The original study, led by Li and colleagues, assembled an impressive array of experimental tools to implicate NIK. The team analyzed retinal transcriptomic data, exposed a human microglial cell line known as HMC3 to advanced glycation end products, the damaging sugar-derived molecules that accumulate in diabetes, and then used genetic knockdown of NIK alongside a pharmacological inhibitor called B022 to see what happened. They also set up co-culture systems in which microglia and endothelial cells, the building blocks of blood vessels, were grown together to model the crosstalk that occurs at the blood-retinal barrier. The results pointed in a consistent direction: when NIK activity was reduced, inflammatory signaling quieted down and the integrity of the barrier improved, suggesting that NIK participates in the inflammatory signaling relevant to retinal vascular injury.

But the interpretation of those results has become the flashpoint of the debate. Li and colleagues framed their findings largely through the lens of M1/M2 polarization, a long-standing model in immunology that treats macrophages and microglia as existing in two opposing states. In this binary picture, M1 cells are inflammatory warriors that pump out tumor necrosis factor-alpha, interleukin-1 beta, and interleukin-6, while M2 cells are the healers, producing anti-inflammatory mediators such as interleukin-10 and repairing tissue. According to this framework, diseases like diabetic retinopathy arise when the balance tips too far toward M1, and therapies work by pushing cells back toward M2. It is an appealingly simple story, and it has dominated the literature for nearly two decades.

The trouble, as Jing Chen of the People’s Hospital of Leshan argues in a letter to the editor, is that the study’s own data do not fit that simple story. In the AGE-treated HMC3 cells, both CD68-positive and CD206-positive cells increased, markers that under the binary model would be assigned to opposing phenotypes. At the same time, elevated levels of the inflammatory cytokines TNF-alpha, IL-1 beta, and IL-6 were accompanied by increased IL-10, the archetypal anti-inflammatory signal. Under a strict reciprocal switch model, these markers should move in opposite directions. Instead, they rose together, a pattern far more consistent with overlapping or coexisting activation programs than with cells flipping from one fixed identity to another. As Chen emphasizes, this is not a quibble over nomenclature imposed from outside; the discrepancy arises directly from the study’s own measurements.

There are also technical reasons why bulk measurements of a handful of canonical markers cannot settle the question. When a population of cells is measured in aggregate, it is impossible to determine whether apparently opposing markers are co-expressed within the same cells, whether they come from distinct cellular subsets, or whether they reflect transitions between transcriptional states. In retinal tissue, the problem is compounded because bulk measurements cannot separate resident microglia from infiltrating myeloid cells that flood in from the circulation as the barrier breaks down. And a change in a small panel of markers, however canonical, does not define a complete transcriptional state. The reduction in M1-associated markers and the increase in M2-associated markers after NIK inhibition therefore support a shift in inflammatory phenotype, but they do not by themselves establish a conversion between fixed M1 and M2 identities. What they are compatible with is something more interesting: a mixed activation landscape in which NIK influences one or more disease-associated microglial programs.

This reinterpretation is not happening in a vacuum. The microglia field has been undergoing a conceptual revolution, driven largely by single-cell RNA sequencing technologies that can profile the gene expression of thousands of individual cells at once. In 2022, a landmark consensus paper in Neuron by Paolicelli, Sierra, Stevens, and colleagues argued that the field had outgrown the M1/M2 dichotomy and should embrace a multidimensional, context-dependent view of microglial states. Under this framework, microglia do not occupy one of two poles but instead slide along continuous axes of gene expression, adopting transient, disease-specific transcriptional programs that cannot be captured by any short list of surface markers. The states observed in a dish, moreover, often bear little resemblance to the states that emerge in living tissue under disease pressure.

