Sex disparities in diagnosis, treatment response, and outcomes exist across cardiovascular, autoimmune, and critical illness. Inflammation is central to these conditions, yet inflammatory blood biomarkers are rarely interpreted in the context of sex, age, or endocrinological factors. No large cohort has established hormone-informed reference ranges for inflammatory biomarker panels, nor described whether the endocrine and immune systems interact in characteristic patterns. In this study, we aim to understand how inflammatory biomarker concentrations vary by sex, age, and hormonal state, and whether reproducible, population-level endocrine-immune phenotypes can be identified. Research objectives include: 1) Generate sex-, age-, and hormone-informed reference intervals for all available Olink inflammatory biomarkers within the UK Biobank; 2) Calculate free testosterone and, where possible, free estradiol, with sensitivity analyses performed for any low-level values; 3) Define endocrine-immune phenotypes and examine associations with cardiovascular and metabolic conditions; 4) Build a comparison tool to benchmark existing and future disease cohorts measured on the same Olink platform. Using dimensionality reduction, unsupervised clustering, and linear modeling, we will examine inflammatory biomarker patterns alongside patient factors such as age, sex, hormone levels, menstrual or menopausal status, comorbidities, and medications. This will be the first population-scale study to generate hormone-informed reference values and putative phenotypes for Olink inflammatory biomarkers, made possible by the scale and depth of the UK Biobank. Applying this framework to our independent cardiac arrest cohort measured on the same panel will allow direct comparison between healthy reference groups and critically ill patients, supporting more targeted and biologically informed clinical applications in cardiac arrest.
