Endothelial‐immune crosstalk contributes to vasculopathy in nonalcoholic fatty liver disease
2022; Springer Nature; Volume: 23; Issue: 6 Linguagem: Inglês
10.15252/embr.202154271
ISSN1469-3178
AutoresChun‐Yi Ng, Khang Leng Lee, Mark Muthiah, Kan Xing Wu, Florence Wen Jing Chioh, Konstanze Tan, Gwyneth Shook Ting Soon, Asim Shabbir, Wai Mun Loo, Zun Siong Low, Qingfeng Chen, Walter Wahli, Nguan Soon Tan, Huck‐Hui Ng, Yock Young Dan, Christine Cheung,
Tópico(s)Systemic Lupus Erythematosus Research
ResumoArticle11 April 2022Open Access Transparent process Endothelial-immune crosstalk contributes to vasculopathy in nonalcoholic fatty liver disease Chun-Yi Ng Chun-Yi Ng Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore Contribution: Data curation, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing - original draft, Writing - review & editing Search for more papers by this author Khang Leng Lee Khang Leng Lee Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore Contribution: Data curation, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing - original draft, Writing - review & editing Search for more papers by this author Mark Dhinesh Muthiah Mark Dhinesh Muthiah Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore Department of Medicine, National University Health System, Singapore, Singapore Contribution: Resources, Data curation, Formal analysis, Writing - review & editing Search for more papers by this author Kan Xing Wu Kan Xing Wu Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore Contribution: Data curation, Formal analysis, Investigation, Visualization, Methodology, Writing - review & editing Search for more papers by this author Florence Wen Jing Chioh Florence Wen Jing Chioh Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore Contribution: Data curation, Formal analysis, Visualization, Methodology, Writing - review & editing Search for more papers by this author Konstanze Tan Konstanze Tan Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore Search for more papers by this author Gwyneth Shook Ting Soon Gwyneth Shook Ting Soon orcid.org/0000-0001-5318-9327 Department of Pathology, National University Health System, Singapore, Singapore Contribution: Data curation, Formal analysis, Investigation, Writing - review & editing Search for more papers by this author Asim Shabbir Asim Shabbir Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore Department of Surgery, University Surgical Cluster, National University Health System, Singapore, Singapore Contribution: Resources, Writing - review & editing Search for more papers by this author Wai Mun Loo Wai Mun Loo Department of Medicine, National University Health System, Singapore, Singapore Contribution: Resources, Writing - review & editing Search for more papers by this author Zun Siong Low Zun Siong Low Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore Contribution: Methodology, Writing - review & editing Search for more papers by this author Qingfeng Chen Qingfeng Chen Institute of Molecular and Cell Biology, Agency for Science Technology and Research (A*STAR), Singapore, Singapore Contribution: Resources, Supervision, Methodology, Writing - review & editing Search for more papers by this author Walter Wahli Walter Wahli Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore Institut national de recherche pour l'agriculture, l'alimentation et l'environnement (INRAE), Toxalim (Research Centre in Food Toxicology), Toulouse, France Center for Integrative Genomics, Université de Lausanne, Le Génopode, Lausanne, SwitzerlandCorrection added on 6 October 2022, after first online publication: Walter Wahli and affiliations 10 and 11 have been added. See the associated Corrigendum at https://doi.org/10.15252/embr.202255871Search for more papers by this author Nguan Soon Tan Nguan Soon Tan orcid.org/0000-0003-0136-7341 Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore School of Biological Sciences, Nanyang Technological University, Singapore, Singapore Contribution: Data curation, Formal analysis, Visualization, Methodology, Writing - review & editing, Resources, Supervision, Writing - review & editing Search for more papers by this author Huck Hui Ng Huck Hui Ng Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore Institute of Molecular and Cell Biology, Agency for Science Technology and Research (A*STAR), Singapore, Singapore School of Biological Sciences, Nanyang Technological University, Singapore, Singapore Genome Institute of Singapore, Agency for Science Technology and Research (A*STAR), Singapore, Singapore Department of Biological Sciences, Faculty of Science, National University of Singapore, Singapore, Singapore Contribution: Resources, Supervision, Funding acquisition, Project administration, Writing - review & editing Search for more papers by this author Yock