Our previous studies demonstrated that MRI-MNP can be used to monitor the unfolding of diabetes in NOD mice, quantify genetically determined variability in disease severity in derivative models, foretell imminent onset of clinical diabetes, and monitor disease reversal subsequent to immunotherapy 6, 7
. More recently, the approach was translated to humans, successfully discriminating normal controls from patients recently diagnosed with T1D, and opening the door to non-invasive monitoring of response to immunotherapy in clinical trials 12
. Here, we focused on optimizing MRI-MNP as a prediction tool in the NOD model. The most striking finding was that MRI signals (T2pre-MNP
and, even better, probe accumulation values) measured during a discrete early time-window distinguished between mice that would or would not go on to develop clinical diabetes and permitted an estimation of time to onset. This observation has important theoretical and practical ramifications.
First, the fact that it is already set at 6–10 weeks of age whether or not a given NOD mouse will eventually develop overt diabetes (usually 2–5 months later) has implications for reigning theories of T1D pathogenesis, at least as concerns the NOD mouse model. Scenarios that require a “second-hit” for progression from insulitis to diabetes – for example, some microbial, dietary or stress-related insult – appear to be inconsistent with such an early window of determinism. Also seemingly disfavored are scenarios calling for delayed stochastic generation of the ultimately pathogenic T or B cell specificities. Rather, our findings argue that some early event predicates clinical diabetes development in a fraction of the NOD mouse colony – some event that occurs before 6 weeks of age – but that regulatory processes keep the insulitic lesion in check for variable lengths of time in different individuals. This conclusion is consistent with a report that early development of IAAs could predict eventual diabetes development in NOD mice 16
, though later studies seemed not to support the generality of this finding 27
The practical implication of the MRI-MNP data is that we are now able to sort individual young NOD mice into those that should or should not progress to clinical T1D. Besides permitting more meaningful interpretations of results from diabetes prevention trials, this ability allows us to address pathogenetic mechanisms in a much more accurate manner. Mechanistic dissections in the NOD model have always been compromised by the heterogeneity in disease penetrance and kinetics; MNP-MRI signals will allow us to correlate chosen experimental parameters with the likelihood and proximity of diabetes onset. While the current fairly high cost of this technique precludes high-throughput use, we anticipate price reductions in time, as is often seen with sophisticated technologies of this nature. Exploiting this approach, we could identify specific immune cells and molecules in the islet infiltrate of 10 week-old NOD mice whose representation was correlated with protection from clinical diabetes.
Both the molecular and cellular analyses pointed to a role for cells of the myeloid lineage in disease attenuation. The set of loci whose expression levels in islet-infiltrating leukocytes had the strongest negative correlation with MRI signals (ie high levels reflected a low probability of progression to diabetes) was highly enriched for genes expressed by monocytes and MFs, in particular tissue-resident MFs. Similarly, the only cell-types with a significant negative correlation with MRI signals were Ly6Chi
monocytes and CRIg+
tissue-resident MFs. A regulatory role for cells of the myeloid lineage would be consistent with the growing number of this lineage’s members recognized to have immunosuppressive activity 28, 29
. As concerns the diabetes context, it was reported long ago that MFs are the earliest detectable hematopoietic cells in the islets of NOD mice and certain other T1D models 11
, and it was generally assumed that they promote insulitis and its progession to diabetes. However, from today’s vantage point, it is not known what particular subsets of monocyte-MFs participate in the insulitic lesion, at what specific disease stages, and whether they have a positive or negative role in diabetes progression.
Of the set of transcripts enriched is the islet infiltrates of diabetes-nonprogressors, we were particularly intrigued by those encoding CRIg because this molecule is expressed exclusively by tissue-resident MFs 18–22
, can inhibit T cell activation, proliferation and cytokine production 19, 23, 24
, and derivative reagents modulate autoimmune/inflammatory diseases, notably experimental arthritis and uveitis 24–26
. Indeed, CRIg proved relevant in the current context: it marked a specific subset of MFs whose representation in the insulitic infiltrate showed a significant negative correlation with 10-week MRI values and most importantly, administration of a CRIg-Fc fusion protein both lowered the MRI values and inhibited development of T1D. How might CRIg+
MFs, CRIg and CRIg-Fc be operating to control progression to overt diabetes? To date, CRIg has been ascribed three functions (reviewed in 30
): in the phagocytosis of particles, microbes and cells, via binding to C3b and iC3b; as an inhibitor of the alternative pathway of complement, through blockade of the C3 and C5 convertases; and as a T cell suppressor, reflecting its membership in the B7 family of co-stimulatory/co-inhibitory receptors. That CRIg’s activity as a negative regulator of T cell activation is important in the diabetes context is supported by the reduced fraction of CD3+
T cells observed in the insulitic lesions of non-progressor NOD mice. According to such a scenario, then, CRIg-Fc would deliver a negative signal directly to T cells. CRIg, as a B7 homologue, is expressed by APCs, not T cells. So, CRIg-Fc would not be expected to block APC-T cell interactions as, for example, T-cell-displayed CTLA4-Ig does, but rather to engage an as-yet-unidentified ligand on T cells, just like PD-L1.Ig delivers a negative signal directly to T cells by engaging PD-1 31
. Indeed, we and others 19
found CRIg-Fc to directly inhibit T cell proliferation in an in vitro
It is also possible that CRIg’s activity in promoting phagocytosis plays a role in keeping diabetes in check in unmanipulated NOD mice. Effective clearing of apoptotic cells, whether engendered by a wave of physiological beta cell death known to take place at 3 weeks of age in rodents (reviewed in 32
) or by some microbial, dietary or stress-inducing insult, could promote tolerance over immunity. Of note, the set of transcripts negatively correlated with diabetes development included a number of others encoding proteins involved in opsonization or phagocytosis. For example, Msr1 and CD14 outfit tissue-resident MFs to clear apoptotic cells and dampen inflammation. In addition, transcripts encoding Timd4 (T cell immunoglobulin and mucin domain containing 4), a recently identified phosphatidylserine receptor 33
, were up-regulated in diabetes-resistant mice. Timd4 is also highly expressed on CRIg+
macrophages, suggesting a potential molecular basis for recognition of apoptotic cells by CRIg+
MFs. The message would be reinforced by local dampening of pathogenic anti-beta cell T lymphocyte reactivity, as discussed above.
Thus, the studies described herein provide proof-of-principle that the ability to distinguish closely matched NOD diabetes progressors and nonprogressors can yield novel mechanistic insights. A next step will be to apply the MRI-MNP approach to at-risk humans to see whether it can be used as a T1D prediction tool.