Researchers led by Professor Jung-woo Chae of Chungnam National University developed a mathematical model designed to capture individual differences in growth response over time among children with ISS receiving growth hormone treatment. The work, made available online in the journal Value in Health on July 21, 2026, takes a deliberately different approach from many earlier attempts to predict treatment outcomes. Rather than measuring success simply as height gain in centimeters, the team analyzed changes in age- and sex-adjusted height percentiles. This distinction matters clinically. A child who grows six centimeters in a year may still fall further behind peers if those peers grew eight centimeters, whereas a child who climbs from the first percentile toward the tenth is genuinely catching up relative to children of the same age and sex. Percentile-based measures therefore provide a more intuitive and clinically meaningful picture of catch-up growth than absolute height gains alone.

The study itself was retrospective and single-center, drawing on medical records from 91 prepubertal Korean children with idiopathic short stature, 41 boys and 50 girls, who received recombinant human growth hormone, the formulation known as somatropin, between July 2020 and December 2023. The hormone was administered subcutaneously six to seven times per week, with doses adjusted during routine clinical care rather than under experimental conditions. This real-world treatment context is important, because it means the model was built on the kind of heterogeneous, individually tailored dosing patterns that pediatricians actually encounter in practice, rather than the rigid protocols of a controlled trial. The researchers collected demographic data, growth measurements, parental heights, laboratory values, and treatment information from the records, assembling a longitudinal dataset that could support sophisticated modeling of growth trajectories.

At the heart of the analysis was a Gompertz nonlinear mixed-effects model, a mathematical framework well suited to biological growth processes. The Gompertz function describes growth that is initially rapid and then progressively slows, a pattern that mirrors how children respond to growth hormone therapy, where early catch-up is often followed by diminishing gains. The mixed-effects structure allows the model to separate population-level trends from individual deviations, meaning it can characterize both the typical response across the study group and the substantial variation between individual children. Critically, the researchers incorporated cumulative growth hormone exposure into the model, so that the total dose a child received over time, not just the prescribed daily amount, could be linked to the observed trajectory of height percentile. Over a mean treatment period of 619 days with a standard deviation of 307 days, the mean height percentile in the cohort rose from 1.26 at baseline to 9.16 at follow-up, a striking illustration of what catch-up growth looks like on the percentile scale.

The model estimated a total growth-response parameter of approximately 17.2 percentile points, representing the potential shift in height percentile attributable to treatment under the fitted framework. Yet the more clinically valuable finding was not the average but the spread: responses differed substantially among patients, and the model identified baseline characteristics that predicted where an individual child was likely to fall within that range. According to Professor Chae, three baseline factors were associated with a greater predicted response: higher body mass index, lower levels of insulin-like growth factor-binding protein 3, known as IGFBP-3, and shorter paternal height. Of these, body mass index showed the strongest association with predicted response. Each of these variables is routinely available before therapy starts, which is precisely what makes the finding actionable. A pediatrician weighing whether to initiate growth hormone treatment can already measure a child’s BMI, order an IGFBP-3 assay, and record parental heights without any additional testing burden.

The biological logic behind these predictors is plausible, even though the study establishes association rather than mechanism. Higher BMI has been linked in prior pediatric endocrinology literature to greater growth hormone responsiveness, possibly reflecting differences in metabolism and hormone signaling in children with more adipose tissue. IGFBP-3 is the principal carrier protein for insulin-like growth factor 1, the mediator through which growth hormone exerts much of its effect on the growth plate, and lower circulating levels may indicate a state in which the growth axis has more room to respond to exogenous stimulation. Shorter paternal height, meanwhile, may serve as a proxy for the genetic height potential that treatment is working against, with children whose fathers are shorter having relatively more percentile ground to recover. The model does not prove these causal pathways, but it demonstrates that routinely collected clinical variables carry genuine predictive information about treatment response.

To translate the statistical framework into something usable at the point of care, the team also developed GrowCast, a web-based tool that generates individualized predicted height and percentile trajectories. The tool requires only seven inputs: the child’s age, sex, current height, weight, paternal height, IGFBP-3 level, and the intended growth hormone dose. From these, it produces modeled growth trajectories that clinicians can inspect, compare, and discuss. Professor Chae emphasized that GrowCast enables clinicians to compare modeled treatment scenarios and communicate potential growth trajectories with patients and families. This simulation capability addresses one of the most persistent communication gaps in pediatric endocrinology. Families often struggle to interpret statements about average response rates, and a visualized, individualized trajectory, complete with the uncertainty inherent in prediction, can ground conversations about what therapy realistically offers a particular child.

