Mining transcriptomics and clinical data reveals ACE2 expression modulators and identifies cardiomyopathy as a risk factor for mortality in COVID-19 patients

AbstractAngiotensin-converting enzyme 2 (ACE2) is the cell-entry receptor for SARS-CoV-2. It plays critical roles in both the transmission and the pathogenesis of the coronavirus disease 2019 (COVID-19). Comprehensive profiling of ACE2 expression patterns will help researchers to reveal risk factors of severe COVID-19 illness. While the expression of ACE2 in healthy human tissues has been well characterized, it is not known which diseases and drugs might modulate the ACE2 expression. In this study, we developed GENEVA (GENe Expression Variance Analysis), a semi-automated framework for exploring massive amounts of RNA-seq datasets. We applied GENEVA to 28,6650 publicly available RNA-seq samples to identify any previously studied experimental conditions that could directly or indirectly modulate ACE2 expression. We identified multiple drugs, genetic perturbations, and diseases that modulate the expression of ACE2, including cardiomyopathy, HNF1A overexpression, and drug treatments with RAD140 and Itraconazole. Our unbiased meta-analysis of seven datasets confirms ACE2 up-regulation in all cardiomyopathy categories. Using electronic health records data from 3936 COVID19 patients, we demonstrate that patients with pre-existing cardiomyopathy have an increased mortality risk than age-matched patients with other cardiovascular conditions. GENEVA is applicable to any genes of interest and is freely accessible at http://genevatool.org.

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Systematic identification of ACE2 expression modulators reveals cardiomyopathy as a risk factor for mortality in COVID-19 patients

Genome Biology ◽

10.1186/s13059-021-02589-4 ◽

2022 ◽

Vol 23 (1) ◽

Author(s):

Navchetan Kaur ◽

Boris Oskotsky ◽

Atul J. Butte ◽

Zicheng Hu

Keyword(s):

Expression Patterns ◽

High Risk Group ◽

Joint Analysis ◽

Rna Seq ◽

Experimental Conditions ◽

Healthy Human ◽

Genetic Perturbations ◽

Drug Treatments ◽

Multiple Drugs ◽

Systematic Identification

Abstract Background Angiotensin-converting enzyme 2 (ACE2) is the cell-entry receptor for SARS-CoV-2. It plays critical roles in both the transmission and the pathogenesis of COVID-19. Comprehensive profiling of ACE2 expression patterns could reveal risk factors of severe COVID-19 illness. While the expression of ACE2 in healthy human tissues has been well characterized, it is not known which diseases and drugs might be associated with ACE2 expression. Results We develop GENEVA (GENe Expression Variance Analysis), a semi-automated framework for exploring massive amounts of RNA-seq datasets. We apply GENEVA to 286,650 publicly available RNA-seq samples to identify any previously studied experimental conditions that could be directly or indirectly associated with ACE2 expression. We identify multiple drugs, genetic perturbations, and diseases that are associated with the expression of ACE2, including cardiomyopathy, HNF1A overexpression, and drug treatments with RAD140 and itraconazole. Our joint analysis of seven datasets confirms ACE2 upregulation in all cardiomyopathy categories. Using electronic health records data from 3936 COVID-19 patients, we demonstrate that patients with pre-existing cardiomyopathy have an increased mortality risk than age-matched patients with other cardiovascular conditions. GENEVA is applicable to any genes of interest and is freely accessible at http://genevatool.org. Conclusions This study identifies multiple diseases and drugs that are associated with the expression of ACE2. The effect of these conditions should be carefully studied in COVID-19 patients. In particular, our analysis identifies cardiomyopathy patients as a high-risk group, with increased ACE2 expression in the heart and increased mortality after SARS-COV-2 infection.

