What kind of information a clinician wants from an OMICS study? - Lessons Learned from my Study on Acute Respiratory Distress Syndrome (ARDS)

The mortality associated with acute respiratory distress syndrome (ARDS) remains above 40% despite many advances in intensive care. Many clinical trials have evaluated the efficacy of certain drugs in ARDS, but these have mostly failed to improve the clinical course.Acute respiratory distress syndrome (ARDS) is etiologically and clinically a heterogeneous disease. Its diagnostic characteristics and subtype classification, and the application of these features to treatment, have been of considerable interest. ARDS subphenotypes have typically been divided into direct (pulmonary) ARDS and indirect (extrapulmonary) ARDS, according to the etiology.The aim of this study was to find diagnostic metabolites that distinguish sepsis-induced ARDS patients from non-ARDS controls using this targeted metabolomics approach and to identify metabolites and related pathways that can differentiate sepsis-induced direct and indirect ARDS. Using partial least-squares discriminant analysis, we showed that sepsis-induced ARDS patients were metabolically distinct from the non-ARDS controls. The main distinguishing metabolites were lysoPE plasmalogen, PE plasmalogens, and PCs. Sepsis-induced direct and indirect ARDS were also metabolically distinct subgroups, with differences in lysoPCs. Glycerophospholipid and sphingolipid metabolism were the most significant metabolic pathways involved in sepsis-induced ARDS biology and in sepsis-induced direct/indirect ARDS, respectively.These metabolites demonstrated potential as important markers for distinguishing subphenotypes. This study serves as a foundation for future research, transitioning from phenotype analysis to genome investigation, with the aim of identifying biological pathways and processes.From a clinician's perspective, the ultimate objective is to identify the potential causative changes that contribute to these differences and to establish treatment targets through the integration of multi-omics approaches