ArticleEpilepsia2025
Latent cognitive phenotypes in juvenile myoclonic epilepsy: Clinical, sociodemographic, and neuroimaging associations.
Article in Epilepsia, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- The network neuropsychology of neighborhood deprivation in juvenile myoclonic epilepsy.Scientific reports · 2026Article
- Juvenile myoclonic epilepsy heterogeneity uncovered: Z-mapped imaging endophenotypes of cortical and subcortical structures and their clinical, cognitive and psychiatric features.Brain communications · 2026Article
- Article
- General mental ability (Spearman's g) in Juvenile Myoclonic Epilepsy.Epilepsia open · 2025Article
- Juvenile Myoclonic Epilepsy Imaging Endophenotypes and Relationship With Cognition and Resting-State EEG.Human brain mapping · 2025Article
- Cognitive and brain health in juvenile myoclonic epilepsy: Role of social determinants of health.Epilepsia · 2025Article
- Latent cognitive phenotypes in juvenile myoclonic epilepsy: Clinical, sociodemographic, and neuroimaging associations.Epilepsia · 2025Article
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Authors and funding
9 authors.
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Abstract
objectiveApplication of cluster analytic procedures has advanced understanding of the cognitive heterogeneity inherent in diverse epilepsy syndromes and the associated clinical and neuroimaging features. Application of this unsupervised machine learning approach to the neuropsychological performance of persons with juvenile myoclonic epilepsy (JME) has yet to be attempted, which is the intent of this investigation.
methodsA total of 77 JME participants, 19 unaffected siblings, and 44 unrelated controls, 12 to 25 years of age, were administered a comprehensive neuropsychological battery (intelligence, language, memory, executive function, and processing speed), which was subjected to factor analysis followed by K-means clustering of the resultant factor scores. Identified cognitive phenotypes were characterized and related to clinical, family, sociodemographic, and cortical and subcortical imaging features.
resultsFactor analysis revealed three underlying cognitive dimensions (general ability, speed/response inhibition, and learning/memory), with JME participants performing worse than unrelated controls across all factor scores, and unaffected siblings performing worse than unrelated controls on the general mental ability and learning/memory factors, with no JME vs sibling differences. K-means clustering of the factor scores revealed three latent groups including above average (31.4% of participants), average (52.1%), and abnormal performance (16.4%). Participant groups differed in their distributions across the latent groups (p < 0.001), with 23% JME, 22% siblings, and 2% unrelated controls in the abnormal performance group; and 18% JME, 21% siblings, and 59% unrelated controls in the above average group. Clinical epilepsy variables were unassociated with cluster membership, whereas family factors (lower parental education) and abnormally increased thickness and/or volume in the frontal, parietal, and temporal-occipital regions were associated with the abnormal cognition group. SIGNIFICANCE: Distinct cognitive phenotypes characterize the spectrum of neuropsychological performance of patients with JME for which there is familial (sibling) aggregation. Phenotypic membership was associated with parental (education) and imaging characteristics (increased cortical thickness and volume) but not basic clinical seizure features.
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