Superiority of transcriptional profiling over procalcitonin for distinguishing bacterial from viral lower respiratory tract infections in hospitalized adults.

Nicolas M Suarez, Eleonora Bunsow, Ann R Falsey, Edward E Walsh, Asuncion Mejias, Octavio Ramilo
Author Information
  1. Nicolas M Suarez: Center for Vaccines and Immunity Division of Pediatric Infectious Diseases, The Research Institute at Nationwide Children's Hospital, The Ohio State University College of Medicine, Columbus.
  2. Eleonora Bunsow: Center for Vaccines and Immunity Division of Pediatric Infectious Diseases, The Research Institute at Nationwide Children's Hospital, The Ohio State University College of Medicine, Columbus.
  3. Ann R Falsey: Department of Medicine, University of Rochester Rochester General Hospital, New York.
  4. Edward E Walsh: Department of Medicine, University of Rochester Rochester General Hospital, New York.
  5. Asuncion Mejias: Center for Vaccines and Immunity Division of Pediatric Infectious Diseases, The Research Institute at Nationwide Children's Hospital, The Ohio State University College of Medicine, Columbus.
  6. Octavio Ramilo: Center for Vaccines and Immunity Division of Pediatric Infectious Diseases, The Research Institute at Nationwide Children's Hospital, The Ohio State University College of Medicine, Columbus.

Abstract

BACKGROUND: Distinguishing between bacterial and viral lower respiratory tract infection (LRTI) remains challenging. Transcriptional profiling is a promising tool for improving diagnosis in LRTI.
METHODS: We performed whole blood transcriptional analysis in 118 patients (median age [interquartile range], 61 [50-76] years) hospitalized with LRTI and 40 age-matched healthy controls (median age, 60 [46-70] years). We applied class comparisons, modular analysis, and class prediction algorithms to identify and validate diagnostic biosignatures for bacterial and viral LRTI.
RESULTS: Patients were classified as having bacterial (n = 22), viral (n = 71), or bacterial-viral LRTI (n = 25) based on comprehensive microbiologic testing. Compared with healthy controls, statistical group comparisons (P < .01; multiple-test corrections) identified 3376 differentially expressed genes in patients with bacterial LRTI, 2391 in viral LRTI, and 2628 in bacterial-viral LRTI. Patients with bacterial LRTI showed significant overexpression of inflammation and neutrophil genes (bacterial > bacterial-viral > viral), and those with viral LRTI displayed significantly greater overexpression of interferon genes (viral > bacterial-viral > bacterial). The K-nearest neighbors algorithm identified 10 classifier genes that discriminated between bacterial and viral LRTI with a 95% sensitivity (95% confidence interval, 77%-100%) and 92% specificity (77%-98%), compared with a sensitivity of 38% (18%-62%) and a specificity of 91% (76%-98%) for procalcitonin.
CONCLUSIONS: Transcriptional profiling is a helpful tool for diagnosis of LRTI.

Keywords

References

  1. Br J Pharmacol. 2010 Jan 1;159(2):253-64 [PMID: 20002097]
  2. Nat Rev Immunol. 2014 Apr;14(4):271-80 [PMID: 24662387]
  3. Nature. 2010 Aug 19;466(7309):973-7 [PMID: 20725040]
  4. Pulm Pharmacol Ther. 2010 Dec;23(6):501-7 [PMID: 20434579]
  5. Clin Infect Dis. 2011 May;52 Suppl 4:S326-30 [PMID: 21460291]
  6. PLoS One. 2012;7(3):e33174 [PMID: 22432004]
  7. PLoS One. 2012;7(4):e34390 [PMID: 22496797]
  8. Clinics (Sao Paulo). 2012 Nov;67(11):1321-5 [PMID: 23184211]
  9. J Infect Dis. 2013 Aug 1;208(3):432-41 [PMID: 23661797]
  10. BMC Biol. 2010;8:84 [PMID: 20619006]
  11. PLoS Med. 2013 Nov;10(11):e1001549 [PMID: 24265599]
  12. Thorax. 2001 Feb;56(2):109-14 [PMID: 11209098]
  13. BMJ. 2005 Jul 2;331(7507):26 [PMID: 15979984]
  14. Thorax. 2006 Jan;61(1):75-9 [PMID: 16227331]
  15. PLoS Med. 2006 Feb;3(2):e76 [PMID: 16401173]
  16. Blood. 2007 Mar 1;109(5):2066-77 [PMID: 17105821]
  17. J Exp Med. 2007 Sep 3;204(9):2131-44 [PMID: 17724127]
  18. Crit Care Med. 2008 Mar;36(3):941-52 [PMID: 18431284]
  19. Immunity. 2008 Jul 18;29(1):150-64 [PMID: 18631455]
  20. N Engl J Med. 2009 Feb 5;360(6):588-98 [PMID: 19196675]
  21. PLoS One. 2009;4(5):e5446 [PMID: 19424507]
  22. JAMA. 2009 Sep 9;302(10):1059-66 [PMID: 19738090]
  23. Proc Natl Acad Sci U S A. 2013 Jul 30;110(31):12792-7 [PMID: 23858444]
  24. Sci Transl Med. 2013 Sep 18;5(203):203ra126 [PMID: 24048524]
  25. PLoS Med. 2013 Oct;10(10):e1001538 [PMID: 24167453]
  26. Clin Infect Dis. 2013 Dec;57 Suppl 3:S139-70 [PMID: 24200831]

Grants

  1. R01 AI079446/NIAID NIH HHS
  2. U19 AI089987/NIAID NIH HHS
  3. AI079446/NIAID NIH HHS
  4. AI089987/NIAID NIH HHS

MeSH Term

Adult
Aged
Biomarkers
Calcitonin
Calcitonin Gene-Related Peptide
Case-Control Studies
Diagnosis, Differential
Female
Gene Expression Profiling
Hospitalization
Humans
Influenza, Human
Male
Middle Aged
Pneumonia, Pneumococcal
Prospective Studies
Protein Precursors
Sensitivity and Specificity
Transcriptome

Chemicals

Biomarkers
CALCA protein, human
Protein Precursors
Calcitonin
Calcitonin Gene-Related Peptide

Word Cloud

Created with Highcharts 10.0.0LRTIbacterialviralbacterial-viralgenes>lowerrespiratorytractprofilingn=procalcitonininfectionsinfectionTranscriptionaltooldiagnosistranscriptionalanalysispatientsmedianageyearshospitalizedhealthycontrolsclasscomparisonsPatientsidentifiedoverexpression95%sensitivityspecificityBACKGROUND:DistinguishingremainschallengingpromisingimprovingMETHODS:performedwholeblood118[interquartilerange]61[50-76]40age-matched60[46-70]appliedmodularpredictionalgorithmsidentifyvalidatediagnosticbiosignaturesRESULTS:classified227125basedcomprehensivemicrobiologictestingComparedstatisticalgroupP<01multiple-testcorrections3376differentiallyexpressed23912628showedsignificantinflammationneutrophildisplayedsignificantlygreaterinterferonK-nearestneighborsalgorithm10classifierdiscriminatedconfidenceinterval77%-100%92%77%-98%compared38%18%-62%91%76%-98%CONCLUSIONS:helpfulSuperioritydistinguishingadultsmicroarrays

Similar Articles

Cited By