Data-driven characterisation of genetic variability in disease pathways and pesticide-induced nervous system disease

17/05/2024

The study highlights the importance of the integration of spatial and genetic data for the prediction of at-risk populations and the guidance of future research and policy. Publication in "Environ Health Perspect"

Pesticide association rules in the 10 high-probability and 10 low-probability states in 1992–2018. High-probability state indicates high disease occurrence and more SNP hits per pesticide per year, and low-probability state indicates low disease occurrence and fewer SNP hits per pesticide per year - https://doi.org/10.1289/EHP14108.
"Our findings support that pesticides contribute to nervous system disease, and we developed priority lists of SNPs, pesticides, and pathways for further study. This data-driven approach can be adapted to other chemicals, diseases, and locations to characterize differential population susceptibility to chemical exposures", Dr. Philipp Antczak (CMMC, University of Cologne); co-author of the study comments.

Chronic human diseases often result from interactions between genetics and environmental factors. There are numerous environmental factors that need to be considered and as such genome-wide association studies (GWAS) have rarely included such factors in their analyses. Environmental factors can range from an individual’s lifestyle to the geographic location in which they live, to all the chemicals and other stressors they are exposed as a result. This highly complex interplay between these factors and the underlying genetics presents a unique challenge, particular when considering, particularly, chemical risk assessment (RA).

Traditional RA approaches tend to evaluate chemicals on a one-by-one basis and follow a one-size-fits-all approach by utilizing arbitrary safety factors that aim to include all individuals. However, over the past several years, there has been a paradigm shift towards the inclusion of new approach methodologies, such as molecular characterizations and in-depth evaluations of chemical mixtures in these regulatory fields, with the objective of ensuring the safety of all individuals.

In a recently published study in Environ Health Perspect by Marissa B. Kosnik, Philipp Antczak and Peter Frantke presents a data-driven characterization of genetic variability in disease pathways and pesticide-induced nervous system disease in the United States population. The study is titled "Data-Driven Characterization of Genetic Variability in Disease Pathways and Pesticide-Induced Nervous System Disease in the United States Population (DOI: 10.1289/EHP14108)". The authors further developed a previously established framework for linking chemicals, single nucleotide polymorphisms (SNPs), and diseases. This framework employs a toxicity pathway-based approach to identify potential associations that extend beyond the information available in each of the datasets.To showcase its application, the authors focused on developing an understanding of the impacts of chemical pesticide use on common nervous system diseases like Alzheimer’s, multiple sclerosis, and Parkinson’s disease in the US.

By creating these intricate associations, the authors were able to identify correlative links between pesticide use, and more specifically the variability of pesticides applied, and their impact on nervous system diseases, also considering potential differences in vulnerability in the human population toward these pesticides.

While the authors made it clear that their findings are preliminary and require further validation it highlights the power of data re-use and integration to assess human health in a wider context.

“Our models developed in this study focused on generating associations between human nervous system diseases and pesticide usage patterns in the United States. The results that there seems to be a clear correlation for several of these associations.With genetic data from each state, we could now develop an individual risk scores based on our research, which would provide individual risk profiles and potentially reduce the occurrence of these diseases.” says Dr. Philipp Antczak, co-authors of the study, who is leading a research group at the Center for Molecular Medicine Cologne (CMMC) at the University of Cologne.

The study underscores the significance of risk assessment in the context of a complex chemical environment and presents methodologies for the utilization of the extensive data that has already been collected. This can assist in developing a more comprehensive understanding of the interrelationship between the created environment and human health, which will be invaluable in ensuring healthy living for all.

Contact
Dr. Phillip Antczak
Center for Molecular Medicine Cologne - University of Cologne
pantczak[at]uni-koeln.de
 

Publication
Data-Driven Characterization of Genetic Variability in Disease Pathways and Pesticide-Induced Nervous System Disease in the United States Population -  Environ Health Perspect. 2024 May; 132(5): 057003. Published online 2024 May 16. doi: 10.1289/EHP14108

  • Marissa B. Kosnik- Quantitative Sustainability Assessment, Dept. of Environmental and Resource Engineering, Technical University of Denmark, Kgs. Lyngby, Denmark and Dept. of Environmental Toxicology, Swiss Federal Institute of Aquatic Science and Technology, Dübendorf, Switzerland
  • Philipp Antczak - Faculty of Medicine and Cologne University Hospital, Center for Molecular Medicine Cologne, University of Cologne, Cologne, Germany
  • Peter Fantke - Quantitative Sustainability Assessment, Dept. of Environmental and Resource Engineering, Technical University of Denmark, Kgs. Lyngby, Denmark

 

 

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