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Interferon-regulated genetic programs and JAK/STAT pathway activate the intronic promoter of the short ACE2 isoform in renal proximal tubules

10.1101/2021.01.15.426908 ◽

2021 ◽

Author(s):

Jakub Jankowski ◽

Hye Kyung Lee ◽

Julia Wilflingseder ◽

Lothar Hennighausen

Keyword(s):

Gene Expression ◽

Proximal Tubule ◽

Expression Profiles ◽

Expression Patterns ◽

Gene Expression Profiles ◽

Regulatory Elements ◽

Rna Seq ◽

Angiotensin Converting Enzyme 2 ◽

Genome Wide ◽

Cytokine Stimulation

SummaryRecently, a short, interferon-inducible isoform of Angiotensin-Converting Enzyme 2 (ACE2), dACE2 was identified. ACE2 is a SARS-Cov-2 receptor and changes in its renal expression have been linked to several human nephropathies. These changes were never analyzed in context of dACE2, as its expression was not investigated in the kidney. We used Human Primary Proximal Tubule (HPPT) cells to show genome-wide gene expression patterns after cytokine stimulation, with emphasis on the ACE2/dACE2 locus. Putative regulatory elements controlling dACE2 expression were identified using ChIP-seq and RNA-seq. qRT-PCR differentiating between ACE2 and dACE2 revealed 300- and 600-fold upregulation of dACE2 by IFNα and IFNβ, respectively, while full length ACE2 expression was almost unchanged. JAK inhibitor ruxolitinib ablated STAT1 and dACE2 expression after interferon treatment. Finally, with RNA-seq, we identified a set of genes, largely immune-related, induced by cytokine treatment. These gene expression profiles provide new insights into cytokine response of proximal tubule cells.

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SARS-CoV-2 receptor is co-expressed with elements of the kinin–kallikrein, renin–angiotensin and coagulation systems in alveolar cells

Scientific Reports ◽

10.1038/s41598-020-76488-2 ◽

2020 ◽

Vol 10 (1) ◽

Author(s):

Davi Sidarta-Oliveira ◽

Carlos Poblete Jara ◽

Adriano J. Ferruzzi ◽

Munir S. Skaf ◽

William H. Velander ◽

...

Keyword(s):

Meta Analysis ◽

Renin Angiotensin System ◽

Cell Entry ◽

Coagulation System ◽

Alveolar Cells ◽

Healthy Human ◽

Angiotensin Converting Enzyme 2 ◽

Renin Angiotensin ◽

Cardiovascular Failure ◽

Lethal Triad

Abstract SARS-CoV-2, the pathogenic agent of COVID-19, employs angiotensin converting enzyme-2 (ACE2) as its cell entry receptor. Clinical data reveal that in severe COVID-19, SARS-CoV-2 infects the lung, leading to a frequently lethal triad of respiratory insufficiency, acute cardiovascular failure, and coagulopathy. Physiologically, ACE2 plays a role in the regulation of three systems that could potentially be involved in the pathogenesis of severe COVID-19: the kinin–kallikrein system, resulting in acute lung inflammatory edema; the renin–angiotensin system, promoting cardiovascular instability; and the coagulation system, leading to thromboembolism. Here we assembled a healthy human lung cell atlas meta-analysis with ~ 130,000 public single-cell transcriptomes and show that key elements of the bradykinin, angiotensin and coagulation systems are co-expressed with ACE2 in alveolar cells and associated with their differentiation dynamics, which could explain how changes in ACE2 promoted by SARS-CoV-2 cell entry result in the development of the three most severe clinical components of COVID-19.

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Meta-analysis of gene expression profiles in granulosa cells during folliculogenesis

Reproduction ◽

10.1530/rep-15-0594 ◽

2016 ◽

Vol 151 (6) ◽

pp. R103-R110 ◽

Cited By ~ 15

Author(s):

Daulat Raheem Khan ◽

Éric Fournier ◽

Isabelle Dufort ◽

François J Richard ◽

Jaswant Singh ◽

...