The two-year simulations built into the study illustrate just how wide the range of predicted outcomes can be. Depending on a child’s body mass index, IGFBP-3 level, paternal height, and cumulative growth hormone exposure, median predicted height percentiles ranged from 4.0 percent in lower-response profiles to 31.0 percent in higher-response profiles. In other words, two children who look superficially similar at the start of treatment could be headed toward very different destinations on the growth chart. This heterogeneity is exactly why a one-size-fits-all description of growth hormone benefit has served families poorly, and why the researchers argue that individual characteristics should be considered when assessing the expected response to therapy. The simulations also allow exploration of different dosage regimens, showing how predicted trajectories shift under various treatment scenarios before any commitment to a particular plan is made.

The researchers are careful about the limits of what they have built. GrowCast is not yet a validated dosing-prescription tool, and the study’s retrospective, single-center design, with its cohort of 91 Korean children, means the model must be tested in larger, prospective, multicenter studies before it can be implemented routinely in clinical practice. Cohort-specific factors, local treatment conventions, and population differences in growth patterns all warrant verification in independent datasets. Nevertheless, the study offers a promising framework for more personalized growth hormone treatment in idiopathic short stature. By combining routinely available baseline characteristics with cumulative growth hormone exposure in a rigorous nonlinear mixed-effects model, the approach may help clinicians estimate individual growth trajectories, support more informed treatment planning, and move pediatric growth hormone therapy away from a trial-and-error enterprise toward genuine personalized medicine.

Subject of Research: Predictive modeling of growth hormone therapy response in children with idiopathic short stature

Article Title: Chungnam National University researchers develop model for predicting growth hormone therapy responses in children with short stature

Article References: Chungnam National University researchers develop model for predicting growth hormone therapy responses in children with short stature. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: idiopathic short stature, growth hormone therapy, Gompertz model, nonlinear mixed-effects modeling, height percentile, pediatric endocrinology, IGFBP-3, body mass index, personalized medicine, pharmacometrics, GrowCast, Value in Health

The phenomenon at the centre of the study is known as browning. White adipose tissue is primarily a storage organ, packing energy into a single large lipid droplet per cell. Under certain conditions, however, white fat depots recruit or generate beige adipocytes, cells enriched with mitochondria and with uncoupling protein 1, or UCP1, a molecule that dissipates the mitochondrial proton gradient as heat rather than capturing the energy as ATP. Browning is normally driven by cold exposure or by beta-adrenergic signalling, the same sympathetic pathway that activates classical brown fat. When beige adipogenesis works well, the body burns more fuel and stores less fat. When it fails, visceral fat expands and metabolic disease tends to follow.

Using male mice, the researchers found that stimulating beta-adrenergic receptors with the drug CL316,243, or exposing animals to cold, unexpectedly triggered an influx of neutrophils into epididymal white adipose tissue, a visceral fat depot, but not into subcutaneous fat or brown fat. These infiltrating neutrophils carried activated neutrophil elastase and proteinase 3, enzymes stored in granules and released during inflammation. At the same time that the tissue was being instructed to brown, the arriving neutrophils were deploying proteases that shut the process down. The team showed that when neutrophil elastase was genetically deleted, or when the enzyme was blocked locally within the fat pad using sivelestat, an approved neutrophil elastase inhibitor, browning of visceral fat in response to adrenergic stimulation was substantially rescued, and UCP1 protein levels rose.

The mechanistic work went several layers deep. First, the proteases acted on beige adipocyte precursors, the progenitor cells from which new beige fat cells arise. Neutrophil elastase and proteinase 3 suppressed the proliferation of these precursors by downregulating CDK4 and cyclin D1, two core components of the cell cycle machinery that drive the G1 to S phase transition. With those drivers suppressed, precursor cells became arrested, reducing the pool of cells available for commitment to the beige lineage. This matters because de novo recruitment of beige adipocytes from progenitors, rather than mere activation of pre-existing cells, is a major route through which visceral fat gains thermogenic capacity during cold adaptation.

Second, the enzymes interfered with the differentiation programme itself. The researchers identified insulin-like growth factor binding protein 3, or IGFBP-3, as a critical substrate. IGFBP-3 supports beige adipocyte differentiation, and the neutrophil proteases cleaved it, degrading the factor and thereby weakening the differentiation signal. Prior literature had established that neutrophil elastase and proteinase 3 can function as IGFBP proteases in inflammatory settings, and the new work places that degradative activity squarely within fat tissue biology, linking it to impaired beige adipogenesis. When protease activity was inhibited, IGFBP-3 was preserved and differentiation proceeded more effectively.

