scholarly journals Cardiac Cell Type-Specific Gene Regulatory Programs and Disease Risk Association

2020 ◽  
Author(s):  
James D. Hocker ◽  
Olivier B. Poirion ◽  
Fugui Zhu ◽  
Justin Buchanan ◽  
Kai Zhang ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Disease Risk ◽  
Cardiovascular Disease Risk ◽  
Cell Types ◽  
Regulatory Elements ◽  
Specific Gene ◽  
Dependent Manner ◽  
Cardiac Cell ◽  
Risk Variants ◽  
Gene Regulatory

ABSTRACTBackgroundCis-regulatory elements such as enhancers and promoters are crucial for directing gene expression in the human heart. Dysregulation of these elements can result in many cardiovascular diseases that are major leading causes of morbidity and mortality worldwide. In addition, genetic variants associated with cardiovascular disease risk are enriched within cis-regulatory elements. However, the location and activity of these cis-regulatory elements in individual cardiac cell types remains to be fully defined.MethodsWe performed single nucleus ATAC-seq and single nucleus RNA-seq to define a comprehensive catalogue of candidate cis-regulatory elements (cCREs) and gene expression patterns for the distinct cell types comprising each chamber of four non-failing human hearts. We used this catalogue to computationally deconvolute dynamic enhancers in failing hearts and to assign cardiovascular disease risk variants to cCREs in individual cardiac cell types. Finally, we applied reporter assays, genome editing and electrophysiogical measurements in in vitro differentiated human cardiomyocytes to validate the molecular mechanisms of cardiovascular disease risk variants.ResultsWe defined >287,000 candidate cis-regulatory elements (cCREs) in human hearts at single-cell resolution, which notably revealed gene regulatory programs controlling specific cell types in a cardiac region/structure-dependent manner and during heart failure. We further report enrichment of cardiovascular disease risk variants in cCREs of distinct cardiac cell types, including a strong enrichment of atrial fibrillation variants in cardiomyocyte cCREs, and reveal 38 candidate causal atrial fibrillation variants localized to cardiomyocyte cCREs. Two such risk variants residing within a cardiomyocyte-specific cCRE at the KCNH2/HERG locus resulted in reduced enhancer activity compared to the non-risk allele. Finally, we found that deletion of the cCRE containing these variants decreased KCNH2 expression and prolonged action potential repolarization in an enhancer dosage-dependent manner.ConclusionsThis comprehensive atlas of human cardiac cCREs provides the foundation for not only illuminating cell type-specific gene regulatory programs controlling human hearts during health and disease, but also interpreting genetic risk loci for a wide spectrum of cardiovascular diseases.

scholarly journals Cardiac cell type–specific gene regulatory programs and disease risk association

2021 ◽  
Vol 7 (20) ◽  
pp. eabf1444
Author(s):  
James D. Hocker ◽  
Olivier B. Poirion ◽  
Fugui Zhu ◽  
Justin Buchanan ◽  
Kai Zhang ◽  
...  
Keyword(s):  
Disease Risk ◽  
Cell Types ◽  
Regulatory Elements ◽  
Specific Gene ◽  
Dependent Manner ◽  
Cardiac Cell ◽  
Limited Information ◽  
Cell Type ◽  
Functional Studies ◽  
Cell Type Specific

Misregulated gene expression in human hearts can result in cardiovascular diseases that are leading causes of mortality worldwide. However, the limited information on the genomic location of candidate cis-regulatory elements (cCREs) such as enhancers and promoters in distinct cardiac cell types has restricted the understanding of these diseases. Here, we defined >287,000 cCREs in the four chambers of the human heart at single-cell resolution, which revealed cCREs and candidate transcription factors associated with cardiac cell types in a region-dependent manner and during heart failure. We further found cardiovascular disease–associated genetic variants enriched within these cCREs including 38 candidate causal atrial fibrillation variants localized to cardiomyocyte cCREs. Additional functional studies revealed that two of these variants affect a cCRE controlling KCNH2/HERG expression and action potential repolarization. Overall, this atlas of human cardiac cCREs provides the foundation for illuminating cell type–specific gene regulation in human hearts during health and disease.

