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Background: Although the prevalence rate of valvular heart disease (VHD) is high in patients with systemic lupus erythematosus (SLE), the predictive factors of concomitant VHD have not been fully evaluated. Methods and results: Among 288 patients with SLE who underwent transthoracic echocardiography at Kumamoto University Hospital from 2016 to 2021, 241 patients with sufficient echocardiographic data were retrospectively analysed. Among them, 22 (9 %) had VHD (10 had mitral regurgitation, 3 had aortic regurgitation, 6 had tricuspid regurgitation, 1 had mitral regurgitation and tricuspid regurgitation, and 2 had a prosthetic cardiac valve). After excluding the two patients with a prosthetic cardiac valve, we divided the remaining patients into two groups: the VHD group and non-VHD group. Multivariate logistic regression analysis revealed that age and the platelet count were significantly and independently associated with having VHD (age: odds ratio, 1.06; 95 % confidence interval, 1.02-1.10; p < 0.01) (platelet count: odds ratio, 0.99; 95 % confidence interval, 0.98-1.00; p < 0.05). After excluding 95 patients aged < 40 years, receiver operating characteristic analysis revealed that the area under the curve of the platelet count for prediction of VHD was 0.73 with an optimal cut-off value of 166.5 × 103/µL (sensitivity: 76.6 %, specificity: 60.0 %). Among patients with a low platelet count (<166.5 × 103/µL), the rate of having VHD was 29 % (12/41 patients). However, among those with a high platelet count (≥166.5 × 103/µL), this rate was only 8 % (8/103 patients). Conclusion: The platelet count is useful to predict concomitant VHD in middle-aged and older patients with SLE.
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INTRODUCTION: Atrial fibrillation (AF) is a common arrhythmia associated with aging. Many known risk factors are associated with AF, but many senior individuals do not develop AF despite having multiple risk factors. This finding suggests that other factors may be involved in AF onset. This study aimed to identify upregulated genes in the peripheral blood and left atrium of patients with AF. These genes may serve as potential biomarkers to predict AF onset risk and its complications. METHODS: Gene expression data were analyzed from blood (n = 3) and left atrial samples (n = 15) of patients with AF and sinus rhythm. We evaluated the significant genes identified using p value analysis of weighted average difference to confirm their rankings. We created figures for the genes using GeneMANIA and performed a functional analysis using Cytoscape3.10.1. Hub and bottleneck genes were identified based on degree and betweenness centrality. We used reference expression (RefEx) to confirm the organs in which the extracted genes were expressed. Heatmaps and Gene ontology term evaluation were performed to further elucidate the biological functions of the genes. RESULTS: We identified 12 upregulated genes (CAST, ASAH1, MAFB, VCAN, DDIT4, FTL, HEXB, PROS1, BNIP3L, PABPC1, YBX3, and S100A6) in both the blood and left atrium of patients with AF. We analyzed the gene functions using GeneMANIA and Cytoscape. The identified genes were involved in a variety of pathways, including lysosomal function and lipid and sphingolipid catabolism. Next, we investigated whether the 12 identified genes identified were systemically expressed or had high organ specificity. Finally, RefEx was used to analyze the gene expression levels in various tissues. Four genes, FTL, ASAH1, S100A6, and PABPC1, were highly expressed in the normal heart tissue. Finally, we evaluated the expression levels of the 12 genes in the blood of patients with AF using a heatmap. Our findings suggest that the 12 genes identified in this study, especially the lysosome-related genes (FTL and ASAH1), may be involved in AF pathogenesis. CONCLUSION: Lysosome-related genes may be important to understand the AF pathophysiology and to develop AF-related future studies.