Unknown,Transcriptomics,Genomics,Proteomics

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The effect of statins on blood gene expression in COPD

ABSTRACT: Background: COPD is currently the fourth leading cause of death worldwide and predicted to rank third by 2020. Statins are commonly used lipid lowering agents with documented benefits on cardiovascular morbidity and mortality, and have also been shown to have pleiotropic effects including anti-inflammatory and anti-oxidant activity. Objective: Identify a gene signature associated with statin use in the blood of COPD patients, and identify molecular mechanisms and pathways underpinning this signature that could explain any potential benefits in COPD. Methods: Whole blood gene expression was measured on 168 statin users and 452 non-users from the ECLIPSE (Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints) study. Gene expression was measured using the Affymetrix Human Gene 1.1 ST microarray chips. Factor Analysis for Robust Microarray Summarization (FARMS) was used to process the expression data and to filter out non-informative probe sets. Differential gene expression analysis was undertaken using the Linear Models for Microarray data (Limma) package adjusting for propensity score and employing a surrogate variable analysis. Similarity of the expression signal with published gene expression profiles was performed in ProfileChaser. Results: 18 genes were differentially expressed between statin users and non-users at a false discovery rate of 10%. Top genes included LDLR, ABCA1, ABCG1, MYLIP, SC4MOL, and DHCR24. The 18 genes were significantly enriched in pathways and biological processes related to cholesterol homeostasis and metabolism, and were enriched for transcription factor binding sites for sterol regulatory element binding protein 2 (SREBP-2). The resulting gene signature showed correlation with Huntington disease, Parkinson’s disease and acute myeloid leukemia. Conclusion: Statins gene signature was not enriched in any pathways related to respiratory diseases, beyond the drug’s effect on cholesterol homeostasis. Study subjects were a subset of those with COPD from the Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE) study (Vestbo et al.), funded by GlaxoSmithKline (GSK Study No. SCO104960, NCT00292552). ECLIPSE is a non-interventional, observational, multicentre, three-year study in people with COPD. Blood was collected in PAXGene tubes and frozen at -80oC. In this work we have looked at the effect of statins on gene expression in 620 subjects of whom 168 were statin users. ECLIPSE study was described in: Vestbo J, Anderson W, Coxson HO, et al.: Evaluation of COPD Longitudinally to Identify Predictive Surrogate End-points (ECLIPSE). Eur Respir J. 2008;31(4):869-73

ORGANISM(S): Homo sapiens

SUBMITTER: Bruce McManus

PROVIDER: E-GEOD-71220 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Project description:Background: COPD is currently the fourth leading cause of death worldwide and predicted to rank third by 2020. Statins are commonly used lipid lowering agents with documented benefits on cardiovascular morbidity and mortality, and have also been shown to have pleiotropic effects including anti-inflammatory and anti-oxidant activity. Objective: Identify a gene signature associated with statin use in the blood of COPD patients, and identify molecular mechanisms and pathways underpinning this signature that could explain any potential benefits in COPD. Methods: Whole blood gene expression was measured on 168 statin users and 452 non-users from the ECLIPSE (Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints) study. Gene expression was measured using the Affymetrix Human Gene 1.1 ST microarray chips. Factor Analysis for Robust Microarray Summarization (FARMS) was used to process the expression data and to filter out non-informative probe sets. Differential gene expression analysis was undertaken using the Linear Models for Microarray data (Limma) package adjusting for propensity score and employing a surrogate variable analysis. Similarity of the expression signal with published gene expression profiles was performed in ProfileChaser. Results: 18 genes were differentially expressed between statin users and non-users at a false discovery rate of 10%. Top genes included LDLR, ABCA1, ABCG1, MYLIP, SC4MOL, and DHCR24. The 18 genes were significantly enriched in pathways and biological processes related to cholesterol homeostasis and metabolism, and were enriched for transcription factor binding sites for sterol regulatory element binding protein 2 (SREBP-2). The resulting gene signature showed correlation with Huntington disease, Parkinson’s disease and acute myeloid leukemia. Conclusion: Statins gene signature was not enriched in any pathways related to respiratory diseases, beyond the drug’s effect on cholesterol homeostasis.