scholarly journals Biomarkers of Blood from Patients with Atherosclerosis Based on Bioinformatics Analysis

2021 ◽  
Author(s):  
Yongjiang Qian ◽  
Lili Zhang ◽  
Zhen Sun ◽  
Guangyao Zang ◽  
Yalan Li ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Disease Risk ◽  
Cardiovascular Disease Risk ◽  
Cell Types ◽  
Diagnostic Techniques ◽  
Gene Expression Omnibus ◽  
Stress Tests ◽  
Data Set ◽  
Blood Biochemical ◽  
Classification Information

Abstract Background: atherosclerosis is a multifaceted disease characterized by the formation and accumulation of plaques that fix to the arteries and causes some cardiovascular disease and vascular embolism. A range of diagnostic techniques, including selective coronary angiography, stress tests, CT, and nuclear scans allow assessment of cardiovascular disease risk and treatment targets. However, there is not a very simple blood biochemical index or biological target for the diagnosis of atherosclerosis at present. So it would be interesting to find a blood biochemical marker for atherosclerosis.Methods: Three datasets from Gene Expression Omnibus (GEO) database were analyzed to obtain differentially expressed genes (DEG) and the results were integrated using Robustrankaggreg algorithm. The genes considered more important by Robustrankaggreg algorithm were put into their own data set and the data set system with cell classification information for verification.Results: 21 possible genes were screened out. Interestingly, we found a good correlation between RPS4Y1, EIF1AY and XIST. In addition, we know the general expression of these genes in different cell types and whole blood cellsConclusions: In this study, we identified BTNL8 and BLNK as having good clinical significance. These results will contribute to the study of the underlying genes involved in the progression of atherosclerosis and provide insights for the discovery of new diagnostic and evaluation methods.

scholarly journals Cell type-specific enhancer-promoter connectivity maps in the human brain and disease risk association

2019 ◽  
Author(s):  
Alexi Nott ◽  
Inge R. Holtman ◽  
Nicole G. Coufal ◽  
Johannes C.M. Schlachetzki ◽  
Miao Yu ◽  
...  
Keyword(s):  
Human Brain ◽  
Psychiatric Disorders ◽  
Complex Traits ◽  
Disease Risk ◽  
Cell Types ◽  
Regulatory Elements ◽  
Gene Promoters ◽  
Cell Type ◽  
Risk Variants ◽  
Cell Type Specific

AbstractUnique cell type-specific patterns of activated enhancers can be leveraged to interpret non-coding genetic variation associated with complex traits and diseases such as neurological and psychiatric disorders. Here, we have defined active promoters and enhancers for major cell types of the human brain. Whereas psychiatric disorders were primarily associated with regulatory regions in neurons, idiopathic Alzheimer’s disease (AD) variants were largely confined to microglia enhancers. Interactome maps connecting GWAS variants in cell type-specific enhancers to gene promoters revealed an extended microglia gene network in AD. Deletion of a microglia-specific enhancer harboring AD-risk variants ablated BIN1 expression in microglia but not in neurons or astrocytes. These findings revise and expand the genes likely to be influenced by non-coding variants in AD and suggest the probable brain cell types in which they function.One Sentence SummaryIdentification of cell type-specific regulatory elements in the human brain enables interpretation of non-coding GWAS risk variants.

scholarly journals Biomarkers of Blood from Patients with Atherosclerosis Based on Bioinformatics Analysis

2021 ◽  
Vol 17 ◽  
pp. 117693432110460
Author(s):  
Yongjiang Qian ◽  
Lili Zhang ◽  
Zhen Sun ◽  
Guangyao Zang ◽  
Yalan Li ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Disease Risk ◽  
Cardiovascular Disease Risk ◽  
Cell Types ◽  
Diagnostic Techniques ◽  
Gene Expression Omnibus ◽  
Stress Tests ◽  
Data Set ◽  
Blood Biochemical ◽  
Classification Information

