Effects of miglustat therapy on neurological disorder and survival in early-infantile Niemann-Pick disease type C: a national French retrospective study.

BACKGROUND: Niemann-Pick disease type C (NP-C) is a rare neurovisceral lysosomal lipid storage disease characterized by progressive neurodegeneration and premature death. While miglustat can stabilize neurological manifestations in later onset forms of NP-C, its efficacy in the early-infantile neurological form has not been demonstrated. In this observational retrospective study, we compared long-term neurodevelopmental outcome and survival between an untreated and a treated group of early infantile NP-C patients. METHODS: Data available on all NP-C patients with early infantile neurological onset diagnosed in France between 1990 and 2013 were compiled. Patients with incomplete data or who had died from a systemic perinatal, rapidly fatal form were excluded. RESULTS: Ten patients were included in the treated group (year of birth: 2006-2012), and 16 patients in the untreated group [born 1987-2005 (n = 15), 2012 (n = 1)]. The median age at neurological onset was 9 months (5-18) in the treated group, and 12 months (3-18) in the untreated group (p = 0.22). Miglustat therapy was started at a median age of 24.5 months (9-29) and median duration was 30 months (11-56). Gastrointestinal adverse events were reported in 7/10 patients on miglustat. All patients developed loss of psychomotor acquisitions or additional neurological symptoms despite miglustat therapy. The ages of developmental milestones and neurological involvement did not significantly differ between the two groups. Four patients in the untreated group were lost to follow up. The 22 remaining patients had died by the end of the study and no patient survived beyond the age of 7.4 years. The median survival age was 4.42 years in the untreated group and 5.56 years in the treated group; the Kaplan-Meier survival curves were not significantly different (log-rank test: p = 0.11). CONCLUSIONS: Miglustat allowed no significant long-term neurodevelopmental improvement nor significant increase of survival in patients with early infantile NP-C.

Characterization of novel CACNA1A splice variants by RNA-sequencing in patients with episodic or congenital ataxia.

Loss of function variants in CACNA1A cause a broad spectrum of neurological disorders, including episodic ataxia, congenital or progressive ataxias, epileptic manifestations or developmental delay. Variants located on the AG/GT consensus splice sites are usually considered as responsible of splicing defects, but exonic or intronic variants located outside of the consensus splice site can also lead to abnormal splicing. We investigated the putative consequences on splicing of 11 CACNA1A variants of unknown significance (VUS) identified in patients with episodic ataxia or congenital ataxia. In silico splice predictions were performed and RNA obtained from fibroblasts was analyzed by Sanger sequencing. The presence of abnormal transcripts was confirmed in 10/11 patients, nine of them were considered as deleterious and one remained of unknown significance. Targeted next-generation RNA sequencing was done in a second step to compare the two methods. This method was successful to obtain the full cDNA sequence of CACNA1A. Despite the presence of several isoforms in the fibroblastic cells, it detected most of the abnormally spliced transcripts. In conclusion, RNA sequencing was efficient to confirm the pathogenicity of nine novel CACNA1A variants. Sanger or Next generation methods can be used depending on the facilities and organization of the laboratories.

Predictive Performance of Population Pharmacokinetic Models of Levetiracetam in Children and Evaluation of Dosing Regimen.

Levetiracetam is a broad-spectrum antiepileptic drug that exhibits high interindividual variability in serum concentrations in children. A population pharmacokinetic approach can be used to explain this variability and optimize dosing schemes. The objectives are to identify the best predictive population pharmacokinetic model for children and to evaluate recommended doses using simulations and Bayesian forecasting. A validation cohort included children treated with levetiracetam who had a serum drug concentration assayed during therapeutic drug monitoring. We assessed the predictive performance of all the population pharmacokinetic models published in the literature using mean prediction errors, root mean squared errors, and visual predictive checks. A population model was finally constructed on the data, and dose simulations were performed to evaluate doses. We included 267 levetiracetam concentrations ranging from 2 to 69 mg/L from 194 children in the validation cohort. Six published models were externally evaluated. Most of the models underestimated the variability of our population. A 1-compartment model with first-order absorption and elimination with allometric scaling was finally fitted on our data. In our cohort, 57% of patients had a trough concentration <12 mg/L and 12% <5 mg/L. To reach a trough concentration >5 mg/L, doses ≥30 mg/kg/d for patients ≤50 kg and ≥2000 mg/d for patients >50 kg are required. In our population, a high percentage of children had low trough concentrations. Our population pharmacokinetic model could be used for therapeutic drug monitoring of levetiracetam in children.

