the level of common metabolic disease associations and modify their genetic architectures and that many of the expected genetic factors behind metabolic disease risks reside in smaller genotyping samples in the form of interacting groups of SNPs. Electronic supplementary material: The online version of this article (10.1186/s12920-018-0373-7) contains supplementary material, which is available to authorized users. äGenetic interaction effects reveal lipid-metabolic and inflammatory pa(epmc).pdf DeepDyve Pubget Overpricing