Introduction: 

A human biomonitoring dataset contains measurement data for endogenous and exogenous compounds.  Targeted and untargeted metabolomics, lipidomics and exposomics datasets can contain thousands of chemicals. These chemicals have functional, biochemical and chemical relationships, leading to correlations among their levels. A correlation observed between two chemicals detected in a human biospecimen can be interpreted in terms of : 

1.  co-exposure : both chemicals are toxic co-exposures but routes can be multiples, such as PFAS and pesticides. 

2.  co-origin : chemicals are from the same known origin (such as PUFAs and PFAS can originate from fish intake) but no shared toxicity

3.  co-metabolism : chemicals are from same metabolic pathways or reaction - such as sulfonation

4.  direct-metabolite : direct substrate-product relationship

5.  metabolic-response : one of the chemical is a metabolic response 

6.  toxicity-marker : one of the chemicals is a known toxicity biomarker

In this exercise, we will go through the correlations that are observed between exposome chemical and other chemicals detected in human biomonitoring datasets. 

1) Exposome Correlation and Interpretation Database (ECID)

-ECID is a NIEHS (U24) funded Biomedical Knowledgebase

-Introduction to www.ecidbase.org and a walk-through the major functions

2) Example Metabolomic Datasets

Download the example data files from the Kidney Precision Medicine Project ( https://www.kpmp.org/ ) at this Zenodo entry https://zenodo.org/records/22558616   : 

Direct links: 

• Blood https://zenodo.org/records/22558616/files/KPMP-B-2024_input.xlsx?download=1    

• Urine https://zenodo.org/records/22558616/files/KPMP-U-2024_input.xlsx?download=1   

• Stool https://zenodo.org/records/22558616/files/KPMP-S-2024_input.xlsx?download=1    

3) Google Colab Notebook

Go to  https://colab.research.google.com/drive/1Vhn-5IaxAXjqNWuyGFbXqiGaMQE1fgrR?usp=sharing