Young Dan Yock Young Dan Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore Department of Medicine, National University Health System, Singapore, Singapore Contribution: Resources, Supervision, Funding acquisition, Project administration, Writing - review & editing Search for more papers by this author Christine Cheung Corresponding Author Christine Cheung [email protected] orcid.org/0000-0001-7127-9107 Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore Institute of Molecular and Cell Biology, Agency for Science Technology and Research (A*STAR), Singapore, Singapore Contribution: Conceptualization, Resources, Formal analysis, Supervision, Funding acquisition, Investigation, Visualization, Methodology, Writing - original draft, Project administration, Writing - review & editing Search for more papers by this author Chun-Yi Ng Chun-Yi Ng Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore Contribution: Data curation, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing - original draft, Writing - review & editing Search for more papers by this author Khang Leng Lee Khang Leng Lee Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore Contribution: Data curation, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing - original draft, Writing - review & editing Search for more papers by this author Mark Dhinesh Muthiah Mark Dhinesh Muthiah Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore Department of Medicine, National University Health System, Singapore, Singapore Contribution: Resources, Data curation, Formal analysis, Writing - review & editing Search for more papers by this author Kan Xing Wu Kan Xing Wu Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore Contribution: Data curation, Formal analysis, Investigation, Visualization, Methodology, Writing - review & editing Search for more papers by this author Florence Wen Jing Chioh Florence Wen Jing Chioh Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore Contribution: Data curation, Formal analysis, Visualization, Methodology, Writing - review & editing Search for more papers by this author Konstanze Tan Konstanze Tan Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore Search for more papers by this author Gwyneth Shook Ting Soon Gwyneth Shook Ting Soon orcid.org/0000-0001-5318-9327 Department of Pathology, National University Health System, Singapore, Singapore Contribution: Data curation, Formal analysis, Investigation, Writing - review & editing Search for more papers by this author Asim Shabbir Asim Shabbir Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore Department of Surgery, University Surgical Cluster, National University Health System, Singapore, Singapore Contribution: Resources, Writing - review & editing Search for more papers by this author Wai Mun Loo Wai Mun Loo Department of Medicine, National University Health System, Singapore, Singapore Contribution: Resources, Writing - review & editing Search for more papers by this author Zun Siong Low Zun Siong Low Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore Contribution: Methodology, Writing - review & editing Search for more papers by this author Qingfeng Chen Qingfeng Chen Institute of Molecular and Cell Biology, Agency for Science Technology and Research (A*STAR), Singapore, Singapore Contribution: Resources, Supervision, Methodology, Writing - review & editing Search for more papers by this author Walter Wahli Walter Wahli Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore Institut national de recherche pour l'agriculture, l'alimentation et l'environnement (INRAE), Toxalim (Research Centre in Food Toxicology), Toulouse, France Center for Integrative Genomics, Université de Lausanne, Le Génopode, Lausanne, SwitzerlandCorrection added on 6 October 2022, after first online publication: Walter Wahli and affiliations 10 and 11 have been added. See the associated Corrigendum at https://doi.org/10.15252/embr.202255871Search for more papers by this author Nguan Soon Tan Nguan Soon Tan orcid.org/0000-0003-0136-7341 Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore School of Biological Sciences, Nanyang Technological University, Singapore, Singapore Contribution: Data curation, Formal analysis, Visualization, Methodology, Writing - review & editing, Resources, Supervision, Writing - review & editing Search for more papers by this author Huck Hui Ng Huck Hui Ng Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore Institute of Molecular and Cell Biology, Agency for Science Technology and Research (A*STAR), Singapore, Singapore School of Biological Sciences, Nanyang Technological University, Singapore, Singapore Genome Institute of Singapore, Agency for Science Technology and Research (A*STAR), Singapore, Singapore Department of Biological Sciences, Faculty of Science, National University of