Gene expression analysis of ischemic and nonischemic cardiomyopathy: shared and distinct genes in the development of heart failure

2005 ◽  
Vol 21 (3) ◽  
pp. 299-307 ◽  
Author(s):  
Michelle M. Kittleson ◽  
Khalid M. Minhas ◽  
Rafael A. Irizarry ◽  
Shui Q. Ye ◽  
Gina Edness ◽  
...  
Keyword(s):  
Gene Expression ◽  
Heart Failure ◽  
Tumor Necrosis Factor Receptor ◽  
Differentially Expressed ◽  
Prediction Algorithm ◽  
Specific Gene ◽  
Angiotensin Converting Enzyme 2 ◽  
End Stage ◽  
Nearest Shrunken Centroids ◽  
Insight Into

Cardiomyopathy can be initiated by many factors, but the pathways from unique inciting mechanisms to the common end point of ventricular dilation and reduced cardiac output are unclear. We previously described a microarray-based prediction algorithm differentiating nonischemic (NICM) from ischemic cardiomyopathy (ICM) using nearest shrunken centroids. Accordingly, we tested the hypothesis that NICM and ICM would have both shared and distinct differentially expressed genes relative to normal hearts and compared gene expression of 21 NICM and 10 ICM samples with that of 6 nonfailing (NF) hearts using Affymetrix U133A GeneChips and significance analysis of microarrays. Compared with NF, 257 genes were differentially expressed in NICM and 72 genes in ICM. Only 41 genes were shared between the two comparisons, mainly involved in cell growth and signal transduction. Those uniquely expressed in NICM were frequently involved in metabolism, and those in ICM more often had catalytic activity. Novel genes included angiotensin-converting enzyme-2 (ACE2), which was upregulated in NICM but not ICM, suggesting that ACE2 may offer differential therapeutic efficacy in NICM and ICM. In addition, a tumor necrosis factor receptor was downregulated in both NICM and ICM, demonstrating the different signaling pathways involved in heart failure pathophysiology. These results offer novel insight into unique disease-specific gene expression that exists between end-stage cardiomyopathy of different etiologies. This analysis demonstrates that transcriptome analysis offers insight into pathogenesis-based therapies in heart failure management and complements studies using expression-based profiling to diagnose heart failure of different etiologies.

Altered expression of a limited number of genes contributes to cardiac decompensation during chronic ventricular tachypacing in dogs

2007 ◽  
Vol 29 (1) ◽  
pp. 76-83 ◽  
Author(s):  
Caroline Ojaimi ◽  
Khaled Qanud ◽  
Thomas H. Hintze ◽  
Fabio A. Recchia
Keyword(s):  
Gene Expression ◽  
Heart Failure ◽  
Decompensated Heart Failure ◽  
Left Ventricular ◽  
Fold Change ◽  
Differentially Expressed ◽  
Altered Expression ◽  
Cardiac Decompensation ◽  
Number Of Genes ◽  
End Stage

Our aim was to determine the changes in the gene expression profile occurring during the transition from compensated dysfunction (CD) to decompensated heart failure (HF) in pacing-induced dilated cardiomyopathy. Twelve chronically instrumented dogs underwent left ventricular pacing at 210 beats/min for 3 wk and at 240 beats thereafter, and four normal dogs were used as control. The transition from CD to HF occurred between the 3rd and 4th wk of pacing, with end-stage HF at 28 ± 1 days. RNA was extracted from left ventricular tissue at control and 3 and 4 wk of pacing ( n = 4) and tested with the Affymetrix Canine Array. We found 509 genes differentially expressed in CD vs. control ( P ≤ 0.05, fold change ≥±2), with 362 increasing and 147 decreasing; 526 genes were differentially expressed in HF vs. control ( P ≤ 0.05; fold change ≥±2), with 439 increasing and 87 decreasing. To better understand the transition, we compared gene alterations at 3 vs. 4 wk pacing and found that only 30 genes differed ( P ≤ 0.05; fold change of ±2). We conclude that a number of processes including normalization of gene regulation during decompensation, appearance of new upregulated genes and maintenance of gene expression all contribute to the transition to overt heart failure with an unexpectedly small number of genes differentially regulated.

scholarly journals Integrated Insight into the Molecular Mechanisms of Spontaneous Abortion during Early Pregnancy in Pigs

2021 ◽  
Vol 22 (12) ◽  
pp. 6644
Author(s):  
Xupeng Zang ◽  
Ting Gu ◽  
Wenjing Wang ◽  
Chen Zhou ◽  
Yue Ding ◽  
...  
Keyword(s):  
Immune Response ◽  
Spontaneous Abortion ◽  
Molecular Mechanisms ◽  
Gene Set Enrichment Analysis ◽  
Differentially Expressed ◽  
Gene Set ◽  
Cerna Network ◽  
Major Interest ◽  
End Stage ◽  
Insight Into

