Plasma cholesterol-induced lesion networks activated before regression of early, mature, and advanced atherosclerosis - PubMed (original) (raw)

. 2014 Feb 27;10(2):e1004201.

doi: 10.1371/journal.pgen.1004201. eCollection 2014 Feb.

Sara Hägg 2, Husain A Talukdar 3, Hassan Foroughi Asl 3, Rajeev K Jain 4, Cecilia Cedergren 3, Ming-Mei Shang 3, Aránzazu Rossignoli 3, Rabbe Takolander 5, Olle Melander 6, Anders Hamsten 7, Tom Michoel 8, Josefin Skogsberg 3

Affiliations

Plasma cholesterol-induced lesion networks activated before regression of early, mature, and advanced atherosclerosis

Johan L M Björkegren et al. PLoS Genet. 2014.

Abstract

Plasma cholesterol lowering (PCL) slows and sometimes prevents progression of atherosclerosis and may even lead to regression. Little is known about how molecular processes in the atherosclerotic arterial wall respond to PCL and modify responses to atherosclerosis regression. We studied atherosclerosis regression and global gene expression responses to PCL (≥80%) and to atherosclerosis regression itself in early, mature, and advanced lesions. In atherosclerotic aortic wall from Ldlr(-/-)Apob (100/100) Mttp (flox/flox)Mx1-Cre mice, atherosclerosis regressed after PCL regardless of lesion stage. However, near-complete regression was observed only in mice with early lesions; mice with mature and advanced lesions were left with regression-resistant, relatively unstable plaque remnants. Atherosclerosis genes responding to PCL before regression, unlike those responding to the regression itself, were enriched in inherited risk for coronary artery disease and myocardial infarction, indicating causality. Inference of transcription factor (TF) regulatory networks of these PCL-responsive gene sets revealed largely different networks in early, mature, and advanced lesions. In early lesions, PPARG was identified as a specific master regulator of the PCL-responsive atherosclerosis TF-regulatory network, whereas in mature and advanced lesions, the specific master regulators were MLL5 and SRSF10/XRN2, respectively. In a THP-1 foam cell model of atherosclerosis regression, siRNA targeting of these master regulators activated the time-point-specific TF-regulatory networks and altered the accumulation of cholesterol esters. We conclude that PCL leads to complete atherosclerosis regression only in mice with early lesions. Identified master regulators and related PCL-responsive TF-regulatory networks will be interesting targets to enhance PCL-mediated regression of mature and advanced atherosclerotic lesions.

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Conflict of interest statement

The authors have declared that no competing interests exist. JLMB is founder, main shareholder and chairman of the board for Clinical Gene Networks AB (CGN) and TM is shareholder. CGN has, however, no current commercial interest or rights in relations to the results presented in this manuscript.

Figures

Figure 1

Figure 1. Atherosclerosis progression in Ldlr−/−Apob 100/100 Mttp flox/flox mice and regression in Ldlr−/−Apob 100/100 Mttp Δ/Δ mice.

(A) Atherosclerosis progression and regression curves. Values are surface lesion area (mean ± SD), assessed by Sudan IV staining, as a percentage of the total area of pinned-out aortas. n = 4–10 per time point. Lesion development in controls without PCL (•) (P<0.001 vs. 30 weeks) and in mice after PCL started at week 30 (▴), 40 (▪), or 50 (formula image). Changes in lesion area between 10 and 20 weeks of low plasma cholesterol were significant only in mice with early lesions (PCL at 30 weeks, P = 0.05). *P = 0.05, ***P<0.001. (B) Representative aortic trees (above) with magnified arches (below) stained with Sudan IV before and 10 and 20 weeks after PCL at 30, 40 and 50 weeks. Graphs indicate degree of regression at that PCL time-point (red).

Figure 2

Figure 2. Immunohistochemical characteristics of representative frozen sections of aortic roots from Ldlr−/−Apob 100/100 Mttp flox/flox and Ldlr−/−Apob 100/100 Mttp Δ/Δ mice.

(A–C) Average percent stained area of total aortic root area (right) and representative stained aortic roots (left). Bars indicate SD. Original magnification, 50×. *P<0.05, **P<0.01, and ***P<0.001. (A) Oil-Red-O staining (n = 6–9 per group). (B) CD68 staining (n = 5–8 per group). (C) Sirius Red staining (collagen) (n = 3 per group). (D) Mean plaque stability score (arbitrary units). Bars indicate SD. Average plaque stability scores were divided by total extent of plaque burden to assess stability per mouse (not individual plaques). Inset: magnifications of plaque stability score/mouse at 30, 40, 50, and 60 weeks before regression.