Project description:Statins, the 3-hydroxy-3-methyl-glutaryl (HMG)-CoA reductase inhibitors, are widely prescribed for treatment of hypercholesterolemia. Although statins are generally well tolerated, up to ten percent of patients taking statins experience muscle related adverse events. Myalgia, defined as muscle pain without elevated creatinine phosphokinase (CPK) levels, is the most frequent reason for discontinuation of statin therapy. The mechanisms underlying statin-associated myalgia are not clearly understood. To elucidate changes in gene expression associated with statin-induced myalgia, we compared profiles of gene expression in the biopsied skeletal muscle from statin-intolerant patients undergoing statin re-challenge versus those of statin-tolerant controls. A robust separation of statin-intolerant and statin-tolerant cohorts was revealed by Principal Component Analysis of differentially expressed genes (DEGs). To identify putative gene expression and metabolic pathways that may be perturbed in skeletal muscles of statin intolerant patients, we subjected DEGs to Ingenuity Pathways (IPA) and DAVID (Database for Annotation, Visualization and Integrated Discovery) analyses. The most prominent pathways altered by statins included cellular stress, apoptosis, senescence and DNA repair (TP53, BARD1, Mre11 and RAD51); activation of pro-inflammatory immune response (CXCL12, CST5, POU2F1); protein catabolism, cholesterol biosynthesis, protein prenylation and RAS-GTPase activation (FDFT1, LSS, TP53, UBD, ATF2, H-ras). Based on these data we tentatively conclude that persistent myalgia in response to statins may emanate from cellular stress underpinned by mechanisms of post-inflammatory repair and regeneration. We also posit that this subset of individuals are genetically predisposed to eliciting altered statin metabolism and/or increased end-organ susceptibility that lead to a range of statin-induced myopathies. This mechanistic scenario further bolstered by the discovery that a number of single nucleotide polymorphisms (e.g., SLCO1B1, SLCO2B1 and RYR2) associated with statin myopathy were observed with increased frequency among statin-intolerant study subjects.

Project description:Background: Cholesterol pathway inhibition by statins prevents breast cancer development in mouse models of breast cancer but their efficacy is not very high (about 50%) . Therefore, the goal of this study is to investigate if the fluvastatin mediated upregulation in the steroid biosynthesis pathway genes limit the efficacy of statin chemoprevention. Methods: A published gene signature of statin resistance was validated in cell line-based models of inherent and acquired resistance during breast cancer. These signatures were next validated in a mouse model of hormone receptor negative breast cancer. Results: We found more than 70% of a published multi-gene fluvastatin resistance signature to be significantly upregulated in an inherently resistant cell line relative to fluvastatin sensitive cell line. We found this inherent statin resistance gene signature to be also shared with the signature of acquired resistance to fluvastatin (13 / 23 total genes). These 13 inherent resistance genes and 10 additional genes mapped to 2 of the top 3 deregulated pathways that are steroid-, and terpenoid backbone- biosynthesis pathway. Next, we tested if one or multiple genes of statin resistance signature, could predict efficacy of statin chemoprevention in the SV40 C3TAg transgenic mouse model. We found upregulation of a large number (19/24) of genes in the tumor bearing mammary glands, suggesting that upregulation of these pathways drives resistance to statin chemoprevention. A subset of 13-genes from this panel was significantly associated with response to statin treatment, as was the expression level of HMGCR alone in a mouse model of breast cancer. Lastly, we studied if a 10-day period of fluvastatin treatment to SV40C3 TAg mice, can also trigger the upregulation of these genes and provide an early signal of statin resistance. These experiments showed that a 10-day period is insufficient to cause a feedback upregulation in steroid biosynthesis pathway genes and thus cannot be used as an early biomarker to detect resistance to fluvastatin. Conclusions: High basal or restorative upregulation in the steroid biosynthesis pathway gene expression after fluvastatin treatment appears to be strongly associated with resistance to statin chemoprevention for breast cancer and may serve as a biomarker to identify patients that are most likely to respond to statins or develop resistance.

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The effect of statins on blood gene expression in COPD

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