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Sifrim–Hitz–Weiss syndrome (SIHIWES) is a recently described multisystemic neurodevelopmental disorder caused by de novo variants inCHD4. In this study, we investigated the clinical spectrum of the disorder, genotype–phenotype correlations, and the effect of different missense variants on CHD4 function. We collected clinical and molecular data from 32 individuals with mostly de novo variants in CHD4, identified through next-generation sequencing. We performed adenosine triphosphate (ATP) hydrolysis and nucleosome remodeling assays on variants from five different CHD4 domains. The majority of participants had global developmental delay, mild to moderate intellectual disability, brain anomalies, congenital heart defects, and dysmorphic features. Macrocephaly was a frequent but not universal finding. Additional common abnormalities included hypogonadism in males, skeletal and limb anomalies, hearing impairment, and ophthalmic abnormalities. The majority of variants were nontruncating and affected the SNF2-like region of the protein. We did not identify genotype–phenotype correlations based on the type or location of variants. Alterations in ATP hydrolysis and chromatin remodeling activities were observed in variants from different domains. The CHD4-related syndrome is a multisystemic neurodevelopmental disorder. Missense substitutions in different protein domains alter CHD4 function in a variant-specific manner, but result in a similar phenotype in humans.

Asymmetric dimethylarginine (ADMA) is an endogenous inhibitor of nitric oxide (NO) synthesis, whereas l-arginine (Arg) and l-homoarginine (hArg) serve as substrates for NO synthesis. ADMA and other methylated arginines are generally believed to exclusively derive from guanidine (N (G))-methylated arginine residues in proteins by protein arginine methyltransferases (PRMTs) that use S-adenosylmethionine (SAM) as the methyl donor. l-Lysine is known for decades as a precursor for hArg, but only recent studies indicate that arginine:glycine amidinotransferase (AGAT) is responsible for the synthesis of hArg. AGAT catalyzes the formation of guanidinoacetate (GAA) that is methylated to creatine by guanidinoacetate methyltransferase (GAMT) which also uses SAM. The aim of the present study was to learn more about the mechanisms of ADMA and hArg formation in humans. Especially, we hypothesized that ADMA is produced by N (G)-methylation of free Arg in addition to the known PRMTs-involving mechanism. In knockout mouse models of AGAT- and GAMT-deficiency, we investigated the contribution of these enzymes to hArg synthesis. Arg infusion (0.5 g/kg, 30 min) in children (n = 11) and ingestion of high-fat protein meals by overweight men (n = 10) were used to study acute effects on ADMA and hArg synthesis. Daily Arg ingestion (10 g) or placebo for 3 or 6 months by patients suffering from peripheral arterial occlusive disease (PAOD, n = 20) or coronary artery disease (CAD, n = 30) was used to study chronic effects of Arg on ADMA synthesis. Mass spectrometric methods were used to measure all biochemical parameters in plasma and urine samples. In mice, AGAT but not GAMT was found to contribute to plasma hArg, while ADMA synthesis was independent of AGAT and GAMT. Arg infusion acutely increased plasma Arg, hArg and ADMA concentrations, but decreased the plasma hArg/ADMA ratio. High-fat protein meals acutely increased plasma Arg, hArg, ADMA concentrations, as well as the plasma hArg/ADMA ratio. In the PAOD and CAD studies, plasma Arg concentration increased in the verum compared to the placebo groups. Plasma ADMA concentration increased only in the PAOD patients who received Arg. Our study suggests that in humans a minor fraction of free Arg is rapidly metabolized to ADMA and hArg. In mice, GAMT and N (G)-methyltransferases contribute to ADMA and hArg synthesis from Arg, whereas AGAT is involved in the synthesis of hArg but not of ADMA. The underlying biochemical mechanisms remain still elusive.

