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Distinct phenotype clusters in childhood inflammatory brain diseases: implications for diagnostic evaluation
Tania Cellucci1, Pascal N Tyrrell, Marinka Twilt
1McMaster Children's Hospital, McMaster University, Hamilton, Ontario, Canada.
Insights
Children with inflammatory brain diseases exhibit distinct clinical patterns. Identifying these clusters aids in diagnosis and tailored evaluation for pediatric neurological conditions.
Area of Science:
- Pediatric Neurology
- Neuroimmunology
- Clinical Data Science
Background:
- Childhood inflammatory brain diseases (IBD) present with diverse clinical manifestations.
- Accurate classification is crucial for timely diagnosis and effective treatment strategies.
Purpose of the Study:
- To identify distinct clusters of pediatric IBD based on initial clinical, laboratory, and imaging findings.
- To determine features driving cluster formation and compare characteristics between clusters.
Main Methods:
- A single-center cohort study analyzed data from 147 children diagnosed with IBD between 1989 and 2010.
- K-means cluster analysis was employed to group patients based on presenting features.
- Associations between clusters and diagnoses were investigated.
Main Results:
- Three distinct patient clusters emerged from the analysis.
- Cluster 1: Paresis, speech deficits; Cluster 2: Behavioral changes, cognitive dysfunction, seizures; Cluster 3: Ataxia, vision abnormalities, seizures.
- MRI findings varied, with unilateral ischemic lesions more common in Cluster 1; clusters correlated with specific diagnoses.
Conclusions:
- Pediatric IBD patients present with distinct phenotypical patterns linked to specific diagnoses.
- These findings support the development of a classification system for childhood IBD.
- Tailored diagnostic pathways are suggested based on identified clusters.
Objective:
To identify distinct clusters of children with inflammatory brain diseases based on clinical, laboratory, and imaging features at presentation, to assess which features contribute strongly to the development of clusters, and to compare additional features between the identified clusters.
Methods:
A single-center cohort study was performed with children who had been diagnosed as having an inflammatory brain disease between June 1, 1989 and December 31, 2010. Demographic, clinical, laboratory, neuroimaging, and histologic data at diagnosis were collected. K-means cluster analysis was performed to identify clusters of patients based on their presenting features. Associations between the clusters and patient variables, such as diagnoses, were determined.
Results:
A total of 147 children (50% female; median age 8.8 years) were identified: 105 with primary central nervous system (CNS) vasculitis, 11 with secondary CNS vasculitis, 8 with neuronal antibody syndromes, 6 with postinfectious syndromes, and 17 with other inflammatory brain diseases. Three distinct clusters were identified. Paresis and speech deficits were the most common presenting features in cluster 1. Children in cluster 2 were likely to present with behavior changes, cognitive dysfunction, and seizures, while those in cluster 3 experienced ataxia, vision abnormalities, and seizures. Lesions seen on T2/fluid-attenuated inversion recovery sequences of magnetic resonance imaging were common in all clusters, but unilateral ischemic lesions were more prominent in cluster 1. The clusters were associated with specific diagnoses and diagnostic test results.
Conclusion:
Children with inflammatory brain diseases presented with distinct phenotypical patterns that are associated with specific diagnoses. This information may inform the development of a diagnostic classification of childhood inflammatory brain diseases and suggest that specific pathways of diagnostic evaluation are warranted.
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