Third, the study revealed an indirect route of inhibition. Neutrophil-derived proteases promoted the polarization of adipose tissue macrophages toward the M1, classically inflammatory phenotype. M1 macrophages secrete pro-inflammatory cytokines that are known to suppress thermogenic gene expression and to antagonize the type 2 immune signals, including eosinophil-derived interleukins and M2 macrophage activity, that normally support beige fat development. By tipping the macrophage balance toward inflammation, neutrophils created a tissue environment hostile to thermogenic adipocyte formation, compounding their direct effects on precursors and differentiation.

Importantly, the findings were not confined to mouse models. Analysis of publicly available single-cell RNA sequencing datasets from human adipose tissue revealed elevated expression of ELANE, the gene encoding neutrophil elastase, and PRTN3, the gene encoding proteinase 3, in visceral fat of individuals with obesity, particularly those with type 2 diabetes, compared with subcutaneous fat. Conversely, IGFBP3 expression in adipocytes showed correlations consistent with the proteolytic pathway identified in mice. In laboratory cultures, recombinant human neutrophil elastase and proteinase 3 suppressed the proliferation of human visceral preadipocytes, arrested their cell cycle, and impaired their differentiation into beige adipocytes, mirroring the murine results at the level of human cells.

The therapeutic implications emerged from experiments in mice fed a high-fat diet. Long-term feeding sustained neutrophil infiltration specifically in epididymal visceral fat over ten months. When diet-induced obese mice received sivelestat, the drug suppressed neutrophil activity, enhanced cold-induced browning of visceral fat, decreased visceral fat content, and increased energy expenditure. Sivelestat is already clinically validated for other indications, having been developed and used as a neutrophil elastase inhibitor for acute lung injury and acute respiratory distress syndrome, notably in Japan and in experimental protocols for COVID-19-related lung damage. The prospect of repurposing an existing, safety-characterized drug for obesity treatment is precisely the kind of translational shortcut that draws attention in metabolic medicine, although the authors and the field will recognize that mouse-to-human translation in adipose biology is notoriously fraught, and that sex differences in both browning and neutrophil behaviour, documented in this study and in prior work, complicate extrapolation.

What makes the study conceptually striking is the reversal of expectations. Earlier research had emphasized destructive roles of neutrophils in adipose tissue, including elastase-driven insulin resistance described by Talukdar and colleagues in 2012, and more recent work has even suggested neutrophils help preserve energy stores in activated fat. The new findings position neutrophils as active gatekeepers of adipose plasticity, dynamically throttling the tissue’s thermogenic capacity exactly when sympathetic signals demand it. Whether this represents an evolutionary trade-off, dampening energy expenditure during inflammatory stress, or a maladaptive modern interaction between chronic low-grade inflammation of obesity and an ancient immune programme, remains an open question. What is clear is that the protease activity provides a concrete, druggable point of intervention in a pathway previously managed only through diffuse targets such as sympathetic stimulation, which carries cardiovascular side effects in humans.

The work also refines the emerging picture of immune-metabolic crosstalk in fat. Eosinophils, M2 macrophages, and type 2 cytokines have been shown to promote beige fat; sympathetic neuron-associated macrophages can do the opposite by consuming norepinephrine. Neutrophils and their serine proteases now join this cast, with a mechanism that operates at three levels at once: cell cycle arrest of progenitors, proteolytic destruction of a differentiation factor, and inflammatory remodelling of the macrophage landscape. For the millions of people carrying metabolically harmful visceral fat, the study suggests that taming neutrophil elastase could, in principle, unlock the fat-burning potential already latent within their tissue, and it hands researchers a precise molecular target with which to test that proposition in the clinic.

Subject of Research: How neutrophil serine proteases inhibit thermogenic browning of visceral white adipose tissue

Article Title: Neutrophil serine proteases inhibit thermogenic capacity of visceral white adipose tissue

Article References: Yuan, L., Wu, X., Zong, J., Jiang, M., Gao, S., Zhang, Z., Huang, X., Zhu, M., Xiang, M., Wang, L., Ping, Z., Pan, Y., Ye, D., Xu, A., & Hoo, R. L. C. (2026). Neutrophil serine proteases inhibit thermogenic capacity of visceral white adipose tissue. Nature Metabolism. https://doi.org/10.1038/s42255-026-01598-6

Image Credits: AI Generated

DOI: 10.1038/s42255-026-01598-6

Keywords: neutrophils, neutrophil elastase, proteinase 3, visceral adipose tissue, fat browning, beige adipocytes, thermogenesis, UCP1, obesity, sivelestat, IGFBP-3, macrophage polarization