Breath can discriminate tuberculosis from other lower respiratory illness in children

Abstract

Pediatric tuberculosis (TB) remains a global health crisis. Despite progress, pediatric patients remain difficult to diagnose, with approximately half of all childhood TB patients lacking bacterial confirmation. In this pilot study (n = 31), we identify a 4-compound breathprint and subsequent machine learning model that accurately classifies children with confirmed TB (n = 10) from children with another lower respiratory tract infection (LRTI) (n = 10) with a sensitivity of 80% and specificity of 100% observed across cross validation folds. Importantly, we demonstrate that the breathprint identified an additional nine of eleven patients who had unconfirmed clinical TB and whose symptoms improved while treated for TB. While more work is necessary to validate the utility of using patient breath to diagnose pediatric TB, it shows promise as a triage instrument or paired as part of an aggregate diagnostic scheme.

Breath biomarkers of insulin resistance in pre-diabetic Hispanic adolescents with obesity

“…These two analytes were previously reported from human metabolomics studies but were never quantified 46 . Similar hydrocarbon metabolites were reported as oxidative stress markers of disease in exhaled breath related to infectious disease 15 , heart disease 52,53 , psychiatric disease 54 , and cancer 55 . This mechanism involves hydrocarbons being triggered or released in to the breath by ROS, a form of oxygen with a reactive electron from the by-product of oxidation metabolism in the mitochondria.…”

“…Although the other six breath metabolites did not reach significance between the groups individually (Supplementary Figure S5), their contribution to the breath-IR model is evident when assessing the diagnostic capability of the model (Figure 5) to identify individuals with IR. A combined signature of breath metabolites is clearly more informative than using a single metabolite which may be indicative of some normal variability in metabolites within and between individuals 15,19,42 .…”

“…All statistical analyses were conducted in R 4.0.3 (R Core Team, Vienna, Austria) 23 . Data cleaning was performed as described 14,15 . In short, a frequency of observation (FOO) cut-offs of 80% was implemented to remove sparse features.…”

“…to identify individuals with IR. A combined signature of breath metabolites is clearly more informative than using a single metabolite which may be indicative of some normal variability in metabolites within and between individuals 15,19,42 .…”

“…The copyright holder for this preprint this version posted June 30, 2021. ; https://doi.org/10.1101/2021.06.23.21259399 doi: medRxiv preprint Non-invasive sampling, such as exhaled breath, provides metabolic information that may be indicative of an individual's health status. Exhaled breath metabolites have been reported in the assessment of infection 14,15 , cognition 16 , metabolic disease 17 , and lifestyle 18 . These studies provide evidence that metabolic markers, which strongly correlate with metabolic dysregulation, can be identified in breath samples.…”