Title: Progerin accelerates atherosclerosis by inducing endoplasmic reticulum stress in vascular smooth muscle cells
Abstract: Report12 March 2019Open Access Source DataTransparent process Progerin accelerates atherosclerosis by inducing endoplasmic reticulum stress in vascular smooth muscle cells Magda R Hamczyk Magda R Hamczyk Centro Nacional de Investigaciones Cardiovasculares Carlos III (CNIC), Madrid, Spain Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV), Spain Departamento de Bioquímica y Biología Molecular, Instituto Universitario de Oncología (IUOPA), Universidad de Oviedo, Oviedo, Spain Search for more papers by this author Ricardo Villa-Bellosta Ricardo Villa-Bellosta Centro Nacional de Investigaciones Cardiovasculares Carlos III (CNIC), Madrid, Spain Fundación Instituto de Investigación Sanitaria Fundación Jiménez Díaz (FIIS-FJD), Madrid, Spain Search for more papers by this author Víctor Quesada Víctor Quesada Departamento de Bioquímica y Biología Molecular, Instituto Universitario de Oncología (IUOPA), Universidad de Oviedo, Oviedo, Spain Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), Spain Search for more papers by this author Pilar Gonzalo Pilar Gonzalo Centro Nacional de Investigaciones Cardiovasculares Carlos III (CNIC), Madrid, Spain Search for more papers by this author Sandra Vidak Sandra Vidak Cell Biology of Genomes Group, National Cancer Institute, NIH, Bethesda, MD, USA Search for more papers by this author Rosa M Nevado Rosa M Nevado Centro Nacional de Investigaciones Cardiovasculares Carlos III (CNIC), Madrid, Spain Search for more papers by this author María J Andrés-Manzano María J Andrés-Manzano Centro Nacional de Investigaciones Cardiovasculares Carlos III (CNIC), Madrid, Spain Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV), Spain Search for more papers by this author Tom Misteli Tom Misteli Cell Biology of Genomes Group, National Cancer Institute, NIH, Bethesda, MD, USA Search for more papers by this author Carlos López-Otín Corresponding Author Carlos López-Otín [email protected] orcid.org/0000-0001-6964-1904 Departamento de Bioquímica y Biología Molecular, Instituto Universitario de Oncología (IUOPA), Universidad de Oviedo, Oviedo, Spain Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), Spain Search for more papers by this author Vicente Andrés Corresponding Author Vicente Andrés [email protected] orcid.org/0000-0002-0125-7209 Centro Nacional de Investigaciones Cardiovasculares Carlos III (CNIC), Madrid, Spain Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV), Spain Search for more papers by this author Magda R Hamczyk Magda R Hamczyk Centro Nacional de Investigaciones Cardiovasculares Carlos III (CNIC), Madrid, Spain Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV), Spain Departamento de Bioquímica y Biología Molecular, Instituto Universitario de Oncología (IUOPA), Universidad de Oviedo, Oviedo, Spain Search for more papers by this author Ricardo Villa-Bellosta Ricardo Villa-Bellosta Centro Nacional de Investigaciones Cardiovasculares Carlos III (CNIC), Madrid, Spain Fundación Instituto de Investigación Sanitaria Fundación Jiménez Díaz (FIIS-FJD), Madrid, Spain Search for more papers by this author Víctor Quesada Víctor Quesada Departamento de Bioquímica y Biología Molecular, Instituto Universitario de Oncología (IUOPA), Universidad de Oviedo, Oviedo, Spain Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), Spain Search for more papers by this author Pilar Gonzalo Pilar Gonzalo Centro Nacional de Investigaciones Cardiovasculares Carlos III (CNIC), Madrid, Spain Search for more papers by this author Sandra Vidak Sandra Vidak Cell Biology of Genomes Group, National Cancer Institute, NIH, Bethesda, MD, USA Search for more papers by this author Rosa M Nevado Rosa M Nevado Centro Nacional de Investigaciones Cardiovasculares Carlos III (CNIC), Madrid, Spain Search for more papers by this author María J Andrés-Manzano María J Andrés-Manzano Centro Nacional de Investigaciones Cardiovasculares Carlos III (CNIC), Madrid, Spain Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV), Spain Search for more papers by this author Tom