Flow cytometry is an essential tool for dissecting the functional complexity of hematopoiesis. We used single-cell “mass cytometry” to examine healthy human bone marrow, measuring 34 parameters simultaneously in single cells (binding of 31 antibodies, viability, DNA content, and relative cell size). The signaling behavior of cell subsets spanning a defined hematopoietic hierarchy was monitored with 18 simultaneous markers of functional signaling states perturbed by a set of ex vivo stimuli and inhibitors. The data set allowed for an algorithmically driven assembly of related cell types defined by surface antigen expression, providing a superimposable map of cell signaling responses in combination with drug inhibition. Visualized in this manner, the analysis revealed previously unappreciated instances of both precise signaling responses that were bounded within conventionally defined cell subsets and more continuous phosphorylation responses that crossed cell population boundaries in unexpected manners yet tracked closely with cellular phenotype. Collectively, such single-cell analyses provide system-wide views of immune signaling in healthy human hematopoiesis, against which drug action and disease can be compared for mechanistic studies and pharmacologic intervention.

The CD4(+)CD25(+) lineage of regulatory T (Treg) cells plays a key role in controlling immune and autoimmune responses and is characterized by a unique transcriptional signature. The transcription factor Foxp3 had been thought to determine the Treg cell lineage, a hypothesis challenged by recent observations. We have performed a cross-sectional analysis of the Treg cell signature in Treg-like cells generated under a number of conditions, with or without Foxp3, to delineate the elements that can be ascribed to T cell activation, interleukin-2, transforming growth factor-beta (TGF-beta) signaling, or Foxp3 itself. These influences synergized to determine many of the signature's components. Much of the Treg cell signature was not ascribable to Foxp3 because it contained gene clusters that are coregulated with, but not transactivated by, Foxp3. Thus, a higher level of regulation upstream of Foxp3 determines the lineage, distinct from elements downstream of Foxp3 that are essential for its regulatory properties.

Summary Whereas countless highly penetrant variants have been associated with Mendelian disorders, the genetic etiologies underlying complex diseases remain largely unresolved. Here, we examine the extent to which Mendelian variation contributes to complex disease risk by mining the medical records of over 110 million patients. We detect thousands of associations between Mendelian and complex diseases, revealing a non-degenerate, phenotypic code that links each complex disorder to a unique collection of Mendelian loci. Using genome-wide association results, we demonstrate that common variants associated with complex diseases are enriched in the genes indicated by this “Mendelian code.” Finally, we detect hundreds of comorbidity associations among Mendelian disorders, and we use probabilistic genetic modeling to demonstrate that Mendelian variants likely contribute non-additively to the risk for a subset of complex diseases. Overall, this study illustrates a complementary approach for mapping complex disease loci and provides unique predictions concerning the etiologies of specific diseases.