Gene expression profiling of human atrial myocardium with atrial fibrillation by DNA microarray analysis

Ohki, Ruri; Yamamoto, Keiji; Ueno, Shu‐ichi; Mano, Hiroyuki; Misawa, Yoshio; Fuse, Katsuo; Ikeda, Uichi; Shimada, Kazuyuki

doi:10.1016/j.ijcard.2004.05.026

Cited by 50 publications

(35 citation statements)

References 30 publications

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“…Kim et al found upregulation of pro-oxidant and downregulation of antioxidant genes. 11 Investigators subsequently found 33 genes with Ͼ50% upregulation and 63 with Ͼ50% downregulation, 12,13 with changes in genes related to cell signaling, inflammation, oxidation and cellular respiration. 13 Barth et al found that the human atrial transcriptome changed to a ventricular-like pattern in AF-patients.…”

Section: Relationship To Previous Findings Regarding Gene-expression mentioning

confidence: 99%

“…11 Investigators subsequently found 33 genes with Ͼ50% upregulation and 63 with Ͼ50% downregulation, 12,13 with changes in genes related to cell signaling, inflammation, oxidation and cellular respiration. 13 Barth et al found that the human atrial transcriptome changed to a ventricular-like pattern in AF-patients. 14 One limitation of these studies was the difference in heart disease between AF-patients (valve disease, often with cardiac hypertrophy, dilation and/or dysfunction) compared with sinusrhythm controls (coronary-artery disease with well-preserved ventricular function).…”

Section: Relationship To Previous Findings Regarding Gene-expression mentioning

confidence: 99%

“…Gene microarray technology permits large-scale analysis of cardiac geneexpression changes, and has been applied to compare AF patients with those in sinus rhythm. Expression profiling has pointed to several AF-related gene-expression changes, [11][12][13][14][15] including alterations associated with oxidative stress, 11 a ventricular-like expression signature 14 and changes in iontransporters. 15 A limitation of this type of clinical geneexpression study is that it is very difficult to differentiate between AF-promoting changes caused by AF and those resulting from underlying cardiac disease.…”

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confidence: 99%

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Contrasting Gene Expression Profiles in Two Canine Models of Atrial Fibrillation

Cardin

Libby

Pelletier

et al. 2007

Circulation Research

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Abstract-Gene-expression changes in atrial fibrillation patients reflect both underlying heart-disease substrates and changes because of atrial fibrillation-induced atrial-tachycardia remodeling. These are difficult to separate in clinical investigations. This study assessed time-dependent mRNA expression-changes in canine models of atrial-tachycardia remodeling and congestive heart failure. Five experimental groups (5 dogs/group) were submitted to atrial (ATP, 400 bpm ϫ24 hours, 1 or 6 weeks) or ventricular (VTP, 240 bpm ϫ24 hours or 2 weeks) tachypacing. The expression of Ϸ21,700 transcripts was analyzed by microarray in isolated left-atrial cardiomyocytes and (for 18 genes) by real-time RT-PCR. Protein-expression changes were assessed by Western blot. In VTP, a large number of significant mRNA-expression changes occurred after both 24 hours (2209) and 2 weeks (2720). In ATP, fewer changes occurred at 24 hours (242) and fewer still (87) at 1 week, with no statistically-significant alterations at 6 weeks. Expression changes in VTP varied over time in complex ways. Extracellular matrix-related transcripts were strongly upregulated by VTP consistent with its pathophysiology, with 8 collagen-genes upregulated Ͼ10-fold, fibrillin-1 8-fold and MMP2 4.5-fold at 2 weeks (time of fibrosis) but unchanged at 24 hours. Other extracellular matrix genes (eg, fibronectin, lysine oxidase-like 2) increased at both time-points (Ϸ10, Ϸ5-fold respectively). In ATP, mRNA-changes almost exclusively represented downregulation and were quantitatively smaller. This study shows that VTP-induced congestive heart failure and ATP produce qualitatively different temporally-evolving patterns of gene-expression change, and that specific transcriptomal responses associated with atrial fibrillation versus underlying heart disease substrates must be considered in assessing gene-expression changes in man. Key Words: arrhythmia Ⅲ remodeling Ⅲ genomic A trial fibrillation (AF) is the most common sustained cardiac rhythm disorder, and with the aging of the population both the prevalence and economic impact of AF are increasing progressively. 1 Although the mechanistic basis of AF remains incompletely understood, active research promises to provide new insights that may lead to improved therapeutic options. 2,3 A variety of animal models have been used to assess AF pathophysiology under controlled conditions. Atrial tachyarrhythmias, including AF itself, alter atrial electrophysiology in ways that promote AF vulnerability. [4][5][6] Experimentally-induced congestive heart failure (CHF) also creates a substrate for AF maintenance, but by quite different mechanisms. 7 The atrial-tachycardia remodeling paradigm shows prominent changes in ion-channel function that lead to action-potential abbreviation and the promotion of atrial reentry. 8,9 CHF-induced ionic-current changes do not promote reentry but may favor ectopic-impulse formation, 10 and CHF-induced fibrosis promotes reentry by interfering with intraatrial conduction. 7 The molecular basis of AF ...

