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Molecular Signatures of Response to Mecasermin in Children With Rett Syndrome
Stephen Shovlin1, Chloe Delepine2, Lindsay Swanson3
1Neuropsychiatric Genetics, Trinity Center for Health Sciences, Trinity Translational Medicine Institute, St James Hospital, Dublin, Ireland.
Frontiers in Neuroscience
|June 17, 2022
Summary
Biomarkers for Rett syndrome (RTT) treatment response were identified using gene expression analysis. Specific gene profiles in responders indicate potential for personalized therapy with Insulin-like Growth Factor 1 (IGF-1).
Area of Science:
- Neuroscience
- Genetics
- Pharmacology
Background:
- Rett syndrome (RTT) is a severe neurodevelopmental disorder with limited treatment options.
- Variability in RTT genotype and phenotype complicates targeted therapy development.
- Insulin-like Growth Factor 1 (IGF-1) shows promise in preclinical models but has inconsistent clinical trial results.
Purpose of the Study:
- To identify molecular biomarkers for treatment response in RTT patients receiving mecasermin (IGF-1).
- To stratify patients based on gene expression profiles and breathing phenotype.
- To explore surrogate endpoints for future clinical trials.
Main Methods:
- RNA sequencing was used to analyze whole blood gene expression in RTT patients from a Phase I mecasermin trial.
- Participants were subclassified based on breathing phenotype improvement (apnea index).
- Differential gene expression was compared between responders and a reference group.
Main Results:
- No significant gene expression changes were observed when all patients were analyzed together.
- Patients with moderate-severe apnea and breathing improvement (Responders) showed distinct transcript profiles compared to the Mecasermin Study Reference (MSR) group.
- The MSR group exhibited significant changes in genes related to inflammatory and immune processes, while responders showed fewer changes.
Conclusions:
- Gene expression profiles are associated with severe breathing phenotype and its improvement following mecasermin treatment in RTT.
- Inflammatory/immune pathways and IGF-1 signaling appear to influence treatment response.
- Transcript profiles show potential as biomarkers for predicting response to IGF-1 therapies in RTT.

