The cellular landscape of human atherosclerosis remains enigmatic. Over many years scientists have shed light on the composition of plaques by conventional approaches like immunohistochemistry. For instance, our group demonstrated regional differences in macrophage subtypes and their phenotypic association with clinically relevant features such as shoulder and cap regions. Recent technological breakthroughs finally allow definition of cellular composition of lesions in situ. By performing single cell RNA sequencing on thousands of cells, we can now define new and disease relevant cell communities. For both murine and human atherosclerosis first steps into this field have been made. In a joint effort between labs from Leiden (Johan Kuiper), Amsterdam (Menno de Winther) and Utrecht (Gerard Pasterkamp) we recently set out to define cell populations in human atherosclerotic endarterectomy samples by single cell approaches. We could identify T-cells subsets based on their activation status and discriminated macrophage populations with specific inflammatory and foam cell characteristics. Endothelial and smooth muscle cells divided over several subsets and suggested cellular dynamics and transitions. By combining scRNA-seq with additional assays we identified transcription factors that regulate specific subpopulations, and we were able to link our findings to GWAS data. This allowed linkage of genetically relevant genes to subpopulations of cells in atherosclerotic plaques, enabling us to better define how particular genetic variation contributes to atherosclerosis risk in the human population. Moreover, our studies pave the way for development of interventions (i.e. therapeutics) that impact specifically on detrimental cells in plaques. Future work from us and other groups should aim at a better and more detailed linking of cellular subpopulations and phenotypes to clinical characteristics and outcome, leveraging the unprecedented potential of single cell technologies to map human pathophysiology and interventions thereof at the cellular level.