BMC cardiovascular disorders · 2019
Integrative genomic analysis identified common regulatory networks underlying the correlation between coronary artery disease and plasma lipid levels.
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Chen Liuying, Yao Yinghao, Jin Chaolun, Wu Shen, Liu Qiang, Li Jingjing, Ma Yunlong, Xu Yizhou, Zhong Yigang
Аннотация
BACKGROUND: Coronary artery disease (CAD) and plasma lipid levels are highly correlated, indicating the presence of common pathways between them. Nevertheless, the molecular pathways underlying the pathogenic comorbidities for both traits remain poorly studied. We sought to identify common pathways and key driver genes by performing a comprehensive integrative analysis based on multi-omic datasets.
METHODS: By performing a pathway-based analysis of GWAS summary data, we identified that lipoprotein metabolism process-related pathways were significantly associated with CAD risk. Based on LD score regression analysis of CAD-related SNPs, significant heritability enrichments were observed in the cardiovascular and digestive system, as well as in liver and gastrointestinal tissues, which are the main regulators for lipid level.
RESULTS: We found there existed significant genetic correlation between CAD and other lipid metabolism related traits (the smallest P value < 1 × 10- 16). A total of 13 genes (e.g., LPA, APOC1, APOE and SLC22A3) was found to be overlapped between CAD and plasma lipid levels. By using the data-driven approach that integrated transcriptome information, we discovered co-expression modules associated prominently with both CAD and plasma lipids. With the detailed topology information on gene-gene regulatory relationship, we illustrated that the identified hub genes played important roles in the pathogenesis of CAD and plasma lipid turbulence.
CONCLUSION: Together, we identified the shared molecular mechanisms underlying the correlation between CAD and plasma lipid levels.
METHODS: By performing a pathway-based analysis of GWAS summary data, we identified that lipoprotein metabolism process-related pathways were significantly associated with CAD risk. Based on LD score regression analysis of CAD-related SNPs, significant heritability enrichments were observed in the cardiovascular and digestive system, as well as in liver and gastrointestinal tissues, which are the main regulators for lipid level.
RESULTS: We found there existed significant genetic correlation between CAD and other lipid metabolism related traits (the smallest P value < 1 × 10- 16). A total of 13 genes (e.g., LPA, APOC1, APOE and SLC22A3) was found to be overlapped between CAD and plasma lipid levels. By using the data-driven approach that integrated transcriptome information, we discovered co-expression modules associated prominently with both CAD and plasma lipids. With the detailed topology information on gene-gene regulatory relationship, we illustrated that the identified hub genes played important roles in the pathogenesis of CAD and plasma lipid turbulence.
CONCLUSION: Together, we identified the shared molecular mechanisms underlying the correlation between CAD and plasma lipid levels.