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Section: Relationship To Previous Findings Regarding Gene-expression mentioning

confidence: 99%

Section: Relationship To Previous Findings Regarding Gene-expression mentioning

confidence: 99%

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confidence: 99%

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Contrasting Gene Expression Profiles in Two Canine Models of Atrial Fibrillation

Cardin

Libby

Pelletier

et al. 2007

Circulation Research

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“…However, arrhythmia often leads to acute HF. CEBPD messenger RNA expression has been induced in the atria of AF patients (Ohki et al, 2005). Transgenic mice major histocompatibility complex (MHC)-CEBPDΔ with inhibited CEBPD splicing activity in the heart leads to a severe form of cardiomyopathy characterized by specific defects in the splicing of CEBPD targets, cardiac hypertrophy, DCM, myocytolysis, fibrosis, changes in gene expression associated with HF, severe cardiac dysfunction, and premature death (Terenzi et al, 2009).…”

Section: Discussionmentioning

confidence: 99%

Transcriptome network analysis of potential candidate genes for heart failure

Chen¹,

Wang²,

Zeng³

2013

Genet. Mol. Res.

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ABSTRACT. The purpose of this study was to examine the hypothesis that a transcriptome network can be developed through a set of transcription factors regulated by the expression of various genes induced by dilated cardiomyopathy can be identified and modulated to respond to heart failure. We searched for significant pathways related to dilated cardiomyopathy using the GSE4172 microarray data to identify potential genes related to heart failure. We mapped differentially expressed genes to pathways and constructed a regulation network to investigate the regulatory relationships between transcription factors and pathways. Some transcription factors and target genes in the networks have been clearly linked to heart failure in previous studies. We also found new transcription factors and target genes, such as CCAAT/ enhancer-binding protein delta and JunB, responsible for inflammatory cardiomyopathy. Transcriptome network analysis was useful in the identification of candidate genes in heart failure. This method is well suited for microarray data and therefore is proposed as a powerful tool in the search for new pathways related to disease.

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“…DNA microarray technology, which simultaneously probes thousands of gene expression profiles, has been successfully used in medical research for disease classification (Agrawal et al, 2002;Ohki et al, 2005). For example, in breast cancer research, Sorlie et al (2003) used gene expression to classify malignant breast tumors into five distinct molecular subtypes.…”

Section: Introductionmentioning

confidence: 99%

The distribution-based p-value for the outlier sum in differential gene expression analysis

Chen¹,

Chen²,

Chan³

2010

Biometrika

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SUMMARYOutlier sums were proposed by Tibshirani & Hastie (2007) and Wu (2007) for detecting outlier genes where only a small subset of disease samples shows unusually high gene expression, but they did not develop their distributional properties and formal statistical inference. In this study, a new outlier sum for detection of outlier genes is proposed, its asymptotic distribution theory is developed, and the p-value based on this outlier sum is formulated. Its analytic form is derived on the basis of the large-sample theory. We compare the proposed method with existing outlier sum methods by power comparisons. Our method is applied to DNA microarray data from samples of primary breast tumors examined by Huang et al. (2003). The results show that the proposed method is more efficient in detecting outlier genes.

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Gene expression profiling of human atrial myocardium with atrial fibrillation by DNA microarray analysis

Cited by 50 publications

References 30 publications

Contrasting Gene Expression Profiles in Two Canine Models of Atrial Fibrillation

Contrasting Gene Expression Profiles in Two Canine Models of Atrial Fibrillation

Transcriptome network analysis of potential candidate genes for heart failure

The distribution-based p-value for the outlier sum in differential gene expression analysis

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