Expanded Phenotypic Spectrum of Neurodevelopmental and Neurodegenerative Disorder Bryant-Li-Bhoj Syndrome with 38 Additional Individuals
Many Scientists Discover Expansion of Phenotypic Spectrum in Bryant-Li-Bhoj Syndrome
Research Background
Bryant-Li-Bhoj Syndrome (BLBS) was classified by OMIM in 2022 (OMIM: 619720, 619721), caused by germline variants in the H3.3 (H3F3A and H3F3B) genes. This syndrome is characterized by developmental delay/intellectual disability, craniofacial anomalies, abnormal muscle tone, and neuroimaging abnormalities. The direction of this study was based on the fact that the clinical features of this disease were not fully encompassed by previous classifications, especially in terms of neurodevelopmental phenotypic characteristics.
Research Source
This study was jointly completed by Dana E. Layo-Carris, Emily E. Lubin, Annabel K. Sangree, and many other scientists, affiliated with multiple research institutions. The research paper was published in the “European Journal of Human Genetics” (2024).
Research Content
The study analyzed data from 96 individuals, including 58 published and 38 unpublished cases, identifying disease-causing missense, synonymous, and stop-loss variants, and providing an in-depth phenotypic description with a focus on the neurodevelopmental components of BLBS. A significant phenomenon observed was phenotypic heterogeneity even among individuals carrying the same variant. The study explored the relationship between gender factors, gene variants, and the location of variants within the H3.3 protein with phenotypic heterogeneity. While no exact genotype-phenotype correlations were confirmed, results suggested that the location of the variant and the affected gene (H3-3A or H3-3B) had a greater impact on the severity of different phenotypes.
Research Methods
The research work encompassed a series of statistical analyses and visualization tools, including circular plot encoding using R language and 3D protein structure modeling. Phenotypic data of patients were obtained from various clinical institutions. The analysis of phenotypic data was categorized into several aspects such as height, weight, cranial conditions, neurodevelopmental milestones, etc. The study considered developmental stages when collecting patient information and adapted definitions of phenotypic standards, such as defining overgrowth as equal to or exceeding the 95th percentile.
Research Results
The study found neuroimaging abnormalities in BLBS patients, including delayed myelination and corpus callosum dysgenesis, accompanied by abnormal muscle tone. The research also pointed out the existence of phenotypic heterogeneity, and that the phenotypic differences caused by gender, genes, and variant locations may be due to other molecular mechanisms, such as changes in nucleosome structure or histone coding caused by H3.3 variants leading to abnormal gene regulation.
Research Conclusions
The study summarized a comprehensive and in-depth understanding of BLBS, pointing out the need for subsequent functional studies to clarify factors affecting phenotypic differences and strategies for future therapeutic interventions. Moreover, it emphasized the importance of sharing patient performance data and global collaboration in data, which will advance clinical understanding of this rare disease and accelerate diagnostic guidance for future patient families.
Research Highlights
- Most significant discovery: Expansion of the phenotypic spectrum of BLBS, in-depth exploration of neurodevelopmental components.
- Significance of problems solved: Clarified more details of BLBS in neurodevelopment, identified phenotypic features not fully covered previously.
- Methodological innovation: Application of circular plot encoding visualization in phenotypic heterogeneity analysis, innovative use of 3D protein structure modeling in interpreting variant impacts.
Research Extension
The study suggests long-term follow-up and multiple assessments of BLBS patients to fully understand their developmental trajectories and the neurodegenerative characteristics of the disease. It also calls for global sharing of data and information on rare diseases, which is key to understanding these conditions and ultimately bringing hope to patient families.