Predicting trajectories of acute illness using RNA velocity of whole blood
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Transcriptomic analyses reveal the status of cells, tissues, or organisms, across states of health and disease. RNA velocity adds a temporal dimension to single cell analyses, predicting future transcriptomic and phenotypic states, based on current spliced and unspliced mRNA of each cell. We hypothesized that RNA velocity could be adapted to predict future clinical status of individuals with acute illness using their whole-blood transcriptome. We developed a method for quantitative prediction of transitions in clinical state from a single time-point sample, which we call VeloCD. This predicted transcriptomic trajectories and future infection status in influenza A and SARS-CoV-2 human challenge studies. In HIV-TB coinfected individuals, it predicted the onset of immune reconstitution inflammatory syndrome. In a multinational observational study of acutely unwell febrile children, VeloCD predicted those with greatest medical care requirements. Our results demonstrate a novel application of RNA velocity to predict the trajectory of acute illness.
