In this grant, we propose to perform gene expression analysis on peripheral blood cells (PBC) of auto-antibody negative first degree relatives of T1D patients (AA- FDRs) and AA+ FDRs who have either progressed (progressors) or not progressed to hyperglycemia (non- progressors), compared to healthy non-T1D related controls. We will also perform gene expression analysis on PBCs of patients enrolled in the TrialNet Abatacept (CTLA4-Ig) New Onset Study (TN-09). The proposed studies will confirm and extend our work on the identification of whole blood biomarkers of disease susceptibility and disease progression in T1D, and initiate our studies on biomarkers of response to therapy. Preliminary data generated under funding from the JDRF suggests that the PBC gene expression profiles of T1D and T1D-related individuals are more similar to each other than to healthy normal non-diabetes-related controls; that is, there is a prodromal gene expression signature that can identify disease risk in the PBCs of AA- FDRs of T1D patients who show no clinical signs of disease. Based on these preliminary data, we hypothesize that families of T1D patients, all have an environmentally-driven, epigenetically-controlled gene expression signature of risk that can be seen in peripheral blood. We identified a subset of AA- FDRs that had elevated levels of interferon-induced gene expression in their PBCs. These individuals also expressed a gene expression signature that was more similar to AA+ FDRs who progressed to hyperglycemia than to AA+ FDRs who did not progress, or to other AA- FDRs, and to controls, suggesting that whole blood gene expression biomarkers could be used to identify individuals who will progress to hyperglycemia prior to seroconversion. In patients who seroconverted (AA+), we found that gene expression was most changed during the early stages of disease (>3 years before the onset of hyperglycemia) in progressors compared to non-progressors. This indicates that we might be able to identify biomarkers that not only distinguish AA+ progressors from AA+ non-progressors, but also predict the rate of disease progression. Finally, studies have shown that PBC gene expression signatures differ in recent onset hyperglycemic patients that responded to anti-CD3 therapy compared to those who did not respond (AbATE trial). We hypothesize that we may also see a difference in gene expression in patients who respond to CTA4-Ig (Abatacept) compared to those who do not respond, 3 months after the initiation of therapy (TN-09). If non-responders could be identified early, this would allow time for other therapies to be tested before total loss of beta cell mass/function occurs.
Three specific aims are proposed. The first specific aim is to validate the prodromal gene expression pattern seen in diabetes related AA- individuals. The second specific aim is to identify both a PBC gene expression signature of T1D disease progression (identifying those who will progress to T1D from those who will not), and a signature of rate of progression. The third specific aim is to ask if there is a PBC gene expression signature that might predict responder vs. non-responder phenotypes for intervention with CTLA4-Ig in recent onset hyperglycemic patients using TN09 samples. The studies described in this application require PBC RNA samples from TrialNet. We have already received >300 samples from the TrialNet repository and have received provisional approval to receive additional samples (letter attached).
As we enter the era of T1D prevention trials, we need validated biomarkers that not only predict risk of T1D development, but can also define the stage of disease and predict the rate of progression to overt hyperglycemia among autoantibody positive (AA+) subjects. Although serum autoantibodies and tests of beta cell function remain the gold standard to identify at-risk patients, it is important to find alternative biomarkers that may be expressed at an earlier time point. These biomarkers can potentially predict AA+ progressors from non- progressors, be used to identify rate of progression, and can aid in patient selection and inclusion in intervention trials. Our preliminary data suggest that there are gene expression signatures in whole blood that might serve as such biomarkers. Additionally, as we enter the era of disease prevention studies in T1D, it is important to try and identify gene expression signatures of responder vs non-responder phenotypes to assist in drug selection. This proposal has received approval for ancillary studies of whole blood RNA obtained form the TrialNet Pathways to Prevention study (TN-01) and TrialNet Abatacept (CTLA4-Ig) New Onset Study (TN09).