Misteli Tom Misteli Cell Biology of Genomes Group, National Cancer Institute, NIH, Bethesda, MD, USA Search for more papers by this author Carlos López-Otín Corresponding Author Carlos López-Otín [email protected] orcid.org/0000-0001-6964-1904 Departamento de Bioquímica y Biología Molecular, Instituto Universitario de Oncología (IUOPA), Universidad de Oviedo, Oviedo, Spain Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), Spain Search for more papers by this author Vicente Andrés Corresponding Author Vicente Andrés [email protected] orcid.org/0000-0002-0125-7209 Centro Nacional de Investigaciones Cardiovasculares Carlos III (CNIC), Madrid, Spain Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV), Spain Search for more papers by this author Author Information Magda R Hamczyk1,2,3, Ricardo Villa-Bellosta1,4, Víctor Quesada3,5, Pilar Gonzalo1, Sandra Vidak6, Rosa M Nevado1, María J Andrés-Manzano1,2, Tom Misteli6, Carlos López-Otín *,3,5 and Vicente Andrés *,1,2 1Centro Nacional de Investigaciones Cardiovasculares Carlos III (CNIC), Madrid, Spain 2Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV), Spain 3Departamento de Bioquímica y Biología Molecular, Instituto Universitario de Oncología (IUOPA), Universidad de Oviedo, Oviedo, Spain 4Fundación Instituto de Investigación Sanitaria Fundación Jiménez Díaz (FIIS-FJD), Madrid, Spain 5Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), Spain 6Cell Biology of Genomes Group, National Cancer Institute, NIH, Bethesda, MD, USA *Corresponding author. Tel: +34 985104202; E-mail: [email protected] *Corresponding author. Tel: +34 914531200; E-mail: [email protected] EMBO Mol Med (2019)11:e9736https://doi.org/10.15252/emmm.201809736 See also: ED Pasquale & G Condorelli (April 2019) 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 Hutchinson–Gilford progeria syndrome (HGPS) is a rare genetic disorder caused by progerin, a mutant lamin A variant. HGPS patients display accelerated aging and die prematurely, typically from atherosclerosis complications. Recently, we demonstrated that progerin-driven vascular smooth muscle cell (VSMC) loss accelerates atherosclerosis leading to premature death in apolipoprotein E-deficient mice. However, the molecular mechanism underlying this process remains unknown. Using a transcriptomic approach, we identify here endoplasmic reticulum stress (ER) and the unfolded protein responses as drivers of VSMC death in two mouse models of HGPS exhibiting ubiquitous and VSMC-specific progerin expression. This stress pathway was also activated in HGPS patient-derived cells. Targeting ER stress response with a chemical chaperone delayed medial VSMC loss and inhibited atherosclerosis in both progeria models, and extended lifespan in the VSMC-specific model. Our results identify a mechanism underlying cardiovascular disease in HGPS that could be targeted in patients. Moreover, these findings may help to understand other vascular diseases associated with VSMC death, and provide insight into aging-dependent vascular damage related to accumulation of unprocessed toxic forms of lamin A. Synopsis In mouse models of Hutchinson–Gilford progeria syndrome (HGPS) featuring ubiquitous or vascular smooth muscle cell (VSMC)-specific progerin expression, RNA sequencing of medial aortas identified a new pathway involved in the etiopathology of the disease. Activation of endoplasmic reticulum (ER) stress and of the unfolded protein response (UPR) was observed prior signs of vascular disease in VSMC-rich aortic media from mouse models of HGPS. ER stress and the UPR were activated in cultured cells derived from HGPS patients and in some organs of the ubiquitous HGPS mouse model. VSMC loss was ameliorated and atherosclerosis was prevented in the HGPS mouse models upon tauroursodeoxycholic acid (TUDCA) treatment. VSMC-specific progeroid mice survival was prolonged by TUDCA, demonstrating its potential as a treatment for vascular disease in HGPS. Introduction Hutchinson–Gilford progeria syndrome (HGPS) is a devastating disease with an estimated prevalence of 1 in 20 million people (www.progeriaresearch.org). Affected children appear normal