Due to the high rate of spontaneous abortion (SAB) in porcine pregnancy, there is a major interest and concern on commercial pig farming worldwide. Whereas the perturbed immune response at the maternal–fetal interface is an important mechanism associated with the spontaneous embryo loss in the early stages of implantation in porcine, data on the specific regulatory mechanism of the SAB at the end stage of the implantation remains scant. Therefore, we used high-throughput sequencing and bioinformatics tools to analyze the healthy and arresting endometrium on day 28 of pregnancy. We identified 639 differentially expressed lncRNAs (DELs) and 2357 differentially expressed genes (DEGs) at the end stage of implantation, and qRT-PCR was used to verify the sequencing data. Gene set variation analysis (GSVA), gene set enrichment analysis (GSEA), and immunohistochemistry analysis demonstrated weaker immune response activities in the arresting endometrium compared to the healthy one. Using the lasso regression analysis, we screened the DELs and constructed an immunological competitive endogenous RNA (ceRNA) network related to SAB, including 4 lncRNAs, 11 miRNAs, and 13 genes. In addition, Blast analysis showed the applicability of the constructed ceRNA network in different species, and subsequently determined HOXA-AS2 in pigs. Our study, for the first time, demonstrated that the SAB events at the end stages of implantation is associated with the regulation of immunobiological processes, and a specific molecular regulatory network was obtained. These novel findings may provide new insight into the possibility of increasing the litter size of sows, making pig breeding better and thus improving the efficiency of animal husbandry production.

Abstract 286: Long Noncoding RNAs Are Differentially Expressed in Heart Failure

2012 ◽  
Vol 111 (suppl_1) ◽  
Author(s):  
Emma L Robinson ◽  
Syed Haider ◽  
Hillary Hei ◽  
Richard T Lee ◽  
Roger S Foo
Keyword(s):  
Gene Expression ◽  
Heart Failure ◽  
Significant Proportion ◽  
Differentially Expressed ◽  
Rna Seq ◽  
Control Of Gene Expression ◽  
Failing Heart ◽  
Novel Transcripts ◽  
Non Coding Rnas

Heart failure comprises of clinically distinct inciting causes but a consistent pattern of change in myocardial gene expression supports the hypothesis that unifying biochemical mechanisms underlie disease progression. The recent RNA-seq revolution has enabled whole transcriptome profiling, using deep-sequencing technologies. Up to 70% of the genome is now known to be transcribed into RNA, a significant proportion of which is long non-coding RNAs (lncRNAs), defined as polyribonucleotides of ≥200 nucleotides. This project aims to discover whether the myocardium expression of lncRNAs changes in the failing heart. Paired end RNA-seq from a 300-400bp library of ‘stretched’ mouse myocyte total RNA was carried out to generate 76-mer sequence reads. Mechanically stretching myocytes with equibiaxial stretch apparatus mimics pathological hypertrophy in the heart. Transcripts were assembled and aligned to reference genome mm9 (UCSC), abundance determined and differential expression of novel transcripts and alternative splice variants were compared with that of control (non-stretched) mouse myocytes. Five novel transcripts have been identified in our RNA-seq that are differentially expressed in stretched myocytes compared with non-stretched. These are regions of the genome that are currently unannotated and potentially are transcribed into non-coding RNAs. Roles of known lncRNAs include control of gene expression, either by direct interaction with complementary regions of the genome or association with chromatin remodelling complexes which act on the epigenome.Changes in expression of genes which contribute to the deterioration of the failing heart could be due to the actions of these novel lncRNAs, immediately suggesting a target for new pharmaceuticals. Changes in the expression of these novel transcripts will be validated in a larger sample size of stretched myocytes vs non-stretched myocytes as well as in the hearts of transverse aortic constriction (TAC) mice vs Sham (surgical procedure without the aortic banding). In vivo investigations will then be carried out, using siLNA antisense technology to silence novel lncRNAs in mice.

scholarly journals Discriminative feature of cells characterizes cell populations of interest by a small subset of genes

2021 ◽  
Author(s):  
Takeru Fujii ◽  
Kazumitsu Maehara ◽  
Masatoshi Fujita ◽  
Yasuyuki Ohkawa
Keyword(s):  
Gene Expression ◽  
Statistical Methods ◽  
Cell Population ◽  
Differentially Expressed Gene ◽  
Adaptive Lasso ◽  
Differentially Expressed ◽  
Small Subset ◽  
Specific Gene ◽  
Large Sample Size ◽  
Discriminative Feature

ABSTRACTStatistical methods for detecting differences in individual gene expression are indispensable for understanding cell types. However, conventional statistical methods have faced difficulties associated with the inflation of P-values because of both the large sample size and selection bias introduced by exploratory data analysis such as single-cell transcriptomics. Here, we propose the concept of discriminative feature of cells (DFC), an alternative to using differentially expressed gene-based approaches. We implemented DFC using logistic regression with an adaptive LASSO penalty to perform binary classification for the discrimination of a population of interest and variable selection to obtain a small subset of defining genes. We demonstrated that DFC prioritized gene pairs with non-independent expression using artificial data, and that DFC enabled to characterize the muscle satellite cell population. The results revealed that DFC well captured cell-type-specific markers, specific gene expression patterns, and subcategories of this cell population. DFC may complement differentially expressed gene-based methods for interpreting large data sets.

scholarly journals Troponin I gene expression during human cardiac development and in end-stage heart failure.

