A concerted effort to tackle the global health problem posed by traumatic brain injury (TBI) is long overdue. TBI is a public health challenge of vast, but insufficiently recognised, proportions. Worldwide, more than 50 million people have a TBI each year, and it is estimated that about half the world's population will have one or more TBIs over their lifetime. TBI is the leading cause of mortality in young adults and a major cause of death and disability across all ages in all countries, with a disproportionate burden of disability and death occurring in low-income and middle-income countries (LMICs). It has been estimated that TBI costs the global economy approximately $US400 billion annually. Deficiencies in prevention, care, and research urgently need to be addressed to reduce the huge burden and societal costs of TBI. This Commission highlights priorities and provides expert recommendations for all stakeholders—policy makers, funders, health-care professionals, researchers, and patient representatives—on clinical and research strategies to reduce this growing public health problem and improve the lives of people with TBI.Additional co-authors: Endre Czeiter, Marek Czosnyka, Ramon Diaz-Arrastia, Jens P Dreier, Ann-Christine Duhaime, Ari Ercole, Thomas A van Essen, Valery L Feigin, Guoyi Gao, Joseph Giacino, Laura E Gonzalez-Lara, Russell L Gruen, Deepak Gupta, Jed A Hartings, Sean Hill, Ji-yao Jiang, Naomi Ketharanathan, Erwin J O Kompanje, Linda Lanyon, Steven Laureys, Fiona Lecky, Harvey Levin, Hester F Lingsma, Marc Maegele, Marek Majdan, Geoffrey Manley, Jill Marsteller, Luciana Mascia, Charles McFadyen, Stefania Mondello, Virginia Newcombe, Aarno Palotie, Paul M Parizel, Wilco Peul, James Piercy, Suzanne Polinder, Louis Puybasset, Todd E Rasmussen, Rolf Rossaint, Peter Smielewski, Jeannette Söderberg, Simon J Stanworth, Murray B Stein, Nicole von Steinbüchel, William Stewart, Ewout W Steyerberg, Nino Stocchetti, Anneliese Synnot, Braden Te Ao, Olli Tenovuo, Alice Theadom, Dick Tibboel, Walter Videtta, Kevin K W Wang, W Huw Williams, Kristine Yaffe for the InTBIR Participants and Investigator

Noonan syndrome is a genetic multisystem disorder characterised by distinctive facial features, developmental delay, learning difficulties, short stature, congenital heart disease, renal anomalies, lymphatic malformations, and bleeding difficulties. Mutations that cause Noonan syndrome alter genes encoding proteins with roles in the RAS–MAPK pathway, leading to pathway dysregulation. Management guidelines have been developed. Several clinically relevant genotype–phenotype correlations aid risk assessment and patient management. Increased understanding of the pathophysiology of the disease could help development of pharmacogenetic treatments.

Noonan syndrome (NS) is a common, clinically and genetically heterogeneous condition characterized by distinctive facial features, short stature, chest deformity, congenital heart disease, and other comorbidities. Gene mutations identified in individuals with the NS phenotype are involved in the Ras/MAPK (mitogen-activated protein kinase) signal transduction pathway and currently explain ∼61% of NS cases. Thus, NS frequently remains a clinical diagnosis. Because of the variability in presentation and the need for multidisciplinary care, it is essential that the condition be identified and managed comprehensively. The Noonan Syndrome Support Group (NSSG) is a nonprofit organization committed to providing support, current information, and understanding to those affected by NS. The NSSG convened a conference of health care providers, all involved in various aspects of NS, to develop these guidelines for use by pediatricians in the diagnosis and management of individuals with NS and to provide updated genetic findings.

Prominent theories of consciousness emphasise different aspects of neurobiology, such as the integration and diversity of information processing within the brain. Here, we combine graph theory and dynamic functional connectivity to compare resting-state functional MRI data from awake volunteers, propofol-anaesthetised volunteers, and patients with disorders of consciousness, in order to identify consciousness-specific patterns of brain function. We demonstrate that cortical networks are especially affected by loss of consciousness during temporal states of high integration, exhibiting reduced functional diversity and compromised informational capacity, whereas thalamo-cortical functional disconnections emerge during states of higher segregation. Spatially, posterior regions of the brain’s default mode network exhibit reductions in both functional diversity and integration with the rest of the brain during unconsciousness. These results show that human consciousness relies on spatio-temporal interactions between brain integration and functional diversity, whose breakdown may represent a generalisable biomarker of loss of consciousness, with potential relevance for clinical practice.