Developmental disorders (DD), including autism spectrum disorder (ASD) and intellectual disability (ID), are a common group of clinical manifestations caused by a variety of genetic abnormalities. Genetic testing, including chromosomal microarray (CMA), plays an important role in diagnosing these conditions, but CMA can be limited by incomplete coverage of genetic abnormalities and lack of guidance for conditions rarely seen by treating physicians. We conducted a longitudinal, randomized controlled trial investigating the impact of a higher resolution 2.8 million (MM) probe-CMA test on the quality of care delivered by practicing general pediatricians and specialists. To overcome the twin problems of finding an adequate sample size of multiple rare conditions and under/incorrect diagnoses, we used standardized simulated patients known as CPVs. Physicians, randomized into control and intervention groups, cared for the CPV pediatric patients with DD/ASD/ID. Care responses were scored against evidence-based criteria. In round one, participants could order diagnostic tests including existing CMA tests. In round two, intervention physicians could order the 2.8MM probe-CMA test. Outcome measures included overall quality of care and quality of the diagnosis and treatment plan. Physicians ordering CMA testing had 5.43% (p<0.001) higher overall quality scores than those who did not. Intervention physicians ordering the 2.8MM probe-CMA test had 7.20% (p<0.001) higher overall quality scores. Use of the 2.8MM probe-CMA test led to a 10.9% (p<0.001) improvement in the diagnosis and treatment score. Introduction of the 2.8MM probe-CMA test led to significant improvements in condition-specific interventions including an 8.3% (p = 0.04) improvement in evaluation and therapy for gross motor delays caused by Hunter syndrome, a 27.5% (p = 0.03) increase in early cognitive intervention for FOXG1-related disorder, and an 18.2% (p<0.001) improvement in referrals to child neurology for Dravet syndrome. Physician use of the 2.8MM probe-CMA test significantly improves overall quality as well as diagnosis and treatment quality for simulated cases of pediatric DD/ASD/ID patients, and delivers additional clinical utility over existing CMA tests.

Recent advances in neuroscience and genetics have greatly expanded our understanding of the brain and of the etiological factors involved in developmental delay and mental retardation. At the same time, the human genome project has yielded a wealth of information on DNA sequencing, regulation of gene expression, epigenetics, and functional aspects of the genome, which newly propels investigation into the pathogenesis of mental retardation. This book makes readily available current knowledge on the subject and applies it to clinical medicine, providing information essential to neurologists, geneticists, physicians and pediatricians as they search for the causes of mental handicap in their patients. Introductory chapters cover normal and abnormal brain structure, neurogenesis, neuronal proliferation, and signal transduction. Latter chapters delve into discussions of both the environmental factors that may lead to neurocognitive deficits and the cytogenetic, biochemical and molecular defects specifically associated with mental retardation. One chapter reviews gene involvement in non-syndromic mental retardation, autism, and language deficits, as well as multifactorial and genetically complex inheritance. The text concludes with a clinically practical discussion of carrier detection, presymptomatic diagnosis, and treatment of various genetic diseases through enzyme therapy, substrate deprivation, and the use of hemapoietic stem cells.

Cohen syndrome (CS) is a rare autosomal recessive condition caused by mutations and/or large rearrangements in the VPS13B gene. CS clinical features, including developmental delay, the typical facial gestalt, chorioretinal dystrophy (CRD) and neutropenia, are well described. CS diagnosis is generally raised after school age, when visual disturbances lead to CRD diagnosis and to VPS13B gene testing. This relatively late diagnosis precludes accurate genetic counselling. The aim of this study was to analyse the evolution of CS facial features in the early period of life, particularly before school age (6 years), to find clues for an earlier diagnosis. Photographs of 17 patients with molecularly confirmed CS were analysed, from birth to preschool age. By comparing their facial phenotype when growing, we show that there are no special facial characteristics before 1 year. However, between 2 and 6 years, CS children already share common facial features such as a short neck, a square face with micrognathia and full cheeks, a hypotonic facial appearance, epicanthic folds, long ears with an everted upper part of the auricle and/or a prominent lobe, a relatively short philtrum, a small and open mouth with downturned corners, a thick lower lip and abnormal eye shapes. These early transient facial features evolve to typical CS facial features with aging. These observations emphasize the importance of ophthalmological tests and neutrophil count in children in preschool age presenting with developmental delay, hypotonia and the facial features we described here, for an earlier CS diagnosis.

Up to half of children with severe developmental disorders of probable genetic origin remain without a genetic diagnosis; here, in a systematic and nationwide study of 1,133 children with severe, undiagnosed developmental disorders, and their parents, exome sequencing and array-based detection of chromosomal rearrangements reveals novel genes causing developmental disorders, increasing the proportion of children that can now be diagnosed to 31%. Gene linkage to developmental disorders Until recently, the discovery of the genetic causes of monogenic disorders has been predominantly phenotype-driven. Up to half of all children with severe developmental disorders of probable genetic origin remain without a genetic diagnosis. This publication from The Deciphering Developmental Disorders Study presents a UK-wide systematic genetic analysis of 1,133 children with severe, undiagnosed developmental disorders, and their parents. Exome sequencing and array-based detection of chromosomal rearrangements revealed 12 previously unknown developmental disorder genes and increased the proportion of children that could be diagnosed by 10%. Despite three decades of successful, predominantly phenotype-driven discovery of the genetic causes of monogenic disorders 1 , up to half of children with severe developmental disorders of probable genetic origin remain without a genetic diagnosis. Particularly challenging are those disorders rare enough to have eluded recognition as a discrete clinical entity, those with highly variable clinical manifestations, and those that are difficult to distinguish from other, very similar, disorders. Here we demonstrate the power of using an unbiased genotype-driven approach 2 to identify subsets of patients with similar disorders. By studying 1,133 children with severe, undiagnosed developmental disorders, and their parents, using a combination of exome sequencing 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 and array-based detection of chromosomal rearrangements, we discovered 12 novel genes associated with developmental disorders. These newly implicated genes increase by 10% (from 28% to 31%) the proportion of children that could be diagnosed. Clustering of missense mutations in six of these newly implicated genes suggests that normal development is being perturbed by an activating or dominant-negative mechanism. Our findings demonstrate the value of adopting a comprehensive strategy, both genome-wide and nationwide, to elucidate the underlying causes of rare genetic disorders.