at birth but show early onset of aging-associated symptoms, including alopecia, reduced subcutaneous fat, osteoporosis, joint stiffness, and dermal abnormalities (Hennekam, 2006; Gordon et al, 2007; Merideth et al, 2008). The most important clinical manifestation of the disease is atherosclerosis, which causes death from myocardial infarction or stroke at an average age of 14.6 years (Ullrich & Gordon, 2015). Progerin also provokes cardiac abnormalities (Merideth et al, 2008; Rivera-Torres et al, 2016; Prakash et al, 2018) and defects in heart valves (Nair et al, 2004; Merideth et al, 2008; Olive et al, 2010; Hanumanthappa et al, 2011) and blood vessels, including vascular smooth muscle cell (VSMC) loss, adventitial thickening, calcification, and extracellular matrix deposition (Stehbens et al, 1999, 2001; Olive et al, 2010). “Classic” HGPS is caused by a point mutation in the LMNA gene (c.1824C>T;p.G608G), which activates a cryptic splice site in exon 11, leading to deletion of 150 nucleotides in the mRNA (De Sandre-Giovannoli et al, 2003; Eriksson et al, 2003). Consequent loss of 50 amino acids near the C terminus of the precursor prelamin A protein affects its post-translational modifications, resulting in the production of a permanently farnesylated mutant protein called progerin. Progerin alters many of the cellular functions normally regulated by lamin A, causing abnormal localization of nuclear envelope proteins, impaired chromatin organization, DNA damage and genome instability, mitochondrial dysfunction, oxidative stress, altered gene transcription and signal transduction, among others (Gordon et al, 2014b; Vidak & Foisner, 2016; Dorado & Andres, 2017). However, only a few studies have investigated the molecular alterations caused by progerin accumulation in VSMCs (Zhang et al, 2011, 2014; Villa-Bellosta et al, 2013; Hamczyk et al, 2018a), and none analyzed it in the context of atherosclerosis, the main death-causing symptom of HGPS, due to lack of adequate animal models. Recently, we have generated an HGPS-like mouse model of ubiquitous progerin expression that reproduces the main features of human HGPS, including VSMC loss in the aortic media, adventitial thickening, accelerated atherosclerosis, and shortened lifespan (Hamczyk et al, 2018b). Moreover, we have shown that limiting progerin expression to VSMCs is sufficient to cause the loss of these cells in the aorta and accelerate atherosclerosis and death, demonstrating a key role of VSMCs in the pathogenesis of HGPS (Hamczyk et al, 2018b). The aim of this study was to identify molecular mechanisms underlying progerin-induced VSMC loss, the principal driver of premature atherosclerosis and death in HGPS. Results To identify pathways underlying progerin-induced VSMC death, we conducted a transcriptomic analysis of progerin-expressing aortas. To this end, we used two mouse models of HGPS, with progerin expressed either ubiquitously (Apoe−/−LmnaG609G/G609G) or restricted to VSMCs (Apoe−/−LmnaLCS/LCSSM22αCre), which fully recapitulate the vascular phenotype observed in HGPS patients (Olive et al, 2010; Hamczyk et al, 2018b). To identify drivers of disease rather than secondary changes, we sought to collect arteries before the onset of evident disease. Since both substantial atherosclerosis and overt aortic structure alterations are found in normal chow-fed 16-week-old mice, but absent in normal chow-fed 8-week-old mice of both genotypes (Hamczyk et al, 2018b), we collected aortas at 8 weeks of age. To specifically detect molecular alterations in VSMC, which appear to be a major progerin target, we digested aortas with collagenase to separate fibroblast-containing adventitia from the VSMC-rich media (Fig 1A). We collected four pooled samples per genotype (Apoe−/−LmnaG609G/G609G and Apoe−/−LmnaLCS/LCSSM22αCre mice and their corresponding littermate controls Apoe−/−Lmna+/+ and Apoe−/−LmnaLCS/LCS, respectively), which showed the expected progerin and lamin A expression as assessed by PCR (Fig 1B). Figure 1. Progerin expression in vascular smooth muscle cell (VSMC)-rich aortic media activates endoplasmic reticulum (ER) stress and unfolded