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. 2022 Nov 1:13:1022750.
doi: 10.3389/fimmu.2022.1022750. eCollection 2022.

A 9-mRNA signature measured from whole blood by a prototype PCR panel predicts 28-day mortality upon admission of critically ill COVID-19 patients

Claire Tardiveau  1   2 , Guillaume Monneret  1   3 , Anne-Claire Lukaszewicz  1   4 , Valérie Cheynet  1   2 , Elisabeth Cerrato  1   2 , Katia Imhoff  1   2 , Estelle Peronnet  1   2 , Maxime Bodinier  1   2 , Louis Kreitmann  1   2 , Sophie Blein  1   2 , Jean-François Llitjos  1   2   4 , Filippo Conti  1   3 , Morgane Gossez  3   5 , Marielle Buisson  6 , Hodane Yonis  7 , Martin Cour  8 , Laurent Argaud  8 , Marie-Charlotte Delignette  9 , Florent Wallet  10 , Frederic Dailler  11 , Céline Monard  4 , Karen Brengel-Pesce  1   2 , Fabienne Venet  3   5 ; RICO study group
Affiliations

A 9-mRNA signature measured from whole blood by a prototype PCR panel predicts 28-day mortality upon admission of critically ill COVID-19 patients

Claire Tardiveau et al. Front Immunol. .

Abstract

Immune responses affiliated with COVID-19 severity have been characterized and associated with deleterious outcomes. These approaches were mainly based on research tools not usable in routine clinical practice at the bedside. We observed that a multiplex transcriptomic panel prototype termed Immune Profiling Panel (IPP) could capture the dysregulation of immune responses of ICU COVID-19 patients at admission. Nine transcripts were associated with mortality in univariate analysis and this 9-mRNA signature remained significantly associated with mortality in a multivariate analysis that included age, SOFA and Charlson scores. Using a machine learning model with these 9 mRNA, we could predict the 28-day survival status with an Area Under the Receiver Operating Curve (AUROC) of 0.764. Interestingly, adding patients' age to the model resulted in increased performance to predict the 28-day mortality (AUROC reaching 0.839). This prototype IPP demonstrated that such a tool, upon clinical/analytical validation and clearance by regulatory agencies could be used in clinical routine settings to quickly identify patients with higher risk of death requiring thus early aggressive intensive care.

Keywords: 28-day mortality prediction; SARS-CoV-2 infection; immune response; personalized medicine; transcriptomic multiplex tool.

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Conflict of interest statement

CT, VC, EC, KI, KB-P, EP, MBo, LK, SB, and J-FL are bioMérieux’s employees. EP, GM, and FV are co-inventors in patent applications covering the following markers: CX3CR1, CD127, IL10 and S100A9. bioFire – a bioMérieux company - holds patents on the technology. This does not alter the authors’ adherence to all the policies on sharing data and materials. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
IPP markers distinguish healthy donors from critically ill COVID-19 patients and are associated with immunological parameters. (A) Non-supervised PCA on IPP markers measured at admission (Day 0) in critically ill COVID-19 patients (n=309) and healthy donors (n=49). (B) Boxplots representation of the expression of IPP markers related to immunological parameters. p values were computed with a Mann-Whitney-Wilcoxon test. Whiskers indicate the 2.5 and 97.5 percentiles.
Figure 2
Figure 2
Description of IPP 9-mRNA and clinical parameters in the RICO cohort of 309 critically ill COVID-19 patients. (A) Expression of IPP markers (values are presented as normalized Cp). (B) Age (years). (C) Clinical scores. All parameters are presented at admission between 28-day survivors (green) and non-survivors (red). When relevant, reference values of healthy donors are presented in grey. The p-value were generated using a Mann-Whitney-Wilcoxon test between survivors and non-survivors.
Figure 3
Figure 3
IPP markers measured at admission predict 28-day mortality in critically ill COVID-19 patients. Area Under the Receiver Operating Characteristics curve (AUC) calculated on the training dataset of 216 patients and the independent test set of 93 critically ill COVID-19 patients using the 9-mRNA panel at their admission in the ICU. The 95% confidence interval (grey) was calculated using bootstrap with 1000 repetitions.
Figure 4
Figure 4
Performance of the 9-mRNA signature combined with age to predict 28-day survival status in critically ill COVID-19 patients at ICU admission. (A) Area Under the Receiver Operating Characteristics curve (AUC) calculated on the training dataset of 216 patients and the independent test set of 93 critically ill COVID-19 patients using the 9-mRNA panel along with the age at their admission in ICU. The 95% confidence interval (grey) is calculated using bootstrap with 1000 repetitions. (B) Probability of 28-day mortality from linear SVM model trained on 9-gene panel (left) and 9-gene panel combined with age (right) on the entire cohort (n=309) of patients and healthy donors (n=49). p-values were generated using a Mann-Whitney-Wilcoxon test between survivors and non-survivors.
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