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Polycomb-associated and Trithorax-associated developmental conditions-phenotypic convergence and heterogeneity
Alice Smail1,2,3, Reem Al-Jawahiri1, Kate Baker4,5,6
1MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK.
Rare variants in Polycomb group (PcG) and Trithorax group (TrxG) genes cause developmental conditions with overlapping phenotypes. Data-driven analysis revealed shared and distinct features, highlighting the complexity of epigenetic gene regulation in human development.
Area of Science:
- Epigenetics and Developmental Biology
- Human Genetics and Genomics
- Computational Biology
Background:
- Polycomb group (PcG) and Trithorax group (TrxG) complexes are key epigenetic regulators essential for development.
- Rare genetic variants in PcG and TrxG genes can lead to a spectrum of developmental disorders.
- Understanding phenotypic variability within these conditions is crucial for diagnosis and management.
Purpose of the Study:
- To delineate phenotypic similarities and differences in developmental conditions associated with rare variants in PcG and TrxG genes.
- To identify common and distinct phenotypic features across different genetic diagnoses within the PcG/TrxG group.
- To explore patient-level phenotypic heterogeneity irrespective of specific genetic diagnosis.
Main Methods:
- Utilized the DECIPHER dataset, analyzing 462 patients with PcG or TrxG-associated conditions.
- Applied Human Phenotype Ontology (HPO) analysis to identify enriched phenotypes.
- Employed semantic similarity analysis and hierarchical clustering for gene group and patient-level analyses.
Main Results:
- PcG/TrxG diagnoses were linked to increased HPO terms for integument, growth, head/neck, limb, and digestive abnormalities.
- Gene group analysis revealed three clusters based on microcephaly, limb/digit dysmorphologies, growth, and behavioral phenotypes.
- Patient-level analysis identified clusters defined by neurodevelopmental and facial dysmorphologies, independent of genetic diagnosis.
Conclusions:
- Data-driven approaches effectively highlight pathway-level phenotypic convergence and individual-level heterogeneity in PcG/TrxG-related disorders.
- Phenotypic clusters at the patient level did not consistently align with specific genetic diagnoses.
- Further research is needed to elucidate the mechanisms underlying phenotypic convergence and variability and to track long-term health characteristics.
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