Singapore, Singapore, Singapore Contribution: Resources, Supervision, Funding acquisition, Project administration, Writing - review & editing Search for more papers by this author Yock Young Dan Yock Young Dan Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore Department of Medicine, National University Health System, Singapore, Singapore Contribution: Resources, Supervision, Funding acquisition, Project administration, Writing - review & editing Search for more papers by this author Christine Cheung Corresponding Author Christine Cheung [email protected] orcid.org/0000-0001-7127-9107 Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore Institute of Molecular and Cell Biology, Agency for Science Technology and Research (A*STAR), Singapore, Singapore Contribution: Conceptualization, Resources, Formal analysis, Supervision, Funding acquisition, Investigation, Visualization, Methodology, Writing - original draft, Project administration, Writing - review & editing Search for more papers by this author Author Information Chun-Yi Ng1, Khang Leng Lee1, Mark Dhinesh Muthiah2,3, Kan Xing Wu1, Florence Wen Jing Chioh1, Konstanze Tan1, Gwyneth Shook Ting Soon4, Asim Shabbir2,5, Wai Mun Loo3, Zun Siong Low1, Qingfeng Chen6, Walter Wahli1,10,11, Nguan Soon Tan1,7, Huck Hui Ng1,2,6,7,8,9, Yock Young Dan2,3 and Christine Cheung *,1,6 1Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore 2Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore 3Department of Medicine, National University Health System, Singapore, Singapore 4Department of Pathology, National University Health System, Singapore, Singapore 5Department of Surgery, University Surgical Cluster, National University Health System, Singapore, Singapore 6Institute of Molecular and Cell Biology, Agency for Science Technology and Research (A*STAR), Singapore, Singapore 7School of Biological Sciences, Nanyang Technological University, Singapore, Singapore 8Genome Institute of Singapore, Agency for Science Technology and Research (A*STAR), Singapore, Singapore 9Department of Biological Sciences, Faculty of Science, National University of Singapore, Singapore, Singapore 10Institut national de recherche pour l'agriculture, l'alimentation et l'environnement (INRAE), Toxalim (Research Centre in Food Toxicology), Toulouse, France 11Center for Integrative Genomics, Université de Lausanne, Le Génopode, Lausanne, Switzerland *Corresponding author. Tel: +65 69047049; E-mail: [email protected] EMBO Reports (2022)23:e54271https://doi.org/10.15252/embr.202154271 Correction(s) for this article Endothelial-immune crosstalk contributes to vasculopathy in nonalcoholic fatty liver disease06 October 2022 PDFDownload PDF of article text and main figures. Peer ReviewDownload a summary of the editorial decision process including editorial decision letters, reviewer comments and author responses to feedback. ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InMendeleyWechatReddit Figures & Info Abstract The top cause of mortality in patients with nonalcoholic fatty liver disease (NAFLD) is cardiovascular complications. However, mechanisms of NAFLD-associated vasculopathy remain understudied. Here, we show that blood outgrowth endothelial cells (BOECs) from NAFLD subjects exhibit global transcriptional upregulation of chemokines and human leukocyte antigens. In mouse models of diet-induced NAFLD, we confirm heightened endothelial expressions of CXCL12 in the aortas and the liver vasculatures, and increased retention of infiltrated leukocytes within the vessel walls. To elucidate endothelial-immune crosstalk, we performed immunoprofiling by single-cell analysis, uncovering T cell intensification in NAFLD patients. Functionally, treatment with a CXCL12-neutralizing antibody is effective at moderating the enhanced chemotactic effect of NAFLD BOECs in recruiting CD8+ T lymphocytes. Interference with the CXCL12-CXCR4 axis using a CXCR4 antagonist also averts the impact of immune cell transendothelial migration and restores endothelial barrier integrity. Clinically, we detect threefold more circulating damaged endothelial cells in NAFLD patients than in healthy controls. Our work provides insight into the modulation of interactions with effector immune cells to mitigate endothelial injury in NAFLD. Synopsis Endothelial chemokine activation is evident in non-alcoholic fatty liver disease patients and mouse diet-induced disease models. The CXCL12-CXCR4 axis mediates the interaction of patient endothelial cells with effector immune cells, potentially leading to vascular injury. NAFLD patient-derived endothelial cells exhibit increased chemokine hallmarks and human leukocyte antigens. Aortas and liver vasculatures of diet-induced NAFLD mice show increased endothelial CXCL12 and leukocyte infiltration. Inhibition of the CXCL12-CXCR4 axis diminishes