Application of an Exploratory Knowledge-Discovery Pipeline Based on Machine Learning to Multi-Scale OMICS Data to Characterise Myocardial Injury in a Cohort of Patients with Septic Shock: An Observational Study.

Bernardo Bollen Pinto,Daniele Braga,Giuseppe Baselli,Cristina Barlassina,Matteo Barcella,On Behalf Of The Shockomics Consortium ,Vicent Ribas Ripoll,Karim Bendjelid,Julia Bauzá-Martinez,Manuela Ferrario,Antoine Herpain,Roberta Pastorelli,Antonia Odena,Eliandre Oliveira,Laia Subirats,Federico Aletti,Paula Subías-Beltrán

doi:10.3390/jcm10194354

Abstract

Currently, there is no therapy targeting septic cardiomyopathy (SC), a key contributor to organ dysfunction in sepsis. In this study, we used a machine learning (ML) pipeline to explore transcriptomic, proteomic, and metabolomic data from patients with septic shock, and prospectively collected measurements of high-sensitive cardiac troponin and echocardiography. The purposes of the study were to suggest an exploratory methodology to identify and characterise the multiOMICs profile of (i) myocardial injury in patients with septic shock, and of (ii) cardiac dysfunction in patients with myocardial injury. The study included 27 adult patients admitted for septic shock. Peripheral blood samples for OMICS analysis and measurements of high-sensitive cardiac troponin T (hscTnT) were collected at two time points during the ICU stay. A ML-based study was designed and implemented to untangle the relations among the OMICS domains and the aforesaid biomarkers. The resulting ML pipeline consisted of two main experimental phases: recursive feature selection (FS) assessing the stability of biomarkers, and classification to characterise the multiOMICS profile of the target biomarkers. The application of a ML pipeline to circulate OMICS data in patients with septic shock has the potential to predict the risk of myocardial injury and the risk of cardiac dysfunction.

Highlights

Sepsis is a life-threatening organ dysfunction caused by a dysregulated immune response to infection [1] and septic shock is its most severe form associated with higher mortality [2]
ShockOmics study, of which 27 patients with septic shock were included in the present analysis (Figure S1)
Twenty patients (74%) had an elevated troponin fitting the pre-defined criteria of myocardial injury (Figure 1)

Summary

Introduction

Sepsis is a life-threatening organ dysfunction caused by a dysregulated immune response to infection [1] and septic shock is its most severe form associated with higher mortality [2]. More than half of the patients with septic shock present elevated levels of circulating cardiac biomarkers, such as troponin ( referred as myocardial injury) and some degree of impairment in echocardiographic indices of diastolic and/or systolic function ( referred as cardiac dysfunction), conditions commonly grouped under the terminology of septic cardiomyopathy (SC) [3]. One likely reason for the lack of successful interventions targeting SC is that we fail to understand the root causes of heart affection (myocardial injury and cardiac dysfunction) in patients with septic shock. The underlying pathophysiology is certainly complex and studies performed in sub-optimal animal models have proposed a number of events and pathways [7] that have rarely been confirmed in human subjects

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