Deep phenotyping of the neuroimaging and skeletal features in KBG syndrome: a study of 53 patients and review of the literature.

BACKGROUND: KBG syndrome is caused by haploinsufficiency of ANKRD11 and is characterised by macrodontia of upper central incisors, distinctive facial features, short stature, skeletal anomalies, developmental delay, brain malformations and seizures. The central nervous system (CNS) and skeletal features remain poorly defined. METHODS: CNS and/or skeletal imaging were collected from molecularly confirmed individuals with KBG syndrome through an international network. We evaluated the original imaging and compared our results with data in the literature. RESULTS: We identified 53 individuals, 44 with CNS and 40 with skeletal imaging. Common CNS findings included incomplete hippocampal inversion and posterior fossa malformations; these were significantly more common than previously reported (63.4% and 65.9% vs 1.1% and 24.7%, respectively). Additional features included patulous internal auditory canal, never described before in KBG syndrome, and the recurrence of ventriculomegaly, encephalic cysts, empty sella and low-lying conus medullaris. We found no correlation between these structural anomalies and epilepsy or intellectual disability. Prevalent skeletal findings comprised abnormalities of the spine including scoliosis, coccygeal anomalies and cervical ribs. Hand X-rays revealed frequent abnormalities of carpal bone morphology and maturation, including a greater delay in ossification compared with metacarpal/phalanx bones. CONCLUSION: This cohort enabled us to describe the prevalence of very heterogeneous neuroradiological and skeletal anomalies in KBG syndrome. Knowledge of the spectrum of such anomalies will aid diagnostic accuracy, improve patient care and provide a reference for future research on the effects of ANKRD11 variants in skeletal and brain development.

ZMYND11 variants are a novel cause of centrotemporal and generalised epilepsies with neurodevelopmental disorder.

ZMYND11 is the critical gene in chromosome 10p15.3 microdeletion syndrome, a syndromic cause of intellectual disability. The phenotype of ZMYND11 variants has recently been extended to autism and seizures. We expand on the epilepsy phenotype of 20 individuals with pathogenic variants in ZMYND11. We obtained clinical descriptions of 16 new and nine published individuals, plus detailed case history of two children. New individuals were identified through GeneMatcher, ClinVar and the European Network for Therapies in Rare Epilepsy (NETRE). Genetic evaluation was performed using gene panels or exome sequencing; variants were classified using American College of Medical Genetics (ACMG) criteria. Individuals with ZMYND11 associated epilepsy fell into three groups: (i) atypical benign partial epilepsy or idiopathic focal epilepsy (n = 8); (ii) generalised epilepsies/infantile epileptic encephalopathy (n = 4); (iii) unclassified (n = 8). Seizure prognosis ranged from spontaneous remission to drug resistant. Neurodevelopmental deficits were invariable. Dysmorphic features were variable. Variants were distributed across the gene and mostly de novo with no precise genotype-phenotype correlation. ZMYND11 is one of a small group of chromatin reader genes associated in the pathogenesis of epilepsy, and specifically ABPE. More detailed epilepsy descriptions of larger cohorts and functional studies might reveal genotype-phenotype correlation. The epileptogenic mechanism may be linked to interaction with histone H3.3.

Phenotype and genotype of 87 patients with Mowat-Wilson syndrome and recommendations for care.

PURPOSE: Mowat-Wilson syndrome (MWS) is a rare intellectual disability/multiple congenital anomalies syndrome caused by heterozygous mutation of the ZEB2 gene. It is generally underestimated because its rarity and phenotypic variability sometimes make it difficult to recognize. Here, we aimed to better delineate the phenotype, natural history, and genotype-phenotype correlations of MWS. METHODS: In a collaborative study, we analyzed clinical data for 87 patients with molecularly confirmed diagnosis. We described the prevalence of all clinical aspects, including attainment of neurodevelopmental milestones, and compared the data with the various types of underlying ZEB2 pathogenic variations. RESULTS: All anthropometric, somatic, and behavioral features reported here outline a variable but highly consistent phenotype. By presenting the most comprehensive evaluation of MWS to date, we define its clinical evolution occurring with age and derive suggestions for patient management. Furthermore, we observe that its severity correlates with the kind of ZEB2 variation involved, ranging from ZEB2 locus deletions, associated with severe phenotypes, to rare nonmissense intragenic mutations predicted to preserve some ZEB2 protein functionality, accompanying milder clinical presentations. CONCLUSION: Knowledge of the phenotypic spectrum of MWS and its correlation with the genotype will improve its detection rate and the prediction of its features, thus improving patient care.

