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Transcriptomic Signature of Atherosclerosis in the Peripheral Blood: Fact or Fiction?
Hsiao-Huei Chen1,2, Alexandre F R Stewart3,4
1Ottawa Hospital Research Institute, University of Ottawa, Ottawa, ON, Canada.
Insights
Gene expression in blood is controversial for predicting coronary artery disease (CAD). MicroRNAs show more promise than genes for accurate CAD biomarker discovery.
Area of Science:
- Biomarkers
- Genomics
- Cardiovascular Disease
Background:
- Gene expression signatures in blood as disease biomarkers is a known concept.
- The utility of peripheral blood mononuclear cell gene expression for reflecting coronary artery disease (CAD) processes in the vessel wall is debated.
- Limited replication (23 out of 706 genes) across 15 studies highlights challenges in identifying reliable gene expression biomarkers for CAD.
Purpose of the Study:
- To review the current understanding of gene expression profiling for predicting coronary artery disease (CAD) status and mortality.
- To evaluate the reliability of gene expression signatures in peripheral blood mononuclear cells as biomarkers for CAD.
- To assess the potential of microRNAs as more consistent biomarkers for CAD compared to messenger RNAs.
Main Methods:
- Comparative analysis of 15 studies identifying differentially expressed genes in CAD.
- Review of 7 studies identifying microRNAs associated with CAD.
- Examination of the impact of genetic heterogeneity and cohort size on biomarker replication.
- Assessment of statistical power requirements for large-scale case-control studies.
Main Results:
- Low replication rates for differentially expressed genes (only 23 genes replicated in at most 3 studies) suggest limitations due to sample size and genetic heterogeneity.
- Larger cohorts (over 5000 individuals) considering genetic variants did not establish gene signatures as reliable biomarkers.
- MicroRNAs demonstrated higher concordance (12 out of 58 identified microRNAs in 2 or more studies), indicating potential for greater accuracy in reflecting disease processes.
- Significant statistical power is needed for robust biomarker identification in large case-control studies.
Conclusions:
- Gene expression profiling in peripheral blood mononuclear cells faces challenges in reliably predicting coronary artery disease (CAD) status due to genetic variability and insufficient statistical power.
- MicroRNAs show greater potential as consistent biomarkers for CAD compared to messenger RNAs, likely due to less influence from individual genetic differences.
- Further large-scale studies are necessary to achieve the statistical power required for validating gene expression signatures as reliable biomarkers for CAD prediction and mortality.
Abstract:
The notion that gene expression signatures in blood can serve as biomarkers of disease states is not new. In the case of atherosclerosis, and coronary artery disease in particular, whether changes in gene expression in peripheral blood mononuclear cells reflects disease processes occurring in the vessel wall remains controversial. When comparing 15 studies that identified 706 differentially expressed genes, only 23 genes were replicated in 2 to 3 studies, at most. This low level of replication may reflect sample sizes too small to overcome heterogeneity in the response to disease. Genetic differences affect how each person responds to disease and what genes are altered. Recent studies with larger cohorts (over 5000 individuals) that considered the effect of common genetic variants still could not claim disease signature genes as biomarkers suggesting that even larger case-control studies will be required to achieve the required statistical power. On the other hand, out of 7 studies that identified 58 microRNAs, 12 were concordant in 2 or more studies, suggesting that microRNAs may be less affected by genetic differences and more accurately reflect the disease process. Here, we review the current state of knowledge on expression profiling and its utility for predicting coronary artery disease status and mortality.
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