Bütünleştirici Analiz Kullanarak Behçet Hastalığında Biyobelirteç Adayları Belirlenmesi

Year 2021, Volume: 9 Issue: 2, 479 - 489, 01.06.2021

Tuba Sevimoğlu

https://doi.org/10.36306/konjes.800688

Abstract

Behçet Hastalığı, vücutta kan damarı iltihabına neden olan ve tüm organ sistemlerini etkileyebilen nadir bir oto enflamatuar ve otoimmün hastalıktır. Hastalığın patofizyolojisi halen araştırılmaktadır.
Semptomlar değişkenlik gösterdiği için teşhis edilmesi zordur ve hastalık için yeterli tıbbi tedavi yoktur.
Bu çalışmada Behçet Hastalığı gen (izole edilmiş CD4 + T hücreleri ve CD14 + monositlerinden örnekler) ve miRNA ekspresyonu (trombosit içermeyen plazmadan örnekler) veri setleri istatistiksel olarak analiz edilmiştir. CD4 + T hücreleri ve CD14 + monositleri için farklı şekilde ifade edilen genler tanımlanmış ve bu verilerle ilişkili miRNA listelenmiştir. Protein-protein ve miRNA - hedef gen etkileşim ağları oluşturulmuş ve bu ağların merkezi olanları her iki hücre tipi için belirlenmiştir. Gen ekspresyon verileri ile ilişkili metabolitler ve metabolik yollar ortaya konulmuş ve ilişkili sinyal yollarını ve hastalıklarını tanımlamak için zenginleştirme analizi yapılmıştır. Trombosit içermeyen plazma örneklerinin farklı olarak ifade edilen miRNA'ları da tanımlanmıştır. Analiz sonuçları, hücre/doku tipine bağlı genomik yeniden programlamayı göstermiştir. Tüm hücre/doku türlerinde merkezi miRNAlar (hsa-miR-17-5p, hsa-miR-603, hsa-miR-375, hsa-miR-107, hsa-miR-454-3p, hsa-miR-650, hsa-miR-142-3p and hsa-miR-765) ve CD4 + ve CD14 + hücreleri için metabolitler (guanidinoasetat ve histon-L-lizin) biyobelirteç adayları olarak belirlenmiştir. Gelecekte yapılacak olan ve bu aday biyobelirteçlere odaklanan deneysel çalışmalar ile bir teşhis kiti veya geliştirilmiş terapötiklerin tasarımı gerçekleştirilebilir.

Keywords

Behçet Hastalığı, gen ifadesi, miRNA, etkileşim ağları, metabolitler

BIOMARKER CANDIDATES IDENTIFIED IN BEHCET’S DISEASE USING INTEGRATIVE ANALYSIS

Abstract

Behcet’s Disease is a rare auto inflammatory and autoimmune disorder that causes blood vessel inflammation throughout the body and can affect all organ systems. The pathophysiology of the disease is still under investigation. Since the symptoms are varying it is difficult to diagnose and there are no sufficient medical treatments for the disease. In this study Behcet’s Disease gene (Samples from isolated CD4+ T cells and CD14+ monocytes) and miRNA expression (samples from platelet free plasma) datasets were statistically analyzed. Differentially expressed genes for CD4+ T cells and CD14+ monocytes have been identified and miRNA associated with this data were listed. Protein-protein and miRNA – target gene interaction networks were constructed and hubs of these networks were identified for both cell types.
Metabolites and metabolic pathways associated with gene expression data were displayed and enrichment analysis was done to identify associated signaling pathways and diseases. Differentially expressed miRNAs of platelet free plasma samples were also identified. The analysis results indicated cell/tissue type dependent genomic reprogramming. Mutual hub miRNAs (hsa-miR-17-5p, hsa-miR-603, hsa-miR- 375, hsa-miR-107, hsa-miR-454-3p, hsa-miR-650, hsa-miR-142-3p and hsa-miR-765) in all cell/tissue types and metabolites (guanidinoacetate and histone-L-lysine) for CD4+ and CD14+ cells may be considered as biomarker candidates. Future studies focusing on these candidate biomarkers might yield a diagnostic kit or design of enhanced therapeutics for Behcet’s Disease.

Keywords

Behcet’s Disease, gene expression, miRNA, interaction networks, metabolites

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