Distinguishing ataxia from developmental coordination disorder

Phenotypic subtypes of Xia-Gibbs syndrome: a latent class analysis

Xia-Gibbs syndrome (XGS) is a rare neurodevelopmental disorder with considerable clinical heterogeneity. To further characterize the syndrome's heterogeneity, we applied latent class analysis (LCA) on reported cases to identify phenotypic subtypes. By searching PubMed, Embase, China National Knowledge Infrastructure and Wanfang databases from inception to February 2024, we enrolled 97 cases with nonsense, frameshift or missense variants in the AHDC1 gene. LCA was based on the following 6 phenotypes with moderate occurrence and low missingness: ataxia, seizure, autism, sleep apnea, short stature and scoliosis. After excluding cases with missing data on all LCA variables or with unmatched phenotype-genotype information, a total of 85 cases were selected for LCA. Models with 1-5 classes were compared based on Akaike Information Criterion, Bayesian Information Criterion, Sample-Size Adjusted BIC and entropy. We used multinomial logistic regression (MLR) analyses to investigate the phenotype-genotype association and potential predictors for class membership. LCA revealed 3 distinct classes labeled as Ataxia subtype (n = 11 [12.9%]), Sleep apnea & short stature subtype (n = 23 [27.1%]) and Neuropsychological subtype (n = 51 [60.0%]). The commonest Neuropsychological subtype was characterized by high estimated probabilities of seizure, ataxia and autism. By adjusting for sex, age and variant type, MLR showed no significant association between phenotypic subtype and variant position. Age and variant type were identified as predictors of class membership. The findings of this review offer novel insights for different presentations of XGS. It is possible to deliver targeted monitoring and treatment for each subtype in the early stage.

Movement Disorders Secondary to Novel Antiseizure Medications in Pediatric Populations: A Systematic Review and Meta-analysis of Risk

Novel antiseizure medications are thought to be safer than their conventional counterparts, though no dedicated analysis of movement disorder risk among pediatric populations using novel antiseizure medications has been completed. We report a systematic review with meta-analysis describing the relationship between novel antiseizure medications and movement disorders in pediatrics.MEDLINE, EMBASE, and the World Health Organization's International Clinical Trials Registry Platform were searched up to October 2020 for randomized controlled trials investigating novel antiseizure medications in pediatric populations. Antiseizure medications included lacosamide, perampanel, eslicarbazepine, rufinamide, fenfluramine, cannabidiol, and brivaracetam. Outcomes were pooled using random effects models; risk difference (RD) and 95% confidence intervals (CIs) were calculated.Twenty-three studies were selected from 1690 nonredundant manuscripts (n = 1912 total). There was a significantly increased risk of movement disorders associated with perampanel (RD 0.07, 95% CI 0.01-0.13; n = 133), though only 1 relevant trial was found. No increased risk of movement disorders was found with other antiseizure medications.Our findings indicate most novel antiseizure medications are safe to use in pediatric populations with respect to movement disorders. However, findings were limited by quality of adverse event reporting.

Focusing on Autism Spectrum Disorder in Xia-Gibbs Syndrome: Description of a Female with High Functioning Autism and Literature Review

Background: Xia–Gibbs syndrome (XGS) is a rare disorder caused by de novo mutations in the AT-Hook DNA binding motif Containing 1 (AHDC1) gene, which is characterised by a wide spectrum of clinical manifestations, including global developmental delay, intellectual disability, structural abnormalities of the brain, global hypotonia, feeding problems, sleep difficulties and apnoea, facial dysmorphisms, and short stature. Methods: Here, we report on a girl patient who shows a peculiar cognitive and behavioural profile including high-functioning autism spectrum disorder (ASD) without intellectual disability and provide information on her developmental trajectory with the aim of expanding knowledge of the XGS clinical spectrum. On the basis of the current clinical case and the literature review, we also attempt to deepen understanding of behavioural and psychiatric manifestations associated with XGS. Results: In addition to the patient we described, a considerable rate of individuals with XGS display autistic symptoms or have been diagnosed with an autistic spectrum disorder. Moreover, the analysis of the few psychopathological profiles of patients with XGS described in the literature shows a frequent presence of aggressive and self-injurious behaviours that could be either an expression of autistic functioning or an additional symptom of the ASD evolution. A careful investigation of the abovementioned symptoms is therefore required, since they could represent a “red flag” for ASD.