Content area

Abstract

Breath analysis is a relatively recent field of research with much promise in scientific and clinical studies. Breath contains endogenously produced volatile organic components (VOCs) resulting from metabolites of ingested precursors, gut and air-passage bacteria, environmental contacts, etc. Numerous recent studies have suggested changes in breath composition during the course of many diseases, and breath analysis may lead to the diagnosis of such diseases. Therefore, it is important to identify the disease-specific variations in the concentration of breath to diagnose the diseases. In this review, we explore methods that are used to detect VOCs in laboratory settings, VOC constituents in exhaled air and other body fluids (e.g., sweat, saliva, skin, urine, blood, fecal matter, vaginal secretions, etc.), VOC identification in various diseases, and recently developed electronic (E)-nose-based sensors to detect VOCs. Identifying such VOCs and applying them as disease-specific biomarkers to obtain accurate, reproducible, and fast disease diagnosis could serve as an alternative to traditional invasive diagnosis methods. However, the success of VOC-based identification of diseases is limited to laboratory settings. Large-scale clinical data are warranted for establishing the robustness of disease diagnosis. Also, to identify specific VOCs associated with illness states, extensive clinical trials must be performed using both analytical instruments and electronic noses equipped with stable and precise sensors.

Details

Title
Smelling the Disease: Diagnostic Potential of Breath Analysis
Author
Sharma, Anju 1 ; Kumar, Rajnish 2 ; Varadwaj, Pritish 1 

 Systems Biology Lab, Indian Institute of Information Technology, Allahabad, Uttar Pradesh, India 
 Amity Institute of Biotechnology, Amity University Uttar Pradesh, Uttar Pradesh, Lucknow Campus, Lucknow, India 
Pages
321-347
Section
REVIEW ARTICLE
Publication year
2023
Publication date
May 2023
Publisher
Springer Nature B.V.
ISSN
11771062
e-ISSN
11792000
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2809205961
Copyright
Copyright Springer Nature B.V. May 2023