Abstract Cell-free RNA (cfRNA) can be used to noninvasively measure dynamic and longitudinal physiological changes throughout the body. While there is considerable effort in the liquid biopsy field to determine disease tissue-of-origin, pathophysiology occurs at the cellular level. Here, we describe two approaches to identify cell type contributions to cfRNA. First we used Tabula Sapiens , a transcriptomic cell atlas of the human body to computationally deconvolve the cell-free transcriptome into a sum of cell type specific transcriptomes, thus revealing the spectrum of cell types readily detectable in the blood. Second, we used individual tissue transcriptomic cell atlases in combination with the Human Protein Atlas RNA consensus dataset to create cell type signature scores which can be used to infer the implicated cell types from cfRNA for a variety of diseases. Taken together, these results demonstrate that cfRNA reflects cellular contributions in health and disease from diverse cell types, potentially enabling determination of pathophysiological changes of many cell types from a single blood test.