Single-cell studies in diabetic retinopathy specifically have made the case even more compelling. Wang and colleagues reported marked microglial heterogeneity and dynamic subtype changes in early experimental diabetic retinopathy, showing that the cellular landscape shifts as the disease progresses. Geng and colleagues, working in a rat model of non-proliferative diabetic retinopathy, identified four distinct microglial subtypes, including an SPP1-high population associated with oxidative stress, apoptosis, and injury to the inner blood-retinal barrier. And in human proliferative diabetic retinopathy, Gu and colleagues described MARCO-positive microglia with dual pro-angiogenic and pro-fibrotic properties, a phenotype that could contribute to both the abnormal vessel growth and the scarring that characterize the advanced disease. These studies differ in species, tissue source, and disease stage, and they do not define a single longitudinal trajectory, nor do they establish NIK as the driver of any of these states. But together they show why a binary framework may miss biologically relevant heterogeneity in diabetic retinopathy, and why the question raised by the NIK study needs sharper tools to answer.

The distinction matters because changes in the abundance of a particular microglial state and changes within a state are biologically different phenomena, and they could imply very different therapeutic effects. If a state-based model is correct, the goal of NIK inhibition would not simply be to suppress M1 and promote M2, but to reduce harmful NIK-dependent programs while preserving the homeostatic and reparative functions that microglia perform in the healthy retina. That is a far more nuanced therapeutic objective, and it demands far more precise experimental designs. Chen also raises a critical caveat about the original study’s in vivo work: because B022 was delivered intravitreally without microglia-specific targeting, the observed improvement in blood-retinal barrier integrity cannot establish that retinal microglial NIK is the cell-specific mediator of the effect. Other cell types in the eye, including endothelial cells and infiltrating immune cells, also rely on NF-κB pathway signaling, and the drug would have reached them all. The pharmacological benefit supports further evaluation of NIK as a therapeutic target, but it is not equivalent to microglia-specific causality.

The path forward, Chen suggests, is concrete and technically achievable. A practical first step would be to compare the retinal transcriptomic data already generated by the original study with published signatures of disease-associated microglial states in diabetic retinopathy, asking whether the genes altered by NIK inhibition overlap with known state markers. That could be followed by single-cell or spatial transcriptomic profiling of retinas after NIK inhibition, which would reveal whether the treatment changes the abundance of particular microglial subtypes, alters their transcriptional programs, or both. Even more decisive would be microglia-restricted manipulation of Map3k14, the gene encoding NIK, combined with lineage-resolved analysis that can distinguish resident microglia from infiltrating macrophages. Such experiments would directly test whether the enzyme acts within microglia to remodel pathogenic states, or whether its protective effects flow through other cellular targets entirely.

None of this diminishes the significance of the original findings; if anything, it sharpens them. The evidence that NIK participates in the inflammatory signaling that damages the blood-retinal barrier in diabetes remains intact, and the pharmacological data justify continued interest in NIK-directed therapy for diabetic retinopathy. What changes is the biological framing: rather than a dial that turns inflammatory cells from bad to good, NIK may be better understood as a regulator of pathogenic microglial state remodeling, a molecular lever that shifts the composition and behavior of a heterogeneous population of immune cells in the diabetic retina. For a disease that affects hundreds of millions of people worldwide and for which current treatments only slow, and do not reverse, the loss of vision, that refined framework could prove to be the difference between another failed anti-inflammatory strategy and a therapy that finally targets the right cells in the right state at the right time.

Subject of Research: The role of NF-κB-inducing kinase in microglial state remodeling and blood-retinal barrier dysfunction in diabetic retinopathy

Article Title: From M1/M2 polarization to disease-associated microglial states: refining the role of NIK in diabetic retinopathy

Article References: Chen, J. (2026). From M1/M2 polarization to disease-associated microglial states: refining the role of NIK in diabetic retinopathy. Journal of Translational Medicine, 24(1), Article 1190. https://doi.org/10.1186/s12967-026-08987-1

Image Credits: AI Generated

DOI: 10.1186/s12967-026-08987-1

Keywords: diabetic retinopathy, microglia, NIK, NF-κB-inducing kinase, M1/M2 polarization, disease-associated microglial states, blood-retinal barrier, single-cell transcriptomics, neuroinflammation, B022, retinal endothelial cells, MAP3K14