Browsing by Author "Tang, Lijiang"

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    Closing gaps in medication taking for secondary prevention of coronary heart disease patients among US adults
    (Elsevier, 2022-11-11) Liu, Xiaowei; Tang, Lijiang; Tang, Ying; Du, Changqing; Chen, Xiaofeng; Xu, Cheng; Yan, Jing; Radiation Oncology, School of Medicine
    Background: The secondary preventive medical remedies used in the U.S. general population, particularly those with numerous co-morbidities, are poorly understood. We aimed to assess health outcomes and the extent of their adherence to guideline-based secondary prevention medications among U.S. coronary heart disease (CHD) patients. Methods: We analysed information from the U.S. National Health and Nutrition Examination Survey (NHANES) from 1999 to 2018 on people in the United States aged 18 to 85 who had a personal history of coronary heart disease (CHD). Logistic regression analyses were used to identify characteristics related to healthcare access that were linked with not taking any indicated drugs among CHD and other co-morbidity patients in the U.S. Results: We gathered 4256 CHD patients aged 18 and above. Angiotensin-converting enzyme inhibitors/angiotensin receptor blockers (ACEIs/ARBs), statins, and antiplatelet medications were taken by 50.94%, 48.26%, 53.41 %, and 19.78% of the population, respectively. Surprising, not received recommended drugs was reached up to 21.12%, and taking all four drugs was only 7.64%. In conclusion, the logistic regression analysis revealed that the chance of not taking prescribed drugs increased with age (18-39), race (Hispanic and Non-Hispanic Black), low income, lack of insurance, and the absence of co-morbidities (hypertension, heart failure, and diabetes mellitus). Conclusions: The gap between the proposed secondary preventative measures and their actual execution remains sizable. In order to achieve 'Healthy Aging', a systematic approach for prevention of CHD is urgently needed.
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    Crucial Genes in Aortic Dissection Identified by Weighted Gene Coexpression Network Analysis
    (Hindawi, 2022-02-07) Zhang, Hongliang; Chen, Tingting; Zhang, Yunyan; Lin, Jiangbo; Zhao, Wenjun; Shi, Yangyang; Lau, Huichong; Zhang, Yang; Yang, Minjun; Xu, Cheng; Tang, Lijiang; Xu, Baohui; Jiang, Jianjun; Chen, Xiaofeng; Radiation Oncology, School of Medicine
    Background: Aortic dissection (AD) is a lethal vascular disease with high mortality and morbidity. Though AD clinical pathology is well understood, its molecular mechanisms remain unclear. Specifically, gene expression profiling helps illustrate the potential mechanism of aortic dissection in terms of gene regulation and its modification by risk factors. This study was aimed at identifying the genes and molecular mechanisms in aortic dissection through bioinformatics analysis. Method: Nine patients with AD and 10 healthy controls were enrolled. The gene expression in peripheral mononuclear cells was profiled through next-generation RNA sequencing. Analyses including differential expressed gene (DEG) via DEGseq, weighted gene coexpression network (WGCNA), and VisANT were performed to identify crucial genes associated with AD. The Database for Annotation, Visualization, and Integrated Discovery (DAVID) was also utilized to analyze Gene Ontology (GO). Results: DEG analysis revealed that 1,113 genes were associated with AD. Of these, 812 genes were markedly reduced, whereas 301 genes were highly expressed, in AD patients. DEGs were rich in certain categories such as MHC class II receptor activity, MHC class II protein complex, and immune response genes. Gene coexpression networks via WGCNA identified 3 gene hub modules, with one positively and 2 negatively correlated with AD, respectively. Specifically, module 37 was the most strongly positively correlated with AD with a correlation coefficient of 0.72. Within module 37, five hub genes (AGFG1, MCEMP1, IRAK3, KCNE1, and CLEC4D) displayed high connectivity and may have clinical significance in the pathogenesis of AD. Conclusion: Our analysis provides the possible association of specific genes and gene modules for the involvement of the immune system in aortic dissection. AGFG1, MCEMP1, IRAK3, KCNE1, and CLEC4D in module M37 were highly connected and strongly linked with AD, suggesting that these genes may help understand the pathogenesis of aortic dissection.
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    Potential influencing factors of aortic diameter at specific segments in population with cardiovascular risk
    (BMC, 2022-02-05) Chen, Tingting; Yang, Xingan; Fang, Xiaoxin; Tang, Lijiang; Zhang, Yang; Weng, Yingzheng; Zhang, Hongliang; Wu, Juntao; Mao, Ping; Xu, Baohui; Jiang, Jianjun; Chen, Xiaofeng; Radiation Oncology, School of Medicine
    Background: Aortic diameter is a critical parameter for the diagnosis of aortic dilated diseases. Aortic dilation has some common risk factors with cardiovascular diseases. This study aimed to investigate potential influence of traditional cardiovascular risk factors and the measures of subclinical atherosclerosis on aortic diameter of specific segments among adults. Methods: Four hundred and eight patients with cardiovascular risk factors were prospectively recruited in the observational study. Comprehensive transthoracic M-mode, 2-dimensional Doppler echocardiographic studies were performed using commercial and clinical diagnostic ultrasonography techniques. The aortic dimensions were assessed at different levels: (1) the annulus, (2) the mid-point of the sinuses of Valsalva, (3) the sinotubular junction, (4) the ascending aorta at the level of its largest diameter, (5) the transverse arch (including proximal arch, mid arch, distal arch), (6) the descending aorta posterior to the left atrium, and (7) the abdominal aorta just distal to the origin of the renal arteries. Multivariable linear regression analysis was used for evaluating aortic diameter-related risk factors, including common cardiovascular risk factors, co-morbidities, subclinical atherosclerosis, lipid profile, and hematological parameters. Results: Significant univariate relations were found between aortic diameter of different levels and most traditional cardiovascular risk factors. Carotid intima-media thickness was significantly correlated with diameter of descending and abdominal aorta. Multivariate linear regression showed potential effects of age, sex, body surface area and some other cardiovascular risk factors on aortic diameter enlargement. Among them, high-density lipoprotein cholesterol had a significantly positive effect on the diameter of ascending and abdominal aorta. Diastolic blood pressure was observed for the positive associations with diameters of five thoracic aortic segments, while systolic blood pressure was only independently related to mid arch diameter. Conclusion: Aortic segmental diameters were associated with diastolic blood pressure, high-density lipoprotein cholesterol, atherosclerosis diseases and other traditional cardiovascular risk factors, and some determinants still need to be clarified for a better understanding of aortic dilation diseases.