Investigation of Ionization Pattern of the Adjacent Acidic Residues in the DXDXE Motif of GH-18 Chitinases Using Theoretical pKa Calculations.

GH-18 chitinases are chitinolytic enzymes, primarily responsible for the recycling of insoluble chitin biomaterials. These enzymes contain three invariant acidic active-site residues within a DXDXE motif, which play a synergistic role in the catalytic cycle of chitin degradation. We employed a pKa calculation approach to approximate the protonation states of residues D1, D2, and E in the DXDXE motif of 75 GH-18 chitinases. Theoretical pH-activity profiles of these enzymes were subsequently constructed and compared with the experimentally determined pH-activity profiles. Theoretical pKa data indicate that in the majority of chitinases the D1 side-chain is in the "up" and the E side-chain in the "down" position, while the position of the D2 side-chain is versatile and depends on the state of the enzyme. The pKa values in 75 GH-18 chitinases were predicted to be <0 for D1, 8-13 for D2, and 6-9 for E, indicating that the D1-D2 pair holds exactly one net negative charge. On the other hand, the catalytic acid E is protonated over the active pH-range, agreeing with the pH-activity curves reported previously for most chitinases. The results obtained from this study help to elucidate the mechanistic details of the concerted participation of D1, D2, and E in the catalytic cycle of chitin hydrolysis by GH-18 chitinases.

Combination of radiofrequency ablation with transarterial chemoembolization for treatment of hepatocellular carcinoma: experience from a Danish tertiary liver center.

BACKGROUND: Recent studies have shown that the combination of radiofrequency ablation (RFA) and transarterial chemoembolization (TACE) for unresectable hepatocellular carcinoma (HCC) may offer a survival advantage compared to monotherapy. PURPOSE: To study the effectiveness of combination therapy with RFA and TACE compared to that of TACE alone in a Scandinavian tertiary liver cancer center. MATERIAL AND METHODS: A retrospective study of the patients treated with combination therapy vis-à-vis TACE alone from June 2007 to November 2012 was performed. Eighteen patients were treated with a combination of RFA and TACE with an interval of 1-4 days between the treatments. For comparison, a group of 18 patients treated with TACE as monotherapy in the same time period was matched with the combination group by demographic data, tumor characteristics, biochemical and clinical parameters, and performance status (PS). RESULTS: Each group consisted of 14 patients with cirrhosis and four without. There were no significant differences between the groups regarding age, gender, tumor characteristics, causes of cirrhosis, levels of bilirubin, creatinine, prothrombin time, Child Pugh score, or World Health Organization (WHO) performance status. The median survival of patients in the RFA + TACE combination group was 586 days compared to 296 days in the control group. The difference was not statistically significant (P = 0.26). However, when we stratified the data for cirrhosis and WHO performance status, patients in the combination group had significantly better survival (P = 0.024). CONCLUSION: Combination therapy with RFA and TACE for unresectable HCC, compared to TACE alone, may offer a survival benefit for a selected group of patients with HCC.

Emergence of lingual dystonia and strabismus in early-onset SCN8A self-limiting familial infantile epilepsy.

Pathogenic variants in SCN8A are associated with a broad phenotypic spectrum, including Self-Limiting Familial Infantile Epilepsy (SeLFIE), characterized by infancy-onset age-related seizures with normal development and cognition. Movement disorders, particularly paroxysmal kinesigenic dyskinesia typically arising after puberty, may represent another core symptom. We present the case of a 1-year-old girl with a familial disposition to self-limiting focal seizures from the maternal side and early-onset orofacial movement disorders associated with SCN8A-SeLFIE. Brain MRI was normal. Genetic testing revealed a maternally inherited SCN8A variant [c.4447G > A; p.(Glu1483Lys)]. After the introduction of valproic acid, she promptly achieved seizure control as well as complete remission of strabismus and a significant decrease in episodes of tongue deviation. Family history, genetic findings, and epilepsy phenotype are consistent with SCN8A-SeLFIE. Movement disorders are an important part of the SCN8A phenotypic spectrum, and this case highlights the novel early-onset orofacial movement disorders associated with this condition. The episodes of tongue deviation and protrusion suggest focal oromandibular (lingual) dystonia. Additionally, while infantile strabismus or esophoria is a common finding in healthy individuals, our case raises the possibility of an ictal origin of the strabismus. This study underscores the importance of recognizing and addressing movement disorders in SCN8A-SeLFIE patients, particularly the rare early-onset orofacial manifestations. It adds to the growing body of knowledge regarding the diverse clinical presentations of SCN8A-associated disorders and suggests potential avenues for clinical management and further research.

