The chemical exposome is the cumulative sum of environmental chemical exposures over an individual’s lifespan, including pollution, dietary substances, and the metabolic products of gut microbiota. Specific environmental chemicals are known to influence health and disease risk, but overall knowledge has advanced too slowly due to a previous focus on a limited number of targeted chemicals and the large volumes of blood required for sensitive analyses. Measurement of the chemical exposome in blood is strategic due to the simultaneous presence of dietary substances, drugs and environmental contaminants, as well as endogenous molecules whose profiles may be impacted by such exposures. To facilitate routine chemical exposomics in health studies, trace analytical methods for small volumes of blood are needed that can quantify a wide range of multiclass target analytes, while also discovering unexpected chemicals in a complex matrix dominated by endogenous molecules. Recognizing that our environment is dynamic, and that human susceptibility to disease changes over the life course, the exposome has always been envisaged as a parameter requiring repeated measures over time. However, fundamental questions remain on the longitudinal stability of the chemical exposome, including its relative stability compared to other omic profiles routinely measured in health studies today. 

The foundation of this doctoral thesis is a chemical exposomics analytical workflow, involving: a sample preparation method for ≤ 200 µL of human blood plasma that minimizes endogenous interferences, a combined targeted/untargeted liquid chromatography-high resolution mass spectrometry (LC-HRMS) acquisition, and a data processing workflow with open science tools to discover and annotate hundreds of small molecules in large datasets. Workflow applications in Swedish cohorts are also demonstrated, including the first cohort-scale application of longitudinal exposomics in blood. 

In Paper I, the selective removal of high abundance phospholipids from plasma enabled the sensitive and quantitative multiclass targeted analysis of 83 priority analytes. In untargeted acquisition, 109 and 28% more non-phospholipid molecular features in positive and negative mode, respectively, were detected with the new method compared to a control method without phospholipid removal. In Paper II, the same method was applied to a longitudinal multiomic wellness cohort, resulting in 519 confident molecular annotations, including novel exposures and correlated co-exposures (i.e. mixtures). A data resource containing the longitudinal stabilities for hundreds of environmental molecules in blood over 2 years revealed that the chemical exposome has low stability compared to other omic profiles in the same individuals, thereby urging repeated exposome measurement in future studies. In Paper III the workflow was applied to plasma from 100 healthy women in a pilot study for exposome and breast cancer, revealing associations between known and unknown chemicals and breast cancer risk factors. Overall, this thesis provides a powerful workflow for plasma chemical exposomics that can be applied at cohort-scale, and the combined products of this thesis will contribute to the design and execution of future exposome studies.