ArticleAMB Express2020
Identification of key genes and pathways in syphilis combined with diabetes: a bioinformatics study.
Article in AMB Express, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed, 7 citations in OpenAlex.
- Type 2 Diabetes Impacts the Efficacy of Syphilis Treatment and is a Risk Factor for Late Syphilis: A Retrospective Cohort Study.Acta dermato-venereologica · 2025Article
- Diagnostic and Therapeutic Approaches for a Diabetic Patient Presenting with Secondary Syphilis and Severe Odynophagia.Medicina (Kaunas, Lithuania) · 2024Article
- Recombinant Treponema pallidum protein Tp0768 promotes proinflammatory cytokine secretion of macrophages through ER stress and ROS/NF-κB pathway.Applied microbiology and biotechnology · 2021Article
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Authors and funding
12 authors at 2 institutions in 1 country.
Funding
Abstract
We noticed that syphilis patients seem to be more susceptible to diabetes and the lesions often involve the kidneys, but the pathogenesis is not yet completely understood. In this study, microarray analysis was performed to investigate the dysregulated expressed genes (DEGs) in rabbit model of syphilis combined with diabetes. A total of 1045 genes were identified to be significantly differentially expressed, among which 571 were up-regulated and 474 were down-regulated (≥ 2.0fold, p < 0.05). Using the database visualization and integration discovery for the Kyoto Encyclopedia of Gene and Genome (KEGG) pathway enrichment analysis. The downregulated DEGs were significantly enriched for biosynthesis of antibiotics, carbon metabolism and protein digestion, while the upregulated DEGs were mainly enriched for cancer and PI3K-Akt signaling pathway. Molecular Complex Detection (MCODE) plugins were used to visualize protein-protein interaction (PPI) network of DEGs and Screening for hub genes and gene modules. ALB, FN1, CASP3, MMP9, IL8, CTGF, STAT3, IGF1, VCAM-1 and HGF were filtrated as the hub genes according to the degree of connectivity from the PPI network. To the best of our knowledge, this study is the first to comprehensively identify the expression patterns of dysregulated genes in syphilis combined with diabetes, providing a basis for revealing the underlying pathogenesis of syphilis combined with diabetes and exploring the goals of therapeutic intervention.
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