Protein dielectric constants determined from NMR chemical shift perturbations.

Understanding the connection between protein structure and function requires a quantitative understanding of electrostatic effects. Structure-based electrostatic calculations are essential for this purpose, but their use has been limited by a long-standing discussion on which value to use for the dielectric constants (ε(eff) and ε(p)) required in Coulombic and Poisson-Boltzmann models. The currently used values for ε(eff) and ε(p) are essentially empirical parameters calibrated against thermodynamic properties that are indirect measurements of protein electric fields. We determine optimal values for ε(eff) and ε(p) by measuring protein electric fields in solution using direct detection of NMR chemical shift perturbations (CSPs). We measured CSPs in 14 proteins to get a broad and general characterization of electric fields. Coulomb's law reproduces the measured CSPs optimally with a protein dielectric constant (ε(eff)) from 3 to 13, with an optimal value across all proteins of 6.5. However, when the water-protein interface is treated with finite difference Poisson-Boltzmann calculations, the optimal protein dielectric constant (ε(p)) ranged from 2 to 5 with an optimum of 3. It is striking how similar this value is to the dielectric constant of 2-4 measured for protein powders and how different it is from the ε(p) of 6-20 used in models based on the Poisson-Boltzmann equation when calculating thermodynamic parameters. Because the value of ε(p) = 3 is obtained by analysis of NMR chemical shift perturbations instead of thermodynamic parameters such as pK(a) values, it is likely to describe only the electric field and thus represent a more general, intrinsic, and transferable ε(p) common to most folded proteins.

Neurodevelopmental and Epilepsy Phenotypes in Individuals With Missense Variants in the Voltage-Sensing and Pore Domains of KCNH5.

BACKGROUND AND OBJECTIVES: KCNH5 encodes the voltage-gated potassium channel EAG2/Kv10.2. We aimed to delineate the neurodevelopmental and epilepsy phenotypic spectrum associated with de novo KCNH5 variants. METHODS: We screened 893 individuals with developmental and epileptic encephalopathies for KCNH5 variants using targeted or exome sequencing. Additional individuals with KCNH5 variants were identified through an international collaboration. Clinical history, EEG, and imaging data were analyzed; seizure types and epilepsy syndromes were classified. We included 3 previously published individuals including additional phenotypic details. RESULTS: We report a cohort of 17 patients, including 9 with a recurrent de novo missense variant p.Arg327His, 4 with a recurrent missense variant p.Arg333His, and 4 additional novel missense variants. All variants were located in or near the functionally critical voltage-sensing or pore domains, absent in the general population, and classified as pathogenic or likely pathogenic using the American College of Medical Genetics and Genomics criteria. All individuals presented with epilepsy with a median seizure onset at 6 months. They had a wide range of seizure types, including focal and generalized seizures. Cognitive outcomes ranged from normal intellect to profound impairment. Individuals with the recurrent p.Arg333His variant had a self-limited drug-responsive focal or generalized epilepsy and normal intellect, whereas the recurrent p.Arg327His variant was associated with infantile-onset DEE. Two individuals with variants in the pore domain were more severely affected, with a neonatal-onset movement disorder, early-infantile DEE, profound disability, and childhood death. DISCUSSION: We describe a cohort of 17 individuals with pathogenic or likely pathogenic missense variants in the voltage-sensing and pore domains of Kv10.2, including 14 previously unreported individuals. We present evidence for a putative emerging genotype-phenotype correlation with a spectrum of epilepsy and cognitive outcomes. Overall, we expand the role of EAG proteins in human disease and establish KCNH5 as implicated in a spectrum of neurodevelopmental disorders and epilepsy.

Highly perturbed pKa values in the unfolded state of hen egg white lysozyme.

The majority of pK(a) values in protein unfolded states are close to the amino acid model pK(a) values, thus reflecting the weak intramolecular interactions present in the unfolded ensemble of most proteins. We have carried out thermal denaturation measurements on the WT and eight mutants of HEWL from pH 1.5 to pH 11.0 to examine the unfolded state pK(a) values and the pH dependence of protein stability for this enzyme. The availability of accurate pK(a) values for the folded state of HEWL and separate measurements of mutant-induced effects on the folded state pK(a) values, allows us to estimate the pK(a) values of seven acidic residues in the unfolded state of HEWL. Asp-48 and Asp-66 display pK(a) values of 2.9 and 3.1 in our analysis, thus representing the most depressed unfolded state pK(a) values observed to date. We observe a strong correlation between the folded state pK(a) values and the unfolded state pK(a) values of HEWL, thus suggesting that the unfolded state of HEWL possesses a large degree of native state characteristics.

