Related Experiment Video
Updated: Jun 28, 2026
Murine Precision-Cut Liver Slices as an Ex Vivo Model of Liver Biology
Published on: March 14, 2020
Longitudinal GGT trajectories identify prognostic phenotypes in paediatric primary sclerosing cholangitis
Daniela Denier1, Yiming Emmett Peng2, Mansi Amin3
1Division of Paediatric Gastroenterology, Hepatology and Nutrition, Department of Paediatrics, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.
Insights
Gamma-glutamyl transferase (GGT) trajectories identify distinct pediatric primary sclerosing cholangitis (PSC) patient groups. Early GGT normalization, not just baseline levels, predicts better transplant-free survival in PSC.
Area of Science:
- Pediatric gastroenterology and hepatology
- Biomarker trajectory analysis
- Clinical heterogeneity in rare diseases
Background:
- Primary sclerosing cholangitis (PSC) exhibits significant clinical variability in children.
- Current prognostic assessments rely on single timepoint biomarker measurements, missing dynamic changes.
- Gamma-glutamyl transferase (GGT) levels at one year are known indicators of favorable outcomes.
Purpose of the Study:
- To identify distinct GGT trajectory phenotypes in pediatric PSC using latent class mixed modeling.
- To evaluate the prognostic significance of these identified GGT trajectory clusters.
- To determine if early biochemical response predicts long-term transplant-free survival in pediatric PSC.
Main Methods:
- Analysis of 782 children with PSC from the Pediatric PSC Consortium with longitudinal GGT data.
- Application of latent class mixed models to log-transformed GGT values.
- Assessment of associations between trajectory clusters and transplant-free survival using Cox proportional hazards models.
Main Results:
- Four distinct GGT trajectory clusters were identified: persistently elevated (23%), moderate-stable (30%), elevated-declining (26%), and persistently low (21%).
- Significant differences in 5-year transplant-free survival were observed across clusters (74% to 96%, p<0.0001).
- The elevated-declining cluster normalized GGT by year one and had favorable outcomes, similar to the persistently low cluster.
Conclusions:
- GGT trajectory phenotypes define clinically meaningful subgroups within pediatric PSC, each with a distinct prognosis.
- Early normalization of GGT, observed in the elevated-declining cluster, is a strong predictor of favorable long-term outcomes.
- Trajectory-based phenotyping, predictable with early GGT values, offers a valuable tool for risk stratification and clinical trial design in pediatric PSC.
Background & Aims:
Primary sclerosing cholangitis (PSC) is characterised by substantial clinical heterogeneity. Although normal gamma-glutamyl transferase (GGT) at 1 yr predicts favourable outcomes, the heterogeneous trajectories underlying this remain uncharacterised. We applied latent class mixed modelling to identify distinct GGT trajectory phenotypes in paediatric PSC and evaluate their prognostic significance.
Methods:
We analysed 782 children with PSC from the Pediatric PSC Consortium who had baseline GGT and at least one additional measurement over 3 yr. Latent class mixed models were fit to log-transformed GGT values, with optimal model selection based on Bayesian Information Criterion and entropy. Cox proportional hazards models assessed associations between trajectory clusters and transplant-free survival, adjusting for baseline characteristics. We used multinomial logistic regression to assess whether cluster membership could be predicted using early markers.
Results:
Four trajectory clusters were identified: persistently elevated (23%), moderate-stable (30%), elevated-declining (26%), and persistently low (21%). The 5-yr transplant-free survival differed markedly: 74%, 86%, 98%, and 96%, respectively (p <0.0001). The elevated-declining and moderate-stable clusters both had elevated baseline GGT but divergent outcomes, with the elevated-declining cluster achieving normalisation by Year 1. In adjusted analyses, persistently elevated and moderate-stable clusters had significantly higher transplant hazard compared with persistently low cluster (HR 6.45, 95% CI 2.87-14.5; HR 3.00, 95% CI 1.31-6.90). Transplant-free survival in the elevated-declining cluster was similar to that in the persistently low cluster (p = 0.22). Favourable clusters had younger age with higher prevalence of inflammatory bowel disease. Cluster membership could be predicted using baseline and 6-month GGT values (AUC 0.83).
Conclusions:
GGT trajectory phenotypes identify clinically meaningful PSC subgroups with distinct prognoses. Early biochemical response, rather than baseline values alone, predicts long-term outcomes.
Impact And Implications:
Prognostic assessment in PSC has relied on cross-sectional biomarker measurements at single time points, limiting the ability to capture dynamic changes over time. By applying trajectory modelling to repeated GGT measurements in 782 children with PSC, we identified four distinct groups with significantly different transplant-free survival. Two clusters with similarly elevated baseline GGT followed divergent trajectories and had very different outcomes, information that cross-sectional assessment would miss. These trajectory phenotypes can be predicted using baseline and 6-month GGT values, offering clinicians an early tool to identify high-risk patients. Trajectory-based phenotyping may also facilitate clinical trial design by enabling patient enrichment strategies and providing an early surrogate endpoint.