Clinical Presentation of a Complex Neurodevelopmental Disorder Caused by Mutations in ADNP

Background In genome-wide screening studies for de novo mutations underlying autism and intellectual disability, mutations in the ADNP gene are consistently reported among the most frequent. ADNP mutations have been identified in children with autism spectrum disorder comorbid with intellectual disability, distinctive facial features, and deficits in multiple organ systems. However, a comprehensive clinical description of the Helsmoortel-Van der Aa syndrome is lacking. Methods We identified a worldwide cohort of 78 individuals with likely disruptive mutations in ADNP from January 2014 to October 2016 through systematic literature search, by contacting collaborators, and through direct interaction with parents. Clinicians filled in a structured questionnaire on genetic and clinical findings to enable correlations between genotype and phenotype. Clinical photographs and specialist reports were gathered. Parents were interviewed to complement the written questionnaires. Results We report on the detailed clinical characterization of a large cohort of individuals with an ADNP mutation and demonstrate a distinctive combination of clinical features, including mild to severe intellectual disability, autism, severe speech and motor delay, and common facial characteristics. Brain abnormalities, behavioral problems, sleep disturbance, epilepsy, hypotonia, visual problems, congenital heart defects, gastrointestinal problems, short stature, and hormonal deficiencies are common comorbidities. Strikingly, individuals with the recurrent p.Tyr719* mutation were more severely affected. Conclusions This overview defines the full clinical spectrum of individuals with ADNP mutations, a specific autism subtype. We show that individuals with mutations in ADNP have many overlapping clinical features that are distinctive from those of other autism and/or intellectual disability syndromes. In addition, our data show preliminary evidence of a correlation between genotype and phenotype.This work was supported by grants from the European Research Area Networks Network of European Funding for Neuroscience Research through the Research Foundation–Flanders and the Chief Scientist Office–Ministry of Health (to RFK, GV, IG). This research was supported, in part, by grants from the Simons Foundation Autism Research Initiative (Grant No. SFARI 303241 to EEE) and National Institutes of Health (Grant No. R01MH101221 to EEE). This work was also supported by the Italian Ministry of Health and ‘5 per mille’ funding (to CR). For many individuals, sequencing was provided by research initiatives like the Care4Rare Research Consortium in Canada or the Deciphering Developmental Disorders (DDD) study in the UK. The DDD Study presents independent research commissioned by the Health Innovation Challenge Fund (Grant No. HICF-1009–003), a parallel funding partnership between the Wellcome Trust and the Department of Health, and the Wellcome Trust Sanger Institute (Grant No. WT098051). The views expressed in this publication are those of the author(s) and not necessarily those of the Wellcome Trust or the Department of Health. The study has UK Research Ethics Committee approval (10/H0305/83, granted by the Cambridge South Research Ethics Committee, and GEN/284/12 granted by the Republic of Ireland Research Ethics Committee). The research team acknowledges the support of the National Institute for Health Research, through the Comprehensive Clinical Research Network

A Robust Protocol to Increase NimbleGen SeqCap EZ Multiplexing Capacity to 96 Samples

<div><p>Contemporary genetic studies frequently involve sequencing of a targeted gene panel, for instance consisting of a set of genes associated with a specific disease. The NimbleGen SeqCap EZ Choice kit is commonly used for the targeted enrichment of sequencing libraries comprising a target size up to 7 Mb. A major drawback of this commercially available method is the exclusive use of single-indexing, meaning that at most 24 samples can be multiplexed in a single reaction. In case of relatively small target sizes, this will lead to excessive amounts of data per sample. We present an extended version of the NimbleGen SeqCap EZ protocol which allows to robustly multiplex up to 96 samples. We achieved this by incorporating Illumina dual-indexing based custom adapters into the original protocol. To further extend the optimization of cost-efficient sequencing of custom target panels, we studied the effect of higher pre-enrichment pooling factors and show that pre-enrichment pooling of up to 12 samples does not affect the quality of the data. To facilitate evaluation of capture efficiency in custom design panels, we also provide a detailed reporting tool.</p></div

Sleep to the beat: A nap favours consolidation of timing

Growing evidence suggests that sleep is important for procedural learning, but few studies have investigated the effect of sleep on the temporal aspects of motor skill learning. We assessed the effect of a 90-min day-time nap on learning a motor timing task, using 2 adaptations of a serial interception sequence learning (SISL) task. Forty-two right-handed participants performed the task before and after a 90-min period of sleep or wake. Electroencephalography (EEG) was recorded throughout. The motor task consisted of a sequential spatial pattern and was performed according to 2 different timing conditions, that is, either following a sequential or a random temporal pattern. The increase in accuracy was compared between groups using a mixed linear regression model. Within the sleep group, performance improvement was modeled based on sleep characteristics, including spindle- and slow-wave density. The sleep group, but not the wake group, showed improvement in the random temporal, but especially and significantly more strongly in the sequential temporal condition. None of the sleep characteristics predicted improvement on either general of the timing conditions. In conclusion, a daytime nap improves performance on a timing task. We show that performance on the task with a sequential timing sequence benefits more from sleep than motor timing. More important, the temporal sequence did not benefit initial learning, because differences arose only after an offline period and specifically when this period contained sleep. Sleep appears to aid in the extraction of regularities for optimal subsequent performance. (PsycINFO Database Recor

Detailed description of the dataset.

