Melissa H Ross1, Brittany L Zick2, Ephraim L Tsalik3. 1. Duke University School of Medicine, Durham, NC, USA. 2. Duke Center for Applied Genomics & Precision Medicine, Durham, NC, USA. 3. Duke University School of Medicine, Durham, NC, USA; Duke Center for Applied Genomics & Precision Medicine, Durham, NC, USA; Durham Veterans Affairs Health Care System, Durham, NC, USA. Electronic address: e.t@duke.edu.
Abstract
PURPOSE: The inappropriate use of antimicrobials, especially in acute respiratory infections (ARIs), is largely driven by difficulty distinguishing bacterial, viral, and noninfectious etiologies of illness. A new frontier in infectious disease diagnostics looks to the host response for disease classification. This article examines how host response-based diagnostics for ARIs are being used in clinical practice, as well as new developments in the research pipeline. METHODS: A limited search was conducted of the relevant literature, with emphasis placed on literature published in the last 5 years (2014-2019). FINDINGS: Advances are being made in all areas of host response-based diagnostics for ARIs. Specifically, there has been significant progress made in single protein biomarkers, as well as in various "omics" fields (including proteomics, metabolomics, and transcriptomics) and wearable technologies. There are many potential applications of a host response-based approach; a few key examples include the ability to discriminate bacterial and viral disease, presymptomatic diagnosis of infection, and pathogen-specific host response diagnostics, including modeling disease progression. IMPLICATIONS: As biomarker measurement technologies continue to improve, host response-based diagnostics will increasingly be translated to clinically available platforms that can generate a holistic characterization of an individual's health. This knowledge, in the hands of both patient and provider, can improve care for the individual patient and help fight rising rates of antibiotic resistance.
PURPOSE: The inappropriate use of antimicrobials, especially in acute respiratory infections (ARIs), is largely driven by difficulty distinguishing bacterial, viral, and noninfectious etiologies of illness. A new frontier in infectious disease diagnostics looks to the host response for disease classification. This article examines how host response-based diagnostics for ARIs are being used in clinical practice, as well as new developments in the research pipeline. METHODS: A limited search was conducted of the relevant literature, with emphasis placed on literature published in the last 5 years (2014-2019). FINDINGS: Advances are being made in all areas of host response-based diagnostics for ARIs. Specifically, there has been significant progress made in single protein biomarkers, as well as in various "omics" fields (including proteomics, metabolomics, and transcriptomics) and wearable technologies. There are many potential applications of a host response-based approach; a few key examples include the ability to discriminate bacterial and viral disease, presymptomatic diagnosis of infection, and pathogen-specific host response diagnostics, including modeling disease progression. IMPLICATIONS: As biomarker measurement technologies continue to improve, host response-based diagnostics will increasingly be translated to clinically available platforms that can generate a holistic characterization of an individual's health. This knowledge, in the hands of both patient and provider, can improve care for the individual patient and help fight rising rates of antibiotic resistance.
Authors: Zoran Stojanovic; Filipe Gonçalves-Carvalho; Alicia Marín; Jorge Abad Capa; Jose Domínguez; Irene Latorre; Alicia Lacoma; Cristina Prat-Aymerich Journal: ERJ Open Res Date: 2022-09-12
Authors: Emily C Lydon; Ricardo Henao; Thomas W Burke; Mert Aydin; Bradly P Nicholson; Seth W Glickman; Vance G Fowler; Eugenia B Quackenbush; Charles B Cairns; Stephen F Kingsmore; Anja K Jaehne; Emanuel P Rivers; Raymond J Langley; Elizabeth Petzold; Emily R Ko; Micah T McClain; Geoffrey S Ginsburg; Christopher W Woods; Ephraim L Tsalik Journal: EBioMedicine Date: 2019-10-17 Impact factor: 8.143