Characterization and Proteome of Circulating Extracellular Vesicles as Potential Biomarkers for NASH - PubMed (original) (raw)
. 2020 Jul 3;4(9):1263-1278.
doi: 10.1002/hep4.1556. eCollection 2020 Sep.
Hirokazu Yamashita 1, Wenhua Ren 2, Mani G Subramanian 3, Robert P Myers 3, Akiko Eguchi 1, Douglas A Simonetto 4, Zachary D Goodman 5, Stephen A Harrison 6, Arun J Sanyal 7, Jaime Bosch 8 9, Ariel E Feldstein 1
Affiliations
- PMID: 32923831
- PMCID: PMC7471415
- DOI: 10.1002/hep4.1556
Characterization and Proteome of Circulating Extracellular Vesicles as Potential Biomarkers for NASH
Davide Povero et al. Hepatol Commun. 2020.
Abstract
Nonalcoholic fatty liver disease (NAFLD) is currently one of most common forms of chronic liver disease globally. NAFLD represents a wide spectrum of liver involvement from nonprogressive isolated steatosis to nonalcoholic steatohepatitis (NASH), characterized by liver necroinflammation and fibrosis and currently one of the top causes of end-stage liver disease and hepatocellular carcinoma. At present, there is a lack of effective treatments, and a central barrier to the development of therapies is the requirement for an invasive liver biopsy for diagnosis of NASH. Discovery of reliable, noninvasive biomarkers are urgently needed. In this study, we tested whether circulating extracellular vesicles (EVs), cell-derived small membrane-surrounded structures with a rich cargo of bioactive molecules, may serve as reliable noninvasive "liquid biopsies" for NASH diagnosis and assessment of disease severity. Total circulating EVs and hepatocyte-derived EVs were isolated by differential centrifugation and size-exclusion chromatography from serum samples of healthy individuals, patients with precirrhotic NASH, and patients with cirrhotic NASH. EVs were further characterized by flow cytometry, electron microscopy, western blotting, and dynamic light scattering assays before performing a proteomics analysis. Our findings suggest that levels of total and hepatocyte-derived EVs correlate with NASH clinical characteristics and disease severity. Additionally, using proteomics data, we developed understandable, powerful, and unique EV-based proteomic signatures for potential diagnosis of advanced NASH. Conclusion: Our study shows that the quantity and protein constituents of circulating EVs provide strong evidence for EV protein-based liquid biopsies for NAFLD/NASH diagnosis.
© 2020 The Authors. Hepatology Communications published by Wiley Periodicals LLC on behalf of American Association for the Study of Liver Diseases.
Figures
FIG. 1
Isolation, detection, and characterization of circulating EVs in serum samples of patients with NASH. (A) Flow chart of circulating EV isolation. (B) Number of calcein/FITC+ circulating EVs detected by flow cytometry in healthy controls (n = 11) or liver biopsy–proven patients with advanced NASH (n = 50). (C) Mean size( 38 ) of circulating EVs measured by dynamic light scattering. (D) Representative TEM microphotographs of circulating EVs. (E) Representative western blots of EV markers Alix, CD63, and TSG101 in healthy controls and patients with advanced NASH. Values represent mean ± SD. Kruskal‐Wallis test with post hoc Mann‐Whitney U test and Bonferroni correction were used for statistical analysis. Abbreviation: HC, healthy control.
FIG. 2
Levels of hepatocyte‐specific circulating EVs correlate with NASH severity. (A) Number of calcein/FITC+ circulating EVs in healthy controls, patients with precirrhotic NASH, and patients with cirrhotic NASH detected by flow cytometry. (B,C) Flow cytometry analysis of hepatocyte‐specific EVs either positive for hepatocyte marker SLC27A5 or ASGPR1. (D) Number of hepatocyte‐specific circulating EVs in individuals with cirrhotic NASH with HVPG lower or greater than 10 mmHg, as indication of clinically significant portal hypertension. (E) Spearman correlation between hepatocyte‐specific circulating EVs and HVPG levels. (F) AUROC curve for hepatocyte‐derived EVs for diagnosis of portal hypertension in patients with cirrhotic NASH. Hepatocyte‐EV count of 668 EVs/ µL or higher serum showed sensitivity of 92% and specificity of 75% for differentiating patients with clinically significant portal hypertension from patients with no clinically relevant portal hypertension (AUROC: 0.79; 95% CI: 0.589‐0.988). Kruskal‐Wallis test with post hoc Mann Whitney U test and Bonferroni correction were used for statistical analysis. Abbreviations: HC, healthy control; ROC, receiver operating characteristic.
