bioRxivBioinformaticsPreprint
The Role of Sex in Atherosclerotic Inflammation and Lipid-Handling Dysfunction
Abstract
Residual risk of cardiovascular events remains despite treatments that effectively lower cholesterol levels and hypertension, suggesting that there must be more variables to consider in atherosclerosis treatment. Several studies have suggested sex1,2,3 and inflammation4,5 as important variables. However, a cross-cohort analysis of sex and risk factors like inflammation and lipid-handling dysfunction is needed to strengthen their connection to atherosclerosis. By using blood transcriptomic profiles of 391 male and female participants, this study revealed that inflammation and lipid-handling dysfunction have sex-specific roles in atherosclerosis. Transcriptomics of 391 human blood samples with varying degrees of atherosclerosis were used to identify sex-specific changes in immune response and lipid-handling in circulating blood cells. Preliminary analyses of both FPKM and normalized counts datasets showed that inflammatory pathway activation and enrichment increased as atherosclerotic disease severity increased across all sexes. Analysis of sex-specific differentially expressed genes (DEGs) using IPAs Canonical Pathways showed that severely impacted females had more enriched inflammatory pathways than severely impacted males. Further cross-cohort analysis of sex-specific inflammation and lipid-handling dysfunction was performed using AtheroSpectrum, a single-sample macrophage annotation tool. AtheroSpectrum confirmed that inflammation was more critical to female atherogenesis and revealed that lipid-handling dysfunction was more critical to male atherogenesis. Our study underscored the importance of inflammation and sex as variables to consider in atherosclerosis treatment, suggesting that treatment should target inflammation and consider sex. Our findings may be used for generating a model to predict atherosclerosis risk based on key DEGs, pathways, sex, and other clinical parameters when available.
- organism: human
- assay: bulk RNA-seq
- research focus: differential expression
- approach: statistical model
- Citations
- 0
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