protein response (UPR) Sample preparation for RNA sequencing (RNAseq). PCR confirmation of proper expression of lamin A and progerin mRNA in pooled medial aortas used for RNAseq. Arbp was used as endogenous control. Bioinformatic analysis detected 776 differentially expressed genes in medial aortas from Apoe−/−LmnaG609G/G609G mice with ubiquitous progerin expression compared with Apoe−/−Lmna+/+ control mice expressing wild-type lamin A/C and 931 genes in medial aortas from Apoe−/−LmnaLCS/LCSSM22αCre mice with VSMC-specific progerin expression compared with Apoe−/−LmnaLCS/LCS control mice expressing lamin C only. There were 176 genes differentially expressed between the two control groups. The Venn diagram shows the overlap between sets of deferentially expressed genes identified in each of the three comparisons (n = 4 pooled medial aortas for each genotype). Correlation between base-2 logarithms of fold change calculated for the 240 genes shared between the comparisons “ubiquitous progerin versus wild-type lamin A/C” and “VSMC-specific progerin versus lamin C only”. RNAseq results were analyzed using Ingenuity Pathway Analysis: (left) canonical pathway heatmap, showing processes affected by progerin expression in VSMC-rich medial aortas. Asterisk (*) indicates pathways which are significantly changed in both comparisons after applying the Benjamini–Hochberg correction for multiple testing; (right) upstream regulator heatmap, showing predicted activation states of transcriptional regulators (black boxes indicate key molecules involved in ER stress and UPR regulation). Genes in each upstream regulator network are shown in the Fig EV2. Source data are available online for this figure. Source Data for Figure 1 [emmm201809736-sup-0009-SDataFig1B.pdf] Download figure Download PowerPoint Differential expression analysis of RNA sequencing data revealed 776 significantly altered genes in the ubiquitous progeroid model and 931 altered genes in the VSMC-specific model (Fig 1C, Datasets EV1 and EV2). Of these differentially regulated genes, 240 were common to both comparisons (Fig 1C, Dataset EV3) and exhibited high correlation (R2 ≈ 0.8, Fig 1D). Analysis of the two controls revealed 176 genes differentially expressed between Apoe−/−LmnaLCS/LCS aorta (expressing lamin C only) and Apoe−/−Lmna+/+ aorta (expressing wild-type lamin A/C; Dataset EV4). However, there was barely any overlap between the gene sets affected by progerin production in Apoe−/−LmnaG609G/G609G and Apoe−/−LmnaLCS/LCSSM22αCre mice and those influenced by the lack of lamin A in Apoe−/−LmnaLCS/LCS mice (Fig 1C). Likewise, we found no overlap in the main pathways affected by progerin expression (Fig EV1A and B) and lack of lamin A (Fig EV1C). Click here to expand this figure. Figure EV1. Pathways affected by lack of lamin A do not overlap with those induced by progerin expression A–C. Stacked bar charts representing pathways significantly changed after applying the Benjamini–Hochberg correction for multiple testing in three comparisons: (A) Apoe−/−LmnaG609G/G609G (ubiquitous progerin) versus Apoe−/−Lmna+/+ (both lamin A and lamin C), (B) Apoe−/−LmnaLCS/LCSSM22αCre (vascular smooth muscle cell (VSMC)-specific progerin) versus Apoe−/−LmnaLCS/LCS (lamin C only, no lamin A), and (C) Apoe−/−LmnaLCS/LCS (lamin C only, no lamin A) versus Apoe−/−Lmna+/+ (both lamin A and lamin C). The numbers of genes in each category (from the Ingenuity Pathway Analysis data base) are indicated above the bars. Download figure Download PowerPoint Comparison analysis identified four pathways that were significantly altered in medial aorta in both the ubiquitous and the VSMC-specific progerin-expressing models: fibrosis, nuclear factor erythroid 2-like 2 (NRF2)-mediated oxidative stress, endoplasmic reticulum (ER) stress response, and unfolded protein response (UPR; Fig 1E, Canonical pathways). We also examined the predicted activation status of upstream regulators based on the expression of their target genes. This analysis revealed that the most differentially regulated factors belong to the ER stress response and ER stress-related UPR. These factors include X-box-binding