<p>Detailed description of the dataset.</p

Sections from a coverage report.

<p>A) Representation of exon coverage, grouped by gene based on information in the provided BED file. The horizontal red line indicates a user-provided coverage threshold. B) Coverage at base level for one exon, allowing the identification of local drops in sequencing depth.</p

Schematic structural representation of the adapter and blocking oligo sequences and the required modifications.

<p>Full-length sequences can be derived from the Illumina sequence letter [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0123872#pone.0123872.ref011" target="_blank">11</a>]. <i>Index = sequence of 6–8 nucleotides that makes each adapter unique</i>, <i>* = phosphothiorate bond</i>, <i>/invdT/ = inverted dT</i>, <i>/phos/ = phosphate group</i>, <i>rc</i>. <i>= reverse complement</i>. Oligonucleotide sequences © 2007–2013 Illumina, Inc. All rights reserved. Derivative works created by Illumina customers are authorized for use with Illumina instruments and products only. All other uses are strictly prohibited.</p

Read distributions by pool, based on the percentage of reads per index.

<p>Pre-enrichment pools were pooled before target capture. Sequencing pool consists of the 4 pre-enrichment pools, combined in a single sequencing run.</p

Individual differences in white matter diffusion affect sleep oscillations

The characteristic oscillations of the sleeping brain, spindles and slow waves, show trait-like, within-subject stability and a remarkable interindividual variability that correlates with functionally relevant measures such as memory performance and intelligence. Yet, the mechanisms underlying these interindividual differences are largely unknown. Spindles and slow waves are affected by the recent history of learning and neuronal activation, indicating sensitivity to changes in synaptic strength and thus to the connectivity of the neuronal network. Because the structural backbone of this network is formed by white matter tracts, we hypothesized that individual differences in spindles and slow waves depend on the white matter microstructure across a distributed network. We recorded both diffusion-weighted magnetic resonance images and whole-night, high-density electroencephalography and investigated whether individual differences in sleep spindle and slow wave parameters were associated with diffusion tensor imaging metrics; white matter fractional anisotropy and axial diffusivity were quantified using tract-based spatial statistics. Individuals with higher spindle power had higher axial diffusivity in the forceps minor, the anterior corpus callosum, fascicles in the temporal lobe, and the tracts within and surrounding the thalamus. Individuals with a steeper rising slope of the slow wave had higher axial diffusivity in the temporal fascicle and frontally located white matter tracts (forceps minor, anterior corpus callosum). These results indicate that the profiles of sleep oscillations reflect not only the dynamics of the neuronal network at the synaptic level, but also the localized microstructural properties of its structural backbone, the white matter tracts

Population pharmacokinetics of cyclosporine in kidney and heart transplant recipients and the influence of ethnicity and genetic polymorphisms in the MDR-1, CYP3A4, and CYP3A5 genes

Our objective was to determine the relationship between single nucleotide polymorphisms (SNPs) in the multidrug resistance 1 (MDR-1) gene and the cytochrome P450 (CYP) genes CYP3A4 and CYP3A5 and the pharmacokinetics of cyclosporine (INN, ciclosporin). Cyclosporine pharmacokinetics of 151 kidney and heart transplant recipients undergoing maintenance therapy was described by use of nonlinear mixed-effects modeling (NONMEM) according to a 2-compartment pharmacokinetic model with first-order absorption and elimination. All patients were genotyped for the CYP3A4*1B and *3 , CYP3A5*3 and *6 , and MDR-1 3435C-->T SNPs. For a typical 70-kg white patient, the following parameters were estimated: absorption rate constant, 1.27 h -1; absorption time lag, 0.47 hour; oral volume of distribution of the central and peripheral compartment, 56.3 and 185.0 L, respectively; oral clearance (Cl/F), 30.7 L/h; and oral intercompartmental clearance, 31.7 L/h. Estimated interpatient variability of Cl/F was 28%. Cl/F was significantly correlated with weight and ethnicity; Cl/F was 13% higher (95% confidence interval, 8%-18%; P <.005) in white patients than in black and Asian patients. In carriers of a CYP3A4*1B variant allele, Cl/F was 9% (95% confidence interval, 1%-17%; P <.05) higher compared with CYP3A4*1 homozygotes, and this effect was independent of ethnicity or weight. Incorporation of these covariates into the NONMEM model did not markedly reduce interpatient variability of Cl/F. None of the other SNPs studied significantly influenced any of the pharmacokinetic parameters. Patients carrying a CYP3A4*1B variant allele have a significantly higher oral cyclosporine clearance compared with patients homozygous for CYP3A4*1 . However, this genetic effect on cyclosporine disposition was small, and genotyping of transplant recipients for CYP3A4 is thus unlikely to assist in planning initial cyclosporine dosin