1993 ◽  
Vol 72 (5) ◽  
pp. 932-938 ◽  
Author(s):  
S Sasse ◽  
N J Brand ◽  
P Kyprianou ◽  
G K Dhoot ◽  
R Wade ◽  
...  
Keyword(s):  
Gene Expression ◽  
Heart Failure ◽  
Troponin I ◽  
Cardiac Development ◽  
End Stage Heart Failure ◽  
End Stage ◽  
I Gene

scholarly journals Identifying functional metabolic shifts in heart failure with the integration of omics data and a cardiomyocyte-specific, genome-scale model

2020 ◽  
Author(s):  
Bonnie V. Dougherty ◽  
Kristopher D. Rawls ◽  
Glynis L. Kolling ◽  
Kalyan C. Vinnakota ◽  
Anders Wallqvist ◽  
...  
Keyword(s):  
Gene Expression ◽  
Heart Failure ◽  
Specific Model ◽  
Metabolic Phenotype ◽  
Scale Model ◽  
Metabolic Markers ◽  
Metabolic Functions ◽  
Carbon Substrates ◽  
End Stage ◽  
Genome Scale

SummaryThe heart is a metabolic omnivore, known to consume many different carbon substrates in order to maintain function. In diseased states, the heart’s metabolism can shift between different carbon substrates; however, there is some disagreement in the field as to the metabolic shifts seen in end-stage heart failure and whether all heart failure converges to a common metabolic phenotype. Here, we present a new, validated cardiomyocyte-specific GEnome-scale metabolic Network REconstruction (GENRE), iCardio, and use the model to identify common shifts in metabolic functions across heart failure omics datasets. We demonstrate the utility of iCardio in interpreting heart failure gene expression data by identifying Tasks Inferred from Differential Expression (TIDEs) which represent metabolic functions associated with changes in gene expression. We identify decreased NO and Neu5Ac synthesis as common metabolic markers of heart failure across datasets. Further, we highlight the differences in metabolic functions seen across studies, further highlighting the complexity of heart failure. The methods presented for constructing a tissue-specific model and identifying TIDEs can be extended to multiple tissue and diseases of interest.

scholarly journals Altered Enhancer and Promoter Usage Leads to Differential Gene Expression in the Normal and Failed Human Heart

2020 ◽  
Vol 13 (10) ◽  
Author(s):  
Anthony M. Gacita ◽  
Lisa Dellefave-Castillo ◽  
Patrick G.T. Page ◽  
David Y. Barefield ◽  
J. Andrew Wasserstrom ◽  
...  
Keyword(s):  
Gene Expression ◽  
Heart Failure ◽  
Ventricular Remodeling ◽  
Regulatory Function ◽  
Specific Gene ◽  
Data Set ◽  
Promoter Usage ◽  
Additional Support ◽  
Cap Analysis ◽  
Genetic Contributions

Background: The failing heart is characterized by changes in gene expression. However, the regulatory regions of the genome that drive these gene expression changes have not been well defined in human hearts. Methods: To define genome-wide enhancer and promoter use in heart failure, cap analysis of gene expression sequencing was applied to 3 healthy and 4 failed human hearts to identify promoter and enhancer regions used in left ventricles. Healthy hearts were derived from donors unused for transplantation and failed hearts were obtained as discarded tissue after transplantation. Results: Cap analysis of gene expression sequencing identified a combined potential for ≈23 000 promoters and ≈5000 enhancers active in human left ventricles. Of these, 17 000 promoters and 1800 enhancers had additional support for their regulatory function. Comparing promoter usage between healthy and failed hearts highlighted promoter shifts which altered aminoterminal protein sequences. Enhancer usage between healthy and failed hearts identified a majority of differentially used heart failure enhancers were intronic and primarily localized within the first intron, revealing this position as a common feature associated with tissue-specific gene expression changes in the heart. Conclusions: This data set defines the dynamic genomic regulatory landscape underlying heart failure and serves as an important resource for understanding genetic contributions to cardiac dysfunction. Additionally, regulatory changes contributing to heart failure are attractive therapeutic targets for controlling ventricular remodeling and clinical progression.

Sign in / Sign up

Export Citation Format

Share Document