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Discovery of pharmaceutically-targetable pathways and prediction of survivorship for pneumonia and sepsis patients from the view point of ensemble gene noise

Tristan de Jong, View ORCID ProfileVictor Guryev, Yury M. Moshkin
doi: https://doi.org/10.1101/2020.04.10.035717
Tristan de Jong
1European Research Institute for the Biology of Ageing, University of Groningen, University Medical Centre Groningen, Groningen, The Netherlands
4Gene Learning Association, Geneva, Switzerland
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Victor Guryev
1European Research Institute for the Biology of Ageing, University of Groningen, University Medical Centre Groningen, Groningen, The Netherlands
4Gene Learning Association, Geneva, Switzerland
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  • For correspondence: yury.moshkin@gmail.com v.guryev@umcg.nl
Yury M. Moshkin
2Federal Research Centre, Institute of Cytology and Genetics, SB RAS, Novosibirsk, Russia
3Institute of Molecular and Cellular Biology, SB RAS, Novosibirsk, Russia
4Gene Learning Association, Geneva, Switzerland
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  • For correspondence: yury.moshkin@gmail.com v.guryev@umcg.nl
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Abstract

Finding novel biomarkers for human pathologies and predicting clinical outcomes for patients is rather challenging. This stems from the heterogenous response of individuals to disease which is also reflected in the inter-individual variability of gene expression responses. This in turn obscures differential gene expression analysis (DGE). In the midst of the COVID-19 pandemic, we wondered whether an alternative to DGE approaches could be applied to dissect the molecular nature of a host-response to infection exemplified here by an analysis of H1N1 influenza, community/hospital acquired pneumonia (CAP) and sepsis. To this end, we turned to the analysis of ensemble gene noise. Ensemble gene noise, as we defined it here, represents a variance within an individual for a collection of genes encoding for either members of known biological pathways or subunits of annotated protein complexes. From the law of total variance, ensemble gene noise depends on the stoichiometry of the ensemble genes’ expression and on their average noise (variance). Thus, rather than focusing on specific genes, ensemble gene noise allows for the holistic identification and interpretation of gene expression disbalance on the level of gene networks and systems. Comparing H1N1, CAP and sepsis patients we spotted common disturbances in a number of pathways/protein complexes relevant to the sepsis pathology which lead to an increase in the ensemble gene noise. Among others, these include mitochondrial respiratory chain complex I and peroxisomes which could be readily targeted for adjuvant treatment by methylene blue and 4-phenylbutyrate respectively. Finally, we showed that ensemble gene noise could be successfully applied for the prediction of clinical outcome, namely mortality, of CAP and sepsis patients. Thus, we conclude that ensemble gene noise represents a promising approach for the investigation of molecular mechanisms of a pathology through a prism of alterations in coherent expression of gene circuits.

Competing Interest Statement

The authors have declared no competing interest.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC 4.0 International license.
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Posted April 11, 2020.
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Discovery of pharmaceutically-targetable pathways and prediction of survivorship for pneumonia and sepsis patients from the view point of ensemble gene noise
Tristan de Jong, Victor Guryev, Yury M. Moshkin
bioRxiv 2020.04.10.035717; doi: https://doi.org/10.1101/2020.04.10.035717
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Discovery of pharmaceutically-targetable pathways and prediction of survivorship for pneumonia and sepsis patients from the view point of ensemble gene noise
Tristan de Jong, Victor Guryev, Yury M. Moshkin
bioRxiv 2020.04.10.035717; doi: https://doi.org/10.1101/2020.04.10.035717

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