Dosing Recommendations for Lamotrigine in Children: Evaluation Based on Previous and New Population Pharmacokinetic Models.

Lamotrigine is a broad-spectrum antiepileptic drug with high interindividual variability in serum concentrations in children. The aims of this study were to evaluate the predictive performance of pediatric population pharmacokinetic (PPK) models published on lamotrigine, to build a new model with our monitoring data and to evaluate the current recommended doses. A validation cohort included patients treated with lamotrigine who had a serum level assayed during therapeutic drug monitoring (TDM). PPK models published in the literature were first applied to the validation cohort. We assessed their predictive performance using mean prediction errors, root mean squared errors, and visual predictive checks. A new model was then built using the data. Dose simulations were performed to evaluate the doses recommended. We included 270 lamotrigine concentrations ranging from 0.5 to 17.9 mg/L from 175 patients. The median (range) age and weight were 11.8 years (0.8-18 years) and 32.7 kg (8-110 kg). We tested 6 PPK models; most had acceptable bias and precision but underestimated the variability of the cohort. We built a 1-compartment model with first-order absorption and elimination, allometric scaling, and effects of inhibitor and inducer comedications. In our cohort, 22.6% of trough concentrations were below 2.5 mg/L. In conclusion, we proposed a PPK model that can be used for TDM of lamotrigine in children. In our population, a high percentage of children had low trough concentrations of lamotrigine. As the intervals of recommended doses are large, we suggest aiming at the higher range of doses to reach the target concentration.

Lessons learned from 40 novel PIGA patients and a review of the literature.

OBJECTIVE: To define the phenotypic spectrum of phosphatidylinositol glycan class A protein (PIGA)-related congenital disorder of glycosylation (PIGA-CDG) and evaluate genotype-phenotype correlations. METHODS: Our cohort encompasses 40 affected males with a pathogenic PIGA variant. We performed a detailed phenotypic assessment, and in addition, we reviewed the available clinical data of 36 previously published cases and assessed the variant pathogenicity using bioinformatical approaches. RESULTS: Most individuals had hypotonia, moderate to profound global developmental delay, and intractable seizures. We found that PIGA-CDG spans from a pure neurological phenotype at the mild end to a Fryns syndrome-like phenotype. We found a high frequency of cardiac anomalies including structural anomalies and cardiomyopathy, and a high frequency of spontaneous death, especially in childhood. Comparative bioinformatical analysis of common variants, found in the healthy population, and pathogenic variants, identified in affected individuals, revealed a profound physiochemical dissimilarity of the substituted amino acids in variant constrained regions of the protein. SIGNIFICANCE: Our comprehensive analysis of the largest cohort of published and novel PIGA patients broadens the spectrum of PIGA-CDG. Our genotype-phenotype correlation facilitates the estimation on pathogenicity of variants with unknown clinical significance and prognosis for individuals with pathogenic variants in PIGA.

Simulations of Valproate Doses Based on an External Evaluation of Pediatric Population Pharmacokinetic Models.

Valproate is an old-generation antiepileptic drug often used in children. The pharmacokinetics of valproate are noteworthy for a large and difficult to predict interindividual variability in measured serum concentrations and for saturable protein binding. A model-based approach to personalize valproate treatment could be relevant in pediatric patients. The aims of this study were to review all published valproate population pharmacokinetic models in children and assess them by external validation to determine their predictive performance. Through simulations with the best model, we evaluated dosing regimen. A validation data set included valproate serum concentrations assayed during routine therapeutic drug monitoring of epileptic children. We applied to our population 11 published pediatric population pharmacokinetic models. For each model, predictive performance was assessed by external validation, using bias and precision calculations as well as goodness-of-fit plots. Dose simulations were conducted with the best predictive model to evaluate dosing regimen. The validation data set contained 178 valproate concentrations ranging from 13.4 to 128 mg/L from 114 patients. The best model exhibited a mean prediction error of 6.6 mg/L and a root mean squared error of 25.1 mg/L, with no model misspecification evidenced by visual predictive check. In our cohort, half the patients had a trough concentration <50 mg/L. Simulations suggested increasing doses, especially for children ≤40 kg. External evaluation of published valproate pharmacokinetic models enabled us to identify a suitable model for simulations and Bayesian forecasting. Dosing regimen should be adjusted to weight, with decreasing doses with increasing weight.