Understanding the relationship between the adaptive immune system and disease risk is critical for developing new therapeutic strategies. Our prior work shows that T cell receptor (TCR) diversity systematically declines with age, differs by sex and varies substantially between individuals even after adjusting for these factors. We developed a correlative model suggesting that this decline in TCR diversity contributes significantly to cancer risk and may account for nearly half of the age-associated risk, including sex differences in cancer incidence. Our findings also indicate that variation in TCR diversity is homeostatically regulated, with cytokines likely playing a central role.
To better understand these relationships and inform potential interventions, our study will pursue three parallel aims:
* !Develop computational methods to extract adaptive immune features from whole genome sequencing (WGS) data. Prior work has shown that T and B cell abundance, clonality, and repertoire diversity can be inferred from WGS. We aim to refine and apply these methods to UK Biobank data to extract immune metrics at scale.
* Test the hypothesis that diminished TCR diversity causally contributes to cancer risk. Our model suggests that age-related risk reflects both mutation burden and immune decline. Using prospective follow-up data, we will evaluate whether reduced immune diversity predicts disease onset.
* Identify genetic and molecular regulators of immune system decline. We observe wide inter-individual variation and an earlier decline in males by ~10 years. We will integrate genetic, proteomic, and biomarker data to identify regulatory mechanisms and potential therapeutic targets.
The scale, longitudinal follow-up, and multimodal data in the UK Biobank provide a unique opportunity to explore the molecular drivers of immune aging and its impact on disease.