The genomes of individuals with severe, undiagnosed developmental disorders are enriched in damaging de novo mutations (DNMs) in developmentally important genes. Here we have sequenced the exomes of 4,293 families containing individuals with developmental disorders, and meta-analysed these data with data from another 3,287 individuals with similar disorders. We show that the most important factors influencing the diagnostic yield of DNMs are the sex of the affected individual, the relatedness of their parents, whether close relatives are affected and the parental ages. We identified 94 genes enriched in damaging DNMs, including 14 that previously lacked compelling evidence of involvement in developmental disorders. We have also characterized the phenotypic diversity among these disorders. We estimate that 42% of our cohort carry pathogenic DNMs in coding sequences; approximately half of these DNMs disrupt gene function and the remainder result in altered protein function. We estimate that developmental disorders caused by DNMs have an average prevalence of 1 in 213 to 1 in 448 births, depending on parental age. Given current global demographics, this equates to almost 400,000 children born per year. Whole-exome analysis of individuals with developmental disorders shows that de novo mutations can equally cause loss or altered protein function, but that most mutations causing altered protein function have not yet been described. De novo mutations in developmental disorders Matthew Hurles, Jeremy McRae and colleagues from the Deciphering Developmental Disorders Study report exome sequencing of 4,293 families containing individuals with severe, undiagnosed developmental disorders. They find enrichment of damaging de novo mutations in 94 genes, implicating them in developmental disorders. They estimate that 42% of the cohort carry pathogenic de novo mutations in coding sequences resulting in disrupted or altered protein function.

De novo mutations in protein-coding genes are a well-established cause of developmental disorders 1 . However, genes known to be associated with developmental disorders account for only a minority of the observed excess of such de novo mutations 1 , 2 . Here, to identify previously undescribed genes associated with developmental disorders, we integrate healthcare and research exome-sequence data from 31,058 parent–offspring trios of individuals with developmental disorders, and develop a simulation-based statistical test to identify gene-specific enrichment of de novo mutations. We identified 285 genes that were significantly associated with developmental disorders, including 28 that had not previously been robustly associated with developmental disorders. Although we detected more genes associated with developmental disorders, much of the excess of de novo mutations in protein-coding genes remains unaccounted for. Modelling suggests that more than 1,000 genes associated with developmental disorders have not yet been described, many of which are likely to be less penetrant than the currently known genes. Research access to clinical diagnostic datasets will be critical for completing the map of genes associated with developmental disorders. By integrating healthcare and exome-sequencing data from parent–offspring trios of patients with developmental disorders, 28 genes that had not previously been associated with developmental disorders were identified.

Purpose Given the rapid pace of discovery in rare disease genomics, it is likely that improvements in diagnostic yield can be made by systematically reanalyzing previously generated genomic sequence data in light of new knowledge. Methods We tested this hypothesis in the United Kingdom–wide Deciphering Developmental Disorders study, where in 2014 we reported a diagnostic yield of 27% through whole-exome sequencing of 1,133 children with severe developmental disorders and their parents. We reanalyzed existing data using improved variant calling methodologies, novel variant detection algorithms, updated variant annotation, evidence-based filtering strategies, and newly discovered disease-associated genes. Results We are now able to diagnose an additional 182 individuals, taking our overall diagnostic yield to 454/1,133 (40%), and another 43 (4%) have a finding of uncertain clinical significance. The majority of these new diagnoses are due to novel developmental disorder–associated genes discovered since our original publication. Conclusion This study highlights the importance of coupling large-scale research with clinical practice, and of discussing the possibility of iterative reanalysis and recontact with patients and health professionals at an early stage. We estimate that implementing parent–offspring whole-exome sequencing as a first-line diagnostic test for developmental disorders would diagnose >50% of patients.