About: In-silico immune cell deconvolution of the airway proteomes of infants with pneumonia reveals a link between reduced airway eosinophils and an increased risk of mortality

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About: In-silico immune cell deconvolution of the airway proteomes of infants with pneumonia reveals a link between reduced airway eosinophils and an increased risk of mortality Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

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type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	In-silico immune cell deconvolution of the airway proteomes of infants with pneumonia reveals a link between reduced airway eosinophils and an increased risk of mortality
Creator	Kibinge, Nelson Mutunga, Martin Njunge, James Gicheru, Elijah Gwela, Agnes Sande, Charles Waeni, Jacqueline
Source	BioRxiv; MedRxiv
abstract	Rationale Pneumonia is a leading cause of mortality in infants and young children. The immune responses in the airway that are associated with mortality are poorly understood. Studies of the cellular immunology of the infant airway have traditionally been hindered by the limited sample volumes available from the young, frail children who are admitted to hospital with pneumonia. This is further compounded by the relatively low frequencies of certain immune cell phenotypes that are thought to be critical to the clinical outcome of infection. To address this, we developed a novel in-silico deconvolution method for inferring the frequencies of immune cell phenotypes in the airway of children with different survival outcomes using proteomic data. Methods Using high-resolution mass spectrometry, we identified > 1,000 proteins expressed in the airways of children who were admitted to hospital with clinical pneumonia. 61 of these children were discharged from hospital and survived for more than 365 days after discharge, while 19 died during admission. We used unsupervised learning by random forest to derive protein classification markers that could be used to deconvolve individual immune cell phenotypes. We applied these phenotype-specific signatures to high-resolution mass spectrometry-based proteomic data obtained from airway samples collected at admission from infants and children who were discharged from hospital and survived for at least one year as well as those who died from pneumonia during the course of admission. Main Results We identified protein classification markers for 33 immune cell phenotypes. Eosinophil-associated protein markers were significantly elevated in airway secretions obtained from pneumonia survivors and were downregulated in children who subsequently died. To confirm these results, we analyzed clinical parameters from >10,000 children who had been admitted with pneumonia in the previous 10 years. The results of this retrospective analysis mirrored airway deconvolution data and showed that survivors had significantly elevated eosinophils at admission compared to fatal cases of pneumonia. Conclusions Airway eosinophils appear to be a critical immune cell phenotype for pneumonia survival in infants and young children.
has issue date	2019-11-13(xsd:dateTime)
bibo:doi	10.1101/840090
has license	biorxiv
sha1sum (hex)	9a3de625119a83aa1401eeb297937d9605f0d1f1
schema:url	https://doi.org/10.1101/840090
resource representing a document's title	In-silico immune cell deconvolution of the airway proteomes of infants with pneumonia reveals a link between reduced airway eosinophils and an increased risk of mortality
schema:publication	bioRxiv
resource representing a document's body	covid:9a3de625119a83aa1401eeb297937d9605f0d1f1#body_text
is schema:about of	named entity 'PNEUMONIA' named entity 'INCREASED RISK' named entity 'Pneumonia' named entity 'leading' named entity 'Studies' named entity 'eosinophils' named entity 'AIRWAY' named entity 'EOSINOPHILS' named entity 'INFANTS' named entity 'CAUSE' named entity 'THOUGHT' named entity 'LEADING' named entity 'CELLULAR IMMUNOLOGY' named entity 'DECONVOLUTION' named entity 'IMMUNE CELL' named entity 'LEAD' named entity 'OUTCOMES' named entity 'YOUNG CHILDREN' named entity 'MORTALITY' named entity 'THESE' named entity 'LINK' named entity 'COMPOUNDED' named entity 'INFANTS' named entity 'MECHANISMS' named entity 'FRAIL' named entity 'INFANT AIRWAY' named entity 'RISK OF' named entity 'DECONVOLUTION' named entity 'INFERRING' named entity 'CERTAIN' named entity 'MORTALITY' named entity 'DIFFERENT' named entity 'POORLY' named entity 'IS A' named entity 'LIMITED' named entity 'OUTCOME' named entity 'METHOD' named entity 'PROTEOMIC' named entity 'DATA' named entity 'AVAILABLE' named entity 'NOVEL' named entity 'SAMPLE' named entity 'RATIONALE' named entity 'ADDRESS' named entity 'STUDIES' named entity 'YOUNG' named entity 'CHILDREN' named entity 'UNDERSTOOD' named entity 'CRITICAL' named entity 'SURVIVAL' named entity 'AIRWAY' named entity 'VOLUMES' named entity 'CLINICAL' named entity 'REDUCED' named entity 'HAVE' named entity 'USING' named entity 'FREQUENCIES' named entity 'PROTEOMES' named entity 'IMMUNE CELL' named entity 'REVEALS' named entity 'PNEUMONIA' named entity 'PHENOTYPES' named entity 'LOW' covid:arg/9a3de625119a83aa1401eeb297937d9605f0d1f1 named entity 'cellular' named entity 'infants' named entity 'phenotypes' named entity 'immune cell' named entity 'volumes' named entity 'clinical outcome' named entity 'immune cell' named entity 'airway' named entity 'deconvolution' named entity 'immune cell' named entity 'proteomes' named entity 'DCs' named entity 'data set' named entity 'proteome'

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