# Exhaled Breath Analysis in Lymphangioleiomyomatosis by Real-Time Proton Mass Spectrometry

## TL;DR

This study uses breath analysis to identify chemical markers for a rare lung disease called LAM, offering a non-invasive diagnostic tool.

## Contribution

The first evidence that exhaled breath VOCs can diagnose LAM and predict its complications using real-time proton mass spectrometry.

## Key findings

- VOCs like lactic acid and methanethiol were identified as potential biomarkers for LAM and its complications.
- A classifier using these VOCs achieved high diagnostic accuracy (AUC = 0.922).
- The VOCs correlated with clinical features like pneumothorax and lung cysts.

## Abstract

Lymphangioleiomyomatosis (LAM) is a rare progressive disease that affects women of reproductive age and is characterized by cystic lung destruction, airflow obstruction, and lymphatic dysfunction. Current diagnostic methods are costly or lack sufficient specificity, highlighting the need for novel non-invasive approaches. Exhaled breath analysis using real-time proton mass spectrometry (PTR-MS) presents a promising strategy for identifying disease-specific volatile organic compounds (VOCs). This cross-sectional study analyzed exhaled breath samples from 51 LAM patients and 51 age- and sex-matched healthy controls. PTR-time-of-flight mass spectrometry (PTR-TOF-MS) was employed to identify VOC signatures associated with LAM. Data preprocessing, feature selection, and statistical analyses were performed using machine learning models, including gradient boosting classifiers (XGBoost), to identify predictive biomarkers of LAM and its complications. We identified several VOCs as potential biomarkers of LAM, including m/z = 90.06 (lactic acid) and m/z = 113.13. VOCs predictive of disease complications included m/z = 49.00 (methanethiol), m/z = 48.04 (O-methylhydroxylamine), and m/z = 129.07, which correlated with pneumothorax, obstructive ventilation disorders, and radiological findings of lung cysts and bronchial narrowing. The classifier incorporating these biomarkers demonstrated high diagnostic accuracy (AUC = 0.922). This study provides the first evidence that exhaled breath VOC profiling can serve as a non-invasive additional tool for diagnosing LAM and predicting its complications. These findings warrant further validation in larger cohorts to refine biomarker specificity and explore their clinical applications in disease monitoring and personalized treatment strategies.