Key result
Adding LncPPARδ to clinical risk factors boosts CAD diagnostic AUC to ~0.79.
Why the study?
The potential of long noncoding RNA NONHSAT112178 (LncPPARδ) as a biomarker for coronary artery disease in peripheral blood monocytes was investigated.
Does circulating LncPPARδ serve as a reliable biomarker for coronary artery disease?
Observational
Does circulating LncPPARδ serve as a reliable biomarker for coronary artery disease?
p-value: p=0.001
Circulating LncPPARδ, especially when combined with traditional risk factors, shows potential as a novel diagnostic biomarker for coronary artery disease.
LncPPARδ may aid monocyte-based CAD detection; leaves open incremental value over conventional risk models in prospective validation.
To investigate long noncoding RNA NONHSAT112178 (LncPPARδ) as a biomarker for coronary artery disease (CAD) in peripheral blood monocyte cells, RT-qPCR was performed to validate the microarray results, receiver operating characteristic curve was applied to study the potential of LncPPARδ as a biomarker. Diagnostic models from LncPPARδ alone or combination of risk factors were constructed by Fisher criteria. The expression of genes neighboring the LncPPARδ gene was examined with RT-qPCR in THP-1 cell line treated with LncPPARδ siRNA. Using a diagnostic model by Fisher criteria, the consideration of risk factors increased the optimal sensitivity from 70.00% to 82.00% and decreased the specificity from 94.00% to 78.00%. The consideration of risk factors also increased area under the receiver operating characteristic curve from 0.727 to 0.785 (P = 0.001), from 0.712 to 0.768 (P = 0.01), and from 0.769 to 0.835 (P = 0.07), in the original, training, and test sets, respectively. Finally, we found that the expression of peroxisome proliferator-activated receptor δ (PPARδ), Adipose Differentiation-Related Protein (ADRP), and Angiopoietin-like 4 (ANGPTL4) were affected by LncPPARδ silencing.Our present study indicated that LncPPARδ, especially combined with risk factors, can be a good biomarker for CAD. LncPPARδ regulates the expression of neighboring protein-coding genes, PPARδ and its direct target genes ADRP and ANGPTL4.
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Cai et al. (2016) conducted an observational in Coronary artery disease. LncPPARδ combined with risk factors vs. LncPPARδ alone was evaluated on Area under the receiver operating characteristic curve (AUC) for CAD diagnosis (p=0.001). Combining LncPPARδ expression with clinical risk factors improved the diagnostic accuracy for coronary artery disease, increasing the area under the ROC curve from 0.727 to 0.785 (P=0.001).
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