High-content flow cytometry and temporal data analysis for defining a cellular signature of graft-versus-host disease

Abstract

Acute graft-versus-host disease (GVHD) is diagnosed by clinical and histologic criteria that are often nonspecific and typically apparent only after the disease is well established. Because GvHD is mediated by donor T cells and other immune effector cells, we sought to determine whether changes within a wide array of peripheral blood lymphocyte populations could predict the development of GvHD. Peripheral blood samples from 31 patients undergoing allogeneic blood and marrow transplant were analyzed for the proportion of 121 different subpopulations defined by 4-color combinations of lymphocyte phenotypic and activation markers at progressive time points posttransplant. Samples were processed using a newly developed high content flow cytometry technique and subjected to a spline- and functional linear discriminant analysis (FLDA)-based temporal analysis technique. This strategy identified a consistent posttransplant increase in the proportion and extent of fluctuation of CD3+CD4+CD8beta+ cells in patients who developed GVHD compared to those that did not. Although larger prospective clinical studies will be necessary to validate these results, this study demonstrates that high-content flow cytometry coupled with temporal analysis is a powerful approach for developing new diagnostic tools, and may be useful for developing a sensitive and specific predictive test for GVHD.

Figure 1. Representative FC-HCS analysis of PBMCs from patients with GvHD

Each panel depicts 2-D contour diagrams of 4-color analyses from a single patient at progressive time points following transplant (day −9 to day +49) using anti-CD4 and anti-CD8β. Typical gates for defining the various subpopulations are depicted in blue.

Figure 2. Summary of the data analysis pipeline

The overall strategy for performing temporal analysis of the high content flow cytometry analysis is summarized. FC-HCS=High Content Flow Cytometry, FLDA=Functional Linear Discriminant Analysis, LOOCV=Leave One Out Cross Validation. The details of each of these steps is described in the Methods section.

Figure 3. The pattern of CD3⁺CD4⁺CD8β⁺ cells following allogeneic transplant differentiates between patients with and without GvHD

Transplant recipients who did not develop GvHD (brown dashed lines) showed little variation in the proportion of CD3⁺CD4⁺CD8β⁺ cells while patients who later developed GvHD (solid blue lines) tended to have significantly higher and more variable values within the first 7-21 days post-transplant. Results are shown for both raw data (Panel A) and FLDA estimated true signal (Panel B).

Figure 4. Representative gating strategy for CD3⁺CD4⁺CD8β⁺ cells and co-expression of CD4, CD8β and CD8 on these cells in a patient with GvHD

In panel A, an example of the CD3⁺CD4⁺CD8β⁺ gating strategy is depicted. Cells were initially gated through a lymphocyte/mononuclear cell gate defined by FSC and SSC properties in the left hand contour plot, then through a CD3⁺ gate (middle histogram) and finally through the upper right gate in the CD4 vs. CD8β contour plot. In panel B, the co-expression of CD4, CD8β and CD8 is demonstrated for various sub-populations defined by the various colored gates in the left hand CD4 vs. CD8β contour plot. The middle histogram demonstrates CD8 expression on CD4^dimCD8β^br (red), CD4^dimCD8β^dim (blue) and CD4^brCD8β^dim (green) subpopulations and the right hand histogram demonstrates CD8 expression on the CD8β⁺CD4⁻ (black) and CD4⁺CD8⁻ (purple) subpopulations defined in the left hand contour plot.

Figure 5. Representative flow cytometric analysis of CD3⁺CD4⁺CD8β⁺ cells in patients who developed GvHD compared to patients who did not develop GvHD

The dot plots are from three representative patients 1 week prior to the diagnosis of GvHD for the patients who developed GvHD and on D+35 (the average day of GvHD development) in the 3 controls who did not develop GvHD.