Atherosclerosis is a multifaceted disease characterized by the formation and accumulation of plaques that attach to arteries and cause cardiovascular disease and vascular embolism. A range of diagnostic techniques, including selective coronary angiography, stress tests, computerized tomography, and nuclear scans, assess cardiovascular disease risk and treatment targets. However, there is currently no simple blood biochemical index or biological target for the diagnosis of atherosclerosis. Therefore, it is of interest to find a biochemical blood marker for atherosclerosis. Three datasets from the Gene Expression Omnibus (GEO) database were analyzed to obtain differentially expressed genes (DEG) and the results were integrated using the Robustrankaggreg algorithm. The genes considered more critical by the Robustrankaggreg algorithm were put into their own data set and the data set system with cell classification information for verification. Twenty-one possible genes were screened out. Interestingly, we found a good correlation between RPS4Y1, EIF1AY, and XIST. In addition, we know the general expression of these genes in different cell types and whole blood cells. In this study, we identified BTNL8 and BLNK as having good clinical significance. These results will contribute to the analysis of the underlying genes involved in the progression of atherosclerosis and provide insights for the discovery of new diagnostic and evaluation methods.

scholarly journals Biomarkers of Blood from Patients with Atherosclerosis Based on Bioinformatics Analysis

2021 ◽  
Author(s):  
Yongjiang Qian ◽  
Lili Zhang ◽  
Zhen Sun ◽  
Guangyao Zang ◽  
Yalan Li ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Disease Risk ◽  
Cardiovascular Disease Risk ◽  
Cell Types ◽  
Diagnostic Techniques ◽  
Gene Expression Omnibus ◽  
Stress Tests ◽  
Data Set ◽  
Blood Biochemical ◽  
Classification Information

Abstract Background: atherosclerosis is a multifaceted disease characterized by the formation and accumulation of plaques that fix to the arteries and causes some cardiovascular disease and vascular embolism. A range of diagnostic techniques, including selective coronary angiography, stress tests, CT, and nuclear scans allow assessment of cardiovascular disease risk and treatment targets. However, there is not a very simple blood biochemical index or biological target for the diagnosis of atherosclerosis at present. So it would be interesting to find a blood biochemical marker for atherosclerosis.Methods: Three datasets from Gene Expression Omnibus (GEO) database were analyzed to obtain differentially expressed genes (DEG) and the results were integrated using Robustrankaggreg algorithm. The genes considered more important by Robustrankaggreg algorithm were put into their own data set and the data set system with cell classification information for verification.Results: 21 possible genes were screened out. Interestingly, we found a good correlation between RPS4Y1, EIF1AY and XIST. In addition, we know the general expression of these genes in different cell types and whole blood cellsConclusions: In this study, we identified BTNL8 and BLNK as having good clinical significance. These results will contribute to the study of the underlying genes involved in the progression of atherosclerosis and provide insights for the discovery of new diagnostic and evaluation methods.

scholarly journals Integrative analysis of multi-omics reveals gene regulatory networks across brain regions from risk variants to phenotypes of Alzheimer’s disease and Covid-19

2021 ◽  
Author(s):  
Saniya Khullar ◽  
Daifeng Wang
Keyword(s):  
Disease Progression ◽  
Temporal Lobe ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Target Genes ◽  
Disease Risk ◽  
Regulatory Elements ◽  
Brain Regions ◽  
Risk Variants ◽  
Gene Regulatory

