Breath analysis is emerging as a powerful non-invasive strategy to advance biomarker detection. Using advanced separation science technologies, researchers can now identify trace volatile organic compounds (VOCs) in exhaled breath that signal infection, providing new tools to safeguard global health through improved biomarker data analysis.
This article is based on insights shared during the webinar "Making Our World a Safer Place Through Science: Identifying Novel Biomarkers of COVID-19 in Breath," which featured expert perspectives from Dr. Amalia Berna of the Children's Hospital of Philadelphia and Matthew Edwards of SepSolve Analytical.
Drawing on their contributions, this article outlines the analytical workflow used to analyze VOCs in pediatric breath samples, highlighting key instrumentation and software innovations, and exploring how these expert-led strategies are shaping the future of non-invasive biomarker detection.
Unlocking Insights from Exhaled Breath
Exhaled breath contains a rich mix of volatile organic compounds (VOCs) that reflect underlying metabolic processes, offering a non-invasive snapshot of health or disease. With over 800 VOCs identified in breath, detecting relevant biomarkers is a significant challenge. Many target compounds appear only at trace levels, requiring high analytical sensitivity, precise separation, and advanced data handling to extract meaningful insights.
This challenge is especially significant in pediatric populations. As Dr. Amalia Berna notes, children often exhibit mild or asymptomatic responses to infections, making traditional diagnostics less effective. Breath-based biomarker detection, therefore, offers a non-invasive, child-friendly alternative that supports rapid screening, particularly when paired with robust biomarker data analysis capable of resolving and interpreting complex chemical profiles.
Biomarker Detection in Action: A COVID-19 Breath Study
Translating breath into diagnostic insight requires a carefully designed analytical pipeline. Berna describes a real-world clinical study conducted at the Children's Hospital of Philadelphia that exemplifies this approach.
In the study, breath samples were collected from children aged 4–20 years who tested either positive or negative for SARS-CoV-2. The goal was to identify reliable volatile biomarkers of COVID-19 that could be detected non-invasively.
Dr. Berna describes a four-part analytical workflow designed to collect, stabilize, and analyze pediatric breath samples for VOC profiling.
Key Steps in Breath-Based Biomarker Detection:
Collect exhaled breath into sorbent tubes
Stabilize samples with diffusion-locking caps
Analyze using thermal desorption, comprehensive two-dimensional gas chromatography, and time-of-flight mass spectrometry (TD–GC×GC–TOF-MS).
Apply ChromCompare+ for feature discovery and data alignment.
Together, these steps formed a streamlined workflow that ensured sample integrity, high-resolution separation, and data-rich analysis, laying the foundation for biomarker validation and discovery.
To strengthen its reliability, the team introduced several key innovations: diffusion locking technology safeguarded samples during transport, dry purging removed moisture without compromising VOC content, and split recollection allowed for partial sample retention to support reanalysis or further validation.
These additions enabled full automation and consistency across the study cohort. "We designed the workflow to be not just high-performing, but also fully automated and reproducible," says Edwards. "That's essential for any clinical study."
Ultimately, this approach yielded a validated panel of six VOCs, mainly aldehydes, that could distinguish between COVID-positive and COVID-negative children. When tested in a second cohort, the model achieved 91% sensitivity and 84% accuracy, demonstrating the promise of breath-based biomarker detection.
Optimizing Separation and Instrumentation in Biomarker Detection
Effective biomarker detection in complex matrices, such as breath, requires exceptional separation power. Breath samples contain hundreds of volatile compounds, many of which have overlapping retention characteristics that challenge conventional one-dimensional GC–MS analysis. "One-dimensional GC–MS just can't resolve everything," explains Edwards. "When you're looking for low-abundance compounds in a matrix like breath, coelution is almost guaranteed without a second dimension."
To address this, GC×GC employs orthogonal separations, first by volatility and then by polarity, creating structured chromatograms that facilitate the differentiation of compound classes and enhance confidence in biomarker identification.
Reverse fill/flush flow modulation enhances this system by delivering sharp peaks without the need for consumables, enabling reliable analysis across a broad range of volatilities. Coupling this with TOF-MS provides femtogram-level sensitivity and a wide linear dynamic range, supporting untargeted screening of trace biomarkers.
Further improving analytical confidence, the team implemented tandem ionization, which produces both high-energy and soft ionization spectra in a single run. This dual output improves isomer discrimination and reduces false positives. "Tandem ionization gives you two complementary views of every compound in one run," adds Edwards. "It dramatically improves confidence when you're trying to identify unknown biomarkers."
Solving Data Complexity with Smart Analysis Tools
With the instrumental workflow yielding a high-resolution VOC profile, the next challenge is extracting meaningful insights from the resulting data. Edwards underscores the importance of robust data analysis tools that can align and compare complex datasets across large cohorts.
In this study, the team used ChromCompare+ to align data and apply statistical methods such as:
- Principal component analysis (PCA) to visualize group separation
- Volcano plots to identify statistically significant features
- Feature discovery tools to isolate key biomarkers among >1 million data points
This streamlined biomarker data analysis enabled the team to refine their dataset to a validated panel with high sensitivity and accuracy, an essential foundation for diagnostic confidence in fast-moving public health settings.
Implications and Future Applications for Biomarker Detection
Edwards notes that the team is exploring how these findings can be translated into portable breath screening technologies that could broaden accessibility and impact. "The ultimate goal is to bring this kind of analysis out of the lab and into the field," he says. "We want to make non-invasive testing widely accessible, especially in public health settings."
To support this vision, the breath biomarker detection approach is now being extended to:
- Other respiratory viral infections to assess biomarker specificity
- Biological mechanism studies to trace metabolite origins
- Extended COVID diagnostics, exploring post-infection breath profiles
- Multisystem inflammatory syndrome in children (MIS-C) (biomarker detection under NIH funding)
Each new application benefits from foundational advances in biomarker data analysis, which guide reproducibility, sensitivity, and diagnostic confidence.
Charting the Future of Breath-Based Diagnostics
The use of advanced analytical platforms for breath VOC profiling represents a significant step forward in pediatric diagnostics. By combining thermal desorption, GC×GC, TOF-MS, and data analysis, researchers can confidently identify hidden biomarkers.
These findings demonstrate the potential of combining biomarker detection with advanced analytical workflows, offering real-world applications for rapid, non-invasive infection screening in pediatric care. As Edwards notes, continued development of breath-based diagnostics could help public health agencies respond more rapidly to emerging infectious threats while reducing the burden on traditional testing systems.
Meet the Experts
Dr. Amalia Berna is a senior research scientist in the Department of Pediatrics at the Children's Hospital of Philadelphia. With a PhD from the Catholic University of Leuven, Belgium, she has extensive experience in volatile organic compound (VOC) profiling and breath analysis. Her work focuses on identifying breath-based biomarkers for infectious and non-infectious diseases in children.
Matthew Edwards is the Business Development Manager for the Americas at SepSolve Analytical. Based in Waterloo, Ontario, he specializes in multidimensional chromatography and mass spectrometry, and is instrumental in bringing advanced analytical solutions to clinical and research laboratories across the Americas.