Toward fast determination of protein stability maps: experimental and theoretical analysis of mutants of a Nocardiopsis prasina serine protease.

The stability of serine proteases is of major importance for their application in industrial processes. Here we study the determinants of the stability of a Nocardiopsis prasina serine protease using fast residual activity assays, a feature classification algorithm, and structure-based energy calculation algorithms for 121 micropurified mutant enzyme clones containing multiple point mutations. Using a multivariate regression analysis, we deconvolute the data for the mutant clones and find that mutations of residues Asn47 and Pro124 are deleterious to the stability of the enzyme. Both of these residues are situated in loops that are known to be important for the stability of the highly homologous α-lytic protease. Structure-based energy calculations with PEATSA give a good general agreement with the trend of experimentally measured values but also identify a number of clones that the algorithm fails to predict correctly. We discuss the significance of the results in relation to the structure and function of closely related proteases, comment on the optimal experimental design when performing high-throughput experiments for characterizing the determinants of protein stability, and discuss the performance of structure-based energy calculations with complex data sets such as the one presented here.

DataPipeline: automated importing and fitting of large amounts of biophysical data.

Raw data from experiments across the biological sciences comes in a large variety of text formats. In small or medium sized laboratories researchers often use an assorted collection of software to interpret, fit, and visualize their data. The spreadsheet is commonly the core component of such a workflow. The limitations of such programs for large amounts of heterogeneous data can be frustrating. We report the construction of DataPipeline, a desktop and command-line application that automates the tasks of importing, fitting, and plotting of text-based data. The software is designed to simplify the process of importing text data from various sources using simple configuration files to describe raw file formats. Once imported, curve fitting can be performed using custom fitting models designed by the user inside the application. Fitted parameters can be grouped together as new datasets to be fitted to other models and experimental uncertainties propagated to give error estimates. This software will be useful for processing of data from high through-put biological experiments or for rapid visualization of pilot data without the need for a chain of different programs to carry out each step. DataPipeline and source code is available under an open source license. The software can be freely downloaded at http://code.google.com/p/peat/downloads/list.

A collaborative environment for developing and validating predictive tools for protein biophysical characteristics.

The exchange of information between experimentalists and theoreticians is crucial to improving the predictive ability of theoretical methods and hence our understanding of the related biology. However many barriers exist which prevent the flow of information between the two disciplines. Enabling effective collaboration requires that experimentalists can easily apply computational tools to their data, share their data with theoreticians, and that both the experimental data and computational results are accessible to the wider community. We present a prototype collaborative environment for developing and validating predictive tools for protein biophysical characteristics. The environment is built on two central components; a new python-based integration module which allows theoreticians to provide and manage remote access to their programs; and PEATDB, a program for storing and sharing experimental data from protein biophysical characterisation studies. We demonstrate our approach by integrating PEATSA, a web-based service for predicting changes in protein biophysical characteristics, into PEATDB. Furthermore, we illustrate how the resulting environment aids method development using the Potapov dataset of experimentally measured ΔΔGfold values, previously employed to validate and train protein stability prediction algorithms.

Capturing, sharing and analysing biophysical data from protein engineering and protein characterization studies.

Large amounts of data are being generated annually on the connection between the sequence, structure and function of proteins using site-directed mutagenesis, protein design and directed evolution techniques. These data provide the fundamental building blocks for our understanding of protein function, molecular biology and living organisms in general. However, much experimental data are never deposited in databases and is thus 'lost' in journal publications or in PhD theses. At the same time theoretical scientists are in need of large amounts of experimental data for benchmarking and calibrating novel predictive algorithms, and theoretical progress is therefore often hampered by the lack of suitable data to validate or disprove a theoretical assumption. We present PEAT (Protein Engineering Analysis Tool), an application that integrates data deposition, storage and analysis for researchers carrying out protein engineering projects or biophysical characterization of proteins. PEAT contains modules for DNA sequence manipulation, primer design, fitting of biophysical characterization data (enzyme kinetics, circular dichroism spectroscopy, NMR titration data, etc.), and facilitates sharing of experimental data and analyses for a typical university-based research group. PEAT is freely available to academic researchers at http://enzyme.ucd.ie/PEAT.