Figure 3

Figure 3. Transcriptional profiling during regression of aortic atherosclerotic lesions in Ldlr−/−Apob 100/100 Mttp flox/flox and Ldlr−/−Apob 100/100 Mttp Δ/Δ mice over time.

Differential expression analyses was used to define sets of genes causally and reactively related to atherosclerosis regression in Ldlr−/−Apob 100/100 Mttp Δ/Δ mice. RNA for the transcriptional profiling was isolated from the atherosclerotic aortic arch. Narrow and bold arrows indicate times of PCL and sacrifice, respectively. Colored horizontal lines indicate time frame of transcriptional profiles used for differential expression analysis to define gene sets. Colors indicate when PCL was started: green, 30 weeks; yellow, 40 weeks; red, 50 weeks. (A) To define the PCL-responsive gene sets, we compared transcriptional profiles (4–6 per time point) of PBS-treated, high-cholesterol littermate controls sacrificed at 30, 40 and 50 weeks with those immediately after PCL. (B) To define the regression-reactive gene sets, we compared transcriptional profiles (3–6 per time point) immediately after PCL with those at 10 weeks after PCL (10 per time point).

Figure 4

Figure 4. PCL-responsive and regression reactive gene sets of atherosclerosis regression.

Venn diagrams showing the percentage/number of differentially expressed genes at 30, 40, and 50 weeks. The colors of the circles indicate when PCL was started: green, 30; yellow, 40 weeks; red, 50 weeks. The percentage in the circles to the left represent the percentage of differentially expressed genes for that section and specific time point. The numbers in circles to the right represent numbers of differentially expressed genes. (A) The PCL-responsive gene sets consist of genes that responded immediately to PCL, initiating regression of early (30 weeks), mature (40 weeks), and advanced (50 weeks) atherosclerosis. (B) The regression-reactive gene sets consist of genes altered in lesions between immediately after PCL and 10 weeks of low plasma cholesterol levels.

Figure 5

Figure 5. CAD-patient macrophage TF-regulatory coexpression networks of PCL-responsive genes linked to atherosclerosis regression.

To learn more about functional interactions of the PCL-responsive gene sets using human orthologs, we used macrophage mRNA profiles (n = 38) from patients with CAD to infer TF-regulatory gene networks. Red square nodes are TFs. Yellow square nodes are specific master regulatory TFs (Table 4): PPARG for the network in early lesions (30 weeks) and MLL5 for the network in mature lesions (40 weeks) and SRSF10 and XRN2 for the network in advanced lesions (50 weeks). Edges are connections between TFs and their first neighbor. (A) At 30 weeks, 53 genes of 215 human orthologs belonged to the TF-regulatory network (P<0.0051), in which the most connected TFs (master regulators) were PPARA (17 edges) and PPARG (13 edges) (Table 2). The TF-regulatory network of PCL-responsive atherosclerosis regression genes at 30 weeks is magnified in (D) to show all nodes. (B) At 40 weeks, 185 genes of 1087 human orthologs in the causal gene set belonged to the TF-regulatory network (P<0.0013). The most connected TFs were HMGB2, ADORA2A, and TERF1, with 61, 59 and 55 edges, respectively (Table 2). (C) At 50 weeks, 379 genes of 1865 human orthologs in the causal gene set belonged to the TF-regulatory network (P<0.00042), in which the most connected TFs were SRSF10, XRN2, and HMGB1, with 71, 67 and 62 edges, respectively (Table 2). (D) A magnification of the TF regulatory network of PCL-responsive genes at week 30, shown in (A).

References

    1. Global Atlas on Cardiovascular Disease Prevention and Control (Mendis S, Puska P, Norrving B, eds). Geneva: World Health Organization, 2011.
    1. Brown MS, Goldstein JL (2006) Biomedicine. Lowering LDL–not only how low, but how long? Science 311: 1721–1723. - PubMed
    1. Brown BG, Zhao XQ, Sacco DE, Albers JJ (1993) Lipid lowering and plaque regression. New insights into prevention of plaque disruption and clinical events in coronary disease. Circulation 87: 1781–1791. - PubMed
    1. LaRosa JC, Grundy SM, Waters DD, Shear C, Barter P, et al. (2005) Intensive lipid lowering with atorvastatin in patients with stable coronary disease. N Engl J Med 352: 1425–1435. - PubMed
    1. Ong HT (2005) The statin studies: from targeting hypercholesterolaemia to targeting the high-risk patient. QJM 98: 599–614. - PubMed

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