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Genetic interaction effects reveal lipid-metabolic and inflammatory pathways underlying common metabolic disease risks

Overview of attention for article published in BMC Medical Genomics, June 2018
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Title
Genetic interaction effects reveal lipid-metabolic and inflammatory pathways underlying common metabolic disease risks
Published in
BMC Medical Genomics, June 2018
DOI 10.1186/s12920-018-0373-7
Pubmed ID
Authors

Hyung Jun Woo, Jaques Reifman

Abstract

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. 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. 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 β-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. 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.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 16 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 31%
Student > Master 3 19%
Professor 1 6%
Student > Bachelor 1 6%
Student > Doctoral Student 1 6%
Other 2 13%
Unknown 3 19%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 4 25%
Medicine and Dentistry 4 25%
Agricultural and Biological Sciences 2 13%
Nursing and Health Professions 2 13%
Unknown 4 25%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 22 June 2018.
All research outputs
#11,652,139
of 13,118,813 outputs
Outputs from BMC Medical Genomics
#575
of 648 outputs
Outputs of similar age
#232,332
of 268,333 outputs
Outputs of similar age from BMC Medical Genomics
#3
of 3 outputs
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