Parkinson’s disease (PD) is the second most prevalent neurodegenerative disease, with an increasing incidence in recent years due to the aging population. Genetic mutations alone only explain <10% of PD cases, while environmental factors, including small molecules, may play a significant role in PD. In the present work, 22 plasma (11 PD, 11 control) and 19 feces samples (10 PD, 9 control) were analyzed by non-target high-resolution mass spectrometry (NT-HRMS) coupled to two liquid chromatography (LC) methods (reversed-phase (RP) and hydrophilic interaction liquid chromatography (HILIC)). A cheminformatics workflow was optimized using open software (MS-DIAL and patRoon) and open databases (all public MSP-formatted spectral libraries for MS-DIAL, PubChemLite for Exposomics, and the LITMINEDNEURO list for patRoon). Furthermore, five disease-specific databases and three suspect lists (on PD and related disorders) were developed, using PubChem functionality to identifying relevant unknown chemicals. The results showed that non-target screening with the larger databases generally provided better results compared with smaller suspect lists. However, two suspect screening approaches with patRoon were also good options to study specific chemicals in PD. The combination of chromatographic methods (RP and HILIC) as well as two ionization modes (positive and negative) enhanced the coverage of chemicals in the biological samples. While most metabolomics studies in PD have focused on blood and cerebrospinal fluid, we found a higher number of relevant features in feces, such as alanine betaine or nicotinamide, which can be directly metabolized by gut microbiota. This highlights the potential role of gut dysbiosis in PD development.
Awareness of the exposome and its influence on health has increased in the last decade. As past exposures can cause changes in human health many years later, delving into the past is relevant for both diagnostic and prevention purposes, but remains a challenging task. Lifestyle, diet and socioeconomic information of the past should be well documented and compatible with modern data science methods. While chemical analysis nowadays makes use of High Resolution Mass Spectrometry (HR-MS) for highly sensitive and comprehensive coverage of samples plus retrospective analysis, these data archives are in the very early stages. Since past measurements are often only available for a limited set of chemicals, adding to this knowledge requires careful selection of sample types and sampling sites, which may not always be available. The choice of analytes and analytical methods should be suitable for the study question—which is not always clear in advance in exposomics. Data interpretation and the use of appropriate databases are indispensable for a proper exposure assessment, and as databases and knowledge grow, re-analysis of physically or digitally archived samples could enable “continuous monitoring” efforts. This review focusses on the chemical analytical approaches necessary to capture the complexity of the historical exposome. Various sample types, analytes as well as analyses and data interpretation methods are discussed in relation to chemical exposures, while the connection to health remains in focus. It ends with perspectives and challenges in assessing the historical exposome, discussing how we can “learn from the past” to build a better future.
R achel Carson's Silent Spring, 1 published just more than 60 years ago, outlined how the indiscriminate use of dichlorodiphenyltrichloroethane (DDT), a potent, environmentally persistent insecticide, was damaging the world's ecosystems, animals, and food supply. There were many other chemicals more persistent than DDT accumulating in the environment when Carson was writing, including per-and polyfluoroalkyl substances (PFAS). While man-made, PFAS were not intended to cause harm, contrary to pesticides such as DDT. Today, ambient PFAS levels are contaminating rain, soil, and drinking water resources worldwide to such an extent that they have caused substantial, irreversible health and environmental damage. 2 Like DDT, PFAS had long been in use by the time Rachel Carson was writing Silent Spring (see Figure 1). However, their environmental presence went unnoticed by Carson and other contemporary environmental researchers. PFAS were entering the environment under the radar, except to those who were manufacturing and emitting them. 3
Background Non-target screening of surface water samples collected over an extended period can reveal interesting temporal patterns in exposome-related pollutants. Additionally, geographical data on pollution sources close to the sampling sites, chemical classification data and the consideration of flow paths can provide valuable information on the origins and potential threat of tentatively identified chemical compounds. In this study, 271 surface water samples from 20 sampling sites across Luxembourg were analysed using high resolution mass spectrometry, complementing routine target monitoring efforts in 2019–2022. Data analysis was performed using the open source R-package patRoon, which offers a customizable non-target workflow. By employing open source workflows featuring scoring terms, like spectral match and applying identification levels, tentative identifications can be prioritized, e.g. based on spectral similarity. Furthermore, by utilizing supplementary database information such as PubChemLite annotation categories and classification software such as classyFire, an overall assessment of the potential threats posed by the tentatively identified chemicals was conducted, enabling the prioritization of chemicals for future confirmation through targeted approaches. Results The study tentatively identified 375 compounds associated with the exposome including benzenoids, organoheterocyclic compounds, and organic phosphoric acids and derivatives (12 classyFire superclasses, 50 sub-classes). The classification analysis not only revealed temporal variations in agrochemicals, with the majority of identifications occurring in May to July, but also highlighted the prevalence of pharmaceuticals such as venlafaxine in surface waters. Furthermore, potential sources of pollutants, like metallurgic industry or household products were explored by considering common uses and geographical information, as commercial uses of almost 100% of the identified chemicals are known. 41 chemicals were suggested for potential inclusion to governmental monitoring lists for further investigation. Conclusions The findings of this study complement existing knowledge on the pollution status of surface water in Luxembourg and highlight the usefulness of non-target screening for identifying temporal and spatial trends in pollutant levels. This approach, performed in a complementary manner to routine monitoring, can help to tentatively identify chemicals of concern for potential inclusion in target monitoring methods following additional confirmation and quantification efforts.
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