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Article: Plasma P-selectin is an early marker of thromboembolism in COVID-19.

Fenyves, Bánk G / Mehta, Arnav / Kays, Kyle R / Goldberg, Marcia B / Hacohen, Nir / Filbin, Michael R

medRxiv : the preprint server for health sciences

2021

Abstract: Coagulopathy and thromboembolism are known complications of SARS-CoV-2 infection. The mechanisms of COVID-19-associated hematologic complications involve endothelial cell and platelet dysfunction and have been intensively studied. We leveraged a ... ...

Abstract	Coagulopathy and thromboembolism are known complications of SARS-CoV-2 infection. The mechanisms of COVID-19-associated hematologic complications involve endothelial cell and platelet dysfunction and have been intensively studied. We leveraged a prospectively collected acute COVID-19 biorepository to study the association of plasma levels of a comprehensive list of coagulation proteins with the occurrence of venous thromboembolic events (VTE). We included in our analysis 305 subjects with confirmed SARS-CoV-2 infection who presented to an urban Emergency Department with acute respiratory distress during the first COVID-19 surge in 2020; 13 (4.2%) were subsequently diagnosed with venous thromboembolism during hospitalization. Serial samples were obtained and assays were performed on two highly-multiplexed proteomic platforms. Nine coagulation proteins were differentially expressed in patients with thromboembolic events. P-selectin, a cell adhesion molecule on the surface of activated endothelial cells, displayed the strongest association with the diagnosis of VTE, independent of disease severity (p=0.0025). This supports the importance of endothelial activation in the mechanistic pathway of venous thromboembolism in COVID-19. P-selectin together with D-dimer upon hospital presentation provided better discriminative ability for VTE diagnosis than D-dimer alone.
Language	English
Publishing date	2021-07-14
Publishing country	United States
Document type	Preprint
DOI	10.1101/2021.07.10.21260293
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Article ; Online: Synaptic polarity and sign-balance prediction using gene expression data in the Caenorhabditis elegans chemical synapse neuronal connectome network.

Fenyves, Bánk G / Szilágyi, Gábor S / Vassy, Zsolt / Sőti, Csaba / Csermely, Peter

PLoS computational biology

2020 Volume 16, Issue 12, Page(s) e1007974

Abstract: Graph theoretical analyses of nervous systems usually omit the aspect of connection polarity, due to data insufficiency. The chemical synapse network of Caenorhabditis elegans is a well-reconstructed directed network, but the signs of its connections are ...

Abstract	Graph theoretical analyses of nervous systems usually omit the aspect of connection polarity, due to data insufficiency. The chemical synapse network of Caenorhabditis elegans is a well-reconstructed directed network, but the signs of its connections are yet to be elucidated. Here, we present the gene expression-based sign prediction of the ionotropic chemical synapse connectome of C. elegans (3,638 connections and 20,589 synapses total), incorporating available presynaptic neurotransmitter and postsynaptic receptor gene expression data for three major neurotransmitter systems. We made predictions for more than two-thirds of these chemical synapses and observed an excitatory-inhibitory (E:I) ratio close to 4:1 which was found similar to that observed in many real-world networks. Our open source tool (http://EleganSign.linkgroup.hu) is simple but efficient in predicting polarities by integrating neuronal connectome and gene expression data.
MeSH term(s)	Animals ; Caenorhabditis elegans/genetics ; Caenorhabditis elegans/physiology ; Caenorhabditis elegans Proteins/genetics ; Caenorhabditis elegans Proteins/metabolism ; Connectome ; Gene Expression ; Neurons/metabolism ; Neurons/physiology ; Synapses/metabolism ; Synapses/physiology
Chemical Substances	Caenorhabditis elegans Proteins
Language	English
Publishing date	2020-12-21
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2193340-6
ISSN	1553-7358 ; 1553-734X
ISSN (online)	1553-7358
ISSN	1553-734X
DOI	10.1371/journal.pcbi.1007974
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Synaptic polarity and sign-balance prediction using gene expression data in the Caenorhabditis elegans chemical synapse neuronal connectome network.

