Clinical and genetic characterization of DNM1l-related disorders: insights into genotype–phenotype correlations - Manting, Xu; Hua, Li; Sheng, Huang; Xiaodi, Han; Dan, Sun; Fang, Fang (Frontiers in Pediatrics, 2025)
ObjectiveThis study aimed to characterize the clinical and genetic spectrum of dynamin 1-like gene (DNM1l)-associated disorders and to investigate genotype-phenotype correlations in the largest integrated cohort reported to date.MethodsClinical and genetic data from eleven Chinese patients with DNM1l variants were prospectively collected between April 2020 and May 2025. In addition, a comprehensive review of all published cases was performed.ResultsA total of 66 cases were analyzed, including 11 newly reported Chinese patients and 55 previously published cases. The most common clinical manifestations were developmental delay (89.4%), epilepsy (66.7%), dystonia (53.0%), ataxia (21.2%), and failure to thrive (18.2%). Abnormal neuroimaging (80.3%) and electroencephalogram (EEG) abnormalities (78.0%) were also frequent. Domain-specific analyses demonstrated that, compared with GTPase domain variants (n = 15), autosomal dominant middle domain variants (n = 43) were associated with significantly higher risks of epilepsy, status epilepticus, cerebral atrophy, and poorer survival, but lower rates of peripheral neuropathy and ataxia (all p < 0.05). Nine patients with middle domain variants exhibited rhythmic high-amplitude delta with superimposed (poly)spikes (RHADS) on EEG. Within the middle domain subgroup, 67.4% developed childhood-onset status epilepticus, whereas the remaining 32.6% presented with infantile encephalopathy without status epilepticus, a phenotype associated with significantly higher mortality and earlier death (both p < 0.05). All 21 patients (100%) with the p.Arg403Cys hotspot variant experienced status epilepticus. The most severe phenotype was observed in two siblings with biallelic truncating variants, both of whom died in the neonatal period. Further cases are required to confirm statistically associations between variant type and clinical severity.ConclusionThis study provides the largest clinical and genetic characterization of DNM1Lassociated disorders to date and establishes genotype-phenotype correlations stratified by protein domain. The identification of RHADS as a distinctive EEG signature highlights its potential utility as a biomarker for specific clinical and genetic subgroups. Validation in larger, independent cohorts is necessary.