chemotaxis of CD8+ T cells and endothelial barrier impairment. NAFLD patients manifest elevated levels of circulating damaged endothelial cells. Introduction Nonalcoholic fatty liver disease is the most common liver disease in developed countries, affecting up to a third of western populations, and up to 40% in South East Asia (Muthiah & Sanyal, 2020). The spectrum of NAFLD includes the more benign nonalcoholic fatty liver, also known as simple steatosis, and the more progressive form of nonalcoholic steatohepatitis (NASH) and can progress to fibrosis (Chalasani et al, 2018). Nonalcoholic steatohepatitis is characterized by lobular inflammation and ballooning and can progress to develop fibrosis. While NAFLD remains a liver disease, the top cause of mortality in patients with NAFLD is cardiovascular mortality, which occurs independently of the shared metabolic risk factors such as insulin resistance and obesity (Targher et al, 2020). Patients with NAFLD are at increased risk of developing multiple vascular complications, including coronary artery disease, cerebrovascular disease, and peripheral vascular disease. There is emerging evidence of the link between NAFLD and impaired vascular health. Clinical measures of vascular function have established the association of reduced flow-mediated vasodilatation, altered carotid artery intimal medial thickness, coronary calcification, and low coronary flow reserve with NAFLD (Sookoian & Pirola, 2008; Federico et al, 2016). In line with this, regression of NAFLD is associated with a lower risk of carotid atherosclerosis in observational cohort studies (Sinn et al, 2016, 2017). Even in the absence of major cardiometabolic risk factors, healthy individuals demonstrated better vascular functions than NAFLD patients (Long et al, 2015; Al-Hamoudi et al, 2020), supporting that NAFLD alone could contribute to the dysfunction of systemic vasculatures. Various mechanisms have been proposed as plausible evidence for accelerated atherosclerosis and increased cardiovascular risks in NAFLD patients, including a high oxidative stress state, macrophage activation (Targher et al, 2010), and systemic release of proatherogenic and thrombotic factors like tumor necrosis factor-α, interleukin-6, and oxidized low-density lipoprotein (Stols-Goncalves et al, 2019). Many of these paracrine mediators are known to activate endothelial cells and potentially result in endothelial dysfunction. Inflammation may also augment lipid risks to further drive atherosclerosis (Libby, 2021). However, there remain knowledge gaps in NAFLD-related endothelial disease biology that are not resolved by the current evaluation of vascular function using imaging modalities and serum biomarkers. We aim to understand the molecular basis of endothelial pathophysiology in NAFLD-associated vasculopathy. Due to the difficulties of obtaining fresh vascular tissues from patients, we harnessed the use of blood outgrowth endothelial cells (BOECs) to develop personalized endothelial models from NAFLD patients and healthy subjects. BOECs originate from endothelial colony-forming cells, which are bone marrow–derived progenitors found in the circulation and within vascular endothelium (Yoon et al, 2005). They are distinct from the early endothelial progenitor cells, which form a heterogeneous culture of monocyte-derived cells from hematopoietic stem cell origin, whereas BOECs give rise to a homogeneous population of mature endothelial cells with cobblestone morphology and are capable of tube formation. While the precursor of BOECs, endothelial colony-forming cells, have been explored for therapeutic revascularization, BOECs prove to be a useful surrogate of patient endothelial cells to investigate the biology of vasculopathy in various disease contexts such as pulmonary arterial hypertension, diabetes, and ischemic heart disease (Paschalaki & Randi, 2018). Patient-derived BOECs were able to recapitulate clinical phenotypic alterations, capture the complexities of genetics and/or epigenetics, and demonstrate differential responses to disease-relevant stressors (Hebbel, 2017). Here, we utilized BOECs to facilitate experimentations including transcriptomic analysis, mechanistic interrogation, and endothelial-immune cell coculture assays. We also analyzed circulating endothelial cells (CECs), which were shed from endothelial lining into the bloodstream following vascular damage (Hebbel, 2017), to yield insights on endothelial injury in NAFLD. Results Development of human blood outgrowth endothelial cells for disease modeling Patients with NAFLD were diagnosed with at least 5% steatosis characterized on liver biopsies, while selected healthy controls had a Controlled Attenuation Parameter score of less than 248 on vibration controlled transient elastography, indicative of less than 5% steatosis (more details in Materials and Methods under "patient enrollment"). We employed established protocols (Martin-Ramirez et al, 2012b; Ormiston et al, 2015) to develop BOECs from NAFLD patients and healthy subjects. Briefly, peripheral blood mononuclear cells (PBMCs) isolated from whole blood samples were cultivated to derive BOECs (Fig 1A). We then characterized the growth dynamics, marker expressions, and functions of NAFLD and healthy control BOECs. BOEC colonies usually emerged after 7–14 days of PBMC cultivation (Fig 1B). The colonies were isolated, passaged into endothelial growth media, and further cultured to stabilize the BOEC lines that displayed cobblestone endothelial cell morphology. Both NAFLD and healthy BOECs had comparable doubling times (Fig 1C). More than 90% of BOECs expressed endothelial markers, including CD31 (PECAM1), CD144 (CDH5), and CD146, but negligible expressions for leukocyte markers CD45, CD14, and CD68 and progenitor cell marker CD133 (Fig 1D), suggesting high purity of our BOEC derivation. Immunostaining confirmed their positive expressions of endothelial markers (Fig 1E). Functionally, the BOECs were able to undergo angiogenesis, typical of endothelial property, in three-dimensional fibrin gel bead-based sprouting assays. Sprouts could be observed as early as 6 h (Fig 1F, representative images). By 24 h, both NAFLD and healthy BOECs showed a comparable number of sprouts per bead and sprout lengths (Fig 1F, lower panel). During sprouting angiogenesis, endothelial cells undergo a series of dynamic changes in their tip- and stalk-like cell phenotypes to facilitate cell migration, proliferation, and stabilization, which ultimately leads to sprout formation (Blanco & Gerhardt, 2013). Phenotypically, we did not observe differences in the angiogenic capacities between NAFLD and healthy BOECs. However, at the molecular level, sprouted NAFLD BOECs might be primed for angiogenesis as demonstrated by their significantly higher gene expressions for tip cell markers than sprouted healthy BOECs (Fig EV1). Concomitantly, the role of pathological angiogenesis in NAFLD is well known, likely driven by pro-angiogenic factors arising from chronic inflammation, tissue hypoxia, and hepatocyte injury (Coulon et al, 2012; Hammoutene & Rautou, 2019; Lefere et al, 2019). Taken together, these quality control characterizations in Figs 1 and EV1 confirmed mature endothelial phenotypes of both NAFLD and healthy BOECs. Good quality cell lines were used for downstream experimentations. Figure 1. Generation and characterization of blood outgrowth endothelial cells from healthy and NAFLD subjects Workflow schematic of BOEC generation from PBMC samples isolated from NAFLD patients and healthy donors. Upper panel: Representative images of BOEC colonies from PBMC cultivation 10 days post-seeding. Dotted line in each image outlines a BOEC colony. Lower panel: Stabilized BOEC cultures after passaging of colonies (scale bar, 250 µm). Proliferation doubling time for NAFLD and healthy BOECs based on passages 2 and 3. Sample sizes are n = 9 healthy, n = 7 NAFLD; with 3 biological replicates per donor. Box-whisker plots indicate median (middle line), 25th, 75th percentile (box), and the lowest/highest data points (whiskers). ns—not significant (t-test). Left panel: Flow cytometry characterization of BOECs for endothelial, leukocyte, and progenitor cell markers (gray—isotype control; red/blue/green/purple—cell lineage marker staining). HUVEC and monocytic THP-1 cells were used as positive controls for endothelial and leukocytic markers, respectively. Right panel: Percentages of positively expressing cells. Sample sizes are n = 4–6 healthy, n = 2–7 NAFLD. Results are indicated by mean ± SD. *P < 0.05; **P < 0.01; ****P < 0.0001; ns—not significant (one-way ANOVA). Representative images of immunostaining for endothelial markers, PECAM1 and CDH5 (scale bar, 100 µm). Left panel: Longitudinal monitoring of BOEC angiogenesis in fibrin gel bead-based sprouting assays over 24 h (representative images; scale bar, 100 µm). Right panel: Box-whisker plots of quantifications of sprout lengths and numbers of sprout per bead at 24 h. n = 3 healthy, n = 3 NAFLD, with 4–5 beads analyzed per donor and 5–11 sprouts per bead. ns—not significant (t-test). Box-whisker plots indicate median (middle line), 25th, 75th percentile (box), and the lowest/highest data points (whiskers). Download figure Download PowerPoint Click here to expand this figure. Figure EV1. Gene expressions of tip-stalk markers in sprouting BOECs Expressions were determined by qPCR and normalized to monolayers (nonsprouting). Data presented as mean ± SD. n = 3 donors; ns—not significant; ****P < 0.0001 (t-test). Download figure Download PowerPoint NAFLD endothelial cells show enhanced chemokine hallmarks To explore the