Bánk G Fenyves / Gábor S Szilágyi / Zsolt Vassy / Csaba Sőti / Peter Csermely

PLoS Computational Biology, Vol 16, Iss 12, p e

2020 Volume 1007974

Abstract	Graph theoretical analyses of nervous systems usually omit the aspect of connection polarity, due to data insufficiency. The chemical synapse network of Caenorhabditis elegans is a well-reconstructed directed network, but the signs of its connections are yet to be elucidated. Here, we present the gene expression-based sign prediction of the ionotropic chemical synapse connectome of C. elegans (3,638 connections and 20,589 synapses total), incorporating available presynaptic neurotransmitter and postsynaptic receptor gene expression data for three major neurotransmitter systems. We made predictions for more than two-thirds of these chemical synapses and observed an excitatory-inhibitory (E:I) ratio close to 4:1 which was found similar to that observed in many real-world networks. Our open source tool (http://EleganSign.linkgroup.hu) is simple but efficient in predicting polarities by integrating neuronal connectome and gene expression data.
Keywords	Biology (General) ; QH301-705.5
Subject code	571
Language	English
Publishing date	2020-12-01T00:00:00Z
Publisher	Public Library of Science (PLoS)
Document type	Article ; Online
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Article ; Online: Plasma P-selectin is an early marker of thromboembolism in COVID-19.

Fenyves, Bánk G / Mehta, Arnav / Kays, Kyle R / Beakes, Caroline / Margolin, Justin / Goldberg, Marcia B / Hacohen, Nir / Filbin, Michael R

American journal of hematology

2021 Volume 96, Issue 12, Page(s) E468–E471

MeSH term(s)	Aged ; Biomarkers/blood ; COVID-19/blood ; COVID-19/complications ; COVID-19/diagnosis ; Female ; Humans ; Male ; P-Selectin/blood ; Prospective Studies ; SARS-CoV-2/isolation & purification ; Thromboembolism/blood ; Thromboembolism/diagnosis ; Thromboembolism/etiology
Chemical Substances	Biomarkers ; P-Selectin ; SELP protein, human
Language	English
Publishing date	2021-10-16
Publishing country	United States
Document type	Letter ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	196767-8
ISSN	1096-8652 ; 0361-8609
ISSN (online)	1096-8652
ISSN	0361-8609
DOI	10.1002/ajh.26372
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Book ; Online: Synaptic polarity and sign-balance prediction using gene expression data in the Caenorhabditis elegans chemical synapse neuronal connectome network

Fenyves, Bank G. / Szilagyi, Gabor S. / Vassy, Zsolt / Soti, Csaba / Csermely, Peter

2021

Abstract	Graph theoretical analyses of nervous systems usually omit the aspect of connection polarity, due to data insufficiency. The chemical synapse network of Caenorhabditis elegans is a well-reconstructed directed network, but the signs of its connections are yet to be elucidated. Here, we present the gene expression-based sign prediction of the ionotropic chemical synapse connectome of C. elegans (3,638 connections and 20,589 synapses total), incorporating available presynaptic neurotransmitter and postsynaptic receptor gene expression data for three major neurotransmitter systems. We made predictions for more than two-thirds of these chemical synapses and observed an excitatory-inhibitory (E:I) ratio close to 4:1 which was found similar to that observed in many real-world networks. Our open source tool (http://EleganSign.linkgroup.hu) is simple but efficient in predicting polarities by integrating neuronal connectome and gene expression data. Comment: 19 pages, 5 figues
Keywords	Quantitative Biology - Molecular Networks ; Quantitative Biology - Genomics ; Quantitative Biology - Neurons and Cognition
Subject code	571
Publishing date	2021-01-13
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Dual Role of an mps-2/KCNE-Dependent Pathway in Long-Term Memory and Age-Dependent Memory Decline.

Fenyves, Bank G / Arnold, Andreas / Gharat, Vaibhav G / Haab, Carmen / Tishinov, Kiril / Peter, Fabian / de Quervain, Dominique / Papassotiropoulos, Andreas / Stetak, Attila

Current biology : CB

2020 Volume 31, Issue 3, Page(s) 527–539.e7

Abstract: Activity-dependent persistent changes in neuronal intrinsic excitability and synaptic strength are underlying learning and memory. Voltage-gated potassium ( ... ...

