The Efficacy of Py-GC–MS in the Microplastic Analysis of Human Blood

A recent study evaluated the suitability of pyrolysis–gas chromatography-mass spectrometry (Py-GC–MS) for detecting and quantifying micro- and nanoplastics (MNPs) in human blood. A new extraction protocol was developed to reduce false positives for polyethylene (PE) and polyvinyl chloride (PVC). Recovery rates varied from 7% to 109%, with surface-modified polystyrene improving nanoparticle recovery. Realistic detection limits were calculated, showing they were up to 20 times higher than those in Milli-Q water. LCGC International spoke to Cassandra Rauert of the Queensland Alliance for Environmental Health Sciences at The University of Queensland (Woolloongabba, Australia), corresponding author for the paper resulting from this study, about her team’s work.

Your study and the resulting paper (1) assessed the appropriateness of pyrolysis–gas chromatography-mass spectrometry (Py-GC–MS) analysis for the quantification of a range of polymers in human blood. Where are these polymers coming from and how do they enter the bloodstream?

We are exposed to micron-sized and nano-sized plastics every day. They are in the food we eat, liquids we drink, and air we breathe and can be in the personal care products we use. However, there is still very little understanding of the biological fate of microplastics and nanoplastics following this exposure. We are still lacking evidence of how even the smallest of nanoparticles can cross biological barriers (for example the gastrointestinal tract-blood barrier) to enter the bloodstream. Human biomonitoring studies (analyzing blood, tissue, and so forth for the presence of these plastics) will help with understanding this, however reliable analytical methods are needed to report this data. This study aimed to assess if the increasingly applied plastics analysis methodology of pyrolysis coupled with GC–MS (Py-GC–MS) is appropriate for human biomonitoring studies or not and showed there are many limitations and challenges with this methodology.

Are there any specific known threats to the human body that are due to, or increased with, the presence of polymers in blood?

We still need more data (and repeated studies) to be confident that polymers do end up in the bloodstream and we have very limited data on potential health effects. However, we do know that the chemicals used in plastics do end up in the bloodstream and there are many known adverse health effects of these endocrine disruptors. So, the story is complicated, it is not just the physical particles we are exposed to but also the chemicals inside these particles.

In your paper, you state “Py-GC–MS, even as an environmental monitoring tool for micro- and nanosized plastics (MNPs) pollution, is still in its infancy and these techniques are employed without fully understanding, or assessing, their uncertainties.” Can you expand on this?

Py-GC–MS is a powerful technique for quantifying and identifying plastics however, as with all analytical techniques, there are limitations as to the information that it can provide. For Py-GC–MS, the main challenge stems from the fact that it is an indirect analysis technique. This means that it doesn’t analyze the plastics directly, it analyses the thermal breakdown products of the plastics (small organic molecules). The challenge arises if there is another compound in the sample that will break down into these same organic molecules. This will provide a false positive for a plastic and as it is the same compound cannot be removed analytically. A good example of this is polyethylene (PE) and lipids/fats. Both molecules are long-chain hydrocarbons and when pyrolyzed, both form the same series of short-chain alkyl compounds. So, if you have fat in your sample (the case for most biological samples), it will ‘look like’ PE and give a false positive for PE. This needs to be further assessed and limitations with all plastics need to be assessed.

How did you work around this in your analysis?

For the example of PE and lipid interferences, we tested a range of developed extraction methods to try and remove the lipid before analysis. There were still trace levels present, so we developed a quality control process for the analytical data instead to tell us if we were looking at PE or an interference. This method is straightforward for analytical chemists and could be adopted by all labs using Py-GC–MS.

Briefly summarize your findings that you discuss in your article and the conclusions you came to after reviewing these findings.

Matrix interferences can be significant in complex matrices and these need to be considered before reporting human biomonitoring data of micro and nanoplastics, to ensure reliability of the data being reported. Secondly, background contamination is a major challenge in all micro and nanoplastics studies and control measures need to be applied and reported appropriately. Thirdly recovery tests (adding plastics to a sample and determining how much is recovered after the sample is processed) are critical for validating methods and assessing if detection limits of the extraction + analysis method prevent biologically plausible concentrations from being detected.

What were the advantages associated with using Py-GC–MS in your study as opposed to other techniques?

Py-GC–MS has many advantages. It is not limited by the size of the plastic particle. It is a mass-spectrometry-based method for identification and quantification which increases the accuracy of identification over library matching. It is a great technique for quantification of many different plastics, but this will be dependent on the matrix being analyzed.

Do you anticipate similar results in using your technique for detecting polymers in other bodily fluids or organs?

Yes, one of the key outcomes of the manuscript was that with current sample processing methods, this technique is not suitable for the quantification of PE or polyvinyl chloride (PVC) in biological matrices. If extraction methods are advanced to reliably remove potential interferences (for example lipids) before analysis this would improve though.

What difficulties did you encounter in your work, specifically sampling and data interpretation challenges?

Developing the protocols for quality control of the data is time-consuming (but necessary). Finding a balance between the number of sample processing steps to remove or reduce interferences and recovery of the particles was also challenging.

How did you process the chemometric data to obtain the results you were looking for?

With the Py-GC–MS system, calibration curves are built from the analysis of pure polymers. The pyrolysis products (breakdown products) are monitored and used to then back-calculate the concentration of the polymer that was in the original sample. We monitor a range of pyrolysis products for each plastic and look at the ratio of the calculated concentration of each. This ratio will change (considerably) if an interference is forming these pyrolysis products rather than the plastic. This is one of the quality control checks we apply to all our data to determine if we are detecting plastic or not.

Were there any factors that might affect the accuracy of your findings?

There is always the possibility of additional matrix interferences affecting other plastics that we are not yet aware of. That is why we need to keep assessing our analytical methods and their suitability for every matrix being studied.

How do you imagine the results of your study can/will be more broadly applied?

The quality control protocols employed to check for PE and PVC interferences can be applied in all studies using Py-GC–MS. We hope this study will lead to further consideration/checks of human biomonitoring data being reported and hopefully improve the reliability of data for regulators and policymakers.

Are there any next steps in this research?

We are currently assessing a range of different biological tissues to assess potential interferences, develop methods to remove or reduce them, assess method recoveries, calculate appropriate detection limits for these tissues, and assess if it is biologically plausible for these concentrations to be present in these matrices.

Reference

1. Rauert, C.; Charlton, N.; Bagley, A.; Dunlop, S. A.; Symeonides, C.; Thomas, K. V. Assessing the Efficacy of Pyrolysis-Gas Chromatography-Mass Spectrometry for Nanoplastic and Microplastic Analysis in Human Blood. Environ. Sci. Technol. 2025, 59 (4), 1984–1994. DOI: 10.1021/acs.est.4c12599

Cassandra Rauert is a Senior Research Fellow at the Queensland Alliance for Environmental Health Sciences (QAEHS) at the University of Queensland (Woolloongabba, Australia). Her current research focusses on human and environmental exposure to micro and nanoplastics. Cassandra is the plastics research lead in the Minderoo Centre – Plastics and Human Health.