Jacob Silterra1, Michael A Gillette1,2,3, Miguel Lanaspa4,5, Karell G Pellé1,6, Clarissa Valim1,6, Rushdy Ahmad1, Sozinho Acácio5,7, Katherine D Almendinger1, Yan Tan1,8, Lola Madrid4,5, Pedro L Alonso4,5, Steven A Carr1, Roger C Wiegand1, Quique Bassat4,9,5, Jill P Mesirov1,10, Danny A Milner1,3,6,11, Dyann F Wirth1,6. 1. Broad Institute of MIT and Harvard, Cambridge. 2. Massachusetts General Hospital. 3. Harvard Medical School. 4. Barcelona Institute for Global Health, Barcelona Centre of International Health Research, Hospital Clínic-Universitat de Barcelona. 5. Centro de Investigação em Saúde de Manhiça. 6. Department of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health. 7. National Institute of Health, Health Ministry, Maputo, Mozambique. 8. Bioinformatics Program, Boston University. 9. Institució Catalana de Recerca i Estudis Avançats, Passeig Lluís Companys 23, 08010 Barcelona. 10. Department of Medicine, University of California, San Diego. 11. Brigham and Women's Hospital, Boston, Massachusetts.
Abstract
Background: Pediatric acute respiratory distress in tropical settings is very common. Bacterial pneumonia is a major contributor to morbidity and mortality rates and requires adequate diagnosis for correct treatment. A rapid test that could identify bacterial (vs other) infections would have great clinical utility. Methods and Results: We performed RNA (RNA-seq) sequencing and analyzed the transcriptomes of 68 pediatric patients with well-characterized clinical phenotype to identify transcriptional features associated with each disease class. We refined the features to predictive models (support vector machine, elastic net) and validated those models in an independent test set of 37 patients (80%-85% accuracy). Conclusions: We have identified sets of genes that are differentially expressed in pediatric patients with pneumonia syndrome attributable to different infections and requiring different therapeutic interventions. Findings of this study demonstrate that human transcription signatures in infected patients recapitulate the underlying biology and provide models for predicting a bacterial diagnosis to inform treatment.
Background: Pediatric acute respiratory distress in tropical settings is very common. Bacterial pneumonia is a major contributor to morbidity and mortality rates and requires adequate diagnosis for correct treatment. A rapid test that could identify bacterial (vs other) infections would have great clinical utility. Methods and Results: We performed RNA (RNA-seq) sequencing and analyzed the transcriptomes of 68 pediatric patients with well-characterized clinical phenotype to identify transcriptional features associated with each disease class. We refined the features to predictive models (support vector machine, elastic net) and validated those models in an independent test set of 37 patients (80%-85% accuracy). Conclusions: We have identified sets of genes that are differentially expressed in pediatric patients with pneumonia syndrome attributable to different infections and requiring different therapeutic interventions. Findings of this study demonstrate that human transcription signatures in infectedpatients recapitulate the underlying biology and provide models for predicting a bacterial diagnosis to inform treatment.
Authors: Emily Speranza; Ignacio Caballero; Anna N Honko; Joshua C Johnson; J Kyle Bohannon; Lisa Evans DeWald; Dawn M Gerhardt; Jennifer Sword; Lisa E Hensley; Richard S Bennett; John H Connor Journal: mBio Date: 2020-06-16 Impact factor: 7.867
Authors: Michael A Gillette; D R Mani; Christopher Uschnig; Karell G Pellé; Lola Madrid; Sozinho Acácio; Miguel Lanaspa; Pedro Alonso; Clarissa Valim; Steven A Carr; Stephen F Schaffner; Bronwyn MacInnis; Danny A Milner; Quique Bassat; Dyann F Wirth Journal: Clin Infect Dis Date: 2021-12-06 Impact factor: 9.079