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Background: atherosclerosis is a multifaceted disease characterized by the formation and accumulation of plaques that fix to the arteries and causes some cardiovascular disease and vascular embolism. A range of diagnostic techniques, including selective coronary angiography, stress tests, CT, and nuclear scans allow assessment of cardiovascular disease risk and treatment targets. However, there is not a very simple blood biochemical index or biological target for the diagnosis of atherosclerosis at present. So it would be interesting to find a blood biochemical marker for atherosclerosis.
Methods: Three datasets from Gene Expression Omnibus (GEO) database were analyzed to obtain differentially expressed genes (DEG) and the results were integrated using Robustrankaggreg algorithm. The genes considered more important by Robustrankaggreg algorithm were put into their own data set and the data set system with cell classification information for verification.
Results: 21 possible genes were screened out. Interestingly, we found a good correlation between RPS4Y1, EIF1AY and XIST. In addition, we know the general expression of these genes in different cell types and whole blood cells
Conclusions: In this study, we identified BTNL8 and BLNK as having good clinical significance. These results will contribute to the study of the underlying genes involved in the progression of atherosclerosis and provide insights for the discovery of new diagnostic and evaluation methods.
Keywords
Blood, Bioinformatics, Biomarker, Atherosclerosis
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This is a preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
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Bioinformatics
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This work is licensed under a CC BY 4.0 License. Read Full License
The most recent version of this article is available here.
Background: atherosclerosis is a multifaceted disease characterized by the formation and accumulation of plaques that fix to the arteries and causes some cardiovascular disease and vascular embolism. A range of diagnostic techniques, including selective coronary angiography, stress tests, CT, and nuclear scans allow assessment of cardiovascular disease risk and treatment targets. However, there is not a very simple blood biochemical index or biological target for the diagnosis of atherosclerosis at present. So it would be interesting to find a blood biochemical marker for atherosclerosis.
Methods: Three datasets from Gene Expression Omnibus (GEO) database were analyzed to obtain differentially expressed genes (DEG) and the results were integrated using Robustrankaggreg algorithm. The genes considered more important by Robustrankaggreg algorithm were put into their own data set and the data set system with cell classification information for verification.
Results: 21 possible genes were screened out. Interestingly, we found a good correlation between RPS4Y1, EIF1AY and XIST. In addition, we know the general expression of these genes in different cell types and whole blood cells
Conclusions: In this study, we identified BTNL8 and BLNK as having good clinical significance. These results will contribute to the study of the underlying genes involved in the progression of atherosclerosis and provide insights for the discovery of new diagnostic and evaluation methods.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
This is a list of supplementary files associated with this preprint. Click to download.
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