Abstract	Activity-dependent persistent changes in neuronal intrinsic excitability and synaptic strength are underlying learning and memory. Voltage-gated potassium (K
MeSH term(s)	Animals ; Caenorhabditis elegans/genetics ; Caenorhabditis elegans/metabolism ; Caenorhabditis elegans Proteins/genetics ; Caenorhabditis elegans Proteins/metabolism ; Memory Disorders ; Memory, Long-Term ; Potassium Channels, Voltage-Gated
Chemical Substances	Caenorhabditis elegans Proteins ; Potassium Channels, Voltage-Gated
Language	English
Publishing date	2020-11-30
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	1071731-6
ISSN	1879-0445 ; 0960-9822
ISSN (online)	1879-0445
ISSN	0960-9822
DOI	10.1016/j.cub.2020.10.069
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Article: Dual role of an mps-2/KCNE-dependent pathway in long-term memory and age-dependent memory decline

Fenyves, Bank G. / Arnold, Andreas / Gharat, Vaibhav G. / Haab, Carmen / Tishinov, Kiril / Peter, Fabian / de Quervain, Dominique / Papassotiropoulos, Andreas / Stetak, Attila

Current Biology

2021 Volume 31, Issue 3, Page(s) 527–539

Abstract: Abstract not released by publisher. ...

Title translation	Doppelrolle eines mps-2/KCNE-abhängigen Weges beim Langzeitgedächtnis und altersabhängigen Gedächtnisverlust
Abstract	Abstract not released by publisher.
Keywords	Animal Research ; Cognitive Aging ; Kaliumkanal ; Kognitives Altern ; Langzeitgedächtnis ; Long Term Memory ; Molecular Neuroscience ; Molekulare Neurowissenschaft ; Neuronen ; Neurons ; Physiological Correlates ; Physiologische Korrelate ; Potassium Channel ; Proteine ; Proteins ; Tierstudien
Language	English
Document type	Article
ZDB-ID	1071731-6
ISSN	1879-0445 ; 0960-9822
ISSN (online)	1879-0445
ISSN	0960-9822
DOI	10.1016/j.cub.2020.10.069
Database	PSYNDEX

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Article ; Online: Longitudinal proteomic analysis of severe COVID-19 reveals survival-associated signatures, tissue-specific cell death, and cell-cell interactions.

Filbin, Michael R / Mehta, Arnav / Schneider, Alexis M / Kays, Kyle R / Guess, Jamey R / Gentili, Matteo / Fenyves, Bánk G / Charland, Nicole C / Gonye, Anna L K / Gushterova, Irena / Khanna, Hargun K / LaSalle, Thomas J / Lavin-Parsons, Kendall M / Lilley, Brendan M / Lodenstein, Carl L / Manakongtreecheep, Kasidet / Margolin, Justin D / McKaig, Brenna N / Rojas-Lopez, Maricarmen /

Cell reports. Medicine

2021 Volume 2, Issue 5, Page(s) 100287

Abstract: Mechanisms underlying severe coronavirus disease 2019 (COVID-19) disease remain poorly understood. We analyze several thousand plasma proteins longitudinally in 306 COVID-19 patients and 78 symptomatic controls, uncovering immune and non-immune proteins ... ...

Abstract	Mechanisms underlying severe coronavirus disease 2019 (COVID-19) disease remain poorly understood. We analyze several thousand plasma proteins longitudinally in 306 COVID-19 patients and 78 symptomatic controls, uncovering immune and non-immune proteins linked to COVID-19. Deconvolution of our plasma proteome data using published scRNA-seq datasets reveals contributions from circulating immune and tissue cells. Sixteen percent of patients display reduced inflammation yet comparably poor outcomes. Comparison of patients who died to severely ill survivors identifies dynamic immune-cell-derived and tissue-associated proteins associated with survival, including exocrine pancreatic proteases. Using derived tissue-specific and cell-type-specific intracellular death signatures, cellular angiotensin-converting enzyme 2 (ACE2) expression, and our data, we infer whether organ damage resulted from direct or indirect effects of infection. We propose a model in which interactions among myeloid, epithelial, and T cells drive tissue damage. These datasets provide important insights and a rich resource for analysis of mechanisms of severe COVID-19 disease.
Language	English
Publishing date	2021-05-03
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ISSN	2666-3791
ISSN (online)	2666-3791
DOI	10.1016/j.xcrm.2021.100287
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Article ; Online: Longitudinal proteomic analysis of severe COVID-19 reveals survival-associated signatures, tissue-specific cell death, and cell-cell interactions

