TY - JOUR
T1 - Multicohort analysis of whole-blood gene expression data does not form a robust diagnostic for acute respiratory distress syndrome
AU - Sweeney, Timothy E.
AU - Thomas, Neal J.
AU - Howrylak, Judie A.
AU - Wong, Hector R.
AU - Rogers, Angela J.
AU - Khatri, Purvesh
N1 - Funding Information:
We thank many authors who contributed the gene expression data reanalyzed here, without whom this would not have been possible. We thank Dr. Jake Hughey for independent statistical review. We thank the Glue Grant investigators for sharing their data publicly; they are supported in this by National Institute of General Medical Sciences Glue Grant Legacy Award R24GM102656.
Funding Information:
1Stanford Institute for Immunity, Transplantation and Infection, Stanford University School of Medicine, Stanford, CA. 2Biomedical Informatics Research, Stanford University School of Medicine, Stanford, CA. 3Division of Pediatric Critical Care Medicine, Penn State Hershey Children’s Hospital, Hershey, PA. 4Division of Pulmonary and Critical Care Medicine, Penn State Milton S. Hershey Medical Center, Hershey, PA. 5Division of Critical Care Medicine, Cincinnati Children’s Hospital Medical Center and Cincinnati Children’s Research Foundation, Cincinnati, OH. 6Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH. 7Department of Medicine, Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, Stanford University School of Medicine, Stanford, CA. Drs. Rogers and Khatri are cosenior authors. Since the time of the article, Dr. Sweeney has moved to Inflammatix. Drs. Sweeney, Rogers, and Khatri conceived the study. Dr. Sweeney carried out the analyses. Drs. Thomas, Howrylak, and Wong annotated the clinical pediatric data. All members revised the article and approved its final version. 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 CareFu-sion. 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. Data and Materials Availability: The Gene Expression Omnibus data can be found online using their accession numbers listed here. The Glue Grant data are publicly available pending institutional review board approval per the instructions found at https://www.gluegrant. org/. The data and code necessary to recreate the multicohort analysis have been deposited online at http://khatrilab.stanford.edu/sepsis; access to the data will be granted after approval by the Glue Grant consortium. For information regarding this article, E-mail: ajrogers@stanford.edu; pkhatri@stanford.edu Copyright © 2018 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved.
Publisher Copyright:
© 2018 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc.
PY - 2018/2
Y1 - 2018/2
N2 - 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 wholeblood 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.
AB - 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 wholeblood 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.
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U2 - 10.1097/CCM.0000000000002839
DO - 10.1097/CCM.0000000000002839
M3 - Article
C2 - 29337789
AN - SCOPUS:85047737579
VL - 46
SP - 244
EP - 251
JO - Critical Care Medicine
JF - Critical Care Medicine
SN - 0090-3493
IS - 2
ER -