RESUMEN
BACKGROUND: The heightened risk of cardiovascular and cerebrovascular events is associated with the increased instability of atherosclerotic plaques. However, the lack of effective diagnostic biomarkers has impeded the assessment of plaque instability currently. This study was aimed to investigate and identify hub genes associated with unstable plaques through the integration of various bioinformatics tools, providing novel insights into the detection and treatment of this condition. METHODS: Weighted Gene Co-expression Network Analysis (WGCNA) combined with two machine learning methods were used to identify hub genes strongly associated with plaque instability. The cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) method was utilized to assess immune cell infiltration patterns in atherosclerosis patients. Additionally, Gene Set Variation Analysis (GSVA) was conducted to investigate the potential biological functions, pathways, and mechanisms of hub genes associated with unstable plaques. To further validate the diagnostic efficiency and expression of the hub genes, immunohistochemistry (IHC), quantitative real-time polymerase chain reaction (RT-qPCR), and enzyme-linked immunosorbent assay (ELISA) were performed on collected human carotid plaque and blood samples. Immunofluorescence co-staining was also utilized to confirm the association between hub genes and immune cells, as well as their colocalization with mitochondria. RESULTS: The CIBERSORT analysis demonstrated a significant decrease in the infiltration of CD8 T cells and an obvious increase in the infiltration of M0 macrophages in patients with atherosclerosis. Subsequently, two highly relevant modules (blue and green) strongly associated with atherosclerotic plaque instability were identified. Through intersection with mitochondria-related genes, 50 crucial genes were identified. Further analysis employing least absolute shrinkage and selection operator (LASSO) logistic regression and support vector machine recursive feature elimination (SVM-RFE) algorithms revealed six hub genes significantly associated with plaque instability. Among them, NT5DC3, ACADL, SLC25A4, ALDH1B1, and MAOB exhibited positive correlations with CD8 T cells and negative correlations with M0 macrophages, while kynurenine 3-monooxygenas (KMO) demonstrated a positive correlation with M0 macrophages and a negative correlation with CD8 T cells. IHC and RT-qPCR analyses of human carotid plaque samples, as well as ELISA analyses of blood samples, revealed significant upregulation of KMO and MAOB expression, along with decreased ALDH1B1 expression, in both stable and unstable samples compared to the control samples. However, among the three key genes mentioned above, only KMO showed a significant increase in expression in unstable plaque samples compared to stable plaque samples. Furthermore, the expression patterns of KMO in human carotid unstable plaque tissues and cultured mouse macrophage cell lines were assessed using immunofluorescence co-staining techniques. Finally, lentivirus-mediated KMO silencing was successfully transduced into the aortas of high-fat-fed ApoE-/- mice, with results indicating that KMO silencing attenuated plaque formation and promoted plaque stability in ApoE-/- mice. CONCLUSIONS: The results suggest that KMO, a mitochondria-targeted gene associated with macrophage cells, holds promise as a valuable diagnostic biomarker for assessing the instability of atherosclerotic plaques.
Asunto(s)
Placa Aterosclerótica , Femenino , Humanos , Masculino , Persona de Mediana Edad , Biología Computacional/métodos , Perfilación de la Expresión Génica , Redes Reguladoras de Genes , Genes Mitocondriales/genética , Macrófagos/metabolismo , Macrófagos/patología , Mitocondrias/metabolismo , Placa Aterosclerótica/genética , Placa Aterosclerótica/patología , Reproducibilidad de los Resultados , Quinurenina 3-Monooxigenasa/genética , Quinurenina 3-Monooxigenasa/metabolismoRESUMEN
The increasing prevalence and expanding distribution of tick-borne viruses globally have raised health concerns, but the full repertoire of the tick virome has not been assessed. We sequenced the meta-transcriptomes of 31 different tick species in the Ixodidae and Argasidae families from across mainland China, and identified 724 RNA viruses with distinctive virome compositions among genera. A total of 1,801 assembled and complete or nearly complete viral genomes revealed an extensive diversity of genome architectures of tick-associated viruses, highlighting ticks as a reservoir of RNA viruses. We examined the phylogenies of different virus families to investigate virome evolution and found that the most diverse tick-associated viruses are positive-strand RNA virus families that demonstrate more ancient divergence than other arboviruses. Tick-specific viruses are often associated with only a few tick species, whereas virus clades that can infect vertebrates are found in a wider range of tick species. We hypothesize that tick viruses can exhibit both 'specialist' and 'generalist' evolutionary trends. We hope that our virome dataset will enable much-needed research on vertebrate-pathogenic tick-associated viruses.