Keyword(s):

Gene Expression ◽

Granulosa Cell ◽

Granulosa Cells ◽

Expression Profiles ◽

Post Partum ◽

Meta Analysis ◽

Expression Patterns ◽

Comprehensive Overview ◽

Experimental Conditions ◽

Physiological Conditions

Abstract Folliculogenesis involves coordinated profound changes in different follicular compartments and significant modifications of their gene expression patterns, particularly in granulosa cells. Huge datasets have accumulated from the analyses of granulosa cell transcriptomic signatures in predefined physiological contexts using different technological platforms. However, no comprehensive overview of folliculogenesis is available. This would require integration of datasets from numerous individual studies. A prerequisite for such integration would be the use of comparable platforms and experimental conditions. The EmbryoGENE program was created to study bovine granulosa cell transcriptomics under different physiological conditions using the same platform. Based on the data thus generated so far, we present here an interactive web interface called GranulosaIMAGE (Integrative Meta-Analysis of Gene Expression), which provides dynamic expression profiles of any gene of interest and all isoforms thereof in granulosa cells at different stages of folliculogenesis. GranulosaIMAGE features two kinds of expression profiles: gene expression kinetics during bovine folliculogenesis from small (6 mm) to pre-ovulatory follicles under different hormonal and physiological conditions and expression profiles of granulosa cells of dominant follicles from post-partum cows in different metabolic states. This article provides selected examples of expression patterns along with suggestions for users to access and generate their own patterns using GranulosaIMAGE. The possibility of analysing gene expression dynamics during the late stages of folliculogenesis in a mono-ovulatory species such as bovine should provide a new and enriched perspective on ovarian physiology.

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Meta-Analysis of Hypoxic Transcriptomes from Public Databases

Biomedicines ◽

10.3390/biomedicines8010010 ◽

2020 ◽

Vol 8 (1) ◽

pp. 10 ◽

Cited By ~ 1

Author(s):

Hidemasa Bono ◽

Kiichi Hirota

Keyword(s):

Gene Expression ◽

Expression Profiles ◽

Meta Analysis ◽

Gene Expression Profiles ◽

Data Driven ◽

Transcriptome Data ◽

Rna Seq ◽

Experimental Conditions ◽

Oxygen Homeostasis ◽

Before And After

Hypoxia is the insufficiency of oxygen in the cell, and hypoxia-inducible factors (HIFs) are central regulators of oxygen homeostasis. In order to obtain functional insights into the hypoxic response in a data-driven way, we attempted a meta-analysis of the RNA-seq data from the hypoxic transcriptomes archived in public databases. In view of methodological variability of archived data in the databases, we first manually curated RNA-seq data from appropriate pairs of transcriptomes before and after hypoxic stress. These included 128 human and 52 murine transcriptome pairs. We classified the results of experiments for each gene into three categories: upregulated, downregulated, and unchanged. Hypoxic transcriptomes were then compared between humans and mice to identify common hypoxia-responsive genes. In addition, meta-analyzed hypoxic transcriptome data were integrated with public ChIP-seq data on the known human HIFs, HIF-1 and HIF-2, to provide insights into hypoxia-responsive pathways involving direct transcription factor binding. This study provides a useful resource for hypoxia research. It also demonstrates the potential of a meta-analysis approach to public gene expression databases for selecting candidate genes from gene expression profiles generated under various experimental conditions.

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Tissue-specific and interferon-inducible expression of non-functional ACE2 through endogenous retrovirus co-option

10.1101/2020.07.24.219139 ◽

2020 ◽

Cited By ~ 3

Author(s):

Kevin Ng ◽

Jan Attig ◽

William Bolland ◽

George R. Young ◽

Jack Major ◽

...

Keyword(s):

De Novo ◽

Expression Patterns ◽

Endogenous Retrovirus ◽

The Novel ◽

Specific Expression ◽

Angiotensin Converting Enzyme 2 ◽

Viral Spread ◽

Novel Transcript ◽

Physiological Processes ◽

Entry Receptor

SummaryAngiotensin-converting enzyme 2 (ACE2) is an entry receptor for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), as well as a regulator of several physiological processes. ACE2 has recently been proposed to be interferon-inducible, suggesting that SARS-CoV-2 may exploit this phenomenon to enhance viral spread and questioning the efficacy of interferon treatment in Coronavirus disease 2019 (COVID-19). Using a recent de novo transcript assembly that captured previously unannotated transcripts, we describe a novel isoform of ACE2, generated by co-option of an intronic long terminal repeat (LTR) retroelement promoter. The novel transcript, termed LTR16A1-ACE2, exhibits specific expression patterns across the aerodigestive and gastrointestinal tracts and, importantly, is highly responsive to interferon stimulation. In stark contrast, expression of canonical ACE2 is completely unresponsive to interferon stimulation. Moreover, the LTR16A1-ACE2 translation product is a truncated, unstable ACE2 form, lacking domains required for SARS-CoV-2 binding and therefore unlikely to contribute to or enhance viral infection.