FIG. 3
Analysis of circulating EVs proteome by SOMAScan protein array in all three cohorts. (A) Venn diagram of differentially expressed EV proteins in patients with precirrhotic NASH versus healthy controls or patients with cirrhotic NASH. (B) Venn diagram of differentially expressed EV proteins in patients with cirrhotic NASH compared with healthy controls or patients with precirrhotic NASH. A cutoff of adjusted P value of 0.01 was used for both Venn diagrams. (C) Unsupervised hierarchical clustering analysis of the top 50 differentially expressed circulating EV proteins in patients with cirrhotic NASH versus patients with precirrhotic NASH versus healthy controls (n = 7/group). The top 50 proteins listed on the heat map were selected based on the adjusted P value of 0.05 from the cirrhotic NASH versus healthy controls comparison. Mean and SD of all three groups were used to normalize the expression value. The closer the color is to bright blue, the lower the expression, whereas the closer the color is to bright red, the higher the expression.
FIG. 4
Analyses of most abundant circulating EV proteins in paired comparisons. Volcano plots illustrating significantly differentially abundant EV‐proteins in patients with cirrhotic NASH versus patients with precirrhotic NASH (A) and patients with cirrhotic NASH versus healthy controls (n = 7/group) (B). The ‐log10 (adjusted P value) is plotted against the log2 fold‐change. The nonaxial vertical blue line denotes no effect in protein expression; green line denotes +0.2‐fold change; and the red line denotes ‐0.2‐fold change. The nonaxial black horizontal line denotes P value greater than 0.005, which is out of the significance threshold (before logarithmic transformation). Unsupervised hierarchical clustering analysis of the top 50 differentially expressed circulating EV proteins in patients with cirrhotic NASH versus patients with precirrhotic NASH (C) and in patients with cirrhotic NASH versus healthy controls (n = 7/group) (D). An adjusted P value of 0.05 was used to generate the heat maps. The closer the color is to bright blue, the lower the expression, whereas the closer the color is to bright red, the higher the expression.
FIG. 5
Performance of circulating EV protein signatures for identification of healthy controls, patients with precirrhotic NASH, or patients with cirrhotic NASH. (A) kTSP votes training heat map of the k‐top performing pairs of circulating EV proteins identified in patients with advanced NASH versus healthy controls during the validation study. The 20 gray boxes correspond to 10 patients with precirrhotic NASH and 10 patients with cirrhotic NASH grouped into one advanced NASH data set, while the red boxes correspond to the 6 healthy controls. (B) AUROC of kTSP‐selected top performing pairs of circulating EV proteins identified in patients with advanced NASH versus healthy controls (AUROC: 0.77; 95% CI: 0.5635‐0.9103). (C) kTSP votes training heat map of the top performing pairs of circulating EV proteins identified in patients with precirrhotic NASH versus patients with cirrhotic NASH during the validation study. Gray and red boxes correspond to each of the 10 patients in the two groups. (D) AUROC of kTSP‐selected top performing pairs of circulating EV proteins identified in patients with precirrhotic NASH versus patients with cirrhotic NASH (AUROC: 0.8; 95% CI: 0.5634‐0.9427). A cutoff value equal to the number of kTPS pairs observed in each group was adopted.
FIG. 6
Pairwise comparisons of different levels of circulating EV proteins in a validation cohort of patients with cirrhotic NASH, patients with precirrhotic NASH, and healthy controls. Boxplots of pairwise comparisons of the top seven highest expressed circulating EV proteins isolated from patients with cirrhotic NASH, patients with precirrhotic NASH, and healthy controls. Data are reported as log2FC for WISP1 (A), AIMP1 (B), IL27RA (C), ICAM2 (D), IL1β (E), STK16 (F), and RGMA (G) for the three comparisons: patients with precirrhotic NASH versus healthy controls (left), patients with cirrhotic NASH versus healthy controls (center), and patients with precirrhotic NASH versus patients with cirrhotic NASH (right). Wilcoxon test (nonparametric, comparing the distributions of pairwise cohorts) and a regular Student t test (comparing means of raw and log2 values) were used to generate the P values reported in the boxplots.
References
- Younossi ZM, Koenig AB, Abdelatif D, Fazel Y, Henry L, Wymer M. Global epidemiology of nonalcoholic fatty liver disease—meta‐analytic assessment of prevalence, incidence, and outcomes. Hepatology 2016;64:73‐84. -PubMed
- Charlton MR, Burns JM, Pedersen RA, Watt KD, Heimbach JK, Dierkhising RA. Frequency and outcomes of liver transplantation for nonalcoholic steatohepatitis in the United States. Gastroenterology 2011;141:1249‐1253. -PubMed
- Wong RJ, Aguilar M, Cheung R, Perumpail RB, Harrison SA, Younossi ZM, et al. Nonalcoholic steatohepatitis is the second leading etiology of liver disease among adults awaiting liver transplantation in the United States. Gastroenterology 2015;148:547‐555. -PubMed
- Doycheva I, Watt KD, Rifai G, Abou Mrad R, Lopez R, Zein NN, et al. Increasing burden of chronic liver disease among adolescents and young adults in the USA: a silent epidemic. Dig Dis Sci 2017;62:1373‐1380. -PubMed
- Younossi Z, Anstee QM, Marietti M, Hardy T, Henry L, Eslam M, et al. Global burden of NAFLD and NASH: trends, predictions, risk factors and prevention. Nat Rev Gastroenterol Hepatol 2018;15:11‐20. -PubMed