Multicohort Analysis of Whole-Blood Gene Expression Data Does Not Form a Robust Diagnostic for Acute Respiratory Distress Syndrome

Timothy E Sweeney, Neal J Thomas, Judie A Howrylak, Hector R Wong, Angela J Rogers, Purvesh Khatri, Timothy E Sweeney, Neal J Thomas, Judie A Howrylak, Hector R Wong, Angela J Rogers, Purvesh Khatri

Abstract

Objectives: To identify a novel, generalizable diagnostic for acute respiratory distress syndrome using whole-blood gene expression arrays from multiple acute respiratory distress syndrome cohorts of varying etiologies.

Data sources: We performed a systematic search for human whole-blood gene expression arrays of acute respiratory distress syndrome in National Institutes of Health Gene Expression Omnibus and ArrayExpress. We also included the Glue Grant gene expression cohorts.

Study selection: We included investigator-defined acute respiratory distress syndrome within 48 hours of diagnosis and compared these with relevant critically ill controls.

Data extraction: We used multicohort analysis of gene expression to identify genes significantly associated with acute respiratory distress syndrome, both with and without adjustment for clinical severity score. We performed gene ontology enrichment using Database for Annotation, Visualization and Integrated Discovery and cell type enrichment tests for both immune cells and pneumocyte gene expression. Finally, we selected a gene set optimized for diagnostic power across the datasets and used leave-one-dataset-out cross validation to assess robustness of the model.

Data synthesis: We identified datasets from three adult cohorts with sepsis, one pediatric cohort with acute respiratory failure, and two datasets of adult patients with trauma and burns, for a total of 148 acute respiratory distress syndrome cases and 268 critically ill controls. We identified 30 genes that were significantly associated with acute respiratory distress syndrome (false discovery rate < 20% and effect size >1.3), many of which had been previously associated with sepsis. When metaregression was used to adjust for clinical severity scores, none of these genes remained significant. Cell type enrichment was notable for bands and neutrophils, suggesting that the gene expression signature is one of acute inflammation rather than lung injury per se. Finally, an attempt to develop a generalizable diagnostic gene set for acute respiratory distress syndrome showed a mean area under the receiver-operating characteristic curve of only 0.63 on leave-one-dataset-out cross validation.

Conclusions: The whole-blood gene expression signature across a wide clinical spectrum of acute respiratory distress syndrome is likely confounded by systemic inflammation, limiting the utility of whole-blood gene expression studies for uncovering a generalizable diagnostic gene signature.

Conflict of interest statement

Drs. Sweeney and Khatri received funding from Inflammatix (co-founders and stock). Dr. Thomas’ institution received funding from the Food and Drug Administration, and he received funding from Therabron and CareFusion. Dr. Wong’s institution received funding from the National Institutes of Health (NIH). Drs. Wong and Rogers received support for article research from the NIH. Dr. Rogers received funding from K23 HL125663. Dr. Khatri received funding from the National Institute of Allergy and Infectious Disease (grants 1U19AI109662, U19AI057229, and U54I117925) and the Bill and Melinda Gates Foundation, and he received support for article research from the NIH and the Bill and Melinda Gates Foundation. Dr. Howrylak disclosed that she does not have any potential conflicts of interest.

Figures

Figure 1.
Figure 1.
The 30 genes found to be significantly differentially expressed in acute respiratory distress syndrome (ARDS) were tested for enrichment in several in vitro cell catheters (both immune cell types and pneumocytes) to assess for the possibility of cell type enrichment in whole blood in ARDS NK = Natural Killer.
Figure 2.
Figure 2.
Discriminatory power for prediction of acute respiratory distress syndrome (ARDS) versus non-ARDS critically ill controls using transcriptomics from whole blood. A single seven-gene set was chosen via forward search. A, Receiver-operating characteristic (ROC) curves. B Test characteristics of each curve at its Youden cutoff. AUC = area under the ROC curve.

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Source: PubMed

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