Acute flaccid rhombencephalomyelitis with radiculitis in a child with an enterovirus A71 infection seen for the first time in Denmark: a case report.

BACKGROUND: Acute flaccid myelitis is a serious condition of the spinal cord. More than 80% of patients experience a mild respiratory illness or fever consistent with a viral infection prior to acute flaccid myelitis development. Enterovirus A71 is known to circulate in Denmark, and has previously been associated with severe neurological symptoms. In this case report we describe acute flaccid rhombencephalomyelitis with radiculitis in an infant with an enterovirus infection. CASE PRESENTATION: The 8-month-old male of Asian origin presented with fever and gastrointestinal symptoms, followed by severe neurological deficits such as flaccid paralysis of the neck and upper extremities. An initial magnetic resonance imaging scan of the brain was normal, and the boy was treated for encephalitis. A follow-up magnetic resonance imaging scan of the brain and spinal cord 1 week later showed the development of pathological symmetrical gray matter hyperintensity lesions on T2-weighted images in the brainstem and upper medulla spinalis, and nerve enhancement in the terminal thread of the spinal cord and the cervical roots; findings consistent with rhombencephalomyelitis with radiculitis causing flaccid paralysis. Enterovirus A71 was detected in both nasopharyngeal and fecal specimens. Other differential diagnostic etiologies of viral and bacterial encephalitis, including poliovirus, were excluded. CONCLUSIONS: This is the first case in Denmark of a patient diagnosed with acute flaccid rhombencephalomyelitis strongly linked to an enterovirus A71 infection. This case emphasizes the diagnostic importance of combining a history of respiratory and/or gastrointestinal illness, fever, and delayed onset of varying degrees of paralysis with progressive characteristic spinal and brain lesions. Analysis of respiratory, fecal, and cerebrospinal samples for the presence of enterovirus, and eliminating other differential pathogens, is essential to confirm the diagnosis.

Integrated prediction of the effect of mutations on multiple protein characteristics.

Site-directed mutagenesis is routinely used in modern biology to elucidate the functional or biophysical roles of protein residues, and plays an important role in the field of rational protein design. Over the past decade, a number of computational tools have been developed that can predict the effect of point mutations on a protein's biophysical characteristics. However, these programs usually provide predictions for only a single characteristic. Furthermore, online versions of these tools are often impractical to use for examination of large and diverse sets of mutants. We have created a new web application, (http://enzyme.ucd.ie/PEAT_SA), that can simultaneously predict the effect of mutations on stability, ligand affinity and pK(a) values. PEAT-SA also provides an expanded feature-set with respect to other online tools which includes the ability to obtain predictions for multiple mutants in one submission. As a result, researchers who use site-directed mutagenesis can access state-of-the-art protein design methods with a fraction of the effort previously required. The results of benchmarking PEAT-SA on standard test-sets demonstrate that its accuracy for all three prediction types compares well to currently available tools. We illustrate PEAT-SA's potential by using it to investigate the influence of mutations on the activity of Subtilisin BPN'. This example demonstrates how the ability to obtain a wide range of information from one source, that can be combined to obtain deeper insight into the influence of mutations, makes PEAT-SA a valuable service to both experimental and computational biologists.

On the development of protein pKa calculation algorithms.

Protein pK(a) calculation methods are developed partly to provide fast non-experimental estimates of the ionization constants of protein side chains. However, the most significant reason for developing such methods is that a good pK(a) calculation method is presumed to provide an accurate physical model of protein electrostatics, which can be applied in methods for drug design, protein design, and other structure-based energy calculation methods. We explore the validity of this presumption by simulating the development of a pK(a) calculation method using artificial experimental data derived from a human-defined physical reality. We examine the ability of an RMSD-guided development protocol to retrieve the correct (artificial) physical reality and find that a rugged optimization landscape and a huge parameter space prevent the identification of the correct physical reality. We examine the importance of the training set in developing pK(a) calculation methods and investigate the effect of experimental noise on our ability to identify the correct physical reality, and find that both effects have a significant and detrimental impact on the physical reality of the optimal model identified. Our findings are of relevance to all structure-based methods for protein energy calculations and simulation, and have large implications for all types of current pK(a) calculation methods. Our analysis furthermore suggests that careful and extensive validation on many types of experimental data can go some way in making current models more realistic.

Remeasuring HEWL pK(a) values by NMR spectroscopy: methods, analysis, accuracy, and implications for theoretical pK(a) calculations.