protein 1 (XBP1), activating transcription factor 4 (ATF4; also known as cyclic AMP-dependent transcription factor ATF-4), eukaryotic translation initiation factor 2-alpha kinase 3 (EIF2AK3; also known as protein kinase RNA-like ER kinase; PERK), and DNA damage-inducible transcript 3 protein (DDIT3; also known as C/EBP-homologous protein, CHOP; Fig 1E, Upstream regulators, genes in each ER stress-related upstream regulator network are shown in Fig EV2A–F). Further overrepresentation test for gene ontology (GO) cellular compartment of 240 genes shared between ubiquitous and VSMC-specific progeroid models showed higher than 10-fold enrichment for sarcoplasmic reticulum (GO:0016529) and sarcoplasm (GO:0016528; Table EV1). Click here to expand this figure. Figure EV2. Genes in the endoplasmic reticulum stress/unfolded protein response-related upstream regulator networks A–F. Heatmaps (from Ingenuity Pathway Analysis) show expression of genes in (A) X-box-binding protein 1 (gene: Xbp1; protein: XBP1), (B) activating transcription factor 4 (gene: Atf4; protein: ATF4), (C) eukaryotic translation initiation factor 2-alpha kinase 3 (gene: Eif2ak3; protein: EIF2AK3, alternatively protein kinase RNA-like ER kinase, PERK), (D) tribbles pseudokinase 3 (gene: Trib3; protein: tribbles homolog 3, TRB3), (E) heat shock protein 5 (gene: Hspa5; protein: endoplasmic reticulum chaperone binding-immunoglobulin protein, BiP, alternatively 78 kDa glucose-regulated protein, GRP78), and (F) DNA damage-inducible transcript 3 (gene: Ddit3; protein: DNA damage-inducible transcript 3 protein, DDIT3, alternatively C/EBP-homologous protein, CHOP) networks. Gene nomenclature displayed on the figure refers to the human orthologue. VSMC, vascular smooth muscle cell. VSMC-SPECIFIC refers to Apoe−/−LmnaLCS/LCSSM22αCre vs Apoe−/−LmnaLCS/LCS comparison and UBIQUITOUS refers to Apoe−/−LmnaG609G/G609G vs Apoe−/−Lmna+/+ comparison. Download figure Download PowerPoint To validate the RNA sequencing results, we performed quantitative real-time PCR on selected ER stress response and UPR genes that were significantly upregulated in aortic media from 8-week-old mice in both progeria models (Fig 2A; see also schemes in Appendix Fig S1 showing genes within ER stress/UPR pathway significantly altered in each model). This analysis confirmed progerin-induced upregulation of Calr, Ddit3, Dnajb9, Hspa5, Hsp90b1, and Pdia4 in VSMC-rich aortic media in both models (Fig 2B and C). We next used quantitative real-time PCR to analyze immortalized HGPS patient-derived cells. A wide range of ER stress-related genes, such as HSP90B1, HSPA5, CALR, and DNAJC3, and the bona fide UPR genes DDIT3, ATF4, EIF2AK3, ERN1, PPP1R15A, and the spliced form of XBP1 were upregulated in HGPS patient cells (Fig 2D). We also assessed whether progerin activates the ER stress response and the UPR in other organs of our progeroid mouse models. Consistent with the ubiquity of progerin expression in Apoe−/−LmnaG609G/G609G mice, induction of ER stress response and the UPR was noted in some organs of these animals, with kidney being the most affected organ and liver the least (Fig 2E). As anticipated, no activation of this stress pathway was detected in kidney, liver, spleen, or heart from Apoe−/−LmnaLCS/LCSSM22αCre mice, consistent with the VSMC-specificity of the model (Fig 2F). The state of ER stress in VSMCs in the aorta of both progeroid mouse models was further confirmed by immunostaining against ER chaperone binding-immunoglobulin protein (BiP, also known as 78 kDa glucose-regulated protein, GRP78; product of Hspa5 gene), calreticulin (product of Calr gene), and protein disulfide isomerase (PDI; product of P4hb gene; Fig 3A and B). Quantitative analysis revealed higher level of these proteins in the aorta of both progeroid mouse models compared with their respective controls (Fig 3C and D). Figure 2. Endoplasmic reticulum (ER) stress and unfolded protein response (UPR) activation in progerin-expressing medial aortas and in Hutchinson–Gilford progeria syndrome (HGPS) patient-derived cells A. Six ER stress/UPR pathway genes selected for quantitative real-time PCR validation