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The filamins are cytoplasmic proteins that regulate the structure and activity of the cytoskeleton by cross-linking actin into three-dimensional networks, linking the cell membrane to the cytoskeleton and serving as scaffolds on which intracellular signaling and protein trafficking pathways are organized (reviewed in refs. 1,2). We identified mutations in the gene encoding filamin B in four human skeletal disorders. We found homozygosity or compound heterozygosity with respect to stop-codon mutations in autosomal recessive spondylocarpotarsal syndrome (SCT, OMIM 272460) and missense mutations in individuals with autosomal dominant Larsen syndrome (OMIM 150250) and the perinatal lethal atelosteogenesis I and III phenotypes (AOI, OMIM 108720; AOIII, OMIM 108721). We found that filamin B is expressed in human growth plate chondrocytes and in the developing vertebral bodies in the mouse. These data indicate an unexpected role in vertebral segmentation, joint formation and endochondral ossification for this ubiquitously expressed cytoskeletal protein.Morphogenesis in vertebrate organisms requires the integration of extracellular signals with alterations in the cellular cytoskeleton. Filamins regulate the organization of cytoskeletal F-actin into either parallel bundles or orthogonal gel networks 3 and also mediate interactions between subcortical actin networks and transmembrane receptors to modulate cell-cell, cell-matrix and intracytoplasmic signal transduction 1,2,4 . Mammals have three filamin genes, FLNA, FLNB and FLNC. FLNA and FLNB seem to be ubiquitously expressed 5,6 ; FLNC is predominantly expressed in muscle. Human filamin genes are highly similar with conserved exon-intron structure, and there is ∼70% homology at the protein level 2,7 . The filamin monomer comprises an N-terminal actin binding domain (ABD) followed by a series of 24 β-sheet repeats that collectively bind many cytoplasmic and transmembrane proteins 1,2 . Filamins exist in vivo as dimers. Dimerization, leading to homo-and possibly heterodimer formation, is mediated by interactions between C-terminal sequences 5,8,9 . Mutations in FLNA produce a spectrum of X-linked malformation and osteochondrodysplasia syndromes. FLNA loss-of-function mutations are usually embryonically lethal in males and underlie a neuronal migration disorder in females 10 . Mutations producing structural changes in the protein lead to numerous developmental anomalies in the brain, skeleton and viscera 11 .Recently the gene associated with SCT, an autosomal recessive disorder characterized by short stature and vertebral, carpal and tarsal fusions 12,13 , was localized on chromosome 3p14 (ref. 14). These studies and further recombination mapping (data not shown) identified a 4.7-cM candidate region, which included a 1.4-Mb region of homozygosity containing 14 genes. Mutations were not found in the candidate genes WNT5A 14 , ASB14 and IL17RD (also known as SEF) in affected individuals from the linked families. The gene FLNB localizes to this interval and, considering the r...

Dense surface models can be used to analyze 3D facial morphology by establishing a correspondence of thousands of points across each 3D face image. The models provide dramatic visualizations of 3D face-shape variation with potential for training physicians to recognize the key components of particular syndromes. We demonstrate their use to visualize and recognize shape differences in a collection of 3D face images that includes 280 controls (2 weeks to 56 years of age), 90 individuals with Noonan syndrome (NS) (7 months to 56 years), and 60 individuals with velo-cardio-facial syndrome (VCFS; 3 to 17 years of age). Ten-fold cross-validation testing of discrimination between the three groups was carried out on unseen test examples using five pattern recognition algorithms (nearest mean, C5.0 decision trees, neural networks, logistic regression, and support vector machines). For discriminating between individuals with NS and controls, the best average sensitivity and specificity levels were 92 and 93% for children, 83 and 94% for adults, and 88 and 94% for the children and adults combined. For individuals with VCFS and controls, the best results were 83 and 92%. In a comparison of individuals with NS and individuals with VCFS, a correct identification rate of 95% was achieved for both syndromes. This article contains supplementary material, which may be viewed at the American Journal of Medical Genetics website at http://www.interscience.wiley.com/jpages/0148-7299/suppmat/index.html.

Deletions of 17p13.3, including the LIS1 gene, result in the brain malformation lissencephaly, which is characterized by reduced gyration and cortical thickening; however, the phenotype can vary from isolated lissencephaly sequence (ILS) to Miller-Dieker syndrome (MDS). At the clinical level, these two phenotypes can be differentiated by the presence of significant dysmorphic facial features and a more severe grade of lissencephaly in MDS. Previous work has suggested that children with MDS have a larger deletion than those with ILS, but the precise boundaries of the MDS critical region and causative genes other than LIS1 have never been fully determined. We have completed a physical and transcriptional map of the 17p13.3 region from LIS1 to the telomere. Using fluorescence in situ hybridization, we have mapped the deletion size in 19 children with ILS, 11 children with MDS, and 4 children with 17p13.3 deletions not involving LIS1. We show that the critical region that differentiates ILS from MDS at the molecular level can be reduced to 400 kb. Using somatic cell hybrids from selected patients, we have identified eight genes that are consistently deleted in patients classified as having MDS. In addition, deletion of the genes CRK and 14-3-3 epsilon delineates patients with the most severe lissencephaly grade. On the basis of recent functional data and the creation of a mouse model suggesting a role for 14-3-3 epsilon in cortical development, we suggest that deletion of one or both of these genes in combination with deletion of LIS1 may contribute to the more severe form of lissencephaly seen only in patients with MDS.