AbstractBackgroundGenome-wide association studies have found many genetic risk variants associated with Alzheimer’s disease (AD). However, how these risk variants affect deeper phenotypes such as disease progression and immune response remains elusive. Also, our understanding of cellular and molecular mechanisms from disease risk variants to various phenotypes is still limited. To address these problems, we performed integrative multi-omics analysis from genotype, transcriptomics, and epigenomics for revealing gene regulatory mechanisms from disease variants to AD phenotypes.MethodFirst, we cluster gene co-expression networks and identify gene modules for various AD phenotypes given population gene expression data. Next, we predict the transcription factors (TFs) that significantly regulate the genes in each module and the AD risk variants (e.g., SNPs) interrupting the TF binding sites on the regulatory elements. Finally, we construct a full gene regulatory network linking SNPs, interrupted TFs, and regulatory elements to target genes for each phenotype. This network thus provides mechanistic insights of gene regulation from disease risk variants to AD phenotypes.ResultsWe applied our analysis to predict the gene regulatory networks in three major AD-relevant regions: hippocampus, dorsolateral prefrontal cortex (DLPFC), and lateral temporal lobe (LTL). These region networks provide a comprehensive functional genomic map linking AD SNPs to TFs and regulatory elements to target genes for various AD phenotypes. Comparative analyses further revealed cross-region-conserved and region-specific regulatory networks. For instance, AD SNPs rs13404184 and rs61068452 disrupt the bindings of TF SPI1 that regulates AD gene INPP5D in the hippocampus and lateral temporal lobe. However, SNP rs117863556 interrupts the bindings of TF REST to regulate GAB2 in the DLPFC only. Furthermore, driven by recent discoveries between AD and Covid-19, we found that many genes from our networks regulating Covid-19 pathways are also significantly differentially expressed in severe Covid patients (ICU), suggesting potential regulatory connections between AD and Covid. Thus, we used the machine learning models to predict severe Covid and prioritized highly predictive genes as AD-Covid genes. We also used Decision Curve Analysis to show that our AD-Covid genes outperform known Covid-19 genes for predicting Covid severity and deciding to send patients to ICU or not. In short, our results provide a deeper understanding of the interplay among multi-omics, brain regions, and AD phenotypes, including disease progression and Covid response. Our analysis is open-source available at https://github.com/daifengwanglab/ADSNPheno.

PKCδ mediates anti-proliferative, pro-apoptic effects of testosterone on coronary smooth muscle

2007 ◽  
Vol 293 (2) ◽  
pp. C805-C813 ◽  
Author(s):  
D. K. Bowles ◽  
K. K. Maddali ◽  
V. C. Dhulipala ◽  
D. H. Korzick
Keyword(s):  
Smooth Muscle ◽  
Disease Risk ◽  
Cardiovascular Disease Risk ◽  
Flow Cytometric Analysis ◽  
Cell Types ◽  
Control Flow ◽  
Dependent Manner ◽  
Coronary Smooth Muscle ◽  
Protein Levels ◽  
Concomitant Reduction

Sex hormone status has emerged as an important modulator of coronary physiology and cardiovascular disease risk in both males and females. Our previous studies have demonstrated that testosterone increases protein kinase C (PKC) δ expression and activity in coronary smooth muscle (CSMC). Because PKCδ has been implicated in regulation of proliferation and apoptosis in other cell types, we sought to determine if testosterone modulates CSMC proliferation and/or apoptosis through PKCδ. Porcine CSMC cultures (passages 2–6) from castrated males were treated with testosterone for 24 h. Testosterone (20 and 100 nM) decreased [3H]thymidine incorporation in proliferating CSMC to 59 ± 5.3 and 33.1 ± 4.5% of control. Flow cytometric analysis demonstrated that testosterone induced G1arrest in CSMC with a concomitant reduction in the S phase cells. Testosterone reduced protein levels of cyclins D1and E and phosphorylation of retinoblastoma protein while elevating levels of p21cip1and p27kip1. There were no significant differences in the levels of cyclins D3, CDK2, CDK4, or CDK6. Testosterone significantly reduced kinase activity of CDK2 and -6, but not CDK4, -7, or -1. PKCδ small interfering RNA (siRNA) prevented testosterone-mediated G1arrest, p21cip1upregulation, and cyclin D1and E downregulation. Furthermore, testosterone increased CSMC apoptosis in a dose-dependent manner, which was blocked by either PKCδ siRNA or caspase 3 inhibition. These findings demonstrate that the anti-proliferative, pro-apoptotic effects of testosterone on CSMCs are substantially mediated by PKCδ.

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