from among those detected as differentially expressed in RNAseq in both the ubiquitous and the vascular smooth muscle cell (VSMC)-specific models. B, C. mRNA levels of the selected genes in medial aortas obtained from 8-week-old Apoe−/−LmnaG609G/G609G mice (B) and Apoe−/−LmnaLCS/LCSSM22αCre mice (C) and their corresponding controls. Hprt and Gusb were used for normalization (n = 4 pools of medial aortas for each genotype). D. Quantification of mRNA levels of several ER stress and UPR genes in patient-derived immortalized human HGPS fibroblasts relative to healthy control. GAPDH was used for normalization and PBGD served as a negative control (n = 3 cultures for each group). E, F. mRNA levels of the selected genes in organs from 8-week-old Apoe−/−LmnaG609G/G609G mice (E) and Apoe−/−LmnaLCS/LCSSM22αCre mice (F) and their corresponding controls. Hprt and Gusb were used for normalization (n = 4 mice for each genotype). Data information: In (B–F), data are presented as mean ± SEM. Statistical differences were analyzed by one-tailed unpaired t-test in (B, C), one-tailed one-sample t-test in (D), and by two-tailed unpaired t-test in (E, F). #P < 0.061, *P < 0.05, **P < 0.01, ***P < 0.001. The exact P-values are shown in Appendix Table S1. Download figure Download PowerPoint Figure 3. Activation of endoplasmic reticulum stress in medial aortas of Apoe−/−LmnaG609G/G609G and Apoe−/−LmnaLCS/LCSSM22αCre mice A, B. Representative immunofluorescence images of aortas from 8-week-old Apoe−/−LmnaG609G/G609G (A) and Apoe−/−LmnaLCS/LCSSM22αCre (B) mice and their corresponding controls stained with anti-α-smooth muscle actin (SMA) antibody (red), endoplasmic reticulum chaperone binding-immunoglobulin protein (BiP, white, upper panel), protein disulfide isomerase (PDI, white, middle panel), and calreticulin (white, bottom panel). Arrowheads indicate BiP-positive cells. Scale bar: 50 μm. L, lumen; M, media; A, adventitia. C, D. Graphs show quantification of BiP, PDI, and calreticulin protein expression in medial aortas from 8-week-old Apoe−/−LmnaG609G/G609G (C) and Apoe−/−LmnaLCS/LCSSM22αCre (D) mice relative to control mice (n = 6–9 mice for each genotype; aortic regions analyzed: aortic arch). Data information: In (C, D), data are mean ± SEM. Statistical differences were analyzed by one-tailed unpaired t-test with Welch's correction. Download figure Download PowerPoint Our RNA sequencing results strongly suggested that progerin-induced ER stress response and UPR might underlie VSMC death and enhance atherosclerosis in the ubiquitous and VSMC-specific progeria mice. We therefore examined the potential benefits of tauroursodeoxycholic acid (TUDCA), a chemical chaperone that augments the capacity of cells to sustain ER stress and protects from apoptosis (Xie et al, 2002; Rivard et al, 2007; Uppala et al, 2017). One-week TUDCA treatment of 8-week-old Apoe−/−LmnaLCS/LCSSM22αCre mice slightly increased in medial aorta the mRNA levels of Pdia4 (coding for a protein disulfide isomerase) and Hsp90b1 (coding for a chaperone; Fig EV3), suggesting mild enhancement of protein folding capacity. Moreover, it markedly decreased the expression of Ddit3 gene coding for DDIT3 (Fig EV3), a pro-apoptotic transcription factor of the UPR machinery, indicating that TUDCA helps to resist ER stress-induced death in VSMCs. Click here to expand this figure. Figure EV3. Treatment with tauroursodeoxycholic acid (TUDCA) reduces Ddit3 gene expression in medial aortas of Apoe−/−LmnaLCS/LCSSM22αCre miceEight-week-old Apoe−/−LmnaLCS/LCS and Apoe−/−LmnaLCS/LCSSM22αCre mice received TUDCA or phosphate-buffered saline (PBS) intraperitoneal injections for 7 consecutive days. Animals were sacrificed at 9 weeks of age, and medial aortas were harvested and pooled (2–3 animals of the same genotype per pool). Six genes related to endoplasmic reticulum stress and the unfolded protein response pathway were analyzed by quantitative real-time PCR. Hprt and Gusb were used for normalization (n = 3 pooled medial aortas for PBS and TUDCA-treated Apoe−/−LmnaLCS/LCS mice, and n = 4 pooled medial aortas for PBS and TUDCA-treated Apoe−/−LmnaLCS/LCSSM22αCre mice). Data