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    Single-Cell RNA Sequencing Reveals Smooth Muscle Cells Heterogeneity in Experimental Aortic Dissection
    (Frontiers Media, 2022-08-11) Xu, Cheng; Liu, Xiaowei; Fang, Xiaoxin; Yu, Lei; Lau, Hui Chong; Li, Danlei; Liu, Xiaoman; Li, Haili; Ren, Justin; Xu, Baohui; Jiang, Jianjun; Tang, Lijiang; Chen, Xiaofeng; Radiation Oncology, School of Medicine
    Purpose: This study aims to illustrate the cellular landscape in the aorta of experimental aortic dissection (AD) and elaborate on the smooth muscle cells (SMCs) heterogeneity and functions among various cell types. Methods: Male Apolipoprotein deficient (ApoE-/-) mice at 28 weeks of age were infused with Ang II (2,500 ng/kg/min) to induce AD. Aortas from euthanized mice were harvested after 7 days for 10×Genomics single-cell RNA sequencing (scRNA-seq), followed by the identification of cell types and differentially expressed genes (DEGs). Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis was conducted. Results: AD was successfully induced in ApoE-/- mice. scRNA-seq identified 15 cell clusters and nine cell types, including non-immune cells (endothelials, fibroblasts, and SMCs) and immune cells (B cells, natural killer T cell, macrophages, dendritic cells, neutrophils, and mast cells). The relative numbers of SMCs were remarkably changed, and seven core DEGs (ACTA2,IL6,CTGF,BGN,ITGA8,THBS1, and CDH5) were identified in SMCs. Moreover, we found SMCs can differentiate into 8 different subtypes through single-cell trajectory analysis. Conclusion: scRNA-seq technology can successfully identify unique cell composition in experimental AD. To our knowledge, this is the first study that provided the complete cellular landscape in AD tissues from mice, seven core DEGs and eight subtypes of SMCs were identified, and the SMCs have evolution from matrix type to inflammatory type.
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    Single-cell RNA Sequencing Technology Revealed the Pivotal Role of Fibroblast Heterogeneity in Ang II-Induced Abdominal Aortic Aneurysms
    (Research Square, 2021-11-02) Weng, Yingzheng; Lou, Jiangjie; Bao, Yizong; Cai, Changhong; Zhu, Kefu; Du, Changqing; Chen, Xiaofeng; Tang, Lijiang; Radiation Oncology, School of Medicine
    The mechanism of abdominal aortic aneurysm (AAA) has not been fully elucidated. In this study, we aimed to map the cellular heterogeneity, molecular alteration, and functional transformation of angiotensin (Ang) II-induced AAA in mice based on single-cell RNA sequencing (sc-RNA seq) technology. sc-RNA seq was performed on suprarenal abdominal aorta tissue from male Apoe-/- C57BL/6 mice of Ang II-induced AAA and shame models to determine the heterogeneity and phenotypic transformation of all cells. Immunohistochemistry was used to determine the pathophysiological characteristics of AAA. The single-cell trajectory was performed to predict the differentiation of fibroblasts. Finally ligand-receptor analysis was used to evaluate intercellular communication between fibroblasts and smooth muscle cells (SMCs). More than 27,000 cells were isolated and 25 clusters representing 8 types of cells were identified, including fibroblasts, macrophages, endothelial cells, SMCs, T lymphocytes, B lymphocytes, granulocytes, and natural killer cells. During AAA progression, the function and phenotype of different type cells altered separately, including activation of inflammatory cells, alternations of macrophage polarization, phenotypic transformation of vascular smooth muscle cells, and endothelial to mesenchymal transformation. The alterations of fibroblasts were the most conspicuous. Single-cell trajectory revealed the critical reprogramming genes of fibroblasts mainly enriched in regulation of immune system. Finally, the ligand-receptor analysis confirmed that disorder of collagen metabolism led by fibroblasts was one of the most prominent characteristics of Ang II-induced AAA. Our study revealed the cellular heterogeneity of Ang II-induced AAA. Fibroblasts may play a critical role in Ang II-induced AAA progression according to multiple biological functions, including immune regulation and extracellular matrix metabolic balance. Our study may provide us with a different perspective on the etiology and pathogenesis of AAA.