Aims Chronic pain affects 10–40% of the population and is expected to increase in aging societies. This project leverages the EpiHealth cohort to explore whether interactions between genetic predispositions and environmental exposures (the exposome) contribute to the development of chronic pain. Background Pain is among the top five global causes of years lived with disability. In Sweden, about 18% of the population experiences chronic pain, with 5–10% suffering from chronic widespread pain (CWP). While chronic localized pain (CLP) is often linked to specific injuries or diseases, CWP is associated with dysfunctional endogenous pain modulation. Genetic factors play a significant role in CWP, with heritability estimates ranging from 30–70%. Several single nucleotide polymorphisms (SNPs) have been implicated in pain modulation pathways. Despite many psychosocial factors being associated with both CLP and CWP, little is known about the environmental component. Emerging evidence suggests neuroimmune interactions and gut microbiome alterations, triggered by environmental agents, may play a role. This supports the "second-hit" hypothesis: genetic susceptibility requires additional environmental exposures to manifest as disease, similar to mechanisms in autoimmune conditions. Methods We will conduct a nested case-control study within the EpiHealth cohort to evaluate gene-environment interactions in CLP and CWP. We will focus on SNPs related to serotonergic, noradrenergic, and opioid signaling (e.g., 5-HT1a receptor, SERT, COMT, OPRM1) and the TSPO gene, linked to stress and metabolic regulation. Data Requirements We will access EpiHealth data on pain and relevant SNPs. Pain will be classified based on body regions using PA_30: CLP will be defined as pain in one region, and CWP as pain in four or more regions. Inclusion criteria include pain duration >3 months/year and intensity >4/10. Ethical permits for the now propsed project has been achived. The project has recived fundning from EpiHealth steering committee and a person at KI biobank is currently extracting the data for us.