OBJECTIVE
This study was undertaken to characterize the clinical and genetic spectrum of RHOBTB2-related disorders (RHOBTB2-RDs) in a Chinese population, explore genotype-phenotype correlations, and develop a refined clinical framework to improve diagnosis and management.
METHODS
We conducted a comprehensive analysis by integrating data from 12 Chinese patients (five retrospective, seven from literature) with 79 international cases from published studies. Genetic analysis focused on variant classification and hotspot identification. Standardized phenotypic data extraction was performed, followed by systematic classification and correlation analyses.
RESULTS
In the Chinese cohort, all variants were de novo missense mutations, with 75% in the Broad-complex, Tramtrack, and Bric-à-brac (BTB) domain and conserved hotspots (e.g., p.Arg483His). Across the combined cohort (N = 91), RHOBTB2-RDs presented a broad phenotypic spectrum. As an exploratory proposal, we introduce paroxysmal encephalopathy with weakness (PEW) as a potential novel clinical phenotypic cluster, strongly associated with BTB domain variants. A practical subtyping framework was proposed: the BTB subtype (severe developmental and epileptic encephalopathy [DEE] with prominent paroxysmal features, often necessitating aggressive seizure management), the truncating/splicing subtype (primarily intellectual disability/developmental delay and movement disorders with epilepsy, requiring focused neurodevelopmental support), the guanosine triphosphatase subtype (a mixed phenotype with a generally more favorable neurodevelopmental course), and the interdomain subtype (frequently associated with PEW alongside DEE or paroxysmal movement disorders).
SIGNIFICANCE
This study systematically characterizes RHOBTB2-RDs in Chinese patients, confirming conserved pathogenic hotspots across ethnicities and identifying population-specific features. The proposed clinical subtyping framework and PEW diagnostic criteria provide valuable tools for improving diagnostic accuracy and guiding personalized management of RHOBTB2-RDs.
Ming Liu, Xiao-Juan Tian, Yu-Pin Ma et al.· Epilepsia· 0 citations
BACKGROUND
Social deficit in autism spectrum disorder (ASD) varies substantially across individuals, yet the neural mechanisms underlying this variability remain poorly understood. Resting state electrophysiological measures may under-engage social information processing and may be less sensitive to ASD-related neural differences. Here we combined EEG with eye tracking during a low demand viewing paradigm to probe neural dynamics and to identify data-driven neurodynamic modes associated with variability in social orienting.
METHODS
We recruited 88 autistic and 71 typically developing (TD) participants for eyes-open resting-state EEG. A subset of these participants, including 58 autistic and 61 TD participants, additionally completed a Social vs. Geometric paradigm with simultaneous EEG and eye tracking. Alpha-band resting-state and task-state EEG were segmented into five microstate (MS) classes (A-E). We compared MS temporal and complexity features between conditions and used support vector machine classification to test whether resting-state or task-state MS features better differentiated ASD from TD participants. For the more discriminative condition, MS-based alpha activity was further characterized by amplitude and phase-locking value (PLV). Participant-level MS-based PLV features were then used for k-means clustering, and moderation models examined whether PLV shaped the association between autistic traits and social orienting.
RESULTS
Task-state MS features differentiated ASD from TD more accurately than resting-state features. Group differences were primarily expressed in MS-based alpha PLV across the five MS classes, whereas alpha amplitude showed no significant group differences. Clustering identified two PLV-based synchronization modes that were present in both ASD and TD participants. Within ASD, these modes differed in social orienting, and MS A PLV moderated the association between autistic traits and social scene preference ratio.
LIMITATIONS
Given the cross-sectional design, tracing the developmental trajectories of these distinct neurodynamic modes will require future multi-center, longitudinal tracking.
CONCLUSIONS
These findings suggest that social orienting variability within ASD is associated with heterogeneous neurodynamic modes that become most visible under naturalistic social input and are more strongly associated with phase synchronization.
Xingke Wang, Sheng Yang, Heli Lu et al.· Molecular Autism· 0 citations
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