Comparative Analysis of Transcriptome Profiles in Patients with Thromboangiitis Obliterans

血栓闭塞性脉管炎患者转录组谱的比较分析

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作者:Gözde Öztan, Nilgün Bozbuğa, Halim İşsever, Fatma Oğuz, İrem Canıaz, Nilgün Yazıksız, Melike Ertan, İbrahim Ufuk Alpagut

Background

Thromboangiitis obliterans (TAO) causes vascular insufficiency due to chronic inflammation and abrupt thrombosis of the medium and small arteries of the extremities. In our study, we aimed to determine biomarkers for the diagnosis of TAO by evaluating 15 male TAO patients with Shinoya diagnostic criteria and 5 healthy controls who did not have TAO-related symptoms in their family histories.

Conclusions

By figuring out the protein expression levels of the genes that have been found to explain how TAO disease works at the molecular level, it will be possible to figure out how well these chosen transcripts can diagnose and predict the disease.

Methods

The Clariom D Affymetrix platform was used to conduct microarray analysis on total RNA extracted from whole blood. A total of 477 genes (FC ≤ 5 or >5) common to the fifteen patient and five control samples were selected using comparative microarray analysis; among them, 79 genes were upregulated and 398 genes were downregulated.

Results

According to FC ≤ 10 or >10, in the same TAO patient and control group, 13 genes out of 28 were upregulated, whereas 15 genes were downregulated. The 11 key genes identified according to their mean log2FC values were PLP2, RPL27A, CCL4, FMNL1, EGR1, EIF4A1, RPL9, LAMP2, RNF149, EIF4G2, and DGKZ. The genes were ranked according to their relative expression as follows: FMNL1 > RNF149 > RPL27A > EIF4G2 > EIF4A1 > LAMP2 > EGR1 > PLP2 > DGKZ > RPL9 > CCL4. Using protein-protein interaction network analysis, RPL9, RPL27A, and RPL32 were found to be closely related to EIF4G2 and EIF4A1. The Reactome pathway found pathways linked to 28 genes. These pathways included the immune system, cellular responses to stress, cytokine signaling in the immune system, and signaling by ROBO receptors. Conclusions: By figuring out the protein expression levels of the genes that have been found to explain how TAO disease works at the molecular level, it will be possible to figure out how well these chosen transcripts can diagnose and predict the disease.

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