The common thread of my research projects is the use of PBMC epigenetics for biomarker discovery. The availability of multimodal single-cell technologies is of great help to my projects. However, I still face two big challenges. First, proper integration of this multimodal data is key to fully explore these datasets, but it is difficult to find the right method among the many methods that have been developed recently. Second, the available PBMC references are not age-spanning while it is known that the immune system is changing upon aging. Additionally, multimodal histone mark data on PBMCs is currently lacking. For these reasons, I aim to create the most comprehensive PBMC atlas covering transcriptomics, surface markers, chromatin states and histone marks on an age spanning cohort. Furthermore, I will define the most optimal integration strategy by benchmarking available tools. Application of the most optimal integration strategy on the PBMC data will result in a comprehensive atlas that will be made publicly available. The atlas will be applied in two of my projects. The first project aims to define cell types linked with immune checkpoint inhibitor response in cancer patients, while in the second one we want to optimize the classification of patients with common variable immunodeficiencies. I am convinced that the generated PBMC atlas and optimized integration strategy will significantly support my projects but will also be of great value for the research community.