Site-specific pK(a) values measured by NMR spectroscopy provide essential information on protein electrostatics, the pH-dependence of protein structure, dynamics and function, and constitute an important benchmark for protein pK(a) calculation algorithms. Titration curves can be measured by tracking the NMR chemical shifts of several reporter nuclei versus sample pH. However, careful analysis of these curves is needed to extract residue-specific pK(a) values since pH-dependent chemical shift changes can arise from many sources, including through-bond inductive effects, through-space electric field effects, and conformational changes. We have re-measured titration curves for all carboxylates and His 15 in Hen Egg White Lysozyme (HEWL) by recording the pH-dependent chemical shifts of all backbone amide nitrogens and protons, Asp/Glu side chain protons and carboxyl carbons, and imidazole protonated carbons and protons in this protein. We extracted pK(a) values from the resulting titration curves using standard fitting methods, and compared these values to each other, and with those measured previously by ¹H NMR (Bartik et al., Biophys J 1994;66:1180­1184). This analysis gives insights into the true accuracy associated with experimentally measured pK(a) values. We find that apparent pK(a) values frequently differ by 0.5­1.0 units depending upon the nuclei monitored, and that larger differences occasionally can be observed. The variation in measured pK(a) values, which reflects the difficulty in fitting and assigning pH-dependent chemical shifts to specific ionization equilibria, has significant implications for the experimental procedures used for measuring protein pK(a) values, for the benchmarking of protein pK(a) calculation algorithms, and for the understanding of protein electrostatics in general.

Progress in the prediction of pKa values in proteins.

The pK(a) -cooperative aims to provide a forum for experimental and theoretical researchers interested in protein pK(a) values and protein electrostatics in general. The first round of the pK(a) -cooperative, which challenged computational labs to carry out blind predictions against pK(a) s experimentally determined in the laboratory of Bertrand Garcia-Moreno, was completed and results discussed at the Telluride meeting (July 6-10, 2009). This article serves as an introduction to the reports submitted by the blind prediction participants that will be published in a special issue of PROTEINS: Structure, Function and Bioinformatics. Here, we briefly outline existing approaches for pK(a) calculations, emphasizing methods that were used by the participants in calculating the blind pK(a) values in the first round of the cooperative. We then point out some of the difficulties encountered by the participating groups in making their blind predictions, and finally try to provide some insights for future developments aimed at improving the accuracy of pK(a) calculations.

Epilepsy features in ARID1B-related Coffin-Siris syndrome.

Coffin-Siris syndrome (CSS) is a rare congenital malformation syndrome, caused by mutations in the ARID1B gene in over half of the cases. While the clinical characteristics of the syndrome have been increasingly described, a detailed evaluation of the epileptic phenotype in patients with ARID1B alterations and CSS has not been approached yet. We report seven patients with ARID1B-related CSS, focusing on epilepsy and its electroclinical features. The evolution of epilepsy and EEG findings of children with CSS are described and compared with patients previously reported in the literature. The patients described here reveal common features, consistent with those of patients previously described in the literature. The epilepsy phenotype of CSS due to ARID1B pathogenic variants may be described as focal epilepsy with seizures, variable in frequency, arising from motor areas, with onset in the first years of life and susceptibility to fever, and interictal perisylvian (centrotemporal) epileptiform abnormalities that are enhanced during sleep with possible evolution to an EEG pattern of continuous spike and wave during sleep (without documented developmental regression). Additional information emerging from other patients is needed to confirm this definition.

Phenotypic heterogeneity and mosaicism in Xia-Gibbs syndrome: Five Danish patients with novel variants in AHDC1.

Xia-Gibbs syndrome (XGS) is a neurodevelopmental disorder characterized by intellectual disability, developmental delay, seizures, hypotonia, obstructive sleep apnoea and mild facial dysmorphism. Heterozygosity for loss-of-function variants in AHDC1, encoding the AT-hook DNA binding motif containing protein 1, were discovered in 2014 as the likely genetic cause of Xia-Gibbs syndrome. We present five patients with Xia-Gibbs syndrome caused by previously unreported variants in AHDC1. Two of the patients share a frameshift variant: c.2849del (p.(Pro950Argfs*192)) in AHDC1. Despite sharing this variant, the two patients show remarkable phenotypic differences underscoring the clinical heterogeneity of Xia-Gibbs syndrome. In addition, we present a case of Xia-Gibbs syndrome caused by mosaicism for an AHDC1 variant.