molecular basis of endothelial pathophysiological mechanisms in NAFLD, we performed RNA-sequencing on BOECs derived from 3 NAFLD patients (2 females and 1 male, 37.7 ± 11.5 years old) and 3 healthy controls (2 females and 1 male, 41.7 ± 8.6 years old) (Appendix Table S1). Principal component analysis illustrated a clear segregation of transcriptomic profiles between NAFLD and healthy groups (Fig 2A). A total of 670 differentially expressed genes were identified, including 535 upregulated genes and 135 downregulated genes in NAFLD BOECs in comparison to healthy BOECs (Fig 2B; false discovery rate < 0.05, P < 0.05; fold change > 2 or < −2, respectively). Gene ontology analysis revealed that NAFLD BOECs are largely enriched in processes related to cell locomotion, extracellular matrix organization and chemotaxis, whereas filament organization and mitogen-activated protein kinase (MAPK) cascade were most prominent in healthy BOECs (Fig 2C). Based on the upregulated genes in NAFLD BOECs, chemotaxis was identified as the most central network (Cluster 1) by molecular complex detection (MCODE), interconnecting with cell chemotaxis (leukocyte migration), cytoskeleton organization, and cell morphogenesis (Fig 2D). In contrast, no MCODE cluster was found using the downregulated gene set (Fig EV2A), suggesting that the upregulated genes in NAFLD BOECs might exert a stronger biological effect due to intertwined processes. Correspondingly, heatmap visualization of the genes from the top enriched network showed that NAFLD BOECs expressed higher levels of chemokines including the CC, CXC, and CX3C families than healthy BOECs (Fig 2E). Figure 2. Transcriptomic analysis of NAFLD and healthy BOECs Principal component analysis of NAFLD (n = 3) and healthy (n = 3) BOEC transcriptomes, with 3 biological replicates per donor. Volcano plot depicting differentially expressed genes comparing NAFLD BOECs with healthy BOECs. Red and blue dots represent upregulated and downregulated genes in NAFLD BOECs, respectively. Enriched gene ontology terms of the differentially expressed genes. Metascape enrichment network visualization showing intracluster and intercluster interactomes of the upregulated genes in NAFLD BOECs. Nodes that share the same cluster annotations are close to each other. Densely connected clusters were identified using MCODE algorithm and outlined in red. Heatmap featuring the genes in MCODE Cluster 1. STRING protein–protein interaction network were analyzed by maximum neighborhood component, showing hub genes as ranked and indicated by gradient of red colors. Blue nodes represent differentially expressed genes in the extended networks. Download figure Download PowerPoint Click here to expand this figure. Figure EV2. Transcriptomes of healthy and NAFLD BOECs Metascape enrichment network visualization of interactomes of the downregulated terms in NAFLD BOECs. No identifiable MCODE complexes were found. Ten MCODE complexes identified in the upregulated networks in NAFLD BOECs, ranked, and colored by their identities. The identities of the complexes were listed in the table. Download figure Download PowerPoint To prioritize candidate genes for further mechanistic interrogation, we used 12 topological data analysis methods to identify and rank top 20 genes per method, which might play a central role in the network interactome (Appendix Table S2). Chemokines including CXCL3, CXCL5, CXCL6, CXCL10, CXCL11, CXCL12, CCL20, and CX3CL1 were consistently reflected by at least 6 topological analysis methods. Of those, CXCL10, CXCL12, and CX3CL1 were ranked as top 3 genes by at least three methods, emphasizing their importance in the network. Fig 2F is a visualization of one of the methods used. We also applied the MCODE algorithm that verified the "chemokine-mediated signaling pathway" as the top MCODE complex containing most of the aforementioned chemokine genes (Fig EV2B). Taken together, enhanced chemokine signatures could be a hallmark for NAFLD endothelial cells. NAFLD patient endothelial cells and vascular endothelia of in vivo disease models demonstrate intensified CXCL12 levels We selected several chemokines from the prioritized list of candidate genes for further validation in a larger number of endothelial cell lines. Gene expression profiling demonstrated that CXCL10 and CXCL12 were significantly upregulated in NAFLD BOECs (n = 10) compared with healthy BOECs (n = 12), while the other chemokines were not significantly different at baseline (Fig 3A, donor demographics in Appendix Table S3). To examine these chemokine expressions under a relevant pathophysiological context, we introduced autologous plasma as a stressor to the BOEC cultures. Upon exposure of BOECs to their autologous plasma, similarly, CXC chemokine ligands were signi
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