PXD025265

PXD025265 is an original dataset announced via ProteomeXchange.

Title	Drivers genes in severe forms of COVID-19
Description	The etiology of severe forms of COVID19, especially in young patients, remains a salient unanswered question. Here we build on a 3-tier cohort where all individuals/patients were strictly below 50 years of age and where a number of comorbidities were excluded at study onset. Besides healthy controls (N=22), these include patients in the intensive care unit with Acute Respiratory Distress Syndrome (ARDS) (“critical group”; N=47), and those in a non-critical care ward under supplemental oxygen (“non-critical group”, N=25). This highly curated cohort allowed us to perform a deep multi-omics approach which included whole genome sequencing, whole blood RNA-sequencing, plasma and peripheral-blood mononuclear cells proteomics, multiplex cytokine profiling, mass-cytometry-based immune cell profiling in conjunction with viral parameters i.e. anti-SARS-Cov-2 neutralizing antibodies and multi-target antiviral serology. Critical patients were characterized by an exacerbated inflammatory state, perturbed lymphoid and myeloid cell compartments, signatures of dysregulated blood coagulation and active regulation of viral entry into the cells. A unique gene signature that differentiates critical from non-critical patients was identified by an ensemble machine learning, deep learning and quantum computing approach. Within this gene network, Structural Causal Modeling identified several ARDS driver genes, among which the up-regulated metalloprotease ADAM9 seems to be a key driver. Inhibition of ADAM9 ex vivo interfered with SARS-Cov-2 uptake and replication in human epithelial cells. Hence we apply a machine learning approach to identify driver genes for severe forms of COVID-19 in a small, uncluttered cohort of patients.
HostingRepository	PRIDE
AnnounceDate	2021-11-25
AnnouncementXML	Submission_2021-11-25_07:27:26.141.xml
DigitalObjectIdentifier
ReviewLevel	Peer-reviewed dataset
DatasetOrigin	Original dataset
RepositorySupport	Unsupported dataset by repository
PrimarySubmitter	Aurélie Hirschler
SpeciesList	scientific name: Homo sapiens (Human); NCBI TaxID: 9606;
ModificationList	acetylated residue; monohydroxylated residue; iodoacetamide derivatized residue
Instrument	Q Exactive

Revision	Datetime	Status	ChangeLog Entry
0	2021-04-08 06:01:28	ID requested
⏵ 1	2021-11-25 07:27:26	announced

Dataset with its publication pending

ProteomeXchange project tag: Sars-cov-2, Covid-19

submitter keyword: SARS-CoV-2, COVID-19, Acute Respiratory Distress Syndrome, mechanical ventilation, multi-omics, artificial intelligence, machine learning, disease severity signatures, therapeutic targets, ADAM9

Christine Carapito
contact affiliation	Laboratoire de Spectrométrie de Masse BioOrganique, Université de Strasbourg, CNRS, IPHC, UMR 7178, Strasbourg, France
contact email	ccarapito@unistra.fr
lab head
Aurélie Hirschler
contact affiliation	LSMBO, IPHC
contact email	aurelie.hirschler@unistra.fr
dataset submitter

Dataset FTP location NOTE: Most web browsers have now discontinued native support for FTP access within the browser window. But you can usually install another FTP app (we recommend FileZilla) and configure your browser to launch the external application when you click on this FTP link. Or otherwise, launch an app that supports FTP (like FileZilla) and use this address: ftp://ftp.pride.ebi.ac.uk/pride/data/archive/2021/11/PXD025265

PRIDE project URI

• PRIDE
  1. PXD025265
     1. Label: PRIDE project
     2. Name: Drivers genes in severe forms of COVID-19