prepared the manuscript and was involved in CDM development (automated and manual approaches), clinical cohort identification and analysis, and three-dimensional imaging analysis N.K. C.), NIH Autoimmunity Centers of Excellence (AI082724), the Arthritis Foundation (RDSA #5411 to V.M.L.), Roche Organ Transplantation Research Foundation (to A.C.), and MedImmune, LLC (R.H. Funding: Supported by grants from the NIH (AR055646 to M.R. Kinloch for careful reading of the manuscript. We thank the University of Chicago Department of Statistics for expert assistance with statistical analysis and input regarding development of a theoretical model for random cell distribution. Such knowledge should help identify diseases, and disease subsets, that may benefit from therapeutic targeting of specific T cell–antigen-presenting cell interactions.
These data suggest that CDM can be used to identify adaptive immune cell networks driving in situ inflammation. Furthermore, only cognate-competent T FH cell populations expressed high levels of Bcl-6 and interleukin-21. Analysis of inflamed human tissues indicated that measurement of internuclear distances between T FH and B cells could be used to discriminate between apparent cognate and noncognate interactions. Therefore, we developed computational tools to quantify spatial relationships between different cell subtypes in tissue.
We hypothesized that by visualizing and quantifying such interactions, we could directly assess T FH cell competency in situ. The delivery of T cell help to B cells requires direct cognate recognition. However, such markers may not reflect in situ function.
Expressed markers define T FH subsets associated with distinct functions in vitro. However, it is difficult to know if they contribute in situ to inflammation. T follicular helper (T FH) cells are critical for B cell activation in germinal centers and are often observed in human inflamed tissue.
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