A Study to Develop a Breath Analysis Test

Overview

About this study

The purposes of this study are to establish breath sample collection and analysis techniques, to establish reference ranges for selected clinical populations, and to assess correlations between breath analysis and presence or absence of clinical or pathological evidence of disease.

Participation eligibility

Participant eligibility includes age, gender, type and stage of disease, and previous treatments or health concerns. Guidelines differ from study to study, and identify who can or cannot participate. There is no guarantee that every individual who qualifies and wants to participate in a trial will be enrolled. Contact the study team to discuss study eligibility and potential participation.

Inclusion Criteria:

Subjects 18 years or older.
Able to provide informed consent.

Exclusion Criteria:

None.

Participating Mayo Clinic locations

Study statuses change often. Please contact the study team for the most up-to-date information regarding possible participation.

Mayo Clinic Location	Status	Contact
Jacksonville, Fla. Mayo Clinic principal investigator Tushar Patel, M.B., Ch.B.	Open for enrollment	Contact information: Lori Chase B.S., CCRP Chase.Lori@mayo.edu

Mayo Clinic Location

Status

Contact

Jacksonville, Fla.

Mayo Clinic principal investigator

Tushar Patel, M.B., Ch.B.

Open for enrollment

Contact information:

Lori Chase B.S., CCRP

Chase.Lori@mayo.edu

More information

Publications

Disease-related effects on hepatic metabolism can alter the composition of chemicals in the circulation and subsequently in breath. The presence of disease related alterations in exhaled volatile organic compounds could therefore provide a basis for non-invasive biomarkers of hepatic disease. This study examined the feasibility of using global volatolomic profiles from breath analysis in combination with supervised machine learning to develop signature pattern-based biomarkers for cirrhosis. Breath samples were analyzed using thermal desorption-gas chromatography-field asymmetric ion mobility spectroscopy to generate breathomic profiles. A standardized collection protocol and analysis pipeline was used to collect samples from 35 persons with cirrhosis, 4 with non-cirrhotic portal hypertension, and 11 healthy participants. Molecular features of interest were identified to determine their ability to classify cirrhosis or portal hypertension. A molecular feature score was derived that increased with the stage of cirrhosis and had an AUC of 0.78 for detection. Chromatographic breath profiles were utilized to generate machine learning-based classifiers. Algorithmic models could discriminate presence or stage of cirrhosis with a sensitivity of 88-92% and specificity of 75%. These results demonstrate the feasibility of volatolomic profiling to classify clinical phenotypes using global breath output. These studies will pave the way for the development of non-invasive biomarkers of liver disease based on volatolomic signatures found in breath. Read More on PubMed

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