are mean ± SEM. Statistical differences were analyzed by one-way ANOVA with Tukey's post hoc test. *P < 0.05, **P < 0.01, ***P < 0.001. Download figure Download PowerPoint After confirming that prolonged TUDCA administration did not trigger any deleterious side effects (Appendix Fig S2), we evaluated its effectiveness in ameliorating vascular disease in high-fat diet-fed ubiquitous and VSMC-specific progeroid mouse models. TUDCA treatment alleviated aortic VSMC loss (Fig 4A and B), adventitial thickening (Fig 4C and D), and inhibited atherosclerosis (Fig 4E and F) in both Apoe−/−LmnaG609G/G609G and Apoe−/−LmnaLCS/LCSSM22αCre mice. Atheromas of TUDCA-treated progeroid animals showed reduced necrotic core size and increased VSMC content (Table EV2), indicating an amelioration of the vulnerable plaque phenotype reported previously in these mice (Hamczyk et al, 2018b). We next assessed the effect of a sustained TUDCA treatment on survival in normal chow-fed progeroid mice. TUDCA prolonged the median lifespan of Apoe−/−LmnaLCS/LCSSM22αCre mice by 38% (median survival: 64.15 weeks in TUDCA-treated versus 46.45 weeks in untreated mice), without significantly affecting the survival of Apoe−/−LmnaG609G/G609G mice (Fig 4G). Figure 4. Tauroursodeoxycholic acid (TUDCA) treatment alleviates vascular phenotype in progeria mouse models and extends lifespan in Apoe−/−LmnaLCS/LCSSM22αCre miceMice were injected 3 times a week with TUDCA or phosphate-buffered saline (PBS), starting at 6 weeks of age for Apoe−/−Lmna+/+ and Apoe−/−LmnaG609G/G609G mice and at 8 weeks of age for Apoe−/−LmnaLCS/LCS and Apoe−/−LmnaLCS/LCSSM22αCre mice. In (A–F), mice were fed a high-fat diet for 8 weeks starting at 8 weeks of age and sacrificed at 16 weeks of age. In (G), mice were fed normal chow. A, B. Representative immunofluorescence images of aortas stained with anti-α-smooth muscle actin (SMA) antibody (red) and Hoechst 33342 (blue). Graphs show quantification of vascular smooth muscle cell (VSMC) content in the media as either % of SMA-positive area (top) or nucleus count (bottom) (n = 6 mice for each group in A; n = 4–5 mice for each group in B; aortic regions analyzed: aortic arch and thoracic aorta). Scale bar: 50 μm. m, media; a, adventitia. C, D. Representative histology sections of hematoxylin & eosin (H&E)-stained aortas. Graphs show quantification of adventitia-to-media thickness ratio (n = 6 mice for each group in C; n = 4–5 mice for each group in D; aortic regions analyzed: aortic arch and thoracic aorta). Scale bar: 100 μm. m, media; a, adventitia. E, F. Representative images of thoracic aortas stained with Oil Red O and quantification of atherosclerosis burden in TUDCA-treated and untreated (PBS) fat-fed mice of the indicated genotypes (n = 7–8 mice for each group in E; n = 6–8 mice for each group in F). G. Kaplan–Meier survival curves of TUDCA-treated and untreated (PBS) mice of the indicated genotypes (n = 7–8 Apoe−/−LmnaG609G/G609G mice for each group; n = 16 Apoe−/−LmnaLCS/LCSSM22αCre mice for each group); P < 0.0001 for TUDCA-treated vs untreated Apoe−/−LmnaLCS/LCSSM22αCre mice (median survival: 64.15 vs 46.45 weeks, respectively). Data information: Data in (A–F), are mean ± SEM. Statistical differences were analyzed by one-tailed unpaired t-test in (A–D), one-way ANOVA with Tukey′s post hoc test in (E, F), and by log-rank test in (G). **P < 0.01, ***P < 0.001. Source data are available online for this figure. Source Data for Figure 4 [emmm201809736-sup-0010-SDataFig4G.pdf] Download figure Download PowerPoint Discussion Given the importance of VSMCs in progerin-driven cardiovascular disease (Stehbens et al, 2001; Olive et al, 2010; Hamczyk et al, 2018b), we sought to identify mechanisms underlying VSMC death and enhanced atherosclerosis in HGPS, which seem to be independent of elevated cholesterol levels in the blood (Gordon et al, 2005; Hamczyk et al, 2018b). Previous in vitro and in vivo studies identified numerous pathways potentially contributing to HGPS (Strandgren et al, 2017). Most of them are mutually dependent, making it difficult to distinguish primary from secondary mechanisms. Our RNAseq analysis