Michael R. Filbin / Arnav Mehta / Alexis M. Schneider / Kyle R. Kays / Jamey R. Guess / Matteo Gentili / Bánk G. Fenyves / Nicole C. Charland / Anna L.K. Gonye / Irena Gushterova / Hargun K. Khanna / Thomas J. LaSalle / Kendall M. Lavin-Parsons / Brendan M. Lilley / Carl L. Lodenstein / Kasidet Manakongtreecheep / Justin D. Margolin / Brenna N. McKaig / Maricarmen Rojas-Lopez /

Cell Reports Medicine, Vol 2, Iss 5, Pp 100287- (2021)

2021

Abstract: Summary: Mechanisms underlying severe coronavirus disease 2019 (COVID-19) disease remain poorly understood. We analyze several thousand plasma proteins longitudinally in 306 COVID-19 patients and 78 symptomatic controls, uncovering immune and non-immune ... ...

Abstract	Summary: Mechanisms underlying severe coronavirus disease 2019 (COVID-19) disease remain poorly understood. We analyze several thousand plasma proteins longitudinally in 306 COVID-19 patients and 78 symptomatic controls, uncovering immune and non-immune proteins linked to COVID-19. Deconvolution of our plasma proteome data using published scRNA-seq datasets reveals contributions from circulating immune and tissue cells. Sixteen percent of patients display reduced inflammation yet comparably poor outcomes. Comparison of patients who died to severely ill survivors identifies dynamic immune-cell-derived and tissue-associated proteins associated with survival, including exocrine pancreatic proteases. Using derived tissue-specific and cell-type-specific intracellular death signatures, cellular angiotensin-converting enzyme 2 (ACE2) expression, and our data, we infer whether organ damage resulted from direct or indirect effects of infection. We propose a model in which interactions among myeloid, epithelial, and T cells drive tissue damage. These datasets provide important insights and a rich resource for analysis of mechanisms of severe COVID-19 disease.
Keywords	COVID-19 severity ; death versus survival ; plasma proteomics ; lung epithelial cells ; T cell activation ; lung monocyte/macrophages ; Medicine (General) ; R5-920
Language	English
Publishing date	2021-05-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: Plasma proteomics reveals tissue-specific cell death and mediators of cell-cell interactions in severe COVID-19 patients.

Filbin, Michael R / Mehta, Arnav / Schneider, Alexis M / Kays, Kyle R / Guess, Jamey R / Gentili, Matteo / Fenyves, Bánk G / Charland, Nicole C / Gonye, Anna L K / Gushterova, Irena / Khanna, Hargun K / LaSalle, Thomas J / Lavin-Parsons, Kendall M / Lilly, Brendan M / Lodenstein, Carl L / Manakongtreecheep, Kasidet / Margolin, Justin D / McKaig, Brenna N / Rojas-Lopez, Maricarmen /

bioRxiv : the preprint server for biology

2020

Abstract: COVID-19 has caused over 1 million deaths globally, yet the cellular mechanisms underlying severe disease remain poorly understood. By analyzing several thousand plasma proteins in 306 COVID-19 patients and 78 symptomatic controls over serial timepoints ... ...

Abstract	COVID-19 has caused over 1 million deaths globally, yet the cellular mechanisms underlying severe disease remain poorly understood. By analyzing several thousand plasma proteins in 306 COVID-19 patients and 78 symptomatic controls over serial timepoints using two complementary approaches, we uncover COVID-19 host immune and non-immune proteins not previously linked to this disease. Integration of plasma proteomics with nine published scRNAseq datasets shows that SARS-CoV-2 infection upregulates monocyte/macrophage, plasmablast, and T cell effector proteins. By comparing patients who died to severely ill patients who survived, we identify dynamic immunomodulatory and tissue-associated proteins associated with survival, providing insights into which host responses are beneficial and which are detrimental to survival. We identify intracellular death signatures from specific tissues and cell types, and by associating these with angiotensin converting enzyme 2 (ACE2) expression, we map tissue damage associated with severe disease and propose which damage results from direct viral infection rather than from indirect effects of illness. We find that disease severity in lung tissue is driven by myeloid cell phenotypes and cell-cell interactions with lung epithelial cells and T cells. Based on these results, we propose a model of immune and epithelial cell interactions that drive cell-type specific and tissue-specific damage in severe COVID-19.
Keywords	covid19
Language	English
Publishing date	2020-11-03
Publishing country	United States
Document type	Preprint
DOI	10.1101/2020.11.02.365536
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