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Avian Expression Patterns and Genomic Mapping Implicate Leptin in Digestion and TNF Signaling, Suggesting that Their Interacting Adipokine Role is Unique to Mammals

International Journal of Molecular Sciences ◽

10.3390/ijms20184489 ◽

2019 ◽

Vol 20 (18) ◽

pp. 4489 ◽

Cited By ~ 3

Author(s):

Eyal Seroussi ◽

Martin Knytl ◽

Frédérique Pitel ◽

Daniel Elleder ◽

Vladimir Krylov ◽

...

Keyword(s):

Meta Analysis ◽

Expression Patterns ◽

Immune Defense ◽

Rna Seq ◽

Appetite Control ◽

Histocompatibility Complex ◽

Leptin Expression ◽

The Brain ◽

Necrosis Factor ◽

Receptor Mrnas

In mammals, leptin and tumor-necrosis factor (TNF) are prominent interacting adipokines mediating appetite control and insulin sensitivity. While TNF pleiotropically functions in immune defense and cell survival, leptin is largely confined to signaling energy stores in adipocytes. Knowledge about the function of avian leptin and TNF is limited and they are absent or lowly expressed in adipose, respectively. Employing radiation-hybrid mapping and FISH-TSA, we mapped TNF and its syntenic genes to chicken chromosome 16 within the major histocompatibility complex (MHC) region. This mapping position suggests that avian TNF has a role in regulating immune response. To test its possible interaction with leptin within the immune system and beyond, we compared the transcription patterns of TNF, leptin and their cognate receptors obtained by meta-analysis of GenBank RNA-seq data. While expression of leptin and its receptor (LEPR) were detected in the brain and digestive tract, TNF and its receptor mRNAs were primarily found in viral-infected and LPS-treated leukocytes. We confirmed leptin expression in the duodenum by immunohistochemistry staining. Altogether, we suggest that whereas leptin and TNF interact as adipokines in mammals, in birds, they have distinct roles. Thus, the interaction between leptin and TNF may be unique to mammals.

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Meta-analysis of hypoxic transcriptomes from public databases

10.1101/267310 ◽

2018 ◽

Cited By ~ 1

Author(s):

Hidemasa Bono ◽

Kiichi Hirota

Keyword(s):

Gene Expression ◽

Expression Profiles ◽

Meta Analysis ◽

Gene Expression Profiles ◽

Data Driven ◽

Transcriptome Data ◽

Rna Seq ◽

Experimental Conditions ◽

Oxygen Homeostasis ◽

Before And After

AbstractHypoxia is the insufficiency of oxygen in the cell, and hypoxia-inducible factors (HIFs) are central regulators of oxygen homeostasis. In order to obtain functional insights into the hypoxic response in a data-driven way, we attempted a meta-analysis of the RNA-seq data from the hypoxic transcriptomes archived in public databases. In view of methodological variability of archived data in the databases, we first manually curated RNA-seq data from appropriate pairs of transcriptomes before and after hypoxic stress. These included 128 human and 52 murine transcriptome pairs. We classified the results of experiments for each gene into three categories: upregulated, downregulated, and unchanged. Hypoxic transcriptomes were then compared between humans and mice to identify common hypoxia-responsive genes. In addition, meta-analyzed hypoxic transcriptome data were integrated with public ChIP-seq data on the known human HIFs HIF-1 and HIF-2 to provide insights into hypoxia-responsive pathways involving direct transcription factor binding. This study provides a useful resource for hypoxia research. It also demonstrates the potential of a meta-analysis approach to public gene expression databases for selecting candidate genes from gene expression profiles generated under various experimental conditions.

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Meta-analysis of RNA-seq studies reveals genes responsible for life stage-dominant functions in Schistosoma mansoni

10.1101/308189 ◽

2018 ◽

Cited By ~ 3

Author(s):

Zhigang Lu ◽

Matthew Berriman

Keyword(s):

Gene Expression ◽

Schistosoma Mansoni ◽

Differential Expression ◽

Meta Analysis ◽

Life Stage ◽

Expression Patterns ◽

Differential Expression Analysis ◽

Housekeeping Genes ◽

Life Stages ◽

Rna Seq

AbstractBackgroundSince the genome of the parasitic flatworm Schistosoma mansoni was sequenced in 2009, various RNA-seq studies have been conducted to investigate differential gene expression between certain life stages. Based on these studies, the overview of gene expression in all life stages can improve our understanding of S. mansoni genome biology.Methodspublicly available RNA-seq data covering all life stages and gonads were mapped to the latest S. mansoni genome. Read counts were normalised across all samples and differential expression analysis was preformed using the generalized linear model (GLM) approach.Resultswe revealed for the first time the dissimilarities among all life stages. Genes that are abundantly-expressed in all life stages, as well as those preferentially-expressed in certain stage(s), were determined. The latter reveals genes responsible for stage-dominant functions of the parasite, which can be a guidance for the investigation and annotation of gene functions. In addition, distinct differential expression patterns were observed between adjacent life stages, which not only correlate well with original individual studies, but also provide additional information on changes in gene expression during parasite transitions. Furthermore, thirteen novel housekeeping genes across all life stages were identified, which is valuable for quantitative studies (e.g., qPCR).Conclusionsthe metaanalysis provides valuable information on the expression and potential functions of S. mansoni genes across all life stages, and can facilitate basic as well as applied research for the community.

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Publicly available transcriptomes provide the opportunity for dual RNA-Seq meta analysis in Plasmodium infection

10.1101/576116 ◽

2019 ◽

Cited By ~ 1

Author(s):

Parnika Mukherjee ◽

Gaétan Burgio ◽

Emanuel Heitlinger

Keyword(s):

Gene Expression ◽

Species Interactions ◽

Homo Sapiens ◽

Meta Analysis ◽

Model Systems ◽

Rna Seq ◽

Experimental Conditions ◽

Regulatory Pathways ◽

Or Gene ◽

Host Parasite

AbstractDual RNA-Seq is the simultaneous analysis of host and parasite transcriptomes. It can potentially identify host-parasite interactions by correlated gene expression. Co-expression might highlight interlinked signalling, metabolic or gene regulatory pathways in addition to potentially physically interacting proteins. Numerous studies on malaria focus on one organism – either the host or the parasite – and the other is considered contaminant. Here we assess the applicability of a meta-analysis approach for dual RNA-Seq.We screened malaria transcriptome experiments for gene expression data from both Plasmodium and its host. Out of 171 malaria studies in Homo sapiens, Macaca mulatta and Mus musculus, we identified 63 studies with the potential to provide host and parasite data. While 16 studies (1950 total samples) explicitly aimed to generate dual RNA-Seq data, 47 (1398 samples) had an original focus on either the host or the parasite. We show that a total of up to 727 samples from blood and liver studies are suitable for dual RNA-Seq analysis. As a proof-of-principle, we conceive and apply a method for meta-analysis linking host-parasite systems via orthologs. Our approach recovered broad processes known to be interlinked between host and parasites in malaria in addition to individual associations between host and parasite proteins. We suggest these for further experimental investigation.We argue that the multitude of variations in experimental conditions found in the selected studies should help narrow down a conserved core of cross-species interactions. In the future, detailed analyses building on the datasets and concepts conceived here, conserved sets of core interacting pathways and co-regulated genes across study systems might be identified. This might also provide the opportunity to gauge the applicability of model systems for different pathways in malaria studies.

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